Miracle-dz/UniFAR-FTUs huggingface dataset:
Rule-based Shield Synthesis for Partially Observable Monte Carlo Planning

Partially Observable Monte-Carlo Planning (POMCP) is a powerful online algorithm able to generate approximate policies for large Partially Observable Markov Decision Processes. The online nature of this method supports scalability by avoiding complete policy representation. The lack of an explicit representation however hinders policy interpretability and makes policy verification very complex. In this work, we propose two contributions. The first is a method for identifying unexpected actions selected by POMCP with respect to expert prior knowledge of the task. The second is a shielding approach that prevents POMCP from selecting unexpected actions. The first method is based on Maximum Satisfiability Modulo Theory (MAX-SMT). It inspects traces (i.e., sequences of belief-action-observation triplets) generated by POMCP to compute the parameters of logical formulas about policy properties defined by the expert. The second contribution is a module that uses online the logical formulas to identify anomalous actions selected by POMCP and substitutes those actions with actions that satisfy the logical formulas fulfilling expert knowledge. We evaluate our approach in two domains. Results show that the shielded POMCP outperforms the standard POMCP in a case study in which a wrong parameter of POMCP makes it select wrong actions from time to time.
Patient Commitment to Cardiac Rehabilitation: A Qualitative Study

Background: Commitment to Cardiac Rehabilitation (CR) is one of the essential strategies to reduce the long-term complications of cardiovascular disease. The attributes of patients' commitment have not been defined distinctly. Thus, the present study aimed to describe the attributes of commitment to CR from the participants' perspective. Materials and Methods: This qualitative study was carried out in Tehran from 2018 to 2019. Data were collected using semi-structured interviews with 30 participants, including 13 CR specialists, 13 patients, and four caregivers, through purposeful sampling. The analysis was performed through the conventional content analysis using the Elo and Kyngäs approach. Results: Commitment to CR has one theme titled the attitudinal-motivational aspect that consists of four categories including attitudinal-cognitive, attitudinal-behavioral, attitudinal-emotional, and motivational as the core features. The commitment to CR is devotion, internal desire, and voluntary obligation to initiate and continue CR cooperatively, all of which are accompanied by the purposeful initiation of the treatment plan. Conclusions: The patient's commitment to CR is an intrinsic interest in achieving health that stems from the acceptance of the disease and the need for treatment. Besides, the rehabilitation team facilitates purposeful interpersonal relationships between the patient and the treatment group. It provides the basis for the patient's active efforts to meet the challenges of the treatment process.
he Effectiveness of Acceptance and Commitment Therapy on Distress and Psychosomatic Symptoms in Patients with type D personality and Gastrointestinal Dysfunction

Background: Anxiety disorders and psychological manifestations play a significant role in the incidence of psychosomatic disorders. Moreover, Personality traits are one of the psychological constructs associated with psychosomatic symptoms. Objective: This study aimed to determine the effectiveness of acceptance and commitment therapy on distress and psychosomatic symptoms in patients with gastrointestinal dysfunction with type D personality.Methods: The present study was a semi-experimental pre-test, post-test design with a control group and follow-up. The statistical population in this study was all patients with functional gastrointestinal disorders (FGID) who were referred to behavioral sciences research center in Isfahan in 2019, 30 patients were selected by targeted sampling method (patients with gastrointestinal dysfunction, except gastrointestinal cancer patients, who had a high de-personality score). Data were obtained using the D-14 personality type scale, ROME III questionnaire, psychological distress, and stress-anxiety-depression disorders (DASS-21). Data analysis was performed using repeated measure analysis of variance by spss.22. Results: The results showed that acceptance and commitment therapy was effective in decreasing distress (p <0.001) and psychosomatic symptoms (p <0.001) in patients with gastrointestinal dysfunction with type D personality. Conclusion: It can be concluded that acceptance and commitment therapy effectively distress and psychosomatic symptoms of patients with gastrointestinal dysfunction with type D personality and improve psychological problems in patients with gastrointestinal dysfunction.
Innovation Processes in Latin American Firms: A Dynamic Capability approach

The aim of this paper is to explore the microfoundations of dynamic capabilities in Latin American firms. In particular, we analyze the sense and shape opportunities, seize opportunities, and maintain competitiveness through reconfiguring assets. Our results suggest that when firms manage their innovation processes based on sensing opportunities and reconfiguring their tangible and intangible assets, they are more likely to improve on four innovation-related outcomes: development of new products and services, profitability, market share, and diversification.
Fast and versatile fluid-solid coupling for turbulent flow simulation

