Miracle-dz/UniFAR-FTUs huggingface dataset:
Continuous Decision Making for On-road Autonomous Driving under Uncertain and Interactive Environments

Although autonomous driving techniques have achieved great improvements, challenges still exist in decision making for variety of different scenarios under uncertain and interactive environments. A good decision maker must satisfy the following requirements: (1) Be in a generic and unified form to cover as more scenarios as possible. (2) Be able to interact properly with other moving obstacles under the uncertainty of their motions. In this paper, the continuous decision making (CDM) framework is proposed to formulate different driving scenarios in a unified way, which encodes the high level decision making information into a continuous reference trajectory that can be naturally combined with a lower level trajectory planner. Within the framework, a maximum interaction defensive policy (MIDP) is proposed, which calculates the best action to interact with stochastic moving obstacles while guaranteeing safety. The method is applied to a ramp merging scenario and the stochastic behavior models of the surrounding vehicles are learned from the NGSIM dataset. Simulations are shown to visualize and analyze the results.
Exploring the Potential of Using Semantic Context and Common Sense in On-Road Vehicle Detection

Vehicle detection is an important research topic for autonomous driving community. Since the great success of deep learning on object detection, almost all vehicle detection methods go along with this line. However, deep learning methods heavily rely on the training data, and the whole mechanism is like a “black box” Therefore, in this paper, we explore a vehicle detection method using traffic semantic context and human common sense instead of relying on the training data. To verify our idea, we compare our method with two classic machine learning methods as well as three state- of-the-art deep learning methods on a dataset collected in real traffics. The results show that our method outperforms others on this dataset. The deep learning methods may exceed ours after enlarging the training data or testing on more complicated datasets. However, the main contribution of this paper is providing inspiration for learning methods, and we believe their performance can be greatly improved after considering the idea of this paper.
Effect of Nanodiamond Addition on Flexural Strength, Impact Strength, and Surface Roughness of PMMA Denture Base

PURPOSE To assess the effect of addition of different concentrations of nanodiamonds (NDs) on flexural strength, impact strength, and surface roughness of heat-polymerized acrylic resin. MATERIALS AND METHODS 120 specimens were fabricated from heat-polymerized acrylic resin. They were divided into a control group of pure polymethylmethacrylate (PMMA; Major.Base.20) and three tested groups (PMMA-ND) with 0.5%wt, 1%wt, and 1.5%wt of added ND to PMMA. Flexural strength was determined using the three-point bending test. Impact strength was recorded by using a Charpy type impact test. Surface roughness test was performed using a Contour GT machine. One-way ANOVA and Tukey's post-hoc analysis (p ≤ 0.05) were used for statistical analysis. RESULTS Acrylic resin reinforced with 0.5% ND displayed significantly higher flexural strength than the unreinforced heat-polymerized specimens, acrylic resin reinforced with 1% ND and the 1.5% ND (p < 0.0001). The impact strength of unreinforced heat-polymerized specimens was significantly higher than all nano-composite materials (p < 0.0001) with no significant difference between 1% ND and the 1.5% ND (p > 0.05). The addition of 0.5% ND and 1% ND significantly decreased the surface roughness in comparison to both control and the 1.5% ND groups (p < 0.0001) while no significant differences between 0.5% ND and 1% ND (p > 0.05) were reported. Nano-composite material (0.5% ND) showed significantly lower surface roughness when compared to other specimens. CONCLUSIONS The addition of NDs to acrylic denture base improved the flexural strength and surface roughness at low concentrations (0.5%), while the impact strength was decreased with ND addition.
Involvement of general practitioners in colorectal cancer voluntary screening campaign: a mixed-methods study.

