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The development of cleaner, more environmentally friendly processes in polymerization technology is crucial due to the prevalent use of volatile organic solvents (VOCs), which are harmful and toxic. Future regulations are likely to limit or ban VOCs. This review explores the use of supercritical solvents, specifically supercritical CO2 (scCO2), in polymerization processes. The study focuses on reversible addition‐fragmentation chain‐transfer (RAFT) induced homo‐polymerization of various monomers using specific chain transfer agents (CTAs) in scCO2. RAFT polymerization, a reversible deactivation radical polymerization (RDRP) polymerization, relies heavily on the choice of CTA, which significantly influences the dispersity and molar mass of the resulting polymers. Stabilizers are also crucial in controlling product specifications for polymerizations in supercritical CO2, except for fluor‐based polymers, although they must be removed and preferably recycled to ensure product purity and sustainability. The review notes that achieving high molar mass through RAFT polymerization in scCO2 is challenging due to solubility limits, which lead to polymer precipitation. Despite this, RAFT polymerization in scCO2 shows promise for sustainable, circular production of low molar mass polymers, although these cannot yet be fully considered green products. [ABSTRACT FROM AUTHOR]

Among the steelmaking slag, secondary metallurgy slag (SMS) is the most problematic to be recycled. Several attempts to recover such slag as lime replacement, slag flux, pozzolanic materials have been made for long time with pros and cons. However, the amount of recyclable slag is limited and often their employment requires higher energy demand than traditional materials. Nevertheless, the use of SMS in agriculture is poorly or never considered. In this article, the legal and technical evaluation of SMS as raw material for fertilizers production is investigated. Compliance of technical specification, toxic metals concentration, and leaching behavior allows to confirm the technical feasibility of SMS use as a raw material for fertilizers manufacture. Both from the literature data and the experimental results on 16 industrial SMS samples, the requirements for calcium‐magnesium‐sulfur‐based fertilizers, soil correctives and for sanitizing agricultural sewage sludge, appear fully satisfied. The CaO concentration in SMS (35–60 wt%) is abundantly higher than the requirements (≥15 wt%) and CaO is present in most part as water‐soluble complexes such as calcium aluminates (70 wt%), silicates (10 wt%), and sulfide (4 wt%). The pH of the SMS samples leachate is comparable to that of fresh lime (12.35 vs 12.46), highlighting a better behavior for sewage sludge sanitation with respect to limestone (9.98). The measured toxic metals and leachate elements concentration over the corresponding admittable threshold are always lower than 0.5 and 1.0 (mg kg−1/mg kg−1) for liming materials. Finally, these results lead to officially approve the use of SMS as soil corrective according to the Italian Fertilizer Regulation. [ABSTRACT FROM AUTHOR]

Background/Purpose Methods Results Conclusions Implantable loop recorders (ILR) are increasingly used in cardiac rhythm monitoring and diagnostic work‐up of unexplained syncope. ILR battery longevity, according to manufacturers' product performance specifications, typically ranges between 2 and 4 years, but real‐world data in this population are lacking.This monocentric, prospective, observational study included consecutive patients with unexplained syncope undergoing ILR implantation between October 2007 and 2019. The main purpose was to determine real‐world battery longevity of ILRs. Diagnostic yield and relationship between arrhythmogenic diagnosis and duration of ILR monitoring were explored.The study included 309 patients (59 years [38–73], 49% female) with ILR implantation for unexplained syncope. Median battery longevity was 42 [40–45] months. A total of 99.5% of ILRs reached prespecified battery longevity. The time to end‐of‐life varied by up to 33 months among the same ILR models. Overall arrhythmogenic diagnostic yield counted 27% (73% sick sinus syndrome, 20% atrioventricular block, and 7% ventricular tachycardia). Median time to diagnosis was 10 [2–25] months, with the latest event at 43 months. The cumulative diagnostic yield for arrhythmogenic event explaining syncope was 4.2%, 6.1%, 9.4%, 14.6%, 19.4%, and 26.7% at 1, 2, 6, 12, 24, and 48 months, respectively. In univariate analysis, first degree AV block and prolonged HV time on EP study were predictors of diagnosis, while QRS duration abnormality borderline missed significance.Real‐world battery longevity of ILRs matched industry projected longevity in 99.5% of patients implanted with ILR for unexplained syncope. A battery longevity of minimum 3.5 years is recommended to maximize the diagnostic yield in this population. [ABSTRACT FROM AUTHOR]

Gender equality is one of the Sustainable Development Goals (SDGs) of the 2030 Agenda. However, in the advertising industry, several studies have shown the low presence of women working in the field of creativity, occupying management positions and being part of festival juries. The aim of the study is to analyse the presence of women in the field of advertising festivals. The methodology is based on a quantitative analysis of the 2000 to 2023 editions of the Club de Creativos National Creativity Awards and the Cannes Lions International Festival of Creativity. The composition of the juries of both festivals, the special awards for professionals in the sector (cdec de Honor and Lion of St. Mark, respectively), the technical specifications of the grand prizes (National Grand Prize for Creativity and Grand Prix won by Spain, respectively) and the management teams of the organising entities are analysed in the indicated period. The results demonstrate the underrepresentation of women in advertising festivals, especially in the composition of the juries, in the special recognitions and in the technical sheets of the most outstanding campaigns, corroborating the findings of previous research. Despite the emerging initiatives that defend parity in the advertising profession, this equality is still not real, nor does it materialize in the events that make the industry visible and recognize its evolution: advertising festivals. [ABSTRACT FROM AUTHOR]

