Miracle-dz/UniFAR-FTUs huggingface dataset:
Market‐based control for linear structures using symplectic theory

Market‐based control (MBC) theory is a type of analogy approach between the behaviors of the free economy market and system control area. The accuracy of the algorithm is mainly determined by the supply and demand models, which are determined by the internal model parameters. In the present study, a deterministic method is proposed to improve the parameters in the models based on symplectic theory by giving the index function and introducing the dual vector so that the dynamic equation is transformed from the Lagrange to Hamilton system. In contrast to the traditional method, symplectic theory describes parameters from a new perspective without trial values, and the model parameters are only related to their own characteristics of the structural vibration system to facilitate practical application. The MBC stability is also deduced based on symplectic theory, which can be applied not only to the time‐invariant MBC system but also to the time‐varying system. To verify the effectiveness of the designed MBC controller, the control strategy is used for a 3‐story structure and a 20‐story structure. The numerical example shows that the deduction of the MBC strategy is effective.
Design of Data-driven Multi-agent Systems

This study discusses the consensus control of multi-agent systems. The consensus can be achieved when the closed-loop system of multi-agent systems is stable. In conventional model-based methods, since the controller is designed based on the dynamic characteristics of the agents, models of the agents must be used. On the other hand, this study examines data-driven design of multi-agent systems. In the proposed method, the controller of a multi-agent system is designed directly from the control data, where the controller structure is fixed. The usefulness of the proposed method is shown through numerical examples.
Predicting a robot’s position on a football field by training a machine learning algorithm on artificially generated data

Training neural networks for robotics with real-world data can be a timely and potentially expensive task. However, many real-world environments can also be simulated inside of modern 3D rendering engines, with Unity being a great and versatile example. With the use of these virtual simulations, machine learning applications can be trained with a greater number of simulated edge-cases together with a reduction in costs. This paper demonstrates the potential of using virtual environments by training a model that can determine the position of a robot on a football field. Furthermore, the virtual environment can simulate many different lighting conditions, which are difficult to capture in a dataset that only contains real-world data. This virtually generated dataset will then be used to train a neural network that can determine the robots position on the football field. The concept and benefits of generating a bird’s eye view model in order to predict a location on the football field will also be explored. Using virtual environments to train neural networks to be used with robotics is not a new concept. Frolov et al. [1] proposes a pipeline that can generate virtual images in order to train convolutional neural networks. This thesis proves that using virtually generated datasets can improve the accuracy of models, specifically models that classify uncommon objects that are difficult to capture in large quantities in real-world datasets. The results of this thesis show that a machine learning model can be fitted on artificially generated data in order to predict a location on a football field with a two time improvement over making random guesses.
‘We will call you madamii’: a researcher’s journey from being viewed as a madame to a madamii by children in a rural village in India

ABSTRACT Researchers who wish to become insiders to children’s cultural worlds need to genuinely engage with the difference in social power between them and their participants. Most published accounts of adult positionality have been provided by those who have explored children’s school practices. The ethnography discussed in this paper focused on the home and school literacy practices of children in a rural village in India. Cognisant of the unequal teacher-student relationships in this part of the world, I positioned myself as a least-teacher which, I argue, presents a cultural approximant for the least-adult role extensively discussed in literature. The role enabled the children to view me differently from their teachers – as a madamii. In this paper, I discuss its various facets with the twin focus of examining the efficacy of the role for future research and its affordances for the vision of a teacher provided by Indian policy documents.
The Relationship between Teachers’ Belief Systems, Creativity and the Use of Technology-based English Teaching

