Site-specific Characteristics Research Articles

Framework for Regional to Global Extension of Optical Water Types for Remote Sensing of Optically Complex Transitional Water Bodies

Water quality indicator algorithms often separate marine and freshwater systems, introducing artificial boundaries and artifacts in the freshwater to ocean continuum. Building upon the Ocean Colour- (OC) and Lakes Climate Change Initiative (CCI) projects, we propose an improved tool to assess the interactions across river–sea transition zones. Fuzzy clustering methods are used to generate optical water types (OWT) representing spectrally distinct water reflectance classes, occurring within a given region and period (here 2016–2021), which are then utilized to assign membership values to every OWT class for each pixel and seamlessly blend optimal in-water algorithms across the region. This allows a more flexible representation of water provinces across transition zones than classic hard clustering techniques. Improvements deal with expanded sensor spectral band-sets, such as Sentinel-3 OLCI, and increased spatial resolution with Sentinel-2 MSI high-resolution data. Regional clustering was found to be necessary to capture site-specific characteristics, and a method was developed to compare and merge regional cluster sets into a pan-regional representative OWT set. Fuzzy clustering OWT timeseries data allow unique insights into optical regime changes within a lagoon, estuary, or delta system, and can be used as a basis to improve WQ algorithm performance.

Derivation of ecotoxicologically acceptable Cu concentrations in soil from different land uses in South Korea

This study aimed to establish ecotoxicologically acceptable Cu concentrations for soil-residing species by integrating the biotic ligand model and the species sensitivity distribution. Statistical analyses were performed on 35 soil solution samples collected from four distinct land use sites: residential, agricultural, forested, and industrial regions. The environmental parameters of these samples, including pH, dissolved organic carbon (DOC), Ca2⁺, Mg2⁺, K⁺, and Na⁺ concentrations, exhibited wide variations across the four regions. Specifically, pH and the concentrations of Mg2⁺, K⁺, and Na⁺ showed significant variability. Additionally, a strong correlation was observed between pH and Ca2⁺, as well as between the DOC concentration and Mg2⁺ and Na⁺. Using the biotic ligand model, we derived the half-maximal effective activities of Cu (EC50{Cu2+}) for 10 soil organisms based on the chemical compositions of the soil solution samples. Additionally, a species sensitivity distribution approach was employed to determine the 5% hazardous concentration (HC5) for soil biota, which was closely associated with DOC and Na⁺ concentrations, with Mg2⁺ playing a secondary role. We attributed these relationships to the formation of DOC complexes that mitigate Cu toxicity, along with competitive interactions with cations. Notably, HC5 values did not differ significantly across sampling sites (p = 0.523). Clustering based on environmental factors grouped the samples into four clusters, each containing soils from different land use types. However, the third cluster included an outlier from agricultural soil due to its unusually high pH and DOC levels. These findings suggest that it is crucial to consider site-specific soil characteristics when determining ecotoxicologically acceptable Cu concentrations, and soil solution characteristics do not always align with specific land use patterns.

Malignant Rhabdoid Tumor and Related Pediatric Tumors: Multimodality Imaging Review with Pathologic Correlation.

Malignant rhabdoid tumors (MRTs) are rare but lethal solid neoplasms that overwhelmingly affect infants and young children. While the central nervous system is the most common site of occurrence, tumors can develop at other sites, including the kidneys and soft tissues throughout the body. The anatomic site of involvement dictates tumor nomenclature and nosology. While the clinical and imaging manifestations of MRTs and other more common entities may overlap, there are some site-specific distinctive imaging characteristics. Irrespective of the site of occurrence, somatic and germline mutations in SMARCB1, and rarely in SMARCA4, underlie the entire spectrum of rhabdoid tumors. MRTs have a simple and remarkably stable genome but can demonstrate considerable molecular and biologic heterogeneity. Related neoplasms encompass an expanding category of phenotypically dissimilar (nonrhabdoid tumors driven by SMARC-related alterations) entities. US, CT, MRI, and fluorodeoxyglucose PET/CT or PET/MRI facilitate diagnosis, initial staging, and follow-up, thus informing therapeutic decision making. Multifocal synchronous or metachronous rhabdoid tumors occur predominantly in the context of underlying rhabdoid tumor predisposition syndromes (RTPSs). These autosomal dominant disorders are driven in most cases by pathogenic variants in SMARCB1 (RTPS type 1) and rarely by pathogenic variants in SMARCA4 (RTPS type 2). Genetic testing and counseling are imperative in RTPS. Guidelines for imaging surveillance in cases of RTPS are based on age at diagnosis. ©RSNA, 2024 Supplemental material is available for this article.

