Large Volume Research Articles

A comprehensive review of strategic management practices in satellite telecommunications, highlighting the role of data analytics in driving operational efficiency and competitive advantage

Satellite telecommunications play a crucial role in modern connectivity, enabling global communication, broadcasting, and internet access. This paper presents a comprehensive review of strategic management practices in the satellite telecommunications industry, with a particular focus on the role of data analytics in enhancing operational efficiency and achieving competitive advantage. The satellite telecommunications sector is characterized by rapid technological advancements, evolving market dynamics, and increasing demand for bandwidth-intensive services. To thrive in this competitive landscape, companies in the industry must adopt strategic management practices that enable them to effectively leverage their resources, capabilities, and market opportunities. One of the key strategic management practices in satellite telecommunications is the integration of data analytics into business operations. Data analytics encompasses the collection, analysis, and interpretation of large volumes of data to extract valuable insights and inform decision-making. By harnessing the power of data analytics, satellite telecommunications companies can optimize their network performance, enhance customer experience, and drive innovation. Data analytics can also help companies in the satellite telecommunications industry to identify new market trends, customer preferences, and competitive threats. By analyzing data from various sources, including satellite sensors, customer feedback, and market research, companies can gain a deeper understanding of their operating environment and make informed strategic decisions. Furthermore, data analytics can enable satellite telecommunications companies to enhance their operational efficiency by optimizing resource allocation, minimizing downtime, and improving network reliability. By using predictive analytics, companies can anticipate equipment failures and proactively address potential issues, thereby reducing maintenance costs and improving service quality. In conclusion, this paper highlights the importance of strategic management practices in the satellite telecommunications industry, with a focus on the role of data analytics in driving operational efficiency and competitive advantage. By adopting data-driven decision-making processes, satellite telecommunications companies can position themselves for long-term success in a rapidly evolving industry landscape.

Culture, prefrontal volume, and memory.

Prior cross-cultural studies have demonstrated differences among Eastern and Western cultures in memory and cognition along with variation in neuroanatomy and functional engagement. We further probed cultural neuroanatomical variability in terms of its relationship with memory performance. Specifically, we investigated how memory performance related to gray matter volume in several prefrontal lobe structures, including across cultures. For 58 American and 57 Taiwanese young adults, memory performance was measured with the California Verbal Learning Test (CVLT) using performance on learning trial 1, on which Americans had higher scores than the Taiwanese, and the long delayed free recall task, on which groups performed similarly. MRI data were reconstructed using FreeSurfer. Across both cultures, we observed that larger volumes of the bilateral rostral anterior cingulate were associated with lower scores on both CVLT tasks. In terms of effects of culture, the relationship between learning trial 1 scores and gray matter volumes in the right superior frontal gyrus had a trend for a positive relationship in Taiwanese but not in Americans. In addition to the a priori analysis of select frontal volumes, an exploratory whole-brain analysis compared volumes-without considering CVLT performance-across the two cultural groups in order to assess convergence with prior research. Several cultural differences were found, such that Americans had larger volumes in the bilateral superior frontal and lateral occipital cortex, whereas Taiwanese had larger volumes in the bilateral rostral middle frontal and inferior temporal cortex, and the right precuneus.

Strain Monitoring of Concrete Using Carbon Black-Based Smart Coatings.

Given the challenges we face of an ageing infrastructure and insufficient maintenance, there is a critical shift towards preventive and predictive maintenance in construction. Self-sensing cement-based materials have drawn interest in this sector due to their high monitoring performance and durability compared to electronic sensors. While bulk applications have been well-discussed within this field, several challenges exist in their implementation for practical applications, such as poor workability and high manufacturing costs at larger volumes. This paper discusses the development of smart carbon-based cementitious coatings for strain monitoring of concrete substrates under flexural loading. This work presents a physical, electrical, and electromechanical investigation of sensing coatings with varying carbon black (CB) concentrations along with the geometric optimisation of the sensor design. The optimal strain-sensing performance, 55.5 ± 2.7, was obtained for coatings with 2 wt% of conductive filler, 3 mm thickness, and a gauge length of 60 mm. The results demonstrate the potential of applying smart coatings with carbon black addition for concrete strain monitoring.

