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[1] The Hawaii Scientific Drilling Program (HSDP) cored and recovered igneous rock from the surface to a depth of 3109 m near Hilo, Hawaii. Much of the deeper parts of the hole is composed of hyaloclastite (fractured basalt glass that has been cemented in situ with secondary minerals). Some hyaloclastite units have been altered in a manner attributed to microorganisms in volcanic rocks. Samples from one such unit (1336 m to 1404 m below sea level) were examined to test the hypothesis that the alteration was associated with microorganisms. Deep ultraviolet native fluorescence and resonance Raman spectroscopy indicate that nucleic acids and aromatic amino acids are present in clay inside spherical cavities (vesicles) within basalt glass. Chemical mapping shows that phosphorus and carbon were enriched at the boundary between the clay and volcanic glass of the vesicles. Environmental scanning electron microscopy (ESEM) reveals two to three micrometer coccoid structures in these same boundaries. ESEM-linked energy dispersive spectroscopy demonstrated carbon, phosphorous, chloride, and magnesium in these bodies significantly differing from unoccupied neighboring regions of basalt. These observations taken together indicate the presence of microorganisms at the boundary between primary volcanic glass and secondary clays. Amino acids and nucleic acids were extracted from bulk samples of the hyaloclastite unit. Amino acid abundance was low, and if the amino acids are derived from microorganisms in the rock, then there are less than 100,000 cells per gram of rock. Most nucleic acid sequences extracted from the unit were closely related to sequences of Crenarchaeota collected from the subsurface of the ocean floor.

Quantitative morphological classication of galaxies is important for understanding the origin of type frequency and correlations with environment. But galaxy morphological classication is still mainly done visually by dedicated individuals, in the spirit of Hubble's original scheme, and its modications. The rapid increase in data on galaxy images 1 at low and high redshift calls for re-examination of the classication schemes and for new automatic methods. Here we show results from the rst systematic comparison of the dispersion among human experts classifying a uniformly selected sample of over 800 digitised galaxy images. These galaxy images were then classied by six of the authors independently. The human classications are compared with each other, and with an automatic classication by Articial Neural Networks (ANN). It is shown that the ANNs can replicate the classication by a h uman expert to the same degree of agreement as that between two h uman experts.Hubble (1) suggested a classication scheme for galaxies which consists of a sequence starting from elliptical galaxies (E) , through lenticular (S0), to spiral galaxies (S), and a parallel branch of spirals with a barred component, leading to the so called`tuning fork' Hubble diagram. This scheme has been extended by astronomers over the years (2{5), to incorporate features such as the strength of the spiral arms, yielding multi-dimensional classication (3; 5). It is remarkable that these somewhat subjective classication labels for galaxies (as seen projected on the sky) correlate well with physical properties such a s colour, dynamical properties (e.g. rotation curves and stellar velocity dispersions) and the mass in neutral hydrogen (6). However, one would like e v entually to devise a scheme of classication, which can be related to the physical processes of galaxy formation. While there have been in recent y ears signicant advances in observational techniques (e.g. telescopes, detectors and reduction algorithms) as well as in theoretical modelling (e.g. N-body and hydrodynamics simulations), galaxy classication remains a subjective area.Quantifying galaxy morphology is important for various reasons. First, it provides important clues to the origin of galaxies and their formation processes. For example, ellipticals and lenticular galaxies comprise only 20% of the galaxies, and there is a striking density-morphology relation (1; 7), indicating that elliptical galaxies mainly re-2 side in high-density regions. Understanding the origin of the type frequency and the density-morphology relation is clearly of fundamental importance. But quantifying these properties requires reliable classication schemes. Second, galaxies can also be used e.g. to measure redshift-independent distances by methods such as the luminosity-rotation velocity relation for spirals (8) and the diameter-velocity dispersion for ellipticals (9). Clearly any observational programme requires an a priori target list of objects for photometric or spectrographic measurements. Therefore galaxy cl...

