Site Classification Research Articles

An equivalent point-source stochastic model of the NGA-East ground-motion models

The main objective of this study is to estimate seismological parameters in Central and Eastern North America (CENA), including the geometrical spreading, anelastic attenuation, stress parameter, and site attenuation parameters. In this study, we use particle swarm optimization (PSO) to invert a weighted average of the median 5%-damped pseudo-spectral acceleration (PSA) predicted from the Next Generation Attenuation-East (NGA-East) ground-motion models (GMMs) to develop a point-source stochastic GMM with a well-constrained set of ground-motion parameters. Magnitude-specific inversions are performed for moment magnitude ranges M = 4.0–8.0, rupture distances Rrup = 1–1000 km, and periods T = 0.01–10 s, and National Earthquake Hazard Reduction Program site class A conditions. The result of this study yields a single stochastic GMM that yields PSA values similar to the median NGA-East GMMs. The parameters derived from this study can be used for the hybrid empirical method (HEM) applications. This study is the first to perform a formal inversion using the GMMs developed for the NGA-East project. The approach has been validated using simulated small-to-moderate magnitude and large-magnitude data derived from the NGA-West2 GMMs.

Effect of Surface Topography on the Primary Stability of Miniscrew Implants in Orthodontics—A Systematic Review and Meta-Analysis

ABSTRACT This present study has the purpose of determining how surface topography of implants affects the initial stability of miniscrew implants (MSIs). Electronic databases like PubMed Central, Scopus, Web of Science, Embase, and Cochrane Library, as well as reference lists, were thoroughly searched up until September 2022. Clinical trials involving individuals who got anchorage through mini-implants, along with information on categories of mini-implants dimension, shape, thread design, and insertion site, were required as part of the eligibility criteria. Primary and secondary stability were also assessed. We carried out selection process for the study, extraction of data, quality assessment, and a meta-analysis. The qualitative synthesis included 10 papers: three randomized, four prospective, and four retrospective clinical investigations. The results of this meta-analysis demonstrate that the clinical state of MIs is controlled by their geometrical surface qualities, which are also influenced by their shape and thread design. According to the evidence this meta-analysis produced, this circumstance exists. The duration of the follow-up period and MI success rates did not correlate with one another.

Site classification Based on Shear Wave Velocity Inversion in The Jlantah Dam Construction Project using the HVSR (Horizontal to Vertical Spectral Ratio) Analysis Method

This research was conducted with the aim to test whether the results of the inversion of the HVSR curve can be used as complementary data for N-SPT values in classifying areas according to site classification. The inversion result in the form of shear wave velocity (VS ) is then compared directly with the N-SPT data in several boreholes. Ellipticity curve method is used for inversion. The data generated in this study are dominant frequency, Amplitude Peak, and H/V curve as a result of the HVSR analysis performed on microtremor data. Furthermore, an inversion was carried out on the H/V curve by taking into account secondary data in the form of borehole, shear wave velocity, density and poisson ratio for each type of lithology. The dominant frequency value obtained has a value range of 0.33 to 17.15 Hz. The Amplitude Peak obtained in the study area has a value range of 1.81 – 11.4. The inversion (VS ) value has a range of 110.5 m/s – 400 m/s, so it is included in the classification of Soft Soil, Medium Soil, and Hard Soil and Soft Rock. The correlation of and N-SPT show that inversion method with HVSR analysis of microtremor data is quite reliable as supporting data for N-SPT. Considering cons of drilling, the method used in this study can be a new alternative for use in construction projects because it can be carried out at a relatively low cost, and is quite simple in terms of data acquisition and processing.

