Ocean surface waves have been utilized as fundamental information in various fields of oceanic research. In this paper, we suggest a simulation and modelling technique for generating an ocean surface wave using an inverse Fast Fourier Transform (iFFT), and we subsequently verify the wave’s accuracy. The conventional method, linear superposition, requires recursive calculation because of the double summation and the time variable; to circumvent this issue, the new algorithm is presented. The Joint North Sea Wave Project (JONSWAP) spectrum is utilized for the ocean surface wave simulation example, and the parameters are the significant wave height (HS) and the zero-crossing wave period (TZ). A coordinate transform for the wavenumber domain was used to apply the inverse FFT algorithm. To verify the accuracy of the simulation result, the relative error between the input condition and the analysis result was calculated. The result for TZ is below 4% relative error, and the maximum relative error for HS is 7%. To avoid the Nyquist frequency for wave-field analysis and simulation, the minimum grid size was calculated by twice applying the maximum wavenumber.

This study aimed to learn disturbance information to effectively control multiple small unmanned surface vehicles (USVs) for marine research purposes at sea. The learned disturbance information was used to investigate the control of multiple USV swarms based on the leading–following formation technique. Numerous studies have already been conducted on swarm control using drones in the air; however, there has been a paucity of studies on swarm control in the sea. Contrary to swarm control in aviation, the fluid density of the sea is high, and the environment is constantly changing; thus, a robot system would be significantly affected by disturbances. This ultimately influences the maintenance of swarm formations and the accomplishment of missions [1,2]. Therefore, it is difficult to control numerous moving objects while maintaining a formation at sea by using the existing aerial drone swarm control technology. To solve this problem, we learned a long short-term memory (LSTM) model with time-series marine environmental data to predict maritime disturbances. Thereafter, the model was applied to a mission-based position control algorithm of each USV constituting the swarm to design a marine unmanned floating vessel swarm control system that can be applied to various marine environments. Specifically, to effectively control numerous small USVs for marine research purposes, ocean currents are learned using the LSTM algorithm, and the predicted ocean currents are used to generate a swarm USV control system for USV formations. In this study, a control system model of several small USVs equipped with two rear thrusters and a front lateral thruster was designed. The LSTM algorithm was learned using the previous ocean current data, and the velocity of the following ocean currents was predicted. The predictions were then used as a system disturbance to determine the thrust of the controller. To measure ocean currents in the sea when each USV moves, the velocity, azimuth, and position (latitude, longitude) data from the GPS mounted on the USV were used to measure the velocity and direction of the hull's movement. Further, the flow rate was measured using a flow rate sensor on a small USV. The USV movement and position were controlled using an artificial neural network-PID (ANN-PID) controller. This study entailed a comparative analysis of the designed USV model results and those generated by the simulator, including the behavior control rule of the USV swarm and the path of the actual USV swarm at sea. It was verified that the effectiveness of the USV mathematical model and behavior control rules. By comparing the movement path of the swarm USV with and without the disturbance learning algorithm and ANN-PID control algorithm applied to the designed simulator, the position error and maintenance performance of the swarm formation were analyzed, and the application results were compared.

While the underwater submersible encounters internal solitary wave (ISW), its loadings and motions would be seriously disturbed. To investigate the interaction effect between the suspended submersible and ISW, a three dimensional ISW-submersible interaction numerical model was established based on the Computational Fluid Dynamics (CFD) method. The generation and propagation of ISW was simulated in a two-layer fluid numerical wave tank according to the eKdV theory. The standard operation equation of submersible was introduced to simulate the six degree of freedom (6DoF) motions of submersible combined with the overset dynamic mesh method. The motion simulation method of submersible was effectively validated by comparing with published experimental results on the motion responses of the slender body under the ISW. Based on the constructed numerical model, the dynamic mechanism between the suspended submersible and ISW were studied, and the effects of the initial submerged depths and the ISW amplitudes on the dynamic responses of the submersible were revealed. According to the numerical results, the motions of the submersible have been significantly determined by its initial submerged depths. The submersible located above the ISW interface has a significant motion along the propagation direction of ISW and its motion trajectory resembles a counterclockwise semi ellipse. The motions of the submersible located below the ISW interface follows with the trace of the lower layer fluid which presented as an unclosed clockwise ellipse. The corresponding motions of the submersible would be increased as the increase of the ISW amplitudes.

This paper presents an optimized energy management strategy for Li-ion power batteries used on electric vehicles (EVs) at low temperatures. Under low-temperature environments, EVs suffer a sharp driving range loss resulted from the energy and power capability reduction of the battery. Simultaneously, because of Li plating, battery degradation becomes an increasing concern as temperature drops. All these factors could greatly increase the total vehicle operation cost. Prior to battery charging and vehicle operating, preheating battery to a battery-friendly temperature is an approach to promote energy utilization and reduce total cost. Based on the proposed LiFePO4 battery model, the total vehicle operation cost under certain driving cycles is quantified in the present paper. Then given a certain ambient temperature, a target temperature of preheating is optimized under the principle of minimizing total cost. As for the preheating method, a liquid heating system is also implemented on an electric bus. Simulation results show that the preheating process becomes increasingly necessary with a decreasing ambient temperature; however, the preheating demand declines as driving range grows. Vehicle tests verify that the preheating management strategy proposed in this paper is able to save total vehicle operation cost.

A new type of artificial block is proposed by modifying the traditional block. Based on the physical model experiment, the wave reflection and run-up characteristics of the new ecological blocks under regular waves were examined, and the influence of the height of the "planting trough" border on the hydrodynamic properties was analyzed. The results indicate that the wave reflection and run-up would decrease with a decrease in the breakwater slope. As wave height increases, wave run-up increases, and the reflection coefficient falls. Wave reflection and run-up increase with an increasing wave period. The relative depth of the water has a smaller impact on the wave reflection than the wave run-up. The reflection coefficient of the new ecological blocks is consistently lower than that of the conventional and continues to decrease as the border of the "planting trough" is raised. The raised borders prevent water loss in the trough, resulting in no significant improvement in the wave run-up performance of the new blocks. The reflection coefficient and the relative run-up R/H gradually increase with the average wave breaking parameter ξ increase. The crude permeability coefficients for the new blocks, New Heights 1 and New Heights 2, are 0.53, 0.53, and 0.54, respectively.

The wave energy converter (WEC) technology constantly develops new designs and models. To encourage its development within the energy sector, research is required to improve current designs and create durable and effective devices. However, it is also crucial to investigate the suitability of a WEC to a site-specific sea condition as this can impact its optimal power absorption and constructability. This study evaluates and compares the efficiency of a heaving buoy with varied geometries in one of the most energetic places along the Mexican coast. A statistical analysis of the wave climate on the coast of Ensenada during the last 42 years is performed to define the conditions to which the device is subjected. The location of the WEC in shallow waters is chosen using a computational model which solves the modified mild slope equation in its elliptic shape. The heaving buoy floater is studied using three distinct geometries: a semi-sphere, a cylinder, and a proposed rounded semi-rectangle. The hydrodynamic response of the three geometries is then analysed in the frequency and time domain using ANSYS AQWA. The hydrodynamic study involves the assessment of the floating body dynamics, exerted forces, the power absorbed as well as the suitability of the proposed power take-off (PTO) system. Findings reveal that the proposed geometry absorbs the most energy, with an annual power of 135.11 MW, and that the transmission PTO design is appropriate for this type of technology.

Abstract: This study investigates the transition to sustainable shipping industry within the framework of the IMO's 2050 carbon neutrality objective, focusing on socio-technical systems analysis. The research delves into the sustainable paradigm shift towards alternative marine fuels such as LNG, methanol, ammonia, and hydrogen from a socio-technical transition perspective, analyzing the multi-level per-spective challenges and opportunities. Specifically, it scrutinizes the implications of adopting these al-ternative fuels for global shipping, identifying technical uncertainties, financial constraints, and infra-structure needs. Through a comprehensive review of existing literature on ship emissions and alterna-tive fuels, coupled with socio-technical transition theory, the study addresses the multifaceted chal-lenges and opportunities in meeting the IMO's environmental objectives. It emphasizes the necessity of collaborative governance, innovative niche strategies, and a holistic approach to leverage the current window of opportunity in facilitating the maritime industry's transition to sustainable fuel options. Fi-nally, this research enhances our understanding of the intricate interplay between technological, social, industrial, and cultural dynamics in the greening of shipping and offers insights into the strategic adop-tion of environmentally friendly marine fuels for a sustainable future.

The study investigated farmers’ perception on pests and diseases management strategies, agricultural practices, production constraints and selection criteria of elite varieties using a survey research design. A total of 700 questionnaires were administered to smallholder farmers who were farming for household consumption, those producing for sale and household consumption and those who were mainly producing for sale because their primary goal was to produce for the market. Findings revealed that the most prevalent pests identified were whiteflies (Bemisia tabaci), grasshoppers (Zonocerus variegatus), aphids (Aphis gossypii), mealybugs (Phenacoccus manihoti), termites (Isoptera), and grasscutters (Thryonomys swinderianus). The three most common diseases of cassava limiting growth and yield with mixed infection include viral, bacterial, and fungal. The study also revealed that only 12.5% of farmers cultivated improved cassava varieties. The management practices implemented encompassed field sanitation and the application of pesticides. Lack of capital and no availability of market were the most important production and marketing constraints faced by farmers in the study area, whereas poundability and high storage root yield are the most preferred traits farmers consider in selecting a new variety. Results suggest that smallholder farmers should endeavor to undergo various developmental programs to develop themselves to increase their competitive advantage in their locality and in the local and global agricultural sectors. In addition, governments and other policy makers should strategize plans and programs that would contribute to smallholder farmers’ agriculture, community and national development.

Despite saltmarshes being considered as nature-based solutions (NbS) towards climate change mitigation, India’s saltmarsh ecosystems are least studied. This study quantifies the seasonal variation in carbon stocks mono-specific saltmarsh species (Porteresia coarctata) and its potential to play an important role in India’s climate change mitigation plans. Seasonal (pre-and post-monsoon) sampling of P. coarctata surface water, biomass and 30 cm sediment core was collected across four locations on the east coast of India to quantify sediment dry bulk density (DBD), organic matter (OM%), organic carbon (Corg%), Corg stocks of sediment and biomass, total carbon (C%) and nitrogen (N%) and stable isotopes of δ13C and δ15N. In general, the sediment DBD, OM and Corg of P. coarctata meadows was higher in post-monsoon and was influenced by salinity and pH changes. Isotope (δ¹³C) modelling of various sediment C sources suggested, particulate organic matter (POM) contribution was highest (0.04-0.79%) followed by P. coarctata (0.01–052%) and other macrophytes across our study locations. The seasonal variation of δ¹³C showed increased contribution of marine derived particulate and dissolved organic matter into P. coarctata meadows in post-monsoon season. Heavier δ¹⁵N values were observed in post-monsoon season suggesting anthropogenic input, that was utilized by P. coarctata to increase its above and below-ground biomass and shoot density. The combined ecosystem (30 cm sediment + biomass) Corg stocks of P. coarctata was 1.7-fold higher in post-monsoon (4021.20± 917 Mg C) compared to pre-monsoon (2297.36 ±647 Mg C) season among the four locations with a sediment Corg contribution >70%. Based on the International Panel for Climate Change Tier II assessment the P. coarctata meadows (443 ha) can help in avoiding the pre and post-monsoon emissions of 8431.34 and 14757.84 Mg CO₂ respectively. The combined price of the total CO₂ equivalent stored in P. coarctata meadows in pre- and post-monsoon is US$ 14.50 and US$ 25.38 million respectively. Further studies quantifying the NbS potential of P. coarctata mono-specific and mixed meadows of India’s coast is needed along with integration of saltmarsh ecosystems into India’s National Action Plan on Climate Change.

: Tunnel instability and lining integrity are intimately tied to the creep properties of the surrounding rock. The acquisition of rock mass creep parameters is critical in ascertaining the appropriate timing for lining construction. Nevertheless, creep tests on rock specimens conducted in a controlled setting cannot be straightforwardly extrapolated to rock mass creep analysis. This study performs laboratory-based creep tests on mudstone samples and establishes the corresponding creep constitutive model. Integration of a Mohr-Coulomb element with the Burgers model in series serves to characterise the yield creep behaviour of the rock mass. Additionally, the research outlines a series of 100 orthogonal experiments utilising randomised creep parameters, and formulates a GA-BP neural network inversion model. Employing long-term deformation measurements from the crown and sidewalls of the project site, this study deduces the creep parameters of the mudstone in the investigated tunnel section and examines the prolonged deformation traits of the surrounding rock. Drawing on the deformation traits of the surrounding rock and the forces impacting the primary support and lining structures, this paper evaluates the earliest and latest viable lining casting periods and pinpoints an optimal timing interval for lining implementation. The methodologies employed herein can serve as a benchmark for analogous endeavors internationally.

Ocean wave energy is a significantly well-liked renewable energy source. The Internet of Things (IoT) offers a great opportunity for development of the ocean wave energy research. The IoT technology significantly enhanced the performance of the ocean wave energy converter (WEC). The data obtained from IoT devices reduce the risk of using WEC. However, Integrating IoT devices with the WEC is a daunting task because controlling the WEC needs real-time data. This paper investigated the performance of WEC and estimate the lifetime of the modules. IoT devices integrated with various sensors determine different parameters and conditions of the ocean. The IoT platform is used for wireless voltmeters, wireless AC current meters, wireless voltage detection, wireless resistance sensors, wireless temperature sensor, wireless accelerometer, wireless pressure meters, and wireless water level sensors to determine the real-time condition of the ocean wave. These devices are also proven to be reliable and accurate.

This work condenses various modeling techniques for different Point Absorber configurations. A combined frequency - time domain model will be developed in Matlab-FORTRAN in order to compute the displacement, velocities and the power absorbed in the heave mode. Additionally, a single buoy motion including multiple degrees of freedom will be investigated as well. Therefore, the diffraction-radiation Boundary Element Method solvers NEMOH and BEMIO will be applied in the calculation of the hydrodynamic coefficients, which will determine the solution of Newtons impulse equations of motion. Initially, the Wave to wire model will be validated through comparison with previous experimental results for a submerged cone cylinder shape (Buldra-FO3). A single, generic, vertical floating cylinder will be contemplated then, that responds to the action of the passing waves excitation. Later, two vertical floating cylinders aligned with the incident wave direction will be modeled for a variable distance between the bodies. For both unidirectional regular and irregular waves as an input in deep water, the convolutive radiation force function term will be hereby approximated through the Prony method. By changing the spatial disposition of the axisymmetric buoys, using for instance triangular or diamond shaped arrays of three and four bodies respectively, the study will focus on the interaction effects for regular waves. The results will highlight the most efficient layout for maximizing the energy production whilst providing important insights into their performance, revealing for instance displacement amplification or capture width ratios in near-resonance conditions.

