Scale Selection Research Articles

How well do workplace-based assessments support summative entrustment decisions? A multi-institutional generalisability study.

Assessment of the Core Entrustable Professional Activities for Entering Residency requires direct observation through workplace-based assessments (WBAs). Single-institution studies have demonstrated mixed findings regarding the reliability of WBAs developed to measure student progression towards entrustment. Factors such as faculty development, rater engagement and scale selection have been suggested to improve reliability. The purpose of this investigation was to conduct a multi-institutional generalisability study to determine the influence of specific factors on reliability of WBAs. The authors analysed WBA data obtained for clerkship-level students across seven institutions from 2018 to 2020. Institutions implemented a variety of strategies including selection of designated assessors, altered scales and different EPAs. Data were aggregated by these factors. Generalisability theory was then used to examine the internal structure validity evidence of the data. An unbalanced cross-classified random-effects model was used to decompose variance components. A phi coefficient of >0.7 was used as threshold for acceptable reliability. Data from 53 565 WBAs were analysed, and a total of 77 generalisability studies were performed. Most data came from EPAs 1 (n = 17 118, 32%) 2 (n = 10 237, 19.1%), and 6 (n = 6000, 18.5%). Low variance attributed to the learner (<10%) was found for most (59/77, 76%) analyses, resulting in a relatively large number of observations required for reasonable reliability (range = 3 to >560, median = 60). Factors such as DA, scale or EPA were not consistently associated with improved reliability. The results from this study describe relatively low reliability in the WBAs obtained across seven sites. Generalisability for these instruments may be less dependent on factors such as faculty development, rater engagement or scale selection. When used for formative feedback, data from these instruments may be useful. However, such instruments do not consistently provide reasonable reliability to justify their use in high-stakes summative entrustment decisions.

The Cerebellar Cognitive Affective/Schmahmann Syndrome Scale in Spinocerebellar Ataxias.

The Cerebellar Cognitive Affective/Schmahmann Syndrome (CCAS) manifests as impaired executive control, linguistic processing, visual spatial function, and affect regulation. The CCAS has been described in the spinocerebellar ataxias (SCAs), but its prevalence is unknown. We analyzed results of the CCAS/Schmahmann Scale (CCAS-S), developed to detect and quantify CCAS, in two natural history studies of 309 individuals Symptomatic for SCA1, SCA2, SCA3, SCA6, SCA7, or SCA8, 26 individuals Pre-symptomatic for SCA1 or SCA3, and 37 Controls. We compared total raw scores, domain scores, and total fail scores between Symptomatic, Pre-symptomatic, and Control cohorts, and between SCA types. We calculated scale sensitivity and selectivity based on CCAS category designation among Symptomatic individuals and Controls, and correlated CCAS-S performance against age and education, and in Symptomatic patients, against genetic repeat length, onset age, disease duration, motor ataxia, depression, and fatigue. Definite CCAS was identified in 46% of the Symptomatic group. False positive rate among Controls was 5.4%. Symptomatic individuals had poorer global CCAS-S performance than Controls, accounting for age and education. The domains of semantic fluency, phonemic fluency, and category switching that tap executive function and linguistic processing consistently separated Symptomatic individuals from Controls. CCAS-S scores correlated most closely with motor ataxia. Controls were similar to Pre-symptomatic individuals whose nearness to symptom onset was unknown. The use of the CCAS-S identifies a high CCAS prevalence in a large cohort of SCA patients, underscoring the utility of the scale and the notion that the CCAS is the third cornerstone of clinical ataxiology.

The malnutrition in AECOPD and its association with unfavorable outcomes by comparing PNI, GNRI with the GLIM criteria: a retrospective cohort study.

