Site Characteristics Research Articles

CONTRASTING CULTURES OF EMERGENCY DEPARTMENT CARE: A QUALITATIVE STUDY OF PATIENTS’ EXPERIENCES OF ATTENDING THE EMERGENCY DEPARTMENT FOR LOW BACK PAIN

Purpose and backgroundAlthough clinical guidelines recommend that low back pain (LBP) is best managed in primary or community care, in the UK and globally, LBP accounts for around 4% of emergency department (ED) attendances. Organising and delivering healthcare to be safe, effective, and acceptable requires hearing patients’ perspectives; this study therefore aimed to explore patients’ experiences of attending the ED for LBP.Methods and resultsThis was a multisite qualitative interview study with 47 adults (aged 23–79 years) who, in the past six weeks, had attended one of four UK NHS emergency departments for LBP (all types and durations). Purposive sampling was used to gain variation in the recruiting site, and LBP and demographic characteristics. Data were collected using individual, semi-structured, telephone interviews (median 45mins). Interviews were audio-recorded, transcribed verbatim, and analysed thematically.We identified significant variation in patients’ experiences of ED care for LBP, which we argue reflects contrasting cultures of ED care. We present three cultures, emergency screening only, ‘cynicism and neglect’, and ‘kindness’; these cultures differ in how they navigate the tension between the ED remit and patients’ perceived needs of care. We draw on Bourdieu's notions of field and habitus and professional identity theory to help explain these findings.ConclusionOur findings suggest unwarranted variation in ED care for LBP. Implications include the need for urgent access to primary and community care and clarity about best practice managing LBP in the ED; best practice guidance and strategies to implement this should be informed by notions of culture and professional identity.No conflicts of interest Sources of fundingHealth Education England & National Institute of Health and Care Research (ICA-CDRF-2018-04-ST2-040)

Research on visual experience evaluation of fortress heritage landscape by integrating SBE–SD method and eye movement analysis

Urbanization has led to homogenizing heritage site landscapes, and the protective measures have become disconnected from public needs. Additionally, the complex and diverse overall characteristics of heritage sites and the uneven distribution of values across different areas are related to the lack of landscape experience assessment. The “subjective + objective” cognitive evaluation and visual perception framework that adopts the Scenic Beauty Estimation Procedure-Semantic Differential (SBE–SD) method and eye-tracking analysis can compensate for the limitations of a single evaluation method by integrating quantitative and qualitative analysis. This research takes the Yi’an Fortress in Zhangpu County, Fujian Province, as the object and examines the visual experiences of different areas and types of landscapes within the Yi’an Fortress. The findings reveal several key insights: (1) Significant differences were found in the landscape experiences of different areas within the heritage site. The visual experience score of the core building area of Yi’an Fortress is (1.01) > the heritage entrance area (0.897) > the residential area (0.841) > the natural ecological area (0.784), indicating that the natural ecological area should be the focus of future protection and development efforts, with a particular emphasis on enhancing the ‘landscape aesthetic’ and ‘landscape cultural’ aspects. (2) The landscape experience scores can be used to understand the reasons for the differences in participants’ experiences of different landscapes. The architectural heritage landscape of the Yi’an Fortress scored highest in the experience evaluation due to its superior performance in terms of ‘landscape form’ factors. The cultural decorative landscape scored next, while the garden greening landscape scored the lowest, due to their poorer performance in terms of ‘landscape form’ and ‘landscape aesthetics’. (3) The eye-tracking data was consistent with the results of the subjective evaluation, validating the “subjective + objective” cognitive evaluation and visual perception framework, employing the SBE–SD method and eye-tracking analysis is a scientific and effective method for assessing the visual experience of heritage landscapes. These results provide a scientific basis for the heritage planners and managers of the Yi’an fortress to improve the landscape environment, better meet public needs, and preserve the unique character of this vital cultural resource. Furthermore, this study offers a new research method and approach for the protection of other heritage landscapes.