The uncertainty in the secondary path of an Active Noise Control (ANC) headphone affects the waterbed effect and stability of the feedback system. This study focuses on the uncertainty of the secondary path when real users wear headphones, and proposes a new uncertainty constraint based on the measured results of the secondary path transfer function under different wearing conditions of dummy head and limited subjects. This constraint and a cascaded second-order infinite impulse response filter with fixed coefficients are used to formulate a control strategic function, which is optimized by the Improved Grey Wolf Optimizer (IGWO) algorithm to obtain the optimal controller with better noise reduction performance. The proposed method and simulation model are validated based on the experimental test results. The results demonstrate that the safety factor and waterbed suppressing factor contained in the proposed uncertainty constraint ensures more stable noise reduction and effective suppression of the waterbed effect for new subjects without a priori data.

The intestinal microbial community of aquatic animals is closely related to the environment and thus affects the health of aquatic animals. Here we investigated annual variation of intestinal bacteria community structures of Ruditapes philippinarum cultured using two different methods, bottom sown and raft hanging. Bacterial diversity of seawater and sediment in different seasons was examined as well. Correlation between R. philippinarum intestinal bacteria community structures and environmental factors was analyzed. The results showed that in the two aquculture areas where R. philippinarum was differentially cultured, bacteria community structure of seawater and sediment both altered with seasons. However, neither seasonal changes nor difference in culture methods could significantly affect the intestinal bacteria community structures of R. philippinarum. Additionally, in terms of the alpha diversity of intestinal bacteria communities, there was no significant difference in R. philippinarum cultured using the two methods. For benthic cultured clams, alpha diversity of the intestinal bacterial communities was often higher than that of the environmental bacterial communities. For raft hanging cultured calms, Alpha diversity of the intestinal bacterial communities was normally comparable with that of the environmental counterparts. Beta diversity analysis showed that the intestinal bacterial community structure of R. philippinarum was mainly determined by both deterministic and stochastic processes. Correlation analysis showed that the intestinal bacterial community structures of R. philippinarum were determined by a variety of environmental factors. For clams collected from the benthic culture area, the intestinal bacterial structure was more correlated with the physicochemical properties of sediment in comparing with those of seawater. For clams collected from the raft-culture area, the intestinal bacterial structure was mainly determined by the phsicochemical characteristics of seawater. This study helps us to better understand the bacterial community structure in complex aquaculture ecosystems, providing a reference for healthy shellfish aquaculture and ecosystem protection in aquaculture area.

Fingerprint recognition systems have achieved widespread integration into various technological devices, including cell phones, computers, door locks, and time attendance machines. Nevertheless, individuals with worn fingerprints encounter challenges when attempting to unlock original fingerprint systems, resulting in disruptions to their daily activities. This study explores two distinct methods for fingerprint backup: traditional fingerprint impression and 3D printing technologies. Unlocking tests were conducted on commonly available optical fingerprint lock-equipped cell phones to assess the efficacy of these methods, particularly in unlocking worn fingerprints. The research findings indicated that traditional fingerprint impression method exhibited high fidelity in reproducing fingerprint patterns, achieving an impressive unlocking success rate of 97.8% for imprinting unworn fingerprints. However, when dealing with worn fingerprints, traditional fingerprint impression technique showed a reduced unlocking success rate, progressively decreasing with increasing degrees of finger wear. In contrast, 3D printed backup fingerprints, with image processing and optimization of ridge height, mitigated the impact of fingerprint wear on unlocking capability, resulting in an unlocking success rate of 84.4% or higher. Thus, the utilization of 3D printing technology proves advantageous for individuals with severely worn or incomplete fingerprints, providing a viable solution for unforeseen circumstances.

The Wave Mode (WM) is a unique imaging mode of spaceborne synthetic aperture radar (SAR), which is dedicatedly designed for global ocean surface wave observations. Since it was firstly achieved in the ERS-1/SAR satellite starting from 1991, the WM data over global oceans have been continuously acquired by the ESA’s SAR instruments onboard the satellites of ERS-2 (1997 – 2011), ENVISAT (2002 – 2012), Sentinel-1A(2014--)/1B(2016--) and the Chinese GaoFen-3 SAR (2016--), for nearly 30 years. Therefore, spaceborne SAR WM data have been a ‘big data’, which however, has not been widely exploited for global ocean wave measurements. In this study, we demonstrate its application on global ocean wave measurements based on the ten-year Advanced SAR (ASAR) WM data.

The Mara River basin (MRB) has a world-famous ecosystem, but the vegetation has been damaged due to economic development in recent years, and there is little known about the area that will experience severe vegetation damage in the future. Based on the vegetation vulnerability system, principal component analysis, and three CMIP6 scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5), vegetation vulnerability was calculated in the base period (2010-2019), near-term period (2020-2059) and long-term period (2060-2099) in the MRB. The spatial cluster of vegetation vulnerability was revealed by spatial correlation analysis, and the transition of vegetation vulnerability of different periods was analyzed by stochastic matrix. The results showed that in all periods, the vulnerability showed a high-high cluster in the east, and a low-low cluster midstream and downstream. From the stochastic matrix, the area of high vulnerability increased the least under the SSP1-2.6, while it increased the most under the SSP5-8.5. The vegetation vulnerability upstream increased the most from the base period to the near-term period and long-term period in the MRB. By comparing the vegetation vulnerability under different scenarios, and pointing out the areas with the highest vulnerability increase, this study can better provide comprehensive decision-making for vegetation protection in the MRB.

Spaceborne altimeters are an important data source for obtaining global sea surface wind speeds (U10). Although many altimeter U10 algorithms have been proposed and they perform well, there is still room for improvement. In this study, the data from ten altimeters were collocated with buoys to investigate the error of the altimeter U10 retrievals. The U10 residuals were found to be significantly dependent on many oceanic and atmospheric parameters. Because these oceanic and atmospheric parameters are inter-correlated, an asymptotic strategy was used to isolate the impact of different parameters and establish a neural-network-based correction model of altimeter U10. The results indicated that significant wave heights and mean wave periods are effective in correcting U10 retrievals, probably due to the tilting modulation of long-waves on the sea surface. After the wave correction, the root-mean-square error of the retrieved U10 was reduced from 1.42 m/s to 1.24 m/s and the impacts of thermodynamic parameters, such as sea surface (air) temperate, became negligible. The U10 residuals after correction showed that the atmospheric instability can lead to errors on extrapolated buoy U10. The buoy measurements with large air-sea temperature differences need to be excluded in the Cal/Val of remotely sensed U10.

In this article, we describe a simple procedure for evaluating the sterility of nutrient media using a shear-horizontal surface acoustic wave (SH-SAW) biosensor. We used the SH-SAW biosensor platform to monitor the time-dependent phase responses of the material for the media that binds to a monolayer of 3-mercaptopropanyl-N-hydroxy succinimide on the biosensor surface. Increases in the phase shift less than 50% of the starting phase shift recorded 180 minutes after the sterilization indicate a successful sterility test of the media. Our devices were then applied to sterility testing using a viable Escherichia coli (E. coli) K-12 solution to confirm our hypothesis. Filtered LB Broth was the negative control, and a 24-hour culture of E. coli was the positive control. Before testing, the cell solution was pelleted, the media decanted, and then replaced with a 1x phosphate-buffered saline solution (1x PBS). Since we know that the N-hydroxysuccinimide residues will bind to amine groups, only in cases where microbial species are present will the surface binding increase greater than 50%. We confirmed our hypothesis using SH-SAW biosensors and overnight E. coli cultures. The sensitivity for our 250 MHz quartz SH-SAW sensors was calculated based on the response from the E. coli K-12 solution over the linear dynamic range, which appears to be 2x10^4 – 2x10^7 CFU per ml and has a sensitivity of S = 1.655x10^5 o m2 Kg-1. The limit of detection (LOD) for these sensors was calculated to be approximately 2x10^-9 grams (g), which is estimated to be approximately 2,000 Escherichia coli (E. coli) K-12 cells. However, the sensitivity and insertion loss remained approximately unchanged before and after coating the sensor with 3,3'-Dithiobis(succinimidyl) Propionate (DSP).

Dearth of information on extent of genetic variability in cassava limits the genetic improvement of cassava in Sierra Leone. This study aimed at assessing the genetic variability and relationships within 103 cassava genotypes using agro-morphological and culinary markers. A field trial was conducted in the School of Agriculture and Food Sciences research site. The experiment was laid in an augmented randomized block design. Morphological classification based on qualitative and quantitative traits categorized the germplasm into three different groups. A total of ten principal components (PCs) in the qualitative and six PCs in the quantitative trait sets accounted for 66.74% and 67.27% of the total genetic variation, respectively. Traits with significantly strong and positive correlations included presence of fruit (PFRT) and presence of seed (PSE)(r = 0.86***),root yield per plant (RYPP) and number of storage root (NSR) (r = 0.76***), RYPP and number of commercial root (NCR) (r = 0.68***), length of leaf lobe (LLL) and width of leaf lobe (WLL) (r = 0.66***),and between NSR and NCR (0.84***). Cooking time, cooking percentage, texture, mealiness, taste and aroma varied widely among the accessions. Findings established that the cassava germplasm possess useful genetic variability that could be exploited through selection for short term release programme, genetic conservation of valuable germplasm and genetic improvement of the crop.

Nucleoside analogs are commonly used drugs for the treatment of cancer and viral infections. Nucleoside deoxyribosyltransferase (NDT) is one of the key enzymes required for the biosynthesis of deoxynucleotides. The feasibility of biochemical transformation processes is usually greatly dependent on the cost of biocatalysts. Therefore, immobilizing and reusing biocatalysts is an approach to be considered to bring biotransformations closer to industrial feasibility, since it not only allows enzymes to be reused but can also improve their stability under several reaction conditions. In this work, histidine tags have been successfully fused to a Nucleoside deoxyribosyltransferase from Lactobacillus reuteri (LrDNT), which has been produced in a bench-scale reactor using a facile araBAD promoter-based protein expression system in an industrial microorganism, the E. coli BL21(DE3) strain. The overexpressed LrNDT was bound to a nickel-chelating agarose affinity chromatography medium via a one-step purification and immobilization process with a 99% yield, retaining about 97% of its initial activity. The optimal conditions for the immobilized LrNDT maintain high enzyme activity within the range of 20-45°C and pH 6.0-7.5. Finally, the immobilized enzyme reactor (IMER) of LrNDT was applied for the continuous-flow biosynthesis of 2'-deoxyadenosine and retained 90% of its activity after 16 hours, providing a theoretical basis for the industrial production of nucleoside analogs.

Abstract: Global ecological concern regarding the transfer of fouling organisms to ship hulls is increasing. This study investigated the species composition, dominant species, distribution patterns, community structure, and life-cycle differences of hull-fouling macroinvertebrates on five research vessels (R/Vs: Isabu, Onnuri, Eardo, Jangmok 1, and Jangmok 2) operated by the Korea Institute of Ocean Science and Technology (KIOST). Hull-fouling macroinvertebrates were collected three to five times on quadrats from the upper and middle sectors of the hull sides, bottom, and niche areas (the propellers and shafts and the thrusters). A total of 47 macroinvertebrate species were identified, represented by 8,519 individuals(ind.)/m2 and a biomass of 1,967 gWWt/m2 on the five vessels. The number of species, density, and biomass were greater on the coastal vessels the Eardo, Jangmok 1, and Jangmok 2 than on the ocean-going vessels the Isabu and Onnuri. Among the coastal vessels, barnacles were the most abundant and had the greatest density, while mollusks had the highest biomass. Differences between hull sectors showed that the highest species abundance and density appeared on all hulls in ports and bays where the Jangmok 1 operated, while the highest species abundance, density, and biomass were identified in the niche areas of the Eardo, which operated farther from the coast. The hull-fouling macroinvertebrates that exceeded 1% of all organisms were the barnacles Amphibalanus amphitrite, Balanus trigonus, and Amphibalanus improvisus; the polychaete Hydroides ezoensis; the bivalves Magallana gigas and Mytilus galloprovincialis; and the amphipod Jassa slatteryi. The dominant species were cosmopolitan and globally distributed, and many of them were cryptogenic. Six native species were identified: M. gigas, H. ezoensis, the amphipod Melita koreana, the isopod Cirolana ko-reana, and the barnacle B. trigonus and F. kondakovi. Eight non-indigenous species (NIS) were de-tected: barnacles A. amphitrite and A. improvisus, the bivalve M. galloprovincialis, the polychaete Perinereis nuntia, amphipods J. slatteryi and Caprella californica, and bryozoans Bugulina californica and Bugula neritina. Of the fouling macroinvertebrates found on the vessel hulls, 13% were native and 17% were NIS. The nMDS ordination analysis of the five vessels showed four clusters of fouling macroinvertebrate communities: two ocean clusters (the Isabu and Onnuri), one coastal cluster (the Eardo and Jangmok 2), and one local cluster (the Jangmok 1). More diverse communities developed on the hulls of vessels that operated locally rather than globally or in deep oceans. Spearman rank correlation showed that biological indices such as number of species, density, and biomass correlated highly and positively with the numbers of days on coastal operations and negatively with the number days on ocean operations. The species diversity index correlated positively with the total number of anchoring days and coastal operation days and negatively with the total number of operation days and ocean operation days. The macroinvertebrates differed by the area of operation, the port of anchorage, the number of days in operation and at anchor, and the hull sectors. There is no previous research data on hull-fouling macroinvertebrates in the Republic of Korea, and this study provides a basis for future studies to identify introduced species and their differences based on operation area.

