Demonstration of an 8-Gbit/s quadrature-phase-shift-keying coherent underwater wireless optical communication link using coherent heterodyne detection under scattering conditions.

In this paper, we experimentally demonstrate an 8-Gbit/s quadrature-phase-shift-keying (QPSK) coherent underwater wireless optical communication (UWOC) link under scattering conditions at 532 nm. At the transmitter, we generate the 532-nm QPSK signal using second-harmonic generation (SHG), where the 1064-nm signal modulated with four phase levels of an 8-phase-shift-keying (8-PSK) format is phase doubled to produce the 532-nm QPSK signal. To enhance the receiver sensitivity, we utilize a local oscillator (LO) at the receiver from an independent laser source. The received QPSK data beam is mixed with the independent LO for coherent heterodyne detection. Results show that the bit error rates (BERs) of the received QPSK signal can reach below the 7% forward error correction (FEC) limit under turbid water with attenuation lengths (γL) up to 7.4 and 6.1 for 2- and 8-Gbit/s QPSK, respectively. The corresponding receiver sensitivities are -34.0 and -28.4 dBm for 2- and 8-Gbit/s QPSK, respectively.

Advancing driver fatigue detection in diverse lighting conditions for assisted driving vehicles with enhanced facial recognition technologies.

Against the backdrop of increasingly mature intelligent driving assistance systems, effective monitoring of driver alertness during long-distance driving becomes especially crucial. This study introduces a novel method for driver fatigue detection aimed at enhancing the safety and reliability of intelligent driving assistance systems. The core of this method lies in the integration of advanced facial recognition technology using deep convolutional neural networks (CNN), particularly suited for varying lighting conditions in real-world scenarios, significantly improving the robustness of fatigue detection. Innovatively, the method incorporates emotion state analysis, providing a multi-dimensional perspective for assessing driver fatigue. It adeptly identifies subtle signs of fatigue in rapidly changing lighting and other complex environmental conditions, thereby strengthening traditional facial recognition techniques. Validation on two independent experimental datasets, specifically the Yawn and YawDDR datasets, reveals that our proposed method achieves a higher detection accuracy, with an impressive 95.3% on the YawDDR dataset, compared to 90.1% without the implementation of Algorithm 2. Additionally, our analysis highlights the method's adaptability to varying brightness levels, improving detection accuracy by up to 0.05% in optimal lighting conditions. Such results underscore the effectiveness of our advanced data preprocessing and dynamic brightness adaptation techniques in enhancing the accuracy and computational efficiency of fatigue detection systems. These achievements not only showcase the potential application of advanced facial recognition technology combined with emotional analysis in autonomous driving systems but also pave new avenues for enhancing road safety and driver welfare.

High beam quality continuous-wave 320 nm UV laser from a walk-off compensated intracavity frequency-doubled Pr:YLF laser.

We report a high beam quality continuous-wave (CW) 320 nm ultra-violet (UV) laser. An end-pumped praseodymium-doped yttrium lithium fluoride (Pr:YLF) laser is constructed in a typical V-shaped cavity structure, while the UV output is obtained through intracavity frequency doubling using L i B 3 O 5 (LBO). We investigate the dependence of the UV output power, as well as the spot profile on the LBO length, and find that the "walk-off" within LBO severely affects both the frequency-doubling efficiency and the beam quality of the UV output. Rotated twin LBO crystals are then applied to substitute for single long LBO crystal to compensate the walk-off effect, resulting in high-power 320 nm output up to 410 mW under the absorbed pump power of 4.0 W at 444 nm, with a high beam quality of M x2=1.02 and M y2=1.04.

Epidemiological feature analysis of SVEIR model with control strategy and variant evolution.