Cycle fatalities in Delhi and their risk factors

There is a lack of research that investigates the risk factors of cycling in low- and middle-income countries. We present descriptive epidemiology of crashes that involved at least one fatal cyclist, over a three-year period (2016–2018) in Delhi, India. Next, we used an unmatched case-control approach to identify road design risk factors of cycle fatalities. Cases were road segments with at least one cycle fatality, and controls were those with none. We developed logistic regression models with cases and controls as binary outcomes to estimate the odds ratio of site characteristics. There were 167 crashes involving at least one cyclist fatality over the study period. Fatal cyclists were almost all males. They were less likely to be children or young adults and less likely to be residents of high-income localities, compared to the general population. One in ten crashes included more than one occupant on a cycle and 5% of fatal victims were pillion riders. Seventy percent crashes occurred at midblock, and majority were backend collisions. Regression shows that road width, traffic speed, and volume of heavy vehicles have strong positive effects on the fatality risk of cyclists. These results can inform strategies to design interventions for safety of cyclists.

Structure and Evolution of Ribosomal Genes of Insect Chromosomes.

Currently, clusters of 45S and 5S ribosomal DNA (rDNA) have been studied in about 1000 and 100 species of the class Insecta, respectively. Although the number of insect species with known 45S rDNA clusters (also referred to as nucleolus-organizing regions, or NORs) constitutes less than 0.1 percent of the described members of this enormous group, certain conclusions can already be drawn. Since haploid karyotypes with single 45S and 5S rDNA clusters predominate in both basal and derived insect groups, this character state is apparently ancestral for the class Insecta in general. Nevertheless, the number, chromosomal location, and other characteristics of both 45S and 5S rDNA sites substantially vary across different species, and sometimes even within the same species. There are several main factors and molecular mechanisms that either maintain these parameters or alter them on the short-term and/or long-term scale. Chromosome structure (i.e., monocentric vs. holokinetic chromosomes), excessive numbers of rRNA gene copies per cluster, interactions with transposable elements, pseudogenization, and meiotic recombination are perhaps the most important among them.

Current limitations and future research needs for predicting soil precompression stress: A synthesis of available data

Precompression stress, compression index, and swelling index are used for characterizing the compressive behavior of soils, and are essential soil properties for establishing decision support tools to reduce the risk of soil compaction. Because measurements are time-consuming, soil compressive properties are often derived through pedotransfer functions. This study aimed to develop a comprehensive database of soil compressive properties with additional information on basic soil properties, site characteristics, and methodological aspects sourced from peer-reviewed literature, and to develop random forest models for predicting precompression stress using various subsets of the database. Our analysis illustrates that soil compressive properties data primarily originate from a limited number of countries. There is a predominance of precompression stress data, while little data on compression index or recompression index are available. Most precompression stress data were derived from the topsoils of conventionally tilled arable fields, which is not compatible with knowledge that subsoil compaction is a serious problem. The data compilation unveiled considerable variations in soil compression test procedures and methods for calculating precompression stress across different studies, and a concentration of data at soil moisture conditions at or above field capacity. The random forest models exhibited unsatisfactory predictive performance although they performed better than previously developed models. Models showed slight improvement in predictive power when the underlying data were restricted to a specific precompression stress calculation method. Although our database offers broader coverage of precompression stress data than previous studies, the lack of standardization in methodological procedures complicates the development of predictive models based on combined datasets. Methodological standardization and/or functions to translate results between methodologies are needed to ensure consistency and enable data comparison, to develop robust models for precompression stress predictions. Moreover, data across a wider range of soil moisture conditions are needed to characterize soil mechanical properties as a function of soil moisture, similar to soil hydraulic functions, and to develop models to predict the parameters of such soil mechanical functions.

Analysis of the Relationship Between Primary Tumor Site and Clinicopathological Characteristics and Survival Prognosis of Breast Cancer Patients Based on SEER Database

