Electrical Manufacturers Research Articles

Usefulness of a new anthropomorphic phantom simulating the chest and abdomen regions in PET tests.

To investigate the clinical utility of a new anthropomorphic phantom that reproduces the chest and abdomen better than the conventional National Electrical Manufacturers Association (NEMA) body phantom, count rates and image quality of PET images obtained from patients were evaluated. Anthropomorphic phantoms were used to include radioactivity in the lung, liver, kidney, and background regions. Two NEMA body phantoms were used for chest and abdominal assessments. The cross calibration factor (CCF) cylinder phantom was also used to reproduce the distribution of radioactivity outside the field of view, simulating the patient brain. Four types of phantoms were used in the PET imaging experiment, and for each phantom, the prompt coincidence count rates, random coincidence count rates, true + scatter coincidence count rates, and single photon count rates were measured. Then, these count rates were compared with count rates from actual clinical data. PET image quality assessment was done using the parameters, noise equivalent count patient (NECpatient), noise equivalent count density (NECdensity), and liver signal-to-noise ratio (SNR). Random coincidence count rates showed that the data obtained from each phantom were in good agreement with the clinical data. True + scatter coincidence count rates had better agreement with clinical data when measured for anthropomorphic phantoms than for the NEMA body phantoms. Furthermore, when the CCF Cylinder phantom simulating the brain was placed outside the imaging field of view, the results were closer to the clinical data. PET image quality was 1.4% higher for NECpatient obtained from anthropomorphic phantoms compared to the mean obtained from clinical data. NECdensity was 15.0% lower than the mean value obtained from clinical data. Liver SNR was 14.8% higher in PET images reconstructed using the 3D-ordered subsets expectation maximization (OSEM) method. It was 10.0% lower in PET images reconstructed with the image reconstruction method Q.Clear (GE Healthcare) using the Bayesian penalized likelihood (BPL) method. The new anthropomorphic phantom was more consistent with the count rates obtained from clinical data than the conventional NEMA body phantoms were and it was able to better simulate the distribution of radioactivity concentrations in the patients by reproducing the distribution of radioactivity concentrations outside the field of view.

Electric Vehicle Traction Battery Recycling Decision-Making Considering Blockchain Technology in the Context of Capacitance Level Differential Demand

In recent years, the rapid growth in electric vehicle ownership has resulted in a significant number of decommissioned traction batteries that will require recycling in the future. As consumer expectations for electric vehicle range continue to rise, the turnover of traction batteries has accelerated substantially. Consequently, there is an urgent need for electric vehicle manufacturers to establish an efficient, recyclable supply chain for the return of end-of-life (EOL) electric vehicle (EV) traction batteries. In this paper, we investigate the closed-loop recycling supply chain for retired power batteries in electric vehicle manufacturers, taking into account blockchain technology and the high range preferences in the electric vehicle market, which are influenced by varying demand for different levels of electric vehicle capacitance. Blockchain, as a distributed and decentralized technology, offers features such as consensus mechanisms, traceability, and security, which have been effectively applied across various fields. In this study, we construct four models involving EV battery manufacturers, EV retailers, and battery comprehensive utilization (BCU) enterprises participating in the recycling process. Through the analysis of a Stackelberg response model, we find that (1) single-channel recycling is less efficient than dual-channel recycling models, a difference driven by the diversity of recycling channels and the variability in recycling markets; (2) Recycling models incorporating blockchain technology demonstrate superior performance compared to those that do not utilize blockchain technology, particularly when the intensity of recycling competition is below 0.76; (3) Traction batteries integrated with blockchain technology exhibit higher recycling rates when the optimization index is below 0.96. Electric vehicle battery manufacturers must evaluate the benefits and costs of adopting blockchain technology; (4) With lower recycling incentive levels and EV range preferences, the single-channel recycling model yields better returns than the other three recycling models. EV manufacturers can enhance overall battery supply chain revenues by establishing varying incentive levels based on market demand for different capacitance levels.

