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The purpose of this paper is to summarize the findings from focus group interviews conducted with librarians and library staff, faculty and students. It highlights the significance of implementing inclusive teaching and culturally responsive strategies in instructional settings and interactions with library patrons and seeks to emphasize the importance of developing guidelines, best practices and effective strategies.

Using focus groups, this study interviewed librarians and library staff, faculty and students. This research approach identified, reviewed and assessed existing programs and practices in instruction and library interactions.

The findings from this paper indicate that while faculty and librarians are making individual efforts to promote inclusivity in teaching and interacting with patrons, many participants expressed the necessity for institutional-level training, guidelines and good practices on how to achieve and implement culturally responsive and inclusive teaching strategies.

The methodology utilized in this study can be adapted by other libraries or institutions aiming to explore the practice of inclusive pedagogy and culturally responsive teaching within their own context. The insights from the study inform the development of strategies that librarians, faculty and staff can employ to integrate inclusive and culturally responsive teaching into their instruction and services for the wider academic community.

The PICCH research project contributes to opening a dialogue between cultural heritage archives and users. Hence, the users are identified and their information needs, the search strategies they apply and the search challenges they experience are uncovered.

A combination of questionnaires and interviews is used for collection of data. Questionnaire data were collected from users of three different audiovisual archives. Semi-structured interviews were conducted with two user groups: (1) scholars searching information for research projects and (2) archivists who perform their own scholarly work and search information on behalf of others.

The questionnaire results show that the archive users mainly have an academic background. Hence, scholars and archivists constitute the target group for in-depth interviews. The interviews reveal that their information needs are multi-faceted and match the information need typology by Ingwersen. The scholars mainly apply collection-specific search strategies but have in common primarily doing keyword searching, which they typically plan in advance. The archivists do less planning owing to their knowledge of the collections. All interviewees demonstrate domain knowledge, archival intelligence and artefactual literacy in their use and mastering of the archives. The search challenges they experience can be characterised as search system complexity challenges, material challenges and metadata challenges.

The paper provides a rare insight into the complexity of the search situation of cultural heritage archives, and the users’ multi-facetted information needs and hence contributes to the dialogue between the archives and the users.

This study aims to enhance the lubrication performance of thrust bearings. The influence of columnar convex–concave compound microtexture on bearing performance is investigated

Based on the compound microtexture model of thrust bearings, considering surface roughness and turbulent effect, the variation of lubrication characteristics with the change in the compound microtexture parameters is studied.

The results indicate that, compared with circular microtexture, the maximum pressure of compound microtexture of thrust bearings increases by 7.42%. Optimal bearing performance is achieved when the internal microtexture depth is 0.02 mm. Turbulent flow states and surface roughness lead to a reduction in the optimal depth. The maximum pressure and load-carrying capacity of the bearing decrease as the initial angle increases, whereas the friction coefficient increases with the increase in the initial angle. The lubrication performance is best for bearings with a circumferential parallel arrangement of microtexture.

The novel composite microtexture with columnar convex-concave is proposed, and the computational model of thrust bearings is set. The influence of surface roughness and turbulent flow on the bearing performance should be considered for better conforming with engineering practice. The effect of microtexture depth, arrangement method and distribution position on the lubrication performance of the compound microtexture thrust bearing is investigated, which is of great significance for improving tribology, thrust bearings and surface microtexture theory.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

This paper identifies that there are benefits that subsidiaries can reap when they are granted greater autonomy in decision making.

The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

The purpose of this paper is to propose an new online path planning method for porcine belly cutting. With the proliferation in demand for the automatic systems of pork production, the development of efficient and robust meat cutting algorithms are hot issues. The uncertain and dynamic nature of the online porcine belly cutting imposes a challenge for the robot to identify and cut efficiently and accurately. Based on the above challenges, an online porcine belly cutting method using 3D laser point cloud is proposed.

The robotic cutting system is composed of an industrial robotic manipulator, customized tools, a laser sensor and a PC.

