Miracle-dz/UniFAR-FTUs huggingface dataset:
Low Obstacle Avoidance for Lower Limb Exoskeletons

Powered lower limb exoskeletons (LLEs) are innovative wearable robots that allow independent walking in people with severe gait impairments. Despite the recent advancements, the use of this promising technology is still restricted to clinical settings; uptake in real-life conditions as a device to promote user independence is still lacking due to the difficulty of controlling these devices in unstructured and complex environments. In this work, we propose a vision-assisted method for low obstacle avoidance to enhance the autonomy of LLEs. The exoskeleton collects information from the surroundings through a RGB-D camera to recognize and segment objects on the ground that might affect the walking pattern. Then, the method identifies suitable foothold positions. In addition, a novel iterative gait trajectory generator is proposed to automatically compute collision-free walking paths. We believe that re-thinking exoskeletons as semi-autonomous agents will represent not only the cornerstone to promote a more symbiotic human-exoskeleton interaction but may also pave the way for the use of this technology in the everyday life.
Analogical Reasoning, Generalization, and Rule Learning for Common Law Reasoning

Research in AI & Law has sought to model common-law case-based reasoning by creating analogies from cases, extracting and applying rules from cases, or both. This paper presents a new approach to extracting legal information from cases and several methods to apply it to new cases, including by analogy and by conversion to logical rules. It evaluates the approaches on a dataset of real-world cases and compares the results to off-the-shelf machine-learning techniques. We conclude that abstract legal information can be extracted from similar cases through analogical generalization, and that the extracted legal schemas can be used to reason about and solve other cases both by analogy and by rules.
CAMBRIDGE WORKING PAPERS IN ECONOMICS Status substitution and conspicuous consumption

This paper adapts ideas from social identity theory to set out a new framework for modelling conspicuous consumption. Notably, this approach can explain two stylised facts about conspicuous consumption that initially seem at odds with one another, and to date have required different families of models to explain each: (1) people consume more visible goods when their neighbours’ incomes rise, but (2) consume less visible goods when incomes of those with the same race in a wider geographic area rise. The first fact is typically explained by ‘Keeping up with the Joneses’ models, and the second by signalling models. Our model also explains related features of conspicuous consumption: that the rich are more sensitive to others’ incomes than the poor, and that the effect of income inequality on consumption differs qualitatively across groups. Importantly, it explains this fourth stylised fact without falling back on differences in preferences across groups, as required in other models. In addition, our model delivers new testable predictions regarding the role of network structure and income inequality for conspicuous consumption. Reference Details CWPE 2324 Published 14 March 2023
An Investigation into the Effects of Border Carbon Adjustments on the Canadian Economy

from the Bank’s Governing Council. This research may support or challenge prevailing policy orthodoxy. Therefore, the views expressed in this paper are solely those of the authors and may differ from official Bank of Canada views. No responsibility for them should be attributed to the Bank. DOI: https://doi.org/10.34989/swp-2023-27 | ISSN 1701-9397 ©2023 Bank of Canada Staff Working Paper/Document de travail du personnel—2023-27 Last updated: May 29, 2023
Interaction Devices and Techniques for 3D Sketching

In the previous chapter, we discussed the different ways to create a stroke. In this chapter, we present various interaction devices and techniques that help users sketch in a 3D environment. An interaction device or technique is a combination of hardware and software elements that help users accomplish a single task [1], in this case, to create 3D sketches. When talking about specific interaction devices or techniques, it is important to consider the needs of the user. For 3D sketching, these needs change depending on the type of sketch the user wants to create [2, 3, 4]. It is also important to consider the affordances that different interaction devices or techniques have, as they affect the way users utilise them [5, 6]. Affordances are an attribute of the tool that shows which features they offer to the user [5, 6]. Based on these considerations, we divide this chapter into two parts. First, we will talk about user interface or interaction technique that allow users to draw conceptual and technical sketches. We will discuss the characteristics that makes them more appropriate for each specific sketch type. Then, we will talk about the functional and physical affordances of a user interface or interaction technique. Here, we will discuss how these affordances can affect the sketch produced by them. This chapter is useful for readers that want to design their interaction device or technique for sketching in 3D, as we discuss the different properties they need to consider. For example, the type of sketch their interaction device or technique can create and the affordances they need to have.
Multi-Agent Deep Reinforcement Learning for Cooperative Edge Caching via Hybrid Communication

