ABSTRACT This article analyses the role of digital technologies and readiness on the adoption of reduce, recycle, and redesign practices, the so-called twin transition. Using the Flash Eurobarometer 486, we apply multivariate probit models to determine the drivers of circular economy practices among European SMEs. We find that the adoption of advanced digital technologies and the development of digital capabilities within the firm are linked with the three key actions of the circular economy. Scale-ups benefit largely from digitalisation when developing all circular economy practices, but start-ups benefit from digital technologies only in the redesign of their existing products. In regard to public policies, our results highlight the importance of supporting a competitive and dynamic market structure to facilitate the twin transition and drive the emergence of digitalised start-ups and scale-ups.

Since the standardization of the grading system for pathologic diagnosis of antibody-mediated and acute cellular rejection, endomyocardial biopsy has remained the gold-standard. However, biopsies are invasive, costly, and limited by sampling error. As such, adjuvant non-invasive methods including cardiac biomarkers, imaging including cardiac magnetic resonance and echocardiography, and donor-specific antibodies and non-HLA antibodies have been traditionally used. However, all these techniques are limited by either sensitivity or specificity. More recently, there has been a shift to other contemporary non-biopsy surrogate markers for rejection surveillance including donor-derived cell free DNA, gene expression profiling, and messenger RNA and micro-RNA in tissue. Herein we review the methods currently utilized to diagnose rejection and their limitations. We find that while there have been significant advancements in technology and non-invasive techniques, no current method alone adequately diagnoses rejection ( Central Image ). Thus, future studies are warranted to investigate new strategies involving a multi-modal approach that incorporates non-invasive diagnostic methods and personalized medicine to monitor postoperative progression in heart transplant patients.

Medical and technological advances have increased the survival rate of children with congenital heart disease, which has led to a deeper understanding of various aspects of their subsequent development. Cardiovascular involvement has a direct impact on feeding, causing sucking and swallowing dysfunctions from birth that can trigger a series of consequences such as malnutrition, dysphagia, and clinical discomfort. This problem not only affects the physiological sphere but also the emotional and family dimensions. This article summarizes key findings in the growing literature on the impact of heart disease on pediatric nutrition and emphasizes the role of speech-language pathology. Further research on this issue is needed to provide greater knowledge that improves the quality of life of these children and their families.

Background Contemporary stroke rehabilitation protocols traditionally emphasise session frequency and treatment duration over intervention intensity—yet emerging evidence suggests we may be preparing patients for therapeutic marathons when their brains demand neuroplastic sprints. Across neuroscientific, behavioural, and clinical domains, convergent data indicate that repetition density, metabolic load, engagement, and temporal compression—not cumulative minutes—constitute the biologically meaningful drivers of neuroplastic and myoplastic adaptation. Objective This Perspective re-examines current rehabilitation paradigms through an intensity-centred lens, synthesising mechanistic evidence, clinical trials, and cross-cultural implementation models to determine whether high-intensity paradigms can more efficiently exploit neuroplastic windows and muscle adaptation dynamics. Methods Evidence was integrated from intensity-focused RCTs, high-repetition upper limb training, HIIT-based protocols, constrained-duration boot-camp models, and comparative observations from West-Cameroon intensive programmes. Mechanistic principles of threshold-dependent plasticity, critical timing windows, and therapeutic momentum were analysed alongside real-world feasibility data from low-resource systems. Results Across studies and contexts, high-intensity protocols—4–6 h/day for 3–4 weeks—consistently produced functional gains equivalent or superior to those achieved through conventional 1–2 h sessions over 12–16 weeks. Both neural and peripheral muscle plasticity responded more robustly to concentrated stimulation than to prolonged low-density regimens. Family-integrated programmes amplified therapeutic density and sustained momentum, demonstrating that intensity can be achieved without advanced technology. Conclusion Rehabilitation effectiveness depends less on session duration than on the biological potency of stimulation delivered per unit time. Intensity-centred models align more closely with known mechanisms of neuroplasticity and muscle adaptation, offering a more efficient, scalable, and context-responsive pathway to post-stroke recovery. Future research should formalise intensity indices, determine minimal effective thresholds, and evaluate phenotype-specific dosing strategies to support the evolution toward precision rehabilitation.

