System Maintenance Research Articles

Numerical modelling of bridge deck reinforcement corrosion based on analysis of GPR data

AbstractThis study explores the impact of corrosion on Ground Penetrating Radar (GPR) responses through practical experiments and numerical modelling, focusing on rebar diameter reduction, corrosion product layer thickness, crack formation and corrosion product filling in vertical and transverse crack. Practical experiments involved GPR testing of reinforced concrete slab. By analyzing B-scans we identify areas with moderate and severe corrosion. Numerical modelling using the Finite Difference Time Domain (FDTD) Method to model GPR signal propagation in a concrete bridge deck with corrosion is applied. Key finding includes a significant 26.70% increase in reflected wave amplitude when corrosion product filling in vertical crack increased by 400%, highlighting its extensive effect on signal GPR propagation. Reduced rebar diameter led to a 9.79% amplitude decrease and a 0.06 ns arrival time delay. Increased corrosion product layer thickness primarily affected arrival time with a 0.06 ns extension but significantly amplified GPR signal amplitude. These findings offer insights for improving GPR based corrosion detection and assessment methods, leading to more robust systems for concrete bridge deck inspection and maintenance. This paper contributes to understanding how corrosion affects the signal that is detected by GPR. This information can be used to improve the way that we manage and assess corrosion in concrete bridge deck.

NexoNet: Blockchain Online Social Media with User-Centric Multiple Incentive Mechanism and PoAP Consensus Mechanism

Online social media (OSM) has revolutionized the manner in which communication unfolds, enabling users to spontaneously generate, disseminate, share, and aggregate multimedia data across the internet. Nevertheless, in this exchange of information, OSM platforms assume a dominant, central role, wielding excessive power. Blockchain online social media (BOSM) seeks to mitigate the drawbacks of traditional centralized OSM by leveraging the decentralized nature of blockchain technology, migrating the functionalities of social media into a decentralized realm, and positioning the users at the core of the OSM ecosystem. However, current BOSM models often rely on tokens for incentives and are hampered by the centralized, inefficient blockchain consensus mechanisms, alongside vulnerabilities such as collusion attacks. This paper introduces a novel blockchain system, NexoNet, tailored for decentralized social media, exploring the application of blockchain technology in the realm of online social media from both technical and economic perspectives. The NexoNet quantifies and evaluates user participation within the system, employing a multiple incentive mechanism to equitably distribute value created by users without the need for tokens. Furthermore, we propose the Proof-of-Active-Participation (PoAP) blockchain consensus mechanism, enabling all users to partake in the maintenance of the blockchain system, thus ensuring its security and efficiency. Theoretical analysis and simulations across various scenarios demonstrate that the NexoNet, with extensive user engagement, achieves equitable value distribution through its multiple incentive mechanism. It successfully safeguards against a spectrum of malicious attacks and attains high transaction processing efficiency. The simulation results show that NexoNet achieves an average transaction throughput of 2000 transactions per second (TPS) and a consensus delay of 2.385 s with 100 maintainers in the network. Furthermore, our tests demonstrated that even collusion with users comprising 75% of the total would only allow an additional 30 chances to propose a block. By deeply integrating user behavior with the underlying mechanisms of the blockchain system, the NexoNet fosters a user-centric blockchain social media ecosystem.

Fault diagnosability of (K 4 – e)-free multiprocessor systems under the PMC and HPMC model

Faulty diagnosability of multiprocessor systems is one of the important evaluating index in the design and maintenance of multiprocessor systems. To address the fault diagnosis problem in processor fault or hybrid fault circumstances the Preparata, Metze and Chien (PMC) model and the hybrid PMC (HPMC) model have been proposed. In this paper, we discuss the t-diagnosability of (K 4 − e)-free multiprocessor systems under the PMC model, the h-restricted vertex diagnosability and the r-restricted edge diagnosability under the HPMC model. Furthermore, we determine the h-restricted vertex diagnosability and the r-restricted edge diagnosability of somewell-known networks under the HPMC model.

