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T cells are integral components of the adaptive immune system, and their responses are mediated by unique T-cell receptors (TCR) that recognize specific antigens from a variety of biological contexts. As a result, analyzing the T-cell repertoire offers a better understanding of immune responses and of diseases like cancer. Next-generation sequencing technologies have greatly enabled the high-throughput analysis of the TCR repertoire. On the basis of our extensive experience in the field from the past decade, we provide an overview of TCR sequencing, from the initial library preparation steps to sequencing and analysis methods and finally to functional validation techniques. With regards to data analysis, we detail important TCR repertoire metrics and present several computational tools for predicting antigen specificity. Finally, we highlight important applications of TCR sequencing and repertoire analysis to understanding tumor biology and developing cancer immunotherapies.

Severe plastic deformation (SPD) can fabricate high-strength materials by forming an ultrafine grained (UFG) microstructure. Low elongation to failure of UFG materials in tensile tests, which has often been regarded as a measure of ductility of materials, has been attributed to low strain hardening of UFG structures where dislocation slip and its accumulation is very limited. In the present work, it is shown that the compressive extensibility of UFG materials can be comparable or potentially superior to that of annealed materials by using a parallel round-bar compression (PRBC) test which was designed for imposing an appropriate stress state preferable for high ductility using the shear mode. The high compressive extensibility of UFG materials can be a result of high accommodation of local strain incompatibility at non-equilibrium grain boundaries and a grain boundary-mediated deformation mechanism, which result in high damage tolerance against void formation and growth. Low strain rate sensitivity indicated that the superplastic viscous nature of deformation is not involved in the high compressive ductility of UFG materials using SPD.

A new rate independent porous plasticity model is proposed for the modeling of ductile damage initiation due to void growth in metallic materials. The model is based on a simple yield description which includes two porosity functions that affect both deviatoric and hydrostatic stress evolution. The current version of the model predicts damage solely due to void growth and it should be extended to include the void initiation and coalescence criteria. The numerical examples study the performance of the developed model for the evolution of porosity through unit cell calculations and for the necking of a uniaxial tensile bar. The preliminary void growth calculations in the unit cell study is acceptable at triaxiality values below 1. (C) 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review line: Peer-review under responsibility of the 1st International Workshop on Plasticity, Damage and Fracture of Engineering Materials organizers.

The basic principles of the governmentality is one of most prominent topics of the Ottoman political writers. Because of the continuing growth and empowerment of the central bureaucracy, the principles which represent the professional values of the bureaucrats have found a place in the nasihatname writings. Per nasihatname writers, the Empire should have been governed in accordance with the suggestions of the educated and wise advisors. In this regard, the concepts of wisdom, which have deep roots in the Turkish government tradition and political Islamic thought, had been reevaluated and presented as the key of the success in the political texts of the Ottomans. This approach gained an institutional base in the Tanzimat period, and the Empire started to be ruled by the councils of the professional technocrats. In this context the central role of the bureaucrats constitutes the bridges between the traditional Ottoman reformist thought and Tanzimat movement which was influenced by the international rivalry. In this way, the tradition of consultation which has deep roots in the Ottoman political thought played an important role in the 19th century transformation of the Empire.

The nationalist movements and colonial ambitions of the Western Powers on the Balkans and North Africa paved the way for the failure of state authority and insurgence of local folk. The claims of Western powers on the Ottoman Empire and their colonial designs were resulted with their support on nationalist movements. Their claim about Ottoman backwardness and their duty on “bringing civilization” for the local people had become an instrument for their ambitions on the region. In this regard, Italy which wanted to take a share on colonial race among the European Nations declared itself as the heir of Great Roman Empire and claimed and invaded the Northern Africa which was a part of ancient Cartage”. Our topic in this regard concentrate on the issues and procedure of the Trablusgarp War. Because of this, it is important for the evaluation and understanding of the Trablusgarp War

We demonstrate that moving the wrist while the fingers perform a grasp increases performance. The coordination shapes the interactions between the fingers, the object and its environment to extend the hand capabilities (e.g. higher payload and precision). We evaluated our hypothesis with a human grasping study where the volunteers grasped objects by moving the soft RBO Hand 2 while its fingers closed in a predefined motion. We limited their ability to coordinate their motion with the finger movements using a compliant robot attached to the hand, and observed that their grasp success decreases with increased constraints. We also successfully transferred one of the observed movement patterns to the robot, indicating that adaptive intrinsic/extrinsic motion increases robotic grasp performance as well.

