Target-Specific Precision of CRISPR-Mediated Genome Editing

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Multisensor Data Fusion for High Quality Data Analysis and Processing in Measurement and Instrumentation

Multisensor data fusion （MDF） is an emerging technology to fuse data from multiple sensors in order to make a more accurate estimation of the environment through measurement and detection. Applications of MDF cross a wide spectrum in military and civilian areas. With the rapid evolution of computers and the proliferation of micro-mechanical/electrical systems sensors, the utilization of MDF is being popularized in research and applications. This paper focuses on application of MDF for high quality data analysis and processing in measurement and instrumentation. A practical, general data fusion scheme was established on the basis of feature extraction and merge of data from multiple sensors. This scheme integrates artificial neural networks for high performance pattern recognition. A number of successful applications in areas of NDI （Non-Destructive Inspection） corrosion detection, food quality and safety characterization, and precision agriculture are described and discussed in order to motivate new applications in these or other areas. This paper gives an overall picture of using the MDF method to increase the accuracy of data analysis and processing in measurement and instrumentation in different areas of applications.     

The refractory periods and threshold potentials of sequential spikes measured by whole-cell recording

Neurons in the central nervous system are thought to program neural language via firing sequential spikes for guiding animal behaviors. The quantitative profiles of spike intrinsic properties are critically important to understand spike programming. We developed approaches with whole-cell recordings to measure the threshold potentials and refractory periods (RPs) of sequential spikes, and to analyze the relationships of these factors with spike timing precision and capacity at the regular-spiking and fast-spiking neurons in cortical slice. The RPs and threshold potentials of sequential spikes at these two groups of neurons are different and are linearly correlated with spike timing precision and capacity. These data suggest that RPs and threshold potentials essentially navigate the spike programming for the precise and loyal encoding of meaningful neural signals. Our study provides the avenues for decoding the spectrum of the neural signals quantitatively.     

不同坡位对GPS项圈定位性能的影响

GPS项圈已广泛应用于大中型野生动物的野外定位监测,支持野生动物生态学研究和保护管理规划.但由于地形等因素影响,GPS项圈返回的数据可能有定位误差和定位数据缺失偏歧.因此,在进行生境选择等相关生态学研究之前,应对GPS项圈的定位性能进行评估.本研究于2019年11月至2020年10月,在云南大理苍山5个测试点各静态放置...     

A bias correction for estimates of effective population size based on linkage disequilibrium at unlinked gene loci*

Analysis of linkage disequilibrium (=mean squared correlation of allele frequencies at different gene loci) provides a means of estimating effective population size (N _e) from a single sample, but this method has seen much less use than the temporal method (which requires at least two samples). It is shown that for realistic numbers of loci and alleles, the linkage disequilibrium method can provide precision comparable to that of the temporal method. However, computer simulations show that estimates of N _e based on for unlinked, diallelic gene loci are sharply biased downwards ( in some cases) if sample size (S) is less than true N _e. The bias is shown to arise from inaccuracies in published formula for when S and/or N _e are small. Empirically derived modifications to for two mating systems (random mating and lifetime monogamy) effectively eliminate the bias (residual bias in % in most cases). The modified method also performs well in estimating N _e in non-ideal populations with skewed sex ratio or non-random variance in reproductive success. Recent population declines are not likely to seriously affect , but if N has recently increased from a bottleneck can be biased downwards for a few generations. These results should facilitate application of the disequilibrium method for estimating contemporary N _e in natural populations. However, a comprehensive assessment of performance of with highly polymorphic markers such as microsatellites is needed.The US Governmentȁ9s right to retain a non-exclusive, royalty-free license in and to any copyright is acknowledged.     

A general framework for subgroup detection via one-step value difference estimation

Recent statistical methodology for precision medicine has focused on either identification of subgroups with enhanced treatment effects or estimating optimal treatment decision rules so that treatment is allocated in a way that maximizes, on average, predefined patient outcomes. Less attention has been given to subgroup testing, which involves evaluation of whether at least a subgroup of the population benefits from an investigative treatment, compared to some control or standard of care. In this work, we propose a general framework for testing for the existence of a subgroup with enhanced treatment effects based on the difference of the estimated value functions under an estimated optimal treatment regime and a fixed regime that assigns everyone to the same treatment. Our proposed test does not require specification of the parametric form of the subgroup and allows heterogeneous treatment effects within the subgroup. The test applies to cases when the outcome of interest is either a time-to-event or a (uncensored) scalar, and is valid at the exceptional law. To demonstrate the empirical performance of the proposed test, we study the type I error and power of the test statistics in simulations and also apply our test to data from a Phase III trial in patients with hematological malignancies.     