Exploring ultrafine particle emission characteristics from in-use light-duty diesel trucks in China using a portable measurement system

Diesel vehicle exhaust is one of the major contributors to ultrafine particles (UFPs) in urban areas in China. However, there is still a lack of knowledge about UFPs emission characteristics from current in-use diesel vehicles. This study has carried out an on-road test of 10 in-use Light-duty Diesel Trucks (LDDTs) with different emission control standards in China using a self-established portable measurement system based on the Electronic Low-pressure Impactor (ELPI) and characterized the ultrafine particle number (PN) concentration, particle size distribution and metal element contents. The results revealed a significant reduction of 93.37% in the average PN0.1 emission factor of LDDTs from China III to China VI. Notably, LDDTs compliant with the China VI vehicle emission control standard exhibited the lowest PN0.1 and PM0.1 emission factors, measuring 4.991 × 1014 #/km and 0.627 g/km, respectively. By taking into account emissions under real driving conditions, we found that the PN emission rates grow with the increase of the Vehicle Specific Power (VSP). The cold-start phase had higher PN emissions than the hot-start phase, with 8590, 1890, 477, and 22 times higher than those of the ambient air (1.18 × 105 #/cm3), respectively. The installation of Diesel Particulate Filter (DPF) can decrease UFPs by more than 99.8%, while the PN emission factor during the DPF regeneration stage (1.85 × 1016 #/km) increased by 5 orders of magnitude that of the DPF normal works (7.51 × 1011 #/km). Metal element contents analysis shows that Fe, Ca, Al and Mg are the dominant elements in UFPs of LDDT exhaust gas, but the element of Ni is slightly increasing in a China VI, possibly due to the new automotive engine exhaust manifolds being made of Ni instead of cast iron for the purpose of having more high-temperature resistance. Our study demonstrates the importance of monitoring and routine maintenance of exhaust after-treatment systems.

An example of a field service plan for oceanographic submerged moorings

Oceanographic mooring missions are critical for advancing our understanding of the world’s oceans and their role in the broader Earth system. These missions rely on the deployment and maintenance of complex observing systems, comprising subsurface, profiling, and surface moorings, which are designed to collect valuable data from the ocean interior. The success of these missions depends on meticulous planning and strategic execution, which are facilitated by the use of Field Service Plans (FSPs). FSPs are comprehensive and adaptable planning tools that integrate safety measures, contingency plans, and timelines to ensure the successful and safe recovery, maintenance, and deployment of mooring systems. In this paper, we provide a comprehensive guide to drafting, implementing, and adapting FSPs tailored to the unique challenges posed by oceanographic mooring missions. We highlight the critical role of FSPs in optimizing safety, data quality, and mission success, while also underscoring the need for flexibility and adaptation. Our aim is to provide practical guidance and a template for researchers, expedition leaders, and institutions engaged in oceanographic research.

A novel hybrid model for multi-step-ahead forecasting of wind speed based on univariate data feature enhancement

Reliable multistep ahead wind speed forecasting (MAWSF) is critical for the energy management of wind farms and the long-term maintenance of wind power systems. However, relying on inherent meteorological features such as temperature and atmospheric pressure often fails to meet the deep learning model’s feature requirements for accurate wind speed forecasting (WSF). This paper introduces a hybrid multistep forecasting model that constructs a univariate wind speed feature enhancement framework, combining random forest (RF) and Transformer models for WSF. Initially, the hybrid enhancement framework decomposes the univariate wind speed data and extracts time-series features, effectively mining the latent feature information. Subsequently, the RF feature selector filters out significant features contributing to WSF and eliminates redundant features to provide stable features. Finally, the Transformer model is utilized for both short-term and long-term MAWSF. This study conducted MAWSF on data with sampling intervals of 20 min, 30 min and 1 h. The results indicate that, compared to existing state-of-the-art models, the hybrid model in MAWSF tasks reduces the dependency of models on inherent meteorological features, achieving more accurate forecasting and faster computation speeds. Ultimately, the proposed model can provide reliable technical support for energy management and maintenance guidance in real-world wind farms.

