Heterogeneous Technologies Research Articles

Terahertz integration platforms using substrateless all-silicon microstructures

The absence of a suitable standard device platform for terahertz waves is currently a major roadblock that is inhibiting the widespread adoption and exploitation of terahertz technology. As a consequence, terahertz-range devices and systems are generally an ad hoc combination of several different heterogeneous technologies and fields of study, which serves perfectly well for a once-off experimental demonstration or proof-of-concept, but is not readily adapted to real-world use case scenarios. In contrast, establishing a common platform would allow us to consolidate our design efforts, define a well-defined scope of specialization for “terahertz engineering,” and to finally move beyond the disconnected efforts that have characterized the past decades. This tutorial will present arguments that nominate substrateless all-silicon microstructures as the most promising candidate due to the low loss of high-resistivity float-zone intrinsic silicon, the compactness of high-contrast dielectric waveguides, the designability of lattice structures, such as effective medium and photonic crystal, physical rigidity, ease and low cost of manufacture using deep-reactive ion etching, and the versatility of the many diverse functional devices and systems that may be integrated. We will present an overview of the historical development of the various constituents of this technology, compare and contrast different approaches in detail, and briefly describe relevant aspects of electromagnetic theory, which we hope will be of assistance.

Role of China's agricultural water policy reforms and production technology heterogeneity on agriculture water usage efficiency and total factor productivity change

Role of China's agricultural water policy reforms and production technology heterogeneity on agriculture water usage efficiency and total factor productivity change

Sports resources utilization efficiency, productivity change, and regional production technology heterogeneity in Chinese Provinces: DEA-SBM and Malmquist Index Approaches.

The efficient allocation of sports resources for optimal outcomes remains a pressing national endeavour in China. Over the past two decades, substantial investments by provincial and national governments have been directed toward sports infrastructure development. This initiative aims to foster sports talent, facilitate excellence, host major sporting events, and enhance national pride and soft power. This study employs a comprehensive methodology encompassing Data Envelopment Analysis-Slack Based Measure (DEA-SBM), Meta Frontier Analysis, and Malmquist Productivity Index to assess Sports Resource Utilization Efficiency (SRUE), Technological Gap Ratio (TGR), and Productivity Growth (MI) across China's 31 provinces and 3 distinct regions for the period 2010-2021. The findings indicate that China's average SRUE stands at 0.6307, revealing an inefficiency of 36.93% in sports resource utilization. Noteworthy efficiency was observed in Beijing, Chongqing, Henan, Shaanxi, Shanghai, and Tianjin during the study duration. Furthermore, a consistent upward trajectory in SRUE from 2010 to 2021 highlights gradual and sustained progress. Comparatively, the eastern region showcases higher technological advancement (average TGR of 0.7598) than the central and western regions. The Malmquist Productivity Index (MI), with an average value of 1.05391, highlights a substantial 5.39% productivity growth. Notably, technological advancement emerges as the primary driver of this productivity increase, evident through the higher Total Factor Productivity Change (TC) of 1.0312 compared to the Efficiency Change (EC) of 1.0209. The Central region's outperforming productivity growth is noteworthy relative to the Eastern and Western regions. Conclusively, the Kruskal-Wallis test confirms significant disparities in the average MI, EC, TC, and TGR among all three regions of China.

Diversified or specialised: firms’ patent portfolio strategies under heterogeneous technology standards

ABSTRACT Research has highlighted the role of patent portfolio strategy on firms’ innovation without elaborating on how to layout the diversity of patent portfolios to improve innovation quality. Drawing on the resource-based view and institutional theory, this research attempts to extend patent portfolio–innovation debate by examining the moderating effects of policy or specifically, technology standard on the patenting–innovation relationship. We argue that the leverage of technology standard could help firms optimise patent portfolios by accessing information, reducing transaction costs, and promoting complementary innovation, and therefore leads to higher innovation quality. Moreover, considering heterogeneous technology standards, in the context of relatively complex and rapidly updated technology standards, specialised patent portfolios are more significant for firms to enhance substantive innovation. Our analysis of data from 729 Chinese manufacturing listed companies provides supports for both the moderating role of technology standard on the patent portfolio–innovation relationship. This paper contributes to patent management literature by elaborating upon the mechanisms of how technology standard can be leveraged to capture value from firms’ patent portfolios.

Blessing or curse: How does sustainable development policy affect total factor productivity of energy-intensive enterprises?

