nils-herrmann/clean_scirepeval huggingface dataset:
Multi-modal Capsule Routing for Actor and Action Video Segmentation Conditioned on Natural Language Queries

In this paper, we propose an end-to-end capsule network for pixel level localization of actors and actions present in a video. The localization is performed based on a natural language query through which an actor and action are specified. We propose to encode both the video as well as textual input in the form of capsules, which provide more effective representation in comparison with standard convolution based features. We introduce a novel capsule based attention mechanism for fusion of video and text capsules for text selected video segmentation. The attention mechanism is performed via joint EM routing over video and text capsules for text selected actor and action localization. The existing works on actor-action localization are mainly focused on localization in a single frame instead of the full video. Different from existing works, we propose to perform the localization on all frames of the video. To validate the potential of the proposed network for actor and action localization on all the frames of a video, we extend an existing actor-action dataset (A2D) with annotations for all the frames. The experimental evaluation demonstrates the effectiveness of the proposed capsule network for text selective actor and action localization in videos, and it also improves upon the performance of the existing state-of-the art works on single frame-based localization.  Overview of the proposed approach. For a given video, we want to localize the actor and action which are described by an input textual query. Capsules are extracted from both the video and the textual query, and a joint EM routing algorithm creates high level capsules, which are further used for localization of selected actors and actions.
TheArchitect: A Serverless-Microservices Based High-level Architecture Generation Tool

Software is ubiquitous in today’s systems and business operations. Most importantly the architecture of a software system determines its quality and longevity, because the development work related to the software system will be carried out to be in line with its architecture design. Hence, it’s highly important to structure the high-level software architecture accordingly to deliver the expected customer requirements while accounting for quality measures such as scalability, high availability and high performance. We propose TheArchitect, a serverless-microservices based high-level architecture generation tool, which will auto generate serverless-microservices based high-level architecture for a given business application, preserving the highlighted quality measures providing a tool based support for the software architect with respect to designing the high-level architecture. TheArchitect will provide any software developer to generate a proper architecture minimizing the involvement of an experienced software architect. Furthermore, the positives that microservices and serverless technologies has brought to the world of software engineering has made the software engineering community shift from the era of building large monolith applications containing overly complex designs, to microservices and serverless based technologies. Hence TheArchitect focuses on generating best fitted microservices and serverless based high-level architecture for a given application.
Complex Word Identification: Convolutional Neural Network vs. Feature Engineering

We describe the systems of NLP-CIC team that participated in the Complex Word Identification (CWI) 2018 shared task. The shared task aimed to benchmark approaches for identifying complex words in English and other languages from the perspective of non-native speakers. Our goal is to compare two approaches: feature engineering and a deep neural network. Both approaches achieved comparable performance on the English test set. We demonstrated the flexibility of the deeplearning approach by using the same deep neural network setup in the Spanish track. Our systems achieved competitive results: all our systems were within 0.01 of the system with the best macro-F1 score on the test sets except on Wikipedia test set, on which our best system is 0.04 below the best macro-F1 score.
POMCPOW: An online algorithm for POMDPs with continuous state, action, and observation spaces

Online solvers for partially observable Markov decision processes have been applied to problems with large discrete state spaces, but continuous state, action, and observation spaces remain a challenge. This paper begins by investigating double progressive widening (DPW) as a solution to this challenge. However, we prove that this modification alone is not sufficient because the belief representations in the search tree collapse to a single particle causing the algorithm to converge to a policy that is suboptimal regardless of the computation time. The main contribution of the paper is to propose a new algorithm, POMCPOW, that incorporates DPW and weighted particle filtering to overcome this deficiency and attack continuous problems. Simulation results show that these modifications allow the algorithm to be successful where previous approaches fail.
Miniature soft hand with curling rubber pneumatic actuators

In medical and biotechnology fields, soft devices are required because of their high safety from low mechanical impedance. FMA (Flexible Microactuator) is one of the typical soft actuators. It consists of fiber-reinforced rubber structure with multi air chambers and realizes bending motion pneumatically. It has been applied to robot hands, robot legs and so on. High potential of FMA has been confirmed by many experiments reported in several papers. However in fabrication process of the actuator, it is difficult to embed the reinforced fiber in the rubber structure. In this study, we aim at development of a fiber less FMA realizing quite large motion, which can be said curling motion, and a soft hand using the actuators. We design the actuator without fiber using nonlinear FEM (Finite Element Method) and derived efficient shape. The actuator is fabricated through micro rubber casting process including micro machining process for molds, micro vacuum rubber molding process and rubber bonding process with surface improvement by excimer light. Basic driving experiments of the actuator showed that it realized curling motion which agreed well with FEM results. And the actuator could grasp a fish egg without breaking. Additionally, we made a soft hand consisting of three curling actuators. This hand also could be manufactured by simple casting process. The developed hand works opening and closing motions well.
Congenitally missing maxillary lateral incisors: treatment.