The intricate motions and complex vortical structures generated by the interaction between fluids and solids are visually fascinating. However, reproducing such a two-way coupling between thin objects and turbulent fluids numerically is notoriously challenging and computationally costly: existing approaches such as cut-cell or immersed-boundary methods have difficulty achieving physical accuracy, or even visual plausibility, of simulations involving fast-evolving flows with immersed objects of arbitrary shapes. In this paper, we propose an efficient and versatile approach for simulating two-way fluid-solid coupling within the kinetic (lattice-Boltzmann) fluid simulation framework, valid for both laminar and highly turbulent flows, and for both thick and thin objects. We introduce a novel hybrid approach to fluid-solid coupling which systematically involves a mesoscopic double-sided bounce-back scheme followed by a cut-cell velocity correction for a more robust and plausible treatment of turbulent flows near moving (thin) solids, preventing flow penetration and reducing boundary artifacts significantly. Coupled with an efficient approximation to simplify geometric computations, the whole boundary treatment method preserves the inherent massively parallel computational nature of the kinetic method. Moreover, we propose simple GPU optimizations of the core LBM algorithm which achieve an even higher computational efficiency than the state-of-the-art kinetic fluid solvers in graphics. We demonstrate the accuracy and efficacy of our two-way coupling through various challenging simulations involving a variety of rigid body solids and fluids at both high and low Reynolds numbers. Finally, comparisons to existing methods on benchmark data and real experiments further highlight the superiority of our method.
A review of the use of machine learning techniques by social media enterprises

In this review, the current status of research on machine learning techniques by social enterprises was explored. First the popularity of social media, the type of big data generated by them, how they are potentially and actually are used were outlined. The general concept of machine learning, components, methods and its application were discussed. On this background, specific methods and stages used in machine analytics of social media were reviewed with explanatory diagrams reproduced from the works of various authors. Bayesian Network and Support Vector Machine are most commonly used methods due to their advantages over other methods. The methods are used mostly for opinion mining, sentiment analysis and trend analysis. Social network analysis and business management are the most frequent applications, although it has been applied in many other fields also. Many new methods and modifications of current methods are being developed almost continuously to solve the problems in current methods. There are also limitations in current machine learning techniques. Samples drawn from big data may not always represent of the population. The gigantic size of data, with low value intensity, spread over several sources and their dynamic nature can cause certain biases. Large computing capacities and sophisticated methods of sampling, extraction and analysis are required to handle big data. Accuracy and objectivity of social media data are not always assured and the problem multiplies with use of diverse data sources. Access and ethical issues may arise. Heterogeneity, noise accumulation, spurious correlations and incidental endogeneity are other problems.
SEARCH FOR IDENTITY IN POST-WAR LEBANON: ARAB VS PHOENICIAN By Ibrahim A. Ghalioum, B.A. A Project Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Arts

This study uses textual analysis and network mapping in order to understand the rhetoric surrounding Phoenicianism in modern day Lebanon, using 1,336 data points from a political discussion forum. The ability of rhetoric grounded in science to persuade others of genetically essentialist views is examined, as well as the ability of social constructionism to naturally resist such rhetoric. We identify common themes found in our data set, the use of science based ethos in Phoenicianist rhetoric, and the growth (or lack thereof) of the Phoenicianist network in order to answer this question. Our research indicates that science based rhetoric and science based proofs do not lead to the growth of a network through the persuasion of others. This also presents us with some interesting opportunities for future research, such as the reasons why Phoenicianism failed to create long lasting identity change in Lebanon. A study on the various environmental factors that resulted in this instance of failed rhetoric could shine a light on the importance of demographics when it comes to successfully creating social movements.
Enterprise-scale conversational agents with knowledge graphs, entity reﬁnement and dynamic conversation ﬂows

A key barrier to the enterprise wide scaling of conversational virtual agents, beyond the signiﬁcant challenges posed by natural language understanding, are that the marginal development and maintenance costs of additional content areas is high. Here we describe an approach for development of virtual agents that scales. Our approach dynamically generates conversational ﬂows from a knowledge graph in a way such that our conversational model can be interpreted as an instance of a (dynamic) ﬁnite state machine. Importantly, our design supports a synergistic collaboration between domain experts and IT professionals using each group’s core competencies. IT is responsible for designing the schema of the knowledge graph and implementation of certain key routines while the domain experts use their expertise to populate the knowledge graph. We have implemented our approach at an American insurance company using it to deploy an internally-facing question-answering virtual agent. A short video overview of our system is available at https://youtu.be/12CsG_HAMhM
Marker-Based Mapping and Localization for Autonomous Valet Parking