Overcoming data utilization challenges for built environment flood resilience: Strategies and best practices

AbstractBuilt environment flood resilience is a critical challenge facing communities worldwide. Amongst various efforts to resilience, the conception towards data utilization becomes popular with enormous technological advancements. Built environment creates varieties of data at larger volumes throughout their life cycle signifying that the importance of these data in the context of flood resilience cannot be ignored. However, despite the power of data, the greatest opportunities that exist for flood resilience enhancement have been mired by numerous and complex unidentified challenges. Thus, identifying these challenges with timely relevant strategies is a significant need. One of the best ways to tackle these challenges is by viewing them through the lens of data life cycle stages. This study, therefore, aimed to identify these challenges in each stage of the data life cycle with strategies to overcome them. Semi‐structured interviews conducted with 12 experts revealed the significant challenges allied with built environment data with potential future strategies. The qualitative content analysis was conducted to analyse the findings. The use of advanced sensing technologies, cloud‐based storage solutions, data governance policies and the development of predictive models are some of the consequential strategies outlined in this study. These findings provide valuable insights and guidance to facilitate built environment data utilization for flood resilience.

Bio-based aerogel composites of coconut pith-derived carbon and chitosan for efficient anionic dye-polluted water treatment

Abstract Biomass-based aerogels are of interest due to their abundant precursors, ease of functionalization, eco-friendliness, low cost, and effectiveness in dye-contaminated water treatment. Coconut pith (CP) known as a by-product after coconut processing is a sponge-like and lightweight material discarded in large volumes. For the first time, carbon micro-particles resulting from two-step treatment and pyrolysis of CP have been successfully incorporated with chitosan to produce aerogel composites by high-speed homogenization and freeze-drying. After pretreatment, holocellulose content and crystallinity index of the recovered CP pulp are respectively 75.4 and 58.6 % along with a solid recovery rate of 27.5 %. Characteristic properties of the aerogel composites are featured by their density as low as 15.23–28.17 mg/cm3, remarkably high porosity of 98.17–99.05 %, and Young’s modulus of 1.64–12.23 kPa. Synergistic effects of the porous network, electrostatic interactions between both amine groups in chitosan and carbon surface with methyl orange (MO) cause the as-fabricated aerogel composites to achieve an extremely high adsorption capacity of 454.13 mg/g and removal efficiency of 92.32 % at initial MO concentration of 500 mg/L. Therefore, the CP-derived carbon/chitosan aerogel composites synthesized from a feasible procedure exhibit their great potential in enhancing the value of coconut waste and dealing with dye-contaminated water pollution by simple and economical adsorption.

Comparison of diffusion ranges at different local anesthetic volumes during superior laryngeal nerve block

ObjectivesUltrasound-guided superior laryngeal nerve (SLN) block is a practical and painless approach to avoid the hemodynamic stress response during endotracheal intubation and relieve sore throat after laryngeal surgery. The main purpose of this study was to establish an optimal dosage of local anesthetic when performing SLN block to help anesthetists balance analgesia and side effects.MethodsTwenty fresh larynx specimens were obtained immediately after resection and then injected with 2-, 3-, 4-, or 5- mL of a lidocaine-blue dye mixture at bilateral SLN puncture sites. Superficial areas of deposited blue dye were measured. Dye leakage and surrounding dyed tissue were recorded. Another 40 patients were included in the ultrasound investigation. Distances between the internal branch of the SLN (iSLN) and adjacent structures were calculated.ResultsThe dye spread area was greater with the administration of larger doses, especially to the visceral space. A 2- or 3-mL injection of local anesthetic was sufficient to infiltrate the SLN gap. A higher incidence of dye leaking out of the thyrohyoid membrane and anterior epiglottis space was observed; furthermore, there was substantially more dyed hyoid/thyroid cartilage with 4 and 5 mL of injected dye mixture than 2 mL. There was no significant difference between the specimen and ultrasound measurements of for length of iSLN-adjacent structures.ConclusionsIn the Chinese population, 2- or 3- mL of local anesthetic is a safe dose during SLN block. A larger volume could overflow from the cavity to cause complications. The thyrohyoid membrane combined with the superior laryngeal artery is a reliable target for positioning the iSLN during ultrasound-guided regional anesthesia.

Contouring aid tools in radiotherapy. Smoothing: the false friend.

