Maintenance Burden Research Articles

Two Hundred Nanometer Thin Multifocal Graphene Oxide Metalens for Varying Magnification Broadband Imaging.

Conventional microscopes, which rely on multiple objective lenses for varying magnifications, are bulky, complex, and costly, making them difficult to integrate into compact devices. They require frequent manual adjustments, complicating the imaging process and increasing maintenance burdens. This paper explores the potential of single ultrathin graphene metalens to address this issue. We propose and demonstrate a 200 nm thin multiaxial focus graphene metalens with high-quality focusing, designed using spatial multiplexing and fabricated by one-step laser nanoprinting. A five-focal graphene metalens has been created, achieving clear imaging with varying magnifications across a broadband covering the entire visible wavelength. The graphene metalens has significantly reduced the size of the imaging system by orders of magnitude and holds profound potential for facilitating the integration and miniaturization of optical microscopic systems.

Applications of AI in public health: Improving access to high-quality evidence syntheses

Abstract Issue Using the best available evidence is crucial for effective public health practice. Health Evidence™ provides access to high-quality synthesis evidence relevant to public health. As the volume of peer-reviewed published literature grows, maintaining a database of this magnitude is increasingly resource-intensive. Artificial intelligence (AI) can be used to reduce the maintenance burden thereby ensuring decision makers can easily access high-quality synthesized public health evidence. These innovative strategies may be transferable to enhance efficient maintenance of large curated databases of published literature. Description of the problem In 2020, The Health Evidence™ team conducted extensive training and testing of a supervised machine learning application to explore the accuracy of AI-assisted reference de-duplication and relevance screening. Finding promising results, the team implemented these AI-assisted strategies in August 2020. To assess the impact on the overall screening burden and time saved, implementation data was analyzed between November 2020 to 2023. Results For these 3+ years, AI assisted de-duplication and relevance screening was applied to 394,903 search results. The AI assisted de-duplication application removed 31% (n = 123,903) of references as duplicates. From the remaining reference sets (n = 272,253), the AI assisted screening application removed 70% (n = 190,966) of references as not relevant. Quality assurance spot testing found minimal classification errors (n = 1). In total, AI assisted approaches reduced the need for manual screening by 80%, saving approximately 626 hours of manual screening time over three years (or approximately 17 hours/month). Lessons With the reality of limited public health resources, continued access to high-quality synthesis evidence is critical. Innovative strategies using AI-assisted applications improves the feasibility of maintaining a large database of quality-appraised public health synthesis evidence. Key messages • Access to high quality synthesis evidence is critical for evidence-informed decision making. • Artificial Intelligence can be used to efficiently identify evidence syntheses relevant for public health.

Intensional Functions

Functions in functional languages have a single elimination form — application — and cannot be compared, hashed, or subjected to other non-application operations. These operations can be approximated via defunctionalization: functions are replaced with first-order data and calls are replaced with invocations of a dispatch function. Operations such as comparison may then be implemented for these first-order data to approximate e.g. deduplication of continuations in algorithms such as unbounded searches. Unfortunately, this encoding is tedious, imposes a maintenance burden, and obfuscates the affected code. We introduce an alternative in intensional functions , a language feature which supports the definition of non-application operations in terms of a function’s definition site and closure-captured values. First-order data operations may be defined on intensional functions without burdensome code transformation. We give an operational semantics and type system and prove their formal properties. We further define intensional monads , whose Kleisli arrows are intensional functions, enabling monadic values to be similarly subjected to additional operations.

Raman Spectroscopy in Optical Non-Invasive Diagnostics of Skin Neoplasms

Introduction. Recent decades indicate a significant increase in the incidence of skin cancer. Aim. To upgrade the specialized device and to improve the quality of skin neoplasm diagnostics. Materials and methods. The study mainly involved the method of non-invasive differential diagnostics of skin neoplasms. The method relies upon optical research methods, including Raman spectroscopy, a spectroscopic technique. A 10-year study, conducted by the Department of Oncology, the Samara Regional Clinical Oncology Dispensary (SOKOD), included more than 500 observations. The study used samples of various skin neoplasms obtained during surgical treatment of patients. Experimental tests provided a certain spectrum of various benign and malignant human skin neoplasms, including melanoma. Results. A series of experimental tests resulted in an experimental setup that is absolutely safe to use. Discussion. The study involved comparison of individual characteristics of the Raman spectra, obtained in the examination of neoplasm and healthy skin for each patient, thereby individualizing the method. The study revealed a high accuracy rate of 92% (with sensitivity of 89%, specificity of 93%), thus minimizing risks of false negative results, which is essential for mass examination. Conclusion. Since the proposed device setup does not require consumable products and different reagents, the method is marked with lower time costs and maintenance burden. Raman spectroscopy obtains a significant potential, thus, can be widely used for skin neoplasms in various medical and preventive institutions.