This study intends to find out teachers’ belief systems, its’ relevant factors and teachers’ creativity which may influence the use of technology for teaching of English at undergraduate level in Islamabad, Pakistan. The study highlights certain problems faced by teachers under belief system and the relevant factors in their implementation of Information and Communication Technology (ICT) for teaching of English inside classrooms. Data was collected through a questionnaire questionnaire based on Decomposed Theory of Planned Behavior (DTPB) from 31 ESL teachers teaching at different colleges in the capital of Pakistan [Islamabad] to know their perceptions, opinions and ideas regarding barriers confronted by them in the implementation of technology for teaching English as Second Language (ESL). Data is analyzed with the help of SPSS 22. The findings of the study revealed internal and external barriers such as beliefs, attitudes, behaviors, subjective norms, professional development, resources, and cross culturalism faced by teachers for incorporating innovation and creativity in their teaching practices through the use of technology in Pakistan. The study concludes with recommendations and suggestions for further research.
Experimental Liver Cirrhosis Inhibits Restenosis after Balloon Angioplasty

The effect of liver cirrhosis on vascular remodeling in vivo remains unknown. Therefore, this study investigates the influence of cholestatic liver cirrhosis on carotid arterial remodeling. A total of 79 male Sprague Dawley rats underwent bile duct ligation (cirrhotic group) or sham surgery (control group) and 28 days later left carotid artery balloon dilatation; 3, 7, 14 and 28 days after balloon dilatation, the rats were euthanized and carotid arteries were harvested. Histological sections were planimetrized, cell counts determined, and systemic inflammatory parameters measured. Up to day 14 after balloon dilatation, both groups showed a comparable increase in neointima area and degree of stenosis. By day 28, however, both values were significantly lower in the cirrhotic group (% stenosis: 20 ± 8 vs. 42 ± 10, p = 0.010; neointimal area [mm2]: 0.064 ± 0.025 vs. 0.138 ± 0.025, p = 0.024). Simultaneously, cell density in the neointima (p = 0.034) and inflammatory parameters were significantly higher in cirrhotic rats. This study demonstrates that cholestatic liver cirrhosis in rats substantially increases neointimal cell consolidation between days 14 and 28. Thereby, consolidation proved important for the degree of stenosis. This may suggest that patients with cholestatic cirrhosis are at lower risk for restenosis after coronary intervention.
Respiratory Muscle Function and Exercise Performance in Adult Patients with Fontan Circulation

At rest, a good Fontan circulation can provide a normal cardiac output (CO). However, as a consequence of its unique hemodynamic nature, the limitations of the Fontan circuit are exposed during exercise. We aimed to provide a comprehensive assessment of the pathophysiology of exercise in adult Fontan patients (FPs) and identify factors limiting their functional capacity (FC). In a single-center study conducted in 37 FPs aged ≥16 years and 19 healthy-controls (HCs) who underwent CPET on a cycle ergometer in February and March 2022, the mean peakVO2 was 21 ± 5.4 mL/kg/min, which was 55% of the predicted value. Morphologically, the left single ventricle showed a higher peakVO2% predicted value (57.4 ± 14.4% vs. 43.4 ± 8.1%, p = 0.045). The factors associated with low peakVO2 values were an early flattened or descending O2 pulse at maximal exertion (52 ± 14% vs. 62 ± 12.5, p = 0.04 and 47.6 ± 9% vs. 60 ± 14, p = 0.018, respectively) and chronotropic insufficiency (53 ± 12% vs. 69.8 ± 20%, p = 0.008). The OUES was found to be a useful parameter to assess the FC in FPs in maximal and submaximal exercise testing. A strong positive correlation was observed between the %OUES and peakVO2%predicted (r = 0.726, p > 0.001). The lung function was impaired in the FPs, mostly with a mild restrictive pattern (56.8%). The FPs showed lower inspiratory muscle strength compared to the HCs but it was not statistically associated with either the peakVO2 or VE/VCO2 slope. Regular intense physical activity improves one’s FC. Although FPs have inspiratory muscle weakness, its impact on their FC is unclear. The peakVO2% predicted grew progressively higher as the level of physical activity increased (low level 49.5 ± 14%, moderate level 55 ± 12%, intense level 69 ± 20%).
Composition followed by differentiation between weighted Bergman-Nevanlinna spaces

In this paper, we characterize boundedness of CID acting on weighted Bergman-Nevanlinna spaces, where CI is the composition operator and D is the differentiation operator. We also provide a necessary condition and a sufficient condition for CID to be compact on weighted BergmanNevanlinna spaces.
Cytokine profile characterization of naïve patients with psoriasis and psoriatic arthritis: implications for a pathogenic disease continuum

