Limitations Of Technology Research Articles

Three-way conceptual knowledge updating in incomplete contexts

We usually encounter incomplete data in daily life due to the uncertainty of data and limitation of data acquisition technology. In formal concept analysis, the incomplete formal context is used to reflect uncertain relation between objects and attributes caused by missing data. The conceptual knowledge of the incomplete formal context is presented by a kind of three-way concept called partially-known formal concept. As time passes and technology matures, some initially missing data becomes obtainable, the incomplete formal context is updated accordingly, and the corresponding concepts change as well. However, obtaining partially-known concepts from the updated context based on definition is time-consuming and does not fully utilize the conceptual knowledge implicit in the original context. In order to make full use of existing conceptual knowledge and acquire new concepts quickly and efficiently, we discuss how to obtain new partially-known formal concepts by updating original partially-known formal concepts, and design corresponding concept updating algorithms. Finally, through data experiments, we validate that our proposed concept update algorithm can significantly improve the efficiency of concept acquisition, especially when the updating rate is small.

The role of renewable energy in achieving sustainable development goals

Renewable energy is a critical enabler of global efforts to achieve the United Nations’ Sustainable Development Goals (SDGs), serving as a foundation for addressing social, economic, and environmental challenges. This review explores the multifaceted role of renewable energy in driving progress across several SDGs, particularly SDG 7 (Affordable and Clean Energy) and SDG 13 (Climate Action), while also contributing to goals such as poverty alleviation (SDG 1), improved health outcomes (SDG 3), economic growth (SDG 8), and sustainable cities (SDG 11). The transition to renewable energy sources—such as solar, wind, hydropower, and geothermal—offers pathways to reduce global carbon emissions, mitigate climate change, and ensure universal access to clean energy. In addition, renewable energy projects promote economic empowerment through job creation and rural electrification, driving inclusive growth in underserved communities. The integration of renewable energy in urban planning also supports sustainable development in cities. However, the adoption of renewable energy faces barriers such as high initial investment costs, technological limitations, and regulatory challenges. This review discusses strategies to overcome these obstacles, emphasizing the importance of supportive policy frameworks, international cooperation, and public-private partnerships. It highlights successful case studies from countries that have leveraged renewable energy to make significant strides toward the SDGs, offering valuable insights for global implementation. As the world approaches the 2030 deadline for the SDGs, renewable energy remains a vital driver of sustainable development, providing innovative solutions to complex global issues while fostering a cleaner, more equitable future.

The Impact of Telemedicine on Chronic Disease Management: A Post-Pandemic Analysis of Patient Outcomes and Accessibility

This study explores the impact of telemedicine on chronic disease management, focusing on patient outcomes and healthcare accessibility in the post-pandemic context. Using a qualitative research approach, the study examines how telemedicine has transformed the management of chronic conditions, especially for patients facing geographical or mobility barriers. Data were collected through in-depth interviews with patients, healthcare providers, and policy experts to gain insights into the experiences and challenges associated with telemedicine for chronic care. The findings reveal that telemedicine has improved patient accessibility to healthcare services, enabling consistent monitoring and timely interventions, which positively impact patient health outcomes. However, the study also identifies challenges, including technological barriers and limitations in patient-provider communication, that may affect care quality and patient satisfaction. Despite these issues, telemedicine is seen as a valuable supplement to traditional healthcare, enhancing healthcare access, especially for underserved populations. This research provides key insights for healthcare policymakers and practitioners in improving telemedicine practices, ensuring that they address accessibility gaps without compromising quality. The study concludes that, with strategic improvements, telemedicine holds significant potential to transform chronic disease management and make healthcare more equitable.

Revolutionizing dairy waste: emerging solutions in conjunction with microbial engineering.