In high-speed rail operations, the pantograph-catenary system is commonly utilised to transmit electricity to the high-speed train. This is achieved through a sliding contact between the pantograph strip and the contact wire of the catenary. The pantograph strip, typically made of softer carbon material, is designed to experience wear, ensuring that the replaceable and cost-effective strip is more likely to deteriorate than the contact wire. However, imperfections in the pantograph strip can adversely affect the interaction performance of the pantograph-catenary system. To quantify the effect of pantograph strip imperfections on the interaction performance, this paper aims to incorporate the measurement data of pantograph strip wear into the numerical simulation of pantograph-catenary interaction. The study collected 58 sets of measurement data on pantograph strip wear from Shanghai Hongqiao station. By employing a well-developed pantograph-catenary model, several numerical simulations were conducted to investigate the dispersion of dynamic behaviours caused by strip wear. The results demonstrate that the inclusion of strip imperfections introduces a certain level of dispersion in the interaction behaviours of the pantograph-catenary system. Specifically, at the operating speed of 300 km/h, strip imperfections can lead to a 16.62% increase in the standard deviation of the contact force and an overall decrease in the minimum contact force. Consequently, it is crucial to update the technical specifications to account for the impact of pantograph strip disturbances. Furthermore, each strip's wear induces a comparable level of dispersion in the contact force standard deviation. However, the contact force on the rear strip typically exhibits greater fluctuation, making it a significant contributor to the overall interaction performance. [ABSTRACT FROM AUTHOR]

This article explores the ethical problems arising from the use of ChatGPT as a kind of generative AI and suggests responses based on the Human-Centered Artificial Intelligence (HCAI) framework. The HCAI framework is appropriate because it understands technology above all as a tool to empower, augment, and enhance human agency while referring to human wellbeing as a "grand challenge," thus perfectly aligning itself with ethics, the science of human flourishing. Further, HCAI provides objectives, principles, procedures, and structures for reliable, safe, and trustworthy AI which we apply to our ChatGPT assessments. The main danger ChatGPT presents is the propensity to be used as a "weapon of mass deception" (WMD) and an enabler of criminal activities involving deceit. We review technical specifications to better comprehend its potentials and limitations. We then suggest both technical (watermarking, styleme, detectors, and fact-checkers) and non-technical measures (terms of use, transparency, educator considerations, HITL) to mitigate ChatGPT misuse or abuse and recommend best uses (creative writing, non-creative writing, teaching and learning). We conclude with considerations regarding the role of hu mans in ensuring the proper use of ChatGPT for individual and social wellbeing. [ABSTRACT FROM AUTHOR]

In today's society, keeping our gardens attractive is complex, especially if you need more time to care for them. This can cause the plant to wilt if it is not watered occasionally to keep the soil moist. In summer, this problem tends to get worse because the temperature tends to rise and reach high degrees. The objective is to design an automatic and manual irrigation system with a humidity detector through hardware programming and free software to solve this. The necessary components will be identified and selected, humidity thresholds will be established, and the adoption of technologies such as internet of things (IoT), Arduino, and humidity sensors will be promoted to solve the problem in automated irrigation systems. The technical specifications of the components are described, and the circuit design is presented. A programming algorithm will be developed to control the frequency and duration of irrigation, as well as the state of the water pump. Implementing the automated system will allow precise water supply control, contributing to the healthy growth of plants and crops in green areas. [ABSTRACT FROM AUTHOR]

Electric mobility is a sustainable alternative for mitigating carbon emissions by replacing the conventional fleet. However, the low availability of data from charging stations makes planning energy systems for the integration of electric vehicles (EVs) difficult. Given this, this work focuses on developing an adaptive computational tool for charging simulation, considering many EVs and mobility patterns. Technical specifications data from many EVs are considered for charging simulation, such as battery capacity, driving range, charging time, charging standard for each EV, and mobility patterns. Different simulations of charging many EVs and analyses of weekly charging load profiles are carried out, portraying the characteristics of the different load profiles and the challenges that system planners expect. The research results denote the importance of considering different manufacturers and models of EVs in the composition of the aggregate charging load profile and mobility patterns of the region. The developed model can be adapted to any system, expanded with new EVs, and scaled to many EVs, supporting different research areas. [ABSTRACT FROM AUTHOR]

Railway transportation has been integrated into people's lives. According to the "Notice on the release of the General Technical Specification of High-speed Railway Power Supply Safety Testing (6C System) System" issued by the National Railway Administration of China in 2012, it is required to install pantograph and slide monitoring devices in high-speed railway stations, station throats and the inlet and exit lines of high-speed railway sections, and it is required to detect the damage of the slider with high precision. It can be seen that the good condition of the pantograph slider is very important for the normal operation of the railway system. As a part of providing power for high-speed rail and subway, the pantograph must be paid attention to in railway transportation to ensure its integrity. The wear of the pantograph is mainly due to the contact power supply between the slide block and the long wire during high-speed operation, which inevitably produces scratches, resulting in depressions on the upper surface of the pantograph slide block. During long-term use, because the depression is too deep, there is a risk of fracture. Therefore, it is necessary to monitor the slider regularly and replace the slider with serious wear. At present, most of the traditional methods use automation technology or simple computer vision technology for detection, which is inefficient. Therefore, this paper introduces computer vision and deep learning technology into pantograph slide wear detection. Specifically, this paper mainly studies the wear detection of the pantograph slider based on deep learning and the main purpose is to improve the detection accuracy and improve the effect of segmentation. From a methodological perspective, this paper employs a linear array camera to enhance the quality of the data sets. Additionally, it integrates an attention mechanism to improve segmentation performance. Furthermore, this study introduces a novel image stitching method to address issues related to incomplete images, thereby providing a comprehensive solution. [ABSTRACT FROM AUTHOR]

This document discusses the intersection of sustainability and digitalization in manufacturing companies, highlighting the challenges they face in addressing environmental and social impacts. The concept of Maintenance 4.0 is introduced as a way to enhance and advance maintenance processes using technologies such as the Industrial Internet of Things (IIoT), Augmented Reality (AR), Virtual Reality (VR), Big Data Analytics (BDA), and AI. The document also provides an overview of 13 articles included in a special issue on Maintenance 4.0 and sustainability, covering topics such as predictive maintenance, augmented reality, digital twins, and environmental considerations in maintenance activities. The authors emphasize the importance of Industry 4.0 technologies in transforming maintenance processes and supporting sustainable development goals. [Extracted from the article]

