We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Many signs in urban areas are bilingual in Chinese and English. It cannot escape the notice of even the most casual bilingual observer that many such signs are woefully (and sometimes hilariously) mistranslated. Mistakes can result from wrong segmentation, wrong word choice, wrong grammar, or inappropriate style, which is particularly important in Chinese. Mistakes can also result from missing crucial information or lack of understanding of English. There are also the ‘innovative analogies’, which give rise to non-existent English words. Also frequently observed are inconsistencies, wavering between the two strategies of pinyin transliteration and meaning translation. The inclusion of mistranslated signs can be pedagogically useful in more than one way. Studying mistranslated signs is an exercise in contrastive analysis. Through detailed analysis of the causes of the mistakes, such signs can be used as negative examples in the teaching of both Chinese and English. They can also be useful to the study and practice of translation.
This chapter investigates the precarious arrangements embedded in the systems and processes of migration management across three different country contexts: the UK, Germany, and Australia. The country comparison shows how precarious workplace/worker and societal arrangements have been woven into the systems of migration management (Paret and Gleeson ; Vosko ). The examination employs an historical methodology to show how approaches to migration management create a racialised precarity in the destination country generally; and more specifically in the destination country labour market where different groups of migrant workers are channelled into and toil in the least favourable areas of the labour market. Accordingly, we shed light on the rules underscoring and the implications of the process of migrant worker acceptance, settlement, and integration in a new land and labour market.
The design of a new digital business model is typically based on shaky assumptions and rough estimates. As the innovator further develops the proposed product or service, they need to carefully collect user feedback and market data to refine the assumptions and generate more precise estimates. Some of the trickiest challenges in launching a digital innovation include customer acquisition, business model validation, and gaining network momentum. This chapter first discusses how to address the challenges of customer acquisition in digital markets, and then describes an experimental method for validating the features of the business model. The chapter finishes with tools for kindling network effects and fomenting the growth of the platform ecosystem.
Spatially resolved transcriptomics (SRT) is a growing field that links gene expression to anatomical context. SRT approaches that use next-generation sequencing (NGS) combine RNA sequencing with histological or fluorescent imaging to generate spatial maps of gene expression in intact tissue sections. These technologies directly couple gene expression measurements with high-resolution histological or immunofluorescent images that contain rich morphological information about the tissue under study. While broad access to NGS-based spatial transcriptomic technology is now commercially available through the Visium platform from the vendor 10× Genomics, computational tools for extracting image-derived metrics for integration with gene expression data remain limited. We developed VistoSeg as a MATLAB pipeline to process, analyze and interactively visualize the high-resolution images generated in the Visium platform. VistoSeg outputs can be easily integrated with accompanying transcriptomic data to facilitate downstream analyses in common programing languages including R and Python. VistoSeg provides user-friendly tools for integrating image-derived metrics from histological and immunofluorescent images with spatially resolved gene expression data. Integration of this data enhances the ability to understand the transcriptional landscape within tissue architecture. VistoSeg is freely available at http://research.libd.org/VistoSeg/.
This chapter advocates viewing the structures of international political systems through the lens of multiple dimensions of social differentiation; the structured processes by which social actors and positions are produced, populated, related, reproduced, and transformed. Social differentiation involves, at minimum, establishing who has what authority over whom with respect to which activities; that is, differentiating actors, activities, and authorities (which usually are complexly interrelated). And in addition to institutional and normative dimensions, which are notoriously excluded from the Waltzian account of structure, social differentiation has important material or geo-technical dimensions that are also ignored in the Waltzian account (which is not, as is often claimed, materialist). More generally, I argue that rather than seek to identify a small number of structural models composed of a few elements, we should aim for a checklist of dimensions of differentiation that illuminate some recurrently important features of the structures of some social and political systems of interest.
In this chapter we describe segmentation— a cognition-based intervention of work-life balance. Segmentation involves creating boundaries (or psychological walls) to insulate life domains. The goal is to prevent negative spillover from the segmented domain to other domains. We discuss four different segmentation interventions that people commonly use to prevent negative spillover: temporal, physical, behavior, and communicative. We also discuss intervention programs that organizations can institutionalize to achieve higher levels of employee work-life balance based on these segmentation interventions.