The dairy industry is grappling with significant challenges in managing effluent due to environmental concerns and stringent regulatory demands, necessitating innovative solutions. The paper investigates how microbial engineering is transforming the treatment of dairy wastewater, offering advanced methods to minimize environmental impact and enhance sustainability. It delves into the current challenges faced by the dairy industry, such as regulatory compliance and the limitations of traditional treatment technologies, and introduces microbial engineering as a promising solution for effluent management. Microbial engineering leverages genetic engineering techniques and microorganisms to enhance the efficiency of treatment processes like bioaugmentation and bioremediation. The environmental and economic benefits of microbial engineering, highlighting its potential to reduce pollution and lower operational costs for the dairy industry. The specific figures can vary based on factors like farm size and location, studies suggest that microbial engineering can reduce wastewater pollution by up to 50% and nutrient runoff by 30%. It also identifies key challenges and there are still areas including strains for specific pollutants (drugs, hormones), enhance degradation pathways, and increase microbes' stability (stress tolerance, long-term viability) that require further innovation to maximize its benefits. Through case studies and success stories, the paper demonstrates practical applications of microbial engineering in managing dairy effluent, illustrating how it can revolutionize industrial practices for a more sustainable future.

Multi-step thermal design of microwave vacuum heating to basaltic regolith simulant towards lunar base construction.

Humanned exploration and extended stay on the Moon are the hottest challenges today. We report highly robust materials by microwave heating under high-vacuum conditions (10- 3 Pa) from a basaltic regolith simulant (FJS-1) to ensure the feasibility of lunar infrastructure construction. The violent degassing dynamics were revealed by monitoring vacuum pressure during heating and analyzing the compounds evolved from basaltic silicate compounds: thermal pyrolysis of silicate compounds became more pronounced above 1000 oC, leading to a catastrophic deformation accompanied by forming countless pores of several hundred µm sizes. The preferential formation of the magnetite phase in vacuum heating dominantly caused the radical change in microwave absorption capacity compared with conventional heating routes using an electrical furnace in atmospheric conditions. Besides, the in-situ measurement of dielectric properties during microwave vacuum heating clarified the increase in one order of magnitude from 100 to 1000 oC. Based on the presumed phenomena during microwave-vacuum heating for basaltic regolith, we propose a new thermal design concept to overcome the practical limitations of microwave technology. The multi-step temperature profile successfully fabricated a highly robust product that demonstrated world-class mechanical performance, equivalent to the compressive strength of 65MPa without any vigorous hydrostatic cold press as a pre-treatment.

Enhancing Thermoelectrical Properties of Silver-Nanowire-Embedded Heatable Textiles via Sputter-Mediated Nanowire Structural Modulation

This study addresses the fabrication of flexible, heatable fabrics via the integration of globally interconnected silver nanowires (Ag NWs) with sputter-deposited silver atoms. Conventional heatable fabrics, which utilize macroscale or nanoscale conductive wires, often face challenges in balancing flexibility, comfort, and structural durability. The proposed method leverages the advantages of nanoscale metallic wires and vacuum-based sputtering, maintaining fabric flexibility while enhancing heating efficiency. The fabrication process involves dip-coating polyester fabric with Ag NWs, followed by sputter deposition to modulate the nanowire morphology, thereby improving key electrical properties such as wire resistance and contact resistance between wires. The experimental results demonstrate that sputter-deposited Ag NW fabrics exhibit significantly enhanced heating capability compared to undeposited, otherwise identical counterparts. Further, the fabrics maintain their heating characteristics under repeated mechanical bending and prolonged electrical stress, highlighting their potential for use in wearable electronic applications. This approach offers a promising solution to the limitations of current heatable textile technologies, providing a pathway for the development of comfortable, efficient, and durable heatable fabrics.

Bioinspired Passive Cooling Hydrogel for Visualizing Hygroscopicity and Desorption Process

AbstractSelf‐hygroscopic hydrogels, characterized by high evaporation enthalpy, cooling efficiency, and self‐regulating properties, have garnered significant attention. However, most current research focuses on enhancing the hygroscopic and desorption performance, often overlooking the importance of monitoring the self‐regulation process, which limits its further application. Advanced visualization technologies, such as in situ electrical impedance tomography, low‐field nuclear magnetic resonance, and hyperspectral imaging, offer potential insights into this behavior, yet they often require additional devices, incur high costs, and involve complex sample preparation processes. Therefore, drawing inspiration from nature, humidity‐color‐sensitive hydrogels (HCSHs) strategy is proposed for visualized cooling. Benefiting from the strong polar responsiveness of the aggregation‐induced emission (AIE) molecules, the hydrogel's fluorescence significantly changes with varying interior water content, thereby its self‐regulation process is monitored easily. Further, the obtained hydrogel could be applied in the electronic device cooling owing to the polymer skeletons’ high swelling ratio, strong adhesion, and excellent self‐hygroscopic properties. This strategy overcomes current limitations in the visual technology of self‐hygroscopic materials and provides new insights into intelligent thermal management for electronic devices.