Contouring accuracy is critical in modern radiotherapy. Several tools are available to assist clinicians in this task. This study aims to evaluate the performance of the smoothing tool in the ARIA system to obtain more consistent volumes. Eleven different geometric shapes were delineated in ARIA v15.6 (Sphere, Cube, Square Prism, Six-Pointed Star Prism, Arrow Prism, And Cylinder and the respective volumes at 45° of axis deviation (_45)) in 1, 3, 5, 7, and 10cm side or diameter each. Post-processing drawing tools to smooth those first-generated volumes were applied in different options (2D-ALL vs 3D) and grades (1, 3, 5, 10, 15, and 20). These volumetric transformations were analyzed by comparing different parameters: volume changes, center of mass, and DICE similarity coefficient index. Then we studied how smoothing affected two different volumes in a head and neck cancer patient: a single rounded node and the volume delineating cervical nodal areas. No changes in data were found between 2D-ALL or 3D smoothing. Minimum deviations were found (range from 0 to 0.45cm) in the center of mass. Volumes and the DICE index decreased as the degree of smoothing increased. Some discrepancies were found, especially in figures with cleft and spikes that behave differently. In the clinical case, smoothing should be applied only once throughout the target delineation process, preferably in the largest volume (PTV) to minimize errors. Smoothing is a good tool to reduce artifacts due to the manual delineation of radiotherapy volumes. The resulting volumes must be always carefully reviewed.

ЭФФЕКТИВНОСТЬ АВТОМАТИЗИРОВАННОГО УПРАВЛЕНИЯ ТРАНСПОРТНЫМИ СРЕДСТВАМИ В ТРАМВАЙНЫХ СИСТЕМАХ

The intellectualization of water transport is accompanied by an expansion of the landscape of threats to transport security, caused by the characteristics and weaknesses of the technologies being introduced, which are the convergence of information and telecommunication technologies, automated and automatic control technologies and artificial intelligence. The peculiarity of these technologies is working with large volumes of information. Violation of the security of information processed in intelligent systems of water transport (illegal access, modification, deletion and similar unauthorized influence) causes a violation of transport security and, as a consequence, the security of critical information infrastructure and the country’s critical infrastructure, national security. Convergent technologies used in intelligent transport systems are characterized by multiple and poorly formalized manifestations of the consequences of threats. The article presents a model for assessing the risks of information security of intelligent water transport systems, based on the methods of the theory of fuzzy sets and fuzzy logic, the use of which makes it possible to take into account the above-mentioned features of the technologies being implemented. The hierarchical structure of the model and the use of fuzzy set theory and fuzzy logic methods make it possible to adapt the model to various risk criteria, types of input data and the level of detail of risk analysis. For the presented model, a methodology for assessing information security risks has been developed and an example of risk calculation is given. The developed model and methodology are intended to build an information security risk management system for autonomous shipping, implementing technologies of hybrid (augmented, extended) intelligence, providing for the use of artificial intelligence controlled by people.

Reinterpreting fundamental plane correlations with machine learning

Abstract This work explores the relationships between galaxy sizes and related observable galaxy properties in a large volume cosmological hydrodynamical simulation. The objectives of this work are to develop a better understanding of both the correlations between galaxy properties and the influence of environment on galaxy physics in order to build an improved model for the galaxy sizes, building off of the fundamental plane. With an accurate intrinsic galaxy size predictor, the residuals in the observed galaxy sizes can potentially be used for multiple cosmological applications, including making measurements of galaxy velocities in spectroscopic samples, estimating the rate of cosmic expansion, and constraining the uncertainties in the photometric redshifts of galaxies. Using projection pursuit regression, the model accurately predicts intrinsic galaxy sizes and have residuals which have limited correlation with galaxy properties. The model decreases the spatial correlation of galaxy size residuals by a factor of ∼ 5 at small scales compared to the baseline correlation when the mean size is used as a predictor.

Outcomes after elevation of serratus anterior fascia flap versus serratus muscle flap in direct-to-implant breast reconstruction following mastectomy: a prospective study.

The purpose of this study was to compare postoperative pain between SF flap and serratus anterior muscle (SM) in direct-to-implant breast reconstruction. This is a prospective cohort study that included 53 women diagnosed with breast cancer who underwent mastectomy and one-stage implant-based breast reconstruction from January 2020 to March 2021. Twenty-nine patients (54.7%) had SF elevation, and 24 patients (45.3%) underwent SM elevation. We evaluated patient-reported early postoperative pain on the first day after surgery. Also, it was reported that all surgical complications in the first month and patient reported outcomes (PROs) were measured with the BRECON 23 questionnaire. The serratus fascia group used implants with larger volumes, 407.6 ± 98.9 cc (p < 0.01). There was no significant difference between the fascial and muscular groups regarding the postoperative pain score reported by the patients (2 versus 3; p = 0.30). Also, there was no difference between the groups regarding early surgical complications and PROs after breast reconstruction. The use of SF seems to cause less morbidity, which makes the technique an alternative to be considered in breast reconstruction. Although there was no statistical difference in postoperative pain scores between the fascia and serratus muscle groups.

