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Food spoilage is mainly caused by microorganisms, such as bacteria. In this study, we measure the autofluorescence in meat samples longitudinally over a week in an attempt to develop a method to rapidly detect meat spoilage using fluorescence spectroscopy. Meat food is a biological tissue, which contains intrinsic fluorophores, such as tryptophan, collagen, nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD) etc. As meat spoils, it undergoes various morphological and chemical changes. The concentrations of the native fluorophores present in a sample may change. In particular, the changes in NADH and FAD are associated with microbial metabolism, which is the most important process of the bacteria in food spoilage. Such changes may be revealed by fluorescence spectroscopy and used to indicate the status of meat spoilage. Therefore, such native fluorophores may be unique, reliable and non-subjective indicators for detection of spoiled meat. The results of the study show that the relative concentrations of all above fluorophores change as the meat samples kept in room temperature (~19°C) spoil. The changes become more rapidly after about two days. For the meat samples kept in a freezer (~ -12°C), the changes are much less or even unnoticeable over a-week-long storage.

Native fluorescence spectra are acquired from fresh normal and cancerous human prostate tissues. The fluorescence data are analyzed using an unsupervised machine learning algorithm such as non-negative matrix factorization. The nonnegative spectral components are retrieved and attributed to the native fluorophores such as collagen, reduced nicotinamide adenine dinucleotide (NADH), and flavin adenine dinucleotide (FAD) in tissue. The retrieved scores of the components are used to estimate the relative concentrations of the native fluorophores such as NADH and FAD and the redox ratio. A supervised machine learning algorithm such as support vector machine (SVM) is used to classify normal and cancerous tissue samples based on either the relative concentrations of NADH and FAD or the redox ratio alone. Various statistical measures such as sensitivity, specificity, and accuracy, along with the area under receiver operating characteristic (ROC) curve are used to show the classification performance. A cross validation method such as leave-one-out is used to further evaluate the predictive performance of the SVM classifier to avoid bias due to overfitting, and the accuracy was found to be 93.3%.

Since 2014, NASA's K2 mission has observed large portions of the ecliptic plane in search of transiting planets and has detected hundreds of planet candidates. With observations planned until at least early 2018, K2 will continue to identify more planet candidates. We present here 275 planet candidates observed during Campaigns 0-10 of the K2 mission that are orbiting stars brighter than 13 mag (in Kepler band) and for which we have obtained high-resolution spectra (R = 44,000). These candidates are analyzed using the vespa package in order to calculate their false-positive probabilities (FPP). We find that 149 candidates are validated with an FPP lower than 0.1%, 39 of which were previously only candidates and 56 of which were previously undetected. The processes of data reduction, candidate identification, and statistical validation are described, and the demographics of the candidates and newly validated planets are explored. We show tentative evidence of a gap in the planet radius distribution of our candidate sample. Comparing our sample to the Kepler candidate sample investigated by Fulton et al., we conclude that more planets are required to quantitatively confirm the gap with K2 candidates or validated planets. This work, in addition to increasing the population of validated K2 planets by nearly 50% and providing new targets for follow-up observations, will also serve as a framework for validating candidates from upcoming K2 campaigns and the Transiting Exoplanet Survey Satellite, expected to launch in 2018. © 2018. The American Astronomical Society. All rights reserved.

The Leading Arm (LA) of the Magellanic Stream is a vast debris field of H i clouds connecting the Milky Way and the Magellanic Clouds. It represents an example of active gas accretion onto the Galaxy. Previously, only one chemical abundance measurement had been made in the LA. Here we present chemical abundance measurements using Hubble Space Telescope/Cosmic Origins Spectrograph and Green Bank Telescope spectra of four AGN sightlines passing through the LA and three nearby sightlines that may trace outer fragments of the LA. We find low oxygen abundances, ranging from 4.0-2.0+2.0% solar to 12.6-4.16.0% solar, in the confirmed LA directions, with the lowest values found in the region known as LA III, farthest from the LMC. These abundances are substantially lower than the single previous measurement, S/H =35 ±7% solar, but are in agreement with those reported in the SMC filament of the trailing Stream, supporting a common origin in the SMC (not the LMC) for the majority of the LA and trailing Stream. This provides important constraints for models of the formation of the Magellanic System. Finally, two of the three nearby sightlines show high-velocity clouds with H i columns, kinematics, and oxygen abundances consistent with LA membership. This suggests that the LA is larger than traditionally thought, extending at least 20° further to the Galactic northwest. © 2018. The American Astronomical Society. All rights reserved.

