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The Trial Innovation Network has established an infrastructure for single IRB review in response to federal policies. The Network’s single IRB (sIRBs) have successfully supported over 70 multisite studies via more than 800 reliance arrangements. This has generated several lessons learned that can benefit the national clinical research enterprise, as we work to improve the conduct of clinical trials. These lessons include distinguishing the roles of the single IRB from institutional Human Research Protections programs, establishing a consistent sIRB review model, standardizing collection of local context and supplemental, study-specific information, and educating and empowering lead study teams to support their sites.

This is a project report to introduce the Comprehensive Sexuality Education Technical Guideline—Adaptation of Global Standards for Potential Use in China (First Edition) (hereafter referred to as the Guideline) as the first adaptation of the International Technical Guidance on Sexuality Education (ITGSE) in China. The project was supported by the United Nations Population Fund (UNFPA) and the United Nations Educational, Scientific and Cultural Organization (UNESCO) from 2018 to 2022. The development process included rounds of participatory consultation, validation, and revisions led by the project team and a group of technical advisers from diverse backgrounds. The Guideline is developed to respond to the increasing demands of a technical tool integrating international standards and local context that can be used by all comprehensive sexuality education (CSE) stakeholders in China. While keeping the structure of the ITGSE, the Guideline made modifications and additions in light of the up-to-date Chinese policies, laws, and relevant national programs, as well as Chinese culture and social norms. It is expected that the Guideline could be widely acknowledged, distributed, and used to inform and support the future development of CSE in China.

Aspect-based sentiment analysis is a fine-grained sentiment analysis task that consists of two types of subtasks: aspect term extraction and aspect sentiment classification. In the aspect term extraction task, current methods suffer from the lack of fine-grained information in aspect term extraction and difficulty in identifying aspect term boundaries. In the aspect sentiment classification task, the current aspect sentiment classifier cannot adapt itself to the text and determine the local context. To address these two challenges, this work proposes an adaptive semantic relative distance approach based on dependent syntactic analysis, which uses adaptive semantic relative distance to determine the appropriate local context for each text and increase the accuracy of sentiment analysis. Meanwhile, the study also predicts the current word labels by combining local information features extracted by local convolutional neural networks and global information features to precisely locate the word labels. In two subtasks, our proposed model improves accuracy and F1 scores on the SemEval-2014 Task 4 Restaurant and Laptop datasets compared to the state-to-the-art approaches, especially in the aspect sentiment classification subtask.

Extracting global and local feature information is still challenging due to the problems of retinal blood vessel medical images like fuzzy edge features, noise, difficulty in distinguishing between lesion regions and background information, and loss of low-level feature information, which leads to insufficient extraction of feature information. To better solve these problems and fully extract the global and local feature information of the image, we propose a novel transscale cascade layered transformer network for enhanced retinal blood vessel segmentation, which consists of an encoder and a decoder and is connected between the encoder and decoder by a transscale transformer cascade module. Among them, the encoder consists of a local-global transscale transformer module, a multi-head layered transscale adaptive embedding module, and a local context(LCNet) module. The transscale transformer cascade module learns local and global feature information from the first three layers of the encoder, and multi-scale dependent features, fuses the hierarchical feature information from the skip connection block and the channel-token interaction fusion block, respectively, and inputs it to the decoder. The decoder includes a decoding module for the local context network and a transscale position transformer module to input the local and global feature information extracted from the encoder with retained key position information into the decoding module and the position embedding transformer module for recovery and output of the prediction results that are consistent with the input feature information. In addition, we propose an improved cross-entropy loss function based on the difference between the deterministic observation samples and the prediction results with the deviation distance, which is validated on the DRIVE and STARE datasets combined with the proposed network model based on the dual transformer structure in this paper, and the segmentation accuracies are 97.26% and 97.87%, respectively. Compared with other state-of-the-art networks, the results show that the proposed network model has a significant competitive advantage in improving the segmentation performance of retinal blood vessel images., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Head detection is a fundamental task, and it plays an important role in many head-related problems. The difficulty in creating the local and global context in the face of significant lighting, orientation, and occlusion uncertainty, among other factors, still makes this task a remarkable challenge. To tackle these problems, this paper proposes an effective detector, the Context Refinement Network (CRN), that captures not only the refined global context but also the enhanced local context. We use simplified non-local (SNL) blocks at hierarchical features, which can successfully establish long-range dependencies between heads to improve the capability of building the global context. We suggest a multi-scale dilated convolutional module for the local context surrounding heads that extracts local context from various head characteristics. In comparison to other models, our method outperforms them on the Brainwash and the HollywoodHeads datasets.