High-precision services of BeiDou navigation satellite system (BDS): current state, achievements, and future directions

With the rapid development of technologies such as autonomous driving and robotic navigation, the demand for accurate and reliable positioning results with BDS has increased. The current status and future development of BDS high precision services are reviewed. The operational PPP-B2b of BDS-3 achieves positioning accuracy at decimeter-level within 14 min and has the drawbacks in regional coverage and long convergence time compared with the international counterparts, such as CLAS of QZSS and HAS of Galileo. A development frame for multi-layer BDS high-precision services is proposed by considering its construction cost, compatibility of user terminal, operating maintenance burden, and service level. The global high-precision service with the improved orbit and clock accuracy enhanced with the inter-satellite link is taken as the most fundamental layer. By incorporating inter-satellite link observations, the orbit errors URE and clock errors are significantly reduced to approximately 0.05 m and 0.16 ns, respectively, which will expand PPP service to global. Based on this, the regional PPP-AR and PPP-RTK services with improved convergence performance are taken as the second layer. With PPP-AR, the convergence time drops to 10 min. With PPP-RTK, the convergence time would be further shortened to less than 3 min. The LEO enhanced PPP service is taken as the third layer which overcomes both drawbacks of the long convergence time of the inter-satellite link enhanced service (the first layer) and the regional coverage of the PPP-AR/PPP-RTK services (the second layer). The simulation results show that by introducing a LEO constellation of 288 satellites, the LEO enhanced PPP can achieve positioning accuracy better than 5 cm within approximately 1 min. In addition, the integration of LEO constellation and PPP-RTK is further proposed to enable instantaneous convergence. The implementation challenges are also presented.

Integrating and Adopting AI in the Radiology Workflow: A Primer for Standards and Integrating the Healthcare Enterprise (IHE) Profiles.

The deployment of artificial intelligence (AI) solutions in radiology practice creates new demands on existing imaging workflow. Accommodating custom integrations creates a substantial operational and maintenance burden. These custom integrations also increase the likelihood of unanticipated problems. Standards-based interoperability facilitates AI integration with systems from different vendors into a single environment by enabling seamless exchange between information systems in the radiology workflow. Integrating the Healthcare Enterprise (IHE) is an initiative to improve how computer systems share information across health care domains, including radiology. IHE integrates existing standards-such as Digital Imaging and Communications in Medicine, Health Level Seven, and health care lexicons and ontologies (ie, LOINC, RadLex, SNOMED Clinical Terms)-by mapping data elements from one standard to another. IHE Radiology manages profiles (standards-based implementation guides) for departmental workflow and information sharing across care sites, including profiles for scaling AI processing traffic and integrating AI results. This review focuses on the need for standards-based interoperability to scale AI integration in radiology, including a brief review of recent IHE profiles that provide a framework for AI integration. This review also discusses challenges and additional considerations for AI integration, including technical, clinical, and policy perspectives.

Feasibility and Acceptability of Universal Adult Screening for Chronic Hepatitis B in Primary Care Clinics

IntroductionTwo-thirds of Americans infected with chronic hepatitis B (CHB) are unaware of their infection. In March 2023, the CDC recommended moving from risk-based to universal adult CHB screening. In April 2022, Stanford implemented CHB universal screening discussion alerts for primary care providers (PCPs). MethodsAfter 6 months, we surveyed 143 PCPs at 13 Stanford primary care clinics about universal CHB screening acceptability and implementation feasibility. We conducted semi-structured interviews with 15 PCPs and 5 medical assistants (MAs) around alerts and CHB universal versus risk-based screening. Results45% of surveyed PCPs responded. 63% reported that universal screening would identify more CHB patients. Pre-implementation, 77% ordered 0-5 CHB screenings/month. Post-implementation, 71% ordered more than 6 screenings/month. 66% shared that universal screening removed the stigma around discussing high-risk behaviors. Interview themes included: 1) Low clinical burden; 2) Current under-screening of at-risk groups; 3) Providers preferred universal screening; 4) Patients accepted universal screening; 5) Ease of CHB alert implementation. ConclusionsConsistent with CDC guidelines, implementing universal CHB screening in primary care clinics in Northern California were feasible, acceptable to providers and patients, eased health maintenance burdens, and improved clinic workflows.

A Wireless Power Transfer Mattress Based System for Perpetually Operating Physiological Monitoring Wearables.

