Miracle-dz/UniFAR-FTUs huggingface dataset:
Ni self-diffusion in refractory Al-Ni melts

This work presents investigations on the Ni self-diffusion coefficient in Al-Ni melts forming the technological relevant intermetallic phases Al50Ni50 and Al25Ni75 by quasielastic neutron scattering. We found that the Ni self-diffusivity at constant temperature is nearly independent of the composition within the composition range between 0 and 50 at. % Al. This may be a result of the small composition dependence of the atomic volume observed in the same range of composition.
The perspectives and pedagogies of middle school social justice educators

Abstract This study presents the perspectives and pedagogical practices of teachers who self-identify as social justice educators. Interviews with these social justice educators, who teach in large, diverse, metropolitan school districts, show that they create equitable spaces for their students. An analysis of the interview data concerning their beliefs and the ways that they describe their engagement with culturally and linguistically diverse learners showed that the practices of these social justice educators center students’ perspectives, propose culturally sustaining choices, provide access to multicultural resources, and offer a space for counternarratives and revisionism in their classrooms.
Nanomechanical properties of dentin treated with a CO2 laser for potential caries inhibition

The effect of pulsed CO2-laser treatments on the microstructure and nanomechanical properties was studied using atomic force microscopy and nanoindentation. The microstructure and roughness of dentin specimens treated by a 9.3 μm CO2 laser at fluences of 0.5; 0.75; 1.0; and 1.5 J/cm2 were evaluated and the elastic modulus and hardness before and after a nine days demin/remin application for laser treatments at 0.75 and 1.5 J/cm2 were determined. The hypothesis that CO2-laser-treatments reduce or inhibit the demineralization process was tested. Surface cracks were observed at fluences of 0.75 J/cm2 and higher. Surface roughness increased strongly after laser irradiation and was about 10 times higher at maximum fluence. Mechanical properties profiles from the laser treated surface to sound dentin showed increased modulus and hardness values at dentin surfaces treated, indicating removal of organic phases and reinforcement of the tissue by increased mineral content. Mechanical properties decreased after demin/remin application in all groups and the hardened surface layer disappeared for samples treated at 0.75 J/cm2. While increased properties were still observed in the laser affected surface zone for treatments at 1.5 J/cm2, demineralization was severe underneath these layers as indicated by a sharp drop in properties. The depth of demineralization was slightly decreased in the laser-treated group compared to the untreated controls. We conclude that CO2-laser treatments produce dentin surfaces with increased nanomechanical properties. These surface layers do not, however, provide protection against demineralization due to surface cracking and possible delamination. Moreover, the surface cracks induced by the laser-irradiation raise concerns about a clinical potential for caries inhibition in dentin.
A new controller design for manipulators using the theory of variable structure systems

A controller design for manipulators using the theory of variable-structure systems (VSS) is presented to deal with the set-point regulation problem. The major obstacle of VSS vector control with strong dynamic coupling is overcome for a class of systems with positive symmetric inertia matrices. Parameter variations can easily be considered in the design methodology, which is readily extendable to a higher number of links. The problem of chattering is solved by the introduction of sliding sectors. >
On the suppression of turbulence by a uniform magnetic field

The suppression of initially isotropic turbulence by the sudden application of a uniform magnetic field is considered. The problem is characterized by three dimensionless numbers, a Reynolds number R, a magnetic Reynolds number Rm and a magnetic interaction parameter N (for definitions, see equations (1.2) and (1.4)). It is supposed that R [Gt ] 1, Rm [Lt ] 1 and N [Gt ] 1. There are two important time scales, ta a time characteristic of magnetic suppression, and t0 = Ntd, the ‘turn-over’ time of the turbulent energy-containing eddies. For 0 < t [Lt ] t0 the response of the energy-containing components of the turbulence to the applied field is linear and the time dependence of the kinetic energy density K(t) and magnetic energy density M(t) are analysed. There are essentially two distinct contributions to each from two domains of wave-number space D1 and D2 (defined in figure 2). In D1 the response is severely anisotropic, while in D2 it is nearly isotropic. The relative importance of the contributions K1(t) (from D1) and K2(t) (from D2) to K(t) depends on the value of the Lundquist number S = (NRm)½. If S [Lt ] 1, then K1(t) dominates for all t [lsim ] t0 and K(t) ∝ t−½ for td [Lt ] t [Lt ] t0. If 1 [Lt ] S [Lt ] R−2m, then a changeover in the dominant contribution occurs when t = O(S½Rm) t0. Analogous results are obtained for the magnetic energy density.
NanopoReaTA: a user-friendly tool for nanopore-seq real-time transcriptional analysis

