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We determine the asymptotic number of regular multipartite hypergraphs, also known as multidimensional binary contingency tables, for all values of the parameters.

In this paper, we tackle the challenging problem of delayed rewards in reinforcement learning (RL). While Proximal Policy Optimization (PPO) has emerged as a leading Policy Gradient method, its performance can degrade under delayed rewards. We introduce two key enhancements to PPO: a hybrid policy architecture that combines an offline policy (trained on expert demonstrations) with an online PPO policy, and a reward shaping mechanism using Time Window Temporal Logic (TWTL). The hybrid architecture leverages offline data throughout training while maintaining PPO's theoretical guarantees. Building on the monotonic improvement framework of Trust Region Policy Optimization (TRPO), we prove that our approach ensures improvement over both the offline policy and previous iterations, with a bounded performance gap of $(2\varsigma\gamma\alpha^2)/(1-\gamma)^2$, where $\alpha$ is the mixing parameter, $\gamma$ is the discount factor, and $\varsigma$ bounds the expected advantage. Additionally, we prove that our TWTL-based reward shaping preserves the optimal policy of the original problem. TWTL enables formal translation of temporal objectives into immediate feedback signals that guide learning. We demonstrate the effectiveness of our approach through extensive experiments on an inverted pendulum and a lunar lander environments, showing improvements in both learning speed and final performance compared to standard PPO and offline-only approaches.

A dihypergraph consists of a set of vertices and a set of directed hyperedges, where each directed hyperedge is partitioned into a head and a tail. Directed hypergraphs are useful in many applications, including the study of chemical reactions or relational databases. We provide asymptotic formulae for the number of directed hypergraphs with given in-degree sequence, out-degree sequence, and the head and tail sizes of all directed hyperedges specified. Our formulae hold when none of the following parameters are too large: the maximum out-degree, the maximum in-degree, the maximum head size and the maximum tail size. If one of the four parameter sequences is near-regular, for example if each directed hyperedge has a tail of roughly the same size, then our formula is obtained using a simple argument based on existing asymptotic enumeration results for sparse bipartite graphs with given degree sequences. We also establish the same formula without the regularity assumption but with a larger relative error term, using a martingale argument., Comment: 29 pages

High proved the following theorem. If the intersections of any two congruent copies of a plane convex body are centrally symmetric, then this body is a circle. In our paper we extend the theorem of High to the sphere and the hyperbolic plane, and partly to spaces of constant curvature. We also investigate the dual question about the convex hull of the unions, rather than the intersections. Let us have in $H^2$ proper closed convex subsets $K,L$ with interior points, such that the numbers of the connected components of the boundaries of $K$ and $L$ are finite. We exactly describe all pairs of such subsets $K,L$, whose any congruent copies have an intersection with axial symmetry; there are nine cases. (The cases of $S^2$ and ${\Bbb{R}}^2$ were described in Part I, i.e., \cite{5}.) Let us have in $S^d$, ${\Bbb{R}}^d$ or $H^d$ proper closed convex $C^2_+$ subsets $K,L$ with interior points, such that all sufficiently small intersections of their congruent copies are symmetric w.r.t.\ a particular hyperplane. Then the boundary components of both $K$ and $L$ are congruent, and each of them is a sphere, a parasphere or a hypersphere. Let us have a pair of convex bodies in $S^d$, ${\Bbb{R}}^d$ or $H^d$, which have at any boundary points supporting spheres (for $S^d$ of radius less than $\pi /2$). If the convex hull of the union of any congruent copies of these bodies is centrally symmetric, then our bodies are congruent balls (for $S^d$ of radius less than $\pi /2$). An analogous statement holds for symmetry w.r.t.\ a particular hyperplane. For $d=2$, suppose the existence of the above supporting circles (for $S^2$ of radius less than $\pi /2$), and, for $S^2$, smoothness of $K$ and $L$. If we suppose axial symmetry of all the above convex hulls, then our bodies are (incongruent) circles (for $S^2$ of radii less than $\pi /2$)., Comment: 48 pages. arXiv admin note: text overlap with arXiv:1601.04494

