Search Results (45)

Background/Objectives: Introducing new transformative surgical technology involves navigating a complex process from design to implementation, often hindered by various barriers that delay the transition into clinical practice. This review critically examines the barriers, proposes a unified guide for medical device implementation in the Australian healthcare system utilising the validated Medtech Innovation Guide, and compares regulatory frameworks in Australia, the United Kingdom, and the United States of America. Methods: We conducted a literature review using MEDLINE and EMBASE with MeSH terms or emtree terms and keywords “new OR novel” AND “surgical device OR medical device OR health technology OR surgical technology OR surgical instrument OR transformative technology OR technological innovation OR technological change” AND “implementation OR adoption OR innovation adoption” AND “surgery OR surgical” AND “Australia”. We also assessed governmental websites (gov.au) and documents as well as the Royal Australasian College of Surgeons (RACS) website, policies, and position statements. Furthermore, Australian medical technology start-up companies were asked for any published roadmaps. Results: Four key stakeholder groups were identified: medical professionals, government, hospitals, and patients/consumers. Barriers include surgeon scepticism, regulatory hurdles (e.g., Australian Register of Therapeutic Goods), hospital clearance processes, and meeting patient expectations. To address these challenges, we propose a five-phase system: surgical device development (phase one), compliance with regulatory processes (phase two), research and experimentation (phase three), finalisation for product launch (phase four), and product launch and assessment (phase five). Conclusions: By following our five-phase guide, innovators may better navigate the complexities of integrating transformative surgical technologies into Australian healthcare. Although there are limitations, this approach is based on the validated Medtech Innovation Guide and may help both experienced and inexperienced practitioners better implement innovative technology; however, real-world validation is required. Full article

This study takes four parallel axial-flow pumps (three in operation + one on standby) as the research object. Using a 1D–3D coupling method, it explores the flow characteristics of axial-flow pumps under different startup strategies during multi-pump parallel operation. Through comparative analysis, the following conclusions are drawn: when all three pumps start simultaneously, the internal pressure exceeds the rated head by 23.43%, and the reverse flow reaches 10.57% of the rated flow. When starting the pumps sequentially with 5 s intervals, the pressure can be reduced to 11.41% above the rated head, but the reverse flow increases to 13.87%. Further extending the startup interval to 15 s results in only minimal improvements compared to 5 s intervals: the maximum internal pressure and maximum reverse flow decrease by just 0.97% and 0.05%, respectively. When valve coordination is added to the 5 s sequential startup strategy (pre-opening the valve to 60% before pump startup), the pressure exceeds the rated head by 10.49%, and the reverse flow exceeds the rated flow by 6.04%. In this scenario, the high-pressure areas and high-turbulence zones on the blade back surfaces are significantly reduced, achieving optimal flow stability. Therefore, the parallel system startup should adopt a coordinated strategy combining moderate time intervals with 60% valve pre-opening. This approach can both avoid excessive pressure impact and effectively control reverse flow phenomena, providing an important basis for optimizing the startup of multi-pump parallel systems. Full article

Dietary choices and patterns have enormous consequences along the lines of individual, community, and planetary health. Excess meat consumption has been linked to chronic disease risk, and at large scales, the underlying industries maintain a massive environmental footprint. For these reasons, public and planetary health experts are unified in emphasizing a whole or minimally processed plant-based diet. In response, the purveyors of ultra-processed foods have added “meat alternatives” to their ultra-processed commercial portfolios; multinational corporations have been joined by “start-ups” with new ultra-processed meat analogues. Here, in our Viewpoint, we revisit the 1990s food industry rhetoric and product innovation, a time in which multinational corporations pushed a great “low-fat transition.” We focus on the McLean Deluxe burger, a carrageenan-rich product introduced by the McDonald’s Corporation in 1991. Propelled by a marketing and media-driven fear of dietary fats, the lower-fat burger was presented with great fanfare. We reflect this history off the current “great protein transition,” a period once again rich in rhetoric, with similar displays of industry detachment from concerns about the health consequences of innovation. We scrutinize the safety of carrageenan and argue that the McLean burger should serve as a cautionary tale for planetary health and 21st century food innovation. Full article

