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Literature and second language vocabulary learning: the role of text-type and teaching approach
Get PDFThis study considers the relative benefits for vocabulary learning of exposure to two types of texts, literary or non-literary, used with two teaching approaches. These approaches were termed functional and creative respectively. In the former, learners’ attention was drawn to factual information and linguistic features in order to develop their linguistic knowledge. In the latter, the aim was to stimulate learners’ personal and emotional response, by drawing their attention to the text’s emotional content and how language was used to express meaning. We analysed data from 160 learners of French in eight schools in England. Learners in four schools studied French poems and those in another four studied French factual texts. Teachers in each text condition employed functional and creative methods of exploitation within a counterbalanced design. We assessed two types of vocabulary knowledge at pre- and post-test: meaning-recall of vocabulary contained in the texts, and learners’ general vocabulary size. Our results indicated learning gains across both text-types. There were however important interactions between text-type and teaching approach and between text-type and the order in which the teaching approaches were used. Finally, we consider the implications of these findings for understanding of vocabulary learning through literature and for classroom practice
Cutting the cake into crumbs: verifying envy-free cake cutting protocols using bounded integer arithmetic
Get PDFFair division protocols specify how to split a continuous resource
(conventionally represented by a cake)
between multiple agents with different preferences.
Envy-free protocols ensure no agent prefers any other
agent's allocation to his own.
These protocols are complex and manual proofs of their correctness may contain errors.
Recently, Bertram and others
developed the DSL Slice for describing these protocols
and showed how verification of envy-freeness can be reduced to
SMT instances in the theory of quantified non-linear real arithmetic.
This theory is decidable, but the decision procedure is slow,
both in theory and in practice.
We prove that,
under reasonable assumptions about the primitive operations used in the protocol,
counterexamples to envy-freeness can always be found with bounded integer arithmetic.
Building on this result,
we construct an embedded DSL for describing cake-cutting protocols in declarative-style C.
Using the bounded model-checker CBMC,
we reduce verifying envy-freeness of a protocol to
checking unsatisfiability of pure SAT instances.
This leads to a substantial reduction in verification time
when the protocol is unfair
Applicability of both/and thinking in international sustainable business studies
Get PDFThe purpose of this article is to provide a methodological demonstration making use of the both/and thinking (BAT) framework to perform analysis of intertemporal tensions. The BAT framework as an analytical tool is able to holistically examine complex multi-level business problems that involve tensions, contradictions and paradox that could be useful to others. Engaging the BAT framework in international sustainable business studies can be a challenging choice as it requires holistic understanding of the affects in the separation of contradictory elements across time and distance to shape research inquiry and direction. The approach considers that while paradoxes deal with contradictions, as a methodological process it enables a strategy for juxtaposing apparent opposites using an integrative lens embedded in BAT. As such, the use of BAT is discussed using a constructionist approach to gain insight and understanding on surfacing intertemporal tensions exemplified by the socio-business case study that is situated in the chocolate industry. The article draws on BAT primary and sub-themes and discusses implications and applications as a technique to frame the grappling of tensions. The findings are guided by the existing literature and the analysis from the empirical case study providing contributions in practice to further support the use of the BAT framework. Paradoxes examined in this article are based on affects for the themes of organizing, belonging, performing and learning. This article provides understanding of the findings to gain insight from an empirical and theoretical perspective to illustrate the practical implications of the methodological approach. As such, the principles of paradox theory are placed in the context of the BAT framework which are exemplified by making use of the empirical case study data to surface the potential applicability of the approach for future research. This article aims to contribute to the business and management methodological literature by demonstrating the use of the BAT approach and contributes with specificity in relation to the paradox taxonomy and the use of the BAT framework. Despite certain limitations, the BAT framework can be an excellent choice for qualitative sustainable business research that deals with contradictory demands
