Miracle-dz/UniFAR-FTUs huggingface dataset:
Metric Planning using Planning Graphs - A First Investigation

A First Investigation Jana Koehler Institute for Computer Science Albert Ludwigs University Am Flughafen 17 79110 Freiburg, Germany koehler@informatik.uni-freiburg.de Abstract After the extension of the graphplan formalism to ADL, another important aspect of planning problems forms the focus for the development of IPP: resourceconstrained planning problems. IPP's basic resource representation language BRL is motivated, and its syntax and semantics are de ned. A sound and complete search algorithm is de ned, which can be easily extended to handle conditional resource e ects. Examples illustrate the use of the BRL formalism. Technical Report No. 127
Phase Transformations Caused by Heat Treatment and High-Pressure Torsion in TiZrHfMoCrCo Alloy

In this work the high-entropy alloy studied contained six components, Ti/Zr/Hf/Mo/Cr/Co, and three phases, namely one phase with body-centered cubic lattice (BCC) and two Laves phases C14 and C15. A series of annealings in the temperature range from 600 to 1000 °C demonstrated not only a change in the microstructure of the TiZrHfMoCrCo alloy, but also the modification of phase composition. After annealing at 1000 °C the BCC phase almost fully disappeared. The annealing at 600 and 800 °C leads to the formation of new Laves phases. After high-pressure torsion (HPT) of the as-cast TiZrHfMoCrCo alloy, the grains become very small, the BCC phase prevails, and C14 Laves phase completely disappears. This state is similar to the state after annealing at high effective temperature Teff. The additional annealing at 1000 °C after HPT returns the phase composition back to the state similar to that of the as-cast alloy after annealing at 1000 °C. At 1000 °C the BCC phase completely wets the C15/C15 grain boundaries (GBs). At 600 and 800 °C the GB wetting is incomplete. The big spread of nanohardness and Young’s modulus for the BCC phase and (C15 + C14) Laves phases is observed.
Disengagement toward brand-based online communities: The role of culture

Abstract With the rise of the internet, online brand communities have gained popularity among users. However, online brand communities continue to face difficulties in engagement and usage despite the advantages it offers. This study examines the dark side of online brand communities. A total of 316 responses from online brand community members were collected to examine the proposed hypotheses based on the Technology–Personal–Environment (TPE) framework. The study also examines the moderating effect of culture (individualism and uncertainty avoidance). The findings suggest that perceived compatibility, inertia and social influence impact the users’ disengagement intention toward online brand communities. Also, individualism and uncertainty avoidance moderated the association between perceived complexity and disengagement intention. The study contributes to the dark side of brand-based online community literature and suggests marketers how to reduce customer disengagement in online brand communities.
Coupling Boltzmann and Navier-Stokes Equations by Half Fluxes

We introduce an adaptative coupling of the Boltzmann and Navier? Stokes equations to compute hypersonic flows around a vehicle at high altitude. The coupling is achieved by matching half fluxes at the interface of the Boltzmann and Navier? Stokes domains. The domains are determined automatically by computing local kinetic residuals on a preliminary Navier? Stokes solution. Our method is developed here for monoatomic gases. Different numerical results illustrate its validity and limits.
Hybrid Knowledge and Data Driven Synthesis of Runtime Monitors for Cyber-Physical Systems

Recent advances in sensing and computing technology have led to the proliferation of Cyber-Physical Systems (CPS) in safety-critical domains. However, the increasing device complexity, shrinking technology sizes, and shorter time to market have resulted in significant challenges in ensuring the reliability, safety, and security of CPS. This article presents a hybrid knowledge and data-driven approach for designing run-time context-aware safety monitors that can detect early signs of hazards and mitigate them in CPS. We propose a framework for formal specification of unsafe system context using Signal Temporal Logic (STL) combined with two optimization approaches for scenario-specific refinement and integration of STL specifications using data collected from closed-loop CPS simulations. We demonstrate the effectiveness of our approach in simulation using an autonomous driving system (ADS) and two closed-loop artificial pancreas systems (APS) as well as a publicly-available clinical trial dataset. The results show that a safety monitor developed with the proposed approaches demonstrates up to 4.7 times increase in average prediction accuracy (F1 score) over several well-designed baseline monitors while reducing both false-positive and false-negative rates in most scenarios.
How to do human evaluation: A brief introduction to user studies in NLP

