Comparative Mapping Research Articles

Mapping building facades using panoramic images captured by Unmanned Aerial Vehicle (UAV)

This work aims to verify the building pathologies of DTIC’s building front (Diretoria de Tecnologia da Informação e Comunicação at Federal University of Pampa – Alegrete/RS, Brazil) by using an Unmanned Aerial Vehicle (UAV). The study was conducted before and six months after its maintenance. Images and inspection records were used to elaborate the Damage Maps and the Grid Method for pathologies quantifications. The comparison of the Damage Maps before and after maintenance has revealed that the intervention (paint) was not efficient, since it has disguised temporarily the anomalies without correcting them. The use of UAV proved to be a good tool for building inspections, providing effective diagnosis, time-saving and security for the operator without working at height.

Identification, computation, and mapping of anthropogenic landforms in urban areas: Case studies in the historical centre of Genoa, Italy (UNESCO World Heritage)

Urban geomorphology is a recent discipline that has gained a great deal of interest amongst the scientific community also for its clear connection with the concept of Anthropocene. The identification of anthropogenic landforms in an urban area requires a multidisciplinary approach, mostly using multi-temporal map comparisons, direct and indirect geognostic surveys, and detailed study of the urban landscape. Mediterranean cities have a particularly complex history: their original settlement usually dates back to the medieval period, but often to more ancient, occasionally even prehistoric, times. The result is an urban landscape characterised by modified natural landforms, but above all by anthropogenic landforms linked to the stratification of various urban phases. Reconstructing the landforms before major anthropogenic impacts of the last centuries is a particularly complex operation, and scientific research appears in its early stages. In this research, we introduce examples of the reconstruction of natural landforms in the historic centre of Genoa, a port city that experienced a peak of expansion in the Middle Ages and the Modern Age. The results obtained on four pilot areas highlight significant and previously unknown anthropic modifications and the associated landforms in the urban landscape. Large excavations, fills supported by ramparts, and sea embankments have been identified and quantitatively evaluated using a mixed approach between different disciplines: historical geography, geomatics, physical geography and geomorphology, and engineering geology. This methodology may be applied to other Mediterranean and extra-European urban contexts and may contribute, on the one hand, to the identification of potential geomorphological risks in urban areas and, on the other hand, to the use of urban landscape forms for geological heritage and geodiversity development activities.

Evaluation of soil quality of cultivated lands with classification and regression-based machine learning algorithms optimization under humid environmental condition

In soil science, machine learning algorithms are preferred for pedotransfer functions due to their rapid data acquisition and high prediction accuracy. The current study aims to evaluate the prediction of soil quality in agricultural lands dominated by the humid Black Sea climate using various algorithms. Both classification and regression-based algorithms (Random Forest-RF, Light Gradient Boosting-LGB, Extreme Gradient Boosting-XGBoost, k-nearest neighbors-kNN, Logistic Regression, multilayer perceptron-MLP, Linear Regression-LR and Bayesian Ridge- BR) were used in the method. The comparison of soil maps is also included. Furthermore, the present study evaluates the Grid Search optimization method with K-Fold Cross Validation (K = 5) for both classification and regression-based algorithms. The prediction of soil quality was performed using class-based and regression-based algorithms. As a result of the study, the RF and XGBoost algorithms achieved an approximate accuracy rate of 92 % in the class-based prediction. In regression-based predictions, the most successful algorithms were BR and LR, with an R2 Score of 0.84. The Grid Search optimization method was used to improve the R2 Score, resulting in an increase to 0.90 and 0.88 for BR and LR, respectively. The optimized hyperparameters showed improved performance in predicting the soil quality index. The present study found that Gaussian and Spherical models had the lowest prediction errors in spatial distribution maps. Tree-based algorithms were found to be suitable for class-based prediction of soil quality, while the linear regression method was appropriate for regression predictions. This study is characterized by a rainy climate resulting in acidic soils with high organic matter content. Planning of new studies in different climates and soil properties is recommended.

