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Immune cell dysfunction within the tumor microenvironment (TME) undermines the control of cancer progression. Established tumors contain phenotypically distinct, tumor-specific natural killer (NK) cells; however, the temporal dynamics, mechanistic underpinning and functional significance of the NK cell compartment remains incompletely understood. Here, we use photo-labeling, combined with longitudinal transcriptomic and cellular analyses, to interrogate the fate of intratumoral NK cells. We reveal that NK cells rapidly lose effector functions and adopt a distinct phenotypic state with features associated with tissue residency. NK cell depletion from established tumors did not alter tumor growth, indicating that intratumoral NK cells cease to actively contribute to anti-tumor responses. IL-15 administration prevented loss of function and improved tumor control, generating intratumoral NK cells with both tissue-residency characteristics and enhanced effector function. Collectively, our data reveals the fate of NK cells after recruitment into tumors and provides insight into how their function may be revived.

Recent advances in multiple object tracking (MOT) rely primarily on visual appearance features to reconnect tracks lost due to occlusions. However, appearance features cannot be relied on to discriminate between objects that are visually similar or identical, such as animals, people in uniform, or mass-produced items. We propose a new model that relies on spatio-temporal motion features rather than appearance features for such videos. Furthermore, training an MOT method often relies on expensive hand labeling of bounding boxes or segmentation masks with ground truth tracks. By contrast, our videos are labeled only with fixed bounding boxes (effectively only positional information). We train our model in a semi-supervised manner using iterative pseudo-labeling (IPL), a technique often used in natural language processing, but not common to computer vision tasks. We show that appearance features are insufficient for reconnecting tracklets in videos of bee foraging, and that our motion-based IPL method offers an improvement over appearance feature methods.

Recent advances in multiple object tracking (MOT) rely primarily on visual appearance features to reconnect tracks lost due to occlusions. However, appearance features cannot be relied on to discriminate between objects that are visually similar or identical, such as animals, people in uniform, or mass-produced items. We propose a new model that relies on spatio-temporal motion features rather than appearance features for such videos. Furthermore, training an MOT method often relies on expensive hand labeling of bounding boxes or segmentation masks with ground truth tracks. By contrast, our videos are labeled only with fixed bounding boxes (effectively only positional information). We train our model in a semi-supervised manner using iterative pseudo-labeling (IPL), a technique often used in natural language processing, but not common to computer vision tasks. We show that appearance features are insufficient for reconnecting tracklets in videos of bee foraging, and that our motion-based IPL method offers an improvement over appearance feature methods.

Hiring managers regularly encounter job applicants with atypical levels of experience across several common domains—For example, occupational experience, general work experience, educational experience, and life experience. Surprisingly, few large-scale studies have investigated how hiring managers respond to applicants with atypical experience for the job, leaving a substantial lacuna in our knowledge. The primary goal of the present study is to examine the association between relative under and overexperience in the aforementioned domains and the likelihood of applicants being subsequently interviewed and eventually hired. We draw on insights from attribution theory to introduce the concept of red flags in the judgment of applicant experience. In doing so, we propose that hiring managers may avoid interviewing and hiring applicants with atypical experience relative to the applicant pool (i.e., relative over or underexperience). Overall, our red flags perspective posits that job applicants with typical amounts of experience will be favored by hiring managers, which may be a useful lens for explaining why highly experienced applicants are not always considered. We test these predictions on a unique dataset parsed from 53,194 résumés and the corresponding application forms from 42 different organizations. Our results are broadly consistent with the red flags perspective, notably uncovering some intricate nonlinear effects. Implications for theory and practice are discussed.

Based on recent developments in science mapping techniques, this chapter presents a review of methodologies that have been used in the field of career studies. We analyzed 831 methods sections from all published articles in five careers journals between 2014 and 2018 to uncover the key methodologies in the field. Our main conclusions are that quantitative methods dominate career studies, although the specific methods applied vary considerably between the clusters we revealed. Furthermore, we found that the methods used in career studies seem to be intricately linked to the discipline that the studies can be tied to, and the journals that publish these studies. We conclude the chapter with recommendations for future research, including the use of more long-term temporal designs, more exchange of knowledge and approaches between disciplines, and an awareness of existing norms and cultures in disciplines.

