Site-specific Characteristics Research Articles

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.

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.

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 Tumours.

The 5th Edition of WHO classification of neuroendocrine neoplasms is built to achieve a uniform terminology and to define a similar diagnostic scheme across different anatomical locations. At variance with the 4th edition, a chapter discussing neuroendocrine neoplasms in non-neuroendocrine organs has been introduced, that proposes a binary system for classification segregating well differentiated neoplasms, termed neuroendocrine tumors (NET), and poorly differentiated neoplasms, termed neuroendocrine carcinomas (NEC). A grading system for NET is based on mitotic index and/or Ki-67 index and/or necrosis, depending on the different location. If already well-established in the digestive system, this approach modifies and homogenize the classification of neuroendocrine neoplasms 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.

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.

Temporal variability and site specificity of thermomechanical weathering in a temperate climate

Thermomechanical processes caused by short- and long-term temperature fluctuations are a prevalent weathering mechanism on exposed rock walls. While many authors have explored the potential for thermomechanical weathering in alpine and polar regions, few have examined the effects of seasonality on weathering in temperate climates. This is pertinent as seasonal climatic conditions may influence both short-term temperature oscillations which produce incipient fractures and diurnal-to annual-scale cycles which propagate pre-existing fractures via thermal fatigue. In this study, three rock outcrops located along the Niagara Escarpment in Hamilton, Canada were monitored to examine changes in the thermal regime at the rock surface and within pre-existing fractures over a 1-year period. Temperature was sampled in 1-min intervals, providing data at a fine temporal resolution. Our unique dataset demonstrates that the rock surface and fracture experience minute-scale temperature oscillations which magnify over time. Longer-term temperature cycles during the year are superimposed upon minute- and diurnal-scale fluctuations which likely augment weathering potential. This produces considerable thermal stress over the year which we estimate to be on the order of 18 GPa at the rock surface and 8 GPa in fractures. We also observed diurnal reversals of the temperature gradient between the rock surface and fracture which may further amplify crack propagation. Seasonality and site-specific characteristics interact to modify different components of the rockwall thermal regime. Vegetation shading has seasonal and diurnal-scale impacts on the temperature gradient between the surface and fracture, and the amplitude of daily warming and cooling cycles. Aspect has a stronger influence on minute-scale temperature oscillations. Estimates of diurnal thermal stress indicate that the thermomechanical weathering potential is seasonally variable, but highest in the spring. Our findings demonstrate that in a temperate climate, rockwall thermal regimes experience variability across the gradient of temporal scale with strong seasonal effects.

Assessment of the Spatiotemporal Variability of Urban Heat Island Intensity in Colombo Metropolitan Area

&#x0D; &#x0D; &#x0D; During the last few decades, the Colombo Metropolitan Area (CMA) has experienced rapid population growth and unplanned urbanization, resulting in the replacement of natural landcover with more impervious surfaces. The primary approach of current study was to determine the gradients of air temperature and assess the spatiotemporal variation of atmospheric urban heat island (AUHI) intensity in the CMA considering a range of rural sites extending in different radial directions from the urban center. A total of sixteen rural observation sites that extend from an urban center in four directions were selected within the CMA, with four sites 3.5 km apart from each other in any direction. The air temperatures at each site were measured using HOBO UX-100-003 temperature data loggers for an 8-day period from 21st to 28th, of February 2022. The normalized difference vegetation index (NDVI) and normalized difference building index (NDBI) were used to determine the influence of land use/land cover on air temperatures. The results revealed that air temperature had a strong positive correlation with NDBI. Thus, the current study suggests that the impervious surface/s is a significant predictor of air temperature over the study area. The higher air temperatures were observed at the urban center in relation to the selected suburban and rural observation sites. Hence, the current study confirms that AUHI exists within the selected study area over the CMA. It was found that AUHI tends to be present throughout the day in the CMA. However, it becomes strong between 12.00 A.M. and 6.00 A.M and mostly weakens in the late afternoon hours. Furthermore, this study found that the timing and magnitudes of AUHI vary from direction to direction across the study area depending on the site-specific characteristics of the rural observation sites. The current study emphasizes that site-specific land use/land cover characteristics can have a significant impact on the interpretation of UHI study results even within a single metropolitan area. Therefore, taking only one rural site might not be effective in determining the UHI intensity and a range of sites need to be considered (to select from) for in-depth analysis of UHI in any given area. The findings of the current study will provide firsthand knowledge for urban planners to identify future trends in UHI in the CMA and will promote further UHI research in this area.&#x0D; Keywords: Rural observation site, Atmospheric urban heat island, Normalized Difference Vegetation Index&#x0D; &#x0D; &#x0D;

Smut fungus (Langdonia walkerae) incidence is lower in two bunchgrass species (Aristida stricta and A. beyrichiana) after fires early in the year.