Rumination in dementia and its relationship with depression, anxiety, and attentional biases
Get PDFRumination (self-referential and repetitive thinking), attentional biases (AB), and impaired cognitive control are theorized as being integral factors in depression and anxiety. Yet, research examining the relationship between rumination, mood, and AB for populations with reduced cognitive control, e.g., people living with dementia (PwD), is lacking. To explore whether literature-based relationships are demonstrated in dementia, PwD (n = 64) and healthy controls (HC) (n = 75) completed an online self-report survey measuring rumination and mood (twice), and a telephone cognitive status interview (once). Rumination was measured as an emotion-regulation style, thinking style, and response to depression. We examined the test-retest reliability of PwD’s (n = 50) ruminative-scale responses, ruminative-scale internal consistency, and correlations between rumination, age, cognitive ability, and mood scores. Also, nine participants (PwD = 6, HC = 3) completed an AB measure via eye-tracking. Participants fixated on a cross, naturally viewed pairs of facial images conveying sad, angry, happy, and neutral emotions, and then fixated on a dot. Exploratory analyses of emotional-face dwell-times versus rumination and mood scores were conducted. Except for the HC group’s reflective response to depression measure, rumination measures were reliable, and correlation strengths between rumination and mood scores (.29 to .79) were in line with literature for both groups. For the AB measure subgroup, ruminative thinking style scores and angry-face metrics were negatively correlated. The results of this study show that literature-based relationships between rumination, depression, and anxiety are demonstrated in dementia, but the relationship between rumination and AB requires further investigation
Inequalities à la Pólya for the Aharonov–Bohm eigenvalues of the disk
Get PDFWe prove an analogue of Pólya’s conjecture for the eigenvalues of the magnetic Schrödinger operator with Aharonov–Bohm potential on the disk, for Dirichlet and magnetic Neumann boundary conditions. This answers a question posed by R. L. Frank and A. M. Hansson in 2008
The role of artificial intelligence in actioning customer insight to manage customer experience throughout the customer journey within service organizations in Jordan
Get PDFCustomer experience management (CXM) has emerged as a significant aspect of business
strategy, acknowledged for its role in fostering sustainable competitive differentiation. In this
context, the utilisation of artificial intelligence (AI) technology in CXM assumes paramount
importance, as it enables organizations to revolutionize customer journeys through AI-driven
CXM. Such AI advancements hold immense potential in improving customer experience and
enhancing organizational performance. However, the CXM field faces challenges in reaching
the expected level of maturity. This research focuses on the role of AI in actioning customer
insights throughout the Customer Journey (CJ) to manage Customer Experience (CX). The
study aims to explore how organizations can effectively utilize AI-derived customer insights to
continuously enhance CX and develop a framework for understanding and managing CX based
on AI-generated insights within service organizations in Jordan. This includes understanding
how AI can be incorporated into the customer insight process and exploring the various ways
organizations utilize AI-driven customer insights to comprehend and manage customer
experience. Additionally, the research seeks to explore the different ways organisations assess
the value of actioning customer insights derived from AI.
Due to the exploratory nature of the topic, a case study approach was deemed appropriate for
investigating the contemporary phenomenon in-depth and within its real-life context. The study
employed a multiple embedded case study design, with the organization as the holistic unit of
analysis and the process of generating and actioning AI-enabled customer insights as the
embedded sub-unit of analysis.
The researcher selected four service organizations in the banking and telecommunications
sectors that have a customer experience management function, program, or practice in place,
have adopted AI technologies, and are accessible and willing to participate. The data collection
techniques provided a rich, detailed, and complete picture of the phenomenon under study.
Purposeful sampling was utilized to collect evidence from multiple informants within each
organization through semi-structured and in-depth interviews and document reviews.
The analysis of the case studies followed the 'stacking comparable cases’ approach
recommended by Miles and Huberman (2014), which involved within-case analysis, cross-case
analysis, and systematic comparison and synthesis. Within-case analysis was used to describe,
understand, and explain what happened in a single, bounded context, while cross-case analysis
was used to identify themes that cut across cases. Finally, systematic comparison and
synthesis were used to compare and contrast findings across sector-specific and all sectors.