Performance assessment of a 30.26 kW grid-connected photovoltaic plant in Egypt

Abstract This paper presents an experimental analysis and performance evaluation of a grid-connected photovoltaic plant installed on the rooftop of the Electronics Research Institute in Cairo, Egypt. Cairo is classified as a hot-desert climate region according to the standard Koppen-Geiger climate classification system. Over a year, we monitored real-time data to assess key system performance metrics, such as energy yield, efficiencies, performance ratio, capacity factor, and losses. Based on the obtained experimental results, the highest final yield of 5.2498 hr/day was observed in the summer, whereas the lowest yield of 3.439 hr/day occurred in the winter months. The photovoltaic plant had an average annual system efficiency of 15.8%, while the photovoltaic and inverter had mean yearly efficiencies of 17.1% and 97.2%, respectively. The average annual performance ratio is 83.03%, and the capacity factor is 18.72%. The monthly total loss exhibited a linear rise alongside increasing ambient temperature and solar irradiance. The ambient temperature affected the system efficiency, photovoltaic efficiency, and performance ratio. The findings can help strengthen forecasts of future large-scale photovoltaic plants in hot desert climates. Moreover, they can guide the design, optimization, operation, and maintenance of new grid-connected photovoltaic systems.

Efeito do uso da Promixalicina no controle de verminose e parâmetros sanguíneos de ovelhas

Sheep producers are increasingly looking for strategies to tackle the problem of worms in animals, as well as to improve the functioning of the animals' immune system. Therefore, two experiments were carried out, in two different properties (with high and low challenges in relation to verminosis) with the objective of, in both, evaluating the effect of using Ovine Promixalicin on OPG (Eggs per gram of Feces) and blood parameters of pregnant and non-pregnant sheep, on two different properties. The indication for use of the product is to, among others, contribute to the control of verminosis. The animals evaluated on the properties came from a pasture production system, with the use of concentrated and/or roughage supplementation if necessary. The animals used were of the Dorper, Texel, Ile de France and Sulfolk breed. The parameters evaluated were OPG, Famacha©, Body Condition Score and blood parameters (lymphocytes, leukocytes and erythrocytes). In relation to experiment one, with a low challenge in relation to worms, the use of Promyxalicin significantly helped to reduce worms and animal well-being, thus helping the herd to increase productive parameters such as weight gain and fertility. In experiment 2, a system with a high challenge in terms of verminosis, the animals remained uniform and controlled by the use of Promyxalicin, including beneficial results in relation to blood parameters, which did not increase during its use. Therefore, the use of Ovine Promixalicin does not alter the consumption of food by animals, as well as being effective in controlling verminosis, including Haemonchus contortus, Trichostrongylus colobriformis, Oesophagostomum columbianum e Strongyloides papillosus, promoting well-being and maintenance of the immune system, especially in pregnant animals, bringing benefits to the sheep production system.

Research on Status Assessment and Operation and Maintenance of Electric Vehicle DC Charging Stations Based on XGboost

With the rapid development of electric vehicles, the infrastructure for charging stations is also expanding quickly, and the failure rate of charging piles is increasing. To address the effective operation and maintenance of charging stations, a method based on the XGBoost algorithm for electric vehicle DC charging stations is proposed. An operation and maintenance system is constructed based on state analysis, considering the operational status of the charging stations and users’ charging habits. Factors such as driving and charging habits, road traffic, and charging station equipment are taken into account. The training sample data are established using historical data, online monitoring data, and external environmental data, and the charging station status evaluation model is trained using the XGBoost algorithm. Based on the condition assessment results, a risk assessment model is established in combination with fault parameters. Risk tracking of the charging stations is conducted using the energy not charged (ENC), evaluating the risk level of each station and determining the operation and maintenance order. The optimal operation and maintenance model for DC charging stations, aimed at achieving both economic and reliability goals, is constructed to determine the operation and maintenance schedule for each station. The results of the case study demonstrate that the state evaluation and operation and maintenance strategy can significantly improve the reliability of the system and the overall benefits of operation and maintenance while meeting the required standards.