Parsing Data Log Hasil Pemblokiran Situs Negatif Di Satuan Kerja Perangkat Aceh

In today's digital age, internet access has become an integral part of everyday life, providing broad access to information and communication. However, these technological advances also bring negative impacts, including the potential for the spread of unwanted content or harm to society. The process of parsing negative site blocking datalog is a technique used to analyze and decipher log data resulting from site blocking activities. In this context, negative site blocking is not only focused on illegal content, but also involves efforts to mitigate cybersecurity threats, including phishing attacks, malware, and other malicious online activities. Use of Observation Methods (Observation), Interviews, Literature Studies where the author made direct observations at the Aceh Communication, Informatics and Coding Agency to find out about the negative site blocking datalog in the Aceh Equipment Work Unit, conducted direct interviews with Field Supervisors and staff at the agency to find out about the process of parsing negative site blocking datalogs at the Aceh Equipment Work Unit, collect and study references related to data parsing, negative site categories, websites, CodeIgniter 4 documentation, Bootstrap documentation, and information system design tools from various journals, theses, articles, and various other reference sources. The proposed system for parsing datalogs has clear functional and non-functional needs. Functional needs involve features such as login, blocking data management, category management, blocking graph representation and reporting. Meanwhile, non-functional needs include authentication security, responsive performance, and an intuitive user interface. Thus, parsing log data resulting from negative site blocking in the Aceh Device Work Unit is expected to provide significant benefits for Diskominsa Aceh in maintaining cyber security and morality in the use of the internet in its territory. These conclusions highlight the importance of implementing sophisticated technology solutions to understand, analyze, and manage block log data efficiently and effectively.
 

Implication of abandoned post‐quarry sites on avifauna composition for strategic landscape restoration in Ndarugu, Kiambu, Kenya

AbstractAbandoned post‐quarry sites have potentiality to be remodeled into natural‐wilderness areas, a desire especially in rapidly urbanizing and transforming landscapes. However, paucity of ecological information on post‐quarry sites limits nature‐based restoration, especially in the sub‐Saharan tropical landscape. This study investigated avifauna composition of post‐quarry sites in Ndarugu, Kenya, relative to non‐quarried sites for conservation role prioritization. Birds were censused in 166 point count stations using the fixed‐radius distance method. Land use land cover types within each point provided the variables for explaining bird occurrence. Observed bird species were classified into functional guilds, avifaunal composition assessed, and bird data subjected to multivariate analysis. In total 158 species, 128 in post‐quarry and 123 in non‐quarried sites, were recorded. Bush‐ and forest‐related species were dominant, constituting over 55% of total observed birds, in both site categories. Six wetland‐related species were detected only in quarried sampling sites. Mann–Whitney statistical tests returned a significant effect of land use category on bird species richness, abundance, and diversity, all higher in post‐quarried than in non‐quarried sites (p < 0.05). Emergent natural shrubs, quarry cliffs, and cultivated farms were most influential to bird community structuring. Nonmetric multidimensional scaling and cluster analysis revealed four functional groups of birds whose species richness increased with number of post‐quarried sampling sites in a cluster. Unique physical features of post‐quarry sites and emergent vegetation types, can be partially mimicked in nature‐oriented rehabilitation planning for long‐term social and ecological benefits.

Implications of the 2020 National Building Code of Canada updates on the design demands for reinforced concrete shear wall buildings

The seismic demands of the Reinforced Concrete Shear Walls (RCSWs) system are determined based on Canada’s National Building Code (NBC). NBC 2020 features the revised Canadian Seismic Hazard Model and presents the possibility of enhancing demand’s accuracy by determining design spectra based on the specific average shear wave velocity, instead of specified site classes. This paper investigates the changes in design demands for RCSWs compared to the previous edition. To do so, fifty-five RCSW prototypes were modelled using distributed mass and stiffness procedure, and their dynamic response was assessed through Modal Response Spectrum Analysis at five locations across Canada. The results highlight significant changes in deformation and force demands, where the majority of cases experienced an increase in 2020 compared to 2015 when demands were determined based on specified site classes. This study also evaluates the log-log interpolation method recommended by NBC 2020 for the design spectral acceleration.

