Thermal resistance from non-equilibrium phonons at Si-Ge interface

As nanostructured devices become prevalent, interfaces often play an important role in thermal transport phenomena. However, interfacial thermal transport remains poorly understood due to complex physics across a wide range of length scales from atomistic to microscale. Past studies on interfacial thermal resistance have focused on interface-phonon scattering at the atomistic scale but overlooked the complex interplay of phonon-interface and phonon-phonon scattering at microscale. Here, we use the Peierls-Boltzmann transport equation to show that the resistance from the phonon-phonon scattering of non-equilibrium phonons near a Si-Ge interface is much larger than that directly caused by the interface scattering. We report that non-equilibrium in phonon distribution leads to significant entropy generation and thermal resistance upon three-phonon scattering by the Boltzmann's H-theorem. The physical origin of non-equilibrium phonons in Ge is explained with the mismatch of phonon dispersion, density-of-states, and group velocity, which serve as general guidance for estimating the non-equilibrium effect on interfacial thermal resistance. Our study bridges a gap between atomistic scale and less studied microscale phenomena, providing comprehensive understanding of overall interfacial thermal transport and the significant role of phonon-phonon scattering

Chinese language promotion : a language ecology perspective and analysis of language policy and planning in the USA, Australia, and Singapore

Along with the rapid development of China’s economy and national strength in recent years, the Chinese government places increased importance on the cultivation of soft power, through which hoping to enhance China’s influence. One of the measures is to vigorously promote Chinese language to the world. However, Chinese language promotion worldwide is a vast complex project. In order to obtain effective promotion results, it demands multi-disciplinary support. Based on relevant theories of language ecology and language policy and planning (LPP), I select three countries, namely the USA, Australia, and Singapore, to investigate Chinese use situation within them and accordingly raise some promotion suggestions, in hope of providing reference value for promoting Chinese elsewhere in the world. Beginning with stating research questions and research design and explaining the ways and the pros and cons of data collection, my thesis then introduces the theoretical framework of language ecology and LPP, including the definition, early development, and relation to my research. Then, the thesis describes some background knowledge on Chinese language, clarifies some basic concepts, and introduces the transformation from Teaching Chinese as a Foreign Language (TCFL) to International Promotion of Chinese Language (IPCL) from a historical perspective in modern times, particularly since the founding of the People’s Republic of China. The next three chapters focus on the in-depth analysis of Chinese usage in the USA, Australia, and Singapore respectively, specifically on the basis of the three countries’ demographic structure, Chinese immigrants, languages and household language use, Chinese learning in local education system, and influential LPP. The final conclusion part summarizes lessons learned and concludes with suggestions that could help achieve better results of Chinese language promotion in the three countries

Digital transition and the clean renewable energy adoption in rural family: evidence from Broadband China

IntroductionThe increasing digital transformation and the global need for sustainable energy solutions have sparked considerable interest in the examination of digital technologies' impact on the adoption of clean renewable energy. However, limited research focuses on energy consumption in rural households, especially in developing countries such as China.MethodsThis study leverages the quasi-natural experiment provided by the Broadband China Policy (BCP) and utilizes data from the China Labor-force Dynamics Survey (CLDS) spanning 2012 to 2016. Our investigation aims to understand the effect of the digital transition on the adoption of clean renewable energy within rural families. We employ staggered Difference-in-Difference (DID) and Doubly Robust Staggered DID estimators to assess this impact, allowing us to explore regional heterogeneity.ResultsOur findings reveal that implementing the BCP significantly influences clean renewable energy adoption, although this effect varies across different regions. Specifically, in the middle region, the BCP results in a notable 5.8% increase in clean renewable energy adoption compared to non-pilot cities. However, in the east and west regions, the BCP is associated with a decrease of 12.6% and 13.5%, respectively, in clean renewable energy adoption. Dynamic effect analysis further indicates that the east region had already experienced high clean renewable energy adoption prior to the BCP's implementation, while the BCP positively influences clean renewable energy intentions in the west region.DiscussionOur analysis identifies three significant channels through which the BCP affects clean renewable energy adoption: population size, economic size, and income level. Larger populations and greater economic size enhance the BCP's impact on clean renewable energy adoption. These findings provide empirical evidence for developing countries that seek to harness digital development for technological advancement, industrial upgrading, and carbon emission reduction