Graph Sampling for Map Comparison

Comparing two road maps is a basic operation that arises in a variety of situations. A map comparison method that is commonly used, mainly in the context of comparing reconstructed maps to ground-truth maps, is based on graph sampling . The essential idea is to first compute a set of point samples on each map and then to match pairs of samples—one from each map—in a one-to-one fashion. For deciding whether two samples can be matched, different criteria, e.g., based on distance or orientation, can be used. The total number of matched pairs gives a measure of how similar the maps are. Since the work of Biagioni and Eriksson [ 11 , 12 ], graph sampling methods have become widely used. However, there are different ways to implement each of the steps, which can lead to significant differences in the results. This means that conclusions drawn from different studies that seemingly use the same comparison method cannot necessarily be compared. In this work we present a unified approach to graph sampling for map comparison. We present the method in full generality, discussing the main decisions involved in its implementation. In particular, we point out the importance of the sampling method (GEO vs. TOPO) and that of the matching definition, discussing the main options used, and proposing alternatives for both key steps. We experimentally evaluate the different sampling and matching options considered on map datasets and reconstructed maps. Furthermore, we provide a code base and an interactive visualization tool to set a standard for future evaluations in the field of map construction and map comparison.

Characterization of a Monoclonal Antibody by Native and Denaturing Top-Down Mass Spectrometry.

Established in recent years as an important approach to unraveling the heterogeneity of intact monoclonal antibodies, native mass spectrometry has been rarely utilized for sequencing these complex biomolecules via tandem mass spectrometry. Typically, top-down mass spectrometry has been performed starting from highly charged precursor ions obtained via electrospray ionization under denaturing conditions (i.e., in the presence of organic solvents and acidic pH). Here we systematically benchmark four distinct ion dissociation methods─namely, higher-energy collisional dissociation, electron transfer dissociation, electron transfer dissociation/higher-energy collisional dissociation, and 213 nm ultraviolet photodissociation─in their capability to characterize a therapeutic monoclonal antibody, trastuzumab, starting from denatured and native-like precursor ions. Interestingly, native top-down mass spectrometry results in higher sequence coverage than the experiments carried out under denaturing conditions, with the exception of ultraviolet photodissociation. Globally, electron transfer dissociation followed by collision-based activation of product ions generates the largest number of backbone cleavages in disulfide protected regions, including the complementarity determining regions, regardless of electrospray ionization conditions. Overall, these findings suggest that native mass spectrometry can certainly be used for the gas-phase sequencing of whole monoclonal antibodies, although the dissociation of denatured precursor ions still returns a few backbone cleavages not identified in native experiments. Finally, a comparison of the fragmentation maps obtained under denaturing and native conditions strongly points toward disulfide bonds as the primary reason behind the largely overlapping dissociation patterns.

Comparative stagewise mapping of trace elements using ICP-OES in five Ayurvedic Marine Drugs highlights their posologic and clinical implications

Rasashastra, an Ayurvedic pharmaceutical branch, scientifically converts natural resources into palatable therapeutic dosage forms. Ayurvedic Marine Drugs (AMD) are mainly calcium carbonate/ calcite, but in Ayurvedic treatment modality they are uniquely used for several ailments. Moreover, their detailed microchemical compositions have seldom been reported. In this study, five raw materials, conch, oyster shell, cowry, coral, and pearl, their transitions during the manufacturing process, and the final drugs were analyzed for identification and quantitation of minor elements using a validated inductively coupled plasma optical emission spectrophotometry method. All the five raw materials contained traces of Al, Ag, B, Ba, Cu, Co, Cr, Fe, Hg, Li, K, Mg, Mn, Na, Ni, Pb, S, Sr, Tl, and Zn. Interestingly, B, Co, Cr, Li, Mn, and Ni were absent in the finished products, whereas Pb and Hg exhibited a considerable decrement during the drug formation. The first three components of principal component analysis together explained 72.09% of variance. Raw AMD indicated positive factor scores, whereas their respective purified and incinerated forms exhibited negative scores. Cluster analysis derived a dendrogram typically forming incinerated AMD group but not for the raw forms. Coral with Mg as highest content was a remarkable outlier in both these analyses as compared to Na in others. In discriminant analysis of the presence/absence of elements and periodic table-based classifications, coral and pearl showed higher variation indicating as discriminants when equated with others. Periodic table-based classification was a better model for discrimination. Correlation analysis in both classifications revealed a strong correlation of conch with oyster shells and vice versa, cowry and pearl with oyster shell and a weak correlation of coral with pearl. Coral was a good predictor followed by conch, pearl, oyster shell, and cowry, sequentially, and can be considered a moderately sensitive but highly specific model. Thus, ICP-OES technique is highly precise and accurate for assessing the micro-composition of raw, in-process, and finished products to ensure their transitions, quality, and genuineness. Such characterized traditional medicines should be further investigated in depth for their mechanistic aspects.Graphical abstract

