拥抱互联 打造船舶领域的“Alpha Go”

12月5日，由我国自主研制的全球第一艘智能船舶-iDolphin 38800吨智能散货船“大智”号（英文名GREAT INTELLIGENCE）在上海海事展上正式交付使用。该船首次实现了智能船舶的实船自主研制并投入商业化运营，是全球首艘获得智能船入级符号（英国劳氏船级社和中国船级社）的真正意义上的智能船舶。近年来，“智能船舶”是业界的热门关键词之一，深受业界关注。随着这次两年一度的中国海事展的盛大开幕，船舶智能化，乃至无人船已经在中国落地生根，蓬勃发展。

Hypoxia-inducible factor 1alpha and vascular endothelial growth factor in Glioblastoma Multiforme:a systematic review going beyond pathologic implications

Glioblastoma multiforme(GBM)is an aggressive primary brain tumor characterized by extensive heterogeneity and vascular proliferation.Hypoxic conditions in the tissue microenvironment are considered a pivotal player leading tumor progression.Specifically,hypoxia is known to activate inducible factors,such as hypoxia-inducible factor 1alpha(HIF-1α),which in turn can stimulate tumor neo-angiogenesis through activation of various downward mediators,such as the vascular endothelial growth factor(VEGF).Here,we aimed to explore the role of HIF-1α/VEGF immunophenotypes alone and in combination with other prognostic markers or clinical and image analysis data,as potential biomarkers of GBM prognosis and treatment efficacy.We performed a systematic review(Medline/Embase,and Pubmed database search was completed by 16th of April 2024 by two independent teams;PRISMA 2020).We evaluated methods of immunoassays,cell viability,or animal or patient survival methods of the retrieved studies to assess unbiased data.We used inclusion criteria,such as the evaluation of GBM prognosis based on HIF-1α/VEGF expression,other biomarkers or clinical and imaging manifestations in GBM related to HIF-1α/VEGF expression,application of immunoassays for protein expression,and evaluation of the effectiveness of GBM therapeutic strategies based on HIF-1α/VEGF expression.We used exclusion criteria,such as data not reporting both HIF-1αand VEGF or prognosis.We included 50 studies investigating in total 1319 GBM human specimens,18 different cell lines or GBM-derived stem cells,and 6 different animal models,to identify the association of HIF-1α/VEGF immunophenotypes,and with other prognostic factors,clinical and macroscopic data in GBM prognosis and therapeutic approaches.We found that increased HIF-1α/VEGF expression in GBM correlates with oncogenic factors,such as miR-210-3p,Oct4,AKT,COX-2,PDGF-C,PLDO3,M2 polarization,or ALK,leading to unfavorable survival.Reduced HIF-1α/VEGF expression correlates with FIH-1,ADNP,or STAT1 upregulation,as well as with clinical manifestations,like epileptogenicity,and a favorable prognosis of GBM.Based on our data,HIF-1αor VEGF immunophenotypes may be a useful tool to clarify MRI-PET imaging data distinguishing between GBM tumor progression and pseudoprogression.Finally,HIF-1α/VEGF immunophenotypes can reflect GBM treatment efficacy,including combined first-line treatment with histone deacetylase inhibitors,thimerosal,or an active metabolite of irinotecan,as well as STAT3 inhibitors alone,and resulting in a favorable tumor prognosis and patient survival.These data were supported by a combination of variable methods used to evaluate HIF-1α/VEGF immunophenotypes.Data limitations may include the use of less sensitive detection methods in some cases.Overall,our data support HIF-1α/VEGF’s role as biomarkers of GBM prognosis and treatment efficacy.

