Array Of Instruments Research Articles

Issue uncertainty and selections of policy instruments in policy pilots: evidence from China’s long-term care insurance

ABSTRACT Policy pilots have been instrumental in governing China’s economic and social development. Prior research has primarily concentrated on examining the types of policy pilots and their promotion strategies through the lens of central-local dynamics, and analysing the organizational models of policy pilots within specific contexts. However, there’s a gap in understandinghow the central government employs policy instruments to foster organizational learning within pilots. In complex policy pilots, there is often uncertainty regarding objectives, pathways, and outcomes. Using China’s Long-Term Care Insurance (LTCI) pilot as a case study, this research reveals that policy pilots utilize distinct sets of policy instruments during the organizational learning process, contingent upon the context. The first set of instruments indicates a shift in the central government’s intervention intensity, ranging from weak to strong, employing autonomous, advocacy, and directive policy instruments in sequence. The second set of instruments shows an evolution in the depth of the central government’s engagement with the policy issues, progressing from shallow to deep, with the use of booster, framework, and calibrated policy instruments, respectively. This study highlights how policy pilots employ a diverse array of instruments to navigate the intricacies of policy implementation when confronting complex social policy challenges.

Estimating the In Situ Stratification via Remotely Sensed Internal Wave Speeds

Abstract This work tests a methodology for estimating the ocean stratification gradient using remotely sensed, high temporal and spatial resolution field measurements of internal wave propagation speeds. The internal wave (IW) speeds were calculated from IW tracks observed using a shore-based, X-band marine radar deployed at a field site on the south-central coast of California. An inverse model, based on the work of Kar and Guha, utilizes the linear internal wave dispersion relation, assuming a constant vertical density gradient is the basis for the inverse model. This allows the vertical gradient of density to be expressed as a function of the internal wave phase speed, local water depth, and a background average density. The inputs to the algorithm are the known cross-shore bathymetry, the background ocean density, and the remotely sensed cross-shore profiles of IW speed. The estimated density gradients are then compared to the synchronously measured vertical density profiles collected from an in situ instrument array. The results show a very good agreement offshore in deeper water (∼50–30 m) but more significant discrepancies in shallow water (20–10 m) closer to shore. In addition, a sensitivity analysis is conducted that relates errors in measured speeds to errors in the estimated density gradients. Significance Statement The propagation speed of ocean internal waves inherently depends on the vertical structure of the water density, which is termed stratification. In this work, we evaluate and test with real field observations a technique to infer the ocean density stratification from internal wave propagation speeds collected from remote sensing images. Such methods offer a way to monitor ocean stratification without the need for extensive in situ measurements.

How is particulate organic carbon transported through the river-fed submarine Congo Canyon to the deep sea?

Abstract. The transfer of carbon from land to the near-coastal ocean is increasingly being recognized in global carbon budgets. However, a more direct transfer of terrestrial organic carbon to the deep sea is comparatively overlooked. Among systems that connect coastal to deep-sea environments, the submarine Congo Canyon is of particular interest since the canyon head starts 30 km into the Congo River estuary, which delivers ∼7 % of the dissolved and particulate organic carbon from the world's rivers. However, sediment and particulate organic carbon transport mechanisms that operate in the Congo Canyon and submarine canyons more globally are poorly constrained compared to rivers because monitoring of deep-sea canyons remains challenging. Using a novel array of acoustic instruments, sediment traps, and cores, this study seeks to understand the hydrodynamic processes that control delivery of particulate organic carbon via the submarine Congo Canyon to the deep sea. We show that particulate organic carbon transport in the canyon axis is modulated by two processes. First, we observe periods where the canyon dynamics are dominated by tides, which induce a background oscillatory flow (speeds of up to 0.15 m s−1) through the water column, keeping muds in suspension, with a net upslope transport direction. Second, fast-moving (up to 8 m s−1) turbidity currents occur for 35 % of the time during monitoring periods and transport particulate organic carbon with mud and sand at an estimated transit flux that is more than 3 to 6 times the flux induced by tides. Organic carbon transported and deposited in the submarine canyon has a similar isotopic composition to organic carbon in the Congo River and in the deep-sea fan at 5 km of water depth. Episodic turbidity currents thus promote efficient transfer of river-derived particulate organic carbon in the Congo submarine fan, leading to some of the highest terrestrial carbon preservation rates observed in marine sediments globally.

