Key Findings Research Articles

Does Fintech Investment in Commercial Banks Improve Business Performance? -- Based on the Empirical Test of 42 Listed Commercial Banks in China from 2010 to 2022

Does Fintech Investment in Commercial Banks Improve Business Performance? -- Based on the Empirical Test of 42 Listed Commercial Banks in China from 2010 to 2022

Effect of Cumulative Spirulina Intake on Broiler Meat Quality, Nutritional and Health-Related Attributes.

This work aimed to assess how different cumulative levels of Spirulina (Arthrospira platensis) intake influence individual broiler meat quality parameters, nutritional value and health-related traits. The data analysed showed varying cumulative Spirulina intake levels, ranging from 3.46 to 521 g/bird, with large changes in meat traits. The key findings indicate that Spirulina intake significantly enhances meat colour, primarily due to its rich carotenoid content. However, this enhancement shows a saturation effect at higher intake levels, where additional Spirulina does not further improve the colour. Regarding the meat nutritional profile, Spirulina increases beneficial n - 3 polyunsaturated fatty acids and reduces lipid oxidation. These effects on meat, however, are not linear and become more complex at higher microalga intake levels. Regarding meat sensory attributes, moderate Spirulina levels positively influence flavour and texture. Still, higher levels may lead to changes not universally preferred by meat consumers, highlighting the need for balanced Spirulina inclusion in diets. Optimal Spirulina cumulative intake levels must be identified to balance meat's nutritional benefits with consumer preferences. Additionally, ensuring Spirulina's purity and adherence to regulatory standards is essential for consumer safety and market access. These findings provide valuable insights for poultry nutritionists and the food industry, emphasising the necessity of a balanced approach to Spirulina's incorporation in poultry diets.

A Critical Analyses on the History of Indigenous Resistance Movements: Lessons for Contemporary Struggles

The research paper, " A Critical Analyses on the History of Indigenous Resistance Movements: Lessons for Contemporary Struggles," comprehensively examines Indigenous resistance movements globally. The primary objectives of this study are to unearth historical narratives of Indigenous resistance, analyse their characteristics, and extract lessons applicable to contemporary struggles for Indigenous rights and social justice. The research employs a multi-faceted methodology to achieve these objectives, encompassing extensive literature review, archival research, and qualitative analysis of selected case studies. Ethical considerations in Indigenous research guide our data collection and analysis process. The key findings of this research illuminate a rich tapestry of Indigenous resistance movements spanning diverse regions and periods. These movements exhibit remarkable resilience, adaptability, and a commitment to cultural preservation in the face of colonial oppression. The study identifies commonalities in their strategies, including grassroots organising, cultural revitalisation, and alliances with sympathetic non-Indigenous groups. The implications of our research are profound. By revisiting the history of Indigenous resistance, we provide contemporary Indigenous communities and activists with valuable insights and inspiration. These historical lessons can inform present-day strategies, contribute to preserving Indigenous cultures, and bolster the pursuit of justice, equity, and self-determination for Indigenous peoples globally. In conclusion, this research underscores the enduring legacy of Indigenous resistance movements and their relevance in addressing the pressing challenges Indigenous communities face today. By mapping this history and distilling its lessons, we aim to promote a deeper understanding of Indigenous struggles and foster solidarity in pursuing a more just and inclusive world.

Applications of data envelopment analysis in acute care hospitals: a systematic literature review, 1984-2022.

This study reviews scholarly publications on data envelopment analysis (DEA) studies on acute care hospital (ACH) efficiency published between 1984 and 2022 in scholarly peer-reviewed journals.We employ systematic literature review (SLR) method to identify and analyze pertinent past research using predetermined steps. The SLR offers a comprehensive resource that meticulously analyzes DEA methodology for practitioners and researchers focusing on ACH efficiency measurement. The articles reviewed in the SLR are analyzed and synthesized based on the nature of the DEA modelling process and the key findings from the DEA models. The key findings from the DEA models are presented under the following sections: effects of different ownership structures; impacts of specific healthcare reforms or other policy interventions; international and multi-state comparisons; effects of changes in competitive environment; impacts of new technology implementations; effects of hospital location; impacts of quality management interventions; impact of COVID-19 on hospital performance; impact of teaching status, and impact of merger. Furthermore, the nature of DEA modelling process focuses on use of sensitivity analysis; choice of inputs and outputs; comparison with Stochastic Frontier Analysis; use of congestion analysis; use of bootstrapping; imposition of weight restrictions; use of DEA window analysis; and exogenous factors. The findings demonstrate that, despite several innovative DEA extensions and hospital applications, over half of the research used the conventional DEA models. The findings also show that the most often used inputs in the DEA models were labor-oriented inputs and hospital beds, whereas the most frequently used outputs were outpatient visits, followed by surgeries, admissions, and inpatient days. Further research on the impact of healthcare reforms and health information technology (HIT) on hospital performance is required, given the number of reforms being implemented in many countries and the role HIT plays in enhancing care quality and lowering costs. We conclude by offering several new research directions for future studies.

