Miracle-dz/UniFAR-FTUs huggingface dataset:
Air-coupled ultrasonic tomographic imaging of concrete elements

Ultrasonic tomography is a powerful tool for identifying defects within an object or structure. This method can be applied on structures where x-ray tomography is impractical due to size, low contrast, or safety concerns. By taking many ultrasonic pulse velocity (UPV) readings through the object, an image of the internal velocity variations can be constructed. Air-coupled UPV can allow for more automated and rapid collection of data for tomography of concrete. This research aims to integrate recent developments in air-coupled ultrasonic measurements with advanced tomography technology and apply them to concrete structures. First, non-contact and semi-contact sensor systems are developed for making rapid and accurate UPV measurements through PVC and concrete test samples. A customized tomographic reconstruction program is developed to provide full control over the imaging process including full and reduced spectrum tomographs with percent error and ray density calculations. Finite element models are also used to determine optimal measurement configurations and analysis procedures for efficient data collection and processing. Non-contact UPV is then implemented to image various inclusions within 6 inch (152 mm) PVC and concrete cylinders. Although there is some difficulty in identifying high velocity inclusions, reconstruction error values were in the range of 1.1-1.7% for PVC and 3.6% for concrete. Based upon the success of those tests, further data are collected using non-contact, semi-contact, and full contact measurements to image 12 inch (305 mm) square concrete cross-sections with 1 inch (25 mm) reinforcing bars and 2 inch (51 mm) square embedded damage regions. Due to higher noise levels in collected signals, tomographs of these larger specimens show reconstruction error values in the range of 10-18%. Finally, issues related to the application of these techniques to full-scale concrete structures are discussed.
Increased Expression of CSF-1 Associates With Poor Prognosis of Patients With Gastric Cancer Undergoing Gastrectomy

AbstractClinical significance of diametrically polarized tumor-associated macrophages in gastric cancer has been elucidated in our previous study, whereas the role of cytokines that orchestrate tumor-associated macrophages polarization in gastric cancer remains elusive. The study aims to evaluate the prognostic value of colony-stimulating factor-1 expression in patients with gastric cancer.We examined the colony-stimulating factor-1 expression in tumor tissues by immunohistochemical staining in retrospectively enrolled 365 patients with gastric cancer undergoing gastrectomy at Zhongshan Hospital during 2008. Kaplan–Meier analysis and Cox regression models were used to evaluate the prognostic value of colony-stimulating factor-1 expression and its association with clinicopathological factors. A predictive nomogram by integrating colony-stimulating factor-1 expression with the TNM staging system was generated for overall survival evaluation of the patients.High colony-stimulating factor-1 expression predicted an unfavorable outcome in gastric cancer. The colony-stimulating factor-1 expression in tumor tissue could give a further discrimination for the prognosis of gastric cancer patients. Cox multivariate analysis identified the colony-stimulating factor-1 expression as an independent prognostic factor. The generated nomogram performed well in predicting the 3- and 5-year overall survival of gastric cancer patients.The colony-stimulating factor-1 is a potential independent adverse prognosticator for gastric cancer patients, which could be integrated with the tumor-associated macrophages staging system to improve the predictive accuracy for overall survival, especially in advanced tumors.
Co-sensitized natural dyes potentially used to enhance light harvesting capability

We present the photoelectrochemical properties of dye-sensitized solar cells using natural pigments containing anthocyanins, betalains, and caroteins. The dyes were adsorbed by a photoanode that was fabricated from nanocrystalline TiO2 on transparent conductive glass. TiO2 comprises of 100% anatase and 90:10 anatase:rutile fraction. The dyes extracted from mangosteen pericarp, Musa aromatica pericarp, Celosia cristata flower and red beet root were characterized through UV-vis and IPCE. The effectiveness of the dyes was explained through photocurrent as a function of incident light power. It was found that the cocktail and multilayered dyes comprised of anthocyanins and caroteins is beneficial to obtain high photocurrent, whereas betalains is not recommended to be applied on untreated TiO2. Due to the bandgap properties of rutile and anatase, the presence of 10% rutile in TiO2 is favourable to further enhance the electron transport.
The vacuolar proton-ATPase plays a major role in several membrane-bounded organelles in Paramecium