Abstract Many research topics in natural language processing (NLP), such as explanation generation, dialog modeling, or machine translation, require evaluation that goes beyond standard metrics like accuracy or F1 score toward a more human-centered approach. Therefore, understanding how to design user studies becomes increasingly important. However, few comprehensive resources exist on planning, conducting, and evaluating user studies for NLP, making it hard to get started for researchers without prior experience in the field of human evaluation. In this paper, we summarize the most important aspects of user studies and their design and evaluation, providing direct links to NLP tasks and NLP-specific challenges where appropriate. We (i) outline general study design, ethical considerations, and factors to consider for crowdsourcing, (ii) discuss the particularities of user studies in NLP, and provide starting points to select questionnaires, experimental designs, and evaluation methods that are tailored to the specific NLP tasks. Additionally, we offer examples with accompanying statistical evaluation code, to bridge the gap between theoretical guidelines and practical applications.
When Multigranularity Meets Spatial–Spectral Attention: A Hybrid Transformer for Hyperspectral Image Classification

The transformer framework has shown great potential in the field of hyperspectral image (HSI) classification due to its superior global modeling capabilities compared to convolutional neural networks (CNNs). To utilize the transformer to model spatial–spectral information, a hybrid transformer that integrates multigranularity tokens and spatial–spectral attention (SSA) is proposed. Specifically, a token generator is designed to embed the multigranularity semantic tokens, which contributes richer image features to the model by exploiting CNN’s local representation capability. Moreover, a transformer encoder with an SSA mechanism is proposed to capture the global dependencies between different tokens, enabling the model to focus on more differentiated channels and spatial locations to improve the classification accuracy. Ultimately, adaptive weighted fusion is applied to different granularity transformer branches to boost HybridFormer’s classification performance. Experiments were conducted on four new challenging datasets, and the results indicate that HybridFormer achieves state-of-the-art results in terms of classification performance. The code of this work will be available at https://github.com/zhaolin6/HybridFormer for the sake of reproducibility.
Nonlinear finite element methods for nonrigid motion analysis

The motion of nonrigid or deformable bodies has been studied in the field of engineering mechanics and applied mathematics for years with great success. In computer vision, the application of engineering mechanics for 3D shape fitting and motion analysis is generally called utilizing deformable shape models or physically-based modeling (usually using linear FEM). Since many real-world materials behave non-linearly when they are subjected to large deformations, one cannot expect a linear FEM to be a good model of many materials undergoing large deformation. This severely restricts the applications of FEM in many nonrigid notion analysis problems. In this paper we propose the use of the nonlinear finite element modeling for the nonrigid motion analysis
Inverse Design of Free-Form Devices With Fabrication-Friendly Topologies Based on Structure Transformation

In order to improve the fabrication robustness of the inverse-designed devices that have complex topology structures, we propose an optimization technique, named as structure transformation (ST), to transform structures of the inverse-designed devices into simple topologies that contain less irregularly tiny features, sharp corners and less boundary regions. The proposed ST technique, based on a new alternately-implementing strategy of optical performance optimization and modified curvature-constrained structure adjustment, effectively facilitates an overall simplification of the structure topologies of devices, enhances their robustness to fabrication uncertainties, and simultaneously maintains or even improves their optical performances. To verify the feasibility of the technique, three types of typical SOI-based devices (T-junction, 1×3 power splitter and 90° crossing) with and without ST were designed, among which the ones without ST were given as control groups. Thanks to the ST, the boundary regions and highly curved ranges in these devices are all significantly reduced, while their performances are well maintained or even improved. Next, the effect of the ST on fabrication tolerances were investigated, and the simulation results show that the devices with ST are more robust to over/under-etching errors than the control groups. At last, the T junction and 1×3 power splitter and their control groups were fabricated each with 6 samples. Measured results show that the performances of the devices with ST deviate from the simulated performances much less than their control groups, which agrees well with the simulated results in fabrication tolerances investigation. Summarily, we proposed and demonstrated a technique that provides the inverse-designed devices new possibilities to achieve simpler topologies with better fabrication robustness and improved performances at the same time.
Euler Solution for a Complete Fighter Aircraft at Sub- and Supersonic Speed,