The goal of the research is to determine the prognostic molecular pathological changes in components and composition, for human brain glioma gradings in comparison with normal tissues in three-dimensional Raman imaging profiles by visible Resonance Raman (VRR) imaging. <p> </p>VRR images from twenty-five specimens including three healthy tissues, one normal control, and twenty-one glioma tissues of grades II, II-III and III-IV with histology examination were measured and investigated using WITec300R confocal micro Raman imaging system with laser excitation of 532nm. <p> </p>Two-dimensional RR spectral mappings performed in 20&mu;m x 20&mu;m generated 400 images which integrated the intensity of the specific biochemical bonds as the third dimension. The three-dimension (3D) map demonstrated the spatial distributions of three selected sets of RR spectra of molecular biomarkers, and revealed significant differences in the spectra between normal and glioma tissues of different grades due to the composition changes in key molimageecules. These RR molecular spectral fingerprints have displayed: a clear enhancement of RR vibrational modes at 1129-1131cm^-1 and 2934cm^-1 which are supposed to be arising from lipoproteins; evident decreased RR vibrational modes at 1442cm^-1 and 2854cm^-1 which are from saturated fatty acids bonds in all-grades of glioma brain tissues compared with normal tissues; and the enhanced RR spectral modes of 1129 cm^-1 and 2938cm^-1 which suggest contribution from lactate. These findings may provide a novel proof for anaerobic glycolysis metabolic process in brain glioma cancer tissues that has been explained by Warburg effects.

Analyzing spectral or imaging data collected with various optical biopsy methods is often times difficult due to the complexity of the biological basis. Robust methods that can utilize the spectral or imaging data and detect the characteristic spectral or spatial signatures for different types of tissue is challenging but highly desired. In this study, we used various machine learning algorithms to analyze a spectral dataset acquired from human skin normal and cancerous tissue samples using resonance Raman spectroscopy with 532nm excitation. The algorithms including principal component analysis, nonnegative matrix factorization, and autoencoder artificial neural network are used to reduce dimension of the dataset and detect features. A support vector machine with a linear kernel is used to classify the normal tissue and cancerous tissue samples. The efficacies of the methods are compared.

Worldwide breast cancer incidence has increased by more than twenty percent in the past decade. It is also known that in that time, mortality due to the affliction has increased by fourteen percent. Using optical-based diagnostic techniques, such as Raman spectroscopy, has been explored in order to increase diagnostic accuracy in a more objective way along with significantly decreasing diagnostic wait-times. In this study, Raman spectroscopy with 532-nm excitation was used in order to incite resonance effects to enhance Stokes Raman scattering from unique biomolecular vibrational modes. Seventy-two Raman spectra (41 cancerous, 31 normal) were collected from nine breast tissue samples by performing a ten-spectra average using a 500-ms acquisition time at each acquisition location. The raw spectral data was subsequently prepared for analysis with background correction and normalization. The spectral data in the Raman Shift range of 750- 2000 cm-1 was used for analysis since the detector has highest sensitivity around in this range. The matrix decomposition technique nonnegative matrix factorization (NMF) was then performed on this processed data. The resulting leave-oneout cross-validation using two selective feature components resulted in sensitivity, specificity and accuracy of 92.6%, 100% and 96.0% respectively. The performance of NMF was also compared to that using principal component analysis (PCA), and NMF was shown be to be superior to PCA in this study. This study shows that coupling the resonance Raman spectroscopy technique with subsequent NMF decomposition method shows potential for high characterization accuracy in breast cancer detection.