Evaluation of the SwiftScan mode in bone single-photon emission computed tomography (SPECT) imaging: effect on imaging quality and a semi-quantitative analysis.

99mTc-stannous methylene diphosphonate (99mTc-MDP) bone single-photon emission computed tomography/computed tomography (SPECT/CT) imaging plays a crucial role in various clinical applications. Many strategies have been developed to reduce the injection activity and procedure time, improve the patient experience and reduce their anxiety prior to and during SPECT imaging. This study aimed to evaluate the SwiftScan mode and its effect on image quality, and diagnostic performance of malignant skeletal lesions in bone SPECT image. 99mTc-MDP SPECT/CT scans were acquired from the National Electrical Manufacturers Association (NEMA) phantom with a sphere-to-background ratio of 10:1, and 69 patients were enrolled in this retrospective study. The patients who showed abnormal uptake of focal 99mTc-MDP on whole-body bone planar scans, underwent local SPECT/CT scans. The image comparison and analysis were performed in three acquisition modes: SwiftScan; SwiftScan-50% (the SwiftScan mode with a 50% reduction in acquisition time); and step-and-shoot (SS). The image mean count, coefficient of variation (COV), radioactive concentration, and signal-to-background ratio (SBR) were measured for each phantom image. Visual assessment (using a 5-point Likert scale), semi-quantitative analysis [to determine the COV, mean of the standard uptake value (SUVmean), maximum of the standard uptake value (SUVmax), and SBR], and receiver operating characteristics (ROC) curve analysis were performed for clinical assessment. The SwiftScan mode obtained better quality images than the SwiftScan-50% and SS modes, and it also had better sphere clarity and lower background COVs (P<0.05). The mean counts of the SwiftScan, and the corresponding radioactive concentration and SBR were significantly higher than those of the SwiftScan-50% and SS (P<0.05), except in relation to the 13-10 mm spheres. A total of 101 abnormal 99mTc-MDP uptake skeletal lesions were included in the clinical study. The SwiftScan had significantly higher visual scores than both the SwiftScan-50% and SS (P<0.001). Additionally, there were significantly higher visual scores in the SwiftScan-50% than SS (P<0.05). The SwiftScan also had a lower COV, indicating reduced image noise. The SUVmax, SUVmean, and SBR for the skeletal lesions were significantly higher in the SwiftScan than the other two modes (P<0.05). The optimal diagnostic cut-off values of the SUVmax for identifying malignant skeletal lesions in the SwiftScan, SwiftScan-50%, and SS were 17.95, 14.75, and 9.94, respectively, but there was no significant difference among the three modes in terms of their differential diagnostic performance (all P>0.05). The SwiftScan showed significant improvements in image quality and the semi-quantitative analysis of bone SPECT imaging. It reduced the scanning time by 50% without compromising the image quality or diagnostic performance. These findings provide valuable insights that may inform the clinical application of the SwiftScan, enhancing qualitative and quantitative diagnosis in bone SPECT imaging.

Lightweight metals and alloys in electric vehicle manufacturing: enhancing performance and efficiency

Lightweight materials have become a key focus in the manufacturing of electric vehicles (EVs) due to their numerous advantages, including corrosion resistance, excellent formability, and high specific strength. In addition to enhancing performance, these materials contribute to a reduced environmental impact, as they are highly recyclable. This article offers a comprehensive overview of the properties, fabrication methods, and applications of lightweight metals and their alloys in the automotive industry. It also provides a comparative analysis of various lightweight materials, highlighting their relative benefits and limitations. By consolidating scientific knowledge and industry insights, this review aims to guide both the automotive industry and the scientific community in advancing the use of lightweight alloys in EVs, contributing to the development of more sustainable and efficient vehicles.