Background The idea of psoriatic disease continuum has been progressively prompted based on the advances of the knowledge about the pathogenic steps underpinning the occurrence of psoriasis (PSO) and psoriatic arthritis (PSA). To evaluate biomolecules (inflammatory cytokines, inflammatory chemokines, cell adhesion and cellular mediators) in naïve patients with PSO, PSA with PSO, and PSA sine PSO. To stratify the results considering the presence of psoriatic nail involvement, extensive skin disease and obesity evaluating all involved patients. Methods By multiplex technology, 20 serum biomolecules were assessed with the inclusion of pro-inflammatory cytokines (GM-CSF, IFN-γ, IL-1α, IL-1β, IL-6, IL-8, IL-12p70, IL-17A, IL-23, TNF), anti-inflammatory cytokines (IFN-α, IL-4, IL-10, IL-13), inflammatory chemokines (IP-10, MCP-1, MIP-1α, MIP-1β), cell adhesion and cellular mediators (ICAM-1, E-selectin, P-selectin). The assessment of possible statistical differences between the means of the three groups was performed by One-Way ANOVA. In addition, by non-parametric T-tests, we stratified the results according to selected clinical characteristics (psoriatic nail involvement, PASI ≥ 10, BMI ≥ 30). Results In 80 assessed naïve patients, patients with PSO showed significant increases of E-selectin (p=0.021) and IL-8 (0.041) than other groups. In patients with PSA with PSO, significant higher levels of ICAM-1 were observed (p=0.009) than other groups. We did not observe further differences comparing pro-inflammatory and anti-inflammatory cytokines, inflammatory chemokines, and cell adhesion and cellular mediators in patients with PSO, PSA with PSO, and PSA sine PSO. Patients with psoriatic onychopathy showed significant increased levels of ICAM-1 (p=0.010) and IP-10 (0.030) than others. In patients with PASI ≥ 10, significantly enhanced values of IL-8 (p=0.004), TNF (p=0.013), E-selectin (p=0.004), MIP-1α (p=0.003), and MIP-1β (p=0.039). In patients with BMI ≥ 30, significantly higher levels of E-selectin were pointed out (p=0.035) than others. Conclusion Our findings may suggest that a similar cytokine profile may characterize naïve patients with PSO, PSA with PSO, and PSA sine PSO, reinforcing the concept of psoriatic disease continuum. However, some differences may be also shown, underlying possible pathogenic differences and leading to the clinical heterogeneity of these patients.
CANDU pressure tube leak detection by annulus gas dew point measurement: a critical review

Abstract In the event of a pressure tube leak from a small through-wall crack during CANDU reactor operations, there is a regulatory requirement – referred to as Leak Before Break (LBB) – for the licensee to demonstrate that there will be sufficient time for the leak to be detected and the reactor shut down before the crack grows to the critical size for fast-uncontrolled rupture. In all currently operating CANDU reactors, worldwide, this LBB requirement is met via continuous dew point measurements of the CO2 gas circulating in the reactor's Annulus Gas System (AGS). In this paper the historical development and current status of this leak detection capability is reviewed and the use of moisture injection tests as a verification procedure is critiqued. It is concluded that these tests do not represent AGS conditions that are to be expected in the event of a real pressure tube leak.
Planetary nebulae as kinematic tracers of galaxy halos

Abstract The kinematics and dynamical properties of galaxy stellar halos are difficult to measure, given the faint surface brightness that characterizes these regions. Gas-rich systems such as spiral galaxies can be probed using the radio Hi emission. Early-type galaxies contain less gas, therefore alternative kinematic tracers need to be used. Planetary Nebulae (PNe) can be easily detected far out in the halo thanks to their bright [O iii] emission at 5007 Å. It is therefore possible to map the halo kinematics also in early-type galaxies, typically out to 5 effective radii or beyond. Thanks to the recent spectroscopic surveys targeting extra-galactic PNe, we can now rely on few tens of galaxies where the kinematics of the stellar halos are measured. I will discuss the most important results: (a) the relation of the stellar surface brightness and the PNe number density; (b) the velocity and velocity dispersion two-dimensional fields; (c) the radial profiles of angular momentum; and (d) the relation between the derived kinematics physical properties of the host galaxies.
A Miniaturized Archimedean Screw Pump for High-Viscosity Fluid Pumping in Microfluidics

