Coarse Mapping Research Articles

Mapping ecological resource use and supply-consumption difference in China from 2000 to 2020

Net primary production (NPP) is a vital ecological resource essential for ecosystem services and economic development. Human appropriation of NPP (HANPP) measures the aggregate impact of human activities on the biomass produced annually in ecosystems. However, the coarse mapping of HANPP hinders the identification of the spatial dynamics in ecological resources use and the high-pressure areas. Using machine learning, our study annually mapped China’s HANPP at 1 km resolution due to grain, wood and animal production as well as land use changes from 2000 to 2020. High-pressure ecological resource zones expanded, primarily due to livestock farming. The pressure of ecological resources varied along the longitudinal axis. Ecological resource use is generally low in poverty areas. The spatial patterns of the supply-consumption difference of the ecological resources were also mapped, reflecting the spatial flows of ecological resources from poverty areas to non-poverty areas. This promotes the sustainable development in both areas.

Intuitive mapping between nonsymbolic quantity and observed action across development

Adults’ concurrent processing of numerical and action information yields bidirectional interference effects consistent with a cognitive link between these two systems of representation. This link is in place early in life: infants create expectations of congruency across numerical and action-related stimuli (i.e., a small [large] hand aperture associated with a smaller [larger] numerosity). Although these studies point to a developmental continuity of this mapping, little is known about the later development and thus how experience shapes such relationships. We explored how number–action intuitions develop across early and later childhood using the same methodology as in adults. We asked 3-, 6-, and 8-year-old children, as well as adults, to relate the magnitude of an observed action (a static hand shape, open vs. closed, in Experiment 1; a dynamic hand movement, opening vs. closing, in Experiment 2) to either a small or large nonsymbolic quantity (numerosity in Experiment 1 and numerosity and/or object size in Experiment 2). From 6 years of age, children started performing in a systematic congruent way in some conditions, but only 8-year-olds (added in Experiment 2) and adults performed reliably above chance in this task. We provide initial evidence that early intuitions guiding infants’ mapping between magnitude across nonsymbolic number and observed action are used in an explicit way only from late childhood, with a mapping between action and size possibly being the most intuitive. An initial coarse mapping between number and action is likely modulated with extensive experience with grasping and related actions directed to both arrays and individual objects.

Coarse-grained modeling of zeolitic imidazolate framework-8 using MARTINI force fields.

In this contribution, the well-known MARTINI particle-based coarse graining approach is tested for its ability to model the ZIF-8 metal-organic framework. Its capability to describe structure, lattice parameters, thermal expansion, elastic constants and amorphization is evaluated. Additionally, the less coarsened models were evaluated for reproducing the swing effect and the host-guest interaction energies were analyzed. We find that MARTINI force fields successfully capture the structure of the Metal-Organic Framework (MOF) for different degrees of coarsening, with the exception of the MARTINI 2.0 models for the less coarse mapping. MARTINI 2.0 models predict more accurate values of C11 and C12, while MARTINI 3.0 has a tendency to underestimate them. Among the possibilities tested, the choice of bead flavors within a particular MARTINI version appears to have a less critical impact in the simulated properties of the empty framework. None of the coarse-grained (CG) models investigated were able to capture the amorphization nor the swing effect within the scope of MD simulations. A perspective on the importance of having a proper Lennard-Jones (LJ) parametrization for modeling guest-MOF and MOF-MOF interactions is highlighted.