Do labor unions enhance corporate social performance? Evidence from Korean financial markets

This study examines the impact of labor unionization on corporate social responsibility (CSR) in South Korean listed companies, particularly in the context of chaebol-affiliated firms. Using a dataset of 2,622 firm-year observations between 2005 and 2009, the study employs regression analyses to explore the relationship between unionization and CSR performance. Key findings indicate a significant negative correlation between labor unionization and CSR engagement, suggesting that unionized firms exhibit less involvement in CSR activities. This association, however, is not significant in chaebol-affiliated firms, where the unique corporate structure and shared resources appear to mitigate the influence of labor unions on CSR. Furthermore, the study reveals a positive link between CSR initiatives and labor productivity in unionized firms, indicating that CSR may enhance employee efficiency. The study highlights the intricate relationships between labor unionization, corporate governance, and CSR, particularly in the context of Korean business conglomerates. It emphasizes the importance of aligning labor interests with CSR commitments and underscores the role of effective corporate governance in promoting CSR activities. The positive impact of CSR on labor productivity underscores its potential in boosting employee performance. AcknowledgmentThis work was supported by the Gachon University research fund of 2023. (GCU-202303770001).

Abstract PR-006: Brain metastases roadmap reveals conserved regulatory dynamics rooted in dormant tumor cells

Abstract Capturing comprehensive brain metastasis landscape is critical to the establishment of effective anti-tumor strategies. This study took advantage of single cell multiomics sequencing to profile the molecular and cellular dynamics in tumor cells and associated microenvironment during brain metastasis. Among different primary cancer types, our data suggest that there are conserved yet distinct tumor cell subpopulations, governed by specific changes in gene expression, chromatin accessibility and tumor-stroma interactions. We characterized the conserved tumor subpopulations of brain metastasis with features of: (1) dormancy, (2) enhanced translation and migration, (3) epithelial to mesenchymal transition and (4) high proliferation rate. In line with previous observations, dormant cells exhibit distinct stimulation for interferon and oxidative phosphorylation. Furthermore, our data suggest that dormant tumor cells increase amino acids metabolism and antigen presentation by upregulating HLA class molecules. Stromal and tumor cells interaction network analysis predicted most active ligands that might shape intratumoral heterogeneity. For example, TGFβ signaling induced by immune cells and astrocytes is associated with tumor cell epithelial to mesenchymal transition. Additionally, results suggest the vascular endothelial niche supports brain metastasis proliferation. Interestingly, dormant tumor cells appear to limit cell-cell interactions with the surrounding microenvironment when compared to other tumor cells subpopulations. Despite pronounced cell plasticity, trajectory analysis uncovered a cell progression pattern and its major sequential states and driving genes. Notably, the trajectory embarked with dormant tumor cells at its root and ended with a prevalence of rapidly proliferating tumor cells. As cycling cancer cells arise, we observed a disruption in circadian rhythm regulators activities, indicating that altered circadian regulation may contribute to brain metastasis progression. This work demonstrated that despite a pronounced intratumoral heterogeneity, brain metastases present conserved tumor subpopulations regardless of the patient and primary type. Importantly, the tumor trajectory provides new insights into the regulatory landscape controlling the transition from dormant to proliferating tumor cells. A novel and key finding in this study is the multiomics characterization of the regulatory landscape shaping human brain metastases. Thus, we believe further understanding of these key regulatory elements could lead to novel tumor targets with broad translational potential. Citation Format: Remi Klotz, Yiru Jess Wang, Alexis Zukowski, Frank Attenelo, Srinivas Ramachandran, Min Yu. Brain metastases roadmap reveals conserved regulatory dynamics rooted in dormant tumor cells [abstract]. In: Proceedings of the AACR Special Conference on Brain Cancer; 2023 Oct 19-22; Minneapolis, Minnesota. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_1):Abstract nr PR-006.

