In distribution network, safe, reliable and fast operation of low-voltage load transfer device plays a vital role in power supply reliability. In this paper, a new 0. 4kV pole-mounted fully insulated and visualized load transfer device (PFIVLTD) is developed, which solves the problems of conventional jumper wire device(JWD), such as high current of single-phase operation, high resistance augmentation rate at contact points, susceptibility to aging of the insulation, clamps liable to break by an external force, and high risk and inefficient operation, and it has the advantages of full insulation and visualization, safety and convenience, economy and reliability. PFIVLTD realizes the intrinsic insulation through a fully insulated and fully enclosed design and ensures the remote visualization of the state of switch through a transparent viewable window at the bottom. Three-phase linkage switch, compact spring operating mechanism, and operating handle design changed the load-transfer-way from single-phase-sequential-operate for thrice direct contact to three-phase-operate for once indirect contact, it also reduced the load transfer operation time of the overhead line from 20 minutes to 3 minutes, and improved the safety and efficiency of 0. 4kV uninterrupted operation. PFIVLTD has been applied in many places in Shanghai City, China since 2022. Engineering practice demonstrated that the new PFIVLTD effectively reduced the tripping rate of overhead line, shortened the user outage time, and enhanced the safety of load transfer operation in contrast with conventional JWD, which provides strong support for maintaining Average Service Availability Index (ASAI) of power supply reliability above 99.999% in Shanghai urban area in 2022.
This study was aimed to investigate the relationship between plasma fibrinogen level and risk for cognitive decline and dementia in patients with mild cognitive impairment (MCI). Elderly patients with suspected cognitive impairment were screened and evaluated periodically. One hundred and eighty-five patients who met the criteria for MCI were enrolled. Blood coagulation functions and plasma fibrinogen levels were measured at baseline. Hyperfibrinogenaemia was defined as plasma fibrinogen ≥3.0 g/l. Global cognitive function was assessed serially with Mini-Mental State Examination (MMSE). The enrolled patients were followed for 2 years to observe if dementia was developed. There were 185 patients diagnosed as MCI, of which 17 (9.2%) deceased, 15 (8.1%) lost to follow-up, and 68 (36.8%) developed dementia during follow-up. Mean of MMSE score of the enrolled patients declined significantly during follow-up (22.0 ± 3.0 vs. 18.1 ± 5.8, p < 0.001). Patients with hyperfibrinogenaemia at baseline had greater MMSE decrement during follow-up than patients with normal fibrinogen level (−5.4 ± 5.4 vs. −3.5 ± 4.5, p < 0.05). Linear regression indicated that plasma fibrinogen level was associated with cognitive decline (R = 0.17, p < 0.05). Patients with hyperfibrinogenaemia had an increased risk for dementia and vascular dementia compared with patients with normal level of plasma fibrinogen (log rank test, p < 0.05). There was a trend that hyperfibrinogenaemia also increased risk for dementia of Alzheimer's type (p = 0.061). It can be concluded that plasma fibrinogen level may be associated with cognitive decline, and hyperfibrinogenaemia may increase risk for dementia in patients with MCI.
Ten hadronic final states of the ${h}_{c}$ decays are investigated via the process $\ensuremath{\psi}(3686)\ensuremath{\rightarrow}{\ensuremath{\pi}}^{0}{h}_{c}$, using a data sample of $(448.1\ifmmode\pm\else\textpm\fi{}2.9)\ifmmode\times\else\texttimes\fi{}{10}^{6}\text{ }\text{ }\ensuremath{\psi}(3686)$ events collected with the BESIII detector. The decay channel ${h}_{c}\ensuremath{\rightarrow}{K}^{+}{K}^{\ensuremath{-}}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{\ensuremath{-}}{\ensuremath{\pi}}^{0}$ is observed for the first time and has a measured significance of $6.0\ensuremath{\sigma}$. The corresponding branching fraction is determined to be $\mathcal{B}({h}_{c}\ensuremath{\rightarrow}{K}^{+}{K}^{\ensuremath{-}}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{\ensuremath{-}}{\ensuremath{\pi}}^{0})=(3.3\ifmmode\pm\else\textpm\fi{}0.6\ifmmode\pm\else\textpm\fi{}0.6)\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}3}$ (where the uncertainties are statistical and systematic, respectively). Evidence for the decays ${h}_{c}\ensuremath{\rightarrow}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{\ensuremath{-}}{\ensuremath{\pi}}^{0}\ensuremath{\eta}$ and ${h}_{c}\ensuremath{\rightarrow}{K}_{S}^{0}{K}^{\ifmmode\pm\else\textpm\fi{}}{\ensuremath{\pi}}^{\ensuremath{\mp}}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{\ensuremath{-}}$ is found with a significance of $3.6\ensuremath{\sigma}$ and $3.8\ensuremath{\sigma}$, respectively. The corresponding branching fractions (and upper limits) are obtained to be $\mathcal{B}({h}_{c}\ensuremath{\rightarrow}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{\ensuremath{-}}{\ensuremath{\pi}}^{0}\ensuremath{\eta})=(7.2\ifmmode\pm\else\textpm\fi{}1.8\ifmmode\pm\else\textpm\fi{}1.3)\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}3}$ $(<1.8\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}2})$ and $\mathcal{B}({h}_{c}\ensuremath{\rightarrow}{K}_{S}^{0}{K}^{\ifmmode\pm\else\textpm\fi{}}{\ensuremath{\pi}}^{\ensuremath{\mp}}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{\ensuremath{-}})=(2.8\ifmmode\pm\else\textpm\fi{}0.9\ifmmode\pm\else\textpm\fi{}0.5)\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}3}$ ($<4.7\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}3}$). Upper limits on the branching fractions for the final states ${h}_{c}\ensuremath{\rightarrow}{K}^{+}{K}^{\ensuremath{-}}{\ensuremath{\pi}}^{0}$, ${K}^{+}{K}^{\ensuremath{-}}\ensuremath{\eta}$, ${K}^{+}{K}^{\ensuremath{-}}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{\ensuremath{-}}\ensuremath{\eta}$, $2({K}^{+}{K}^{\ensuremath{-}}){\ensuremath{\pi}}^{0}$, ${K}^{+}{K}^{\ensuremath{-}}{\ensuremath{\pi}}^{0}\ensuremath{\eta}$, ${K}_{S}^{0}{K}^{\ifmmode\pm\else\textpm\fi{}}{\ensuremath{\pi}}^{\ensuremath{\mp}}$, and $p\overline{p}{\ensuremath{\pi}}^{0}{\ensuremath{\pi}}^{0}$ are determined at a confidence level of 90%.
First flush pollution is a main part of urban non-point source pollution.Presently,a definition of first flush and its discharge volume are unclear.Factors influencing the first flush effect are numerous and complex,often related to local properties.Through analysis of monitored rainfall and roof runoff quality in Beijing stormwater utilization demonstration area,the effect of different first flush dis-charge volumes on pollution load reduction is preliminarily discussed.Under different rainfall characteris-tics,discharging 2 mm precipitation from roof runoff can reduce the pollution load by 20% to 45%.Thus,the first flush discharge volume of roof runoff at 2 mm precipitation is proposed for Beijing.
This article explores the comprehensive recovery strategies necessary for individuals following chemotherapy, focusing on a holistic approach that includes medications, lifestyle changes, and environmental interventions. The initial section delves into the importance of personalized medical interventions such as targeted therapies, immunotherapy and hormonal treatments, highlighting their critical role in effectively controlling cancer while minimizing side effects. Detailed focus on the mechanisms of adverse effects, particularly the neurotoxic effects of chemotherapy drugs on the hippocampus, elucidates the biological basis of chemotherapy-induced cognitive impairment (often referred to as "chemo brain"). Environmental interventions are another core component of recovery strategies focused on reducing toxin exposure and creating therapeutic spaces conducive to recovery. Provides practical advice for achieving a healthier living environment, including choosing organic foods, using natural household products, and improving indoor air quality. The findings presented here provide a fundamental understanding of brain structural changes following chemotherapy, providing insights into potential mitigation strategies for cognitive recovery.
A good scoring function is necessary for ab inito prediction of RNA tertiary structures. In this study, we explored the power of a machine learning based approach as a scoring function. Compared with the traditional scoring functions, the present approach is more flexible in incorporating different kinds of features; it is also free of the difficult problem of choosing the reference state. Two multi-layer neural networks were constructed and trained. They took RNA a structural candidate as input and then output its likeness score that evaluates the likeness of the candidate to the native structure. The first network was working at the coarse-grained level of RNA structures, while the second at the all-atom level. We also built an RNA database and split it into the training, validation, and testing sets, containing 322, 70, and 70 RNAs, respectively. Each RNA was accompanied with 300 decoys generated by high-temperature molecular dynamics simulations. The networks were trained on the training set and then optimized with an early-stop strategy, based on the loss of the validation set. We then tested the performance of the networks on the testing set. The results were found to be consistently better than a recent knowledge-based all-atom potential.