The rapid advancement of digital twin technologies, intelligent manufacturing, and the metaverse has led to an exponential growth of 3D model repositories. However, existing retrieval techniques struggle to accommodate complex user queries that often integrate multiple modalities, including geometric shape, semantic descriptions, structured attributes, and assembly hierarchies. To address this challenge, a novel intent-driven multimodal 3D model retrieval framework is proposed, which is built upon a multi-agent cognitive architecture to enable intelligent understanding and execution of cross-modal queries. At its core is a query-planning agent powered by large language models, which autonomously interprets complex user intents and breaks them down into sub-tasks. These sub-tasks are then executed collaboratively by specialised retrieval agents, including the vector retrieval agent, the structural topological agent, and the attribute filtering agent. A comprehensive database is constructed to incorporate geometric and semantic features, attribute metadata, and hierarchical assembly information. Furthermore, we introduce a multimodal clustering technique to enhance model organisation and retrieval efficiency. Experiments on the Fusion360 Assembly dataset demonstrate that the proposed multi-agent framework achieves superior efficiency and accuracy in handling complex, intent-driven 3D model search tasks.

The rapid advancement of digital technologies has fundamentally transformed modern business operations, making digitalization and information systems essential components of organizational success. This study aims to examine the importance of digitalization and information systems in business through a comprehensive literature review. Using a qualitative research approach, relevant academic articles, books, and conference proceedings were analyzed to identify key themes related to business performance, decision-making, competitive advantage, and implementation challenges. The findings reveal that digitalization significantly enhances operational efficiency, productivity, and customer responsiveness, while information systems such as management information systems, decision support systems, and enterprise resource planning systems play a crucial role in supporting data-driven decision-making and organizational integration. Additionally, the review highlights that digitalization contributes to innovation and sustained competitive advantage when aligned with organizational capabilities and strategic objectives. However, challenges including high implementation costs, skills gaps, cybersecurity risks, and resistance to change remain significant barriers, particularly for small and medium-sized enterprises. This study contributes to the existing body of knowledge by synthesizing fragmented literature and providing a holistic understanding of the strategic importance of digitalization and information systems in business. The findings offer valuable insights for researchers, practitioners, and policymakers seeking to navigate digital transformation effectively.

T-Cell Engagers (TCEs) have recently transformed the therapeutic landscape of hematological malignancies, including relapsed or refractory B-cell non-Hodgkin lymphoma (R/R B-NHL). However, the variability in patient responses underscores the need for a deeper mechanistic understanding of the factors driving efficacy. Immune cell composition and T-cell functional states are emerging as critical determinants of immunotherapy outcomes. Recent advances in scRNA-seq technologies have enabled high-resolution characterization of T-cell states, revealing a spectrum from highly activated effectors to exhausted or dysfunctional subsets within the tumor microenvironment (TME). In this study, we conducted longitudinal scRNA-seq analyses and functional assessments of peripheral blood immune cells (PBMC) from glofitamab-treated R/R B-NHL patients, achieving complete metabolic responders (CMR) or progressive metabolic disease (PMD). Our findings reveal that the maintenance of naive-like ("fresher") T-cell states (particularly the fresher cytotoxic T cells) at early timepoints is associated with clinical efficacy. In line with molecular data, T cells from responders exhibited enhanced functional activity compared to non-responders. Furthermore, the analysis of patient PBMCs and intra-tumor T cells from preclinical tumor models after consecutive glofitamab treatments revealed sustained functional activity, underscoring the long-term durability of T-cell responses. Combination of glofitamab with 4-1BB co-stimulation translated into increased proportions of intra-tumor T cells having a "fresher", naive-like phenotype, ultimately leading to stronger anti-tumor efficacy. Taken together, our findings underscore the therapeutic relevance of "fresher" naive-like T-cell states and the potential of leveraging 4-1BB co-stimulation to overcome TCE resistance and improve clinical responses in aggressive lymphomas.

