Miracle-dz/UniFAR-FTUs huggingface dataset:
H ∞ state-feedback control of bilateral teleoperation systems with asymmetric time-varying delays

In this study, a novel controller synthesis method is proposed for the bilateral teleoperation systems with asymmetric time-varying delays. The main idea of the proposed method is to deal with the control problem for a bilateral teleoperation system under asymmetric time-varying delays as a control problem for a system with multiple input time delays, and then to find the state-feedback control law to stabilise the system with guaranteed H ∞ performance on the defined control output. With intentionally introducing the pretend time delays to the (local) state variables of the master or the slave, the teleoperation controller design problem is converted to a controller synthesis problem for a system with multiple input time delays. Then the state-feedback controllers are designed for both the master and the slave by defining an appropriate Lyapunov–Krasovskii functional candidate and solving linear matrix inequalities. The designed controllers guarantee the closed-loop system stability and system transparency performance in terms of the optimised H ∞ norm on the position and force tracking errors between the master and the slave. At last numerical simulations are used to validate the effectiveness of the proposed method. The results show that the designed controllers can effectively stabilise the present teleoperation system with good transparency performance under time-varying delays.
Zero shot domain adaptation for x-ray baggage scanning

Deep learning based vision models have had significant success recently. However, one of the biggest challenges is to apply the established models to new targets and environments where no samples exist for training. To solve this zero-shot learning problem, we formulated a heterogeneous learning domain adaptation scenario where labeled data from other domains are available for the new target and for some other unrelated classes. We developed an innovative zero-shot domain adaptation (ZSDA) method by implementing end-to-end adversarial training with class-aware alignment and latent space feature transformation. We demonstrated the performance improvements in several applications in comparison with traditional unsupervised domain adaptation (UDA) approach including threat detection in X-ray security screening imagery.
Intra- and interspeaker repetitiveness in Chengdu Mandarin locative variation

Abstract In producing linguistic variation, language users display a tendency to reuse the same variant. This paper compares the empirical properties of different types of repetitiveness in a single case study: locative variation in Chengdu Mandarin. Using conversational data from sociolinguistic interviews, we ask whether within-speaker repetitiveness (persistence) and cross-speaker repetitiveness (convergence) behave similarly with respect to (1) their sensitivity to the linguistic similarity of the prime and target, and (2) their tendency to decline with greater temporal distance between the prime and target. Our results suggest that intraspeaker persistence and interspeaker convergence behave similarly in both respects. We therefore propose that repetitiveness has a common underlying mechanism within and across speakers and encourage future work aimed at testing this hypothesis across other variables and varieties.
A Two-Stage Screw Detection Framework for Automatic Disassembly Using a Reflection Feature Regression Model

For remanufacturing to be more economically attractive, there is a need to develop automatic disassembly and automated visual detection methods. Screw removal is a common step in end-of-life product disassembly for remanufacturing. This paper presents a two-stage detection framework for structurally damaged screws and a linear regression model of reflection features that allows the detection framework to be conducted under uneven illumination conditions. The first stage employs reflection features to extract screws together with the reflection feature regression model. The second stage uses texture features to filter out false areas that have reflection features similar to those of screws. A self-optimisation strategy and weighted fusion are employed to connect the two stages. The detection framework was implemented on a robotic platform designed for disassembling electric vehicle batteries. This method allows screw removal to be conducted automatically in complex disassembly tasks, and the utilisation of the reflection feature and data learning provides new ideas for further research.
Panic Attack, Severe Hypophosphatemia and Rhabdomyolysis in the Setting of a Motor Functional Neurological Disorder

