nils-herrmann/clean_scirepeval huggingface dataset:
Using massively multiplayer online role playing games (MMORPGs) to support second language learning: Action research in the real and virtual world

Massively Multiplayer Online Role Playing Games (MMORPGs) create large virtual communities. Online gaming shows potential not just for entertaining, but also for education. The aim of this research project is to investigate the use of commercial MMORPGs to support second language teaching. MMORPGs offer a digital safe space in which students can communicate by using their target language with global players. This qualitative research based on ethnography and action research investigates the students’ experiences of language learning and performing while they play in the MMORPGs. Research was conducted in both the ‘real’ and ‘virtual’ worlds. In the real world the researcher observes the interaction with the MMORPGs by the students through actual discussion, and screen video captures while they are playing. In the virtual world, the researcher takes on the role of a character in the MMORPG enabling the researcher to get an inside point of view of the students and their own MMORPG characters. This latter approach also uses action research to allow the researcher to provide anonymous/private support to the students including in-game instruction, confidence building, and some support of language issues in a safe and friendly way. Using action research with MMORPGs in the real world facilitates a number of opportunities for learning and teaching including opportunities to practice language and individual and group experiences of communicating with other native/ second language speakers for the students. The researcher can also develop tutorial exercises and discussion for teaching plans based on the students’ experiences with the MMORPGs. The results from this research study demonstrate that MMORPGs offer a safe, fun, informal and effective learning space for supporting language teaching. Furthermore the use of MMORPGs help the students’ confidence in using their second language and provide additional benefits such as a better understanding of the culture and use of language in different contexts.
Where-and-When to Look: Deep Siamese Attention Networks for Video-based Person Re-identification

Video-based person re-identification (re-id) is a central application in surveillance systems with significant concern in security. Matching persons across disjoint camera views in their video fragments is inherently challenging due to the large visual variations and uncontrolled frame rates. There are two steps crucial to person re-id, namely discriminative feature learning and metric learning. However, existing approaches consider the two steps independently, and they do not make full use of the temporal and spatial information in videos. In this paper, we propose a Siamese attention architecture that jointly learns spatiotemporal video representations and their similarity metrics. The network extracts local convolutional features from regions of each frame, and enhance their discriminative capability by focusing on distinct regions when measuring the similarity with another pedestrian video. The attention mechanism is embedded into spatial gated recurrent units to selectively propagate relevant features and memorize their spatial dependencies through the network. The model essentially learns which parts (where) from which frames (when) are relevant and distinctive for matching persons and attaches higher importance therein. The proposed Siamese model is end-to-end trainable to jointly learn comparable hidden representations for paired pedestrian videos and their similarity value. Extensive experiments on three benchmark datasets show the effectiveness of each component of the proposed deep network while outperforming state-of-the-art methods.
The life cycle of Sclerocollum saudii Al-Jahdali, 2010 (Acanthocephala: Palaeacanthocephala: Rhadinorhynchidae) in amphipod and fish hosts from the Red Sea.

The rhadinorhynchid Sclerocollum saudii Al-Jahdali, 2010 was found in the intestine of its type host, Siganus rivulatus Forsskål & Niebuhr, 1775, a siganid fish permanently resident in a lagoon within the mangrove swamps found on the Egyptian coast of the Gulf of Aqaba (between 28°7'N and 28°18'N). Larval forms of this acanthocephalan (acanthors, acanthellae and cystacanths) were only found in Megaluropus agilis Hoek, 1889 (Crustacea: Gammaridae), a benthic amphipod abundant on algae and seagrasses in the lagoon. So, this life cycle of S. saudii was elucidated under semi-natural conditions: embryonated eggs of S. saudii were directly ingested by the amphipod and hatched in its intestine; the released acanthor penetrated the intestinal epithelium in 12-18 h to reach the connective tissue serosa, where it remained for about 3 days, then penetrated the intestinal wall and remained attached to its outer surface for 4 days. It then detached and dropped free in the amphipod haemocoel and transformed into an oval acanthella, growing for 16 days to reach the cystacanth stage. The cystacanth at 46 days post-infection was infective to fish (excysted in its intestine as an active juvenile). Male and female juveniles reached maturity 17 and 23 days post-infection. Recently copulated females first appeared 26 days post-infection and all females seemed to be copulated at 28 days post-infection; partially and fully gravid females first appeared 31 and 35 days post-infection. Mature males and fully gravid females started to die off naturally 31 and 43 days post-infection and were totally expelled from the fish intestine by 42 and 52 days post-infection. The cycle was completed in 89 days and is similar to other known palaeacanthocephalan life cycles, but has its own characteristics.
Stretch and activation of the human biarticular hamstrings across a range of running speeds

