Miracle-dz/UniFAR-FTUs huggingface dataset:
Crack Detection from the Slope of the Mode Shape Using Complex Continuous Wavelet Transform

Abstract: A new method for cracks detection in beams is proposed by using the slope of the mode shape to detect cracks, and by introducing the angle coefficients of complex continuous wavelet transform. This study is aimed at detecting the location of the nonpropagating transverse crack. A series of beams with cracks that are simulated by rotational springs with equivalent stiffness are analyzed. The mode shape and the slope of this lumped crack model are calculated. Through complex continuous wavelet transform of the slope of the mode shape using Complex Gaus1 wavelet (CGau1), the locations of cracks are detected from the modulus line and the angle line of wavelet coefficients. By comparison, the singularity is much more apparent from the angle line of complex continuous wavelet transform. This demonstrates that the proposed method outperforms the existing method of wavelet transform of the mode shape with real wavelets. Also, this method can detect cracks in beams with different boundary conditions. The influence of crack locations and crack depth on crack detection is discussed. Finally, the noise effect is studied. Through the multiscale analysis, the locations of cracks may be detected from the angle of wavelet coefficients.
Electrospinning of poly(ethylene‐co‐vinyl acetate)/clay nanocomposite fibers

Poly(ethylene-co-vinyl acetate)/clay nanocomposite fibers were fabricated using electrospinning. The fiber diameters were controlled by varying the polymer/chloroform concentration, which resulted in fibers with diameters ranging from 1 to 15 μm. The clay concentration was varied from 0.35 to 6.6 wt %. Scanning electron microscopy revealed that the fiber diameter increased with increasing clay concentration, whereas beading decreased. Transmission electron microscopy revealed a disruption of the spherulite structures by clay, which is consistent with heterogeneous nucleation. Shear modulus force microscopy indicated a reduction in melting point (Tm) with decreasing diameter for fibers thinner than 15 μm, which was confirmed by temperature dependent X-ray diffraction data. For fibers thinner than 8 μm, the presence of clay further enhanced the reduction of Tm. © 2009 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 47: 2501–2508, 2009
SUMMeR: Sub-Nyquist MIMO Radar

Multiple-input multiple-output (MIMO) radar exhibits several advantages with respect to the traditional radar array systems in terms of flexibility and performance. However, MIMO radar poses new challenges for both hardware design and digital processing. In particular, achieving high azimuth resolution requires a large number of transmit and receive antennas. In addition, digital processing is performed on samples of the received signal, from each transmitter to each receiver, at its Nyquist rate, which can be prohibitively large when high resolution is needed. Overcoming the rate bottleneck, sub-Nyquist sampling methods have been proposed that break the link between radar signal bandwidth and sampling rate. In this paper, we extend these methods to MIMO configurations and propose a sub-Nyquist MIMO radar (SUMMeR) system that performs both time and spatial compression. We present a range-azimuth-Doppler recovery algorithm from sub-Nyquist samples obtained from a reduced number of transmitters and receivers, that exploits the sparsity of the recovered targets’ parameters. This allows us to achieve reduction in the number of deployed antennas and the number of samples per receiver, without degrading the time and spatial resolutions. Simulations illustrate the detection performance of SUMMeR for different compression levels and shows that both time and spatial resolution are preserved, with respect to classic Nyquist MIMO configurations. We also examine the impact of design parameters, such as antennas’ locations and carrier frequencies, on the detection performance, and provide guidelines for their choice.
Hunger States Control the Directions of Synaptic Plasticity via Switching Cell Type-Specific Subunits of NMDA Receptors

It remains largely unknown whether and how hunger states control activity-dependent synaptic plasticity, such as long-term potentiation (LTP) and long-term depression (LTD). We here report that both LTP and LTD of excitatory synaptic strength within the appetite control circuits residing in hypothalamic arcuate nucleus (ARC) behave in a manner of hunger states dependence and cell type specificity. For instance, we find that tetanic stimulation induces LTP at orexigenic agouti-related protein (AgRP) neurons in ad libitum fed mice, whereas it induces LTD in food-deprived mice. In an opposite direction, the same induction protocol induces LTD at anorexigenic pro-opiomelanocortin (POMC) neurons in fed mice but weak LTP in deprived mice. Mechanistically, we also find that food deprivation increases the expressions of NR2C/NR2D/NR3-containing NMDA receptors (NMDARs) at AgRP neurons that contribute to the inductions of LTD, whereas it decreases their expressions at POMC neurons. Collectively, our data reveal that hunger states control the directions of activity-dependent synaptic plasticity by switching NMDA receptor subpopulations in a cell type-specific manner, providing insights into NMDAR-mediated interactions between energy states and associative memory. SIGNIFICANCE STATEMENT Based on the experiments performed in this study, we demonstrate that activity-dependent synaptic plasticity is also under the control of energy states by regulating NMDAR subpopulations in a cell type-specific manner. We thus propose a reversible memory configuration constructed from energy states-dependent cell type-specific bidirectional conversions of LTP and LTD. Together with the distinct functional roles played by NMDAR signaling in the control of food intake and energy states, these findings reveal a new reciprocal interaction between energy states and associative memory, one that might serve as a target for therapeutic treatments of the energy-related memory disorders or vice versa.
Material properties and fracture mechanics in relation to ceramic machining