Robotic grasp in complex open-world scenarios requires an effective and generalizable perception. Estimating object’s pose is needed in a variety of practical grasping scenarios. Here we present a novel approach of pose estimation of textureless and textured objects. The algorithm utilizes a single RGB-D image to exploit depth invariant, oriented point pair feature as well as local contextual sensitivity in cluttered environments. To enhance the performance of the voting process and improve learning efficiency, we employ a global pruning algorithm that reduces the risk of overfitting and simplifies the structure of decision trees after compensating for the complementary information among multiple trees by optimizing a designed global objective function. Finally, we also refine the pose obtained from the above stage. The proposed approach of estimating 6-D (degree of freedom) poses of textured and textureless objects is evaluated on publicly available data sets against the recent works under various conditions. It illustrates that our framework is superior to these recent works. Further, we perform extensive qualitative experiments of robotic grasp to illustrate the proposed approach can be applied to practical scenarios. Note to Practitioners—This article is motivated by the problem of the pose estimation of textured and textureless objects in clutter environments. It is difficult for conventional works to address the issue of estimating textured or textureless objects’ poses in such scenarios. We considered that a novel system should be able to obtain the 6-D poses of objects. Therefore, we investigate the combined use of multiple split functions with different characteristics. Learning the model based on Hough forests always cost much computational resource; therefore, we construct a novel pruned Hough forest for solving this issue. Through the comparison and robotic grasp verifications, the behavior of our system can be used in practical applications. In future, we will deploy the proposed system in robotic assembling tasks. [ABSTRACT FROM AUTHOR]

Background: The implementation of certification procedures across healthcare systems is an essential component of the management process. Several promising approaches were developed toward a successful implementation of such policies; however, a precise adaptation and implementation to each local context was essential. Local activities must be considered in order to generate more pragmatic recommendations for managers. In this study, we built a framework for the implementation of certification procedures at nurse activity level. This was developed using two objectives: the identification of key implementation process components, and the integration of these components into a framework which considered the local socio-material context of nurses' work.Methods: We used a two-step mixed approach. The first was inductive and consisted of a qualitative case study conducted between April and December 2019. Here, we analyzed the implementation of certification procedures in a French teaching hospital. Data were collected using semi-structured interviews and observations. In the second approach, emerging data were deductively analyzed using the Quality Implementation Tool (QIT) and Translational Mobilization Theory (TMT). Analyses were combined to construct an implementation framework.Results: Sixteen interviews were conducted with participants from different organizational levels, managers, mid-managers, and nurses. Additionally, 83 observational hours were carried out in two different wards. Our results showed that, (1) All retrieved elements during the process were successfully captured by the QIT components, only one component was not applicable. (2) We identified elements related to the local activity context, with the different interrelationships between actors, actions, and contexts using the TMT. (3) Our analyses were integrated and translated into a framework that presents the implementation of certification procedures in healthcare facilities, with a specific interest to the nurse/mid-manager level. By initially using QIT, the framework components took on a transversal aspect which were then adapted by TMT to the local work context.Conclusions: We successfully generated a framework that supports the implementation of certification procedures at the activity level. Our approach identified a broader vision of the interactions between proximity managers, teams, and contexts during change mobilization, which were not encompassed by transversal framework only, such as QIT. In the future, more empirical studies are needed to test this framework. [ABSTRACT FROM AUTHOR]

National labor unions in the United States have formally supported undocumented immigrants since 2000. However, drawing on 69 interviews conducted between 2012 and 2016 with union and immigrant rights leaders, this article offers a locally grounded account of how union solidarity with undocumented immigrants has varied notably across the country. We explore how unions in San Francisco and Houston have engaged with Obama-era immigration initiatives that provided historic relief to some undocumented immigrants. We find that San Francisco's progressive political context and dense infrastructure of immigrant organizations have enabled the city's historically powerful unions to build deep institutional solidarity with immigrant communities during the Deferred Action for Childhood Arrivals (DACA [2012]) and Deferred Action for Parents of Americans (DAPA [2014]) programs. Meanwhile, Houston's politically divided context and much sparser infrastructure of immigrant organizations made it necessary for the city's historically weaker unions to build solidarity with immigrant communities through more disparate channels. [ABSTRACT FROM AUTHOR]