183 GHz Water Megamasers in Active Galactic Nuclei: A New Accretion Disk Tracer

We present the results of an Atacama Large Millimeter/submillimeter Array survey to identify 183 GHz H2O maser emission from active galactic nuclei (AGNs) already known to host 22 GHz megamaser systems. Out of 20 sources observed, we detect significant 183 GHz maser emission from 13; this survey thus increases the number of AGN known to host (sub)millimeter megamasers by a factor of 5. We find that the 183 GHz emission is systematically fainter than the 22 GHz emission from the same targets, with typical flux densities being roughly an order of magnitude lower at 183 GHz than at 22 GHz. However, the isotropic luminosities of the detected 183 GHz sources are comparable to their 22 GHz values. For two of our sources—ESO 269-G012 and the Circinus galaxy—we detect rich 183 GHz spectral structure containing multiple line complexes. The 183 GHz spectrum of ESO 269-G012 exhibits the triple-peaked structure characteristic of an edge-on AGN disk system. The Circinus galaxy contains the strongest 183 GHz emission detected in our sample, peaking at a flux density of nearly 5 Jy. The high signal-to-noise ratios achieved by these strong lines enable a coarse mapping of the 183 GHz maser system, in which the masers appear to be distributed similarly to those seen in VLBI maps of the 22 GHz system in the same galaxy and may be tracing the circumnuclear accretion disk at larger orbital radii than the 22 GHz masers. This newly identified population of AGN disk megamasers presents a motivation for developing VLBI capabilities at 183 GHz.

Coarse-to-Fine Hybrid 3D Mapping System With Co-Calibrated Omnidirectional Camera and Non-Repetitive LiDAR

This letter presents a novel 3D mapping robot with an omnidirectional field-of-view (FoV) sensor suite composed of a non-repetitive LiDAR and an omnidirectional camera. Thanks to the non-repetitive scanning nature of the LiDAR, an automatic targetless co-calibration method is proposed to simultaneously calibrate the intrinsic parameters for the omnidirectional camera and the extrinsic parameters for the camera and LiDAR, which is crucial for the required step in bringing color and texture information to the point clouds in surveying and mapping tasks. Comparisons and analyses are made to target-based intrinsic calibration and mutual information (MI)-based extrinsic calibration, respectively. With this co-calibrated sensor suite, the hybrid mapping robot integrates both the odometry-based mapping mode and stationary mapping mode. Meanwhile, we proposed a new workflow to achieve coarse-to-fine mapping, including efficient and coarse mapping in a global environment with odometry-based mapping mode; planning for viewpoints in the region-of-interest (ROI) based on the coarse map (relies on the previous work [1]); navigating to each viewpoint and performing finer and more precise stationary scanning and mapping of the ROI. The fine map is stitched with the global coarse map, which provides a more efficient and precise result than the conventional stationary approaches and the emerging odometry-based approaches, respectively.

The Complementary Value of XBT and Argo Observations to Monitor Ocean Boundary Currents and Meridional Heat and Volume Transports: A Case Study in the Atlantic Ocean

AbstractThis work assesses the value of expendable bathythermograph (XBT) and Argo profiling float observations to monitor the Atlantic Ocean boundary current systems (BCS), meridional overturning circulation (MOC), and meridional heat transport (MHT). Data from six XBT transects and available Argo floats in the Atlantic Ocean for the period from 2000 to 2018 are used to estimate the structure and variability of the BCS, MOC, and MHT, taking into account different temporal and spatial mapping strategies. The comparison of Argo data density along these six XBT transects shows that Argo observations outnumber XBT observations only above mapping scales of 30 days and 3° boxes. The comparison of Argo and XBT data for the Brazil Current and Gulf Stream shows that Argo cannot reproduce the structure and variability of these currents, as it lacks sufficient resolution to resolve the gradients across these narrow jets. For the MHT and MOC, Argo estimates are similar to those produced by XBTs at a coarse mapping resolution of 5° and 30 days. However, at such a coarse resolution the root-mean-square errors calculated for both XBT and Argo estimates relative to a high-resolution baseline are higher than 3 Sv (1 Sv ≡ 106 m3 s−1) and 0.25 PW for the MOC and MHT, respectively, accounting for about 25%–30% of their mean values due to the smoothing of eddy variability along the transects. A key result of this study is that using Argo and XBT data jointly, rather than separately, improves the estimates of MHT, MOC, and BCS.

Multi scale hard x-ray microscopy

The structure of crystalline materials is typically organised hierarchically on several length scales. Hard x-ray microscopy is presented as a collection of modalities that allows to zoom into a mm-sized sample to acquire 3D maps of any embedded region and at essentially all relevant length scales. For coarse mapping of grains, their orientations and average stress state diffraction based tomography methods can sample thousands of grains with a resolution of 2 µm. At the 100 nm scale, domains and dislocations and their associated strain fields can be visualised by diffraction microscopy. Similar to dark field electron microscopy, diffraction and imaging can be combined in several ways. For the ultimate resolution, a bulk version of coherent diffraction imaging is introduced. Hard x-ray microscopy is optimised for acquisition of 3D movies: directly visualising the structural changes during nucleation and growth, deformation or damage. The state of art is provided along with examples of use. I discuss how hard x-ray microscopy studies can enable the formulation and validation of improved multiscale models that account for the entire heterogeneity of materials.