The management of nutritional risk has garnered significant attention in individuals diagnosed with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) due to the high prevalence of malnutrition and its correlation with unfavorable outcomes. While numerous rating scales exist to assist in assessment for both clinical and research purposes, there is considerable variability in the selection of scales based on the characteristics of the study participants and the study design. The objective of this study was to examine the efficacy of the Geriatric Nutritional Risk Index (GNRI) and Prognostic Nutritional Index (PNI) in identifying malnutrition and predicting prognosis in elderly AECOPD patients. From January 2022 to December 2022, a consecutive inclusion of elderly AECOPD patients admitted to the First Affiliated Hospital of Zhengzhou University was conducted. Diagnosing malnutrition in patients using PNI and GNRI, comparing the results with the diagnostic outcomes based on the Global Leadership Initiative on Malnutrition (GLIM) criteria through Receiver Operating Characteristic curves. Logistic regression analysis was employed to assess the risks associated with length of stay (LOS), hospitalization costs, and Charlson Comorbidity Index (CCI) based on GLIM, GNRI, or PNI. A total of 839 elderly AECOPD patients were investigated in the study. The GNRI and PNI demonstrated a sensitivity of 89.5 and 74.1%, specificity of 77.2 and 66.4%, and an area under the curve of 0.834 and 0.702, respectively. The identification of high malnutrition-risk cases using the GLIM, GNRI and PNI were associated with a significant increase in the risk of LOS over 7 days [odds ratio (95% CI) for GLIM, GNRI, PNI: 1.376 (1.033-1.833); 1.405 (1.070-1.846); 1.875 (1.425-2.468)] and higher hospitalization expenses [OR (95% CI) for GLIM, GNRI: 1.498 (1.080-2.080); 1.510 (1.097-2.079)], but not with the CCI. According to our study, it is possible to use GNRI and PNI as alternatives to GLIM in the context of AECOPD, which makes it easier to identify malnutrition. The utilization of GNRI and PNI as alternatives to GLIM in the context of AECOPD enables the identification of malnutrition. The presence of malnourished individuals experiencing AECOPD is correlated with higher probabilities of extended hospital stays and escalated in-hospital expenses.

Simulation Study on Rain-Flood Regulation in Urban “Gray-Green-Blue” Spaces Based on System Dynamics: A Case Study of the Guitang River Basin in Changsha

Urban rainstorms and flood disasters are the most common and severe environmental problems worldwide. Many factors influence rain-flood control simulation, forming a complex network system of interconnected and mutually constraining elements. In terms of spatial scale selection, existing research on rain-flood disaster risk largely relies on a single-scale infrastructure index system and has not yet focused on urban “gray-green-blue” spatial scale simulations for rain-flood storage. Regarding research methodology, applying system dynamics methods to the simulation of rain-flood storage and disaster prevention planning in watershed cities is still in its initial stages. System dynamics models can simulate the feedback interactions among various sub-elements in the coupled mega-system, fully addressing complex issues within the system structure that involve multiple variables, non-linear relationships, and numerous feedback loops, thereby compensating for the inadequacies of traditional linear models in the collaborative management of rain-flood risks. Taking the Changsha Guitang River Basin as an example, this paper constructs a system dynamics model covering four dimensions: natural environment, socio-economics, internal structure, and policy development. It aims to derive the optimal planning scheme for gray-green-blue spatial coordination in rain-flood storage by weighing four different development scenarios. The simulation results show: (1) Simply changing the surface substrates without considering rainwater discharge and the plan that emphasizes the construction of municipal drainage facilities will see the capacity gap for rain-flood storage-space construction continue to widen by 2035. This indicates that the plans mentioned above will struggle to bear the socio-economic losses cities face during rain-flood disasters. (2) The plan of combining gray and green infrastructures sees the rain-flood storage construction capacity turn from negative to positive from 2024, rising to 52.259 billion yuan by 2035. This reflects that the plan can significantly reduce the rainwater volume in the later stages of low-impact development infrastructure construction, mitigate rain-flood disaster risks, and reduce government investment in rain-flood disaster risk management, making it a relatively excellent long-term rain-flood storage space planning option. (3) The rain-flood regulation space planning scheme, under the combined effect of the urban “gray-green-blue” network system, sees the capacity for rain-flood storage construction turn positive a year earlier than the previous plan, reaching 54.232 billion yuan by 2035. This indicates that the scheme can not only effectively respond to extreme flood and rainstorm disasters but also maintain ecological environment benefits and mitigate the socio-economic losses caused by disasters, making it the optimal choice for future government disaster management planning. The research results provide a theoretical framework and practical insights for territorial spatial planning, rain-flood control management, and resilient city construction in watershed areas.