Implementing traceability technologies to promote ethical sourcing in Ghana’s fashion and apparel industry

ABSTRACT The demand for traceability has emerged as a significant imperative within the framework of an ethical supply chain that includes multiple stages. This study focusses on the implementation and impact of traceability technology in the Ghanaian fashion industry. The study employed descriptive and explanatory research, using a 700-stakeholder sample, a standardised questionnaire, and descriptive and inferential statistical methods. The findings of the study indicate that QR codes, GPS tracking, sustainable material tracing, and consumer interaction apps demonstrate a high level of effectiveness within the Ghanaian fashion business. The implementation of traceability technology faces challenges like limited knowledge, research insufficient, lack of coordination, policy absence, financial constraints, technological infrastructure limitations, data privacy concerns, opposition, and training gaps. Stakeholders generally support the implementation of coordination policies and regulatory compliance strategies, suggesting that factors like awareness, research, cost, infrastructure, data protection, opposition, and training should be prioritised.

Bridging the gap: opportunities, challenges, and future directions for teleradiology in rural healthcare

Teleradiology, the electronic transmission of radiological images and data for diagnostic purposes, holds significant promise for improving healthcare access in rural and underserved regions. This review explores the opportunities and challenges of implementing teleradiology in rural settings, where limited access to radiology services exacerbates healthcare disparities. Teleradiology offers multiple benefits, including improved access to timely diagnostics, enhanced decision-making, and cost savings for rural patients who would otherwise need to travel to urban centers for radiology services. It has shown positive outcomes globally, with examples in India, Mali, the Democratic Republic of Congo, and Brazil, demonstrating its feasibility and potential to reduce geographic health inequities. However, implementing teleradiology in these settings faces several challenges, such as technological limitations, workforce shortages, regulatory and legal barriers, data security concerns, and cultural acceptance issues. Solutions and recommendations include investments in infrastructure, workforce training, supportive regulatory frameworks, secure data management, and adaptable telehealth models that consider socioeconomic factors in rural areas. By addressing these challenges, stakeholders can enhance the impact of teleradiology in rural healthcare systems, ultimately contributing to reduced disparities and improved healthcare outcomes. This review provides a comprehensive overview of the current landscape and suggests actionable pathways for advancing teleradiology in rural settings worldwide.

New colleague or gimmick hurdle? A user-centric scoping review of the barriers and facilitators of robots in hospitals.

Healthcare systems are confronted with a multitude of challenges, including the imperative to enhance accessibility, efficiency, cost-effectiveness, and the quality of healthcare delivery. These challenges are exacerbated by current healthcare personnel shortages, prospects of future shortfalls, insufficient recruitment efforts, increasing prevalence of chronic diseases, global viral concerns, and ageing populations. To address this escalating demand for healthcare services, healthcare systems are increasingly adopting robotic technology and artificial intelligence (AI), which promise to optimise costs, improve working conditions, and increase the quality of care. This article focuses on deepening our understanding of the barriers and facilitators associated with integrating robotic technologies in hospital environments. To this end, we conducted a scoping literature review to consolidate emerging themes pertaining to the experiences, viewpoints perspectives, and behaviours of hospital employees as professional users of robots in hospitals. Through screening 501 original research articles from Web-of-Science, we identified and reviewed in full-text 40 pertinent user-centric studies of the integration of robots into hospitals. Our review revealed and analysed 14 themes in-depth, of which we identified seven as barriers and seven as facilitators. Through a structuring of the barriers and facilitators, we reveal a notable misalignment between these barriers and facilitators: Finding that organisational aspects are at the core of most barriers, we suggest that future research should investigate the dynamics between hospital employees as professional users and the procedures and workflows of the hospitals as institutions, as well as the ambivalent role of anthropomorphisation of hospital robots, and emerging issues of privacy and confidentiality raised by increasingly communicative robots. Ultimately, this perspective on the integration of robots in hospitals transcends debates on the capabilities and limits of the robotic technology itself, shedding light on the complexity of integrating new technologies into hospital environments and contributing to an understanding of possible futures in healthcare innovation.