Analysis of experimental results shows that by comparing with machine vision, laser sensor-based robot cutting has more advantages, and it can handle different carcass sizes.

An image pyramid method is used for dimensionality reduction of the 3D laser point cloud. From a detailed analysis of the outward and inward cutting errors, the outward cutting error is the limiting condition for reducing the segments by segmentation algorithm.

The purpose of this study is to explain the following questions: First, whether the executive equity incentive has an impact on enterprise innovation and digital transformation; Second, if there is any influence, whether there is difference between state-owned enterprises and private enterprises in the research conclusions; Third, whether the digital transformation of enterprises has had an intermediary effect between executive equity incentive and enterprise innovation; Fourth, whether the proportion of independent directors in the corporate governance mechanism has a regulatory effect.

In the context of China's promotion of “digital China” construction and high-quality development of economic innovation, this paper takes Shanghai and Shenzhen A-share listed companies in 2011–2019 as a sample, empirically studies the linear and nonlinear relationship between executive equity incentive and enterprise digital transformation and innovation, and further considers the regulatory effect of heterogeneous property rights and the proportion of independent directors, with a view to improving the reform of China's enterprise equity incentive system make contributions to enterprise innovation and digital transformation.

The results show that executive equity incentive has a positive role in promoting enterprise digital transformation and innovation, and enterprise digital transformation has a positive role in promoting enterprise innovation; Digital transformation of enterprises has a partial intermediary effect between executive equity incentive and enterprise innovation.

First, it expands the research on the economic consequences of enterprise salary incentive system. Second, it expands the research on the specific role path of enterprise digital economy transformation. Third, provide new ideas for the reform of corporate governance mechanism.

Due to the financial disturbances created by the COVID-19 pandemic and the burden on the government exchequer, it is expected to see a rise in the knowledge base of the research corpus so far as the government's fiscal sustainability is concerned. Therefore, the present research examines a systematic quantitative analysis of public debt sustainability research by applying a bibliometric approach. Research also analyzes journals, institutions, countries and authors contributing to public debt sustainability.

This paper scrutinizes the published scientific research on public debt sustainability based on the dataset of 535 articles from 1991 to 2021 obtained from the Scopus database. Biblioshiny (R-based application) and VoSviewer software were used to perform bibliometric analysis through Performance analysis and science mapping techniques. The authors combined co-citation analysis (CCA), bibliometric analysis, keyword co-occurrence analysis (KCA) and a conceptual thematic map of the most cited articles to find the intellectual structure.

The research identified three dominating clusters, e.g. fiscal sustainability and policy rules, empirical sustainability testing and debt and growth dynamics. Another finding was that most articles were analytical and empirical and few descriptive articles were found. Owing to the empirical nature of the domain, the issues concerning public debt sustainability have continued to change over the past decades for different economies, reflecting the complexity and diversity of economic structures of different economies at different times.

The insight of this article provides academicians and researchers with a more refined comprehension of the conceptual and intellectual structure of the research corpus. The present research complements the existing literature review studies by pushing the research towards emerging or less developed issues such as financial and debt crises.

This study aims to study the distribution characteristics of antibiotic resistance in direct-eating food and analysis of Citrobacter freundii genome and pathogenicity. Residual antibiotics and antibiotic resistance genes (ARGs) in the environment severely threaten human health and the ecological environment. The diseases caused by foodborne pathogenic bacteria are increasing daily, and the enhancement of antibiotic resistance of pathogenic bacteria poses many difficulties in the treatment of disease.

In this study, six fresh fruits and vegetable samples were selected for isolation and identification of culturable bacteria and analysis of antibiotic resistance. The whole genome of Citrobacter freundii isolated from cucumber was sequenced and analyzed by Oxford Nanopore sequencing.