Electric Vehicle Battery Supply Strategy Considering Brand Spillover Effect

Electric vehicle manufacturers ensure power battery supply through either direct sourcing or technology cooperation. This paper examines the battery supply strategy of an entrant manufacturer(m2), in a two-tier supply chain that includes a battery supplier (s), an incumbent manufacturer (m1), and the aforementioned entrant. It investigates these strategies under the influence of the brand spillover effect. It reveals that when m1 opts for direct battery procurement, if m2 boasts higher after-sales service standards, adopting a technology cooperation strategy becomes more advantageous. A sweet spot exists wherein, given m2's brand power and after-sales service level fall within a certain range, all supply chain participants can achieve mutual benefits. In scenarios where m1 depends on technology cooperation for its battery supply, it is advisable for m2 to mirror this approach by also engaging in technology cooperation.

Analisis Hubungan Citra Merk dan Kualitas Produk Terhadap Kepuasan Konsumen Pengguna Kendaraan Listrik di Indonesia

This study aims to analyze the influence of brand image and product quality on customer satisfaction in the electric vehicle industry in Indonesia. A strong brand image and high-quality products are critical factors for electric vehicle manufacturers to build consumer trust and increase sales. In the context of the growth of electric vehicles as an environmentally friendly alternative, this research is grounded in the concepts of customer satisfaction, brand image, and product quality. The study employs a quantitative approach, utilizing a survey involving 154 respondents who are users of two- and four-wheeled electric vehicles. The collected data were analyzed using multiple linear regression to examine the partial and simultaneous effects of the two independent variables on the dependent variable. The results show that brand image and product quality have a significant positive influence, both partially and simultaneously, on customer satisfaction. These findings contribute theoretically to the marketing literature by reinforcing the role of brand image and product quality in enhancing customer satisfaction. Furthermore, the results can be useful for the electric vehicle industry in Indonesia in efforts to improve customer satisfaction through the optimization of brand image and the quality of products offered.

Comparative Assessment of Agreement in Uniformity Analyses across Quality Control Software Platforms

Abstract Objective In nuclear medicine, quality control (QC) activities adhere to international standards, yet their complexity can pose challenges. Gamma camera manufacturers have introduced integrated QC software, offering instantaneous results. However, the agreement of these automated processes with established protocols remains uncertain. This study aims to clarify this uncertainty by comparatively analyzing uniformity from various software solutions for a dual-head gamma camera. Methods The study utilized integrated QC analysis software and three free QC analysis tools (IAEA-NMQC Toolkit, NM Toolkit, and Fiji) for uniformity analyses. Following the National Electrical Manufacturers Association standards, NEMA Standards Publication NU 1-2018, the intrinsic uniformity test was performed on a GE Discovery NM/CT 670 Pro system. Ten uniformity QC images underwent analysis with both integrated QC software and alternative software. Data agreements were tested using the Blant–Altman regression-based analysis. Results Significant differences were observed in integral and differential uniformities (p &lt; 0.001). The central field of view (useful field of view) integral uniformity mean differences for NMQC Toolkit, NM Toolkit, and Fiji were 2.46% (2.34%), 2.44% (2.31%), and 2.56% (2.64%), respectively. Conversely, x-differential and y-differential uniformity mean differences were consistently under 2%. Regression-based analysis confirmed good agreement between computed values. Conclusion The integrated QC software of Discovery NM/CT 670 Pro provides reliable uniformity analysis, aligned with the NEMA standards. Variations in computed values may stem from differences in pixel values and applied data corrections.