The achievement of sustainable development in energy-intensive sectors is crucial for promoting long-term economic growth and stability. Utilizing the National Sustainable Development Plan for Resource-based Cities (2013–2020) (SDP) in China as a quasi-experiment, we examine the effect of sustainable development policy on the productivity performance of energy-intensive firms. Our analysis of data from Chinese listed companies between 2006 and 2020 reveals that the SDP significantly enhances the productivity performance of treated firms. Our investigation into the pathways towards sustainability reveals that these firms rely on both resource reallocation and technological innovation to cope with the impact of the SDP. Specifically, firms with stronger environmental regulations and more human capital tend to accumulate total factor productivity growth through technological innovation, while firms with greater resource dependence and political connections tend to benefit more from resource reallocation efforts. By exploring the mechanisms through which these policies impact productivity and sustainability, we provide valuable information for policymakers and managers to embrace heterogenous technology pathways towards sustainable development.

Energy efficiency evaluation, technology gap ratio, and determinants of energy productivity change in developed and developing G20 economies: DEA super-SBM and MLI approaches

This study employed Slack-based measure (SBM), Meta-frontier analysis, and Malmquist–Luenberger index (MLI) approaches to measure energy efficiency (EE), production technology heterogeneity, and energy productivity variation and its main determinants in developed and developing G20 countries for the period 1995–2020. The study's findings are: (i) Average EE for G20 countries is 0.8577, but still has an improvement potential of 14.23 percent. (ii) Developed countries have a higher average EE than developing (0.8927 > 0.8290). Results further revealed that energy efficiency scores in Argentina, Australia, Brazil, France, Saudi Arabia, South Africa, the US, the UK, and Korea are>1. (iii) Technology gap ratio (TGR) value in developed countries is higher than in developing (0.9869 > 0.6801), indicating that developed countries have advanced energy technologies superiority. The average MLI is less than one, showing a decline in energy productivity mainly due to a decline in technical efficiency, as EC < TC. (iv) Developed G20 countries get 0.64 percent aggregate growth in energy productivity as their MLI score is 1.0064, mainly due to technological growth (TC = 1.0161). Developing G20 countries, on the other hand, witnessed a decline in their energy productivity during 1995–2020, as MLI = 0.9925 > 1, designating that, on average, there is a 0.75 % decline in MLI.

Locationally Varying Production Technology and Productivity: The Case of Norwegian Farming

In this study, we leverage geographical coordinates and firm-level panel data to uncover variations in production across different locations. Our approach involves using a semiparametric proxy variable regression estimator, which allows us to define and estimate a customized production function for each firm and its corresponding location. By employing kernel methods, we estimate the nonparametric functions that determine the model’s parameters based on latitude and longitude. Furthermore, our model incorporates productivity components that consider various factors that influence production. Unlike spatially autoregressive-type production functions that assume a uniform technology across all locations, our approach estimates technology and productivity at both the firm and location levels, taking into account their specific characteristics. To handle endogenous regressors, we incorporate a proxy variable identification technique, distinguishing our method from geographically weighted semiparametric regressions. To investigate the heterogeneity in production technology and productivity among Norwegian grain farmers, we apply our model to a sample of farms using panel data spanning from 2001 to 2020. Through this analysis, we provide empirical evidence of regional variations in both technology and productivity among Norwegian grain farmers. Finally, we discuss the suitability of our approach for addressing the heterogeneity in this industry.

Energy efficiency and environmental impacts of horizontal small wind turbines in Austria

Small wind turbines (SWT) can contribute to the urgent need of transforming the energy system. Nevertheless, due to the heterogeneity of SWT technology, a high variety in environmental impacts of SWT exist. To evaluate whether the use of horizontal SWT can efficiently contribute to a renewable energy system, Life Cycle Assessments of two SWT, a commercial Schachner SW5 and a do-it yourself turbine in the Piggot Pig2F design, were conducted. The energy payback time was calculated using performance measurements from a rural and a suburban site in Austria. Results show that SWTs can reduce greenhouse gas emissions of the Austrian electricity production with calculated global warming potentials of 62gCO2eq/kWh (SW5) and 94gCO2eq/kWh (Pig2F) respectively. For both SWTs, the sub-system tower with foundation contributes about half to their overall global warming potential as well as to the cumulative energy demand. An improved shaping of SWT technology is therefore exemplified by both SWTs. The analysis shows that 19 out of 20 considered impact categories can be reduced by using secondary (recycled) or re-used steel, especially for the tower. The rural and suburban use of horizontal SWT can potentially contribute to reduce the environmental impacts of Austrian electricity production. Nevertheless, it becomes evident that a more sustainable shaping of SWT technology is highly recommendable.

