Bottom partner B' and Zb production at the LHC

Some new physics models, such as "beautiful mirrors" scenario, predict the existence of the bottom partner $B'$. Considering the constraints from the data for the $Z\rightarrow b\bar{b}$ branching ratio $R_{b}$ and the $FB$ asymmetry $A_{FB}^{b}$ on the relevant free parameters, we calculate the contributions of $B'$ to the cross section $\sigma(Zb)$ and the $Z$ polarization asymmetry $A_{Z}$ for $Zb$ production at the $LHC$. We find that the bottom partner $B'$ can generate significant corrections to $\sigma(Zb)$ and $A_{Z}$, which might be detected in near future.Comment: 15 pages, 5 figures. Version published in Phys. Lett.

A Conceptual Framework for Data Property Protection Based on Blockchain

Blockchain is a new decentralized infrastructure and distributed computing paradigm. The blockchain technology has the characteristics of decentralization, time series data, collective maintenance, programmable and secure. This paper addresses the needs of China Mobile\u27s digital intellectual property protection and transaction, and uses the relevant design and technology in the blockchain to propose solutions and ideas for identity authentication and traceability of China Mobile\u27s digital intellectual property transactions. Finally, the design concept of blockchain architecture based on China Mobile digital intellectual property transaction is proposed

A Triple-Network Dynamic Connection Study in Alzheimer's Disease

© 2022 Meng, Wu, Liang, Zhang, Xu, Yang and Meng. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY). https://creativecommons.org/licenses/by/4.0/Alzheimer's disease (AD) was associated with abnormal organization and function of large-scale brain networks. We applied group independent component analysis (Group ICA) to construct the triple-network consisting of the saliency network (SN), the central executive network (CEN), and the default mode network (DMN) in 25 AD, 60 mild cognitive impairment (MCI) and 60 cognitively normal (CN) subjects. To explore the dynamic functional network connectivity (dFNC), we investigated dynamic time-varying triple-network interactions in subjects using Group ICA analysis based on k-means clustering (GDA-k-means). The mean of brain state-specific network interaction indices (meanNII) in the three groups (AD, MCI, CN) showed significant differences by ANOVA analysis. To verify the robustness of the findings, a support vector machine (SVM) was taken meanNII, gender and age as features to classify. This method obtained accuracy values of 95, 94, and 77% when classifying AD vs. CN, AD vs. MCI, and MCI vs. CN, respectively. In our work, the findings demonstrated that the dynamic characteristics of functional interactions of the triple-networks contributed to studying the underlying pathophysiology of AD. It provided strong evidence for dysregulation of brain dynamics of AD.Peer reviewedFinal Published versio

What do we visually focus on in a World Heritage Site? A case study in the Historic Centre of Prague

Since socio-economic development is associated with artificial construction, heritage environments must be protected and renewed while adapting to such development. Many World Heritage Sites’ visual integrity is endangered by new construction. The paper aims to explore people’s visual focus patterns concerning the integrity of heritage to ensure that traditional culture is not endangered by the construction and development of modern life, and to protect Outstanding Universal Values. In this study, visual heatmaps are generated to investigate people’s visual integrity in the Historic Centre of Prague from micro to macro viewpoints using an eye tracker. We found that humans’ perspectives are unobstructed or concentrated, and the view of main attractions is generally maintained by a buffer zone. However, newly constructed high-rise buildings can result in major visual concerns. Therefore, new buildings with large heights and strong contrasting colours should be restricted to World Heritage Sites. Moreover, complex artistic effects (facade midline, domes, mural painting, faces of sculptures) will likely attract people’s attention. In contrast, visual focus is not concentrated on greenery, roofs and floors. Accordingly, greenery could become a flexible space to serve as a background for buildings and landscape nodes. Furthermore, visual focal factors are associated with two significant aspects: people and the environment. Since people and transportation could pose visual concerns, tourism managers should optimise for characteristics such as controlling the density of pedestrian flow and planning parking spaces. The visual patterns identified could be useful for the design, conservation, and management of visual integrity in cultural heritage sites to avoid the spread of artificial constructions within the boundaries of heritage sites, which may lead to their being endangered or delisted

Electrospun Nanocomposite Fibrous Membranes for Sustainable Face Mask Based on Triboelectric Nanogenerator with High Air Filtration Efficiency

Air pollution caused by the rapid development of industry has always been a great issue to the environment and human being’s health. However, the efficient and persistent filtration to PM0.3 remains a great challenge. Herein, a self-powered filter with micro–nano composite structure composed of polybutanediol succinate (PBS) nanofiber membrane and polyacrylonitrile (PAN) nanofiber/polystyrene (PS) microfiber hybrid mats was prepared by electrospinning. The balance between pressure drop and filtration efficiency was achieved through the combination of PAN and PS. In addition, an arched TENG structure was created using the PAN nanofiber/PS microfiber composite mat and PBS fiber membrane. Driven by respiration, the two fiber membranes with large difference in electronegativity achieved contact friction charging cycles. The open-circuit voltage of the triboelectric nanogenerator (TENG) can reach to about 8 V, and thus the high filtration efficiency for particles was achieved by the electrostatic capturing. After contact charging, the filtration efficiency of the fiber membrane for PM0.3 can reach more than 98% in harsh environments with a PM2.5 mass concentration of 23,000 µg/m3, and the pressure drop is about 50 Pa, which doesn’t affect people’s normal breathing. Meanwhile, the TENG can realize self-powered supply by continuously contacting and separating the fiber membrane driven by respiration, which can ensure the long-term stability of filtration efficiency. The filter mask can maintain a high filtration efficiency (99.4%) of PM0.3 for 48 consecutive hours in daily environments

An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning

Catastrophic forgetting (CF) is a phenomenon that occurs in machine learning when a model forgets previously learned information as it learns new information. As large language models (LLMs) have shown excellent performance, it is interesting to uncover whether CF exists in the continual fine-tuning of LLMs. In this study, we empirically evaluate the forgetting phenomenon in LLMs' knowledge, from the perspectives of domain knowledge, reasoning, and reading comprehension. The experiments demonstrate that catastrophic forgetting is generally observed in LLMs ranging from 1b to 7b. Furthermore, as the scale increases, the severity of forgetting also intensifies. Comparing the decoder-only model BLOOMZ with the encoder-decoder model mT0, BLOOMZ suffers less forgetting and maintains more knowledge. We also observe that LLMs can mitigate language bias (e.g. gender bias) during continual fine-tuning. Moreover, we find that ALPACA can maintain more knowledge and capacity compared with LLAMA during the continual fine-tuning, which implies that general instruction tuning can help mitigate the forgetting phenomenon of LLMs in the further fine-tuning process