Material removal rate, surface finish, and subsurface damage are largely governed by fracture mechanics and plastic deformation, when ceramics are machined using abrasive methods. A great deal of work was published on the fracture mechanics of ceramics in the late 1970s and early 1980s, although this work has never resulted in a comprehensive model of the fixed abrasive grinding process. However, a recently published model describes many of the most important features of the loose abrasive machining process, for example depth of damage, surface roughness, and material removal rate. Many of the relations in the loose abrasive machining model can be readily discerned from fracture mechanics models, in terms of material properties. By understanding the mechanisms of material removal, from a material properties perspective, we can better estimate how one material will machine in relation to another. Although the fracture mechanics models may have been developed for loose abrasive machining, the principles of crack initiation and propagation are equally valuable for fixed abrasive machining. This report provides a brief review of fracture in brittle materials, the stress distribution induced by abrasives, critical indenter loads, the extension of cracks, and the relation of the fracture process to material removal.
Prediction of risk of diabetic retinopathy for all-cause mortality, stroke and heart failure

Abstract To examine and quantify the potential relation between diabetic retinopathy (DR) and risk of all-cause mortality, stroke and heart failure (HF). The resources of meta-analysis of epidemiological observational studies were from Pub-med, EMBASE, CINAHL, Cochrane Library, conference, and proceedings. Random/fixed effects models were used to calculate pooled subgroup analysis stratified by different grades of DR was performed to explore the potential source of heterogeneity. Statistical manipulations were undertaken using program STATA. Of the included 25 studies, comprising 142,625 participants, 19 studies were concluded to find the relation of DR to all-cause mortality, 5 for stroke, and 3 for HF. Risk ratio (RR) for all-cause mortality with the presence of DR was 2.33 (95% CI 1.92–2.81) compared with diabetic individuals without DR. Evidences showed a higher risk of all-cause mortality associated with DR in patients with T2D or T1D (RR 2.25, 95% CI 1.91–2.65. RR 2.68, 95% CI 1.34–5.36). According to different grades of DR in patients with T2D, RR for all-cause mortality varied, the risk of nonproliferative diabetic retinopathy (NPDR) was 1.38 (1.11–1.70), while the risk of proliferative diabetic retinopathy (PDR) was 2.32 (1.75–3.06). There was no evidence of significant heterogeneity (Cochran Q test P = 0.29 vs 0.26, I2 = 19.6% vs 22.6%, respectively). Data from 5 studies in relation to DR and the risk of stroke showed that DR was significantly associated with increased risk of stroke (RR = 1.74, 95%CI: 1.35–2.24), compared with patients without DR. Furthermore, DR (as compared with individuals without DR) was associated with a marginal increased risk of HF in patients with diabetes mellitus (DM) (n = 3 studies; RR 2.24, 95% CI 0.98–5.14, P = 0.056). Our results showed that DR increased the risk of all-cause mortality, regardless of the different stages, compared with the diabetic individuals without DR. DR predicted increased risk of stroke and HF. Although only 3 studies about HF were available, the association between DR and HF should be careful.
Computational Media Aesthetics: Finding Meaning Beautiful

Content management's future is bright. Innovative media management, annotation, delivery, and navigation services will enrich online shopping, help-desk services, and anytime-anywhere training over wireless devices. Semantics-based annotations will break the traditional linear manner of accessing and browsing media and will support vignette-oriented access of audio and video. This can lead to new offerings of customized media management utilities for various market segments such as online education and training, advertising, news networks, and broadcasting studios. However, the semantic gap between the rich meaning that users want when they query and browse media and the shallowness of the content descriptions that we can actually compute is weakening today's automatic content-annotation systems. This is a crucial obstacle that we must overcome to achieve that bright future. A serious need exists to develop algorithms and technologies that can annotate content with deep semantics and establish semantic connections between media's form and function, for the first time letting users access indexed media and navigate content in unforeseeable and surprising ways. To address these underlying problems,, we advocate an approach that markedly departs from existing methods' based on detecting and annotating low-level audio-visual features. To go beyond representing what a video or movie directly shows, we postulate that we must analyze and interpret the content's visual, aural, and emotional impact. Our contention is that we must understand compositional and aesthetic media principles to guide content analysis.
Improved soft ISI cancellation for turbo equalization using full soft output channel decoder's information