This Element argues that the low dynamism of low- to mid-income Arab economies is explained with a set of inter-connected factors constituting a 'segmented market economy'. These include an over-committed and interventionist state with limited fiscal and institutional resources; deep insider-outsider divides among firms and workers that result from and reinforce wide-ranging state intervention; and an equilibrium of low skills and low productivity that results from and reinforces insider-outsider divides. These mutually reinforcing features undermine encompassing cooperation between state, business and labor. While some of these features are generic to developing countries, others are regionally specific, including the relative importance and historical ambition of the state in the economy and, closely related, the relative size and rigidity of the insider coalitions created through government intervention. Insiders and outsiders exist everywhere, but the divisions are particularly stark, immovable and consequential in the Arab world.
Conducting market research to find solutions, identifying opportunities and defining the value of new inventions are some of the key points covered in this chapter. A carefully defined indication can make the difference between success and failure in medical product development and this chapter explains how to get better at nailing the exact problem to be solved. Market segmentation examples and cases show how to prevent being misled on market size and market projections. A referral chain tool is presented for closely analyzing market positioning and value proposition of the new technology or product. Key market drivers and hurdles used to dynamically determine market size, adoption rates, and strategize on product development cycles are discussed and presented in this chapter.
The early 2000s were a period of social policy expansion in Latin America. New programs were created in healthcare, pensions, and social assistance, and previously excluded groups were incorporated into existing policies. What was the character of this social policy expansion? Why did the region experience this transformation? Drawing on a large body of research, this Element shows that the social policy gains in the early 2000s remained segmented, exhibiting differences in access and benefit levels, gaps in service quality, and unevenness across policy sectors. It argues that this segmented expansion resulted from a combination of short and long-term characteristics of democracy, favorable economic conditions, and policy legacies. The analysis reveals that scholars of Latin American social policy have generated important new concepts and theories that advance our understanding of perennial questions of welfare state development and change.
We propose an easy to implement yield curve extrapolation method to determine long-term interest rates suitable for regulatory valuation. We empirically evaluate this approach for the German nominal bond market, by estimating the model on bonds with maturities up to 20 years and assessing the out-of-sample performance for bonds with maturities beyond 20 years. Even though observed long-term yields are somewhat lower than the predicted yields, the method performs quite well empirically given its simplicity. We perform a case study on pension fund liability valuation and show that our proposed method would have a substantial impact on liability values.
Higher thalamic volume has been found in children with obsessive-compulsive disorder (OCD) and children with clinical-level symptoms within the general population (Boedhoe et al. 2017, Weeland et al. 2021a). Functionally distinct thalamic nuclei are an integral part of OCD-relevant brain circuitry.
Objectives
We aimed to study the thalamic nuclei volume in relation to subclinical and clinical OCD across different age ranges. Understanding the role of thalamic nuclei and their associated circuits in pediatric OCD could lead towards treatment strategies specifically targeting these circuits.
Methods
We studied the relationship between thalamic nuclei and obsessive-compulsive symptoms (OCS) in a large sample of school-aged children from the Generation R Study (N = 2500) (Weeland et al. 2021b). Using the data from the ENIGMA-OCD working group we conducted mega-analyses to study thalamic subregional volume in OCD across the lifespan in 2,649 OCD patients and 2,774 healthy controls across 29 sites (Weeland et al. 2021c). Thalamic nuclei were grouped into five subregions: anterior, ventral, intralaminar/medial, lateral and pulvinar (Figure 1).
Results
Both children with subclinical and clinical OCD compared with controls show increased volume across multiple thalamic subregions. Adult OCD patients have decreased volume across all subregions (Figure 2), which was mostly driven by medicated and adult-onset patients.
Conclusions
Our results suggests that OCD-related thalamic volume differences are global and not driven by particular subregions and that the direction of effects are driven by both age and medication status.
Fluorescence microscopy techniques have experienced a substantial increase in the visualization and analysis of many biological processes in life science. We describe a semiautomated and versatile tool called Cell-TypeAnalyzer to avoid the time-consuming and biased manual classification of cells according to cell types. It consists of an open-source plugin for Fiji or ImageJ to detect and classify cells in 2D images. Our workflow consists of (a) image preprocessing actions, data spatial calibration, and region of interest for analysis; (b) segmentation to isolate cells from background (optionally including user-defined preprocessing steps helping the identification of cells); (c) extraction of features from each cell; (d) filters to select relevant cells; (e) definition of specific criteria to be included in the different cell types; (f) cell classification; and (g) flexible analysis of the results. Our software provides a modular and flexible strategy to perform cell classification through a wizard-like graphical user interface in which the user is intuitively guided through each step of the analysis. This procedure may be applied in batch mode to multiple microscopy files. Once the analysis is set up, it can be automatically and efficiently performed on many images. The plugin does not require any programming skill and can analyze cells in many different acquisition setups.