Elucidation of FDG-PET Imaging Characteristics that Reflect the Heterogeneity within Tumors Due to Variability in Metabolic Activity: A Phantom Study

Abstract Objective Focusing on the heterogeneity within cancer lesions and revealing cancer lesions with a high signal-to-noise ratio will help improve the quality of positron emission tomography (PET) images. This study aimed to understand how glucose metabolic activity can be shown with less statistical noise using a quality assessment phantom modeled after cancer lesions with a two-layer structure and a Clear adaptive Low-noise Method (CaLM) filter. Materials and Methods A National Electrical Manufacturers Association phantom with two spheres with a two-layer structure filled with 2-deoxy-2[18F]fluoro-D-glucose (inner and outer diameters of the spheres were 13/22 and 22/37 mm, respectively; radioactivity ratio of the background [BG] to outer sphere layer was 1:4; and BG-to-inner sphere layer ratios were 1:1, 1:2, and 1:3) was evaluated. The acquisition time was set at 120 seconds, and imaging was repeated five times. The image data in photomultiplier tube (PMT)-PET were reconstructed using a time-of-flight (TOF) ordered subset expectation maximization (OSEM) algorithm (point spread function [PSF] − , iteration: 3, subset: 10) with a 4-mm Gaussian filter (GF) for normal images. Silicon photomultiplier (SiPM)-PET data were reconstructed using a TOF OSEM algorithm (PSF − , iteration: 2, subset: 12) and a 3-mm GF for normal images. The target images were reconstructed using three CaLM parameters (mild, standard, and strong). All the obtained images were investigated quantitatively, with calculation of maximum standard uptake value (SUVmax), coefficient of variation (CV), and contrast-to-noise ratio (CNR), after setting regions of interest on the lesions. Statistical analysis using the Dunnett's test compared normal images (control group) and target images (treatment group). Statistical significance was considered at p &lt; 0.05. Results Quantitative assessment revealed that the SUVmax of target images (standard and strong) was equivalent to that of normal images in PMT-PET, with SUVmax of 3 to 3.5 for both layers. The SUVmax in SiPM-PET was similar across all CaLM types, ranging from 3 to 4 for all spheres. The target images (standard and strong) had a significantly reduced CV and improved CNR compared with normal images. Conclusion The boundary of the 22/37-mm spheres was visible with CaLM (strong) at radioactivity ratios of 1:4:1 and 1:4:2 on both scanners. For the 13/22-mm sphere boundary, visibility with CaLM (strong) was observed only with SiPM-PET, with the SUVmax equivalent to normal images. CaLM (strong) was deemed the optimal postprocessing filter for PMT-PET due to significant improvements in CV and CNR, while CaLM (standard) was suggested as the optimal filter for SiPM-PET due to excessive BG smoothing.

Coupled Electro-Thermal-Aging Battery Pack Modeling—Part 1: Cell Level

This paper presents a modeling approach to capture the coupled effects of electrical–thermal aging in Li-ion batteries at the cell level. The proposed semi-empirical method allows for a relatively high accuracy and low computational cost compared to expensive computer simulations. This is something current models often lack but is essential for system level simulations, relevant for electric vehicle manufacturers. The aging analysis includes both cycling and calendar effects across the lifetime of the cell and reversible and irreversible heat in a lumped-mass model to capture the temperature evolution of the cell in operation. The Thévenin equivalent circuit model with capacitance used to simulate the electrical behavior of the cell was experimentally validated, showing a high correlation with the proposed model during the charging and discharging phases. A maximum error of 3% on the voltage reading was identified during discharge with the complete model. This model was also designed to be used as a stepping stone for a comprehensive model at the module and vehicle levels that can later be used by designers.

Toward the Construction of a Sustainable Society: Assessing the Temporal Variations and Two-Dimensional Decoupling of Carbon Dioxide Emissions in Anhui Province, China