Structural control of igneous intrusions on fluid migration in sedimentary basins: the case study of large bitumen seeps at Cerro Alquitrán and Cerro La Paloma, northern Neuquén Basin, Argentina

Abstract Cooling subvolcanic igneous intrusions are known to have a tremendous impact on fluid flow in the shallow Earth's crust. However, the long-term post-cooling legacy of subvolcanic intrusions on fluid flow has received much less attention. Here we describe geological examples in the Andean foothills, Argentina, showing that igneous intrusions have long-term effects on fluid flow after their emplacement and cooling. The case study consists of ∼11 Myr-old eroded andesitic intrusions of Cerro Alquitrán and Cerro La Paloma, northern Neuquén Basin, Argentina, at the rims of which large volumes of bitumen are naturally seeping out at the Earth's surface. The intrusions exhibit laccolithic shapes with steep-sided contacts with the host rock. Near the intrusive contacts, the andesite is intensely broken along concentric breccia bands and fracture bands, interpreted as resulting from syn-emplacement brittle magma deformation, which represent high-permeability pathways for the migrating bitumen. Organic geochemical analyses of the bitumen show that the seeping oils were generated from incipiently mature Vaca Muerta sections located in a regional kitchen to the west, implying a lateral migration of ∼10–20 km. The Cerro Alquitrán and Cerro La Paloma intrusions are demonstrative examples highlighting how extinct subvolcanic intrusions have long-term consequences for subsurface fluid circulations in sedimentary basins.

Metabolites rapid-annotation in mice by comprehensive method of virtual polygons and Kendric mass loss filtering: A case study of Dendrobium nobile Lindl

With significant advancements in high-resolution mass spectrometry, there has been a substantial increase in the amount of chemical component data acquired from natural products. Therefore, the rapid and efficient extraction of valuable mass spectral information from large volumes of high-resolution mass spectrometry data holds crucial significance. This study illustrates a targeted annotation of the metabolic products of alkaloid and sesquiterpene components from Dendrobium nobile (D. nobile) aqueous extract in mice serum through the integration of an in-houses database, R programming, a virtual metabolic product library, polygonal mass defect filtering, and Kendrick mass defect strategies. The research process involved initially establishing a library of alkaloids and sesquiterpenes components and simulating 71 potential metabolic reactions within the organism using R programming, thus creating a virtual metabolic product database. Subsequently, employing the virtual metabolic product library allowed for polygonal mass defect filtering, rapidly screening 1705 potential metabolites of alkaloids and 3044 potential metabolites of sesquiterpenes in the serum. Furthermore, based on the chemical composition database of D. nobile and online mass spectrometry databases, 95 compounds, including alkaloids, sesquiterpenes, and endogenous components, were characterized. Finally, utilizing Kendrick mass defect analysis in conjunction with known alkaloids and sesquiterpenes targeted screening of 209 demethylation, methylation, and oxidation products in phase I metabolism, and 146 glucuronidation and glutathione conjugation products in phase II metabolism. This study provides valuable insights for the rapid and accurate annotation of chemical components and their metabolites in vivo within natural products.

Feasibility of wastewater-based detection of emergent pandemics through a global network of airports.

Wastewater-based surveillance has been put into practice during the pandemic. Persistence of SARS-CoV-2 in faeces of infected individuals, and high volume of passengers travelling by air, make it possible to detect virus from aircraft wastewater, lending itself to the potential identification of a novel pathogen prior to clinical diagnosis. In this study, we estimated the likelihood of detecting the virus through aircraft wastewater from the probabilities of air travel, viral shedding, defecation, testing sensitivity, and sampling. We considered various hypothetical scenarios, with diverse sampling proportions of inbound flights, surveillance airports, and sources of outbreaks. Our calculations showed that the probability of detecting SARS-CoV-2 would increase exponentially against time in the early phase of the pandemic, and would be much higher if the 20 major airports in Asia, Europe, and North America cooperated to perform aircraft wastewater surveillance. We also found other contributors to early detection, including high sampling proportion of inbound flight at destination airports, small population size of the epicentre relative to the travel volume, and large volume of outbound travelers to major airports around the globe. We concluded that routine aircraft wastewater monitoring could be a feasible approach for early identification and tracking of an emerging pathogen with high faecal shedding rates, particularly when implemented through a global surveillance network of major airports.