Summary Oxford Nanopore Technologies’ (ONT) sequencing platform offers an excellent opportunity to perform real-time analysis during sequencing. This feature allows for early insights into experimental data and accelerates a potential decision-making process for further analysis, which can be particularly relevant in the clinical context. Although some tools for the real-time analysis of DNA-sequencing data already exist, there is currently no application available for differential transcriptome data analysis designed for scientists or physicians with limited bioinformatics knowledge. Here we introduce NanopoReaTA, a user-friendly real-time analysis toolbox for RNA sequencing data from ONT. Sequencing results from a running or finished experiment are processed through an R Shiny-based graphical user interface (GUI) with an integrated Nextflow pipeline for whole transcriptome or gene-specific analyses. NanopoReaTA provides visual snapshots of a sequencing run in progress, thus enabling interactive sequencing and rapid decision-making that could also be applied to clinical cases. Availability https://github.com/AnWiercze/NanopoReaTA Contact buttamer@uni-mainz.de and sugerber@uni-mainz.de
Amphetamine disrupts dopamine axon growth in adolescence by a sex-specific mechanism in mice

Initiating drug use during adolescence increases the risk of developing addiction and psychiatric disorders later in life, with long-term outcomes varying according to sex and exact timing of use. Even though most individuals begin experimenting with drugs of abuse in adolescence, to date, the cellular and molecular underpinnings explaining differential sensitivity to detrimental drug effects remain unknown. The Netrin-1/DCC guidance cue system plays a critical role in the adolescent development of mesocorticolimbic dopamine circuitry, segregating the cortical and limbic pathways. Adolescent experiences, including exposure to drugs of abuse, can regulate Dcc expression in male mice, placing Netrin-1/DCC signaling as a potential molecular link between experience and enduring changes to circuitry and behavior. Here we show that exposure to a recreational-like regimen of amphetamine (AMPH) in adolescence induces sex- and age-specific alterations in Dcc expression in the ventral tegmental area. Female mice are protected against the deleterious long-term effects of AMPH-induced Dcc regulation by compensatory changes in the expression of its binding partner, Netrin-1. AMPH induces targeting errors in mesolimbic dopamine axons and triggers their ectopic growth to the prefrontal cortex, only in early-adolescent male mice, underlying a male-specific vulnerability to its enduring cognitive effects. Upregulating DCC receptor expression in dopamine neurons in adolescent males using a neuron-optimized CRISPR/dCas9 Activation System induces female-like protection against the persistent effects of AMPH in early adolescence on inhibitory control. Netrin-1/DCC signaling is therefore a molecular switch which can be differentially regulated in response to the same experience as function of age and sex of the individual, leading to divergent long-term outcomes associated with vulnerable or resilient phenotypes.
Jaccard dissimilarity in stochastic community models based on the species-independence assumption

Understanding how the spatial variation in species composition (beta-diversity) varies with biotic and abiotic conditions is one of the ultimate goals in biology. Theory predicts that beta-diversity is a consequence of two factors, species-level differences (defined as the variations among species in the probabilities that species are present in the landscape) and spatial heterogeneity (defined as the difference, between two sites, in the probabilities with which species are present). At present, however, the importance of each factor is unclear. Here, we take a probabilistic and combinatorial approach to examine the effects of species differences and spatial heterogeneity on the degree to which species assemblages in two spatial locations differ in species compositions. We first derived analytical and approximation formulae of the expectation and variance of the pairwise beta-diversity, based on the assumption that the presence probabilities of species are independent of each other. Though it seems intuitive that greater species differences leads to greater beta-diversity, our methods predict that the reverse is likely to occur under some circumstances; strikingly, when space is homogeneous, beta-diversity decreases with increasing species differences. This prediction suggests that policy making for increasing species traits-variation would, without adequately managing environmental heterogeneity, induce biotic homogeneization, resulting in undesired outcomes. Second, we illustrate our method using data from five woodpecker species in Switzerland, showing that the woodpecker species’ joint distributions change considerably with time, and also that such changes are basically explained by the changes in the incidences of some of the species. The new framework can improve our understanding of how pairwise beta-diversity responds to species differences and spatial heterogeneity.
The MOV10 RNA helicase is a dosage-dependent host restriction factor for LINE1 retrotransposition in mice

