Miracle-dz/UniFAR-FTUs huggingface dataset:
Technical details regarding compositional veriﬁcation with event priorities

: In this study, we address the veriﬁcation of non-blockingness for modular discrete-event systems, i.e., discrete-event systems that are composed from component models by synchronous composition. Speciﬁcally, we extend the approach of compositional veriﬁcation as poposed by Flordal and Malik (2009) and Pilbrow and Malik (2015) to prioritised events. This report is meant as a supplement to a manuscript submitted to WODES 2022 in that it contains various technical proofs omitted due to page restrictions. In turn, we do neither repeat the introduction, nor the application examples in this document. 1
Model-assisted identiﬁcation of metabolic engineering strategies for Jatropha curcas lipid pathways

SUMMARY Efﬁcient approaches to increase plant lipid production are necessary to meet current industrial demands for this important resource. While Jatropha curcas cell culture can be used for in vitro lipid production, scaling up the system for industrial applications requires an understanding of how growth conditions affect lipid metabolism and yield. Here we present a bottom-up metabolic reconstruction of J. curcas supported with labeling experiments and biomass characterization under three growth conditions. We show that the metabolic model can accurately predict growth and distribution of ﬂuxes in cell cultures and use these ﬁndings to pinpoint energy expenditures that affect lipid biosynthesis and metabolism. In addition, by using constraint-based modeling approaches we identify network reactions whose joint manipulation optimizes lipid production. The proposed model and computational analyses provide a stepping stone for future rational optimization of other agronomically relevant traits in J. curcas .
Embeddings for Trust-Based Collaborative Filtering

In this work, we study the utility of graph embeddings to generate latent user representations for trust-based collaborative ﬁlter-ing. In a cold-start setting, on three publicly available datasets, we evaluate approaches from four method families: (i) factorization-based, (ii) random walk-based, (iii) deep learning-based, and (iv) the Large-scale Information Network Embedding (LINE) approach. We ﬁnd that across the four families, random-walk-based approaches consistently achieve the best accuracy. Besides, they result in highly novel and diverse recommendations. Furthermore, our results show that the use of graph embeddings in trust-based collaborative ﬁltering signiﬁcantly improves user coverage.
Numerical and experimental estimation of building wall heat flux in presence of moisture transfer

Insulating building envelope is an efficient way to increase building energy efficiency and minimize greenhouse gas emissions related to heating. After building refurbishment, on-site measurements are suitable for verifying the actual thermal transmission properties of plane building components. For instance, the standard ISO 9869-1 describes a HFM method based on the measurement of surface heat flux with heat flow sensor (HFS). This method has been extensively investigated in the literature and successfully applied on vapor tight building walls. Nevertheless, hygroscopic building insulation materials (like biobased materials) are increasingly used, and heat transfer are coupled to moisture transfer within the wall. In this case, the HFS acts as a vapor barrier: it modifies the local moisture transfer and the associated latent heat flux. In this view, this study aims to clarify what it is measured with HFS in presence of moisture transfer. The question is first treated by numerical simulation of heat and moisture transfer within hygroscopic building wall. Then, experiments are carried out on hygroscopic building insulation where the moisture effects are exaggerated.
Experimental study on the capillary water absorptivity of an aerogel-based coating mortar under subsequent drying and wetting cycles

Aerogel-based coating mortars with thermal conductivities ranging from 30 to 50 mW/(m·K) are an emerging type of thermal insulation coating mortar. They are intended for retrofitting uninsulated building envelopes due to their thermal performance which is comparable to conventional thermal insulation materials such as mineral wool. Meanwhile, their long-term hygrothermal performance and the reliability of the material properties are not fully demonstrated since these normally are declared based on single-cycle laboratory measurements. This paper presents laboratory measurements to determine the capillary water absorptivity of a commercial aerogel-based coating mortar after three consecutive wetting and drying cycles. The effect of the chosen drying (elevated versus room temperature) and sealing condition (sealed versus unsealed samples) on the measurement results were also assessed. The results show that the capillary water absorptivity of the samples increased after each repeated wetting and drying cycle regardless of the drying and sealing conditions. After three cycles, the measured capillary water absorption was more than five times higher than the initial measurement. Future research should investigate the causes of the observation and whether it applies to other aerogel-based coating mortars.
Light Curves and Period Analysis of Beta Lyrae Stars

We present the light-curve period analysis of 36 Beta Lyrae stars from the OMC Archive. We check the reference period of the sample by applying the phase dispersion minimization periodogram. From our research, we determine the orbital period of five stars in the sample. One of them is CP Psc, showing a prominent hump in the light curve before the deeper eclipse, and revealing a period of 0.6847936 day. Additionally, we improved the previously published orbital period for 27 stars. Within this sample, we discovered three stars with the O’Connell effect, and we identified a system with a second period known as II Per, with an orbital period of 0.4798512 day and a long period 9.2724776 days. The light curve of V 747 Cen can be reproduced with a dark spot of temperature about 70% its surroundings, which covers one of the poles of the more massive star.
Laser-Doppler Anemometry for detection of the velocity field in the ventilated, asymmetrically heated channel - a case study

