This volume assembles a broad spectrum of methods used in long non-coding RNAs (lncRNA) research, ranging from computational annotation of lncRNA genes to molecular and cellular analyses of the function of individual lncRNA. Long Non-Coding RNAs: Methods and Protocols also discusses methods used to study circular RNAs and RNA splicing, as well as influential findings on lncRNA in human diseases. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Thorough and cutting-edge, Long Non-Coding RNAs: Methods and Protocols is a must-have for molecular biologists, cell and developmental biologists, specialists who conduct disease-oriented research, and bioinformatics experts who seek a better understanding on lncRNA expression and function by computational analysis of the massive sequencing data that are rapidly accumulating in recent years.

This book covers dynamic simulation of deformable objects, which is one of the most challenging tasks in computer graphics and visualization. It focuses on the simulation of deformable models with anisotropic materials, one of the less common approaches in the existing research. Both physically-based and geometrically-based approaches are examined. The authors start with transversely isotropic materials for the simulation of deformable objects with fibrous structures. Next, they introduce a fiber-field incorporated corotational finite element model (CLFEM) that works directly with a constitutive model of transversely isotropic material. A smooth fiber-field is used to establish the local frames for each element. To introduce deformation simulation for orthotropic materials, an orthotropic deformation controlling frame-field is conceptualized and a frame construction tool is developed for users to define the desired material properties. The orthotropic frame-field is coupled with the CLFEM model to complete an orthotropic deformable model. Finally, the authors present an integrated real-time system for animation of skeletal characters with anisotropic tissues. To solve the problems of volume distortion and high computational costs, a strain-based PBD framework for skeletal animation is explained; natural secondary motion of soft tissues is another benefit. The book is written for those researchers who would like to develop their own algorithms. The key mathematical and computational concepts are presented together with illustrations and working examples. It can also be used as a reference book for graduate students and senior undergraduates in the areas of computer graphics, computer animation, and virtual reality. Academics, researchers, and professionals will find this to be an exceptional resource.

This book introduces new techniques for cellular image feature extraction, pattern recognition and classification. The authors use the antinuclear antibodies (ANAs) in patient serum as the subjects and the Indirect Immunofluorescence (IIF) technique as the imaging protocol to illustrate the applications of the described methods. Throughout the book, the authors provide evaluations for the proposed methods on two publicly available human epithelial (HEp-2) cell datasets: ICPR2012 dataset from the ICPR'12 HEp-2 cell classification contest and ICIP2013 training dataset from the ICIP'13 Competition on cells classification by fluorescent image analysis. First, the reading of imaging results is significantly influenced by one's qualification and reading systems, causing high intra- and inter-laboratory variance. The authors present a low-order LP21 fiber mode for optical single cell manipulation and imaging staining patterns of HEp-2 cells. A focused four-lobed mode distribution is stable and effective in optical tweezer applications, including selective cell pick-up, pairing, grouping or separation, as well as rotation of cell dimers and clusters. Both translational dragging force and rotational torque in the experiments are in good accordance with the theoretical model. With a simple all-fiber configuration, and low peak irradiation to targeted cells, instrumentation of this optical chuck technology will provide a powerful tool in the ANA-IIF laboratories. Chapters focus on the optical, mechanical and computing systems for the clinical trials. Computer programs for GUI and control of the optical tweezers are also discussed. to more discriminative local distance vector by searching for local neighbors of the local feature in the class-specific manifolds. Encoding and pooling the local distance vectors leads to salient image representation. Combined with the traditional coding methods, this method achieves higher classification accuracy. Then, a rotation invariant textural feature of Pairwise Local Ternary Patterns with Spatial Rotation Invariant (PLTP-SRI) is examined. It is invariant to image rotations, meanwhile it is robust to noise and weak illumination. By adding spatial pyramid structure, this method captures spatial layout information. While the proposed PLTP-SRI feature extracts local feature, the BoW framework builds a global image representation. It is reasonable to combine them together to achieve impressive classification performance, as the combined feature takes the advantages of the two kinds of features in different aspects. Finally, the authors design a Co-occurrence Differential Texton (CoDT) feature to represent the local image patches of HEp-2 cells. The CoDT feature reduces the information loss by ignoring the quantization while it utilizes the spatial relations among the differential micro-texton feature. Thus it can increase the discriminative power. A generative model adaptively characterizes the CoDT feature space of the training data. Furthermore, exploiting a discriminant representation allows for HEp-2 cell images based on the adaptive partitioned feature space. Therefore, the resulting representation is adapted to the classification task. By cooperating with linear Support Vector Machine (SVM) classifier, this framework can exploit the advantages of both generative and discriminative approaches for cellular image classification. The book is written for those researchers who would like to develop their own programs, and the working MatLab codes are included for all the important algorithms presented. It can also be used as a reference book for graduate students and senior undergraduates in the area of biomedical imaging, image feature extraction, pattern recognition and classification. Academics, researchers, and professional will find this to be an exceptional resource.