Exploring Shear Wave Velocity—NSPT Correlations for Geotechnical Site Characterization: A Review

Shear wave velocity (Vs) is a critical parameter in geophysical investigations, micro-zonation research, and site classification. In instances where conducting direct tests at specific locations is challenging due to equipment unavailability, limited space, or initial instrumentation costs, it becomes essential to estimate Vs directly, using empirical correlations for effective site characterization. The present review paper explores the correlations of Vs with the standard penetration test (SPT) for geotechnical site characterization. Vs, a critical parameter in geotechnical and seismic engineering, is integral to a wide range of projects, including foundation design and seismic hazard assessment. The current paper provides a detailed analysis of the key findings, implications for geotechnical engineering practice, and future research needs in this area. It emphasizes the importance of site-specific calibration, the impact of geological background, depth-dependent behavior, data quality control, and the integration of Vs data with other geophysical methods. The review underlines the continuous monitoring of Vs values due to potential changes over time. Addressing these insights and gaps in research contributes to the accuracy and safety of geotechnical projects, particularly in seismic-prone regions.

One Avocado per Day as Part of Usual Intake Improves Diet Quality: Exploratory Results from a Randomized Controlled Trial

BackgroundFew clinical trials have evaluated diet quality change as a predictor of intervention effectiveness. ObjectivesThe aim of this study was to examine changes in the Healthy Eating Index (HEI)-2015 after a food-based intervention, and assess the associations between HEI-2015 change and intervention effects on cardiometabolic risk–related outcomes. MethodsThe Habitual Diet and Avocado Trial was a 26-wk, multicenter, randomized, controlled parallel-arm study. Participants were 1008 individuals aged ≥25 y with abdominal obesity (females ≥ 35 inches; males ≥ 40 inches). The avocado-supplemented diet group was provided 1 avocado per day, and the habitual diet group maintained their usual diet. Change in diet quality was assessed using the HEI-2015 from a single 24-h recall conducted at 4 time points. Mixed models were used for analysis. ResultsThe avocado-supplemented diet group had a greater increase in the HEI-2015 (4.74 points; 95% CI: 2.93, 6.55) at 26 wk than the habitual diet group. Compared with the habitual diet group, the avocado-supplemented diet group had greater increases in the following HEI-2015 components from baseline: total vegetables (0.99 points; 95% CI: 0.77, 1.21), fatty acid ratio (2.25 points; 95% CI: 1.74, 2.77), sodium (1.03 points; 95% CI: 0.52, 1.55), refined grains (0.82 points; 95% CI: 0.32, 1.31), and added sugars (0.84 points; 95% CI: 0.49, 1.19). No differences in HEI-2015 improvements were observed by race, ethnicity, study site, body mass index, or age category. In the avocado-supplemented diet compared with the habitual diet group, the HEI-2015 increased in females (6.50 points; 95% CI: 4.39, 8.62) but not in males (0.02 points; 95% CI: −3.44, 3.48). Median HEI-2015 change was not associated with intervention-related changes in cardiometabolic disease risk factors. ConclusionsIntake of 1 avocado per day for 26 wk in adults with abdominal obesity increased adherence to the Dietary Guidelines for Americans. Changes in diet quality did not predict changes in risk factors for cardiometabolic disease.This trial was registered at clinicaltrials.gov as NCT03528031 (https://clinicaltrials.gov/study/NCT03528031).

Seismic Microzonation Map of Chiang Mai Basin, Thailand

The seismic site effect which is controlled by local geological conditions is a key parameter of seismic hazards analysis. This paper presents an observational study of microtremor data to investigate the dynamic characteristics of soil in the Chiang Mai basin (Chiang Mai and Lumphun province), Northern Thailand. The Chiang Mai basin was formed on terrace sediments and alluvium sediments. The horizontal vertical spectral ratio (HVSR) analyses of ambient noise data at 101 sites in the basin were analyzed for an average smoothed HVSR curve to estimate the amplification factor and fundamental resonance frequency of each observation point. We also evaluated the shear wave velocity using the HVSR inversion technique based on the diffuse field assumption. Tests undertaken include a comparison of the HVSR of a significant earthquake that was detected at stations in the basin and a nearby bedrock site. The results indicate that the resonance frequency ranges between 0.15 - 0.4 Hz at sites having large thicknesses of soft sediments. The lowest resonance frequencies occur in the center of the basin, whereas higher resonance frequencies were observed in the areas of the shallowest bedrock in the west and east of the basin. It can be inferred that the western margin of the Chiang Mai basin is a steep slope, while the eastern margin of the basin is a low-angle west-dipping basement. The amplification factor ranges between 3 - 5 times, in the middle of the basin. Most of the Chiang Mai basin area is classified as site D soil (stiff soil) relative to alluvium sediments, and a region of class C soil (very dense soil) conforms to the terrace sediments located on the eastern edge of the basin. The soil classification is based on shear wave velocity (Vs30) determined by HVSR inversion. HIGHLIGHTS HVSR analysis and inversion of HVSR from 101 survey points in Chiang Mai basin The Chiang Mai basin area is at high risk from seismic amplification that amplifies a ground motion between 3 - 5 times in the middle of the basin at a dominant frequency range from 0.15 - 0.4 Hz The lowest Vs30 values location is in the middle of the basin classified as site class E (soft soil), while most of the basin area is classified as site D soil (stiff soil) corresponding to alluvium sediments. The class C soil (very dense soil) area conforms to the terrace sediments located on the eastern edge of the basin GRAPHICAL ABSTRACT

