Search Results (37)

Zirconium-89 (⁸⁹Zr) is a widely used radionuclide in immune-PET imaging due to its physical decay characteristics. Despite its importance, the production of ⁸⁹Zr radiopharmaceuticals remains largely manual, with limited cost-effective automation solutions available. To address this, we developed an automated system for the agile and reliable production of radiopharmaceuticals. The system performs transmutations, dissolution, and separation for a range of radioisotopes. Steps in the production of ⁸⁹Zr-oxalate are used as an exemplar to illustrate its use. Three-dimensional (3D) printing was exploited to design and manufacture a target holder able to include solid targets, in this case an ⁸⁹Y foil. Spot welding was used to attach ⁸⁹Y to a refractory tantalum (Ta) substrate. A commercially available CPU chiller was repurposed to efficiently cool the metal target. Furthermore, a commercial resin (ZR Resin) and compact peristaltic pumps were employed in a compact (10 × 10 × 10 cm³) chemical separation unit that operates automatically via computer-controlled software. Additionally, a standalone 3D-printed unit was designed with three automated functionalities: photolabelling, vortex mixing, and controlled heating. All components of the assembly, except for the target holder, are housed inside a commercially available hot cell, ensuring safe and efficient operation in a controlled environment. This paper details the design, construction, and modelling of the entire assembly, emphasising its innovative integration and operational efficiency for widespread radiopharmaceutical automation. Full article

Background/Objectives: Artificial intelligence (AI) has emerged as a promising field in the era of personalized oncology due to its potential to save time and workforce while serving as a supportive tool in patient management decisions. Although several studies in the literature have explored the integration of AI into oncology practice across different tumor types, available data remain limited. In our study, we aimed to evaluate the role of AI in the management of complex cancer cases by comparing the decisions of an in-house tumor board and ChatGPT-4o for patients with various tumor types. Methods: A total of 102 patients with diverse cancer types were included. Treatment and follow-up decisions proposed by both the tumor board and ChatGPT-4o were independently evaluated by two medical oncologists using a 5-point Likert scale. Results: Analysis of agreement levels showed high inter-rater reliability (κ = 0.722, p < 0.001 for tumor board decisions; κ = 0.794, p < 0.001 for ChatGPT decisions). However, concordance between the tumor board and ChatGPT was low, as reflected in the assessments of both raters (Rater 1: κ = 0.211, p = 0.003; Rater 2: κ = 0.376, p < 0.001). Both raters more frequently agreed with the tumor board decisions, and a statistically significant difference between tumor board and AI decisions was observed for both (Rater 1: Z = +4.548, p < 0.001; Rater 2: Z = +3.990, p < 0.001). Conclusions: These findings suggest that AI, in its current form, is not yet capable of functioning as a standalone decision-maker in the management of challenging oncology cases. Clinical experience and expert judgment remain the most critical factors in guiding patient care. Full article

The residential construction sector is critical to economic stability and housing availability. Residential construction demands often fluctuate due to demographic, economic, social, or market condition variables. This study seeks to investigate the significance of these external variables and produce a predictive model for residential construction demand using ElasticNet regression. Adopting New Zealand as a case study and leveraging datasets from Statistics New Zealand, this research identifies key demographic, economic, and market factors influencing four building categories: retirement villages, apartments, multiunit developments, and standalone houses. The research results indicate that age groups, particularly the 20−39 and 65+ age groups, and economic indicators, such as the house price index and unemployment rates, have high prediction powers. The models showed high accuracy for some categories, with R² values exceeding 0.87 for retirement villages and 0.91 for multi-units. Challenges were encountered with standalone houses and apartments due to residual variance. The research findings highlight the importance of targeted urban planning and policy adjustments to satisfy the requirements of specific age groups, address housing affordability and demographic shifts, and cater to prevailing market conditions. This research provides practical insights and guidance for urban planners, public housing agencies, residential developers, and residential contractors while offering a robust methodological framework for predictive modelling in the construction sector. Full article