TIMTAM: Tunnel-Image Texturally Accorded Mosaic for Location Refinement of Underground Vehicles With a Single Camera

Many mine-site processes such as vehicle operation require localisation systems that are reliable, robust and work in a range of environmental conditions. In underground operations, GPS is not available: solutions instead rely on static infrastructure or expensive, laser-based solutions with limited operational capability. In this letter we present a new vision-based technique, Tunnel-IMage Texturally-Accorded Mosaic (TIMTAM), for sub-metre, infrastructure-free localisation in underground mining environments using a single camera. Our approach stitches upward-facing camera images to form planar mosaic maps, using locations generated by the coarse mapping engine based on a small number of manually anchored locations. Localisation is achieved by refining coarse location estimations with a best fit pixel location for the query image within a search neighbourhood in the mosaic map. Our direct pixel-based method is more robust to the challenging illumination and surface-texture environments encountered in underground mine operations than feature-based techniques. Localisation refinement is only triggered when a confidence threshold for the estimate is exceeded. The system is evaluated in a real world mine tunnel, with results showing that the confidence threshold approach is predictive of the quality of the location estimate refinement, and achieves a reduction in mean localisation metric error of up to ∼ 66% from simulated coarse results.

Free coarse groups

Abstract A coarse group is a group endowed with a coarse structure so that the group multiplication and inversion are coarse mappings. Let ( X , ℰ ) {(X,\mathcal{E})} be a coarse space, and let 𝔐 {\mathfrak{M}} be a variety of groups different from the variety of singletons. We prove that there is a coarse group F 𝔐 ⁢ ( X , ℰ ) ∈ 𝔐 {F_{\mathfrak{M}}(X,\mathcal{E})\in\mathfrak{M}} such that ( X , ℰ ) {(X,\mathcal{E})} is a subspace of F 𝔐 ⁢ ( X , ℰ ) {F_{\mathfrak{M}}(X,\mathcal{E})} , X generates F 𝔐 ⁢ ( X , ℰ ) {F_{\mathfrak{M}}(X,\mathcal{E})} and every coarse mapping ( X , ℰ ) → ( G , ℰ ′ ) {(X,\mathcal{E})\to(G,\mathcal{E}^{\prime})} , where G ∈ 𝔐 {G\in\mathfrak{M}} , ( G , ℰ ′ ) {(G,\mathcal{E}^{\prime})} is a coarse group, can be extended to coarse homomorphism F 𝔐 ⁢ ( X , ℰ ) → ( G , ℰ ′ ) {F_{\mathfrak{M}}(X,\mathcal{E})\to(G,\mathcal{E}^{\prime})} . If 𝔐 {\mathfrak{M}} is the variety of all groups, the groups F 𝔐 ⁢ ( X , ℰ ) {F_{\mathfrak{M}}(X,\mathcal{E})} are asymptotic counterparts of Markov free topological groups over Tikhonov spaces.

Unstructured coarse mesh finite difference method to accelerate k-eigenvalue and fixed source neutron transport calculations

