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Digital assets (DAs) such as cryptocurrencies, tokenized securities, stablecoins, non-fungible tokens (NFTs), and central bank digital currencies, are transforming financial markets with new business models, investment opportunities, and transaction efficiencies. Underpinned by blockchain, distributed ledger technology, and smart contracts, digital innovations are reshaping the financial ecosystem. However, their rapid growth introduces substantial risks, including fraud, market manipulation, cybersecurity threats, and regulatory uncertainty. This position paper offers an interdisciplinary and empirically grounded analysis of the DA landscape. We define and classify major asset types, trace their evolution from speculative instruments to functional tools, and assess current adoption trends. Additional technological developments (e.g., decentralized finance and NFT expansion) are examined for their role in accelerating this transformation. We also analyze the global regulatory landscape, highlighting jurisdictional differences, classification challenges, and emerging governance frameworks. To address key risks, we derive mitigation strategies via quantitative analysis and case-based evidence. The risks include balancing innovation with investor protection through adaptive regulatory design, promoting cross-border regulatory harmonization to prevent arbitrage and fragmentation, and supporting experimentation through regulatory sandboxes and innovation hubs. By adopting a forward-looking, evidence-based, and collaborative regulatory approaches, stakeholders can harness the benefits of DAs while managing systemic risks and maintaining market integrity.

Artificial intelligence (AI) transforms extreme-weather forecasting by delivering faster and more accurate predictions at a fraction of the computational cost of traditional models. However, these advances are often accompanied by opaque decision processes, raising challenges for trust, equity, and long-term resilience in early warning systems. This article examines transparency in AI-based forecasting across three dimensions-predictive integrity, societal fairness, and long-term resilience-and argues that accuracy alone is insufficient in high-stakes contexts. Drawing on recent regulatory developments and global meteorological practice, we outline practical measures such as harmonized forecast labeling, impact-ready model cards, and extreme-event regulatory sandboxes. Embedding these measures within international frameworks is essential to ensure that the speed and efficiency of AI-driven forecasts translate into effective, trusted, and equitable early warning systems.

The secondary use of electronic health records (EHRs) poses legal challenges, particularly when the responsibility for managing EHRs lies with local or regional authorities. This article presents a case-based analysis of the secondary use of EHR data in contexts where data privacy responsibilities are managed regionally in Sweden. Using two distinct purposes for the secondary use of the digital tool Patient Overview Breast Cancer: (i) assessing the uptake of new treatment strategies in a real-world setting for quality assurance, and (ii) evaluating the effectiveness of these strategies in specific patient subgroups with limited evidence for research purposes, the study explored the distinctions between research and quality assurance, the legal implications of each framework, and the potential role of federated learning as a privacy-preserving technological solution. Federated learning offers a promising approach to overcome legal and organizational barriers to secondary use of regional EHRs in Sweden, enabling scalable, clinically meaningful insights for cancer care. However, its effective implementation requires a unified national framework that balances personal integrity with patient safety, supported by regulatory sandboxes.

Quantum computing (QC) is rapidly developing as an enabling technology that could potentially have major impacts in pharmaceutical drug research and development, but also faces significant challenges in terms of regulation in drug development and drug control contexts. The purpose of this review is to assess different ways that existing pharmaceutical regulations, both within and outside regions such as the EU and US, enable, limit, or necessitate modification for applications throughout the drug development process. A regulatory science-based analytical approach was used to examine how existing regulatory instruments, such as the FDA's Emerging Technology, EMA's DARWIN EU, and ICH, measure up to the validation, transparency, and reproducibility imperatives it is believed would emerge from drug development involving quantum technology. Relevant case studies were reviewed to provide context for new governance structures and global regulatory precursors. Although regulators have implemented various flexible pathways-including regulatory sandboxes, model-informed drug development, and adaptive licensing-these mechanisms currently still fail adequately to address the challenges of verification and auditability and the integrity of quantum algorithms for molecular modeling, pharmacogenomics, and pharmacovigilance. The main gaps were identified in ethical oversight, cybersecurity, and model validation standards. Coordinated regulatory science will help enable the safe, effective, and regulatory-acceptable use of quantum computing for pharmaceutical R&D. The combination of established standards in guidelines such as ICH E6(R3), GAMP 5, and GDPR with quantum-specific validation and governance pathways could enable responsible innovation while maintaining patient safety, data integrity, and public trust.

Ontario faces persistent diagnostic imaging (DI) challenges, which includes fragmented implementation of Artificial Intelligence (AI) solutions. The Canadian Association of Radiologists (CAR) has emphasized the need for freely available, modality-specific sandboxes to safely evaluate and refine AI tools prior to clinical use. In response, this paper proposes a provincially governed AI Sandbox for Diagnostic Imaging, designed to enable secure testing, validation, and scaling of AI innovations within a privacy-by-design framework. The AI Sandbox integrates six policy domains, such as clinical utility, ethics and privacy, technical design, governance, legal compliance, and sustainability, to guide responsible adoption. Supported by the Ontario Ministry of Health's commitment to trustworthy AI, this initiative aims to foster equitable, transparent, and system-wide innovation in diagnostic imaging.