Scalable variable selection for two-view learning tasks with projection operators

In this paper we propose a novel variable selection method for two-view settings, or for vector-valued supervised learning problems. Our framework is able to handle extremely large scale selection tasks, where number of data samples could be even millions. In a nutshell, our method performs variable selection by iteratively selecting variables that are highly correlated with the output variables, but which are not correlated with the previously chosen variables. To measure the correlation, our method uses the concept of projection operators and their algebra. With the projection operators the relationship, correlation, between sets of input and output variables can also be expressed by kernel functions, thus nonlinear correlation models can be exploited as well. We experimentally validate our approach, showing on both synthetic and real data its scalability and the relevance of the selected features.

Quality Development of Soft Drinks Based on the Qualimetric Model Engineering

A number of doctrinal documents of the Russian Federation define the need for the non-communicable chronic disease prevention, and as a consequence, the health promotion by including specialized foods in the diet. From the list of homogeneous product groups, beverages are the most convenient for the functional property development, have simple production technology and are in demand with different population groups. All of those things determine the prospects for further development of the alcohol-free beverages. To forecast the quality and consumer characteristics of the projected alcohol-free beverages, a man developed a process for qualimetric model engineering of the expected assortment properties of drinks based on aspen leaves containing substances with pronounced antioxidant properties based on the example of the Yugorsky drink. The relevance of such research consists in the complex development including the maximum quality properties set of the projected product, in the formation of which engineers, consumers and experts participate. The development process of a qualimetric model for the quality engineering of beverages consists of five stages: identification of significant indicators inherent in this product group; "properties tree" developmen alcohol-free beverages; selection or development of scales for the beverage consumer properties assessment, weighting coefficient determination; complex (integral) indicator determination of the beverage quality. The authors emphasize the stages study depth importance of the new product development process and the degree of its detailing, depending on the knowledge and vision of all participants in the process.

Algorithmic uncertainties in geolocating social media data for disaster management

ABSTRACT The rapid development of information and communications technology has turned individuals into sensors, fostering the growth of human-generated geospatial big data. In disaster management, geospatial big data, mainly social media data, have opened new avenues for observing human responses to disasters in near real-time. Previous research relies on geographical information in geotags, content, and user profiles to locate social media messages. However, less than 1% of users geotag their messages, leaving geolocating users through user profiles or message content addresses increasingly crucial. This paper evaluates and visualizes the margin of error incurred when using user profiles or message-mentioned addresses to geolocate social media data for disaster research. Using Twitter data during the 2017 Hurricane Harvey as an example, this research assessed the inconsistencies in predicting users’ locations in various administrative units during each disaster phase using three geolocating strategies. The results reveal that the similarities between geotags, and user profile locations decrease from 94.07% to 64.56%, 43.9%, 31.82%, 27.05%, and 26.7% as the geographical scale changes from country to state, county, block group, 1-kilometer, and 30-meter levels. These similarities are overall higher than the agreements between locations derived from geotags and tweet content. The geolocation consistencies among the three methods remain stable across disaster phases. The impacts of uncertainties in geolocating Twitter data for disaster management applications were further unraveled. The findings offer valuable insights into the trade-off between spatial scale and geolocation accuracy and inform the selection of appropriate scales when applying different geolocating strategies in future social media-based investigations.

SSPNet: Scale and spatial priors guided generalizable and interpretable pedestrian attribute recognition

Global feature based Pedestrian Attribute Recognition (PAR) models are often poorly localized when using Grad-CAM for attribute response analysis, which has a significant impact on the interpretability, generalizability and performance. Previous researches have attempted to improve generalization and interpretation through meticulous model design, yet they often have neglected or underutilized effective prior information crucial for PAR. To this end, a novel Scale and Spatial Priors Guided Network (SSPNet) is proposed for PAR, which is mainly composed of the Adaptive Feature Scale Selection (AFSS) and Prior Location Extraction (PLE) modules. The AFSS module learns to provide reasonable scale prior information for different attribute groups, allowing the model to focus on different levels of feature maps with varying semantic granularity. The PLE module reveals potential attribute spatial prior information, which avoids unnecessary attention on irrelevant areas and lowers the risk of model over-fitting. More specifically, the scale prior in AFSS is adaptively learned from different layers of feature pyramid with maximum accuracy, while the spatial priors in PLE can be revealed from part feature with different granularity (such as image blocks, human pose keypoint and sparse sampling points). Besides, a novel IoU based attribute localization metric is proposed for Weakly-supervised Pedestrian Attribute Localization (WPAL) based on the improved Grad-CAM for attribute response mask. The experimental results on the intra-dataset and cross-dataset evaluations demonstrate the effectiveness of our proposed method in terms of mean accuracy (mA). Furthermore, it also achieves superior performance on the PCS dataset for attribute localization in terms of IoU. Code will be released at https://github.com/guotengg/SSPNet.