The complex interactions were performed among non-pharmaceutical interventions, vaccinations, and hosts for all epidemics in mainland China during the spread of COVID-19. Specially, the small-scale epidemic in the city described by SVEIR model was less found in the current studies. The SVEIR model with control was established to analyze the dynamical and epidemiological features of two epidemics in Jinzhou City led by Omicron variants before and after Twenty Measures. In this study, the total population (N) of Jinzhou City was divided into five compartments: the susceptible (S), the vaccinated (V), the exposed (E), the infected (I), and the recovered (R). By surveillance data and the SVEIR model, three methods (maximum likelihood method, exponential growth rate method, next generation matrix method) were governed to estimate basic reproduction number, and the results showed that an increasing tendency of basic reproduction number from Omicron BA.5.2 to Omicron BA.2.12.1. Meanwhile, the effective reproduction number for two epidemics were investigated by surveillance data, and the results showed that Jinzhou wave 1 reached the peak on November 1 and was controlled 7 days later, and that Jinzhou wave 2 reached the peak on November 28 and was controlled 5 days later. Moreover, the impacts of non-pharmaceutical interventions (awareness delay, peak delay, control intensity) were discussed extensively, the variations of infection scales for Omicron variant and EG.5 variant were also discussed. Furthermore, the investigations on peaks and infection scales for two epidemics in dynamic zero-COVID policy were operated by the SVEIR model with control. The investigations on public medical requirements of Jinzhou City and Liaoning Province were analyzed by using SVEIR model without control, which provided a possible perspective on variant evolution in the future.

PatWRKY71 transcription factor regulates patchoulol biosynthesis and plant defense response.

Patchoulol, a valuable compound belonging to the sesquiterpenoid family, is the primary component of patchouli oil produced by Pogostemon cablin (P. cablin). It has a variety of pharmacological and biological activities and is widely used in the medical and cosmetic industries. However, despite its significance, there is a lack of research on the transcriptional modulation of patchoulol biosynthesis.Salicylic acid (SA), is a vital plant hormone that serves as a critical signal molecule and plays an essential role in plant growth and defense. However, to date, no studies have explored the modulation of patchoulol biosynthesis by SA. In our study, we discovered that the application of SA can enhance the production of patchoulol. Utilizing transcriptome analysis of SA-treated P. cablin, we identified a crucial downstream transcription factor, PatWRKY71. The transcription level of PatWRKY71 was significantly increased with the use of SA. Furthermore, our research has revealed that PatWRKY71 was capable of binding to the promoter of PatPTS, ultimately leading to an increase in its expression. When PatWRKY71 was silenced by a virus, the expression of both PatWRKY71 and PatPTS was reduced, resulting in the down-regulation of patchoulol production. Through our studies, we discovered that heterologous expression of PatWRKY71 leads to an increase in the sensitivity of Arabidopsis to salt and Cd, as well as an outbreak of reactive oxygen species (ROS). Additionally, we uncovered the regulatory role of PatWRKY71 in both patchoulol biosynthesis and plant defense response. This discovery provided a theoretical basis for the improvement of the content of patchoulol and the resistance of P. cablin through genetic engineering.

A new metal ion chelator attenuates human tau accumulation-induced neurodegeneration and memory deficits in mice.

Neuronal neurofibrillary tangles containing Tau hyperphosphorylation proteins are a typical pathological marker of Alzheimer's disease (AD). The level of tangles in neurons correlates positively with severe dementia. However, how Tau induces cognitive dysfunction is still unknown, which leads to a lack of effective treatments for AD. Metal ions deposition occurs with tangles in AD brain autopsy. Reduced metal ion can improve the pathology of AD. To explore whether abnormally phosphorylated Tau causes metal ion deposition, we overexpressed human full-length Tau (hTau) in the hippocampal CA3 area of mice and primary cultured hippocampal neurons (CPHN) and found that Tau accumulation induced iron deposition and activated calcineurin (CaN), which dephosphorylates glycogen synthase kinase 3 beta (GSK3ß), mediating Tau hyperphosphorylation. Simultaneous activation of CaN dephosphorylates cyclic-AMP response binding protein (CREB), leading to synaptic deficits and memory impairment, as shown in our previous study; this seems to be a vicious cycle exacerbating tauopathy. In the current study, we developed a new metal ion chelator that displayed a significant inhibitory effect on Tau phosphorylation and memory impairment by chelating iron ions in vivo and in vitro. These findings provide new insight into the mechanism of memory impairment induced by Tau accumulation and develop a novel potential treatment for tauopathy in AD.