Though caching on edge servers is widely acknowledged to be essential, it is not trivial to cache content on edge servers adaptively without any prior knowledge of the distribution of content popularity across the users. Several edge caching algorithms have been proposed in the literature based on multi-agent reinforcement learning (MARL) for dynamic control, however, they ignored the non-stationarity and partial-observability issues commonly existing in multi-agent systems. In an MARL-based edge caching application where agents collaborate towards a common goal, communication is essential as their decisions are jointly applied to improve collective intelligence. However, most existing methods proposed to exchange messages between agents have not considered the induced communication overhead, which is critical in practice with real-world multi-agent applications. In this paper, we propose a new MARL framework for edge caching where agents learn to construct, exchange and interpret collective messages for individual benefits, while controlling the complex collaborative task of cache replacement in a communication-efficient manner. With a standard edge caching model, we show that with limited communication and delays introduced, our proposed framework is able to outperform existing rule-based and learning-based caching policy alternatives.
Closing the Loop on Runtime Monitors with Fallback-Safe MPC

When we rely on deep-learned models for robotic perception, we must recognize that these models may behave unreliably on inputs dissimilar from the training data, compromising the closed-loop system's safety. This raises fundamental questions on how we can assess confidence in perception systems and to what extent we can take safety-preserving actions when external environmental changes degrade our perception model's performance. Therefore, we present a framework to certify the safety of a perception-enabled system deployed in novel contexts. To do so, we leverage robust model predictive control (MPC) to control the system using the perception estimates while maintaining the feasibility of a safety-preserving fallback plan that does not rely on the perception system. In addition, we calibrate a runtime monitor using recently proposed conformal prediction techniques to certifiably detect when the perception system degrades beyond the tolerance of the MPC controller, resulting in an end-to-end safety assurance. We show that this control framework and calibration technique allows us to certify the system's safety with orders of magnitudes fewer samples than required to retrain the perception network when we deploy in a novel context on a photo-realistic aircraft taxiing simulator. Furthermore, we illustrate the safety-preserving behavior of the MPC on simulated examples of a quadrotor. We open-source our simulation platform and provide videos of our results at our project page: https://tinyurl.com/fallback-safe-mpc.
Magnetic helicity of solar active regions

Abstract Magnetic helicity is a quantity that describes the linkage and twistedness/shear in the magnetic field. It has the unique feature that it is probably the only physical quantity which is approximately conserved even in resistive MHD. This makes magnetic helicity an ideal tool for the exploration of the physics of eruptive events. The concept of magnetic helicity can be used to monitor the whole history of a CME event from the emergence of twisted magnetic flux from the convective zone to the eruption and propagation of the CME into interplanetary space. In this article, I discuss the sources of the magnetic helicity injected into active regions and the role of magnetic helicity in the initiation of solar eruptions.
Raising the Level of Abstraction for Time-State Analytics With the Timeline Framework

Across many domains, we observe a growing need for more complex time-state analytics , which entails context-sensitive stateful computations over continuously-evolving systems and user/machine states. For instance, in video distribution, we want to analyze the total time video sessions spend in a buffering state. We argue that modern data processing systems entail (a) high development time and complexity and (b) poor cost-performance tradeoffs, for such workloads. We make a case for a Timeline abstraction for serving this class of workloads. By raising the level of abstraction using Timelines, we can reduce development complexity and improve cost-performance tradeoffs. We demonstrate the early promise in a production-scale video analytics deployment. We posit that the Timeline abstraction is more generally applicable across domains and enables new opportunities for further research.
oTree Markets

This paper presents oTree Markets, a ﬂexible framework for the construction of market simulation experiments in oTree. oTree Markets provides three components: a Python implementation of a Continuous Double Auction exchange, a reference text-based interface and an oTree layer for communication and state management. These three components are designed with modularity in mind, with the intent that each of them could be replaced with modiﬁed versions to suit the needs of a wide variety of market simulation experiments.
Formulation of Combustion Acoustic Coupling using Multiple Time and Length Scales

The governing equations for combustion acoustic interaction in a generalized multiple time and length scale regime is derived from the full compressible Navier Stokes equations. The equations are shown to reduce to their counterparts for single-time-multiple-length scale and multiple-time-single-length scale regimes reported in the literature. The acoustics is driven by the divergence of the base-flow velocity in the multi-time-length scale whereas it is the heat release rate fluctuations in the single-time-multiple-length scale regimes. The acoustics is not driven by the flow in the multiple-time-single-length scale regime. The acoustics in turn aects the base-flow through the acoustic Reynolds stress in the multipletime-single-length scale and multiple-time-length scale regimes and through the gradient in acoustic pressure in the single-time-multiple-length scale regime. The behaviour of the coupled system is predicted numerically in the present work for a laminar non-premixed flame at a backward facing step in the multiple-time-length scale regime. The acoustic Reynolds stress is observed to play a key role in the evolution of the coupled system, as it gradually evolves towards a single-time-multiple-length scale leading to combustion instability.
MODELLING THE IMPACT OF EXCHANGE RATE VOLATILITY ON TRADE FLOWS IN NIGERIA