Graphene growth on widely used dielectrics/insulators via chemical vapor deposition (CVD) is a strategy toward transfer-free applications of CVD graphene for the realization of advanced composite materials. Here, we develop graphene-skinned alumina fibers/fabrics (GAFs/GAFFs) through graphene CVD growth on commercial alumina fibers/fabrics (AFs/AFFs). We reveal a vapor-surface-solid growth model on a non-metallic substrate, which is distinct from the well-established vapor-solid model on conventional non-catalytic non-metallic substrates, but bears a closer resemblance to that observed on catalytic metallic substrates. The metalloid-catalytic growth of graphene on AFs/AFFs resulted in reduced growth temperature (~200 °C lower) and accelerated growth rate (~3.4 times faster) compared to that obtained on a representative non-metallic counterpart, quartz fiber. The fabricated GAFF features a wide-range tunable electrical conductivity (1-15000 Ω sq−1), high tensile strength (>1.5 GPa), lightweight, flexibility, and a hierarchical macrostructure. These attributes are inherited from both graphene and AFF, making GAFF promising for various applications including electrical heating and electromagnetic interference shielding. Beyond laboratory level preparation, the stable mass production of large-scale GAFF has been achieved through a home-made roll-to-roll system with capacity of 468-93600 m2/year depending on product specifications, providing foundations for the subsequent industrialization of this material, enabling its widespread adoption in various industries. Chemical vapor deposition (CVD) of graphene on widely used insulators can promote its application for functional composite materials. Here, the authors report the large-scale production of graphene alumina fibers/fabrics via a metalloid-catalytic CVD growth process on commercial alumina, showing their application for electrical heating and electromagnetic shielding. [ABSTRACT FROM AUTHOR]

Fuel cell vehicles are considered as the direct alternative to fuel vehicles due to their similar driving range and refueling time. The United Nations World Forum for Harmonization of Vehicle Regulations (UN/WP29) released the Global Technical Regulation on Hydrogen and Fuel Cell Vehicles (GTR13) in July 2013, which was the first international regulation in the field of fuel cell vehicles. There exist some differences between GTR13 and the existing safety technical specifications and standards in China. This paper studied the safety requirements of the GTR13 compressed hydrogen storage system, analyzed the current hydrogen storage safety standards for fuel cell vehicles in China, and integrated the advantages of GTR13 to propose relevant suggestions for future revision of hydrogen storage standards for fuel cell vehicle in China. [ABSTRACT FROM AUTHOR]

Pharmacopeia monographs are not intended to establish biosimilarity. However, the US Food and Drug Administration (FDA) has stopped the US Pharmacopeia (USP) from creating monographs for biological drugs due to the need for side-by-side comparisons with the reference products. The USP can create Biological Product Specifications (BPS), not to be labeled as monographs, based on the analytical testing of reference products and validated test methods that will remove the need for side-by-side analytical testing of biosimilars with reference products. Scientific arguments confirm that this plan is logical and capable of creating global quality standards for biosimilars to allow their interchangeability with other biosimilars. While the regulatory agencies have waived many high-cost biosimilar tests, analytical assessment is the most sensitive test; reducing its cost will further enhance the entry of biosimilars with no clinically meaningful difference. [ABSTRACT FROM AUTHOR]

There is a growing need for a more streamlined and automated method of refining biofuels, as there are currently no universally applicable process inspection instruments on the market. All process variables in bio-oil upgrading operations are maintained according to the offline specifications of the products and intermediates. Failure of the process and loss of resources can result from batch-wise monitoring not having real-time product standards. Consequently, in order to cut down on waste and lessen the chances of process failure, a quick and accurate tool for specifying intermediates and products is required. To resolve this issue, we created a model using response surface methodology and an artificial neural network that can increase the bio-oil yield involving parameters, i.e., biomass particle size (mm), temperature (°C), and residence time (min). The maximum bio-oil production (47.0883%) was achieved at 3 mm particle size, 523°C temperature, and 20 min residence time. All results are "better" for root mean squared error (∼1), and the highest coefficient of regression for bio-oil production is in the range of 0.97–0.99. Temperature is the most significant factor in bio-oil yield, followed by particle size and residence time. Based on physicochemical properties, bio-oil has the maximum kinematic viscosity (11.3 Cst) and water content (18.7%). Making bio-oil precious compounds allows it to be used as boiler feedstock and steam generation fuel. [ABSTRACT FROM AUTHOR]

In the process of industrial production, products with different specifications (i.e., the difference in geometry, process conditions, and machine conditions, etc.) have different quality data distributions, which lead to a decrease in the accuracy of traditional data-driven quality prediction models that require the same quality data distribution. At the same time, due to economic cost factors, obtaining a large amount of accumulated data for different specifications is difficult, and the re-modeling data accumulation of multiple cross-specifications is insufficient. In order to solve the quality prediction problem of production with different data distributions and poor data accumulation, we use the deep transfer learning (DTL) method with unsupervised dynamic domain adaptation (DDA) to transfer the domain invariant features learned from labeled specification products (source domain) to other unlabeled new specification products (target domain). In order to improve the success rate of cross-domain quality prediction, the Wasserstein distance adapter is designed to match appropriate source domain samples and target domain samples to build multiple transfer tasks that are suitable for transfer. At the same time, the dynamic distribution adaptation and dynamic adversarial adaptation are combined to extract the domain invariant features to improve the adaptability of the prediction model for products with new specifications (e.g., size difference) and unlabeled and limited quality data. Finally, a comprehensive experiment is carried out using the actual production data of products with different specifications. The experimental results show that compared with the traditional non-transfer deep learning methods, the MAE, RMSE, and R2 of the proposed DTL method are improved by 18.26%, 16.66%, and 22.48% respectively. Compared with other transfer methods, the MAE, RMSE, and R2 of the DTL proposed in this paper are improved by 10.45%, 10.96%, and 9.72% respectively. [ABSTRACT FROM AUTHOR]