PurposeThis study aimed to analyze the association between the primary tumor site and clinicopathological characteristics and survival prognosis of breast cancer (BC) patients using a large population database. MethodsBC patients screened in the Surveillance, Epidemiology, and End Results (SEER) database were categorized into 6 groups based on primary sites. Descriptive statistics, Kaplan-Meier curves, Cox regression models, forest plots were used to assess the effect of primary sites on overall survival (OS) and breast cancer-specific survival (BCSS). Multivariate Cox proportional analyses were conducted to calculate hazard ratios (HRs) and adjusted subgroups’ hazard ratios (AHRs). Nomograms were utilized to predict OS and BCSS. ResultsAmong 193,043 BC patients, the highest incidence was found in the upper outer quadrant (52.60%). Central portion patients are associated with more clinical features indicating a poor prognosis, and had worse OS and BCSS than other sites. Univariate and multifactorial Cox analyses showed associations between OS/BCSS and various factors. Subgroup analyses revealed differences in OS and BCSS between central portion and upper outer quadrant varied among age, T and N stage. The nomogram was established to predict the survival of central portion BC patients. ConclusionsPrimary tumor site is associated with clinicopathological features and prognosis of BC, may be influenced by age at diagnosis and T and N stage. Central portion BC patients have worse prognosis due to older age at diagnosis, higher T stage and higher likelihood of lymph node metastasis. Early diagnosis and treatment may help to improve survival of central portion BC.

Adaptations and early adoption of a family caregiver intervention in the Veterans Affairs Health Care System: A multimethod pragmatic approach for national scaling.

To examine the relationship between site-level adaptation and early adoption of Caregivers Finding Important Resources, Support, and Training (FIRST) training during national implementation across diverse Veteran Health Administration (VA) medical centers. We enrolled and evaluated 25 VA medical centers (VAMCs). Along with administrative data on site characteristics, we examined site-reported data on adaptations and intervention adoption, defined as ≥4 training classes delivered to ≥5 caregivers at 6 months from April through October 2022. A type III hybrid implementation-effectiveness cluster randomized controlled trial, randomized VAMCs 1:1 to receive foundational (low-touch) implementation support (n = 12) or the addition of enhanced (high-touch) implementation support (n = 13). At key implementation phases, VAMCs were asked to report adaptations including content, contextual modifications (format, setting, personnel, and population), and training of providers. We describe site-level adaptations by arm and by organizational characteristics that included VAMC complexity level, staffing, rurality, and organizational readiness to change. We used qualitative comparative analysis to identify unique adaptations that contributed to intervention adoption at 6 months. VAMCs randomized to receive enhanced support reported slightly more adaptations than those randomized to foundational support. At 6 months, VAMCs with two or more adaptations adopted Caregivers FIRST at a higher rate than those with fewer adaptations (90% vs. 44%). Staffing adaptations (e.g., who delivered the intervention), format and content (e.g., modified delivery pace), and referring provider training were unique adaptations to adopting sites. Site-level adaptations were diverse and occurred more frequently in sites with early adoption of Caregivers FIRST. Future research should identify best practices of supporting and monitoring intervention adaptation. Understanding the role of adaptation in early adoption success could assist other healthcare systems in implementing interventions for caregivers.

Prospective multicenter study to describe the prevalence, outcomes, and management of phosphate disorders in intensive care patients: Study protocol for part B of the international GUTPHOS study

BackgroundAberrations in blood phosphate (Pi) levels, whether presenting as hypo- or hyperphosphatemia, appear to be associated with clinical complications and adverse outcomes in patients admitted to an intensive care unit (ICU). However, the prevalence of Pi disorders and the association with subsequent factors and organ failures leading to death in ICU patients are poorly described. Despite endeavors to understand the etiology and treatment of low Pi levels from systematic reviews and meta-analyses, the literature lacks comprehensive guidance for managing hypophosphatemia. Hyperphosphatemia, on the other hand, appears to be associated with higher mortality among critically ill patients, yet its prevalence among ICU patients, particularly following phosphate repletion, remains unknown. The present study aims to investigate the prevalence of Pi abnormalities upon ICU admission and their incidence during the first week of ICU stay, the factors associated with Pi alterations, and the effect of phosphate repletion on the normalization of Pi levels, and its associations with clinical outcomes. MethodsThis multicentre, prospective, non-interventional cohort study will include at least 1000 consecutive adult ICU patients (≥18 years) as part B of the GUTPHOS study. Sites are eligible if an anticipated minimal inclusion of 50 eligible patients during eight weeks from January 2024 until June 2024 and daily phosphate measurements during the first seven days of ICU stay are expected. All consecutive adult patients admitted to a participating ICU during the recruitment period, lasting up to eight weeks, or up to 120 patients if enrollment reaches that limit earlier, will be included. Study parameters include study site characteristics, patient demographics, daily assessment of Pi levels, Pi-related treatment, feeding details, renal replacement therapy details, the incidence of refeeding-associated hypophosphatemia and administered medication (during the first seven calendar days of ICU stay). There will be a follow-up period of a maximum of 90 days to document 28- and 90-day all-cause mortality as the primary outcome. Multiple logistic regression will be used to assess independent associations with mortality in addition to Receiver Operating Characteristics curves to identify cut-off Pi values associated with mortality and overcorrection. Linear mixed models will be conducted to assess Pi treatment effects. Subgroup analyses will be performed based on Pi abnormalities observed during ICU admission, categorized as normo-, hypo-, hyper-, or mixed, along with its severity (mild, moderate, or severe). DiscussionThe GUTPHOS study will be the first multicentre, prospective observational cohort study to investigate the prevalence, management practices, and consequent outcomes associated with Pi abnormalities during the first week of ICU admission. Its results may bridge the current evidence gap in repletion protocols while establishing the groundwork for a subsequent randomized controlled trial. Clinical trial registryNCT05909722.

