nils-herrmann/clean_scirepeval huggingface dataset:
A Survey on Vehicular Social Networks

This paper surveys recent literature on vehicular social networks that are a particular class of vehicular ad hoc networks, characterized by social aspects and features. Starting from this pillar, we investigate perspectives on next-generation vehicles under the assumption of social networking for vehicular applications (i.e., safety and entertainment applications). This paper plays a role as a starting point about socially inspired vehicles and mainly related applications, as well as communication techniques. Vehicular communications can be considered the “first social network for automobiles” since each driver can share data with other neighbors. For instance, heavy traffic is a common occurrence in some areas on the roads (e.g., at intersections, taxi loading/unloading areas, and so on); as a consequence, roads become a popular social place for vehicles to connect to each other. Human factors are then involved in vehicular ad hoc networks, not only due to the safety-related applications but also for entertainment purposes. Social characteristics and human behavior largely impact on vehicular ad hoc networks, and this arises to the vehicular social networks, which are formed when vehicles (individuals) “socialize” and share common interests. In this paper, we provide a survey on main features of vehicular social networks, from novel emerging technologies to social aspects used for mobile applications, as well as main issues and challenges. Vehicular social networks are described as decentralized opportunistic communication networks formed among vehicles. They exploit mobility aspects, and basics of traditional social networks, in order to create novel approaches of message exchange through the detection of dynamic social structures. An overview of the main state-of-the-art on safety and entertainment applications relying on social networking solutions is also provided.
Phenomics of rice early vigour and drought response: Are sugar related and morphogenetic traits relevant?

Early vigour (biomass accumulation) is a useful but complex trait in rainfed rice (Oryza sativa L). Little is known on trade-offs with drought tolerance. This study explored the relevance of (sugar) metabolic and morphogenetic traits to describe the genetic diversity of rice early vigour and its phenotypic plasticity under drought conditions. A greenhouse experiment was conducted to characterize on a panel of 43 rice genotypes plant morphogenesis and sugar concentration in expanded (source) and expanding (sink) leaves. Across genotypes in control treatment, leaf starch concentration was negatively correlated with organogenetic development rate (DR, defined as leaf appearance rate on main stem). Genotypes with small leaves had high DR and tiller number but low leaf starch concentration. Under drought, vigorous genotypes showed stronger growth reduction. Starch concentration decreased in source leaves, by contrast with soluble sugars and with that observed in sink leaves. Accordingly, genotypes were grouped in three clusters differing in constitutive vigour, starch storage and growth maintenance under drought showing a trade off between constitutive vigour and drought tolerance. It was therefore suggested that non structural carbohydrates, particularly starch, were relevant markers of early vigour. Their relevance as markers of growth maintenance under drought needs to be further explored. Results are discussed regarding novel process based traits to be introduced in the GRiSP (Global Rice Science Partnership) phenotyping network.
Cartesian admittance control with on-line gravity and friction observer compensation for elastic joint robots

In this paper, a Cartesian admittance controller with on-line gravity and friction observer compensation based on passivity theory for elastic joint robots is proposed. For this study, a compliance and position controller for joint and Cartesian level has been described with dual loop construction: an outer-loop admittance control, and an inner-loop motor side position with torque feedback control. In terms of torque feedback, a physical interpretation is addressed and analyzed. Regarding as admittance controller of the elastic joint, two type (stiffness and damping) of the systematic control model can be represented. In addition to an on-line gravity compensation based-on output-side encodes has been proposed. Moreover, in order to achieve high trajectory tracking performance, a friction observer based compensation is applied also. Furthermore, aimed at the control performance of the stiffness, damping, and admittance control algorithm are assessed by a simulation, respectively. Finally, the simulation studies reveal a better effect regarding as the position tracking and torque output in contrast to without friction passivity algorithm and proportional-derivative (PD) control. In addition, the response of proposed compliance control method is effective for external force.
Effect of Dry Needling on Thigh Muscle Strength and Hip Flexion in Elite Soccer Players.