Sustainable Development in Rural Underserved Communities through Improved Responsible Management of Decentralized Wastewater Infrastructure: A Focus on the Alabama Black Belt.

Despite global efforts on meeting sustainable development goals by 2030, persistent and widespread sanitation deficits in rural, underserved communities in high-income countries─including the United States (US)─challenge achieving this target. The recent US federal infrastructure funding, coupled with research efforts to explore innovative, alternative decentralized wastewater systems, are unprecedented opportunities for addressing basic sanitation gaps in these communities. Yet, understanding how to best manage these systems for sustainable operations and maintenance (O&M) is still a national need. Here, we develop an integrated management approach for achieving such sustainable systems, taking into account the utility structure, operational aspects, and possible barriers impeding effective management of decentralized wastewater infrastructure. We demonstrate this approach through a binomial logistic regression of survey responses from 114 public and private management entities (e.g., water and sewer utilities) operating in 27 states in the US, targeting the rural Alabama Black Belt wastewater issues. Our assessment introduces policy areas that support sustainable decentralized wastewater systems management and operations, including privatizing water-wastewater infrastructure systems, incentivizing/mandating the consolidation of utility management of these systems, federally funding the O&M, and developing and retaining water-wastewater workforce in rural, underserved communities. Our discussions give rise to a holistic empirical understanding of effective management of decentralized wastewater infrastructure for rural, underserved communities in the US, thereby contributing to global conversations on sustainable development.

Effect of Management Information System on Growth of Agro-Firms in Anambra State

The study examined the effect of management information systems on the growth of agro-firms in Anambra State. The objectives were to: determine the effect of decision-making information systems on the Return on Investment (ROI) of agro-businesses in Anambra State, Nigeria, and ascertain the extent to which database management systems affect the ROI of agro-businesses in Anambra State, Nigeria. The study adopted a survey research design, with data generated from both primary and secondary sources. The data collection method was a questionnaire, which was randomly administered to staff of selected agro-firms. The population of the study was 6,727, while the sample size was 1,293, out of which 929 questionnaires were retrieved. The hypotheses were tested using the multiple regression analysis method at a 0.05% level of significance. The findings revealed that decision-making information systems had a significant effect on the ROI of agro-businesses in Anambra State, with a t-statistic of 7.743 and a probability value of 0.000. Additionally, database information systems had a significant effect on the ROI of agro-businesses in Anambra State, with a t-statistic of 2.476 and a probability value of 0.013. The study concluded that management information systems have a significant positive effect on agro-firms in Anambra State. It recommended that agricultural firms should invest in advanced decision support tools to aid data-driven decisions that maximize ROI. Furthermore, agro-business managers should focus on optimizing their database information systems to improve data organization and accessibility. Regular maintenance and updates of the database systems are crucial for ensuring accurate and timely information, which can positively impact ROI.

Estimation of the world market and application of nanomaterials in the aerospace industry

The object of the study is the global aerospace market status, segment analysis, dynamics, competition, and prospects. The methods of searching and analyzing literature data, summarizing, systematizing, and visualizing data with diagrams are used. The aerospace industry is at the forefront of technological innovation and is constantly searching for new advanced materials to improve productivity, efficiency, and safety. The aerospace market encompassing the design, manufacture, and maintenance of aircrafts, space vehicles, and related systems. It includes the commercial and military sectors, as well as the space exploration field. The world market of the aerospace industry was studied. Factors affecting the market positively and negatively were identified. According to the global aerospace market segmentation by vehicle types, the leading position in 2023 was occupied by the commercial aircrafts segment with a share of 63.4 %; by the vehicle size – by the narrow-body aircraft segment (72.4 %); by the end consumer – by the private sector segment (65.4 %); by operation – by manually operated aircrafts segment (79.4 %); and by geographic regions – by the North American segment (47.3 %). The main strategic trends and directions of the further aerospace market development are presented. The world market of aerospace materials was studied. Factors affecting market dynamics are identified, and market challenges are highlighted. According to the world aerospace market segmentation by the materials types, the leading place in 2022 belonged to the composite materials segment with a share of 69 %; by the aircraft type – to the commercial aircrafts segment (51 %); and by geographical regions – to the European segment (35.0 %). The trends of the sustainable aerospace industry development are summarized: modern aircraft design, use of sustainable aviation fuel, urban air mobility, modern traffic technology, and air transportation management optimization. For each trend, possible actions leading to changes in the aerospace industry are considered. The question of the nanomaterials use in the space industry is considered. Some characteristics and possibilities of application of nanocomposite materials, nanocoatings, nanofluids, nanosensors, and carbon nanotubes, as well as examples of the nanomaterials application in aircraft components are given. The industry problems are identified, and their possible solutions are given.