Although Eulerian approaches are standard in computational acoustics, they are less effective for certain classes of problems like bubble acoustics and combustion noise. A different approach for solving acoustic problems is to compute with individual particles following particle motion. In this paper, a Lagrangian approach to model sound propagation in moving fluid is presented and implemented numerically, using three meshfree methods to solve the Lagrangian acoustic perturbation equations (LAPE) in the time domain. The LAPE split the fluid dynamic equations into a set of hydrodynamic equations for the motion of fluid particles and perturbation equations for the acoustic quantities corresponding to each fluid particle. Then, three meshfree methods, the smoothed particle hydrodynamics (SPH) method, the corrective smoothed particle (CSP) method, and the generalized finite difference (GFD) method, are introduced to solve the LAPE and the linearized LAPE (LLAPE). The SPH and CSP methods are widely used meshfree methods, while the GFD method based on the Taylor series expansion can be easily extended to higher orders. Applications to modeling sound propagation in steady or unsteady fluids in motion are outlined, treating a number of different cases in one and two space dimensions. A comparison of the LAPE and the LLAPE using the three meshfree methods is also presented. The Lagrangian approach shows good agreement with exact solutions. The comparison indicates that the CSP and GFD method exhibit convergence in cases with different background flow. The GFD method is more accurate, while the CSP method can handle higher Courant numbers.

Reactions of quinones with compounds containing an amino group can produce a wide variety of addition or substitution products that depend on reactivity of both quinone and amino derivative. 6,7-Dichloropyrido[1,2-a]benzimidazole-8,9-diones undergo selective nucleophilic substitution reaction with different benzohydrazides and α-hydroxy-p-quinone imine derivatives stabilized by strong intramolecular hydrogen bond were isolated. Synthesized compounds represent a combination of several structural motifs: benzimidazole core fused with α-hydroxy-p-quinone imine which contains a benzamido fragment. The protonation/deprotonation processes were investigated in a solution using UV-Vis spectroscopy and 1H NMR titration experiment. X-ray crystallography analysis revealed a set of weak non-covalent interactions such as intra- and intermolecular hydrogen bonds and π-π stacking. Additionally, the redox behavior of 6,7-dichloropyrido[1,2-a]benzimidazole-8,9-dione and its p-imino derivative was investigated in acidic and neutral environment using cyclic voltammetry measurements. Cathode material based on 6,7-dichloropyrido[1,2-a]benzimidazole-8,9-dione could act as potential effective active electrode in aqueous electrolyte batteries, however further optimization is required.

This study provides, to our knowledge, the first detailed analysis of how surface oil modifies air-sea interaction in a two-way coupled model, i.e., the coupled-ocean-atmosphere-wave-sediment-transport (COAWST) model modified to account for oil-related changes to air-sea fluxes. This study investigates the effects of oil on surface roughness, surface wind, surface and near surface temperature differences, and boundary-layer stability, and how those conditions ultimately affect surface stress. We first conducted twin coupled modeling simulations with and without the influence of oil over the Deepwater Horizon (DWH) oil spill period (April 21 to May 5, 2010) in the Gulf of Mexico. Then we compared the results by using a modularized flux model with parameterizations selected to match those selected in the coupled model adapted to either ignore or account for different atmospheric/oceanic processes in calculating surface stress. When non-oil inputs to the bulk formula treated as unchanged by oil, the surface stress changes are always negative due to oil-related damping of surface roughness alone. However, the oil-related changes to 10-m wind speed and boundary-layer stability are found to play a dominant role in surface stress changes relative to those due to the oil-related surface roughness changes, highlighting that most of the changes in surface stress are due to the oil-related changes in wind speed and boundary-layer stability. Finally, the oil-related changes to surface stress due to the combined oil-related changes in surface roughness, surface wind, and boundary-layer stability are not large enough to have a major impact on the surface current and surface oil transport, indicating that the feedbacks from the surface oil to the surface oil movement itself are minor for forecasting the surface oil transport unless the fractional oil coverage is much larger than found in this study.

The development of computational acoustics allows simulation of sound generation and propagation in complex environment. In particular, meshfree methods are widely used to solve acoustics problems through arbitrarily distributed field points and approximation smoothness flexibility. As a Lagrangian meshfree method, smoothed particle hydrodynamics (SPH) method reduce the difficulty in solving problems with deformable boundaries, complex topologies, or multiphase medium. The traditional SPH method has been applied in acoustic simulation. This study presents the corrective smoothed particle method (CSPM), which is a combination of SPH kernel estimate and Taylor series expansion. The CSPM is introduced as a Lagrangian approach to improve accuracy in solving acoustic wave equations in the time domain. Moreover, a boundary treatment technique based on the hybrid meshfree and finite difference time domain (FDTD) method is proposed to represent different acoustic boundaries with particles. To model sound propagation in pipes with different boundaries, soft, rigid, and absorbing boundary conditions are built with this technique. Numerical results show that the CSPM algorithm is consistent and demonstrates convergence with exact solutions. Main computational parameters are discussed, and different boundary conditions are validated to be effective for benchmark problems in computational acoustics.

The decay of the low-mode internal tide due to the superharmonic energy cascade is investigated in a realistically forced global Hybrid Coordinate Ocean Model (HYCOM) simulation with 1/25 degrees (4 km) horizontal grid spacing. Time-mean and depth-integrated supertidal kinetic energy is found to be largest near low-latitude internal tide generation sites, such as the Bay of Bengal, Amazon Shelf, and Mascarene Ridge. The supertidal kinetic energy can make up to 50% of the total internal tide kinetic energy several hundred kilometers from the generation sites. As opposed to the tidal flux divergence, the supertidal flux divergence does not correlate with the barotropic to baroclinic energy conversion. Instead, the time-mean and depth-integrated supertidal flux divergence correlates with the nonlinear kinetic energy transfers from (sub)tidal to supertidal frequency bands as estimated with a novel coarse-graining approach. The regular spaced banding patterns of the surface-intensified nonlinear energy transfers are attributed to semidiurnal mode 1 and mode 2 internal waves that interfere constructively at the surface. This causes patches where both surface tidal KE and nonlinear energy transfers are elevated. The simulated internal tide off the Amazon shelf steepens significantly near these patches, generating solitary-like waves in good agreement with Synthetic Aperture Radar (SAR) imagery. Globally, we find that regions of high supertidal energy flux also show a high correlation with observed instances of solitary nonlinear internal waves.

Large-scale hydrological modeling in China is challenging given the sparse meteorological stations and large uncertainties associated with atmospheric forcing data.Here we introduce the development and use of the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) in the Heihe River Basin(HRB) for improving hydrologic modeling, by leveraging the datasets from the China Meteorological Administration Land Data Assimilation System (CLDAS)(including climate data from nearly 40000 area encryption stations, 2700 national automatic weather stations, FengYun (FY) 2 satellite and radar stations). CMADS uses the Space Time Multiscale Analysis System (STMAS) to fuse data based on ECWMF ambient field and ensure data accuracy. In addition, compared with CLDAS, CMADS includes relative humidity and climate data of varied resolutions to drive hydrological models such as the Soil and Water Assessment Tool (SWAT) model. Here, we compared climate data from CMADS, Climate Forecast System Reanalysis (CFSR) and traditional weather station (TWS) climate forcing data and evaluatedtheir applicability for driving large scale hydrologic modeling with SWAT. In general, CMADS has higher accuracy than CFRS when evaluated against observations at TWS; CMADS also provides spatially continuous climate field to drive distributed hydrologic models, which is an important advantage over TWS climate data, particular in regions with sparse weather stations. Therefore, SWAT model simulations driven with CMADS and TWS achieved similar performances in terms of monthly and daily stream flow simulations, and both of them outperformed CFRS. For example, for the three hydrological stations (Ying Luoxia, Qilian Mountain, and ZhaMasheke) in the HRB at the monthly and daily Nash-Sutcliffe efficiency ranges of 0.75-0.95 and 0.58-0.78, respectively, which are much higher than corresponding efficiency statistics achieved with CFSR (monthly: 0.32-0.49 and daily: 0.26 – 0.45). The CMADS dataset is available free of charge and is expected to a valuable addition to the existing climate reanalysis datasets for deriving distributed hydrologic modeling in China and other countries in East Asia.

Ocean wave energy conversion as one of the renewable clean energy sources is attracting the research interests of many people. This review introduces different types of power take-off technology of wave energy converters. The main focus is the linear direct drive power take-off devices as they have the advantages for ocean wave energy conversion. The designs and optimizations of power take-off systems of ocean wave energy converters have been studied from reviewing the recently published literature. Also, the simple hydrodynamics of wave energy converters have been reviewed for design optimization of the wave energy converters at specific wave sites. The novel mechanical designs of the power take-off systems have been compared and investigated in order to increase the energy harvesting efficiency.

This compendium presents new mathematical techniques for modeling Point Absorbers. A combined frequency-time domain framework is developed. It is used to simulate the energy generated by the wave farms. With Matlab and Fortran as a base, this leads to obtain physical variables of primary importance, namely position, velocity and power to energy net balance relationships of absorption. Integration of different degrees of freedom with heave as main executable leads in turn to a single buoy motion focus. Acquisition of the needed hydrodynamic coefficients is provided through application of potential field solvers with Boundary Element Methodology background. Initially, this Wave-to-motion model is validated by comparison with previous experimental results for a floating cone cylinder shape (Buldra-FO3). A single, generic, vertical floating cylinder is contemplated then, that responds to the action of the passing regular waves excitation. Later, two equally sized vertical floating cylinders aligned with the incident wave direction are modeled for a variable distance between the bodies. For both unidirectional regular and irregular waves as an input in deep water, we approximate the convolutive radiation force function term through the Prony method. By changing the spatial disposition of the axisymmetric buoys, using for instance triangular or rectangular shaped arrays of three and four bodies respectively, the study delves into motion characteristics for regular waves. The results highlight efficient layouts for maximizing the energy production whilst providing important insights into their performance, revealing displacement amplification- and capture width-ratios, while deriving in possible interpretations of scenarios related to the known park effect. These terms are encompassed by the novelty of a new conceptual Post-Processing methodology in the field, which leads to obtain an optimal distance for the separated bodies with effective energy absorption in a regular wave regime. The main objective is to generate a tendency within the hydrodynamic field of study, which is the Wave to motion perspective. More generally, this computational excursion envisions and depicts potential fields of study, which will surely enhance new connections and link this renewable energy form. Therefore, this research delves first into the historical and technical background on Ocean Wave Energy. Next, it is in the section regarding Materials and Methods, where boundaries and related equations are introduced step by step, together with latter mentioned case scenarios, and their corresponding configuration parameters. A separate section frames then the scope of results, while finally, there is an ensuing discussion and conclusions for evaluation assessment.

Marine cold air outbreaks (MCAOs) are large-scale events in which cold air masses are advected over open ocean. It is well-known that these events are linked to the formation of polar lows and other mesoscale phenomena associated with high wind speeds, and that they therefore in some cases represent a hazard to maritime activities. However, it is still unknown whether MCAOs are generally conducive to higher wind speeds than normal. Here this is investigated by comparing ocean near-surface wind speeds during MCAOs in atmospheric reanalysis products with different horizontal grid spacings, along with two case studies using a convection-permitting numerical weather prediction model. The study regions are the Labrador Sea and the Greenland–Iceland–Norwegian (GIN) Seas, where MCAOs have been shown to be important for air–sea interaction and deep water formation. One of the main findings is that wind speeds during the strongest MCAO events are higher than normal and higher than wind speeds during less severe events. Limited evidence from the case studies suggests that reanalyses with grid spacings of more than 50 km underestimate winds driven by the large ocean–atmosphere energy fluxes during MCAOs. The peak times of MCAO usually occur when baroclinic waves pass over the regions. Therefore, the strong wind episodes during MCAOs generally last for just a few days. However, MCAOs can persist for 50 days or more.

The present study aims to develop an efficient numerical method for computing the diffraction and radiation of water waves with horizontal long cylindrical structures, such as floating breakwaters. A higher-order scheme is used to discretize geometry of the structure as well as the relevant physical quantities. As the kernel of this method, Wehausen’s free-surface Green function is calculated by a newly-developed Gauss-Kronrod adaptive quadrature algorithm after elimination of its Cauchy-type singularities. To improve computational efficiency, a Chebyshev approximation approach is applied to a fast calculation of the Green function that needs evaluation thousands of times. In addition, OpenMP parallel technique is used to the formation of influence coefficient matrix, which significantly reduces CPU time. Finally, computations are performed on wave exciting forces and hydrodynamic coefficients for the long cylindrical structures, either floating or submerged. Comparison with other numerical and analytical methods demonstrates good performance of the present method.

Sea surface salinity (SSS) is one of the Essential Climate Variables (ECVs) as defined by the Global Climate Observing System (GCOS). Acquiring high-quality SSS datasets with high spatial-temporal resolution is cruicial for research on the hydrological cycle and earth climate. This study assessed the quality of SSS data provided by four high-resolution ocean reanalysis products, including the Hybrid Coordinate Ocean Model (HYCOM) 1/12° global reanalysis, the The Copernicus Global 1/12° Oceanic and Sea Ice GLORYS12 Reanal-ysis, the Simple Ocean Data Assimilation (SODA) reanalysis, the ECMWF Oceanic Reanalysis System 5 (ORAS5) product and the Estimating the Circulation and Climate of the Ocean Phase II (ECCO2) reanalysis. Regional comparison in the Mediterranean Sea shows that reanalysis largely depicts the accurate spatial SSS structure away from river mouths and coastal areas but slightly underestimates the mean SSS values. Better SSS reanalysis performance is found in the Levantine Sea while larger SSS uncertainties are found in the Adriatic Sea and the Aegean Sea. The global comparison with CMEMS level-4 (L4) SSS show generally con-sistent large-scale structures. The mean ΔSSS between monthly gridded reanalysis data and in situ analyzed data is -0.1 PSU in the open seas between 40°S and 40°N with the mean Root Mean Square Deviation (RMSD) generally smaller than 0.3 PSU and the majority of correlation coefficients higher than 0.5. Comparison with collocated buoy salinity shows that reanalysis products well captures the SSS variations at the locations of tropical moored buoy arrays at weekly scale. Among all the four products, the data quality of HYCOM re-analysis SSS is highest in marginal sea, GLORYS12 has the best performance in the global ocean especially in tropical regions. Comparatively, ECCO2 has the overall worst performance to reproduce SSS states and variations by showing the largest discrepancies with CMEMS L4 SSS.

It is well-known that surface plasmon wave propagates along a straight line, but this common sense was broken by the artificial curved light – plasmon Airy beam. In this paper, we introduce a new class of curved surface plasmon wave - the photonic hook plasmon. It propagates along wavelength scaled curved trajectory with radius less than surface plasmon polariton wavelength, and can exist despite the strong energy dissipation at the metal surface.

