bluuebunny/crossref_metadata_2025_split huggingface dataset:
An autoethnography of a transformative odyssey: decolonizing anthropology, the hegemony of English, and the pursuit of plurilogies
Authors: Ali Inayat 
Published: June 2024

AbstractIn this autoethnographic account of my own transformative odyssey, via drawing on my personal experiences as a Pakistani anthropologist, I explore the pervasive impacts of English language hegemony in academia. Contextualizing this hegemony within the ongoing discussions on the possibility of “decolonizing anthropology,” I ask about the possibility and affordability of promoting publications in native languages, thereby challenging the status quo wherein non-native English-speaking authors bear the financial burdens of translations. Also, I question the abilities and readiness of major anthropological platforms to embrace sessions or panels in native languages to promote plurilogies—a term I created to refer to the coexistence and acceptance by major anthropological platforms of multiple diverse perspectives, narratives, or wisdoms. By asking these questions, I hope to prompt a reevaluation of the dominance of English within the field as well as a reflexive anthropology that urges anthropologists to seek innovative means of communication and understanding.
Temporal and spatial effects of manufacturing agglomeration on CO2 emissions: evidence from South Korea
Authors: Wu Zhen , Woo Su-Han , Oh Jin-Ho , Lai Po-Lin 
Published: June 2024

AbstractStudies have shown that industrial agglomeration has a facilitating effect on carbon emission reduction. However, discussions on the impact of manufacturing agglomeration on emission reduction have not simultaneously considered spatial correlation and temporal continuity. Addressing this gap, this study develops a dynamic spatial econometric model rooted in agglomeration economic theory to simultaneously assess the spatial and temporal impacts of manufacturing agglomeration on carbon emission reduction. Utilizing panel data from 17 major South Korean regions from 2013 to 2019, the research investigates the internal mechanisms and spatial effects of manufacturing agglomeration on reducing carbon emissions. The findings reveal that the relationship between manufacturing agglomeration (specialization and diversification) and carbon emissions in South Korea shows an inverted U-shape. Moreover, regarding the temporal continuity of carbon emissions, in the short term, specialized agglomeration is beneficial to reduce local and neighboring carbon emissions. In the long run, the effect of specialized agglomeration on the overall carbon emission reduction is still obvious. However, diversified agglomeration can only reduce local carbon emissions in the short term, but the spillover effect on neighboring areas is not obvious. In the long run, diversified agglomeration can effectively reduce local carbon emissions, but the spillover effect on neighboring areas is still not obvious. These nuanced insights are crucial for policymakers aiming to leverage industrial agglomeration for carbon emissions reduction effectively.
Exploring the spatiotemporal evolution mechanism of rural e-commerce: insights from the experience of Taobao towns in China
Authors: Cui Xufeng , Huang Wei , Zhang Jing , Deng Wei 
Published: June 2024

AbstractIn the era of the digital economy, rural e-commerce has emerged as a compelling catalyst for driving the modernization of agriculture and rural areas. It has given rise to notable exemplars such as “Taobao villages” and “Taobao towns”, paving the way for scalable pathways toward rural revitalization. The transition from Taobao villages to Taobao towns signifies the evolution of rural e-commerce from scattered nodes to interconnected networks, reflecting a significant development trend. While existing studies have primarily focused on the spatiotemporal patterns of Taobao villages, limited research has been conducted on the spatiotemporal characteristics and the underlying evolution mechanism of Taobao towns. To fill the research gap, this study investigates the spatial-temporal evolution of Taobao towns employing geospatial methods and identifies key contributing factors using GeoDetector in China. The results show that: (1) The coverage of Taobao towns expands year by year in all provinces and cities, showing a “T-shaped and three-center” spatial pattern with a decreasing gradient from southeast to northwest. (2) Taobao towns in the central area are developing rapidly and are becoming an emerging development center. (3) The development of Taobao towns is the result of a combination of multiple factors, including regional economic base, social environment, market atmosphere, transportation conditions, infrastructure construction, etc. The study can provide Chinese experience for rural development and transformation.
The influence of robot applications on rural labor transfer
Authors: Yu Kaizhi , Shi Yao , Feng Jiahan 
Published: June 2024