Organic toxicants and emerging contaminants in hospital interiors before and during the SARS-CoV2 pandemic: alkanes and PAHs.

Indoor pollution and deposition dust (DD), in particular, are acquiring concern, due to long exposure time and importance of intake by humans through contact and ingestion. Hospitals look a special category of sites, owing to peculiar contaminants affecting them and to presence of people prone to adverse effects induced by toxicants. Four in-field campaigns aimed at understanding the chemical composition of DD were performed in five Italian hospitals. Measurements were performed before (autumn 2019), during (spring 2021), and after (winter 2022) the peak of SARS-CoV2 and when restrictions caused by pandemic were revoked (winter 2023). Parallel measurements were made outdoors (2022), as well as in a university and a dwelling. Targeted contaminants were n-alkanes and polycyclic aromatic hydrocarbons (PAHs), while iso- and anteiso-alkanes were analyzed to assess the impact of tobacco smoking. Total n-alkanes ranged from 3.9 ± 2.3 to 20.5 ± 4.2mg/g, with higher percentages of short chain homologs in 2019. PAHs ranged from 0.24 ± 0.22 to 0.83 ± 0.50mg/g, with light congeners (≤ 228 a.m.u.) always exceeding the heavy ones (≥ 252 a.m.u.). According to carbon preference indexes, alkanes originated overall from anthropogenic sources. Microorganisms resulted to affect a hospital, and tobacco smoke accounted for ~ 4-20‰ of DD mass. As for PAH sources, the diagnostic concentration ratios suggested the concourse of biological matter burning and vehicle emission. Benzo[a]pyrene equivalent carcinogenic and mutagenic potencies of depositions at hospitals ranged ~ 9-39μg/g and ~ 15-76μg/g, respectively, which seems of concern for health. DD composition in hospitals was different from that outside the premises, as well as that found at university and at dwelling.

Enviromic prediction enables the characterization and mapping of Eucalyptus globulus Labill breeding zones

Genotype-environment interaction is pervasive in forest genetics. Delineation of spatial breeding zones (BZs) is fundamental for accommodating genotype-environment interaction. Here we developed a BZ classification pipeline for the forest tree Eucalyptus globulus in 2 Australian regions based on phenotypic, genomic, and pedigree data, as well on a detailed environmental characterization (“envirotyping”) and spatial mapping of BZs. First, the factor analytic method was used to model additive genetic variance and site–site genetic correlations (rB) in stem volume across 48 trials of 126,467 full-sib progeny from 2 separate breeding programs. Thirty-three trials were envirotyped using 145 environmental variables (EVs), involving soil and landscape (71), climate (73), and management (1) EVs. Next, sparse partial least squares-discriminant analysis was used to identify EVs that were required to predict classification of sites into 5 non-exclusive BZ classes based on rB. Finally, these BZs were spatially mapped across the West Australian and “Green Triangle” commercial estates by enviromic prediction using EVs for 80 locations and 15 sets of observed climate data to represent temporal variation. The factor analytic model explained 85.9% of estimated additive variance. Our environmental classification system produced within-zone mean rB between 0.76 and 0.84, which improves upon the existing values of 0.62 for Western Australia and 0.67 for Green Triangle as regional BZs. The delineation of 5 BZ classes provides a powerful framework for increasing genetic gain by matching genotypes to current and predicted future environments.