Histo- and molecular pathology in gastroenteropancreatic neuroendocrine neoplasms

Neuroendocrine neoplasms are classified according to the WHO classification based on morphological criteria into neuroendocrine tumors, neuroendocrine carcinomas, and mixed neuroendocrine-non-neuroendocrine neoplasms. Neuroendocrine tumors are well differentiated neoplasms and show characteristic site-specific histological and molecular features, which is important for their clinical management. In cases dealing with metastasis, pathology often can help to identify the primary tumors using a small immunohistochemical marker panel. Neuroendocrine carcinomas are poorly differentiated neoplasms. They are subdivided into neuroendocrine carcinomas of small cell and large cell type. The molecular profile of neuroendocrine carcinomas and mixed neuroendocrine-non-neuroendocrine neoplasms shows a close relationship to conventional adenocarcinomas with site-specific features. Molecular analysis of neuroendocrine carcinomas and neuroendocrine-non-neuroendocrine neoplasms are not yet fully integrated in daily diagnostics and are mainly performed in the context of precision oncology.

Vibroacoustic characterization of a chamber music concert room in the context of the urban texture

The integrated interpretation of the tangible and intangible dimensions of cultural heritage assets is challenging, since much of the required information is often lost or difficult to find. In particular, when coming to the functional planning of historic spaces or archaeological sites, documental or archival sources are scarce or even absent. Consequently, to support the interpretation of these functional design and planning elements, which are related to the life of communities that inhabited those areas, quantitative methods, such as a physical characterization of site-specific environmental variables, may assume a great relevance, like in the case of the vibro-acoustic properties conceived for specific uses or performances, as theatres, cathedrals or other public spaces. With this goal in mind, we have started a pilot experimental activity, aiming at characterizing the vibroacoustic fingerprint, i.e. the vibro-acoustic site-specific features, of a historic building private chamber music concert room, located in the centre of Napoli (South Italy). This work, based on the integration of different sensors and modelling tools, has allowed to observe the site-specific vibroacoustic features not only in relation to the geometric features of the space, but also in relation to the surrounding urban landscape morphology. Consequently, the results have evidenced the presence of a site-specific vibroacoustic fingerprint, related to how the structure and the surrounding urban morphology were planned. The applied integration of a unifying model, previously validated in the literature, and of broadband vibroacoustic measures, has allowed to evidence some quantitative elements, that, characterizing the interaction between spaces and the people living them, constitute a possible basis for interpreting the heritage intangible components (design according to functional and/or symbolic purposes) in relation to different structural urbanistic and architectural elements (tangible heritage).

Intelligent fault detection of photovoltaic panel using neural networks

This research primarily aims to leverage artificial neural network technology for diagnosing power output issues in photovoltaic (PV) panels stemming from fluctuations in solar irradiance and temperature. The proposed diagnostic approach relies on constructing a reference model that captures the expected normal operating behavior of the PV panel under fault-free conditions. This reference model is then compared against the actual power output, and the difference, known as the residual, is analyzed to detect potential faults. The neural network is trained using real-world data inputs like solar irradiance and temperature measurements, with the sole output being the power produced by the PV panel. Through training, the neural network learns to map the complex non-linear relationships between environmental inputs and expected power output, effectively modeling the PV system's intrinsic behavior under healthy conditions. Results demonstrate the neural network-based approach's remarkable ability to diagnose faults with high accuracy while avoiding potential non-linear complications. This intelligent monitoring system provides a reliable protocol for early fault detection through training on actual measurements, eliminating the need for complex mathematical models. Consequently, it streamlines the maintenance process by negating intricate procedures to identify PV panel issues. The neural network effectively learns the mapping between environmental conditions and expected power output through exposure to real-world data during training. By analyzing deviations from this learned mapping, represented by the residual signal, the approach can reliably detect anomalies indicative of faults or performance degradation in the PV system. This data-driven nature allows the system to adapt to site-specific characteristics and capture non-linear effects without explicit modeling.

