珠江口盆地珠一坳陷古近系高自然伽马砂岩形成机制及油气地质意义

运用放射性元素寻找油气是一种非常规油气勘探手段。近年来,在珠江口盆地珠一坳陷富烃凹陷周边古近系钻遇高自然伽马(GR)砂岩,其GR值(100~300 API)甚至大于同区泥岩的GR值(100~200 API)。为了弄清该特殊现象背后的地质意义,对珠江口盆地珠一坳陷古近系高自然伽马砂岩开展了铀(U)、钍(Th)、钾(K)等3种元素含量与GR值的相关趋势线分析,从井震特征、岩性特征及矿物成分特征等入手分析了砂岩GR值增高的主要原因及成因机制,探讨了放射性元素聚集的条件、运移通道、驱动力以及油气意义。结果表明:西江、惠州地区由U含量增高导致砂岩GR值偏高,恩平、番禺地区由K,Th含量增高导致砂岩GR值偏高;砂岩GR值增高有两大成因机制,一是地下流体带来的放射性元素离子U4+在氧化-还原面处富集后导致地层GR值偏高,这种特殊现象说明在具有连通基底大断裂旁的圈闭中,U4+的富集指示了曾经油气的存在,证实了研究区油气运移通道的有效性,对于油气藏的预测有着非常重要的指导性意义,二是地表流体带来的含放射性元素的矿物大量沉积后导致地层GR值偏高,含放射性元素矿物性质不稳定,可指示近源供给的存在,对于判断物源及沉积环境有着非常重要的意义。该研究成果为预测研究区油气成藏有利区带提供了依据。     

基于层次分析法的叶用甜菜种质资源观赏性评价

根据叶用甜菜品种的观赏特性,运用层次分析法初步建立叶用甜菜品种观赏价值的评价模型,包含叶梗、叶片和整体感3个方面共11个评价因子。结果表明:叶梗是评价叶用甜菜观赏价值的核心要素;叶梗色、叶梗厚、叶丛型是重要因子,分别以红、粉红、粉白叶梗,叶梗厚度厚和直立型叶丛为优良性状。利用该评价模型对8个甜菜品种进行观赏价值综合评价,筛选出‘Clnx-blush2018'、'Clnx-fen2018’和‘荷兰必久'3个观赏价值高、适于市场推广叶品种。     

一类分数阶微积分的中值定理及应用

Riemann-Liouville分数阶微积分算子是一类带有一个函数的分数阶微积分算子的特殊情形，以Riemann-Liouville分数阶微积分算子的积分中值定理和微分中值定理为基础，我们得到了一类带有一个函数的分数阶微积分算子的积分中值定理和微分中值定理，并给出其在计算方面的一些应用。     

自重湿陷性黄土地基预钻孔浸水处理的可靠度设计方法

为解决传统预浸水法存在的浸水时间长、浸水处理范围难以确定等不足,基于土体中水分运移规律,依据可靠度理论、极限状态设计方法及复合 Poisson 过程原理,提出一种消除黄土湿陷性的处理浸水方法——预钻孔浸水法。给出了利用预钻孔浸水法对自重湿陷性黄土地基进行浸水时,水平向及竖直向浸水影响范围的确定模型;在此基础上结合达西定律给出了浸水孔设计参数如孔深、孔间距及浸水孔个数的确定方法。结合铜川某工程,设计进行了现场预钻孔浸水试验,对该方法的合理性进行了验证,并通过现场钻探、现场勘探、室内湿陷性试验等方法对该方法的处理效果进行了评价。该浸水方法具有浸水时间短、浸水影响范围可根据浸水孔布设进行控制等优点,且浸水处理效果良好,完全符合施工要求。     

减振沟对爆破振动加速度峰值减振效应的试验研究

通过对减振沟开挖前后两个阶段爆破振动加速度峰值的监测,采用回归分析的方法,得到两种情况下的萨道夫斯基经验公式。通过对比分析的方法,得到减振沟对振动加速度峰值的减振规律。结果表明,合理的开挖减振沟可有效地降低爆破振动加速度峰值。     

Deterministic and probabilistic ship pitch prediction using a multi-predictor integration model based on hybrid data preprocessing,reinforcement learning and improved QRNN

The deterministic and probabilistic prediction of ship motion is important for safe navigation and stable real-time operational control of ships at sea. However, the volatility and randomness of ship motion, the non-adaptive nature of single predictors and the poor coverage of quantile regression pose serious challenges to uncertainty prediction, making research in this field limited. In this paper, a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved quantile regression neural network (QRNN) is proposed to explore the deterministic and probabilistic prediction of ship pitch motion. To validate the performance of the proposed multi-predictor integrated prediction model, an experimental study is conducted with three sets of actual ship longitudinal motions during sea trials in the South China Sea. The experimental results indicate that the root mean square errors (RMSEs) of the proposed model of deterministic prediction are 0.0254°, 0.0359°, and 0.0188°, respectively. Taking series #2 as an example, the prediction interval coverage probabilities (PICPs) of the proposed model of probability predictions at 90%, 95%, and 99% confidence levels (CLs) are 0.9400, 0.9800, and 1.0000, respectively. This study signifies that the proposed model can provide trusted deterministic predictions and can effectively quantify the uncertainty of ship pitch motion, which has the potential to provide practical support for ship early warning systems.     