PURPOSE To investigate the attitudes and willingness of the general practitioners (GPs) as well as their actual participation in the voluntary colorectal cancer (CRC) screening campaign without additional financial incentives for them, combining quantitative and qualitative approaches. METHODS A multiple-case practice based study was designed using a mixed method, triangulation techniques and a sequential explanatory design strategy. The study included all 41 GPs practices in the Municipality of Asenovgrad. A questionnaire, face-to-face semi-structured interviews, nonparticipant direct structured observations and documentation review were used to collect data. Variation analysis, alternative analysis for percentage calculation and Mann-Whitney U test to compare two independent groups and Fisher's Exact Test were used. Statistical significance of the null hypothesis was assumed at p<0.05. RESULTS Older GPs (p=0.015) and those working with a practice nurse (p=0.000) were more inclined to participate in the CRC screening campaign. GPs more knowledgeable of the importance of CRC screening with iFOBT (immunochemical faecal occult blood test), (p=0.002) and those trusting its quality (p=0.007) were more willing and ready to take part in the screening campaign. Among barriers that GPs encountered in the present screening campaign were lack of knowledge and experience about iFOBT, lack of materials and insufficient incentives. CONCLUSION Some limitations influence the voluntary participation of GPs in CRC screening campaign that have to be considered before decisions can be made on the implementation of population-based CRC screening programme in Bulgaria in accordance with European guidelines on best practice.
Direct-Vlasov Study of Electron Cooling Mechanisms in Paraxial , Unmagnetized Plasma Thruster Plumes IEPC-2017-104

A model of an unmagnetized, steady-state, paraxial, collisionless, quasineutral plasma plume expanding into vacuum is presented. Electrons are treated kinetically, relying on the first-order conservation of their averaged radial action integral for the integration of Vlasov’s equation, whereas ions are treated as a cold species. The quasi-2D behavior of plasma density; self-consistent electric potential; electron pressure, and temperature is analyzed. In particular, the model yields the electron cooling rate in the collisionless plume, which differs from the Boltzmann relation or polytropic laws usually employed in fluid and PIC/fluid hybrid plume models. A simplified polytropic law is derived that is consistent with the kinetic electron expansion, which can replace current models in electric space propulsion plasma-spacecraft interaction codes.
Tree – ring growth response of scots pine (Pinus Sylvestris l.) to climate change / Nur Idzhainee Hashim, Rob Marrs and Nor Hanisah Mohd Hashim

Dendrochronology is the scientific discipline of determining the relationship between tree growth and climate , and is determined using the annual growth rings. This provides a potential method for monitoring climate change. Climate usually acts as a major factor influencing the tree growth. Here, the effects of climate of a conifer species was assessed in relation to measured climatic variables. Tree cores of Scots Pine (Pinus sylvestris) w ere sampled from a forestry plantation at Hordron Edge, Derbyshire to determine the relationship between ann ual growth incremen t and four climate variables (maximum temperature, minimum temperature, grass minim um temperature and rainfall). Standard dendrochronological techniques were used to collect, prepare and measure tree–ring width increments . Climate data were derived from the British Atmospheric Data Centre (BADC) from 1921–2013. Tree-ring widths were as cross referenced to the climate data to enable growth dynamics of (Pinus sylvestris) to be investigated. In this study there was no significan t correlation between growth and climatic variables; overall average mean sensitivity ( m s ) was 0.28 mm, only five of the 20 trees were sensitive to climate ( m s >0.3) with the other 15 trees being complacen t ( m s <0.3). The growth incremen t index p ortra yed a cyclic pattern of tree growth through time with peaks (fast growth) and troughs (slow growth) throughout the period. There were no significan t first-order relationships found between tree growth indices and any of the four climatic variables tested. This result suggests that cl ima t ic variables were not significan t in controlling tree growth at this site.
A Study on Comparison and Analysis of Usability Evaluation Model for Gameplay