Effect of adoption of organic farming on technical efficiency of olive-growing farms: empirical evidence from West Bank of Palestine

Organic farming is one of the methods that increases the value added of agricultural products in a sustainable way. This paper examines how the adoption of organic farming has impacted the technical efficiency of Palestinian olive-growing farms in the West Bank. Using cross-sectional data of olive farms in the Jenin governorate, we employ an input-oriented data envelopment analysis framework to compute radial and input use efficiencies. Considering heterogeneity in technology between organic and conventional farming, a metafrontier with a directional distance function approach was applied. As self-selection bias may exist due to the decision to adopt organic farming, we apply the endogenous switching regression method to reduce bias caused by unobserved heterogeneity. Results suggest that organic farms in Jenin are not less efficient than conventional farms. Their organic farming method improves input use efficiency with respect to labor and cost relative to conventional farming. While organic farming is commonly considered to be less efficient and more costly, our findings from Jenin imply that it is, in fact, a more efficient method. We suggest that promoting organic olive farming could offer an effective strategy for small farms to add value, despite the severe geopolitical constraints of farming in the West Bank.

Technological profiles, upgrading and the dynamics of growth: Country-level patterns and trajectories across distinct stages of development

We investigate the dynamic and qualitative nature of technological change in 96 countries between 1980 and 2021 from a structuralist technology upgrading perspective. First, drawing from patent data, we map the dynamics of technological knowledge by exploring the growth rates and significance of technology clusters. Second, we explore whether there is a relationship between specific technology clusters and economic growth. Third, we examine whether countries at different levels of development share similar or heterogeneous technology upgrading profiles and how patterns of technology upgrading have changed over time. We use a long-term, technology-level, cross-country patent dataset, and to address the issues identified we apply two complementary analytical methods: Generalized Method of Moments (GMM) panel data analysis and Fuzzy Set Qualitative Comparative Analysis (fs/QCA). We find a significant association between growth dynamics and country-level specific technology clusters that is driven by the ongoing ICT-based technological revolution and enabling nanotechnology, biotechnology and automation tools. Heterogenous trajectories in technological profiles allowed us to distinguish between more productive and less productive technology upgrading profiles at different income levels. Our results suggest that innovation policy should go beyond mission oriented policies focused solely on newly emerging technologies. Instead, it should develop policy mixes conceived as portfolios of missions focused on technology clusters with disparate objectives, requirements and institutional setups.

The driving effect of energy demand evolution: From the perspective of heterogeneity in technology

The driving effect of energy demand evolution: From the perspective of heterogeneity in technology

Exploring the potential of material information in patent data: The case of solid-state batteries

The investigation of high-performance materials represents an essential step in the battery industry to develop innovative technologies. While patent analysis could help promote research and development (R&D) by providing insights into innovative activities, the significance of material information contained in patent documents for the advancement of battery technologies has not yet been investigated. This study explored the potential of material information derived from patent data for analyzing the patent landscape by introducing a novel analysis framework. It uses patent claims collected between 2010 and 2021 from the domain of solid-state battery technology to extract and transform material information. This study relies on 1-mode network analysis to construct a material network and a 2-mode network analysis is applied to quantify the extent of the chemical portfolios of assignees. The results indicate that the polymer-based electrolytes are highlighted as the dominant type in the solid-state batteries. A glance at the chemical portfolios of assignees reveals a heterogeneous technology profile, pointing to a highly diversified material knowledge across several industries. The proposed analysis framework is expected to offer a new empirical perspective on the patent landscape in the battery sector by exploiting material information. Broadening the view of material research within the battery sector can support R&D managers and research scientists in the design of improved material search strategies and the selection of appropriate collaborations partners for the respective process.

Tracing green growth through industrial resource efficiency patterns: The role of competitiveness and clean technologies

AbstractThe European Green Deal entails benefits for industrial transition to cleaner production through resource efficiency, paving the way to green transition. We develop a conceptual framework to study the drivers of resource efficiency of European industries towards green growth via segments of the countries' competitiveness under technological heterogeneity. Data on 13 industries in 17 European countries over an 8‐year period is used. Evidence shows that isolated efforts to improve productive performance harms environmental efficiency in low competitiveness countries. Results show that industrial environmental performance is affected by country's competitiveness, contributing to the implementation of the New Industrial Strategy of Europe.