Ni-based superalloys are critical materials in aerospace and power generation industries due to their exceptional high-temperature performance, achieved through carefully designed chemical compositions and meticulously controlled microstructures. Traditionally, these components are manufactured through subtractive processes that are costly and time-intensive, yet even these high-value components are prone to damage during prolonged service in harsh environments, necessitating innovative methods for manufacturing, remanufacturing, and repair. Recent advancements in 3D-printing technologies have demonstrated significant potential in addressing these needs, particularly for nonweldable Ni-based superalloys, but formidable challenges remain. Key issues include preventing crack formation, controlling crystal grain structure, and optimizing precipitate volume fraction and morphology to enhance mechanical properties. Here,an overview of the recent studies that have elucidated fundamental mechanisms underlying these challenges, such as elemental microsegregation, melt pool morphology, and the spatiotemporal distributions of microscopic defects and stresses, is presented. Based on these insights, strategies involving the optimization of printing parameters and the implementation of heat treatments are developed to improve the printability and microstructural controllability. By examining the fabrication of a turbine blade as an example, this review highlights the progress made, the persistent challenges, and future opportunities for the 3D printing of high-performance Ni-based superalloy components.

Growing global population and climate change concerns have caused major challenges for sustainable food production to meet the growing food demand. High mechanization, drought intensity, fertilizer application, energy use, and irregular climate change adaptation are the major challenges faced by agriculture. In the Kingdom of Saudi Arabia, the climate is very harsh, and the country depends highly on agriculture to meet domestic food demands. This generates major challenges for the agricultural system to produce sufficient quantities of food with minimal carbon footprints. Therefore, this study aims to analyze the impact of growing mechanization (Mech), water productivity (WP), climate change technology adaptation (CCA), fertilizer consumption (FC), agriculture growth (AG), and energy consumption in agriculture (ENA) on CO 2 emissions in agriculture in both the short and long run. For this purpose, an autoregressive distributed lag (ARDL) model was applied to the data for 1992–2021. According to the unit root test, all variables were integrated in order I(1), and the ARDL bound test for the cointegration tests ensured the long-run relationships among the variables. Moreover, the ARDL model passed all diagnostic tests, and CUSUM and CUSUMQ confirmed the stability of the model. The findings revealed that Mech has a strong negative impact in the long run while significant positive impact in the short run on CO 2 emission. Both WP and CCA significantly reduced CO 2 emissions in both the short and long run. FC causes an increase in CO 2 emissions in both the short and long run. AG reduces CO 2 emissions, whereas ENA increases CO 2 emissions only in the long run. The findings suggest that the government should focus on efficient and eco-friendly mechanization, energy sources, adoption of efficient irrigation systems, and promote R&D for advanced climate change-oriented technologies to enhance agricultural environmental sustainability by reducing CO 2 emissions in agriculture.

Expanding the Stokes shift of lead-halide perovskite nanocrystals (NCs) without compromising their sharp, fast excitonic emission has remained elusive, as high halide mobility erases the compositional gradients required for stable core/shell architectures. Here, it is shown that introducing a CdCl2 passivation step prior to halide exchange provides a simple solution. Treating CsPbCl3 NCs with CdCl2 eliminates halide-vacancy traps, enhances emission yield, and crucially blocks inward diffusion of I-, arresting the Cl- → I- exchange after just a few monolayers. This produces CsPbCl3/CsPbI3 core/shell NCs that absorb at 3.14eV from the core and emit at 1.91eV from the shell, achieving an apparent Stokes shift of ≈1.2eV. The heterostructures exhibit ≈70% photoluminescence quantum yield, fast emission lifetime (≈10ns) and complete suppression of reabsorption losses, as confirmed by liquid-waveguiding experiments. Transient absorption spectroscopy and DFT modeling reveal an inverted type-I band alignment with ultrafast (≈60ps) core-to-shell exciton transfer. This fully solution-processed chemistry enables heterostructuring-based wavefunction engineering - long employed to expand the capabilities of conventional quantum dots - now realized in perovskite NCs, which provides a practical route to reabsorption-free perovskite emitters for advanced photonic and quantum technologies.