This paper presents an optimized turbo equalizer based on Laot's turbo equalization scheme by means of soft intersymbol interference (ISI) cancellation. Due to Berrou's turbo-principle, common turbo equalization schemes use the extrinsic information as a-priori input for the equalizer. In contrast to this, we propose the use of the full soft output channel decoder's information for the turbo interference canceller. The performance of this improved turbo equalizer by means of soft interference cancellation is evaluated in the environment of two channels, which introduce severe ISI. Simulation results show that the proposed turbo equalizer achieves a performance gain of up to 4 dB compared to Laot's original approach. The performance gain is achieved without any increase of computational complexity. Moreover, we apply a modified extrinsic information transfer (EXIT) chart to the proposed turbo equalizer and illustrate the convergence advantages in comparison to Laot's approach.
On the vulnerability of face recognition systems towards morphed face attacks

Morphed face images are artificially generated images, which blend the facial images of two or more different data subjects into one. The resulting morphed image resembles the constituent faces, both in visual and feature representation. If a morphed image is enroled as a probe in a biometric system, the data subjects contributing to the morphed image will be verified against the enroled probe. As a result of this infiltration, which is referred to as morphed face attack, the unambiguous assignment of data subjects is not warranted, i.e. the unique link between subject and probe is annulled. In this work, we investigate the vulnerability of biometric systems to such morphed face attacks by evaluating the techniques proposed to detect morphed face images. We create two new databases by printing and scanning digitally morphed images using two different types of scanners, a flatbed scanner and a line scanner. Further, the newly created databases are employed to study the vulnerability of state-of-the-art face recognition systems with a comprehensive evaluation.
Development of Shape Memory Alloys

Recent development of shape memory alloys is reviewed, emphasis being placed on theTi–Ni, Cu–based and ferrous alloys which are considered as practical materials for applications among many shape memory alloys. Crystal structures of the parent and martensitic phases are described, and the crystallography of the martensitic transformations is also briefly explained. The origins of the shape memory effect and the shape memory mechanisms are discussed on the basis of the crystal structure and the crystallography of the martensitic transformations. Since an applied stress also induces the martensitic transformations, successive stages of the martensitic transformations are reviewed briefly in Cu–based and Ti–Ni alloys, which show martensite-to-martensite transformations upon loading. Then, characterization of the shape memory alloys are reviewed in detail; i.e., phase diagrams, transformation temperatures, transformation process, stress-induced transformation, aging effects, cycling effects, fracture, fatigue, grain refinement, and so on.
Weapon damage is associated with contest dynamics but not mating success in fallow deer (Dama dama)

Antlers function as primary weapons during fights for many species of ungulate. We examined the association between antler damage and (i) contest dynamics: the behavioural tactics used during fighting including fight duration, and (ii) mating success, fighting rate and dominance. Structural damage of the antlers was associated with contest dynamics: damage was negatively associated with jump clash attacks by individuals with damaged antlers, whereas opponents were more likely to physically displace individuals with damaged antlers during fighting. We found a positive association between dominance and damage indicating that high-ranking individuals were likely to have breaks to their antlers. We found no evidence that damage was associated with either mating success or the number of fights individuals engaged in. Our study provides a new perspective on understanding the association between contest dynamics and weapon structure, while also showing that damage has limited fitness consequences for individuals.
Evolution of developmental sequences in lepidosaurs

Background Lepidosaurs, a group including rhynchocephalians and squamates, are one of the major clades of extant vertebrates. Although there has been extensive phylogenetic work on this clade, its interrelationships are a matter of debate. Morphological and molecular data suggest very different relationships within squamates. Despite this, relatively few studies have assessed the utility of other types of data for inferring squamate phylogeny. Methods We used developmental sequences of 20 events in 29 species of lepidosaurs. These sequences were analysed using event-pairing and continuous analysis. They were transformed into cladistic characters and analysed in TNT. Ancestral state reconstructions were performed on two main phylogenetic hypotheses of squamates (morphological and molecular). Results Cladistic analyses conducted using characters generated by these methods do not resemble any previously published phylogeny. Ancestral state reconstructions are equally consistent with both morphological and molecular hypotheses of squamate phylogeny. Only several inferred heterochronic events are common to all methods and phylogenies. Discussion Results of the cladistic analyses, and the fact that reconstructions of heterochronic events show more similarities between certain methods rather than phylogenetic hypotheses, suggest that phylogenetic signal is at best weak in the studied developmental events. Possibly the developmental sequences analysed here evolve too quickly to recover deep divergences within Squamata.
Feature-Level Change Detection Using Deep Representation and Feature Change Analysis for Multispectral Imagery

