Coherence-Assisted Superradiant Laser with Hz Linewidth and 10−1010^{-10}W Power

The superradiant laser, based on the clock transition between the electric ground state $^1$S$_0$ and the metastable state $^3$P$_0$ of fermionic alkaline-earth(-like) atoms, has been proposed to be a new promising light source with linewidth being the order of millihertz. However, due to the small $^1$S$_0$-to-$^3$P$_0$ transition strength, the steady-state power in that system is relatively low ($\sim 10^{-12}$W). In this work, we propose an alternative superradiant laser scheme based on a Raman-transition-induced coupling between the $^3$P$_0$ and $^3$P$_1$ states in bosonic alkaline-earth(-like) atoms, and achieve a laser with linewidth $\lesssim 2\pi\times1$Hz and power $\gtrsim 10^{-10}$W ($\sim 10^{3}$ photons in steady state) at a small pumping cost. The Raman beams play two significant roles in our scheme. First, the coherence between the dark and bright states induced by the Raman beams produce a new local minimum in the pumping-linewidth curve with pumping rate lower than $2\pi \times 10$kHz, which is beneficial for continuous output. Second, the Raman beams mix the long-lived $^3$P$_0$ state into the lasing state and thus reduce the linewidth. Our work greatly improves the output performance of the superradiant laser system with coherence induced by Raman transitions and may offer a firm foundation for its practical use in future

SaaFormer: Spectral-spatial Axial Aggregation Transformer for Hyperspectral Image Classification

Hyperspectral images (HSI) captured from earth observing satellites and aircraft is becoming increasingly important for applications in agriculture, environmental monitoring, mining, etc. Due to the limited available hyperspectral datasets, the pixel-wise random sampling is the most commonly used training-test dataset partition approach, which has significant overlap between samples in training and test datasets. Furthermore, our experimental observations indicates that regions with larger overlap often exhibit higher classification accuracy. Consequently, the pixel-wise random sampling approach poses a risk of data leakage. Thus, we propose a block-wise sampling method to minimize the potential for data leakage. Our experimental findings also confirm the presence of data leakage in models such as 2DCNN. Further, We propose a spectral-spatial axial aggregation transformer model, namely SaaFormer, to address the challenges associated with hyperspectral image classifier that considers HSI as long sequential three-dimensional images. The model comprises two primary components: axial aggregation attention and multi-level spectral-spatial extraction. The axial aggregation attention mechanism effectively exploits the continuity and correlation among spectral bands at each pixel position in hyperspectral images, while aggregating spatial dimension features. This enables SaaFormer to maintain high precision even under block-wise sampling. The multi-level spectral-spatial extraction structure is designed to capture the sensitivity of different material components to specific spectral bands, allowing the model to focus on a broader range of spectral details. The results on six publicly available datasets demonstrate that our model exhibits comparable performance when using random sampling, while significantly outperforming other methods when employing block-wise sampling partition.Comment: arXiv admin note: text overlap with arXiv:2107.02988 by other author

Electrocatalytic Refinery toward Green Production of Chemicals through N2 and CO2 Electroreduction