We report the first measurements of transverse single-spin asymmetries for inclusive jet and jet+π± production at midrapidity from transversely polarized proton-proton collisions at √s=500 GeV. The data were collected in 2011 with the STAR detector sampled from 23 pb−1 integrated luminosity with an average beam polarization of 53%. Asymmetries are reported for jets with transverse momenta 6<pT<55 GeV/c and pseudorapidity |η|<1. Presented are measurements of the inclusive-jet azimuthal transverse single-spin asymmetry, sensitive to twist-3 initial-state quark-gluon correlators; the Collins asymmetry, sensitive to quark transversity coupled to the polarized Collins fragmentation function; and the first measurement of the “Collins-like” asymmetry, sensitive to linearly polarized gluons. Within the present statistical precision, inclusive-jet and Collins-like asymmetries are small, with the latter allowing the first experimental constraints on gluon linear polarization in a polarized proton. At higher values of jet transverse momenta, we observe the first nonzero Collins asymmetries in polarized-proton collisions, with a statistical significance of greater than 5σ. The results span a range of x similar to results from semi-inclusive deep-inelastic scattering but at much higher Q2. The Collins results enable tests of universality and factorization breaking in the transverse momentum-dependent formulation of perturbative quantum chromodynamics.

We have measured the absolute proper motion of the Sextans dwarf spheroidal galaxy using Subaru Suprime-Cam images taken at three epochs, with a time baseline of ~10 yr. We astrometrically calibrate each epoch by constructing distortion-correction 'maps' from the best available Subaru Suprime-Cam dithered data sets and from Gaia Data Release 1 positions. The magnitude limit of the proper motion study is V ~ 24. The area covered is 26.7 × 23.3 arcmin2, which is still within the core radius of Sextans. The derived proper motion is (μα, μδ) = (-0.409 ± 0.050, -0.047 ± 0.058) mas yr-1. The direction of motion is perpendicular to the major axis of the galaxy. Our measurement, combined with radial velocity and distance from the literature, implies a low eccentricity orbit, with a moderate inclination to the Galactic plane, and a period of 3 Gyr. Sextans is now some 0.4 Gyr away from its pericentre (rperi ~ 75 kpc), moving towards its apocentre (rapo ~ 132 kpc). Its orbit is inconsistent with membership to the vast polar structure of Galactic satellites. © 2018 The Author(s).

In this review volume, the editors have included the state-of-the-art research and development in nano composites, and optical electronics written by experts in the field. In addition, it also covers applications for emerging technologies in High-Speed Electronics. In summary, topics covered in this volume includes various aspects of high performance materials and devices for implementing High-Speed Electronic systems. © 2019 by World Scientific Publishing Co. Pte. Ltd. All rights reserved.

Context.-Distinguishing chromophobe renal cell carcinoma (chRCC), especially in the presence of eosinophilic cytoplasm, from oncocytoma on hematoxylin-eosin can be difficult and often requires time-consuming ancillary procedures that ultimately may not be informative. Objective.-To explore the potential of multiphoton microscopy (MPM) as an alternative and rapid diagnostic tool in differentiating oncocytoma from chRCC at subcellular resolution without tissue processing. Design.-Unstained, deparaffinized tissue sections from 27 tumors (oncocytoma [n = 12], chRCC [n = 12], eosinophilic variant of chRCC [n = 1], and atypical oncocytic renal neoplasm [n = 2]) were imaged with MPM. Morphologic evaluation and automated quantitative morphometric analysis were conducted to distinguish between chRCC and oncocytoma. Results.-The typical cases of oncocytomas (12 of 12) and chRCC (12 of 12) could be readily differentiated on MPM based on the morphologic features similar to hematoxylin-eosin. The most striking MPM signature of both of the tumors was the presence of autofluorescent intracytoplasmic granules, which are not seen on hematoxylin-eosin-stained slides. Although we saw these granules in both types of tumors, they appeared distinct, based on their size, shape, cytoplasmic distribution, and autofluorescence wavelengths, and were valuable in arriving at a definitive diagnosis. For oncocytomas and chRCC, high diagnostic accuracies of 100% and 83.3% were achieved on blinded MPM and morphometric analysis, respectively. Conclusions.-To the best of our knowledge, this is the first demonstration of MPM to distinguish chRCC from oncocytoma in fixed tissues. Our study was limited by small sample size and only a few variants of oncocytic tumors. Prospective studies are warranted to assess the utility of MPM as a diagnostic aid in oncocytic renal tumors. © Copyright 2018 College of American Pathologists.