With the progressive reduction in virgin material availability and the growing global concern for sustainability, civil engineering researchers worldwide are shifting their attention toward exploring alternative and mechanically sound technological solutions. The feasibility of preparing both cold and hot asphalt mixtures (AMs) for road pavement binder layers with construction and demolition wastes (C&DWs) and reclaimed asphalt pavement (RAP) partially replacing virgin materials like limestone aggregates and filler has already been proven. The technical suitability and compliance with technical specifications for road paving materials involved the evaluation of mechanical and volumetric aspects by means of indirect tensile strength tests and saturated surface dry voids, respectively. Thus, the main goal of the present study is to train, validate, and test selected machine learning algorithms based on data obtained from the previous experimental campaign with the aim of predicting the volumetric properties and the mechanical performance of the investigated mixtures. A comparison between the predictions made by ridge and lasso regression techniques and both shallow (SNN) and deep neural network (DNN) models showed that the latter achieved better predictive capabilities, highlighted by fully satisfactory performance metrics. DNN performance can be summarized by R2 values equal to 0.8990 in terms of saturated surface dry void predictions, as well as 0.9954 in terms of indirect tensile strength predictions. Predicted observations can be thus implemented within the traditional mix design software. This would reduce the need to carry out additional expensive and time-consuming experimental campaigns. [ABSTRACT FROM AUTHOR]

The prompt emphasizes the importance of identifying victims in a disaster area within 48 hours and highlights the potential benefits of using drones in search and rescue missions. However, the use of drones is limited by factors such as battery life, processing speed, and communication range. To address these limitations, the paper presents a detailed research study on the most effective flying pattern for drones during search and rescue missions. The study utilized energy consumption and coverage area as performance metrics and collected precise images that could be analyzed by the forensic team. The research was conducted using OMNET++ and fieldwork at Pulau Sebang, Melaka, in collaboration with search and rescue agencies in Malaysia. The results suggest that the square flying pattern is the most effective, as it provides the highest coverage area with reasonable energy utilization. Both simulation and fieldwork results showed coverage of 100% and 97.96%, respectively, for this pattern. Additionally, the paper provides technical specifications for rescue teams to use when deploying drones during search and rescue missions. [ABSTRACT FROM AUTHOR]

Electrical machines that can run at high speeds are more and more studied as they can respond to the increasing need of power onboard of aircrafts. However, to allow high-speed operability mechanical handling of the rotating parts need to be insured. In this paper an analytic design process of a novel high-speed induction machine is presented. The analytical magnetic and mechanical models developed are presented and validated with finite element simulations. The magnetic model is based on a classic equivalent electrical diagram of induction machine with a specific adaptation for the rotor leakage inductance as the squirrel cage is buried. The mechanical model is based on a field displacement approach leading to the stress tensor in all the rotating part. A four degrees of freedom vibration analysis model considering gyroscopic effects based on Euler–Lagrange equation allows to identify the critical speeds of the system. It is shown that some geometrical parameters will have opposed effects on the two physics. Thus, an optimization-based coupling between the different physics allows to design rapidly the desired machine regarding any technical specifications as analytical models are being used. [ABSTRACT FROM AUTHOR]

Background: 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) is commonly used for diagnosis of dementia because brain glucose metabolism reflects neuronal activity. However, as [18F]FDG is an analogue of glucose, accumulation of tracer in the brain is affected by plasma glucose levels. In contrast, cerebral blood flow (CBF) tracers are theoretically unaffected by plasma glucose levels and are therefore expected to be useful alternatives for the diagnosis of dementia in patients with diabetes. The techniques currently used for CBF imaging using single photon emission computed tomography (SPECT) and [15O]H2O positron emission tomography (PET), but these are limited by their insufficient resolution and sensitivity for regional brain imaging, especially in patients with brain atrophy. N-isopropyl-4-[11C]methylamphetamine ([11C]MMP) is a possible CBF tracer with high resolution and sensitivity that exhibits comparable performance to that of [15O]H2O in conscious monkey brains. We performed process validation of the radiosynthesis and preclinical development of [11C]MMP prior to clinical translation. Results: The decay-corrected yields of [11C]MMP at the end of synthesis were 41.4 ± 6.5%, with 99.7 ± 0.3% radiochemical purity, and 192.3 ± 22.5 MBq/nmol molar activity. All process validation batches complied with the product specifications. The acute toxicity of MMP was evaluated at a dose of 3.55 mg/kg body weight, which is 10,000 times the potential maximum clinical dose of [11C]MMP. The acute toxicity of [11C]MMP injection at 150 or 200 times, to administer a postulated dose of 740 MBq of [11C]MMP, was also evaluated after the decay-out of 11C. No acute toxicity of MMP and [11C]MMP injection was found. No mutagenic activity was observed for MMP. The effective dose calculated according to the Medical Internal Radiation Dose (MIRD) method was 5.4 µSv/MBq, and the maximum absorbed dose to the bladder wall was 57.6 µGy/MBq. MMP, a derivative of phenylalkylamine, showed binding to the sigma receptor, but had approximately 1/100 of the affinity of existing sigma receptor imaging agents. The affinity for other brain neuroreceptors was low. Conclusions: [11C]MMP shows acceptable pharmacological safety at the dose required for adequate PET imaging. The potential risk associated with [11C]MMP PET imaging is well within the acceptable dose limit. [ABSTRACT FROM AUTHOR]