Increase in muscle force, endurance, and flexibility is desired in elite athletes to improve performance and to avoid injuries, but it is often hindered by the occurrence of myofascial trigger points. Dry needling (DN) has been shown effective in eliminating myofascial trigger points.



This randomized controlled study in 30 elite youth soccer players of a professional soccer Bundesliga Club investigated the effects of four weekly sessions of DN plus water pressure massage on thigh muscle force and range of motion of hip flexion. A group receiving placebo laser plus water pressure massage and a group with no intervention served as controls. Data were collected at baseline (M1), treatment end (M2), and 4 wk follow-up (M3). Furthermore, a 5-month muscle injury follow-up was performed.



DN showed significant improvement of muscular endurance of knee extensors at M2 (P = 0.039) and M3 (P = 0.008) compared with M1 (M1:294.6 ± 15.4 N·m·s, M2:311 ± 25 N·m·s; M3:316.0 ± 28.6 N·m·s) and knee flexors at M2 compared with M1 (M1:163.5 ± 10.9 N·m·s, M2:188.5 ± 16.3 N·m·s) as well as hip flexion (M1: 81.5° ± 3.3°, M2:89.8° ± 2.8°; M3:91.8° ± 3.8°). Compared with placebo (3.8° ± 3.8°) and control (1.4° ± 2.9°), DN (10.3° ± 3.5°) showed a significant (P = 0.01 and P = 0.0002) effect at M3 compared with M1 on hip flexion; compared with nontreatment control (-10 ± 11.9 N·m), DN (5.2 ± 10.2 N·m) also significantly (P = 0.049) improved maximum force of knee extensors at M3 compared with M1. During the rest of the season, muscle injuries were less frequent in the DN group compared with the control group.



DN showed a significant effect on muscular endurance and hip flexion range of motion that persisted 4 wk posttreatment. Compared with placebo, it showed a significant effect on hip flexion that persisted 4 wk posttreatment, and compared with nonintervention control, it showed a significant effect on maximum force of knee extensors 4 wk posttreatment in elite soccer players.
Diffuse axonal injury and traumatic coma in the primate.

Traumatic coma was produced in 45 monkeys by accelerating the head without impact in one of three directions. The duration of coma, degree of neurological impairment, and amount of diffuse axonal injury (DAI) in the brain were directly related to the amount of coronal head motion used. Coma of less than 15 minutes (concussion) occurred in 11 of 13 animals subjected to sagittal head motion, in 2 of 6 animals with oblique head motion, and in 2 of 26 animals with full lateral head motion. All 15 concussioned animals had good recovery, and none had DAI. Conversely, coma lasting more than 6 hours occurred in one of the sagittal or oblique injury groups but was present in 20 of the laterally injured animals, all of which were severely disabled afterward. All laterally injured animals had a degree of DAI similar to that found in severe human head injury. Coma lasting 16 minutes to 6 hours occurred in 2 of 13 of the sagittal group, 4 of 6 in the oblique group, and 4 of 26 in the lateral group, these animals had less neurological disability and less DAI than when coma lasted longer than 6 hours. These experimental findings duplicate the spectrum of traumatic coma seen in human beings and include axonal damage identical to that seen in sever head injury in humans. Since the amount of DAI was directly proportional to the severity of injury (duration of coma and quality of outcome), we conclude that axonal damage produced by coronal head acceleration is a major cause of prolonged traumatic coma and its sequelae.
Modelling the High-Frequency FX Market : an Agent-Based Approach