Enhancing Urban Above-Ground Vegetation Carbon Density Mapping: An Integrated Approach Incorporating De-Shadowing, Spectral Unmixing, and Machine Learning

Accurately mapping urban above-ground vegetation carbon density presents challenges due to fragmented landscapes, mixed pixels, and shadows induced by buildings and mountains. To address these issues, a novel methodological framework is introduced, utilizing a linear spectral unmixing analysis (LSUA) for shadow removal and vegetation information extraction from mixed pixels. Parametric and nonparametric models, incorporating LSUA-derived vegetation fraction, are compared, including linear stepwise regression, logistic model-based stepwise regression, k-Nearest Neighbors, Decision Trees, and Random Forests. Applied in Shenzhen, China, the framework integrates Landsat 8, Pleiades 1A & 1B, DEM, and field measurements. Among the key findings, the shadow removal algorithm is effective in mountainous areas, while LSUA-enhanced models improve urban vegetation carbon density mapping, albeit with marginal gains. Integrating kNN and RF with LSUA reduces errors, and Decision Trees, especially when integrated with LSUA, outperform other models. This study underscores the potential of the proposed framework, particularly the integration of Decision Trees with LSUA, for advancing the accuracy of urban vegetation carbon density mapping.

The Role of Artificial Intelligence in the Diagnosis of Neoplastic Diseases: A Systematic and Bibliometric Review

The Role of Artificial Intelligence in the Diagnosis of Neoplastic Diseases: A Systematic and Bibliometric Review

Optimization and design of a new column sequencing for crude oil distillation at Basrah refinery

Abstract The utilization of distillation stands as a predominant separation method within the chemical and petroleum industries, prominently influencing operational costs and environmental impact due to energy consumption. Enhancing energy efficiency holds paramount significance in elevating the sustainability and overall efficacy of distillation operations. Within this study, we introduce an innovative approach termed “marginal vapor flow (MVF)” to optimize the distillation column sequence for crude oil processing, focusing on the third distillation unit at the Basra Refinery. This research evaluates diverse column designs through streamlined simulations using Aspen HYSYS V11 software. The study determines total energy consumption as a benchmark, comparing it against the optimal sequence recommended by the MVF methodology. A novel application of the downward reduction equation to crude oil guides the selection of light and heavy components. Key findings from this comprehensive analysis showcase the potency of combining MVF with Aspen HYSYS for optimizing crude oil distillation column sequences. Aspen HYSYS, a widely recognized process simulation tool, accurately represents distillation processes. Simultaneously, MVF facilitates the determination of optimal column sequences based on marginal vapor flow rates. Notably, the results reveal that within the studied sequences, sequence 9 exhibits the lowest total MVF of (1393.4 kmol/h), signifying its optimality, while sequence 2 displays the highest total MVF of (4827.3 kmol/h), representing the least favorable scenario. Simulation of the optimal sequence derived through the MVF approach exhibits a remarkable 35% reduction in energy consumption compared to real-life operations. Conversely, simulating the least favorable sequence demonstrates a substantial 32% increase in energy consumption compared to actual operations. This study underscores the pivotal role of MVF methodology in optimizing distillation sequences for enhanced energy efficiency, providing actionable insights for refining operations to significantly reduce energy consumption and operational costs while advancing sustainability goals.

The effect of smooth parametrizations on nonconvex optimization landscapes

AbstractWe develop new tools to study landscapes in nonconvex optimization. Given one optimization problem, we pair it with another by smoothly parametrizing the domain. This is either for practical purposes (e.g., to use smooth optimization algorithms with good guarantees) or for theoretical purposes (e.g., to reveal that the landscape satisfies a strict saddle property). In both cases, the central question is: how do the landscapes of the two problems relate? More precisely: how do desirable points such as local minima and critical points in one problem relate to those in the other problem? A key finding in this paper is that these relations are often determined by the parametrization itself, and are almost entirely independent of the cost function. Accordingly, we introduce a general framework to study parametrizations by their effect on landscapes. The framework enables us to obtain new guarantees for an array of problems, some of which were previously treated on a case-by-case basis in the literature. Applications include: optimizing low-rank matrices and tensors through factorizations; solving semidefinite programs via the Burer–Monteiro approach; training neural networks by optimizing their weights and biases; and quotienting out symmetries.

A Patient-Centered Approach to Vernal Keratoconjunctivitis (VKC): A Podcast.