Optimizing Terrain Classification Methods for the Determination of Bedrock Depth and the Average Shear Wave Velocity of Soil

The advancement of remote sensing has enabled the creation of high-resolution Digital Elevation Models (DEMs). Topographic features such as slope gradient (SG), local convexity (LC), and surface texture (ST), derived from DEMs, are related to subsurface geological conditions. In South Korea, bedrock depth (Dbedrock) and the average shear wave velocity of soil (VSsoil) serve as metrics for determining the site class, which represents the degree of site amplification in seismic design criteria. These metrics, typically measured through geotechnical and geophysical investigations, require predictive methods for preliminary estimation over large areas. Previous studies developed an automatic terrain classification (AC) scheme using SG, LC, and ST, and subsequent research revealed that terrain classification effectively represents subsurface conditions such as Dbedrcok and average shear wave velocity down to 30 m depth. However, AC intrinsically depends on the regional features of DEMs, dividing regions based on nested means of topographic features (SG, LC, and ST). In this study, we developed two terrain classification methods to determine the thresholds of class divisions, aiming to optimize Dbedrock and VSsoil predictions: Sequentially Optimized Classification (SOC) and Non-Sequentially Optimized Classification (NOC). Through the study of the sensitivity of terrain classification methods, smoothing levels, and threshold levels for terrain class generation, we identified the best classification method by comparing it with the geological and mountainous region distribution. Subsequently, we developed DEM-dependent regression models for each class to enhance the accuracy of predicting Dbedrock and VSsoil. The main findings of this study are: (1) the terrain class map suggested in this study represents the distribution of alluvial plane and mountainous regions well, and (2) the DEM calibration for each class provides increased accuracy of Dbedrock and VSsoil predictions in South Korea. We anticipate that the terrain class map, along with Dbedrock and VSsoil maps, will be effectively utilized in geological interpretations and land-use planning for seismic design.

Wind energy potential assessment: a case study in Central India

Access to sustainable energy is important for economic development and environmental protection. The shift towards renewable energy is essential for mitigating climate change and ensuring long-term energy sustainability. Though developing nations possess significant renewable energy capacity, transitioning to renewable sources remains a challenge. India's expanding wind energy sector has the potential to lower carbon dioxide emissions and produce energy in a sustainable manner. This research uses the Windographer software to conduct a comprehensive analysis of the wind energy potential at a distinct site in Nagpur, India. The assessment includes monthly average wind speeds, wind rose diagrams that show the prevailing wind directions, and wind power density (WPD) calculations. These factors together establish the site's classification. In this study, Weibull parameters are derived using four distinct methods to estimate the probability distribution function. The average WPD is found to be 13.63 and 71.08 W/m2 at heights of 10 and 100 m above ground level, respectively. Through wind turbine output analysis, numerous turbine models are assessed for suitability at the specified location. The Windtec DD 3000-125 model, interestingly, has a maximum capacity factor of 9.27%. The results highlight comparatively low wind potential in the studied region. Nevertheless, a wind turbine at this location can produce about 2 412 379 kW of electricity annually using the aforementioned wind turbine model.

