Miracle-dz/UniFAR-FTUs huggingface dataset:
Probing the stability landscape of cylindrical shells for buckling knockdown factors

The buckling response of axially compressed cylindrical shells is well known for its imperfection sensitivity. Mapping out a stability landscape by localized probing has recently been proposed as a rational means for establishing shell buckling knockdown factors. Probing using a point force directed radially inwards and perpendicular to the cylinder wall is based on the insight that a localized single dimple exists as an edge state in the basin boundary of the stable prebuckling equilibrium. Here, we extend the idea of probing to bi-directional inwards and outwards forces to trigger both single-dimple and double-dimple edge states. We identify key features of the ensuing probing stability landscape and generalize these to derive three design curves of varying conservatism that are a function of the non-dimensional Batdorf parameter only. Interestingly, the most conservative of the three knockdown curves bounds a large dataset of experimental buckling results from below, despite being derived from probing features of geometrically perfect cylinders. Overall, the three design curves permit a more nuanced design approach than legacy knockdown factors, as different levels of conservatism can be chosen based on expected manufacturing quality. For instance, the most and least conservative of the three design guidelines differ by a factor of 3 for the most slender cylinder geometries, and the associated reduction in safety factor has profound implications for efficient structural design. This article is part of the theme issue ‘Probing and dynamics of shock sensitive shells’.
NOVEL CLASSIFICATION OF CORONARY ARTERY DISEASE USING HEART RATE VARIABILITY ANALYSIS

Coronary artery disease (CAD) is a leading cause of death worldwide. Heart rate variability (HRV) has been proven to be a non-invasive marker of the autonomic modulation of the heart. Nonlinear analyses of HRV signals have shown that the HRV is reduced significantly in patients with CAD. Therefore, in this work, we extracted nonlinear features from the HRV signals using the following techniques: recurrence plots (RP), Poincare plots, and detrended fluctuation analysis (DFA). We also extracted three types of entropy, namely, Shannon entropy (ShanEn), approximation entropy (ApEn), and sample entropy (SampEn). These features were subjected to principal component analysis (PCA). The significant principal components were evaluated using eight classification techniques, and the performances of these techniques were evaluated to determine which presented the highest accuracy in classifying normal and CAD classes. We observed that the multilayer perceptron (MLP) method resulted in the highest classification accuracy (89.5%) using our proposed technique.
Principles of vectorial tomography—the effects of model parametrization and regularization in tomographic imaging of seismic anisotropy

SUMMARY Imaging seismic anisotropy is equivalent to determining the spatial variations of an anisotropy vector. This anisotropy vector can be described by its projection on the axes of a geographical reference frame or by a length and two angles that define the orientation of this vector with respect to the reference axes. Classical tomographic approaches use the former description, which leads to a linear inverse problem. When anisotropy varies spatially over scales smaller than the Fresnel zone, damping and smoothing produce strong artefacts in the solution, in particular for the amplitude of anisotropy. Regularization constraints favour models in which anisotropy is weak where fabrics are disoriented. These shortcomings can be overcome by the latter choice of parametrization, which leads to a non-linear inverse problem. The direct resolution of this strongly non-linear problem by a Gauss-Newton algorithm is difficult. It converges only if the starting model is sufficiently close to the global minimum of the misfit function. However, a robust and stable solution can be obtained following a 3-step algorithm, which consists in (1) inverting the fast directions, the amplitudes of anisotropy being fixed to an arbitrary (but small) constant value, (2) finding the average amplitude of anisotropy inside the model and (3) inverting the fluctuations of anisotropy with respect to this average value.
Study of the mechanical response of carbon nanotubes‐SU8 composites by nanoindentation