This article presents a novel wireless power mattress-based system architecture tailored to guarantee continuous energy for in-home environment healthcare wearables intended to be used in the context of patients who would benefit from long-term monitoring of specific physiological biomarkers. The design demonstrates that it is possible to transfer over 20 mW at a primary-secondary distance of 20.7 cm, whilst still keeping within all FCC/ICNIRP safety regulations, using the proposed simplified beamforming-controlled power transfer multi-input single-output system. Compared with other beamforming-controlled based works, the proposed design used non-coupling coil arrays, significantly reducing the algorithmic complexity. An on-chip wireless power charger system was also designed to provide high-efficiency power storage (89.3% power conversion efficiency and 83.9% power charge efficiency), guaranteeing wearables can continuously maintain their functionality. In contrast with conventional NiMh chargers, this work proposes a trimming function that makes it compatible with batteries of varying capacities. It also employs a four-stage charge loop to ensure safety and sustainability during the charging process. Overall, this work shows that by relying on wireless power transfer, it is, in principle, possible to create a safe wearable that could enable continuous monitoring of certain healthcare biomarkers with little or zero maintenance burden for the patients or carers.

EventGeoScout: Fostering Citizen Empowerment and Augmenting Data Quality through Collaborative Geographic Information Governance and Optimization

In this manuscript, we present EventGeoScout, an innovative framework for collaborative geographic information management, tailored to meet the needs of the dynamically changing landscape of geographic data integration and quality enhancement. EventGeoScout enables the seamless fusion of open data from different sources and provides users with the tools to refine and improve data quality. A distinctive feature of our framework is its commitment to platform-agnostic data management, ensuring that processed datasets are accessible via standard Geographic Information System (GIS) tools, reducing the maintenance burden on organizations while ensuring the continued relevance of the data. Our approach goes beyond the boundaries of traditional data integration, enabling users to fully harness the power of geospatial information by simplifying the data creation process and providing a versatile solution to the complex challenges posed by layered geospatial data. To demonstrate the versatility and robustness of EventGeoScout as an optimization tool, we present a case study centered on the Uncapacitated Facility Location Problem (UFLP), where a genetic algorithm was used to achieve outstanding performance on both traditional computing platforms and smartphone devices. As a concrete case study, we applied our solution in the context of the Málaga City Marathon, using the latest data from the last edition of the marathon.

Aging Rate Equalization Strategy for Battery Energy Storage Systems in Microgrids

It is urgent to reduce the maintenance burden and extend the service life of recycled batteries used in microgrids. However, the corresponding balancing techniques mainly focus on the state of health (SOH) balancing for unique converter structures or with complex SOH estimators. This paper proposes an aging rate equalization strategy for microgrid-scale battery energy storage systems (BESSs). Firstly, the aging rate equalization principle is established based on the relationship among throughput, state of charge (SOC), and injected/output power of a BESS, which is obtained according to the semi-empirical life model of the battery. Second, based on the established principle, the droop coefficients of energy storage systems (ESUs) are designed in the lower-level control, which can ensure the aging rate equalization of ESUs in one. The upper-level control optimizes the output of multiple microgrids. Then, the stability of the proposed aging rate equalization strategy is proven by a small-signal analysis. The performance analysis shows that the proposed aging rate equalization can also realize SOC balance. Finally, the RTLAB hardware-in-the-loop tests are carried out to illustrate the outstanding performance of the proposed strategy for extending the battery service life and ensuring microgrid operation stability.

The Ligo-Virgo-KAGRA Computing Infrastructure for Gravitational-wave Research

The LIGO, VIRGO and KAGRA Gravitational-wave (GW) observatories are getting ready for their fourth observational period, O4, scheduled to begin in March 2023, with improved sensitivities and thus higher event rates. GW-related computing has both large commonalities with HEP computing, particularly in the domain of offline data processing and analysis, and important differences, for example in the fact that the amount of raw data doesn’t grow much with the instrument sensitivity, or the need to timely generate and distribute “event candidate alerts” to EM and neutrino observatories, thus making gravitational multi-messenger astronomy possible. Data from the interferometers are exchanged between collaborations both for low-latency and offline processing; in recent years, the three collaborations designed and built a common distributed computing infrastructure to prepare for a growing computing demand, and to reduce the maintenance burden of legacy custom-made tools, by increasingly adopting tools and architectures originally developed in the context of HEP computing. So, for example, HTCondor is used for workflow management, Rucio for many data management needs, CVMFS for code and data distribution, and more. We will present GW computing use cases and report about the architecture of the computing infrastructure as will be used during O4, as well as some planned upgrades for the subsequent observing run O5.