Free-breathing 3D phase-resolved functional lung MRI vsbreath-hold hyperpolarized 129Xe ventilation MRI in patients with chronic obstructive pulmonary diseaseand healthy volunteers.

3D phase-resolved functional lung (PREFUL) MRI offers evaluation of pulmonary ventilation without inhalation of contrast agent. This study seeks to compare ventilation maps obtained from 3D PREFUL MRI with a direct ventilation measurement derived from 129Xe MRI in both patients with chronic obstructive pulmonary disease (COPD) and healthy volunteers. Thirty-one patients with COPD and 12 healthy controls underwent free-breathing 3D PREFUL MRI and breath-hold 129Xe MRI at 1.5 T. For both MRI techniques, ventilation defect (VD) maps were determined and respective ventilation defect percentage (VDP) values were computed. All parameters of both techniques were compared by Spearman correlation coefficient (r) and the differences between VDP values were quantified by Bland-Altman analysis and tested for significance using Wilcoxon signed-rank test. In a regional comparison of VD maps, spatial overlap and Sørensen-Dice coefficients of healthy and defect areas were computed. On a global level, all 3D PREFUL VDP values correlated significantly to VDP measure derived by 129Xe ventilation imaging (all r > 0.65; all p < 0.0001). 129Xe VDP was significantly greater than 3D PREFUL derived VDPRVent (mean bias = 10.5%, p < 0.001) and VDPFVL-CM (mean bias = 11.3%, p < 0.0001) but not for VDPCombined (mean bias = 1.7%, p = 0.70). The total regional agreement of 129Xe and 3D PREFUL VD maps ranged between 60% and 63%. Free-breathing3D PREFUL MRI showed a strong correlation with breath-hold hyperpolarized 129Xe MRI regarding the VDP values and modest differences in the detection of VDs on a regional level. 3D PREFUL MRI correlated with 129Xe MRI, unveiling regional differences in COPD defect identification. This proposes 3D PREFUL MRI as a ventilation mapping surrogate, eliminating the need for extra hardware or inhaled gases. Current non-invasive evaluation techniques for lung diseases have drawbacks; 129Xe MRI is limited by cost and availability. 3D PREFUL MRI correlated with 129Xe MRI, with regional differences in identifying COPD defects. 3DPREFUL MRI can provide ventilation mapping without the need for additional hardware or inhaled gases.

Genetic analysis of yield components in buckwheat using high-throughput sequencing analysis and wild resource populations.

Fagopyrum tataricum, an important medicinal and edible crop, possesses significant agricultural and economic value. However, the development of buckwheat varieties and yields has been hindered by the delayed breeding progress despite the abundant material resources in China. Current research indicates that quantitative trait loci (QTLs) play a crucial role in controlling plant seed type and yield. To address these limitations, this study constructed recombinant inbred lines (RILs) utilizing both cultivated species and wild buckwheat as raw materials. In total, 84,521 Single Nucleotide Polymorphism (SNP) markers were identified through Genotyping-by-Sequencing (GBS) technology, and high-resolution and high-density SNP genetic maps were developed, which had significant value for QTL mapping, gene cloning and comparative mapping of buckwheat. In this study, we successfully identified 5 QTLs related to thousand grain weight (TGW), 9 for grain length (GL), and 1 for grain width (GW) by combining seed type and TGW data from 202 RIL populations in four different environments, within which one co-located QTL for TGW were discovered on the first chromosome. Transcriptome analysis during different grain development stages revealed 59 significant expression differences between the two materials, which can serve as candidate genes for further investigation into the regulation of grain weight and yield enhancement. The mapped major loci controlling TGW, GL and GW will be valuable for gene cloning and reveal the mechanism underlying grain development and marker-assisted selection in Tartary buckwheat.