Hydropower’s ability to start up and shut down quickly, combined with its flexible regulation characteristics, effectively alleviates frequency fluctuations caused by new energy sources, ensuring the safe and stable operation of the power system. However, during peak-frequency regulation tasks, the transition processes associated with the startup, shutdown, and load changes introduce frequent shocks to subsystems such as the hydro-turbine, governor, and diversion systems. These shocks pose significant challenges to the safe and stable operation of hydropower plants. Therefore, this study constructs a coupled hydraulic–mechanical–electrical model that incorporates the diversion system, hydro-turbine, governor, generator, and load, based on operational data from a real-world hydropower plant in China. The load increase transition process is selected for parameter sensitivity analysis to evaluate the influence of various structural, operational, and control parameters on unit stability and to identify key parameters affecting stability. The results indicate that the initial load exhibits the highest sensitivity to inversion power peak and rotational speed overshoot, with sensitivity values of 0.14 and 0.0038, respectively. The characteristic water head shows the greatest sensitivity to the inversion power peak time and rotational speed peak time, with values of 0.31 and 0.43, respectively. Additionally, the integration gain significantly influences the rotational speed rise time, with a sensitivity value of 0.30. These findings provide a theoretical basis for optimizing the parameter selection in hydropower plants. Full article

This study proposes an audit model to modernize artisanal manufacturing companies and facilitate their transition to Industry 4.0. Based on Lean Manufacturing, Lean Thinking, and Lean Management principles, the model enhances operational efficiency and competitiveness while considering the resource constraints of Small and Medium-Sized Enterprises (SMEs). It provides a structured approach to identifying key improvement areas and guiding digital transformation. The research follows a four-phase methodology: (1) a company assessment questionnaire to diagnose the current state, (2) a method matrix to analyze improvement strategies, (3) a dimension map to structure key transformation areas, and (4) prioritization of improvement dimensions to define a tailored action plan. A case study in an SME validated its applicability. Findings show that the model helps identify critical improvement factors and implement targeted Lean interventions, enhancing Industry 4.0 readiness. It enables a progressive adoption of digital enablers while optimizing traditional manufacturing processes. The originality of this study lies in its integrated auditing framework, structured around four dimensions and twelve key factors. It introduces a 48-question assessment tool, methods matrices, and prioritization mechanisms. Additionally, it defines four strategic development stages—Readiness, Start-up, In-transition, and Advanced—providing a roadmap for continuous improvement in SMEs. Full article

The article discusses the application of advanced data mining methods applicable to electricity consumption within a local power system in Poland. This analysis involves power demand. It is aimed at predicting daily demand variations. In such a case, system demand is characterized by high variability over a short period of time, e.g., 24 h. This constitutes a significant issue within a small power grid. It entails effective load programming on a given day and time. Therefore, the authors of the paper suggested employing artificial intelligence to forecast industrial power grid load for successive time intervals of the operation process. Such a solution applied within a power system enables appropriate start-up/shut-down planning, as well as generator operation at a specific capacity in power plants. It thus allows continuous power system (on-line) load demand balancing. Predicting power system load also involves determining moments, e.g., of power plant start-up, transition times to maximum or minimum output, or also the shut-down of such a process. This means ongoing and continuous (automatic) impact on electricity distribution. It significantly reduces carbon dioxide atmospheric emissions and allows zero-emission, e.g., wind, hydro, geothermal, or solar plants to meet current power needs. The issue associated with operating small ‘island’ power systems is a dynamic and rapid change in power demand. This is related to the area-based—‘island’—use’ of available power sources that can only be operated within a specific area. A very important problem occurring within these structurally small grids is the continuous forecasting of load changes and real-time response to power demand (i.e., balancing power demand through in-house or available power sources). Full article