As the development of human-centered products and contents has increased, the studies focusing on emotion of product and usability evaluation have been actively conducted recently. In particular, the importance of usability evaluation for game has emerged since development of game requires high cost and involves lots of developers with strong pressure not to fail. There are wide range of games in terms of genre and platform. Games even under same genre present uniquely different user emotion in accordance to UI, game usability and design. Therefore usability evaluation for game is necessary to be suited for the features of game correspondingly. This study introduces the method to reconstruct usability evaluation heuristics suitable for situations and purposes based on the analysis of traditional heuristics.
[Research Paper] Untangling Composite Commits Using Program Slicing

Composite commits are a common mistake in the use of version control software. A composite commit groups many unrelated tasks, rendering the commit difficult for developers to understand, revert, or integrate and for empirical researchers to analyse. We propose an algorithmic foundation for tool support to identify such composite commits. Our algorithm computes both a program dependence graph and the changes to the abstract syntax tree for the files that have been changed in a commit. Our algorithm then groups these fine-grained changes according to the slices through the dependence graph they belong to. To evaluate our technique, we analyse and refine an established dataset of Java commits, the results of which we also make available. We find that our algorithm can determine whether or not a commit is composite. For the majority of commits, this analysis takes but a few seconds. The parts of a commit that our algorithm identifies do not map directly to the commit's tasks. The parts tend to be smaller, but stay within their respective tasks.
Artificial pathway emergence in central metabolism from three recursive phosphoketolase reactions

The promiscuous activities of a recursive, generalist enzyme provide raw material for the emergence of metabolic pathways. Here, we use a synthetic biology approach to recreate such an evolutionary setup in central metabolism and explore how cellular physiology adjusts to enable recursive catalysis. We generate an Escherichia coli strain deleted in transketolase and glucose 6‐phosphate dehydrogenase, effectively eliminating the native pentose phosphate pathway. We demonstrate that the overexpression of phosphoketolase restores prototrophic growth by catalyzing three consecutive reactions, cleaving xylulose 5‐phosphate, fructose 6‐phosphate, and, notably, sedoheptulose 7‐phosphate. We find that the activity of the resulting synthetic pathway becomes possible due to the recalibration of steady‐state concentrations of key metabolites, such that the in vivo cleavage rates of all three phosphoketolase substrates are similar. This study demonstrates our ability to rewrite one of nature's most conserved pathways and provides insight into the flexibility of cellular metabolism during pathway emergence.
Network-wide Crowd Flow Prediction of Sydney Trains via Customized Online Non-negative Matrix Factorization

Crowd Flow Prediction (CFP) is one major challenge in the intelligent transportation systems of the Sydney Trains Network. However, most advanced CFP methods only focus on entrance and exit flows at the major stations or a few subway lines, neglecting Crowd Flow Distribution (CFD) forecasting problem across the entire city network. CFD prediction plays an irreplaceable role in metro management as a tool that can help authorities plan route schedules and avoid congestion. In this paper, we propose three online non-negative matrix factorization (ONMF) models. ONMF-AO incorporates an Average Optimization strategy that adapts to stable passenger flows. ONMF-MR captures the Most Recent trends to achieve better performance when sudden changes in crowd flow occur. The Hybrid model, ONMF-H, integrates both ONMF-AO and ONMF-MR to exploit the strengths of each model in different scenarios and enhance the models' applicability to real-world situations. Given a series of CFD snapshots, both models learn the latent attributes of the train stations and, therefore, are able to capture transition patterns from one timestamp to the next by combining historic guidance. Intensive experiments on a large-scale, real-world dataset containing transactional data demonstrate the superiority of our ONMF models.
Soluble Thrombomodulin Attenuates Endothelial Cell Damage in Hepatic Sinusoidal Obstruction Syndrome