Multiwalled carbon nanotubes (MWCNTs)/SU8 composites have been produced to enhance the mechanical properties of SU8 photoresist. We have studied the influence of SU8 solvent on the structural homogeneity of composites through nanoindentation testing. It is found that acetone and propylene glycol methyl ether acetate (PGMEA) are very suitable solvents to prepare MWCNTs/SU8 composites with significant increase of the Young's modulus (EY). The highest increase of EY in respect to the parent material of 104% was obtained with acetone as solvent. It was noticed that the remaining solvent in the composite influences strongly EY, as well.
Monopole Dissociation in the Early Universe

It has recently been shown that topological excitations of metastable phases such as non-Abelian monopoles can dissociate and decay through the radial expansion of the excitation core. In this paper it is indicated that, according to some grand unified field theories, the monopole dissociation process might occur in the early Universe. In particular, the case of an SU(5)-symmetric grand unified field theory which breaks spontaneously to SU(4)\ifmmode\times\else\texttimes\fi{}U(1) symmetry and then to SU(3)\ifmmode\times\else\texttimes\fi{}SU(2)\ifmmode\times\else\texttimes\fi{}U(1) symmetry is studied, and it is demonstrated that monopoles that are created in the transition from SU(5) symmetry to SU(4)\ifmmode\times\else\texttimes\fi{}U(1) symmetry generally dissociate after the SU(4)\ifmmode\times\else\texttimes\fi{}U(1) phase becomes metastable with respect to the SU(3)\ifmmode\times\else\texttimes\fi{}SU(2)\ifmmode\times\else\texttimes\fi{}U(1) phase but before there is any significant spontaneous production of bubbles associated with barrier penetration from the SU(4)\ifmmode\times\else\texttimes\fi{}U(1) phase to the SU(3)\ifmmode\times\else\texttimes\fi{}SU(2)\ifmmode\times\else\texttimes\fi{}U(1) phase. Thus, the monopole dissociation process does indeed occur in such models and the monopoles may act as seeds for the inhomogeneous phase transition from SU(4)\ifmmode\times\else\texttimes\fi{}U(1) symmetry to SU(3)\ifmmode\times\else\texttimes\fi{}SU(2)\ifmmode\times\else\texttimes\fi{}U(1) symmetry. If the transition occurs inhomogeneously, the transition temperature is higher and less latent heat is released in the transition.
A Brief Study on a Novel Texture Spectrum Descriptor for Material Images

The local binary pattern (LBP) operator has been proved to be theoretically simple yet very effective for texture description. However, it lacks the full description of texture in a region and produces a rather long histogram. A novel texture spectrum descriptor was proposed to alleviate these limitations in the paper. It uses the relation of 3 pixels in an 8-neighborhood, the center and the center-symmetric pixels, to define the local texture patterns. The new operator fully uses the texture information contained in the 8-neighbourhood and produces a rather short histogram. On the other hand, the new operator also has the same desirable properties as LBP, such as tolerance to illumination changes and computational simplicity. Experimental results demonstrate that the new descriptor achieves better performance than the conventional LBP with a rather short histogram
Research on Abnormal Detection Algorithm of Aerospace TT&C Equipment-Based on Temporal Association Rules

Aiming at the problems in traditional time series data association mining, such as huge candidate set space, low mining efficiency, and mining results not meeting the time series requirements, we obtain the key parameters of the operation state of the aerospace TT&C equipment firstly, and uses the temporal association rule mining (TSAR) algorithm based on temporal constraints, establish the candidate set of association rule mining, trim the candidate set space according to temporal constraints, and mine frequent patterns that conform to temporal constraints. Then, the asymmetric J-measure method is used to extract the multi-dimensional association rules with the maximum amount of information. Finally, abnormal detection of aerospace TT&C equipment operation state is realized by mining temporal association rules of key parameters. The experimental results show that, compared with the traditional association rule mining algorithm, TSAR model can effectively mine temporal association rules containing more information, and can also efficiently analyze the abnormal time points of the operation state of aerospace TT&C equipment, providing support for knowledge discovery and anomaly detection of aerospace TT&C equipment.
Dynamic Personalized POI Sequence Recommendation with Fine-Grained Contexts