Forest disturbances caused by insects, pathogens, and fire continue to increasingly occur within forests across the United States and around the world. Given the dynamic nature of these forest disturbances and the role played by local residents in risk management, it is valuable to explore how the human experience, attitudes, and behaviors associated with these ecological processes may evolve over time. In this paper, we assess temporal changes in local residents' perceptions and actions in response to the mountain pine beetle outbreak that affected large swaths of forests in north central Colorado. Through analyses of secondary and household survey data from 2007 and 2018, we note significant changes in these aspects and identify factors consistently associated with individual and community activeness. The study contributes to knowledge of dynamic socioecological considerations of forest disturbances and improves understanding of how social sciences can help to identify opportunities and barriers to effective forest ecosystem management. [ABSTRACT FROM AUTHOR]

Globalization, digital technologies, societal and environmental concerns influence the way family firms operate locally and internationally. Family firms are often torn between their local and global environments, simultaneously visible and embedded in their local environment while marketing their products and services abroad. Unlike large multinationals that have often lost their roots, family firms manifest an active interest in maintaining their local roots and traditions. Moreover, increasing concerns with sustainable development call for continuity through sustainability aimed at improving local and global socioeconomic conditions. This editorial of the special issue on 'Locality and Internationalization of Family Firms' discusses this tension that family firms face and how they can build bridges between communities increasingly drifting apart. By bridging local and global environments, family firms can contribute to the sustainable development of society. We present a research agenda addressing this particular bridging function of family firms and propose several avenues for future research. [ABSTRACT FROM AUTHOR]

This paper explores the interaction and interdependence between family firms and sparsely populated regions. Interactivity underlines the dynamics of the setting and how it changes based on activities between the firm and the context, whereas interdependence refers to how the family firm and the region become mutually reliant on one another. Five case studies show that while the firms act under similar conditions in terms of disparity, their interplay with and dependence on the region differ. The study points to how the citizenship of the family firms is fundamental and how employment is at the heart of the interdependence, while those firms interacting most strongly with the region are those expanding beyond what would be expected by a family firm in terms of traditions and risk aversion. This again indicates a complex pattern of interactivities and interdependencies between family firms and sparsely populated regions. The paper provides important dimensions to theories on family firms' local contexts specifically related to under-researched settings of sparsely populated regions and important implications for managers, public actors and policy makers, not the least related to support to such contexts. [ABSTRACT FROM AUTHOR]

Assuming fertility variations across urban–rural gradients, our study focuses on the traditional polarization in urban and rural fertility, offering a refined interpretation of demographic processes associated with population density. More specifically, we tested the intimate relationship between local fertility and population density, comparing the outcomes of a classical urban–rural model (reflecting a linear relationship between the two variables) with those of a more complex quadratic model (implying the so-called ‘suburban fertility hypothesis’) in Greece. We considered fertility dynamics in three districts (urban, suburban, and rural) of 51 Greek prefectures for the last two decades (2000–2009 and 2010–2019) and controlled for the diverging impact of local contexts at different population density levels. Taken as a measure of ‘maturity’ of regional systems, urban fertility surpassed rural fertility in almost all prefectures of Greece. An additional sign of maturity in metropolitan systems indicates that suburban birth rates are higher than urban birth rates in prefectures with high population density (Athens, Thessaloniki, Heraklion, and Patras). The regression outcomes document a specific response of fertility to regional development, evidencing a spatially differentiated shift from classical urban–rural disparities toward a more complex model with the emergence of suburban poles. From this perspective, fertility divides reflect the evolutions of socioeconomic forces (more or less rapidly) along the urban gradient.

Background: The purpose of this study is to analyse what factors that explain individual differences in walking and cycling when commuting in different parts of Sweden. Walking and cycling is potentially accessible all over the country, while well developed public transport is mainly a viable option in densely populated areas. Methodology: The importance of differences in local characteristics for the choice of transport mode will be scrutinised, together with individual differences in attitudes andpreferences. Data is collected through a survey sent to people living in five Swedish municipalities with different demographic, socio-economic ,infrastructural and geographical characteristics. Results: The results for the pooled sample indicate that the choice to walk/cycle when commuting is related to health considerations and environmental concerns. Distance to work/school is also an important factor. Men tend to be more prone to choose active transport, and so do respondents with lower income. The results further reveal that availability of safe routes for walking and cycling are important for the choice to walk/cycle when commuting. As health considerations are important, we suggest policy makers to stress health motives when they promote walking and cycling in the future. Our results further suggest that it is important to consider availability and accessibility in community planning, and to prioritize safety and comfort of walking and cycling, not least in parts of the country where public transport is not an economically viable option. [ABSTRACT FROM AUTHOR]