Nickel Nitride Particles Supported on 2D Activated Graphene–Black Phosphorus Heterostructure: An Efficient Electrocatalyst for the Oxygen Evolution Reaction

Hydrogen is regarded as the most promising green clean energy in the 21st century. Developing the highly efficient and low‐cost electrocatalysts for oxygen evolution reaction (OER) is of great concern for the hydrogen industry. In the water electrolyzed reaction, the overpotential and the kinetics are the main hurdles for OER. Therefore, an efficient and durable oxygen evolution reaction electrocatalyst is required. In this study, an activated graphene (AG)–black phosphorus (BP) nanosheets hybrid is fabricated for supporting Ni3N particles (Ni3N/BP‐AG) in the application of OER. The Ni3N particles are combined with the BP‐AG heterostructure via facile mechanical ball milling under argon protection. The synthesized Ni3N/BP‐AG shows excellent catalytic performance toward the OER, demanding the overpotential of 233 mV for a current density of 10 mA cm−2 with a Tafel slope of 42 mV dec−1. The Ni3N/BP‐AG catalysts also show remarkable stability with a retention rate of the current density of about 86.4% after measuring for 10 000 s in potentiostatic mode.A black phosphorus (BP)–activated graphene (AG) heterostructure is designed for supporting nickel nitride (Ni3N) to enhance the performance of oxygen evolution reaction (OER). The Ni3N/BP‐AG exhibits excellent electrocatalytic performance toward OER with low overpotential and small Tafel slope. It also shows remarkable stability with a retention rate of ≈86.4% OER activity after 10 000 s.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152804/1/smll201901530.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/152804/2/smll201901530_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/152804/3/smll201901530-sup-0001-S1.pd

Image Super-Resolution using Efficient Striped Window Transformer

Transformers have achieved remarkable results in single-image super-resolution (SR). However, the challenge of balancing model performance and complexity has hindered their application in lightweight SR (LSR). To tackle this challenge, we propose an efficient striped window transformer (ESWT). We revisit the normalization layer in the transformer and design a concise and efficient transformer structure to build the ESWT. Furthermore, we introduce a striped window mechanism to model long-term dependencies more efficiently. To fully exploit the potential of the ESWT, we propose a novel flexible window training strategy that can improve the performance of the ESWT without additional cost. Extensive experiments show that ESWT outperforms state-of-the-art LSR transformers, and achieves a better trade-off between model performance and complexity. The ESWT requires fewer parameters, incurs faster inference, smaller FLOPs, and less memory consumption, making it a promising solution for LSR.Comment: SOTA lightweight super-resolution transformer. 8 pages, 9 figures and 6 tables. The Code is available at https://github.com/Fried-Rice-Lab/FriedRiceLa

Glucose metabolism reprogramming promotes immune escape of hepatocellular carcinoma cells

Hepatocellular carcinoma (HCC) is a complex process that plays an important role in its progression. Abnormal glucose metabolism in HCC cells can meet the nutrients required for the occurrence and development of liver cancer, better adapt to changes in the surrounding microenvironment, and escape the attack of the immune system on the tumor. There is a close relationship between reprogramming of glucose metabolism and immune escape. This article reviews the current status and progress of glucose metabolism reprogramming in promoting immune escape in liver cancer, aiming to provide new strategies for clinical immunotherapy of liver cancer

Constant Light Exposure Alters Gut Microbiota and Promotes the Progression of Steatohepatitis in High Fat Diet Rats