Manufacture of CD22 CAR T cells following positive versus negative selection results in distinct cytokine secretion profiles and γδ T cell output

Chimeric antigen receptor Tcells (CART) have demonstrated curative potential for hematological malignancies, but the optimal manufacturing has not yet been determined and may differ across products. The first step, Tcell selection, removes contaminating cell types that can potentially suppress Tcell expansion and transduction. While positive selection of CD4/CD8 Tcells after leukapheresis is often used in clinical trials, it may modulate signaling cascades downstream of these co-receptors; indeed, the addition of a CD4/CD8-positive selection step altered CD22 CART potency and toxicity in patients. While negative selection may avoid this drawback, it is virtually absent from good manufacturing practices. Here, we performed both CD4/CD8-positive and -negative clinical scale selections of mononuclear cell apheresis products and generated CD22 CARTs per our ongoing clinical trial (NCT02315612NCT02315612). While the selection process did not yield differences in CART expansion or transduction, positively selected CART exhibited a significantly higher invitro interferon-γ and IL-2 secretion but a lower invitro tumor killing rate. Notably, though, CD22 CART generated from both selection protocols efficiently eradicated leukemia in NSG mice, with negatively selected cells exhibiting a significant enrichment in γδ CD22 CART. Thus, our study demonstrates the importance of the initial Tcell selection process in clinical CART manufacturing.

Adaptive detection of tool-workpiece contact for nanoscale tool setting based on multi-scale decomposition of force signal

Due to tool wear under long-time and long-distance cutting, it is inevitable to change the tool to achieve relay machining. However, the existing tool setting methods based on visual inspection and trial cutting have the problems of low precision and complicated process, resulting in low precision and poor consistency of surface quality in relay machining. In order to solve the above problems, this paper proposes a method to detect the contact status between the tool and the workpiece with the discrete wavelet transform (DWT) of force signal to realize the nanoscale tool setting. Firstly, a weighted smoothness evaluation metric is proposed to guide the selection of wavelet basis function and decomposition scale of DWT to achieve noise suppression and impact signal enhancement. Then, the force signal processed by DWT under the optimal parameters is input to density-based spatial clustering of applications with noise (DBSCAN) to detect the contact status between the tool and the workpiece. The parameters selection of DBSCAN is adaptively realized by differential evolution (DE) algorithm so as to improve the accuracy of the contact detection. Finally, ultra-precision tool setting experiments were carried out on the single-point diamond turning tools with a radius of 10um and workpieces with various materials such as brass, copper and red copper. The results show that the wavelet basis function and decomposition scale with the minimum value of the proposed metric are optimal for the task. In analysis of force signals with different signal-to-noise ratios (1 dB, 5 dB, 12.5 dB, 20 dB), the proposed metric all works well. In terms of the contact detection between the tool and workpiece, the proposed method achieves 0 % false positive rate compared to other detection methods, and the corresponding tool setting accuracy is about 3 nm, which is much higher than the traditional tool setting method.

Pain Scales: What Are They and What Do They Mean.

It is essential to have validated and reliable pain measurement tools that cover a wide range of areas and are tailored to individual patients to ensure effective pain management. The main objective of this review is to provide comprehensive information on commonly used pain scales and questionnaires, including their usefulness, intended purpose, applicability to different patient populations, and associated advantages and disadvantages. Acute pain questionnaires typically focus on measuring the severity of pain and the extent of relief achieved through interventions. Chronic pain questionnaires evaluate additional aspects such as pain-related functional limitations, psychological distress, and psychological well-being. The selection of an appropriate pain scale depends on the specific assessment objectives. Additionally, each pain scale has its strengths and limitations. Understanding the differences among these pain scales is essential for selecting the most appropriate tool tailored to individual patient needs in different settings. Medical professionals encounter challenges in accurately assessing pain. Physicians must be familiar with the different pain scales and their applicability to specific patient population.