In response to escalating environmental concerns and the imperative for a transition to a more sustainable economy, the European Union enacted a new regulation on the electric battery market in July 2023. This regulation integrates the principles of the circular economy, as outlined in the European Green Deal, addressing all phases of the battery life cycle, including the mining of raw materials, product design, production processes, reuse, and recycling. In light of this development, the principal manufacturers of electric vehicles (EVs) and hybrid electric vehicles (HEVs) have undertaken various circular economy (CE) and life cycle (LC) strategies. Their objective is to align their operations with these new regulatory requirements and enhance their sustainability credentials. The global automotive industry, encompassing thousands of entities with an annual turnover exceeding USD 3 trillion, is a significant economic sector. Within this industry, it is estimated that more than 50 manufacturers are involved in the production of EVs, ranging from established automakers to emerging startups. This study applies content analysis to obtain qualitative and quantitative information from data disclosed by companies and organizations, with a specific focus on entities that currently feature EVs or HEVs. The methodology involves examining publicly available reports and corporate disclosures to assess industry trends and regulatory compliance. For this purpose, the analysis selected the 10 largest EV manufacturers in the world, based on sales reports provided by the manufacturers themselves and their respective market shares, as reported by automotive news portals and blogs. The evaluation of their actions was derived from the annual sustainability reports of these companies, with the aim of identifying the practices already implemented and their anticipated contributions to extending battery life and minimizing environmental impact. Full article

The transformation of energy markets is at a crossroads in the search for how they must evolve to become ecologically friendly systems and meet the growing energy demand. Currently, methodologies based on bibliographic data analysis are supported by information and communication technologies and have become necessary. More sophisticated processes are being used in energy systems, including new digitalization models, particularly driven by artificial intelligence (AI) technology. In the present bibliographic review, 342 documents indexed in Scopus have been identified that promote synergies between AI and the energy transition (ET), considering a time range from 1990 to 2024. The analysis methodology includes an evaluation of keywords related to the areas of AI and ET. The analyses extend to a review by authorship, co-authorship, and areas of AI’s influence in energy system subareas. The integration of energy resources, including supply and demand, in which renewable energy sources play a leading role at the end-customer level, now conceived as both producer and consumer, is intensively studied. The results identified that AI has experienced notable growth in the last five years and will undoubtedly play a leading role in the future in achieving decarbonization goals. Among the applications that it will enable will be the design of new energy markets up to the execution and start-up of new power plants with energy control and optimization. This study aims to present a baseline that allows researchers, legislators, and government decision-makers to compare their benefits, ambitions, strategies, and novel applications for formulating AI policies in the energy field. The developments and scope of AI in the energy sector were explored in relation to the AI domain in parts of the energy supply chain. While these processes involve complex data analysis, AI techniques provide powerful solutions for designing and managing energy markets with high renewable energy penetration. This integration of AI with energy systems represents a fundamental shift in market design, enabling more efficient and sustainable energy transitions. Future lines of research could focus on energy demand forecasting, dynamic adjustments in energy distribution between different generation sources, energy storage, and usage optimization. Full article

The conversion of air currents through wind turbine technology stands as one of the most significant and effective means of generating green electricity. Wind turbines featuring a horizontal axis exhibit the greatest installed capacity. The study establishes a mathematical model for large wind turbines, categorized by megawatt output, utilizing measured data for key parameters, including wind speed, power output from the generator, and rotational speed. The analysis of the system’s behavior on startup—the cut-in wind speed, is conducted by transitioning the electric generator into motor mode. A mathematical model has been established for the dual-powered motor configuration, wherein both the stator and rotor are connected to a common frequency network, facilitating a shift to synchronous motor functionality. The equation that describes the kinetic moment highlights the importance of attaining optimal velocity, while simultaneously accounting for variations in the load angle. These fluctuations are observable in both the power output and the electrical currents. The simulations that have been processed are derived from experimental data, specifically inputs obtained from a 1.5 MW wind turbine located in the Oravita region of southwestern Romania. The paper thus outlines essential elements concerning the functionality of high-power wind turbines that utilize wound rotor induction generators, aiming to guarantee optimal performance from the moment the wind speed reaches the cut-in threshold. Full article