The human biarticular hamstrings [semimembranosus (SM), semitendinosus (ST) and biceps femoris long head (BFLH)] have an important role in running. This study determined how hamstrings neuro-mechanical behaviour changed with faster running, and whether differences existed between SM, ST and BFLH. Whole-body kinematics and hamstrings electromyographic (EMG) activity were measured from seven participants running at four discrete speeds (range: 3.4 ± 0.1 to 9.0 ± 0.7 m/s). Kinematic data were combined with a three-dimensional musculoskeletal model to calculate muscle–tendon unit (MTU) stretch and velocity. Activation duration and magnitude were determined from EMG data. With faster running, MTU stretch and velocity patterns remained similar, but maxima and minima significantly increased. The hamstrings were activated from foot-strike until terminal stance or early swing, and then again from mid-swing until foot-strike. Activation duration was similar with faster running, whereas activation magnitude significantly increased. Hamstrings activation almost always ended before minimum MTU stretch, and it always started before maximum MTU stretch. Comparing the hamstrings, maximum MTU stretch was largest for BFLH and smallest for ST irrespective of running speed, while the opposite was true for peak-to-peak MTU stretch. Furthermore, peak MTU shortening velocity was largest for ST and smallest for BFLH at all running speeds. Finally, for the two fastest running speeds, the amount of MTU stretch that occurred during terminal swing after activation had started was less for BFLH compared to SM and ST. Differences were evident in biarticular hamstrings neuro-mechanical behaviour during running. Such findings have implications for hamstrings function and injury.
Hybrid Tele-Manipulation System Using a Sensorized 3-D-Printed Soft Robotic Gripper and a Soft Fabric-Based Haptic Glove

This paper presents a hybrid tele-manipulation system, comprising of a sensorized 3-D-printed soft robotic gripper and a soft fabric-based haptic glove that aim at improving grasping manipulation and providing sensing feedback to the operators. The flexible 3-D-printed soft robotic gripper broadens what a robotic gripper can do, especially for grasping tasks where delicate objects, such as glassware, are involved. It consists of four pneumatic finger actuators, casings with through hole for housing the actuators, and adjustable base. The grasping length and width can be configured easily to suit a variety of objects. The soft haptic glove is equipped with flex sensors and soft pneumatic haptic actuator, which enables the users to control the grasping, to determine whether the grasp is successful, and to identify the grasped object shape. The fabric-based soft pneumatic haptic actuator can simulate haptic perception by producing force feedback to the users. Both the soft pneumatic finger actuator and haptic actuator involve simple fabrication technique, namely 3-D-printed approach and fabric-based approach, respectively, which reduce fabrication complexity as compared to the steps involved in a traditional silicone-based approach. The sensorized soft robotic gripper is capable of picking up and holding a wide variety of objects in this study, ranging from lightweight delicate object weighing less than 50 g to objects weighing 1100 g. The soft haptic actuator can produce forces of up to 2.1 N, which is more than the minimum force of 1.5 N needed to stimulate haptic perception. The subjects are able to differentiate the two objects with significant shape differences in the pilot test. Compared to the existing soft grippers, this is the first soft sensorized 3-D-printed gripper, coupled with a soft fabric-based haptic glove that has the potential to improve the robotic grasping manipulation by introducing haptic feedback to the users.
Accelerometer Data Collection and Processing Criteria to Assess Physical Activity and Other Outcomes: A Systematic Review and Practical Considerations.

Accelerometers are widely used to measure sedentary time, physical activity, physical activity energy expenditure (PAEE), and sleep-related behaviors, with the ActiGraph being the most frequently used brand by researchers. However, data collection and processing criteria have evolved in a myriad of ways out of the need to answer unique research questions; as a result there is no consensus.



The purpose of this review was to: (1) compile and classify existing studies assessing sedentary time, physical activity, energy expenditure, or sleep using the ActiGraph GT3X/+ through data collection and processing criteria to improve data comparability and (2) review data collection and processing criteria when using GT3X/+ and provide age-specific practical considerations based on the validation/calibration studies identified.



Two independent researchers conducted the search in PubMed and Web of Science. We included all original studies in which the GT3X/+ was used in laboratory, controlled, or free-living conditions published from 1 January 2010 to the 31 December 2015.



The present systematic review provides key information about the following data collection and processing criteria: placement, sampling frequency, filter, epoch length, non-wear-time, what constitutes a valid day and a valid week, cut-points for sedentary time and physical activity intensity classification, and algorithms to estimate PAEE and sleep-related behaviors. The information is organized by age group, since criteria are usually age-specific.