The amount of data produced with the introduction of social media tools has reached gigantic size. In analyzing data, and now traditional methods are no longer enough, the concept of “Big Data” has entered our lives. There is an inevitable need to produce meaningful summaries by analyzing data at huge size. Large data tools are used to meet this need. In order to have knowledge about human behaviors using these tools and to develop solutions in this direction, social media and especially Twitter data are being studied. As is known, the concept of crypto currency, which has come from trends in recent years, attracts more and more people. In this study, approaches to the most commonly used crypto currencies were examined for the first time using large data tools. The meaningless data on twits which is taken from Twitter has been cleared and the approaches of users against crypto paralysis have been analyzed by using various classifiers and the results have been shown.

In this paper we present an approach for creating complete shape representations from a single depth image for robot grasping. We introduce algorithms for completing partial point clouds based on the analysis of symmetry and extrusion patterns in observed shapes. Identified patterns are used to generate a complete mesh of the object, which is, in turn, used for grasp planning. The approach allows robots to predict the shape of objects and include invisible regions into the grasp planning step. We show that the identification of shape patterns, such as extrusions, can be used for fast generation and optimization of grasps. Finally, we present experiments performed with our humanoid robot executing pick-up tasks based on single depth images and discuss the applications and shortcomings of our approach.

Robots are inherently limited by constraints on their motor power, battery life, and structural rigidity. Using simple machines and exploiting their mechanical advantage can significantly increase the breadth of a robot’s capabilities. In this work, we present an autonomous planner which allows a robot to determine how arbitrary rigid objects in its environment can be utilized in machine designs to overcome physical challenges. First, the designed structure must be sufficient to achieve a task given the input force and torque that can be applied by the robot. Second, the structure must be accessible to the robot given its kinematics and geometry so that it can actually be used to perform the task. The output of our algorithm is the configuration of the design components, the pose of the robot to make contact with the design, and the motor torques needed to actuate it. We demonstrate results with the robot Golem Krang, using levers as simple machines, to overturn 100 kg load and to push 240 kg wheeled obstacle.

On the path to full autonomy, robotic agents have to learn how to manipulate their environments for their benefit. In particular, the ability to design structures that are functional in overcoming challenges is imperative. The problem of automated design of functional structures (ADFS) addresses the question of whether the objects in the environment can be placed in a useful configuration. In this work, we first make the observation that the ADFS problem represents a class of problems in high dimensional, continuous spaces that can be broken down into simpler subproblems with semantically meaningful actions. Next, we propose a framework where discrete actions that induce constraints can partition the solution space effectively. Subsequently, we solve the original class of problems by searching over the available actions, where the evaluation criteria for the search is the feasibility test of the accumulated constraints. We prove that with a sound feasibility test, our algorithm is complete. Additionally, we argue that a convexity requirement on the constraints leads to significant efficiency gains. Finally, we present successful results to the ADFS problem.

With the advent of affordable RGBD sensors such as the Kinect, the collection of depth and appearance information from a scene has become effortless. However, neither the correct noise model for these sensors, nor a principled methodology for extracting planar segmentations has been developed yet. In this work, we advance the state of art with the following contributions: we correctly model the Kinect sensor data by observing that the data has inherent noise only over the measured disparity values, we formulate plane fitting as a linear least-squares problem that allow us to quickly merge different segments, and we apply an advanced Markov Chain Monte Carlo (MCMC) method, generalized Swendsen-Wang sampling, to efficiently search the space of planar segmentations. We evaluate our plane fitting and surface reconstruction algorithms with simulated and real-world data.