This paper presents the design and the performance of a wide tuning-range millimeter-wave (mm-wave) two-core class-C 60 GHz VCO in 40 nm CMOS process, which can be integrated into wireless communication transceivers and radar sensors. The proposed architecture consists of a two-core 30 GHz fundamental VCO, a gain-boosted frequency doubler and an adaptive bias configuration. The two-core fundamental VCO structure achieves frequency generation in the vicinity of 30 GHz, where each VCO core targets a different frequency band. The two bands have sufficient overlap to accommodate for corner variations providing a large continuous tuning range. The desired frequency band is selected by activating or deactivating the appropriate VCO core, resulting in a robust switchless structure. This approach enables a considerably broad tuning range without compromising phase noise performance. Furthermore, the proposed topology utilizes an adaptive bias mechanism for robust start-up. Initially, the selected VCO core begins oscillating in class-B mode, and subsequently it transitions into class-C operation to offer improved performance. From post-layout simulations, after frequency doubling, the low-band VCO covers frequencies from 50.25 to 60.40 GHz, while the high-band VCO core spans frequencies from 58.8 to 73 GHz, yielding an overall tuning range of 36.92%. Owing to the gain-boosting topology, output power exceeds −14.2 dBm across the whole bandwidth. Simulated phase noise remains better than −92.1 dBc/Hz at a 1 MHz offset for all bands. Additionally, the two VCO cores never operate simultaneously, aiding in power efficiency. Full article

This research systematically synthesizes findings from mainstream authoritative journals regarding intrapreneurial capability, and redefines the concept and dimensions of intrapreneurial capability from a process perspective, but also develops a theoretical framework for the operational mechanism of internal entrepreneurial capability, following the analytical approach of “resource support—generation process—operational results”. Empirical exploration is carried out by selecting typical cases. Findings indicate that intrapreneurial capability serves as the original driving force for achieving rapid growth in internal entrepreneurship. The generation of intrapreneurial capability undergoes a process of evolution from a single dimension to multiple dimensions, and the operational mechanism of intrapreneurial capability involves both main and auxiliary lines working in conjunction. This mechanism continuously promotes rapid iterative growth within enterprises. The contributions of this study are as follows: It redefines the concept of intrapreneurial capability from a process perspective, introducing three elements the concept encompasses—internal entrepreneurial context, comprehensive competence, and innovative output. Unlike previous academic considerations that focused on a single dimension of intrapreneurial capability, the multidimensional classification proposed in this study aids in comprehensively understanding the generation and innovation output processes of intrapreneurial capability. It also constructs a framework for the operational mechanism of intrapreneurial capability for the first time, which can comprehensively address the antecedents, outcomes, and interactions among different dimensions of internal entrepreneurial capability. Longitudinal case analysis provides reliable practical support for validating the conceptual connotations and operational mechanism framework proposed in this study. This study is beneficial for both domestic and international internal entrepreneurial enterprises, especially for startups to understand internal entrepreneurial capability from a holistic perspective, facilitating a swift transition from single-dimensional to multidimensional capability development and transformation, and providing a significant reference value for creating sustainable, internal, entrepreneurial performance. Full article

To date, deep-tech entrepreneurship and sustainable entrepreneurship are both attracting the interest of researchers. Indeed, deep-tech is being employed to address future sustainable challenges in the present. Nevertheless, the process of deep-tech startups is filled with distinct obstacles. These types of startups may necessitate a more targeted sustainable entrepreneurial process and specialised knowledge compared to conventional technological startups or general sustainable entrepreneurial processes. Currently, most publications discuss either a sustainable entrepreneurial process or conventional technical startups. Therefore, this article aims to investigate the process of sustainable entrepreneurs as they transition from startup ventures to scaleup enterprises within the context of the deep-tech industry. Based on previous sustainable entrepreneurial processes, a multiple case study was conducted within six deep-tech startups, using a narrative progress research strategy, to find the sustainable process pattern. A conceptual model of a sustainable entrepreneurial process in deep-tech industry is established, including five phases with six activities: (i) Sustainable idea definition; (ii) Sustainable opportunity recognition and evaluation; (iii) Venture launch; (iv.i) Sustainable products/services development; (iv.ii) New sustainable enterprise financing; and (v) Sustainable enterprise scaleup. This process enables sustainable deep-tech entrepreneurs, policymakers, and financial investors to necessarily have an overview of the key entrepreneurial stages to navigate from the startup to the scaleup process. Full article