Governance of Electronic Health Record Modification at U.S. Academic Medical Centers.

A key aspect of electronic health record (EHR) governance involves the approach to EHR modification. We report a descriptive study to characterize EHR governance at academic medical centers (AMCs) across the United States. We conducted interviews with the Chief Medical Information Officers of 18 AMCs about the process of EHR modification for standard requests. Recordings of the interviews were analyzed to identify categories within prespecified domains. Responses were then assigned to categories for each domain. At our AMCs, EHR requests were governed variably, with a similar number of sites using quantitative scoring systems (7, 38.9%), qualitative systems (5, 27.8%), or no scoring system (6, 33.3%). Two (11%) organizations formally review all requests for their impact on health equity. Although 14 (78%) organizations have trained physician builders/architects, their primary role was not for EHR build. Most commonly reported governance challenges included request volume (11, 61%), integrating diverse clinician input (3, 17%), and stakeholder buy-in (3, 17%). The slowest step in the process was clarifying end user requests (14, 78%). Few leaders had identified metrics for the success of EHR governance. Governance approaches for managing EHR modification at AMCs are highly variable, which suggests ongoing efforts to balance EHR standardization and maintenance burden, while dealing with a high volume of requests. Developing metrics to capture the performance of governance and quantify problems may be a key step in identifying best practices.

Ultrasonic transducer for high temperature thickness monitoring

Refineries typically undergo 30–60 days of programmed shutdowns every 4 to 6 years to assess the integrity of infrastructure not accessible during service. So far, the literature demonstrated the feasibility of using ultrasonic probes for continuous long-term monitoring up to 350°C. However, when the temperature keeps rising, an air- or water-cooling system is required or a long delay line is used to move the probe away from the heat source. Providing a real time monitoring solution for the most critical components operating at high temperature would increase safety and reduce the maintenance burden. In this talk, an ultrasonic probe operating completely immersed inside a 600°C (1112°F) environment for extended periods of time is presented. The design of the transducer will be discussed. Its small footprint enables it to be mounted at several critical and difficult to access locations. In order to validate performances transducers were mounted on plates and pipes of different materials and thicknesses and the assembly was put inside a furnace. The results of long-term stability at 600°C, the consistency of the measurements over a temperature range from 20°C to 600°C, and the robustness during aggressive thermal cycling will be presented.

Is high-speed rail a sustainable mobility option? A life-cycle assessment of the Basque Y project in Spain

The Basque Y High Speed Rail connection between Madrid and the Basque Autonomous Community is, quite exceptionally, a mixed freight and passengers HSR line, that has been presented as a fundamental step towards a more sustainable mobility. In this paper, a life-cycle assessment (LCA) is conducted to assess the environmental performance of the line throughout its lifetime, based on the latest data available, including both construction and maintenance burdens. Results show that this new corridor is not justified in terms of reducing emissions and energy consumption, mainly due to its low transport density. It also has a negligible impact on Spanish current low rail freight traffic. We conclude, therefore, that Spain needs to reconsider its AVE network expansion if aiming at increasing rail's modal share and meeting the emissions targets set by the EU. From a policy perspective, many information inconsistencies have been found regarding the demand projections of freight transport, which cast serious doubt about the decision-making process behind Trans-European transport projects.

Advancing Predictive Maintenance: A Study of Domain Adaptation for Fault Identification in Gearbox Components

This paper explores the use of machine learning in predictive maintenance, which has been increasingly demanded in recent years to reduce downtime and maintenance burden. The challenge of different data distributions between training and test data in machine learning is common in predictive maintenance where equipment operation patterns can change, leading to reduced operational efficiency. The authors validate a domain-adaptive anomaly detection method combining CNN and MMD, which achieves similar accuracy with PCA, SVD, and other dimensionality reduction methods. The study also shows that the method maintains accuracy even when the number of normal data in the target domain is 1/10 of the source domain.

Challenges for implementing biophilic strategies in Australian building design

Although biophilic design, particularly, direct nature integration (DNI) strategies like green roofs and green walls are associated with multiple benefits including building occupants’ well-being and carbon sequestration, their adoption in building design is limited in some developed countries like Australia. Architects and building sustainability consultants significantly influence design decisions; however, research focused on exploring DNI adoption barriers from their perspective is limited. Therefore, this research aimed to investigate the challenges limiting adoption of DNI strategies in Australia through the lens of innovation adoption theories. Semi-structured interviews with 24 architects and sustainability consultants focused on identifying barriers stemming from “organisation”, “building client”, “designer”, “innovation”, and “socio-political influencers”. Like in previous studies, “budget constraints” and “maintenance burden” were identified as key barriers in this research, thus, affirming their persisting negative impact on DNI adoption. However, the innovation adoption framework led to identifying new barriers like “builder influence” (socio-political influencers), “employment circumstances” (designer), and “business constraints” (organisation). The new barriers discovered in this research may be relevant to other countries; however, further studies are needed to identify dimensions relevant to other contexts. These studies will benefit from the research framework developed in this research.

