Clinical observation of laser treatment for central serous chorioretinopathy choroidal diseases and study on relationship between visual acuity with leakage location

AIM:To analyze the low energy laser photocoagulation under treatment of central serous chorioretinopathy(CSC)correlation of clinical effect and visual acuity with leakage location.<p>METHODS:Using low energy laser on the leakage point in the parafoveal and 53 cases of central serous chorioretinopathy patients underwent laser closed, drug treatment group and 33 cases as control. Comparison of two groups was observed before and after treatment in patients with symptoms, ocular fundus, fundus fluorescein angiography(FFA)changes, fundus optical coherence tomography technology(OCT)examination, visual acuity improved in degree, and the relationship between the cure rate, relapse rate. All 126 cases were associated with visual leakage location analysis. <p>RESULTS:The cure rate of lasercomparison: 4 weeks after operation, the cure rate was 92.5%. The drug therapy group at 4 weeks after treatment cure rate was 30.3%.The two groups were compared(<i>P</i><0.01), and there was significant difference. The laser group and treatment group after treatment in 2 weeks, 4 weeks, in March June, and there was significant difference(<i>P</i><0.01). The medicine group the recurrence rate was 12.1%, the lasertreatment group and recurrence rate was 11.3%. The two groups were compared, no significant difference(<i>P</i>>0.05). Nonparametriccorrelation analysis method to compare the relationship between visual acuity and fluorescence leakage point location, the correlation coefficient(<i>r</i>=0.216, <i>P</i>=0.0001), there is a positive linear correlation between. <p>CONCLUSION:The leakage point in the parafoveal outside in early stagelaser in the treatment of low energy laser, can shorten the course of disease, improve the cure rate of visual acuity and clinical, and improve the visual quality, but can not reduce the recurrence rate. There is a positive correlation between visual acuity and leakage location, clinicalguidance for prognosis and treatment

Effect of dynamic route guidance on urban traffic network under Connected Vehicle environment

Although Connected Vehicle technology is developing rapidly, connected vehicles (CV) are going to mix with the traditional vehicles (i.e., non-connected vehicles) for a long time. The effects of deploying CV on urban traffic systems are actually not clear. The main objective of this study is to evaluate the potential effects of route guidance under connected vehicle environment on an urban traffic network in terms of traffic mobility and safety. Microscopic simulation approach is used to conduct CV environment simulation and the rolling horizon approach is used for information updating among the connected vehicles. Meanwhile, driving behavior is modeled through aggressiveness and awareness of drivers. Traffic mobility for the road network was measured by average trip time and average vehicle trip speed. A surrogate measure, i.e., the time-to-collision involved incident rate for one kilometer driven, was used to assess the safety of the road network. Based on a real urban traffic network, the impacts of market penetration levels of connected vehicles and information updating intervals were studied. Simulation results showed that market penetration level of connected vehicles has little impact on the mobility and safety of road network. In addition, according to the simulation conducted in this paper, shorter updating interval is shown to be likely to lead to better mobility, while the safety of road network is likely to decline, under the assumptions embraced in the simulation. By contrast, the&nbsp;simulation also showed that longer updating interval is likely to lead to better safety and decreased mobility

The relationship between self-efficacy and aggressive behavior in boxers: the mediating role of self-control

P. 1-9El comportamiento agresivo ha sido uno de los temas centrales de la psicología deportiva, mientras que el comportamiento agresivo de los boxeadores ha recibido una atención limitada. Aunque algunas publicaciones informaron que la autoeficacia se relaciona con el comportamiento agresivo, el mecanismo por el cual la autoeficacia afecta el comportamiento agresivo no está claro. El presente estudio investigó la relación entre la autoeficacia y el comportamiento agresivo, así como el efecto del autocontrol como factor mediador. Este estudio utiliza la Escala de autoeficacia para atletas, el Cuestionario de autocontrol para atletas y el Cuestionario de agresión de Buss-Perry. Esta relación se explora a través de medidas auto-informadas de N = 414 boxeadores profesionales chinos, n = 243 eran hombres y n = 171 mujeres, la edad promedio fue M = 17.72 años (SD = 3.147), los participantes, el número promedio de los años de ejercicio fueron M = 3.89 años (SD = 2.734); Los resultados mostraron que los boxeadores masculinos reportaron mayor agresividad que las boxeadoras; se encontró que la autoeficacia y el autocontrol mejoraron a medida que aumentaba la edad de los participantes; A mayor nivel de competencia, mayores niveles de autoeficacia y autocontrol; La autoeficacia se relacionó negativamente con el comportamiento agresivo y se correlacionó positivamente con el autocontrol. El autocontrol también se correlacionó negativamente con el comportamiento agresivo entre los boxeadores. El autocontrol tuvo un efecto de mediación total en la relación entre la autoeficacia y el comportamiento agresivoS

N6-Methyladenosine-Mediated Overexpression of Long Noncoding Rna ADAMTS9-AS2 Triggers Neuroblastoma Differentiation via Regulating lin28B/Let-7/MYCN Signaling