This review will help researchers and practitioners to make better decisions before (i.e., device placement and sampling frequency) and after (i.e., data processing criteria) data collection using the GT3X/+ accelerometer, in order to obtain more valid and comparable data.
Mechanisms of cytochrome c release from mitochondria

In healthy cells, cytochrome c (Cyt c) is located in the mitochondrial intermembrane/intercristae spaces, where it functions as an electron shuttle in the respiratory chain and interacts with cardiolipin (CL). Several proapoptotic stimuli induce the permeabilization of the outer membrane, facilitate the communication between intermembrane and intercristae spaces and promote the mobilization of Cyt c from CL, allowing for Cyt c release. In the cytosol, Cyt c mediates the allosteric activation of apoptosis-protease activating factor 1, which is required for the proteolytic maturation of caspase-9 and caspase-3. Activated caspases ultimately lead to apoptotic cell dismantling. Nevertheless, cytosolic Cyt c has been associated also to vital cell functions (i.e. differentiation), suggesting that its release not always occurs in an all-or-nothing fashion and that mitochondrial outer membrane permeabilization may not invariably lead to cell death. This review deals with the events involved in Cyt c release from mitochondria, with special attention to its regulation and final consequences.
Traffic forecasting for mobile networks with multiplicative seasonal ARIMA models

Traffic forecasting is an important task which is required by overload warning and capacity planning for mobile networks. Based on analysis of real data collected by China Mobile Communications Corporation (CMCC) Heilongjiang Co. Ltd, this paper proposes to use the multiplicative seasonal ARIMA models for mobile communication traffic forecasting. Experiments and test results show that the whole solution presented in this paper is feasible and effective to fulfill the requirements in traffic forecasting application for mobile networks.
Gait abnormalities in hemiplegia: their correction by ankle-foot orthoses.

Hemiparetic gait is characterized by slow speed and poorly coordinated movements. Because the values of gait parameters vary with changes in speed, the slow speed that is typical of hemiparetic gait necessitates applying controls for the influence of speed when comparing hemiparetic and able-bodied persons. Gait kinetics and kinematics were measured in seven hemiparetic and seven able-bodied adults to compare their gait patterns at similar speeds and to assess the effectiveness of ankle-foot orthoses which were double-stopped in 5 degrees of dorsiflexion or 5 degrees of plantarflexion. Hemiparetic persons ambulating without the orthoses had a shorter step length, longer duration stance, and shorter duration swing than normal. They displayed greater than normal flexion of the affected hip during midstance, which, by putting the center of mass farther in front of the knee, may explain the increased knee extension moment due to vertical force. Affected hip adduction during single support was less in hemiparetic persons than in able-bodied persons, indicating a decreased lateral shift to the paretic side. During the swing phase, the affected limbs of hemiparetic persons were in less knee flexion and less dorsiflexion than normal, necessitating circumduction to achieve toe clearance. Ankle-foot orthoses increased walking speed to normalize heelstrike duration through use of an optimally adjusted plantarflexion stop. An improperly adjusted orthosis may produce an exaggerated knee flexion moment resulting in knee instability.
Fully Motion-Aware Network for Video Object Detection

Video objection detection is challenging in the presence of appearance deterioration in certain video frames. One of typical solutions is to enhance per-frame features through aggregating neighboring frames. But the features of objects are usually not spatially calibrated across frames due to motion from object and camera. In this paper, we propose an end-to-end model called fully motion-aware network (MANet), which jointly calibrates the features of objects on both pixel-level and instance-level in a unified framework. The pixel-level calibration is flexible in modeling detailed motion while the instance-level calibration captures more global motion cues in order to be robust to occlusion. To our best knowledge, MANet is the first work that can jointly train the two modules and dynamically combine them according to the motion patterns. It achieves leading performance on the large-scale ImageNet VID dataset.
A unified statistical approach for determining significant signals in images of cerebral activation.

We present a unified statistical theory for assessing the significance of apparent signal observed in noisy difference images. The results are usable in a wide range of applications, including fMRI, but are discussed with particular reference to PET images which represent changes in cerebral blood flow elicited by a specific cognitive or sensorimotor task. Our main result is an estimate of the P-value for local maxima of Gaussian, t, chi(2) and F fields over search regions of any shape or size in any number of dimensions. This unifies the P-values for large search areas in 2-D (Friston et al. [1991]: J Cereb Blood Flow Metab 11:690-699) large search regions in 3-D (Worsley et al.  and the usual uncorrected P-value at a single pixel or voxel.
On the Control and Properties of Supercoiled Polymer Artificial Muscles

Robotics have long sought an actuation technology comparable to or as capable as biological muscle tissue. Natural muscles exhibit a high power-to-weight ratio, inherent compliance and damping, fast action, and a high dynamic range. They also produce joint displacements and forces without the need for gearing or additional hardware. Recently, supercoiled commercially available polymer threads (sewing thread or nylon fishing lines) have been used to create significant mechanical power in a muscle-like form factor. Heating and cooling the polymer threads causes contraction and expansion, which can be utilized for actuation. In this paper, we describe the working principle of supercoiled polymer (SCP) actuation and explore the controllability and properties of these threads. We show that under appropriate environmental conditions, the threads are suitable as a building block for a controllable artificial muscle. We leverage off-the-shelf silver-coated threads to enable rapid electrical heating while the low thermal mass allows for rapid cooling. We utilize both thermal and thermomechanical models for feed-forward and feedback control. The resulting SCP actuator regulates to desired force levels in as little as 28 ms. Together with its inherent stiffness and damping, this is sufficient for a position controller to execute large step movements in under 100 ms. This controllability, high performance, the mechanical properties, and the extremely low material cost are indicative of a viable artificial muscle.
Vascular endothelium and the blood-brain barrier.