基于SVD和SSA-VMD降噪的轴承故障特征提取

针对强噪声背景下轴承故障特征提取困难的问题，提出一种基于奇异值分解和参数优化变分模态分解联合降噪的轴承故障特征提取方法(SSVMD)：首先，对原始信号进行奇异值分解(Singular Value Decomposition，SVD)处理，运用奇异值差分谱法选取有效奇异值并将原始信号重构得到初步降噪信号；其次，为防止故障信息丢失，将残余信号进行麻雀算法(Sparrow Search Algorithm，SSA)优化的变分模态分解(Variational Mode Decomposition，VMD）算法处理，得到最佳的模态个数K和惩罚参数α，选取峭度值最大、包络熵最小的IMF分量与初步降噪信号叠加得到最终降噪信号，并对信号进行包络分析；最后，通过仿真和试验数据分析得出，该方法能在信噪比很低的情况下降低噪声含量并提取轴承故障特征，为设备的状态监测和故障诊断提供理论依据。     

价值网络语境下企业设计价值创新路径研究

目的 在新的视角下，提出一种价值创新路径模型，对设计驱动型企业的价值实现方式进行有效补充。方法 通过文献研究，论述了企业关系由价值链到价值网转变的历史趋势;通过比较研究，对价值实现过程中主客体之间的4种关系进行了类比分析，提出了不同主客体关系状态下设计实践的具体表现方式。结果 在价值网络语境下，以价值论为理论依据，从主客体之间的关系入手，构建设计价值创新路径模型。结论 通过分析证明:“主客体统一状态”是企业价值创造的理想状态;主客体关系一直处于动态的变化过程中;客体对主体的“意义”也一直处于动态变化中。在这种动态变化的关系网络中，设计驱动方式已经成为企业创新的重要模式，企业如何捕获并诠释“意义”，成为价值实现的关键所在。     

Comparative analysis of inbreeding parameters and runs of homozygosity islands in 2 Italian autochthonous cattle breeds mainly raised in the Parmigiano-Reggiano cheese production region

Reggiana and Modenese are autochthonous cattle breeds, reared in the North of Italy, that can be mainly distinguished for their standard coat color (Reggiana is red, whereas Modenese is white with some pale gray shades). Almost all milk produced by these breeds is transformed into 2 mono-breed branded Parmigiano-Reggiano cheeses, from which farmers receive the economic incomes needed for the sustainable conservation of these animal genetic resources. After the setting up of their herd books in 1960s, these breeds experienced a strong reduction in the population size that was subsequently reverted starting in the 1990s (Reggiana) or more recently (Modenese) reaching at present a total of about 2,800 and 500 registered cows, respectively. Due to the small population size of these breeds, inbreeding is a very important cause of concern for their conservation programs. Inbreeding is traditionally estimated using pedigree data, which are summarized in an inbreeding coefficient calculated at the individual level (F_PED). However, incompleteness of pedigree information and registration errors can affect the effectiveness of conservation strategies. High-throughput SNP genotyping platforms allow investigation of inbreeding using genome information that can overcome the limits of pedigree data. Several approaches have been proposed to estimate genomic inbreeding, with the use of runs of homozygosity (ROH) considered to be the more appropriate. In this study, several pedigree and genomic inbreeding parameters, calculated using the whole herd book populations or considering genotyping information (GeneSeek GGP Bovine 150K) from 1,684 Reggiana cattle and 323 Modenese cattle, were compared. Average inbreeding values per year were used to calculate effective population size. Reggiana breed had generally lower genomic inbreeding values than Modenese breed. The low correlation between pedigree-based and genomic-based parameters (ranging from 0.187 to 0.195 and 0.319 to 0.323 in the Reggiana and Modenese breeds, respectively) reflected the common problems of local populations in which pedigree records are not complete. The high proportion of short ROH over the total number of ROH indicates no major recent inbreeding events in both breeds. ROH islands spread over the genome of the 2 breeds (15 in Reggiana and 14 in Modenese) identified several signatures of selection. Some of these included genes affecting milk production traits, stature, body conformation traits (with a main ROH island in both breeds on BTA6 containing the ABCG2, NCAPG, and LCORL genes) and coat color (on BTA13 in Modenese containing the ASIP gene). In conclusion, this work provides an extensive comparative analysis of pedigree and genomic inbreeding parameters and relevant genomic information that will be useful in the conservation strategies of these 2 iconic local cattle breeds.     

Analysis of operating limits and combustion state regulation for low-calorific value gases in industrial burners

The effective and efficient utilization of low-calorific value (LCV) gases has gained increasing attention in scientific research and industrial fields. In this study, the combustion characteristics of three LCV gases in practical devices are analyzed by using a nonadiabatic perfectly stirred reactor model. The complete steady-state solution in the temperature-residence time parameter space is obtained with arc-length continuation. The stable operation region is quantified by the eigenvalue analysis. The transition of solution curves is quantified with heat loss coefficient. Five key system parameters are systematically investigated on their effects on stability limits. With the combustion performance being quantified by a combustion state index, a combustion state regulation method is proposed to find the optimal regulation path of system parameters. Active subspace method is further applied to shorten the regulation step by identifying the active direction. The proposed method and findings are useful for optimal regulation of burning LCV gases in industrial burners.