This study comprehensively assessed carbon dioxide emissions over a span of two decades, from 2000 to 2020, with the decomposition and decoupling analyses considering multiple influence factors across both short-term and long-term dimensions. The results revealed great fluctuations in the decoupling analysis index (DAI) for subjected sectors such as natural resource processing, electricity, gas, water, textiles, machinery, and electronics manufacturing. Of note, significantly changed sectoral DAIs were observed in urban traffic and transportation, logistics warehousing, and the postal industry within Anhui Province. In contrast, the DAIs of other sectors and social services exhibited a weak decoupling state in Anhui Province. The industrial sectors responsible for mining and textiles and the energy structure encompassing electricity, gas, and water emerged as the primary contributors to carbon dioxide emissions. Additionally, the efficiency of the socio-economic development (EDE) was identified as the principal driver of carbon dioxide emissions during the observed period, while the energy consumption intensity (ECI) served as the putative crucial inhibiting factor. The two-dimensional decoupling of carbon dioxide emissions attributable to the EDE demonstrated a gradual transition from industrial sectors to buildings and tertiary industries from 2000 to 2020. In the future, the interaction between urban carbon dioxide emissions and the socio-economic landscape should be optimized to foster integrated social sustainable development in Anhui Province.

Developing electric vehicles in China and the United States: Revisiting debates on industrial strategy

AbstractMotivationStrategies to develop manufacturing industry are the subject of lively debate over whether to follow or defy national comparative advantage. Electric vehicles (EVs), a major change for automobile manufacturers, are no exception.Despite the US government's promotion of global integration to activate the semi‐invisible hand of market forces, neither traditional Detroit automakers nor new firms, even with government grants or loans, were able to launch EVs on the world market promptly, with the notable exception of Tesla. In China, the government helped dozens of domestic electric vehicle manufacturers enter the market through formidable government subsidies. However, none of China's manufacturers, other than Wuling, were able to surpass Tesla in sales in China.The rapid growth of Tesla and Wuling without relying heavily on government protection and subsidies raises the question of whether their success can be attributed to other forms of state intervention.PurposeWhat policies and strategies enable manufacturers to develop and market a new technology, such as EVs? What can we learn by comparing the experiences of US and Chinese vehicle manufacturers?We consider these questions and what the implications are for debates about industrial development strategy.Methods and approachWe compare four carmaking firms—GM, Tesla, BYD, and Wuling—their business strategies and their interactions with the US and Chinese states. We draw on company reports, government documents, and press reports.FindingsBoth China and the US employed semi‐developmentalist, semi‐neoliberal policies to promote the manufacture of EVs. The US subsidized research and development in its automobile industry and provided incentives to consumers. It has subsequently moved to lending to the most promising firms for EV production. China, in contrast, has selectively subsidized EV firms all the way from development to marketing.Subsidies from the US government have been steady: they are expected to stay this way in the near term. However, the fastest‐growing carmakers have used outward foreign direct investment to gain competitive advantage. China's subsidies, on the other hand, have been unstable: linked to the performance of the target firms. The higher the firm's profit, the lower the subsidies and vice versa. China has been careful with subsidies to prevent rent seeking and moral hazard.Neither following nor defying comparative advantage explains the strategies followed by the four firms: comparative advantage considerations have been tempered by the possibilities of foreign investment.Policy implicationsThe results imply that traditional developmental strategies have resorted to inward foreign direct investment in high‐income countries as a means to learn technologies and outward foreign direct investment in low‐ and medium‐income countries as a way to reduce production costs, but have missed the comparative advantage of outward and inward foreign direct investment, and strategic mixes of these, when developing and diffusing radical innovation like EVs.

Performance Characteristics of a New Generation 148-cm Axial Field-of-View uMI Panorama GS PET/CT System with Extended NEMA NU 2-2018 and EARL Standards.