The statistical analysis of impact of the top 50 solar flares of X-class (1997-2023) on the global seismic activity, as well as on the earthquake preparation zones located in illuminated part of the globe and in the area of 5000 km radius around the subsolar point was carried out. It is shown by a method of epoch superposition that for all cases the increase of seismicity is observed, especially in the region around the subsolar point (up to 38%) during 10 days after the solar flare in comparison with preceding 10 days. The case study of aftershock sequence of strong M=9.1 earthquake (Su-matra-Andaman Islands, 26.12.2004) after the solar flare of X7.2 class (20.01.2005) demonstrated that the number of aftershocks with magnitude M≥2.5 increases more than 20 times after the solar flare with a delay of 7 days. For the case of the Darfield earthquake (M=7.1, 04.09.2010, New Zealand) it was shown that strong solar flares of class X and M probably triggered two strong aftershocks (M>6) with the same delay of 6 days on the Port Hills fault, which is the most sensitive to external electromagnetic impact from point of view of the fault electrical conductivity and orientation. Based on the obtained results the possible application of natural electromagnetic triggering of earthquakes is discussed for a short-term earthquake prediction using confidently recorded strong external electromagnetic triggering impacts on the specific earthquake preparation zones, as well as ionospheric perturbations due to aerosol emission from the earthquake sources recorded by satellites.

This paper introduces a new destriping algorithm for remote sensing data. The method is based on combined Haar Stationary Wavelet transform and Fourier filtering. State-of-the-Art methods based on the discrete wavelet transform (DWT) may not always be effective and may cause different artifacts. Our contribution is three-fold: i) we propose to use the Undecimated Wavelet transform (UWT) to avoid as much as possible shortcomings of the classical DWT; ii) we combine a spectral filtering and UWT using the simplest possible wavelet, the Haar basis, for a computational efficiency; iii) we handle 2D fields with missing data, as commonly observed in ocean remote sensing data due to atmospheric conditions (e.g., cloud contamination). The performances of the proposed filter are tested and validated on the suppression of horizontal strip artifacts in cloudy L2 Sea Surface Temperature (SST) and ocean color snapshots.

In order to correct attenuated millimeter-wavelength (Ka-band) radar data and address the problem of instability, an attenuation correction methodology (attenuation correction with variation trend constraint; VTC) was developed. Using synchronous observation conditions and multi-band radars, the VTC method adopts the variation trends of reflectivity in X-band radar data captured with wavelet transform as a constraint to adjust reflectivity factors of millimeter-wavelength radar. The correction was evaluated by comparing reflectivities obtained by millimeter-wavelength cloud radar and X-band weather radar. Experiments showed that attenuation was a major contributory factor in the different reflectivities of the two radars when relatively intense echoes exist, and the attenuation correction developed in this study significantly improved data quality for millimeter-wavelength radar. Reflectivity differences between the two radars were reduced and reflectivity correlations were enhanced. Errors caused by attenuation were eliminated, while variation details in the reflectivity factors were retained. The VTC method is superior to the bin-by-bin method in terms of correction amplitude and can be used for attenuation correction of shorter wavelength radar assisted by longer wavelength radar data.

Dissolved organic matter (DOM) in the ocean represents about 662 billion tonnes of C, 200 times more than the living biomass. It is produced mainly by microbial primary production. The largest fraction of this DOM is old (>weeks to months) and both chemically and biologically recalcitrant. The remainder is young (seconds to weeks), more labile and surface active. It also changes the rheological properties in the bulk phase of the water and at interfaces including the sea surface microlayer (SML). In order of abundance, this DOM consists of sugars, amino acids, fatty acids and nucleic acids, often incorporated into complex polymers. The DOM molecules are produced by microbial genes, and are further modified by enzymes themselves produced by genes. The properties of ocean water and its interfaces as well as biogeochemical fluxes may thus be modified by ocean microbial genes. These fluxes influence ocean and atmospheric climate, which in return acts on the biota. Therefore the ocean microbial genomes and the fluxes and climates they influence may be subject to Darwinian-type selection. Research programmes need to integrate ocean ecology, rheology, biogeochemistry and genomics, to find the associations among them. Discovery of commercial bioactive molecules may be a bonus.

Genetic diversity is very important in crop improvement. This study was carried out to assess the genetic diversity and the number of unique multilocus genotypes (MLGs) in cassava collection in Burkina Faso. To achieve this objective 130 cassava accessions were genotyped using 32 simple sequence repeat (SSR) markers. The results revealed that among these markers, twelve (12) were highly informative, with the PIC values greater than 0.50, twelve (12) were moderately informative, with the PIC values ranged between 0.25 and 0.50, and eight (8) were not very informative, with the PIC values lower than 0.25. A moderate level of genetic diversity was found for the population, indicated by the average expected heterozygosity (0.45) and the observed heterozygosity (0.48). About 83.8% of unique multilocus genotypes were found in the cassava collection indicating that SSR markers seem to be most appropriate for MLGs identification. Population structure analysis based on hierarchical clustering identified two subpopulations and Bayesian approach suggested five clusters. Additionally, DAPC analysis separated the cassava accessions into 13 subpopulations. The comparison of these results and the previous study using SNP, suggest that each type of markers can be used to assessment the genetic structure of cassava grown in Burkina Faso.

Functional osseoconductive coatings based on hydroxylapatite (HAp) and applied preferentially by atmospheric plasma spraying to medical implant surfaces are a mainstay of modern implantology. During contact with the hot plasma jet, HAp particles melt incongruently and undergo complex dehydration and decomposition reactions that alter their phase composition and crystallographic symmetry, and thus, the physical and biological properties of the coatings. Surface analytical methods such as laser-Raman and nuclear magnetic resonance (NMR) spectroscopies are useful tools to assess the structural changes of HAp imposed by heat treatment during their flight along the hot plasma jet. In this contribution, the controversial information on the existence or non-existence of oxyapatite, i.e. fully dehydrated HAp as a thermodynamically stable compound is highlighted.

Seasonal climatology of salinity fronts in the South Atlantic has been created from satellite SMOS sea surface salinity (SSS) measurements, 2011-2019, processed at the Barcelona Expert Center of Remote Sensing (BEC) and provided as high-resolution (1/20°) SSS data. The SSS fronts are identified with narrow zones of enhanced horizontal gradient magnitude (GM) of SSS computed with the Belkin-O’Reilly algorithm. Seasonal climatologies are generated for large-scale open-ocean SSS fronts and for low-salinity regions maintained by the Rio de la Plata discharge, Magellan Strait outflow, Congo River discharge, and Benguela upwelling. To facilitate feature recognition in satellite imagery, the salinity gradient has been log-transformed, which improved visual contrast of gradient maps, revealing new features. A 2000-km-long triangular area in the eastern tropical-subtropical Atlantic is filled with regular quasi-meridional mesoscale striations that form a giant ripple field with a 100-km wave length extending from Africa toward the NE Brazil. South of the Tropical Front, within the subtropical high-salinity pool, a trans-ocean quasi-zonal narrow linear belt of SSS maximum is documented. The Smax belt shifts north-south seasonally while retaining its well-defined linear morphology, which is suggestive of a mechanism that maintains this feature. In the SW Atlantic, the Rio de la Plata plume expands in winter (June-July), reaching across the South Brazilian Bight, up to Cabo Frio (23°S) and beyond. The Plata estuarine front moves in and out seasonally. Farther south, the Magellan Strait outflow expands northward in winter up to 39-40°S to nearly join the Plata outflow. In the SE Atlantic, the Congo River plume spreads radially from the river mouth, with the spreading direction varying seasonally and interannually. The plume is often bordered from the south by a quasi-zonal front along 6°S. The diluted Congo River water spreads southward seasonally down to the thermal Angola-Benguela Front at 16°S. The Benguela upwelling is delineated by a meridional front, which extends north alongshore up to 20°S, where the low-salinity Benguela upwelling water meets the high-salinity tropical water (“Angola water”) to form a salinity front, which is separate from the thermal Angola-Benguela Front at 16°S. The Angola water thus forms a wedge between the low-salinity waters of the Congo River outflow in the north and Benguela upwelling in the south. This high-salinity wedge is bordered by salinity fronts that migrate north-south seasonally.

This contribution attempts to provide a state-of-the-art account on the physicochemical and biomedical properties of plasma-sprayed hydroxylapatite (HAp) coatings that are routinely applied to the surfaces of metallic endoprosthetic and dental root implants, designed to replace or restore lost functions of diseased or damaged tissues of the human body. Even though the residence time of powder particles of HAp in the plasma jet is extremely short, the high temperature applied introduces compositional and structural changes of the precursor hydroxylapatite that severely affect its chemical and physical properties and in turn, its biomedical performance. These changes are based on the incongruent melting behaviour of HAp and can be traced, among many other analytical techniques, by high-resolution synchrotron X-ray diffraction, vibrational (Raman), and nuclear magnetic resonance (NMR) spectroscopies. In vivo reactions of the plasma-sprayed coatings with extracellular fluid (ECF) can be assessed and predicted by in vitro testing using simulated body fluids as proxy agents. Ways are being discussed to safeguard appropriate biological performance of hydroxylapatite coatings in long-term service by controlling their phase content, porosity, surface roughness, residual stress distribution, and adhesion to the implant surface.

The internal wave recognition algorithm in an ocean data buoy system can be used to realize the real-time and flexible observation of internal waves, but there is no accurate automatic recognition method. To meet the need for automatic, real-time, and reliable internal wave recognition, an automatic internal wave recognition algorithm has been proposed for a tightly profiled intelligent buoy system. The sea profile temperature data collected by the Bailong buoy system in the Andaman Sea in 2018 were used to train and test the internal wave recognition neural network model, which consists of two parts: feature extraction and feature classification. The experiment compares the long short-term memory network (LSTM), convolutional neural network (CNN) with different layers, and deep neural network (DNN) without a feature extraction network and adjusts the number of convolutional nuclei and convolutional strides to improve the feature extraction efficiency. Experiments show that the best results can be obtained when a CNN layer is used as the feature extraction network, the convolutional step length is 4, the number of convolutional kernels is 5. The recall reaches 95.31% and the precision is 97.53%. The internal wave identification delay of the algorithm is 5.0862 minutes, the number of parameters is 1593, and the number of calculations is 3024. The algorithm can be directly deployed to the ocean data buoy system to realize the demand for automatic, real-time and reliable internal wave identification at the buoy end.

Density functional theory (DFT) calculations of hydrogen adsorption on titanium nitride had previously shown that hydrogen may adsorb on both titanium and nitrogen sites with a moderate adsorption energy. Further, the diffusion barrier was also found to be low. These findings may qualify TiN, a versatile multifunctional material with electronic conductivity, as electrode material for the hydrogen evolution reaction (HER). This was the main impetus of this work which aims to experimentally and theoretically investigate the electrocatalytic properties of TiN-layers that were processed on Ti substrate using reactive ion sputtering. The properties are discussed focusing on the role of oxygen defects introduced during the sputtering process on the HER. Based on DFT calculations, it is shown that these oxygen defects alter the electronic environment of the Ti atoms which entails a low hydrogen adsorption energy in the range of -0.1 eV; this leads to HER performances that match those of Pt-NPs in acidic media. When a few nanometr thick layer of Pd-NPs is sputtered on-top of the TiN-layer, the performance is drastically reduced. This is interpreted in terms of oxygen defects being scavenged by the Pd-NPs near the surface which is thought to reduce the hydrogen adsorption sites.

The mechanism of sex determination and differentiation in animals remains a central focus of reproductive and developmental biology research, and the regulation of sex differentiation in amphioxus remains poorly understood. Cytochrome P450 Family 19 Subfamily A member 1 (CYP19A1) is a crucial sex differentiation gene that catalyzes the conversion of androgens into estrogens. In this study, we identified two aromatase-like genes in amphioxus: cyp19-like1 and cyp19-like2. Cyp19-like1 is more primitive and may represent the ancestral form of cyp19 in zebrafish and other vertebrates. Cyp19-like2, on the other hand, is likely the result of gene duplication within am-phioxus suggesting its potential role as a key gene in sex differentiation. To gain further insights into the expression patterns of these two aromatase-like, we examined their expression in different gonad tissues and during different stages of gonad development. While the expression patterns of the two genes differ in gonad tissues, both are highly expressed in the gonad primordium and are primarily localized to microsomal membrane systems. However, as development proceeds, their expression levels decrease significantly. This study enhances our understanding of sex dif-ferentiation mechanisms in amphioxus and provides valuable insights into the formation and evolution of sex determination mechanisms in vertebrates.

Extraction of high-resolution surface waves is essential in surface-wave survey. Because reflections usually interfere with surface waves on X component in a multicomponent seismic exploration, it is difficult to extract dispersion curves of surface waves. The situation goes more serious when the frequencies and velocities of higher-mode surface waves are close to those of PS-waves. A method for surface-wave extraction is proposed based on the morphological differences between reflections and surface waves. Frequency-domain high-resolution linear Radon transform (LRT) and time-domain high-resolution hyperbolic Radon transform (HRT) are used to represent surface waves and reflections respectively. Then, the sparse representation problem based on the morphological component analysis (MCA) is built and optimally solved to obtain high-fidelity surface waves. An advantage of our method is its ability to extract surface waves when their frequencies and velocities are close to those of reflections. Furthermore, results of synthetic and field examples confirm that the proposed method can attenuate the distortion of surface-wave dispersive energy caused by reflections, which contributes to extracting accurate dispersion curves.