Let us have in S^2, R^2 or H^2 a pair of convex bodies, for S^2 different from S^2, such that the intersections of any congruent copies of them are centrally symmetric. Then our bodies are congruent circles. If the intersections of any congruent copies of them are axially symmetric, then our bodies are circles. Let us have in S^2, R^2 or H^2 proper closed convex subsets K,L with interior points, such that the numbers of the connected components of the boundaries of K and L are finite. If the intersections of any congruent copies of K and L are centrally symmetric, then K and L are congruent circles, or, for R^2, parallel strips. We describe all pairs of such subsets K,L, whose any congruent copies have an intersection with axial symmetry. For S^2, R^2 and H^2 there are 1, 5 and 9 cases, resp. Let us have in S^d, R^d or H^d proper closed convex C^2_+ subsets K,L with interior points, such that all sufficiently small intersections of their congruent copies are symmetric w.r.t. a particular hyperplane. Then the boundary components of both K and L are congruent, and each of them is a sphere, a parasphere or a hypersphere. Let us have a pair of convex bodies in S^d, R^d or H^d, which have at any boundary points supporting spheres, for S^d of radius less than \pi/2. If the convex hull of the union of any congruent copies of these bodies is centrally symmetric, then our bodies are congruent balls, for S^d of radius less than \pi/2. An analogous statement holds for symmetry w.r.t. a particular hyperplane. For d=2 suppose the existence of the above supporting circles, for S^2 of radius less than \pi/2, and for S^2 smoothness of K and L. If we suppose axial symmetry of all the above convex hulls, then our bodies are circles, for S^2 of radii less than \pi/2., Comment: 42 TEX pages. Misprints corrected. arXiv admin note: text overlap with arXiv:1601.04494

Observed evolution of the total mass distribution with redshift is crucial to testing galaxy evolution theories. To measure the total mass distribution, strong gravitational lenses complement the resolved dynamical observations currently limited to $z \lesssim 0.5$. Here we present the lens models for a pilot sample of seven galaxy-scale lenses from the ASTRO3D Galaxy Evolution with Lenses (AGEL) survey. The AGEL lenses, modeled using HST/WFC3-F140W images with Gravitational Lens Efficient Explorer (GLEE) software, have deflector redshifts between $0.3 < z_{\rm defl} < 0.9$. Assuming a power-law density profile with slope $\gamma$, we measure the total density profile for the deflector galaxies via lens modeling. We also measure the stellar velocity dispersions ($\sigma_{\rm obs}$) for four lenses and obtain $\sigma_{\rm obs}$ from SDSS-BOSS for the remaining lenses to test our lens models by comparing observed and model-predicted velocity dispersions. For the seven AGEL lenses, we measure an average density profile slope of $-1.95 \pm 0.09$ and a $\gamma$--$z$ relation that does not evolve with redshift at $z<1$. Although our result is consistent with some observations and simulations, it differs from other studies at $z<1$ that suggest the $\gamma$--$z$ relation evolves with redshift. The apparent conflicts among observations and simulations may be due to a combination of 1) systematics in the lensing and dynamical modeling; 2) challenges in comparing observations with simulations; and 3) assuming a simple power-law for the total mass distribution. By providing more lenses at $z_{\rm defl} > 0.5$, the AGEL survey will provide stronger constraints on whether the mass profiles evolve with redshift as predicted by current theoretical models., Comment: Accepted for publication in the Astrophysical Journal (ApJ) 24 Pages, 8 Figures, 3 Tables

We investigate the behaviour of $r$-neighbourhood bootstrap percolation on the binomial $k$-uniform random hypergraph $H_k(n,p)$ for given integers $k\geq 2$ and $r\geq 2$. In $r$-neighbourhood bootstrap percolation, infection spreads through the hypergraph, starting from a set of initially infected vertices, and in each subsequent step of the process every vertex with at least $r$ infected neighbours becomes infected. For our analysis the set of initially infected vertices is chosen uniformly at random from all sets of given size. In the regime $n^{-1}\ll n^{k-2}p \ll n^{-1/r}$ we establish a threshold such that if the number of initially infected vertices remains below the threshold, then with high probability only a few additional vertices become infected, while if the number of initially infected vertices exceeds the threshold then with high probability almost every vertex becomes infected. In fact we show that the probability of failure decreases exponentially., Comment: 32 pages 2 figures