Unstructured coarse mesh finite difference (CMFD) method was implemented to accelerate the k-eigenvalue and fixed source neutron transport calculations in the nodal SN transport code DNTR, which was based on arbitrary triangular-z meshes. The same triangular-z meshes were adopted in the CMFD calculation to accommodate the arbitrary problem boundaries and simplify the coarse mesh generation and mapping processes. Two-level CMFD formulations were derived for the k-eigenvalue problems, and the few-group CMFD calculation was used to speed up the convergence of the multigroup CMFD calculation. For the fixed source problems in the neutronics analyses of subcritical reactors or transient neutron transport calculations, a special ks iteration method by introducing the source multiplication factor ks was employed in the SN transport calculation to remove the dependence of the convergence rate on the subcriticality. Multigroup CMFD formulations were established to accelerate the convergence of the ks iteration procedure in the fixed source neutron transport calculation. The acceleration effects of CMFD on the k-eigenvalue and fixed source calculations were verified using four representative neutron transport problems, i.e. the small fast breeder reactor with Cartesian boundaries, the BN-600 fast reactor with hexagonal boundaries, the space nuclear power reactor with cylindrical boundaries, and the accelerator driven subcritical reactor with hexagonal boundaries. The numerical results showed that for the first three eigenvalue problems, the multigroup CMFD achieved a speedup of total computation time by a factor of 2–5, and the two-level CMFD reduced the computation time by a factor of 3–7. It was also shown that the multigroup CMFD was able to accelerate the ks iteration procedure in the fixed source problems by a factor of about 6. The implementation of the unstructured CMFD method turns the DNTR code into an efficient neutron transport solver with flexible geometry treatment capability for both k-eigenvalue and fixed source problems.

Fast shading correction for cone beam CT in radiation therapy via sparse sampling on planning CT.

The image quality of cone beam computed tomography (CBCT) is limited by severe shading artifacts, hindering its quantitative applications in radiation therapy. In this work, we propose an image-domain shading correction method using planning CT (pCT) as prior information which is highly adaptive to clinical environment. We propose to perform shading correction via sparse sampling on pCT. The method starts with a coarse mapping between the first-pass CBCT images obtained from the Varian TrueBeam system and the pCT. The scatter correction method embedded in the Varian commercial software removes some image errors but the CBCT images still contain severe shading artifacts. The difference images between the mapped pCT and the CBCT are considered as shading errors, but only sparse shading samples are selected for correction using empirical constraints to avoid carrying over false information from pCT. A Fourier-Transform-based technique, referred to as local filtration, is proposed to efficiently process the sparse data for effective shading correction. The performance of the proposed method is evaluated on one anthropomorphic pelvis phantom and 17 patients, who were scheduled for radiation therapy. (The codes of the proposed method and sample data can be downloaded from https://sites.google.com/view/linxicbct) RESULTS: The proposed shading correction substantially improves the CBCT image quality on both the phantom and the patients to a level close to that of the pCT images. On the phantom, the spatial nonuniformity (SNU) difference between CBCT and pCT is reduced from 74 to 1HU. The root of mean square difference of SNU between CBCT and pCT is reduced from 83 to 10HU on the pelvis patients, and from 101 to 12HU on the thorax patients. The robustness of the proposed shading correction is fully investigated with simulated registration errors between CBCT and pCT on the phantom and mis-registration on patients. The sparse sampling scheme of our method successfully avoids false structures in the corrected CBCT even when the maximum registration error is as high as 8mm. We develop an effective shading correction algorithm for CBCT readily implementable on clinical data as a software plug-in without modifications of current imaging hardware and protocol. The algorithm is directly applied on the output images from a commercial CBCT scanner with high computational efficiency and negligible memory burden.

A dynamic task mapping algorithm for SDNoC

The task mapping has a significant impact on the system performance of Network-on-Chip(NoC). In this paper, we propose a dynamic task mapping algorithm for Software-Defined-Network-on-Chip(SDNoC). The hierarchical design of SDNoC promotes the flexibility of NoC and provides the running environment for dynamic mapping algorithm with software techniques. The goal of dynamic task mapping is to minimize communication cost of the application execution and to achieve the load balance among routers. The tasks of applications are assigned to suitable network nodes by the proposed task coarse mapping and task fine mapping for minimum communication cost and flits load balance among routers. A simulation platform is presented to confirm the effectiveness of the proposed approach. The simulation results show that the communication cost and the standard deviation of routers flit load have been reduced by 2.8% and 8.1% compared with the reported dynamic mapping method. The execution time of applications and consuming time of mapping are less 9.3% and 28.2% compared with the reported dynamic mapping respectively.

Single Image Super-Resolution Using Global Regression Based on Multiple Local Linear Mappings.