Identification of Risk Factors for Severe Younger and Older Driver Crashes in Massachusetts

Systemic safety analysis is a comprehensive and proactive approach to identifying and addressing high-risk roadway features and crash types that contribute to severe crashes. The Massachusetts Department of Transportation identified 14 emphasis areas for systemic improvement, including younger and older driver crashes. Research was undertaken to conduct separate comprehensive analyses of fatal and serious injury crashes involving younger and older drivers, using a systemic safety approach to develop risk factors and identify critical locations within the state. The study utilized crash, roadway, driver’s license, citation, healthy aging, and environmental justice data from various sources. Negative binomial regression models were developed to relate crash frequency with town-specific traffic, behavior, and site characteristics, considering exposure and spatial variance. The findings highlighted the significance of multiple risk factors contributing to severe crash frequency. For younger drivers, the presence of young drivers in the town, risk-taking behaviors such as unbelted and impaired driving, and infrastructure characteristics, particularly high-speed facilities and historically underinvested infrastructure, were key contributors to crash frequency. Older drivers’ crash frequency was influenced by the presence of older drivers, healthy aging indicators, risk-taking behaviors, and high-speed facilities. Based on the model results, risk scores were developed for each variable in the model and applied to each town. Towns were ranked using percentile ranking to classify them into primary and secondary risk categories. The towns identified in the primary risk category (18 towns in the top 5 percentiles) captured approximately 13.5% of severe younger driver crashes and 14.5% of severe older driver crashes.

Physical and geochemical responses to bottom trawling on naturally disturbed sediments in the eastern Bering Sea

Abstract Recent concerns that commercial bottom trawling can contribute to a significant release of sequestered marine carbon have highlighted a need for research in this area. Here, a Before-After Control-Impact (BACI) experimental design was utilized in a previously untrawled area of the eastern Bering Sea. Six pairs of experimental and control corridors were sampled before, after, and 1 year after a trawl disturbance. Each experimental corridor was fished four consecutive times over ∼12 h with a commercial otter trawl. Results were contextualized with minimum detectable effects (MDE), and showed no evidence of a trawl effect on total organic carbon (P = .999, MDE ± 0.05% TOC), total nitrogen (P = .999, MDE ± 0.02% TN), δ13C, and δ15N isotope ratios and sediment size classes. Interannual changes observed in δ15N, sand, silt, and clay are attributed to natural variation. The study suggests that the characteristics of the study site, such as storm disturbances, high sand content, and low carbon content, limited the bottom-trawl effect on sediment composition following this initial trawl disturbance. The findings highlight the importance of site-specific studies that account for local conditions to support best management practices for commercial bottom trawling.

Prognostic Utility of the Flow Cytometry and Clonality Analysis Results for Feline Lymphomas.