Professional Competency Requirements for Maintenance and Operation of Power Battery Systems

The power battery system is one of the high-risk components for new energy vehicles, and standardized operation and maintenance is one of the effective measures to improve the safety of new energy vehicles. The operation and maintenance of the power battery system includes daily operation, first level maintenance, and second level maintenance. A combination of practical research and theoretical analysis is adopted to confirm different maintenance tasks, job contents, and technical requirements, in order to improve the standardization and safety of operations. Fault mode analysis is a continuation of fault maintenance and provides practical basis for the design and process improvement of power battery systems.

Evaluation of Effluent Quality Trends Before and After Filtration Through the Composite Filter from Shirere Wastewater Treatment Plant to River Isiukhu in Kakamega County, Kenya

The current stabilization ponds as wastewater treatment practices in urban areas have proven insufficient with continued discharge of untreated wastes into water bodies. Their challenge comes from inappropriate system selection and maintenance, improper design, construction mistakes, physical damage and hydraulic overload. Appropriate infrastructural technologies for waste removal that can be adopted in the drainage channels of effluents into water bodies are scarce. This study incorporates a reactor based composite filter of pumice and sand as an innovative approach for removing residual waste in effluents discharged from Shirere Wastewater Treatment Plant into River Isiukhu, Kakamega Municipality. The objective of the study was to evaluate the trend of effluent quality from Shirere wastewater treatment plant upto river Isiukhu before and after installation of composite granular filter. Effluents, drinking water from Shirere WWTP, Shikoye stream, River Isiukhu and protected spring along Shikoye stream, were collected using presterilized water sampling containers for microbial quality analysis at MMUST and KACWASCO laboratories. The measurements were carried out using UV-VIS spectrophotometer at 752 nanometer wavelengths. Research design was experimental. The average reduction of COD in the mid-season of June to August was 42.2 ±4.6%, being the highest. Concomitantly, the BOD removal by the filter in the season of June to August was19.6±7% and 15.6 ±3.5% for September to November. The average rate of TSS removal in June to August was 19.3±4.5% followed by 16.6±3.8% in September to November and 11.6±7% in March to May. The average rate of Nitrate removal in June to August was 41.8±7.6% followed by 30.0±2.2% for March to May and 25±8.6% for September to November. Phosphates had an average rate of removal in June to August at 31.9±2.7% followed by 20.6±4.8% for September to November and 20.0 ±4.3% for March to May. Specifically, for the first season of March – May 2021 at 200 mm filtration depth were carried out at effluent flow rate of 0.0032 and volume, 0.234 Concentrations of most parameters were above NEMA standards, like COD was 322mg/l yet maximum should be 100 mg/l. Therefore, it was concluded that silica pumice composite filter performance was achieved by big variations in the concentrations of COD, BOD, TSS, Phosphates and Nitrates at Shirere WWTP after filtration which was attributed to effective removing capacity. The effluent concentrations from sampling sites S1-S3 and S5-S7 were found to be above the NEEMA standards implying the high risk of using Isiukhu water and catchment area. Thus, this study recommended that, the composite filter reduced concentrations of all the parameters (COD, BOD, TSS, PO3, NO3) significantly from Shirere WWTP along Shikoye stream up to the confluence of river Isiukhu. Most of the parameters after filtration were ranging within the required standards of NEMA. The requisite measure of adopting new technology of composite filtration should be sustained.