Genome-Wide Characterization of Fructose 1,6-Bisphosphate Aldolase Genes and Expression Profile Reveals Their Regulatory Role in Abiotic Stress in Cucumber.

The fructose-1,6-bisphosphate aldolase (FBA) gene family exists in higher plants, with the genes of this family playing significant roles in plant growth and development, as well as response to abiotic stresses. However, systematic reports on the FBA gene family and its functions in cucumber are lacking. In this study, we identified five cucumber FBA genes, named CsFBA1-5, that are distributed randomly across chromosomes. Phylogenetic analyses involving these cucumber FBAs, alongside eight Arabidopsis FBA proteins and eight tomato FBA proteins, were conducted to assess their homology. The CsFBAs were grouped into two clades. We also analyzed the physicochemical properties, motif composition, and gene structure of the cucumber FBAs. This analysis highlighted differences in the physicochemical properties and revealed highly conserved domains within the CsFBA family. Additionally, to explore the evolutionary relationships of the CsFBA family further, we constructed comparative syntenic maps with Arabidopsis and tomato, which showed high homology but only one segmental duplication event within the cucumber genome. Expression profiles indicated that the CsFBA gene family is responsive to various abiotic stresses, including low temperature, heat, and salt. Taken together, the results of this study provide a theoretical foundation for understanding the evolution of and future research into the functional characterization of cucumber FBA genes during plant growth and development.

Genome-wide analysis of the SWEET gene family in Hemerocallis citrina and functional characterization of HcSWEET4a in response to salt stress

Sugars will be eventually effluxed transporters (SWEETs) have been confirmed to play diverse physiological roles in plant growth, development and stress response. However, the characteristics and functions of the SWEET genes in Hemerocallis citrina remain unclear and poorly elucidated. In this study, the whole genome of Hemerocallis citrina was utilized to conduct bioinformatics analysis and a total of 19 HcSWEET genes were successfully identified. Analysis of the physicochemical properties indicated dominant differences among these HcSWEETs. A phylogenetic analysis revealed that HcSWEET proteins can be divided into 4 clades ranging from Clade I to IV, where proteins within the same clade exhibited shared conserved motifs and gene structures. Five to six exons were contained in the majority of HcSWEET genes, which were unevenly distributed across 11 chromosomes. The gene duplication analysis showed the presence of 4 gene pairs. Comparative syntenic maps revealed that the HcSWEET gene family might present more closed homology in monocotyledons than dicotyledons. Cis-acting element analysis of HcSWEET genes indicated key responsiveness to various hormones, light, and stresses. Additionally, transcriptome sequencing analysis suggested that most HcSWEET genes had a relatively higher expression in roots, and HcSWEET4a was significantly up-regulated under salt stress. Overexpression further verified the possibility that HcSWEET4a was involved in response to salt stress, which provides novel insights and facilitates in-depth studies of the functional analysis of HcSWEETs in resistance to abiotic stress.

The Adaptive Role of Bark in the Diet of Budongo Chimpanzees (Pan troglodytes schweinfurthii)

AbstractThe ingestion of bark has been observed across the animal kingdom and is well documented in free-ranging chimpanzees. Thus far, the best-supported hypothesis for the adaptive function of this behavior is the fallback food hypothesis, which asserts that chimpanzees consume bark and cambium when preferred foods are scarce. However, alternative explanations exist, including the essential nutrient and mineral hypothesis, the self-medication hypothesis, and the stressed-tree hypothesis. We tested whether the fallback food hypothesis can explain bark-feeding across two communities of Eastern chimpanzees (Pan troglodytes schweinfurthii) in the Budongo Forest, Uganda. We used 13 years of the site’s long-term behavioral data, 5 years of food availability data, and 8 months of direct and indirect observations. We also conducted eight 400-m line transects to collect data on the distribution of tree species across community home ranges. We employed several analyses, including Pearson correlation tests, qualitative comparisons of descriptive data and heat maps, and interpretation of behavioral anecdotes. We found varying patterns of bark-feeding seasonality across tree species, with bark-feeding on several species showing no correlation with food scarcity. We also identified differences in the amounts of bark targeted between tree species and report anecdotal evidence of chimpanzees prioritizing bark over high-value foods. Lastly, we found that bark-feeding on certain species disproportionally occurs far from community core areas, despite relative abundance of these species within the home range. As a result, we argue that the fallback food hypothesis cannot explain bark-feeding across all tree species. Instead, we present supporting evidence for several alternative hypotheses, including self-medication, thereby challenging the widely accepted function of this behavior.

