The recent discovery of superconductivity in pressurized bilayer nickelate La_(3)Ni_(2)O_(7) has triggered tremendous research ***,the experimentally observed oxygen deficiency implies that obtaining perfect stoichiom...
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The recent discovery of superconductivity in pressurized bilayer nickelate La_(3)Ni_(2)O_(7) has triggered tremendous research ***,the experimentally observed oxygen deficiency implies that obtaining perfect stoichiometric single crystals is still *** influence of oxygen deficiency on physical properties remains ***,we construct a chemical potential phase diagram to characterize the stability of La_(3)Ni_(2)O_(7).The narrow stable region explains the difficulty of synthesizing pure ***,oxygen defect studies reveal that the interlayer apical oxygen vacancy has the highest defect concentrations and is responsible for oxygen ***,unfolding band structures show as the oxygen-deficient variant increases,Ni 3d_(z^(2)) bands shift toward a lower energy position under the Fermi level at Γ point,which is adverse to the metallization of Ni 3d_(z^(2)) ***,high-pressure calculations indicate that oxygen vacancy would destroy the hybridization of interlayer Ni 3d_(z^(2)) orbitals,and the larger the oxygen deficiency,the higher the pressure needed to metalize the Ni 3d_(z^(2))***,the oxygen deficiency would suppress the emergence of superconductivity in La_(3)Ni_(2)O_(7–δ).Our results elucidate the mechanism of oxygen deficiency for superconductivity in La_(3)Ni_(2)O_(7–δ) and provide instructive guidance to the experimental research.
Background With the development of the Internet,the topology optimization of wireless sensor networks has received increasing ***,traditional optimization methods often overlook the energy imbalance caused by node loa...
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Background With the development of the Internet,the topology optimization of wireless sensor networks has received increasing ***,traditional optimization methods often overlook the energy imbalance caused by node loads,which affects network *** To improve the overall performance and efficiency of wireless sensor networks,a new method for optimizing the wireless sensor network topology based on K-means clustering and firefly algorithms is *** K-means clustering algorithm partitions nodes by minimizing the within-cluster variance,while the firefly algorithm is an optimization algorithm based on swarm intelligence that simulates the flashing interaction between fireflies to guide the search *** proposed method first introduces the K-means clustering algorithm to cluster nodes and then introduces a firefly algorithm to dynamically adjust the *** The results showed that the average clustering accuracies in the Wine and Iris data sets were 86.59%and 94.55%,respectively,demonstrating good clustering *** calculating the node mortality rate and network load balancing standard deviation,the proposed algorithm showed dead nodes at approximately 50 iterations,with an average load balancing standard deviation of 1.7×10^(4),proving its contribution to extending the network *** This demonstrates the superiority of the proposed algorithm in significantly improving the energy efficiency and load balancing of wireless sensor networks to extend the network *** research results indicate that wireless sensor networks have theoretical and practical significance in fields such as monitoring,healthcare,and agriculture.
Aerosol hygroscopicity and liquid water content(ALWC)have important influences on the environmental and climate effect of *** this study,we measured the hygroscopic growth factors(GF)of particles with dry diameters of...
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Aerosol hygroscopicity and liquid water content(ALWC)have important influences on the environmental and climate effect of *** this study,we measured the hygroscopic growth factors(GF)of particles with dry diameters of 40,80,150,and 200 nm during the wintertime in *** the GF-derived hygroscopicity parameter(κ_(gf))and ALWC increased with particle size,but displayed differing diurnal variations,withκ_(gf)peaking around the midday,while ALWC peaking in the early ***,ammonium and oxygenated organic aerosols(OOA)were found as the chemical components mostly strongly correlated with ALWC.A closure study suggests that during midday photo-oxidation and nighttime high ALWC periods,theκof organic aerosols(κ_(org))was underestimated when using previous ***,we re-constructed parameterizations forκ_(org)and the oxidation level of organics for these periods,which indicates a higher hygroscopicity of photochemically formed OOA than the aqueous OOA,yet both being much higher than the generally assumed OOA ***,in a typical high ALWC episode,concurrently increased ALWC,nitrate,OOA as well as aerosol surface area and mass concentrations were observed under elevated ambient *** strongly indicates a coupled effect that the hygroscopic secondary aerosols,in particular nitratewith strong hygroscopicity,led to large increase in ALWC,which in turn synergistically boosted nitrate and OOA formation by heterogeneous/aqueous *** interaction may represent an important mechanism contributing to enhanced formation of secondary aerosols and rapid growth of fine particulate matter under relatively high RH conditions.
Low-resource machine translation holds significant practical importance for the translation of small languages. Currently, the primary challenge in low-resource machine translation is the scarcity of bilingual paralle...
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Image captioning is a multimodal task that involves both computer vision and natural language processing. In recent years, to address the issue of insufficient visual information, multiple features are often used. How...
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With the rise of encrypted traffic,traditional network analysis methods have become less effective,leading to a shift towards deep learning-based *** these,multimodal learning-based classification methods have gained ...
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With the rise of encrypted traffic,traditional network analysis methods have become less effective,leading to a shift towards deep learning-based *** these,multimodal learning-based classification methods have gained attention due to their ability to leverage diverse feature sets from encrypted traffic,improving classification ***,existing research predominantly relies on late fusion techniques,which hinder the full utilization of deep features within the *** address this limitation,we propose a novel multimodal encrypted traffic classification model that synchronizes modality fusion with multiscale feature ***,our approach performs real-time fusion of modalities at each stage of feature extraction,enhancing feature representation at each level and preserving inter-level correlations for more effective *** continuous fusion strategy improves the model’s ability to detect subtle variations in encrypted traffic,while boosting its robustness and adaptability to evolving network *** results on two real-world encrypted traffic datasets demonstrate that our method achieves a classification accuracy of 98.23% and 97.63%,outperforming existing multimodal learning-based methods.
To address issues of missed detections and low accuracy in existing smoke detection algorithms when dealing with variable smoke patterns in small-scale objects and complex environments, FAR-YOLO was proposed as an enh...
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A knowledge graph (KG) is a form of representing knowledge of the objective world. With the expansion of knowledge, KGs frequently incorporate new entities, which often possess limited associated data, known as few-sh...
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The rapid development of neuromorphic computing has led to widespread investigation of artificial *** synapses can perform parallel in-memory computing functions while transmitting signals,enabling low-energy and fast...
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The rapid development of neuromorphic computing has led to widespread investigation of artificial *** synapses can perform parallel in-memory computing functions while transmitting signals,enabling low-energy and fast artificial *** are the most ideal endpoint for the application of artificial *** the human nervous system,there are different types of synapses for sensory input,allowing for signal preprocessing at the receiving ***,the development of anthropomorphic intelligent robots requires not only an artificial intelligence system as the brain but also the combination of multimodal artificial synapses for multisensory sensing,including visual,tactile,olfactory,auditory,and *** article reviews the working mechanisms of artificial synapses with different stimulation and response modalities,and presents their use in various neuromorphic *** aim to provide researchers in this frontier field with a comprehensive understanding of multimodal artificial synapses.
Human hand gesture recognition is important to human-computer interaction. Gesture recognition based on RGB and Depth (RGB-D) data exploits both RGB and depth images to provide comprehensive results. However, the rese...
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