阿尔茨海默病病变相关脑区Pgc-1alpha敲除小鼠模型的构建

目的:构建在阿尔茨海默病(Alzheimer′s disease,AD)病变相关脑区过氧化物酶体增殖物激活受体γ辅激活因子-1α(peroxisome proliferator-activated receptorγcoactivator-1 alpha,Pgc-1alpha)敲除小鼠。方法:引入Pgc-1alpha条件性敲除杂合子小鼠(Pgc-1alphafl/+),通过自交获得Pgc-1alpha条件性敲除纯合子小鼠(Pgc-1alphafl/fl)。将Pgc-1alphafl/fl纯合子小鼠和在AD病变脑区(皮层、海马)特异性表达Cre重组酶的Cre工具鼠(Calb1-Cre)杂交,提取子代转基因小鼠基因组DNA,行PCR鉴定,确定其基因型;采用蛋白免疫印迹技术检测转基因小鼠与野生型小鼠脑区及肾脏PGC-1α蛋白表达。结果:双重PCR鉴定结果显示,同时扩增出400 bp及444 bp条带的小鼠为AD病变脑区Pgc-1alpha敲除纯合子小鼠(Pgc-1alphafl/fl::Calb1-Cre,Pgc-1alpha-/-)。蛋白免疫印迹结果显示,与野生型小鼠相比,条件性敲除小鼠脑区PGC-1α蛋白表达明显减少(P<0.05)。结论:成功构建在AD病变相关脑区Pgc-1alpha敲除小鼠。

A higher prediction accuracy–based alpha–beta filter algorithm using the feedforward artificial neural network

The alpha–beta filter algorithm has been widely researched for various applications,for example,navigation and target tracking systems.To improve the dynamic performance of the alpha–beta filter algorithm,a new prediction learning model is proposed in this study.The proposed model has two main components:(1)the alpha–beta filter algorithm is the main prediction module,and(2)the learning module is a feedforward artificial neural network(FF‐ANN).Furthermore,the model uses two inputs,temperature sensor and humidity sensor data,and a prediction algorithm is used to predict actual sensor readings from noisy sensor readings.Using the novel proposed technique,prediction accuracy is significantly improved while adding the feed‐forward backpropagation neural network,and also reduces the root mean square error(RMSE)and mean absolute error(MAE).We carried out different experiments with different experimental setups.The proposed model performance was evaluated with the traditional alpha–beta filter algorithm and other algorithms such as the Kalman filter.A higher prediction accuracy was achieved,and the MAE and RMSE were 35.1%–38.2%respectively.The final proposed model results show increased performance when compared to traditional methods.

Numerical study of alpha particle loss with toroidal field ripple based on CFETR steady-state scenario

Effects of plasma equilibrium parameters on the alpha particle loss with the toroidal field ripple based on the CFETR steady-state scenario have been numerically investigated by the orbit-following code GYCAVA. It is found that alpha particle losses decrease and loss regions become narrower with the plasma current increasing or with the magnetic field decreasing. It is because the ripple stochastic transport and the ripple well loss of alpha particle are reduced with the safety factor decreasing. Decrease of the plasma density and temperature can reduce alpha particle losses due to enhancement of the slowing-down effect. The direction of the toroidal magnetic field can significantly affect heat loads induced by lost alpha particle. The vertical asymmetry of heat loads induced by the clockwise and counter-clockwise toroidal magnetic fields are due to the fact that the ripple distribution is asymmetric about the mid-plane, which can be explained by the typical orbits of alpha particle. The maximal heat load of alpha particle for the clockwise toroidal magnetic field is much smaller than that for the counter-clockwise one.

Alpha7 nicotinic receptors as potential theranostic targets for experimental stroke

Inflammatory reflex and cholinergic anti-inflammatory pathway:Innate immune system triggers a local inflammatory response following an injury or a pathogen invasion.Likewise,this inflammatory response is limited by rapid,localized,and adaptive anti-inflammatory responses which are crucial for maintaining homeostasis.Hence,the loss of these responses converts a limited and protective inflammatory response into an excessive and harmful response.Anti-inflammatory responses are integrated into the central nervous system,since the central nervous system accumulates information about harmful events,activates defenses,and builds memory for survival.At the same time,it has been demonstrated that hypothalamic neuronal signaling can be altered by inflammation in peripheral tissues.Additionally,immune cells release neuropeptides and neurotransmitters such as acetylcholine(ACh),the main neurotransmitter of the parasympathetic autonomic nervous system,evidencing the communication between the immune and nervous systems(Tracey,2002).

Alpha-synuclein in mitochondrial dysfunction:opportunities or obstacles

Recent work suggests a link betweenα-synuclein(α-syn)and mitochondrial dysfunction;however,the mechanisms of howα-syn influences mitochondrial function are still unclear.Most notably,whetherα-syn plays a direct role during mitochondrial function and/or whether diseasedα-syn-mediated mitochondrial dysfunction is a potential modifiable risk factor in Parkinson’s disease(PD)is unknown.To date,mutations in more than eight genes cause familial PD(fPD)and have functions in diverse pathways including synaptic homeostasis,mitochondria maintenance,autophagy/lysosome,and ubiquitin-proteasome pathways.