The depletion of fossil fuels and rapid environmental deterioration call for the development of clean and sustainable energy supplies for the future. Recently, the electrocatalytic refinery (e-refinery) is emerging as a more sustainable and environmentally benign strategy to harness renewable energy for the production of value-added chemicals. As the second most produced chemical in the world, ammonia has played a significant role in agriculture and chemical engineering, and now severs as one promising medium for hydrogen storage, due to its higher energy density. Thus, exploration of strategies to produce ammonia (NH3) powered by renewable energy with decreased carbon emissions has raised widespread interests among researchers. Up till now, two main routes with lower carbon emission levels have been proposed: (1) steam methane reforming coupled Haber-Bosch process (SMR-HB) with carbon capture and storage technologies (SMR-HB + CCS) and (2) direct electrocatalytic nitrogen (N2) reduction reaction (NRR) in aqueous conditions. For the CCS, electrocatalytic reduction of carbon dioxide (CO2) to other carbonaceous products is regarded as the highly effective pathway. However, the difficulty to achieve these two routes is to develop electrocatalysts for effective activation and conversion of the reactants (like N2 and CO2). Therefore, this Thesis aims to design and synthesize novel nanostructured materials as efficient electrocatalysts for N2 and CO2 reduction reactions. In conjunction with the electrocatalyst engineering, detailed investigations on catalyst “structure-to-performance” correlations are also elaborated to guide the design of catalysts for future applications in other fields. In this Thesis, a systematic review on the roadmap towards electrocatalytic green NH3 production is provided (Chapter 2). This chapter critically evaluates the challenges of NRR and discusses several emerging strategies for green ammonia synthesis beyond conventional catalyst design and engineering, including electrocatalytic nitrogen oxidation, electrocatalytic nitrate reduction, bioelectrocatalysis and redox-mediated electrocatalysis. The first study of this Thesis (Chapter 3) focuses on a comprehensive and accurate evaluation of NRR performance by employing in situ fragmented bismuth nanoparticles as a promising candidate for ambient NRR. NRR performance is rigorously evaluated in both neutral and acid electrolyte through ionic chromatograph and isotope labelling testing. Online differential electrochemical mass spectrometry (DEMS) detects the production of NH3 and N2H2 during NRR, suggesting a possible pathway through two-step reduction and decomposition. The second section of this Thesis (Chapter 4 and 5) explores novel strategies for efficient CO2 fixation to produce value-added chemicals via electrocatalytic CO2 reduction (CRR). In/ex situ characterizations unravel the in-depth understanding on the complicated surface reconstruction of Bi-MOFs under CRR conditions, which can be controlled using electrolyte and potential mediation. The intentionally reconstructed Bi catalyst exhibits excellent activity and selectivity for formate production. It is also revealed that unsaturated surface Bi atoms are formed during reconstruction and become the active sites. The optimized CO2-to-CO performance is achieved on the asymmetric dual-atom NiCu catalysts which are distributed within threshold distance on the N-doped graphene. The simulation results and electrocatalytic experiments unravel the inter-metal interaction with a threshold effect. The random distribution algorithm and mathematical modelling establish the relationship between diatomic distance and metal loading amount, benefiting the design of dual-atom catalysts for other electrocatalytic reactions and applications. In the third part of this Thesis (Chapter 6), a simple and straightforward strategy based on the “adsorption-sonication” route is developed for the synthesis of noblemetal single atom catalysts (SACs) on C3N4, including Pd, Pt, Ag, and Au. It is found the Pt SACs on the C3N4 (Pt-CN) exhibit promising electrocatalytic nitrate reduction for ammonia production. The Pt-CN achieves the maximized FE for ammonia of 80.42% at 0.45 V versus reversible hydrogen electrode (vs RHE) and the highest ammonia yield of 10.65 μmol cm2 h1 at 0.8 V in 0.1 M KNO3/0.5 M K2SO4 electrolyte. This work deepens the understanding of the growth mechanism of SACs, explores some new insights into employing traditional wet chemistry in SACs preparation, and also paves the way for their future industrial production and application.Thesis (Ph.D.) -- University of Adelaide, School of Chemical Engineering and Advanced Materials, 202

The Hidden Integration of Eurasia: East-West Relations in the History of Technology

“East” and “West” have long been prominent categories in the history of technology. The historical literature that claims to deal with comparisons or connections between East and West from a technological point of view is rich and fascinating. Yet, so far there has been no attempt to succinctly summarize or synthesize the main findings. This article takes a first step towards such a synthesis. It does so by addressing technological interaction between three broadly defined geographical regions: (1) Western Europe and North America; (2) Eastern Europe, Russia and Central Asia; and (3) the non-Russian Far East. The article suggests that East–West studies in the history of technology can be divided into three sets, which would benefit from greater interaction with each other: studies of East–West and West– East technology transfer; studies comparing the evolution of Eastern and Western technological levels and technological “styles”; and studies of large technical systems that materially interconnect East and West

Transforming the Narrative of the History of Chinese Technology: East and West in Bertrand Gille’s Histoire des Techniques

In his magisterial The History of Techniques, the French historian of technology Bertrand Gille (1920–1980) constructs a Western-centric world history of technology based on a technical systems approach. In doing so, he is forced to deal with the tension between Western-centric approaches and the conventional narrative of the history of Chinese technology. In order to avoid internal contradictions within his world history framework, Gille reconfigures the historical narrative about ancient China’s great inventions, arguing against unidirectional technology transfer and introducing the alternative notions of technological concomitant evolution and technological exchange. While Gille integrates ancient China into the general technological development of the world, he treats China as a blocked technical system and as “the other” in the West’s technological self-perception

Factors influencing sleep disturbances among spouse caregivers of cancer patients in Northeast China.

