Search Results (709)

Precision agriculture and sustainable farming practices require autonomous environmental monitoring systems capable of operating in remote areas with limited energy and connectivity. However, the high cost of existing professional technology remains a significant barrier to widespread adoption. This study presents the development of a solar-powered smart sensing node designed for autonomous operation that integrates TinyML and dual-mode wireless connectivity via LoRaWAN and Wi-Fi for intelligent monitoring. The system features a custom-designed cup anemometer and multispectral sensing capabilities integrated into a compact single-tower architecture. All structural components, including radiation shields and a modular PVC frame, were designed for low-cost manufacturing and mass production. A single hermetic housing protects the core control electronics and is designed to improve durability in harsh outdoor environments. A Multi-Layer Perceptron model was implemented on the edge to enable intelligent data fusion and compensation, while a dynamic sampling strategy optimized power consumption. Experimental results demonstrate the feasibility of the proposed architecture through adaptive spectral acquisition over a daily illumination cycle, embedded MLP-based sensor fusion, and telemetry-oriented data compression that substantially reduces the number of transmitted samples. The main contribution of this work is a system-level architecture that integrates sensing, embedded intelligence, solar-energy harvesting, hybrid wireless communication, and telemetry optimization into a compact, low-cost, and field-deployable prototype IoT platform for sustainable precision agriculture. Full article

Child marriage remains a persistent barrier to girls and young women’s education, health, and socioeconomic advancement in many parts of Sub-Saharan Africa. This paper examines the perceived economic empowerment initiatives contributed to expanding life choices, including the prevention of child marriage and the delay of early marriage, within the Girls Get Equal (GGE) project implemented between 2020 and 2024 across three districts (Nkasi, Kalambo and Sumbawanga DC) in the Rukwa Region of Tanzania between 2020 and 2024. The paper adopted an explanatory mixed-methods case study design to explain aggregated project outcome indicators with participants’ lived experiences captured through focus group discussions and key informant interviews. Endline evaluation interviews and focus group discussions were re-analyzed using a six-stage thematic analysis approach. The paper demonstrates that imparting skills in technical and business fields leads to robust job creation outcomes. A large majority of trained youth transitioned into employment or self-employment and a substantial proportion maintained stable income-generating activities. On top of that, community-based infrastructures, particularly savings and loan groups, emerged as important financial mechanisms as they enabled structures supporting enterprise development and household resilience. The integration of quantitative trends and qualitative narratives suggests that economic empowerment interventions can expand girls’ economic agency and influence their informed decision-making processes related to marriage. Finally, the findings suggest that combining vocational skills development with access to financial capital represents a promising pathway for addressing structural drivers of early and child marriage in economically vulnerable contexts. Full article

While enterprise artificial intelligence (AI) adoption is crucial for high-quality economic development, many companies have yet to adopt AI in practice. Enterprise quality management (QM), serving as an internalized foundation of standardized processes and data governance, may critically enable AI adoption, yet this relationship remains underexplored. Utilizing panel data from Chinese A-share listed companies (2007–2023), we employ a fixed-effects regression model, supplemented by a series of methods to address endogeneity, including the instrumental variables approach, difference-in-differences, and event studies. Results indicate that QM significantly promotes enterprise AI adoption, which further enhances enterprise performance. This positive effect of QM on AI adoption is amplified by high innovation sustainability and chief executive officers (CEOs) with IT backgrounds, and is particularly pronounced in large, non-state-owned firms within highly competitive industries and the eastern regions of China. Theoretically, this study extends the literature on the antecedents of AI adoption by identifying enterprise QM as a crucial, yet overlooked, internal driver. Practically, aligning AI integration with established quality frameworks, cultivating leadership with IT expertise, and fostering a supportive environment provide a viable pathway to overcome AI adoption barriers. Full article