Site effect on seismic response of buried nuclear power plant structure

The development of multifunctional, multipurpose small modular next generation nuclear reactors has become a trend in designing small-scale nuclear power stations. In this study, taking a new next-generation buried nuclear power structure as the target structure, a 3D finite element model of the site-nuclear power plant structure system was established, and its response at different sites was studied. Using the internal substructure method, this study initially explored the impact of earthquake input and artificial boundary locations on the structural response. The results indicate that the internal substructure method enhances computational efficiency without compromising accuracy. For this model, it is recommended to input earthquake motion close to the structure, set the lateral boundary location to three times the width of the structure, and set the bottom boundary location to two times the depth of the structure. Subsequently, an investigation into the response of the structure at varying site wave velocities is conducted. The results show that as the wave velocity increases, the acceleration response intensifies, while the displacement response diminishes. However, the relationship is nonlinear; the response exhibits less variation with increasing site wave velocity. The seismic response of a structure is profoundly influenced by site conditions, emphasizing the imperative need for careful consideration of specific site characteristics in seismic analyses. In addition, the response pattern of the overall structure is significantly different from that of conventional large surface-sited nuclear power plants, and further research should be conducted on the seismic response characteristics of buried nuclear power plants.

Understanding the dynamics of microplastics transport in urban stormwater runoff: Implications for pollution control and management

The transport of microplastics (MPs) from urban environments to water resources via stormwater runoff poses significant concerns due to its adverse impacts on water safety and aquatic ecosystems. This study presents a modeling approach aimed at understanding the transport mechanisms of MPs in an urban residential setting, considering settling and buoyant MPs. To consider the effect of MP shapes, the settling velocity of various settling MPs in shapes of fibers, films, and fragments was calculated. Using an analogy of sediment transport, a Rouse number criterion was used to analyze the transport of MPs. For buoyant MPs, it was assumed that they transport as wash-load as soon as they float in the water and the travel time for them to reach the storm drain was determined. The calculation of settling velocity revealed the influence of shape on the settling velocity of MPs was particularly pronounced as the equivalent diameter of the MPs increased. The transport mechanism for the smallest settling MPs, irrespective of their shapes, density, and depth of flow, was wash-load. However, for larger MPs, the shape and size distribution of settling MPs, along with the depth of flow and slope significantly influenced their transport mechanisms compared to sediment particles. The influence of weathering on the MPs’ transport mechanisms depended on their sizes and shapes. The site-specific characteristics, including slope and surface friction, significantly influenced the velocity of stormwater runoff and, consequently, the extent of MP transport during rain events. Moreover, an evaluation of the transport mechanism of settling MPs was conducted using the reported field data on MP abundance in road dust collected from residential and traffic sites. This study underscores the complexity of MP transport dynamics and provides a foundation for developing targeted strategies to mitigate MP pollution in urban environments.

Mesoscale-coupled Large Eddy Simulation for Wind Resource Assessment

Turbulence, a key driver of wind turbine loads, is central in the assessment of turbine suitability and performance, and consequently impacts the expected energy production of a wind farm. Conventional flow modeling methods for wind resource assessment (WRA) typically lack the ability to resolve turbulence due to key simplifications in their formulation. This work applies Large Eddy Simulation (LES) to address these limitations and deliver high-fidelity wind condition predictions at 24 wind farm sites. The model includes recently improved boundary conditions to downscale information from global weather models via a mesoscale layer. Validation of the model is presented through comparison to over 100 years of measurements, with comparison of the time-series, distributions and spectra. Validation results indicate excellent performance of the model for key flow quantities including wind speed, turbulence and direction. Comparison of spectra indicates a significant improvement in the representation of the atmospheric energy cascade when compared to previous approaches. The results are significant for wind-farm site assessment as they demonstrate the feasibility of applying accurate LES at a commercial scale. LES also provides a step change in the quality of model predictions through resolving time and site-specific turbulence characteristics. The application of the model for WRA is a step towards improved understanding of the wind resource, as well as an improved suitability assessment process itself.

