Research Applications Research Articles

Compact remanence-free permanent magnet-based variable magnetic field source.

We demonstrate a simple and compact variable magnetic field source based on the permanent cube magnet array approximating a Halbach cylinder. The large air gap area accommodates standard cryostat tails while providing a high uniformity and magnetic field stability of up to 0.5T over regions of up to about a centimeter. It eliminates magnetic remanence effects and produces reproducible fields without the need for feedback. Thanks to the low cost and exceptional energy efficiency, it provides an accessible solution for modest magnetic field requirements in a wide range of research applications.

Walking borders, risk and belonging: the walking interview as biographical method and doing mobility justice

ABSTRACT This paper engages with the long history of work in Mobilities research and makes a contribution from a different angle, by introducing and discussing creative applications of biographical research using the walking interview as biographical method (WIBM), that captures the sensory, embodied, affective aspects of lived lives and lived experiences, the intersecting oppressions and possibilities for praxis, focusing upon research on borders, risk and belonging, funded by the Leverhulme Trust. It argues that applying the WIBM opens up possibilities for doing “mobility justice”, through a relational, cultural and socio-spatial examination and analysis of lived lives, in the context of geo-political, cultural worlds (and scales). In doing so, the paper examines, through two short examples, creative applications of walking as an arts-based practice through the walking interview as biographical method (WIBM) to contribute to doing “mobility justice” as a transdisciplinary practice, as an “ethical and just” process and practice. Methodologically, the paper opens a space for dialogue on the transformative role of walking, listening as partial understanding, (partial understanding because although incredibly powerful, the biographical method can never give us total knowledge/understanding of the lives of others and this is not its aim) “resonance” and the potential for solidarity, as part of an ethics of listening, including possible impact on policy and practice, especially in diverse research and social contexts.

3D modeling of normal skin and cutaneous squamous cell carcinoma. A comparative study in 2D cultures, spheroids, and 3D bioprinted systems.

The current cancer research and drug testing are primarily based on 2D cell cultures and animal models. However, these methods have limitations and yield distinct drug response patterns. This study addressed this gap by developing an innovativein vitrohuman three-dimensional (3D) normal skin model and a multicellular model of human cutaneous squamous cell carcinoma (cSCC) using 3D bioprinting technology. Comparative analyzes were performed between bioprinted 3D-cSCC model, consisting of HaCaT keratinocytes, primary normal human dermal fibroblasts and A431 cancer cells (tricellular), bioprinted 3D-A431 model composed of A431 cancer cells only (monocellular), A431 cancer cell spheroids, and conventional 2D models. The models were structurally characterized by light microscopy, immunofluorescence (LIVE/DEAD assay, confocal microscopy) and immunohistochemistry (hematoxylin/eosin, p63, vimentin, Ki67, epidermal growth factor receptor stainings). The spatial arrangement of the 3D models was analyzed using the ARIVIS scientific image analysis platform. All models were also functionally assessed by cetuximab (CTX) response testing with the MTS assay. 3D-cSCC models were maintained for up to 16 weeks. Morphological and histological examinations confirmed the presence of skin-like layers in the bioprinted 3D models of normal skin, and the intricate and diverse features of the bioprinted skin cancer model, replicating the criticalin vivocharacteristics. In both mono- and tricellular bioprinted tumor constructs, there was a gradual formation and continuous growth of spheroid-like clusters of cancer cells, significantly influencing the morphology of the models. Cancer cells in the 3D bioprinted constructs showed reduced sensitivity to CTX compared to spheroids and 2D cultures. This study underscores the potential of 3D multicellular models in elucidating drug responses and gaining a better understanding the intricate interplay of cellular components within the tumor microenvironment. Developing the multicellular 3D tumor model paves the way for new research critical to advancing fundamental cancer research and future clinical applications, particularly drug response testing.