The vascular endothelium has become a major focus of attention in long-term control of vascular pathophysiology and disease progression. Apart from providing the lining of the vessel, endothelial cells perform and control many functions such as cell migration, remodeling, proliferation, apoptosis, the production, secretion, and metabolism of proteins and small molecules, and the regulation of the contractility of vascular smooth muscle cells. Endocrine regulation of vascular tone by small-molecule messengers and factors related to cell growth, vessel wall thickening, and the development of atherosclerosis has been the target of many investigations in the past. These have led to a much better understanding of large-vessel disease, particularly in the coronary arteries. The sudden loss of patency of vessels of larger caliber such as coronary arteries, carotid arteries, or femoral arteries often creates a suddenmajor health hazard.Given the ratio of surface covered by endothelial cells to the volume of blood in a given segment, the power of the endothelium to locally control pathological events is certainly maximal in small-caliber vessels, which contain the majority of endothelial cells within the vascular tree, and much less in larger vessels such as the coronary or carotid arteries. The unique location of certain vascular pathology already suggests local or segmental differences in endothelial function within certain segments of the vasculature. These differences may apply not only to localization but more so to the time course or the response to certain physiological or pathological
Accelerator Design with Effective Resource Utilization for Binary Convolutional Neural Networks on an FPGA

In binary convolutional neural networks (BCNN), arithmetic operations are replaced by bitwise operations and the required memory size is greatly reduced, which is a good opportunity to accelerate training or inference on FPGAs. This paper proposes a BCNN architecture with a single engine that achieves high resource utilization. The proposed design deploys a large number of processing elements in parallel to increase throughput, and a forwarding scheme to increase resource utilization on the existing engine. In addition, we demonstrate a novel reuse scheme to make fully-connected layers exploit the same engine. The proposed design is combined with an inference environment for comparison and implemented on a Xilinx XCVU190 FPGA. The implemented design uses 61k look-up tables (LUTs), 45k flip-flops (FFs), and 13.9Mbit block RAM (BRAM). In addition, it achieves 61.6 GOPS/kLUT at 240MHz, which is 1.16 times higher than that of the best prior BCNN design, even though it uses a single engine without optimal configurations on each layer.
Segmentation and classification of time series using ordinal pattern distributions

The distribution of ordinal patterns in time series has been found to reflect important qualitative features of the underlying system dynamics. Abrupt changes in the dynamics typically result in clearly visible differences between the distributions before and after the break. Recurring dynamical regimes can be discovered by classifying the distributions in different parts of the time series. This paper discusses two algorithms which exploit the relation between ordinal pattern distributions and system dynamics for the segmentation and classification of time series. The first algorithm employs a kernel-based statistic, the Maximum Mean Discrepancy of ordinal pattern distributions, to detect and locate change points in the time series. The second algorithm uses clustering of the ordinal pattern distributions to classify time series segments with similar dynamics. The methodology is applied to various real-life time series from physiology and economics.
Assessing the Contribution of Twitter's Textual Information to Graph-based Recommendation

Graph-based recommendation approaches can model associations between users and items alongside additional contextual information. Recent studies demonstrated that representing features extracted from social media (SM) auxiliary data, like friendships, jointly with traditional users/items ratings in the graph, contribute to recommendation accuracy. In this work, we take a step further and propose an extended graph representation that includes socio-demographic and personal traits extracted from the content posted by the user on SM. Empirical results demonstrate that processing unstructured textual information collected from Twitter and representing it in structured form in the graph improves recommendation performance, especially in cold start conditions.
Microstrip-based ultra-wideband composite BPF with short-circuited stubs

In this paper, the design and realization of microstrip-based ultra-wideband (UWB) composite bandpass filter (BPF) with short-circuited stubs is presented. The BPF is compositely constructed from the step impedance lowpass filter (LPF) and the optimum distributed highpass filter (HPF). Prior to the realization, the performances of filter and its physical dimension are investigated numerically to obtain the optimum design. The BPF is deployed on a grounded FR4 Epoxy dielectric substrate with the thickness of 0.8mm and the dimension of 25mm x 25mm. From the measurement result, it shows that the realized UWB composite BPF has 3dB bandwidth response of 10.03GHz ranges from 1.86GHz to 11.89GHz.