Vernal keratoconjunctivitis (VKC) is a rare yet severe form of allergic conjunctivitis predominantly affecting children, mainly boys, with a global prevalence and a higher incidence in certain geographical regions. The disease is characterized by seasonal exacerbations. VKC presents with ocular surface inflammation leading to various distressing symptoms such as itching, redness, mucous discharge, and pain. The disease primarily manifests bilaterally, though it may initially appear unilaterally. If left untreated, VKC can result in corneal complications, including shield ulcers and vision impairment, affecting daily activities and psychosocial well-being, especially in children. The diagnosis of VKC involves identifying key clinical findings on the ocular surface such as Tranta dots, giant papillae, or shield ulcers. Management follows a stepwise approach, including anti-allergic eye drops, steroid eye drops, and topical medications like cyclosporine, which may take up to 3months to show efficacy. Allergic sensitization, often to inhaled allergens like pollen and house dust mites, is associated with VKC in half of the cases. Understanding and managing these allergies through measures such as avoidance, sensitization control, and co-treatment of associated conditions like asthma and rhinoconjunctivitis are essential in VKC management. Atopic keratoconjunctivitis (AKC), a related condition associated with atopic dermatitis and asthma, shares similarities with VKC but typically affects young adults. However, there is an observed spectrum between the two diseases, indicating similar treatment strategies for both. VKC treatment requires a patient-centered approach, involving informed and supported parents, considering economic factors due to costly eye drops, and ensuring accessibility and practicality of treatment, especially in children. A multidisciplinary team collaboration, including ophthalmologists, pediatricians, and dermatologists, optimizes patient care. The rewarding aspect of VKC treatment lies in witnessing children regain their quality of life, overcome vision challenges, and thrive in their daily activities. In conclusion, understanding VKC, its associated allergies, and employing a comprehensive, patient-centered approach are crucial in managing this challenging condition, particularly in children, to enhance their vision and overall well-being.

(198) Harnessing the Power of Tantric Practices: A Revolutionary Path to Enhanced Sexual Well-being and Transformation

Abstract Introduction In recent years, the integration of holistic practices in the field of sexual medicine has gained significant attention. Among these practices, tantra stands out as a revolutionary approach that emphasizes mindfulness, energy cultivation, and connection. This article explores the profound impact of tantric practices on sexual well-being, drawing from a qualitative study involving six individuals who have experienced transformative changes in their lives through the practice of tantra. Their stories provide compelling evidence of the effectiveness of tantra in reducing anxiety, cultivating meaningful relationships, and enhancing overall sexual health. Objective This study aimed to assess the therapeutic benefits of tantra as an intervention for emotional regulation, specifically targeting symptoms of anxiety and depression while promoting relaxation and emotional connection. Through qualitative interviews with diverse tantra educators and practitioners, the study sought to understand the observed changes in their personal lives and relationships resulting from tantra mindfulness exercises. Methods This qualitative study employed interpretative phenomenological analysis (IPA) to explore the lived experiences of six tantra educators and practitioners. Interviews were conducted using a structured set of questions to ensure consistency. The interviews were recorded, transcribed, and analyzed to understand the changes observed in participants' lives and relationships as a result of practicing tantra mindfulness exercises. The study also referred to previous research on meditation and neuroplasticity to explore potential neurological changes associated with tantra practices. Results The findings of this qualitative study underscore the importance of embracing a multidimensional approach to sexual medicine. By integrating tantric philosophy and techniques into existing frameworks, professionals in the field can provide a holistic and sustainable approach to enhancing sexual well-being. Tantra offers a rich tapestry of practices that go beyond addressing physical symptoms, recognizing the interconnectedness of mind, body, and spirit in the pursuit of sexual health and fulfillment. Conclusions The conclusion summarizes the key research findings, emphasizing the transformative power of tantric practices in enhancing sexual well-being and fostering meaningful relationships. It highlights the potential of tantra to revolutionize the understanding and treatment of sexual concerns in the field of sexual medicine. The conclusion emphasizes the importance of a multidimensional approach to sexual medicine and encourages the incorporation of tantra for a more holistic approach to sexual well-being. Disclosure No.