Background: While the Veterans Health Administration (VHA) MOVE! weight management program is effective in helping patients lose weight and is available at every VHA medical center across the United States, reaching patients to engage them in treatment remains a challenge. Facility-based MOVE! programs vary in structures, processes of programming, and levels of reach, with no single factor explaining variation in reach. Configurational analysis, based on Boolean algebra and set theory, represents a mathematical approach to data analysis well-suited for discerning how conditions interact and identifying multiple pathways leading to the same outcome. We applied configurational analysis to identify facility-level obesity treatment program arrangements that directly linked to higher reach.Methods: A national survey was fielded in March 2017 to elicit information about more than 75 different components of obesity treatment programming in all VHA medical centers. This survey data was linked to reach scores available through administrative data. Reach scores were calculated by dividing the total number of Veterans who are candidates for obesity treatment by the number of "new" MOVE! visits in 2017 for each program and then multiplied by 1000. Programs with the top 40 % highest reach scores (n = 51) were compared to those in the lowest 40 % (n = 51). Configurational analysis was applied to identify specific combinations of conditions linked to reach rates.Results: One hundred twenty-seven MOVE! program representatives responded to the survey and had complete reach data. The final solution consisted of 5 distinct pathways comprising combinations of program components related to pharmacotherapy, bariatric surgery, and comprehensive lifestyle intervention; 3 of the 5 pathways depended on the size/complexity of medical center. The 5 pathways explained 78 % (40/51) of the facilities in the higher-reach group with 85 % consistency (40/47).Conclusions: Specific combinations of facility-level conditions identified through configurational analysis uniquely distinguished facilities with higher reach from those with lower reach. Solutions demonstrated the importance of how local context plus specific program components linked together to account for a key implementation outcome. These findings will guide system recommendations about optimal program structures to maximize reach to patients who would benefit from obesity treatment such as the MOVE!Program: [ABSTRACT FROM AUTHOR]

The article contributes to understanding the political economy of implementation of social protection programmes at local level. Current debates are dominated by technocratic arguments, emphasizing the lack of financial resources, technology or skills as major barriers for effective implementation. Describing how chiefs, assistant-chiefs and community elders are routinely at the centre stage of core implementation processes, including targeting, enrolment, delivery, monitoring, awareness and information, data collection or grievance and redress, this study on Kenya argues for the need to look more closely into the local political economy as an important mediating arena for implementing social policies. Implementation is heavily contingent upon the local social, political and institutional context that influences and shapes its outcomes. These processes are ambivalent involving multiple forms of interactions between 'formal' and 'informal' institutional structures, which may support initial policy objectives or induce policy outcomes substantially diverging from intended policy objectives. [ABSTRACT FROM AUTHOR]

While marital age is the highest worldwide, spatial disparities still exist among European regions. Although Mediterranean societies were traditionally characterized by high propensity to marriage, mean age at marriage in recent times has converged to particularly high levels typical of Western and Northern Europe. Since a spatially explicit analysis of nuptiality patterns is relatively scarce for Southern European countries, the present study investigates marriage timing in 51 Greek prefectures, assuming changes in the local context as a factor leading to marriage postponement. A positive trend in the age at marriage was observed in Greek prefectures between 1980 and 2017. While differences in the mean age at marriage diverged substantially between rural areas and urban contexts in the early 1980s, social factors leading to differentiated patterns of marriage postponement caused a greater spatial heterogeneity in marriage timing in more recent times. Results of this study outline the importance of local contexts shaping social attitudes and behaviors toward marriage. Increasingly complex demographic processes were observed along the urban–rural gradient, whose investigation requires more integrated approaches focusing on population patterns at both micro- and macro-scale. [ABSTRACT FROM AUTHOR]

The aim of the study is to explore the links that firms from low and medium technology (LMT) industries establish with universities for innovative purposes. Even though knowledge transfer from university to industry has generally increased over time, it has mostly been directed at firms in high-tech industries (HT) due to the belief that firms from LMT industries often lack the absorptive capacity necessary to take advantage of external knowledge. In the case of LMT industries, university-industry knowledge transfer has received less attention from management and innovation studies, and understanding the specific conditions where universities may contribute to the innovative effort of LMT firms largely remains unexplored. With the aim of contributing to this debate, the paper focuses on the wine sector, generally considered an LMT industry. Firstly, the study assesses to which type of innovation promoted by winemakers do universities effectively contribute. Secondly, the study examines under what conditions universities assume a relevant role in the innovative activity of LMT firms. To test our hypotheses, the study uses primary data collected through a survey targeting Italian wine SMEs and runs a set of econometric evaluations. Findings show that universities represent a relevant source of knowledge mainly for organizational and commercial innovation, but not for product innovation. For these purposes, university knowledge related to social sciences has a more relevant input for firms than does knowledge with higher scientific and technological content. [ABSTRACT FROM AUTHOR]