Simple process-led algorithms for simulating habitats (SPLASH v.2.0): robust calculations of water and energy fluxes

Abstract. The current representation of key processes in land surface models (LSMs) for estimating water and energy balances still relies heavily on empirical equations that require calibration oriented to site-specific characteristics. When multiple parameters are used, different combinations of parameter values can produce equally acceptable results, leading to a risk of obtaining “the right answers for the wrong reasons”, compromising the reproducibility of the simulations and limiting the ecological interpretability of the results. To address this problem and reduce the need for free parameters, here we present novel formulations based on first principles to calculate key components of water and energy balances, extending the already parsimonious SPLASH model v.1.0 (Davis et al., 2017, GMD). We found analytical solutions for many processes, enabling us to increase spatial resolution and include the terrain effects directly in the calculations without unreasonably inflating computational demands. This calibration-free model estimates quantities such as net radiation, evapotranspiration, condensation, soil water content, surface runoff, subsurface lateral flow, and snow-water equivalent. These quantities are derived from readily available meteorological data such as near-surface air temperature, precipitation, and solar radiation, as well as soil physical properties. Whenever empirical formulations were required, e.g., pedotransfer functions and albedo–snow cover relationships, we selected and optimized the best-performing equations through a combination of remote sensing and globally distributed terrestrial observational datasets. Simulations at global scales at different resolutions were run to evaluate spatial patterns, while simulations with point-based observations were run to evaluate seasonal patterns using data from hundreds of stations and comparisons with the VIC-3L model, demonstrating improved performance based on statistical tests and observational comparisons. In summary, our model offers a more robust, reproducible, and ecologically interpretable solution compared to more complex LSMs.

Mapping sub-surface distribution of soil organic carbon stocks in South Africa's arid and semi-arid landscapes: Implications for land management and climate change mitigation

Soil organic carbon (SOC) stocks are critical for land management strategies and climate change mitigation. However, understanding SOC distribution in South Africa's arid and semi-arid regions remains a challenge due to data limitations, and the complex spatial and sub-surface variability in SOC stocks driven by desertification and land degradation. Thus, to support soil and land-use management practices as well as advance climate change mitigation efforts, there is an urgent need to provide more precise SOC stock estimates within South Africa's arid and semi-arid regions. Hence, this study adopted remote-sensing approaches to determine the spatial sub-surface distribution of SOC stocks and the influence of environmental co-variates at four soil depths (i.e., 0-30 cm, 30-60 cm, 60-100 cm, and 100-200 cm). Using two regression-based algorithms, i.e., Extreme Gradient Boosting (XGBoost) and Random Forest (RF), the study found the former (RMSE values ranging from 7.12 t/ha to 29.55 t/ha) to be a superior predictor of SOC in comparison to the latter (RMSE values ranging from 7.36 t/ha to 31.10 t/ha). Nonetheless, both models achieved satisfactory accuracy (R2 ≥ 0.52) for regional-scale SOC predictions at the studied soil depths. Thereafter, using a variable importance analysis, the study demonstrated the influence of climatic variables like rainfall and temperature on SOC stocks at different depths. Furthermore, the study revealed significant spatial variability in SOC stocks, and an increase in SOC stocks with soil depth. Overall, these findings enhance the understanding of SOC dynamics in South Africa's arid and semi-arid landscapes and emphasizes the importance of considering site specific topo-climatic characteristics for sustainable land management and climate change mitigation. Furthermore, the study offers valuable insights into sub-surface SOC distribution, crucial for informing carbon sequestration strategies, guiding land management practices, and informing environmental policies within arid and semi-arid environments.

Changes in categorization or nomenclature within neuroendocrine tumors.