Microfluidic devices have revolutionized the field of lab-on-a-chip by enabling precise manipulation of small fluid volumes for various biomedical applications. However, most existing microfluidic pumps struggle to handle high-viscosity fluids, limiting their applicability in certain areas that involve bioanalysis and on-chip sample processing. In this paper, the design and fabrication of a miniaturized Archimedean screw pump for pumping high-viscosity fluids within microfluidic channels are presented. The pump was 3D-printed and operated vertically, allowing for continuous and directional fluid pumping. The pump’s capabilities were demonstrated by successfully pumping polyethylene glycol (PEG) solutions that are over 100 times more viscous than water using a basic mini-DC motor. Efficient fluid manipulation at low voltages was achieved by the pump, making it suitable for point-of-care and field applications. The flow rates of water were characterized, and the effect of different screw pitch lengths on the flow rate was investigated. Additionally, the pump’s capacity for pumping high-viscosity fluids was demonstrated by testing it with PEG solutions of increasing viscosity. The microfluidic pump’s simple fabrication and easy operation position it as a promising candidate for lab-on-a-chip applications involving high-viscosity fluids.
Local Rejection Sampling with Soft Filters

We study a new LLL-like framework for rejection sampling, which naturally generalizes the variable-framework for the Lovász local lemma (LLL) and the LLL-based Partial Rejection Sampling of Guo, Jerrum and Liu [STOC’17]. In this new framework, the occurrence of a bad event is biased by the current evaluation of variables, rather than being determined by them as in the standard setting of LLL. Such generalization allows us to model rejection samplings with soft filters. We give a generic algorithm, called Local Rejection Sampling, for sampling from the correct distribution arising from the rejection rules. For rejection sampling with soft filters, this algorithm only updates variables which are local to the violated events in the dependency graph, making it suitable for sampling with local computation or on dynamic input. As a nontrivial consequence, for any distribution defined by local constraints, if a decay of correlation property known as the strong spatial mixing holds, there is a distributed zero-error Las Vegas algorithm for sampling precisely from this distribution within O(log n) rounds. This research is supported by the National Key R&D Program of China 2018YFB1003202 and the National Science Foundation of China under Grant Nos. 61722207 and 61672275. State Key Laboratory for Novel Software Technology, Nanjing University. Emails: fengwm@smail.nju.edu.cn, yahui.liu@smail.nju.edu.cn, yinyt@nju.edu.cn.
Nonautonomous functional equations and nonlinear evolution operators

L’accès aux archives de la revue « Rendiconti del Seminario Matematico della Università di Padova » (http://rendiconti.math.unipd.it/) implique l’accord avec les conditions générales d’utilisation (http://www.numdam.org/conditions). Toute utilisation commerciale ou impression systématique est constitutive d’une infraction pénale. Toute copie ou impression de ce fichier doit contenir la présente mention de copyright.
Trends, Variability, and Seasonality of Maximum Annual Daily Precipitation in the Upper Vistula Basin, Poland

The aim of this study was to detect trends in maximum annual daily precipitation in the Upper Vistula Basin. We analyzed data from 51 weather stations between 1971 and 2014. Then we used the Mann–Kendall test to detect monotonical trends of the precipitation for three significance levels: 1, 5, and 10%. Our analysis of weather conditions helped us describe the mechanism behind the formation of maximum annual daily precipitation. To analyze precipitation seasonality, we also used Colwell indices. Our study identified a significant trend of the highest daily precipitation for the assumed significance levels (0.01, 0.05, 0.1) for 22% of the investigated weather stations at different elevations. The significant trends found were positive and an increase in precipitation is expected. From 1971 to 2014, the maximum daily total precipitation most often occurred in the summer half-year, i.e., from May until September. These months included a total of 88% of days with the highest daily precipitation. The predictability index for the highest total precipitation within the area was high and exceeded 5%. It was markedly affected by the coefficient of constancy (C) and to a lesser degree by the seasonality index (M). Our analysis demonstrated a convergence of the Colwell indices and frequency of cyclonic situation and, therefore, confirmed their usability in the analysis of precipitation seasonality.
Post-Monsoon Season Precipitation Reduction over South Asia: Impacts of Anthropogenic Aerosols and Irrigation