To investigate the effect of prohexadione-calcium (Pro-Ca) primed on seed germination and seedling growth of oilseed rape under salt stress, to alleviate the inhibition of soil salinization on the growth of oilseed rape, and to improve the sustainability of agricultural production. Using Huayouza 158R and Huayouza 62 as test materials, the regulation of seed germination and seedling growth under the stresses of 0, 100, and 150 mM NaCl (S0, S100, and S150) was investigated after the primed of Pro-Ca. We conducted six treatments, S0: non-primed + 0 mM NaCl, PCS0: Pro-Ca primed + 0 mM NaCl, S100: non-primed + 100 mM NaCl, PCS100: Pro-Ca primed + 100 mM NaCl, S150: non-primed + 150mM NaCl, Pro-Ca+S150: Pro-Ca primed + 150 mM NaCl. The results showed that salt stress inhibited seed germination and seedling growth, and Pro-Ca primed significantly increased the germination index and vigor index of oilseed rape seeds. The average germination time and malondialdehyde (MDA) content were significantly reduced, which resulted in the optimal initiation fiddling concentration of 8mg·L-1. The morphological parameters of oilseed rape decreased significantly under salt stress, with leaf area decreasing by 70.69% and 75.03% and total chlorophyll content decreasing by 18.55% and 18.68% at S150. With the rise of salt stress, the changes of each photosynthetic parameter were somewhat similar, and Pn, Gs, Ci, and Tr continued to decline, indicating that the effects of salt stress on photosynthesis in oilseed rape might be mainly attributed to stomatal restriction and inhibition of photosynthetic pigment synthesis. While Na+ and MDA contents increased significantly, reaching a peak at S150, indicating that Na+ content increased significantly under salt stress, which resulted in the slow growth of oilseed rape and weak plants under the influence of Na+ salt damage. After Pro-Ca primed, leaf area and photosynthetic pigment synthesis increased, and the initiation treatment promoted the rise of Pn, Gs, Ci, and Tr under salt stress. The Na+ content decreased by 7.29% and 6.96% in PCS100 compared with S100, decreased by 9.23% and 25.02% in PCS150 compared with S150, and increased in K+ and Mg2+ after Pro-Ca primed. At this time, the antioxidant enzyme activities increased, and the MDA content and relative conductivity decreased. It was concluded that Pro-Ca primed improved the photosynthetic capacity of oilseed rape by promoting leaf growth, stomatal opening, and photosynthetic pigment synthesis. At the same time, reducing Na+ content and promoting K+ and Mg2+ absorption and antioxidant enzyme activities together alleviate salt damage and improve salt tolerance of oilseed rape.

Unmanned Underwater Vehicles (UUVs) are pivotal in ocean exploration, research, and various industrial activities such as marine mining and offshore engineering. However, traditional methods of navigating these vehicles face significant challenges, mainly due to the inefficacy of electromagnetic waves in water, leading to signal loss. To address these limitations, researchers are increasingly turned learning, an artificial intelligence technique capable of learning from data-enhancing underwater navigation, mainly through visual Simultaneous Localization and Mapping (SLAM). This paper explores integrating deep learning methodologies and sensor technologies to revolutionize underwater navigation for UUVs. Proprioceptive sensors, along with exteroceptive sensors, are crucial in accurately measuring and comprehending the underwater environment. Additionally, the paper provides detailed insights into the processes of underwater SLAM, camera-based underwater positioning systems, sonar systems for underwater navigation, and the utilization of Lidar in underwater navigation. Furthermore, it delves into applying deep learning techniques in underwater SLAM, offering a comprehensive understanding of the innovative processes driving advancements in underwater vehicle navigation. By leveraging these advancements, this research aims to improve underwater navigation systems' precision, reliability, and adaptability, thereby unlocking new frontiers in ocean exploration and industrial applications for UUVs.

Conditions under which compositions of component systems form a well-defined system-of-systems here are formulated at a fundamental level. Statement of what defines a well-defined composition and sufficient conditions guaranteeing such a result offers insight into exemplars that can be found in special cases such as differential equation and discrete event systems. For any given global state of a composition, two requirements can be stated informally as: 1) the system can leave this state, i.e., there is at least one trajectory defined that starts from the state, and 2) the trajectory evolves over time without getting stuck at a point in time. Considered for every global state, these conditions determine whether the resultant is a well-defined system and if so, whether it is non-deterministic or deterministic. We formulate these questions within the framework of iterative specifications for mathematical system models that are shown to be behaviorally equivalent to the Discrete Event System Specification (DEVS) formalism. This formalization supports definitions and proofs of the afore-mentioned conditions. Implications are drawn at the fundamental level of existence where the emergence of a system from an assemblage of components can be characterized. We focus on systems with feedback coupling where existence and uniqueness of solutions is problematic.

This paper analyses the application of deep learning techniques for predicting wave overtopping events in port environments using sea state and weather forecasts as inputs. The study was conducted in the outer port of Punta Langosteira, A Coruña, Spain. A video recording infrastructure was installed to monitor overtopping events from 2015 to 2022, identifying 3709 overtopping events. The data collected was merged with actual and predicted data for the sea state and weather conditions during the overtopping events, creating three datasets. We used these datasets to create several machine learning models to predict whether an overtopping event would occur based on sea state and weather conditions. The final models achieved a high accuracy level during the training and testing stages: 0.81, 0.73, and 0.84 average accuracy during training and 0.67, 0.48, and 0.86 average accuracy during testing, respectively. The results of this study have significant implications for port safety and efficiency, as wave overtopping events can cause disruptions and potential damage. Using deep learning techniques for overtopping prediction can help port managers take preventative measures and optimize operations, ultimately improving safety and helping to minimize the economic impact that overtopping events have on the port's activities.

Marine industries are dependent on the ocean and often have a direct impact on the marine environment. Although previous studies have talked about pollution from marine industries, it is not known to what extent and to what extent these behaviors affect the ocean. Therefore, this study examines the impacts of major marine industries on the marine environment, using China as an example. The Ministry of Ecology and Environment of the People's Republic of China categorizes the quality of seawater into Class I, Class II, Class III, Class IV, and Inferior Class IV in descending order according to the quality from good to poor. In this study, water quality of Class I and Class II are defined as good quality seawater, Class III as average quality, Class IV and Class IV as poor quality, and the proportion of the area of seawater with different water quality to the total area of the sea area symbolizes the overall quality of the marine environment. We use panel data from 11 provinces and cities along the coast of mainland China from 2006 to 2020, estimated by the full feasible generalized least squares (FGLS) method, to study the impacts of the development of coastal tourism, marine transportation, marine shipbuilding, marine salt, mariculture, and marine fishing on the marine environment. The empirical results show that, in descending order of the degree of influence, the marine industries that cause a decrease in the area of good quality seawater are coastal tourism, mariculture and shipbuilding, and the marine industries that cause an increase in the area of poor quality seawater are marine transportation and shipbuilding, while the marine salt industry has no obvious influence on the marine environment, and the development of the marine fishing industry indirectly contributes to the improvement of the marine environment.

Climate change poses a significant threat to global food security, necessitating a thorough examination across multiple dimensions. Establishing appropriate food security evaluation indicators that align with the evolving concept of food security is imperative. This study enhances food security evaluation by refining a multi-dimensional framework and analyzing the impact of climate change across various regions from 2002 to 2021. By constructing an Food Security Index system composed of a three-tier indicator system and employing the entropy method for weighting, we assess the impacts of climate change on food security using a climate-economic model. Regression analysis reveals a negative linear relationship between mean temperatures and food security (p<0.01), while precipitation impacts food security non-linearly, particularly exhibiting inverse U-shaped patterns in major grain-producing and grain-consuming areas. Extreme high temperatures consistently reduce food security, whereas extreme precipitation displays a complex, statistically significant inverse U-shaped association. In regions where production and consumption are balanced, mean temperatures have a negative effect on food security, while precipitation exhibits a positive correlation, but excessive precipitation can have adverse effects. These findings highlight the intricate interplay between climate change, regional disparities, and food security in China, emphasizing the need to consider multi-dimensional factors and regional variations in addressing food security challenges. These insights are invaluable for policy-making and planning aimed at enhancing food security in China.

This topical review describes the results of recent research into and development of silicon nitride, a ceramic material with unique properties. The outcome of this ongoing research strongly encourages the use of monolithic silicon nitride and coatings as contemporary and future biomaterial for a variety of medical applications. Crystallographic structure, synthesis and processing of monolithic structures and coatings, and examples of their medical applications are covered that relate to spinal, orthopedic and dental implants, bone grafts and scaffolds, platforms for intelligent synthetic neural circuits, antibacterial and antiviral particles and coatings, optical biosensors, and nano-photonic waveguides for sophisticated medical diagnostic devices. The examples provided show convincingly that silicon nitride is destined to become a leader to replace titanium and other entrenched biomaterials in many fields of medicine.

A method for solving the turbulence equations embedded in the sigma ocean general ocean circulation model is proposed. Like the general circulation model, the turbulence equations are solved using the splitting method by physical processes. The turbulence equations are split into two main stages describing transport-diffusion and generation-dissipation processes. Parameterization of turbulence in the framework of equations allows, at the generation-dissipation stage, to use both numerical and analytical solutions and to ensure high efficiency of the algorithm. The results of large-scale ocean dynamics simulation taking into account the parameterization of vertical turbulent exchange are considered. Numerical experiments were carried out using k-omega turbulence model embedded to the Institute of Numerical Mathematics Ocean general circulation Model (INMOM). Both the circulation and turbulence models are solved using the splitting method with respect to physical processes. The coupled model is used to simulate the hydrophysical fields of the North Atlantic and Arctic Oceans for 1948--2009. The model has a horizontal resolution of 0.25 degree and 40 sigma-levels along the vertical. The sensitivity of the solution to the changes in mixing parameterization is studied. Experiments demonstrate that taking into account the climatic annual mean buoyancy frequency improves the reproduction of large-scale ocean characteristics. There is a positive effect of Prandtl number variations for reproducing the upper mixed layer depth. The experiments also demonstrate the computational effectiveness of the proposed approach in solving the turbulence equations.

The increasing demand for higher power in rocket launchers is driving the development of higher power nozzles, achieved essentially by increasing the expansion ratio. However, this can lead to flow separation and resulting unsteady, asymmetrical forces, called side loads, which can limit the life of both the nozzle itself and other engine components. If this problem can be overcome, engine performance can be significantly increased. Therefore, various separation control methods have been proposed, but none have been fully implemented to date due to the uncertainties associated with modeling and predicting the flow phenomena. A numerical study of high area ratio rocket engine is presented to analyze the aeroelastic performance of the structure under the condition of flow separation. The finite volume method, the 2nd order upwind scheme and the extended wall function are used to analyze the flow inside the rocket nozzle and the transition of the Free Shock Separation (FSS) to Restricted Shock Separation (RSS) separation pattern ) to be discussed in detail. Since the location of the flow separation point depends heavily on the flow.

The effect of graphene (GR) on Ni surface relaxation and reconstruction in three different substrate orientations: {111}, {001}, {011}, at two different temperatures: 300K and 400K was studied using Molecular Dynamics simulation. The change of the interplanar distances of the substrate and redistribution of Ni and C atoms in direction perpendicular to the surface were compared with the equilibrium state of GR and bulk Ni, in the absence of the counterpart. The surface reconstruction for GR/Ni system was analyzed base on the calculated radial pair distribution function of Ni and C atoms. The surface roughness was visualized using 2D atomic distribution maps. For the studied substrate orientations and temperatures, it was found that the most densely packed orientation of the Ni base {111} provides minimal changes of the structural parameters of both counterparts at 400 K.

In mesoscale eddies, chemical properties and biological composition are different from those in surrounding water, due to their unique physical processes. It is unclear how physical-biological coupling occurs in warm-core eddies, particularly since no study has examined the relationship between bacteria and viruses. The purpose of the present study was to examine the influence of anticyclonic warm eddy on the relationship between bacterial and viral abundances as well as viral activity (viral production) in different depths. In the core of warm eddy, bacterial abundance (0.48 to 2.82 ×105 cells mL−1) fluctuated less than that of the outside eddy (1.12 to 7.03×105 cells mL−1). In particular, there was four-folds higher of viral-bacterial abundance ratio (VBR) estimated within the eddy below DCM than the outside eddy. We suggest that prevailing physical forces with downwelling at the center of the anticyclonic warm eddy, viruses can also be transmitted into the deep ocean directly through adsorption on particulate organic matter during sinking. Overall, our findings provide valuable insights into the interaction between bacterial and viral communities and their ecological mechanism within the warm eddy.

Ship wave is of great interest for wave drag, coastal erosion and ship detection. In this paper, a highly-paralleled numerical scheme is proposed for simulating three-dimensional (3-D) nonlinear Kelvin ship waves effectively. First, a numerical model for nonlinear ship waves is established based on potential flow theory, boundary integral method and Jacobian-free Newton-Krylov (JFNK) method. In order to improve computational efficiency and reduce data storage of JFNK method, a banded preconditioner method is then developed by formulating the optimal bandwidth selection rule. After that, a Graphics Process Unit (GPU) based parallel computing framework is designed, and a GPU solver is developed by using Compute Unified Device Architecture (CUDA) language. Finally, numerical simulations of 3-D nonlinear ship waves under multiple scales are performed by using the GPU and CPU solvers. Simulation results show that the proposed GPU solver is more efficient than the CPU solver with the same accuracy. More than 66% GPU memory can be saved and the computational speed can be accelerated up to 20 times. Hence, the computation time for Kelvin ship waves simulation can be significantly reduced by applying the GPU parallel numerical scheme, which lays a solid foundation for practical ocean engineering.

We have carried out a systematic review of the scientific literature published on PM and, more specifically, on its presence in fish and seafood of interest to the population from Mediterranean area. Given its preference and wide acceptability in the scientific community, we followed the PRISMA. The potential functional and clinical toxicity in humans due to MP in fish must be considered by the chemical composition of the microplastics the presence of PM and its additives, associated contaminants and pathogens in fish and shellfish, as well as the possible effects on human health, requires improving legislation on evaluation and providing a basis for consumer protection.

Validation of satellite sea surface salinity (SSS) products is typically based on comparisons with in-situ measurements at a few meters depth, that are mostly done at a single location and time. The difference in term of spatio-temporal resolution between the in-situ near-surface salinity and the two-dimensional satellite SSS results in a sampling mismatch uncertainty. The Climate Change Initiative (CCI) project has merged SSS from three satellite missions. Using an optimal interpolation, weekly and monthly SSS and their uncertainties are estimated at a 50 km spatial resolution over the global ocean. Over the 2016-2018 period the mean uncertainty on weekly CCI SSS is 0.13, whereas the standard deviation of weekly CCI minus in-situ Argo salinities is 0.24. Using high resolution SSS simulations, we estimate the expected uncertainty due to the CCI versus Argo sampling mismatch. Most of the largest spatial variability of the satellite minus Argo salinity are observed in regions with large mismatch. A quantitative validation is performed by considering the statistical distribution of the CCI minus Argo salinity normalized by the sampling and retrieval uncertainties. This quantity should follow a Gaussian distribution with a standard deviation of 1, if all uncertainty contributions are properly considered. We find that 1) the sampling mismatch can explain most of the observed differences between Argo and CCI data, especially for monthly products and in dynamical regions (river plumes, fronts), 2) overall, the uncertainties are well estimated in CCI version 3, much better compared to CCI version 2. There are a few dynamical regions where discrepancies remain, and where the satellite SSS, their associated uncertainties and the sampling mismatch estimates should be further validated.