(1) Background: panic attack is often regarded as a benign disorder with variable physical and psychological symptoms. (2) Case Presentation: We here report the case of a 22-year-old patient known for an episode of motor functional neurological disorder a year earlier who presented a panic attack with hyperventilation causing severe hypophosphatemia and rhabdomyolysis, as well as mild tetraparesis. Electrolyte disturbances quickly resolved after phosphate substitution and rehydration. However, clinical signs suggesting a relapse of a motor functional neurological disorder appeared (improved walking with dual tasks). Diagnostic workup, including brain and spinal magnetic resonance imaging, as well as electroneuromyography and genetic testing for hypokalemic periodic paralysis, was unremarkable. Tetraparesis, lack of endurance, and fatigue eventually improved after several months. (3) Conclusions: the present case report highlights the intertwined relationship between a psychiatric disorder, leading to hyperventilation and acute metabolic disturbances, and functional neurological manifestations.
Chemical Composition and Biological Activity of Salvia officinalis L. Essential Oil

In our study, we investigated the chemical composition and cytotoxic activity of essential oils isolated from Dalmatian sage (Salvia officinalis L.) collected along the Adriatic coast of Croatia. Scanning electron microscopy (SEM) was used to examine the morphology of the stem and leaf surfaces. Essential oil excretory glands were detected on both the leaves and stem surfaces. The essential oils were isolated by hydrodistillation, and their chemical composition was determined by gas chromatography and mass spectrometry (GC-MS). Sage essential oils were mixtures of terpene compounds, among which the most common were: α- and β-thujone, camphor, and 1,8-cineol. Cytotoxic activity was tested using MTS assay on multiple cell lines: normal and immortalized fibroblasts (HF77FA and HDF-Tert), immortalized lung line (BEAS-2B), and breast adenocarcinoma (MDA-MB-231). The growth of treated cells was determined relative to control conditions without treatment. The immortalized lung line was the least resistant to the activity of the essential oils, whereas immortalized fibroblasts were the most resistant. Statistical analysis has connected the cytotoxic effect and chemical composition of the studied essential oils. To the best of our knowledge, this work is the first testing of the cytotoxic activity of S. officinalis EO’s on the BEAS-2B, HF77FA, and HDF-Tert cell lines. The presented data on essential oil chemical composition and cytotoxic effect on 4 types of human cells supports pharmacotherapeutic potential this plant is known to have.
Biogeochemical and Physical Assessment of CMIP5 and CMIP6 Ocean Components for the Southwest Pacific Ocean

The biogeochemical (BGC) and physical capabilities of 16 CMIP5 and 16 CMIP6 Earth System models are examined in relation to present day (1976–2005) observational data sets for a region of the southwest Pacific Ocean (SWPAC). A relative ranking scheme enables identification of a “best” model ensemble over SWPAC, with the CMIP6 models having generally better physical representations compared to the CMIP5 set, but the BGC improvements less marked. For the period 2081–2100 using RCP8.5 and SSP585 for CMIP5 and CMIP6, respectively, we find significant surface temperature increases and mixed layer depth reductions compared to present day over SWPAC, and reductions in the macronutrients but increases in surface iron. Surface chlorophyll and zooplankton and integrated primary production are all found to decrease by end of century over SWPAC except for the southernmost waters. Sea surface salinity significantly freshens in Subantarctic Water, whereas the Tasman Sea is becoming saltier. Using our “best” ensemble, depth‐integrated area averaged chlorophyll and zooplankton are found to decrease by 11% and 16%, respectively, compared to present day over SWPAC, emphasizing that these surface decreases are manifest at all depths in the model.
Genome-Wide Screening Identifies Gene AKR1C1 Critical for Resistance to Pirarubicin in Bladder Cancer