Transposable elements constitute nearly half of the mammalian genome and play important roles in genome evolution. While a multitude of both transcriptional and post-transcriptional mechanisms exist to silence transposable elements, control of transposition in vivo remains poorly understood. MOV10, an RNA helicase, is a potent inhibitor of mobilization of retrotransposons and retroviruses in cell culture assays. Here we report that MOV10 restricts LINE1 retrotransposition in mice. Although MOV10 is broadly expressed, its loss causes only incomplete penetrance of embryonic lethality, and the surviving MOV10-deficient mice are healthy and fertile. Biochemically, MOV10 forms a complex with UPF1, a key component of the nonsense-mediated mRNA decay pathway, and primarily binds to the 3’UTR of somatically expressed transcripts in testis. Consequently, loss of MOV10 results in an altered transcriptome and a modest upregulation of two LINE1 families in testis. Analyses using a LINE1 reporter transgene reveal that loss of MOV10 leads to increased LINE1 retrotransposition in somatic and reproductive tissues from both embryos and adult mice. Moreover, the degree of LINE1 retrotransposition inhibition is dependent on the Mov10 gene dosage. Furthermore, MOV10 deficiency reduces reproductive fitness over successive generations. Our findings demonstrate that MOV10 attenuates LINE1 retrotransposition in a dosage-dependent manner in mice. Author summary Transposable elements (TEs), including L1 and SINEs, are abundant in the genome and play important roles in evolution, development, and diseases. While TEs propagate in individuals and across generations, the host organism needs to suppress them, resulting in an ongoing arms race between TEs and the host genome. L1, a retrotransposon, accounts for about 17% of the mammalian genome. L1 encodes two proteins, which bind to the L1 transcript to form L1 ribonucleoprotein particles. L1 proliferates in the genome via retrotransposition. A multitude of transcriptional and post-transcriptional mechanisms exist to suppress TEs, however, retrotransposition of TEs remains poorly understood. L1 ribonucleoprotein particles are associated with a large number of host proteins, one of which is the MOV10 RNA helicase. MOV10 exhibits anti-viral activities against retroviruses such as HIV-1. In cultured cells, MOV10 is a potent inhibitor of retrotransposition of L1, SINEs, and IAP. Although MOV10 is expressed in a broad range of tissues, loss of MOV10 causes only incomplete penetrance of embryonic lethality. The viable MOV10-deficient mice are grossly normal and fertile. Importantly, analyses using a L1 transgene reporter reveal that MOV10 inhibits L1 retrotransposition in both somatic tissues and reproductive tissues in a gene dosage-dependent manner. Therefore, MOV10 functions as a host restriction factor for L1 and possibly other transposable elements in vivo.
Highly defended nudibranchs ‘escape’ to visually distinct background habitats

The ‘escape and radiate’ hypothesis predicts that once species have evolved aposematism, defended species can utilise more visually diverse visual backgrounds as they ‘escape’ the need to be well camouflaged. This enables species to explore new ecological niches, resulting in increased diversification rates. To test this hypothesis’ ‘escape’ component, we examined whether the background habitats of 12 nudibranch mollusc species differed among species depending on the presence and strength of chemical defences. We obtained a rich array of colour pattern statistics using Quantitative Colour Pattern Analysis (QCPA) to analyse backgrounds viewed through the eyes of a potential predator (triggerfish, Rhinecanthus aculeatus). Colour pattern analysis was done at viewing distances simulating an escalating predation sequence. We identified four latent factors comprising 17 non-correlated colour pattern parameters, which captured the among-species variability associated with differences in chemical defences. We found that chemically defended species, indeed, were found on visually distinct backgrounds with increased colour and luminance contrast, independent of viewing distance. However, we found no evidence for increased among-species background diversity coinciding with the presence and strength of chemical defences. Our results agree with the ‘escape and radiate’ hypothesis, suggesting that potent chemical defences in Dorid nudibranchs coincide with spatiochromatic differences of visual background habitats perceived by potential predators. Lay Summary According to the ‘escape and radiate’ hypothesis, the ability to store potent chemical defences as protection from predators enables animals to be minimally dependent on matching visual backgrounds for camouflage. We found evidence supporting this hypothesis in 12 species of nudibranch molluscs. Aposematic species were found on visual backgrounds that differed consistently in appearance from the visual background of undefended cryptic species. However, we found no difference in the variability of visual backgrounds between species with or without chemical defences. This suggests that warning colouration in eastern Australian Dorid nudibranchs coincides with broadly generalisable spatiochromatic properties of visual backgrounds.
Theoretical phonon thermal conductivity of Si/Ge superlattice nanowires

An incoherent particle model has been developed to calculate the phonon thermal conductivity of superlattice nanowires. This is an extension of the photon net-radiation method and Schuster–Schwarzschild approximation to dispersive acoustic phonons in a gray medium. By comparing the roughness and geometric variations of typical nanowires to the characteristic phonon wavelength (∼1 nm at 300 K), diffuse scattering and incoherent three-dimensional dispersion are justified. An isotropic sine-type (Born–von Karman) dispersion is used, which requires only the sound velocity, atomic number density, and bulk conductivity to fully describe a material. A simple picture is also given in terms of Matthiessen’s rule and three effective mean free paths. Agreement with available experimental data is poor at the smallest diameters, but good above 30 nm diameter. Compared to a conventional superlattice, calculations show that the additional sidewall scattering in a superlattice nanowire can reduce the thermal conductivity.
From Meaning-making to Meaning-sharing: Participatory Interpretation in a 3D Virtual Heritage Site