The development of computational-intelligence based strategies for electronic markets has been the focus of intense research. In order to be able to design efficient and effective automated trading strategies, one first needs to understand the workings of the market, the strategies that traders use and their interactions as well as the patterns emerging as a result of these interactions. In this paper, we develop an agent-based model of the FX market which is the market for the buying and selling of currencies. Our agent-based model of the FX market (ABFXM) comprises heterogeneous trading agents which employ a strategy that identifies and responds to periodic patterns in the price time series. We use the ABFXM to undertake a systematic exploration of its constituent elements and their impact on the stylized facts (statistical patterns) of transactions data. This enables us to identify a set of sufficient conditions which result in the emergence of the stylized facts similarly to the real market data, and formulate a model which closely approximates the stylized facts. We use a unique high frequency dataset of historical transactions data which enables us to run multiple simulation runs and validate our approach and draw comparisons and conclusions for each market setting.
Assessing the Usability of a Wearable Computer System For Outdoor Pedestrian Navigation

The paper outlines a pilot test on the UCSB Wearable Computer developed in conjunction with Project Battuta. The UCSB Wearable incorporates geographic context information (location and orientation) to display an electronic digital map to a user via a Heads-Up Display (HUD). Features of the custom designed Geographic Referenced Graphic Environment (GEORGE) software allow the user to switch between types of maps, and automatically center and rotate the map. The pilot study used pre and post-experiment questionnaires, performance records and interaction logs to evaluate which aspects of the system were most useful both in terms of user attitudes and objective performance on a navigation task. Zoom, pan and auto-rotate features were shown to be well used, while subjects showed indifference to map type and perspective view options. Performance on the wayfinding task generally improved over each segment of the trial, with subjects approaching normal walking speeds at the end of the trial.
Design-for-Assembly (DFA) by Reverse Engineering

`Design-for-Assembly (DFA)" is an engineering concept concerned with improving product designs for easier and less costly assembly operations. Much of academic or industrial eeorts in this area have been devoted to the development of analysis tools for measuring the \assemblability" of a design. On the other hand, little attention has been paid to the actual redesign process. The goal of this paper is to develop a computer-aided tool for assisting designers in redesigning a product for DFA. One method of redesign, known as the \replay and modify" paradigm, is to replay a previous design plan, and modify the plan wherever necessary and possible, in accordance to the original design intention, for newly speciied design goals 24]. The \replay and modify" paradigm is an eeective redesign method because it ooers a more global solution than simple local patch-ups. For such a paradigm, design information, such as the design plan and design rationale, must be recorded during design. Unfortunately, such design information is not usually available in practice. To handle the potential absence of the required design information and support the \replay and modify" paradigm, the redesign process is modeled as a reverse engineering activity. Reverse engineering roughly refers to an activity of inferring the process, e.g. the design plan, used in creating a given design, and using the inferred knowledge for design recreation or redesign. In this paper, the development of an interactive computer-aided redesign tool for Design-for-Assembly, called REVENGE (REVerse ENGineering), is presented. The architecture of REVENGE is composed of mainly four activities: design analysis, knowledge acquisition, design plan reconstruction, and case-based design modiication. First a DFA analysis is performed to uncover any undesirable aspects of the design with respect to its assemblability. REVENGE , then, interactively solicits designers for useful design information that might not be available from standard design documents such as design rationale. Then, a heuristic algorithm reconstructs a default design plan. A default design plan is a sequence of probable design actions that might have led to the original design. DFA problems identiied during the analysis stage are mapped to the portion of the design plan from which they might have originated. Problems that originate from the earlier portion of the design plan are attacked rst. A case-based approach is used to solve each problem by retrieving a similar redesign case and adapting it to the current situation. REVENGE has been implemented, and has been tested …
The role of Apriori algorithm for finding the association rules in Data mining

Now a day's Data mining has a lot of e-Commerce applications. The key problem is how to find useful hidden patterns for better business applications in the retail sector. For the solution of these problems, The Apriori algorithm is one of the most popular data mining approach for finding frequent item sets from a transaction dataset and derive association rules. Rules are the discovered knowledge from the data base. Finding frequent item set (item sets with frequency larger than or equal to a user specified minimum support) is not trivial because of its combinatorial explosion. Once frequent item sets are obtained, it is straightforward to generate association rules with confidence larger than or equal to a user specified minimum confidence. The paper illustrating apriori algorithm on simulated database and finds the association rules on different confidence value.
PennCOSYVIO: A challenging Visual Inertial Odometry benchmark