The topic of double-skin façades (DSFs) is re-emerging in the research environment, with studies ranging from architectural design concepts to specific investigations of heat and mass transfer in a vertical channel. These studies reflect a lack of comprehension of the phenomena taking place within the DSF cavities. This work presents a case study, where the Laser-Doppler Anemometry principle, combined with video registration of smoke movement, is used to establish the velocity and flow patterns in an asymmetrically heated ventilated channel in a controlled environment. The authors of this work contribute to the research field by addressing the pros and cons of the Laser-Doppler Anemometry approach for the measurement of the vertical velocity component in a DSF and presenting an example of obtained experimental results for the validation of CFD models. The results of this work address the velocity distribution for the vertical 2D cross plane of the DSF cavity. The analysis of the measurement data includes an assessment of the stability of the flow and fluctuations throughout the measurement period.
Optical Cable Fault Diagnosis and Auxiliary Decision-making Based on Knowledge Graph

The operational status of power communication optical cables is directly related to the safety of power transmission lines and communication systems. Traditional cable maintenance modes face challenges in fault localization. This article proposes a platform for optical cable fault diagnosis and decision support, which is constructed at three levels: the data layer, ontology layer, and application layer. The key aspect of this platform is the utilization of a knowledge graph to map the status of the cable system. The method proposed in this article effectively addresses the pain points of traditional maintenance modes.
Research on Denoising of GIS Ultra-High Frequency Partial Discharge Signal Based on VMD Combined with S-G Filter

Given the problem that it is easy to receive thermal noise interference from the electronic circuit and equipment circuit of the detection system in the current feature frequency detection of Gas Insulated Switchgear (GIS) equipment, this paper proposes an ultra-high frequency (UHF) signal noise reduction method based on variational mode decomposition (VMD) combined with Savitzky-Golay (S-G) filter and tests it through simulation. By using VMD combine with the S-G filter method, the signal-to-noise ratio (SNR) of signals can be effectively improved and the interference of white noise to signals can be reduced.
Stability Analysis for Vehicular Platooning Subjects to Disturbances

In our work, a control problem of vehicular communications platooning, subject to disturbances, is researched. To eliminate the spacing errors of the platooning, a novel effective non-singular terminal sliding-mode control (TSMC) law is designed for the following vehicles, where the problem of singularity is addressed. Furthermore, a coupled sliding-mode surface is presented for vehicular platooning. Then, based on Lyapunov stability theory, the spacing errors for the platooning can be forced into the designed TSMC surface in finite time and finally reach zero. The string stability of the platooning is also proven via a series of Laplace transforms. Finally, the validity of the proposed law in dealing with disturbances is expressed in simulation results.
A Routing Algorithm Based on Software-Defined Computing First Network

With the continuous development of mobile Internet technology, new services and applications appear, such as AR/VR, Internet of Vehicles, and Ultra HD Video. They not only require higher network bandwidth resources but also need more computing resources to ensure normal operation and user experience. As a new network technology, computing first network promotes the deep integration of distributed computing resources and networks to make efficient use of these resources. This paper proposes a computing power routing algorithm based on software-defined computing first network (SD-CFN) architecture. It comprehensively considers computing resources and available bandwidth resources of network links. Experimental results show that compared with the nearby scheduling strategy, the proposed computing power routing algorithm can better allocate computing resources to services. Moreover, it can improve the utilization rate of computing resources and provide optimal bandwidth resources in the process of service transmission.
Unraveling the Geologic History of Miranda’s Inverness Corona

Miranda is the only icy body whose surface is known to contain the enigmatic features called corona—ovoid to trapezoidal areas of deformation. In this work, we seek to constrain potential formation mechanisms for Inverness Corona, the youngest known region on Miranda. To do this, we created the first detailed geologic map of Inverness, enabling the creation of a stratigraphic column of the order of events that formed this region. We employed a previously published Digital Elevation Model of the northern region of Inverness Corona to analyze the spacing of features in the region, which we propose to be extensional in origin. From this, we estimate an approximate brittle ice shell thickness of 2.5–3.8 km at the time of the region’s formation, indicating that Miranda’s brittle ice shell may have been relatively thin in the geologically recent past. We propose that Inverness formed from extension driven by a rising diapir or ice-shell thickening from a recent orbital resonance with Umbriel. The Uranus Orbiter and Probe mission is the highest priority flagship mission recommendation of the 2023–2032 Planetary Science and Astrobiology Decadal Survey. As such, we suggest measurements related to imaging, composition, gravity, and ice-shell thickness to gain an understanding of the geologic and orbital histories of the Uranian satellites, which would have implications for the evolution of the system as a whole.
Research on the Application of Motor Field-Oriented Control in Vehicles