Networking Architectures and Protocols for IoT Applications in Smart Cities: Recent Developments and Perspectives

Numerous municipalities employ the smart city model in large cities to improve the quality of life of their residents, utilize local resources efficiently, and save operating expenses. This model incorporates many heterogeneous technologies such as Cyber-Physical Systems (CPS), Wireless Sensor Networks (WSNs), and Cloud Computing (ClCom). However, effective networking and communication protocols are required to provide the essential harmonization and control of the many system mechanisms to achieve these crucial goals. The networking requirements and characteristics of smart city applications (SCAs) are identified in this study, as well as the networking protocols that can be utilized to serve the diverse data traffic flows that are required between the dissimilar mechanisms. Additionally, we show examples of the networking designs of a few smart city systems, such as smart transport, smart building, smart home, smart grid, smart water, pipeline monitoring, and control systems.

English

For decades, debates among African leaders have centred on possible solutions to the continent&#39;s food security dilemma. If not addressed, the continued increase in population density and the accompanying pressures from conflicting demands for land in many Sub-Saharan African nations, including Nigeria, have the potential to exacerbate the arable land situation in the near future. To achieve increased production, African farmers must increase their use of productivity-enhancing tools such as irrigation, improved seeds, fertilizer, and modern farm management practices. The use of Urea Deep Placement (UDP) technology to boost nitrogen availability, a key ingredient in rice production, was introduced to rice farmers in selected Northern Nigerian states. Empirical information on the economics of the use of this technology in rice production is scanty, hence this study. Based on data collected from three hundred UDP users and non-users, this study examined the cost structure, the profitability and productivity of rice farm in the presence of technological heterogeneity. The study employed descriptive statistics, logistic regression, and the Latent class generation modes. The data was divided into two groups based on their production functions. The study concluded that farmers that used urea deep production technology outperformed non-users. However, in the short run, this technology is labour intensive. To solve the excessive labour use in the short run and to make rice production appealing to the young people who make up the majority of Nigeria&#39;s labour force, labour-saving technology must be combined with UDP technology. Key words: Productivity, profitability, technological heterogeneity, urea deep placement, rice.

Impacts of Symptom Checkers for Laypersons' Self-diagnosis on Physicians in Primary Care: Scoping Review.

Symptom checkers (SCs) for laypersons' self-assessment and preliminary self-diagnosis are widely used by the public. Little is known about the impact of these tools on health care professionals (HCPs) in primary care and their work. This is relevant to understanding how technological changes might affect the working world and how this is linked to work-related psychosocial demands and resources for HCPs. This scoping review aimed to systematically explore the existing publications on the impacts of SCs on HCPs in primary care and to identify knowledge gaps. We used the Arksey and O'Malley framework. We based our search string on the participant, concept, and context scheme and searched PubMed (MEDLINE) and CINAHL in January and June 2021. We performed a reference search in August 2021 and a manual search in November 2021. We included publications of peer-reviewed journals that focused on artificial intelligence- or algorithm-based self-diagnosing apps and tools for laypersons and had primary care or nonclinical settings as a relevant context. The characteristics of these studies were described numerically. We used thematic analysis to identify core themes. We followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist to report the study. Of the 2729 publications identified through initial and follow-up database searches, 43 full texts were screened for eligibility, of which 9 were included. Further 8 publications were included through manual search. Two publications were excluded after receiving feedback in the peer-review process. Fifteen publications were included in the final sample, which comprised 5 (33%) commentaries or nonresearch publications, 3 (20%) literature reviews, and 7 (47%) research publications. The earliest publications stemmed from 2015. We identified 5 themes. The theme finding prediagnosis comprised the comparison between SCs and physicians. We identified the performance of the diagnosis and the relevance of human factors as topics. In the theme layperson-technology relationship, we identified potentials for laypersons' empowerment and harm through SCs. Our analysis showed potential disruptions of the physician-patient relationship and uncontested roles of HCPs in the theme (impacts on) physician-patient relationship. In the theme impacts on HCPs' tasks, we described the reduction or increase in HCPs' workload. We identified potential transformations of HCPs' work and impacts on the health care system in the theme future role of SCs in health care. The scoping review approach was suitable for this new field of research. The heterogeneity of technologies and wordings was challenging. We identified research gaps in the literature regarding the impact of artificial intelligence- or algorithm-based self-diagnosing apps or tools on the work of HCPs in primary care. Further empirical studies on HCPs' lived experiences are needed, as the current literature depicts expectations rather than empirical findings.