Advancing patient-centered cancer care: a systematic review of electronic patient-reported outcome measures.

Electronic Patient-Reported Outcome Measures (ePROMs) have emerged as valuable tools in cancer care, facilitating the comprehensive assessment of patients' physical, psychological, and social well-being. This study synthesizes literature on the utilization of ePROMs in oncology, highlighting the diverse array of measurement instruments and questionnaires employed in cancer patient assessments. By comprehensively analyzing existing research, this study provides insights into the landscape of ePROMs, informs future research directions, and aims to optimize patient-centred oncology care through the strategic integration of ePROMs into clinical practice. A systematic review was conducted by searching peer-reviewed articles published in academic journals without time limitations up to 2024. The search was performed across multiple electronic databases, including PubMed, Scopus, and Web of Science, using predefined search terms related to cancer, measurement instruments, and patient assessment. The selected articles underwent a rigorous quality assessment using the Mixed Methods Appraisal Tool (MMAT). The review of 85 studies revealed a diverse range of measurement instruments and questionnaires utilized in cancer patient assessments. Prominent instruments such as the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) and the Patient Reported Outcome-Common Terminology Criteria for Adverse Events (PRO-CTCAE) were frequently referenced across multiple studies. Additionally, other instruments identified included generic health-related quality of life measures and disease-specific assessments tailored to particular cancer types. The findings indicated the importance of utilizing a variety of measurement tools to comprehensively assess the multifaceted needs and experiences of cancer patients. Our systematic review provides a comprehensive examination of the varied tools and ePROMs employed in cancer care, accentuating the perpetual requirement for development and validation. Prominent instruments like the EORTC QLQ-C30 and PRO-CTCAE are underscored, emphasizing the necessity for a thorough assessment to meet the multifaceted needs of patients. Looking ahead, scholarly endeavours should prioritize the enhancement of existing tools and the creation of novel measures to adeptly address the evolving demands of cancer patients across heterogeneous settings and populations.

Analytically pricing volatility options and capped/floored volatility swaps with nonlinear payoffs in discrete observation case under the Merton jump-diffusion model driven by a nonhomogeneous Poisson process

In this paper, we introduce novel analytical solutions for valuating volatility derivatives, including volatility options and capped/floored volatility swaps, employing discrete sampling within the framework of the Merton jump-diffusion model, which is driven by a nonhomogeneous Poisson process. The absence of a comprehensive understanding of the probability distribution characterizing the realized variance has historically impeded the development of a robust analytical valuation approach for such instruments. Through the application of the cumulative distribution function of the realized variance conditional on Poisson jumps, we have derived explicit expectations for the derivative payoffs articulated as functions of the extremum values of the square root of the realized variance. We delineate precise pricing structures for an array of instruments, encompassing variance and volatility swaps, variance and volatility options, and their respective capped and floored variations, alongside establishing put-call parity and relationships for capped and floored positions. Complementing the theoretical advancements, we substantiate the practical efficacy and precision of our solutions via Monte Carlo simulations, articulated through multiple numerical examples. Conclusively, our analysis extends to the quantification of jump impacts on the fair strike prices of volatility derivatives with nonlinear payoffs, facilitated by our analytic pricing expressions.