The motor application of the FOC strategy of the hybrid system in this text is the battery heat control. The specific contents are as below: SVPWM control. SVPWM is based on the three-phase symmetrical sine wave voltage supply and three-phase symmetrical motor stator ideal flux circle as a reference standard, with different switching modes of three-phase inverter for appropriate switching, to form PWM wave and to form the actual flux vector to track its accurate flux circle. By applying reactive voltage with high-frequency variation and using the FOC control strategy, the inductance characteristic of the motor winding is constantly utilized to generate alternating current on the bus. By taking advantage of the high internal resistance of the cell at low temperatures, the joule heat is constantly generated on the cell. While avoiding the risk of lithium analysis of the cell, heat is generated from the cell itself, and the temperature of the cell is raised. The vehicle results are conducted and show that the battery heat performance is enhanced.
Communication Energy Optimization of UAV-assisted WSN Data Transmission

Unmanned aerial vehicle (UAV)-assisted wireless sensor network (WSN) data transmission is a hot topic of research in recent years. This article mainly focuses on the energy consumption optimization of WSN data transmission with the assistance of UAVs. First, we established a communication coverage model for UAV-WSN and derived the energy consumption of data transmission for UAV-WSN, determining the optimal number of cluster heads (CHs) under different UAV flight heights. Second, we built a model for the energy consumption of WSN data transmission and the UAV flight height, and determined the optimal flight height of the UAV, while also dividing the UAV task area into segments. Then, we proposed a model that dynamically optimized the UAV data collection position according to the CH location, which can further reduce the energy consumption of CHs during data transmission. Finally, we used simulation experiments to verify the feasibility and effectiveness of our proposed scheme.
A Bi-directional Attention Based End to End Mispronunciation Detection and Diagnosis of Mandarin

An increasing number of individuals are acquiring proficiency in Mandarin, signifying the growing significance of employing computer-assisted pronunciation training systems for Mandarin learners. One pivotal component within these systems is the technique for identifying and addressing mispronunciations, known as Mispronunciation Detection and Diagnosis (MDD). Recently, certain end-to-end techniques have tried to fuse features of prompt text and acoustic features into the model for training and have shown good results. However, previous approaches have fused acoustic features with prompt text features by a simple attention mechanism. In this paper, we posit that the impact of text features varies significantly when mapped to distinct acoustic characteristics. Furthermore, we propose that the prompt text can lead the model towards achieving an integrated text-audio representation, thereby enhancing the inference quality. Hence, this article presents a model aimed at detecting and diagnosing mispronunciations. The model utilizes a bidirectional attention mechanism to integrate acoustic and prompt text features. Good results were achieved by conducting experiments on a self-built dataset of short Mandarin read-aloud texts.
Power-Impact-Harmonic Characteristics Analysis and Modeling of Diversified Power Loads in Urban Power Grid

Different load models of the same load have different effects on power flow calculation, short circuit calculation, voltage stability, and frequency stability after power system accidents. In this paper, some power load components in urban power grids are modeled by analyzing and fitting the measured power curve of load components, and they are divided into the power model, impact model, and harmonic model according to their characteristics. The power model includes the power models of some household appliances, industrial motors, and arc furnaces. The impact model includes the time series fitting model and probability fitting model. According to the measured power curve of load components, the load model established in this paper can avoid some risks of power calculation caused by the absence of a detailed load model.
Assessing the potential of free tropospheric water vapour isotopologue satellite observations for improving the analyses of latent heating events