Background: Integrating diverse sensor technologies into smart insoles offers significant potential for monitoring biomechanical metrics; enhancing sports performance; and managing therapeutic interventions, diseases, disorders, and other health-related issues. The variation in sensor types and applications requires a systematic review to synthesize existing evidence and guide future innovations. Objectives: This review aims to identify, categorize, and critically evaluate the various sensors used in smart insoles, focusing on their technical specifications, application scopes, and validity. Methods: Following the PRISMA guidelines, a search was conducted in three major electronic databases, namely, PubMed, Scopus, and Web of Science, for relevant literature published from 2014 to 2024. Other works not located in the mentioned databases were added manually by parallel searches on related themes and suggestions from the website of the databases. To be eligible, studies were required to describe sensor implementation in insoles, specify the sensor types, and report on either validation experiments or practical outcomes. Results: The search identified 33 qualifying studies. Proper analysis revealed a dominance of pressure sensors, with accelerometers and gyroscopes also being widely used. Critical applications included gait analysis, posture correction, and real-time athletic and rehabilitation feedback. The review also examined the relative effectiveness of different sensor configurations. Conclusions: This systematic review comprehensively classifies sensor technologies within smart insoles and highlights their broad application potential across various fields. Future research should aim to standardize measurement protocols, enhance sensor integration, and advance data processing techniques to boost functionality and clinical applicability. [ABSTRACT FROM AUTHOR]

With the rapid advancement of computer vision, machine learning, and consumer electronics, eye tracking has emerged as a topic of increasing interest in recent years. It plays a key role across diverse domains including human–computer interaction, virtual reality, and clinical and healthcare applications. Near-eye tracking (NET) has recently been developed to possess encouraging features such as wearability, affordability, and interactivity. These features have drawn considerable attention in the health domain, as NET provides accessible solutions for long-term and continuous health monitoring and a comfortable and interactive user interface. Herein, this work offers an inaugural concise review of NET for health, encompassing approximately 70 related articles published over the past two decades and supplemented by an in-depth examination of 30 literatures from the preceding five years. This paper provides a concise analysis of health-related NET technologies from aspects of technical specifications, data processing workflows, and the practical advantages and limitations. In addition, the specific applications of NET are introduced and compared, revealing that NET is fairly influencing our lives and providing significant convenience in daily routines. Lastly, we summarize the current outcomes of NET and highlight the limitations. [ABSTRACT FROM AUTHOR]

Many aviation education and training programs are expanding their learning materials to include virtual learning environments (VLEs) that utilize virtual reality (VR) technology. While developing training materials and the VLE, an understanding of technical specification requirements is needed to inform stakeholders who need to choose a headset for a given training scenario. As part of a larger initiative to compare the usability of multiple VR headsets for implementation into procedural training, a review of the extant literature was conducted to identify technical specifications of VR head-mounted displays, followed by a pilot test of a headmounted display (HMD) comparison methodology that considers VR HMD technical specifications ("tech specs") and usability aspects. This report identifies key technical specifications for VR HMDs which can be used as a guideline as technology changes. Further research and collaboration are anticipated to elaborate on the technical specifications to recommend for aviation training initiatives. [ABSTRACT FROM AUTHOR]

This study aims to propose a thermal loop model-based simulation and analysis method for predicting the hotspot temperature of converter transformers in Ultra-High Voltage Direct Current (UHVDC) transmission systems, aiming to address the technical deficiencies in hotspot temperature monitoring of converter transformers in UHVDC transmission engineering. With the advancement of UHVDC transmission technology, converter transformers have emerged as critical electrical components. Operating at elevated voltage levels and accommodating large capacities, these converter transformers experience substantial losses within their windings. Consequently, the issue of winding overheating has become increasingly prominent. The method involves utilizing MATLAB/Simulink to simulate the temperature rise model of converter transformers. The hotspot temperature model adopted in this paper is simple and easy to understand, enabling effective simulation analysis of the top-oil temperature and hotspot temperature of the converter transformer. Configuring simulation parameters derived from existing technical specifications and monitoring data, and subsequently computing the hotspot temperature to satisfy engineering criteria. The simulation analysis of the converter transformer with a rated capacity of 412 300 kVA is conducted using Infolytica MagNet. By comparing the measured data of the top oil temperature and hotspot temperature of the converter transformer with the calculation results of the standard model and the simulation results, the rationality and accuracy of the heat circuit model calculation are verified. This hotspot temperature simulation analysis method provides a new solution for the hotspot temperature detection of the converter transformer. [ABSTRACT FROM AUTHOR]

Due to the continuous introduction of new building technologies, research results, and technical specifications, the design and construction process of buildings has become extremely complex, paying more attention to the sustainable development of the building itself; it not only requires close communication between project participants, but also an in-depth analysis of building performance and structure is required during the design phase. Building Information Modeling (BIM) technology has been widely used in the development of the construction industry in recent years. It can effectively realize the integration of building information, so that all parties involved in the project can work together based on the same platform, which can more effectively improve work efficiency and save resource input, lower construction costs, and ultimately achieve the goal of sustainable development. On the basis of summarizing the previous research results, this paper uses BIM technology to analyze the optimization effect of large-scale construction engineering from the aspects of information model, resource allocation and technology optimization. The analysis results provide reference for subsequent in-depth research. [ABSTRACT FROM AUTHOR]

The foundation industries in the UK were responsible for emitting 42 Mt CO2eq in 2020, which is approximately 10% of the yearly territorial greenhouse gas emissions. The UK government decarbonisation roadmap issued in 2015 predicted that high-tech strategies such as carbon capture and utilisation, hydrogen and biofuels, as well as electrification of processes are key for achieving the climate mitigating targets by 2050. In this study, a critical assessment was performed on the limitations to achieve these high-tech strategies such as biomass availability, capital investment, and technology readiness. The study is the first to use the UK carbon budget values as the resource limit for the high-tech decarbonisation strategies. The findings show that the significant uncertainty associated with the high-tech scenarios limits their decarbonisation potential by 2050. More importantly, to stay within the mid-century carbon budget for the foundation industries, 20–40% reduction in production, through circular economic strategies such as material efficiency and/or changes in product specifications, is required in order to achieve the decarbonisation targets. [ABSTRACT FROM AUTHOR]