Automatic Detection of Visual Changes between X-Ray Images to Support Antifraud Customs Control at Ports - A Preliminary Study

One of the goals of customs authorities is to identify, at borders, cargos that do not match their declaration, contain illegal items, or pose a hazard to society. Customs X-ray inspection procedures enable the detection of suspicious cargos and are an excellent support tool for customs officials. The ISACC project, funded under the Interreg IPA Cross-border Cooperation Italy-Albania-Montenegro Programme aims at developing a web platform that integrates data, coming from heterogeneous technologies and systems, in order to provide a rich information base supporting customs authorities during antifraud controls. In this paper, we propose a preliminary study, based on the SIFT algorithm, for the automatic detection of visual changes between scanner X-Ray images, that are part of this information base.

Understanding the driving factors and finding the pathway to mitigating carbon emissions in China's Yangtze River Delta region

Technological progress is an effective tool for controlling carbon emissions. However, because the connection between technological progress and carbon emissions remains under-theorized, the literature often discusses the overall effect of technological progress, ignoring the heterogeneity of technology. To better understand the driving factors of carbon emissions, we develop a new theoretical model based on the Green Solow model, in which technology is divided into production, energy conservation, and energy substitution technologies. Dynamic panel models are then applied to show the driving influence of different factors affecting carbon emissions in the Yangtze River Delta (YRD) region between 2000 and 2017. The results indicate that total technological progress is conducive to reducing carbon emissions. The heterogeneity analysis indicates a positive reduction effect on carbon emissions for energy substitution and energy conservation technologies, but not for production technology. Interestingly, production technology significantly drives carbon emissions. However, the results also suggest that to control carbon emissions, it is necessary to promote production technology. Further analysis suggests that production technology plays an important role in the effectiveness of energy conservation and energy substitution technologies in decreasing carbon emissions.

Uncertainty-Informed Operation Coordination in a Water-Energy Nexus

The widespread deployment of smart heterogeneous technologies and the growing complexity in our modern society calls for effective coordination of the interdependent lifeline networks. In particular, operation coordination of electric power and water infrastructures is urgently needed as the water system is one of the most energy-intensive networks, an interruption in which may quickly evolve into a dramatic societal concern. The closely-intertwined ecosystem of water and power infrastructures is commonly known as water-energy nexus. This paper develops a novel analytic for uncertainty-aware day-ahead operation optimization of the interconnected power and water systems (PaWS). Joint probabilistic constraint (JPC) programming is employed to capture the uncertainties in wind resources and water demand forecasts. The proposed integrated stochastic model is presented as a non-linear non-convex optimization problem, where the non-linear hydraulic constraints in the water network are linearized using piece-wise linearization technique, and the non-convexity is efficiently tackled with a Boolean solution methodology to convert the proposed model with JPCs to a tractable mixed-integer linear programming (MILP) formulation that can be quickly solved to optimality. The suggested framework is applied to a 15-node commercial-scale water network jointly operated with a power transmission system using a modified IEEE 57-bus test system. The numerical results demonstrate the of the proposed stochastic framework, resulting in cost reduction (13&#x0025; on average when compared to the traditional setting) and energy saving of the integrated model under different realizations of uncertain renewable energy sources (RESs) and water demand scenarios. Additionally, the scalability of the proposed model is tested on a modified IEEE 118-bus test system connected to five water networks.

Cultural Differences and Bilateral Trade: An Empirical Study Based on Industrial Data from OECD and BRIICS Countries

ABSTRACT This study extends the cross-sectional gravity function in the Eaton and Kortum model to a panel-data model based on 36 OECD and six BRIICS countries from 2010 to 2018 and introduce heterogeneous technology to measure the competitiveness of each country by interaction fixed effects. The results illustrate that the total cultural distance between countries significantly impedes bilateral trade, as it increases trade costs. The conclusions are robust with instrumental variables, alternative measurement of cultural differences, and extended time window estimation. And the effects present heterogeneity in sub-dimensions of cultural distance and sub-industries.