The Wind‐Blown Sand Experiment in the Empty Quarter Desert: Roughness Length and Saltation Characteristics

AbstractThe Empty Quarter Desert, one of Earth's major dust sources, frequently experiences dust storms due to wind erosion. Despite its significance as a primary dust source on a global scale, in‐situ observations from this region had not been reported until very recently. In summer 2022, the WInd‐blown Sand Experiment (WISE) Phase‐1 was initiated in the Empty Quarter Desert of the United Arab Emirates, and continued until 7 February 2023. Utilizing a diverse array of instruments, we measured winds, temperature, humidity, radiation fluxes, saltation, and the physical and optical properties of dust aerosols, atmospheric electric fields, and soil characteristics. A total of 38 distinct sand‐saltation events were recorded from September 2022 to February 2023, with activity peaking between 13:00 and 14:00 local time. Key findings include the identification of dominant wind patterns, and the measurement of the average aerodynamic roughness length (z0) at 0.8 ± 0.6 mm, and the thermal roughness length (zh) at 0.3 ± 0.5 mm—the first estimation of zh for this area. In‐situ observations revealed that dust particle concentrations near the surface increased 1.7‐fold on days with saltation compared to days without it. Moreover, we determined a wind‐speed threshold for initiating saltation at 7.70 m s−1. This comprehensive data set significantly advances our understanding of atmospheric‐soil interactions and sand movement dynamics, providing invaluable insights for ongoing research into desert environments and the global dust cycle.

Crosswalk between the PROMIS physical function CAT and PROMIS upper extremity CAT v1.2 in a hand surgery population

BackgroundThere is no gold standard patient-reported outcome measure (PROM) in hand surgery. As a result, a diverse array of PROM instruments have been utilized across centers over time. Lack of score interchangeability limits the ability to compare or conglomerate scores when new instruments are introduced. Our aim was to develop a linkage for the PROMIS UE CAT v1.2 and PROMIS PF CAT scores and develop crosswalk tables for interconversion between these PROMs.MethodsRetrospective review was conducted to identify adult (≥ 18y) patients seen by orthopaedic hand surgeons at a single academic tertiary care hospital who had completed PROMIS UE CAT v1.2 and PROMIS PF CAT score at the same visit. For those with multiple visits, only one randomly selected visit was included in the analyses. Pearson’s correlation was calculated to determine the linear relationship between the scores. Linkage from PF to UE was performed utilizing several commonly utilized equating models (identity, mean, linear, equipercentile and circle-arc methods). The performance of the models was assessed using intraclass correlation (ICC) between observed PROMIS UE CAT v1.2 and estimated PROMIS UE CAT v1.2 scores generated using the model as well as Root Mean Square Error (RMSE). The model chosen as the ‘best’ was further assessed for population invariance using root expected mean squared difference (REMSD) where < 0.08 were considered good.ResultsOf 10,081 included patients, mean age was 48.3 (SD = 17.0), and 54% were female (5,477/10,081). Mean UE CAT v1.2 and PF CAT scores were 37 (SD = 9.8) and 46 (SD = 10.0), respectively. There was a strong correlation between the scores (Pearson correlation r = 0.70). All methods performed acceptably (ICC ≥ 0.66 and RMSE < = 7.52 for all). The equipercentile method had the highest ICC (ICC = 0.70 (95% CI 0.69–0.71)) while the mean and circle arc methods had the lowest RMSE. The circle arc method is the most reliable with the smallest standard error and has satisfactory population invariance across age group (REMSD 0.065) and sex (REMSD 0.036).ConclusionsCrosswalk tables to be used for bidirectional conversion between scores were created.Level of evidence: III.

Strategic Analysis of Feature Selection Methods for Enhanced Dental Therapy Recognition in Machine Learning Applications

The popularity of smart clinics has increased significantly as a result of technical developments in fields like computer vision. At the heart of such systems is the ability to recognize objects and activities as well as perceive the environment as a whole. This is crucial for both eco-independent systems and human-machine interaction, especially in settings with constrained workspaces, like dental care. Our study delves into an extensive analysis of multiple machine learning models designed to robustly predict dental treatments. These models encompass Lazy Instance-based Learning, Sequential Minimal Optimization, Hoeffding Tree, and Random Tree. Leveraging object-oriented input sourced from gaze-guided wearable cameras, we scrutinize intricate attributes such as material properties, patients' dental conditions, and the array of instruments in use. Notably, we exploit the insight that identifying visual cues during an activity holds the potential to address the specific therapy identification challenge. Utilizing a dental data set that we gathered in the real world, we conducted our experiments and discovered that combining multiple criteria enhances accuracy in comparison to using each one alone. We did see, nevertheless, that in certain circumstances employing the symptoms alone produced superior outcomes. Additionally, symptoms demonstrated to have lesser error than combination in terms of RMS error convergence. Finally, we observed that the machine learning models' build and test durations increased as a result of the combined method. This demonstrates that adding additional parameters does not necessarily result in better outcomes in machine learning applications generally and in medical/dental applications in particular. Instead, it relies on the machine learning tool used, the settings taken into account and the input data provided. The versatility of our approach extends beyond dental contexts. It has been systematically validated across diverse domains, including the recognition of kitchen activities within smart home environments. This methodology holds relevance for various outdoor scenarios where the focal point of attention guides ongoing activities.