The 2 major treatment approaches for congenitally missing maxillary lateral incisors are space closure via orthodontic therapy, or space opening to allow prosthodontic replacements either with a fixed prosthesis or single-tooth implant. Both of these treatment approaches can potentially compromise aesthetics, periodontal health, and function. It is essential for an interdisciplinary dental specialty team to establish realistic treatment objectives, communicate the sequence of treatment, interact during treatment, evaluate dental and gingival aesthetics, and position teeth to permit proper prosthetic treatment. If this interdisciplinary approach is used, the aesthetics and long-term dental health of the patient following treatment will be greatly enhanced.
Early Fusion of Camera and Lidar for robust road detection based on U-Net FCN

Automated vehicles rely on the accurate and robust detection of the drivable area, often classified into free space, road area and lane information. Most current approaches use monocular or stereo cameras to detect these. However, LiDAR sensors are becoming more common and offer unique properties for road area detection such as precision and robustness to weather conditions. We therefore propose two approaches for a pixel-wise semantic binary segmentation of the road area based on a modified U-Net Fully Convolutional Network (FCN) architecture. The first approach UView-Cam employs a single camera image, whereas the second approach UGrid-Fused incorporates a early fusion of LiDAR and camera data into a multi-dimensional occupation grid representation as FCN input. The fusion of camera and LiDAR allows for efficient and robust leverage of individual sensor properties in a single FCN. For the training of UView-Cam, multiple publicly available datasets of street environments are used, while the UGrid-Fused is trained with the KITTI dataset. In the KITTI Road/Lane Detection benchmark, the proposed networks reach a MaxF score of 94.23% and 93.81% respectively. Both approaches achieve realtime performance with a detection rate of about 10 Hz.
Towards a Definition of Knowledge Graphs

Recently, the term knowledge graph has been used frequently in research and business, usually in close association with Semantic Web technologies, linked data, large-scale data analytics and cloud computing. Its popularity is clearly influenced by the introduction of Google’s Knowledge Graph in 2012, and since then the term has been widely used without a definition. A large variety of interpretations has hampered the evolution of a common understanding of knowledge graphs. Numerous research papers refer to Google’s Knowledge Graph, although no official documentation about the used methods exists. The prerequisite for widespread academic and commercial adoption of a concept or technology is a common understanding, based ideally on a definition that is free from ambiguity. We tackle this issue by discussing and defining the term knowledge graph, considering its history and diversity in interpretations and use. Our goal is to propose a definition of knowledge graphs that serves as basis for discussions on this topic and contributes to a common vision.
A Haptic Knob for Rehabilitation of Hand Function

This paper describes a novel two-degree-of-freedom robotic interface to train opening/closing of the hand and knob manipulation. The mechanical design, based on two parallelogram structures holding an exchangeable button, offers the possibility to adapt the interface to various hand sizes and finger orientations, as well as to right-handed or left-handed subjects. The interaction with the subject is measured by means of position encoders and four force sensors located close to the output measuring grasping and insertion forces. Various knobs can be mounted on the interface, including a cone mechanism to train a complete opening movement from a strongly contracted and closed hand to a large opened position. We describe the design based on measured biomechanics, the redundant safety mechanisms as well as the actuation and control architecture. Preliminary experiments show the performance of this interface and some of the possibilities it offers for the rehabilitation of hand function.
Compact SRR Loaded UWB Circular Monopole Antenna With Frequency Notch Characteristics

This paper presents the design of a compact split ring resonator (SRR) loaded coplanar waveguide (CPW) fed ultrawideband circular monopole antenna having frequency notch characteristics. The electromagnetic coupling of the SRR with the CPW yields the frequency notch. Fabricated prototypes were measured and compared with simulations and good agreement was obtained. The impedance and radiation plots confirm the suppression of the desired notch frequency. A theoretical formulation to calculate the notch frequency is also proposed and validated.
CARDIA: study design, recruitment, and some characteristics of the examined subjects.