We consider a synchronous process of particles moving on the vertices of a graph $G$, introduced by Cooper, McDowell, Radzik, Rivera and Shiraga (2018). Initially, $M$ particles are placed on a vertex of $G$. In subsequent time steps, all particles that are located on a vertex inhabited by at least two particles jump independently to a neighbour chosen uniformly at random. The process ends at the first step when no vertex is inhabited by more than one particle; we call this (random) time step the dispersion time. In this work we study the case where $G$ is the complete graph on $n$ vertices and the number of particles is $M=n/2+\alpha n^{1/2} + o(n^{1/2})$, $\alpha\in \mathbb{R}$. This choice of $M$ corresponds to the critical window of the process, with respect to the dispersion time. We show that the dispersion time, if rescaled by $n^{-1/2}$, converges in $p$-th mean, as $n\rightarrow \infty$ and for any $p \in \mathbb{R}$, to a continuous and almost surely positive random variable $T_\alpha$. We find that $T_\alpha$ is the absorption time of a standard logistic branching process, thoroughly investigated by Lambert (2005), and we determine its expectation. In particular, in the middle of the critical window we show that $\mathbb{E}[T_0] = \pi^{3/2}/\sqrt{7}$, and furthermore we formulate explicit asymptotics when $|\alpha|$ gets large that quantify the transition into and out of the critical window. We also study the (random) total number of jumps that are performed by the particles until the dispersion time is reached. In particular, we prove that it centers around $\frac{2}{7}n\ln n$ and that it has variations linear in $n$, whose distribution we can describe explicitly., Comment: 37 pages 2 figures

We consider the open problem concerning the possible lack of concentration of the degree distribution in preferential attachment graphs with random initial degree, when its distribution is characterized by extremely heavy tails of power-law type. We show that the addition of such a large number of edges causes a significant upset of the degree distribution, leading to its non-concentration. Furthermore, we show that the smallest value of the exponent for which the degree distribution exhibits concentration is 2.

Control barrier functions (CBF) have become popular as a safety filter to guarantee the safety of nonlinear dynamical systems for arbitrary inputs. However, it is difficult to construct functions that satisfy the CBF constraints for high relative degree systems with input constraints. To address these challenges, recent work has explored learning CBFs using neural networks via neural CBF (NCBF). However, such methods face difficulties when scaling to higher dimensional systems under input constraints. In this work, we first identify challenges that NCBFs face during training. Next, to address these challenges, we propose policy neural CBF (PNCBF), a method of constructing CBFs by learning the value function of a nominal policy, and show that the value function of the maximum-over-time cost is a CBF. We demonstrate the effectiveness of our method in simulation on a variety of systems ranging from toy linear systems to an F-16 jet with a 16-dimensional state space. Finally, we validate our approach on a two-agent quadcopter system on hardware under tight input constraints., Comment: Submitted to ICRA 2024. Project page can be found at https://mit-realm.github.io/pncbf

Temporal logic is an important tool for specifying complex behaviors of systems. It can be used to define properties for verification and monitoring, as well as goals for synthesis tools, allowing users to specify rich missions and tasks. Some of the most popular temporal logics include Metric Temporal Logic (MTL), Signal Temporal Logic (STL), and weighted STL (wSTL), which also allow the definition of timing constraints. In this work, we introduce PyTeLo, a modular and versatile Python-based software that facilitates working with temporal logic languages, specifically MTL, STL, and wSTL. Applying PyTeLo requires only a string representation of the temporal logic specification and, optionally, the dynamics of the system of interest. Next, PyTeLo reads the specification using an ANTLR-generated parser and generates an Abstract Syntax Tree (AST) that captures the structure of the formula. For synthesis, the AST serves to recursively encode the specification into a Mixed Integer Linear Program (MILP) that is solved using a commercial solver such as Gurobi. We describe the architecture and capabilities of PyTeLo and provide example applications highlighting its adaptability and extensibility for various research problems.