Patterned Lead-Free Double Perovskite/Polymer Fluorescent Piezoelectric Composite Films for Advanced Anti-Counterfeiting.

The limitations of single fluorescent anti-counterfeiting technologies necessitate the development of more sophisticated encryption methods to protect information and data. Traditional optical anti-counterfeiting encryption techniques, which rely on light sources with varying wavelengths to identify information, are now insufficient to meet contemporary security demands due to their restricted response to a narrow range of wavelengths. In this study, the fabrication of patterned, lead-free double perovskite (DP)/poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE)) fluorescent piezoelectric composite films (CFs) is reported. These CFs integrate the up-conversion and down-conversion photoluminescent properties of Cs2Na0.8Ag0.2BiCl6:Yb3+/Er3+ DP crystals with the piezoelectric properties of P(VDF-TrFE) film, facilitating multi-modal information protection. The fluorescent signals of different concealed information in CFs are observable under the excitation of 365nm UV light and 980nm infrared (IR) light. Additionally, external pressure applied at various locations on the CFs generates corresponding electrical signals, thereby providing triple-layer encryption for protected information. A multifunctional anti-counterfeiting device has been further developed by integrating patterned optical and electrical responses onto flexible CFs, achieving synergistic protection of information security in cross fields and bringing a significant advancement to the high-level anti-counterfeiting market.

CNSC-11. INVESTIGATION OF GLIOBLASTOMA NEURON-TUMOR NETWORKS WITH RABIES-BASED RETROGRADE TRACING

Abstract Glioblastomas are primary brain tumors known for their whole-brain invasion and high therapeutic resistance. In previous studies, neuron-to-glioma synapses have been shown to promote glioblastoma progression. A deep characterization of this communication and of tumor-connected neurons has not been possible due to technological limitations. We adapted a rabies virus-based retrograde tracing approach to investigate and manipulate neuron-tumor networks. Interestingly, we found that glioblastoma cells rapidly integrated into neural circuits across the brain, engaging with distal neurons of diverse subtypes in very early stages of tumor development. Beyond glutamatergic neurons, we identified cholinergic neurons as drivers of glioblastoma cell invasion. We revealed patient- and tumor cell state-dependent differences in the expression of synaptogenic genes which also correlated with neuron-tumor connectivity and tumor cell invasivity. Notably, radiotherapy led to increased neuron-tumor connectivity mediated via neuronal hyperexcitability. The anti-epileptic drug perampanel alongside radiotherapy mitigated this effect and enhanced treatment efficacy by simultaneous neuronal activity inhibition. Utilizing our rabies-based approach, we genetically ablated tumor-connected neurons leading to a significantly decreased tumor progression offering a potential novel therapeutic avenue. Taken together, we developed a framework for dedicated analysis of multicellular neuron-tumor networks and propose our methodology as a versatile and adaptable approach to tackle glioblastoma.

Analysis of non-targeted variants by invasive prenatal diagnosis for pregnant women undergoing preimplantation genetic testing