The results show that 270 strains of bacteria were identified in 6 samples. From 12 samples of direct food, 2 kinds of probiotics and 10 kinds of opportunistic pathogens were screened. The proportion of Citrobacter freundii screened from cucumber was significantly higher than that from other samples, and it showed resistance to a variety of antibiotics. Whole genome sequencing showed that Citrobacter freundii was composed of a circular chromosome containing signal peptides, transmembrane proteins and transporters that could induce antibiotic efflux, indicating that Citrobacter freundii had strong adaptability to the environment. The detection of genes encoding carbohydrate active enzymes is more beneficial to the growth and reproduction of Citrobacter freundii in crops. A total of 29 kinds of ARGs were detected in Citrobacter freundii, mainly conferring resistance to fluoroquinolones, aminoglycosides, carbapenem, cephalosporins and macrolides. The main mechanisms are the change in antibiotic targets and efflux pumps, the change in cell permeability and the inactivation of antibiotics and the detection of virulence factors and ARGs, further indicating the serious risk to human health.

The detection of genomic islands and prophages increases the risk of horizontal transfer of virulence factors and ARGs, which spreads the drug resistance of bacteria and pathogenic bacteria more widely.

Manufacturing small and medium-sized enterprises (SMEs) are heading towards smart manufacturing despite growing challenges caused by globalisation and rapid technological advancement. These SMEs, particularly textile SMEs of Bangladesh, also face challenges in implementing sustainability and organisational ambidexterity (OA) due to resource constraints and limitations of conventional leadership styles. Adopting paradoxical leadership (PL) and entrepreneurial bricolage (EB) is important to overcome the challenges. However, these dynamics are less explored in academia, especially in the Bangladeshi textile SMEs context. Hence, the purpose of this study is to investigate the influence of the adoption of smart technologies (ASTs), PL and OA, EB on sustainable performance (SP) of textile SMEs in Bangladesh.

A cross-sectional and primary quantitative survey was conducted. Data from 361 textile SMEs were collected using a structured self-administrated questionnaire and analysed by partial least square structural equation modelling (PLS-SEM).

The statistical outcome confirms that ASTs and PL significantly influence SP and OA. OA plays a significant mediating role for PL and is insignificant for ASTs, and EB significantly moderates among ASTs, PL and SP.

As this study is cross-sectional and focussed on a single city (Dhaka, Bangladesh), conducting longitudinal studies and considering other parts of the country can provide exciting findings.

This research provides valuable insights for policymakers, management and textile SMEs in developing and developed countries. By adopting unique and innovative OA, PL and EB approaches, manufacturing SMEs, especially textile companies, can be more sustainable.

This study has a novel, pioneering contribution, as it empirically validates the role of multiple constructs such as AST, PL, OA and EB towards SP in the context of textile SMEs in a developing country like Bangladesh.

Light field images (LFIs) have gained popularity as a technology to increase the field of view (FoV) of plenoptic cameras since they can capture information about light rays with a large FoV. Wide FoV causes light field (LF) data to increase rapidly, which restricts the use of LF imaging in image processing, visual analysis and user interface. Effective LFI coding methods become of paramount importance. This paper aims to eliminate more redundancy by exploring sparsity and correlation in the angular domain of LFIs, as well as mitigate the loss of perceptual quality of LFIs caused by encoding.

This work proposes a new efficient LF coding framework. On the coding side, a new sampling scheme and a hierarchical prediction structure are used to eliminate redundancy in the LFI's angular and spatial domains. At the decoding side, high-quality dense LF is reconstructed using a view synthesis method based on the residual channel attention network (RCAN).

In three different LF datasets, our proposed coding framework not only reduces the transmitted bit rate but also maintains a higher view quality than the current more advanced methods.

(1) A new sampling scheme is designed to synthesize high-quality LFIs while better ensuring LF angular domain sparsity. (2) To further eliminate redundancy in the spatial domain, new ranking schemes and hierarchical prediction structures are designed. (3) A synthetic network based on RCAN and a novel loss function is designed to mitigate the perceptual quality loss due to the coding process.