We present PennCOSYVIO, a new challenging Visual Inertial Odometry (VIO) benchmark with synchronized data from a VI-sensor (stereo camera and IMU), two Project Tango hand-held devices, and three GoPro Hero 4 cameras. Recorded at UPenn's Singh center, the 150m long path of the hand-held rig crosses from outdoors to indoors and includes rapid rotations, thereby testing the abilities of VIO and Simultaneous Localization and Mapping (SLAM) algorithms to handle changes in lighting, different textures, repetitive structures, and large glass surfaces. All sensors are synchronized and intrinsically and extrinsically calibrated. We demonstrate the accuracy with which ground-truth poses can be obtained via optic localization off of fiducial markers. The data set can be found at
Empty Cities: Image Inpainting for a Dynamic-Object-Invariant Space

In this paper we present an end-to-end deep learning framework to turn images that show dynamic content, such as vehicles or pedestrians, into realistic static frames. This objective encounters two main challenges: detecting all the dynamic objects, and inpainting the static occluded background with plausible imagery. The second problem is approached with a conditional generative adversarial model that, taking as input the original dynamic image and its dynamic/static binary mask, is capable of generating the final static image. The former challenge is addressed by the use of a convolutional network that learns a multi-class semantic segmentation of the image. These generated images can be used for applications such as augmented reality or vision-based robot localization purposes. To validate our approach, we show both qualitative and quantitative comparisons against other state-of-the-art inpainting methods by removing the dynamic objects and hallucinating the static structure behind them. Furthermore, to demonstrate the potential of our results, we carry out pilot experiments that show the benefits of our proposal for visual place recognition.
Side-channel power analysis of XTS-AES

XTS-AES is an advanced mode of AES for data protection of sector-based devices. Compared to other AES modes, it features two secret keys instead of one, and an additional tweak for each data block. These characteristics make the mode not only resistant against cryptoanalysis attacks, but also more challenging for side-channel attack. In this paper, we propose two attack methods on XTS-AES overcoming these challenges. In the first attack, we analyze side-channel leakage of the particular modular multiplication in XTS-AES mode. In the second one, we utilize the relationship between two consecutive block tweaks and propose a method to work around the masking of ciphertext by the tweak. These attacks are verified on an FPGA implementation of XTS-AES. The results show that XTS-AES is susceptible to side-channel power analysis attacks, and therefore dedicated protections are required for security of XTS-AES in storage devices.
Rate of entropy model for irreversible processes in living systems

In living systems, it is crucial to study the exchange of entropy that plays a fundamental role in the understanding of irreversible chemical reactions. However, there are not yet works able to describe in a systematic way the rate of entropy production associated to irreversible processes. Hence, here we develop a theoretical model to compute the rate of entropy in the minimum living system. In particular, we apply the model to the most interesting and relevant case of metabolic network, the glucose catabolism in normal and cancer cells. We show, (i) the rate of internal entropy is mainly due to irreversible chemical reactions, and (ii) the rate of external entropy is mostly correlated to the heat flow towards the intercellular environment. The future applications of our model could be of fundamental importance for a more complete understanding of self-renewal and physiopatologic processes and could potentially be a support for cancer detection.
Statistical Downscaling of ERA-Interim Forecast Precipitation Data in Complex Terrain Using LASSO Algorithm

1 College of Geographical Sciences, Fujian Normal University, Fuzhou 350007, China 2 Fujian Provincial Engineering Research Center for Monitoring and Assessing Terrestrial Disasters, Fuzhou 350007, China 3Department of Geography, Ludwig-Maximilians-Universität München, 80333 Munich, Germany 4 Institute of Water Management, Hydrology and Hydraulic Engineering, University of Natural Resources and Life Sciences, 1190 Vienna, Austria
The influence of ergonomic factors and perceptual-motor abilities on handwriting performance.