AbstractEmployment is a pivotal driver for ensuring and enhancing people’s livelihoods, with stable employment forming the bedrock for achieving high-quality economic development. In this study, CMDS data from 2014–2018, IFR data, and micro-data from China’s Second National Economic Census were utilized to analyze the impact of robot applications on rural labor migration in China, exploring both theoretical and empirical dimensions, particularly the crowding-out effect. The research findings suggest that robot applications influence labor demand through expansion and substitution effects. The results show robot applications significantly increased the probability of rural labor considering re-migration, with a 1% increase in urban robot density resulting in a 0.249% increase in the likelihood of rural labor re-migration. In addition, robot applications were found to reduce the migration rate of urban labor and increase the probability of rural laborers returning to the agricultural sector. Based on mechanism analyses, robot applications were found to have pronounced passive effects in accelerating rural labor migration, particularly among groups with lower skill levels, individuals aged over 44, those in low-skilled occupations, those possessing strong mobility, and those residing in economically developed areas. The conclusions of this study provide new insights for stabilizing employment and optimizing rural labor migration in the context of artificial intelligence development.
Novel two-dimensional radio frequency energy harvesting system: Design and implementation
Authors: Morsy Ismail Morsy Ahmed , Saleh Khalid 
Published: June 2024

Recently, numerous published research studies and projects have focused on designing a passive charger for earphones and mobile phones. Such studies depend on a one-dimensional (1D) voltage multiplier circuit using a Schottky diode. To increase the harvested power, this study presents a novel two-dimensional (2D) radio frequency (RF) energy harvesting system based on a wideband microstrip antenna. The fabrication and design analysis of the 2D-RF n-stage voltage multiplier circuit using a zero-biasing Schottky diode are carried out. The design of this 2D-RF energy harvester is based on the idea of multi-RF current source passive energy harvesters that feed only one load through the main n-stage voltage multiplier circuit to increase the load current and consequently the power delivered to this load. This circuit was fabricated using a 10.4 relative permittivity FR4 substrate. In addition, the matching between the RF antenna output and the input of the 2D-RF voltage multiplier circuit was considered in the design analysis and fabrication to prevent RF power reflection. The circuit was simulated using ORCAD 9.1, and the simulation results were investigated at different frequencies and values of load resistance. In addition, the experimental results of the prototype model are compared with those of earlier related work. Finally, the results proved that the output power delivered from the proposed 2D system is approximately equal to that delivered by the 1D system multiplied by the number of RF voltage multiplier circuit stages 100 cm away from the RF source.
A silicon photonics waveguide-coupled colloidal quantum dot photodiode sensitive beyond 1.6 µm
Authors: Pang Chao , Deng Yu-hao , Kheradmand Ezat , Hagelsieb Luis Moreno , Guo Yujie , Cheyns David , Geiregat Pieter , Hens Zeger , Van Thourhout Dries 
Published: June 2024

Silicon photonics faces a persistent challenge in extending photodetection capabilities beyond the 1.6 µm wavelength range, primarily due to the lack of appropriate epitaxial materials. Colloidal quantum dots present a promising solution here, offering distinct advantages, such as infrared wavelength tunability, cost-effectiveness, and facile deposition. Their unique properties position them as a potential candidate for enabling photodetection in silicon photonics beyond the conventional telecom wavelength, thereby expanding the potential applications and capabilities within this domain. In this study, we have successfully integrated lead sulfide (PbS) colloidal quantum dot photodiodes (QDPDs) onto silicon waveguides using standard process techniques. The integrated photodiodes exhibit a remarkable responsivity of 1.3 A/W (with an external quantum efficiency of 74.8%) at a wavelength of 2.1 µm, a low dark current of only 106 nA, and a bandwidth of 1.1 MHz under a −3 V bias. To demonstrate the scalability of our integration approach, we have developed a compact 8-channel spectrometer incorporating an array of QDPDs. This achievement marks a significant step toward realizing a cost-effective photodetector solution for silicon photonics, particularly tailored for a wide range of sensing applications around the 2 µm wavelength range.
Graphene-based tunable tri-band terahertz refractive index sensor
Authors: Fu Maixia , Zhang Tiantian , Niu Yingying , Guo Shaoshuai , Wang Zhaoying , Liu Xueying 
Published: June 2024