Background: Hepatic sinusoidal obstruction syndrome (SOS), also known as veno-occlusive disease, is a form of drug-induced liver injury, the initial morphological changes associated with which occur in liver sinusoidal endothelial cells (LSECs). Recombinant human soluble thrombomodulin (rTM) is reported to have anti-inflammatory and cytoprotective effects. Therefore, we investigated the ability of rTM to protect endothelial cells and enhance their functions in a monocrotaline (MCT)-induced model of SOS. Materials and Methods: Human umbilical vein endothelial cells were assessed in vitro following administration of MCT (2-4 mM) with/without rTM (10-100 ng/ml) to investigate the effect of rTM on cell proliferation and apoptosis. In vivo experiments were performed with Crl:CD1 mice divided into three groups: rTM (rTM + MCT), placebo (control diluent + MCT), and control (control diluent only). LSECs [cluster of differentiation (CD) 31+CD34+ vascular endothelial growth factor receptor 3 (VEGFR3)+ cells] from these mice were identified using fluorescence-activated cell sorting and assessed by quantitative real-time polymerase chain reaction (qPCR). Results: In vitro, caspase-3 and -7 activities were significantly lower and cell viability (as assessed by MTT assays) significantly higher in the rTM group than in the placebo group. Moreover, levels of p-AKT increased upon rTM administration. In vivo, damage to LSECs in zone 3 of the hepatic acinus was attenuated and the number of LSECs were maintained in the rTM group, in contrast to the placebo group. Furthermore, expression of Nos3 (encoding endothelial nitric oxide synthase) was higher and that of plasminogen activator inhibitor 1 (Pai1) lower in LSECs from mice in the rTM group than in those from the placebo group. Conclusion: rTM can attenuate SOS by protecting LSECs and enhancing their functions.
Role of Heparin Irrigation in the Management of Superficial Burns with Special Reference to Pain Relief and Wound Healing: A Pilot Study

Introduction The objective of this study was to assess the effect of heparin irrigation in the management of superficial first and second degree burns with special reference to pain relief and wound healing. Materials and methods This pilot study was carried out over a period of 12 months in a tertiary care centre in South India. The study patients were divided into two groups: the heparin group and the saline control group. In the control group, the burn wound was irrigated with 100 mL of normal saline before the conventional dressing with silver sulfadiazine. In the heparin irrigation group, the wound was irrigated with heparin solution before the conventional dressing. Wound healing was assessed in terms of necrotic tissue score and granulation tissue score. Patient satisfaction in terms of patient satisfaction score, visual analogue scale (VAS) score, and length of hospitalization were compared between the two groups. Results A total of 40 patients were analysed in the study, 20 patients in each group. Both the groups were comparable with respect to age, gender, co-morbidities, body mass index (BMI), and degree of burns. Wound healing parameters like necrotic tissue score of six [40% vs. 50%; p = 0.024] and granulation tissue score of four [85% vs. 65%; p= 0.06] were significant in the heparin group compared to the control group. However, the difference was not statistically significant. The mean length of hospitalization between the two groups [10.5 days vs. 12.6 days; p = 0.74] were not statistically significant. Similarly, there was no statistically significant difference between the two groups with respect to the VAS pain score on the seventh dressing day [6.9 vs. 7.3; p= 0.321]. Conclusion In comparison to saline irrigation, heparin irrigation would result in better wound healing in superficial first and second-degree burns. The length of hospital stay in days and VAS pain score on the seventh dressing day were not statistically significant between the two groups.
Requiem for a heavyweight – can anything more be learned from homing pigeons about the sensory and spatial-representational basis of avian navigation?