A low-cost approach to determine the optimum conductor plate thickness of linear permanent magnet eddy current brakes

This paper proposes a low-cost approach to determine the optimum Conductor Plate (CP) thickness without needs for mathematical models and large data volumes, which means that 0.6 times of the Standard Depth of Penetration (SDoP) can be directly selected as the optimum CP thickness without calculation. Firstly, the SDoP is introduced. Then, the influences of speed and conductivity on the optimum CP thickness are investigated. Finally, the relationship between the SDoP and the optimum CP thickness is found. The optimum CP thickness can be selected directly according to the relationship without mathematical models and large data volumes. It not only guarantees high braking force, but also reduces the weight of the LPMECBs as much as possible.

“HOT” ChatGPT: The Promise of ChatGPT in Detecting and Discriminating Hateful, Offensive, and Toxic Comments on Social Media

Harmful textual content is pervasive on social media, poisoning online communities and negatively impacting participation. A common approach to this issue is developing detection models that rely on human annotations. However, the tasks required to build such models expose annotators to harmful and offensive content and may require significant time and cost to complete. Generative AI models have the potential to understand and detect harmful textual content. We used ChatGPT to investigate this potential and compared its performance with MTurker annotations for three frequently discussed concepts related to harmful textual content on social media: Hateful, Offensive, and Toxic (HOT). We designed five prompts to interact with ChatGPT and conducted four experiments eliciting HOT classifications. Our results show that ChatGPT can achieve an accuracy of approximately 80% when compared to MTurker annotations. Specifically, the model displays a more consistent classification for non-HOT comments than HOT comments compared to human annotations. Our findings also suggest that ChatGPT classifications align with the provided HOT definitions. However, ChatGPT classifies “hateful” and “offensive” as subsets of “toxic.” Moreover, the choice of prompts used to interact with ChatGPT impacts its performance. Based on these insights, our study provides several meaningful implications for employing ChatGPT to detect HOT content, particularly regarding the reliability and consistency of its performance, its understanding and reasoning of the HOT concept, and the impact of prompts on its performance. Overall, our study provides guidance on the potential of using generative AI models for moderating large volumes of user-generated textual content on social media.

Kawai-type multianvil ultrahigh-pressure technology.

Since the large-volume press with a double-stage multianvil system was created by the late Professor Naoto Kawai, this apparatus (Kawai-type multianvil apparatus or KMA) has been developed for higher-pressure generation, in situ X-ray and neutron observations, deformation experiments, measurements of physical properties, synthesis of high-pressure phases, etc., utilizing its large sample volume and capacity in stable and homogeneous high temperature generation compared to those of competitive diamond anvil cells. These advancements in KMA technology have been made primarily by Japanese scientists and engineers, which yielded a wealth of new experimental data on phase transitions, melting relations, and physical characteristics of minerals and rocks, leading to significant constraints on the structures, chemical compositions, and dynamics of the deep Earth. KMA technology has also been used for synthesis of novel functional materials such as nano-polycrystalline diamond and transparent nano-ceramics, opening a new research field of ultrahigh-pressure materials science.

Robust, Ultrafast and Reversible Photoswitching in Bulk Polymers Enabled by Octupolar Molecule Design

AbstractImproving the photoswitching rate and robustness of photochromic molecules in bulk solids is paramount for practical applications but remains an on‐going challenge. Here, we introduce an octupolar design paradigm to develop a new family of visible light organic photoswitches, namely multi‐branched octupolar Stenhouse Adducts (MOPSAs) featuring a C3‐symmetrical A3‐(D‐core) architecture with a dipolar donor–acceptor (D–A) photochrome in each branch. Our design couples multi‐dimensional geometric and electronic effects of MOPSAs to enable robust ultrafast reversible photoswitching in bulk polymers. Specifically, the optimal MOPSA (4 wt %) in commercial polyurethane films accomplishes nearly 100 % discoloration in 6 s under visible light with ∼ 100 % thermal‐recovery in 17.4 s at 60 °C, while the acquired kinetics constants are 3∼7 times that of dipolar DASA counterpart and 1∼2 orders of magnitude higher than those of reported DASAs in polymers. Importantly, the MOPSA‐doped polymer films sustain 500 discoloration/recovery cycles with slow degradation, superior to the existing DASAs in polymers (≤30 cycles). We discover that multi‐dipolar coupling in MOPSA enables enhanced polarization and electron delocalization, promoting the rate‐determining thermal cyclization, while the branched and non‐planar geometry of MOPSA induces large free volume to facilitate the isomerization. This design can be extended to develop spiropyran or azobenzene‐based ultrafast photochromic films. The superior photoswitching performance of MOPSAs together with their high‐yield and scalable synthesis and facile film processing inspires us to explore their versatile uses as smart inks or labels for time‐temperature indicators, optical logic encryption and multi‐levelled data encryption.

