Deformation and orientation effects in the driving potential of the dinuclear model

A double-folding method is used to calculate the nuclear and Coulomb interaction between two deformed nuclei with arbitrary orientations. A simplified Skryme-type interaction is adopted. The contributions of nuclear interaction and Coulomb interaction due to the deformation and orientation of the nuclei are evaluated for the driving potential used in the description of heavy-ion fusion reaction. So far there is no satisfactory theory to describe the evolution of the dynamical nuclear deformation and orientations during the heavy-ion fusion process. Our results estimated the magnitude of above effects.Comment: 15 pages, 6 figures, Accepted by Eur. Phys. Jour.

Urban-rural disparity in mortality patterns of respiratory diseases among older adults - China, 1987-2021.

What is already known about this topic? Respiratory diseases (RDs) are the primary cause of death in older adults in China. However, there is limited evidence regarding the disparity in mortality rates of RDs between urban and rural areas among the elderly population. What is added by this report? The age-standardized mortality rate (ASMR) due to RDs in the elderly population in both urban and rural areas of China has shown a consistent decrease. This trend is observed in both males and females. However, there was no significant change in the average annual percentage of ASMR for pneumonia among the urban elderly population and rural elderly men throughout the study period. What are the implications for public health practice? Efforts should be made in China to reduce mortality from chronic lower respiratory disease and pneumonia among the elderly, particularly in urban populations

Fiber absorption measurement errors resulting from re-emission of radiation

We show that errors in the absorption measured in rare-earth-doped fibers can exceed 50% and severely distort the spectral shape. This is a result of re-emission in fibers with overlapping absorption and emission spectra

Multiobjective Guided Priors Improve the Accuracy of Near-Infrared Spectral Tomography for Breast Imaging

An image reconstruction regularization approach for magnetic resonance imaging-guided near-infrared spectral tomography has been developed to improve quantification of total hemoglobin (HbT) and water. By combining prior information from dynamic contrast enhanced (DCE) and diffusion weighted (DW) MR images, the absolute bias errors of HbT and water in the tumor were reduced by 22% and 18%, 21% and 6%, and 10% and 11%, compared to that in the no-prior, DCE- or DW-guided reconstructed images in three-dimensional simulations, respectively. In addition, the apparent contrast values of HbT and water were increased in patient image reconstruction from 1.4 and 1.4 (DCE) or 1.8 and 1.4 (DW) to 4.6 and 1.6

Tunable Cu 2 O Nanocrystals Fabricated by Free Dealloying of Amorphous Ribbons

This work discovers that Cu 2 O nanocrystals with controllable structures can be synthesized on surfaces of nanoporous Cu and amorphous ribbons by free dealloying of Cu-based amorphous alloys in acidic solutions. Technological parameters, such as the acid, acid concentration, and dealloying time strongly influence the crystal size, structure and morphology of Cu 2 O. Cu 2 O nanocubes are fabricated on surfaces of nanoporous Cu in the hydrofluoric acid treated alloy, while various Cu 2 O particles are tailored on surfaces of amorphous alloys immersed in hydrochloric acid for different time. The increasing dealloying time and adsorbed oxygen improve the growth rates along the 1 0 0 direction of Cu 2 O crystals relative to that of the 1 1 1 direction, which is the key to change the shapes of Cu 2 O crystals. The understanding of morphology evolution of Cu 2 O nanocrystals in this work is helpful in tailoring Cu 2 O particles with designable shapes and controllable properties in application fields