This study investigates the impact of the persistent exchange rate volatility on trade flows in Nigeria, for the period of 1970-2021, using secondary data obtained from various sources. Data were analyzed using descriptive tools like tables, graphs and other econometric methods, such as the Two Stage Least Squares method. Result of the trade flows equation indicates that though all the explanatory variables conformed to theoretical a priori expectation, none was statistically significant at 5% level. It confirms a negative and insignificant impact of exchange rate volatility on trade flows in Nigeria. Further findings from the EGARCH model indicate that exchange rate volatility in Nigeria has been high, persistent and asymmetric with positive leverage and high clustering effect over the study period. The study recommends pragmatic economic diversification away from oil to the tradable lagging sectors of agriculture, manufacturing and the services sector, in order to stabilize the long run value of the exchange rate. Also, appropriate monetary-fiscal policy measures should be adopted in order to reduce exchange rate volatility, particularly the supply-sided approach. Nigeria should also increasingly open up her economy to foreign trade in order to harness foreign direct investment inflow into the economy.
HOMOTOPY PERTURBATION METHOD FOR A MODIFIED

In this article, the Homotopy Perturbation Method (HPM) is employed to approximate solutions of a modified Lotka Volterra equation. HPM has been introduced by He to solve approximately linear or nonlinear differential equations. Approximate polynomials have also been constructed to find approximate solutions of a modified Lotka Volterra system. Numerical comparisons are made between HPM and maple numerical results. AMS Subject Classification: 34A34, 65L05.
From economic difficulties to psychological maladjustment in Italian women during the Covid-19 pandemic: does marital dissatisfaction moderate or mediate this association?

Introduction The empirical study about the negative impact of economic difficulties due to Covid- 19 on the psychological well-being of Italian women by considering perceived stress and marital satisfaction is an area worthy of investigation. The study explored these variables by hypothesizing that marital satisfaction (DAS) could moderate or mediate the links between economic difficulties, perceived stress (PSS), and psychological maladjustment (PGWBI). Methods A total of 320 Italian women completed an online survey about the study’s variables during the lockdown period. Women’s perceptions of economic difficulties due to COVID- 19 restrictions were detected through an ad-hoc specific question. Perceived stress, marital satisfaction and psychological maladjustment were assessed by standardized questionnaires (Perceived Stress Scale 10, Dyadic Satisfaction Scale and Psychological General Well-being Inventory). Results 39.7% of women who answered the online survey said that the Covid-19 significantly impacted their family income. Results indicated that marital satisfaction did not moderate the associations investigated. Conversely, data showed how economic difficulties (X) predicted lower psychological maladjustment through the mediation of perceived Stress (M1), which, in turn, was associated with higher levels of marital dissatisfaction (M2). Conclusion The results of the present study confirm the significant role of marital dissatisfaction in explaining the indirect effects of economic difficulties on psychological maladjustment in women. In particular, they indicated a significant spillover effect which transmitted strains experienced in one domain (economic difficulties) to another (the dissatisfaction of the couple), which in turn affected the psychological maladjustment.
Visualizing Quantum Mechanical Phenomena

In this paper we discuss several ways to visualize stationary and non-stationary quantum mechanical systems. We demonstrate an approach for the quantitative interpretation of probability density isovalues which yields a reasonable correlation between isosurfaces for different timesteps. As an intuitive quantity for visualizing the momentum of a quantum system we propose the probability flow density which can be treated by vector field visualization techniques. Finally, we discuss the visualization of non-stationary systems by a sequence of single timestep images.
Job satisfaction and characteristics among staff of public higher educational institutions in Ghana