Use of Terrestrial High Frequency Signals in Riometer Data to Explore the Size of D‐Region Electron Density Enhancements

AbstractThis paper presents the first observations from the prototype Space Weather Adaptive Network (SWAN) riometers, which are capable of simultaneous measurements of narrow‐band terrestrial signal power and Cosmic Noise Absorption (CNA). We describe a methodology by which we can use coincident CNA and loss of known skywave‐mode, High Frequency (HF) signals to estimate a minimum size (geographic extent) of D‐region electron density enhancements. We demonstrate our technique with an example event. This methodology and early results provide a pathfinder for a continent‐wide array of SWAN instruments which would be capable of utilizing multiple intersecting terrestrial HF ray paths to reconstruct the size of D‐region electron density enhancements at the time of initial HF signal loss.

Design improvements to the SNS ion source and diagnostics

The U.S. Spallation Neutron Source (SNS) is a state-of-the-art neutron scattering facility delivering the world’s most intense pulsed-neutron beams to a wide array of instruments which are used to conduct investigations in many fields of science and engineering. The accelerator system is fed by an RF-driven, multicusp, H− ion source which nominally provides pulsed beam currents of 50-60 mA (1ms, 60Hz). This report provides a discussion of ongoing design improvements to the SNS ion source and Low Energy Beam Transport (LEBT) as well as diagnostic upgrades undertaken since the previous ICIS conference. These improvements include (i) simple mechanical modifications to the source outlet aperture which resulted in dramatically increased extracted beam current and comparable or lower emittance at similar beam currents, (ii) design improvements to the LEBT chopper target which will enable full power beam-dumping during physics studies, (iii) refinement of the SNS Allison emittance scanner that has enabled the first reliable LEBT beam measurements at full beam power (65kV, 50-100mA, 1ms, 60Hz) on the SNS ion source test stand and (iv) the implementation of a thermal imaging camera for the monitoring the LEBT electrode temperatures. (v) The design of an advanced Cs system, capable of more efficient Cs utilization with significantly lower Cs losses from the source is also presented. Mechanical details, computational simulations and experimental results are discussed within the context of these improvements.

BRICS expansion: new geographies and spheres of cooperation. Editorial for special Issue

Starting from January 1, 2024 the ranks of the BRICS grouping expanded to include new regional powers from the Global South. The paper aims to explore the implications of the new composition of the BRICS grouping for the vectors of its economic cooperation. The conclusion reached in the paper is that the widening of the ranks of the BRICS raises the importance of coordinating policies in the economic sphere, macroeconomic policy specifically, with particular attention to reforming the BRICS Contingent Reserve Arrangement (BRICS CRA). To estimate the prospects of the BRICS development after the expansion is to assist the group’s financial institutions, including the New Development Bank and the BRICS CRA, in the creation of a diversified array of policy instruments aimed at providing support for economic development of the expanded BRICS association members.