Biofilm-associated bacterial infections, notorious for their resistance to standard therapies, pose a critical challenge in clinical practice. Micro and nanomotors (MNMs) have emerged as dynamic tools capable of penetrating biofilm matrices and enabling targeted antimicrobial delivery through autonomous motion. Recent advances in nanoarchitectonic design, spanning fuel-free or chemical propulsion, biohybrid systems, and multimodal actuation, significantly enhance their therapeutic precision and biocompatibility. This review critically examines the evolution of MNM materials, geometries, and designs, emphasizing their mechanical disruption of extracellular polymeric substances and synergistic bactericidal effects. Innovations such as cascade-driven MNMs and stimuli-responsive platforms demonstrate >90 % biofilm eradication in vitro and accelerated wound healing in vivo. What distinguishes this review from existing literature is its integrated focus on regulatory and translational barriers to clinical adoption, an aspect seldom addressed in prior MNM reviews. In addition to advances in materials and design, we discuss challenges that must be overcome for clinical translation, including long-term biosafety, degradation, scalable manufacturing under Good Manufacturing Practice (GMP), and regulatory ambiguities surrounding nanoscale medical devices. We outline a path forward for addressing these barriers by emphasizing the need for standardized toxicity testing, stronger interdisciplinary collaboration, and the use of emerging regulatory tools such as Safe(r) Innovation Approaches (SIA), the EU's Safe and Sustainable by Design (SSbD) initiative, and regulatory sandboxes to help accelerate clinical translation. By integrating material and design innovation with regulatory foresight, MNM technology holds transformative potential for combating antibiotic-resistant infections and redefining the eradication of biofilms.

Geothermal energy has been increasingly gaining attention with the global transition to sustainable energy. One critical component of utilizing geothermal energy is the borehole heat exchanger (BHE), which can extract thermal energy from or inject it into the ground. Sandbox tests are often used to assess the performance of BHEs and to validate the analytical and numerical models for BHEs. However, until now, there has been no design standard for sandbox tests; a systematic review of sandbox test setups for BHE applications is notably absent from the existing literature. To address this need, a comprehensive overview was conducted for sandbox test setups used for simulating and assessing BHEs. First, the physical components of the sandbox test were introduced, including the sandbox frame, heat exchanger pipes, filling materials, seepage conditions, grouting materials, and insulation layers. In addition, the setups of the physical components of existing sandbox tests were reviewed. Furthermore, the methods to determine sandbox size and experiment duration for sandbox tests were discussed. Finally, key issues were indentified in current sandbox setups, and new insights were given to address these challenges, providing new perspectives for designing sandbox tests and thus promoting geothermal energy research.

Elucidating key driving factors and the underlying mechanisms governing the complex subsurface fate of Light non-aqueous phase liquids (LNAPL) is essential for effective pollution characterization and remediation. Here, we develop the "data-mechanism" integrated framework DFEMR (dataset development - feature evaluation - mechanistic revelation). The DFEMR framework synergizes sandbox simulations with data-driven analysis to identify key driving factors through feature importance and XGBoost-SHAP (eXtreme Gradient Boosting - SHapley Additive exPlanations) contributions, which are mechanistically validated by targeted controlled experiments. Results showed a "tripartite spatiotemporal pattern" of LNAPL in the vadose zone, with total petroleum hydrocarbon (TPH) and environmental variables exhibiting an "accumulation-breakthrough" trend. "Position-Y" and "Volumetric Water Content (VWC)" achieved leading positions in the driving factors' ranking, while pH and "oxidation-reduction potential (ORP)" was identified as the regulatory factors. Critically, controlled experiments provided mechanistic explanations for data-driven insights: VWC modulated LNAPL's sorption and partitioning, altered its dynamic equilibrium at varying depths while synergizing with pH and ORP to achieve optimal biodegradation amount (5707-9638 mg/kg) and rate (22.21-24.37%) at 10-15% levels. Pilot-scale application confirmed the framework's generalization capability. DFEMR enhances interpretability of data-driven models and overcomes variable prioritization constraints of conventional experiments, offering a holistic approach for elucidating LNAPL migration and attenuation.