The vacuolar proton-ATPase (V-ATPase) is a multisubunit enzyme complex that is able to transfer protons over membranes against an electrochemical potential under ATP hydrolysis. The enzyme consists of two subcomplexes: V0, which is membrane embedded; and V1, which is cytosolic. V0 was also reported to be involved in fusion of vacuoles in yeast. We identified six genes encoding c-subunits (proteolipids) of V0 and two genes encoding F-subunits of V1 and studied the role of the V-ATPase in trafficking in Paramecium. Green fluorescent protein (GFP) fusion proteins allowed a clear subcellular localization of c- and F-subunits in the contractile vacuole complex of the osmoregulatory system and in food vacuoles. Several other organelles were also detected, in particular dense core secretory granules (trichocysts). The functional significance of the V-ATPase in Paramecium was investigated by RNA interference (RNAi), using a recently developed feeding method. A novel strategy was used to block the expression of all six c- or both F-subunits simultaneously. The V-ATPase was found to be crucial for osmoregulation, the phagocytotic pathway and the biogenesis of dense core secretory granules. No evidence was found supporting participation of V0 in membrane fusion.
A hybrid approach to cluster detection

Recent technological advances require computer algorithms that can effectively analyze and classify data on a large scale that was unachievable just a few years ago. For instance, in response to a query, commercial search engines routinely consider web pages amounting into billions while genomic searches may deal with a search space of a similar or even higher magnitude. Clustering algorithms are an ideal choice to quickly categorize data; they are conceptually simple and require little background knowledge. Many clustering algorithms have been introduced in recent decades; but each approach brought along new challenges to consider, such as outlier handling, detection of arbitrary shaped clusters, processing speed, and dependence on usersupplied parameters. PYRAMID, or parallel hybrid clustering using genetic programming and multiobjective fitness with density, is a clustering algorithm that we introduced in a previous research. It addresses several of the above challenges by using a combination of data parallelism, a form of genetic programming, and a multi-objective density-based fitness function. This paper summarizes some of the characteristics of PYRAMID along with experiments that were performed on multiple challenging datasets. Empirical results derived from these experiments are presented and future directions are proposed.
Utility of polarized dermoscopy in the diagnosis of cutaneous lupus erythematosus and morphea

Dermoscopy is a non-invasive in vivo technique to help visualize morphological structures on the surface and subsurface of the skin, non-visible with the naked eye. It is tipically used to improve the diagnostic accuracy of pigmented skin lesions and skin tumors, but in recent years its use has been extended to other dermatological conditions. The use of polarized light in dermoscopy allows a better visualization of vascular structures and other changes in the dermis such as collagen depositin and fibrosis, which would make it a good tool for clinical orientation in inflammatory conditions such as cutaneous lupus erythematosus and morphea, considered in the spectrum of autoimmune connective tissue diseases, with diverse clinical cutaneous manifestations. Up to date studies of dermoscopic clues in these two entities are still scarce and results are not uniform. We performed a retrospective analysis of dermoscopic images in patients with pathological confirmation of the clinical diagnosis in order to find the common features and clues for dermoscopic diagnosis.
Influence of carbon black in polychloroprene organoclay nanocomposite with improved mechanical, electrical and morphology characteristics

The effect of carbon black on nanoclay filled polychloroprene (CR) composites has been investigated. The nanoclay loading is fixed at 5 part per hundred rubbers (phr), and carbon black loading varied from 5 to 20 phr in rubber compounds. The rubber nanocomposites are prepared in laboratory by mixing in two-roll mill. The addition of nanoclay enhances mechanical properties especially tear strength and decreases water absorption without change in electrical properties compared to gum rubber vulcanisates. Wide angle X-ray diffraction and transmission electron microscopy are used to study the microstructure of CR nanocomposites. The addition of 5 parts of nanoclay to 15 phr carbon black filled samples shows synergistic effect between the fillers and suggests that the reinforcement is due to a more developed filler network formation in hybrid filler system than that in single phase filler. Significant improvement in mechanical, electrical and low water absorption properties has been obtained with these nanoclay and carbon black filled rubber nanocomposites. The paper concludes that nanocomposites containing a mixture of organoclay and carbon black in right proportion can be a substitute for rubber components used in underwater cable and device encapsulation applications.
Model‐based design of experiments for cellular processes

Model‐based design of experiments (MBDOE) assists in the planning of highly effective and efficient experiments. Although the foundations of this field are well‐established, the application of these techniques to understand cellular processes is a fertile and rapidly advancing area as the community seeks to understand ever more complex cellular processes and systems. This review discusses the MBDOE paradigm along with applications and challenges within the context of cellular processes and systems. It also provides a brief tutorial on Fisher information matrix (FIM)‐based and Bayesian experiment design methods along with an overview of existing software packages and computational advances that support MBDOE application and adoption within the Systems Biology community. As cell‐based products and biologics progress into the commercial sector, it is anticipated that MBDOE will become an essential practice for design, quality control, and production. WIREs Syst Biol Med 2013, 5:181–203. doi: 10.1002/wsbm.1204
The Characterization of Soil Properties to Develop “Soil Management/Mapping Units” Using High-Resolution Remotely Sensed Data Sets

