Miracle-dz/UniFAR-FTUs huggingface dataset:
Generating Interior Design from Text: A New Diffusion Model-Based Method for Efficient Creative Design

Because interior design is subject to inefficiency, more creativity is imperative. Due to the development of artificial intelligence diffusion models, the utilization of text descriptions for the generation of creative designs has become a novel method for solving the aforementioned problem. Herein, we build a unique interior decoration style dataset. Thus, we solve the problem pertaining to the need for datasets, propose a new loss function that considers the decoration style, and retrain the diffusion model using this dataset. The trained model learns interior design knowledge and can generate an interior design through text. The proposed method replaces the designer’s drawing with computer-generated creative design, thereby enhancing the design efficiency and creative generation. Specifically, the proposed diffusion model can generate interior design images of specific decoration styles and spatial functions end to end from text descriptions, and the generated designs are easy to modify. This novel and creative design method can efficiently generate various interior designs, promote the generation of creative designs, and enhance the design and decision-making efficiency.
Self-assembled GLP-1/glucagon peptide nanofibrils prolong inhibition of food intake

Introduction Oxyntomodulin (Oxm) hormone peptide has a number of beneficial effects on nutrition and metabolism including increased energy expenditure and reduced body weight gain. Despite its many advantages as a potential therapeutic agent, Oxm is subjected to rapid renal clearance and protease degradation limiting its clinical application. Previously, we have shown that subcutaneous administration of a fibrillar Oxm formulation can significantly prolong its bioactivity in vivo from a few hours to a few days. Methods We used a protease resistant analogue of Oxm, Aib2-Oxm, to form nanfibrils depot and improve serum stability of released peptide. The nanofibrils and monomeric peptide in solution were characterized by spectroscopic, microscopic techniques, potency assay, QCM-D and in vivo studies. Results We show that in comparison to Oxm, Aib2-Oxm fibrils display a slower elongation rate requiring higher ionic strength solutions, and a higher propensity to dissociate. Upon subcutaneous administration of fibrillar Aib2-Oxm in rodents, a 5-fold increase in bioactivity relative to fibrillar Oxm and a significantly longer bioactivity than free Aib2-Oxm were characterized. Importantly, a decrease in food intake was observed up to 72-hour post-administration, which was not seen for free Aib2-Oxm. Conclusion Our findings provides compelling evidence for the development of long-lasting peptide fibrillar formulations that yield extended plasma exposure and enhanced in vivo pharmacological response.
Maximum Acceptable Risk as Criterion for Decision-Making in Autonomous Vehicle Trajectory Planning

Autonomous vehicles are being developed to make road traffic safer in the future. The time when autonomous vehicles are actually safe enough to be used in real traffic is a current subject of discussion between industry, science, and society. In our work, we propose a new approach to the risk assessment of autonomous vehicles based on risk-benefit analysis, as it is already established in other areas, such as the registration of pharmaceuticals. In this context, we address the question of socially acceptable risk for mobility and investigate this concept as a decision-making criterion in trajectory planning. We make the first attempt to quantify an accepted risk by comparing autonomous vehicles with other types of mobility while taking into account the ethical and psychological effects important to the acceptance of autonomous vehicles. We show how an accepted risk contributes to the transparent decision-making of autonomous vehicles at the maneuver level. Finally, we present a method for considering accepted risk in trajectory planning. The evaluation of this algorithm in a simulation of 2,000 scenarios reveals that lower risk thresholds can actually reduce risks in trajectory planning. The code used in this research is publicly available as open-source software: https://github.com/TUMFTM/EthicalTrajectoryPlanning.
Positioning Accuracy Analysis of Industrial Robots Based on Non-Probabilistic Time-Dependent Reliability