Additive manufacturing, also known as 3D printing (3DP), is intended to enable personalised medicine by producing drug products on demand at the Point of Care (PoC), with dose, drug-release profile, and geometry tailored to the individual patient. Despite its promise, widespread adoption is limited by the absence of ready-to-use quality control (QC) methods for printlets at the PoC. Process Analytical Technology (PAT) tools, particularly vibrational spectroscopic methods like Near-Infrared and Raman spectroscopy, can offer real-time monitoring to ensure the safety and consistency of printed dosage forms. Integrating these tools within a Quality-by-Design (QbD) framework can enhance process understanding, control variability, and minimise risk. Regulatory implementation and technological innovation remain essential for the broader clinical implementation of 3DP in pharmaceutical manufacturing. This review presents an overview of currently existing studies on PAT tools explored for non-destructive quality control across 3DP techniques, examines the correlation between Critical Process Parameters (CPPs), Critical Material Attributes (CMAs), and the Critical Quality Attributes (CQAs) of 3D-printed dosage forms within a QbD context, and outlines the current regulatory landscape alongside key limitations and future directions for the broader integration of 3DP into pharmaceutical development and manufacturing. Current evidence shows that PAT application remains uneven across printing technologies and is predominantly directed at final product quality control, rather than the real-time process monitoring required for a fully closed-loop QbD framework. Existing spectroscopic models are largely restricted to single formulations, printers, and APIs, and the absence of standardised validation reporting and transferability assessments represents a key barrier to routine implementation. Full article

Digital Twin technologies hold significant promise for advancing smart campus initiatives by enabling data-driven management of facilities, sustainability planning, and safety monitoring. Despite this potential, affordability remains a critical barrier to widespread adoption across higher education institutions. This study introduces an initial exploratory scenario-based affordability index for campus digital twin and maps the affordability of implementing campus digital twin across 1872 U.S. higher education institutions using spatial analysis techniques. Sensitivity analysis is also conducted to evaluate the robustness of the results. Our analysis yields three key findings: (1) Under the baseline scenario, most campuses show moderate-to-high affordability with spatial clusters concentrated in coastal and metropolitan regions, while nearly one-quarter remain unaffordable or marginally affordable, with clusters located in the Midwest. (2) Private institutions demonstrate relatively greater affordability than public institutions, with for-profit private institutions exhibiting higher affordability than their non-profit counterparts. Spatial aggregation patterns further reveal heterogeneity in affordability between these sectors. (3) States with strong economic and educational infrastructures, such as California, contain a greater number of affordable campuses for digital twin implementation, while resource-constrained states face significant barriers. These findings remain generally robust and consistent across the baseline and sensitivity scenarios. The results underscore the need for standardized cost models, public cost databases, targeted policy guidance, and multi-stakeholder collaboration to promote equitable adoption. By positioning digital twins as strategic tools for campus resilience, efficiency, and innovation, this study advances the conceptual understanding of their role in higher education and provides exploratory yet actionable insights for institutional leaders and policymakers to support inclusive digital transformation. Full article

Aluminium is increasingly being adopted in large-scale structural applications due to its high strength-to-weight ratio, corrosion resistance, and excellent recyclability, making it attractive for automotive, aerospace, infrastructure, and renewable energy sectors. Despite these advantages, welding remains a major barrier to the wider use of aluminium in load-carrying structures. This challenge is particularly critical for precipitation-hardened 6xxx series aluminium alloys, where welding-induced thermal cycles can lead to significant strength degradation in the heat-affected zone (HAZ). Strength losses of up to approximately 50% may occur as a result of precipitate dissolution and coarsening. In addition, weld quality can be further compromised by defects such as porosity and lack of fusion. Laser-based welding has emerged as a promising alternative to conventional arc welding due to its high energy density and low overall heat input. These characteristics enable narrower HAZ, reduced distortion, and improved mechanical performance of welded joints, while also offering high productivity and potential cost reductions in the fabrication of large aluminium structures. This paper details industrial challenges, weldability limits, and the mechanisms of beam oscillation, which has emerged as a primary solution for stabilising the keyhole, suppressing porosity, and refining microstructure. A case study has also been included in this paper to show the potential of laser oscillation in pore suppressing in hybrid laser-arc welding (HLAW) of 6082 aluminium. Full article