Feline lymphoma, a prevalent cancer in cats, exhibits varied prognoses influenced by anatomical site and cellular characteristics. In this study, we investigated the utility of flow cytometry and clonality analysis via PCR for antigen receptor rearrangement (PARR) with respect to characterizing the disease and predicting prognosis. For this purpose, we received fine needle aspirates and/or blood from 438 feline patients, which were subjected to flow cytometry analysis and PARR. We used a subset of the results from patients with confirmed B- or T-cell lymphomas for comparison to cytological or histological evaluation (n = 53). Using them as a training set, we identified the optimal set of flow cytometry parameters, namely forward scatter thresholds, for cell size categorization by correlating with cytology-defined sizes. Concordance with cytological sizing among this training set was 82%. Furthermore, 90% concordance was observed when the proposed cell sizing was tested on an independent test set (n = 24), underscoring the reliability of the proposed approach. Additionally, lymphoma subtypes defined by flow cytometry and PARR demonstrated significant survival differences, validating the prognostic utility of these methods. The proposed methodology achieves high concordance with cytological evaluations and provides an additional tool for the characterization and management of feline lymphoproliferative diseases.

Factors Influencing Neuromuscular Blockade Reversal Choice in the United States Before and During the COVID-19 Pandemic: Retrospective Longitudinal Analysis.

Neuromuscular blockade (NMB) agents are a critical component of balanced anesthesia. NMB reversal methods can include spontaneous reversal, sugammadex, or neostigmine and the choice of reversal strategy can depend on various factors. Unanticipated changes to clinical practice emerged due to the COVID-19 pandemic, and a better understanding of how NMB reversal trends were affected by the pandemic may help provide insight into how providers view the tradeoffs in the choice of NMB reversal agents. We aim to analyze NMB reversal agent use patterns for US adult inpatient surgeries before and after the COVID-19 outbreak to determine whether pandemic-related practice changes affected use trends. A retrospective longitudinal analysis of a large all-payer national electronic US health care database (PINC AI Healthcare Database) was conducted to identify the use patterns of NMB reversal during early, middle, and late COVID-19 (EC, MC, and LC, respectively) time periods. Factors associated with NMB reversal choices in inpatient surgeries were assessed before and after the COVID-19 pandemic reached the United States. Multivariate logistic regression assessed the impact of the pandemic on NMB reversal, accounting for patient, clinical, procedural, and site characteristics. A counterfactual framework was used to understand if patient characteristics affected how COVID-19-era patients would have been treated before the pandemic. More than 3.2 million inpatients experiencing over 3.6 million surgical procedures across 931 sites that met all inclusion criteria were identified between March 1, 2017, and December 31, 2021. NMB reversal trends showed a steady increase in reversal with sugammadex over time, with the trend from January 2018 onwards being linear with time (R2>0.99). Multivariate analysis showed that the post-COVID-19 time periods had a small but statistically significant effect on the trend, as measured by the interaction terms of the COVID-19 time periods and the time trend in NMB reversal. A slight increase in the likelihood of sugammadex reversal was observed during EC relative to the pre-COVID-19 trend (odds ratio [OR] 1.008, 95% CI 1.003-1.014; P=.003), followed by negation of that increase during MC (OR 0.992, 95% CI 0.987-0.997; P<.001), and no significant interaction identified during LC (OR 1.001, 95% CI 0.996-1.005; P=.81). Conversely, active reversal (using either sugammadex or neostigmine) did not show a significant association relative to spontaneous reversal, or a change in trend, during EC or MC (P>.05), though a slight decrease in the active reversal trend was observed during LC (OR 0.987, 95% CI 0.983-0.992; P<.001). We observed a steady increase in NMB active reversal overall, and specifically with sugammadex compared to neostigmine, during periods before and after the COVID-19 outbreak. Small, transitory alterations in the NMB reversal trends were observed during the height of the COVID-19 pandemic, though these alterations were independent of the underlying NMB reversal time trends.

Wireworm species associated with corn and soybean agroecosystems in Ontario, Canada.

