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At least 10 global digital elevation models (DEMs) at one-arc-second resolution now cover Earth. Comparing derived grids, like slope or curvature, preserves surface spatial relationships, and can be more important than just elevation values. Such comparisons provide more nuanced DEM rankings than just elevation root mean square error (RMSE) for a small number of points. We present three new comparison categories: fraction of unexplained variance (FUV) for grids with continuous floating point values; accuracy metrics for integer code raster classifications; and comparison of stream channel vector networks. We compare six global DEMs that are digital surface models (DSMs), and four edited versions that use machine learning/artificial intelligence techniques to create a bare-earth digital terrain model (DTM) for different elevation ranges: full Earth elevations, under 120 m, under 80 m, and under 10 m. We find edited DTMs improve on elevation values, but because they do not incorporate other metrics in their training they do not improve overall on the source Copernicus DSM. We also rank 17 common geomorphic-derived grids for sensitivity to DEM quality, and document how landscape characteristics, especially slope, affect the results. None of the DEMs perform well in areas with low average slope compared to reference DTMs aggregated from 1 m airborne lidar data. This indicates that accurate work in low-relief areas grappling with global climate change should use airborne lidar or very high resolution image-derived DTMs.

An efficient and robust soil moisture (SM) sampling scheme that can capture the spatial variability of SM is required for the accurate calibration and validation of satellite-based SM retrievals. Often, this process requires numerous sampling points, consuming a significant amount of time. Therefore, it is crucial to develop efficient sampling methods for the improvement of satellite-based SM estimations. The objectives of this study were to define an efficient sampling strategy that could be beneficial for the validation of satellite SM estimations; investigate the role of RS covariates in developing such a strategy; and evaluate the performance of the new sampling scheme over various spatial and temporal domains. In this study, we used the conditioned Latin hypercube sampling (cLHS) algorithm to define an efficient sampling strategy. To this end, remote sensing (RS) raster and digital elevation models (DEM) were used to identify numerous environmental covariates to locate sampling points for characterizing spatial variability of SM at the agricultural field scale. A random forest-based technique, the Boruta algorithm, was also applied to select the most important covariates for utilization into the cLHS algorithm. We used the statistical moments (mean and standard deviation, SD) of the field to select the efficient sample size that can best represent SM status in the field. To evaluate the new sampling scheme, a second data set obtained during a different month for the same agricultural field was used. However, because of the potential for high spatial and temporal correlations between training and test covariates when obtained for the same region, we also used different test datasets in New Zealand to evaluate the sampling scheme. Results showed that the RS covariates obtained from SAR and optical imagery were among the most significant covariates for capturing the spatial variability of SM even if they were not acquired on the day of collection. Also, the new sampling scheme could capture the SM spatial pattern of the field for both test datasets with RMSE less than 4% volumetric SM, which is within the range of the expected performance for most satellite SM products. The evaluation of the new sampling scheme on the New Zealand datasets confirmed the functionality of the proposed sampling scheme for a different temporal and spatial domain.

Surface roughness plays an important role in microwave remote sensing. In the agricultural domain, surface roughness is crucial for soil moisture retrieval methods that use electromagnetic surface scattering or microwave radiative transfer models. Therefore, improved characterization of Soil Surface Roughness (SSR) is of considerable importance. In this study, three approaches, including a standard pin profiler, a LiDAR point cloud generated from an iPhone 12 Pro, and a Structure from Motion (SfM) photogrammetric point cloud, were applied over 24 surface profiles with different roughness variations to measure surface roughness. The objective of this study was to evaluate the capability of smartphone-based LiDAR technology to measure surface roughness parameters and compare the results of this technique with the more common approaches. Results showed that the iPhone LiDAR technology, when point cloud data is captured in a fine-resolution mode, has a significant correlation with SfM photogrammetry (R2 = 0.70) and a relatively close agreement with pin profiler (R2 = 0.60). However, this accuracy tends to be greater for random surfaces and rough profiles with row structure orientations. The results of this study confirm that smartphone-based LiDAR can be used as a cost-effective, fast, and time-efficient alternative tool for measuring surface roughness, especially for rough, wide, and inaccessible areas.