Criticality assessment of minerals associated with China's battery technologies

Power batteries require mineral resources such as nickel, cobalt, lithium, iron, graphite, and manganese. However, the analysis of the key mineral criticality scores related to China's battery industry is limited. To provide a reference for the research and development as well as the design of battery technologies from a criticality assessment perspective, this study employs indicators such as Herfindahl-Hirschman Index, World Governance Indicators, the innovation factors, and others to construct a criticality assessment framework for evaluating the critical situations of nine minerals and eighteen battery technologies in China. The key findings include: LiFePO4 exhibited the lowest criticality score among lithium-ion batteries. Considering energy density, some sodium-ion batteries posed higher criticality scores compared to lithium batteries. To reduce criticality scores from the perspective of battery materials, at least two other high-score materials required attention, apart from lithium-sulfur batteries. Supply concentration was the most crucial indicator among the five criticality indicators for lithium and cobalt, showing an overall increasing trend. Economic importance consistently remained at 100 for nickel, iron, aluminum, and manganese.

Job polarization and non-standard work: Evidence from France

Using annual and quarterly data from the French LFS, we investigate the interplay between the extensive and intensive margins of labor adjustment, job polarization, and non-standard work (NS) along the business cycle. We find that the declines in aggregate work hours during economic downturns can primarily be attributed to the reduction in routine standard employment (R,S) during past recessions in France. We then study the dynamics of routine standard employment, highlighting several key findings: (i) The primary drivers of R,S employment are inflows from routine non-standard work (R,NS) and unemployment. (ii) Individuals who lose R,S jobs are more likely to transition to R,NS positions following a brief period of unemployment. (iii) A majority of transitions within this employment category occur within the same employer, resulting in asymmetric adjustments in individual working hours. This often involves a notable increase in hours following either a contractual upgrade or a change in employer. Finally, we draw a comparative analysis between these findings and the United States, where the dynamics of routine employment appear distinct, despite a similar trend in job polarization.

A study of postgraduate students’ research training environment and innovation capabilities: The mediating role of academic interest and aspiration

ABSTRACT The purpose of this study is to examine the mediating role of academic interest and academic aspirations in shaping postgraduate students’ innovation abilities. A sample of 847 postgraduate students from the regions of Jiangsu, Zhejiang, and Shanghai was utilised. Structural equation model, employing partial least squares, a second-generation statistical software package, was employed for data analysis. The study reveals three key findings. First of all, it affirms a significant and positive correlation between the research training environment and the innovation abilities of postgraduate students. Secondly, it identifies academic interests and aspirations as crucial mediators within the intricate network of relationships connecting the research training environment and research innovation capabilities among postgraduate students in China. Moreover, academic interest and academic aspirations sequentially mediate this process, shedding light on the nuanced dynamics involved. Using these insights, higher education administrators can improve postgraduate student development and research training procedures.

Investigating the Influence of Heavy Metals and Environmental Factors on Metabolic Syndrome Risk Based on Nutrient Intake: Machine Learning Analysis of Data from the Eighth Korea National Health and Nutrition Examination Survey (KNHANES).

This study delves into the complex interrelations among nutrient intake, environmental exposures (particularly to heavy metals), and metabolic syndrome. Utilizing data from the Korea National Health and Nutrition Examination Survey (KNHANES), machine learning techniques were applied to analyze associations in a cohort of 5719 participants, categorized into four distinct nutrient intake phenotypes. Our findings reveal that different nutrient intake patterns are associated with varying levels of heavy metal exposure and metabolic health outcomes. Key findings include significant variations in metal levels (Pb, Hg, Cd, Ni) across the clusters, with certain clusters showing heightened levels of specific metals. These variations were associated with distinct metabolic health profiles, including differences in obesity, diabetes prevalence, hypertension, and cholesterol levels. Notably, Cluster 3, characterized by high-energy and nutrient-rich diets, showed the highest levels of Pb and Hg exposure and had the most concerning metabolic health indicators. Moreover, the study highlights the significant impact of lifestyle habits, such as smoking and eating out, on nutrient intake phenotypes and associated health risks. Physical activity emerged as a critical factor, with its absence linked to imbalanced nutrient intake in certain clusters. In conclusion, our research underscores the intricate connections among diet, environmental factors, and metabolic health. The findings emphasize the need for tailored health interventions and policies that consider these complex interplays, potentially informing future strategies to combat metabolic syndrome and related health issues.