Copyright of Journal Public Administration & Social Management / Administração Pública e Gestão Social is the property of Administracao Publica e Gestao Social and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Intus-Legere Historia is the property of Intus-Legere Historia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Background Implementation of new programs within healthcare systems can be extraordinarily complex. Individuals within the same healthcare organization often have different perspectives on how implementation of a new program unfolds over time, and it is not always clear in the midst of implementation what issues are most important or how to address them. An implementation support team within the Veterans Health Administration (VHA) sought to develop an efficient method for eliciting an ongoing, detailed and nuanced account of implementation progress from multiple viewpoints that could support and inform active implementation of two new VHA programs. Methods The new Prospectively-Reported Implementation Update and Score (“PRIUS”) provided a quick, structured, prospective and open-ended method for individuals to report on implementation progress. PRIUS updates were submitted approximately twice a month. Responding to the prompt “What are some things that happened over the past two weeks that seem relevant from your perspective to the implementation of this project?”, individuals scored each update with a number ranging from + 3 to − 3. Results In 2016–17, individuals submitted over 600 PRIUS updates across the two QI projects. PRIUS-based findings included that staff from different services reported fundamentally different perspectives on program implementation. Rapid analysis and reporting of the PRIUS data led directly to changes in implementation. Conclusions The PRIUS provided an efficient, structured method for developing a granular and context-sensitive account of implementation progress. The approach appears to be highly adaptable to a wide range of settings and interventions.

Empirical research has long shown positive connections between urban green spaces and their users' wellbeing. But compelling evidence does not always lead to appropriate investment. In a study of the contribution of urban nature to mental wellbeing in Sheffield, UK, the authors identified greenspace investments that could lead to improved wellbeing and discussed their implementation with local stakeholders. However, this qualitative study also revealed a series of reasons why stakeholders in Sheffield would not proceed with such investments. Using the concept of 'logics of inaction' to examine stakeholders' reasoning, this paper considers why such logics arise. It finds a mismatch between available evidence and the evidence practitioners say they need to justify investments. One consequence is that practitioners' capacity to act on new knowledge is reduced, limiting innovation and potential benefits. [ABSTRACT FROM AUTHOR]

How does local demographic context shape political behavior? We investigate how racial isolation, one of the natural consequences of structural segregation, is related to racial voting in South Africa. Using a variety of new datasets, which include for the first time high resolution census data from before the end of apartheid, we leverage plausibly exogenous variation in the extent to which local segregation persisted after the end of apartheid to study this relationship. Whites who are more isolated engage in more racial voting, measured as the probability of voting along racial lines, against black political parties. Using geo-referenced survey data for over 39,000 people we then present individual level evidence consistent with our findings, and discuss potential mechanisms. [ABSTRACT FROM AUTHOR]

The link between the management of uncertainty and knowledge creation is the core element behind firm survival, as these two factors are critical for true innovation. This article links the survival of highly innovative firms to their knowledge creation and application in the context of two types of uncertainty management: (i) the individual firm's ability to handle uncertainty; (ii) the aggregate local "neuroticism" in facing uncertainty that characterizes the geographic location where the firm operates. The study is inspired by Audretsch and Dohse's model of firm growth and geographic location. We augment this model with George Shackle's potential surprise function for handling individual uncertainty. Additionally, we extend the model by also considering the psychological profile of localities, in particular their level of neuroticism according to the so-called Big Five taxonomy. Using data for the highly innovative Cambridge Region (UK) for the period 2010–2014, we find that, on individual level, the daring companies survive less frequently, but appear to live longer if they manage to survive. Survival also appears to be influenced by locational characteristics related to the local level of neuroticism. In particular, being located in a place with higher neuroticism is associated with lower survival rates. [ABSTRACT FROM AUTHOR]

The paper deals with the different contextual factors that may influence the speaker's stylistic choices. The perspective taken follows (Kovecses, 2015) who looks at contextual components as frames that are nested in one another: the physical setting as the outermost frame, which includes the social frame that contains the cultural frame and so on, and the innermost frame where we find the speaker, the hearer and the topic The topic under analysis is climate change communication, more precisely the British Prime Minister's address at the conference known as COP26 (Conference of the Parties, the 26th edition), hosted at Glasgow, at the beginning of November, 2021. [ABSTRACT FROM AUTHOR]

This study deals with actual trends and developments in the research of community interpreting in the global, but also in local context. In the general introduction we try to define the term community interpreting according to the latest trends in this field. Our goal is to set some basic features, which can help to create a universal definition of the actual content of the term community interpreting. In the next part we concentrate on the development in the world and try to analyse the most significant research projects in the field. Finally, we show a short overview of the most important initiatives in the local context en introduce our own starting research, which will be focussed on the analysis of the actual state of community interpreting in Slovakia.