Bringing Sustainable Development to the Corporate Level: Boards’ Cognitive Biases towards ESG and Relevant Debiasing Interventions

The proposed research is an attempt to view how internationally recognised principles of sustainable development can be implemented at the corporate level, in particular, how the company’s board of directors should respond to climate and environmental challenges. Specifically, the paper examines the problem of reducing board members' repeated cognitive biases towards such a mainstream governance concept as ESG (Environmental, Social and Corporate Governance). The research focuses on the five most well-known cognitive biases of a board towards ESG, often encountered and described conceptually in behavioural literature: over-optimism, status quo effect, confirmation bias, hyperbolic discounting, and groupthink. Subsequently, the paper draws recommendations for overcoming or mitigating these biases by introducing and describing several debiasing interventions and quality control tools. These tools are conditionally divided into three groups: changing incentives, optimising choice architecture, and debiasing training. The author believes that incorporating behavioural insights into an analysis of the board’s ESG commitment would bring a fresh perspective to this research area, which now is typically dominated by a rational choice framework. The paper combines theoretical analysis of the existing literature in law, behavioural economics and psychology with qualitative research application based on data obtained from first-hand observations, board empirical studies, questionnaires, and focus groups.

Multi-Layered Metamaterial Absorber: Electromagnetic and Thermal Characterization

Metamaterials, recognized as advanced artificial materials endowed with distinctive properties, have found diverse applications in everyday life, military endeavors, and scientific research. Starting from monolayer metamaterials, multilayer ones are increasingly researched, especially in the field of electromagnetic wave absorption. In this article, we propose a multilayer metamaterial-absorber (MA) structure comprising two resonant layers crafted with copper and FR-4 dielectric. The presented multilayer MA structure exhibited an absorption greater than 90% in a frequency range from 4.84 to 5.02 GHz, with two maximum absorption peaks at 4.89 and 4.97 GHz. The bandwidth of the multilayer MA surpassed that of the individual single-layer MAs, with extension fractions reaching 360% and 257%, respectively. Through the simulation and calculation, the field distribution and equivalent circuit model elucidated that both individual magnetic resonances and their interplay contribute significantly to the absorption behavior of the multilayer MA. The absorption of the proposed multilayer MA structure was also investigated for the oblique incidence in the transverse electric (TE) and transverse magnetic (TM) modes. In the TE mode, the absorption intensity of two maximum peaks was maintained at over 93% up to an incident angle of 40 degrees and dropped to below 80% at an incident angle of 60 degrees. In the TM mode, the absorption was more stable and not significantly affected by the incident angle, ranging from 0 to 60 degrees. An absorption greater than 97% was observed when the incident angle increased from 0 to 60 degrees in the TM mode. Additionally, the approach in our work was further demonstrated by adding more resonant layers, making 3- and 4-layer structures. The results indicated that the absorption bandwidths of the 3- and 4-layer structures increased by 16% and 33%, respectively, compared to the bilayer structure. Furthermore, we analyzed the thermal distribution within the MA to understand the dissipation of absorbed electromagnetic energy. This research offers valuable insight into the augmented MA through a multilayer structure, presenting the implications for microwave applications like electromagnetic shielding, as well as in the design of MAs for terahertz devices and technologies, including emission and thermal imaging. These findings contribute to the advancement of knowledge in enhancing the absorption capabilities across various frequency ranges, expanding the potential applications of metamaterials.

Multiscale differential geometry learning of networks with applications to single-cell RNA sequencing data

Single-cell RNA sequencing (scRNA-seq) has emerged as a transformative technology, offering unparalleled insights into the intricate landscape of cellular diversity and gene expression dynamics. scRNA-seq analysis represents a challenging and cutting-edge frontier within the field of biological research. Differential geometry serves as a powerful mathematical tool in various applications of scientific research. In this study, we introduce, for the first time, a multiscale differential geometry (MDG) strategy for addressing the challenges encountered in scRNA-seq data analysis. We assume that intrinsic properties of cells lie on a family of low-dimensional manifolds embedded in the high-dimensional space of scRNA-seq data. Multiscale cell–cell interactive manifolds are constructed to reveal complex relationships in the cell–cell network, where curvature-based features for cells can decipher the intricate structural and biological information. We showcase the utility of our novel approach by demonstrating its effectiveness in classifying cell types. This innovative application of differential geometry in scRNA-seq analysis opens new avenues for understanding the intricacies of biological networks and holds great potential for network analysis in other fields.