This paper focuses on a vertical axial flow pump and employs a 1D-3D coupling method to investigate the effects of different gate pre-opening angles on the internal and external flow characteristics of the axial flow pump during startup. Through comparative analysis, the following conclusions are drawn: In the study, a fully open gate is defined as 1, while a fully closed gate is defined as 0. When starting the axial flow pump with different valve pre-opening degrees, backflow occurs within the first 20 s of startup, and the backflow rate inside the pump gradually increases with the increase in the valve pre-opening degree. At a valve pre-opening degree of 0.6, the maximum backflow rate inside the pump reaches 5.89% of the rated flow rate. When starting the pump with the valve fully open, the maximum backflow rate reaches 10.98% of the rated flow rate, and the efficiency is affected by the backflow rate. The valve pre-opening degree has little impact on the axial force acting on the impeller during startup. When starting with a valve pre-opening degree of 0.6, the internal pressure difference in the pump is minimized. Within the first 20 s of startup, the internal pressure difference in the impeller is 28.96% higher and the flow velocity is 14.62% higher with valve pre-opening degrees of 0.8 and 1.0 compared to a 0.6 degree opening. During the initial stage of pump startup, with valve pre-opening degrees of 0.8 and 1.0, the pressure fluctuation amplitude inside the pump is minimal, with maximum relative amplitudes of only 0.621 and 0.525, which are 41.00% and 28.51% lower than the maximum amplitudes at 0 and 0.2 degrees, respectively. In summary, the peak pressure inside the pump is minimized when the valve pre-opening degree is around 0.8, while the pressure difference and flow velocity are relatively lower at a pre-opening degree of 0.6. It is recommended to start the pump with a valve pre-opening degree of around 0.6 to 0.8. Full article

To investigate the hydraulic characteristics during the start-up process of a full-flow pumped storage unit under low-head conditions, numerical simulations were conducted to study the dynamic characteristics during the process, providing a detailed analysis of the dynamic behavior of the internal flow field during the transition period as well as the associated variation in external performance parameters. Study results revealed a vortex-shedding phenomenon during the initial phase of the start-up process. These vortices restrict the flow, initiating a water hammer effect that abruptly elevates the upstream pressure within the runner. As the high-pressure water hammer dissipated, the flow rate rapidly increased, leading to a secondary but relatively weaker water hammer effect, which caused a momentary drop in pressure. This series of events ultimately resulted in significant oscillations in the unit’s head. After the guide vanes stop opening, the vortex structures at the runner inlet and outlet gradually weaken. As the runner torque continues to decline, the unit gradually approaches a no-load condition and enters the S-shaped region. Concurrently, pressure pulsations intensify, and unstable vortex formations reemerge along the leading and trailing edges of the runner blades. The escalated flow velocity at the runner’s exit contributes to the elongation of the vortex band within the draft tube, ultimately configuring a double-layer vortex structure around the central region and the pipe walls. This configuration of vortices precipitates the no-load instability phenomenon experienced by the unit. Full article

The yielding transition, structural relaxation, and mechanical properties of metallic glasses subjected to repeated loading are examined using molecular dynamics simulations. We consider a poorly annealed Cu-Zr amorphous alloy periodically deformed in a wide range of strain amplitudes at room temperature. It is found that low-amplitude cyclic loading leads to a logarithmic decay of the potential energy, and lower energy states are attained when the strain amplitude approaches a critical point from below. Moreover, the potential energy after several thousand loading cycles is a linear function of the peak value of the stress overshoot during startup continuous shear deformation of the annealed sample. We show that the process of structural relaxation involves collective, irreversible rearrangements of groups of atoms whose spatial extent is most pronounced at the initial stage of loading and at higher strain amplitudes. At the critical amplitude, the glass becomes mechanically annealed for a number of transient cycles and then yields via the formation of a shear band. The yielding transition is clearly marked by abrupt changes in the potential energy, storage modulus, and fraction of atoms with large nonaffine displacements. Full article