Digital advertising finances much of the open web, yet relies on tracking technologies that regulators increasingly seek to restrict. In response, industry has developed privacy-enhancing technologies intended to preserve advertising performance while limiting data collection, but their economic effects remain largely untested. We study this question using an open, industry-wide field experiment jointly overseen by Google and the UK Competition and Markets Authority, in which Chrome users were randomly assigned to browse with third-party cookies enabled, with cookies disabled, or with Google's Privacy Sandbox replacing cookies. Combining this experimental variation with proprietary data from a major ad management firm, we analyze more than 200 million ad impressions across over 5,000 publishers worldwide. Removing third-party cookies reduces publisher advertising revenue by 29.1%. Privacy Sandbox recovers only 4.2% of this lost revenue; this estimate reflects observed adoption and performance during the study period and may reflect modest industry adoption. Privacy-preserving auctions also increase ad latency, reducing impression delivery and further limiting revenue performance. Together, these findings provide a large-scale experimental benchmark for evaluating privacy-preserving reforms and demonstrate the difficulty of reconciling privacy protection with the economics of online content provision.

Most studies about the groundwater circulation well (GCW) and relevant approaches coupled with other remediation techniques were conducted under ambient temperature conditions. To address this gap, using a series of laboratory-scale sandbox experiments, complemented by numerical simulations, the present study aims to evaluate the remediation performances of this coupled thermal conductive heating (TCH) - GCW system for both the conservative tracer (brilliant blue) and the semi-volatile organic pollutant (nitrobenzene). For the conservative tracer, the remediation processes of the GCW were significantly expedited by heating, but the final remediated area and the remediation efficiency demonstrated similar results for different heating conditions. For example, under the heating temperature of 110 °C, the required remediation time consumption results for observation points had reduced by 2.5%-50% compared with the no-heating condition, but the final remediated area results under heating conditions only increased by less than 6%. For nitrobenzene, higher heating temperatures can lead to better remediation performances, especially in tailing zones. Under the heating conditions, the remediated areas of nitrobenzene increased from 53.95% to 99.74%, and the required remediation time consumption results decreased by 4%-95%. Based on scenario analysis using numerical simulations, the relative contributions of four mechanism processes for removing nitrobenzene using the TCH-GCW approach were quantified and ranked as: convection > > hydrodynamic dispersion > volatilization > adsorption, while the removal of the conservative tracer was attributed to convection. The removed masses and relative contributions of nitrobenzene due to dispersion and volatilization increased as the heating temperature increased.

Compact antennas with ultra-wideband operation and stable radiation are essential for portable and airborne ground-penetrating radar (GPR), yet miniaturization in the sub 3 GHz region is strongly constrained by the wavelength-driven aperture requirement and often leads to impedance discontinuity and radiation instability. This paper presents a compact aperture-slot antipodal Vivaldi antenna (AS-AVA) designed under a radiation stability-driven co-design strategy, where the miniaturization features are organized along the energy propagation path from the feed to the flared aperture. The proposed structure combines (i) aperture-slot current-path engineering with controlled meandering to extend the low-frequency edge, (ii) four tilted rectangular slots near the aperture to restrain excessive edge currents and suppress sidelobes, and (iii) back-loaded parasitic patches for coupling-based impedance refinement to eliminate residual mismatch pockets. A fabricated prototype on FR-4 (thickness 1.93 mm) occupies 111.15×156.82 mm2 and achieves a measured S11 below -10 dB from 0.63 to 2.03 GHz (fractional bandwidth 105.26%). The measured realized gain increases from 2.1 to 7.5 dBi across the operating band, with stable far-field radiation patterns; the group delay measured over 0.6-2.1 GHz remains within 4-8 ns, indicating good time-domain fidelity for stepped-frequency continuous-wave (SFCW) operation. Finally, the antenna pair is integrated into an SFCW-GPR testbed and validated in sandbox and outdoor experiments, where buried metallic targets and a subgrade void produce clear B-scan signatures after standard processing. These results confirm that the proposed AS-AVA provides a practical trade-off among miniaturization, broadband matching, and radiation robustness for compact sub 3 GHz GPR platforms.

This paper presents Jub, a Life Science and Healthcare Data Platform (LSHDP) based on generic sandboxes that integrate AI tools and cloud storage into big data science services. Jub automatically and transparently creates data science services to transform datasets into massive information products by using a profiling methodology. These products are presented by generic-secure cloud-based FAIR observatories adding Programmable, Configurable/Customizing, Adaptable, and Resiliency properties (PCA-FAIR-R). This enables organizations to conduct and customize complex analytics processes to support decision-making. We conducted a study case to convert mortality, climate, and pollutants datasets (2000-2023) reported by the Mexican Government into a solid core hub of information products: 16 strategic data observatories based on 85,171,404 information products created from 114,155,622 spatio-temporal profiles of the International Classification of Diseases (ICD-10) mortality classes/strata and cancerogenic substances. An exploratory study revealed highlights about the significance of breast cancer mortality rate growth showing possible associations with air pollutants. This paper also describes the lessons learned from the practice and experience of implementing Jub sandboxes-based observatories for the Population-based Cancer Registry Network deployed on the Mexican territory in 12 Mexican states by public healthcare institutions, as well as to implement bone cancer deep-learning-based diagnosis at a national Hospital.