Turkey's Highway Technical Specification (HTS) necessitates gritting of pavement surface courses for the regions where the high-polishing resistant aggregate (PSV ≥ 50) is lacking or hard to reach. The gritting is defined as the spreading of 1–3 mm magmatic origin aggregates with the rate of 1.5–2 kg/m2 to the pavement surface after the roller's first pass. This study investigates the effect of gritting construction parameters (aggregate type, size, amount, and time of spreading) on pavement surface texture and skid resistance by monitoring the performance of nine test sections over more than three years under real traffic and environmental conditions. Considering the field observations, reduction in skid resistance with respect to traffic, in terms of equivalent standard axle load, is modeled for all test sections, and their service life is calculated. The results show that test sections gritted with the slag-origin aggregates perform better and yield nearly twice the service life of the one specified in the HTS. Accordingly, using slags in pavement gritting would provide safer and more sustainable highways. [ABSTRACT FROM AUTHOR]

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Background: One of the organisational strategies to ensure the use of relevant good practises for each stage in the life cycle of pharmaceutical products is the market surveillance program, which aims to demonstrate product specification adherence. It uses analytical pharmacopoeial and literature-based approaches primarily to carry out quality control on the chosen pharmaceutical items. Aim: Development of a program for analytical control of different medicinal products containing 25 mg hydrochlorothiazide. Materials and Methods: European Pharmacopoeia and USP HPLC methods for assay and related substances were applied in prescription medicines. Results: The system suitability tests were evaluated for each method, and the results of each generated group of products were compared. The quantitative content values deviation and the quantitative limitations for each impurity were determined. The deviations are in the range 0.76%-4.01%. Calculated RSD values are below 2%. The results obtained by both methods are within the acceptable limits of 95%-105%. In the European Pharmacopoeia method, the limits of three impurities were determined and seven more were found and marked as unknown. The USP method allows identification of only one impurity. Conclusion: For the market surveillance program for pharmaceuticals containing hydrochlorothiazide, an analytical control program has been developed. The program combines multiple pharmacopoeial HPLC methods and compares the outcomes with an initial assessment of each method's applicability for all pharmaceuticals containing hydrochlorothiazide. [ABSTRACT FROM AUTHOR]

Background: Acute otitis media (AOM) causes inflammation and hearing loss. Ventilation tubes are key in treatment. 3D printing improves prostheses in otorhinolaryngology, offering precision and greater adaptability. Materials and methods: An experimental study was conducted with Wistar rats from July to December 2020. 3D tympanostomy tube models were designed, with technical specifications and tests performed on inexpensive 3D printers. The tympanostomy tube was inserted endoscopically. Results: Procedures were performed on five rats with implants in both ears. Pre-intervention pathologies, such as atical retraction and glue ear, were found. The PLA-printed tympanostomy tube showed improvement after adjustments. Histopathological results revealed significant middle and inner ear damage. Conclusion: In our study, the design and 3D printing of implants fulfilled the desired functions when modified, with a height of 5 mm. Complications included PLA degradation and ear damage. There were no adverse events during observation, highlighting the need for further research on 3D-printed implants. [ABSTRACT FROM AUTHOR]

This study aimed to analyze and optimize the thermal induction hardening process applied to toothed transmission gears, focusing on thermal aspects, structural deformation, and topology optimization, while exploring the feasibility of various materials and operating conditions. The research simulated thermal and deformation behavior using a computer model, comparing results with experimental data through the Ansys® platform 2022 R1. The methodology encompassed thermal and deformation analyses, topology optimization to identify removable regions without compromising part integrity, and a sensitivity study to evaluate the different materials and operating conditions. This study validates the precision of computational models in predicting thermal and deformation behavior in toothed gears under thermal induction hardening, introducing topology optimizations and alternative materials, and providing novel perspectives for the more efficient and cost-effective manufacturing of these components. Comparative thermal analysis revealed a maximum relative error of less than 6% between temperatures from the computer model and experimental results, while deformation comparisons exhibited a maximum relative error of less than 7%, affirming the simulation model's accuracy in predicting and managing deformations within acceptable thresholds. Topology optimization successfully pinpointed removable regions without compromising structural integrity, enabling the production of lighter and more economical devices. Future endeavors should concentrate on additional tests to verify the feasibility of reducing power and cooling temperature without compromising product specifications. Furthermore, it is advisable to explore alternative materials and apply the developed methodology in diverse industrial settings to generalize the findings and amplify the impact of the proposed optimizations. [ABSTRACT FROM AUTHOR]

Ammonia as a fuel has been known for several years, but only relatively recently has it attracted interest for study and use as a marine fuel. A forthcoming generation of sustainable, economically viable, and safe technologies for the large-scale onboard storage of ammonia as a marine fuel is being developed. This article presents a structured approach to carrying out Quality Function Deployment (QFD) for evaluating a project solution at the strategic level. The "House of Quality" (HoQ) method is utilised since it provides the means for inter-functional planning and communications among people with different problems and responsibilities. The project requirements are defined and lead to functional technical characteristics to satisfy these needs. The approach allows for the application of a weighting scheme to rank the perceived relative importance of the requirements, the difficulty involved in implementing the technologies, and the relationship between requirements and functional technical characteristics. QFD analysis prioritises safety compliance, technical specifications, emission control, and operational efficiency. The added value of this work is beyond the life of a project since it may provide assistance to the stakeholders in assessing the applicability of ammonia fuel solutions given the resources available to them. This feature will enable the justification of further investment into specific technologies based on their potential impact. [ABSTRACT FROM AUTHOR]

ABSTRACT Recombinant adeno‐associated virus (AAV) has become a popular platform for many gene therapy applications. The strength of AAV‐based products is a critical quality attribute that affects the efficacy of the drug and is measured as the concentration of vector genomes, or physical titer. Because the dosing of patients is based on the titer measurement, it is critical for manufacturers to ensure that the measured titer of the drug product is close to the actual concentration of the batch. Historically, dosing calculations have been performed using the measured titer, which is reported on the drug product label. However, due to recent regulatory guidance, sponsors are now expected to label the drug product with nominal or “target” titer. This new expectation for gene therapy products can pose a challenge in the presence of process and analytical variability. In particular, the manufacturer must decide if a dilution of the drug substance is warranted at the drug product stage to bring the strength in line with the nominal value. In this paper, we present two straightforward statistical methods to aid the manufacturer in the dilution decision. These approaches use the understanding of process and analytical variability to compute probabilities of achieving the desired drug product titer. We also provide an approach for determining an optimal assay replication strategy for achieving the desired probability of meeting drug product release specifications. [ABSTRACT FROM AUTHOR]