The uMI Panorama GS PET/CT system is a new long-axial-field-of-view scanner featuring high sensitivity, time-of-flight (TOF) resolution, spatial resolution, and count rate performance. The aim of this study is to assess the PET system on the basis of the National Electrical Manufacturers Association (NEMA) NU 2-2018 and European Association of Nuclear Medicine Research Limited (EARL) standards. Methods: Spatial resolution, count rate performance, sensitivity, accuracy, image quality, TOF resolution, and coregistration accuracy were evaluated following the NEMA NU 2-2018 standard. Additional experiments included energy resolution, 200-cm-long line sources for sensitivity, a 175-cm-long scatter phantom for count rate and TOF resolution, as well as the compliance with the EARL guideline. Moreover, an 18F-FDG PET patient study was reconstructed with various frame durations. Results: The PET system achieved sub-3-mm transaxial and axial spatial resolutions at a 1-cm radial offset. The sensitivities with the 70-cm-long and 200-cm-long line sources were observed to be 176.3 and 90.8 kcps/MBq, respectively, at the center of the field of view. The noise-equivalent count rates (NECRs) of the 70-cm-long and 175-cm-long scatter phantoms were measured to be 3.35 Mcps at 57.57 kBq/mL and 2.24 Mcps at 33.27 kBq/mL, respectively. The TOF resolutions for both phantoms were approximately 189 ps at 5.3 kBq/mL and lower than 200 ps below the NECR peaks. The absolute count rate errors of all 34 acquisitions were less than 3% below the NECR peak for the 70-cm-long scatter phantom. With the standard NEMA image quality phantom experiment, the contrast recovery coefficient varied from 68.17% to 94.20% and the background variabilities were all below 2%. The maximum PET/CT coregistration error was 1.33 mm. Regarding EARL compliance, the gaussian filter of 5-mm full width at half maximum could produce acceptable images. The patient data demonstrate visually satisfactory image quality with short frames (less than 1 min). Conclusion: The uMI Panorama GS exhibits spatial resolution and TOF resolution similar to those of the uMI Panorama system (35-cm axial field of view), despite the extended axial field of view. The 148-cm axial coverage, sub-200-ps TOF resolution, high sensitivity, and count rate performances are expected to yield superior image quality and offer new opportunities for various clinical applications.

Integrated problem of car sequencing and vehicle routing on an automotive mixed-model assembly line

We address an integrated problem of car sequencing on an automotive mixed-model assembly line and multi-trip vehicle routing for external sync-part supply. The sync-parts, usually characterized by large size and highly customized, are directly delivered from suppliers to the assembly line without intermediate inventory. The goal is to find a joint schedule of car sequencing and vehicle routing so as to minimize the overall makespan. To tackle this intricate problem, we develop a mixed-integer linear programming model by employing the constraint linearization technique. A new meta-heuristic named MS-ALNS-VND is proposed combining multiple start strategy, adaptive large neighborhood search (ALNS) and variable neighborhood descent (VND). Numerical experimental results show that MS-ALNS-VND can solve small-sized instances to optimality in much less running time compared to Gurobi. For medium- and large-sized instances, MS-ALNS-VND outperforms ALNS and VND in both best or average objective values. A case study from an electric automobile manufacturer in China demonstrates the applicability and efficiency of our algorithm.

Perbaikan Nilai Overall Equipment Effectiveness dengan Metode Total Productive Maintenance pada PT. Electric Vehicle Trimotorindo

This research was conducted to increase the Overall Equipment Effectiveness (OEE) value at PT Electric Vehicle Trimotorindo, which is an electric vehicle manufacturing company. The main problem faced by the company is the decline in OEE value every month due to lack of machine maintenance and deterioration in production quality. The method used in this study is Total Productive Maintenance (TPM), which involves identifying the factors that cause production losses through the analysis of Six Big Losses. The results show that the OEE value has increased from 78.61% to 80.36% after improvements through TPM, especially in increasing the quality rate from 88.48% to 92.23%. The conclusion of this study is that the application of TPM can improve the effectiveness of machine use and production quality, which ultimately contributes to the improvement of the company's productivity.