Based on recent developments in science mapping techniques, this chapter presents a review of methodologies that have been used in the field of career studies. We analyzed 831 methods sections from all published articles in five careers journals between 2014 and 2018 to uncover the key methodologies in the field. Our main conclusions are that quantitative methods dominate career studies, although the specific methods applied vary considerably between the clusters we revealed. Furthermore, we found that the methods used in career studies seem to be intricately linked to the discipline that the studies can be tied to, and the journals that publish these studies. We conclude the chapter with recommendations for future research, including the use of more long-term temporal designs, more exchange of knowledge and approaches between disciplines, and an awareness of existing norms and cultures in disciplines.

QuestionThe context for the implementation of evidence-based psychological treatments (EBPTs) often differs from the context in which the treatment was developed, which necessitates adaptations. In this systematic review we build on, and add to, prior approaches by examining the method used to guide such adaptations. In particular, we sought to elucidate the extent to which an empirical process is used.Study selection and analysisWe focused on publications describing adaptations made to EBPTs for adults diagnosed with a mental illness. We searched PubMed, PsycINFO, Embase and Web of Science from database inception to July 2018. Two raters independently coded the articles for the method used to conduct the adaptation, the reason for and nature of the adaptation, and who made the adaptation.FindingsThe search produced 20 194 citations, which yielded 152 articles after screening. The most commonly used methods for planned adaptations were literature review (57.7%), clinical intuition (47.0%) and theory (38.9%). The use of data from stakeholder interviews ranked fourth (21.5%) and the use of other types of data (eg, pilot study, experiment, survey, interview) ranked last at fifth (12.1%). Few publications reporting ad hoc adaptations were identified (n=3).ConclusionsThis review highlights a need to (a) educate providers and researchers to carefully consider the methods used for the treatment adaptation process, and to use empirical methods where possible and where appropriate, (b) improve the quality of reporting of stakeholder interviews and (c) develop reporting standards that articulate optimal methods for conducting treatment adaptations.

Based on recent developments in science mapping techniques, this chapter presents a review of methodologies that have been used in the field of career studies. We analyzed 831 methods sections from all published articles in five careers journals between 2014 and 2018 to uncover the key methodologies in the field. Our main conclusions are that quantitative methods dominate career studies, although the specific methods applied vary considerably between the clusters we revealed. Furthermore, we found that the methods used in career studies seem to be intricately linked to the discipline that the studies can be tied to, and the journals that publish these studies. We conclude the chapter with recommendations for future research, including the use of more long-term temporal designs, more exchange of knowledge and approaches between disciplines, and an awareness of existing norms and cultures in disciplines.

Digital transformation is having a significant impact on society, with new and innovative technology leading to new practices for organizations. The public sector is one sector that seeks to implement digital transformation to solve issues that are currently impacting this sector. One of the main goals of using digital technology is to implement E-Government, in which the public sector uses digital channels to provide services and interact with the stakeholders. The Swedish Government has set a national agenda in which it is stated that the public sector in Sweden should be the best in the world at utilizing digital solutions. Despite that there are many benefits associated with implementing E-Government, the actual implementation has been slow. A study from 2007 found that municipalities in Sweden were still at a very early stage in E-Government implementation. However, since then there has not been any research that investigated the current state of E-Government implementation, despite the topic being highly relevant. Therefore this research paper attempted to understand which stage of E-Government implementation municipalities in Sweden are currently at. This was done by creating a framework that consisted of important factors for implementing E-Government, and then applying the framework to five Swedish Municipalities. The results and analysis found that there had been certain progress in the development of E-Government, in terms of stating more clear objectives and goals, better organizational structures, such as implementing a top-down approach for planning digital transformation initiatives within the organization, and an increase in cooperation. In general, municipalities in Sweden were at a similar level of implementing E-Government initiatives, but were yet to have a fully implemented E-Government. Furthermore, depending on the specific environment of the municipality, the progress of implementing E-Government would be either faster or slower. There was