A coupled approach for planning in vulnerable coastal landscapes

One of the most problematic steps in planning and management of vulnerable coastal systems under high level of uncertainties is anticipating potential design scenarios where multiple spatial scales interact. The mutual interference between beach morphodynamics and infrastructural needs of the wide territory poses several questions to urban planners and architects. In this study we assess the ability of the proposed coupled approach of MIKE 21 Spectral Wave and XBeach to significantly improve our understanding of vulnerable barrier beaches in urbanized areas, and hence to contribute to improved system design and management. Specifically, to improve the result accuracy and the time-computational efficiency of the proposed coupled approach, an additional module was developed. Located in the West Metropolitan Area of Cagliari city (Sardinia, IT), the barrier beach of La Playa is an important evacuation route that has experienced a coastal squeeze process under the increase in magnitude and frequency of sea storms. From an extensive beach survey, the “whole model composition” supports the selection of the territorial scale as the reference for defining a potential design scenario at the local scale in La Playa beach. While ordinary (10-year return time) storms create a nearshore sand berm with a protective function for the barrier beach and evacuation route against future storms, extreme (140-year return time) storms significantly erode the beach with a shoreline moving approximately 15 m landward and an overwash of Qcrest >20 l/m/s. Acting as a rigid impermeable obstacle against landward barrier migration, the evacuation route is destroyed. Urban planners and architects should consider the downgrade of the evacuation route as a part of a design potential scenario capable of minimizing the territorial vulnerability and reducing the local vulnerability. Rebuilt with environment-friendly functional road materials, this design scenario can also define a new flexible landward limit of the barrier beach and restore an eventual migration.

Landscape research: from paradigm through GIS technology to monitoring (on the example of the territory of the Slobozhansky National Nature Park)

For 10 years, a group of specialists from the department of physical geography and cartography has been exploring the territories of national parks consistently using information technology tools, improving their use in combination with ground test landscape surveys. This article reflects the experience of such scientific and applied development in relation to the territory of Slobozhansky National Nature Park. The purpose of this development is to improve the existing technologies of complex interpretation of geodata for the design and monitoring of the territory in their systematic combination with the methods of online mapping and in-depth meaningful interpretation for the scientific support of the organization of the territory and the administration of the national parks. This article covers currently known and possible scientific approaches and measures that rely on scientific and applied measures used by the national parks administration in management processes. The most recent issues highlighted in this article compared to the previous published works of the authors are the formulation of the trinity paradigm of the process of creating a landscape model of the territory. A set of individual tasks is defined, the consistent implementation of which ensures the achievement of the goal: selection of appropriate types, scales and optical ranges of remote sensing, taking into account the landscape conditions inherent in the location of the territory of the national park; development, on these grounds, of the technology of thematic landscape mapping, geoecological assessment and control of results on test areas of the terrain; peculiarities of drawing legends of applied landscape maps using GIS technologies; making corrections and additions to the existing defining documents of projects of the national park organization and developing recommendations for their improvement; design of the monitoring system of Slobozhansky National Nature Park. In the paradigm of applied landscape research, the national park should be designed based on the trinity of remote sensing and human intelligence: a) the technical level of providing remote sensing; b) taking into account the ambiguity of the optical image of the area depending on the purpose of geodata interpretation; c) tasks that are also solved ambiguously: the selection of certain ranges and scales of soundings, the selection of test areas and even the compilation of legends of a large-scale landscape map. The specified ambiguity is manifested in the variability of constructions and creates the subjectivity of applied landscape research. Methodological basis. The system-structural approach is manifested in the identification and identification of those spatial connections between visually significant and hidden from direct observation properties (mainly water-heat balance indicators) of the landscape, which change in an ambiguous dependence on regional background indicators, therefore must be taken into account in design and monitoring. Scientific results. In addition to theoretical generalizations, the article briefly presents the implementation of the highlighted approach in the study of landscapes of the Slobozhansky National Nature Park.