A tunable tri-band terahertz refractive index sensor based on graphene is proposed and designed. The structure of the sensor comprises a gold (Au) substrate layer, a dielectric layer (Topas), and a graphene pattern layer. The numerical simulation results demonstrate that the sensor exhibits three narrowband absorption peaks at 1.68, 3.82, and 4.78 THz, and the corresponding absorption rate can reach 99.9%, 98.0%, and 97.9%, respectively. By adjusting the Fermi level of graphene, the resonant frequency of the sensor can be effectively tuned. Notably, due to the rotational symmetry of the structure, the sensor shows insensitivity to transverse magnetic and transverse electric polarizations of incident light. By varying the refractive index of surrounding analytes, the sensor’s sensitivity and Figure of Merit (FOM) are studied. The sensitivities of the three resonance peaks are 0.59, 1.19, and 1.38 THz/RIU, with corresponding FOM values of 2.57, 3.40, and 6.58, respectively. Furthermore, the feasibility and effectiveness of the designed sensor in practical applications are verified by testing five types of samples. These findings indicate that the proposed sensor has superior performance in sensitivity and selectivity, which makes it have a great potential for applications in the fields of material characterization, environmental monitoring, and biomedicine detection in the terahertz band.
Driver at 10 MJ and 1 shot/30 min for inertial confinement fusion at high gain: Efficient, compact, low-cost, low laser–plasma instabilities, beam color selectable from 2ω/3ω/4ω, applicable to multiple laser fusion schemes
Authors: Sui Zhan , Lan Ke 
Published: June 2024

The achievement of ignition at the National Ignition Facility (NIF) has prompted a global wave of further research on inertial fusion energy (IFE). However, IFE requires a target gain G of 30–100, and it is hard to achieve fusion at such high gain with the energy, configuration, and technical approach of the NIF. Here, we present a conceptual design for a next-generation laser driver that is applicable to multiple laser fusion schemes and provides 10 MJ, 2–3 PW at 3ω (or 2ω, in which case the energy and power can be higher), and one shot per 30 min, with the aim of achieving G &gt; 30. It is also efficient, compact, and low in cost, and it has low susceptibility to laser–plasma instabilities.
The mechanical properties of bettong and potoroo foods
Authors: Mitchell D. Rex , Ledogar Justin A. , Andrew Damien , Mathewson Ian , Weisbecker Vera , Vernes Karl 
Published: June 2024

Potoroid marsupials (bettongs and potoroos of the family Potoroidae) are considered ecosystem engineers because of the roles they play in maintaining biodiversity. However, severe declines since European arrival have necessitated intense conservation efforts. Vital to these efforts is an understanding of the physical challenges that define their niches. The mechanical properties of their foods, such as toughness and stiffness, represent a physical interface with the environment that can contribute to quantitatively defining their niches. Here, we provide mechanical property data from wild bettong and potoroo foods, such as roots and tubers, fruit, fungi, invertebrates, seeds, and leaves. Toughness ranged from approximately 56.58 J/m2 (fungal sporocarp of Descolea sp.) to 2568.15 J/m2 (tubers of the blue yam, Brunoniella australis). Similarly, stiffness of the wild foods ranged from 1.15 MPa for Descolea sp. to 30.4 MPa for B. australis. However, the mechanical demands of accessing the kernels from within the shells (testae) of sandalwood and quandong (Santalum spp.) seeds far exceed measurements of any foods tested. We also tested some farmed foods, alongside inclusion of data from previous studies. Taken together, these data can also improve selection of comparable foods in designing diets for potoroids, and other species, in captivity.
Induced magneto-conductivity in a two-nodeWeyl semimetal under Gaussian random disorder
Authors: Xu 徐 Chuanxiong 川雄 , Yu 于 Haoping 昊平 , Zhou 周 Mei 梅 , Ji 吉 Xuanting 轩廷 
Published: June 2024