Capacity development for disaster risk reduction is considered an important approach emphasized in the Sendai Framework for Disaster Risk Reduction 2015–2030. However, questions regarding progress and an effective approach remain. The purpose of this paper is, through a study in Sri Lanka, to identify the capacity development for disaster risk reduction by analyzing related strategies and methodologies for the development to occur. A capacity development project was taken as a case study in which 6709 people in disaster-affected areas in the southern, northern, and eastern areas of Sri Lanka were targeted. The primary data analysis used the results of the questionnaire survey comprising quantitative and qualitative questions to assess the training. The overall results indicate a positive response to the training, as the training themes matched the local people's needs and concerns. The indicators of overall evaluation and understanding knowledge scored higher compared to the relevance/application of the training scores. The psychosocial trainings were positively scored in all districts except one area, where war-affected people need special care. In addition, the participants valued the first aid training because of the high practicality thereof in their daily lives, and mixing soft and hard components in the training. The greater flexibility and adaptability are essential in the process of implementation.

Abstract Background Protein secondary structure is the three dimensional form of local segments of proteins and its prediction is an important problem in protein tertiary structure prediction. Developing computational approaches for protein secondary structure prediction is becoming increasingly urgent. Results We present a novel deep learning based model, referred to as CNNH_PSS, by using multi-scale CNN with highway. In CNNH_PSS, any two neighbor convolutional layers have a highway to deliver information from current layer to the output of the next one to keep local contexts. As lower layers extract local context while higher layers extract long-range interdependencies, the highways between neighbor layers allow CNNH_PSS to have ability to extract both local contexts and long-range interdependencies. We evaluate CNNH_PSS on two commonly used datasets: CB6133 and CB513. CNNH_PSS outperforms the multi-scale CNN without highway by at least 0.010 Q8 accuracy and also performs better than CNF, DeepCNF and SSpro8, which cannot extract long-range interdependencies, by at least 0.020 Q8 accuracy, demonstrating that both local contexts and long-range interdependencies are indeed useful for prediction. Furthermore, CNNH_PSS also performs better than GSM and DCRNN which need extra complex model to extract long-range interdependencies. It demonstrates that CNNH_PSS not only cost less computer resource, but also achieves better predicting performance. Conclusion CNNH_PSS have ability to extracts both local contexts and long-range interdependencies by combing multi-scale CNN and highway network. The evaluations on common datasets and comparisons with state-of-the-art methods indicate that CNNH_PSS is an useful and efficient tool for protein secondary structure prediction.

Abstract Background Proper implementation of evidence-based interventions is necessary for their full impact to be realized. However, the majority of research to date has overlooked facilitators and barriers existing outside the boundaries of the implementing organization(s). Better understanding and measurement of the external implementation context would be particularly beneficial in light of complex health interventions that extend into and interact with the larger environment they are embedded within. We conducted a integrative systematic literature review to identify external context constructs likely to impact implementation of complex evidence-based interventions. Methods The review process was iterative due to our goal to inductively develop the identified constructs. Data collection occurred in four primary stages: (1) an initial set of key literature across disciplines was identified and used to inform (2) journal and (3) author searches that, in turn, informed the design of the final (4) database search. Additionally, (5) we conducted citation searches of relevant literature reviews identified in each stage. We carried out an inductive thematic content analysis with the goal of developing homogenous, well-defined, and mutually exclusive categories. Results We identified eight external context constructs: (1) professional influences, (2) political support, (3) social climate, (4) local infrastructure, (5) policy and legal climate, (6) relational climate, (7) target population, and (8) funding and economic climate. Conclusions This is the first study to our knowledge to use a systematic review process to identify empirically observed external context factors documented to impact implementation. Comparison with four widely-utilized implementation frameworks supports the exhaustiveness of our review process. Future work should focus on the development of more stringent operationalization and measurement of these external constructs.