Wireworms, the larvae of click beetles (Coleoptera: Elateridae), are often the target of insecticide seed treatments commonly used in corn (Zea mays L.) and soybean (Glycine max (L.) Merr.) production in North America. Nevertheless, there is a lack of knowledge of the species, life history, and economic impact of wireworms present in these agroecosystems. An extensive survey of wireworms was conducted in corn and soybean fields in Ontario, Canada, from 2014 to 2017 to document species distribution and co-occurrence and to identify risk factors related to their abundance. In total, 4,332 specimens were collected from 1,245 different sampling records. The dominant species collected was Limonius agonus (Say) (Coleoptera: Elateridae) comprising 71.5% of the specimens. The remaining wireworm specimens were identified as Hypnoidus abbreviatus (Say), Melanotus similis (Kirby), M. cribulosus (LeConte), M. depressus (Melsheimer), M. communis (Gyllenhal), Agriotes mancus (Say), Aeolus mellillus (Say), and Hemicrepidius spp (Germar). Multiple wireworm species were found to commonly occur within the same field and the same sample. Path analysis was conducted to investigate whether site, soil, and agronomic characteristics influenced wireworm distribution and abundance. Several significant relationships were found between wireworm species and geographic factors, soil texture, and agronomic practices. The results of this survey provide critical information that can be used to improve integrated pest management of the major wireworm genera found in corn and soybean agroecosystems in Ontario.

Site-Specific Deterministic Temperature and Dew Point Forecasts with Explainable and Reliable Machine Learning

Site-specific weather forecasts are essential for accurate prediction of power demand and are consequently of great interest to energy operators. However, weather forecasts from current numerical weather prediction (NWP) models lack the fine-scale detail to capture all important characteristics of localised real-world sites. Instead, they provide weather information representing a rectangular gridbox (usually kilometres in size). Even after post-processing and bias correction, area-averaged information is usually not optimal for specific sites. Prior work on site-optimised forecasts has focused on linear methods, weighted consensus averaging, and time-series methods, among others. Recent developments in machine learning (ML) have prompted increasing interest in applying ML as a novel approach towards this problem. In this study, we investigate the feasibility of optimising forecasts at sites by adopting the popular machine learning model “gradient boosted decision tree”, supported by the XGBoost package (v.1.7.3) in the Python language. Regression trees have been trained with historical NWP and site observations as training data, aimed at predicting temperature and dew point at multiple site locations across Australia. We developed a working ML framework, named “Multi-SiteBoost”, and initial test results show a significant improvement compared with gridded values from bias-corrected NWP models. The improvement from XGBoost (0.1–0.6 °C, 4–27% improvement in temperature) is found to be comparable with non-ML methods reported in the literature. With the insights provided by SHapley Additive exPlanations (SHAP), this study also tests various approaches to understand the ML predictions and increase the reliability of the forecasts generated by ML.

High-resolution harvester data for estimating rolling resistance and forest trafficability

AbstractInformation on terrain conditions is a prerequisite for planning environmentally and economically sustainable forest harvesting operations that avoid negative impact on soils. Current soil data are coarse, and collecting such data with traditional methods is expensive. Forest harvesters can be harnessed to estimate the rolling resistance coefficient ($$\mu _{RR}$$ μ RR ), which is a proxy for forest trafficability. Using spatio-temporal data on engine power used, speed travelled, and machine inclination, $$\mu _{RR}$$ μ RR can be computed for harvest areas. This study describes an extensive, high-resolution data on $$\mu _{RR}$$ μ RR collected in a boreal forest landscape in Southern Finland during the non-frost period of 2021, covering roughly 50 km of harvester routes. We report improvements in removing some of the previous restrictions on calculating $$\mu _{RR}$$ μ RR on steeper slopes, enabling the calculation within a $$-10^{\circ }$$ - 10 ∘ to $$+10^{\circ }$$ + 10 ∘ slope range with a speed range of 0.6–1.2 ms$$^{-1}$$ - 1 . We characterise the variation in $$\mu _{RR}$$ μ RR both between and within 11 test sites harvested during the April-August period. The site mean $$\mu _{RR}$$ μ RR varies from $$\sim$$ ∼ 0.14 to 0.19 and shows significant differences between the sites. Using simulations of the hydrological state of the soil and open spatial data on forest and topography, we identify features that best explain the extremes of $$\mu _{RR}$$ μ RR within the sites. Several wetness-related indices, such as the depth-to-water index with varying thresholds, explain the $$\mu _{RR}$$ μ RR extremes, while biomass-related stand attributes indirectly explain these through their linkage to site and soil characteristics. Obtaining $$\mu _{RR}$$ μ RR from actual operational data extends the capabilities of large-scale harvester-based data collection and paves the way for building data-driven models for trafficability prediction.