A novel method for positioning accuracy analysis based on non-probabilistic time-dependent reliability is proposed for industrial robots with multisource uncertainties. To overcome the limitation of the probabilistic method in analyzing fewer samples, in this article, we consider uncertain parameters as unknown-but-bounded (UBB). The interval transformation matrix of robots and the uncertain position of the end-effectors are accurately estimated using the proposed method based on the Denavit–Hartenberg (D–H) method for forward kinematics of industrial robots. According to the Delaunay triangulation method combined with the interval method, the positioning accuracy analysis method is investigated to accurately estimate the trajectory bounds, which is more suitable for the complex trajectory of the robotic end-effector. A novel reliability method for positioning accuracy based on a non-probabilistic time-dependent model is proposed to analyze the reliability of positional accuracy in industrial robots. The interval process model and the first-passage theory are applied to constitute the non-probabilistic time-dependent reliability with different dimensions and various thresholds, which are more appropriate for the positioning accuracy analysis of industrial robots with lines, curves, and spiral trajectories. The proposed method is verified using two numerical examples compared with the Monte Carlo simulations (MCS).
Electrical conduction of ion tracks in tetrahedral amorphous carbon: temperature, field and doping dependence and comparison with matrix data

This paper gives an extended overview of the electrical properties of ion tracks in hydrogen-free tetrahedral amorphous carbon (ta-C) with a sp3 bond fraction of about 80%. The films were grown by mass selected ion beam deposition of 100 eV 12C+ ions. The ion tracks are generated by irradiation of ta-C films with uranium ions of 1 GeV kinetic energy. Along the ion path a conversion from diamond-like (sp3) carbon to graphite-like (sp2) carbon takes place. Topography and current measurements of individual ion tracks were performed by atomic force microscopy at ambient temperature. The temperature dependence of the electric conductivity was studied between 15 and 390 K by means of 0.28 mm2 large contact pads averaging over about 107 tracks. For each sample and at each temperature the conductivity as a function of the applied electrical field (non-ohmic behaviour) was measured separately and the data were extrapolated to field zero. In this way, the zero-field conductivity was determined independent from the field dependence. In spite of large differences in the absolute values, the temperature dependence of the zero-field conductivities is found to be very similar in shape for all samples. The conductivities follow a T − 1/4 ? > law up to temperatures slightly below room temperature. At higher temperatures a transport mechanism based on over-barrier hopping dominates with an activation energy of about 220 meV for tracks and 260 meV for the ta-C matrix. The field dependence measurements show that the deviation of the I–V characteristics from ohmic behaviour decreases with increasing zero-field conductivity. We also tested Cu-doped ta-C samples and found that they conduct significantly better than pure ta-C. However, the doping also increases the zero-field conductivity resulting in a weaker contrast between the track and matrix. The data are interpreted within the so-called ‘barrier model’ where the electrons are assumed to move fairly freely in well-conducting sp2 regions but encounter barriers in track sections consisting of more sp3-like bonds.
The littlest Higgs and its phenomenological implications for flavor changing neutral currents and lepton flavor violating processes

Throughout this work we study several prominent flavor changing neutral current processes and lepton flavor violating decays in the Littlest Higgs model without T-parity and with T-parity. Beginning with a brief introduction to the Standard Model of particle physics we discuss the Little Hierarchy Problem, present the Littlest Higgs model and analyze its impact on rare decays. Subsequently, we introduce the Littlest Higgs model with T-parity, which cures several shortcomings of the Littlest Higgs model. Finally, we show an extensive numerical analysis of several flavor changing neutral current processes and lepton flavor violating decays in this model.
Interface Characteristics of Tungsten-Particle-Reinforced Zr-Based Bulk-Metallic-Glass Composites with Different Tungsten Particle Sizes