Digital transformation is having a significant impact on society, with new and innovative technology leading to new practices for organizations. The public sector is one sector that seeks to implement digital transformation to solve issues that are currently impacting this sector. One of the main goals of using digital technology is to implement E-Government, in which the public sector uses digital channels to provide services and interact with the stakeholders. The Swedish Government has set a national agenda in which it is stated that the public sector in Sweden should be the best in the world at utilizing digital solutions. Despite that there are many benefits associated with implementing E-Government, the actual implementation has been slow. A study from 2007 found that municipalities in Sweden were still at a very early stage in E-Government implementation. However, since then there has not been any research that investigated the current state of E-Government implementation, despite the topic being highly relevant. Therefore this research paper attempted to understand which stage of E-Government implementation municipalities in Sweden are currently at. This was done by creating a framework that consisted of important factors for implementing E-Government, and then applying the framework to five Swedish Municipalities. The results and analysis found that there had been certain progress in the development of E-Government, in terms of stating more clear objectives and goals, better organizational structures, such as implementing a top-down approach for planning digital transformation initiatives within the organization, and an increase in cooperation. In general, municipalities in Sweden were at a similar level of implementing E-Government initiatives, but were yet to have a fully implemented E-Government. Furthermore, depending on the specific environment of the municipality, the progress of implementing E-Government would be either faster or slower. There was

A quantum channel is said to be a mixed-unitary channel if it can be expressed as a convex combination of unitary channels. We prove that, given the Choi representation of a quantum channel, it is NP-hard with respect to polynomial-time Turing reductions to determine whether or not that channel is a mixed-unitary channel. This hardness result holds even under the assumption that the channel is not within an inverse-polynomial distance (in the dimension of the space upon which it acts) of the boundary of the mixed-unitary channels., Comment: 24 pages

Black carbon (BC) contributes to Arctic warm- ing, yet sources of Arctic BC and their geographic con- tributions remain uncertain. We interpret a series of recent airborne (NETCARE 2015; PAMARCMiP 2009 and 2011 campaigns) and ground-based measurements (at Alert, Bar- row and Ny-Ålesund) from multiple methods (thermal, laser incandescence and light absorption) with the GEOS-Chem global chemical transport model and its adjoint to attribute the sources of Arctic BC. This is the first comparison with a chemical transport model of refractory BC (rBC) measure- ments at Alert. The springtime airborne measurements per- formed by the NETCARE campaign in 2015 and the PA- MARCMiP campaigns in 2009 and 2011 offer BC vertical profiles extending to above 6 km across the Arctic and in- clude profiles above Arctic ground monitoring stations. Our simulations with the addition of seasonally varying domes- tic heating and of gas flaring emissions are consistent with ground-based measurements of BC concentrations at Alert and Barrow in winter and spring (rRMSE < 13 %) and with airborne measurements of the BC vertical profile across the Arctic (rRMSE = 17 %) except for an underestimation in the middle troposphere (500–700 hPa). Sensitivity simulations suggest that anthropogenic emis- sions in eastern and southern Asia have the largest effect on the Arctic BC column burden both in spring (56 %) and annu ally (37 %), with the largest contribution in the middle tropo- sphere (400–700 hPa). Anthropogenic emissions from north- ern Asia contribute considerable BC (27% in spring and 43 % annually) to the lower troposphere (below 900 hPa). Biomass burning contributes 20 % to the Arctic BC column annually. At the Arctic surface, anthropogenic emissions from northern Asia (40–45 %) and eastern and southern Asia (20– 40 %) are the largest BC contributors in winter and spring, followed by Europe (16–36 %). Biomass burning from North America is the most important contributor to all stations in summ