Ischemic colitis and proctitis is a rare manifestation of systemic lupus erythematosus (SLE) and results from mesenteric vasculitis. Owing to diverse blood supply and presence of multiple collaterals, rectum is the least effected site in SLE enteritis. Ischemic proctocolitis as the presenting feature of SLE is exceedingly rare, with only three cases reported in the published scientific literature. We present the first case of SLE presenting as ischemic proctitis, leading to intraperitoneal hemorrhage and abdominal compartment syndrome. A young lady presented with ischemic proctitis and a hematoma masquerading as a pelvic mass, with subsequent development of massive intraperitoneal hemorrhage, shock, and rectal perforation. The patient required urgent surgery and was initiated on high-dose steroids.

Adequate descriptions of soil surface roughness are vital for the accurate retrieval of soil moisture maps from remote sensing products. Terrestrial laser scanners (TLSs) have the potential to offer a more comprehensive method of measuring surface roughness than traditional techniques, but are underused in this application. This research examines the use of TLSs for measuring the surface roughness of bare agricultural fields in Elora, Ontario. Through the development and application of an innovative plug-in called Roughness from Point Cloud Profiles (RPCP), this research compares TLS surface roughness characterizations to those derived from a pin profiler. In most cases, the root mean square height (RMSH) measurements obtained from the pin profiler are within 1.5 cm of those obtained from Light Detection and Ranging (LiDAR). Nearly 90% of the l measurements obtained from the TLS were >5 cm larger than those from the pin profiler. Discrepancies between pin profiler and TLS roughness characterizations can be partially explained by LiDAR shadowing in some cases, but are likely caused by other factors such as de-trending techniques, profile length, and profile orientation. The results of this research illustrate roughness variations across fields and between roughness profile orientations according to tillage structures.

Accurate yield estimation and optimized agricultural management is a key goal in precision agriculture, while depending on many different production attributes, such as soil properties, fertilizer and irrigation management, the weather, and topography.The need for timely and accurate sensing of these inputs at the within field-scale has led to increased adoption of very high-resolution remote and proximal sensing technologies. With regard to topography attributes, greater attention is currently being devoted to LiDAR datasets (Light Detection and Ranging), mainly because numerous topographic variables can be derived at very high spatial resolution from these datasets. The current study uses LiDAR elevation data from agricultural land in southern Ontario, Canada to derive several topographic attributes such as slope, and topographic wetness index, which were then correlated to seven years of crop yield data. The effectiveness of each topographic derivative was independently tested using a moving-window correlation technique. Finally, the correlated derivatives were selected as explanatory variables for geographically weighted regression (GWR) models. The global coefficient of determination values (determined from an average of all the local relationships) were found to be R2 = 0.80 for corn, R2 = 0.73 for wheat, R2 = 0.71 for soybeans and R2 = 0.75 for the average of all crops. These results indicate that GWR models using topographic variables derived from LiDAR can effectively explain yield variation of several crop types on an entire-field scale.

Se examina la forma en que Alemania y Estados Unidos han adaptado sus leyes y políticas de control de exportación de armas cortas y ligeras (SALW, por sus siglas en inglés) frente a México, país que pasa actualmente por una severa crisis de derechos humanos. A partir de entrevistas efectuadas en Alemania y Estados Unidos, así como de reportes oficiales y bibliografía secundaria, el artículo identifica que mientras Alemania ha retraído sus exportaciones de SALW a México, las empresas estadounidenses continúan exportando prácticamente sin restricciones. El texto presenta contribuciones a dos debates académicos: el estudio de la participación de actores no estatales en el proceso de toma de decisiones en política de exportación de armas y el examen de cómo las normas internacionales afectan el comportamiento y las prácticas de los Estados nacionales, un tema clave en la agenda constructivista de las Relaciones Internacionales.

Surface roughness is an important factor in many soil moisture retrieval models. Therefore, any mischaracterization of surface roughness parameters (root mean square height, RMSH, and correlation length, ʅ) may result in unreliable predictions and soil moisture estimations. In many environments, but particularly in agricultural settings, surface roughness parameters may show different behaviours with respect to the orientation or azimuth. Consequently, the relationship between SAR polarimetric variables and surface roughness parameters may vary depending on measurement orientation. Generally, roughness obtained for many SAR-based studies is estimated using pin profilers that may, or may not, be collected with careful attention to orientation to the satellite look angle. In this study, we characterized surface roughness parameters in multi-azimuth mode using a terrestrial laser scanner (TLS). We characterized the surface roughness parameters in different orientations and then examined the sensitivity between polarimetric variables and surface roughness parameters; further, we compared these results to roughness profiles obtained using traditional pin profilers. The results showed that the polarimetric variables were more sensitive to the surface roughness parameters at higher incidence angles (θ). Moreover, when surface roughness measurements were conducted at the look angle of RADARSAT-2, more significant correlations were observed between polarimetric variables and surface roughness parameters. Our results also indicated that TLS can represent more reliable results than pin profiler in the measurement of the surface roughness parameters.