This book offers a dynamic introduction to the new developments on national security review of foreign direct investment (FDI) from the perspectives of both domestic law and international investment law. COVID-19 and the Russian invasion of Ukraine have intensified FDI screening to an unprecedented scale, yet its purposes, scope, and potential impact remain ambiguous and controversial. The work first attests the legitimacy of FDI screening by using national security constitutional theory. Part I explicates the national security, public order and public health exceptions clauses in international investment law, and the novel EU Regulation on FDI screening. Part II provides an in-depth analysis of FDI screening in China, France, Germany, Italy, the Netherlands, Poland, and the UK, which have either witnessed momentous changes in domestic law recently, or have adopted new laws to cope with the growing security concerns. The book illustrates how States and the EU are using legal instruments to tackle exigent and emerging challenges and the complexity of national security emanated from foreign investment, in the context of evolving disruptive digital technologies and the structural change of the global economy. The volume will be of great value to a wide range of audiences including academics in investment and trade law, legal practitioners, in-house counsels, policymakers, business professionals and law and business students at the graduate level.

Soybean (Glycine max L. (Merr)) is one of the most important crops worldwide. Soybean seeds are vital for both protein meal and vegetable oil. Soybean was domesticated in China, and since last 4-5 decades it has become one of the most widely grown crops around the globe. The crop is grown on an anticipated 6% of the world's arable land, and since the 1970s, the area in soybean production has the highest percentage increase compared to any other major crop. It is a major crop in the United States, Brazil, China and Argentina and important in many other countries. The cultivated soybean has one wild annual relative, G. soja, and 23 wild perennial relatives. Soybean has spread to many Asian countries two to three thousand years ago, but was not known in the West until the 18th century. Among the various constraints responsible for decrease in soybean yields are the biotic and abiotic stresses which have recently increased as a result of changing climatic scenarios at global level. A lot of work has been done for cultivar development and germplasm enhancement through conventional plant breeding. This has resulted in development of numerous high yielding and climate resilient soybean varieties. Despite of this development, plant breeding is long-term by nature, resource dependent and climate dependent. Due to the advancement in genomics and phenomics, significant insights have been gained in the identification of genes for yield improvement, tolerance to biotic and abiotic stress and increased quality parameters in soybean. Molecular breeding has become routine and with the advent of next generation sequencing technologies resulting in SNP based molecular markers, soybean improvement has taken a new dimension and resulted in mapping of genes for various traits that include disease resistance, insect resistance, high oil content and improved yield. This book includes chapters from renowned potential soybean scientists to discuss the latest updates on soybean molecular and genetic perspectives to elucidate the complex mechanisms to develop biotic and abiotic stress resilience in soybean. Recent studies on the improvement of oil quality and yield in soybean have also been incorporated.