Background/Objectives: Cold atmospheric plasma (CAP) has shown a strong anticancer effect on a variety of tumors, presenting a new approach for the effective treatment of oral squamous cell carcinoma (OSCC), one of the most prevalent malignant neoplasms with a high mortality rate. Here, we aimed to comprehensively investigate the antitumor potential of two approaches of CAP treatment on both two-dimensional and three-dimensional OSCC cell line models, as well as to analyze whether plasma treatment enhances the sensitivity of OSCC to chemotherapy. Methods: An in-house designed plasma needle, with helium as a working gas, was used to treat the SCC-25 cell line directly or indirectly via plasma-treated medium (PTM). The antitumor effect of CAP was assessed by measuring cell viability, apoptosis, adhesion, and migration. In addition, the combined effect of PTM and cisplatin was analyzed in SCC-25 tumor spheroids, as a more complex and reliable in vitro model. Results: Both plasma treatments showed time-dependent antitumor effects affecting their viability, adhesion, and migration. The rate of apoptosis was higher after incubation with PTM and is mediated by the intrinsic pathway. By utilizing the 3D spheroid carcinoma model, we confirmed the antitumor potential of CAP and additionally demonstrated an increased chemosensitivity of PTM-treated carcinoma cells. Conclusions: The results of our study illustrate a promising avenue for the application of CAP as a therapeutic option for OSCC, either as a standalone treatment or in combination with cisplatin. Full article

This paper presents an optimized method for evaluating and enhancing the crashworthiness of an electric vehicle (EV) battery frame, leveraging finite element model (FEM) simulations with minimal computational effort. The study begins by utilizing a publicly available LS-DYNA model of a conventional Toyota Camry, simplifying it to include only the structures relevant to a side pole crash scenario. The crash simulations adhere to FMVSS214 and UNR135 standards, while also extending to higher speeds of 45 km/h to evaluate performance under more severe conditions. A dummy frame with virtual mass is integrated into the model to approximate the realistic center of gravity (COG) of an EV and to facilitate visualization. Based on the side pole crash results, critical parameters are extracted to inform the development of load cases for the EV battery. The proposed battery frame, constructed from aluminum, houses a representative volume of battery cells. These cells are defined through a homogenization process derived from individual and pack of cell crash tests. The crashworthiness of the battery frame is assessed by measuring the overall intrusion along the Y-axis and the specific intrusion into the representative volume. This method not only highlights the challenges of adapting conventional vehicle platforms for EVs or for dual compatibility with both conventional and electric powertrains but also provides a framework for developing and testing battery frames independently. By creating relevant load cases derived from full vehicle crash data, this approach enables battery frames to be optimized and evaluated as standalone components, offering a method for efficient and adaptable battery frame development. This approach provides a streamlined yet effective process for optimizing the crash performance of EV battery systems within existing vehicle platforms. Full article