Wired-Wireless Hierarchical Sensor Network using Zero power Sensor Node

The wireless sensor network, WSN, is a promising technology to make our social life better. However, the maintenance of the battery attached to each sensor node avoids WSN widely be used. The zero standby-power sensor node (ZSSN) extends battery life by eliminating standby power, but they impose high cost and maintenance burdens because each node has its own battery and wireless module. This paper proposes a wired-wireless hierarchical sensor network consisting of a small network group of ZPSNs (Zero power sensor node) with large capacitor as power supply that are wired together, and the parent node has a wireless module and an energy harvester. The proposed WSN can suppress the number of energy harvesters and wireless modules to that of groups. There are no batteries by replaced to the capacitors. That is, our WSN can reduce the maintenance and cost caused by which there is no battery, and each only parent node has wireless module and energy harvester. The experimental result shows that the standby ZPSN can keep enough voltage 48 days on the large capacitor to operate in active mode correctly.

ZENBU-Reports: a graphical web-portal builder for interactive visualization and dissemination of genome-scale data.

In the genomic era, data dissemination and visualization is an integral part of scientific publications and research projects involving international consortia producing massive genome-wide data sets, intra-organizational collaborations, or individual labs. However, creating custom supporting websites is oftentimes impractical due to the required programming effort, web server infrastructure, and data storage facilities, as well as the long-term maintenance burden. ZENBU-Reports (https://fantom.gsc.riken.jp/zenbu/reports) is a web application to create interactive scientific web portals by using graphical interfaces while providing storage and secured collaborative sharing for data uploaded by users. ZENBU-Reports provides the scientific visualization elements commonly used in supplementary websites, publications and presentations, presenting a complete solution for the interactive display and dissemination of data and analysis results during the full lifespan of a scientific project both during the active research phase and after publication of the results.

Automatic differentiation for orbital-free density functional theory.

Differentiable programming has facilitated numerous methodological advances in scientific computing. Physics engines supporting automatic differentiation have simpler code, accelerating the development process and reducing the maintenance burden. Furthermore, fully differentiable simulation tools enable direct evaluation of challenging derivatives-including those directly related to properties measurable by experiment-that are conventionally computed with finite difference methods. Here, we investigate automatic differentiation in the context of orbital-free density functional theory (OFDFT) simulations of materials, introducing PROFESS-AD. Its automatic evaluation of properties derived from first derivatives, including functional potentials, forces, and stresses, facilitates the development and testing of new density functionals, while its direct evaluation of properties requiring higher-order derivatives, such as bulk moduli, elastic constants, and force constants, offers more concise implementations than conventional finite difference methods. For these reasons, PROFESS-AD serves as an excellent prototyping tool and provides new opportunities for OFDFT.

Deep Brain Stimulation for Substance Use Disorders? An Exploratory Qualitative Study of Perspectives of People Currently in Treatment.

Although previous studies have discussed the promise of deep brain stimulation (DBS) as a possible treatment for substance use disorders (SUDs) and collected researcher perspectives on possible ethical issues surrounding it, none have consulted people with SUDs themselves. We addressed this gap by interviewing people with SUDs. Participants viewed a short video introducing DBS, followed by a 1.5-hour semistructured interview on their experiences with SUDs and their perspective on DBS as a possible treatment option. Interviews were analyzed by multiple coders who iteratively identified salient themes. We interviewed 20 people in 12-step-based, inpatient treatment programs (10 [50%] White/Caucasian, 7 Black/African American [35%], 2 Asian [10%], 1 Hispanic/Latino [5%], and 1 [5%] Alaska Native/American Indian; 9 women [45%], 11 men [55%]). Interviewees described a variety of barriers they currently faced through the course of their disease that mirrored barriers often associated with DBS (stigma, invasiveness, maintenance burdens, privacy risks) and thus made them more open to the possibility of DBS as a future treatment option. Individuals with SUDs gave relatively less weight to surgical risks and clinical burdens associated with DBS than previous surveys of provider attitudes anticipated. These differences derived largely from their experiences living with an often-fatal disease and encountering limitations of current treatment options. These findings support the study of DBS as a treatment option for SUDs, with extensive input from people with SUDs and advocates.