The key findings of this thesis contribute to the realms of theory and empirical research, as well
as the practical role and implementation of AI in the field of CXM. Firstly, the development of
the Customer Experience-Based View (CXBV) framework introduces a significant theoretical
advancement, demonstrating AI’s transformative implications in CXM. Building upon the
Resource-Based View (RBV) and Knowledge-Based View (KBV), the CXBV framework
incorporates six critical capabilities central to successful CXM, which include customer
experience strategy, customer journey management, customer intelligence approach, agile
operations, the CX data-to-value process, and the harnessing of AI capabilities.
Further, this study brings to light the importance of additional dimensions such as customer
experience strategy, customer journey management, customer intelligence, and agile
operations, collectively substantiating the CX data-to-value creation process. It emphasizes the
need for a comprehensive understanding of the transformation of customer data into customer
experience actions.
Moreover, this research establishes the intermediary role of customer intelligence in the data-to-value creation process. It posits the necessity of interpreting and understanding customer
insights prior to their implementation. The study identifies two specific categories of AI analytics,
namely AI-enabled data-to-insights analytics and AI-enabled intelligence-to-action analytics,
demonstrating AI’s potential to transform customer data into actionable insights.
From a practitioner standpoint, this thesis offers actionable insights and recommendations,
particularly tailored to the telecommunications and banking sectors. The study's findings
provide insights into how organizations can leverage AI-generated customer insights to manage
customer experience effectively. This is exemplified by strategies such as providing customized
consumer experiences, delivering seamless customer service across touchpoints, innovating,
and developing data-driven products, and refining organizational processes. The research also
highlights the importance of assessing the value of AI-generated customer insights, which can
enable organizations to optimize their CXM strategies and improve customer loyalty.
Lastly, the findings illuminate the immense latent value of AI-generated customer insights in
enhancing various customer experience outcomes. It outlines how AI can enhance customer
satisfaction, loyalty, and even facilitate revenue growth while enabling strategic customer
acquisition. Furthermore, AI’s predictive capabilities are highlighted as instrumental in
facilitating proactive decision-making and aligning business strategies with future trends and
customer expectations. These findings culminate in providing a comprehensive scholarly
understanding of the intersection of AI and CXM in the business and management domain,
enhancing the discourse in both academia and industry
Using biochar for environmental recovery and boosting the yield of valuable non-food crops: the case of hemp in a soil contaminated by potentially toxic elements (PTEs)
Get PDFHemp (Cannabis sativa L.) is known to tolerate high concentrations of soil contaminants which however can limit its biomass yield. On the other hand, organic-based amendments such as biochar can immobilize soil contaminants and assist hemp growth in soils contaminated by potentially toxic elements (PTEs), allowing for environmental recovery and income generation, e.g. due to green energy production from plant biomass. The aim of this study was therefore to evaluate the suitability of a softwood-derived biochar to enhance hemp growth and promote the assisted phytoremediation of a PTE-contaminated soil (i.e., Sb 2175 mg kg-1; Zn 3149 mg kg-1; Pb 403 mg kg-1; and Cd 12 mg kg-1). Adding 3% (w/w) biochar to soil favoured the reduction of soluble and exchangeable PTEs, decreased soil dehydrogenase activity (by ~2.08-fold), and increased alkaline phosphomonoesterase and urease activities, basal respiration and soil microbial carbon (by ~1.18-, 1.22-, 1.22-, and 1.66-fold, respectively). Biochar increased the abundance of selected soil culturable microorganisms, while amplicon sequencing analysis showed a positive biochar impact on α-diversity and the induction of structural changes on soil bacterial community structure. Biochar did not affect root growth of hemp but significantly increased its aboveground biomass by ~1.67-fold for shoots, and by ~2-fold for both seed number and weight. Biochar increased the PTEs phytostabilisation potential of hemp with respect to Cd, Pb and Zn, and also stimulated hemp phytoextracting capacity with respect to Sb. Overall, the results showed that biochar can boost hemp yield and its phytoremediation effectiveness in soils contaminated by PTEs providing valuable biomass that can generate profit in economic, environmental and sustainability terms
Proposition of an SNP set to replace SSRs for standardized cultivar identification in apple