To compare the results of invasive prenatal diagnosis and preimplantation genetic testing (PGT) and explore the underlying mechanism. Clinical data of pregnant women undergoing PGT and invasive prenatal diagnosis at the Sixth Affiliated Hospital of Sun Yat-sen University from January 2019 to December 2022 were collected. The results of PGT and invasive prenatal diagnosis were compared, and the outcomes of pregnancies were followed up. This study has been approved by the Medical Ethics Committee of the Sixth Affiliated Hospital of Sun Yat-sen University (No. 2022ZSLYEC-491). A total of 172 couples were included in this study, and 26 non-targeted variants were discovered upon prenatal diagnosis, including 10 cases (38.5%) by chromosomal karyotyping, 15 (57.7%) by chromosomal microarray analysis (CMA), and 1 (3.8%) by whole exome sequencing. The 10 karyotypic anomalies had included 6 chromosomal polymorphisms, 2 chromosomal mosaicisms, 1 paternally derived translocation, and 1 missed maternal chromosomal inversion. CMA has identified 15 copy number variations (CNVs), which included 11 microdeletions and microduplications, 3 loss of heterozygosity, and 1 low-level mosaicism of paternal uniparental disomy. One CNV was classified as pathogenic, and another one was likely pathogenic, whilst the remaining 13 were classified as variants of uncertain significance. Therefore, 8.7% of CNVs was detected by invasive prenatal diagnosis after PGT. 92.3% (24/26) of the non-targeted variants have been due to technological limitations of next-generation sequencing (NGS). Invasive prenatal diagnosis after PGT can detect non-targeted variants, which may further reduce the incidence of birth defects.

The role of big data in transforming financial management in U.S. healthcare: A conceptual framework

This paper explores the transformative role of big data in financial management within the U.S. healthcare sector, highlighting its capacity to address long-standing financial inefficiencies, enhance decision-making, and improve regulatory compliance. Big data technologies, such as predictive analytics and real-time financial reporting, provide healthcare institutions with the tools to forecast financial trends, optimize budgeting, and mitigate risks. Despite the significant benefits, the adoption of big data in healthcare finance faces challenges, including data privacy concerns, regulatory complexities, and technological limitations. The paper examines these barriers and enablers, offering strategic recommendations for healthcare institutions and policymakers to optimize the use of big data. By improving data governance, upgrading infrastructure, and fostering collaboration across departments, healthcare organizations can maximize the impact of big data on their financial operations. The review concludes with a call for continued policy support and financial incentives to encourage the broader adoption of big data in healthcare finance, ultimately promoting cost efficiency and operational resilience in the sector. Keywords: Big Data, Healthcare Financial Management, Predictive Analytics, Data Governance, Regulatory Compliance, Financial Decision-Making.

Circular agro-economies (CAE): reducing waste and increasing profitability in agriculture

This paper explores the concept of Circular Agro-Economies (CAE), a sustainable agricultural model focused on recycling agricultural by-products to minimize waste and maximize profitability for farmers. In contrast to traditional linear agricultural systems, CAE promotes resource efficiency and the development of new value chains through the reuse of organic materials. The paper examines the environmental, economic, and social benefits of adopting CAE, including waste reduction, cost savings, rural development, and job creation. It also discusses the significant barriers to adoption, such as technological limitations, financial constraints, and policy-related challenges. Finally, practical recommendations for farmers, policymakers, and businesses are provided to support the successful implementation of CAE, highlighting the collaborative efforts needed to overcome existing challenges and realize the full potential of this model. Keywords: Circular Agro-Economies, Agricultural Waste Recycling, Sustainable Agriculture, Resource Efficiency, Rural Development, Profitability in Farming.

A review of carbon nanotube field effect transistor from structure and properties to applications

Abstract. In the pursuit of next-generation electronic devices that overweigh the limitations of traditional silicon-based technologies, Carbon Nano Tube Field Effect Transistors (CNTFETs) have garnered significant attention. Unlike conventional Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs), CNTFETs utilize the exceptional properties of Carbon Nanotubes (CNTs) as the channel material, promising substantial improvements in performance, power consumption, and scalability. This paper presents a comprehensive overview of CNTFETs, delving into their fundamental structures and underlying principles. It critically examines the unique characteristics that make CNTFETs an attractive alternative, including their superior carrier mobility, reduced leakage currents, and compatibility with nanoscale fabrication techniques. This review explores the application prospects of CNTFETs, spanning from high-speed digital circuits to energy-efficient sensors and beyond. Despite their promising potential, the paper also acknowledges recent challenges associated with CNTFETs, such as challenges in material synthesis, integration with existing semiconductor processes, and cost considerations. By addressing these challenges and fostering interdisciplinary research collaborations, the widespread adoption of CNTFETs in integrated circuits could revolutionize the electronics industry, enabling the development of more efficient, powerful, and sustainable devices for the future.