Abstract : A survey is given on the construction of a novel high resolution Euler code which is applied for airflow calculations past a fighter type aircraft. The principle feature of the flow solver is a Godunov type averaging procedure based on the eigenvalue analysis of the Euler equations by means of which the fluxes are evaluated at the finite volume faces which separate constant sets of flow variables on either side. The procedure is third order accurate and locally monotonicity preserving thus avoiding the drawbacks of global TVD-schemes. The grid generation for complex configuration is performed from solutions of linear biharmonic equations with only one parameter prescribed by the program user. Vector computer performance of the explicit and implicit program versions are considered.
CA II K Line: A New Metallicity Indicator for RR Lyrae Stars

In order to check and, possibly, improve the Preston's ΔS calibration scale, CCD spectra have been obtained for 26 field RR Lyrae variables of Bailey type ab. The spectra cover the wavelength region 3900 ≤ λ ≤ 4400A at a dispersion of 43 A mm −1 . Particular care has been taken to obtain the spectra when the objects were at minimum light. For eleven program stars with direct [Fe/H] values available in the literature, it is found that the equivalent width of the Ca II K line is extremely well correlated with the [Fe/H] values, the best-fit relation being [Fe/H] = 0.53 W'(K) - 3.08, where W'(K) is the equivalent width of the K line corrected for the interstellar contribution
(Retracted) Mimicking human vision systems: deep-learning-based feature fusion for semantic image retrieval

Abstract. The Editor-in-Chief and the publisher have retracted this article, which was submitted as part of a guest-edited special section. An investigation uncovered evidence of systematic manipulation of the publication process, including compromised peer review. The Editor and publisher no longer have confidence in the results and conclusions of the article. ZC and LZ agreed with retraction.
Differential geometry of the cortical surface

The cortical fold is one of the most striking features of the brain and it plays a tremendously important role in understanding brain function. In this paper we build a precise mathematical representation of a typical cortical surface. This representation will allow us to make statements about the geometry of the surface and will enable us to compute intrinsic geometrical properties such as the Mean and the Gaussian curvature of the surface.
Predictors of Overweight and Obesity in Early Care and Education Teachers during COVID-19

The purpose of this cross-sectional study was to determine individual, sociocultural, policy, and economic predictors of overweight/obesity in early care and education (ECE) teachers to identify modifiable opportunities to enhance the health of this critical workforce. ECE teachers (n = 1434) in the U.S. completed an online survey in late spring to mid-summer 2020. Teachers self-reported height and weight; body mass index (BMI) and weight status were calculated. Teachers reported micro-environment variables including age, race, gender, obesogenic lifestyle behaviors, well-being, food security, personal health, stress, job stress, type of ECE, COVID-19 teaching modality, and age of children in the classroom. Logistic regression predicting overweight/obesity and linear regression predicting BMI were conducted. Teachers with more years of teaching experience (OR: 1.022: 95% CI 1.005, 1.039) and higher consumption of fast food (2.038: 1.310, 3.169) had higher odds of overweight/obesity. Teachers with higher levels of education (0.58: 0.407, 0.828) and higher physical health (0.836: 0.775, 0.902) had lower odds of overweight/obesity. Other variables were not associated with overweight/obesity. Variables significant in logistic regression were also associated with higher BMI. Additionally, Native American race (β = 2.467 SE = 1.206) and sedentary hours/day (β = 0.152 SE = 0.075) were associated with higher BMI. Implications for enhancing workplace health for these ECE teachers are emerging.
Is the vitamin D status of patients with COVID-19 associated with reduced mortality? A systematic review and meta-analysis