VRR spectroscopy was used for BCC and normal skin tissues with 532nm excitation. The spectra showed significant changes in collagen, carotenoids and lipids. These enhanced fingerprints demonstrate a potential use as label-free pathology method. © 2018 The Author(s).

A clear distinction between oncocytoma and chromophobe renal cell carcinoma (chRCC) is critically important for clinical management of patients. But it may often be difficult to distinguish the two entities based on hematoxylin and eosin (H and E) stained sections alone. In this study, second harmonic generation (SHG) signals which are very specific to collagen were used to image collagen fibril structure. We conduct a pilot study to develop a new diagnostic method based on the analysis of collagen associated with kidney tumors using convolutional neural networks (CNNs). CNNs comprise a type of machine learning process well-suited for drawing information out of images. This study examines a CNN model's ability to differentiate between oncocytoma (benign), and chRCC (malignant) kidney tumor images acquired with second harmonic generation (SHG), which is very specific for collagen matrix. To the best of our knowledge, this is the first study that attempts to distinguish the two entities based on their collagen structure. The model developed from this study demonstrated an overall classification accuracy of 68.7% with a specificity of 66.3% and sensitivity of 74.6%. While these results reflect an ability to classify the kidney tumors better than chance, further studies will be carried out to (a) better realize the tumor classification potential of this method with a larger sample size and (b) combining SHG with two-photon excited intrinsic fluorescence signal to achieve better classification. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

Resonance Raman spectroscopy using 532nm excitation was used to distinguish normal brain tissue from different grades of glioma tissues. Principal component analysis was used to analyze the spectral data and achieved high accuracy. © 2018 The Author(s).

We are conducting a search for binary companions around 11 hot-Jupiter hosts from the Kilodegree Extremely Little Telescope (KELT) survey and a large comparison sample of stars shown by KELT to not host a transiting hot Jupiter. The primary stars are bright (7.5 < V < 11) and of similar distance from Earth (100 < d < 300 pc). In this paper, we present the results of our observations using the Differential Speckle Survey Instrument. We observed 9 of the 14 KELT planet hosts that are visible from the northern hemisphere and 51 comparison stars, discovering two new potential companions and re-observing two previously known possible binary systems and one confirmed binary system. We provide an estimate of the chance alignment probability for our observed candidate binaries. © 2017 The American Astronomical Society. All rights reserved.

A main goal of NASA's Kepler Mission is to establish the frequency of potentially habitable Earth-size planets (). Relatively few such candidates identified by the mission can be confirmed to be rocky via dynamical measurement of their mass. Here we report an effort to validate 18 of them statistically using the BLENDER technique, by showing that the likelihood they are true planets is far greater than that of a false positive. Our analysis incorporates follow-up observations including high-resolution optical and near-infrared spectroscopy, high-resolution imaging, and information from the analysis of the flux centroids of the Kepler observations themselves. Although many of these candidates have been previously validated by others, the confidence levels reported typically ignore the possibility that the planet may transit a star different from the target along the same line of sight. If that were the case, a planet that appears small enough to be rocky may actually be considerably larger and therefore less interesting from the point of view of habitability. We take this into consideration here and are able to validate 15 of our candidates at a 99.73% (3σ) significance level or higher, and the other three at a slightly lower confidence. We characterize the GKM host stars using available ground-based observations and provide updated parameters for the planets, with sizes between 0.8 and 2.9 R ⊕. Seven of them (KOI-0438.02, 0463.01, 2418.01, 2626.01, 3282.01, 4036.01, and 5856.01) have a better than 50% chance of being smaller than 2 R ⊕ and being in the habitable zone of their host stars. © 2017. The American Astronomical Society. All rights reserved..