Wave attenuation and transformation across a highly turbid muddy tidal flat-salt marsh system

Understanding wave processes within the coastal system is crucial for the appropriate design of coastal prevention engineering and offshore structures. To address the limitations of field observations and traditional methods, an array of pressure sensors and optical instruments were deployed across a shoreward intertidal flat consisting of the fluid muddy seabed, bare flat, and salt marsh in a highly turbid coastal area. We found that the Spartina alterniflora salt marsh has the strongest wave dissipation capacity. Although bare flats have the weakest wave dissipation capacity, they are the most extensive within the intertidal zone, resulting in substantial total wave energy dissipation. A noteworthy positive feedback between fluid mud and wave dissipation is observed. Additionally, the incident waves undergo complex transitions during propagation, which are strongly modulated by tidal influences. In particular, when the wave propagation direction is opposite to the tidal current, there is an amplification of wave energy within the tidal flat. This amplification is attributed to the "jacking effect" of the tidal current, hindering the transformation of the wind waves into the low-energy capillary waves. It is important to note that the high-energy infragravity waves are gradually released and steadily increase as the incident waves propagate shoreward. This implies their potentially significant role in nearshore processes, especially during extreme dynamic events or along extensive coastlines.

The U. S. Commercial and Investment Banks, the Eurocurrency Markets, and the International Economy: from the Late 1970s Through the Start of the 1980s

This article, through the case study of Merrill Lynch and Lehman Brothers, investigates the role of U. S. commercial and investment banks in the development of the Eurocurrency markets from the 1970s to the start of the new decade, as well as the investment activities of U. S. financial institutions in the new financial environment of the 1980s based on the appearance of new financial actors and instruments. The first purpose is to frame the investment activities of American banking in the Eurodollar and other non resident markets against the backdrop of changing market pressures on the dollar from the first oil shock through to the monetary and financial consequences of combined second oil crisis and the historic decision by the newly appointed Chairman of the Board of Governors of the Federal Reserve System Paul A. Volcker to raise interest rates at unprecedented highs since 1980. Therefore, this article links the investment behaviour of American banks to the trajectory of U. S. dollar in the foreign exchange markets between the two oil crises of the 1970s. Secondly, this contribution pinpoints the variety of financial activities of American bankers during this period, which went way beyond the Eurodollar markets and involved, at least by the mid-1970s, a wide array of financial instruments both overseas and on domestic markets, from government securities to commercial paper assets. In the third instance, the aim is, as much as possible, to shed some preliminary lights on how the process of securitising, typical of the 1980s, was on the investment portfolios of American investors by the start of this decade. At the outset of this three-fold research target, the final objective is to make sense of the limited role of Eurodollar dealings and offerings in the context of trading and investment activities of U. S. financial institutions during the time frame considered, and particularly since the start of the new decade. In turn, this article suggests the multi-fold scope of financial activities of American banks in the context of macroeconomic and monetary transformations following the end of fixed exchange rates, the tottering of the dollar in the foreign exchange markets, and the meteoric rise of unregulated money markets since the 1970s, as well as the rise of securitisation since circa the year 1980.

Rationalising Mid‐Century Choice of Law: Legal Technique and its Limits in the ‘Dark Science’ of Conflicts

Under the common banner of a search for a ‘more rational’ approach to choice of law, US conflict‐of‐laws scholars of the late 1950s and the 1960s produced an impressive array of new technical instruments for their discipline. This article situates their work in the broader contexts of innovations in the social‐ and behavioural sciences and in legal‐ and political theory of this period. On this contextual reading, the methodological clashes of the so‐called ‘choice‐of‐law revolution’ change in shape and become part of a much larger story – one with relevance also outside the discipline and beyond the United States. That story is about different degrees of faith in the capacities of technical instruments and practices, like legal doctrine, to manage and resolve conflict, by making disparate factors commensurable, and by affording outcomes that optimise all competing interests in play. By revisiting these mid‐century battles over conflicts methods in light of contemporaneous understandings of ‘rationality’ and ‘legitimacy’ in other fields, the article contributes to our understanding of the genealogy of post‐war choice of law, as well as of the history of these ideals – and their technical means – in modern legal thought.