A comparative analysis of organic substrates from industrial wastewater streams for enhanced electricity production using a double chamber microbial fuel cell (DCMFC)

This study investigates the startup sequence of a Double Chamber Microbial Fuel Cell (DCMFC) for the treatment of diverse industrial wastewater streams, including biorefinery, dairy, and mixed sources. It presents a comprehensive startup and calibration procedure for the essential electrical components, utilizing MATLAB-SIMULINK to establish typical resistance calibration curves and correlate measured electrical parameters with expected values. This approach enables a robust experimental startup protocol for the DCMFC under psychrophilic and thermophilic conditions. The study explores the impact of fundamental operating parameters on determining the experimental Hydraulic Retention Time (HRT) of the DCMFC. Specifically, it examines the effects of catholyte type (Phosphate PO43−buffer) and three distinct organic substrates: dairy wastewater, biorefinery wastewater, and mixed substrates (50% v/v dairy).Electricity production is evaluated in terms of voltage yield (mV), Columbic efficiency (CE) (%), and overall growth yield (Y). The study also assesses the COD (Chemical Oxygen Demand) mass balance component's influence on COD removal efficiency to establish a viable operating HRT during the startup phase. Key findings include startup experimental voltage yields of 145.2 mV for biorefinery, 85 mV for mixed wastewater, and an impressive 357 mV for dairy wastewater. Columbic efficiencies of 0.92%, 0.77%, and 0.02% were respectively achieved. Furthermore, the study reveals a viable experimental HRT, ranging from 72 to 96 hours, for both biorefinery/mixed and dairy/mixed wastewater sources, facilitating startup electricity generation and efficient removal of organic contaminants. These findings contribute to the advancement of sustainable wastewater treatment and bioelectricity generation, offering valuable insights for practical applications.

Influence of milling parameters on the microstructural evolution mechanism of 7075-T6 aluminum alloy

This study evaluates the influence of milling parameters on the milling process and microstructural changes in 7075-T6 aluminum alloy using experimental and simulation methods. Key findings include a direct correlation between milling parameters and higher chip temperatures, particularly influenced by milling speed which at its third level can cause temperature elevations up to 36 °C, ordered by impact as ap > f > v.Increasing milling depth markedly affects grain recrystallization, especially near the tool's trailing face (P3), leading to a 45.8% reduction in dynamic recrystallization, whereas lower depths expedite this process. Additionally, grain size and number at the leading face (P1) are also depth-dependent, with larger grains diminishing in volume yet increasing in quantity as depth increases. Enhanced milling speeds up to 500 mm/min significantly refine grains to near 1 μm at P1, with an 80.7% rise in recrystallization numbers, while at P3, grain size initially contracts then enlarges at 416 mm/min. Feed rate primarily impacts the quantity of recrystallized grains at the tool tip (P2), with a notable 60.4% increment and a swift transition from larger to smaller grains. Both P1 and P2 experience about a 20% reduction in grain growth due to feed rate, with more pronounced effects at P1 and the fragmentation of larger boundary grains into smaller, irregular shapes.

Patent protection, externalities, and income inequality

AbstractThis paper develops a Schumpeterian growth model with considering consumption and leisure externalities. The main purpose of this study is to investigate the effect of patent protection policy on growth and inequality, as well as the interaction between policy effect and externalities. According to the log form utility function specification, this means that the elasticity of intertemporal substitution is unity. The following are the key findings of this paper. Patent protection policy encourages innovation and increases employment in the R&D industry, which enhances economic growth while increasing income inequality. In regard to externalities, an increase in the degree of consumption (leisure) externalities results in a higher (lower) growth rate and more (smaller) income inequality. When consumption (leisure) externality is greater intensity, the growth effect of patent protection policy becomes stronger (weaker), while its influence on expanding income inequality lessens (enhances). Finally, both the Pareto optimal patent protection policy and the optimal patent policy under the maximization of social welfare positively correlate with consumption externalities, but negatively correlate with leisure externalities.

Extreme single-excitation subradiance from two-band Bloch oscillations in atomic arrays

Atomic arrays provide an important quantum optical platform with photon-mediated dipole–dipole interactions that can be engineered to realize key applications in quantum information processing. A major obstacle for such applications is the fast decay of the excited states. By controlling two-band Bloch oscillations of single excitation in an atomic array under an external magnetic field, here we show that exotic subradiance can be realized and maintained with orders of magnitude longer than the spontaneous decay time in atomic arrays with the finite size. The key finding is to show a way for preventing the wavepacket of excited states scattering into the dissipative zone inside the free space light cone, which therefore leads to the excitation staying at a subradiant state for an extremely long decay time. We show that such operation can be achieved by introducing a spatially linear potential from the external magnetic field in the atomic arrays and then manipulating interconnected two-band Bloch oscillations along opposite directions. Our results also point out the possibility of controllable switching between superradiant and subradiant states, which leads to potential applications in quantum storage.