Background: Non-alcoholic fatty liver disease (NAFLD) poses a significant health concern worldwide. With the progression of urbanization, light pollution may be a previously unrecognized risk factor for NAFLD/NASH development. However, the role of light pollution on NAFLD is insufficiently understood, and the underlying mechanism remains unclear. Interestingly, recent studies indicate the gut microbiota affects NAFLD/NASH development. Therefore, the present study explored effects of constant light exposure on NAFLD and its related microbiotic mechanisms. Material and method: Twenty-eight SD male rats were divided into four groups (n=7 each): rats fed a normal chow diet, and exposed to standard light-dark cycle (ND-LD); rats fed a normal chow diet, and exposed to constant light (ND-LL); rats fed a high fat diet, and exposed to standard light-dark cycle (HFD-LD); and rats on a high fat diet, and exposed to constant light (HFD-LL). Body weight, hepatic pathophysiology, gut microbiota, and short/medium chain fatty acids in colon contents, serum lipopolysaccharide (LPS) and liver LPS-binding protein (LBP) mRNA expression were documented post intervention and compared among groups. Result: In normal chow fed groups, rats exposed to constant light displayed glucose abnormalities and dyslipidemia. In HFD-fed rats, constant light exposure exacerbated glucose abnormalities, insulin resistance, inflammation and liver steatohepatitis. Constant light exposure altered composition of gut microbiota in both normal chow and HFD fed rats. Compared with HFD-LD group, HFD-LL rats displayed less Butyricicoccus, Clostridium and Turicibacter, butyrate levels in colon contents, decreased colon expression of occludin-1 and zonula occluden‐1 (ZO-1) , and increased serum LPS and liver LBP mRNA expression. Conclusion: Constant light exposure impacts gut microbiota and its metabolic products, impairs gut barrier function and gut-liver axis, promotes NAFLD/NASH progression in HFD rats

On the Circular Polarisation of Repeating Fast Radio Bursts

Fast spinning (e.g., sub-second) neutron star with ultra-strong magnetic fields (or so-called magnetar) is one of the promising origins of repeating fast radio bursts (FRBs). Here we discuss circularly polarised emissions produced by propagation effects in the magnetosphere of fast spinning magnetars. We argue that the polarisation-limiting region is well beyond the light cylinder, suggesting that wave mode coupling effects are unlikely to produce strong circular polarisation for fast spinning magnetars. Cyclotron absorption could be significant if the secondary plasma density is high. However, high degrees of circular polarisation can only be produced with large asymmetries in electrons and positrons. We draw attention to the non-detection of circular polarisation in current observations of known repeating FRBs. We suggest that the circular polarisation of FRBs could provide key information on their origins and help distinguish different radiation mechanisms.Comment: ApJ accepte

Individual tree-based forest species diversity estimation by classification and clustering methods using UAV data

Monitoring forest species diversity is essential for biodiversity conservation and ecological management. Currently, unmanned aerial vehicle (UAV) remote sensing technology has been increasingly used in biodiversity monitoring due to its flexibility and low cost. In this study, we compared two methods for estimating forest species diversity indices, namely the spectral angle mapper (SAM) classification approach based on the established species-spectral library, and the self-adaptive Fuzzy C-Means (FCM) clustering algorithm by selected biochemical and structural features. We conducted this study in two complex subtropical forest areas, Mazongling (MZL) and Gonggashan (GGS) National Nature Forest Reserves using UAV-borne hyperspectral and LiDAR data. The results showed that the classification method performed better with higher values of R2 than the clustering algorithm for predicting both species richness (0.62 > 0.46 for MZL and 0.55 > 0.46 for GGS) and Shannon-Wiener index (0.64 > 0.58 for MZL, 0.52 > 0.47 for GGS). However, the Simpson index estimated by the classification method correlated less with the field measurements than the clustering algorithm (R2 = 0.44 and 0.83 for MZL and R2 = 0.44 and 0.62 for GGS). Our study demonstrated that the classification method could provide more accurate monitoring of forest diversity indices but requires spectral information of all dominant tree species at individual canopy scale. By comparison, the clustering method might introduce uncertainties due to the amounts of biochemical and structural inputs derived from the hyperspectral and LiDAR data, but it could acquire forest diversity patterns rapidly without distinguishing the specific tree species. Our findings underlined the advantages of UAV remote sensing for monitoring the species diversity in complex forest ecosystems and discussed the applicability of classification and clustering methods for estimating different individual tree-based species diversity indices