Black carbon (BC) contributes to Arctic warm- ing, yet sources of Arctic BC and their geographic con- tributions remain uncertain. We interpret a series of recent airborne (NETCARE 2015; PAMARCMiP 2009 and 2011 campaigns) and ground-based measurements (at Alert, Bar- row and Ny-Ålesund) from multiple methods (thermal, laser incandescence and light absorption) with the GEOS-Chem global chemical transport model and its adjoint to attribute the sources of Arctic BC. This is the first comparison with a chemical transport model of refractory BC (rBC) measure- ments at Alert. The springtime airborne measurements per- formed by the NETCARE campaign in 2015 and the PA- MARCMiP campaigns in 2009 and 2011 offer BC vertical profiles extending to above 6 km across the Arctic and in- clude profiles above Arctic ground monitoring stations. Our simulations with the addition of seasonally varying domes- tic heating and of gas flaring emissions are consistent with ground-based measurements of BC concentrations at Alert and Barrow in winter and spring (rRMSE < 13 %) and with airborne measurements of the BC vertical profile across the Arctic (rRMSE = 17 %) except for an underestimation in the middle troposphere (500–700 hPa). Sensitivity simulations suggest that anthropogenic emis- sions in eastern and southern Asia have the largest effect on the Arctic BC column burden both in spring (56 %) and annu ally (37 %), with the largest contribution in the middle tropo- sphere (400–700 hPa). Anthropogenic emissions from north- ern Asia contribute considerable BC (27% in spring and 43 % annually) to the lower troposphere (below 900 hPa). Biomass burning contributes 20 % to the Arctic BC column annually. At the Arctic surface, anthropogenic emissions from northern Asia (40–45 %) and eastern and southern Asia (20– 40 %) are the largest BC contributors in winter and spring, followed by Europe (16–36 %). Biomass burning from North America is the most important contributor to all stations in summ

Digital computers entered our homes, landed on our desktops, slipped into our pockets, and have seemingly become ubiquitous. At an ever faster pace, these devices have become highly interconnected and interoperable. Consequently, our archives, our work, our actions, and our interactions are increasingly digitalized and stored in databases or made accessible via the Internet. This data, generally characterized by high volume, variety, and velocity (i.e., accumulation rate), has come to be called “Big Data”. As of yet, Big Data has seldom been utilized in management research. Therefore, this dissertation explores the opportunities that Big Data brings for management scholars and describes three distinct projects that show how Big Data can be utilized in management research.

This study continues a previous face recognition investigation using uncooled infrared technology. The database developed in an earlier study is further expanded to include 50 volunteers with 30 facial images from each subject. The automatic image reduction method reduces the pixel size of each image from 160x120 to 60x45 . The study reexamines two linear classification methods: the Principal Component Analysis (PCA) and Fisher Linear Discriminant Analysis (LDA). Both PCA and LDA apply eigenvectors and eigenvalues concepts. In addition, the Singular Value Decomposition based Snapshot method is applied to decrease the computational load. The K-fold Cross Validation is applied to estimate classification performances. Results indicate that the best PCA-based method (using all eigenvectors) produces an average classification performance equal to 79.22%. Incorporated with PCA for dimension reduction, the LDA-based method achieves 94.58% accuracy in average classification performance. Additional testing on unfocused images produces no significant impact on the overall classification performance. Overall results again confirm uncooled IR imaging can be used to identify individual subjects in a constrained indoor environment., The original document contains color images.

Infrared imaging devices offer the main advantage of being robust to ambient illumination changes and recent technological advances have significantly improved the resolution of cheaper uncooled infrared (IR) versions to the point where they may become widely applicable in the IR face recognition field. This study applies two linear classification schemes; the Principal Component Analysis and the Fisherface procedure to the recognition of faces collected using an uncooled IR camera under indoor controlled conditions. Results show the selected uncooled IR camera has sufficient resolution to allow for discrimination between the subjects contained in our experimental database collected. Results show also consistent better performances for LDA than for PCA-based schemes. We also discuss the impact of the first few top eigenvectors on PCA-based classification performances.

There was a rapid expansion of high voltage transmission lines in Queensland from around 1955 to 1990, but in recent years as the transmission network has matured, the focus has switched from construction to maintenance of these lines. The Queensland Electricity Transmission Corporation (QETC), which is responsible for operating and maintaining the high voltage network is looking closely at it's maintenance practices in order to reduce costs and improve the returns on the capital invested in the assets. Maintenance has traditionally been done on a time interval basis but in recent years there has been a trend for maintenance practices to be based on a condition monitoring and life assessment approach. The foundation of these practices is that maintenance strategies use meaningful data and that maintenance is only performed when unacceptable indicators are shown. Maintenance of a transmission system represents a very large investment in labour and capital. Consequently, maintenance practices should aim to maximise their effectiveness at marginal cost, whilst ensuring that considerations of public safety and the environment are taken into account in the formulation of policy. The research work is set in the context of Reliability Centred Maintenance. This is a structured approach which uses the logic of failure modes effects analysis to indentify the function and the manner in which failure of a component or components occur, and to assist in divising appropriate preventive maintenance measures. The study reviewed the types of preventive and corrective maintenance which are carried out on the line components, the types of failures and the empirical studies which have endeavoured to assess the useful life of these components. The review found that complete life data exists for some insulators of a particular manufacture in aggressive environments but the data for conductors is largely incomplete. To arrive at an optimal maintenance activity, life models for each of the