—Autonomous valet parking (AVP) is one of the most important research topics of autonomous driving in low-speed scenes, with accurate mapping and localization being its key technologies. The traditional visual-based method, due to the change of illumination and appearance of the scene, easily causes localization failure in long-term applications. In order to solve this problem, we introduce visual ﬁducial markers as artiﬁcial landmarks for robust mapping and localization in parking lots. Firstly, the absolute scale information is acquired from ﬁducial markers, and a robust and accurate monocular mapping method is proposed by fusing wheel odometry. Secondly, on the basis of the map of ﬁducial markers that are sparsely placed in the parking lot, we propose a robust and efﬁcient ﬁltering-based localization method, which realizes accurate real-time localization of vehicles in parking lot. Compared with the traditional visual localization methods, we adopt artiﬁcial landmarks, which have strong stability and robustness to illumination and viewpoint changes. Meanwhile, because the ﬁducial markers can be selectively placed on the columns and walls of the parking lot, it is not easy to be occluded compared to the ground information, ensuring the reliability of the system. We have veriﬁed the effectiveness of our methods in real scenes. The experiment results show that the average localization error is about 0.3 m in a typical autonomous parking operation at a speed of 10km/h.
S-D Logic and the Open Innovation Paradigm: Marketing for un-embedded technologies

Purpose During the last decade, firms have been modifying their innovation management processes to generate, implement and exploit new technological knowledge. A gradual shift from a closed to an open model of innovation has been the recurring pattern of this change. Following the new open innovation paradigm, firms have to revise their overall strategic orientation and to adapt their managerial procedures accordingly. We state that the perspective suggested by the New Service-Dominant (S-D) Logic can offer a useful guideline to firms in the implementation of an Open Innovation (OI) model. Design, Methodology, Approach We analyze the OI paradigm through the lenses of S-D Logic by emphasizing aspects that are common to the two perspectives, like the customers’ participation in value creation, the complex networks of interaction among actors, and the difference between value proposition and value actualization. Findings This paper presents three main contributions. First, by means of the S-D Logic mindset, we characterize the bases of the OI paradigm. Second, for each of the ten foundational premises that depict the S-D Logic, we provide instantiations arising from firms that have implicitly adopted the OI paradigm. And finally, we move a step forward and discuss how suggestions provided by the S-D Logic can be put in practice within the context of the OI model. Originality This study integrates views from two different areas of knowledge (marketing and innovation) and especially from two new relevant perspectives of thought that allows for a better managerial response to the current trends of the global economy.
Inferring high-resolution traffic accident risk maps based on satellite imagery and GPS trajectories

Traffic accidents cost about 3% of the world’s GDP and are the leading cause of death in children and young adults. Accident risk maps are useful tools to monitor and mitigate accident risk. We present a technique to generate high-resolution (5 meters) accident risk maps. At this high resolution, accidents are sparse and risk estimation is limited by bias-variance trade-off. Prior accident risk maps either estimate low-resolution maps that are of low utility (high bias), or they use frequency-based estimation techniques that inaccurately predict where accidents actually happen (high variance). To improve this trade-off, we use an end-to-end deep architecture that can input satellite imagery, GPS trajectories, road maps and the history of accidents. Our evaluation on four metropolitan areas in the US with a total area of 7,488 km2 shows that our technique outperform prior work in terms of resolution and accuracy.
OP-SCAN120216 358..366

Voters tend to misattribute issue positions to political candidates that are consistent with their partisan affiliation, even though these candidates have never explicitly stated or endorsed such stances. The prevailing explanation in political science is that voters misattribute candidates issue positions because they use their political knowledge to make educated but incorrect guesses. We suggest that voter errors can also stem from a different source: false memories. The current study examined event-related potential (ERP) responses to misattributed and accurately remembered candidate issue information. We report here that ERP responses to misattributed information can elicit memory signals similar to that of correctly remembered old information a pattern consistent with a false memory rather than educated guessing interpretation of these misattributions. These results suggest that some types of voter misinformation about candidates may be harder to correct than previously thought.
The role of adverse childhood experiences, self control and Dark Triad in the development of criminal behaviour. Correlative and differential aspects