Spotlight on a Thought Leader - How to Become an Effective Communicator: Schulz von Thun’s Contribution to Business Communication

This article explores the ingredients of effective business communication, presenting the extensive work of German psychologist and communication expert Friedemann Schulz von Thun. Over the course of his 50-year career, Schulz von Thun has developed numerous frameworks and tools that enhance our understanding of how to talk to one another to settle disagreements, promote strong relationships and foster individual as well as organizational success. We offer a concise synthesis of his most influential concepts (i.e., the square of communication, the inner team, and the value square) and illustrate their application in communication research and practice.

Force-Encoding DNA Nanomachines for Simultaneous and Direct Detection of Multiple Pathogenic Bacteria in Blood.

Pathogen detection is growing in importance in the early stages of bacterial infection and treatment due to the significant morbidity and mortality associated with bloodstream infections. Although various diagnostic approaches for pathogen detection have been proposed, most of them are time-consuming, with insufficient sensitivity and limited specificity and multiplexing capability for clinical use. Here, we report a force-encoding DNA nanomachine for simultaneous and high-throughput detection of multiple pathogens in blood through force-induced remnant magnetization spectroscopy (FIRMS). The force-encoding DNA nanomachines coupled with DNA walkers enable analytical sensitivity down to a single bacterium via a cascade signal amplification strategy. More importantly, it allows for rapid and specific profiling of various pathogens directly in blood samples, without being affected by factors such as light color and solution properties. We expect that this magnetic sensing platform holds great promise for various applications in biomedical research and clinical diagnostics.

Mutual information between joint angles and toe height in healthy subjects

Understanding the relationship between the position of the foot and the lower limb joint angles during normal gait is critical for the identification of the mechanisms involved in pathological gait. In this article, we introduce a novel framework that characterizes this relationship using mutual information in healthy subjects. The nonlinear connection between these variables is quantified using mutual information, and the MINE algorithm is used for precise estimation. Several simulations over Gaussian bivariate random variables reveal that overfitting is a critical factor affecting mutual information estimations by MINE, and we propose a simple methodology to address this issue when using gait signals. Our findings indicate that the statistical dependency between joint angles and toe height is symmetrical between the limbs for healthy subjects. Additionally, our results show that the ipsilateral knee angle holds the most significant amount of information regarding the toe height. In simpler terms, this knee angle serves as the most reliable predictor for toe height, and vice versa. To further enhance our understanding, we have developed a mutual information reference profile that enables the comparison of how the relationship between these biomechanical variables evolves under pathological conditions. The findings have significant implications for gait analysis and may aid in the identification and understanding of gait abnormalities in various contexts, contributing to the advancement of biomechanical research and clinical applications.

FlashPCR: Revolutionising qPCR by Accelerating Amplification through Low ∆T Protocols.

Versatility, sensitivity, and accuracy have made the real-time polymerase chain reaction (qPCR) a crucial tool for research, as well as diagnostic applications. However, for point-of-care (PoC) use, traditional qPCR faces two main challenges: long run times mean results are not available for half an hour or more, and the requisite high-temperature denaturation requires more robust and power-demanding instrumentation. This study addresses both issues and revises primer and probe designs, modified buffers, and low ∆T protocols which, together, speed up qPCR on conventional qPCR instruments and will allow for the development of robust, point-of-care devices. Our approach, called "FlashPCR", uses a protocol involving a 15-second denaturation at 79 °C, followed by repeated cycling for 1 s at 79 °C and 71 °C, together with high Tm primers and specific but simple buffers. It also allows for efficient reverse transcription as part of a one-step RT-qPCR protocol, making it universally applicable for both rapid research and diagnostic applications.