With the growing demand for infrastructure and transportation facilities, the need for advanced structural health monitoring (SHM) systems is critical. This study introduces two innovative, cost-effective, standalone, and open-source data acquisition devices designed to enhance SHM through the latest sensing technologies. The first device, termed CEDAS_acc, integrates the ADXL355 MEMS accelerometer with a RaspberryPi mini-computer, ideal for measuring strong ground motions and assessing structural modal properties during forced vibration tests and structural monitoring of mid-rise buildings. The second device, CEDAS_geo, incorporates the SM24 geophone sensor with a Raspberry Pi, designed for weak ground motion measurements, making it suitable for seismograph networks, seismological research, and early warning systems. Both devices function as acceleration/velocity Data Acquisition Systems (DAS) and standalone data loggers, featuring hardware components such as a single-board mini-computer, sensors, Analog-to-Digital Converters (ADCs), and micro-SD cards housed in protective casings. The CEDAS_acc includes a triaxial MEMS accelerometer with three ADCs, while the CEDAS_geo uses horizontal and vertical geophone elements with an ADC board. To validate these devices, rigorous tests were conducted. Offset Test, conducted by placing the sensor on a leveled flat surface in six orientations, demonstrating the accelerometer’s ability to provide accurate measurements using gravity as a reference; Frequency Response Test, performed at the Gebze Technical University Earthquake and Structure Laboratory (GTU-ESL), comparing the devices’ responses to the GURALP-5TDE reference sensor, with CEDAS_acc evaluated on a shaking table and CEDAS_geo’s performance assessed using ambient vibration records; and Noise Test, executed in a low-noise rural area to determine the intrinsic noise of CEDAS_geo, showing its capability to capture vibrations lower than ambient noise levels. Further field tests were conducted on a 10-story reinforced concrete building in Gaziantep, Turkey, instrumented with 8 CEDAS_acc and 1 CEDAS_geo devices. The building’s response to a magnitude 3.2 earthquake and ambient vibrations was analyzed, comparing results to the GURALP-5TDE reference sensors and demonstrating the devices’ accuracy in capturing peak accelerations and modal frequencies with minimal deviations. The study also introduced the Record Analyzer (RECANA) web application for managing data analysis on CEDAS devices, supporting various data formats, and providing tools for filtering, calibrating, and exporting data. This comprehensive study presents valuable, practical solutions for SHM, enhancing accessibility, reliability, and efficiency in structural and seismic monitoring applications and offering robust alternatives to traditional, costlier systems. Full article

Egg production is amongst the most rapidly expanding livestock sectors worldwide. A large share of non-renewable energy use in egg production is due to the operation of heating, ventilation, and air conditioning (HVAC) systems. Reducing energy use, therefore, is essential to decreasing the environmental impacts of intensive egg production. This review identifies market-ready alternatives (such as heat pumps and earth–air heat exchangers) to traditional HVAC systems that could be applied in the industrial egg sector, specifically focusing on their use in temperate and continental climates. For this analysis, energy simulations were run to estimate the typical thermal loads of caged and free-run poultry housing systems in various Canadian locations, which were used as examples of temperate and continental climates. These estimations were then used to evaluate alternative HVAC systems for (1) their capability to meet the energy demands of egg production facilities, (2) their environmental impact mitigation potential, and (3) their relative affordability by considering the insights from a systematic review of 225 relevant papers. The results highlighted that future research should prioritize earth–air heat exchangers as a complementary system and ground source heat pumps as a stand-alone system to reduce the impacts associated with conventional HVAC system operation in egg production. Full article

With the ageing of the population in Western countries, the prevalence of disability and mobility problems is increasing, highlighting the urgent need to improve accessibility in environments where people spend a significant amount of time, such as collective housing. This paper examines the accessibility of building entrances in collective housing in the Region of Murcia, south-eastern Spain, where 9.8% of the population is estimated to live with disabilities. Starting with a thorough review of national and regional accessibility regulations, this study applies a robust methodology by conducting fieldwork in 150 buildings to assess compliance and identify barriers. The methodology involved a systematic assessment of the accessibility of entrances, using criteria derived from the regulations, and a specific proposal of the accessibility solutions required for each case. The key findings show that the most effective way for improving the accessibility is a properly constructed ramp, with over 40% of buildings requiring the installation or improvement of ramps, either as a stand-alone solution or in combination with other adaptations. In 54% of cases, a multi-faceted approach was required to meet accessibility standards. It was also noted that older buildings typically require higher adaptation costs. Based on these findings, the study provides specific recommendations, such as the construction of ramps and other critical interventions, to improve the accessibility of buildings. These recommendations have the potential to guide public policy and drive improvements in urban planning to make residential areas more accessible. Full article