In frequently burned southeastern USA pine-grassland communities, wiregrass (Aristida stricta and A. beyrichiana) are dominant bunchgrasses whose flowers are infected during flowering by a smut fungus (Langdonia walkerae). We hypothesized that because prescribed fire timing affects wiregrass flowering patterns, it could affect smut incidence (occurrence of smut on plants) and severity of infection in inflorescences and spikelets. Because soil order could influence plant susceptibility, we hypothesized that these patterns would differ between soil orders. We hypothesized differences between species as representative of geographic variation in this ecosystem. We surveyed the incidence and severity of L. walkerae in wiregrass populations (85 populations at 14 sites) that had been prescription burned at different times during the previous year. We used binomial regressions to test whether incidence and severity differed by burn day, soil order, or species, with site as a random effect. Fires that occurred in the winter were associated with significantly lower incidence than fires later in the year (as the months progressed into summer). Plants growing on Spodosol soils were significantly less likely to be infected than those on other soils. More variation in incidence, however, was explained by site, suggesting that site-specific characteristics were important. Smut severity in inflorescences and spikelets was greater overall in populations of A. stricta than in southern populations (A. beyrichiana). Our findings indicate that fire timing and soil order affect L. walkerae incidence in wiregrass plants, but neither appears to be associated with greater severity. Patterns of smut infection are related to site history and geographic variation.

The Site/Group Extended Data Format and Tools.

Comparative sequence analysis permits unraveling the molecular processes underlying gene evolution. Many statistical methods generate candidate positions within genes, such as fast or slowly evolving sites, coevolving groups of residues, sites undergoing positive selection, or changes in evolutionary rates. Understanding the functional causes of these evolutionary patterns requires combining the results of these analyses and mapping them onto molecular structures, a complex task involving distinct coordinate referential systems. To ease this task, we introduce the site/group extended data format, a simple text format to store (groups of) site annotations. We developed a toolset, the SgedTools, which permits site/group extended data file manipulation, creating them from various software outputs and translating coordinates between individual sequences, alignments, and three-dimensional structures. The package also includes a Monte-Carlo procedure to generate random site samples, possibly conditioning on site-specific features. This eases the statistical testing of evolutionary hypotheses, accounting for the structural properties of the encoded molecules.

Theft and Vandalism Control Measures on Construction Sites

Purpose: The goal of this study is to determine and improve the best security practices within Ghanaian construction sites to control theft and vandalism incidents.&#x0D; Design/Methodology/Approach: A purposive sampling technique was adopted for the population which were indigenous small and medium-sized construction firms of D1KI and D2K2 categories to complete the semi-structured questionnaire. Out of the total of 80 questionnaires distributed, only 65 responses were retrieved for analysis. Descriptive statistics comprising, frequencies and mean scores were used. &#x0D; Findings: The findings showed that the most effective and often utilized security measure on construction sites is the hiring of watchmen, with security cameras, alarm systems, and warning signs being the least frequently employed. Sites would most likely be protected from theft by effective implementation of the most important security measures while also guaranteeing that the value for money invested in site security is also realized.&#x0D; Research Limitation/Implications: The effectiveness of theft and vandalism control measures may vary based on specific site characteristics, such as location, size, and type of construction. Generalising findings from one site to all construction contexts may not be applicable.&#x0D; Social Implication: Incidents of theft and vandalism can lead to social tensions within the community, especially if residents perceive construction activities as a source of risk. Effective control measures mitigate these tensions, fostering a more harmonious relationship between construction companies and the local population.&#x0D; Practical Implication: Minimizing the impact of theft and vandalism contributes to the timely completion of construction projects. Unanticipated delays due to security incidents can be avoided, ensuring that projects adhere to planned schedules and deadlines.&#x0D; Originality/ Value: The originality of this paper lies in its targeted investigation into theft and vandalism control measures on small and medium-sized construction sites, offering innovative and contextually relevant solutions that address the unique challenges faced by SMEs in the construction industry.

Factors with ambiguous qualities for Cultural World Heritage Sites

The aim of this study is to investigate factors with both beneficial and harmful qualities for Cultural World Heritage Sites. Particular but not exclusive attention is given to aspects relating to tourism and infrastructure. Data from the World Heritage List for North America and Europe, linked to the 2014 UNESCO Periodic Report II, are employed for the analysis. A simultaneous Bivariate Probit model estimation is carried out on the 30,954 observations and 402 Heritage Sites. World Heritage managers assess that certain factors are both beneficial and harmful for their sites. These contradictory perceptions appear most commonly in relation to tourism/visitors/recreation (28% of the sites), ground transport infrastructure (16%) and to the Society's valuing of heritage (12%). Besides this, ambivalent perceptions are also identified for housing, commercial development, land conversion, forestry/timber production and renewable energy facilities, although to a lesser extent. Estimation results reveal that the highest degree of ambivalence occurs in relation to tourism/visitors/recreation, interpretive and sightseeing facilities and ground transport infrastructure when location and specific site characteristics are controlled for. Thus, the results coincide only to some extent with the descriptive statistics. Compared to other groups of Cultural World Heritage Sites (cultural landscapes, religious sites and other sites) managers of cities have a significantly lower probability of perceiving the different factors as harmful.