Due to the noise interference and redundancy in multispectral images, it is promising to transform the available spectral channels into a suitable feature space for relieving noise and reducing the redundancy. The booming of deep learning provides a flexible tool to learn abstract and invariant features directly from the data in their raw forms. In this letter, we propose an unsupervised change detection technique for multispectral images, in which we combine deep belief networks (DBNs) and feature change analysis to highlight changes. First, a DBN is established to capture the key information for discrimination and suppress the irrelevant variations. Second, we map bitemporal change feature into a 2-D polar domain to characterize the change information. Finally, an unsupervised clustering algorithm is adopted to distinguish the changed and unchanged pixels, and then, the changed types can be identified by classifying the changed pixels into several classes according to the directions of feature changes. The experimental results demonstrate the effectiveness and robustness of the proposed method.
Automatic detection of facial actions from 3D data

We address the person-independent recognition problem of facial expressions using static 3D face data. The novel approach to the facial expression recognition uses non-rigid registration of surface curvature features. 3D face data is cast onto 2D feature images, which are then subjected to elastic deformations in their parametric space. Each Action Unit (AU) detector is trained over its respective influence domain on the face. The registration task is incorporated in the multiresolution elastic deformation scheme, which yields adequate registration accuracy for mild pose variations. The algorithm is fully automatic and is free of the burden of first localizing anatomical facial points. The algorithm was tested on 22 facial action units of Facial Action Coding System. Promising results obtained indicate that we have an operative device for facial action unit detection, and an intermediate step to infer emotional or mental states. Moreover, experiments conducted with low intensity AU12 - Lip Corner Puller points to the potential of 3D data and the proposed method in subtle expression detection.
In search of target class definition in tandem feature extraction

In the tandem feature extraction scheme a Multi-Layer Perceptron (MLP) with softmax output layer is discrimi-natively trained to estimate context independent phoneme posterior probabilities on a labeled database. The outputs of the MLP after nonlinear transformation and Principal Component Analysis (PCA) are used as features in a Gaussian Mixture Model (GMM) based recognizer. The baseline tandem system is trained on 56 Context Independent (CI) phoneme targets. In this paper we examine alternatives to CI phoneme targets by grouping phonemes using apriori and and data-derived knowledge. On connected digit recognition task we achieve comparable performance to the baseline system using fewer data-derived classes.
Automatic Acquisition of Ranked Qualia Structures from the Web

This paper presents an approach for the automatic acquisition of qualia structures for nouns from the Web and thus opens the possibility to explore the impact of qualia structures for natural language processing at a larger scale. The approach builds on earlier work based on the idea of matching specific lexico-syntactic patterns conveying a certain semantic relation on the World Wide Web using standard search engines. In our approach, the qualia elements are actually ranked for each qualia role with respect to some measure. The specific contribution of the paper lies in the extensive analysis and quantitative comparison of different measures for ranking the qualia elements. Further, for the first time, we present a quantitative evaluation of such an approach for learning qualia structures with respect to a handcrafted gold standard.
On the implausibility of classical client blind quantum computing

We define the functionality of delegated pseudo-secret random qubit generator (PSRQG), where a classical client can instruct the preparation of a sequence of random qubits at some distant party. Their classical description is (computationally) unknown to any other party (including the distant party preparing them) but known to the client. We emphasize the unique feature that no quantum communication is required to implement PSRQG. This enables classical clients to perform a class of quantum communication protocols with only a public classical channel with a quantum server. A key such example is the delegated universal blind quantum computing. Using our functionality one could achieve a purely classical-client computational secure verifiable delegated universal quantum computing (also referred to as verifiable blind quantum computation). We give a concrete protocol (QFactory) implementing PSRQG, using the Learning-With-Errors problem to construct a trapdoor one-way function with certain desired properties (quantum-safe, two-regular, collision-resistant). We then prove the security in the Quantum-Honest-But-Curious setting and briefly discuss the extension to the malicious case.
Role of analgesics, sedatives, neuromuscular blockers, and delirium

A major focus on critical care medicine concerns the institution of life-support therapies, such as mechanical ventilation, during periods of organ failure to permit a window of opportunity to diagnose and treat underlying disorders so that patients may be returned to their prior functional status upon recovery. With the growing success of these intensive care unit-based therapies and longer-term follow-up of patients, severe weakness involving the peripheral nervous system and muscles has been identified in many recovering patients, often confounding the time course or magnitude of recovery. Mechanical ventilation is often accompanied by pharmacologic treatments including analgesics, sedatives, and neuromuscular blockers. These drugs and the encephalopathies accompanying some forms of critical illness result in a high prevalence of delirium in mechanically ventilated patients. These drug effects likely contribute to an impaired ability to assess the magnitude of intensive care unit-acquired weakness, to additional time spent immobilized and mechanically ventilated, and to additional weakness from the patient’s relative immobility and bedridden state. This review surveys recent literature documenting these relationships and identifying approaches to minimize pharmacologic contributions to intensive care unit-acquired weakness.