Hydrographic Characteristics and Oceanic Heat Flux in the Upper Arctic Ocean over the Alpha Ridge Observed by the DTOP Platform in 2018 and 2021

In 2018 and 2021,the Drift-Towing Ocean Profilers(DTOP)provided extensive temperature and salinity data on the upper 120m ocean through their drifts over the Alpha Ridge north of the Canada Basin.The thickness and temperature maximum of Alaska Coastal Water(ACW)ranged from 20m to 40m and-1.5℃to-0.8℃,respectively,and the salinity generally maintained from 30.2 to 32.5.Comparison with World Ocean Atlas 2018’s climatology manifested a 40m-thick and warm ACW roughly ex-ceeding the temperature maximum by 0.4–0.5℃in June–August 2021.This anomalously warm ACW was highly related to the ex-pansion of the Beaufort Gyre in the negative Arctic Oscillation phase.During summer,the under-ice oceanic heat flux F_(w)^(OHF)was elevated,with a maximum value of above 25Wm^(-2).F_(w)^(OHF)was typically low in the freezing season,with an average value of 1.2Wm^(-2).The estimates of upward heat flux contributed by ACW to the sea ice bottom F_(w)^(OHF)were in the range of 3–4Wm^(-2)in June–August 2021,when ACW contained a heat content of more than 80MJm^(-2).The heat loss over this period was driven by a weak stratification upon the ACW layer associated with a surface mixed layer(SML)approaching the ACW core.After autumn,F_(w)^(OHF)was reduced(<2 Wm^(-2))except during rare events when it elevated F_(w)^(OHF)slightly.In addition,the intensive and widespread Ekman suction,which created a violent upwelling north of the Canada Basin,was largely responsible for the substantial cooling and thinning of the ACW layer in the summer of 2021.

基于改进Alpha Shape算法的点云数据岛屿边界提取

针对机载LiDAR点云的岛屿岸线提取过程复杂、附属岛屿岸线难以提取等问题,提出一种基于改进Alpha Shape算法的点云数据岛屿边界提取方法。首先利用布料模拟滤波算法剔除非岛屿点云数据,通过欧式聚类进行不同岛屿的提取,再将岛屿点云数据投影至二维平面,并根据岛屿点云构建格网。在此基础上使用自适应Alpha Shape算法,对提取出的岛屿点云进行边界提取,即可得到岛屿的岸线轮廓。选取新西兰的玛提尤/萨姆斯岛作为研究区域,并将本文算法与Alpha Shape算法进行对比,结果表明:本文算法提取岛屿边界点云的精准度为97.78%,可以准确地提取岛屿岸线,为海岛规划提供参考。

AlphaFold 3将助力药物研发

2024年5月8日出版的《自然》报道了AlphaFold 3能以较高准确率预测蛋白质与其他生物分子相互作用的结构。AlphaFold 3是该人工智能模型的最新迭代,准确率与之前的专用工具相比显著提升,该模型由谷歌DeepMind和Isomorphic实验室的团队研发。这一最新模型能够预测蛋白质数据库(Protein Data Bank)内几乎所有分子类型复合物的结构。

数学计算法和软件拟合法在虚拟和真实alpha粒子能损测量Mylar膜厚度实验中的比较

根据中山大学物理与天文学院近代物理实验虚拟核实验连续三个年级的本科生实验报告,发现学生在用数学公式计算Mylar膜厚度时,与理论值出现较大误差,各年级的平均相对误差分别为445.02%、335.45%和519.92%。为了查找误差原因,做了真实核实验并依旧采用数学计算方法计算Mylar膜厚度,发现仍旧与理论值出现较大误差,相对误差值为207.72%。而采用Srim软件计算虚拟核实验Mylar膜厚度和真实核实验Mylar膜厚度时,相对误差很小,分别为7.47%和20.1%。从而判定,用数学组合公式在计算多原子化合物Mylar膜时,不准确度较高,误差较大。

Gross Alpha and Beta Activities and Related Lifetime Risks Assessment Due to Ingestion of Drinking Water from Different Sources in the District of Abidjan, Cote d’Ivoire