The 5th edition of the World Health Organization (WHO) classification of neuroendocrine neoplasms (NENs) is built to achieve a uniform terminology and to define a similar diagnostic scheme across different anatomic locations. Since the 4th edition, a chapter discussing NENs in nonneuroendocrine organs has been introduced, which proposes a binary system for classification segregating well-differentiated neoplasms, termed neuroendocrine tumors (NETs), and poorly differentiated neoplasms, termed neuroendocrine carcinomas (NECs). A grading system for NETs is based on mitotic index and/or Ki-67 index and/or necrosis, depending on the different locations. Although this approach has been already well established in the digestive system, it modifies and homogenizes the classification of NENs in the urinary tract, in female genital organs, and in the male genital system. In the lung and thymus, the double terminology of carcinoid/NET, already introduced in the 5th edition of the WHO classification of thoracic tumors, is endorsed. This approach undoubtedly helps the multidisciplinary approach for the diagnosis and clinical management of patients affected by these neoplasms, without losing site-specific characteristics that influence the clinical and biological behavior of tumors in different anatomical sites. Other major advances of the new WHO scheme are the homogenization of epidemiological data and the correct integration of data from prospective future studies aimed at the definition of molecular profiles and at the identification of tumor type-specific and patient-specific therapeutic approaches.

In-situ groundwater remediation of contaminant mixture of As(III), Cr(VI), and sulfanilamide via electrochemical degradation/transformation using pyrite

Electrochemical advanced oxidation processes (EAOPs) are effective in removing persistent contaminants from groundwater. However, their practical applicability depends significantly on various site-specific characteristics. Therefore, the primary objective of this investigation was to study the feasibility of EAOPs and pyrite, which is a sulfide mineral, to effectively remove the mixture of arsenic (As (III)), chromium (Cr (VI)), and sulfanilamide in groundwater. We conducted a comparison of three systems: (1) EAOP alone, (2) pyrite alone, and (3) a combined EAOP and pyrite system. In EAOP alone, sulfanilamide was effectively oxidized (80%), while the electrochemical transformation of As(III)/Cr(VI) into As(V)/Cr(III) was limited. In just the pyrite system, As(III), Cr(VI), and sulfanilamide were adsorbed onto the surface of pyrite (60%, 20%, and 18%). Neither the EAOP nor the pyrite system alone could effectively treat the contaminants mixture. Nonetheless, the combined system completely removed As(III), Cr(VI), and sulfanilamide by the synergistic reaction. This could be attributed to the formation of green rust, a natural adsorbent mineral produced as a reaction of dissolved iron, generated via electrochemical pyrite oxidation, with the groundwater electrolyte (e.g., CO3 or SO4). This system harmonized the combined approach of EAOP and pyrite to effectively eliminate both organic and inorganic contaminants. Environmental implicationA paper proposed electrochemical oxidation (EO) with pyrite to remove both organic and inorganic contaminants from groundwater. The removal performance of the combined system was evaluated, and the synergistic mechanism was revealed. The combination of EO and pyrite with synergistic removal effectively removed the mixture of both contaminants. This could be attributed by the formation of green-rust by electrochemical activation for pyrite. Compared to the single system of EO and pyrite alone, the combined system with EO and pyrite improved removal performance. Results suggested that the combined system could be used for green groundwater remediation.

Enhancing Primary Care and Mental Health Integration for Women Veterans with Complex Healthcare Needs Using Evidence-Based Quality Improvement.

Women Veterans with co-morbid medical and mental health conditions face persistent barriers accessing high-quality health care. Evidence-based quality improvement (EBQI) offers a systematic approach to implementing new care models that can address care gaps for women Veterans. This study examines factors associated with the successful deployment of EBQI within integrated health systems to improve primary care for women Veterans with complex mental health needs. Following a 12-site (8 EBQI, 4 control) cluster randomized study to evaluate EBQI effectiveness, we conducted an in-depth case study analysis of one women's health clinic that used EBQI to improve integrated primary care-mental health services for women Veterans. Our study sample included providers, program managers, and clinic staff at a women Veteran's health clinic that, at the time of the study, had one Primary Care and Mental Health Integration team and one women's health primary care provider serving 800 women. We analyzed interviews conducted 12 months, 24 months, and 4 years post-implementation and call summaries between the clinic and support team. We conducted qualitative thematic analysis of interview and call summary data to identify EBQI elements, clinic characteristics, and reported challenges and successes within project development and execution. The clinic harnessed core EBQI elements (multi-level stakeholder engagement, data-driven progress-monitoring, PDSA cycles, sharing results) to accomplish pre-defined project goals, strengthen inter-disciplinary partnerships, and bolster team confidence. Clinic characteristics that facilitated implementation success included prior QI experience and an organizational culture responsive to innovation, while lack of pre-existing guidelines and limited access to centralized databases posed implementation challenges. Successful practice transformation emerges through the interaction of evidence-based methods and site-specific characteristics. Examining how clinic characteristics support or impede EBQI adaptation can facilitate efforts to improve care within integrated health systems.