Super-resolution (SR) has become more vital, because of its capability to generate high-quality ultra-high definition (UHD) high-resolution (HR) images from low-resolution (LR) input images. Conventional SR methods entail high computational complexity, which makes them difficult to be implemented for up-scaling of full-high-definition input images into UHD-resolution images. Nevertheless, our previous super-interpolation (SI) method showed a good compromise between Peak-Signal-to-Noise Ratio (PSNR) performances and computational complexity. However, since SI only utilizes simple linear mappings, it may fail to precisely reconstruct HR patches with complex texture. In this paper, we present a novel SR method, which inherits the large-to-small patch conversion scheme from SI but uses global regression based on local linear mappings (GLM). Thus, our new SR method is called GLM-SI. In GLM-SI, each LR input patch is divided into 25 overlapped subpatches. Next, based on the local properties of these subpatches, 25 different local linear mappings are applied to the current LR input patch to generate 25 HR patch candidates, which are then regressed into one final HR patch using a global regressor. The local linear mappings are learned cluster-wise in our off-line training phase. The main contribution of this paper is as follows: Previously, linear-mapping-based conventional SR methods, including SI only used one simple yet coarse linear mapping to each patch to reconstruct its HR version. On the contrary, for each LR input patch, our GLM-SI is the first to apply a combination of multiple local linear mappings, where each local linear mapping is found according to local properties of the current LR patch. Therefore, it can better approximate nonlinear LR-to-HR mappings for HR patches with complex texture. Experiment results show that the proposed GLM-SI method outperforms most of the state-of-the-art methods, and shows comparable PSNR performance with much lower computational complexity when compared with a super-resolution method based on convolutional neural nets (SRCNN15). Compared with the previous SI method that is limited with a scale factor of 2, GLM-SI shows superior performance with average 0.79 dB higher in PSNR, and can be used for scale factors of 3 or higher.

High resolution characterization of the soil organic carbon depth profile in a soil landscape affected by erosion

The identification of soil management strategies as well as the evaluation of their effectiveness requires detailed information on the spatial and temporal patterns of soil organic carbon storage. High-resolution SOC profile data are generally not available and traditional methods for collecting these are time consuming and costly. Recent studies use geo-statistical approaches to assess the three-dimensional patterns of SOC storage. However, there is still a large discrepancy between the continuous and high resolution mapping of the horizontal SOC variability on the one hand, and the coarse and discontinuous mapping of the vertical SOC profile on the other. In this study, we combine spectroscopic techniques with spatial modeling in a small, cultivated catchment in Germany and we evaluate the contribution of soil redistribution processes and topographical parameters to the observed spatial and vertical patterns. Using high-resolution data from soil cores, we evaluated the robustness of a third order polynomial function to model the vertical SOC profile. Using a crossvalidation, our results show that this approach results in a robust model (RSME=0.24%) and performs better than the widely used exponential depth model (RMSE=0.39%). In a next step, we evaluated the relationship between the parameters of the SOC depth model and co-variables including soil redistribution (inferred from 137Cs data) and topographical indices using a multiple linear regression model. The performance was calculated by cross-validation and we found a low robustness of the models because of the low number of profiles (i.e. n=19). A statistical evaluation of the co-variables highlighted two key factors influencing the SOC vertical distribution. Soil redistribution processes mainly influenced the surface SOC content (first centimeters) whereas the shape of the depth distribution was controlled by slope curvature alone. The mapping of polynomial parameters was validated using an external SOC profile dataset and showed a poor prediction of the surface content but a good prediction of the depth distribution once the surface SOC content is known (RMSE=0.15–0.25%C). This suggests that estimating the vertical SOC profile from topsoil data by applying remote sensing data, in combination with our SOC profile model, is promising and can will result in an accurate mapping of 3D SOC patterns at a very high resolution.

Roll Your Own Web Database: An Innovative Approach for Providing Searchable Web Content

The paper is aimed at addressing two issues: first, despite of the importance of semantic information in HTML pages, it is often ignored by search engines due to various technology difficulties; second, the ambiguity problem sometimes makes results returned by search engines much less useful. OOSM, a schema model as well as a set of information processing tools, is proposed in the paper. OOSM develops the concept of coarse mapping, that is, users are allowed (but not restricted) to associate a grammar node to a sub section instead of a single node on a HTML page. AS a result, minor modifications of the annotated HTML page can be tolerated. We believe that OOSM is a right solution for the issues presented in this paper.