This book covers dynamic simulation of deformable objects, which is one of the most challenging tasks in computer graphics and visualization. It focuses on the simulation of deformable models with anisotropic materials, one of the less common approaches in the existing research. Both physically-based and geometrically-based approaches are examined. The authors start with transversely isotropic materials for the simulation of deformable objects with fibrous structures. Next, they introduce a fiber-field incorporated corotational finite element model (CLFEM) that works directly with a constitutive model of transversely isotropic material. A smooth fiber-field is used to establish the local frames for each element. To introduce deformation simulation for orthotropic materials, an orthotropic deformation controlling frame-field is conceptualized and a frame construction tool is developed for users to define the desired material properties. The orthotropic frame-field is coupled with the CLFEM model to complete an orthotropic deformable model. Finally, the authors present an integrated real-time system for animation of skeletal characters with anisotropic tissues. To solve the problems of volume distortion and high computational costs, a strain-based PBD framework for skeletal animation is explained; natural secondary motion of soft tissues is another benefit. The book is written for those researchers who would like to develop their own algorithms. The key mathematical and computational concepts are presented together with illustrations and working examples. It can also be used as a reference book for graduate students and senior undergraduates in the areas of computer graphics, computer animation, and virtual reality. Academics, researchers, and professionals will find this to be an exceptional resource.

This volume assembles a broad spectrum of methods used in long non-coding RNAs (lncRNA) research, ranging from computational annotation of lncRNA genes to molecular and cellular analyses of the function of individual lncRNA. Long Non-Coding RNAs: Methods and Protocols also discusses methods used to study circular RNAs and RNA splicing, as well as influential findings on lncRNA in human diseases. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Thorough and cutting-edge, Long Non-Coding RNAs: Methods and Protocols is a must-have for molecular biologists, cell and developmental biologists, specialists who conduct disease-oriented research, and bioinformatics experts who seek a better understanding on lncRNA expression and function by computational analysis of the massive sequencing data that are rapidly accumulating in recent years.

Edited by some of the most experienced authors in the field, Biomedical Imaging provides comprehensive coverage on medical and biological imaging. Original research and critical reviews on software and hardware technologies for medical and biological imaging tasks are presented in the book, along with data processing in all imaging modalities for molecular, cellular, anatomical and functional imaging. Research topics include image acquisition, registration, reconstruction, multimodality methods, noise filtering and image enhancement, segmentation, classification and feature detection, model and atlas based imaging, as well as system development and acceleration technologies. Biomedical Imaging is comprised of 40 contributed chapters, which are organized in such a way that researchers, engineers, clinical practitioners and graduate students can easily follow up with relevant topics, and will benefit from reading the views of the domain experts in their fields.

Grid and Pervasive Computing (GPC) is an annual international conference on the emerging areas of grid computing and pervasive computing, aimed at p- viding an exciting platform and paradigm for all-the-time, everywhere services. GPC 2010 provided a high-pro?le, leading-edgeforum for researchersand dev- opers from industry and academia to present their latest research in the ?eld of grid and pervasive computing. Three workshops were held in conjunction with the GPC 2010 conference: * The First International Workshop on Intelligent Management of Networked Environment (IMNE 2010) * International Workshop on Multimedia Applications for Cloud (MAC 2010) * The 6thInternationalWorkshopon Mobile Commerce andServices (WMCS 2010) The proceedingsof these workshoparealso included in this volume. We received 184 papers originating from 22 countries. The Program Committee ?nally - lected 67 papers for presentation at the conference and inclusion in this LNCS volume. At GPC 2010, we were very pleased to have four distinguished invited speakers, who delivered state-of-the-art information on the conference topics: * A grid based virtual laboratory for HIV drugranking by Peter Sloot (U- versity of Amsterdam, The Netherlands) * Solving the scalability dilemma with clouds, crowds, and algorithms by Michael J. Franklin (University of California, Berkeley, USA) * The trend of cloud computing - from industry's perspective by Enwei Xie (Microsoft Greater China Region, China) * Towards ubiquitous a?ective learning by Bin Hu (The Birmingham City University, UK) Theconferencewouldnothavebeenpossiblewithoutthesupportofmanypeople andorganizationsthathelped invariouswaysto makeita success.