Simple Summary Bladder cancer is one of the most common malignant tumors in the urinary system. Pirarubicin (THP) perfusion therapy is an important treatment method for non-muscle-invasive bladder cancer. However, an increasing number of cases of recurrence or progression of bladder cancer caused by THP resistance have been reported. Therefore, we urgently need to find the critical genes that cause THP resistance in bladder cancer. In this study, we obtained the critical gene AKR1C1 that causes resistance of bladder cancer to THP via CRISPR/dCas9 SAM. This study not only verified that AKR1C1 can cause resistance of bladder cancer cells to THP both in in vivo and in vitro, but also found that THP treatment can gradually increase the expression of AKR1C1, thus causing resistance to the drug. In addition, we also found that aspirin, the AKR1C1 inhibitor, and tempol, the ROS scavenger, can effectively overcome the drug resistance caused by AKR1C1. Abstract Non-muscle-invasive bladder cancer (NMIBC) is a common tumor of the urinary system. Given its high rates of recurrence, progression, and drug resistance, NMIBC seriously affects the quality of life and limits the survival time of patients. Pirarubicin (THP) is a bladder infusion chemotherapy drug recommended by the guidelines for NMIBC. Although the widespread use of THP reduces the recurrence rate of NMIBC, 10–50% of patients still suffer from tumor recurrence, which is closely related to tumor resistance to chemotherapy drugs. This study was performed to screen the critical genes causing THP resistance in bladder cancer cell lines by using the CRISPR/dCas9-SAM system. Thus, AKR1C1 was screened. Results showed that the high expression of AKR1C1 could enhance the drug resistance of bladder cancer to THP both in vivo and in vitro. This gene could reduce the levels of 4-hydroxynonenal and reactive oxygen species (ROS) and resist THP-induced apoptosis. However, AKR1C1 did not affect the proliferation, invasion, or migration of the bladder cancer cells. Aspirin, which is an AKR1C1 inhibitor, could help reduce the drug resistance caused by AKR1C1. After receiving THP treatment, the bladder cancer cell lines could upregulate the expression of the AKR1C1 gene through the ROS/KEAP1/NRF2 pathway, leading to resistance to THP treatment. Using tempol, which is an inhibitor of ROS, could prevent the upregulation of AKR1C1 expression.
Entropy Noise Generation and Reduction in a Heated Nozzle Flow

Core noise gained increasing interest concerning the total noise emission of aero-engines. Hereby, direct and indirect combustion noise plays an important role. While direct combustion noise has its origin by unsteady heat release directly in the reaction zone, indirect noise is generated by accelerated fluctuations of entropy or vorticity in the turbine nozzle guide vane (NGV) at the outlet of the combustion chamber. This paper investigates the noise generation of accelerated cold spots through a nozzle structure at the Hot Acoustic Test rig (HAT) at DLR Berlin. The nozzle setup is derived from the geometry of a full scale NGV concerning the flow gradients. The cold spots are produced by injection of air at ambient temperature into the heated mean flow. In a further step a first attempt for entropy noise reduction by bias-flow liners are examined.
Optimal Selection of Weather Stations for Electric Load Forecasting

For the proper planning and operation of any electric power system, it is essential to have a reliable software tool that allows for accurate short-term forecasting of electric power consumption. Temperature is one of the most important drivers of electric energy consumption and selecting the appropriate weather station or combination of weather stations is crucial for improving the forecasting accuracy. In this study, we propose an algorithm to determine the optimal selection of weather stations based on (i) an initial reduction in problem complexity, which drastically decreases the computational cost, and (ii) a posterior incremental search algorithm. The proposed methodology, which identifies the optimal number of weather locations to be used and their specific geographical locations, is exhaustively tested using three insightful case studies using real data from the Spanish mainland electric power grid and two different weather forecast databases, denoting a significant reduction in forecasting errors. The developed method is currently in use by the Spanish transmission system operator (Red Eléctrica de Espa na, REE) to make hourly forecasts.
Role Determination of Impedance Coupling in GCC With DC-Link Virtual Inertia Control

Virtual inertia control (VIC) allows grid-connected converter (GCC) to emulate inertia via the dc-link capacitance. Yet, such a scheme's stability impact revealed by the impedance perspective is often overlooked, resulting in coupling issues between the converter and the grid. This article presents a comprehensive analysis of the effect of the dc-link's VIC on the GCC system. The GCC's small-signal impedance model is first proposed, which reveals a strong impedance coupling between the GCC's d-axis and q-axis elements due to VIC and PLL. Subsequently, the method for the role determination of impedance coupling is proposed to investigate the coupling influencing mechanism on the system. It quantifies the impedance coupling effect on the grid's stability margin. This also allows the critical GCC controllers to be separately designed based on the GCC impedance coupling and noncoupling terms. Facing the strong coupling issue, improved VIC is further proposed to weaken the coupling effect and, thus, broaden the range of available control parameters. Numerical and experimental results are presented to verify the theoretical analysis.
Substellar companions in low-mass eclipsing binaries - NSVS 01286630, NSVS 02502726, and NSVS 07453183