Explanation-Guided Backdoor Attacks on Model-Agnostic RF Fingerprinting

Despite the proven capabilities of deep neural networks (DNNs) for radio frequency (RF) fingerprinting, their security vulnerabilities have been largely overlooked. Unlike the extensively studied image domain, few works have explored the threat of backdoor attacks on RF signals. In this paper, we analyze the susceptibility of DNN-based RF fingerprinting to backdoor attacks, focusing on a more practical scenario where attackers lack access to control model gradients and training processes. We propose leveraging explainable machine learning techniques and autoencoders to guide the selection of positions and values, enabling the creation of effective backdoor triggers in a model-agnostic manner. To comprehensively evaluate our backdoor attack, we employ four diverse datasets with two protocols (Wi-Fi and LoRa) across various DNN architectures. Given that RF signals are often transformed into the frequency or time-frequency domains, this study also assesses attack efficacy in the time-frequency domain. Furthermore, we experiment with potential defenses, demonstrating the difficulty of fully safeguarding against our attacks

Registered Attribute-Based Signature

This paper introduces the notion of registered attribute-based signature (registered ABS). Distinctly different from classical attribute-based signature (ABS), registered ABS allows any user to generate their own public/secret key pair and register it with the system. The key curator is critical to keep the system flowing, which is a fully transparent entity that does not retain secrets. Our results can be summarized as follows. -This paper provides the first definition of registered ABS, which has never been defined. -This paper presents the first generic fully secure registered ABS over the prime-order group from $k$-Lin assumption under the standard model, which supports various classes of predicate. -This paper gives the first concrete registered ABS scheme for arithmetic branching program (ABP), which achieves full security in the standard model. Technically, our registered ABS is inspired by the blueprint of Okamoto and Takashima[PKC\u2711]. We convert the prime-order registered attribute-based encryption (registered ABE) scheme of Zhu et al.[ASIACRYPT\u2723] via predicate encoding to registered ABS by employing the technique of re-randomization with specialized delegation, while we employ the different dual-system method considering the property of registration. Prior to our work, the work of solving the key-escrow issue was presented by Okamoto and Takashima[PKC\u2713] while their work considered the weak adversary in the random oracle model

Particle transfer and fusion cross-section for Super-heavy nuclei in dinuclear system

Within the dinuclear system (DNS) conception, instead of solving Fokker-Planck Equation (FPE) analytically, the Master equation is solved numerically to calculate the fusion probability of super-heavy nuclei, so that the harmonic oscillator approximation to the potential energy of the DNS is avoided. The relative motion concerning the energy, the angular momentum, and the fragment deformation relaxations is explicitly treated to couple with the diffusion process, so that the nucleon transition probabilities, which are derived microscopically, are time-dependent. Comparing with the analytical solution of FPE, our results preserve more dynamical effects. The calculated evaporation residue cross sections for one-neutron emission channel of Pb-based reactions are basically in agreement with the known experimental data within one order of magnitude.Comment: 19 pages, plus 6 figures, submitted to Phys. Rev.

Modeling the resumption of work and production of enterprises during COVID-19: An SIR-based quantitative framework

The ongoing COVID-19 pandemic has evolved beyond being a public health crisis as it has exerted worldwide severe economic impacts, triggering cascading failures in the global industrial network. Although certain powerful enterprises can remain its normal operation during this global shock, what's more likely to happen for the majority, especially those small- and medium-sized firms, is that they are experiencing temporary suspension out of epidemic control requirement, or even permanent closure due to chronic business losses. For those enterprises that sustain the pandemic and only suspend for a relatively short period, they could resume work and production when epidemic control and prevention conditions are satisfied and production and operation are adjusted correspondingly. In this paper, we develop a novel quantitative framework which is based on the classic susceptible-infectious-recovered (SIR) epidemiological model (i.e., the SIR model), containing a set of differential equations to capture such enterprises' reactions in response to COVID-19 over time. We fit our model from the resumption of work and production (RWP) data on industrial enterprises above the designated size (IEDS). By modeling the dynamics of enterprises' reactions, it is feasible to investigate the ratio of enterprises' state of operation at given time. Since enterprises are major economic entities and take responsibility for most output, this study could potentially help policy makers better understand the economic impact caused by the pandemic and could be heuristic for future prevention and resilience-building strategies against suchlike outbreaks of public health crises