地震前后垂直形变场动态演化的量化指标

提出一种表达垂直形变场动态演化过程的量化指标——区域应变率、应变集中度。在此基础上，对南北地震带各水准监测区近30年的垂直形变资料进行了实际计算．并结合具体震例进行了对比研究。结果表明：量化指标在一定程度上能够反映地震前后形变场的动态演化过程和地壳运动状态，对地震的中长期预报有一定的积极意义。     

利用历史有感地震目录（M≥3（1／2））研究华北地区地震活动性特征

对新编的华北地区历史有感地震目录（３（１／２）≤Ｍ＜４（１／２））的精度和可信度进行了讨论。认为该地震目录从１４８４年后的记载率较高，它的发震时间、震中位置和震级的精度基本可以满足研究历史地震活动性的需要。它与中国地震目录（Ｍ≥４（３／４））比较，补充了相当数量的３（１／２）≤Ｍ≤４（１／２）的地震。利用历史有感地震目录分析了华北北部部分６级以上的历史地震，结果表明，这些地震在强震发生前具有明显的空区、条带、地震活动性增强、平静等前兆特征，同时，也显示了某些强＊发生前的前震活动和主震之后起伏的强余震活动     

台湾海峡西岸重力场变化梯度场图像分析

讨论了应用曲面拟合技术和利用离散的重力观测点的重力变化对特定研究区的重力场变化进行数值模拟以获取该区重力变化空间梯度场图像的具体方法;并应用该方法获得了2004年3月福建安溪3.6级地震前的重力变化空间梯度场图像,发现空间梯度场图像能清晰地反映出地震前重力场群体性变化的差异性;利用此方法对2005年6月~2006年3月间台湾海峡西岸重力场变化进行数值模拟,获得其空间梯度场图像。     

长诏断裂带垂直运动与地震关系初探

利用跨断层短水准资料分析了长诏断裂带断层活动特征，结果表明：长诏断裂带总体活动性质基本相同．分时段活动性质有所不同。断层各段多数以压性逆断为主，不同于历史地质考察结果。此外，长诏断裂带各断裂都具有分段活动特点。     

昆仑山口大地震与地形变异常的讨论

针对昆仑山口大地震，总结了多种地形变（大地测量）手段所显示的异常变化及其时空分布，结果显示：8．1级大震前存在空间尺度大，时间尺度的地形变前兆异常，简要介绍了相关的异常图像，给出了初步解释，并对未来震情的发展进行了探讨，认为近期内强震活动向华北迁移的可能性不大。     

形变大地测量学的进展、问题与地震预报

简要概括了形变大地测量学的革命性进展，研讨了它的科学特色、功能和定义以及对地球科学和防灾减灾的推动。形变大地测量学有助于从根本上击破多年来制约地震预报的“瓶颈”，但也存在不少急待解决的问题。着重研讨了在21世纪前10年，形变大地测量学如何依托多年的学科积累并充分受益于人造卫星和数字化等新技术，开展创新性研究和试验以推进地震预报。为此，对当前的研究工作提出了12条科学技术途径。最后对学科名称提出了建议。     

概率赋范空间的S-凸和K-凸

文献[1][2]认为M－PN空间是局部凸的。通过定理说明这个结论对t-模T（a,b)≥min(a,b)时成立。又通过反例表明，当t-模型T（a,b)=max(a b-1,0）时无论邻域Nθ（ε，λ）概率有界还是概率半有界结论均不成立。还讨论了Takahashi凸性并对S－凸和K－凸作了比较。     

Wolf-Rayet stars

Summary Recent literature on Population I Wolf-Rayet star research extending from the Milky Way to blue compact dwarf galaxies is reviewed, broken down into inventory, basic parameters and galactic distribution, atmospheres, binaries, intrinsic variability, mass loss, enrichment and evolution. Also the incidence of Wolf-Rayet stars with variable non-thermal radio emission, excess X-ray fluxes, and episodic/periodic IR excesses is reviewed. These phenomena appear to be associated with wind-wind interaction in wide long-period WR+OB binaries and with wind-compact object interaction in WR+c binaries, with orbit sizes of the order of magnitude of the WR radio photosphere sizes or larger.     

Detecting the first objects in the mid-infrared with the Next Generation Space Telescope

We calculate the expected mid-infrared (MIR) molecular hydrogen line emission from the first objects in the Universe. As a result of their low masses, the stellar feedback from massive stars is able to blow away their gas content and collect it into a cooling shell where H₂ rapidly forms and IR roto-vibrational (as for example the rest-frame 2.12 μm) lines carry away a large fraction (up to 10 per cent) of the explosion energy. The fluxes from these sources are in the range 10⁻²¹–10⁻¹⁷ erg s⁻¹ cm⁻² . The highest number counts are expected in the 20-μm band, where about 10⁵ sources deg⁻² are predicted at the limiting flux of 3×10⁻¹⁸ erg s⁻¹ cm⁻². Among the planned observational facilities, we find that the best detection perspectives are offered by the Next Generation Space Telescope ( NGST ), which should be able to reveal about 200 first objects in one hour observation time at its limiting flux in the above band. Therefore, mid-IR instruments appear to represent perfect tools to trace star formation and stellar feedback in the high ( z ≳5) redshift Universe.     

Prediction of Stellar Atmospheric Parameters using Instance-Based Machine Learning and Genetic Algorithms

In this article we present a method for the automated prediction of stellar atmospheric parameters from spectral indices. This method uses a genetic algorithm (GA) for the selection of relevant spectral indices and prototypical stars and predicts their properties, using the k-nearest neighbors method (KNN). We have applied the method to predict the effective temperature, surface gravity, metallicity, luminosity class and spectral class of stars from spectral indices. Our experimental results show that the feature selection performed by the genetic algorithm reduces the running time of KNN up to 92%, and the predictive accuracy error up to 35%. This revised version was published online in July 2006 with corrections to the Cover Date.