Detection of skin cancer has become an increasingly prevalent health issue for which there is a need for reliable methods of detection to improve patient outcomes, minimize delays in diagnosis, and ensure clinical referral. Advances in computer vision and artificial intelligence have allowed automatic analyses of dermoscopic, clinical, and smartphone imaging of skin lesions. While numerous models have been found to perform very well on the basis of curated benchmark datasets, their accuracy in practical settings still needs to be evaluated. This review critically evaluates the literature from 2015 to 2025. Rather than considering the Dice, Jaccard, AUC, sensitivity, and specificity metrics on an absolute basis, this review evaluates them relative to dataset quality, validation process, external testing, statistical analysis, and risk of bias. Key areas of focus include dataset imbalance, lack of coverage of darker skin, poor external validation, explainability, uncertainty quantification, and barriers to clinical adoption. This review provides valuable insights for researchers, practitioners, dataset producers, and healthcare providers involved in developing AI-enabled dermatology tools. Full article

Thymic epithelial tumors (TETs), comprising thymomas and thymic carcinomas, are rare, biologically heterogeneous thoracic malignancies with limited therapeutic advances since platinum-based regimens were adopted decades ago. Recent genomic and immunophenotypic profiling has uncovered recurrent genomic alterations and high programmed death-ligand 1 (PD-L1) expression, particularly in thymic carcinoma, yet few targeted or immunotherapies have achieved regulatory approval. This mini-review synthesizes current knowledge on TET heterogeneity and the genomic landscape, evaluates the clinical evidence supporting targeted agents and immune checkpoint inhibitors, and examines emerging biomarkers, including circulating tumor DNA. We also address practical barriers to precision oncology in TETs: challenges of next-generation sequencing implementation and cost in resource-limited settings; scarcity of large, biomarker-driven trials; and safety concerns unique to TETs (immune-related toxicity). Finally, we discuss the translational hurdles for antibody–drug conjugates and cellular therapies, limited validated cell surface targets, antigen heterogeneity, and preclinical model gaps and outline strategic paths forward to enable rational, safe, and equitable precision therapeutics for TET patients. Full article

Digital twin (DT) technology has emerged as a cornerstone of Industry 4.0, facilitating real-time synchronization between physical assets and virtual models to drive operational excellence. Unlike prior surveys that address singular industrial domains, presenting qualifications in general terms without paradigm-to-task mapping, this review uniquely synthesizes DT architectural maturation across Technology Readiness Levels (TRLs) 1 through 9, quantitative performance outcomes from 39 documented industrial implementations spanning 10 sectors, and an explicit algorithmic taxonomy mapping distinct AI paradigms to specific functional DT requirements. By synthesizing empirical data across the aerospace, automotive, and manufacturing sectors, this study evaluates the quantitative impact of DT implementation, highlighting significant gains in predictive maintenance, production efficiency, and design cycle reduction. This research further examines the synergistic role of Machine Learning (ML) paradigms integrated within DT systems, specifically, physics-informed neural networks (PINNS), generative adversarial networks (GANs), deep transfer learning, reinforcement learning, and federated learning, in enhancing diagnostic accuracy and enabling autonomous decision-making. Despite these advancements, this review identifies critical barriers in data interoperability, cybersecurity, and workforce expertise that impede widespread adoption. This paper concludes by outlining future research directions, emphasizing the necessity for standardized data protocols and secure, distributed DT ecosystems to unlock the full potential of cyber-physical integration in a data-driven industrial landscape. Full article

Forest certification has become an important market-based tool for promoting environmental sustainability, biodiversity conservation, and improved governance across agricultural and forest production systems. This state-of-the-art (SotA) review examines forest and cocoa certification schemes in Brazil, focusing on cocoa-based agroforestry systems in southern Bahia. Major programs, including the Forest Stewardship Council (FSC), Brazilian Forest Certification Program (Cerflor), Instituto Biodinâmico (IBD), UTZ Certified (UTZ), Rainforest Alliance (RA), and Geographical Indication (GI) systems, were analyzed for implementation, sustainability outcomes, and accessibility across producer groups. This SotA review identifies persistent barriers to certification adoption, including high costs, complex regulations, limited technical capacity, and unequal access among producers. Certification adoption varies substantially among producer groups, with cooperatives playing a critical role as intermediaries that reduce barriers and facilitate market access. Finally, this SotA review proposes a conceptual classification of cocoa producers and an AI-enabled perspective for deforestation-free certification in biodiversity hotspots such as southern Bahia, offering new insights into sustainable cocoa production and forest conservation. Full article