Multi-period, multi-objective optimisation of the Northern Lights and Stella Maris carbon capture and storage chains

A multi-objective optimisation model for CCS chains, aiming to minimise costs and greenhouse gas emissions, considering various transport options is presented. The model builds upon previous work and covers the CCS chain elements after CO2 is captured, including conditioning, pipeline and batch-wise transportation, intermediate hub storage and injection at CO2 storage fields. A prospective Life Cycle Inventory is integrated to evaluate emissions from batch-wise transportation. The model is parameterised for accurate estimations based on site-specific characteristics and is implemented in two standalone CCS chains, that are analogues to the Northern Lights project with dominant ship transport and the Stella Maris concept with direct injection ship transport, also incorporating distinct emission profiles, intermediate storage hubs and injection sites. A third implementation combining both chain concepts is implemented. By increasing in a step-wise manner the weight of the emissions in the objective function, the model evaluates cost and emission trade-offs. The optimisation selects costlier wells to minimise emissions and shifts from batch-wise ships to cross-continent pipelines. Chain emissions decrease over time with CO2 supply increase. Shipping operation dominates emissions, followed by well construction and infrastructure construction. Across all the implementations, the GHG emission intensity of the chain, after CO2 is captured, ranged from 3.3 to 14.2 %, depending on the concept and transport option adopted and accounting for regional characteristics (i.e., the electricity supply mix per country).

Site-Invariant Meta-Modulation Learning for Multisite Autism Spectrum Disorders Diagnosis.

Large amounts of fMRI data are essential to building generalized predictive models for brain disease diagnosis. In order to conduct extensive data analysis, it is often necessary to gather data from multiple organizations. However, the site variation inherent in multisite resting-state functional magnetic resonance imaging (rs-fMRI) leads to unfavorable heterogeneity in data distribution, negatively impacting the identification of biomarkers and the diagnostic decision. Several existing methods have alleviated this shift of domain distribution (i.e., multisite problem). Statistical tuning schemes directly regress out site disparity factors from the data prior to model training. Such methods have a limitation in processing data each time through variance estimation according to the added site. In the model adjustment approaches, domain adaptation (DA) methods adjust the features or models of the source domain according to the target domain during model training. Thus, it is inevitable that it needs updating model parameters according to the samples of a target site, causing great limitations in practical applicability. Meanwhile, the approach of domain generalization (DG) aims to create a universal model that can be quickly adapted to multiple domains. In this study, we propose a novel framework for disease diagnosis that alleviates the multisite problem by adaptively calibrating site-specific features into site-invariant features. Specifically, it applies directly to samples from unseen sites without the need for fine-tuning. With a learning-to-learn strategy that learns how to calibrate the features under the various domain shift environments, our novel modulation mechanism extracts site-invariant features. In our experiments over the Autism Brain Imaging Data Exchange (ABIDE I and II) dataset, we validated the generalization ability of the proposed network by improving diagnostic accuracy in both seen and unseen multisite samples.

Incorporating high-resolution climate, remote sensing and topographic data to map annual forest growth in central and eastern Europe

To enhance our understanding of forest carbon sequestration, climate change mitigation and drought impact on forest ecosystems, the availability of high-resolution annual forest growth maps based on tree-ring width (TRW) would provide a significant advancement to the field. Site-specific characteristics, which can be approximated by high-resolution Earth observation by satellites (EOS), emerge as crucial drivers of forest growth, influencing how climate translates into tree growth. EOS provides information on surface reflectance related to forest characteristics and thus can potentially improve the accuracy of forest growth models based on TRW. Through the modelling of TRW using EOS, climate and topography data, we showed that species-specific models can explain up to 52 % of model variance (Quercus petraea), while combining different species results in relatively poor model performance (R2 = 13 %). The integration of EOS into models based solely on climate and elevation data improved the explained variance by 6 % on average. Leveraging these insights, we successfully generated a map of annual TRW for the year 2021. We employed the area of applicability (AOA) approach to delineate the range in which our models are deemed valid. The calculated AOA for the established forest-type models was 73 % of the study region, indicating robust spatial applicability. Notably, unreliable predictions predominantly occurred in the climate margins of our dataset. In conclusion, our large-scale assessment underscores the efficacy of combining climate, EOS and topographic data to develop robust models for mapping annual TRW. This research not only fills a critical void in the current understanding of forest growth dynamics but also highlights the potential of integrated data sources for comprehensive ecosystem assessments.