In 1984, a prospective cohort study, Coronary Artery Risk Development in Young Adults (CARDIA) was initiated to investigate life-style and other factors that influence, favorably and unfavorably, the evolution of coronary heart disease risk factors during young adulthood. After a year of planning and protocol development, 5,116 black and white women and men, age 18-30 years, were recruited and examined in four urban areas: Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota, and Oakland, California. The initial examination included carefully standardized measurements of major risk factors as well as assessments of psychosocial, dietary, and exercise-related characteristics that might influence them, or that might be independent risk factors. This report presents the recruitment and examination methods as well as the mean levels of blood pressure, total plasma cholesterol, height, weight and body mass index, and the prevalence of cigarette smoking by age, sex, race and educational level. Compared to recent national samples, smoking is less prevalent in CARDIA participants, and weight tends to be greater. Cholesterol levels are representative and somewhat lower blood pressures in CARDIA are probably, at least in part, due to differences in measurement methods. Especially noteworthy among several differences in risk factor levels by demographic subgroup, were a higher body mass index among black than white women and much higher prevalence of cigarette smoking among persons with no more than a high school education than among those with more education.
Industrial cyber physical systems: A survey for control-engineering tools

Cyber Physical Systems (CPS) play significant role in shaping smart manufacturing systems. CPS integrate computation with physical processes where behaviors are represented in both cyber and physical parts of the system. In order to understand CPS in the context of smart manufacturing, an overview of CPS technologies, components, and relevant standards is presented. A detailed technical review of the existing engineering tools and practices from major control vendors has been conducted. Furthermore, potential research areas have been identified in order to enhance the tools functionalities and capabilities in supporting CPS development process.
'teen Mental Health First Aid': a description of the program and an initial evaluation.

Many adolescents have poor mental health literacy, stigmatising attitudes towards people with mental illness, and lack skills in providing optimal Mental Health First Aid to peers. These could be improved with training to facilitate better social support and increase appropriate help-seeking among adolescents with emerging mental health problems. teen Mental Health First Aid (teen MHFA), a new initiative of Mental Health First Aid International, is a 3 × 75 min classroom based training program for students aged 15-18 years.



An uncontrolled pilot of the teen MHFA course was undertaken to examine the feasibility of providing the program in Australian secondary schools, to test relevant measures of student knowledge, attitudes and behaviours, and to provide initial evidence of program effects.



Across four schools, 988 students received the teen MHFA program. 520 students with a mean age of 16 years completed the baseline questionnaire, 345 completed the post-test and 241 completed the three-month follow-up. Statistically significant improvements were found in mental health literacy, confidence in providing Mental Health First Aid to a peer, help-seeking intentions and student mental health, while stigmatising attitudes significantly reduced.



teen MHFA appears to be an effective and feasible program for training high school students in Mental Health First Aid techniques. Further research is required with a randomized controlled design to elucidate the causal role of the program in the changes observed.
Social experience, behavior, and stress in guinea pigs

This study examined the effect of varying rearing and testing conditions on guinea pig aggression, courting behavior, endocrine responses and body weight. Pairs of 7-8-month-old males were placed in chronic confrontations for 6-50 days in 2 m2 enclosures. Social behavior was recorded with a total of 882 h observation time. Body weight as well as plasma glucocorticoid, testosterone and norepinephrine titers were determined for each male 20 h before, and 4, 52 and 124 h after, the onset of the chronic encounters. Three experiments were conducted: in Experiment I, 7 pairs of males, each male raised singly with one female (FRM), were confronted in the presence of an unfamiliar female, in Experiment II, 6 pairs of FRM were confronted with no female present, and in Experiment III, 7 pairs of males which were raised in different large colonies were confronted in the presence of an unfamiliar female. In Experiment II and III low levels of aggression, no distinct endocrine changes and no indications of physical injury occurred in winners or losers, whereas in Experiment I high levels of aggression and courting behavior, extreme increases in glucocorticoid titers and distinct decreases in body weights were found in both males. Losers, however, were affected to a much greater extent than winners. These findings suggest that in guinea pigs a causal relationship exists between social rearing conditions, behavior as adults and degree of social stress in chronic encounters.
Replacing the Grid Interface Transformer in Wind Energy Conversion System With Solid-State Transformer