Neuroblastomas have shed light on the differentiation disorder that is associated with spontaneous regression or differentiation in the same tumor at the same time. Long noncoding RNAs (lncRNAs) actively participate in a broad spectrum of biological processes. However, the detailed molecular mechanisms underlying lncRNA regulation of differentiation in neuroblastomas remain largely unknown. Here, we sequenced clinical samples of ganglioneuroma, ganglioneuroblastoma, and neuroblastoma. We compared transcription profiles of neuroblastoma cells, ganglion cells, and intermediate state cells; verified the profiles in a retinoic acid-induced cell differentiation model and clinical samples; and screened out the lncRNA ADAMTS9 antisense RNA 2 (ADAMTS9-AS2), which contributed to neuroblastoma differentiation. ADAMTS9-AS2 upregulation in neuroblastoma cell lines inhibited proliferation and metastatic potential. Additional mechanistic studies illustrated that the interactions between ADAMTS9-AS2 and LIN28B inhibited the association between LIN28B and primary let-7 (pri-let-7) miRNA, then released pri-let-7 into cytoplasm to form mature let-7, resulting in the inhibition of oncogene MYCN activity that subsequently affected cancer stemness and differentiation. Furthermore, we showed that the observed differential expression of ADAMTS9-AS2 in neuroblastoma cells was due to N6-methyladenosine methylation. Finally, ADAMTS9-AS2 upregulation inhibited proliferation and cancer stem-like capabilities in vivo. Taken together, these results show that ADAMTS9-AS2 loss leads to malignant neuroblastoma by increasing metastasis and causing dysfunctional differentiation

Experimental Trapped-ion Quantum Simulation of the Kibble-Zurek dynamics in momentum space

The Kibble-Zurek mechanism is the paradigm to account for the nonadiabatic dynamics of a system across a continuous phase transition. Its study in the quantum regime is hindered by the requisite of ground state cooling. We report the experimental quantum simulation of critical dynamics in the transverse-field Ising model by a set of Landau-Zener crossings in pseudo-momentum space, that can be probed with high accuracy using a single trapped ion. We test the Kibble-Zurek mechanism in the quantum regime in the momentum space and find the measured scaling of excitations is in accordance with the theoretical prediction.Comment: 10 pages, 3 figures Published in Scientific Reports, http://www.nature.com/articles/srep3338

A Hybrid Short-term Traffic Flow Forecasting Method Based on Neural Networks Combined with K-Nearest Neighbor

It is critical to implement accurate short-term traffic forecasting in traffic management and control applications. This paper proposes a hybrid forecasting method based on neural networks combined with the K-nearest neighbor (K-NN) method for short-term traffic flow forecasting. The procedure of training a neural network model using existing traffic input-output data, i.e., training data, is indispensable for fine-tuning the prediction model. Based on this point, the K-NN method was employed to reconstruct the training data for neural network models while considering the similarity of traffic flow patterns. This was done through collecting the specific state vectors that were closest to the current state vectors from the historical database to enhance the relationship between the inputs and outputs for the neural network models. In this study, we selected four different neural network models, i.e., back-propagation (BP) neural network, radial basis function (RBF) neural network, generalized regression (GR) neural network, and Elman neural network, all of which have been widely applied for short-term traffic forecasting. Using real world traffic data, the  experimental results primarily show that the BP and GR neural networks combined with the K-NN method have better prediction performance, and both are sensitive to the size of the training data. Secondly, the forecast accuracies of the RBF and Elman neural networks combined with the K-NN method both remain fairly stable with the increasing size of the training data. In summary, the proposed hybrid forecasting  approach outperforms the conventional forecasting models, facilitating the implementation of short-term  traffic forecasting in traffic management and control applications

Experimental beating the standard quantum limit under non-markovian dephasing environment

Entanglement enhanced quantum metrology has been well investigated for beating the standard quantum limit (SQL). However, the metrological advantage of entangled states becomes much more elusive in the presence of noise. Under strictly Markovian dephasing noise, the uncorrelated and maximally entangled states achieve exactly the same measurement precision. However, it was predicted that in a non-Markovian dephasing channel, the entangled probes can recover their metrological advantage. Here, by using a highly controlled photonic system, we simulate a non-Markovian dephasing channel fulfill the quadratic decay behaviour. Under such a channel, we demonstrate the GHZ states can surpass the SQL in a scaling manner, up to six photons. Since the quadratic decay behavior is quite general for short time expansion in open quantum systems (also known as the quantum Zeno effect), our results suggest a universal and scalable method to beat the SQL in the real-word metrology tasks.Comment: 11 Pages, 6 Figure

Analysis on the characteristics of geological disasters and effectiveness of early warning duiring heavy rainfall on “23•7” in Beijing

Extreme rainfall is often accompanied by mass geological disasters, which seriously endangers the safety of people 's lives and property in prone areas and affects the healthy development of the economy and society. Summarizing and analyzing the time-space distribution characteristics of geological disasters due to extreme rainfall and the effectiveness of early warning is of great significance for improving the comprehensive defense ability against geological disasters. Taking the sudden geological disasters caused by “23•7” heavy rainfall in 2023 as the research object, based on the refined precipitation data from the Beijing sudden geological disaster monitoring and early warning system, the time-space distribution characteristics of “23•7” heavy rainfall and the development and distribution characteristics of geological disasters were analyzed, and the early warning effect of geological disasters was discussed. The results show that the“23•7”heavy rainfall has the characteristics such as a large total amount, strong rainfall, long duration and wide range, and the disasters due to extreme rainfall have the characteristics of group occurrence. The multi-dimensional early warning of geological disaster classification has achieved remarkable results and has achieved the goal of zero casualties due to geological disasters under extreme weather conditions. The research results can provide a reference for actively preventing and scientifically responding to extreme rainfall geological disasters