This study has explored the use of portfolios and of awareness-raising of literacy networks in a CLIL lecture preparation class for first-year undergraduates in a Japanese university. It is argued that CLIL-related literature has a paucity of practical studies investigating these two elements essential to autonomy-building, particularly for students who have been previously mostly exposed to teacher-centered modes of instruction. Questionnaires asking students their perceptions of portfolio use and self-study were gathered over three years and were coupled with a one year small-scale data set of student-drawn ‘literacy maps’ exploring who and what materials students had consulted to produce a final lecture-related report. Findings revealed increased awareness of the importance of portfolio and self-study and even their cross-fertilization over to other classes across the language and content curricula; however, some reticence was evident regarding self-scoring in self-study mode, showing that the transition from traditional teacher-centredness at high school had not yet been overcome. Also, of importance was the initially extensive use of self-access center advisors which, when withdrawn, may have negatively impacted students’ literacy networks. Implications to be drawn from this study lie primarily in the expanded use of portfolios and increased awareness-raising of student networks as important means towards the development of autonomous study skills and literacy. Questions do, however, remain as to the extent that this approach actually mirrors English-medium instruction in content classes at the university.

Research on so-called “minor taxa” at mesophotic depths has lagged behind that of more commonly researched groups such as fish or hard corals. Exemplar taxa include species of the order Zoantharia, benthic colonial anemones that are cosmopolitan in distribution but understudied in many ecoregion and ecosystems. In this study, we examine the results of rare mesophotic to deep sea surveys (one rebreather, one remotely operated submersible (ROV) + net survey, two ROV surveys) from Japan and Israel. We examined the collected images and video data to provide a first estimate of Zoantharia diversity at mesophotic depths. Zoantharians were observed in all surveys, indicating their ubiquitous presence in mesophotic and deeper ecosystems. Additionally, specimens (n = 12) acquired via these surveys were phylogenetically analyzed with three DNA markers. Phylogenetic results showed the presence of undescribed species based on the uniqueness of acquired DNA sequences, including one specimen belonging to the family Abyssoanthidae, previously only reported from depths below 2000 m. Other specimens belong to groups that inhabit shallower and deeper depths (Antipathozoanthus, Epizoanthus, and Parazoanthidae). These results depart from surveys of mesophotic coral ecosystem fishes and crustaceans, which indicate affiliations almost exclusively with shallow genera and families. We hypothesize that mesophotic depths are an ecotone for zoantharian diversity, with links to both deeper and shallower ecosystem diversity. Future surveys in mesophotic depths should incorporate phylogenetic methods to better catalog so-called “minor taxa” (not only including Zoantharia) and enhance the scientific foundation for conserving the biodiversity of these threatened ecosystems.

This study reports on the longitudinal analysis of a structured after-school arts program for Canadian youth, ages 9 to 15 years, from low-income communities where the relationship of peer social support, family interactions, and psychosocial outcomes is evaluated. Multi-level growth curve analyses suggest an increase in prosocial development with peer social support and a decrease in prosocial development when negative family interactions are present. Comparisons between matched controls, using estimated linear propensity scores, revealed significant improvement in prosocial behaviors for the intervention group. The structured after-school arts program was found to increase prosocial behaviors and bonding with peers for youth from low-income communities. (Contains 3 tables.)

Objectives: This study reports on the concept and method of linear propensity scores used to obtain a comparison group from the National Longitudinal Survey of Children and Youth to assess the effects of a longitudinal, structured arts program for Canadian youth (aged 9 to 15 years) from low-income, multicultural communities. Method: This study compares 183 children in a community arts project to 183 children from a national longitudinal survey using propensity score matching. The variables included baseline scores of child-rated conduct problems, indirect aggression, emotional problems, self-esteem, and prosocial behavior and child gender, person most knowledgeable (PMK) education, PMK marital status, household income, and family functioning. Results: Mean score comparison showed that the groups were very similar on all covariates. Conclusions: Propensity score matching offers an alternative to true randomization that is cost-effective and convenient, particularly important for social work research in community-based organizations with a limited budget. (Contains 2 tables.)