The accelerating diffusion of artificial intelligence (AI) in Europe raises pressing distributional questions about employment, social cohesion, and sustainable development in disadvantaged regions. Research has concentrated on advanced urban economies, leaving the implications of AI for peripheral small and medium-sized enterprises (SMEs) operating under weak human capital, thin digital infrastructure, and constrained social capital, underexplored. We examine the interplay between AI adoption, social capital formation, workforce dynamics, and sustainable development in Eastern Macedonia and Thrace (EMT), one of the EU’s least developed regions. Regional unemployment and educational-attainment data from Eurostat and ELSTAT are incorporated as contextual evidence anchoring the qualitative findings. Drawing on Bitsani’s Biocultural City framework which treats human, social, and cultural capital as interdependent dimensions of regional sustainability, we thematically analysed twelve semi-structured interviews with SME owners and managers conducted in early 2025 using Atlas.ti, yielding 19 codes grouped into six categories. Knowledge deficits and financial constraints emerge as primary barriers, while external technology partnerships, targeted education, and economic incentives operate as enablers, all mediated by social and human capital availability. Read through this framework, AI adoption in peripheral economies emerges less as a purely technological or financial challenge than as a social and human capital one, embedded in a biocultural environment shaped by brain drain, institutional thinness, and weak civic intermediation. Without parallel investment in digital literacy, organizational culture, and inter-firm networks, AI risks reproducing rather than reducing employment inequalities. The study draws policy implications for EU Cohesion programming and Sustainable Development Goals 4, 8, 9, 10, and 17. Full article

This study examines South Africa’s financial inclusion landscape, with a focus on how regulatory design, consumer capability, and community-based financial ecosystems shape equitable access to financial services. Despite sustained policy commitments, financial inclusion outcomes remain suboptimal, with approximately 3.9 million low-income adults lacking access to basic financial services such as savings and credit accounts. The paper contributes to the financial inclusion discourse by assessing whether government and regulatory institutions have enabled access for low-income groups or reinforced existing patterns of exclusion. Using a qualitative thematic analysis of academic literature, national policy documents, and regulatory frameworks, the study identifies key structural barriers and enabling factors influencing financial inclusion in South Africa. Adopting an institutional-capability approach, the analysis integrates regulatory theory with insights from behavioural finance and community-based financial systems. The findings indicate that while the Financial Sector Regulation Act represents a significant milestone by establishing financial inclusion as a statutory objective, meaningful progress depends on a stronger emphasis on financial literacy, differentiated consumer education, and context-responsive product design. The study further highlights that fintech innovation presents both opportunities and risks, expanding access while intensifying regulatory asymmetries and operational vulnerabilities. A holistic policy approach that promotes inclusive institutional design, revised credit risk assessment frameworks, and gender-responsive financial products is therefore essential to advancing South Africa’s financial inclusion agenda. Full article

This review synthesizes recent advances in WHO-endorsed NAATs for TB diagnosis and drug resistance detection. We examine the principles, genetic targets, diagnostic performance, implementation settings, and programmatic role of assays across the spectrum of technological complexity, from cartridge-based platforms to line probe assays and sequencing-based technologies. In addition, we highlight emerging molecular tools that show promise for future WHO endorsement and may further strengthen decentralized and near-patient testing. Low- and moderate-complexity assays such as Xpert^® MTB/RIF, Xpert^® Ultra, and Truenat^TM MTB/MTB Plus have emerged as essential frontline tools for TB diagnosis and rifampicin resistance detection, especially in decentralized settings. LPAs, including GenoType^® MTBDRplus and MTBDRsl, extend resistance profiling to isoniazid, fluoroquinolones, and second-line injectables, and remain valuable in intermediate and central laboratories. More recent developments, including Xpert^® XDR, Deeplex^® Myc-TB, AmPORE-TB^®, and TBseq^®, enable broader resistance detection and, in the case of targeted sequencing assays, comprehensive characterization of multidrug-resistant and extensively drug-resistant TB (MDR/XDR-TB). Emerging diagnostic innovations—such as CRISPR-based detection systems, streamlined isothermal amplification assays, and portable sequencing technologies—further expand the landscape and may complement existing WHO-endorsed platforms. Importantly, these technologies reduce delays in regimen selection, improve patient outcomes, and provide critical data for surveillance. Nevertheless, performance gaps for rare mutations, limited sensitivity in paucibacillary or extrapulmonary disease, infrastructure requirements, and cost remain barriers to universal adoption. The evolution of TB molecular diagnostics demonstrates a clear shift toward more rapid, accurate, and comprehensive resistance detection. No single assay is universally optimal, yet the combined portfolio, spanning rapid cartridge-based NAATs, LPAs, and next-generation sequencing, forms a complementary framework for improving diagnosis, optimizing treatment, and supporting global TB elimination strategies. Full article