Satellite-based observations of free tropospheric water vapour isotopologue ratios ( δ D) with good global and temporal coverage have become recently available. We investigate the potential of these observations for constraining the uncertainties of the atmospheric analyses ﬁelds of speciﬁc humidity ( q ), temperature ( T ), and δ D and of variables that capture important properties of the atmospheric water cycle, namely the vertical velocity ( ω ), the latent heating rate ( Q 2 ), and the precipitation rate (Prcp). Our focus is on the impact of the δ D observations if used in addition to the observation of q and T , which are 5 much easier to be observed by satellites and routinely in use for atmospheric analyses. For our investigations we use an Ob-serving System Simulation Experiment, i.e. simulate the satellite observations of q , T , and δ D with known uncertainties, then use them within a Kalman ﬁlter based assimilation framework in order to evaluate their potential for improving the quality of atmospheric analyses. The study is made for low latitudes ( 30 ◦ S to 30 ◦ N) and for 40 days between mid-July and end of August 2016. We ﬁnd that the assimilation of q and T observations alone well constrains the atmospheric q and T ﬁelds (analyses 10 skills in the free troposphere of up to 60%), and moderately constrains the ﬁelds of δ D, ω , Q 2 , and Prcp (analyses skills of 20%-40%). The additional assimilation of δ D observations further improves the quality of the analyses of all variables. We use Q 2 as proxy for the presence of condensation and evaporation processes, and we show that the additional improvement is rather weak when evaporation or condensation are negligible (additional analyses skills of generally below 5%), and strongest for high condensation rates (additional skills of about 15% and above). The very high condensation rates (identiﬁed by large 15 positive Q 2 values) are rare, but related to extreme events (very high ω and Prcp) that are not well captured in the analyses (for these extreme events also the analyses uncertainties of ω , Q 2 , and Prcp are very large), i.e. the additional assimilation of
DISTANCES BETWEEN SETS — A SURVEY

The purpose of this paper is to give a survey on the notions of distance between subsets either of a metric space or of a measure space, including deﬁnitions, a classiﬁcation, and a discussion of the best-known distance functions, which is followed by a review on applications used in many areas of knowledge, ranging from theoretical to practical applications.
Piecewise Linear Parametrization of Policies for Interpretable Deep Reinforcement Learning

Learning inherently interpretable policies is a central challenge in the path to developing autonomous agents that humans can trust. We argue for the use of policies that are piecewise-linear. We carefully study to what extent they can retain the interpretable properties of linear policies while performing competitively with neural baselines. In particular, we propose the HyperCombinator (HC), a piecewise-linear neural architecture expressing a policy with a controllably small number of sub-policies. Each sub-policy is linear with respect to interpretable features, shedding light on the agent’s decision process without needing an additional explanation model. We evaluate HC policies in control and navigation experiments, visualize the improved interpretability of the agent and highlight its trade-off with performance.
Preliminary identi ﬁ cation of key miRNAs, signaling pathways, and genes associated with Hirschsprung's disease by analysis of tissue microRNA expression pro ﬁ les

Background: Hirschsprung's disease (HSCR) is a congenital gut motility disorder of infants, and if left untreated, it is fatal to the affected infants. This study aimed to identify key microRNAs (miRNAs), signaling pathways and genes involved in the pathogenesis of HSCR. Methods: The miRNA microarray dataset GSE77296 was downloaded. Nine colon tissue samples were available: six from HSCR patients and three matched control samples. Differentially expressed miRNAs (DEMs) were identified after data preprocessing. Target genes of the selected upregulated and downregulated DEMs were predicted. In addition, functional enrichment analyses for the selected DEMs and target genes were conducted. Finally, interaction networks between the DEMs and target genes were constructed. Results: A total of 162 DEMs (73 upregulated and 89 downregulated) were obtained. A total of 2511 DEM-target gene pairs for the 40 selected DEMs were identi ﬁ ed, including 1645 pairs for the upregulated DEMs and 866 pairs for the downregulated DEMs. The upregulated DEM miR-141-3p and down-regulated DEM miR-30a-3p were identi ﬁ ed as key miRNAs by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and network analyses. Besides, KEGG pathway enrichment analysis revealed that pathways in cancer and the mitogen-activated protein kinase (MAPK) signaling pathway were key pathways. The key genes frizzled class receptor 3 ( FZD3 ) and docking protein 6 ( DOK6 ) were obtained through the DEM-target gene interaction networks. Conclusion: Two key miRNAs (miR-141-3p and miR-30a-3p), the MAPK signaling pathway and two key genes ( FZD3 and DOK6 ) were implicated in the pathogenesis of HSCR. World J Pediatr 2017;13(5):489-495
Iridescence untwined: honey bees can separate hue variations in space and time

Iridescence is a phenomenon whereby the hue of a surface changes with viewing or illumination angle. Many animals display irides-cence but it currently remains unclear whether relevant observers process iridescent color signals as a complex collection of colors (spatial variation), or as moving patterns of colors and shapes (temporal variation). This is important as animals may use only the spatial or temporal component of the signal, although this possibility has rarely been considered or tested. Here, we investigated whether honey bees could separate the temporal and spatial components of iridescence by training them to discriminate between iridescent disks and photographic images of the iridescent patterns presented by the disks. Both stimuli therefore contained spatial color variation, but the photographic stimuli do not change in hue with varying angle (no temporal variation). We found that individual bee observers could discriminate the variable patterns of iridescent disks from static photographs during unrewarded tests. Control experiments showed that bees reliably discriminated iridescent disks from control silver disks, showing that bees were processing chromatic cues. These results suggest that honey bees could selectively choose to attend to the temporal component of iridescent signals to make accurate decisions.