We recently used near-infrared spectroscopy to improve the characterization of 76 low-mass stars around which K2 had detected 79 candidate transiting planets. 29 of these worlds were new discoveries that had not previously been published. We calculate the false positive probabilities that the transit-like signals are actually caused by non-planetary astrophysical phenomena and reject five new transit-like events and three previously reported events as false positives. We also statistically validate 17 planets (7 of which were previously unpublished), confirm the earlier validation of 22 planets, and announce 17 newly discovered planet candidates. Revising the properties of the associated planet candidates based on the updated host star characteristics and refitting the transit photometry, we find that our sample contains 21 planets or planet candidates with radii smaller than 1.25 R ⊕, 18 super-Earths (1.25-2 R ⊕), 21 small Neptunes (2-4 R ⊕), three large Neptunes (4-6 R ⊕), and eight giant planets (&gt;6 R ⊕). Most of these planets are highly irradiated, but EPIC 206209135.04 (K2-72e, ), EPIC 211988320.01 (), and EPIC 212690867.01 () orbit within optimistic habitable zone boundaries set by the "recent Venus" inner limit and the "early Mars" outer limit. In total, our planet sample includes eight moderately irradiated 1.5-3 R ⊕ planet candidates (F p ≲ 20 F ⊕) orbiting brighter stars (Ks &lt; 11) that are well-suited for atmospheric investigations with the Hubble, Spitzer, and/or James Webb Space Telescopes. Five validated planets orbit relatively bright stars (Kp &lt; 12.5) and are expected to yield radial velocity semi-amplitudes of at least 2 m s-1. Accordingly, they are possible targets for radial velocity mass measurement with current facilities or the upcoming generation of red optical and near-infrared high-precision RV spectrographs. © 2017. The American Astronomical Society. All rights reserved..

We propose the measurement of net Λ and Λ helicity, correlated event by event with the magnitude and sign of charge separation along the event's magnetic field direction, as a probe to investigate the chiral magnetic effect (CME) in heavy-ion collisions. With a simple simulation model of heavy-ion events that includes effects of local parity violation, we estimate the experimental correlation signal that could be expected at RHIC given the results of previous measurements that are sensitive to the CME. © 2017 American Physical Society.

We present measurements of bulk properties of the matter produced in Au+Au collisions at √sNN=7.7,11.5,19.6,27, and 39 GeV using identified hadrons (π±, K±, p, and ¯p) from the STAR experiment in the Beam Energy Scan (BES) Program at the Relativistic Heavy Ion Collider (RHIC). Midrapidity (|y|<0.1) results for multiplicity densities dN/dy, average transverse momenta ⟨pT⟩, and particle ratios are presented. The chemical and kinetic freeze-out dynamics at these energies are discussed and presented as a function of collision centrality and energy. These results constitute the systematic measurements of bulk properties of matter formed in heavy-ion collisions over a broad range of energy (or baryon chemical potential) at RHIC.

Given the frequency of stellar multiplicity in the solar neighborhood, it is important to study the impacts this can have on exoplanet properties and orbital dynamics. There have been numerous imaging survey projects established to detect possible low-mass stellar companions to exoplanet host stars. Here, we provide the results from a systematic speckle imaging survey of known exoplanet host stars. In total, 71 stars were observed at 692 and 880 nm bands using the Differential Speckle Survey Instrument at the Gemini-north Observatory. Our results show that all but two of the stars included in this sample have no evidence of stellar companions with luminosities down to the detection and projected separation limits of our instrumentation. The mass-luminosity relationship is used to estimate the maximum mass a stellar companion can have without being detected. These results are used to discuss the potential for further radial velocity follow-up and interpretation of companion signals. © 2017. The American Astronomical Society. All rights reserved..