The influence of developmental mortality on optimal sex allocation under local mate competition

In panmictic populations, optimal sex allocation is, under theassumptions of Fisher's model, not influenced by the probabilityof offspring developmental mortality, or by differences in mortalitybetween the sexes. In contrast, when mating opportunities areconfined to siblings, developmental mortality can influenceoptimal sex allocation. Many animal species have both localmating and developmental mortality. We show that when developmentalmortality is random for individual offspring, optimal sex allocationis influenced by mortality among males but not among females.Male mortality increases the allocation to males, but this shouldnever be male biased, even under extreme male mortality. Thisresult applies both when mothers are able to control the sexof individual offspring precisely, and when sex is allocatedwith binomial probability. The influence of mortality becomesprogressively larger when the variance of the distribution ofmortality over clutches diminishes. The reduction in fitnessis greater than the proportion of mortality, especially at smallclutch sizes, and mortality reduces the advantage of producingprecise sex ratios, and of local mate competition in general.     

Precision agriculture: a challenge for crop nutrition management

Precision agriculture was initiated in the mid 1980s, using newly available technologies, to improve the application of fertilizers by varying rates and blends as needed within fields. Presently, the concept has been adapted to a variety of practices, crops, and countries. Its adoption varies significantly by cropping system, regions, and countries but it is progressively introduced or evaluated around the world. Several types of challenges limit a broader adoption: socio-economical, agronomical, and technological. Socio-economical barriers are principally costs and lack of skills. Agronomical challenges are lack of basic information, inadequate sampling and scouting procedures, absence of site-specific fertilizer recommendations, misuse of information, and lack of qualified agronomic services. There are multiple technological barriers that relate to machinery, sensor, GPS, software, and remote sensing. However, these barriers will be progressively lifted and precision agriculture will be a significant component of the agricultural system of the future. It offers a variety of potential benefits in profitability, productivity, sustainability, crop quality, food safety, environmental protection, on-farm quality of life, and rural economic development.     

The effects of environmental heterogeneity on root growth and root/shoot partitioning

AIMS: The purpose of this Botanical Briefing is to stimulate reappraisal of root growth, root/shoot partitioning, and analysis of other aspects of plant growth under heterogeneous conditions. SCOPE: Until recently, most knowledge of plant growth was based upon experimental studies carried out under homogeneous conditions. Natural environments are heterogeneous at scales relevant to plants and in forms to which they can respond. Responses to environmental heterogeneity are often localized rather than plant-wide, and not always predictable from traditional optimization arguments or from knowledge of the ontogenetic trends of plants growing under homogeneous conditions. These responses can have substantial impacts, both locally and plant-wide, on patterns of resource allocation, and significant effects on whole-plant growth. Results from recent studies are presented to illustrate responses of plants, plant populations and plant communities to nutritionally heterogeneous conditions. CONCLUSIONS: Environmental heterogeneity is a constant presence in the natural world that significantly influences plant behaviour at a variety of levels of complexity. Failure to understand its effects on plants prevents us from fully exploiting aspects of plant behaviour that are only revealed under patchy conditions. More effort should be invested into analysis of the behaviour of plants under heterogeneous conditions.     

Sizing-up finite fluorescent particles with nanometer-scale precision by convolution and correlation image analysis

Determining the positions, shapes and sizes of finite living particles such as bacteria, mitochondria or vesicles is of interest in many biological processes. In fluorescence microscopy, algorithms that can simultaneously localize such particles as a function of time and determine the parameters of their shapes and sizes at the nanometer scale are not yet available. Here we develop two such algorithms based on convolution and correlation image analysis that take into account the position, orientation, shape and size of the object being tracked, and we compare the precision of the two algorithms using computer simulations. We show that the precision of both algorithms strongly depends on the objects size. In cases where the diameter of the object is larger than about four to five times the beam waist radius, the convolution algorithm gives a better precision than the correlation algorithm (it leads to more precise parameters), while for smaller object diameters, the correlation algorithm gives superior precision. We apply the convolution algorithm to sequences of confocal laser scanning micrographs of immobile Escherichia coli bacteria, and show that the centroid, the front end, the rear end, the left border and the right border of a bacterium can be determined with a signal-to-noise-dependent precision down to ~5 nm.