This research consists of two studies that aimed primarily on identifying the links between adverse childhood experiences, the level of self-control, the „dark” personality traits, and also their relationship with criminal behavior. In the first study we aimed to establish a relationship between all the variables. A sample of 232 psychology students participated in the research. They reported that they experienced a number of emotional adverse events in their childhood, and these events were positively associated with low levels of self-control and dark personality traits. The second study aimed to replicate the results obtained in the first study. Furthermore, we want to see the differences related to these variables between inmates and psychology students. In this study participated 87 inmates and 87 psychology students. The results showed that inmates predominantly experienced adverse childhood events of a physical nature, while students predominantly experienced adverse emotional events. It has been shown that psychopathy has been positively associated with offending behavior and the high frequency of adverse childhood events. The low level of self-control has been positively associated with adverse childhood events and negative personality traits. Further studies are needed in order to establish students' sensitivity thresholds in relation to adverse childhood events and to clarify the impact these events have had on students.
The Role of Plant-Associated Bacteria, Fungi, and Viruses in Drought Stress Mitigation

Drought stress is an alarming constraint to plant growth, development, and productivity worldwide. However, plant-associated bacteria, fungi, and viruses can enhance stress resistance and cope with the negative impacts of drought through the induction of various mechanisms, which involve plant biochemical and physiological changes. These mechanisms include osmotic adjustment, antioxidant enzyme enhancement, modification in phytohormonal levels, biofilm production, increased water and nutrient uptake as well as increased gas exchange and water use efficiency. Production of microbial volatile organic compounds (mVOCs) and induction of stress-responsive genes by microbes also play a crucial role in the acquisition of drought tolerance. This review offers a unique exploration of the role of plant-associated microorganisms—plant growth promoting rhizobacteria and mycorrhizae, viruses, and their interactions—in the plant microbiome (or phytobiome) as a whole and their modes of action that mitigate plant drought stress.
What to expect from alternative management strategies to conserve seabirds? Hints from a dynamic modelling framework applied to an endangered population

The worldwide decline of seabird populations due to the combined effects of global and regional changes is creating immense challenges for managers and conservationists. Predicting population responses to proposed management strategies could provide the most effective tools to prevent, halt and reverse ongoing declines. System dynamic modelling frameworks are considered particularly relevant to interrelate biological, ecological and environmental characteristics and to predict population trends. A system dynamics model was designed, compiling diverse information concerning a relict population of the European Shag located in western Iberia, to outline the most effective management options for its conservation. The simulations demonstrate that mortality caused by invasive animals and bycatch mortality were the main reasons for the current population decline. Without management interventions, a decrease of 8% was projected for the next decade, which could be mitigated by specific conservation actions. The results show the usefulness of dynamic modelling frameworks to understand local cause‐effect relationships and species responses to ecosystem management under changing environmental conditions. We highlight that the framework proposed, after specific parameterization, could be easily adaptable to other species within similar socio‐ecological systems.
Implications and Recommendations for Equivalence Testing in Measures of Movement Behaviors: A Scoping Review

Equivalence testing may provide complementary information to more frequently used statistical procedures because it determines whether physical behavior outcomes are statistically equivalent to criterion measures. A caveat of this procedure is the predetermined selection of upper and lower bounds of acceptable error around a specified zone of equivalence. With no clear guidelines available to assist researchers, these equivalence zones are arbitrarily selected. A scoping review of articles implementing equivalence testing was performed to determine the validity of physical behavior outcomes; the aim was to characterize how this procedure has been implemented and to provide recommendations. A literature search from five databases initially identified potentially 1,153 articles which resulted in the acceptance of 19 studies (20 arms) conducted in children/youth and 40 in adults (49 arms). Most studies were conducted in free-living conditions (children/youth = 13 arms; adults = 22 arms) and employed a ±10% equivalence zone. However, equivalence zones ranged from ±3% to ±25% with only a subset using absolute thresholds (e.g., ±1,000 steps/day). If these equivalence zones were increased or decreased by ±5%, 75% (15/20, children/youth) and 71% (35/49, adults), they would have exhibited opposing equivalence test outcomes (i.e., equivalent to nonequivalent or vice versa). This scoping review identifies the heterogeneous usage of equivalence testing in studies examining the accuracy of (in)activity measures. In the absence of evidence-based standardized equivalence criteria, presenting the percentage required to achieve statistical equivalence or using absolute thresholds as a proportion of the SD may be a better practice than arbitrarily selecting zones a priori.