Cycle anatomy and variability in the storm-dominated type cincinnatian (Upper Ordovician): coming to grips with cycle delineation and genesis

Although parasequence and sequence are scale-independent terms, they are frequently applied only to specific scales of cycles. For example, meter-scale cycles are commonly assumed to be parasequences or PACs. In the Upper Ordovician Kope and Fairview Formations of northern Kentucky, we examined a succession of 50 meter-scale cycles that have been variously interpreted as deepening-upward, shallowing-upward, or showing no relationship with water depth. Our analysis shows that these cycles, characterized by shifts in storm-bed proximality, are highly variable in their thickness and internal construction. Most cycles are best considered high-frequency sequences, because deepening-upward intervals are common, and many cycles contain evidence of abrupt basinward shifts in facies as expected at sequence boundaries. A minority fit the parasequence model of shallowing-upward cycles bounded by flooding surfaces. Larger, 20 m scale cycles are defined by systematic thickening and thinning trends of meter-scale cycles. However, meter-scale cycles do not display any systematic trends in cycle anatomy as a function of position within the 20 m cycles or position within the Kope and Fairview Formations. The high cycle variability and the lack of systematic stratigraphic organization with respect to longer-term cyclicity reflect either the irregularity of relative sea-level changes, the poor recording of sea-level changes in this deep-water setting, or the generation of these cycles by climate-induced cyclicity in storm intensity. These three mechanisms would generate similar patterns at the outcrop scale, so it is not possible at the present to distinguish between them.     

麻粒岩成因：变质观

尽管许多当代评述都强调麻粒岩在其压力—温度(P—T)条件和轨迹方面的一致性,但实际上麻粒岩保存了指示它们的形成模式多样性的一系列重要的岩石学特征。对90多个麻粒岩地体或产状的测定,揭示出其中50％以上记录了超出许多作者提出的7.5±1Kb和800±50℃平均麻粒岩范围的P—T条件。特别是,不断识别出的温度很高(900～1000℃)的一些地体的数量还在增加,这两种P—T条件都是根据特殊的矿物组合和地温压力测定确定的。确定和解释P—T历史的岩石成因网格和地温压力测定法二者都是在反应结构范围内判断的,而反应结构既可证明很大的P—T条件范围确实是真实的,又可证明近等温减压(ITD)和近等压冷却(IBC)两种P—T轨迹都是主要的。正象在南印度和斯里兰卡见到的那样,由富CO_2流体进入而引起斜长角闪岩—麻粒岩的转化是一种例外情况,不代表大多数地体中有关的流体过程。然而,人们认为缺少流体条件是在接近它们记录的热高峰时间的大多数麻粒岩的特征。把ITD麻柱岩解释为地壳碰撞增厚过程中形成的。伴随的岩浆填加作用是一个重要的额外热源。但没有把侵蚀作用单独看作是碰撞后的主要减薄过程。换言之,ITD轨迹是在中等或略低的速率扩张期间与构造剥露有关的、削减非常迅速的(1～2mm/年暴露)阶段产生的。IBC麻粒岩可能形成于各种各样的环境中。呈现逆时针P—T历史的麻粒岩被解释为形成于大量岩浆增生作用的下部地区,这些地区有或无附加地壳扩张。正常厚度地壳的扩张期间也可形成浅部(<0.5GPa)的IBC麻枉岩,但较深层位的IBC则要求更复杂的模式。在地壳深部出现的许多IBC麻粒岩可能形成于经受碰撞后非常迅速(5mm/a)扩张变薄的增厚地壳中。推测在许多麻粒岩中与其说ITD,还不如说IBC轨迹的保存主要是与增厚地壳的扩张减薄的速率和时间范围有关,而且也应当见到ITD到IBC之间的混杂轨迹。大多数IBC麻粒岩,也许还有许多ITD麻粒岩,都没有作为产生它们的构造幕的结果暴露在地表,但是,它们在这些事件之后,在中部或下部地壳中保留了很长一段时间(100～200Ma)。大多数麻粒岩地体最后剥露只有通过它们掺杂到与其形成无关的、后来的构造和岩浆事件中才能发生。     

Composition and distribution of beach debris in Orange County, California

Many studies have quantified debris collected on beaches around the world. Only a few of those studies have been conducted in the United States, and they are largely limited to semi-quantitative efforts performed as part of volunteer clean-up activities. This study quantifies the distribution and composition of beach debris by sampling 43 stratified random sites on the Orange County, California coast, from August to September 1998. We estimated that approximately 106 million items, weighing 12 metric tons, occur on Orange County beaches. The most abundant items were pre-production plastic pellets, foamed plastics, and hard plastics. Debris density on the remote rocky shoreline was greater than that on high-use sandy beaches for most debris items. This finding partially reflects the periodic clean-up of high-use beaches by local municipalities, and also indicates that a high percentage of the observed debris was transported to the site from waterborne sources.     

On the Maximum Mass of Differentially Rotating Neutron Stars

The analysis of spectral lag between energy bands, which combines temporal and spectral analyses, can add strict constraints to gamma-ray burst (GRB) models. In previous studies, the lag analysis focused on the lags between channel 1 (25-57 keV) and channel 3 (115-320 keV) from the Burst and Transient Source Experiment (BATSE). In this Letter, we analyzed the cross-correlation average lags (including approximate uncertainties) between energy bands for two GRB samples: 19 events detected by Ginga and 109 events detected by BATSE. We paid special attention to the BATSE GRBs with known redshifts because there has been a reported connection between lag and luminosity. This extends our knowledge of spectral lags to lower energy ( approximately 2 keV). We found that lags between energy bands are small. The lag between the peak of approximately 50 keV photons and that of approximately 200 keV photons is approximately 0.08 s. The upper limit in the lag between approximately 9 and approximately 90 keV photons is approximately 0.5 s. Thus, there are not large shifts at low energy. We found that about 20% of GRBs have detectable lags between energy bands in the Ginga and BATSE samples. From the internal shock model, we found that there are three sources of time structure in GRB pulses: cooling, hydrodynamics, and angular effects. We argue that cooling is much too fast to account for our observed lags and that angular effects are independent of energy. Thus, only hydrodynamics can produce these lags. Perhaps the radiation process varies as the reverse shock moves through the shell.     

Latin hypercube approach to estimate uncertainty in ground water vulnerability

A methodology is proposed to quantify prediction uncertainty associated with ground water vulnerability models that were developed through an approach that coupled multivariate logistic regression with a geographic information system (GIS). This method uses Latin hypercube sampling (LHS) to illustrate the propagation of input error and estimate uncertainty associated with the logistic regression predictions of ground water vulnerability. Central to the proposed method is the assumption that prediction uncertainty in ground water vulnerability models is a function of input error propagation from uncertainty in the estimated logistic regression model coefficients (model error) and the values of explanatory variables represented in the GIS (data error). Input probability distributions that represent both model and data error sources of uncertainty were simultaneously sampled using a Latin hypercube approach with logistic regression calculations of probability of elevated nonpoint source contaminants in ground water. The resulting probability distribution represents the prediction intervals and associated uncertainty of the ground water vulnerability predictions. The method is illustrated through a ground water vulnerability assessment of the High Plains regional aquifer. Results of the LHS simulations reveal significant prediction uncertainties that vary spatially across the regional aquifer. Additionally, the proposed method enables a spatial deconstruction of the prediction uncertainty that can lead to improved prediction of ground water vulnerability.