Evaluating the Impact of Renewable Energy Policy Instruments on Capacity Expansion: Insights from the Visegrad Group Countries

Renewable energy technologies have reached a pivotal point, demonstrating cost competitiveness with traditional energy sources and a continuing trend of affordability. Nevertheless, the successful deployment of renewable energy capacity crucially depends on the efficacy of renewable energy policy tools, casting a veil of uncertainty over their actual influence on the expansion of renewable electricity generation. This research delves into the array of policy instruments designed to bolster renewable energy capacity. Employing an econometric analysis, this study meticulously examines these policy tools, with a particular emphasis on feed-in tariffs, quotas, tenders, and tax incentives, seeking to facilitate the adoption of renewable energy within the Visegrad group countries, comprising the Czech Republic, Hungary, Poland, and Slovakia. Drawing from a comprehensive panel dataset spanning the years from 1990 to 2020, our findings unveil a nuanced perspective on the effectiveness of these renewable energy policy tools. Notably, our results underscore the varying degrees of success among different policy instruments, all of which significantly contribute to the advancement of renewable energy sources. A key revelation arises from the limited impact of quotas, a frequently employed regulatory measure, in stimulating the expansion of renewable electricity generation capacity. In contrast, feed-in tariffs, tenders, and tax incentives emerge as potent drivers in achieving this pivotal objective. This research sheds light on the dynamic landscape of renewable energy policy instruments, offering valuable insights for policymakers and stakeholders engaged in advancing sustainable and resilient energy ecosystems in the Visegrad group countries and beyond.

Effectiveness of environmental regulations: firm’s decisions and welfare implications

In this paper, we compare four policy instruments–tax, subsidy, binding emissions and cap-and-trade, to determine which policy is the most effective and whether they are equivalent. We also examine if a firm’s policy preference differs from that of a policymaker. Our motivation stems from the global use of a wide array of pollution instruments. Using a game theoretic approach, we analyze how carbon abatement, production quantity, profitability and welfare vary between different policy tools. We find that the tax policy is equivalent to the binding emission standards while welfare comparison shows that the highest welfare is attributed to either the tax or subsidy policy depending on the levels of environmental damage. We find that both the policymaker and the firm prefer a subsidy policy under lower thresholds of environmental damage. Exploring hybrid policies, we find that a multi-part tariff contract jointly implements the socially optimal outcomes and leads to a win-win situation for both the firm and the policymaker. Our findings offer guidance for policymakers and managers to implement appropriate policies based on the degree of environmental damage and to consider using hybrid policies that achieve higher pollution abatement and improved welfare.

Study on Grid-Connected Power Quality Improvement of Wind Farms Based on Repetitive Controller

The project highlights the wind energy and the process followed in the wind farms in order to generate the energy by using wind power and wind capacity as well. Moreover, it has been observed that wind energy is also considered one of the most effective electrical energy sources. The application of wind energy can be beneficial for different aspects of the business sectors of different countries across the globe and this is possible because of its cost-effectiveness. Furthermore, this study encompasses the strategies employed within wind farms to preserve and efficiently harness wind power for the generation of electrical energy. Notably, the project delineates the utilization of a diverse array of instruments, each instrumental in the conversion of wind power into valuable wind energy. Beyond the realm of technology, wind farms grapple with a spectrum of formidable challenges, stemming from the inherently capricious nature of wind. In addition, various issues concerning power quality and the stability of the power system have also been identified within these wind farms. To ameliorate these multifaceted challenges, the project introduces a range of meticulous control measures for implementation.

Multi-objective Snow Ablation Optimization Algorithm: An Elementary Vision for Security-Constrained Optimal Power Flow Problem Incorporating Wind Energy Source with FACTS Devices