Aqueous Zn-ion batteries (AZIBs) have been widely regarded as promising alternatives to Li-ion batteries (LIBs) owing to their intrinsic safety and cost-effectiveness. Nonetheless, spontaneous side reactions at the Zn anode dominate the platelet packing mode of Zn plating/stripping, thus undermining the anode's reversibility. To enable the future development of AZIBs, undesirable side reactions at the Zn anode need to be fully unveiled to understand intrinsic Zn plating/stripping processes. This review offers innovative and comprehensive insights to mitigate the side reactions at the Zn anode that have not been reported to date. It commences with a profound understanding of Zn redox chemistry with side reactions involved. Subsequently, the main initiators of side reactions are discussed; the mainstream strategies used to decouple main/side reactions are considered and analyzed from the thermodynamics and kinetics viewpoints based on different mechanisms; and cutting-edge research breakthroughs are summarized. Additionally, advanced characterization technologies are expounded, equipping readers with measures to intuitively detect side reactions. Finally, current challenges related to side reactions are presented, accompanied by proposed feasible solutions to inspire readers for the future development of AZIBs.

The severe shortage of donor organs and limitations of current disease models highlight the urgent need for transformative strategies in tissue engineering (TE) and regenerative medicine (RM). Bioprinting has emerged as a powerful approach for creating functional tissues and organs, yet current workflows remain labor-intensive, variable, and challenging to scale. The convergence of artificial intelligence (AI), advanced bioprinting technologies, robotics, biosensing, and cutting-edge biological methods is catalyzing the development of self-driving bioprinting laboratories-a fully integrated, autonomous, closed-loop system capable of designing, fabricating, maturing, and assessing living tissue constructs, as well as supporting seamless transplantation, with minimal human intervention. By integrating autonomous cellular farming, on-demand bioink formulation, intelligent optical and digital reconstruction platforms, AI-driven bioprinting, intelligent bioreactors, and robotic transplantation within a sterile, interconnected ecosystem, such platforms can continuously learn, adapt, and optimize workflows, enabling standardized, scalable tissue manufacturing and facilitating a seamless transition from bench to bedside. This perspective outlines the foundational technologies, opportunities, and challenges for realizing self-driving bioprinting, envisioning a future where intelligent, automated platforms transform TE and RM into a scalable, predictive, and clinically integrated discipline at the forefront of precision medicine.

Digital light processing (DLP) three-dimensional (3D) printing has been considered one of the most sustainable additive manufacturing methods for high-speed and high-resolution construction. As 3D printing technology advances, a continuous printing process is achieved, which brings controllable parameters along with printing. Herein, we propose a refilling-driven particle redistribution mechanism during continuous printing, enabling the simultaneous control of microparticle distribution and 3D functionalization. The microparticle properties (dimension, wettability, and quantity ratio) and printing speed influenced the microparticle moving tendency and distribution law, which are versatile for different kinds of microparticles. Based on the single-microparticle distribution law, the motion of multidimensional microparticles along the resin refilling process can be controlled, through which microparticles can be controlled to locate inside different parts of the cured structure or inside the liquid resin. Selective microparticle separation from multidimensional mixed microparticles can be realized, with the special characteristics of small microparticle extraction from mixed microparticles. In addition, one-step printing of a two-dimensional (2D) or 3D wetting pattern can thus be realized by regulating the location of microparticles with different wettabilities and ratios. The 3D wetting patterns of the outer surfaces of structures and microfluidic inner surfaces can be one-step-printed, which satisfies the urgent demand for functionality beyond simple structural fabrication and expands the application scope of continuous 3D printing.

Abstract Industry 4.0 and blockchain technology are transforming manufacturing processes with automation, real-time data exchange capabilities and promoting trust across the supply chain. However, the assessment of the readiness of Industry 4.0 and blockchain technology within the manufacturing sector is preliminary for the successful integration of these technologies and thus transforming manufacturing processes. While Industry 4.0 readiness is not a new concept, and several Industry 4.0 readiness models have been devised specifically for SMEs across developed countries, no blockchain-related readiness model could be traced in the literature. Additionally, developed countries are maturing in the adoption of advanced technologies, while developing countries have showcased challenges in embracing Industry 4.0 and blockchain technology. This study systematically reviews and compares the readiness factors for the adoption of Industry 4.0 and blockchain in the manufacturing sector to provide directions for future research for digital transformation. A total of 63 articles were reviewed and analysed. The findings reveal 33 dimensions with an overlap of 9 common readiness dimensions across Industry 4.0 and Blockchain readiness, while the rest of the dimensions are distinctive. Industry 4.0 readiness is primarily marked by integrating information technology across the business for data management and planning the strategic integration of advanced technologies. On the contrary, blockchain readiness is more contingent upon standardisation and infrastructure. The present research is among the few studies that offer a comparative analysis of the readiness dimensions identified for Industry 4.0 and blockchain. Manufacturing firms can use these insights for a holistic approach towards the adoption of Industry 4.0 and blockchain, ensuring a secure digital transformation.