Prognostic factors and mortality predictive scale in patients treated with in-hospital extracorporeal cardiopulmonary resuscitation

Abstract Background Extracorporeal cardiopulmonary resuscitation (ECPR) is a rescue option in cardiac arrest (CA) refractory to advanced life support. Patient selection is challenging, evidence is limited and randomized studies are lacking regarding in-hospital CA. Purpose Our objective was the identification of factors associated with survival in in-hospital ECPR. Methods Retrospective analysis of consecutive cases of venoarterial extracorporeal membrane oxygenator (VA-ECMO) for ECPR indication in a referral center. The ECPR alert includes in-hospital cardiologist/intensivist, on-call interventional cardiologist/cardiac surgeon for cannulation, and on-call perfusionist. We analyzed baseline variables related to CA and ECPR technique and studied their relationship with in-hospital survival. Results Out of 207 VA-ECMO implants between 2014-feb 2023, we selected the ECPR cases: N=59 (28.5%). Baseline, admission and ECPR characteristics are collected in the table. ECMO-VA support intention was bridge to recovery in 68% of cases, transplant 5%, ventricular assist device 5% and decision 22%. The most frequent access was percutaneous femoro-femoral, and ECPR was unsuccessful (no flow, no rhythm, or impossibility of cannulation in 11.8% of cases). All patients underwent temperature control at 36ºC with ECMO. Overall in-hospital survival was 18.6% (n=11) (cerebral performance cathegory 1-2), and the most frequent causes of death were refractory shock/multiple organ failure (49%) and anoxic encephalopathy (25%). The patients who died were significantly younger, had peripheral vascular disease (PAD), higher creatinine, LDH and lactate levels, longer CA duration, and its ECMO implantation was more frequent during on-call hours (table). Lactate &amp;gt;10.05 predicted mortality (AUC 0.693, Sens 67,3%, Esp 80%). The time under VA-ECMO support and mechanical ventilation, and the use of adrenaline infusion were more frequent in the survivors (table). At multivariate analysis, a longer CA duration (HR 0.947, CI95% 0.900-0.977, p0,040) was the only factor independently associated with in-hospital mortality. We developed a predictive scale including factors related to survival (lactate &amp;gt;10.05, &amp;gt;60 minutes CA, PAD, on-call time) which predicted 100% with 3 or more factors (p&amp;lt;0.001) (figure 2). Conclusions In-hospital ECPR is an option for refractory cardiac arrest, with high mortality. CA duration was the only factor independently associated with in-hospital mortality. Three or more adverse factors (lactate &amp;gt;10.05, &amp;gt;60 minutes CA, PAD, on-call time) predicted 100% mortality. Randomized studies are needed to determine a better selection of patientsBaseline, admission and ECPRMortality predictive scale after ECPR

MANAJEMEN SARANA PRASARANA DALAM MENINGKATKAN MUTU PENDIDIKAN DI SDN SERANG 3

The background for this research was to see the condition of the school which was quite large for the elementary school level. The purpose of this research is to describe how the management of facilities and infrastructure in SDN Serang 3. The method used in this study is a qualitative method and data collection techniques by observation and interviews with related parties. The conclusion of this study is that based on the results of research related to the management of facilities and infrastructure in improving the quality of education at SDN Serang 3 it is good, all stages of management of facilities and infrastructure at SDN Serang 3 have been carried out starting from the planning, procurement, inventory, distribution, maintenance up to elimination and accountability. SDN Serang 3 at the planning stage, the team and the school principal have analyzed the school's needs such as what facilities and infrastructure are lacking and what facilities and infrastructure are needed. Schools use BOS funds effectively and efficiently. All facilities and infrastructure owned were purchased with BOS funds or assistance from the government. In the process of procuring facilities and infrastructure that was carried out at SDN Serang 3, a priority scale selection was carried out which prioritized facilities and infrastructure that really had to be expedited. Schools also carry out inventory properly and write off assets in accordance with applicable regulations and are accountable to the agency.

Multi-scale feature selection network for lightweight image super-resolution

Recently, many super-resolution (SR) methods based on convolutional neural networks (CNNs) have achieved superior performance by utilizing deep and heavy models, which may not be suitable for real-world low-budget devices. To address this issue, we propose a novel lightweight SR network called a multi-scale feature selection network (MFSN). As the basic building block of MFSN, the multi-scale feature selection block (MFSB) is presented to extract the rich multi-scale features from a coarse-to-fine receptive field level. For a better representation ability, a wide-activated residual unit is adopted in each branch of MFSB except the last one. In MFSB, the scale selection module (SSM) is designed to effectively fuse the features from two adjacent branches by adjusting receptive field sizes adaptively. Further, a comprehensive channel attention mechanism (CCAM) is integrated into SSM to learn the dynamic selection weight by considering the local and global inter-channel dependencies. Extensive experimental results illustrate that the proposed MFSN is superior to other lightweight methods.