Freshwater is essential for sustaining the health of humans, animals, and ecosystems; however, agricultural activities remain a major source of water pollution globally. This review examines how crop production, livestock farming, and aquaculture contribute to water contamination, the effectiveness of current European policies, and the potential of sustainable mitigation strategies. Evidence from the research identified pesticides, herbicides, veterinary antibiotics, nutrient runoff, aquaculture effluents, and microplastics as the primary agricultural pollutants affecting surface and groundwater quality. These contaminants have been linked to ecosystem degradation, biodiversity loss, endocrine disruption, antimicrobial resistance, and adverse human health outcomes. Despite extensive regulatory frameworks, including the Water Framework Directive, Nitrates Directive, Farm to Fork Strategy, and European Green Deal, significant implementation and monitoring challenges remain. Current evidence indicates that only 40% of European surface waters achieve “good” ecological status, highlighting persistent water quality concerns across the region. The review further identified precision irrigation, Internet of Things (IoT)-enabled monitoring, biopesticides, hydroponic systems, and integrated multi-trophic aquaculture as promising solutions for reducing agricultural impacts on water resources. However, barriers, including high implementation costs, technological limitations, and inconsistent policy enforcement, continue to hinder widespread adoption. Overall, the findings demonstrate that while existing policies have improved water governance, stronger regulatory enforcement, greater investment in sustainable technologies, and increased adoption of nature-based solutions are required to reduce agricultural water pollution. An integrated approach combining technological innovation, policy support, and sustainable farming practices is essential to protect freshwater resources and ensure long-term environmental sustainability. Full article

Peritoneal metastasis (PM) is the most frequent and lethal pattern of dissemination in gastrointestinal malignancies. Despite advances in systemic chemotherapy, outcomes remain poor because the unique biology of PM, characterized by poor vascularization and the peritoneal–plasma barrier (PPB), limits drug penetration and contributes to treatment resistance. To address these challenges, several locoregional treatment strategies have been developed, including cytoreductive surgery plus hyperthermic intraperitoneal chemotherapy (CRS + HIPEC) and pressurized intraperitoneal aerosol chemotherapy (PIPAC). However, their widespread adoption is constrained by invasiveness, strict patient selection, and inconsistent survival benefits. Normothermic intraperitoneal and systemic treatment (NIPS) has emerged as a practical and less invasive alternative, particularly in East Asia. Through an implanted intraperitoneal port, NIPS enables repeated drug administration, providing sustained regional exposure while imposing minimal procedural burden. Importantly, it can be readily integrated with systemic chemotherapy, making it suitable for long-term multimodal treatment. Among available agents, paclitaxel (PTX) is particularly well suited for intraperitoneal administration because of its prolonged retention within the peritoneal cavity and limited systemic absorption. These pharmacokinetic properties allow high local drug concentrations with relatively low systemic toxicity. Consequently, PTX-based NIPS represents a biologically rational and clinically feasible treatment strategy for PM. This review summarizes the pharmacological rationale, clinical evidence, and emerging innovations in drug formulation and delivery that may further enhance the efficacy of PTX-based intraperitoneal chemotherapy for this challenging disease. Full article