ABSTRACT To conduct a systematic review and meta-analysis of studies assessing the association between serum vitamin D status and mortality in patients with COVID- 19. We searched PubMed and Embase for studies addressing the association of serum vitamin D levels and COVID-19 mortality published until April 24, 2022. Risk ratios (RRs) and 95% confidence interval (CIs) were pooled using fixed or random effects models. The risk of bias was assessed using the Newcastle-Ottawa Scale. The meta-analysis included 21 studies that measured serum vitamin D levels close to the date of admission, of which 2 were case- control and 19 were cohort studies. Vitamin D deficiency was associated with COVID-19 mortality in the overall analysis but not when the analysis was adjusted to vitamin D cutoff levels < 10 or < 12 ng/mL (RR 1.60, 95% CI 0.93-2.27, I2 60.2%). Similarly, analyses including only studies that adjusted measures of effect for confounders showed no association between vitamin D status and death. However, when the analysis included studies without adjustments for confounding factors, the RR was 1.51 (95% CI 1.28-1.74, I2 0.0%), suggesting that confounders may have led to many observational studies incorrectly estimating the association between vitamin D status and mortality in patients with COVID-19. Deficient vitamin D levels were not associated with increased mortality rate in patients with COVID-19 when the analysis included studies with adjustments for confounders. Randomized clinical trials are needed to assess this association.
Uplink Signal Detection via Look-Up Table-Based AMP for Massive MIMO Systems

We propose a novel look-up table (LUT)-based multi-user detection (MUD) algorithm to imitate approximate message passing (AMP) for uplink signal detection in massive multi-user multi-input multi-output (MU-MIMO) systems. When AMP is implemented with double-precision arithmetic, the dramatic increase in power consumption and process latency becomes a major barrier to practical application, as the system scale expands. To circumvent this issue, we design a novel referential AMP detector composed of many small LUTs cascaded hierarchically, where only informative integer-valued messages are exchanged on a factor graph (FG). Our method tracks the discrete distribution of the LUT outputs according to the multi-layer structure, and successively determines non-uniform quantization thresholds of the LUTs, using an unsupervised learning approach. Specifically, the thresholds at each level of the hierarchy, i.e., layer, are optimized by clustering with the Lloyd-Max algorithm with initial values given by the k-means++ method, in order to minimize the performance degradation caused by quantization errors. The efficacy of the proposed referential AMP detector is confirmed by numerical simulations, which show that the proposed method significantly outperforms the state-of-the-art (SotA) in terms of the bit error rate (BER) performance in various channel models. The results also indicate the referential AMP is robust to changes in wireless channels, and then clarify the reason in terms of the algorithmic structure.
Outstanding Sorption of Copper (II) Ions on Porous Phenothiazine-Imine-Chitosan Materials

The aim of this work was to investigate the ability of a solid-state material, prepared by crosslinking chitosan with a phenothiazine-based aldehyde, to remove copper (II) ions from aqueous solutions, in a fast and selective manner. The metal uptake experiments, including the retention, sensibility, and selectivity against eight different metal ions, were realized via batch adsorption studies. The capacity of the material to retain copper (II) ions was investigated by spectrophotometric measurements, using poly(ethyleneimine) complexation agent, which allowed detection in a concentration range of 5–500 µM. The forces driving the copper sorption were monitored using various methods, such as FTIR spectroscopy, X-ray diffraction, SEM-EDAX technique, and optical polarized microscopy, and the adsorption kinetics were assessed by fitting the in vitro sorption data on different mathematical models. The phenothiazine-imine-chitosan material proved high ability to recover copper from aqueous media, reaching a maximum retention capacity of 4.394 g Cu (II)/g adsorbent when using a 0.5 M copper solution, which is an outstanding value compared to other chitosan-based materials reported in the literature to this date. It was concluded that the high ability of the studied xerogel to retain Cu (II) ions was the result of both physio- and chemo-sorption processes. This particular behavior was favored on one hand by the porous nature of the material and on the other hand by the presence of amine, hydroxyl, imine, and amide groups with the role of copper ligands.
Interaction of a vortex ring with a single bubble: bubble and vorticity dynamics