An Introduction to Lagrange Multipliers: Theory and Applications in Economics

The purpose of this paper is to explore the basic applications of the Lagrange multiplier method in economics and to help beginners build their understanding of this mathematical tool. Tesla Inc. is used as a case study to examine how it maximizes profits by optimizing pricing and marketing expenses under given market conditions and constraints. The context of the study includes the importance of maintaining Tesla’s leadership position as the world’s leading electric car manufacturer in a competitive market. In this paper, the Lagrange multiplier method is used to incorporate specific market share and marketing expense constraints into the profit function and to find the extreme values by constructing the Lagrange function and solving for the derivatives. However, the results of the study show that the solutions obtained are extreme minima rather than the expected maxima. This result highlights the possible limitations of the Lagrange multiplier method in economic optimization problems. Nonetheless, this paper provides valuable lessons for understanding and applying the Lagrange multiplier method and points the way for further research on the application of optimization methods in economic decision making.

A self-organizing map clustering adaptive artificial neural network model for analysis critical success factors in different phases of MTO projects case study: electrical equipment manufacturer and supplier in Iran

PurposeThe purpose of this paper is to investigate the benefit of critical success factors (CSFs) clustering in different phases of make-to-order (MTO) projects and develop standards for management.Design/methodology/approachThis study is based on a questionnaire survey. First of all, collecting data by structured interviews, relying on a questionnaire and second from leader contractors who are active in the engineering and steel industry (in Iran). So, the requirements and objective of the research are presented to the top management of MTO projects to gain their support in data collection. Then 20 CSFs were identified by the literature review so a questionnaire survey was prepared for the CSFs assessment and interview with the experts. Finally analyzing the importance and performance of CSFs in project phases and cluster them in different project phases with self-organizing map as one of the artificial neural network (ANN) approaches due to high predictive accuracy. Review the research result with the top management of MTO project and examine the results obtained from neural networks and validation indices.FindingsCluster analysis shows that the implementation phase is the most important stage in MTO organizations and the other phases like feasibility and start-up, design and planning, delivery and end-phase should be also considered as effective phases in determining the level of organization performance. Different industries with additional data at different periodic times will verify the result. Furthermore, testing the other ANN model will improve risk analysis and could shift this classification approach to a regression type.Research limitations/implicationsThe main limitation of the research is related to the sample. Research findings are limited to the time of data collection so validity is limited to the mentioned time. Different industries with additional data will verify the result. Furthermore, testing different ANN models such as K-MEANS, non-negative matrix factorization (NMF) analyses will improve risk analysis and could meet different classification results to find gaps.Practical implicationsIn this paper, CSF and project phase dimensions are viewed together which is necessary to meet better results for simplifying social and economic benefits. Merge the new findings and latest technologies could prepare the best results and enable managers to create a better framework or implement key factors for minimizing waste.Originality/valueThis paper moves the definition of MTO organizations beyond measuring cost, complexity and financial variables by clustering CSFs in different phases of projects. So, the results enable managers to use this concept in their daily production to minimize waste and could be implemented to efficiently choose factors.

Performance evaluation of a small-animal PET scanner with 213 mm axis using NEMA NU 4-2008.

Long-axis positron emission tomography (PET) has emerged as one of the recent research directions in PET due to its ability to significantly enhance sensitivity and counting performance for low-dose imaging, rapid imaging, and whole-body dynamicimaging. The PET system presented in this study is a long-axis animal PET based on lutetium-yttrium orthosilicate and silicon photomultiplier, designed for whole-body imaging in rats. It features a diameter of 143 mm and an axial length of 213.3 mm. This study evaluated the performance of this PET system in accordance with the National Electrical Manufacturers Association (NEMA) NU 4-2008standards. The performance evaluation was conducted according to the NEMA NU 4-2008 standards in terms of spatial resolution, sensitivity, counting rate performance, scatter fraction (SF) and image quality. In addition, a rat imaging study was conducted to assess the imaging capability of this PETsystem. The average energy resolution of the PET system was 12.87%, the average coincidence timing resolution was 751 ps. The FWHM of spatial resolution reconstructed by filtered back projection and 3D-OSEM-PSF algorithm at 5 mm radial offset from the axial center were 1.65 and 0.88 mm. The peak absolute sensitivity measured by a point source at the center of the field of view was evaluated as 6.71% (361-661keV) and 10.31% (250-750 keV). For the mouse-like phantom, the SF was 11.0% and the peak noise equivalent counting rate (NECR) was 1193 kcps at 94.2 MBq (2.54 mCi). For the rat-like phantom, the SF was 26.8% and the NECR was 682.5 kcps at 78.6 MBq (2.12 mCi). The performance measurement results demonstrate that this PET system exhibits high sensitivity and count rate performance, making it potential for high-quality whole-body dynamic imaging ofrats.