Attention‐generative adversarial networks for simulating rain field

AbstractThe synthesis of rain fields is essential in multiple research fields and applications, including Single‐image Derain. However, there is a lack of research on simulated rain fields, and the existing rain field generation models struggle to capture complex spatial distributions and generate truly random rain fields. To address this, the authors propose a generative adversarial networks‐based rain field generation network, which consists of a generator, a discriminator, and a feature extraction block that can produce realistic and complex rain fields. The authors’ experiments demonstrate that this method achieves an average Frechet Inception Distance score of 0.035, and user studies indicate that the generated rain distribution looks naturally.

Theoretical Research and Practical Application of the Rural Cultural Enhancement by Creative Designs Under Rural Vitalization—A Case Study of Shanxi Province

Theoretical Research and Practical Application of the Rural Cultural Enhancement by Creative Designs Under Rural Vitalization—A Case Study of Shanxi Province

Co-delivery of doxorubicin and STING agonist cGAMP for enhanced antitumor immunity

Many chemotherapeutic agents can induce immunogenic cell death (ICD), which leads to the release of danger-associated molecular patterns (DAMPs) and tumor-associated antigens. This process promotes dendritic cells (DCs) maturation and cytotoxic T lymphocyte (CTL) infiltration. However, cancer cells can employ diverse mechanisms to evade the host immune system. Recent studies have shown that stimulator of interferon genes (STING) agonists, such as cGAMP, can amplify ICD-triggered immune responses and enhance the infiltration of immune cells into the tumor microenvironment (TME). Building upon these findings, we constructed a doxorubicin (DOX) and cGAMP co-delivery system (DOX/cGAMP@NPs) for melanoma and triple-negative breast cancer (TNBC) therapy. The results demonstrated that DOX could effectively destroy tumors and induce the release of DAMPs by ICD. Furthermore, in orthotopic 4T1 tumors mice model and subcutaneous B16 tumor mice model, cGAMP could promote the maturation of DCs and CD8+ T cell activation and infiltration by inducing the secretion of type I interferons and pro-inflammation cytokine, which amplified the antitumor immune response induced by DOX. This strategy also promoted the depletion of immunosuppressive cells, potentially alleviating the immunosuppressive TME. In conclusion, our study highlights the combination of DOX-induced ICD and the immune-enhancing properties of cGAMP holds significant implications for future research and clinical applications.

Flexural behaviors of a novel precast hollow UHPC composite beam reinforced with inverted T-shaped steel: Experimental investigation and theoretical analysis

To fully utilize the excellent mechanical properties and durability of ultra-high performance concrete (UHPC) as well as reduce the production cost, a novel UHPC encasing inverted T-steel (PUES) composite beam with hollow section is proposed in this paper. This paper aims to study the flexural behaviors of PUES beams, a bending test program consisted of one solid PUES beam and seven hollow PUES beams is carried out. The test parameters include thickness of inverted T-shape steel flange, tensile reinforcement ratio and stud spacing. The results showed that the PUES beams failed in the typical flexural failure mode and exhibited excellent ductility without obvious drop in load. Compared to composite beam with solid section, the hollow section had negligible influence on the flexural performance of PUES beams, while it saved 26 % UHPC used compared with the one with solid section. The increasing of the thickness of inverted T-shape steel flange and the reinforcement ratio effectively improved the stiffness and the flexural capacity of PUES beams, while the larger diameter of reinforcement incurred an obvious reduction of ductility. An excessively large stud spacing resulted in a poor composite behavior and a reduction of flexural capacity. Based on the analysis of the experimental results, calculating methods considering the shear connection degree between inverted T-steel and peripheral reinforced UHPC were developed to predict the ultimate flexural capacity of the hollow PUES beams. This study provides a reference for further research and practical engineering applications of this innovation composite beam.