Gastric neuroendocrine neoplasms.

Gastric neuroendocrine neoplasms (gNENs) display peculiar site-specific features among all NENs. Their incidence and prevalence have been rising in the past few decades. gNENscomprise gastric neuroendocrine carcinomas (gNECs) and gastricneuroendocrine tumours (gNETs), the latter further classified into three types. Type I anatype II gNETs are gastrin-dependent and develop in chronic atrophic gastritis and as part of Zollinger-Ellison syndrome within a multiple endocrine neoplasia type 1 syndrome (MEN1), respectively. Type III or sporadic gNETs develop in the absence of hypergastrinaemia and in the context of a near-normal or inflamed gastric mucosa. gNECs can also develop in the context of variable atrophic, relatively normal or inflamed gastric mucosa. Each gNEN type has different clinical characteristics and requires a different multidisciplinary approach in expert dedicated centres. Type I gNETs are managed mainly by endoscopy or surgery, whereas the treatment of typeII gNETs largely depends on the management of the concomitant MEN1. Type III gNETs may require both locoregional approaches and systemic treatments; NECs are often metastatic and therefore require systemic treatment. Specific data regarding the systemic treatment of gNENs are lacking and are derived from the treatment of intestinal NETs and NECs. An enhanced understanding of molecular and clinical pathophysiology is needed to improve the management and outcomes of patients' gNETs.

Carbon Storage and Sequestration Analysis by Urban Park Grid Using i-Tree Eco and Drone-Based Modeling

Urban areas play a crucial role in carbon absorption, while also producing a considerable amount of carbon emissions. However, there has been a lack of research that has systematically examined the carbon storage and sequestration in green spaces located within urban environments, at a spatial scale. This study analyzes carbon storage and sequestration in Yurim Park, Daejeon, South Korea on a grid basis to fill the research gap. The research compares the variation in sequestration capacity across different grids and provides insights into the development of sustainable urban parks in urban planning. The classification of grids is based on specific site characteristics, such as land cover, tree distribution, type, and density. This results in a total of seven distinct types. The study employs a combination of the I-tree eco model, drone-based modeling, and on-site surveys to estimate carbon storage and sequestration in urban parks. The results show that the average carbon storage per unit area in the entire park was 15.3 tons of carbon per hectare, ranging from a minimum of 5.0 to a maximum of 21.4 tons per hectare. For the planted area, the average carbon storage was 8.6 tons per hectare. Grids with green areas dominated by broad-leaved trees and closed canopy cover had the highest carbon sequestration and storage values. The planting area ratio and the type of trees planted were found to directly influence the carbon sequestration capacity per unit area of urban parks. This study stands out from previous research by conducting a detailed area-based comparison and analysis of carbon sequestration capacity in urban parks using sophisticated measurement techniques. The findings offer direct insights into strategies and policies for securing future urban carbon sinks and can be of practical use in this regard.

Socioeconomic and ethnic disparities associated with access to cochlear implantation for severe-to-profound hearing loss: A multicentre observational study of UK adults.