Chapter 6 focuses on labor market developments and preferences for unemployment policies. Using data from Germany, we show that increasingly, labor market risks can be predicted with a small set of observables (education, occupation, and location), while the relevance of private information has declined over time. Polarization over unemployment policies has risen at the same time. We also explore – theoretically and empirically – how people translate their labor market situation into political preferences and show the importance of social networks in the process. Lastly, the chapter describes a case study of a fascinating reform in the Swedish unemployment insurance system, which shows what happens when unemployment insurance contributions and benefits are tied to unemployment risk, as would happen in a private market. Thus, the Swedish case provides a window into the (possible) future of segmented social policy programs that we predict will become more commonplace.
Cryo-soft-X-ray tomography is being increasingly used in biological research to study the morphology of cellular compartments and how they change in response to different stimuli, such as viral infections. Segmentation of these compartments is limited by time-consuming manual tools or machine learning algorithms that require extensive time and effort to train. Here we describe Contour, a new, easy-to-use, highly automated segmentation tool that enables accelerated segmentation of tomograms to delineate distinct cellular compartments. Using Contour, cellular structures can be segmented based on their projection intensity and geometrical width by applying a threshold range to the image and excluding noise smaller in width than the cellular compartments of interest. This method is less laborious and less prone to errors from human judgement than current tools that require features to be manually traced, and it does not require training datasets as would machine-learning driven segmentation. We show that high-contrast compartments such as mitochondria, lipid droplets, and features at the cell surface can be easily segmented with this technique in the context of investigating herpes simplex virus 1 infection. Contour can extract geometric measurements from 3D segmented volumes, providing a new method to quantitate cryo-soft-X-ray tomography data. Contour can be freely downloaded at github.com/kamallouisnahas/Contour.
This chapter focuses on how people create psychological walls around life domains that contain negative affect to prevent spillover of these bad feelings into other life domains. Several segmentation strategies are desribed: temporal, physical, behavior, and communication.
This chapter summarizies the behavioral strategies related to the balance life. These involve principles related to satisfaction limits, full spectrum of needs, diminishing satisfaction, positive spillover, segmentation, compensation, role conflict, role enrichment.
Chapter 2 tackles aspects of cognitive processing that can be observed in the course of a translation task, from the moment a translator begins to read a text-to-be-translated until the translation has been finalized. It begins by recording the historical development of research into the translation process and how the task of translation has been modelled. It moves on to examining how advances in methodological approaches have contributed to the development of early models, providing empirical evidence from verbal reports, keylogging and eye tracking. Contemporary translation process research focuses on text reading, segmentation and production; and advances in computational linguistics have enhanced descriptions and identification of translation units, attention, production and alignment.
This chapter is the first of two chapters relating to business strategy and covers the most fundamental aspects in terms of strategic planning and positioning. The starting point is a discussion of the concept of competitive advantage, and how this relates to value creation. Different types of competitive advantage, based on costs and benefits, are discussed, and these are related to market positioning, targeting and segmentation. The relevance of price elasticity is explained in the context of positioning and competitive advantage. Various forms of integration are discussed, in terms of vertical, horizontal and diversification aspects. The nature, costs and benefits of each of these forms is explained. Recent trends in diversification are discussed, along with empirical studies. As with other chapters, case studies are vital in order to illustrate the management principles; in this case, three prominent tech firms are discussed in terms of their strategy development since their origins: Apple, Netflix and Tesla. Although all of them are high-cap tech firms of global reach, they each have quite different prospects.
Chapter 8 discusses how our framework can be operationalised in cross-cultural pragmatic research focusing on the analytic unit of speech act. We first propose a typology of speech acts. This typology is essentially different from others, in that it provides a system of speech acts based on their interactional and relational functions. We argue that in using any typology of speech acts, it is fundamental for the cross-cultural pragmatician to avoid unnecessarily proliferating speech act categories. After outlining our model typology of speech acts, we provide a coding scheme by means of which speech acts can be systematically described in data analysis.
We present an unsupervised machine learning approach for segmentation of static and dynamic atomic-resolution microscopy data sets in the form of images and video sequences. In our approach, we first extract local features via symmetry operations. Subsequent dimension reduction and clustering analysis are performed in feature space to assign pattern labels to each pixel. Furthermore, we propose the stride and upsampling scheme as well as separability analysis to speed up the segmentation process of image sequences. We apply our approach to static atomic-resolution scanning transmission electron microscopy images and video sequences. Our code is released as a python module that can be used as a standalone program or as a plugin to other microscopy packages.