This study investigated the interfacial characteristics of tungsten-particle-reinforced Zr-based bulk-metallic-glass composites (Wp/Zr-BMGs) with varying tungsten-particle sizes. To this end, Wp/Zr-BMGs with three different Wp sizes were fabricated using spark plasma sintering. Subsequently, the microstructures and interfacial structures of the Wp/Zr-BMGs were extensively examined, and the mechanical properties of the microzone at the Wp/Zr-BMG interface were evaluated using a nanoindentation method. The results revealed that the interfaces of Wp/Zr-BMGs, irrespective of the Wp size, exhibited dissolution-diffusion characteristics. Moreover, the thickness of the interface diffusion layer was positively correlated to the size of Wp. The addition of Wp enhanced the elastic modulus and hardness of Zr-BMGs at the interface, as these effects are inversely related to the Wp size. Furthermore, this study established a relationship between the interfacial mechanical properties and the interfacial characteristics of particle-reinforced bulk-metallic-glass composites. Thus, this study can serve as a guide for future research in the field of Wp/Zr-BMGs and similar particle-reinforced composites.
Exploring and Exploiting High-Order Spatial–Temporal Dynamics for Long-Term Frame Prediction

Long-term spatial-temporal frame prediction focuses on predicting future image frames precisely, which has numerous applications in real-world scenarios. Existing deep learning prediction models mainly rely on advanced neural network architectures to model complicated spatial-temporal features, which make few efforts to explore high-order correlations to better capture long-term dynamics. Their prediction on long-term frames suffers from inaccurate visual and motion detail issue. In this article, we propose a high-order prediction model for long-term frame prediction, which improves the appearance and motion details by designing special high-order correlation modules in two aspects. First, to enhance the appearance details of predicted frames, we propose a high-order appearance encoder module, where high-order appearance features can be effectively captured with a carefully designed Non-local ConvLSTM. Second, to guarantee the motion accuracy of predicted sequences, we carefully design a high-order motion encoder module, which can accurately capture and preserve the high-order motion patterns with adaptive motion extractors and progressive memory banks, respectively. Comprehensive experiments are conducted on six challenging datasets from real-world scenarios, which demonstrate the effectiveness and superiority of our proposed method over state-of-the-art methods.
Lissajous confocal fluorescent endomicroscopy with a lever mechanism and a frequency separation by an asymmetric polymer tube

Abstract We present a confocal fluorescent endomicroscopic system with a Lissajous scan using an asymmetric polymer tube and piezoelectric (PZT) tube actuator. The fiber cantilever’s scanning part is often inside the PZT tube actuator to reduce the scanner’s rigid length and enhance the beam deflection via a lever mechanism. Here, the mathematical model of the PZT tube actuator-based lever mechanism is first proposed by considering the piezoelectric parameters of the actuator and Euler-Bernoulli beam deflection, showing a good agreement with experimental data. In addition, an elliptical polymer tube is used to divide the resonant frequencies of the fiber cantilever, allowing enough scanning amplitudes and alleviating the inherent cross-coupling issue of a PZT tube actuator. The design optimization is performed by selecting the optimal lever length and the shape of the PFA tube. The implemented endomicroscopic probe could successfully acquire imaging results from both a lens-cleaning tissue and an ex-vivo mouse colon.
The second strong X-ray flare and multifrequency variability of 1ES 1959+650 in 2016 January-August

The X-ray variability of the BL Lacertae source 1ES 1959 + 650 was studied intensively with X-ray telescope (XRT) onboard Swift during 2016 January–August. In this paper, we present the results obtained during this campaign. A long-term high X-ray state was superimposed by shorter-term ﬂares by a factor of 1.9–4.7. We found 35 instances of intra-day variability which showed very fast ﬂux changes by 14–21 per cent occurring within 1 ks and a decline by a factor of 2.3 in 17.2 ks. Similarly to the previous years, this period sometimes was characterized by a lack of correlated X-ray and TeV variability, indicating that the high-energy emission in 1ES 1959 + 650 was generated in the emission region more complex than a single zone. The source showed a signiﬁcant X-ray – high-energy ﬂux correlation, while the former was not correlated with the optical–UV ﬂuxes. The best ﬁts of the 0.3–10 keV spectra were mainly obtained using the log-parabola model. Strong spectral variability was detected, shifting the peak of the spectral energy distribution by more than 10 keV that happens rarely in blazars. During some strong short-term ﬂares, the photon index at 1 keV frequently became harder than 1.70, and the spectral evolution was characterized by a harder-when-brighter behaviour.
Transformer 2β regulates the alternative splicing of cell cycle regulatory genes to promote the malignant phenotype of ovarian cancer