A significant declining trend of post-monsoon season precipitation in South Asia is observed between 2000–2014. Two major anthropogenic climate change drivers, aerosols and irrigation, have been steadily increasing during this period. The impacts of their regional and seasonal forcings on the post-monsoon precipitation reduction is investigated in this study through using idealized global climate simulations. The increased post-monsoon aerosol loadings lead to surface cooling downwind of the source areas by reduced surface shortwave flux. The addition of post-monsoon irrigation induces a stronger temperature decrease mainly around the irrigation hotspots by enhanced evaporation. Precipitation over West and North India is reduced post-monsoon by either aerosol or irrigation, which is mainly contributed by the anomalous subsidence. With concurrent forcings, the surface cooling and precipitation decrease are stronger and more extended spatially than the response to the separate forcing, with nonlinear amplification in surface cooling, but nonlinear damping in precipitation reduction. The anomalous vertical motion accelerates the transition of the regional meridional circulation, and hence the earlier withdrawal of the summer monsoon, which is consistent with the observed signals. The current results highlight the importance of including anthropogenic aerosol and irrigation effects in present and future climate simulations over South Asia.
Simulation Tools for Urban Search and Rescue Robotics

Real world experiments are critical for validating performance of new concepts and algorithms in robotics field. Yet, experiments tend to be too expensive in terms of time and resources of a research team. Moreover, it is not feasible to conduct thousands of complex experiments with a physical robot in a real environment. To check new ideas, preliminary evaluate new algorithms and interaction protocols, on first stages of a research project it is reasonable to start within a simulation. To produce relevant results, a simulator should provide adequate models of robots and environments with realistic physical properties. This paper presents an overview of our experience in using robot operating system (ROS) with Gazebo and Webots simulators for urban search and rescue robotics projects and considers constructing new models of mobile robots and complicated environments, algorithm validation and comparative analysis.
A Wasserstein Generative Adversarial Network–Gradient Penalty-Based Model with Imbalanced Data Enhancement for Network Intrusion Detection

In today’s network intrusion detection systems (NIDS), certain types of network attack packets are sparse compared to regular network packets, making them challenging to collect, and resulting in significant data imbalances in public NIDS datasets. With respect to attack types with rare data, it is difficult to classify them, even by using various algorithms such as machine learning and deep learning. To address this issue, this study proposes a data augmentation technique based on the WGAN-GP model to enhance the recognition accuracy of sparse attacks in network intrusion detection. The enhanced performance of the WGAN-GP model on sparse attack classes is validated by evaluating three sparse data generation methods, namely Gaussian noise, WGAN-GP, and SMOTE, using the NSL-KDD dataset. Additionally, machine learning algorithms, including KNN, SVM, random forest, and XGBoost, as well as neural network models such as multilayer perceptual neural networks (MLP) and convolutional neural networks (CNN), are applied to classify the enhanced NSL-KDD dataset. Experimental results revealed that the WGAN-GP generation model is the most effective for detecting sparse data probes. Furthermore, a two-stage fine-tuning algorithm based on the WGAN-GP model is developed, fine-tuning the classification algorithms and model parameters to optimize the recognition accuracy of the sparse data probes. The final experimental results demonstrate that the MLP classifier significantly increases the accuracy rate from 74% to 80% after fine tuning, surpassing all other classifiers. The proposed method exhibits a 10%, 7%, and 13% improvement over untuned Gaussian noise enhancement, untuned SMOTE enhancement, and no enhancement.