Behavioral consequences of exotic host plant adoption and the differing roles of male harassment on female movement in two checkerspot butterflies

Herbivorous insects may evolve convergent behaviors when independent adoption of a shared novel host plant places populations in environmental conditions that diverge from the ancestral state. We investigated the behavioral consequences of adopting Plantago lanceolata, an exotic species to North America, in populations of Euphydryas p. phaeton and Euphydryas editha taylori, on the east and west coasts of North America. Activity budgets and short-term movements suggested that innate species tendencies exert a greater impact on behavior than adoption of the same exotic host plant. However, female E. phaeton from a Plantago-dependent population spent more time inspecting host plants than females from a population dependent on the native host plant, Chelone glabra. Both checkerspot species had similar diffusion coefficients (D) regardless of host plant association. But, E. e. taylori step-lengths appeared bimodal and power law distributed while E. phaeton step-lengths were unimodal and best fit by an exponential distribution. We attribute this bimodal step-length distribution to the persistent harassment of courting males which induces a “long-distance” evasive flight in otherwise sedentary E. e. taylori females. In contrast, the longer distance step-lengths of E. phaeton were associated with the inspection of oviposition plants. These two checkerspot species appear to move greater distances across the reproductive landscape with contrasting motivational states that could lead to either intimate mapping (E. phaeton) or coarse mapping (E. e. taylori) of host resources.

A large QTL for fear and anxiety mapped using an F2 cross can be dissected into multiple smaller QTLs

Using chromosome substitution strains (CSS), we previously identified a large quantitative trait locus (QTL) for conditioned fear (CF) on mouse chromosome 10. Here, we used an F2 cross between CSS-10 and C57BL/6J (B6) to localize that QTL to distal chromosome 10. That QTL accounted for all the difference between CSS-10 and B6. We then produced congenic strains to fine-map that interval. We identified two congenic strains that captured some or all the QTL. The larger congenic strain (Line 1: 122.387121-129.068 Mb; build 37) appeared to account for all the difference between CSS-10 and B6. The smaller congenic strain (Line 2: 127.277-129.068 Mb) was intermediate between CSS-10 and B6. We used haplotype mapping followed by quantitative polymerase chain reaction to identify one gene that was differentially expressed in both lines relative to B6 (Rnf41) and one that was differentially expressed between only Line 1 and B6 (Shmt2). These cis-eQTLs may cause the behavioral QTLs; however, further studies are required to validate these candidate genes. More generally, our observation that a large QTL mapped using CSS and F2 crosses can be dissected into multiple smaller QTLs shows a weaknesses of two-stage approaches that seek to use coarse mapping to identify large regions followed by fine-mapping. Indeed, additional dissection of these congenic strains might result in further subdivision of these QTL regions. Despite these limitations, we have successfully fine-mapped two QTLs to small regions and identified putative candidate genes, showing that the congenic approach can be effective for fine-mapping QTLs.

An ENU mutagenesis approach to dissect “self”-induced immune responses

The immune system exerts a critical function as it recognizes and eliminates transformed or neoplastic cells, a process also referred to as immunosurveillance. NK cells play a particularly important role in that they are able to recognize tumor cells via “missing-self”—i.e., the absence of major histocompatibility complex Class I on target cells. Moreover, recent studies suggest that NK cells also participate in the onset and regulation of adaptive immune responses. The exact molecular pathways by which this occurs, however, remain poorly understood. To obtain further insight into the genes that are required for self-induced immune responses via NK cell-mediated cell death, our laboratory initiated a forward genetic approach using N-ethyl-N-nitrosourea (ENU) as a mutagen. Specifically, we tested the ability of NK cells from G3 ENU germline mice to recognize missing-self target cells and induce CD8+ T-cell responses following immunization with irradiated tumor cells. Here we present two ENU germline mutants, designated Ace and Chip, that are defective in the recognition of β-2 microglobulin-deficient target cells, yet exhibit improved clearance of B16 melanoma cells in vivo. Coarse mapping and whole genome sequencing of the Chip mutation revealed a missense mutation causing a T’A amino acid substitution in the highly conserved third immuno-receptor tyrosine-based switch motif of CD244 (2B4). The forward genetic approach described here promises to reveal important insight into critical genes that are required for host responses involved in anticancer immunity.