The value of the concept of 'school' in metascience is examined with reference to the 'Chicago School, of sociology during the period from 1900 to 1952. The notion of school is widely used by sociologists in accounting for developments within their discipline. However, the use of schools as a framework for documenting and interpreting the history of sociology tends to obscure the complexity and variety of intellectual development. Five myths about the 'Chicago School' are identified: that its members were social ameliorists; that they were primarily ethnographers; that they exhibited little concern with theory; that they were heavily reliant on a framework provided by the social psychological perspective of George Herbert Mead; and that they were an insular group with little direct involvement in, or long term impact on, the development of sociology in the United States. It is argued that sociological work at the University of Chicago was an integral part of American sociology throughout the period under study and that the 'Chicago School' did not display a distinct set of theoretical and methodological ideas. What was common to the the members of the sociology department of the University of Chicago was in large part also typical of American sociology as a whole. In the light of this empirical study, the potential of the metascientific models proposed by Mullins (1973) and Tiryakian (1979a, 1979b) is examined in detail both in terms of their theoretical underpinnings and their approach to the case study material. 'Doubt is cast on the value of these models and the implications of this for a 'schools' or 'unit approach' to metascience are considered. It is suggested that a schools approach which concentrates on the knowledge transformative processes within a school rather than on identifying schools with a distinct set of ideas might be a more profitable way of developing a theory of the production of sociological knowledge and would be less likely to perpetrate myt

This study continues a previous face recognition investigation using uncooled infrared technology. The database developed in an earlier study is further expanded to include 50 volunteers with 30 facial images from each subject. The automatic image reduction method reduces the pixel size of each image from 160 120 to 60 45 . The study reexamines two linear classification methods: the Principal Component Analysis (PCA) and Fisher Linear Discriminant Analysis (LDA). Both PCA and LDA apply eigenvectors and eigenvalues concepts. In addition, the Singular Value Decomposition based Snapshot method is applied to decrease the computational load. The K-fold Cross Validation is applied to estimate classification performances. Results indicate that the best PCA-based method (using all eigenvectors) produces an average classification performance equal to 79.22%. Incorporated with PCA for dimension reduction, the LDA-based method achieves 94.58% accuracy in average classification performance. Additional testing on unfocused images produces no significant impact on the overall classification performance. Overall results again confirm uncooled IR imaging can be used to identify individual subjects in a constrained indoor environment., http://archive.org/details/infraredfacereco109451553, Lieutenant, United States Navy, Approved for public release; distribution is unlimited.

The value of the concept of 'school' in metascience is examined with reference to the 'Chicago School, of sociology during the period from 1900 to 1952. The notion of school is widely used by sociologists in accounting for developments within their discipline. However, the use of schools as a framework for documenting and interpreting the history of sociology tends to obscure the complexity and variety of intellectual development. Five myths about the 'Chicago School' are identified: that its members were social ameliorists; that they were primarily ethnographers; that they exhibited little concern with theory; that they were heavily reliant on a framework provided by the social psychological perspective of George Herbert Mead; and that they were an insular group with little direct involvement in, or long term impact on, the development of sociology in the United States. It is argued that sociological work at the University of Chicago was an integral part of American sociology throughout the period under study and that the 'Chicago School' did not display a distinct set of theoretical and methodological ideas. What was common to the the members of the sociology department of the University of Chicago was in large part also typical of American sociology as a whole. In the light of this empirical study, the potential of the metascientific models proposed by Mullins (1973) and Tiryakian (1979a, 1979b) is examined in detail both in terms of their theoretical underpinnings and their approach to the case study material. 'Doubt is cast on the value of these models and the implications of this for a 'schools' or 'unit approach' to metascience are considered. It is suggested that a schools approach which concentrates on the knowledge transformative processes within a school rather than on identifying schools with a distinct set of ideas might be a more profitable way of developing a theory of the production of sociological knowledge and would be less likely to perpetrate myt