The Point Of Interest (POI) sequence recommendation is the key task in itinerary and travel route planning. Existing works usually consider the temporal and spatial factors in travel planning. However, the external environment, such as the weather, is usually overlooked. In fact, the weather is an important factor because it can affect a user’s check-in behaviors. Furthermore, most of the existing research is based on a static environment for POI sequence recommendation. While the external environment (e.g., the weather) may change during travel, it is difficult for existing works to adjust the POI sequence in time. What’s more, people usually prefer the attractive routes when traveling. To address these issues, we first conduct comprehensive data analysis on two real-world check-in datasets to study the effects of weather and time, as well as the features of the POI sequence. Based on this, we propose a model of Dynamic Personalized POI Sequence Recommendation with fine-grained contexts (DPSR for short). It extracts user interest and POI popularity with fine-grained contexts and captures the attractiveness of the POI sequence. Next, we apply the Monte Carlo Tree Search model (MCTS for short) to simulate the process of recommending POI sequence in the dynamic environment, i.e., the weather and time change after visiting a POI. What’s more, we consider different speeds to reflect the fact that people may take different transportation to transfer between POIs. To validate the efficacy of DPSR, we conduct extensive experiments. The results show that our model can improve the accuracy of the recommendation significantly. Furthermore, it can better meet user preferences and enhance experiences.
Bemerkungen zur Theorie der freien Turbulenz .

Zur Einfuhrung fur den nachfolgenden Aufsatz von H. Gortler wird ein Uberblick uber den derzeitigen Stand der Grundformeln der turbulenten Ausbreitung gegeben. Es wird dabei auch zu den von H. Reichardt vorgeschlagenen Ansatzen Stellung genommen.
Creating PublicSpaces: Centering Public Values in Digital Infrastructures

Institutions like public and universities face conflicts of values when using surveillant digital tools: organizations bound to protect the privacy and respect their autonomy of their constituents - which we term “values-led organizations” - find those values undermined by tools they must use to conduct business online. A Dutch nonprofit, Public Spaces, has developed a self-audit method for documenting dependencies on such tools and working to find values-consistent alternatives. The Public Spaces Digital Power Wash is a method applicable to other tensions between organizational values and values embedded in digital tools. We expand from this specific case study to consider the larger challenge of tensions between organizational values and the behavior of digital tools and examine the possibility that values-led organizations could take the lead in building digital public infrastructures that value the autonomy and privacy of citizens.
Towards Informative and Diverse Dialogue Systems Over Hierarchical Crowd Intelligence Knowledge Graph

Knowledge-enhanced dialogue systems aim at generating factually correct and coherent responses by reasoning over knowledge sources, which is a promising research trend. The truly harmonious human-agent dialogue systems need to conduct engaging conversations from three aspects as humans, namely (1) stating factual contents (e.g., records in Wikipedia), (2) conveying subjective and informative opinions about objects (e.g., user discussions on Twitter), and (3) impressing interlocutors with diverse expression styles (e.g., personalized expression habits). The existing knowledge base is a standardized and unified coding for factual knowledge, which could not portray the other two kinds of knowledge to make responses more informative and expressive diverse. To address this, we present CrowdDialog, a crowd intelligence knowledge-enhanced dialogue system, which takes advantage of “crowd intelligence knowledge” extracted from social media (with rich subjective descriptions and diversified expression styles) to promote the performance of dialogue systems. Firstly, to thoroughly mine and organize the crowd intelligence knowledge underlying large-scale and unstructured online contents, we elaborately design the Crowd Intelligence Knowledge Graph (CIKG) structure, including the domain commonsense subgraph, descriptive subgraph, and expressive subgraph. Secondly, to reasonably integrate heterogeneous crowd intelligence knowledge into responses while ensuring logicality and fluency, we propose the Gated Fusion with Dynamic Knowledge-Dependent (GFDD) model, which generates responses from the semantic and syntactic perspective with the context-aware knowledge gate and dynamic knowledge decoding. Finally, extensive experiments over both Chinese and English dialogue datasets demonstrate that our approach GFDD outperforms competitive baselines in terms of both automatic evaluation and human judgments. Besides, ablation studies indicate that the proposed CIKG has the potential to promote dialogue systems to generate fluent, informative, and diverse dialogue responses.
Polarization bistability in long-wavelength multitransverse-mode VCSELs induced by orthogonal optical injection