Integrating Vision: From Neuroscience to Artificial Intelligence

Abstract. This review article explores the complex interplay between neuroscience and artificial intelligence, focusing on vision processing and its applications. It starts by outlining the biological basis of vision, delving into how visual information is processed and encoded in the brain. The discussion then transitions to artificial intelligence, particularly machine vision, highlighting the advancements and technologies that mimic biological processes. A critical analysis compares how visual information is utilized in both biological organisms and artificial systems, with an emphasis on cognitive functions and neural encoding. The challenges of integrating vision across various sensory modalities are examined, underscoring the technological and cognitive limitations currently faced. The review culminates by identifying potential research paths aimed at closing the gap between neuroscience and AI. This involves enhancing the understanding and functionality of vision in multisensory contexts, striving to foster a more comprehensive approach to artificial intelligence that mirrors the complexity of human perception.

Advancing language learning: The impact and challenges of Computer-Assisted Language Learning (CALL)

Abstract. Computer-Assisted Language Learning (CALL) represents a transformative approach in modern education, integrating technology to enhance language acquisition effectively. This comprehensive review examines the various dimensions of CALL, focusing on its deployment through interactive software, online courses, mobile applications, and the accompanying challenges. Quantitative analyses reveal significant improvements in learner engagement and cognitive load management due to multimedia and interactive content. Moreover, the adaptability of CALL to cater to individual learning needs through personalized and adaptive learning systems demonstrates a superior proficiency acquisition rate. Despite these advancements, CALL implementation faces substantial barriers including technological limitations, the need for extensive teacher training, and concerns regarding data privacy and security. This article assesses the statistical impact of these elements on language learning outcomes and suggests strategies for overcoming the associated challenges. Through mixed-methods research and longitudinal studies, the effectiveness of CALL platforms is substantiated, highlighting their pivotal role in reshaping language education across diverse demographic and geographic spectrums.

Digital Gig Work Under Unstable Energy Infrastructures: Invisible Workarounds and Alternative Imaginaries

Digital upskilling and remote work are frequently presented as pathways for displaced communities who face political, economic crises and employment barriers. The viability and stability of available energy infrastructures for these communities is critical to the long-term success of these proposed job trajectories. In this paper, we investigate how 17 Syrian refugees living in Lebanon navigate their local unstable energy infrastructures to conduct digital gig work and receive digital training. We found that digital gig work and training are workarounds to the political and social inaccessibility of local labor markets for refugees and that participants rely on a series of material energy strategies to optimize their electricity access. We argue that to support refugees conducting digital gig work and training, we must recognize and account for ecological, social, and technological limitations and frailties in the development of technological solutions and draw our attention to how infrastructures are perpetually undergoing processes of breakdown, repair, and renewal. We argue that this attention to ongoing transformation and renewal creates new opportunities for productive and creative reconfiguration as well as modes through which CSCW may intervene in unstable energy contexts. From this perspective, we emphasize the importance of better resourcing displaced communities with information regarding energy access and supporting them in establishing and strengthening their own visions for alternative energy systems and employment pathways.

Heterogeneous Online Computational Platform for GEM-Based Plasma Impurity Monitoring Systems

The fusion energy research field presents many intricate challenges that require resolution. Many diagnostic systems employed in experiments are approaching the limits of current technology. Implementing efficient measurements requires using an appropriate set of tools to facilitate the optimal utilization of hardware. Fusion energy measurements must provide low latency processing with the capacity for future improvements and the ability to handle complex data flows efficiently. The presented work addresses these requirements and describes the implementation of a high-performance, low-latency software platform with convenient development for soft X-ray (SXR) plasma impurities emission tracing—the Asynchronous Complex Computation Platform (AC2P). This article presents the architectural design, implementation details, and performance and latency measurements based on the raw data acquired from the WEST tokamak and laboratory tests. AC2P provides the tools to develop low-latency, multi-core, multi-device complex data flow graph scale-up solutions for measuring impurities in hot plasmas. The system has been designed to operate online during experiments, calculate the energy distribution, position and occurrence time of SXR photons, monitor the data stream’s quality and archive any abnormalities for subsequent offline verification and algorithm improvement. This article presents AC2P, which operates as part of the SXR measurement system on the WEST tokamak.