The Manganari's Legacy: an atlas of the Black Sea, Drawn from Nature

This article delves into the historical and cartographic significance of the Manganari Atlas, a monumental work that marked a pivotal moment in the maritime cartography of the Black Sea during the nineteenth century. Originating from the Russian Empire's strategic desire to enhance navigation and assert its presence in the Black Sea, the atlas represents not only a technical achievement in mapping but also a cultural and political artifact of its time. Through a meticulous analysis of the atlas, this study highlights the challenges encountered in its creation, the technical innovations employed, and the political motivations driving its development. The atlas is examined not merely as a collection of maps but as a synthesis of the cultural, linguistic, and geopolitical landscape of the era, reflecting the Russian Empire's aspirations. The panoramic images by Kukharevsky are particularly noted for their potential to aid in coastal geomorphological studies and the reconstruction of various geographical landscapes. The article also addresses the necessity of understanding the technical aspects of cartography for accurate analysis and comparison of historical maps.

High-resolution mapping of tree species and associated uncertainty by combining aerial remote sensing data and convolutional neural networks ensemble

Mapping tree species diversity is essential for monitoring and managing forest ecosystems. Automating ecoforestry mapping using remote sensing images remains an important challenge due to the tremendous variability in forest covers and the conditions under which images used for classification are acquired. Deep learning algorithms have been increasingly used over the last few years to analyse remote sensing data for mapping tree species. However, most of these studies focus only on a small number of species or a limited area and avoid providing a spatially explicit representation of the uncertainty related to the predictions, rendering them unsuitable for operational use.In this study, we used an ensemble of convolutional neural networks to map forest species and land cover types across a 10,000 km2 area in Quebec, Canada, spanning mixed and boreal forests. We built a georeferenced label database to train and test nine models, which resulted from the combination of three training datasets and three-commonly used convolutional neural network architectures (VGG16, ResNet50v2, Densenet121). These models were trained on multiband aerial photographs and a canopy height model derived from airborne lidar point clouds and used to map the diversity and distribution of tree species and land cover types. The level of agreement among models was used to generate uncertainty maps. The performance of the super-ensemble using 1311 independent forest inventory plots and assessed the extent to which uncertainty maps could serve as a spatially explicit indicator of model performance.The super-ensemble achieved 90% global accuracy. Our results indicated that the performance of the super-ensemble surpassed that of all individual architectures while also showing a positive effect of the canopy height model on performance. The comparison of the super-ensemble map with the proportion of basal area measured in forest inventory plots confirmed the reliability of the model over the study area. Our results also indicated that mapping the inter-model agreement provides a reliable spatially explicit estimate of model performance. The robustness and reliability of the proposed approach support its use in an operational context while also providing a conceptual framework to evaluate the reliability of uncertainty maps.

Hybrid Democratic Innovations: If and When They Impact Decision-Making

ABSTRACT Increased citizen participation through democratic innovation is an increasingly popular response to the dual challenges of complex global problems and democratic malaise. Hybrid democratic innovations (HDIs), which combine deliberative and plebiscitary elements, could potentially realise the benefits of both forms, including improving the impact on decision-making. This paper explores the conditions under which a range of hybrid democratic innovations impact decision-making on policy. Using fuzzy-set Qualitative Comparative Analysis, two sufficient pathways where HDIs achieve impact on decision-making are identified. Strikingly, an active public engagement strategy is present in both of these routes to impact on decision-making, highlighting its importance – although always in combination with other design and contextual conditions. In regional or national-level cases with impact, we find an active public engagement strategy occurs in combination with a tight connection to representative institutions and on issues of low complexity. In local-level cases with impact, an active public engagement strategy occurs in combination with low rates of citizen participation, a finding which downplays the importance of the rate of participation on impact on decision-making. By assembling a comparative mapping of the field of HDIs, this paper helps us better understand when they (can) have an impact.