Bibliometric Analysis of Research Hotspots and Frontiers in Progress towards the Sustainable Development Goals

The United Nations Sustainable Development Goals (SDGs), established in 2015, are binding targets for monitoring the sustainable status of all countries in the world. Developing localized SDGs indicator systems, assessing SDGs progress comprehensively, and creating policy tools have gradually become the hotspots of scientific research and practical application of the SDGs. To systematically sort out the research status of the SDGs progress and identify problematic gaps, this paper uses bibliometric methods to analyse the scientific knowledge mapping of SDGs research, sort out the general characteristics, scientific cooperation, cutting-edge hotspots and future research trends of SDGs research. Besides, this paper promotes the integration of academic research into concrete practice by linking it to mainstream SDGs progress reports. The results show that: ① The amount of SDGs research literature in 2015–2022 is on a growing trend, and the existing research is characterised by multidisciplinary crossover. Research institutions such as Utrecht University, the Chinese Academy of Sciences, and the University of the Chinese Academy of Sciences have contributed the most to SDGs research. ② The research hotspots include the SDGs practice of different responsible subjects, the comprehensive assessment of the progress of SDGs, the scientific research of SDGs indicators, and the research on the interaction between the goals of SDGs. ③ Environmental issues, indicators, energy transition, education and agriculture are the hot directions of SDGs research. Energy saving and carbon reduction, sustainable practices of supply chain management, and promoting the progress of environmental dimension goals are the focus of subsequent research. According to the results of the bibliometric analysis, future SDGs research should pay attention to strengthening multi-party cooperation, using innovative technologies to support the assessment of SDGs progress, and formulating sustainable development strategies.

Construction of a New Probe Based on Copper Chaperone Protein for Detecting Cu2+ in Cells.

Biomacromolecular probes have been extensively employed in the detection of metal ions for their prominent biocompatibility, water solubility, high selectivity, and easy modification of fluorescent groups. In this study, a fluorescent probe FP was constructed. The probe FP exhibited high specificity recognition for Cu2+. With the combination of Cu2+, the probe was subjected to fluorescence quenching. The research suggested that the probe FP carried out the highly sensitive detection of Cu2+ with detection limits of 1.7 nM. The fluorescence quenching of fluorescamine was induced by Cu2+ perhaps due to the PET (photoinduced electron transfer) mechanism. The FP-Cu2+ complex shows weak fluorescence, which is likely due to the PET quenching effect from Cu2+ to fluorescamine fluorophore. Moreover, the probe FP can be employed for imaging Cu2+ in living cells. The new fluorescent probe developed in this study shows the advantages of good biocompatibility and low cytotoxicity. It can be adopted for the targeted detection of Cu2+ in cells, and it has promising applications in the mechanism research and diagnosis of Cu2+-associated diseases.

Knowledge, Perceptions and Attitude of Researchers Towards Using ChatGPT in Research.

ChatGPT, a recently released chatbot from OpenAI, has found applications in various aspects of life, including academic research. This study investigated the knowledge, perceptions, and attitudes of researchers towards using ChatGPT and other chatbots in academic research. A pre-designed, self-administered survey using Google Forms was employed to conduct the study. The questionnaire assessed participants' knowledge of ChatGPT and other chatbots, their awareness of current chatbot and artificial intelligence (AI) applications, and their attitudes towards ChatGPT and its potential research uses. Two hundred researchers participated in the survey. A majority were female (57.5%), and over two-thirds belonged to the medical field (68%). While 67% had heard of ChatGPT, only 11.5% had employed it in their research, primarily for rephrasing paragraphs and finding references. Interestingly, over one-third supported the notion of listing ChatGPT as an author in scientific publications. Concerns emerged regarding AI's potential to automate researcher tasks, particularly in language editing, statistics, and data analysis. Additionally, roughly half expressed ethical concerns about using AI applications in scientific research. The increasing use of chatbots in academic research necessitates thoughtful regulation that balances potential benefits with inherent limitations and potential risks. Chatbots should not be considered authors of scientific publications but rather assistants to researchers during manuscript preparation and review. Researchers should be equipped with proper training to utilize chatbots and other AI tools effectively and ethically.