Robust, Ultrafast and Reversible Photoswitching in Bulk Polymers Enabled by Octupolar Molecule Design.

Improving the photoswitching rate and robustness of photochromic molecules in bulk solids is paramount for practical applications but remains an on-going challenge. Here, we introduce an octupolar design paradigm to develop a new family of visible light organic photoswitches, namely multi-branched octupolar Stenhouse Adducts (MOPSAs) featuring a C3-symmetrical A3-(D-core) architecture with a dipolar donor-acceptor (D-A) photochrome in each branch. Our design couples multi-dimensional geometric and electronic effects of MOPSAs to enable robust ultrafast reversible photoswitching in bulk polymers. Specifically, the optimal MOPSA (4 wt %) in commercial polyurethane films accomplishes nearly 100 % discoloration in 6 s under visible light with ∼ 100 % thermal-recovery in 17.4 s at 60 °C, while the acquired kinetics constants are 3∼7 times that of dipolar DASA counterpart and 1∼2 orders of magnitude higher than those of reported DASAs in polymers. Importantly, the MOPSA-doped polymer films sustain 500 discoloration/recovery cycles with slow degradation, superior to the existing DASAs in polymers (≤30 cycles). We discover that multi-dipolar coupling in MOPSA enables enhanced polarization and electron delocalization, promoting the rate-determining thermal cyclization, while the branched and non-planar geometry of MOPSA induces large free volume to facilitate the isomerization. This design can be extended to develop spiropyran or azobenzene-based ultrafast photochromic films. The superior photoswitching performance of MOPSAs together with their high-yield and scalable synthesis and facile film processing inspires us to explore their versatile uses as smart inks or labels for time-temperature indicators, optical logic encryption and multi-levelled data encryption.

Will Artificial Intelligence Affect How Cultural Heritage Will Be Managed in the Future? Responses Generated by Four genAI Models

Generative artificial intelligence (genAI) language models have become firmly embedded in public consciousness. Their abilities to extract and summarise information from a wide range of sources in their training data have attracted the attention of many scholars. This paper examines how four genAI large language models (ChatGPT, GPT4, DeepAI, and Google Bard) responded to prompts, asking (i) whether artificial intelligence would affect how cultural heritage will be managed in the future (with examples requested) and (ii) what dangers might emerge when relying heavily on genAI to guide cultural heritage professionals in their actions. The genAI systems provided a range of examples, commonly drawing on and extending the status quo. Without a doubt, AI tools will revolutionise the execution of repetitive and mundane tasks, such as the classification of some classes of artifacts, or allow for the predictive modelling of the decay of objects. Important examples were used to assess the purported power of genAI tools to extract, aggregate, and synthesize large volumes of data from multiple sources, as well as their ability to recognise patterns and connections that people may miss. An inherent risk in the ‘results’ presented by genAI systems is that the presented connections are ‘artifacts’ of the system rather than being genuine. Since present genAI tools are unable to purposively generate creative or innovative thoughts, it is left to the reader to determine whether any text that is provided by genAI that is out of the ordinary is meaningful or nonsensical. Additional risks identified by the genAI systems were that some cultural heritage professionals might use AI systems without the required level of AI literacy and that overreliance on genAI systems might lead to a deskilling of general heritage practitioners.

Focusing of water waves with a shallow-draft cylinder array

The propagation of water waves can be manipulated via artificial structures. However, such structures usually need to possess a large volume ratio in water, and it may not be easy to build and move them in practical ocean engineering. Here, we theoretically propose and experimentally demonstrate a fixed, shallow-draft cylinder array that can refract and focus water waves within a wide range of wavelengths. When impinging upon the cylinder array from a region of water without structures, water waves can be slightly reflected at the surface of the array and speeded up in the array. As a result, favorable focusing performances such as a short focal length and high intensity at the focal point are observed.