Compositionality is a critical aspect of scalable system design. Reinforcement learning (RL) has recently shown substantial success in task learning, but has only recently begun to truly leverage composition. In this paper, we focus on Boolean composition of learned tasks as opposed to functional or sequential composition. Existing Boolean composition for RL focuses on reaching a satisfying absorbing state in environments with discrete action spaces, but does not support composable safety (i.e., avoidance) constraints. We advance the state of the art in Boolean composition of learned tasks with three contributions: i) introduce two distinct notions of safety in this framework; ii) show how to enforce either safety semantics, prove correctness (under some assumptions), and analyze the trade-offs between the two safety notions; and iii) extend Boolean composition from discrete action spaces to continuous action spaces. We demonstrate these techniques using modified versions of value iteration in a grid world, Deep Q-Network (DQN) in a grid world with image observations, and Twin Delayed DDPG (TD3) in a continuous-observation and continuous-action Bullet physics environment. We believe that these contributions advance the theory of safe reinforcement learning by allowing zero-shot composition of policies satisfying safety properties.

The nature of interaction within Interactive Digital Narrative (IDN) is inherently complex. This is due, in part, to the wide range of potential interaction modes through which IDNs can be conceptualised, produced and deployed and the complex dynamics this might entail. The purpose of this whitepaper is to provide IDN practitioners with the essential knowledge on the nature of interaction in IDNs and allow them to make informed design decisions that lead to the incorporation of complexity thinking throughout the design pipeline, the implementation of the work, and the ways its audience perceives it. This white paper is concerned with the complexities of authoring, delivering and processing dynamic interactive contents from the perspectives of both creators and audiences. This white paper is part of a series of publications by the INDCOR COST Action 18230 (Interactive Narrative Design for Complexity Representations), which all clarify how IDNs representing complexity can be understood and applied (INDCOR WP 0 - 5, 2023)., Comment: 17 pages, 1 figure

The exploration of entrepreneurship has become a priority for scientific research in recent years. Understanding this phenomenon is particularly important for the transformation of entrepreneurship into action, which is a key factor in early-stage entrepreneurial activity. This gains particular relevance in the university environment, where, in addition to the conventional teaching and research functions, the entrepreneurial university operation based on open innovation, as well as the enhancement of entrepreneurial attitudes of researchers and students, are receiving increased attention. This study is based on a survey conducted among students attending a Hungarian university of applied science in Western Transdanubia Region who have demonstrated their existing entrepreneurial commitment by joining a national startup training and incubation programme. The main research question of the study is to what extent student entrepreneurship intention is influenced by the environment of the entrepreneurial university ecosystem and the support services available at the university. A further question is whether these factors are able to mitigate the negative effects of internal cognitive and external barriers by enhancing entrepreneurial attitudes and perceived behavioural control. The relatively large number of students involved in the programme allows the data to be analysed using SEM modelling. The results indicate a strong covariance between the perceived university support and environment among students. Another observation is the distinct effect of these institutional factors on perceived behavioural control of students.

We consider a synchronous process of particles moving on the vertices of a graph $G$, introduced by Cooper, McDowell, Radzik, Rivera and Shiraga (2018). Initially, $M$ particles are placed on a vertex of $G$. At the beginning of each time step, for every vertex inhabited by at least two particles, each of these particles moves independently to a neighbour chosen uniformly at random. The process ends at the first step when no vertex is inhabited by more than one particle. Cooper et al. showed that when the underlying graph is the complete graph on~$n$ vertices, then there is a phase transition when the number of particles $M = n/2$. They showed that if $M<(1-\varepsilon)n/2$ for some fixed $\varepsilon>0$, then the process finishes in a logarithmic number of steps, while if $M>(1+\varepsilon)n/2$, an exponential number of steps are required with high probability. Here we provide a thorough asymptotic analysis of the dispersion time around criticality, where $\varepsilon = o(1)$, and describe the transition from logarithmic to exponential time. As a consequence of our results we establish, for example, that the dispersion time is in probability and in expectation in $\Theta(n^{1/2})$ when $|\varepsilon| = O(n^{-1/2})$, and provide qualitative bounds for its tail behavior., Comment: An extended abstract containing some results of this work appears in the proceedings of EUROCOMB '23