Patients with severe-to-profound hearing loss may benefit from management with cochlear implants. These patients need a referral to a cochlear implant team for further assessment and possible surgery. The referral pathway may result in varied access to hearing healthcare. This study aimed to explore referral patterns and whether there were any socioeconomic or ethnic associations with the likelihood of referral. The primary outcome was to determine factors influencing referral for implant assessment. The secondary outcome was to identify factors impacting whether healthcare professionals had discussed the option of referral. A multicentre multidisciplinary observational study was conducted in secondary care Otolaryngology and Audiology units in Great Britain. Adults fulfilling NICE (2019) audiometric criteria for implant assessment were identified over a 6-month period between 1 July and 31 December 2021. Patient- and site-specific characteristics were extracted. Multivariable binary logistic regression was employed to compare a range of factors influencing the likelihood of implant discussion and referral including patient-specific (demographics, past medical history, and degree of hearing loss) and site-specific factors (cochlear implant champion and whether the hospital performed implants). Hospitals across all 4 devolved nations of the UK were invited to participate, with data submitted from 36 urban hospitals across England, Scotland, and Wales. Nine hospitals (25%) conducted cochlear implant assessments. The majority of patients lived in England (n = 5,587, 86.2%); the rest lived in Wales (n = 419, 6.5%) and Scotland (n = 233, 3.6%). The mean patient age was 72 ± 19 years (mean ± standard deviation); 54% were male, and 75·3% of participants were white, 6·3% were Asian, 1·5% were black, 0·05% were mixed, and 4·6% were self-defined as a different ethnicity. Of 6,482 submitted patients meeting pure tone audiometric thresholds for cochlear implantation, 311 already had a cochlear implant. Of the remaining 6,171, 35.7% were informed they were eligible for an implant, but only 9.7% were referred for assessment. When adjusted for site- and patient-specific factors, stand-out findings included that adults were less likely to be referred if they lived in more deprived area decile within Indices of Multiple Deprivation (4th (odds ratio (OR): 2·19; 95% confidence interval (CI): [1·31, 3·66]; p = 0·002), 5th (2·02; [1·21, 3·38]; p = 0·05), 6th (2·32; [1·41, 3·83]; p = 0.05), and 8th (2·07; [1·25, 3·42]; p = 0·004)), lived in London (0·40; [0·29, 0·57]; p < 0·001), were male (females 1·52; [1·27, 1·81]; p < 0·001), or were older (0·97; [0·96, 0·97]; p < 0·001). They were less likely to be informed of their potential eligibility if they lived in more deprived areas (4th (1·99; [1·49, 2·66]; p < 0·001), 5th (1·75; [1·31, 2·33], p < 0·001), 6th (1·85; [1·39, 2·45]; p < 0·001), 7th (1·66; [1·25, 2·21]; p < 0·001), and 8th (1·74; [1·31, 2·31]; p < 0·001) deciles), the North of England or London (North 0·74; [0·62, 0·89]; p = 0·001; London 0·44; [0·35, 0·56]; p < 0·001), were of Asian or black ethnic backgrounds compared to white patients (Asian 0·58; [0·43, 0·79]; p < 0·001; black 0·56; [0·34, 0·92]; p = 0·021), were male (females 1·46; [1·31, 1·62]; p < 0·001), or were older (0·98; [0·98, 0·98]; p < 0·001). The study methodology was limited by its observational nature, reliance on accurate documentation of the referring service, and potential underrepresentation of certain demographic groups. The majority of adults meeting pure tone audiometric threshold criteria for cochlear implantation are currently not appropriately referred for assessment. There is scope to target underrepresented patient groups to improve referral rates. Future research should engage stakeholders to explore the reasons behind the disparities. Implementing straightforward measures, such as educational initiatives and automated pop-up tools for immediate identification, can help streamline the referral process.

Arbuscular Mycorrhizal Fungi and Rhizobium Improve Nutrient Uptake and Microbial Diversity Relative to Dryland Site-Specific Soil Conditions.