Sharing channel choices for electric vehicle battery manufacturers when considering range anxiety among heterogeneous consumers

PurposeThis study aims to investigate the optimal pricing decisions and shared channel strategy selection of battery manufacturers considering heterogeneous consumers' range anxiety.Design/methodology/approachAmidst the rapid growth of the electric vehicle sector, countries are promoting upgrades in the automotive industry. However, insufficient driving range causes consumer range anxiety. The study utilizes the Stackelberg game model to assess how range anxiety influences battery manufacturers' pricing and channel strategy decisions across three strategies.FindingsWe find that electric vehicle battery manufacturers' decisions to cooperate with third-party sharing platforms (TPSPs) are primarily influenced by fixed costs and consumer range anxiety levels. As range anxiety increases, the cost threshold for joining shared channels rises, reducing cooperation likelihood. However, considering diverse consumer needs, especially a higher proportion of leisure-oriented consumers, increases the likelihood of cooperation. Furthermore, higher battery quality makes direct participation in shared channels more probable.Originality/valueIn the electric vehicle industry, range anxiety is a significant concern. While existing literature focuses on its impact on consumer behavior and charging infrastructure, this study delves into battery manufacturers' strategic responses, offering insights into channel options and pricing strategies amidst diverse consumer segments.

How Does Innovation-Collaboration Network Structure Influence Regional Economic Resilience?

This paper examines whether different structures of co-patenting networks affect regional economic adaptation and adaptability in divergent ways. Adaptation differentiates from adaptability by recovering in a pre-shock growth path, while adaptability entails forging a new growth path. Focusing on computer, electronic, and electrical equipment manufacturing industries in U.S. metropolitan and micropolitan areas from 1990 to 2012, the study reveals that complete networks, characterized by closely connected nodes, promote adaptation but weaken adaptability. In contrast, coalitional networks, featuring loosely connected subgroups, enhance adaptability but hurt adaptation. The study contributes to regional economic resilience literature by empirically demonstrating the trade-off relationship between adaptation and adaptability from network structures’ perspective. Practically, the study helps policy makers to effectively allocate stimuli, such as grants and tax incentives, to develop targeted co-patenting networks to improve adaptation or adaptability.

El auge del coche eléctrico en China y su impacto en la Unión Europea

Rationale China’s electric vehicle sector has recently aroused considerable interest thanks to its rapid growth and current dominance of the global market. Given the importance of the automotive sector in Spain and the European Union (EU), and the recent introduction of tariffs, it is worth exploring the factors behind this rise. Takeaways •Battery electric vehicle (BEV) market penetration in the EU has grown notably in recent years: in 2023 BEVs accounted for 15% of all vehicles sold (5.4% in Spain), a figure well above the 1.9% recorded in 2019 (0.7% in Spain). •China has secured its status as the world’s leading electric vehicle manufacturer and exporter, its output proving particularly popular in the European market. As a consequence, the market share of BEVs made in China rose from 0.4% of new BEV registrations in 2019 to 20% in 2023. •The success of Chinese BEV exports rests on lower manufacturing costs, thanks largely to China’s control over the supply chain, government support policies at various stages of production and the country’s early embrace of electric vehicles.