Scaling factors for 1-D ground response amplification in a soft soil basin

Basin presence is believed to affect the ground surface response due to earthquakes, particularly in areas around the basin edge. Previous studies showed that 1-D and 2-D wave propagation analyses resulted in significant differences in amplification at the basin edge. However, the link between 1-D and 2-D responses has not been studied for engineering practices. In practical application, seismic studies were commonly performed using 1-D analysis, for example, to develop a city micro-zonation map. Based on practical considerations, it is necessary to estimate the scaling factor for the 1-D analysis by considering the basin presence, particularly for one containing soft soil. There are three stages carried out in this study. The first stage: collecting data on some basin geometries for the 2-D modeling references and then defining selected site class and input motions. The second stage: modeling 1-D and 2-D wave propagation using D-MOD and Fast Lagrangian Analysis of Continua (FLAC), respectively. The third stage: comparing spectral acceleration resulting from the 1-D and 2-D analyses to obtain the scaling factors. This research studied and reported the relationship between PGA values varied as 0.2 g, 0.3 g, 0.4 g, and 0.5 g, basin geometry (e.g., the angle was set to 5°, 10°, 15°, 30°, and 45°, with depth and width variations of 0.0125, 0.025, 0.05, 0.075, 0.1, 0.2, and 0.4, while the basin width was adjusted to 500 m, 1 km, 2 km, and 4 km), and the spectral acceleration in several observation points on the ground surface. Based on this evaluation, a series of scaling factors are proposed. These factors can be used for spectral acceleration from available hazard maps, commonly developed based on 1-D analysis. The application example of this scaling factor is presented in this study, using the Bandung Basin case.

Ground motion models for regions with limited data: Data‐driven approach

AbstractThe ground motion model (GMM) for response spectra is crucial to hazard studies and structural design. GMM developed for regions with abundant data can capture appropriate spectral attenuation characteristics. However, several seismically active regions, such as the Himalayas, have limited recorded data, and thus, traditionally, simulated, or other regional data are supplemented with the available data for developing a GMM. Despite data augmentation, GMMs developed for such regions cannot appropriately depict attenuation characteristics. Therefore, the paper presents a comprehensive study encompassing the development of data‐driven approaches to obtain GMM for response spectra using the Himalayan crustal data with inputs: magnitude, distance, site class, depth, and a flag corresponding to the horizontal and vertical components. In this regard, GMM using transfer learning is initially developed from a pre‐trained model using global crustal data. Additionally, GMM using the XGBoost approach with monotonic constraints enforced on inputs is developed. These approaches could not capture trends appropriately. Finally, a monotonic constrained transfer learning model is developed to appropriately depict magnitude saturation and scaling, magnitude‐dependent geometric spreading, anelastic attenuation, depth scaling, site amplification, and other desired characteristics.

People and sites as community resources for preventing and managing chronic health conditions: A conceptual analysis.

The prevention and management of chronic non-communicable diseases (NCDs) require community-based efforts-especially as their burden grows, and recognition of the need for engaging diverse stakeholders in care grows. The aim of this conceptual analysis was to categorise existing community resources (people and sites) used to support such efforts, the mechanisms by which they work, and the conditions that constrain their effectiveness. We developed an initial framework for categorising community resources. We then used a sample of the literature- 24 studies from 12 countries-to refine and enrich the framework. We identified seven categories of sites ('where': House, Meeting place, Community health centre, Primary health care centre, Mobile clinic, Pharmacy, and Hospital) and ten categories of people ('who': Community Health Worker, Nurse/Midwife, Health educator, Physician, Primary Health Care Worker, Peer Group, Navigator, Pharmacist, Cultural Advisor, Family caregiver). We identified eight mechanisms through which those resources improve NCD prevention and management: Context specific engagement, Personalised and integrated care, Community health worker led knowledge dissemination, Social support through family and/or friends, Extending the reach of the health system, Social support through peer groups, Task shifting, and Training of health workforce. We identified two broad categories of constraints on these mechanisms: (i) health system barriers such as inadequate workforce, training, coordination and engagement; and (ii) socio-economic, political, and cultural barriers to care. The conceptual categories (of people and sites as resources, the mechanisms through which they work and the contextual constraints on their effectiveness) identified in this analysis may be useful in further analysing current approaches in NCD efforts using community resources, in informing the development of community-based efforts, and in exploring the commonalities and transferable insights between different locations or settings around the world and between different efforts to prevent and manage NCDs within communities.