How do the economic effects of immigration affect radical right support? The evidence in support of the labour market competition theory — which posits that the economic threat posed by immigration to jobs and wages leads to radical right voting — has been mixed. On the one hand, individual‐level surveys underreport economic drivers because of social desirability bias. On the other hand, contextual studies show contradictory findings due to an over‐reliance on units of analysis that are too aggregated to meaningfully capture the competitive threat posed by immigrants. This paper identifies the influence of labour market competition on radical right voting at a local level in contexts where native workers are directly affected by the arrival of immigrants who have similar or higher skillsets. Using an original longitudinal dataset of fine‐grained municipal electoral, demographic and economic data from France over the 2002–2017 period, the paper provides empirical evidence of local contextual influences of economic competition between natives and immigrants of any skillset. Under local conditions of material deprivation, measured by the local unemployment rate, the effect of labour market competition on municipalities' radical right vote share is amplified. Moreover, higher radical right support is observed in municipalities with a higher share of any one of the following groups: low‐skilled natives, medium‐skilled immigrants or high‐skilled immigrants. This supports the hypothesis that immigrants with higher qualifications are compelled to accept lower‐skilled jobs, and are thus perceived as a competitive threat to low‐skilled natives. By reconciling radical right contextual studies and research on the political economy of immigration policies, this paper highlights the importance of a local analysis in detecting the effect of labour market competition on radical right support. This paper also explains why some local areas are more prone to radical right support than others over time. [ABSTRACT FROM AUTHOR]

Immigration, economic hardship, and the European Union (EU) are typically emphasized as key concerns for the electorates of European populist radical right (PRR) parties. At the subnational level, however, these parties perform increasingly well in areas relatively unaffected by ethnic diversity, postindustrial economic decline, or transnationalism. What explains this paradox? Through a novel longitudinal analysis of rich municipal electoral, economic, and demographic data from Finland, this study uncovers the conditions under which immigration, economic hardship, and EU transfers influence support for the PRR. Although levels of ethnic diversity or economic hardship poorly predict support for these parties, they find fertile ground in areas undergoing rapid ethnic changes or economic decline. Growing reliance on EU funds, in contrast, decreases their anti-EU appeals. Thus, by clearly differentiating structural conditions from cyclical effects, this study helps reconcile rival theoretical perspectives on social contact and receptiveness toward immigrants and debates over the economy's effects on these parties' performance. [ABSTRACT FROM AUTHOR]

Topic modeling is an active research field due to its broad applications such as information retrieval, opinion extraction and authorship identification. It aims to discover topic structures from a collection of documents. Significant progress have been made by the latent dirichlet allocation (LDA) and its variants. However, the "bag-of-words" assumption is usually made for the whole document by conventional methods, which ignores the semantics of local context that play crucial roles in topic modeling and document understanding. In this paper, we propose a novel coordinated embedding topic model (CETM), which incorporates spectral decomposition and clustering technique by leveraging both global and local context information to discover topics. In particular, CETM learns coordinated embeddings by using spectral decomposition, capturing the word semantic relations effectively. To infer the topic distribution, we employ a clustering algorithm to capture semantic centroids of coordinated embeddings and derive a fast algorithm to obtain the topic structures. We conduct extensive experiments on three real-world datasets to evaluate the effectiveness of CETM. Quantitatively, compared to state-of-the-art topic modeling approaches, CETM achieves significantly better performance in terms of topic coherence and text classification. Qualitatively, CETM is able to learn more coherent topics and more accurate word distributions for each topic. [ABSTRACT FROM AUTHOR]

Existing saliency models typically incorporate contexts holistically. However, for each pixel, usually only part of its context region contributes to saliency prediction, while other parts are likely either noise or distractions. In this paper, we propose a novel pixel-wise contextual attention network (PiCANet) to selectively attend to informative context locations at each pixel. The proposed PiCANet generates an attention map over the contextual region of each pixel and construct attentive contextual features via selectively incorporating the features of useful context locations. We present three formulations of the PiCANet via embedding the pixel-wise contextual attention mechanism into the pooling and convolution operations with attending to global or local contexts. All the three models are fully differentiable and can be integrated with convolutional neural networks with joint training. In this work, we introduce the proposed PiCANets into a U-Net model for salient object detection. The generated global and local attention maps can learn to incorporate global contrast and regional smoothness, which help localize and highlight salient objects more accurately and uniformly. Experimental results show that the proposed PiCANets perform effectively for saliency detection against the state-of-the-art methods. Furthermore, we demonstrate the effectiveness and generalization ability of the PiCANets on semantic segmentation and object detection with improved performance. [ABSTRACT FROM AUTHOR]

Edge detection plays an important role in many computer vision systems. In this paper, we propose a novel application agnostic algorithm for prediction of probabilities based on the contextual information available and then apply the algorithm for estimating the probability of pixels belonging to an edge using surrounding pixel values as local contexts. We then proceed to test different image transformations as input layers, such as the Canny edge detector. We propose two different architectures, one single layered and one multilayered, which approach the scaling problem by creating scaled side outputs and combining them via a logistic regression layer. We tested our approach on the BSDS500 edge detection dataset with optimistic results. [ABSTRACT FROM AUTHOR]