We discuss some of the lessons the investigators learned during the development, implementation, and dissemination phases of the National Arts and Youth Demonstration Project (NAYDP). The lessons learned are relevant to various groups involved in large-scale, multi-site, community-based intervention studies: parents, youth, researchers, project staff, policy makers, and funders. Specific lessons learned include: (1) how to engage the community; (2) methodological lessons, including cross-site training and monitoring adherence to research protocol; (3) recruiting and sustaining involvement of parents and youth; (4) program development; and (5) dissemination strategies.

This article describes the methodology and program effects of a multicomponent model of interventions designed to prevent antisocial behaviour in secondary school students. Interventions included cooperative learning, classroom management, and peer tutoring, mentoring, and mediation. Data from the Secondary Schools Demonstration Project (SSDP) implemented in Ontario, Canada, schools were analyzed to assess whether the interventions had similar and/or differential effects on groups of students with low and high risks for antisocial behaviour. The study involved a two-group matched comparison before-and-after design. Data were collected at baseline for all ninth-grade students (average age 14 years) in the four schools, and from a subsample of the students at follow-up. The findings showed that the interventions generated similar improvements in the low and high-risk groups of youth. However, the positive effects were slightly more pronounced in the low-risk youth. The discussion proposes future directions for research and practice. (Contains 3 tables.)

This study reports on the longitudinal examination of a structured arts program for Canadian youth, aged 9 to 15 years, from low-income communities. Evaluated were the extent to which community-based organizations successfully recruited and retained youth in the program and whether they demonstrated improvement with respect to artistic ability (combination of theatre, visual, and media arts) and psychosocial indicators. The results suggest successful recruitment and good retention rates. Multilevel growth curve analyses of observational and behavioral outcomes are presented. Observer ratings showed significant gains in artistic and social skills. Comparisons with matched controls using estimated linear propensity scores revealed a significant reduction in emotional problems for the intervention group. The overall conclusion is that youth from low-income communities benefit from structured arts programs. (Contains 3 tables.)

This article describes the methodology and program effects of the Secondary Schools Demonstration Project (SSDP) conducted in four Ontario schools. The objective of the study was to evaluate the extent to which a universal program model of three interventions--cooperative learning; classroom management; and peer-helping approaches that included tutoring and mediation--can reduce the prevalence of antisocial behaviour. The study employed a two-group matched comparison before-and-after design. It involved the collection of baseline data on all ninth grade students (average age of 14 years) in four schools, and the selection of a sub-sample for a more detailed follow-up. Of the 13 measures analyzed, the results were statistically significant on four variables: student perception of teacher, student sense of belonging, student attachment to school, and truancy, suspensions, and behaviour problems. The findings of the study are discussed in relation to the methodological issues involved in implementing and evaluating multi-component interventions in secondary schools. Secondary Schools Demonstration Project Outcome Measures are appended. (Contains 4 tables.)

The validity of a scale, from the Ontario Health Survey, measuring the subjective sense of well-being, for a large multicultural population in Metropolitan Toronto, is examined through principal components analysis with oblique rotation. Four factors are extracted. Factor 1, is a stress and strain factor, and consists of health worries, feeling exhausted and worn out, and feeling tense. Factor 2, interpreted as a sense of control, consists of no health worries, and ability to handle feelings. Factor 3, interpreted as positive affect, consists of having an interesting life, feeling cheerful and light-hearted, feeling loved, feeling relaxed and full of vitality. Factor 4 is interpreted as a despondency factor consists of feeling lonely, having a boring life, inability to control feelings and feeling low. The statistic of multiple discriminant analysis between the variables, sex, age, and ethnic groupings, as independent discriminating variables and the four factor scores as dependent variables, is calculated. The results show that the observed mean variance in the well-being factor scores cannot be explained by the respondents being either female or male, or being a certain age or by belonging to specific cultural groupings. These results are discussed in relation to other studies on the dimensions of subjective well-being.