In this work we report on an experimental investigation of the bistability found in 1550 nm multitransverse-mode VCSELs subject to orthogonal optical injection. The VCSEL emits in two transverse modes that are linearly polarized in a direction referred as parallel. We study the dependence of the bistable behaviour on the detuning between the frequency of the externally injected signal and the frequency of the subsidiary orthogonal linear polarization of the fundamental mode of the VCSEL. Different qualitative behaviors of the power of each polarized transverse mode versus the optically injected power appear depending on the value of the frequency detuning. Bistable regions are very narrow for positive and small negative values of the frequency detuning. However very wide hysteresis cycles are obtained for large and negative values of the frequency detuning. Bistability is found for both the fundamental and the high-order transverse mode. The shape of the hysteresis cycle depends on the transverse mode under consideration. The power of the parallel polarized fundamental transverse mode decreases gradually as the injected power is increased. However the behaviour of the parallel polarized high-order transverse mode is different because its power remains constant as the optical injected power is increased until it suddenly drops to low levels. This kind of behaviour is of interest for obtaining good quality all-optical inversion and all-optical regeneration.
Importance Sampling for Estimating p Values in Linkage Analysis

Importance sampling methods are proposed for estimating the probability that the maximum of a random process exceeds a high threshold, with particular attention to assessing genome-wide significance levels in linkage analysis. The proposed algorithm is applied to computing the conditional significance level, given observed phenotypes, of scan statistics to map quantitative traits in experimental populations and in extended pedigrees of moderate size with partially informative markers. For detecting an additive effect in an intercross, the importance sampling algorithm is roughly 100 times as efficient as direct Monte Carlo simulation when the true significance level is about . 05. For pedigrees with partially informative markers, the efficiency varies greatly with intermarker distance, marker polymorphism, sample size, and missing data. In this case the importance sampling algorithm is used to efficiently explore how p values vary with these parameters. Extensions of the algorithm are discussed for the case of multidimensional statistics that arise when considering dominance effects or searching for multiple loci that may involve interactions.
A nonlinear analysis of pulsatile flow in arteries

An approximate numerical method for calculating flow profiles in arteries is developed. The theory takes into account the nonlinear terms of the Navier-Stokes equations as well as the nonlinear behaviour and large deformations of the arterial wall. Through the locally measured values of the pressure, pressure gradient and pressure–radius function the velocity distribution and wall shear at a given location along the artery can be determined. The computed results agree well with the corresponding experimental data.
Multipurpose controller synthesis in LQG optimal systems

The paper indicates some inaccuracies in an earlier paper by B.S. Chen and W.J. Wang (see ibid., vol.131, p.182-8, 1984). In particular, if the plant is stable, it is not possible to use the algorithm given by the paper to design an LQG optimal controller that achieves the desired purposes.
Inter-university variations in undergraduate non-completion rates: A statistical analysis by subject of study

