Miracle-dz/UniFAR-FTUs huggingface dataset:
A MIML-LSTM neural network for integrated fine-grained event forecasting

Societal event forecasting plays a significant role in crisis warning and emergency management. Most traditional prediction methods focus on predicting whether specific events would happen or not. However, the results of these methods are not always informative for the policy makers due to excessive frequency, lack of details and supportive evidence about the predictive events. In this paper, we focus on the problem of integrated fine-grained event forecasting which is to predict the attributes of events and find out related precursors. Given a collection of news sequences, we transform the problem into a Multi-Instance Multi-Label learning (MIML) framework. Considering the sequential influence of events and hybridity of news, we implement the MIML framework based on the Long Short-Term Memory (LSTM) neural network, and propose the model called MIML-LSTM to extract three levels of deep features which represent news article, daily status and news sequence respectively. Based on this hierarchical representation, we design a compositional objective function for joint training of each part. Taking multiple types of protest event prediction as a demonstration, we evaluate the proposed model on news streams from three countries in Latin America, and the experimental results show the effectiveness of our model on integrated fine-grained event forecasting.
Using Industrial Robots as Haptic Devices for VR-Training

Many VR-training application require the integration of haptics, i.e. for surgical training. However, surgical VR-training is still limited to minimal invasive surgeries. For surgeries where high forces occur, like hip replacement, no VR-training applications have been developed. One cause for this is the lack of appropriate haptic devices which can deliver high forces. Novel industrial collaborative robots can provide high forces. Although, they lack control interfaces allowing to use them as haptic devices. We present 4 approaches for using these robots as general, multipurpose haptic input and output devices. The implemented approach was integrated into a VR hip replacement training application. An initial assessment demonstrates the general feasibility of our solution.
Continuous and intermittent heat acclimation and decay in team sport athletes

Abstract The aim of this study was to compare the impact of continuous (CON) and intermittent (INT) heat acclimation protocols on repeat-sprint performance, and to also assess the degree of performance decay following acclimation. Using a pair-matched, between subjects design, 16 trained male team sport athletes were allocated to either INT (8 sessions over 15 days) or CON acclimation (8 sessions over 8 days) groups. Participants performed a heat tolerance test (HTT) involving 60-min of repeat-sprint cycling with a 10-min half time break (in 35.3 ± 0.7°C, 60.1 ± 4.0%; RH) two days pre- (pre-HTT) and post-acclimation (post-HTT1). Decay was investigated with two further HTT's completed over the next two weeks (post-HTT2 and post-HTT3). Results showed the post-HTT1 performance variables [mean power (pre-HTT; INT = 1002.07 ± 173.74, CON = 1057.10 ± 180.07 / post-HTT1; INT = 1097.11 ± 186.85, CON = 1163.77 ± 184.65 W), mean power (W.kg−1), total work (kJ) and work (J.kg−1)] were greater than pre-HHT (p < 0.001) after acclimation, with no differences between INT and CON. No differences in final core and mean skin temperatures or heart rate existed after INT or CON acclimation, however 30 min measures for thermal sensation, perceived thirst and ratings of perceived exertion (as well as the final measure) were lower in post-HTT1 (p < 0.05) in CON. Performance and thermoregulatory responses in post-HTT2 and 3 were similar to post-HTT1 in both INT and CON. These results indicate that prolonged repeat-sprint exercise in the heat is improved after acclimation involving short, high-intensity cycling sessions using either CON or INT protocols, with performance well-maintained over the subsequent 2 weeks, despite removal of the heat stimulus.
Multimodal Assessment of Human Innovation Perception Based on Eye Tracking, Electroencephalography and Electrocardiography

In this work we investigate the capacity of evaluating human innovation perception from psycophysiological data, including electroencephalography (EEG), electrocardiography (ECG), and eye-gaze, measured with a wearable eye tracking device and an EEG headset. In order to do so, a dataset was collected while 36 participants watched video clips of the exterior and interior of four different car models, one of which was a futuristic concept car, under two different scenarios. The first involved a “first impressions”, unguided period and the second a guided period where participants were explicitly asked to attend to innovative areas of interest (AOI) in the vehicles. In both cases, participants reported their perceived level of innovation of the different AOIs. Experimental results showed that three metrics used for cognitive state assessment stood out for innovation perception assessment on a per-car basis, namely gaze average fixation duration, measured from the eye tracker, arousal (measured from ECG), and motivation (EEG). When averaging over cars and focusing on AOIs, in turn, cognitive load (EEG) showed importance. Lastly, while the guided protocol showed higher correlation when analyzing responses per-vehicle, the opposite behavior was observed when focusing only on AOIs, irrespective of the vehicle. In this scenario, the unguided condition resulted in higher correlation for the majority of the tested metrics.
What changes when? A reply to Beauchaine and Slep