Payment for ecosystem services (PES) is the main economic instrument developed for natural resource conservation. Evidence has shown the importance of local context in PES design and implementation and the complexity of defining and specifying that context. Using the socio-ecological systems framework, through surveys and interviews conducted in San Antonio, an indigenous community in Mexico with a forest socio-ecological system, this paper analyzes 13 variables as a way to approximate local context. The results show that the main contextual variables are forest cover, opportunity costs, livelihood, income, motivations and attitudes toward conservation, confidence and cooperation, traditional management practices, internal organization, land tenure, rules for the management and use of natural resources, presence and history of non-governmental organizations, economic and conservation history and distance to markets. In addition, the analysis of local context and PES outcomes in San Antonio leads us to conclude that a close relationship exists between the local context variables and the variables defined as causes of the PES outcomes. [ABSTRACT FROM AUTHOR]

This article draws on insights from disaster anthropology and medical anthropology, using examples from community-based research after Post-Tropical Cyclone Sandy on Staten Island, and after Hurricanes Irma and Maria in Puerto Rico, illustrating how lack of cultural knowledge and contextual "not seeing" hampers both emergency response and longer term recovery efforts. Using these two distinct examples, it reveals underlying biases within the culture of emergency management that hamper agency effectiveness. It then makes recommendations as to how emergency management personnel can work to overcome these biases, and quickly obtain and incorporate previously unfamiliar information about local context. Building equitable partnerships with local organizations and networks will better support disaster preparedness, emergency response, and recovery efforts. [ABSTRACT FROM AUTHOR]

In the 21st century, the need for regulation of the manager's role is incorporated into the discourse of school management. The documental research carried out included the analysis of official documents from Feira de Santana - Bahia, Brazil between 1990 and 2015, applying the Policy Cycle as the methodological approach. The results showed that the predominant management model emerges from the interrelationships between school, local authorities, national context and production of official documents. The election of principals, in order to provide the management function, revealed evidence for the understanding of the democratic management model in Feira de Santana, influenced by the participation of both teaching movements and the local population. [ABSTRACT FROM AUTHOR]

Several studies provide evidence of group-centric policy attitudes, that is, citizens evaluating policies based on linkages with visible social groups. The existing literature generally points to the role of media imagery, rhetoric and prominent political sponsors in driving group-centric attitudes. This article theorizes and tests an alternative source: exposure to rising local ethnic diversity. Focusing on the issue of crime, it first develops a theoretical account of how casual observation in the local context can give rise to ethnic stereotypes. Then, using two large, nationally representative datasets on citizen group and policy attitudes linked with registry data on local ethnic diversity, each spanning 20 years, it shows that crime attitudes become more strongly linked with immigration attitudes as local ethnic diversity rises. The results suggest that the typically emphasized 'top-down' influence on group-centric attitudes by elite actors is complemented by 'bottom-up' local processes of experiential learning about group–policy linkages. [ABSTRACT FROM AUTHOR]

This paper reports the findings of a study that analyzed the marketing activities of a number of vocational schools in a municipality where these organizations were allowed to compete for students. The research employed a qualitative, exploratory and descriptive design. The data was collected through interviews with school leaders, regional education authorities and civil society stakeholders, as well as an analysis of school promotional and informational materials. The study shows that marketing played a minor role in school leaders' management activities and that these leaders addressed marketing in a mostly unsystematic, informal and intuitive way. We explain this in terms of the specific nature of the local context in which the schools operated, namely, the levels of structural and behavioral competition in the vocational school system and the way the market is regulated by public authorities. [ABSTRACT FROM AUTHOR]

Spain is one of the European countries where the immigrant population has grown the most during the first years of this century. However, crime rates have remained constant in this period, even have decreased slightly, so the evolution of both phenomena does not allow to establish a positive relationship between them. Nevertheless, empirical evidence has shown that the immigration experiences differ according to local host conditions. In this way, the context would facilitate the involvement of immigrants in criminal activities. Empirical studies that address the family and social circumstances of immigrants at the local level and from a criminological perspective have not been carried out in Spain. To fill this gap, 173 immigrants were interviewed between 2017 and 2018, in order to study the relationship between local host conditions and self-reported crime, victimisation, and the perception about social control. Findings indicate that a troubled neighbourhood explains the crime committed by immigrants and their victimisation, that committing crimes and being a victim is related, and that immigrants who have committed a crime or have been victim of crime do not have a good opinion about the police and criminal justice system. [ABSTRACT FROM AUTHOR]