Assessment of Soil-site Suitability for Major Horticulture Crops in Chikkumbi-3 Micro-watershed (4D7C5O2f), Karnataka Using Remote Sensing and GIS Techniques

Detailed soil resource inventorization was carried out at 1:7,920 scale in Chikkumbi-3 micro watershed, savadatti taluk, Belagavi district with an objective to assess the land suitability for various horticultural crops in the watershed. The soils of Chikkumbi-3 micro-watershed are characterized and classified into 3 soil series (CLK, CKB and HNL) comprising of 5 mapping units. The soil site characteristics and climatic factors were evaluated for its suitability for major horticultural crops viz., tomato, cabbage, chilli, rose, jasmine and coconut. The analysis revealed that the soil series CLK (Chulki), CKB (Chikkumbi), and HNL (Hanchinal) are presently not suitable for growing coconut due to significant limitations in physical conditions, rooting, and moisture. However, the region is deemed moderately to marginally suitable for the cultivation of tomato, cabbage, chilli, rose and jasmine. The main limitations in all the soil series found to be texture, CaCO3 content and climatic factors. These findings serve as foundational data for identifying specific soil constraints, aiding in the development of sustainable strategies for crop production in the study area.

Accuracy of navigation guided implant surgery for immediate loading complete arch restorations: Prospective clinical trial.

To assess navigation accuracy for complete-arch implant placement with immediate loading of digitally prefabricated provisional. Consecutive edentulous and terminal dentition patients requiring at least one complete-arch FDP were treated between December 2020 and January 2022. Accuracy was evaluated by superimposing pre-operative and post-operative cone beam computed tomography (CBCT), recording linear (mm) and angular (degrees) deviations. T-tests were performed to investigate the potential effect of the registration algorithm (fiducial-based vs. fiducial-free), type of references for the fiducial-free algorithm (teeth vs. bone screws), site characteristic (healed vs. post-extractive), implant angulation (axial vs. tilted), type of arch (maxilla vs. mandible) on the accuracy with p-value <0.05. Twenty-five patients, 36 complete-arches, and 161 implants were placed. The overall mean angular deviation was 2.19° (SD 1.26°). The global platform and apex mean deviations were 1.17 mm (SD 0.57 mm), and 1.30 mm (SD 0.62 mm). Meaningful global platform (p = 0.0009) and apical (p = 0.0109) deviations were experienced only between healed and post-extraction sites. None of the analyzed variables significantly influenced angular deviation. Minor single-axis deviations were reported for the type of jaw (y-axis at implant platform and apex), registration algorithm (y-axis platform and z-axis deviations), and type of references for the fiducial-free algorithm. No statistically significant differences were found in relation to implant angulation. Within the study limitations navigation was reliable for complete-arch implant placement with immediate loading digitally pre-fabricated FDP. AI-driven surface anatomy identification and calibration protocol made fiducial-free registration as accurate as fiducial-based, teeth and bone screws equal as references. Implant site characteristics were the only statistically significant variable with healed sites reporting higher accuracy compared to post-extractive. Live-tracked navigation surgery enhanced operator performance and accuracy regardless of implant angulation and type of jaw. A mean safety room of about 1 mm and 2° should be considered.

Perceived Soundscape Experiences and Human Emotions in Urban Green Spaces: Application of Russell’s Circumplex Model of Affect

Humans perceive their surrounding environments largely through their experiences of sight and hearing. The perceived environmental information then brings on neurophysiological changes, so as to influence human emotions. These mutually influenced relations have been widely utilized by many environmental psychologists to explore potential avenues for improving human emotions through design interventions. However, to date, no efficient and accurate way has been established to describe these relationships. Inspired by Russell’s model of emotion, this study aims to develop an efficient process that uses coordinate mapping and can intuitively describe the impact of visual-aural perceptive attributes on human emotions. Taking typical urban green spaces (UGSs) in Chengdu as examples, this study first measured the visual and aural characteristics of study sites perceived by people and their emotional responses. The study then established the use of emotional status on a coordinate axis, allowing each visual-aural attribute corresponding to each emotional response to be projected onto the coordinates. Results suggested that the dataset composed of 279 evaluations could be classified into three distinct types of visual-aural settings and the distribution of emotions is evidently varied in different settings. It was found that aesthetic and order of visual aspects as well as eventful and harmonious soundscape in environments are more likely to make people feel pleasure, while openness and layering of the visual landscape can easily arouse people’s positive status. The research outcome broadens the practical path of soundscape research, centring on human emotions, experiences and feelings, such as the pleasantness and arousal raised in Russell’s theory of emotion. The study also makes an empirical contribution to the design of UGSs based on multi-sensory perception and serves the purpose of improving people’s environmental experiences.