Abstract In their commentary, Beauchaine and Slep (2018) raise important issues regarding research on behavioral parenting training (BPT). In this reply we highlight key points of agreement and respond to issues that we feel require clarification. BPT has been repeatedly proven effective in decreasing disruptive child behavior (also in the work of our research team). Yet, there is much to learn about for whom and how BPT is effective. Specifically, assessing the how (i.e., mediation) comes with many challenges. One of these challenges is taking into account the timeline of change, and being able to infer causal mechanisms of change. We argue that cross-lagged panel models (which we, and many other scholars, used) are a valid and valuable method for testing mediation. At the same time, our results raise important questions, specifically about the timing and form of expected changes in parenting and child behavior after BPT. For example, are these changes linear and gradual or do they happen more suddenly? To select the appropriate design, assessment tools, and statistical models to test mediation, we need to state detailed hypotheses on what changes when. An important next step might be to assess multiple putative mediators on different timescales, not only before and after, but specifically also during BPT.
RST 3D: A Comprehensive Gesture Set for Multitouch 3D Navigation

We present a comprehensive multitouch input mapping for 3D navigation of multiscale 3D models. In contrast to prior work, our technique offers explicit control over 3D rotation, 3D translation, and uniform scaling with manipulative gestures that do not require graphical widgets. Our proposed technique is consistent with the established RST mapping (rotation, scaling, translation) for 2D mul-titouch input and follows suggestions from prior work on multitouch 3D interaction. Our implementation includes a rendering technique that can reduce perceptual conflicts of 3D touch input on stereoscopic displays. We also report on two user studies that informed the suggested interaction design and confirmed its usability.
Photoneutron Dose Estimation in GRID Therapy Using an Anthropomorphic Phantom: A Monte Carlo Study

Background: In the past, GRID therapy was used as a treatment modality for the treatment of bulky and deeply seated tumors with orthovoltage beams. Now and with the introduction of megavoltage beams to radiotherapy, some of the radiotherapy institutes use GRID therapy with megavoltage photons for the palliative treatment of bulky tumors. Since GRID can be a barrier for weakening the photoneutrons produced in the head of medical linear accelerators (LINAC), as well as a secondary source for producing photoneutrons, therefore, in terms of radiation protection, it is important to evaluate the GRID effect on photoneutron dose to the patients. Methods: In this study, using the Monte Carlo code MCNPX, a full model of a LINAC was simulated and verified. The neutron source strength of the LINAC (Q), the distributions of flux (φ), and ambient dose equivalent (H*[10]) of neutrons were calculated on the treatment table in both cases of with/without the GRID. Finally, absorbed dose and dose equivalent of neutrons in some of the tissues/organs of MIRD phantom were computed with/without the GRID. Results: Our results indicate that the GRID increases the production of the photoneutrons in the LINAC head only by 0.3%. The calculations in the MIRD phantom show that neutron dose in the organs/tissues covered by the GRID is on average by 48% lower than conventional radiotherapy. In addition, in the uncovered organs (by the GRID), this amount is reduced to 25%. Conclusion: Based on the findings of this study, in GRID therapy technique compared to conventional radiotherapy, the neutron dose in the tissues/organs of the body is dramatically reduced. Therefore, there will be no concern about the GRID effect on the increase of unwanted neutron dose, and consequently the risk of secondary cancer.
Mitigating the Impact of Plug-In Electric Vehicles on Distribution Systems Using Demand-Side Management of Electric Water Heaters

This paper proposes the use of electric water heaters (EWH), already existing in residential distribution systems, to mitigate the impacts of the increasing integration of plug-in electric vehicles (PEVs). By controlling the thermostat setpoint of the EWHs within the distribution system, the peak demand due to the PEVs charging is flattened. The proposed control scheme has been verified using a simulation model developed in MATLAB environment. Simulation results on a 33-bus distribution test system reveal the potential of the proposed control scheme to mitigate the impacts of increased PEV penetration while meeting the EWHs hot water demand requirements.
Reduction of Power Losses of SiC MOSFET Based Power Modules in Automotive Traction Inverter Applications

Recent advancements in Silicon Carbide MOSFET technologies both in design and processing have enabled its full adoption in automotive traction applications. This work theoretically and experimentally demonstrates how a traction inverter realized with SiC MOSFET power modules can reduce inverter power losses compared to conventional inverter with silicon based IGBT and diode power modules. The traction inverter is the main focus because it consumes the largest amount of energy from the battery of a Plug-In Hybrid or Battery Electric Vehicles. Reduction in power losses will directly improve battery range or increase miles per gallon of the vehicle.
Performance Characterization of Low-Latency Adaptive Streaming From Video Portals