Thanks to the recent development of innovative instruments and software with high accuracy and resolution, 3D modelling provides useful insights in several sectors (from industrial metrology to cultural heritage). Moreover, the 3D reconstruction of objects of artistic interest is becoming mandatory, not only because of the risks to which works of art are increasingly exposed (e.g., wars and climatic disasters) but also because of the leading role that the virtual fruition of art is taking. In this work, we compared the performance of four 3D instruments based on different working principles and techniques (laser micro-profilometry, structured-light topography and the phase-shifting method) by measuring four samples of different sizes, dimensions and surface characteristics. We aimed to assess the capabilities and limitations of these instruments to verify their accuracy and the technical specifications given in the suppliers' data sheets. To this end, we calculated the point densities and extracted several profiles from the models to evaluate both their lateral (XY) and axial (Z) resolution. A comparison between the nominal resolution values and those calculated on samples representative of cultural artefacts was used to predict the performance of the instruments in real case studies. Overall, the purpose of this comparison is to provide a quantitative assessment of the performance of the instruments that allows for their correct application to works of art according to their specific characteristics. [ABSTRACT FROM AUTHOR]

The Avalanche Terrain Exposure Scale (ATES) is an avalanche terrain classification system used to assess and communicate the exposure of backcountry terrain to the threat from avalanches, independent of daily hazard conditions. Commonly known as terrain ratings, these classifications are determined by an analysis of individual terrain parameters, which are then systematically combined to produce a single rating. The ATES model includes technical specifications for assessing terrain as well as corresponding communication scales for effectively sharing ratings with different kinds of backcountry users. ATES ratings are found in guidebooks and route descriptions or displayed spatially on maps. The system was originally introduced in Canada in 2004 as a risk management tool in conventional avalanche safety practices for public recreation and workplace avalanche safety. This paper introduces ATES v.2, an update to the system that expands the original scale from three levels to five by including Class 0 – Non-Avalanche Terrain, and Class 4 – Extreme Terrain. The original ATES v.1/04 and the ATES Zoning Model are merged into a single, five-level, updated version of ATES. ATES ratings can be applied as Areas, Zones, Corridors, or Routes and then communicated using models for backcountry travel and waterfall ice climbing. [ABSTRACT FROM AUTHOR]

In the last decade, Smart Glasses (SG) and augmented reality (AR) technology have gained considerable interest in all production sectors. In the agricultural field, an SG can be considered a valuable device to support farmers and agricultural operators. SGs can be distinguished by technical specification, type of display, interaction system, and specific features. These aspects can affect their integration into farms, influencing users' experience and the consequent level of performance. The aim of the study was to compare four SGs for AR with different technical characteristics to evaluate their potential integration in agricultural systems. This study analyzed the capability of QR code reading in terms of distance and time of visualization, the audio–video quality of image streaming during conference calls and, finally, the battery life. The results showed different levels of performance in QR code reading for the selected devices, while the audio–video quality in conference calls demonstrated similar results for all the devices. Moreover, the battery life of the SGs ranged from 2 to 7 h per charge cycle, and it was influenced by the type of usage. The findings also underlined the potential use and integration of SGs to support operators during farm management. Specifically, SGs might enable farmers to obtain fast and precise augmented information using markers placed at different points on the farm. In conclusion, the study highlights how the different technical characteristics of SG represent an important factor in the selection of the most appropriate device for a farm. [ABSTRACT FROM AUTHOR]

This study demonstrates a failure identification methodology applied to a preprocessing facility generating conversion-ready feedstocks from biomass meeting conversion process critical quality attribute (CQA) specifications. Failure Modes and Effects Analysis (FMEA) was used as an industrially relevant risk analysis approach to evaluate a logging residue preprocessing system to prepare feedstock for pyrolysis conversion. Risk evaluations considered both system-level and operation unit-level assessments considering process efficiency, product quality, cost, sustainability, and safety. Key outputs included estimations of semi-quantitative risk scores for each failure, identification of the failure impacts, identification of failure causes associated with material attributes and process parameters, ranking success rates of failure detection methods, and speculation of potential mitigation strategies for decreasing failure risk scores. Results showed that deviations from moisture specifications had cascading consequences for other CQAs along with process safety implications. Failures linked to fixed carbon specifications carried the highest risk scores for product quality and process efficiency impacts. As increased throughput can be inversely related to meeting product quality specifications; achieving throughput and other material-based CQAs simultaneously will likely require system optimization or prioritization based on system economics. Ultimately, this work successfully demonstrates FMEA as a risk analysis approach for other bioenergy process systems. [ABSTRACT FROM AUTHOR]

Among the essential tools to address global environmental information requirements are the Earth-Observing (EO) satellites with free and open data access. This paper reviews those EO satellites from international space programs that already, or will in the next decade or so, provide essential data of importance to the environmental sciences that describe Earth's status. We summarize factors distinguishing those pioneering satellites placed in space over the past half century, and their links to modern ones, and the changing priorities for spaceborne instruments and platforms. We illustrate the broad sweep of instrument technologies useful for observing different aspects of the physio-biological aspects of the Earth's surface, spanning wavelengths from the UV-A at 380 nanometers to microwave and radar out to 1 m. We provide a background on the technical specifications of each mission and its primary instrument(s), the types of data collected, and examples of applications that illustrate these observations. We provide websites for additional mission details of each instrument, the history or context behind their measurements, and additional details about their instrument design, specifications, and measurements. [ABSTRACT FROM AUTHOR]