Recent advances in digital heritage have led to participatory interpretation that enables the creation of content provided by individuals as well as content from official cultural institutions. Although researchers have developed systems supporting participatory interpretation, little is known about how people experience participatory interpretation that is socially generated. To investigate this, we developed a mobile Virtual Reality application called MyInterpret and conducted a user study with 17 participants. The study results showed that user-generated interpretation significantly improving user experience, participants created and perceived user-generated interpretation differently from the official interpretation, and social features were used for engaging with user-generated content. We outline the implications of our work for curators and designers, and discuss how they may benefit from considering ‘participatory interpretation’ in the future.
Testing for Cointegration in Linear Quadratic Models

This paper evaluates the finite sample performance of various tests for cointegration by Monte Carlo methods. The evaluation takes place within the linear quadratic model. The results indicate sharp differences in the tests to detect cointegrating relations especially when the cost of adjustment term and the number of regressors are large. Although no single test dominates for all the parameter settings considered, overall the augmented Dickey-Fuller and the Phillips type of test (1987) seem the most reliable in terms of test size and power.
Towards possibilistic JDPAF

Joint probabilistic data association filter (JPDAF) was proposed first by Y. Bar-Shalom and E. Tsee (1975) to deal with multiple target tracking in a cluttered environment where the origin of measurements (hits) is ill-known, Thus, the association target measurement is the main purpose of JPDAF. The basis of the filter is the calculus of the joint probabilities over all targets and hits. The algorithm assigns a weight for reasonable hits and uses a weighted centroid of those hits to update the track. A novel weight assignment based on possibility theory and a similarity based approach is put forward and illustrated with a simulation example.
Application of Supercapacitor Energy Storage Systems in Frequency-Controlled Electric Drives: a Review

In the article the review of using the supercapacitor energy storage systems in frequency-controlled alternating current electric drives for various purposes are given. The article discusses various variants for connecting the electric energy storage devices based on batteries and supercapacitors to electric drive systems. The structures of the power part of combined (hybrid) power supplies for electric drives of vehicles (hybrid electric vehicles and urban transport), general industrial electric drives (cranes, freight and passenger elevators) are given. The review focuses attention on the problems, that are typical for traditional solutions for the power part of electric drive systems, as well as on the effect, which can be obtained, when supercapacitor energy storage systems are used in frequency-controlled electric drives.
Context-Enriching Feature Selection Method for Industrial Machine Learning

An industrial process consists of a complex network of thousands of elements interconnected by the flow of material, energy, and information. Each of these elements can be attached to several sensors producing different process signals. Building robust industrial machine learning (ML) models requires handling this multi-dimensional process data while incorporating the process domain knowledge in the feature selection activity. Despite the variety of methods that automate this feature selection task, in industrial practice, they are outperformed with the manual feature selection by domain experts as embedding the industrial domain knowledge. In this paper, we introduce a feature selection method for industrial ML that (1) automatically captures domain knowledge from process topology models that hold information on the plant process and (2) uses it to identify the relevant features (i.e., process signals) to a specified process element to which an ML model is being built. We performed an empirical case study on two industrial use cases to evaluate the effectiveness and efficiency of the proposed method in comparison to existing ones from the literature. In the first use case, our method improved the ML model performance with accuracy of 95% and recall of 91%, compared to a baseline model that achieved 70% and 5% respectively. It also decreased the training time by 81% with a simpler model. In the second use case, our method competed equally with the other methods with regards to model performance, however, it outperformed them in decreasing the training time by 64% with a simpler model.
Precise Positioning Model of Back Propagation Neural Network Based on Genetic Algorithm Optimization

Damage identification and location is a critical problem in structural health monitoring. The fundamental idea is to employ features like amplitude thresholds and signal timing differences to identify and localize structural damage by acquiring anomalous signals brought on by damage. The method proposed in this paper addresses the shortcomings of existing localization methods, such as slow localization efficiency, low localization accuracy, and poor model generalization. Firstly, by employing data cleaning principles to clean invalid data, then the decision tree classification model is used to distinguish the presence of interference signals, and finally, the BP neural network localization model based on genetic algorithm optimization is established to identify and localize the damage. Both signal interference and no signal interference were used in the studies with pulsed radio transmission. By changing the position of the anchor point of the excitation signal and the target point of the acquisition signal, the distance data from the anchor point to the target point at different locations was collected using the time of arrival (TOF) based ranging principle, and the validity of the positioning model was finally verified. Without taking into account the location of the target and anchor, the model can precisely identify and localize damage. It can be used as a reference for further structural health monitoring studies, with good prospects for application.