Get PDFApple is one of the most important fruit crops grown in temperate regions. Ex situ conservation of apple genetic resources mainly relies on grafted trees maintained in orchards, which can be space- and labor-intensive. To help collection managers to compare their germplasm with others’ at both the national and international levels, Malus UNiQue genotype codes (MUNQ) were proposed for all accessions sharing the same genetic marker profile. These genetic profiles were initially obtained using a standardized set of 16 SSRs. However, an impending difficulty in SSR analysis is expected and many genetic studies nowadays use SNP markers. SNP-based MUNQ assignment is expected to be more streamlined, but just like for SSRs, it will be essential that a consistent marker set is used across studies worldwide to enable comparisons among them without genotyping each new unique individual with a more expensive array. For this reason, we developed a set of 96 SNP markers that can unequivocally distinguish cultivars in apple collections and detect redundancy faster at low cost. To support this approach, we started from genome-wide SNP genotypic data obtained with the apple 20K and/or 480K arrays for 2120 unique individuals, including 2036 with a MUNQ code assigned through SSR markers. A total of 182 SNPs were tested using the KASP technology in nanofluidic Integrated Fluidic Circuit (IFC) to finally choose a set of 96 SNPs ensuring that each pair of individuals among all 2120 was distinguished by at least 6 SNPs in the absence of missing data. A comparison of MUNQ code assignment for 754 newly genotyped accessions using the standardized set of 16 SSRs and the new set of 96 SNPs was performed. It was possible to group accessions with essentially unique profiles using SNP data, and the groups obtained were almost always consistent with groups obtained with SSR data. Thus, a transition from the SSR-based MUNQ system to a SNP-based MUNQ system will be possible
FDI and human capital development: a tale of two Southeast Asian economies
Get PDFMiddle-income economies must prioritise human capital development to ensure long-term sustainable growth and economic upgrading. While foreign direct investment (FDI) is believed to aid this endeavour, its impact on technical vocational education and training (TVET) remains understudied. This research explores the influence of FDI by multinational enterprises (MNEs) at various stages of global value chains (GVCs) on TVET graduate numbers in Vietnam and Indonesia from 2006 to 2016. Our findings reveal that greenfield FDI plays a role in shaping TVET supply, with heterogeneous effects across different GVC segments and subnational regions. Specifically, FDI in logistics, sales and marketing, and support and servicing are associated with an increase in the supply of TVET graduates in the region, whereas FDI in headquarters and production may lead to a decline in technical skills. To address these dynamics, public policies should prioritise flexible education systems capable of adapting to MNEs' evolving skill demands. By doing so, these economies can elevate local human capital levels and avoid the stagnation often associated with middle-income traps. This research underscores the importance of aligning policy with the needs of a rapidly changing global economy to foster sustainable development
Animal-derived foods: consumption, composition and effects on health and the environment: an overview
Get PDFConsumption of animal-derived foods (ADFs), particularly red meat, is declining in high-income countries because of concerns over health and the effects on climate change but is increasing in low- and middle-income countries. As a group of foods, ADFs are high in good-quality protein and several key vitamins and minerals (notably vitamin B12, iron and zinc). There is evidence, though, that processed red meat poses risks of cardiovascular disease (CVD) and colorectal cancer and the same risks, although not so strong, are apparent for unprocessed red meat. Milk and milk products generally have a neutral disease risk and there is evidence of reduced risks of CVD and colorectal cancer. Similarly, white meat (chicken and fish) is not associated with disease risk whilst eggs have been linked with increased CVD risk because of their cholesterol content. The risks of chronic disease seem higher in high-income than in low- and middle-income countries, possibly due to different levels of consumption. Production of ADFs results in high greenhouse gas emissions per unit of output compared with plant proteins. Ruminant meat production has particularly high costs but wide variation between farms in different regions of the world suggests costs can be significantly lowered by changes to production systems. Reducing ADF consumption to benefit health and the environment has been proposed but in low-income countries, current levels of consumption of ADFs may be compatible with health and climate targets