Late-stage ovarian cancer (OC) has a poor prognosis and a high metastasis rate, but the underlying molecular mechanism is unclear. RNA binding proteins (RBPs) play important roles in posttranscriptional regulation in the contexts of neoplasia and tumor metastasis. In this study, we explored the molecular functions of a canonical RBP, Transformer 2β homolog (TRA2B), in cancer cells. TRA2B knockdown in HeLa cells and subsequent whole-transcriptome RNA sequencing (RNA-seq) analysis revealed the TRA2B-regulated alternative splicing (AS) profile. We disrupted TRA2B expression in epithelial OC cells and performed a series of experiments to confirm the resulting effects on OC cell proliferation, apoptosis and invasion. TRA2B-regulated AS was tightly associated with the mitotic cell cycle, apoptosis and several cancer pathways. Moreover, the expression of hundreds of genes was regulated by TRA2B, and these genes were enriched in the functions of cell proliferation, cell adhesion and angiogenesis, which are related to the malignant phenotype of OC. By integrating the alternatively spliced and differentially expressed genes, we found that AS events and gene expression were regulated independently. We then explored and validated the oncogenic functions of TRA2B by knocking down its expression in OC cells. The high TRA2B expression was associated with poor prognosis in patients with OC. In ovarian tissue, TRA2B expression showed a gradual increasing trend with increasing malignancy. We demonstrated the important roles of TRA2B in ovarian neoplasia and aggressive OC behaviors and identified the underlying molecular mechanisms, facilitating the targeted treatment of OC.
Reducing the Dimensional Dependence for Rank-Based Similarity Search

In this paper we try to introduce a data structure for k-NN search, the Rank Cover Tree (RCT). The pruning tests for RCT rely on the comparison of similarity values not on the other properties of the underlying space, such as the triangle inequality. Objects are selected according to their ranks with respect to the query object, allowing much tighter control on the overall execution costs. Theoretical analysis shows that with very high probability, the RCT returns a correct query result in time that depends very competitively on a measure of the intrinsic dimensionality of the data set. The experimental results for the RCT show that non-metric pruning strategies for similarity search can be practical even when the representational dimension of the data is extremely high. They also show that the RCT is capable of meeting or exceeding the level of performance of state-of-the-art methods that make use of metric pruning or other selection tests involving numerical constraints on distance values.
Fibre Processes and their Applications

The main purpose of the study was to improve the physical properties of the modelling of compressed materials, especially fibrous materials. Fibrous materials are finding increasing application in the industries. And most of the materials are compressed for different applications. For such situation, we are interested in how the fibre arranged, e.g. with which distribution. For given materials it is possible to obtain a three-dimensional image via micro computed tomography. Since some physical parameters, e.g. the fibre lengths or the directions for points in the fibre, can be checked under some other methods from image, it is beneficial to improve the physical properties by changing the parameters in the image. In this thesis, we present a new maximum-likelihood approach for the estimation of parameters of a parametric distribution on the unit sphere, which is various as some well known distributions, e.g. the von-Mises Fisher distribution or the Watson distribution, and for some models better fit. The consistency and asymptotic normality of the maximum-likelihood estimator are proven. As the second main part of this thesis, a general model of mixtures of these distributions on a hypersphere is discussed. We derive numerical approximations of the parameters in an Expectation Maximization setting. Furthermore we introduce a non-parametric estimation of the EM algorithm for the mixture model. Finally, we present some applications to the statistical analysis of fibre composites.
Brief paper Conjugate Lyapunov functions for saturated linear systems