HIGH DISTANCE KNOTS IN CLOSED 3-MANIFOLDS

Let M be a closed 3-manifold with a given Heegaard splitting. We show that after a single stabilization, some core of the stabilized splitting has arbitrarily high distance with respect to the splitting surface. This generalizes a result of Minsky, Moriah, and Schleimer for knots in S3. We also show that in the complex of curves, handlebody sets are either coarsely distinct or identical. We define the coarse mapping class group of a Heegaard splitting, and show that if (S, V, W) is a Heegaard splitting of genus ≥2, then the coarse mapping class group of (S, V, W) is isomorphic to the mapping class group of (S, V, W).

Principles and practices of plant penomics. Volume 1. Genome mapping

This volume is the first of a three-volume series. The 11 chapters of the volume provide the reader with the basic knowledge on the approaches, tools and platforms required to map genomes and extract useful information for different applications, particularly for tagging Mendelian and quantitative genes. The first four chapters present a vibrant historical summary of the main features of the genetic materials and marker classes required for the construction of linkage maps. The next four chapters provide a detailed description on how the genomics approach can best be used to unravel the genetic basis of traits, all the way from the primary and coarse mapping of genes and QTL to their cloning. A number of valuable examples have been critically surveyed, thus providing the reader with an accurate overview of what can reasonably be achieved and the effort it will require. Of particular value to newcomers in the genomics world are the two chapters devoted to bioinformatics, computer strategies and software for gene mapping. Finally, one chapter illustrates the main genomic initiatives undertaken so far. This volume is well poised to become a reference classic for those willing to engage in the study of the structure and evolution of plant genomes and how this information can be used to improve crop performance. The volume is particularly valuable to those with limited or even no knowledge of the fundamentals of plant genomics, an attribute also clearly implied by the title of the series. Among the many merits of this volume, the main one is the clarity with which the information is presented, a feature particularly valuable for the neophytes. Nonetheless, a number of chapters clearly go beyond this basic level of knowledge and provide an ample list of references that can be accessed for further reading. The figures very clearly report the basic features of the relevant marker classes and approaches, a particularly valuable feature for teaching purposes. Additionally, a number of well-organized and informative tables summarize relevant key features. The list of abbreviations is very handy and provides a quick overview of the genomics jargon used (and often abused) that may otherwise discourage newcomers to take full advantage of the analytical power and potential of the genomic approach. Similarly useful is the simple and well-organized analytical index. Notwithstanding the year of publication (2008) of the volume, only a handful of the quoted references are from 2007 and only a few more are from 2006. This shortcoming probably reflects a delay in finalizing the volume and its prevailing scholastic orientation coherently with what is stated by the editors in the Preface: ‘ … it is essential that academics in these broad disciplines have available the lucid deliberations of the basic concepts and strategies of plant genomics to enhance their own studies, training and expertise’. The step-by-step structure of most chapters provides even the most recalcitrant reader with the opportunity to wade through all the topics easily in a clear and logical fashion. This feature makes the volume particularly valuable for teaching students at low and intermediate levels and for scientists willing to engage, either theoretically or practically, for the first time with the genomics approach. This volume also targets students and researchers in plant science and biotechnology with an interest in genomics who are willing to undertake a more in-depth journey, either from an academic or applicative standpoint. The content and style of the volume clearly reflect the fact that it is the first of a three-volume set. Although the book is an excellent buy as a stand-alone volume, its value will be enhanced when considered in conjunction with the remaining two volumes that will soon be published in the series. In summary, the volume Genome Mapping represents a valuable resource for those students and scientists willing to take advantage of the research and applicative possibilities offered by plant genomics. This book provides an excellent starting point to further knowledge on genome structure and gene function, and demonstrates how the genomics paradigm can be exploited to provide breeders and other scientists with the information required to more effectively unravel and manipulate trait complexity and crop performance.