The intent of this research was to assess the possible use of high resolution remotely sensed hyperspectral and multispectral data to characterize soil types, specifically focusing on organic matter content, in an associative manner with the results obtained from traditional Order 1 and Order 2 soil surveys. A chi-square analysis indicated a strong association between soil type and organic matter content. A Cramer’s V analysis (of a supervised classification) indicated a stronger relationship between the Order 1 and organic matter. However, when an unsupervised classification scheme was applied to the aerial imagery, again using Cramer’s analysis, the Order 2 out-performed the Order 1. This superior performance was due in part to the grouping of multi-band spectral response patterns into statistically separable clusters. A One-Way ANOVA analysis indicated that all soils were significantly different in the Order 2 survey for both the hyperspectral and the multispectral data sets. However, the Order 1 results show the ITD sensor more successfully grouping the darker soils than did the ATLAS which grouped the lighter soils. A linear discriminate analysis (LDA) demonstrates that the computer classification of images more successfully assessed the Order 2 survey than the Order 1. Again it is worth noting that the LDA also grouped the soils in a similar manner as did the ANOVA in that the ITD sensor grouped the darker soils and the ATLAS sensor grouped the lighter soils. This sensor preference is another significant secondary finding of this study. Despite the subjective nature of the soil mapping exercise and the use of un-calibrated data sets, high resolution imagery was able to differentiate different soil mapping scales. Even though associations were relatively low statistically, this study supports the hypothesis that high resolution imagery, although limited by its two-dimensional capabilities, can be effectively used as a predictive tool, although with the current technological limits, the imagery cannot serve as a surrogate for more traditional soil surveys.
Discovery of local topics by using latent spatio-temporal relationships in geo-social media

ABSTRACT Social networks have played a crucial role as information channels for people to understanding their daily lives beyond merely being communication tools. In particular, coupling social networks with geographic location has boosted the worth of social media to not only enable comprehension of the effects of natural phenomena such as global warming and disasters, but also the social patterns of human societies. However, the high rate of social data generation and the large amounts of noisy data makes it difficult to directly apply social media to decision-making processes. This article proposes a new system of analyzing the spatio-temporal patterns of social phenomena in real time and the discovery of local topics based on their latent spatio-temporal relationships. We will first describe a model that represents the local patterns of populations of geo-tagged social media. We will then define a local topic whose keywords share a region in space and time and present a system implementation based on existing open source technologies. We evaluated the model of local topics with several ways of visualization in experiments and demonstrated a certain social pattern from a dataset of daily Twitter streams. The results obtained from experiments revealed certain keywords had a strong spatio-temporal proximity even though they did not occur in the same message.
Is Schizotypy per se a Suitable Endophenotype of Schizophrenia? – Do Not Forget to Distinguish Positive from Negative Facets

In 2003, Gottesman and Gould advocated using the endophenotype concept in psychiatry genetics; describing it as a measurable component “along the pathway between disease and distal genotype” (p. 636). Especially in schizophrenia research, the idea of endophenotypes has gathered a wide following. Meehl’s definition of schizotaxia [Ref. (1), p. 829], as “an ‘integrative neural defect’ as the only direct phenotypic consequence produced by the genetic mutation” and “This neural integrative defect […] is all that can properly be spoken of as inherited. The imposition of a social learning history upon schizotaxic individuals results in a personality organization which I shall call, following Rado, the schizotype” (p. 830; my emphasis) reminds clearly of the aforementioned endophenotype description.
Digital analysis technique for uncertainty reduction in colorimetric arsenic detection method

This article proposes an alternative to increase the reliability and reproducibility of a colorimetric method to measure arsenic (As) concentrations. The method of analysis developed incorporates a digital analysis technique to eliminate the operator dependence of results, and As concentrations are quantitatively determined from digital levels computed from photographs of the colorimetric reaction that emerges during the test. This technique allows the sensitivity of the detection to be increased at low concentration ranges, which is of fundamental importance for the detection of As given the current acceptable limit for drinking water. The results obtained show a very good correlation between As concentrations determined by means of analytical laboratory techniques and the method proposed in this research.
Blind quantum computing with two almost identical states