Drinking good quality water is essential for better health. It is therefore essential to assess the radiological quality of all water consumed in the District of Abidjan in order to prevent related hazards. Thus, the objective of this study was to assess the risk of cancer due to the ingestion of alpha and beta emitting radionuclides in the different types of water consumed in the region. A total of 63 water samples with 43 tap water samples, 5 bottled mineral water and 15 sachet water samples was collected and taken to GAEC laboratory for analysis. The low background Gas-less Automatic Alpha/Beta counting system (Canberra iMaticTM) was used to determine alpha and beta activity concentrations. Activity concentrations of both gross alpha and gross beta obtained in water sample were respectively lower than the WHO recommended limits of 0.1 Bq/l and 1 Bq/l. Also, the annual effective dose and total equivalent effective dose found in mineral bottled water samples were higher than in other types of water. The assessment of radiological lifetime risk has shown values of cancer risk due to ingestion alpha and beta emitters lower than recommended limit. These results indicate that there is no health hazard associated to consumption of water in the District of Abidjan.

一种alpha噪声背景下的波达方向估计算法

针对在alpha噪声干扰背景下传统DOA估计算法大多性能不佳的问题,提出一种基于相关熵的降维MUSIC估计算法。首先基于阵列信号模型和alpha噪声特性分析alpha噪声背景下的信号接收模型,然后引入相关熵算子并与降维MUSIC算法相结合,最后使用Matlab对所提算法进行仿真,仿真结果证明了所提算法的有效性。该算法提升了alpha噪声干扰下的目标参数估计精度,在雷达目标探测领域有一定的工程应用价值。

Alpha稳定分布噪声下基于轻量级网络的自动调制识别技术

自动调制识别在无线通信领域发挥了巨大作用。多数研究中假设的加性高斯白噪声信道已不再满足实际信道环境的准确描述。实际中,由于闪电、雷暴、多用户干扰、设备故障等原因,信道环境中广泛存在Alpha稳定分布噪声。因此对其开展研究更符合实际且具有挑战性。该文针对Alpha稳定分布噪声提出了一种预处理联合轻量级网络的调制识别方法。首先,通过对数域映射及阈值限制对接收信号进行预处理,抑制由Alpha稳定分布噪声带来的尖锐脉冲将信号幅度控制到合理范围;然后,提出一种基于Ghost模块的轻量级网络来完成信号的调制识别分类任务。实验结果表明,与现有的CLDNN(Convolutional Long Short-term Deep Neural Network)、CNN(Convolutional Neural Network)、ResNe(t Residual Network)相比,本文所提方法具有较高的识别准确率及较低的计算复杂度。

改进Alpha Shapes和快速凸壳算法的SVM故障诊断

现有的基于凸壳的支持向量机(SVM)算法处理机械装备产生的大规模原始数据时间太长。针对这一问题,通过结合轮廓提取算法(Alpha Shapes)和快速凸壳算法,提出一种结合改进快速凸壳算法的SVM用于故障诊断研究。该融合算法利用改进简化的Alpha Shapes算法提取点集的边界数据点,作为改进的快速凸壳算法的对象,减少凸壳算法递归的工作量。实验结果表明:该算法平均只提取了数据集0.26%的数据点,且计算的时间也相应降低。最后实验同样表明该算法的性能优于单一的SVM算法。

Where Does AlphaGo Go: From Church-Turing Thesis to AlphaGo Thesis and Beyond

An investigation on the impact and significance of the AlphaGo vs. Lee Sedol Go match is conducted, and concludes with a conjecture of the AlphaGo Thesis and its extension in accordance with the Church-Turing Thesis in the history of computing. It is postulated that the architecture and method utilized by the AlphaGo program provide an engineering solution for tackling issues in complexity and intelligence. Specifically, the AlphaGo Thesis implies that any effective procedure for hard decision problems such as NP-hard can be implemented with AlphaGo-like approach. Deep rule-based networks are proposed in attempt to establish an understandable structure for deep neural networks in deep learning. The success of AlphaGo and corresponding thesis ensure the technical soundness of the parallel intelligence approach for intelligent control and management of complex systems and knowledge automation. © 2014 Chinese Association of Automation.