In this work, we consider a one-dimensional laminated beam in the case of non-equal wave speeds with only one infinite memory on the effective rotation angle. In this case, we establish the general decay result for the energy of solution without any kind of internal or boundary control. The main result is obtained by applying the method used in Guesmia et al. (Electron. J. Differential Equations 193: 1-45, 2012) and the second-order energy.

The unsteady flow around the monopile under the influence of wave and vibration is studied by numerical method. Based on VOF model and SST Turbulence model, combined with Intermittent Transition model and dynamic mesh method, wave generation and pile vibration in numerical flume are simulated. The flow field around vibrating monopile in a calm water flume and a wave flume is simulated and the simulation results are compared. The calculation results show that the monopile vibration has a great disturbance to the unsteady flow around the pile, and the disturbance degree intensifies with the increase of the vibration amplitude of the monopile: Under the action of inertia, the vibration of the monopile leads to the reattachment of the shedding vortices; Under the influence of the reattachment vortices, the asymmetry of the vorticity on the side wall of the monopile intensifies; The intensification of the disturbance causes the reduction of the phase lead angle of the bed shear stress on the side of the single pile, and an additional high bed shear stress appears on the side of the monopile. In addition, the vortex structure formed alternately around the monopile during the vibration process leads to the periodic change of the high bed shear stress.

The intense motion of a ship can greatly impacts the comfort of crew members and the safety of the vessel. Therefore, accurately estimating and predicting ship attitudes has become an important issue. This paper introduces the latest development in functional deep learning model called DeepOnet. It takes wave height as input and ship motion as output, using a cause-to-result prediction approach. The modeling data used in this study is sourced from publicly available experimental data from the Iowa Institute of Hydraulic Research. Firstly, parameters system tuning was conducted for the neural network's hyperparameters to determine the appropriate combination of parameters. Secondly, the DeepOnet model for wave height and multi-degree-of-freedom motion was established, and the influence of increasing time steps on prediction accuracy was examined. Finally, a comparison was made between the DeepOnet model and the classical time series model LSTM. It was found that the DeepOnet model had a 10-fold improvement in accuracy for roll and heave attitudes. Moreover, as the forecast duration increased, the advantage of DeepOnet showed a trend of strengthening. As a functional prediction model, DeepOnet provides a new promising tool for very short-term prediction of ship motion.

Antioxidant, anti-inflammatory and chemo-preventive features have been reported for the carotenoid diatoxanthin. Diatoxanthin is only produced by a few groups of microalgae where it functions in photoprotection. Its large-scale production in microalgae is currently not feasible. In fact, rapid conversion into the inactive pigment diadinoxanthin is triggered when the cells are removed from the high-intensity light source, which will be the case during large-scale harvesting of microalgae biomass. Zeaxanthin epoxidase (ZEP) 2 and/or ZEP3 have been suggested to be responsible for the back-conversion of high-light accumulated diatoxanthin to diadinoxanthin in low light in diatoms. Using the CRISPR/Cas9 gene editing technology we knocked out the ZEP2 and ZEP3 genes in the already commercially used marine diatom Phaeodactylum tricornutum to investigate their role in the diadinoxanthin-diatoxanthin cycle, and to determine if one of the mutant strains could function as a diatoxanthin production line. Light shift experiments proved that ZEP3 encodes the enzyme converting diatoxanthin to diadinoxanthin in low light. Loss of ZEP3 caused the high-light accumulated diatoxanthin to be stable for several hours after the cultures had been returned to low light, suggesting that zep3 mutant strains could be suitable as commercial production lines of diatoxanthin.

The bioindicator potential of seagrass ecosystems in coastal trace metal monitoring is low for tropical island ecosystems. This study evaluated the bioindicator potential of six seagrass species exposed to anthropogenic trace metal pollution in the Andaman and Nicobar Islands (ANI) of India. Sediment and seagrass biomass, samples were analyzed for trace metals (Co, Cr, Cu, Fe, Mg, Mn, Ni, Pb, Zn) from four locations of ANI exposed to anthropogenic contamination. Geo accumulation Index values indicated moderate trace metal contamination in seagrass sediment. Seagrass trace metal accumulation from sediment was both species-specific and location- specific for ANI. Small seagrass species such as H. ovalis, H. beccarii and H. uninervis accumulated the maximum concentration of six trace metals (Cr, Cu, Fe, Ni, Pb, Zn) in their tissues compared to big seagrass species like T. hemprichii and E. acoroides of ANI. This study indicates leaves of small seagrass and roots of big seagrass species can serve as short- and long-term bioindicators respectively, of coastal trace metal contamination in tropical islands of ANI.

To conduct high-precision and high-resolution numerical simulation of complex flow structures in turbomachinery, a high-order finite volume weighted essentially non-oscillatory (WENO) scheme for the large eddy simulation (LES) is improved and embedded into the three-dimensional viscous unsteady CFD solver NUAA-Turbo. Firstly, the spectral characteristics and unsteady convergence of the improved WENO scheme are studied. Compared with the classical WENO scheme, the improved WENO scheme has better dissipation and dispersion characteristics and faster convergence speed. Then, the coefficient CW of the Wall-Adapting Local Eddy-viscosity (WALE) model is calibrated by decaying homogeneous isotropic turbulence (DHIT) test case. Finally, the scheme is applied to conduct high-precision LES calculations of turbulent boundary layer flow, supersonic compression corner flow, and low-pressure turbine cascade separation flow. The numerical simulation results show that this WENO scheme has excellent shock wave capture ability and turbulence resolution and can capture more flow field details with less mesh size, greatly reducing the computational cost and laying a foundation for large-scale engineering application of LES.

Unmanned vehicles (UVs) have become increasingly important in various scenarios of civil and military operations. The present work aims at the conceptual design of a modular Amphibious Unmanned Ground Vehicle (A-UGV), that can be easily adapted for different types of land and/or water missions, with low monetary cost (<5k€, without sensors). Basing the design on the needs highlighted in the 2021 review of the Strategic Directive of the Portuguese Navy, the necessary specifications and requirements are established for two mission scenarios. Then a market research analysis focused on vehicles currently available, and their technological advances, is conducted to identify existing UVs solutions and respective characteristics/capabilities of interest to the current work. To study and define the geometry of the hull and the configuration of the A-UGV itself, preliminary computational structural and fluid analyses are carried out to ensure it complies with the specifications initially established. As a result, one obtains a fully electric vehicle, with approximate dimensions of 1050×670×450mm (length-width-height), enabled with 6×6 traction capable of reaching 20km/h in land, possesses amphibious capabilities of independent propulsion in water up to 8kts, and with an estimated autonomy of over 60 minutes.

This study assesses the performance of the Weather Research and Forecasting (WRF) model using a high-resolution spatial grid (1 km) with various combinations of physical parameterization packages to simulate a severe event in August 2021 in the southeastern Brazilian coast. After determining the optimal set of physical parameterizations for representing wind patterns during this event, a year-long evaluation was conducted, covering forecast horizons of 24, 48, and 72 hours. The simulation results were compared with observational wind data from four weather stations. The findings highlight variations in the efficacy of different physical parameterization sets, with certain sets encountering challenges in accurately depicting the peak of the severe event. The most favorable results were achieved using a combination of Tiedtke (cumulus), Thompson (microphysics), TKE (boundary layer), Monin-Obukhov (surface layer), Unified-NOAH (land surface), and RRTMG (shortwave and longwave radiation). Over the one-year forecasting period, the WRF model effectively represented the overall wind pattern, including forecasts up to three days in advance (72-hour forecast horizon). Generally, the statistical metrics indicate robust model performance, even for the 72-hour forecast horizon, with correlation coefficients consistently exceeding 0.60 at all analyzed points. While the model proficiently captured wind distribution, it tended to overestimate northeast wind speed and gust intensities. Notably, forecast accuracy decreased as stations approached the ocean, exemplified by the ATPM station.

This study introduces an alternative to the existing methods for measuring ocean currents based on a recently developed technology. The SailBuoy is an unmanned surface vehicle powered by wind and solar panels that can navigate autonomously to predefined way-points and record velocity profiles using an integrated downward-looking Acoustic Doppler Profiler (ADCP). Data, collected on two validation campaigns, shows a satisfactory correlation between the SailBuoy current records and traditional observation techniques such as bottom mounted and moored current profilers and moored single-point current meter. While the highest correlations were found in tidal signals, strong current, and calm weather conditions, low current speeds and varying high wave and wind conditions reduced correlation considerably. Filtering out some events with high sea surface roughness associated with high wind and wave conditions may increase the SailBuoy ADCP listening quality and lead to better correlations. Not yet resolved is a systematic offset between the measurements obtained by the SailBuoy and the reference instruments of ± 0.03 m/s. Possible reasons are discussed to be the differences between instruments (various products) as well as changes in background noise levels due to environmental conditions.

This paper is aimed at studying the temporal evolution of the surface displacements occurred over the past few years in the ocean-reclaimed platforms of the Shanghai megacity (China), which are mainly ascribable to consolidation processes of large dredger fills and alluvial deposits. With respect to previous analyses carried out over the same area, this work provides a joint multi-platform differential interferometry synthetic aperture radar (DInSAR) analysis, based on the application of the advanced Small BAseline Subset (SBAS) algorithm. This led us to retrieve long-term deformation time-series that are helpful for a better understanding of the on-going deformation phenomena. To this aim, we have exploited two sequences of SAR data collected by the ASAR/ENVISAT and by the COSMO-SkyMed (CSK) sensors, respectively, spanning the whole time period from 2007 to 2016. Unfortunately, the large time gap (of about three years) existing between the available ASAR/ENVISAT and CSK datasets gave rise to additional difficulties for their combination. Nevertheless, this problem has been faced by benefiting from the knowledge of a time-dependent model describing the temporal evolution of the expected deformations affecting the Shanghai ocean-reclaimed platforms.

As the energy efficiency demands for future buildings become increasingly stringent, preliminary assessments of energy consumption are mandatory. These are possible only through numerical simulations, whose reliability crucially depends on boundary conditions. We therefore investigate their role in numerical estimates for the usage of geothermal energy, performing annual simulations of transient heat transfer for a building employing a geothermal heat pump plant and energy piles. Starting from actual measurements, we solve the heat equations in 2D and 3D using COMSOL Multiphysics and IDA-ICE, and discover a negligible impact of the multiregional ground surface boundary conditions. Moreover, we verify that the thermal mass of the soil medium induces a small vertical temperature gradient on the piles surface. We also find a roughly constant temperature on each horizontal cross-section, with nearly identical values if the average temperature is integrated over the full plane or evaluated at one single point. Calculating the yearly heating need for an entire building we then show that the chosen upper boundary condition affects the energy balance dramatically. Using directly the pipes’ outlet temperature induces a 54% overestimation of the heat flux, while the exact ground surface temperature above the piles reduces the error to 0.03%.

In this paper, a semi-empirical model of air waves induced by falling rock is described. The model is composed of a uniform motion phase (velocity close to 0 m·s^-1) and an acceleration movement phase. The uniform motion phase was determined based on experimentally and the acceleration movement phase was derived by theoretical analysis. A series of experiments were performed to verify the semi-empirical model and elucidated the law of the uniform motion phase. The acceleration movement phase accounted for a larger portion with a greater height of the falling rock. Experimental results of different falling heights of the goaf showed close agreement with theoretical analysis values. The semi-empirical model could accurately and conveniently estimate the velocity of air wave induced by falling rock. Thus, the semi-empirical model can provide a reference and basis for estimating the speed of air waves and designing protective measures in mines.

Downward short-wave (SW) solar radiation is the only essential energy source powering the atmospheric dynamics, ocean dynamics, biochemical processes, etc. on our planet. Clouds are the main factor limiting the SW flux over the land and the Ocean. For the accurate meteorological measurements of the SW flux one needs expensive equipment - pyranometers. For some cases where one does not need golden-standard quality of measurements, we propose estimating incoming SW radiation flux using all-sky optical RGB imagery which is assumed to incapsulate the whole information about the SW flux. We used DASIO all-sky imagery dataset with corresponding SW downward radiation flux measurements registered by an accurate pyranometer. The dataset has been collected in various regions of the World Ocean during several marine campaigns from 2014 to 2022, and it will be updated. We demonstrate the capabilities of several machine learning models in this problem, which are multilinear regression, Random Forests, Gradient Boosting and convolutional neural networks (CNN). We also applied the inverse target frequency (ITF) re-weighting of the training subset and the approach of pre-classification in order to raise the SW flux approximation quality. We found that the CNN is capable of approximating downward SW solar radiation with higher accuracy compared to existing empiric parameterizations. We also found that the ITF reweighting of the training subset increases the approximation quality substantially. The estimates of the SW radiation flux using all-sky imagery may be of particular use in case of the need for the fast radiative budgets assessment of a site.

Assessing corneal biomechanics in vivo has long been a challenge in the field of ophthalmology. Although recent wave-based optical coherence elastography (OCE) methods have shown promise in this area, the effect of intraocular pressure (IOP) on mechanical wave propagation in the cornea remains unclear. To address this, we constructed an artificial eye model and performed surface wave OCE measurements in the radial directions (54–324°) of the silicone cornea at varying IOP levels (10–40 mmHg). The results demonstrated increases in wave propagation speeds (mean ± STD) from 6.55 ± 0.09 m/s (10 mmHg) to 9.82 ± 0.19 m/s (40 mmHg), leading to an estimate of Young’s modulus, which increased exponentially from 145.23 ± 4.43 kPa to 326.44 ± 13.30 kPa. Our implementation of an artificial eye model highlighted that the impact of IOP on Young’s modulus (ΔE = 165.59 kPa, IOP: 10–40 mmHg) was more significant than the effect of stretching of the silicone cornea (ΔE = 15.79 kPa, relative elongation: 0.98%–6.49%). Our study sheds light on the potential of using an artificial eye model in OCE research for corneal biomechanics. Furthermore, it is critical to consider the impact of IOP on measurement results when utilizing wave-based OCE in clinical settings for enhanced assessment of corneal biomechanics.