Non-completion of higher education degree courses is a considerable problem, incurring costs on the taxpayer, higher education institutions and the students who fail to complete. Closer examination of the data reveals that non-completion rates in higher education vary substantially across institutions and by subject of degree. The purpose of this paper is to investigate, within each of 13 broad subject categories, the potential determinants of inter-university variations in non-completion rates. Published data are used to compute university non-completion rates over four time periods and to construct corresponding explanatory variables which could potentially be related to non-completion rates. The explanatory variables measure the characteristics (both academic and socioeconomic) of students recruited by universities and the characteristics of the institutions themselves. The significance of the relationship between the possible explanatory variables and non-completion rates within each given subject is assessed using both weighted leastsquares and weighted logit analysis. The conclusions drawn from the results of each technique are identical, and, therefore, for interpretation reasons, only the results of the weighted least-squares analysis are reported. As expected, the academic quality of student entrants is an important determinant of non-completion rates in the majority of subjects, although the magnitude of the effect varies according to subject. Variables reflecting the age and gender mix of university entrants are generally not significantly related to noncompletion rates. The characteristics of institutions which are significantly related to non-completion rates in specific subjects include the staff student ratio and the length of the degree course
Differential operators cononically associated to a conformal structure.

Soit (M,g) une variete pseudoriemannienne de dimension n. On donne des formules explicites pour un operateur d'ordre 4. D 4 ,k sur les k-formes dans M, n¬=1, 2, 4 pour un operateur D6 d'ordre 6 sur les fonctions n¬=1, 2, 4 et pour un operateur d'ordre 6 sur les (n-6)/2-formes, n=6, 8, 10, . , qui sont covariants par deformation et transformation conforme de g. On calcule divers operateurs covariants non lineaires conformes associes
Stability analysis of delayed neural networks

In this paper, the author derives several sufficient conditions for the asymptotic stability of delayed neural networks. These conditions ensure the asymptotic stability of the equilibrium point of a delayed neural network independently of the delay parameter. The results obtained impose constraint conditions on the interconnection matrix of the neural system. These results are also compared with the earlier results derived in the literature.
On pth Roots in Henselian Valued Fields

Let v be a Henselian valuation of arbitrary rank of a field K of characteristic zero with value group G and residue field of characteristic p > 0. Suppose that K contains a primitive pth root of unity. It is well known that if d is an element of K with then (1 + d)1/p ∈ K. In this article we investigate whether is the smallest among all elements λ of G which have the property that whenever v(d) > λ, d ∈ K then 1 + d is a pth power in K.
A versatile CRISPR-based system for lineage tracing in living plants

Individual cells give rise to diverse cell lineages during the development of multicellular organisms. Understanding the contribution of these lineages to mature organisms is a central question of developmental biology. Several techniques to document cell lineages have been used, from marking single cells with mutations that express a visible marker to generating molecular bar codes by CRISPR-induced mutations and subsequent single-cell analysis. Here, we exploit the mutagenic activity of CRISPR to allow lineage tracing within living plants. Cas9-induced mutations are directed to correct a frameshift mutation that restores expression of a nuclear fluorescent protein, labelling the initial cell and all progenitor cells with a strong signal without modifying other phenotypes of the plants. Spatial and temporal control of Cas9 activity can be achieved using tissue-specific and/or inducible promoters. We provide proof of principle for the function of lineage tracing in two model plants. The conserved features of the components and the versatile cloning system, allowing for easy exchange of promoters, are expected to make the system widely applicable. SIGNIFICANCE STATEMENT By targeting Cas9 in a tissue- and time-specific way to correct a frameshift mutation, resulting in fluorescence labelling of nuclei, we generated a method for in vivo visual lineage tracing in two model plants. The versatile cloning system makes the system widely applicable in other plants.
Establishing interpretable fuzzy models from numeric data

In this paper, a rule-base self-extraction and simplification method is proposed to establish interpretable fuzzy models from numerical data. A fuzzy clustering technique is used to extract the initial fuzzy rule-base. The number of fuzzy rules is determined by the proposed fuzzy partition validity index. To reduce the complexity of fuzzy models without decreasing the model accuracy significantly, some approximate similarity measures are presented and a parameter fine-tuning mechanism is introduced to improve the accuracy of the simplified model. Using the proposed similarity measures, the redundant fuzzy rules are removed and similar fuzzy sets are merged to create a common fuzzy set. The simplified rule base is computationally efficient and linguistically tractable. The approach has been successfully applied to non-linear function approximation and mechanical property prediction for hot-rolled steels.