News-based websites and portals provide significant amounts of multimedia content to accompany news stories and articles. In this context, the HTTP adaptive streaming is generally used to deliver video over the best-effort Internet, allowing smooth video playback and an acceptable Quality Of Experience (QoE). To stimulate the user engagement with the provided content, such as browsing between videos, reducing the videos’ startup time has become more and more important: while the current median load time is in the order of seconds, research has shown that the user waiting times must remain below two seconds to achieve an acceptable QoE. In this paper, four complementary components are optimized and integrated into a comprehensive framework for low-latency delivery of news-related video content: 1) server-side encoding with short video segments; 2) HTTP/2 server push at the application layer; 3) server-side user profiling to identify relevant content for a given user; and 4) client-side storage to hold proactively delivered content. Using a large data set of a major Belgian news provider, containing millions of text- and video-based article requests, we show that the proposed framework reduces the videos’ startup time in different mobile network scenarios by over 50%, thereby improving the user interaction and skimming available content.
Agency Enhances Body Ownership Illusion of Being a Virtual Bat

This poster describes a within-subject study of agency's influence on virtual body ownership (VBO) using anatomically similar but morphologically different body of a virtual bat. Paricipants were exposed to flight under four conditions: voluntary movement through virtual environment (VE) with avatar present, voluntary movement through virtual environment (VE) with avatar absent, voluntary limbs movement without movements through VE, and finally involuntary movement of the avatar through VE. The results suggest that agency enhances VBO illusion the most under participants' full control during flight locomotion.
Using Machine Learning to Enable Probabilistic Reliability Assessment in Operation Planning

In the context of operation planning, probabilistic reliability assessment essentially boils down to predicting, efficiently and with sufficient accuracy, various economic and reliability indicators reflecting the expected performance of the system over a certain look-ahead horizon, so as to guide the operation planner in his decision-making. In order to speedup the crude Monte Carlo approach, which would entail a very large number of heavy computations, we propose in this paper an approach combining Monte Carlo simulation, machine learning and variance reduction techniques such as control variates. We provide an extensive case study testing this approach on the three-area IEEE-RTS96 benchmark, in the context of day-ahead operation planning while using a security constrained optimal power flow model to simulate real-time operation according to the N-1 criterion. From this case study, we can conclude that the proposed approach allows to reduce the number of heavy computations by about an order of magnitude, without sacrificing accuracy.
Analysis of the risk factors that determine composite graft survival for fingertip amputation

The composite graft is the only surgical method that is able to maintain digital length and provide soft tissue coverage without donor site morbidities in microsurgically non-replantable fingertip amputations. This study aimed to explore the risk factors that determine the survival of composite grafts. Clinical characteristics associated with graft survival were retrospectively analysed by a comparison between the graft survival and failure groups. Of 94 patients who underwent a composite graft for fingertip amputation, the graft survived in 84 (89%). Surviving grafts showed reperfusion within 1 week. Multivariate analysis revealed that graft failure was independently associated with a crushing injury. Based on the risk factors from the comparison analyses and a review of previously published studies, a cutting injury, grafting the injured finger within 5 hours of injury, and being a non-smoker are associated with good results. In these circumstances, excellent outcomes with a high success rate can be achieved by composite graft in most adult patients as an alternative treatment to microsurgical replantation. Level of evidence: IV
A Routing Protocol for LoRA Mesh Networks

A limitation of current LoRa networks is their single-hop nature. This causes difficulties in areas with poor Internet access, such as remote rural areas, or challenging radio environments, for example in metropolitan areas, as the LoRa gateway must be placed at a location with backhaul access to the network server, but must nonetheless be reachable by all end devices. To facilitate these applications, we present a new routing protocol to enable mesh networking with LoRa, allowing for multihop networking between gateways to extend coverage. Our protocol is tailored specifically to the requirements of LoRa networks. We have developed a proof-of-concept implementation of the protocol and have shown its effectiveness in both laboratory tests and a field trial in a real-world LoRa deployment.
Aggregated Dynamic Equivalent of a Distribution System Hosting Inverter-Based Generators

An equivalent, i.e. a reduced-order model, of active distribution networks is derived, for use in (phasor-mode) dynamic simulations of large-disturbances. In the unreduced model, the network hosts a large number of inverter-based generators, responding to the disturbances in accordance with recent or near-future grid codes. The aggregated equivalent is of the “grey-box” type and its parameters are tuned in the least-square sense to match the dynamic responses of the unreduced system to several training disturbances. Changes in operating point are easily reflected when initializing the reduced model. Simulations are reported on a detailed 75-bus distribution system. The accuracy of the equivalent has been checked with respect to untrained disturbances and changes of the operating point.
Object identity as a query language primitive