In this paper, we first discuss the research status and application progress of the finite element method and the smoothed particle method. By analyzing the advantages of the smoothed particle method and the finite element method, a new coupling algorithm, namely FEM-SPH algorithm, is proposed. By the method of comparison, it shows that finite element method and SPH method in the simulation of large deformation problems each have advantages and disadvantages, the finite element method smoothed particle coupling algorithm is effective to achieve the performance of high computational efficiency and can naturally simulate large deformation problems across. In the process of calculation, the large deformation unit can be freely into an algorithm to facilitate the calculation accuracy and efficiency of three methods of numerical simulation. Through the study found, FEM-SPH algorithm not only overcome the defect of smooth particle tensile instability, but also overcomes the problem of low efficiency of finite element computation. To further test the FEM-SPH algorithm has advantages in the practical engineering, we have carried out the actual test to the example of the super high speed collision, concluded that, since the target of most of the computational domain is always finite element, smoothed particle focused only in contact with the projectile and target of local area, particle number is not much, the whole calculation process just ten minutes, computational efficiency has been greatly improved, at the same time in the simulation of large deformation, the advantage is very obvious .This provides a criterion for the actual project, depending on the specific material deformation mode and choose a more appropriate conversion algorithm.

This paper presents a numerical study on the laser shock wave propagation in a 3D woven CFRP material by means of detailed and homogenized FE models. The aim of the study is to numerically characterize the shock wave response of the 3D woven CFRP in terms of back face velocity profiles and the induced damage and to investigate whether the detailed FE models could be replaced by homogenized FE models. The 3D woven geometry was designed using the TexGen software, while the numerical analyses were executed using the LS-Dyna explicit FE software. A high-strain rate behavior was considered for the matrix. The fiber bundles in the detailed models were modeled as a high fiber content unidirectional composite laminate, with its mechanical properties calculated by micromechanical equations. Both for the fiber bundles of the detailed model and the homogenized models a progressive damage material model was applied. The results of the detailed model reveal a considerable effect of material’s architecture on the shock wave propagation and the sensitivity of the back face velocity profile to the spot location. Consequently, the homogenized model is not capable of accurately simulating the shock wave response of the 3D woven composite. Moreover, the detailed predicts with high accuracy matrix cracking in the resin-rich areas and in the bundles as well as fiber failure. On the contrary, the homogenized model predicts matrix cracking at the same areas and no fiber failure.

Estimating ground surface PM2.5 with fine spatiotemporal resolution is a critical technique for exposure assessments in epidemiological studies of its health risks. Previous studies have utilized monitoring, satellite remote sensing or air quality modeling data to evaluate the spatiotemporal variations of PM2.5 concentrations, but such studies rarely combined these data simultaneously. We develop a three-stage model to fuse PM2.5 monitoring data, satellite-derived aerosol optical depth (AOD) and community multi-scale air quality (CMAQ) simulations together and apply it to estimate daily PM2.5 at a spatial resolution of 0.1˚ over China. Performance of the three-stage model is evaluated using a cross-validation (CV) method step by step. CV results show that the finally fused estimator of PM2.5 is in good agreement with the observational data (RMSE = 23.00 μg/m^3 and R2 = 0.72) and outperforms either AOD-retrieved PM2.5 (R2 = 0.62) or CMAQ simulations (R2 = 0.51). According to step-specific CVs, in data fusion, AOD-retrieved PM2.5 plays a key role to reduce mean bias, whereas CMAQ provides all-spacetime-covered predictions, which avoids sampling bias caused by non-random incompleteness in satellite-derived AOD. Our fused products are more capable than either CMAQ simulations or AOD-based estimates in characterizing the polluting procedure during haze episodes and thus can support both chronic and acute exposure assessments of ambient PM2.5. Based on the products, averaged concentration of annual exposure to PM2.5 was 55.75 μg/m3, while averaged count of polluted days (PM2.5 > 75 μg/m3) was 81, across China during 2014. Fused estimates will be publicly available for future health-related studies.

In this paper we report a new development on the numerical model for aluminum-steam combustion. This model is based on diffusion flame of continuum regime and the thermal equilibrium between the particle and the flow field, which can be used to calculate the aluminum particle combustion model for two phase calculation conditions. The model prediction is in good agreement with the experimental data. A new type of vortex combustor was proposed for the combustion of aluminum and steam, and the mathematical model of the two phase reacting flow with in this combustor was established. The turbulence effects are modeled using the Reynolds Stress Model (RSM) with Linear Pressure-Strain approach, and the Eddy-Dissipation model is used to simulate the gas phase combustion. Aluminum particles are injected into the vortex combustor and form a swirling flow around the chamber and their trajectories are traced using the Discrete Phase Model (DPM). The simulation results show that the vortex combustor can achieve high efficient combustion of aluminum and steam. The influencing factors, such as the eccentric distance of the inlet of aluminum particles, particle size and steam inlet diameter, etc., are studied. The work described in this paper represents an attempt to the design of a vortex combustor in order to increase aluminum combustion efficiency.

Fire detection from satellite sensors relies on an accurate estimation of the unperturbed state of a target pixel, from which an anomaly can be isolated. Methods for estimating the radiation budget of a pixel without fire depend upon training data derived from the location's recent history of brightness temperature variation over the diurnal cycle, which can be vulnerable to cloud contamination and the effects of weather. This study proposes a new method that utilises the common solar budget found at a given latitude in conjunction with an area's local solar time to aggregate a broad-area training dataset, which can be used to model the expected diurnal temperature cycle of a location. This training data is then used in a temperature fitting process with the measured brightness temperatures in a pixel, and compared to pixel-derived training data and contextual methods of background temperature determination. Results of this study show similar accuracy between clear-sky medium wave infrared upwelling radiation and the diurnal temperature cycle estimation compared to previous methods, with demonstrable improvements in processing time and training data availability. This method can be used in conjunction with brightness temperature thresholds to provide a baseline for upwelling radiation, from which positive thermal anomalies such as fire can be isolated.

Seismic travel time tomography using surface waves is an effective tool for three-dimensional crustal imaging. Historically, these surface waves are the result of active seismic sources or earthquakes. More recently, however, also surface waves retrieved through the application of seismic interferometry are exploited. Conventionally, two-step inversion algorithms are employed to solve the tomographic inverse problem. That is, a first inversion results in frequency-dependent, two-dimensional maps of phase velocity, which then serve as input for a series of independent, one-dimensional frequency-to-depth inversions. As such, a two-dimensional grid of localized depth-dependent velocity profiles are obtained. Stitching these separate profiles together subsequently yields a three-dimensional velocity model. Relatively recently, a one-step three-dimensional non-linear tomographic algorithm has been proposed. The algorithm is rooted in a Bayesian framework using Markov chains with reversible jumps, and is referred to as transdimensional tomography. Specifically, the three-dimensional velocity field is parameterized by means of a polyhedral Voronoi tessellation. In this study, we investigate the potential of this algorithm for the purpose of recovering the three-dimensional surface-wave-velocity structure from ambient noise recorded on and around the Reykjanes Peninsula, southwest Iceland. To that end, we design a number of synthetic tests that take into account the station configuration of the Reykjanes seismic network. We find that the algorithm is able to recover the 3D velocity structure at various scales in areas where station density is high. In addition, we find that the standard deviation on the recovered velocities is low in those regions. At the same time, the velocity structure is less well recovered in parts of the peninsula sampled by fewer stations. This implies that the algorithm successfully adapts model resolution to the density of rays. Also, it adapts model resolution to the amount of noise on the travel times. Because the algorithm is computationally demanding, we modify the algorithm such that computational costs are reduced while sufficiently preserving non-linearity. We conclude that the algorithm can now be applied adequately to travel times extracted from (time-averaged) station-station cross correlations by the Reykjanes seismic network.

The variation of aerosols, especially dust aerosol, in time and space plays an important role in climate forcing studies. Aerosols can effectively reduce land surface longwave emission and re-emit energy at a colder temperature, making estimation of downwelling surface longwave radiation (DSLR) with satellite data difficult. Using the latest atmospheric radiative transfer code (MODTRAN 5.0), we simulate the outgoing longwave radiation (OLR) and DSLR under different land surface and atmospheric profile conditions. The results show that dust aerosol has an obvious “warming” effect to longwave radiation compared with other aerosols, that aerosol longwave radiative forcing (ALRF) increased with increasing aerosol optical depth (AOD), and that the atmospheric water vapor content (WVC) is critical to the understanding of ALRF. A method is proposed to improve the accuracy of DSLR estimation from satellite data for the skies under heavy dust aerosols. The AOD and atmospheric WVC under cloud-free conditions with a relatively simple satellite-based radiation model that yields the high accurate DSLR under heavy dust aerosol are used explicitly as model input to reduce the effects of dust aerosol on the estimation of DSLR. Validations of the proposed model with satellites data and field measurements show that it estimates the DSLR accurately under heavy dust aerosol skies. The root mean square errors (RMSEs) are 20.4 W/M² and 24.2 W/M² for Terra and Aqua satellites, respectively, at the Yingke site, and the biases are 2.7 W/M² and 9.6 W/M², respectively. For the Arvaikheer site, the RMSEs are 23.2 W/M² and 19.8 W/M² for Terra and Aqua, respectively, and the biases are 7.8 W/M² and 10.5 W/M², respectively. The proposed method is especially applicable to acquire relatively high accurate DSLR under heavy dust aerosol using MODIS data with available WVC and AOD data.

We review time expansion wave theory and refine our model showing it to accurately match observed cosmological luminosity data. The theory augments general relativity to create a container within which quantum effects can be explained by treating time as an artefact of a fourth spatial dimension that we observe as the expansion of the universe. This leads us to explain mass creation, the speed of light limit, gravity, black holes without singularities and other macroscopic effects. Our model leads to an expansion velocity of 6.87 0.36 × 106 ms-1, which results in a Hubble expansion rate constant of 71.3 3.7 km/s/Mpc. Because of the finite window of time in which we exist, an extra a degree of freedom is available leading to interesting interpretations at the subatomic level. At this size range, then a spin is allowed within the time dimension explaining why wave particle duality occurs and explains the electromagnetic force and other quantum mechanical properties. It provides a solution to the double slit conundrum and can explain how quantum entangled partners can behave in a quantum way and pass seemingly time-defying information. The potential quantitative origin of the fine structure constant which governs the size of the electromagnetic force is also strongly indicated by this theory.

Frontal Polymerization (FP) is recognized as a polymer synthesis method capable of generating a highly localized and self-propagating exothermic front, considered a more rapid and energy-efficient manufacturing scheme for polymer-based fiber-reinforced composite materials. This study conducts a numerical investigation based on the Finite Element Method into the initiation and propagation of frontal polymerization of acrylamide. Utilizing Differential Scanning Calorimetry (DSC) experiments, the study phenomenologically tests the curing kinetics reactions of acrylamide (AM) in deep eutectic solvent (DES)-based polymerizable systems, thereby establishing a curing kinetics model for the autocatalytic reaction of polyacrylamide. By coupling the heat conduction diffusion equation of the frontal polymerization reaction, the Finite Element Method is employed to solve the reaction-diffusion model, aiming to explore the evolution of temperature and degree of curing during the manufacturing process. The results demonstrate the reliability and accuracy of the nth-order autocatalytic model in the study of curing kinetics for DES-based synthesis, indicating that the front propagation speed of the AM-based FP reaction is influenced by the activation temperature, duration of activation temperature, and initial temperature of the solution. Experimental validation of the polyacrylamide manufacturing through frontal polymerization corroborates the accuracy and reliability of the model predictions, providing a reference for the numerical model study and temperature control in the synthesis of acrylamide composite hydrogels via FP.

By using Modified simple equation method, we study the Cahn Allen equation which arises in many scientific applications such as mathematical biology, quantum mechanics and plasma physics. As a result, the existence of solitary wave solutions of the Cahn Allen equation is obtained. Exact explicit solutions interms of hyperbolic solutions of the associated Cahn Allen equation are characterized with some free parameters. Finally, the variety of structure and graphical representation make the dynamics of the equations visible and provides the mathematical foundation in mathematical biology, quantum mechanics and plasma physics.

This study examines the effect of surface currents on the bulk algorithm calculation of wind stress estimated using the scatterometer data during 2007-2020 in the Indian Ocean. In the study region as a whole the wind stress decreased by 5.4% by including currents into the wind stress equation. The most significant reduction in the wind stress is found along the most energetic regions with strong currents such as Somali Current, Equatorial Jets and Aghulhas retroflection. A highest reduction of 11.5% is observed along the equator where the Equatorial Jets prevail. A sensitivity analysis has been carried out for the study region and for different seasons to assess the relative impact of winds and currents in the estimation of wind stress by changing the winds while keeping the currents constants and vice versa. The inclusion of currents decreased the wind stress and this decrease is prominent when the currents are stronger. This study showed that equatorial Indian Ocean is the most sensitive region where the current can impact on wind stress estimation. The results showed that uncertainties in the wind stress estimations are quite large at regional levels and hence better representation of wind stress incorporating ocean currents should be considered in the ocean/climatic models for accurate air-sea interaction studies.

The last-mile logistics in cities have become an indispensable part of the urban logistics system. This study aims to explore the effective selection of last-mile logistics nodes to enhance the efficiency of logistics distribution, strengthen the corporate distribution image, and further reduce corporate operating costs and alleviate urban traffic congestion. This paper proposes a clustering-based approach to identify urban logistics nodes from the perspective of geographic information fusion. This method comprehensively considers several key indicators, including the coverage, balance, and urban traffic conditions of logistics distribution. Additionally, we employed a greedy algorithm to identify secondary nodes around primary nodes, thus constructing an effective nodal network. To verify the practicality of this model, we conducted an empirical simulation study using the logistics demand and traffic conditions in the Xianlin District of Nanjing. This research not only identified the locations of primary and secondary logistics nodes but also provided a new perspective for constructing the urban last-mile logistics system, enriching the academic research related to logistics node construction. The results of this study are of significant theoretical and practical importance for optimizing urban logistics networks, enhancing logistics efficiency, and promoting the improvement of urban traffic conditions.

Detection of early stage corrosion on slender steel members is crucial for preventing buckling failures of steel structures. An active photoacoustic fiber optic sensors (FOS) system has been reported for early stage steel corrosion detection of steel plates and rebars using surface ultrasonic waves. The objective of this paper is to investigate the surface corrosion/rust detection problem on steel rods using numerically simulated surface ultrasonic waves. The finite element method (FEM) is applied in simulating the propagation of ultrasonic waves on steel rod models. Transmission mode of damage detection is adopted, in which one source (transmitter) and one sensor (receiver) are considered. In this research, radial displacements at the receiver were simulated and analyzed by short-time Fourier transform (STFT) for detecting, locating, and quantifying a surface rust located between the transmitter and the receiver. From our time domain and frequency domain analyses, it is found that the presence, location, and dimensions (length, width, and depth) of surface rust can be estimated by ultrasonic waves propagating through the surface rust.