Much of the recent work developing formal methods techniques to specify or learn the behavior of autonomous systems is predicated on a belief that formal specifications are interpretable and useful for humans when checking systems. Though frequently asserted, this assumption is rarely tested. We performed a human experiment (N = 62) with a mix of people who were and were not familiar with formal methods beforehand, asking them to validate whether a set of signal temporal logic (STL) constraints would keep an agent out of harm and allow it to complete a task in a gridworld capture-the-flag setting. Validation accuracy was $45\% \pm 20\%$ (mean $\pm$ standard deviation). The ground-truth validity of a specification, subjects' familiarity with formal methods, and subjects' level of education were found to be significant factors in determining validation correctness. Participants exhibited an affirmation bias, causing significantly increased accuracy on valid specifications, but significantly decreased accuracy on invalid specifications. Additionally, participants, particularly those familiar with formal methods, tended to be overconfident in their answers, and be similarly confident regardless of actual correctness. Our data do not support the belief that formal specifications are inherently human-interpretable to a meaningful degree for system validation. We recommend ergonomic improvements to data presentation and validation training, which should be tested before claims of interpretability make their way back into the formal methods literature.

We present Self-Driven Strategy Learning ($\textit{sdsl}$), a lightweight online learning methodology for automated reasoning tasks that involve solving a set of related problems. $\textit{sdsl}$ does not require offline training, but instead automatically constructs a dataset while solving earlier problems. It fits a machine learning model to this data which is then used to adjust the solving strategy for later problems. We formally define the approach as a set of abstract transition rules. We describe a concrete instance of the sdsl calculus which uses conditional sampling for generating data and random forests as the underlying machine learning model. We implement the approach on top of the Kissat solver and show that the combination of Kissat+$\textit{sdsl}$ certifies larger bounds and finds more counter-examples than other state-of-the-art bounded model checking approaches on benchmarks obtained from the latest Hardware Model Checking Competition., Comment: Condensed version published at FMCAD'23

In this paper, we present a framework for online parameter estimation and uncertainty quantification in the context of adaptive safety-critical control. The key insight enabling our approach is that the parameter estimate generated by the continuous-time recursive least squares (RLS) algorithm at any point in time is an affine transformation of the initial parameter estimate. This property allows for parameterizing such estimates using objects that are closed under affine transformation, such as zonotopes, and enables the efficient propagation of such set-based estimates as time progresses. We illustrate how such an approach facilitates the synthesis of safety-critical controllers for systems with parametric uncertainty and additive disturbances using control barrier functions, and demonstrate the utility of our approach through illustrative examples., Comment: To appear at the 2024 American Control Conference

This paper explores continuous-time control synthesis for target-driven navigation to satisfy complex high-level tasks expressed as linear temporal logic (LTL). We propose a model-free framework using deep reinforcement learning (DRL) where the underlying dynamic system is unknown (an opaque box). Unlike prior work, this paper considers scenarios where the given LTL specification might be infeasible and therefore cannot be accomplished globally. Instead of modifying the given LTL formula, we provide a general DRL-based approach to satisfy it with minimal violation. To do this, we transform a previously multi-objective DRL problem, which requires simultaneous automata satisfaction and minimum violation cost, into a single objective. By guiding the DRL agent with a sampling-based path planning algorithm for the potentially infeasible LTL task, the proposed approach mitigates the myopic tendencies of DRL, which are often an issue when learning general LTL tasks that can have long or infinite horizons. This is achieved by decomposing an infeasible LTL formula into several reach-avoid sub-tasks with shorter horizons, which can be trained in a modular DRL architecture. Furthermore, we overcome the challenge of the exploration process for DRL in complex and cluttered environments by using path planners to design rewards that are dense in the configuration space. The benefits of the presented approach are demonstrated through testing on various complex nonlinear systems and compared with state-of-the-art baselines. The Video demonstration can be found here:https://youtu.be/jBhx6Nv224E.