In wind energy conversion systems, the fundamental frequency step-up transformer acts as a key interface between the wind turbine and the grid. Recently, there have been efforts to replace this transformer by an advanced power-electronics-based solid-state transformer (SST). This paper proposes a configuration that combines the doubly fed induction generator-based wind turbine and SST operation. The main objective of the proposed configuration is to interface the turbine with the grid while providing enhanced operation and performance. In this paper, SST controls the active power to/from the rotor side converter, thus, eliminating the grid side converter. The proposed system meets the recent grid code requirements of wind turbine operation under fault conditions. Additionally, it has the ability to supply reactive power to the grid when the wind generation is not up to its rated value. A detailed simulation study is conducted to validate the performance of the proposed configuration.
Apomixis in agriculture: the quest for clonal seeds

Apomixis, or asexual reproduction through seeds, is a natural trait that could have an immense positive impact on crop production. Apomictic breeding strategies could allow the fixation and indefinite propagation of any desired genotype, however complex. Apomicts display a wide variety of developmental mechanisms, which can be viewed as a short-circuiting of sexual development. Gametophytic and sporophytic apomixis are distinguished by the developmental origin of apomictically derived embryos. Genetic studies suggest that individual elements of gametophytic apomixis, such as apomeiosis and parthenogenesis, are either controlled by one or two dominant Mendelian factors. As recombination around apomeiosis loci is suppressed, it is currently not known how complex these loci are. Much less is known regarding the genetic control of sporophytic apomixis but initial studies suggest a complex genetic control. Genetic analyses of sexual reproduction in plant model systems have identified genes that, when mutated, display elements of apomixis. Such studies help in the identification of candidate genes and promoters that can be used for the de novo engineering of apomixis through biotechnology. Molecular genetic studies in apomictic and sexual systems will generate the knowledge necessary for the engineering of conditional apomixis technology. Approaches encouraging collaboration and widespread dissemination of the acquired knowledge will constitute the most innovative route to the development, deployment and acceptance of apomixis technology in agriculture
Blind image separation based on reorganization of block DCT

Blind image separation consists in processing a set of observed mixed images to separate them into a set of original components. Most of the current blind separation methods assume that the sources are as statistically independent or sparsity as possible given the observations. However, these hypotheses do not hold in real world situation. Considering that the images do not satisfy the independent and sparsity conditions, so the mixed images cannot be separated with independent component analysis and sparse component analysis directly. In this paper, a method based on reorganization of blocked discrete cosine transform (RBDCT) is first proposed to separate the mixed images. Firstly, we get the sparse blocks through RBDCT, and then select the sparsest block adaptively by linear strength in which the mixing matrix can be estimated by clustering methods. In addition, a theoretical result about the linearity of the RBDCT is proved. The effectiveness of the proposed approach is demonstrated by several numerical experiments and compared the results with other classical blind image methods.
A 71–76 GHz CMOS variable gain amplifier using current steering technique

A 71-76 GHz high dynamic range CMOS RF variable gain amplifier (VGA) is presented. Variable gain is achieved using two current-steering trans-conductance stages, which provide high linearity with relatively low power consumption. The circuit is fabricated in a MS/RF 90-nm CMOS technology and consumes 18-mA total current from a 2-V supply. This VGA achieves a 14-dB maximum gain, a 30-dB gain controlled range, and a 4-dBm output saturation power. To the authorpsilas knowledge, this VGA demonstrates the highest operation frequency among the reported CMOS VGAs.
A Hilbert Transform-Based Smart Sensor for Detection, Classification, and Quantification of Power Quality Disturbances

Power quality disturbance (PQD) monitoring has become an important issue due to the growing number of disturbing loads connected to the power line and to the susceptibility of certain loads to their presence. In any real power system, there are multiple sources of several disturbances which can have different magnitudes and appear at different times. In order to avoid equipment damage and estimate the damage severity, they have to be detected, classified, and quantified. In this work, a smart sensor for detection, classification, and quantification of PQD is proposed. First, the Hilbert transform (HT) is used as detection technique; then, the classification of the envelope of a PQD obtained through HT is carried out by a feed forward neural network (FFNN). Finally, the root mean square voltage (Vrms), peak voltage (Vpeak), crest factor (CF), and total harmonic distortion (THD) indices calculated through HT and Parseval's theorem as well as an instantaneous exponential time constant quantify the PQD according to the disturbance presented. The aforementioned methodology is processed online using digital hardware signal processing based on field programmable gate array (FPGA). Besides, the proposed smart sensor performance is validated and tested through synthetic signals and under real operating conditions, respectively.