U-Net Convolutional Neural Network for Mapping Natural Vegetation and Forest Types from Landsat Imagery in Southeastern Australia.

Accurate and comparable annual mapping is critical to understanding changing vegetation distribution and informing land use planning and management. A U-Net convolutional neural network (CNN) model was used to map natural vegetation and forest types based on annual Landsat geomedian reflectance composite images for a 500 km × 500 km study area in southeastern Australia. The CNN was developed using 2018 imagery. Label data were a ten-class natural vegetation and forest classification (i.e., Acacia, Callitris, Casuarina, Eucalyptus, Grassland, Mangrove, Melaleuca, Plantation, Rainforest and Non-Forest) derived by combining current best-available regional-scale maps of Australian forest types, natural vegetation and land use. The best CNN generated using six Landsat geomedian bands as input produced better results than a pixel-based random forest algorithm, with higher overall accuracy (OA) and weighted mean F1 score for all vegetation classes (93 vs. 87% in both cases) and a higher Kappa score (86 vs. 74%). The trained CNN was used to generate annual vegetation maps for 2000-2019 and evaluated for an independent test area of 100 km × 100 km using statistics describing accuracy regarding the label data and temporal stability. Seventy-six percent of pixels did not change over the 20 years (2000-2019), and year-on-year results were highly correlated (94-97% OA). The accuracy of the CNN model was further verified for the study area using 3456 independent vegetation survey plots where the species of interest had ≥ 50% crown cover. The CNN showed an 81% OA compared with the plot data. The model accuracy was also higher than the label data (76%), which suggests that imperfect training data may not be a major obstacle to CNN-based mapping. Applying the CNN to other regions would help to test the spatial transferability of these techniques and whether they can support the automated production of accurate and comparable annual maps of natural vegetation and forest types required for national reporting.

When and where? Day-night alterations in wild boar space use captured by a generalized additive mixed model.

Wild boar (Sus scrofa), an abundant species across Europe, is often subjected to management in agro-ecosystems in order to control population size, or to scare them away from agricultural fields to safeguard crop yields. Wild boar management can benefit from a better understanding on changes in its space use across the diel cycle (i.e., diel space use) in relation to variable hunting pressures or other factors. Here, we estimate wild boar diel space use in an agro-ecosystem in central Belgium during four consecutive "growing seasons" (i.e., April-September). To achieve this, we fit generalized additive mixed models (GAMMs) to camera trap data of wild boar aggregated over 1-h periods. Our results reveal that wild boar are predominantly nocturnal in all of the hunting management zones in Meerdaal, with activity peaks around sunrise and sunset. Hunting events in our study area tend to take place around sunrise and sunset, while non-lethal human activities occur during sunlight hours. Our GAMM reveals that wild boar use different areas throughout the diel cycle. During the day, wild boar utilized areas in the centre of the forest, possibly to avoid human activities during daytime. During the night, they foraged near (or in) agricultural fields. A post hoc comparison of space use maps of wild boar in Meerdaal revealed that their diurnal and nocturnal space use were uncorrelated. We did not find sufficient evidence to prove that wild boar spatiotemporally avoid hunters. Finally, our work reveals the potential of GAMMs to model variation in space across 24-h periods from camera trap data, an application that will be useful to address a range of ecological questions. However, to test the robustness of this approach we advise that it should be compared against telemetry-based methods to derive diel space use.

The Effect of Remimazolam on Seizure Profile, Hemodynamics, and Recovery in Patients With Electroconvulsive Therapy Comparison With Propofol and Etomidate: A Retrospective Study.