Purpose This study aims to examine and estimate the impact of the transformation of banking operations from traditional banking to digital banking and income diversification on the stability of banks in Southeast Asian countries during the period from 2006 to 2021. Design/methodology/approach The study uses a Bayesian model to examine the impact of digital transformation (represented by the variables: BIS: Number of broadband internet subscribers, in thousands; and MB100: Number of mobile phone subscribers, per 100 people LN) along with bank income diversification represented by (LA: Bank liquid assets compared to deposits and short-term capital sources; and NII: Bank non-interest income compared to total income, in percent) on the stability of banks (represented by ZCORE: Z-score of the banking system). Data are taken from 2006 to 2021 at annual frequency in 10 countries: Brunei, Cambodia, Indonesia, Laos, Myanmar, Thailand, East Timor, Singapore, Malaysia and Vietnam. In addition, the study also conducts a robustness test of the research model through the use of ordinary least squares, fixed effects model, random effects model and feasible generalized least squares models. Findings When banks diversify their non-interest income, it creates positive effects on bank stability by reducing their dependence on traditional credit business activities, which contain many potential risks. However, the banking sector of Southeast Asian countries is in the early stages of digital transformation, so the cost of digitalization creates great pressure on financial capital flows and causes weakening of bank stability. Practical implications Cost is an issue that needs to be considered for the digital transformation process of banks. Banks can take advantage of technologies and technology transfer activities from advanced countries to shorten the time and reduce costs for the digitalization process of business activities. National development policies need to aim at equipping modern technology infrastructure to create an advanced ecosystem to support the digital transformation activities of banks. Banks need to integrate income diversification and digital transformation to aim for stable and sustainable development in the long term. Originality/value This study provides empirical evidence on the dual impact of income diversification and digital transformation on the stability of Southeast Asian banks. The study proposes several recommendations for policymakers to aim at achieving stable and sustainable growth for banks in Southeast Asia.

Premarital sexual behavior in adolescents is a public health issue influenced by various individual, social, and environmental factors. Changes in social norms, technological advancements, and limited reproductive health knowledge make adolescents a group vulnerable to risky sexual behavior. This study aims to examine the factors influencing premarital sexual behavior among adolescents based on the Health Belief Model (HBM) approach. The method used is a Systematic Literature Review (SLR), review national and international scientific articles published between 2013 and 2025. Data sources were abtained from Google Scholar and ScienceDirect, with inclusion criteria including articles in Indonesia and English, open access, full text, and relevant to HBM components. The study result indicate that factors such as perceived barriers, self-efficacy, and the quality of information play an important role in shaping adolescent sexual behavior. Low knowledge and limited perception oh the negative impacts of premarital sex increase the risk of engaging in risky sexual behavior. In addition, health promotion interventions based on the Health Belief Model (HBM) have been proven effective in improving knowledge, attitudes, and preventive behaviors regarding premarital sex among adolescents. Therefore, the HBM approach is recommended as a basis for developing comprehensive and sustainable adolescent reproductive health education and promotion programs.