The energy demand of private households contributes globally to 36.5% of the total CO₂ emissions. To analyze the emissions reduction potential, we conducted a comparative life cycle assessment of a proton exchange membrane fuel cell in a residential application and a conventional system with a stand-alone gas condensing boiler and electricity from a grid mix. The period under review was referred to as the service life of the PEMFC and is assumed to be 10 years (83,038 h of PEMFC). The applicability of this in a single-family house built between 1991 and 2000 under German climatic conditions was investigated. The functional unit is set to the thermal energy demand of 16,244 kWh/a and electricity demand of 4919 kWh/a of a single-family house. The impact assessment method “CML 2001–August 2016” was used in this investigation. The manufacturing phase of the proton exchange membrane fuel cell showed disadvantages, whereby the use phase had significant advantages in most of the environmental impact categories as compared to the conventional energy supply system. Considering the whole life cycle, the advantages from the use phase could outperform the disadvantages from the manufacturing phase in most of the impact categories, except for ADP elements and TETP. Full article

This paper presents a spatiotemporal deep learning approach for mouse behavioral classification in the home-cage. Using a series of dual-stream architectures with assorted modifications for optimal performance, we introduce a novel feature sharing approach that jointly processes the streams at regular intervals throughout the network. The dataset in focus is an annotated, publicly available dataset of a singly-housed mouse. We achieved even better classification accuracy by ensembling the best performing models; an Inception-based network and an attention-based network, both of which utilize this feature sharing attribute. Furthermore, we demonstrate through ablation studies that for all models, the feature sharing architectures consistently outperform the conventional dual-stream having standalone streams. In particular, the inception-based architectures showed higher feature sharing gains with their increase in accuracy anywhere between 6.59% and 15.19%. The best-performing models were also further evaluated on other mouse behavioral datasets. Full article

There are many remote buildings that cannot be supplied by alternating electricity of the utility grid. Due to this, this study proposes adopting Direct Current (DC) appliances for a stand-alone remote building. Direct Current can be supplied from a suitable photovoltaic array which can harvest renewable solar energy. This proposal guarantees an efficient power system by removing the necessity of including an inverter, power filter, insulation transformer, and a complicated controller, which are usually needed for producing Alternating Current (AC) power to feed AC loads using a PV system. When the proposal is applied, the PV system will be more efficient, simple, affordable, and more compact. A detailed power requirement calculation for a typical house uses DC appliances, generalized steps to design a suitable PV array, and an Artificial Neural Network (ANN) algorithm for guaranteeing Maximum Power Point Tracking (MPPT); all of which are introduced for remote buildings. The main contribution of this paper is proposing an integrated design of a DC unit of 11 kW·h PV system for stand-alone buildings that eliminates three stages that improves the system performance compared to AC unit. The introduced study includes PV array calculation based on PV module of 220 W with an intelligent algorithm of four layers. The Mean Squared Error (MSE) of the proposed ANN equals 2.7107 × 10⁻⁵ to guarantee a fast and accurate MPP tracking for continuously harvesting maximum power from the incident sunlight. An energy storage unit of 12 batteries 12 V/150 Ah of matrix dimensions 3 × 4 is designed in the DC unit for energy saving to feed the DC appliances during night hours. MATLAB/Simulink Version R2015b is used to simulate the introduced DC power unit and collect the testing records for analyzing the unit performance. Full article

In this paper, a novel microgrid (MG) concept suitable for direct current (DC) multibus architectures is depicted. Multibus feature is improved in order to distribute power in DC using a number of buses at different voltage level. A teachers offices building that houses several kinds of loads, including a charging station for electric vehicles (EV), is considered to validate the strategy. Several topologies of power electronics converters (PECs) are included in the system to perform specific tasks and providing isolation between bus and final loads. In order to develop the PECs, first, a switching function is used to obtain average model of each converter. Then, converters design is done by using well known methods that allow to obtain parameter values of all the devices in every version of each kind of converter. A hierarchical control is selected to govern the direct current microgrid (DCMG). At a lower control level, local control stage is implemented and tuned using models and designs obtained, with linear controllers in some PECs and classic strategies in others. In higher control level, there is a supervisory strategy that prioritizes the use of generated power to supply the building’s loads. This energy management system (EMS) is based in Petri net theory; it consists of a start-up test, then source condition synchronous algorithm and load condition synchronous algorithm operate the DCMG according to the mentioned priority. Finally, PECs are tested on standalone, performing in closed loop, facing load changes to verify the adequate operation. Some trajectories of a simplified version of the CDMG are tested with local control in order to validate the multibus multivoltage concept. In order to verify coordinated control, some events managed by EMS are presented. Full article