Aims. As part of our long-term observational project we aim to measure very precise mid-eclipse times for low-mass eclipsing binaries, which are needed to accurately determine their period changes. Over two hundred new precise times of minimum light recorded with CCD were obtained for three eclipsing binaries with short orbital periods: NSVS 01286630 ( P = 0 . d 38), NSVS 02502726 (0 . d 56), and NSVS 07453183 (0 . d 37). Methods. O − C diagrams of studied stars were analysed using all reliable timings, and new parameters of the light-time e ﬀ ect were obtained. Results. We derived for the ﬁrst time or improved the very short orbital periods of third bodies of between one and seven years for all measured low-mass systems. We calculated that the lowest masses of the third components are between those of red and brown dwarfs. The multiplicity of these systems also plays an important role in the precise determination of their physical parameters. This research is part of an ongoing collaboration between professional astronomers and the Czech Astronomical Society, Variable Star and Exoplanet Section.
CNLRA: Critical Node and Link Reconnect Algorithm for Wireless ADHOC Networks using Graph Theory

Maintaining connectivity is a prime concern in most of the applications in wireless adhoc networks. Failure of a node may partition the network into disjoint segments and may hinder the data communication. Timely identification of such nodes and rapid recovery procedures are of great importance for survivability. In this paper we proposed a graph theoretic based Critical Node Reconnect Algorithm (CNRA) and Critical Link Reconnect Algorithm (CLRA) for connectivity maintenance by endowing with a new link. Through simulation we have shown the efficiency of our algorithm. Compared to similar work, our proposed algorithm has less overhead and delay. The packet delivery ratio and the throughput are increased.
The last stages of star formation in the dwarf spheroidal galaxy Sextans.

This thesis is anchored in the research of better understanding of the chemical evolution of galaxies. Many dwarf spheroidal galaxies (dSph) are orbiting the Milky Way displaying various star formation histories. The formation of these dwarf galaxies and the drivers of their evolution are still not well understood. We studied in detail one of them, Sextans, a low mass dSph composed of an old population. 90% of Sextans stars were formed 11-14 Gyr ago (Lee et al. 2009). Battaglia et al. (2011) show the presence of a radial metallicity gradient in Sextans considering observation based on intermediate resolution spectroscopy until the tidal radius. For a projected radius R 0.8 deg all stars are metal-poor [Fe/H] < -2.2 dex. Due to its distance and its low surface brightness high resolution spectra are required to obtain accurate abundances. Up to recently only 14 Sextans stars have been observed in high resolution spectroscopy (Shetrone et al. 2001; Aoki et al. 2009; Tafelmeyer et al. 2010; Honda et al. 2011) but in majority they were focused only on extremely metal-poor stars. In order to understand the chemical evolution of Sextans we needed to study a statistically significant sample of stars covering a larger metallicity range. This has been done in this work based on the largest high resolution spectroscopic sample of 87 red giant branch stars ever obtained in such low mass dwarf spheroidal galaxies. Our sample of stars located in the center of Sextans displays a large metallicity distribution ranging from -1.0 dex to -3.5 dex. We derived abundances of 10 elements : 3 alpha-elements (Mg, Ca and Ti), 5 iron-peak elements (Sc, Cr,Mn, Co and Ni) and 2 neutron-capture elements (Ba and Eu). Combining the results we had the first picture of the chemical evolution of Sextans. From [alpha/Fe] distribution reflecting the ratio between supernovae [SNe II/SNe Ia], we found that the domination of SNeIa in chemical evolution occurred around [Fe/H] = -2.0 dex. A lower knee than for Fornax and Sculptor suggests that star formation was less efficient in Sextans in agreement with their respective estimated mass. The absence of intrinsic scatter in [alpha/Fe] showed that in the center of Sextans the interstellar medium has been homogeneously enriched through star formation. Some hypothesis like tidal interactions with the Milky Way could explain this abundance homogeneity in the center of the galaxy and the metallicity gradient toward the outskirts. Abundances in iron-peak elements and neutron-capture elements give new observational constraints for a better understanding of the various nucleosynthesis sources of these elements.
An extension of the factoring likelihood approach for non-monotone missing data