Difficulty with handwriting is one of the most frequent reasons that children in the public schools are referred to occupational therapy. Current research on the influence of ergonomic factors, such as pencil grip and pressure, and perceptual-motor factors traditionally believed to affect handwriting, is reviewed. Factors such as visual perception show little relationship to handwriting, whereas tactile-kinesthetic, visual-motor, and motor planning appear to be more closely related to handwriting. By better understanding the ergonomic and perceptual-motor factors that contribute to and influence handwriting, therapists will be better able to design rationally based intervention programs.
Enhancing Drug-Drug Interaction Extraction from Texts by Molecular Structure Information

We propose a novel neural method to extract drug-drug interactions (DDIs) from texts using external drug molecular structure information. We encode textual drug pairs with convolutional neural networks and their molecular pairs with graph convolutional networks (GCNs), and then we concatenate the outputs of these two networks. In the experiments, we show that GCNs can predict DDIs from the molecular structures of drugs in high accuracy and the molecular information can enhance text-based DDI extraction by 2.39 percent points in the F-score on the DDIExtraction 2013 shared task data set.
Development of a steerable, wheel-type, in-pipe robot and its path planning

This paper presents the development of a steerable, wheel-type, in-pipe robot and its path planning. First, we show the construction of the robot and demonstrate its locomotion inside a pipe. The robot is composed of two wheel frames and an extendable arm which links the centers of the two wheel frames. The arm presses the frames against the interior wall of a pipe to support the robot. The wheels of the frames are steered independently so that the robot can turn within a small radius of rotation. Experimental results of the locomotion show that the steering control is effective for autonomous navigation to avoid obstacles and to enter the joint spaces of Land T-shaped pipes. Generally, autonomous navigation is difficult for wheel-type robots because the steering angles required to travel along a desired path are not easily determined. In our previous work, the relationship between the steering angles and locomotion trajectories in a pipe has already been analyzed. Using this analysis, we propose the path planning in pipes.
Development and verification of tendon-driven rotary actuator for haptics with flexible actuators and a PE line

In the future, robots will be important device widely in our daily lives to achieve complicated tasks. To achieve the tasks, there are some demands for the robots. In this paper, two strong demands of them are taken attention. First one is multiple-degrees of freedom (DOF), and the second one is miniaturization of the robots. Although rotary actuators is necessary to get multiple-DOF, miniaturization is difficult with rotary motors which are usually utilized for multiple-DOF robots. Here, tendon-driven rotary actuator is a candidate to solve the problems of the rotary actuators. The authors proposed a type of tendon-driven rotary actuator using thrust wires. However, big mechanical loss and frictional loss occurred because of the complicated structure of connection points. As the solution for the problems, this paper proposes a tendon-driven rotary actuator for haptics with thrust wires and polyethylene (PE) line. In the proposed rotary actuator, a PE line is used in order to connect the tip points of thrust wires and the end effector. The validity of the proposed rotary actuator is evaluated by experiments.
Combined Syntactic and Semantic Kernels for Text Classification

The exploitation of syntactic structures and semantic background knowledge has always been an appealing subject in the context of text retrieval and information management. The usefulness of this kind of information has been shown most prominently in highly specialized tasks, such as classification in Question Answering (QA) scenarios. So far, however, additional syntactic or semantic information has been used only individually. In this paper, we propose a principled approach for jointly exploiting both types of information. We propose a new type of kernel, the Semantic Syntactic Tree Kernel (SSTK), which incorporates linguistic structures, e.g. syntactic dependencies, and semantic background knowledge, e.g. term similarity based on WordNet, to automatically learn question categories in QA. We show the power of this approach in a series of experiments with a well known Question Classification dataset.