Identifying flexible loads, such as a heat pump, has an essential role in a home energy management system. In this study, an adaptive ensemble filtering framework integrated with long short-term memory (LSTM) is proposed for identifying flexible loads. The proposed framework, called AEFLSTM, takes advantage of filtering techniques and the representational power of LSTM for load disaggregation by filtering noise from the total power and learning the long-term dependencies of flexible loads. Furthermore, the proposed framework is adaptive and searches ensemble filtering techniques, including discrete wavelet transform, low-pass filter, and seasonality decomposition, to find the best filtering method for disaggregating different flexible loads (e.g., heat pumps). Experimental results are presented for estimating the electricity consumption of a heat pump, a refrigerator, and a dishwasher from the total power of a residential house in British Columbia (a publicly available use case). The results show that AEFLSTM can reduce the loss error (mean absolute error) by 57.4%, 44%, and 55.5% for estimating the power consumption of the heat pump, refrigerator, and dishwasher, respectively, compared to the stand-alone LSTM model. The proposed approach is used for another dataset containing measurements of an electric vehicle to further support the validity of the method. AEFLSTM is able to improve the result for disaggregating an electric vehicle by 22.5%. Full article

This manuscript proposes an integrated system for treating hospital solid waste (H.S.W.) consisting of an incineration and frictional sterilization system capable of operating during normal and emergency situations. We analyzed the benefits of integrating different hospital solid waste (H.S.W.) treatment systems with the existing stand-alone incineration system, with a particular emphasis on the thermal friction sterilization integration system. The objective was to define the economic advantages and benefits in terms of resources recovery of using the thermal frictional sterilization–incineration integrated system during the hospital’s normal and emergency/pandemic operating conditions. We modeled three modeling scenarios based on normal and emergency operating conditions. The results show that the H.S.W. was composed of 74% general H.S.W. Existing incineration systems would be the most expensive process because the sanitary transportation cost represented approximately 96% of the H.S.W. costs. The hospital would realize 40–61% savings relative to the existing method if the integrated incineration–frictional systems were implemented to treat 50–70% of H.S.W.; the savings were better than in other scenarios. Proposed scenario 3 had a much better resources recovery factor than scenarios 1 and 2. This modeling study showed that a thermal frictional sterilization–incineration system could work well even under emergency conditions if the H.S.W. in-house sorting/transportation/storage process is modified to cater to other H.S.W. treatment/sterilization systems. Full article

The environmental impacts of single-use plastics are increasing worldwide due to the continual rise in consumption and a lack of appropriate collection and management systems in many countries. Various programs, known as container deposit schemes (CDS), have been implemented to improve the collection and recycling of single-use plastic containers. This research investigated the drivers and barriers of CDS uptake in Perth, Western Australia. The study surveyed over 400 individuals within Perth regarding their engagement with and usage of the local CDS, known as “Containers for Change”, which was implemented in October 2020. This research found that there is a high level of public awareness (98%) of the scheme, and it has been widely adopted across Perth within the first year of its implementation; however, logistical challenges and container eligibility were found to be key barriers to the uptake of the scheme. It was noted that there is some skepticism toward waste management practices in Australia, and knowledge of the benefits of CDS appears to be lacking. Recommendations for improving the functionality and uptake of the Containers for Change scheme are to increase the range of bottles accepted within the scheme, create more accessible and convenient drop-off locations for containers, and improve/increase education regarding the benefits of the scheme. This research is limited by a response rate that was dominated by individuals living in stand-alone houses; however, with the majority of Perth residents living in stand-alone houses, this research remains valuable. There is scope for further research into skepticism regarding waste management practices in Australia, as well as the logistical challenges of CDS uptake by apartment dwellers. Full article