To compare seizure-related, hemodynamic, and recovery outcomes when using remimazolam for ECT with those of other anesthetics, specifically propofol and etomidate. A total of 49 patients who underwent 405 ECT treatment sessions under general anesthesia were retrospectively analyzed. Remimazolam, propofol, and etomidate were used for 93, 138, and 174 ECT sessions, respectively. The primary outcome was durations of motor and electroencephalogram (EEG) seizure activity, whereas secondary outcomes included hemodynamics (ie, mean arterial pressure [MAP] and heart rate [HR] at various time points from induction to postanesthesia care unit [PACU] discharge), antihypertensive drugs administration after electrical stimulus, and recovery profiles (ie, length of PACU stay and incidence of postictal confusion). Durations of motor and EEG seizures were shorter for remimazolam than etomidate (motor, P < 0.001; EEG, P = 0.003) but similar compared with propofol (motor, P = 0.191; EEG, P = 0.850). During seizure, remimazolam showed a comparable MAP and HR to etomidate (MAP: P = 0.806; HR: P = 0.116). The antihypertensive drug use was lowest for remimazolam (6.8%), followed by propofol (35.6%) and etomidate (65.6%), and the mean length of PACU stay was comparable for remimazolam (19.7 min), propofol (22.8 min), and etomidate (24.5 min). The occurrence of postictal confusion did not differ among the 3 agents (P > 0.050). Remimazolam is a promising anesthetic option for ECT because of its comparable seizure profiles, stable hemodynamics, and comparable PACU stay when compared with propofol and etomidate without additional adverse events.

Mutual recognition of qualifications, health workforce migration, and graduate outcomes: a comparative mapping study of undergraduate dental education in Europe

BackgroundThe resource needs of health services are served by the recognition of qualifications across borders which allows professionals to migrate between countries. The movement of dentists across the European Union (EU), especially into the United Kingdom (UK), has provided a valuable boost to workforce supply. Recent changes to policy recognising overseas qualifications have brought attention to the equivalence of qualifications awarded in EU countries. Professional regulators need to be confident that dentists who qualified elsewhere have the appropriate knowledge, skills and experience to practise safely and effectively. The aim of this study was to compare UK and EU dental curricula, identify any differences, and compare the extent of pre-qualification clinical experience.MethodsThis was a mixed methods study comprising a questionnaire and website searches to identify information about curricula, competences, and quality assurance arrangements in each country. The questionnaire was sent to organisations responsible for regulating dental education or dental practice in EU member states. This was supplemented with information obtained from website searches of stakeholder organisations for each country including regulators, professional associations, ministries, and providers of dental education. A map of dental training across the EU was created.ResultsNational learning outcomes for dental education were identified for seven countries. No national outcomes were identified 13 countries; therefore, learning outcomes were mapped at institution level only. No information about learning outcomes was available for six countries. In one country, there is no basic dental training. Clinical skills and communication were generally well represented. Management and leadership were less represented. Only eight countries referenced a need for graduates to be aware of their own limitations. In most countries, quality assurance of dental education is not undertaken by dental organisations, but by national quality assurance agencies for higher education. In many cases, it was not possible to ascertain the extent of graduates’ direct clinical experience with patients.ConclusionsThe findings demonstrate considerable variation in learning outcomes for dental education between countries and institutions in Europe. This presents a challenge to decision-makers responsible for national recognition and accreditation of diverse qualifications across Europe to maintain a safe, capable, international workforce; but one that this comparison of programmes helps to address.

Comparison of Immunofluorescence Mapping and Immunohistochemistry in the Auxiliary Diagnosis of Congenital Epidermolysis Bullosa: Erratum

Comparison of Immunofluorescence Mapping and Immunohistochemistry in the Auxiliary Diagnosis of Congenital Epidermolysis Bullosa: Erratum

What can be said?

Abstract We employ a cluster approach to explore the comparative semantic maps of several markers of modal possibility – the “potential” prefix nga‑ and expressions meaning, roughly, ‘know how to’ and ‘be able to’ – in four South African Nguni languages: isiNdebele, isiZulu, isiXhosa, Siswati. We also compare the Nguni results with results from Xitsonga, a closely related language outside of the Nguni clade. The languages exhibit cross-linguistic differences in the expansion of core meanings, some of which do not appear to follow the cross-linguistically common diachronic pattern in which goal-oriented modality precedes deontic modality. In addition, the distinction between inherent and learned ability is salient in several of these languages. Semantic maps of the markers’ functional distributions further show the diversity of modal systems that can be found even in closely related languages in significant contact with one another.