Pain assessment & management decision-making in pediatric critical care

PurposeThe aim of this study was to explore how nurses in the Pediatric Intensive Care Unit (PICU) reach their pain management decisions in children who are mechanically ventilated and chemically paralyzed. Design and methodsA qualitative descriptive design was used following a quantitative phase of a multi-method study. Eighteen PICU nurses participated in semi-structured interviews aiming at understanding how they assess pain and make management decisions. Content analysis was used to guide coding and generate themes. ResultsThree major themes were identified: 1) Assessment or cues that nurses use to trigger a pain assessment; 2) Mental models or patterns that nurses create to interpret cues to guide decision-making; 3) External factors that inhibit or facilitate decision-making. Overall, nurses rely on physiological cues to assess pain. From there, a large amount of variation exists on how nurses interpret those cues to make their pain management decision. External factors such as unit culture, perceived barriers and facilitators, and the nurse's experiences impacted how decisions are made. ConclusionsVariation exists in the mental models' nurses create to make their pain management decision in this population. Nurses reported confusion on pain and sedation scale selection and various documentation practices for pain assessment. “Assume pain present” was identified as a concept and documentation practice that may guide decisions; further research is needed. Practice implicationsDevelopment of clinician decision support tools that not only aid their understanding of reliable pain cues but also help create clear documentation practices may help nurses make pain management decisions.

Effects of temperature heterogeneity on freshwater turtle habitat selection at their northern range limit

Environmental temperature is a crucial resource for ectotherms, affecting their physiology, behaviour and fitness. To maintain body temperatures within a suitable performance range, ectotherms select thermally-favourable locations, but this selection may be challenging in environments with high spatio-temporal heterogeneity. We assessed thermal habitat selection in two freshwater turtles (Emydoidea blandingii; Chrysemys picta) within a thermally heterogeneous environment at two spatial scales (selection of home ranges within the landscape, selection of locations within home ranges) and across seasons, by comparing temperatures at turtle locations vs. those available in the environment. Turtles selected warmer locations compared to those available in aquatic and terrestrial habitats only within home ranges, but did not show any temperature preferences when selecting home ranges at the larger scale. Turtles selected locations that were less thermally-variable than their surroundings, both at the home range scale and within home ranges. Thermal habitat selection was strongest during colder and more thermally-variable pre-nesting season compared to later periods. Despite differences in thermal mass between species, both species responded similarly to temperature variation. We conclude that freshwater turtles at their northern range margin select suitable microclimates within the suite of conditions that are naturally available.

Strain regularisation using a non-local method in Coupled Eulerian-Lagrangian analyses

Conventional finite element analyses generally suffer from mesh dependency when considering softening effects. Non-local strain regularisation techniques have been developed to address this issue, which are generally complex to implement. In view of this, this paper introduces an more efficient procedure for implementation of a non-local method in Abaqus for Coupled Eulerian-Lagrangian (CEL) large deformation finite element undrained analyses. Results from a series of biaxial compression simulations demonstrate that the non-local method with a strain-softening Tresca model in CEL avoids mesh dependency. Owing to the stationary Eulerian element and the built-in mapping algorithm in CEL, high computational efficiency is achieved, adding no more than 12% to the computational cost. Guidance is provided on selection of internal length scales, element sizes and the search radius to ensure efficient non-local calculations, and it is shown that a softening scaling rule can also be used to allow use of practical mesh densities for some boundary value problems. Simulations of a number of classical geotechnical problems demonstrate the type of boundary value problems where the non-local method can effectively mitigate the mesh dependency, whilst also highlighting that the method fails to control the strain localisation that develops at soil-structure interfaces due to geometrical issues.

Identification of Important Factors When Measuring School Climate: Latent Construct Validation and Exploration.

Researchers regularly must decide what information is necessary to understand school climate and how to include climate in a study. For example, which factors and/or scales should be used, is using just 1 scale for school climate sufficient, and to what extent does the selection of a single scale influence the research findings? Understanding what factors to consider and which available scales to review will assist those interested in measuring school climate. This study explores 8 validated scales related to school climate. Data used are from a previous study (Social and Character Development cooperative agreement funded by IES #R305L030072 and #R305A080253) that looked at Positive Action, a social emotional and character development program for elementary-, middle-, and high-school students. Scale correlations and factor analyses show how these scales work together to measure overall middle school climate.