We demonstrate the power of object identities (oids) as a database query language primitive. We develop an object-based data model, whose structural part generalizes most of the known complex-object data models: cyclicity is allowed in both its schemas and instances. Our main contribution is the operational part of the data model, the query language IQL, which uses oids for three critical purposes: (1) to represent data-structures with sharing and cycles, (2) to manipulate sets, and (3) to express any computable database query. IQL can be type checked, can be evaluated bottom-up, and naturally generalizes most popular rule-based languages. The model can also be extended to incorporate type inheritance, without changes to IQL. Finally, we investigate an analogous value-based data model, whose structural part is founded on regular infinte trees and whose operational part is IQL.
LAIM: A Linear Time Iterative Approach for Efficient Influence Maximization in Large-Scale Networks

The problem of influence maximization (IM) has been extensively studied in recent years and has many practical applications such as social advertising and viral marketing. Given the network and diffusion model, IM aims to find an influential set of seed nodes so that targeting them as diffusion sources will trigger the maximum cascade of influenced individuals. The largest challenge of the IM problem is its NP-hardness, and most of the existing approaches are with polynomial time complexity, making themselves unscalable to very large networks. To address this issue, in this paper, we propose LAIM: a linear time iterative approach for efficient IM on large-scale networks. Our framework has two steps: 1) influence approximation and 2) seed set selection. In the first step, we propose an iterative algorithm to compute the local influence of a node based on a recursive formula and use the local influence to approximate its global influence. In the second step, the $k$ influential seed nodes are mined based on the approximated influence in the first step. Based on our model, we theoretically prove that the proposed approach has linear time and space complexity. We further accelerate our algorithm with simple modifications and propose its fast version. Experimental results on eight real-world large-scale networks exhibit the superiority of our approach over the state-of-the-art methods in terms of both effectiveness and efficiency.
Molecular cloning and expression of ghrelin in the hypothalamus–pituitary–gastrointestinal tract axis of the Yak (Bos grunniens) in the Qinghai–Tibetan Plateau

Ghrelin is a very important brain–gut peptide that modulates appetite and energy metabolism in mammals. The yak is the only large mammal that can adapt to the cold temperatures and hypoxia conditions present in the Qinghai–Tibet Plateau. However, there are no reports on ghrelin molecular characterization and expression in the hypothalamus–pituitary–digestive tract axis of the yak to date. In this study, the coding region sequence of the yak ghrelin, containing a complete ORF (351) encoding for 117 amino acids, was cloned. Immunohistochemistry analysis of the yak samples showed that ghrelin‐immunoreactive cells were expressed at the arcuate nucleus (ARC), the ventromedial nucleus (VMN), the dorsomedial nucleus (DMN) of the hypothalamus and also at the anterior pituitary. Ghrelin‐positive cells were also present in approximately two thirds of the submucosa of the abomasum fundic gland and mucous layer of the duodenum intestinal gland. Ghrelin's mRNA highest expression occurred in the abomasum sample, followed by the duodenum, hypothalamus and lowest at the pituitary gland. The level of ghrelin mRNA measured in yak was higher than in cattle for all the tissues that were compared. The ghrelin protein and mRNA expression profiles were similar. These data imply that the high expression of ghrelin in the hypothalamus–pituitary–digestive tract axis of yak could aid adaptation to the extreme environment better than cattle, by improving appetite and fat accumulation, regulating body temperature and reducing energy consumption via regulating energy metabolism.
Polarization Engineered Enhancement Mode High Breakdown Voltage GaN CAVET

In this work we propose and simulate a polarization engineered enhancement mode current aperture vertical electron transistor (P-CAVET). The novelty of the proposed structure lies in using polarization engineering to achieve enhancement mode operation. The current blocking layer (CBL) of proposed P-CAVET is hybrid in nature and consist of an oxide part and AIN part. Aluminum Nitride (AIN) portion of CBL is used to lift the triangular well existing at AIGaN/GaN interface above the Fermi level, thus achieving the enhancement mode operation. The CBL provides better suppression of vertical leakage which improves the breakdown voltage. The proposed structure does not need any p-type doping either for achieving enhancement mode operation or for forming current blocking layer. A 2-D calibrated simulation study has revealed that the proposed device exhibits a threshold voltage of 3.1V and breakdown voltage improvement of 100% over the conventional device CAVET.
Climb, Fly, Stack: Design of Tangible and Gesture-Based Interfaces for Natural and Efficient Interaction

This paper describes three novel 3D interaction metaphors conceived to fulfill the three tasks proposed in the current edition of the IEEE VR 3DUI Contest. We propose the VladdeR, a tangible interface for Virtual laddeR climbing, the FPDrone, a First Person Drone control flying interface, and the Dice Cup, a tangible interface for virtual object stacking. All three interactions take advantage of body proprioception and previous knowledge of real life interactions without the need of complex interaction mechanics: climbing a tangible ladder through arm and leg motions, control a drone like a child flies an imaginary plane by extending your arms or stacking objects as you will grab and stack dice with a dice cup.