Arbuscular mycorrhizal fungi (AMF) and rhizobium play a significant role in plant symbiosis. However, their influence on the rhizosphere soil microbiome associated with nutrient acquisition and soil health is not well defined in the drylands of Montana (MT), USA. This study investigated the effect of microbial inoculants as seed treatment on pea yield, nutrient uptake, potential microbial functions, and rhizosphere soil microbial communities using high-throughput sequencing of 16S and ITS rRNA genes. The experiment was conducted under two contrasting dryland conditions with four treatments: control, single inoculation with AMF or Rhizobium, and dual inoculations of AMF and Rhizobium (AMF+Rhizobium). Our findings revealed that microbial inoculation efficacy was site-specific. AMF+Rhizobium synergistically increased grain yield at Sidney dryland field site (DFS) 2, while at Froid site, DFS 1, AMF improved plant resilience to acidic soil but contributed a marginal yield under non-nutrient limiting conditions. Across dryland sites, the plants' microbial dependency on AMF+Rhizobium (12%) was higher than single inoculations of AMF (8%) or Rhizobium (4%) alone. Variations in microbial community structure and composition indicate a site-specific response to AMF and AMF+Rhizobium inoculants. Overall, site-specific factors significantly influenced plant nutrient uptake, microbial community dynamics, and functional potential. It underscores the need for tailored management strategies that consider site-specific characteristics to optimize benefits from microbial inoculation.

Site-specific stochastic ground motion model utilizing deterministic physics-informed simulations: A Bayesian approach

Limited availability of recorded ground motions poses a challenge for reliable probabilistic seismic-hazard analysis (PSHA), even in highly seismic regions like the Western United States. Stochastic ground motions are commonly employed to address this challenge. However, the stochastic ground motion models (GMMs) may not consistently generate ground motions compatible with the site hazard due to their calibration using global data, failing to capture site-specific characteristics adequately. In the absence of recorded motions, physics-informed simulations provide a viable alternative but are deterministic with limitations of their own that makes them challenging to support PSHA. This article introduces a Bayesian framework that combines prior knowledge from a stochastic GMM, calibrated with global data, with site-specific data obtained from deterministic physics-informed simulations. The proposed framework utilizes the Rezaeian–Der Kiureghian (2010) model as the stochastic GMM and incorporates site-specific data from the CyberShake 15.12 study. By updating the mean and variance of the predictive relationships, along with the marginal distribution of the model parameters, through Bayesian inference, this framework allows for the simulation of site-specific ground motions consistent with the site characteristics. The statistics of peak ground acceleration distributions, as well as both the median and variability of the elastic response spectra, obtained from the calibrated stochastic GMM, demonstrate consistency with those derived using GMMs based on the Next Generation Attenuation (NGA) database.

Combining groundwater and game-theoretical models for determining the sustainable yield in a heavily stressed aquifer system

Sustainable groundwater abstraction is nowadays widely debated and the application of criteria available in the literature is not easy depending on site-specific features of the systems. In the Tivoli Plain (Rome, Italy) the same groundwater resource is exploited by an important thermal plant for therapeutic purposes and is subject to dewatering for the extraction of travertine by numerous quarries, thus representing a significant case of conflict among different resources users. The study proposes a new approach in defining the sustainability of groundwater exploitation by matching the results of groundwater flow model with those of a game model. From the conceptual hydrogeological model and the numerical flow simulations, the sustainability conditions for the groundwater withdrawals are obtained and the hydrodynamic interferences between the different users are assessed. The results of numerical simulations were encapsulated in the game-theoretical model in order to find conceptual solutions to maximize the profit related to quarry’s economy and, at the same time, to limit the quantitative and qualitative decline of the thermal waters. Assuming that the sustainability of the groundwater abstraction from the quarry area depends on ensuring residual groundwater flow to the thermal springs and the river, a cooperative game among the different players has been developed. The strategy of a player is bound by the influence of dewatering on the springs and the river and the player’s utility is proportional to the total quantity of travertine extracted. Results indicate that the “price of sustainability” would be around a 23% reduction of the total exploited travertine volume, driven by an overall reduction in dewatering of about 31%, if compared to that necessary to reach the maximum depth of excavation. For the different groups of quarries the reduction of the pumping flow is not homogeneous but varies according to the position of the pumping center in the groundwater flow net and its distance from boundaries to be captured. Therefore, the combination of the flow model with the game model solutions appears to be a valuable tool to achieve sustainable groundwater management in a conflicting situation among different users. In addition, the game model allows to introduce other players and/or to find out other, non-cooperative solutions.