Alpha-7 nicotinic acetylcholine receptor agonist treatment in a rat model of Huntington's disease and involvement of heme oxygenase-1

Neuroinflammation is a common element involved in the pathophysiology of neurodegenerative diseases.We recently reported that repeated alpha-7 nicotinic acetylcholine receptor（α7 n ACh R） activations by a potent agonist such as PHA 543613 in quinolinic acid-injured rats exhibited protective effects on neurons.To further investigate the underlying mechanism,we established rat models of early-stage Huntington＇s disease by injection of quinolinic acid into the right striatum and then intraperitoneally injected 12 mg/kg PHA 543613 or sterile water,twice a day during 4 days.Western blot assay results showed that the expression of heme oxygenase-1（HO-1）,the key component of the cholinergic anti-inflammatory pathway,in the right striatum of rat models of Huntington＇s disease subjected to intraperitoneal injection of PHA 543613 for 4 days was significantly increased compared to the control rats receiving intraperitoneal injection of sterile water,and that the increase in HO-1 expression was independent of change in α7 n ACh R expression.These findings suggest that HO-1 expression is unrelated to α7 n ACh R density and the increase in HO-1 expression likely contributes to α7 n ACh R activation-related neuroprotective effect in early-stage Huntington＇s disease.

模型与数据双驱动的失眠脑电alpha节律研究

失眠是一种典型的睡眠障碍,以入睡困难、睡眠深度或频度过短、早醒及睡眠时间不足等为主要特征。临床上一些失眠患者在快速眼动(REM)睡眠期会出现明显的脑电alpha节律活动增强现象,但发生这一现象的内在机制尚不清楚。基于此,从计算神经科学的角度出发,结合Liley神经计算模型与临床失眠脑电数据,探索失眠患者在REM期典型放电节律的发生机制。首先,设计一种基于马尔可夫蒙特卡洛的Liley模型关键参数的自动选择与估计方法;其次,结合失眠患者脑电数据,确定影响alpha节律发放的模型关键参数,并据此给出失眠患者REM期脑电alpha节律活动增强的机制假设:抑制性突触活动强度的降低会诱导alpha节律活动的增强。所获结果对于改善失眠患者的睡眠质量并控制病情发展具有一定的指导作用和临床价值。

Advanced algorithms for retrieving pileup peaks of digital alpha spectroscopy using antlions and particle swarm optimizations

Optimization algorithms are applied to resolve the second-order pileup(SOP)issue from high counting rates occurring in digital alpha spectroscopy.These are antlion optimizer(ALO)and particle swarm optimization(PSO)algorithms.Both optimization algorithms are coupled to one of the three proposed peak finder algorithms.Three custom time-domain algorithms are proposed for retrieving SOP peaks,namely peak seek,slope tangent,and fast array algorithms.In addition,an average combinational algorithm is applied.The time occurrence of the retrieved peaks is tested for an elimination of illusive pulses.Conventional methods are inaccurate and timeconsuming.ALO and PSO optimizations are used for the localization of retrieved peaks.Optimum cost values that achieve the best fitness values are demonstrated.Thus,the optimum positions of the detected peak heights are achieved.Evaluation metrics of the optimized algorithms and their influences on the retrieved peaks parameters are established.Comparisons among such algorithms are investigated,and the algorithms are inspected in terms of their computational time and average error.The peak seek algorithm achieves the lowest average computational error for pulse parameters(amplitude and position).However,the fast array algorithm introduces the largest average error for pulse parameters.In addition,the peak seek algorithm coupled with an ALO or PSO algorithm is observed to realize a better performance in terms of the optimum cost and computational time.By contrast,the performance of the peak seek recovery algorithm is improved using the PSO.Furthermore,the computational time of the peak optimization using the PSO is much better than that of the ALO algorithm.As a final conclusion,the accuracy of the peaks detected by the PSO surpasses that for the peaks detected by the ALO.The implemented peak retrieval algorithms are validated through a comparison with experimental results from previous studies.The proposed algorithms achieve a notable precision for compensation of the SOP peaks within the alpha ray spectroscopy at a high counting rate.

假如AlphaGo用来做情报

在刚刚结束的人机围棋巅峰对决中,谷歌人工智能围棋程序Alpha Go以4:1击败了人类选手李世石。全世界都兴奋了,似乎每一个人都想说上几句话,那几天如果开口不谈论"阿尔法狗"都不好意思。其实,只有真正理解人工智能——Artificial Intelligence(AI)的专业人士才能说出一些"所以然"来。人工智能界明白:这是深度学习(deep-learning)和大数据技术的胜利。在这样的"科技大事件"发生的时刻。