AI Based Chatbots for Mental Health Care: A Systematic Review

Medicinal utilization of Expert systems for psychological resilience maintenance have proficient a accelerated float in the spent a small number of years. AI empowered chatbot shareware and administration have been supervising fundamental therapeutical hospitalization that were beforehand unique feasible from master and skilled medicare executives. Such resources, which orbit from “essential psychologist” to “community cybermens” in mental health, attempt to enhance serving production and cost handling, as well as gathering the mental health needs of unprotected and disadvantaged citizenery. Nevertheless, there is still a substantial gap between recent progress in AI mental health and the widespread use of these solutions by healthcare exponents in therapeutic settings. Furthermore, therapy are recurrently developed without clear ethical proceedings. While AI-enabled solutions show promise in the realm of mental health, further research is needed to address the ethical and communal aspects of these technologies, as well as to establish efficient exploration and therapeutic practices in this fresh sector.

Characterizing the evolution of defense in a tripartite marine symbiosis using adaptive dynamics

Abstract The evolution and maintenance of symbiotic systems remains a fascinating puzzle. While the coevolutionary dynamics of bipartite (host–symbiont) systems are well-studied, the dynamics of more complex systems have only recently garnered attention with increasing technological advances. We model a tripartite system inspired by the marine symbiotic relationship between the alga Bryopsis sp., its intracellular defensive bacterial symbiont “Candidatus Endobryopsis kahalalidifaciens,” which produces a toxin that protects the alga against fish herbivores, and the sea-slug Elysia rufescens (Zan et al., 2019), which is not deterred by the toxin. We disentangle the role of selection on different actors within this system by investigating evolutionary scenarios where defense evolves as (i) a host-controlled trait that reduces algal reproductive ability; (ii) a symbiont-controlled trait that impacts symbiont transmission; and (iii) a trait jointly controlled by both host and symbiont. Optimal investment in defensive toxins varies based on the characteristics of the host, symbiont, and sea slug; and evolutionary trajectories are modulated by trade-off shape, i.e., a strongly decelerating trade-off between defense and symbiont transmission can drive symbiont diversification via evolutionary branching. Increasing slug herbivory reduces host investment in defense to favor reproduction, while symbiont investment in defense first declines and then increases as host density declines to the degree that horizontal symbiont transmission is no longer beneficial. Increasing vertical transmission selects for reduced defense by the host when it evolves as a jointly controlled trait, as a result of investment by the symbiont. Our theoretical exploration of the evolution of defensive symbiosis in scenarios involving interactions with multiple herbivores provides a first window into the origin and maintenance of the Bryopsis sp. system, and adds another piece to the puzzle of the evolution of symbiotic systems.

Exploring the Impact of 3D Printing Parameters on the THz Optical Characteristics of COC Material.

In terahertz (THz) optical systems, polymer-based manufacturing processes are employed to ensure product quality and the material performance necessary for proper system maintenance. Therefore, the precise manufacturing of system components, such as optical elements, is crucial for the optimal functioning of the systems. In this study, the authors investigated the impact of various 3D printing parameters using fused deposition modeling (FDM) on the optical properties of manufactured structures within the THz radiation range. The measurements were conducted on 3D printed samples using highly transparent and biocompatible cyclic olefin copolymer (COC), which may find applications in THz passive optics for "in vivo" measurements. The results of this study indicate that certain printing parameters significantly affect the optical behavior of the fabricated structures. The improperly configured printing parameters result in the worsening of THz optical properties. This is proved through a significant change in the refractive index value and undesirable increase in the absorption coefficient value. Furthermore, such misconfigurations may lead to the occurrence of defects within the printed structures. Finally, the recommended printing parameters, which improve the optical performance of the manufactured structures are presented.