Abstract
Measuring the magneto-conductivity induced from impurities may help determine the impurity distribution and reveal the structure of a Weyl semimetal sample. To verify this, we utilize the Gaussian random disorder to simulate charged impurities in a two-node Weyl semimetal model and investigate the impact of charged impurities on magneto-conductivity in Weyl semimetals. We first compute the longitudinal magnetic conductivity and find that it is positive and increases proportionally with the parameter governing the Gaussian distribution of charged impurities, suggesting the presence of negative longitudinal magneto-resistivity. Then we consider both the intra-valley and inter-valley scattering processes to calculate the induced transverse magneto-conductivity in the model. Our findings indicate that both inter-valley and intra-valley scattering processes play important roles in the transverse magneto-conductivity. The locations of Weyl nodes can also be determined by magneto-conductivity measurements. This is possible if the magnetic field strength and the density of charged impurities are known. Alternatively, the measurement of magnetic conductivity may reveal the distribution of charged impurities in a given sample once the locations of the Weyl nodes have been determined. These findings can aid in detecting the structure of a Weyl semimetal sample, enhancing comprehension of magnetotransport in Weyl semimetals and promoting the development of valley electronics.
Data-driven models in fusion exhaust: AI methods and perspectives
Authors: Wiesen S. , Dasbach S. , Kit A. , Jaervinen A.E. , Gillgren A. , Ho A. , Panera A. , Reiser D. , Brenzke M. , Poels Y. , Westerhof E. , Menkovski V. , Derks G.F. , Strand P. 
Published: June 2024

Abstract
A review is given on the highlights of a scatter-shot approach of developing machine-learning methods and artificial neural networks based fast predictors for the application to fusion exhaust. The aim is to enable and facilitate optimized and improved modeling allowing more flexible integration of physics models in the light of extrapolations towards future fusion devices. The project encompasses various research objectives: (a) developments of surrogate model predictors for power & particle exhaust in fusion power plants; (b) assessments of surrogate models for time-dependent phenomena in the plasma-edge; (c) feasibility studies of micro–macro model discovery for plasma-facing components surface morphology & durability; and (d) enhancements of pedestal models & databases through interpolators and generators exploiting uncertainty quantification. Presented results demonstrate useful applications for machine-learning and artificial intelligence in fusion exhaust modeling schemes, enabling an unprecedented combination of both fast and accurate simulation.
The effects of common reservoirs on the performance of a quantum refrigerator
Authors: Liu Yue , Yan Wei-Bin , Xia Yun-Jie , Man Zhong-Xiao 
Published: June 2024

Abstract
In this work, we study and find that the performance of an autonomous refrigerator can be improved by means of collective dissipations of common reservoirs. The refrigerator is based on a four-level system with two degenerate levels, coupled to three thermal reservoirs with different temperatures. Our study reveals that utilizing only one common reservoir can not significantly enhance the refrigerator’s performance. However, when two reservoirs are shared simultaneously, the performance improvement becomes more evident. Furthermore, we find that the refrigerator’s performance can be further enhanced by operating in a regime where the decoherence-free subspace is present. Our results indicate that careful engineering is essential to maximize the benefits of common reservoirs in enhancing the performance of quantum thermal machines.
Switchable image displays in tri-channel phase-change metasurfaces
Authors: Wang Bo , Li Yifan , Cui Yilong , Xiang Chenxuan , Guo Kenan , Xiao Shuyuan , Liu Tingting 
Published: June 2024

Abstract
Optical metasurfaces enable to manipulate light fields across multiple physical dimensions, significantly enhancing information density, security, and system integration. Here, we propose a general platform of multi-functional phase-change metasurfaces for dynamic image displays in the visible range, enabled by active manipulation of optical spectrum, amplitude, and phase, leading to threefold dynamic exhibition functions. Through elaborately encoding the tri-channel information using a single-cell metasurface composed of

Sb
2

S
3

nanobricks, three distinct functions are integrated and the flexibility of dynamic switch is allowed. Leveraging the tunable properties of

Sb
2

S
3

between amorphous and crystalline states, the switchable displays are realized, including a structural-color image, and grayscale and holographic images with independent-encryption polarization freedom. The proposed metasurfaces open new avenues in multi-functional meta-devices for optical storage, displays, and security applications.
An EPR study of point defects in zinc oxide thin films
Authors: Heydari Jinan Fadel Mohammad Ali , Yükselici Mehmet Hikmet 
Published: June 2024