Forestry and mensuration characteristics of pine stands in the recreation and health-improving forests in the Left Bank Steppe

The study of forestry and stand mensuration characteristics of pine stands in recreational and health-improving forests of the Left Bank Steppe was conducted based on forest management materials. The distribution of pine stands in the recreational and health-improving forests of the region by location, origin, forest types, age groups and classes, site classes, and relative density of stocking was analyzed. For pine stands within the forest areas of green belt) (sites where forest activities are permitted), indicators of the use of forest potential by modal pines were calculated to compare reference stands. It was found that the pine plantations in the recreational and health-improving forests of the region grow in an area of more than 83 thousand hectares. In terms of area, man-made pine stands significantly dominate, the share of which is 93.6 % of the total area, the rest of the area (6.4%) is occupied by pine forests of natural origin. The predominance of pine stands within green belt was revealed. Their proportion is 76.1 % of the total area, including the forestry zone - 59.7 % and the forest park zone – 16.4 %. The significant area of the investigated pine plantations (37% of the total area) is located in the conditions of a fresh oak-pine (mixed) forest on transitional, relatively poor soils (subor in Ukrainian). The most part of forest is middle-aged stands (59.3 % of the total forest area and 70.5 % of the total stock of wood). Moreover, pine forest of I (39,2 %) and II (31,1 %) site classes and 0.7–0.8 density dominated (73.5 %). The rate of utilization of the forest potential by modal pines within forest areas of green belt compared reference stands is relatively low and reaches 63 %.

A method for evaluating sediment-induced macroinvertebrate community composition changes in Idaho streams.

Human activities can increase sediment delivery to streams, changing the composition, distribution, and abundance of stream aquatic life. Few U.S. states have numeric water quality standards for streambed sediment under the Clean Water Act, so managers often need to develop local application-specific benchmarks. This study developed stream surface fine sediment <2 mm (sand and fines, SF) and macroinvertebrate fine sediment biotic index (FSBI) benchmarks and an application framework to test for sediment-induced macroinvertebrate community composition changes in 1st-4th order Idaho streams. FSBI reference benchmarks were calculated as the 25th percentile FSBI value among reference sites within three ecoregion-based site classes. Two approaches were used to develop SF benchmarks. Quantile regression was used to define reach-specific SF benchmarks representing an upper bound value expected under reference conditions. In addition, logistic regression was used to predict SF values with 50% and 75% probability that FSBI is worse than reference within each stream order and site class. The strength of association between SF benchmarks and macroinvertebrate community condition was evaluated by calculating relative risk using multiple datasets and examining responses of multiple macroinvertebrate indicators to SF benchmark status. SF reference benchmarks generally had stronger associations with poor macroinvertebrate condition than SF stressor-response benchmarks. Across datasets and macroinvertebrate indicators, poor macroinvertebrate condition was 1.8-3 times more likely when SF reference benchmarks were exceeded than when achieved. We propose rating the strength of evidence for a surface fine sediment-induced macroinvertebrate community composition change at the sample event scale as 'unlikely' if both SF and FSBI reference benchmarks are achieved, having 'mixed evidence' if only one reference benchmark is achieved, and 'likely' if both reference benchmarks are not achieved. We recommend combining ratings with other relevant data in a weight-of-evidence approach to assess if sediment impairs aquatic life.

Machine Learning Model for Building Type Classification of Cultural Heritage Sites along Jiangnan Canal: A Comparative Study of Historical and Modern Images

Machine Learning Model for Building Type Classification of Cultural Heritage Sites along Jiangnan Canal: A Comparative Study of Historical and Modern Images

ОБЕСПЕЧЕНИЕ МУЛЬТИМОДАЛЬНОСТИ В ТУРИСТИЧЕСКИХ МАРШРУТАХ НА ПРИМЕРЕ ВОЛГОГРАДСКОЙ ОБЛАСТИ

The paper uses a systematic approach in creating the proposed tourism system. The use of ontology has made it possible to develop a classification of tourist sites in the Volgograd region. The concepts of tourist bus routes have been developed on the basis of classification and established ontological relationships. According to the level of transport use and its interaction, it is proposed to divide the concepts of tourist routes into micro-levels, meso-levels and macro-levels of the tourism system being developed. A heat map of the transport accessibility of the Volgograd region has been compiled, which made it possible to ensure the use of different types of transport in multimodal tourist routes. Multimodal routes of tourist buses have been developed, technical, operational and economic indicators of the functioning of the buses used have been determined.