Abstract The role of Higher Educational Institutions (HEIs) in preparing human resource for local, national and global sustainable development is paramount. Such role can be adequately performed by competent staff who are satisfied with their jobs. This study determined the extent of the relationship between job satisfaction and characteristics in public HEIs in Ghana. The study employed the cross-sectional survey design. Factor analysis and canonical correlation analysis were applied to the data collected from three categories of staff from four public universities constituting a sample size of 452. Results show that social status, recognition, remuneration and conducive work environment informed their job satisfaction. For the dimensions of job characteristics, the most important was the variety of tasks performed on the job, followed by the feedback employees received from the job outcomes. The other three dimensions were task significance, autonomy and task identity. A positive canonical correlation existed between the first canonical pair of functions, suggesting a significant relationship between the two sets of solutions. There was a possible negative relationship between remuneration and a combination of task significance and task identity. The recommendations involved leadership providing adequate information on activities, motivation packages, feedback and conducive workplace environment to the staff.
Frames and constructions enhance text coherence: The case of DNI resolutions in spoken discourse

Abstract The paper reports on a corpus-based study investigating the impact of frames and constructions on establishing text coherence. Partly conducted in collaboration with the International Computer Science Institute / FrameNet, Berkeley, the study is based on systematic annotations of so-called Definite Null Instantiations (DNIs). A DNI, sometimes also called anaphoric NI, is a syntactically non-instantiated core frame element (FE), whose identity can be inferred from the co(n)text. By analyzing forms and functions of DNIs in spoken discourse, I will argue that omitted core FEs are often found to be specified in adjacent sentences, yielding frame-triggered text coherence. The case study sheds light on the text-linguistic relevance of frames and constructions. At the same time it paves the way for further investigations of textual reference in a cognitive-linguistic framework.
Topological Properties of some Benzenoid Chemical Structures by Using Face Index

A variety of graphical invariants have been described and tested, offering lots of applications in the fields of Nano chemistry, computational networks and different scientific research areas. One commonly studied group of invariants is the topological index, which allows the prediction of the chemical, biological and physical properties of a chemical structure. Topological indexes are numerical quantities that can be used to describe the properties of the molecular graph. In this article, we computed the face index formula for certain molecular structures of benzenoid series such as polycyclic aromatic hydrocarbon (PAH), jagged-rectangle benzenoid system (JRB[m,n]) and the series of concealed non-kekulean benzenoid system.
Seeing Photons in Color

Megapixel single-photon avalanche diode (SPAD) arrays have been developed recently, opening up the possibility of deploying SPADs as generalpurpose passive cameras for photography and computer vision. However, most previous work on SPADs has been limited to monochrome imaging. We propose a computational photography technique that reconstructs high-quality color images from mosaicked binary frames captured by a SPAD array, even for high-dyanamic-range (HDR) scenes with complex and rapid motion. Inspired by conventional burst photography approaches, we design algorithms that jointly denoise and demosaick single-photon image sequences. Based on the observation that motion effectively increases the color sample rate, we design a blue-noise pseudorandom RGBW color filter array for SPADs, which is tailored for imaging dark, dynamic scenes. Results on simulated data, as well as real data captured with a fabricated color SPAD hardware prototype shows that the proposed method can reconstruct high-quality images with minimal color artifacts even for challenging low-light, HDR and fast-moving scenes. We hope that this paper, by adding color to computational single-photon imaging, spurs rapid adoption of SPADs for real-world passive imaging applications.
Effect of Si segregation at grain boundaries on the mechanical behaviours of ageing Al metallization layer in insulated gate bipolar transistor module

ABSTRACT In this study, the evolution of the Si atom distribution within an Al metallization layer in an insulated gate bipolar transistor (IGBT) module during power cycling is studied experimentally through electron backscatter diffraction (EBSD) observations, X-ray diffraction (XRD) measurements, and scanning electron microscopy (SEM) characterization. Molecular dynamics (MD) simulations are applied to study the effects of Si segregation on the mechanical properties of the Al metallization layer. The results show that Si segregation toward the Al grain boundaries occurs as the number of power cycles increases, and this behaviour strongly influences the recrystallization, texture, grain size and mechanical performance of the Al metallization layer.
LOW-TEMPERATURE PARTICLE DETECTORS

▪ Abstract The need for very good energy resolution in experiments in particle and astroparticle physics and the need to detect very small energy depositions are the major motivations for the development of low-temperature particle detectors. Because the energy quanta associated with superconductors and lattice vibrations (phonons) are more than one hundred times smaller, substantial improvements have been obtained in energy resolution and in sensitivity over conventional detectors. Furthermore, these detection schemes permit tailoring of target or absorber materials to match the physics requirements. In this article, the basic physics principles behind various methods of detecting excitations induced by particle interactions in bulk single-crystal materials at low temperatures are reviewed. We also present an overview of progress toward implementation of particle physics experiments, such as detection of low-energy neutrinos, search for dark-matter particles, search for neutrino-less double β decay, and .