Axial resolution is one of the most important characteristics of a microscope. In all microscopes, a high axial resolution is desired in order to discriminate information efficiently along the longitudinal direction. However, when studying thick samples that do not contain laterally overlapping information, a low axial resolution is desirable as information from multiple planes can be recorded simultaneously from a single camera shot instead of plane-by-plane mechanical refocusing. In this study, we increased the focal depth of an infrared microscope non-invasively by introducing a binary axicon fabricated on barium fluoride substrate close to the sample. Preliminary results of imaging thick and sparse silk fibers showed an improved focal depth with a slight decrease in lateral resolution and increase in background noise.

Urban rail transit hub platform is the most important area for passenger flow distribution. In order to calculate passenger flow volume in platform and evaluate platform service level during rush hours, this paper presents a method for modeling and simulation of passenger flow distribution in platform. Passenger flow distribution model (PFDM) is proposed based on the basic analysis and the superposition principle of passenger flow. Simulation design for PFDM is proposed by Anylogic, which contains simulation process and simulation model. Experiment results show that PFDM and simulation design are effective and accordant with the reality scenario, and the simulation precision is comparatively ideal. This research could provide a beneficial reference for train scheduling and operation management under the viewpoint of traffic safety and service level.

We aimed to investigate the relationship between membrane material and development of membrane fouling in a membrane bioreactor (MBR) using membranes with different pore sizes and hydrophilicities. Batch filtration tests were performed using submerged single hollow fiber membrane ultrafiltration (UF) modules with different polymeric membrane materials including cellulose acetate (CA), polyethersulfone (PES), and polyvinylidene fluoride (PVDF) with activated sludge taken from a municipal wastewater treatment plant. The three UF hollow fiber membranes were prepared by a non-solvent-induced phase separation method and had similar water permeabilities and pore sizes. The results revealed that transmembrane pressure (TMP) increased more sharply for the hydrophobic PVDF membrane than for the hydrophilic CA membrane in batch filtration tests, even when membranes with similar permeabilities and pore sizes were used. PVDF hollow fiber membranes with smaller pores had greater fouling propensity than those with larger pores. In contrast, CA hollow fiber membranes showed good mitigation of membrane fouling regardless of pore size. The results obtained in this study suggest that the surface hydrophilicity and pore size of UF membranes clearly affect the fouling properties in MBR operation when using activated sludge.

Electrical contacts are important circuit components with diverse industrial applications, and their failure can lead to multiple unwanted effects. Hence, the behavior of electrical contacts is a widely studied topic in scientific literature based on various approaches, tools, and techniques. The present study proposes a numerical modeling and simulation approach based on the Holm contact theory to study the dependence between the electric potential and the temperature within an electrical contact. Structured in 5 sections, the research was conducted using COMSOL Multiphysics software and its solid-state mechanics, electric current, and heat transfer modules in order to highlight contact behavior from mechanical, electrical and thermal points of view: the von Mises stress, contact force, the electric field amplitude, the variation of the electrical potential along the current path, the temperature gradient, and dependence of temperature along the contact elements edges were obtained by simulation and graphically represented. The results are in line with the expectations and with past research that was studied in the literature review.

We present a surface acoustic wave (SAW) sensor array for microRNA (miRNA) detection that utilizes photocatalytic silver staining on titanium dioxide (TiO2) nanoparticles as a signal enhancement technique for high sensitivity with an internal reference sensor for high reproducibility. A sandwich hybridization was performed on working sensors of the SAW sensor array that could simultaneously capture and detect three miRNAs (miRNA-21, miRNA-106b, and miRNA-155) known to be upregulated in cancer. Sensor responses due to signal amplification varied depending on the concentration of synthetic miRNAs. It was confirmed that normalization (a ratio of working sensor response to reference sensor response) screened out background interferences by manipulating data and minimized non-uniformity in the photocatalytic silver staining step by suppressing disturbances to both working sensor signal and reference sensor signal. Finally, we were able to successfully detect target miRNAs in cancer cell-derived exosomal miRNAs with performance comparable to the detection of synthetic miRNAs.

Shear dynamics simulation under extreme pressure was used to optimise the composition of ester-based lubricant base oil and extreme pressure additives. As a result, the ester-based lubricant in the weak-gel drilling fluid achieves reduction and increases the efficiency in drilling construction, and the field operation efficiency improves. The results of base oil lubrication simulation show that three base oils, namely, methyl oleate, ethyl oleate and butyl oleate, can be stably adsorbed on the surface layer of the shear surface. Methyl oleate has the lowest system temperature after shear stabilisation and has a high load-bearing capacity. The shear stress of methyl oleate decreases by changing the initial shear temperature and speed. It increases by 6.36 MPa when the speed increases from 10 m/s to 30 m/s. At this time, the shear stress of butyl oleate increases by 10.11 MPa. The results of the four-ball friction experiments show that the radius of the abrasion spot of methyl oleate is 179.83 μm, which is smaller than that of the other two base oils. Moreover, the friction coefficient of methyl oleate is 0.0018, which is approximately 1/3 of that of butyl oleate. Methyl oleate has better lubrication efficiency. The shear simulation results are consistent with the experimental results. The simulation can be used for the molecular design of lubricant materials. The oleic acid amide–containing amine group and the glyceride oleic–containing hydroxyl group were selected as the extreme pressure functional components for shear simulation. Results show that the shear stress of oleic acid amide is much lower than that of oleic acid glyceride when the initial shear temperature and speed change. The extreme pressure lubrication component–containing amine group is better than the extreme pressure lubrication material–containing hydroxyl group. The effects of different oleamide contents in the two-component mixtures on the lubricating properties were investigated through shear simulation, with methyl oleate as the base oil and oleamide as the extreme pressure functional component. The simulation results show that the lubricant has the optimal shear stress when 10% oleamide is added to the lubricant. The base properties of the lubricant were tested using a mixture of 90% methyl oleate and 10% oleamide, formulated as a lubricant. Results show that the friction coefficient can be reduced to 0.03 when 0.5% of the lubricant is added to the base mud. Moreover, the lubricant film formed shows high strength. Then, 1% lubricant was added to the weak-gel drilling fluid to evaluate the effect of the lubricant on the gel structure of the drilling fluid. Results show that adding lubricant does not affect the rheological properties of the drilling fluid. The gel structure of the system also remains stable even after 7 days of continuous ageing. The results of the field experiments in Hua3-01 well show that adding 1% ester-based lubricant to the field drilling fluid reduces the drilling friction by 33%. Thus, the efficiency of directional side drilling can be effectively improved, complicated accidents, such as poor starting and stopping of drilling and stuck jamming, can be avoided, and the goals of reducing quantity and increasing efficiency can be completed.

In the case of a Cu-Mo-W polymetallic ore, the wastewater from the scheelite cleaning flowsheet contains large amounts of residual flocculants and metal ions, and the separation of chalcopyrite and molybdenite require a large number of environmentally harmful depressants. Therefore, it is necessary to find new methods to reduce the environmental and cost pressures of wastewater treatment and the use of depressants. In this work, the flotation wastewater from scheelite cleaning flowsheet for the separation of chalcopyrite and molybdenite by selective surface passivation was investigated for the first time. Flotations of single minerals and artificially mixed minerals with or without immersion pretreatment in the presence and absence of aeration were performed. The results showed that pulp pH had no effect on the flotation of either mineral, and a molybdenite recovery of 93.22% with chalcopyrite recovery of 10.77% was achieved under the conditions of 10 days of immersion pretreatment with aeration, 350 mg/L of kerosene, and 100 mg/L of MIBC. By combining the electrochemical cyclic voltammetry analysis and characterization by XRD and SEM, the selective surface passivation mechanism of chalcopyrite was discussed, which could be due to the coverage of the insoluble oxidation products, especially jarosite. This work has simultaneously achieved the depressant-free flotation separation of molybdenite and chalcopyrite and the reuse of scheelite flotation wastewater, which is of great significance for environmental protection and cost saving.

Maritime data not only identify financial resources that can significantly enhance the efficiency of shipping companies but also play a pivotal role in promoting eco-friendly and sustainable shipping practices. However, active corporate strategies are required to include maritime data essential for the commercial operation of autonomous ships in the form of corporate assets by transparent evaluating the data. The aim of this study is to review previous studies on da-ta-valuation models, identify a valuation model suitable for maritime business, consider the characteristics of maritime data. The analytic hierarchy process (AHP) method is used to derive priorities for valuing maritime data assets, with emphasis placed on the characteristics of mari-time data, followed by the character of the future-oriented maritime-data market and the da-ta-valuation model. The results obtained that the most important factors in selecting a maritime data-valuation model by analyzing the AHP method were identified as the characteristics of the maritime data(M1). The next most important factors analyzed were the features of the mari-time-data market(M2) and the features of the maritime data-valuation model(M3) in order. In addition, the characteristics of maritime data were preferentially considered among the main criteria, and the market approach (A2) was selected as the most optimal valuation model. The potential impact of this implementation could contribute to the establishment of an intelligent technology market by estimating the value of data and developing a platform for maritime data trading, allowing for more efficient data sharing and utilization by maritime autonomous sur-face ship(MASS).

A multiscale model that enables quantitative understanding and prediction of the size effect on scattering properties of micro- and nanostructures is crucial for the design of LED surface textures optimized for high light extraction efficiency (LEE). In this paper, a hybrid process for combining full-wave finite-difference time-domain simulation and a ray-tracing technique based on a bidirectional scattering distribution function model is proposed. We apply this method to study the influence of different pattern sizes of a patterned sapphire substrate on GaN-based LED light extraction from the microscale to the nanoscale. The results show that near-wavelength–scaled patterns with strong diffraction are not expected to enhance LEE. By contrast, microscaled patterns with optical diffusion behavior have the highest LEE at a specific aspect ratio, and subwavelength-scaled patterns that have antireflection properties show marked enhancement of LEE for a wide range of aspect ratios.

Although, promotion of urbanization culture in recent decades has made inevitable development of cities in the world, however, the development can be guided in a direction that leave, to the extent possible, minimum socioeconomic and environmental impacts. For this, it is required to first forecast auto-spreading orientation of cities and suburbs in rural areas over time and then avoid shapeless growth of cities. This paper is an attempt to develop a dynamic hybrid model based on logistic regression (LR), Markov chain (MC), and cellular automata (CA) for prediction of future urban sprawl in fast-growing cities. The model was developed using 12 widely-used urban development criteria, whose significant coefficient was determined by logistic regression, and validated by relative operating characteristic (ROC) analysis. The validated model was run in Guilan, a tourist province in northern Iran with a very high rate of urban development. For this, changes in the area of urban land use were detected over the period of 1989 to 2013 and then, future sprawl of the province was forecasted by the years 2025 and 2037. The analysis results revealed that the area of urban land use was increased by more than 1.7 % from 36012.5 ha in 1989 to 59754.8 ha in 2013, and the area of Caspian Hyrcanian forestland was reduced by 31628 ha. The results also predicted an alarming increase in the rate of urban development in the province by the years 2025 and 2037, during which urban land use is predicted to develop 0.9 % and 1.38 %, respectively. The development pattern is expected to be uneven and scattered, without following any particular direction. The development will occur close to the existing or newly-formed urban basements as well as around major roads and commercial areas. This development, if not controlled, will lead to the loss of 13863 ha of Hyrcanian forests and if the trend continues, 21013 ha of Hyrcanian forests and 20208 ha of Barren/open lands are expected to be destroyed by the year 2037. In general, the proposed model is an efficient tool for the support of urban planning decisions and facilitates the process of sustainable development of cities by providing decision-makers with an overview on future development of cities where the growth rate is very fast.

A power factor correction (PFC) rectifier is compulsory for any electronic circuitry connected to the electrical grid. The majority of PFCs that are utilized are based on a step-up converter that supplies high DC voltage at its output terminal. Electric vehicle battery voltage varies from a few hundred to almost a thousand volts. Thus, an additional conversion step is obligatory when designing an all-brand universal charger. This paper presents a new type of front-end versatile step up / down three voltage level PFC. The rectifier can operate in continuous conduction mode or discontinuous conduction mode. First, the rectifier’s principle of operation is described, and then an innovative rectifier is analyzed for continuous and discontinuous conduction modes. Finally, the proposed theory is experimentally validated in a multiplier-less dual loop mode at discontinuous conduction modes. It was shown that although there is no multiplier use in the control circuitry, the power factor is near unity. It was revealed that the rectifier could swing the output voltage from 50 V to 900 V while the input voltage was 230 Vrms. The innovative topology suits any standard PFC rectifier, three-level voltage supplement, and dual-stage low-voltage power supply.

The effects of the surface waves generated by the wind have a significant effect on the currents. A wave current coupled model plays an important role in the design of offshore structures. The interaction between fluids such as incompressible ocean waves and current and offshore structures is significant with many real-time applications in offshore engineering. These coupled models can be applied to Offshore Floating Production Operating and offloading (FPSO), Wind or current turbines and offshore pipelines. The complex issues related to the design are analyzed by using Computational Fluid Dynamics, which requires an investigation of the multiphase flow between wave and current and the structure which is considered restrictive due to the computational cost. If viscous effects are neglected then the single-phase flow models have been recommended, where wave-current interaction have been modelled successfully. Models have been developed where velocities and pressure are computed and the results can be verified with the experimental results available in the literature. In this study the existing numerical methods, mesh types are discussed along with their coupling methods. Here single-phase and multiphase models with small and medium movement are reviewed and their applications are highlighted.

Two coupled climate models which participated the CMIP6 project (Coupled Model Intercomparison Project Phase 6), the Earth System Model of Chinese Academy of Sciences version 2 (CAS-ESM2-0) and the Nanjing University of Information Science and Technology Earth System Model version 3 (NESM3), were assessed in terms of the impact of four new sea ice parameterization schemes. These four new schemes are related to air-sea heat flux, radiation penetration and absorption, melt ponds, ice-ocean flux, respectively. To evaluate the effectiveness of these schemes, key sea ice variables with and without these new schemes, such as sea ice concentration (SIC) and sea ice thickness (SIT), were compared against observation and reanalysis product from 1980 to 2014. The simulations followed the design of historical experiments within the CMIP6 framework. The results revealed that both models demonstrated improvements in simulating Arctic SIC and SIT when the new parameterization schemes were implemented. The model bias of SIC in some marginal sea ice zones of Arctic was reduced, especially during March. The SIT was increased and the transpolar gradient of SIT was reproduced. The changes of spatial pattern of SIC and SIT after adding new schemes bear similarities between the two coupled models. This suggests that the new schemes have potential for broad application in climate models, especially for those with underestimated SIT.