There are at present ${\cal O}(100)$ gravitational-wave candidates from compact binary mergers reported in the astronomical literature. As detector sensitivities are improved, the catalog will swell in size: first to ${\cal O}(1000)$ events in the A+ era and then to ${\cal O}(10^6)$ events in the era of third-generation observatories like Cosmic Explorer and the Einstein Telescope. Each event is analyzed using Bayesian inference to determine properties of the source including component masses, spins, tidal parameters, and the distance to the source. These inference products are the fodder for some of the most exciting gravitational-wave science, enabling us to measure the expansion of the Universe with standard sirens, to characterise the neutron star equation of state, and to unveil how and where gravitational-wave sources are assembled. In order to maximize the science from the coming deluge of detections, we introduce GWCloud, a searchable repository for the creation and curation of gravitational-wave inference products. It is designed with five pillars in mind: uniformity of results, reproducibility of results, stability of results, access to the astronomical community, and efficient use of computing resources. We describe how to use GWCloud with examples, which readers can replicate using the companion code to this paper. We describe our long-term vision for GWCloud., Comment: 14 pages, 9 figures

The model shift of higher education in Hungary brought not only the deepening of university-industry relations and technology transfer processes, but also contribute the emerging role of universities in shaping regional innovation policy. This process provides a new framework for cooperation between actors in regional innovation ecosystems and raises the relationship between economic-governmental-academic systems to a new level. Active involvement of government, the predominance of state resources, and the strong innovation-organizing power of higher education institutions are similarities that characterize both the Hungarian and Chinese innovation systems. This paper attempts to gather Chinese good practices whose adaptation can contribute to successful public-university collaboration. In the light of the examined practices, the processes related to the university model shift implemented so far can be placed in a new context, which are presented through the example of the Sz\'echenyi Istv\'an University of Gy\H{o}r., Comment: in Chinese

The progress made by the entrepreneurial university, which is a newly emerging category in Hungarian higher education after its change of model, has not only deepened relations between universities and the industry and intensified the technology and knowledge transfer processes, but also increased the role of universities in shaping regional innovation policy. This transformation places co-operation between the actors of the regional innovation ecosystem and the relationships between the economic, governmental and academic systems into a new framework. The purpose of this paper is to describe the process of the change in the model through a specific example, and to outline the future possibilities of university involvement in the currently changing Hungarian innovation policy system.

The number, importance, and popularity of rankings measuring innovation performance and the strength and resources of ecosystems that provide its spatial framework are on an increasing trend globally. In addition to influencing the specific decisions taken by economic actors, these rankings significantly impact the development of innovation-related policies at regional, national, and international levels. The importance of startup ecosystems is proven by the growing scientific interest, which is demonstrated by the increasing number of related scientific articles. The concept of the startup ecosystem is a relatively new category, the application of which in everyday and scientific life has been gaining ground since the end of the 2000s. In parallel, of course, the demand for measurability and comparability has emerged among decision-makers and scholars. This demand is met by startup ecosystem rankings, which now measure and rank the performance of individual ecosystems on a continental and global scale. However, while the number of scientific publications examining rankings related to higher education, economic performance, or even innovation, can be measured in the order of thousands, scientific research has so far rarely or tangentially addressed the rankings of startup ecosystems. This study and the related research intend to fill this gap by presenting and analysing the characteristics of global rankings and identifying possible future research directions.