The regional coverage satellite constellations are in demand for fulfilling earth observation needs of specific user regions of interest as opposed to global coverage thus enhancing the revisit period for the area. In this paper, we present a few key mission aspects of the regional coverage constellation designed and operated by the Indian Space Research Organization (ISRO) in low earth orbit. ISRO developed three X-Band Synthetic Aperture Radar (SAR) Earth Observation satellites and placed them in three inclined orbit planes to enhance the Indian region's coverage. This is India's first inclined orbit constellation designed for remote sensing applications in low earth orbit. The satellites were built around a standard bus carrying a Synthetic Aperture Radar payload with a deployable Radial Rib Antenna (RRA). They were designed to achieve a high agility capability. As SAR sensors are capable of all-weather, day, and night imaging; thus, most suitable in inclined orbits where the illumination conditions vary continuously for imaging. Though the inclined orbits provide more revisit opportunities to the region of interest, their characteristics pose challenges in mission design and operations. Though the mission design and planning involved a host of elements, this paper brings out the details of a few key mission analysis elements, planning aspects and operations that were critical in the course of various mission phases. The mission analysis included mission-specific requirements like launch windows selection for the constellation and reference attitude generation specific to inclined orbit geometry. Mission planning had to take care of Radial Rib Antenna (RRA) deployment requirements which were very critical for the mission, apart from taking care of individual subsystem requirements. The SAR payload data product quality and targeting accuracy are very sensitive to the satellite image point range (vis-a-vis SAR operation data window). Extensive post-launch calibration activity was carried out to meet all these mission requirements and data product specifications. The challenge was in fixing the payload beam alignment and fixing the uncertainties in onboard and ground computations. The paper also describes the methods of fixing all possible error sources affecting the high-resolution SAR payload performance. • The regional coverage satellite constellations are in demand for area targets coverage. • Inclined orbit constellations are more suitable for regional coverage using SAR sensors. • Mission operations plans need to consider all the specific requirements of spacecraft systems. • Pre-launch and post -launch calibrations of sensors is mandatory for achieving system performance. [ABSTRACT FROM AUTHOR]

In response to the significant challenge posed by the trade-off between the efficiency of separating potato soil and minimizing potato peel damage in the 4SW-170 potato excavator, this study focused on enhancing the design of the swing separation sieve. The objective was to develop a novel separation sieve comprising three distinct orders of sieve surfaces. Building upon this foundation, the EDEM-Adams coupled simulation method was employed to explore the fragmentation and separation attributes of potato–soil aggregates. This investigation aimed to elucidate the behavior of potato–soil aggregates within the operational scope of the novel swing separation sieve. Subsequently, the optimized parameters were validated through field tests. The findings indicate a direct correlation between the fracture ratio of the cohesive bond and the crank speed, illustrating an increase in the former with higher crank speeds. Conversely, an inverse relationship exists between the fracture ratio and the sieve inclination angle, demonstrating a decrease in the ratio as the sieve inclination increases. At a machine speed of 1.9 km/h, the fracture ratio of the cohesive bond attains its peak value. The force exerted on potatoes at their maximum point escalates with rising crank speed but diminishes with increasing machine speed. Conversely, the effect of sieve inclination on the peak force applied to the potatoes is deemed inconsequential. The most effective parameter configuration for the separation sieve comprises a crank speed of 180 revolutions per minute (r/min), a machine speed of 1.9 km per hour (km/h), and a sieve inclination of 14.4°. Field trials have confirmed that the parameter combination yielded a potato detection rate of 98.01% and a mere 0.68% rate of potato skin breakage, meeting the stipulated technical specifications of the potato harvester. [ABSTRACT FROM AUTHOR]

An engineering-to-order company has developed multi-spindle wheel nutrunner machines for automotive wheel mounting. The rotating shaft component that supports that machine has experienced compressive and twisting stress during operation, resulting in damage not only to the shaft but also some parts attached to the wheel. This study uses the house of quality (HOQ) and finite element method (FEM) approaches to redesign the rotary shaft to meet quality standards for its engineers, as customers, in a systematic way by using qualitative data from interviews, documents, and questionnaires provided by five rotary shaft engineering experts. Based on the importance levels of technical specifications obtained from the HOQ results, two rotary shaft redesign models for the redesigned models 1 and 2 obtain the maximum von Mises stress from the virtual testing using FEM analysis of 277.5 MPa and 111.8 MPa, respectively, which are below the company standard maximum yield strength of 470 MPa. Hence, using the company's minimum safety factor, the redesigned model 2 is chosen for the improved version of rotary shaft design. [ABSTRACT FROM AUTHOR]

The main raw materials in the ceramic wall tiles are clay, kaolin, calcite, and feldspar. The technical properties of the tiles (water absorption, total shrinkage, dry firing strength, fracture strength) and the desired physical properties (L, a, b, surface smoothness) vary depending on the raw material content in the recipe. Rheological parameters are crucial in the formulation development stages to avoid production problems and to ensure the final desired product parameters. Density, viscosity, and sieve analysis have therefore been included in the developed formulations. The use of raw materials from the region close to the production facility facilitates easy access to these materials. Thanks to this advantage, the use of domestic raw materials is becoming more widespread. In addition to the use of alternative raw materials, it contributes to the reduction of greenhouse gas emissions. The aim of this study, is to formulate a recipe for wall tiles using kaolins from the Kütahya region instead of clay from the Afyon region. Recipes containing 2%, 4%, 6%, and 8% of Kütahya region kaolin, with a corresponding reduction in clay from the Afyon region, were developed and sintered at 1130-1150°C with a 29-minute firing cycle. By analyzing the technical properties of the developed formulations, it was found that a maximum of 2% of Kütahya region kaolin could be used in the wall tile formulation. It was found that exceeding this percentage was not feasible due to the associated increase in water absorption, expansion of product size, and decrease in dry strength. [ABSTRACT FROM AUTHOR]