The interaction of a single bubble with a single vortex ring in water has been studied experimentally. Measurements of both the bubble dynamics and vorticity dynamics have been done to help understand the two-way coupled problem. The circulation strength of the vortex ring ( ${\it\Gamma}$ ) has been systematically varied, while keeping the bubble diameter ( $D_{b}$ ) constant, with the bubble volume to vortex core volume ratio ( $V_{R}$ ) also kept fixed at about 0.1. The other important parameter in the problem is a Weber number based on the vortex ring strength $(\mathit{We}=0.87{\it\rho}({\it\Gamma}/2{\rm\pi}a)^{2}/({\it\sigma}/D_{b});a=\text{vortex core radius},{\it\sigma}=\text{surface tension})$ , which is varied over a large range, $\mathit{We}=3{-}406$ . The interaction between the bubble and ring for each of the $\mathit{We}$ cases broadly falls into four stages. Stage I is before capture of the bubble by the ring where the bubble is drawn into the low-pressure vortex core, while in stage II the bubble is stretched in the azimuthal direction within the ring and gradually broken up into a number of smaller bubbles. Following this, in stage III the bubble break-up is complete and the resulting smaller bubbles slowly move around the core, and finally in stage IV the bubbles escape. Apart from the effect of the ring on the bubble, the bubble is also shown to significantly affect the vortex ring, especially at low $\mathit{We}$ ( $\mathit{We}\sim 3$ ). In these low- $\mathit{We}$ cases, the convection speed drops significantly compared to the base case without a bubble, while the core appears to fragment with a resultant large decrease in enstrophy by about 50 %. In the higher- $\mathit{We}$ cases ( $\mathit{We}>100$ ), there are some differences in convection speed and enstrophy, but the effects are relatively small. The most dramatic effects of the bubble on the ring are found for thicker core rings at low $\mathit{We}$ ( $\mathit{We}\sim 3$ ) with the vortex ring almost stopping after interacting with the bubble, and the core fragmenting into two parts. The present idealized experiments exhibit many phenomena also seen in bubbly turbulent flows such as reduction in enstrophy, suppression of structures, enhancement of energy at small scales and reduction in energy at large scales. These similarities suggest that results from the present experiments can be helpful in better understanding interactions of bubbles with eddies in turbulent flows.
A Method for Separating the O/X Mode Signals in Vertical Ionograms Based on Improved U-Shaped Encoder–Decoder Network

The accuracy of O/X mode separation in vertical ionograms directly determines the quality of pattern discrimination results and metrics, which is of great significance to ionospheric research. It is extremely complicated to separate the O/X mode of the vertical ionograms because of the environmental noise, interference, and the time-varying dispersion characteristics of the ionosphere itself. In this article, we propose a method for separating the O/X mode signal in vertical ionograms based on an improved U-shaped encoder–decoder network, named vertical ionogram separation U-shaped network (VIS-UNet). Our model is based on the encoder–decoder architecture. It introduces the residual convolution to avoid network performance degradation and utilizes the attention module to improve the attention of the signal characteristic. In addition, we design an adaptive loss function to expedite the convergent speed of the model. Experimental results show that our model performs better than the baselines for the task of the O/X mode signal separation: 1) the method in this article has low requirements on the vertical ionospheric sounding system and the ionograms obtained by the single-channel vertical ionospheric sounding system can realize the separation of O/X mode signal at the pixel level; 2) it has strong universality and is insensitive to the signal integrity and the ionospheric pattern of the vertical ionograms; and 3) it performs better for the separation task. The mean intersection over union (MIOU) of the O/X mode separation task reaches 91.97% and the performance is significantly improved compared with the existing methods.