The question of whether a fully classical client can delegate a quantum computation to an untrusted quantum server while fully maintaining privacy (blindness) is one of the big open questions in quantum cryptography. Both yes and no answers have important practical and theoretical consequences, and the question seems genuinely hard. The state-of-the-art approaches to securely delegating quantum computation, without exception, rely on granting the client modest quantum powers, or on additional, non-communicating, quantum servers. In this work, we consider the single server setting, and push the boundaries of the minimal devices of the client, which still allow for blind quantum computation. Our approach is based on the observation that, in many blind quantum computing protocols, the "quantum" part of the protocol, from the clients perspective, boils down to the establishing classical-quantum correlations (independent from the computation) between the client and the server, following which the steering of the computation itself requires only classical communication. Here, we abstract this initial preparation phase, specifically for the Universal Blind Quantum Computation protocol of Broadbent, Fitzsimons and Kashefi. We identify sufficient criteria on the powers of the client, which still allow for secure blind quantum computation. We work in a universally composable framework, and provide a series of protocols, where each step reduces the number of differing states the client needs to be able to prepare. As the limit of such reductions, we show that the capacity to prepare just two pure states, which have an arbitrarily high overlap (thus are arbitrarily close to identical), suffices for efficient and secure blind quantum computation.
Acceptability and benefit of rectal irrigation in patients with low anterior resection syndrome: a qualitative study

Low anterior resection syndrome (LARS) following rectal cancer surgery impairs the patient's quality of life (QoL). Rectal irrigation has been demonstrated to be effective for anterior resection syndrome but many surgeons do not suggest it as a treatment. This feasibility study aimed to explore treatment acceptability and the benefit of rectal irrigation in patients who developed LARS following an anterior resection for rectal cancer.
Factorial models and refiltering for speech separation and denoising

This paper proposes the combination of several ideas, some old and some new, from machine learning and speech processing. We review the max approximation to log spectrograms of mixtures, show why this motivates a “refiltering” approach to separation and denoising, and then describe how the process of inference in factorial probabilistic models performs a computation useful for deriving the masking signals needed in refiltering. A particularly simple model, factorial-max vector quantization (MAXVQ), is introduced along with a branch-and-bound technique for efficient exact inference and applied to both denoising and monaural separation. Our approach represents a return to the ideas of Ephraim, Varga and Moore but applied to auditory scene analysis rather than to speech recognition. 1. Sparsity & Redundancy in Spectrograms 1.1. The Log-MaxApproximation When two clean speech signals are mixed additively in the time domain, what is the relationship between the individual log spectrograms of the sources and the log spectrogram of the mixture? Unless the sources are highly dependent (synchronized), the spectrogram of the mixture is almost exactly the maximum of the individual spectrograms, with the maximum operating over small time-frequency regions (fig. 2). This amazing fact, first noted by Roger Moore in 1983, comes from the fact that unless e1 and e2 are both large and almost equal, log(e1 + e2) ≈ max(log e1, log e2) (fig. 1a). The sparse nature of the speech code across time and frequency is the key to the practical usefulness of this approximation: most narrow frequency bands carry substantial energy only a small fraction of the time and thus it is rare that two independent sources inject large amounts of energy into the same subband at the same time. (Figure 1b shows a plot of the relative energy of two simultaneous speakers in a narrow subband; most of the time at least one of the two sources shows negligible power.) 1.2. Masking and Refiltering Fortunately, the speech code is also redundant across timefrequency. Different frequency bands carry, to a certain extent, independent information and so if information in some bands is suppressed or masked, even for significant durations, other bands can fill in. (A similar effect occurs over time: if brief sections of the signal are obscured, even across all bands, the speech is still intelligible; while also useful, we do not exploit this here.) This is partly why humans perform so well on many monaural speech separation and denoising tasks. When we solve the cocktail party problem or recognize degraded speech, we are doing structural analysis, or a kind of “perceptual grouping” on the incoming sound. There is substantial evidence that the appropriate subparts of an audio signal for use in grouping may be narrow frequency bands over short times. To generate these parts computationally, we can perform multiband analysis – break the original speech signal y(t) into many subband signals bi(t) each lo g e2 ma
Safety of Oxygreen®, an ozone treatment on wheat grains. Part 2. Is there a substantial equivalence between Oxygreen-treated wheat grains and untreated wheat grains?

The Oxygreen® process is a new process based on wheat grain treatment by ozone (produced in situ), in a closed sequential batch reactor. The Oxygreen® process offers a close, homogeneous, and controlled contact between the gas and the grain. It is proposed for use for wheat grain decontamination (insects, fungi, bacteria, mycotoxins, pesticides). It takes place in classical milling diagram, and occurs after grain cleaning and before milling. The aim of the study reported here was to determine if Oxygreen® treatment could induce in the grain the formation of processing-related compounds, and if these compounds are specific or could be recognized as classical modifications already used in the cereal industry (milling, baking). Studies were performed in order to evaluate any effect of Oxygreen® treatment on vitamins, ferulic acid, phytates, proteins, carbohydrates, and lipids. It was concluded that there was no detectable substantial difference between ozone-treated grains and the untreated ones, although some quantitative differences can occur. The more detectable differences concern concentration of free sugars, and inhibition of some oxidative enzymes. These quantitative differences are very slight compared to the modifications that occur in dough, after addition of oxidative products directly in flour, or during kneading and dough fermentation.