Wavelet-based spatiotemporal sparse quaternion dictionary learning for reconstruction of multi-channel vibration data

Accurate reconstruction of multi-source data information plays an essential role in remote intelligent operation, and prognostic and health maintenance (RIO-PHM) of industrial systems. However, traditional signal reconstruction methods such as compressed sensing fail to capture the spatio-temporal characteristics and coupling nature of the multi-source or multi-channel data. To alleviate this bottleneck, in this paper, a new wavelet-based spatiotemporal sparse quaternion dictionary learning (WSTS-QDL) algorithm is formulated for the reconstruction of multi-channel vibration data for the first time. Specifically, the wavelet-based spatiotemporal sparse low-rank matrix (SLRM) algorithm is elaborated and the sparse coefficient matrix of the multi-channel signals can be estimated using the split Bregman iteration (SBI) technique. Then, quaternion-based dictionary learning is introduced for multi-channel data reconstruction according to the updated sparse coefficient matrix during quaternion dictionary learning. Eventually, two equipmental scenarios including run-to-failure data of rolling bearing in bearing test bench and vibration signal of the failured bearing in corn thresher, are utilized for verification. The experimental results demonstrate that the highest recovery accuracy performance with scoring function and the lowest errors are achieved by the proposed method in contrast with the state-of-the-art benchmarks such as orthogonal matching pursuit (OMP) method and spatiotemporal sparse Bayesian learning (SSBL), and the waveform of phase space trajectory and points cloud distribution of the Poincare section in the original signal are similar/same to that obtained by the proposed method.

Characterization of Two Novel PNKP Splice-Site Variants in a Proband With Microcephaly, Intellectual Disability, and Multiple Malformations.

Polynucleotide kinase phosphatase (PNKP), encoded by the PNKP gene, is a DNA processing enzyme involved in double-strand break and single-strand break repair pathways, which are essential for genome stability and for the correct development and maintenance of human nervous system. PNKP biallelic loss-of-function variants have been associated with a broad spectrum of neurological anomalies, ranging from congenital microcephaly with intellectual disability and seizures (MCSZ), to later onset forms of ataxia-oculomotor apraxia (AOA4) or peripheral neuropathy (CMT2B2). We report the atypical clinical manifestations of a patient with severe microcephaly, short stature, developmental delay, conductive hearing loss, and tracheoesophageal malformation, in the absence of seizures. Whole exome sequencing analysis identified two novel, compound heterozygous splice-site variants in the PNKP gene (NM_007254.4): c.1448+1G > A and c.199-8_199-5del. To demonstrate the effect of both variants on the splicing process and prove their pathogenicity, we performed a hybrid minigene assay, which successfully highlighted a deleterious impact on the transcript, particularly regarding the c.199-8_199-5del variant. The uncommon clinical features of the proband and the identification of two newly associated pathogenic variants add further evidence to the allelic and phenotypic heterogeneity of the PNKP locus.

UK national survey on nuclear medicine in-house clinical software: the calm before the storm.

The use of in-house developed software as a medical device (IHD-SaMD) is core to many nuclear medicine (NM) services in the UK, including applications in nonimaging studies and image processing. Expected regulatory changes in 2025 could have significant implications due to a lack of resources and expertise in the implementation and maintenance of software Quality Management Systems (QMS) and associated standards. This survey investigated the national use of IHD-SaMD and the readiness of services to adapt to the upcoming regulatory changes. An online survey was used to investigate the current national usage of IHD-SaMD. Representatives of 64 UK NM physics services were invited to participate, with 43 responding. It was found that 98% of respondents use IHD-SaMD clinically. About 65% use IHD-SaMD that respondents felt was under-supported (e.g. legacy software). Approximately 60% of respondents use or support two or more pieces of IHD-SaMD. Around 66% of respondents use a QMS in their department, with about 48% using a software-specific QMS. Most respondents indicate understaffing, particularly with regard to IT/software skillsets. Almost all respondents indicate without an increase in the preparedness and understanding of the requirements, all dependent clinical services would be severely impacted or indeed stopped. This national survey shows that pending regulatory changes could significantly impact NM services, up to and including stopping clinical services. Additional resources would be required to support in-house software management under an appropriate QMS or move to European conformity marking (CE)-marked software where available. This must be urgently considered and addressed by all NM stakeholders.