Breast cancer is the most prevalent malignancy among women worldwide, and radiotherapy (RT) plays a central role in reducing local recurrence and improving survival. Technological advances such as three-dimensional conformal RT (3D-CRT), intensity-modulated RT (IMRT), volumetric-modulated arc therapy (VMAT), and particle therapies have enhanced dose conformity and reduced exposure to surrounding healthy tissues, particularly the lungs. Nevertheless, radiation-induced lung injury (RILI) remains a clinically relevant concern because of the close anatomical relationship between the breast and lung. RILI is a biphasic process, comprising early radiation pneumonitis and late radiation-induced pulmonary fibrosis, with severity influenced by dose distribution and treatment modality. While 3D-CRT carries a moderate risk due to limited beam modulation, IMRT and VMAT improve target coverage but may increase low-dose exposure to larger lung volumes, potentially increasing the risks of subclinical injury and, in the long term, secondary malignancy. Adjunctive lung-sparing strategies, including deep inspiration breath-hold and image-guided techniques, further reduce pulmonary dose. Proton beam therapy, particularly pencil beam scanning, offers additional lung protection through Bragg peak–based dose deposition, minimizing exit dose and irradiation of non-target tissues. Early clinical data suggest a lower incidence of RILI with PBT, although long-term outcomes remain under investigation. Carbon ion RT remains investigational in breast cancer. This review summarizes current evidence on RILI risk across modern RT modalities. A deeper understanding of modality-specific risks is essential for guiding personalized treatment planning and implementing effective lung-sparing strategies.

The cyborg and posthumanism era poses significant challenges to human understanding of identity, morality, and spirituality due to the dominance of science and technology. This article examines the concept of lex cybernetica from a Christian ethical perspective, emphasizing the ethical boundaries that believers must observe in engaging with technological advancement. Through theological and ethical approaches, this study highlights the moral issues arising from innovations such as artificial intelligence, biotechnology, nanotechnology, and virtual reality, in order to help individuals remain grounded in Christian values. Employing a qualitative methodology that includes case studies, literature review, and theological descriptive analysis, the findings discuss cyborgs and posthumanism, human–technology integration, and theological reflections on humans as co-creators, ideal creations, and the relationship between soteriology and eschatology within the context of technological development.

Rectal neuroendocrine tumors (rNETs) are among the most common NETs and account for approximately 12-27% of all gastrointestinal NETs in North America. Significant discrepancies persist in the management of NETS regarding surveillance strategies, staging modalities, high-risk features, and criteria for surgical intervention. This guideline updates current practices of rectal NETs stage I-III with the utilization of GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) methodology and consensus DELPHI agreement across leading experts in the North American region. Several technological advances such as 68-Gallium-or 64 Cu-DOTATATE SRRT PET/CT and broad adoption of pelvic MRI has improved staging of rNETs, along with modified endoscopic mucosal and submucosal resection and full thickness excision techniques that demonstrate efficacy and safety for resection. Pivotal long-term outcome studies provide insight to 1) risk factors for regional lymph node metastasis, 2) the impact of R1 excision (endoscopic), 3) best practices for intermediate sized rNETs (11-20mm), and 4) risk in small rNETs (<10 mm). Recommendations were developed upon evidence-based conclusions from the GRADE review to define the role of baseline staging with MRI, advanced endoscopy and transanal endoscopic surgical methods appropriate for T1 rNETs, the role of salvage therapy in cases of R1 resection, and the consideration of pathologic variables to direct definitive treatment and surveillance. Advances in screening programs and imaging allow for improved detection and staging of rNETs, while long-term outcome studies can better direct patients towards evidence-based treatment management and rectal organ preservation through less radical resection methods.

Purpose This study aims to explore an extended technology incentive model (TIM) alongside a third-order user evaluation construct to predict consumer behavioral outcomes (trust, flow, engagement, customer satisfaction and purchase intention) in the rapidly evolving food service industry. Over the past decade, and especially in the post-COVID-19 era, technological advancements such as Augmented reality (AR) and 3D visual enhancements have revolutionized consumer experiences, offering immersive, reality-like interactions that enhance engagement and satisfaction. Specifically, the study explores the impact of consumers' flow and trust on engagement, ultimately impacting their satisfaction and purchase intention in an AR-based food ordering platform setting. Design/methodology/approach A survey was conducted among the audiences of Kuala Lumpur, Malaysia, using purposive sampling. We finalized a sample of 391 for the statistical procedures to obtain the measurements and structural models. Findings Findings indicate that technological factors significantly influence behavioral factors. Drawing on the principles of adopting new technology to promote a business, this study advances in understanding how consumers respond to different technologies in food businesses. Originality/value This study's theoretical and practical implications offer valuable insights for enhancing the consumer's shopping experience through AR-based ordering platforms in food businesses.