BACKGROUND: In China, spouse caregivers of cancer patients (SCCPs) are involved in all aspects of patient care and experience psychological distress which could result in sleep disturbance and fatigue. However, few studies have explored the differences between SCCPs and the general population, or what factors affect SCCPs' sleep. This study aims to (1) Compare the differences in sleep disturbances and fatigue severity between SCCPs and the age- and gender-matched general population, and (2) Identify selected personal characteristics, including coping style that affect sleep disturbances in SCCPs. METHODOLOGY/PRINCIPAL FINDINGS: The Stress and Coping Model was used to guide this study. Participants were recruited from the northeast part of China and included 600 people from the general population and 300 SCCPs. Participants completed a socio-demographic form, Fatigue Scale-14, trait Coping Style Questionnaire, and Symptom Checklist-90. RESULTS: The majority of the participants were middle age, most of whom (78.7%) spent more than 8 hours each day taking care of their spouses. Compared to the general population, the SCCPs experienced significant sleep disturbances with a mean of 7.30 (SD = 1.27), and fatigue severity with a mean of 8.11 (SD = 3.25). Among the selected SCCPs' personal characteristics, current poor health status (β = 0.14, P<0.001), having a spouse under mixed treatment (β = 0.13, p<0.001), and financial burden (β = 0.14, P<0.001) are the significant predictors for sleep disturbances. Positive coping is the predictor for fewer sleep disturbances (β = 0.27, P<0.001). Those who reported sleep disturbances also experienced higher physical and mental fatigue severity (P<0.001). CONCLUSION: Intervention to improve coping style in SCCPs is needed. Further research is also needed to explore the other mediators and moderators that regulate sleep disturbance and health outcomes in the SCCPs

Support for Situation-Awareness in Trustworthy Ubiquitous Computing Application Software

Due to the dynamic and ephemeral nature of ubiquitous computing (ubicomp) environments, it is especially important that the application software in ubicomp environments is trustworthy. In order to have trustworthy application software in ubicomp environments, situation-awareness (SAW) in the application software is needed for enforcing flexible security policies and detecting violations of security policies. In this paper, an approach is presented to providing development and runtime support for incorporating SAW in trustworthy ubicomp application software. The development support is to provide SAW requirement specification and automated code generation for achieving SAW in trustworthy ubicomp application software, and the runtime support is for context acquisition, situation analysis, and situation-aware communication. To realize our approach, the improved Reconfigurable Context-Sensitive Middleware (RCSM) is developed for providing the above development and runtime support. Keywords: Trustworthy ubiquitous application software, situation-awareness, Situation-Aware Interface Definition Language (SA-IDL), Situation-Aware (SA) middleware, SA security policies, development and runtime support

A Fractional-Order Telegraph Diffusion Model for Restoring Texture Images with Multiplicative Noise

Multiplicative noise removal from texture images poses a significant challenge. Different from the diffusion equation-based filter, we consider the telegraph diffusion equation-based model, which can effectively preserve fine structures and edges for texture images. The fractional-order derivative is imposed due to its textural detail enhancing capability. We also introduce the gray level indicator, which fully considers the gray level information of multiplicative noise images, so that the model can effectively remove high level noise and protect the details of the structure. The well-posedness of the proposed fractional-order telegraph diffusion model is presented by applying the Schauder’s fixed-point theorem. To solve the model, we develop an iterative algorithm based on the discrete Fourier transform in the frequency domain. We give various numerical results on despeckling natural and real SAR images. The experiments demonstrate that the proposed method can remove multiplicative noise and preserve texture well

Effects of Elevated CO2 Concentration and Nitrogen Addition on Soil Respiration in a Cd-Contaminated Experimental Forest Microcosm

Forests near rapidly industrialized and urbanized regions are often exposed to elevated CO2, increased N deposition, and heavy metal pollution. To date, the effects of elevated CO2 and/or increased N deposition on soil respiration (Rs) under heavy metal contamination are unclear. In this study, we firstly investigated Rs in Cd-contaminated model forests with CO2 enrichment and N addition in subtropical China. Results showed that Rs in all treatments exhibited similar clear seasonal patterns, with soil temperature being a dominant control. Cadmium addition significantly decreased cumulative soil CO2 efflux by 19% compared to the control. The inhibition of Rs caused by Cd addition was increased by N addition (decreased by 34%) was partially offset by elevated CO2 (decreased by 15%), and was not significantly altered by the combined N addition and rising CO2. Soil pH, microbial biomass carbon, carbon-degrading hydrolytic enzymes, and fine root biomass were also significantly altered by the treatments. A structural equation model revealed that the responses of Rs to Cd stress, elevated CO2, and N addition were mainly mediated by soil carbon-degrading hydrolytic enzymes and fine root biomass. Overall, our findings indicate that N deposition may exacerbate the negative effect of Cd on Rs in Cd-contaminated forests and benefit soil carbon sequestration in the future at increasing atmospheric CO2 levels