Abstract
We studied ZnO thin films deposited on glass slides by thermal evaporation in vacuum followed by heat treatment in open air or Ar flow. The samples were characterized using x-ray diffraction, Raman scattering, photoluminescence (PL), and electron paramagnetic resonance (EPR) spectroscopy. We observed a broad PL band in the visible region at spectral positions of 504 and 560 nm and a low-intensity band in the UV region at 390 nm. The EPR spectra display a clear first derivative structure at

g
=
1.96

at temperatures below 200 K. The PL spectrum shows red-shifted valence to conduction band emission due to electron hole recombination through shallow surface states. We found an activation energy of E

a
= 4.2 meV using the Arrhenius plot and estimated concentrations of paramagnetic defects and spin–spin relaxation time constants of 1016 m−3 and 10–14 s, respectively.
Multi-qubit dynamical decoupling for enhanced crosstalk suppression
Authors: Niu Siyuan , Todri-Sanial Aida , Bronn Nicholas T 
Published: June 2024

Abstract
Dynamical decoupling (DD) is one of the simplest error suppression methods, aiming to enhance the coherence of qubits in open quantum systems. Moreover, DD has demonstrated effectiveness in reducing coherent crosstalk, one major error source in near-term quantum hardware, which manifests from two types of interactions. Static crosstalk exists in various hardware platforms, including superconductor and semiconductor qubits, by virtue of always-on qubit-qubit coupling. Additionally, driven crosstalk may occur as an unwanted drive term due to leakage from driven gates on other qubits. Here we explore a novel staggered DD protocol tailored for multi-qubit systems that suppresses the decoherence error and both types of coherent crosstalk. We develop two experimental setups—an ‘idle–idle’ experiment in which two pairs of qubits undergo free evolution simultaneously and a ‘driven-idle’ experiment in which one pair is continuously driven during the free evolution of the other pair. These experiments are performed on an IBM Quantum superconducting processor and demonstrate the significant impact of the staggered DD protocol in suppressing both types of coherent crosstalk. When compared to the standard DD sequences from state-of-the-art methodologies with the application of X2 sequences, our staggered DD protocol enhances circuit fidelity by 19.7% and 8.5%, respectively, in addressing these two crosstalk types.
Economic and environmental assessment of the Korea urban railway and its greenhouse gas mitigation potential
Authors: Jeong Wonwoo , Park HyeMin 
Published: June 2024

Abstract
Railways can simultaneously transport large quantities of freight and passengers, making them energy-efficient and economical modes of transportation. Changing the materials that constitute a significant portion of rail track systems can help mitigate climate change. Gravel and concrete trackbed methods are commonly employed in railway construction. This study proposes the utilization of the asphalt concrete trackbed method, which is currently being researched and developed in South Korea, in addition to traditional gravel and cement concrete methods, and presents its economic feasibility and environmental benefits. The asphalt concrete trackbed method, which has already been implemented in regions such as China, Australia, and Europe, can also be applied in other areas. This study analyzed the carbon emissions and economic feasibility in the construction, usage, and disposal stages of cement concrete and asphalt concrete trackbeds. Previous research on carbon emissions analysis has faced challenges in applying geographical and climatic, as well as energy sources, to individual cases in the context of construction in Korea. Using the Korean Life Cycle Inventory database, this study indicated that asphalt concrete exhibits approximately 2.65-times lower carbon emissions than cement concrete. In Korea, railway construction involves 1,998 tons of asphalt concrete mixture, 1,820 cubic meters of cement concrete, and 59 tons of rebar per kilometer. Furthermore, the asphalt concrete trackbed method shows potential cost savings of approximately 29,000 EUR when converted to the 2021 EAU value. Thus, asphalt concrete trackbeds not only provide environmental benefits, they are also economically viable. However, further research is required to establish precise standards for on-site construction. This study is expected to provide foundational data for promoting the widespread adoption of asphalt concrete trackbeds in areas that produce asphalt concrete.