Based on a recent duality theory for linear differential inclusions (LDIs), the condition for stability of an LDI in terms of one Lyapunov function can be easily derived from that in terms of its conjugate function. This paper uses a particular pair of conjugate functions, the convex hull of quadratics and the maximum of quadratics, for the purpose of estimating the domain of attraction for systems with saturation nonlinearities. To this end, the nonlinear system is locally transformed into a parametertized LDI system with an effective approach which enables optimization on the parameter of the LDI along with the optimization of the Lyapunov functions. The optimization problems are derived for both the convex hull and the max functions, and the domain of attraction is estimated with both the convex hull of ellipsoids and the intersection of ellipsoids. A numerical example demonstrates the effectiveness of this paper’s methods. 2005 Elsevier Ltd. All rights reserved.
Kalman Filtering with Correlated Noises over Unreliable Communication Network

In this paper, we study the Kalman filtering problem with correlated noises one time apart, when part or all of the observation measurements are lost in a random way due to unreliable link between controller and estimator. By "one time apart" we mean that the process noise at time step does not contribute to the system measurement at time step . Rather, it is the process noise at time step that contributes to the system measurement at time step . Observation losses can occur in a distributed control system where measurements are taken at different sensors in different physical locations, or one sensor needs to send its data in multiple packets. We formulate the Kalman filtering problem with correlated noises at one time apart and derived the Kalman filter update equations with random observation measurements. Then, we showed that the estimation error covariance (performance index) became a random quantity when the system measurements were collected at different intervals with different probability arrival rate. As a result, we investigated the statistical convergence properties of the performance index and found the stable and unstable regions so that this criterion could be bounded in a stable region and unbounded in an unstable one. The results are illustrated with some simple numerical examples. Keywords: Kalman Filtering; State estimation; Correlated Noises ; dropping network
Modeling of speckle noise using bessel K-form probability density function

Speckle noise is an inherent phenomenon in medical ultrasound images. Since it degrades an ultrasound image quality and reduces its diagnostic value, reduction of speckle noise is a very important p re-processing s tep in ultrasound image pr ocessing. F or t his pur pose, t he knowledge o f t he st atistics o f speckle noise is necessary; e specially in the multi-resolution transform domain due to their sparse and ef ficient representation of images and henceforth their widespread application in developing efficient speckle reduction methods. In this thesis, the statistics of log-transformed speckle noise in various multi-resolution transform domains is i nvestigated. The r eason f or c onsidering t he l og-transformed n oise i s t he p revalence o f homomorphic ap proaches for speckle r eduction i n the l iterature w here the m ultiplicative speckle noise is converted to an additive one by log-transformation and subsequently reduced by a pplying a dditive no ise reduction t echniques. In this t hesis, a Bessel K -Form ( BKF) probability density function (pdf) is proposed as a highly suitable prior for modeling the logtransformed speckle noise i n t he w ell-known discrete w avelet transform (D WT), c urvelet transform, dua l-tree c omplex w avelet t ransform ( DT-CWT) a nd contourlet t ransform domains. The m otivations for us ing t he B KF pdf a re the he avy-tailed n ature o f t he l ogtransformed speckle noise, and the effectiveness of the BKF pdf in capturing the statistics of heavy-tailed , reported in several research works in the literature. Maximum likelihoodbased methods are presented for estimating the parameters of the BKF pdf. The appropriateness of the BKF pdf in modeling the speckle noise is extensively explored for the case o f simulated noise o f d ifferent l evels as w ell a s r eal m edical u ltrasound i mages in various t ransform domains that include the DWT, curvelet transform, DT-CWT and contourlet transform. It is shown that, in general the BKF can model the statistics of the various transform coefficients corresponding t o l og-transformed s peckle be tter t han t he t raditional Gaussian an d n ormal inverse Gaussian (NIG) pdfs. It is expected that the findings of this thesis would encourage researchers i n d eveloping e ffective a nd i mproved m ulti-resolution t ransform-based algorithms for reducing the speckle noise from medical ultrasound images.