We apply and compare various Arti cial Neural Network (ANN) and other algorithms for automatic morphological classi cation of galaxies. The ANNs are presented here mathematically, as non-linear extensions of conventional statistical methods in Astronomy. The methods are illustrated using di erent subsets from the ESO-LV catalogue, for which both machine parameters and human classi cation are available. The main methods we explore are: (i) Principal Component Analysis (PCA) which tells how independent and informative the input parameters are. (ii) Encoder Neural Network which allows us to nd both linear (PCA-like) and non-linear combinations of the input, illustrating an example of unsupervised ANN. (iii) Supervised ANN (using the Backpropagation or Quasi-Newton algorithms) based on a training set for which the human classi cation is known. Here the output for previously unclassi ed galaxies can be interpreted as either a continuous (analog) output (e.g. T-type) or a Bayesian a posteriori probability for each class. Although the ESO-LV parameters are sub-optimal, the success of the ANN in reproducing the human classi cation is 2 T-type units, similar to the degree of agreement between two human experts who classify the same galaxy images on plate material. We also examine the aspects of ANN con gurations, reproducibility, scaling of input parameters and redshift information.

We train Arti cial Neural Networks to classify galaxies based solely on the morphology of the galaxy images as they appear on blue survey plates. The images are reduced and morphological features such as bulge size and the number of arms are extracted, all in a fully automated manner. The galaxy sample was rst classi ed by 6 independent experts. We use several de nitions for the mean type of each galaxy, based on those classi cations. We then train and test the network on these features. We nd that the rms error of the network classi cations, as compared with the mean types of the expert classi cations, is 1.8 Revised Hubble Types. This is comparable to the overall rms dispersion between the experts. This result is robust and almost completely independent of the network architecture used.

Failure to precisely distinguish malignant from healthy tissue has severe implications for breast cancer surgical outcomes. Clinical prognoses depend on precisely distinguishing healthy from malignant tissue during surgery. Laser Raman spectroscopy (LRS) has been previously shown to differentiate benign from malignant tissue in real time. However, the cost, assembly effort, and technical expertise needed for construction and implementation of the technique have prohibited widespread adoption. Recently, Raman spectrometers have been developed for non-medical uses and have become commercially available and affordable. Here we demonstrate that this current generation of Raman spectrometers can readily identify cancer in breast surgical specimens. We evaluated two commercially available, portable, near-infrared Raman systems operating at excitation wavelengths of either 785 nm or 1064 nm, collecting a total of 164 Raman spectra from cancerous, benign, and transitional regions of resected breast tissue from six patients undergoing mastectomy. The spectra were classified using standard multivariate statistical techniques. We identified a minimal set of spectral bands sufficient to reliably distinguish between healthy and malignant tissue using either the 1064 nm or 785 nm system. Our results indicate that current generation Raman spectrometers can be used as a rapid diagnostic technique distinguishing benign from malignant tissue during surgery.

"Hairy blobs" are unusual clumps of organic bodies and sulfate crystals that have been found in evaporite minerals grown in acid saline lakes. Here, we document modern hairy blobs in halite and gypsum from 5 modern acid saline lakes in southern Western Australia, and Permian hairy blobs trapped in halite from the mid-Permian Opeche Shale in the subsurface of North Dakota. These are among the first microbial remains described from acid saline lake environments. They give clues about the role of microorganisms in the acidity, geochemistry, and mineralogy of these extreme environments. This study also may add to the inventory of life in extreme environments and help predict possible martian life-forms and the method of preservation.

We examined the common, iron-magnesium silicate minerals olivine and pyroxene in basalt and in mantle rocks to determine if they exhibit textures similar to bioweathering textures found in glass. Our results show that weathering in olivine may occur as long, narrow tunnels (1-3 microm in diameter and up to 100 microm long) and as larger irregular galleries, both of which have distinctive characteristics consistent with biological activity. These weathering textures are associated with clay mineral by-products and nucleic acids. We also examined olivine and pyroxene in martian meteorites, some of which experienced preterrestrial aqueous alteration. Some olivines and pyroxenes in the martian meteorite Nakhla were found to contain tunnels that are similar in size and shape to tunnels in terrestrial iron-magnesium silicates that contain nucleic acids. Though the tunnels found in Nakhla are similar to the biosignatures found in terrestrial minerals, their presence cannot be used to prove that the martian alteration features had a biogenic origin. The abundance and wide distribution of olivine and pyroxene on Earth and in the Solar System make bioweathering features in these minerals potentially important new biosignatures that may play a significant role in evaluating whether life ever existed on Mars.