Adolescent gaming addiction (GA) has been linked to a range of adverse health outcomes. However, whether the associated health risks differ across game genres remains poorly understood. Guided by VanderWeele's multidimensional flourishing framework, this study aims to examine genre-specific associations between GA and flourishing among adolescents. This study used a cross-sectional observational design. A total of 2194 middle school students were recruited via convenience sampling from a private tutoring center in a northwestern city in China. Eligibility criteria were (1) enrollment in participating classes at the tutoring center, (2) provision of both student and parental consent, and (3) presence during questionnaire administration. The mean age of participants was 14.53 (SD 0.76) years; 985 (44.90%) were boys and 1174 (53.51%) were girls. During class time, students completed paper-based questionnaires that assessed their demographics, gaming addiction, and flourishing. Participants listed up to 3 video games played in the past month and rated their addiction to each. Games were classified into 8 genres: action and adventure (AA), sandbox and simulation (SS), multiplayer online battle arena (MOBA), shooting, strategy, casual, sports, and role-playing. Flourishing was assessed using the Human Flourishing Index across 5 domains: happiness and life satisfaction, mental and physical health, meaning and purpose, character and virtue, and close social relationships. Robust linear regression analyses (α=.05) showed that AA addiction was associated with lower overall flourishing (b=-3.11, 95% CI -4.34 to -1.88) and all 5 subdomains (happiness and life satisfaction: b=-0.46, 95% CI -0.75 to -0.17; mental and physical health: b=-0.61, 95% CI -0.88 to -0.34; meaning and purpose: b=-0.55, 95% CI -0.82 to -0.27; character and virtue: b=-0.74, 95% CI -1.06 to -0.43; and close social relationships: b=-0.62, 95% CI -0.92 to -0.32). MOBA addiction was associated with lower overall flourishing (b=-1.33, 95% CI -2.34 to -0.32), character and virtue (b=-0.34, 95% CI -0.59 to -0.08), and meaning and purpose (b=-0.34, 95% CI -0.56 to -0.11). SS addiction was associated with lower overall flourishing (b=-3.42, 95% CI -5.80 to -1.04), close social relationships (b=-0.86, 95% CI -1.46 to -0.27), and mental and physical health (b=-1.09, 95% CI -1.60 to -0.58). This study provides novel evidence that the association between GA and adolescent flourishing is genre dependent. In contrast to prior research that conceptualizes health narrowly or unidimensionally, a multidimensional perspective provides a more nuanced understanding of the health risks associated with GA. The findings advance the field by showing that addiction to AA, MOBA, and SS games is associated with greater health risks than addiction to other genres. Accordingly, prevention, education, and policy efforts should prioritize higher-risk genres to promote adolescent health.

Background/Objectives:Rhodobacter sphaeriids is considered a promising biomanufacturing platform due to its capacity to convert CO2 into value-added products. To enhance the yield of CO2-derived products, understanding extracellular metabolite dynamics during autotrophic growth is essential. However, the extracellular metabolite profiles of R. sphaeroides under autotrophic conditions have not been reported. Methods: In this study, we performed a comprehensive analysis of extracellular metabolites produced under autotrophic conditions using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS) and liquid chromatography time-of-flight mass spectrometry (LC-TOFMS). Results: A total of 62 putative metabolites were detected, of which 23 were measured above the quantification limit. Metabolites involved in glycolysis and gluconeogenesis constituted the largest proportion of extracellular metabolites, with lactic acid exhibiting the highest accumulation levels. To investigate the transcriptional changes associated with metabolite accumulation, we analyzed gene expression and observed the downregulation of glycolytic genes, including pgi, gapB, and lctB, whereas cfxA, encoding fructose-1,6-bisphosphate aldolase, was upregulated under autotrophic conditions compared to heterotrophic conditions. Conclusions: These results suggest that the carbon assimilation metabolic flux in R. sphaeroides shifts toward the CBB cycle and lactic acid overflow metabolism under autotrophic conditions. Collectively, these findings provide new insights into metabolic regulation during autotrophic growth and offer a basis for reducing extracellular byproduct formation and improving CO2-based biological production in R. sphaeroides.

This Perspective examines Thailand's role in cell and gene therapy, focusing on regulatory development and early clinical experience. These therapies are used in Thailand for β-thalassemia, or blood cancer, together with the evolving ATMP regulatory framework and the ATMP Sandbox Project. Rather than cataloguing global indications, we analyze how selected advances intersect with Thailand's health system, highlighting opportunities and constraints for its role as a regional site for ATMP research, manufacturing, and access in Southeast Asia.