This study delves into the exploration of a novel Multi-objective Snow Ablation Optimizer (MOSAO) algorithm, tailored for addressing expansive Optimal Power Flow (OPF) challenges inherent in intricate power systems. These systems are often complemented with the integration of renewable energy modalities and the state-of-the-art Flexible AC Transmission Systems (FACTS). Building upon the foundational framework of a previously documented single-objective Snow Ablation Optimizer, we have evolved it into the MOSAO paradigm. This transformation is achieved by harnessing the potency of non-dominated sorting coupled with the crowding distance strategy. The task of OPF magnifies in complexity when integrating renewable energy resources due to their inherent unpredictability and intermittent nature. As the modern power landscape evolves, FACTS devices are witnessing an increasing deployment to mitigate network demand and alleviate congestion issues. Within the ambit of this research, we've incorporated a stochastic wind energy source, working synergistically with an array of FACTS instruments. These encompass the static VAR compensator, thyristor-controlled series compensator and thyristor-driven phase shifter, all operating within the confines of an IEEE-30 bus framework. Strategic placement and calibration of these FACTS devices aim to optimize the system by minimizing the cumulative fuel expenditure. The capricious essence of wind as an energy source is elegantly depicted through the lens of Weibull probability density graphs. To distil the optimal middle-ground solutions, we've employed a fuzzy decision-making matrix. When benchmarking our findings against those derived from other esteemed optimization algorithms, we observe a notable distinction. The results from the modified IEEE-30 bus system accentuate the superior convergence, diversity and distribution attributes of MOSAO, especially when scrutinizing power flows. The MOSAO source code is available at: https://github.com/kanak02/MOSAO.

Lagoon hydrodynamics of pearl farming islands: the case of Gambier (French Polynesia)

Abstract. Between 2019 and 2020, the Gambier lagoon was instrumented over a period of 9 months with a large array of autonomous oceanographic instruments measuring temperature, pressure, and current. Two deployments were conducted from June to October 2019 (Leg1) and from late October 2019 to late February 2020 (Leg2). A total of 16 instrumented locations were spread across the lagoon and on the forereef. Physical parameters were measured to characterize the wave climate, tide and surges, lagoonal circulation, and spatial and vertical temperature variabilities. Those observations were part of the ANR-funded MANA project (2017–2022) and its derivatives that were aimed at improving knowledge of processes influencing the spat collection of Pinctada margaritifera oysters that are used for black pearl farming and production. This dataset was a prerequisite for the development of a high-resolution biophysical model on the Gambier lagoon that is aimed at understanding the connectivity of oyster larvae (Bruyère et al., 2023a). The sampling strategy focused on the northern region of the Gambier lagoon and especially on the sub-lagoon of Rikitea, which is a prime spat collection site. The dataset was post processed, quality controlled, and is archived in a dedicated repository with a permanent DOI via the SEANOE marine data platform (https://doi.org/10.17882/94148, Andréfouët et al., 2023b).

An Open-Access Data Set of Active-Source and Passive-Wavefield DAS and Nodal Seismometer Measurements at the Newberry Florida Site

Abstract This article documents a comprehensive subsurface imaging experiment using seismic waves in a well-studied outdoor laboratory at Newberry, Florida, which is known for significant spatial variability, karstic voids, and underground anomalies. The experiment used approximately two kilometers of distributed acoustic sensing (DAS) fiber-optic cable, forming a dense 2D array of 1920 horizontal-component channels, and a 2D array of 144 SmartSolo three-component nodal seismometers, to sense active-source and passive-wavefield seismic waves. The active-source data were generated using a powerful, triaxial vibroseis shaker truck (T-Rex) and impact sources (accelerated weight drop and an eight-pound sledgehammer) that were simultaneously recorded by both the DAS and nodal seismometers. The vibroseis truck was used to excite the ground in three directions (two horizontal and one vertical) at 260 locations inside and outside the instrumented array, whereas the impact sources were used at 268 locations within the instrumented array. The passive-wavefield data recorded using the nodal seismometers comprised 48 hr of ambient noise collected over a period of four days in four 12-hour time blocks, whereas the passive wavefield data collected using DAS consisted of four hours of ambient noise recordings. This article aims to provide a comprehensive overview of the testing site, experiment layout, the DAS and nodal seismometer acquisition parameters, and implemented raw data processing steps. Although potential use cases, such as surface-wave testing, full-waveform inversion, and ambient noise tomography, are discussed relative to example data, the focus of this article is on documenting this unique data set and presenting its initial data quality rather than on generating subsurface imaging results. The raw and processed data, along with detailed documentation of the experiment and Python tools to aid in visualizing the DAS data set, have been made publicly available.