Beta diversity of restored river dike grasslands is strongly influenced by uncontrolled spatio‐temporal variability

AbstractAimsUnderstanding the spatio‐temporal patterns of restoration outcomes is crucial to improve predictability of restoration. High beta diversity of species‐rich communities is sought because it increases overall biodiversity and improves ecosystem stability and multifunctionality. For predictive restoration, it is important to identify the significance of drivers like site characteristics but also uncontrolled factors such as spatial effects, historical factors, and year effects.LocationDikes at river Danube, SE Germany.MethodsWe studied dike grasslands 4–19 years after restoration over five years (2017–2021, 41 plots in 12 sites). We calculated beta diversity indices to describe spatial variation and temporal turnover, including their additive components ‘replacement’ and ‘nestedness’, or ‘gains’ and ‘losses’. We analysed the main drivers of beta diversity like local site characteristics, landscape, and historical factors.ResultsSpatial variation of the restored dike grasslands was dominated by the replacement component and showed no homogenisation despite a significant temporal turnover. The replacement drivers changed over time, although replacement was mainly affected by slope aspect and landscape factors. Historical factors were inconsistent over time, and no statistically clear drivers of nestedness were found. The dike grasslands exhibited a year‐to‐year turnover in species composition of 37 ± 11%. Gains and losses were balanced over time, although the ratio changed and was most pronounced on south‐facing slopes.ConclusionsThe restored grasslands exhibited spatial variation by site characteristics but also by spatial factors which were not controlled by restorations. Moreover, high non‐directional temporal turnover occurred, caused most likely by weather fluctuations, slightly varying management, and stochastic biotic dynamics. Thus, flexible targets are recommended for restoration monitoring, by defining a set of desired states within a certain range. Furthermore, the dominance of the replacement component of spatial variation should move the focus from defining one precise restoration approach to defining a set of possible methods which together would foster beta diversity.

Landscape genomics reveals genetic signals of environmental adaptation of African wild eggplants.

Crop wild relatives (CWR) provide a valuable resource for improving crops. They possess desirable traits that confer resilience to various environmental stresses. To fully utilize crop wild relatives in breeding and conservation programs, it is important to understand the genetic basis of their adaptation. Landscape genomics associates environments with genomic variation and allows for examining the genetic basis of adaptation. Our study examined the differences in allele frequency of 15,416 single nucleotide polymorphisms (SNPs) generated through genotyping by sequencing approach among 153 accessions of 15 wild eggplant relatives and two cultivated species from Africa, the principal hotspot of these wild relatives. We also explored the correlation between these variations and the bioclimatic and soil conditions at their collection sites, providing a comprehensive understanding of the genetic signals of environmental adaptation in African wild eggplant. Redundancy analysis (RDA) results showed that the environmental variation explained 6% while the geographical distances among the collection sites explained 15% of the genomic variation in the eggplant wild relative populations when controlling for population structure. Our findings indicate that even though environmental factors are not the main driver of selection in eggplant wild relatives, it is influential in shaping the genomic variation over time. The selected environmental variables and candidate SNPs effectively revealed grouping patterns according to the environmental characteristics of sampling sites. Using four genotype-environment association methods, we detected 396 candidate SNPs (2.5% of the initial SNPs) associated with eight environmental factors. Some of these SNPs signal genes involved in pathways that help adapt to environmental stresses such as drought, heat, cold, salinity, pests, and diseases. These candidate SNPs will be useful for marker-assisted improvement and characterizing the germplasm of this crop for developing climate-resilient eggplant varieties. The study provides a model for applying landscape genomics to other crops' wild relatives.