Analysis of physical and mechanical properties of granite under different cooling methods under high-temperatures thermal cycles

This study explores the impact of external pressure and high-temperature erosion on the physical and mechanical properties of granite, the geothermal well storage medium, during geothermal exploitation. Objectives include evaluating the effects of repeated heating and cooling cycles at different temperatures on porosity, permeability and mechanical performance, with a focus on confining pressure's influence on permeability. The results indicate that under water-cooling and ambient conditions, porosity and permeability increase with cycle repetition, whereas compressive strength and elastic modulus decrease. Notably, Group B's (water-cooled) mechanical performance surpasses that of Group A (room temperature cooling) when porosity is below 1.5%. However, with increasing porosity owing to thermal cycling, Group B's granite becomes inferior to that of Group A. Micro-computed tomography scans reveal a post-cycling granite pore structure dominated by horizontal cracks, with primary uniaxial compression damage in the vertical direction. Thermal cycling reduces crack paths and load-bearing capacity, diminishing granite's mechanical performance. This study offers insights into subtle interactions between cooling methods and porosity during geothermal energy exploitation. It provides valuable guidance for optimizing geothermal energy use and mitigating potential adverse impacts on rock integrity, laying a foundation for further research and practical applications in geothermal energy exploitation.

An Image Classification Method of Unbalanced Ship Coating Defects Based on DCCVAE-ACWGAN-GP

Affected by the improper operation of the workers, environmental changes during drying and curing or the quality of the paint itself, diverse defects are produced during the process of ship painting. The traditional defect recognition method relies on expert knowledge or experience to detect defects, which is not conducive to ensuring the effectiveness of defect recognition. Therefore, this paper proposes an image generation and recognition model which is suitable for small samples. Based on a deep convolutional neural network (DCNN), the model combines a conditional variational autoencoder (DCCVAE) and auxiliary conditional Wasserstein GAN with gradient penalty (ACWGAN-GP) to gradually expand and generate various coating defect images for solving the overfitting problem due to unbalanced data. The DCNN model is trained based on newly generated image data and original image data so as to build a coating defect image classification model suitable for small samples, which is conducive to improving classification performance. The experimental results showed that our proposed model can achieve up to 92.54% accuracy, an F-score of 88.33%, and a G mean value of 91.93%. Compared with traditional data enhancement methods and classification algorithms, our proposed model can identify various defects in the ship painting process more accurately and consistently, which can provide effective theoretical and technical support for ship painting defect detection and has significant engineering research value and application prospects.

Reimagining learning through AI art: the promise of DALL-E and MidJourney for education and libraries

Purpose This paper aims to explore the potential impact of artificial intelligence (AI) image generators, specifically MidJourney and DALL-E, on education and library services. The study aims to understand how these tools can revolutionize learning experiences and library resources while also addressing the ethical considerations surrounding their use. Design/methodology/approach This study investigates the technical foundations of MidJourney and DALL-E, highlighting their neural network architectures. It also traces the iterative refinement of these models and examines cost, accessibility and the unique prompt-guided capabilities of DALL-E 3. Findings MidJourney and DALL-E show remarkable progress in generating high-quality, photorealistic images from text prompts. The iterative refinement of these models demonstrates a trend toward improved creative output and user accessibility. DALL-E 3, in particular, allows users to guide image generation through prompt modifications, offering unprecedented control over the creative process. The study identifies potential applications in personalized learning, visual communication and research support in libraries, while recognizing challenges such as cost and accessibility. Originality/value This research innovatively explores AI's impact on education and libraries, detailing applications in personalized learning and research while addressing legal and ethical considerations.