ABSTRACT The homing pigeon (Columba livia) has long served as a study species to exhaustively investigate the sensory and spatial (map)-representational mechanisms that guide avian navigation. However, several factors have contributed to recent questioning of whether homing pigeons are as valuable as they once were as a general model for the study of the sensory and map-like, spatial-representational mechanisms of avian navigation. These reservations include: the success of this research program in unveiling navigational mechanisms; the burgeoning of new tracking technologies making navigational experiments on long-distance migratory and other wild birds much more accessible; the almost complete loss of the historically dominant, large-scale pigeon loft/research facilities; and prohibitive university per diem costs as well as animal care and use restrictions. Nevertheless, I propose here that there remain good prospects for homing pigeon research that could still profoundly influence how one understands aspects of avian navigation beyond sensory mechanisms and spatial-representational strategies. Indeed, research into neural mechanisms and brain organization, social/personality influences and genetics of navigation all offer opportunities to take advantage of the rich spatial behavior repertoire and experimental convenience of homing pigeons. Importantly, research in these areas would not necessarily require the large number of birds typically used in the past to study the sensory guidance of navigation. For those of us who have had the opportunity to work with this remarkable animal, one research door may be closing, but a window into exciting future opportunities lies ajar. Summary: For decades, homing pigeons have served as the premier model for understanding the mechanisms of bird navigation. However, their value may be diminishing as the study of navigational mechanisms used by migratory and other wild birds becomes more accessible.
Attention and Language Ensemble for Scene Text Recognition with Convolutional Sequence Modeling

Recent dominant approaches for scene text recognition are mainly based on convolutional neural network (CNN) and recurrent neural network (RNN), where the CNN processes images and the RNN generates character sequences. Different from these methods, we propose an attention-based architecture1 which is completely based on CNNs. The distinctive characteristics of our method include: (1) the method follows encoder-decoder architecture, in which the encoder is a two-dimensional residual CNN and the decoder is a deep one-dimensional CNN. (2) An attention module that captures visual cues, and a language module that models linguistic rules are designed equally in the decoder. Therefore the attention and language can be viewed as an ensemble to boost predictions jointly. (3) Instead of using a single loss from language aspect, multiple losses from attention and language are accumulated for training the networks in an end-to-end way. We conduct experiments on standard datasets for scene text recognition, including Street View Text, IIIT5K and ICDAR datasets. The experimental results show our CNN-based method has achieved state-of-the-art performance on several benchmark datasets, even without the use of RNN.
Causal Dependencies for Future Interest Prediction on Twitter

The accurate prediction of users' future topics of interests on social networks can facilitate content recommendation and platform engagement. However, researchers have found that future interest prediction, especially on social networks such as Twitter, is quite challenging due to the rapid changes in community topics and evolution of user interactions. In this context, temporal collaborative filtering methods have already been used to perform user interest prediction, which benefit from similar user behavioral patterns over time to predict how a user's interests might evolve in the future. In this paper, we propose that instead of considering the whole user base within a collaborative filtering framework to predict user interests, it is possible to much more accurately predict such interests by only considering the behavioral patterns of the most influential users related to the user of interest. We model influence as a form of causal dependency between users. To this end, we employ the concept of Granger causality to identify causal dependencies. We show through extensive experimentation that the consideration of only one causally dependent user leads to much more accurate prediction of users' future interests in a host of measures including ranking and rating accuracy metrics.
The Dynamic Design Space During a Game Jam

Game jams have gained an increasingly important role in game development communities, and have attracted attention in academia as well. However, research on how game jam formats shapes and drives creativity and design processes is scarce, and needs further development in order to advance our understanding of unique types of design processes. To provide insight on the complex inner workings of game jams, this paper presents an autobiographical design case study demonstrating how design space theory may be used as a theoretical framework that supports the documentation and analysis of a game jam. The main contribution is detailed exemplars of events that, for this particular game jam, had significant influence on how the design space was transformed. Furthermore, we discuss several points of interest for future studies of the transformation of the design space during game jams.
Euthymia in Diabetes

Abstract Euthymia, or optimal mood, is an integral part of health. A diagnosis of diabetes poses multiple challenges to mental and emotional health and may lead to psychological and psychiatric dysfunction. Such conditions influence glycaemic control negatively and may act as barriers to achievement of desired biomedical outcomes. This article describes the concept of euthymia in diabetes and calls for euthymia to be accepted as a target, as well as a tool, in modern diabetes care.