Let $\{p_1, \ldots , p_n \} \subset {\Bbb{R}}^2$ be a separated point set, i.e., any two points have a distance at least $1$. Let $k \ge 1$ be an integer, and $1 \le t_1 < \ldots < t_k$ be real numbers. Let $\delta > 0$. Suppose for all $1 \le \ell (1) \le \ell (2) < \ell (3) \le k$ that $|t_{\ell (3)} / (t_{\ell (1)} + t_{\ell (2)}) - 1| \ge \delta $. Then for $n \ge n_{k, \delta }$, the number of pairs $\{ p_i,p_j\} $, for which $d(p_i,p_j) \in [t_1, t_1 + 1] \cup \ldots \cup [t_k, t_k + 1] $, is at most $n^2/4 + C_{k,\delta }n$. This is sharp, up to the value of the constant $C_{k,\delta } > 0$., Comment: 9 pages

We introduce "entanglement", a novel metric to measure how synchronized communication between team members is. This measure calculates the Euclidean distance among team members' social network metrics timeseries. We validate the metric with four case studies. The first case study uses entanglement of 11 medical innovation teams to predict team performance and learning behavior. The second case looks at the e-mail communication of 113 senior executives of an international services firm, predicting employee turnover through lack of entanglement of an employee. The third case analyzes the individual employee performance of 81 managers. The fourth case study predicts performance of 13 customer-dedicated teams at a big international company by comparing entanglement in the e-mail interactions with satisfaction of their customers measured through Net Promoter Score (NPS). While we can only speculate about what is causing the entanglement effect, we find that it is a new and versatile indicator for the analysis of employees' communication, analyzing the hitherto underused temporal dimension of online social networks which could be used as a powerful predictor of employee and team performance, employee turnover, and customer satisfaction.

IRAS 20319+3958 in Cygnus X South is a rare example of a free-floating globule (mass ~240 Msun, length ~1.5 pc) with an internal HII region created by the stellar feedback of embedded intermediate-mass stars, in particular, one Herbig Be star. Here, we present a Herschel/HIFI CII 158 mu map of the whole globule and a large set of other FIR lines (mid-to high-J CO lines observed with Herschel/PACS and SPIRE, the OI 63 mu line and the CO 16-15 line observed with upGREAT on SOFIA), covering the globule head and partly a position in the tail. The CII map revealed that the whole globule is probably rotating. Highly collimated, high-velocity CII emission is detected close to the Herbig Be star. We performed a PDR analysis using the KOSMA-tau PDR code for one position in the head and one in the tail. The observed FIR lines in the head can be reproduced with a two-component model: an extended, non-clumpy outer PDR shell and a clumpy, dense, and thin inner PDR layer, representing the interface between the HII region cavity and the external PDR. The modelled internal UV field of ~2500 Go is similar to what we obtained from the Herschel FIR fluxes, but lower than what we estimated from the census of the embedded stars. External illumination from the ~30 pc distant Cyg OB2 cluster, producing an UV field of ~150-600 G0 as an upper limit, is responsible for most of the CII emission. For the tail, we modelled the emission with a non-clumpy component, exposed to a UV-field of around 140 Go., Comment: accepted by Astronomy & Astrophysics

The increasing complexity of modern configurable systems makes it critical to improve the level of automation in the process of system configuration. Such automation can also improve the agility of the development cycle, allowing for rapid and automated integration of decoupled workflows. In this paper, we present a new framework for automated configuration of systems representable as state machines. The framework leverages model checking and satisfiability modulo theories (SMT) and can be applied to any application domain representable using SMT formulas. Our approach can also be applied modularly, improving its scalability. Furthermore, we show how optimization can be used to produce configurations that are best according to some metric and also more likely to be understandable to humans. We showcase this framework and its flexibility by using it to configure a CGRA memory tile for various image processing applications.

We find an asymptotic enumeration formula for the number of simple $r$-uniform hypergraphs with a given degree sequence, when the number of edges is sufficiently large. The formula is given in terms of the solution of a system of equations. We give sufficient conditions on the degree sequence which guarantee existence of a solution to this system. Furthermore, we solve the system and give an explicit asymptotic formula when the degree sequence is close to regular. This allows us to establish several properties of the degree sequence of a random $r$-uniform hypergraph with a given number of edges. More specifically, we compare the degree sequence of a random $r$-uniform hypergraph with a given number edges to certain models involving sequences of binomial or hypergeometric random variables conditioned on their sum., Comment: To appear in Combinatorics, Probability and Computing

lazybvtoint is a new prototype SMT-solver, that will participate in the incremental and non-incremental tracks of the \qfbv logic.