We address the problem of parameter estimation in multivariate distributions under ignorable non-monotone missing data. The factoring likelihood method for monotone missing data, termed by Rubin (1974), is extended to a more general case of non-monotone missing data. The proposed method is equivalent to the Newton-Raphson method for the observed likelihood, but avoids the burden of computing the flrst and the second partial derivatives of the observed likelihood. Instead, the maximum likelihood estimates and their information matrices for each partition of the data set are computed separately and combined naturally using the generalized least squares method. A numerical example is presented to illustrate the method. A Monte-Carlo experiment compares the proposed method with the EM method.
On the genesis of the Haumea system

This research was partially supported by Spanish grants AYA2011-06202-C02-01 (JLO) and AYA2011-06202-C02-02 (ACB). RGH gratefully acknowledges financial support by CONICET through PIP 114-201101-00358 and Junta de Andalucia 2012-FQM1776.
Learning engineering: What it is, why I’m involved, and why I think more of you should be

In the article I am responding to (Lee, 2023, this issue and volume), Victor Lee makes the claim that because learning sciences is already an applied science, we do not need another field called Learning Engineering. And because there are currently so many disconnected communities of people writing about learning engineering and calling themselves learning engineers, and many of those people have been advocating for a far less expansive view of what learning entails than the learning sciences community proposes, he wonders whether connecting the learning sciences and learning engineering will diminish the learning sciences. These concerns, I believe, are unfounded; instead, I believe, as I’ve been preaching for the past decade (Kolodner, ISLS keynote, 2012), that we should be more worried that what we are learning in our research is not better appreciated and known by others outside of the learning sciences community. What we have learned about how to support learning and the work we’ve done toward showing what’s possible to implement in schools, should be, but is still little present, in the imagination of policy makers, teachers, parents, administrators, and the designers of curriculum and learning technologies. One reason for that is that too many in the education, academic, and policy “establishments” value lab-based and large-scale experimental research over what we do. Another reason is that we aren’t involved enough in participating in activities that would challenge establishment views. Yet another is that we (the learning sciences community) are not preparing and encouraging our students to take positions in organizations that are designing the newest learning technologies and curriculum products, or in organizations that are helping educators and educational organizations refine their pedagogical approaches, cultures, and social practices.
The Fibonacci Primes Under Modulo 4

The research on prime numbers is an interesting topic in Analytic Number Theory. The Fibonacci sequence is one of the most popular sequences in mathematics. In this paper, we will discuss the prime numbers of the Fibonacci sequence, which we call Fibonacci primes. The goal of this paper is to prove that starting with F5 = 5 , all the Fibonacci primes p are satisfied with p o1 mod4 ( ) , on the basis of the Pythagorean theorem.
Social preferences and sales performance

We use an incentivized experimental game to uncover heterogeneity in social preferences among salespeople in a large Austrian retail chain. Our results show that the majority of agents take the welfare of others into account but a significant fraction reveal selfish behavior. Matching individual behavior in the game with firm data on sales performance shows that agents with social preferences achieve a significantly higher revenue per customer. However, at the same time, they achieve fewer sales per day. Both effects offset each other, so that the overall association with total sales revenue becomes insignificant. Our findings highlight the nuanced role of selfish versus social preferences in sales contexts with important implications for economic research.