Tensor Networks for Dimensionality Reduction and Large-Scale Optimizations. Part 2 Applications and Future Perspectives

Part 2 of this monograph builds on the introduction to tensor networks and their operations presented in Part 1. It focuses on tensor network models for super-compressed higher-order representation of data/parameters and related cost functions, while providing an outline of their applications in machine learning and data analytics. A particular emphasis is on the tensor train (TT) and Hierarchical Tucker (HT) decompositions, and their physically meaningful interpretations which reflect the scalability of the tensor network approach. Through a graphical approach, we also elucidate how, by virtue of the underlying low-rank tensor approximations and sophisticated contractions of core tensors, tensor networks have the ability to perform distributed computations on otherwise prohibitively large volumes of data/parameters, thereby alleviating or even eliminating the curse of dimensionality. The usefulness of this concept is illustrated over a number of applied areas, including generalized regression and classification (support tensor machines, canonical correlation analysis, higher order partial least squares), generalized eigenvalue decomposition, Riemannian optimization, and in the optimization of deep neural networks. Part 1 and Part 2 of this work can be used either as stand-alone separate texts, or indeed as a conjoint comprehensive review of the exciting field of low-rank tensor networks and tensor decompositions.Comment: 232 page

Tensor Networks for Dimensionality Reduction and Large-Scale Optimizations. Part 2 Applications and Future Perspectives

Part 2 of this monograph builds on the introduction to tensor networks and their operations presented in Part 1. It focuses on tensor network models for super-compressed higher-order representation of data/parameters and related cost functions, while providing an outline of their applications in machine learning and data analytics. A particular emphasis is on the tensor train (TT) and Hierarchical Tucker (HT) decompositions, and their physically meaningful interpretations which reflect the scalability of the tensor network approach. Through a graphical approach, we also elucidate how, by virtue of the underlying low-rank tensor approximations and sophisticated contractions of core tensors, tensor networks have the ability to perform distributed computations on otherwise prohibitively large volumes of data/parameters, thereby alleviating or even eliminating the curse of dimensionality. The usefulness of this concept is illustrated over a number of applied areas, including generalized regression and classification (support tensor machines, canonical correlation analysis, higher order partial least squares), generalized eigenvalue decomposition, Riemannian optimization, and in the optimization of deep neural networks. Part 1 and Part 2 of this work can be used either as stand-alone separate texts, or indeed as a conjoint comprehensive review of the exciting field of low-rank tensor networks and tensor decompositions.Comment: 232 page

Age dependence of serum beta-N-acetylhexosaminidase (NAG) activity

Serum Nacetyl-beta-Dglucosaminidase (NAG; EC 3.2.1.30) is a hexosaminidase and may be a predictor of vascular injury, e.g., in infant respiratory distress syndrome, pneumonia, bronchopulmonary dysplasia and necrotizing enterocolitis. To estimate the new diagnostic prospects we have modified our urinary NAG assay. In this sensitive colorimetric microassay, VRAGlcNAc was used as a substrate. In the present study the age dependence of serum NAG activity was investigated in newborn babies, infants (124 months), children (218 years) and adults (1980 years). Serum NAG activity was found to be agedependent; it is higher in early childhood (1159 U/l) but decreases to a constant value at the age of 12 years. After the age of 2 years it is similar to adults NAG (1030 U/l). In pediatrics agematched reference ranges must be taken into consideration

Radiation Hardness of Thin Low Gain Avalanche Detectors

Low Gain Avalanche Detectors (LGAD) are based on a n++-p+-p-p++ structure where an appropriate doping of the multiplication layer (p+) leads to high enough electric fields for impact ionization. Gain factors of few tens in charge significantly improve the resolution of timing measurements, particularly for thin detectors, where the timing performance was shown to be limited by Landau fluctuations. The main obstacle for their operation is the decrease of gain with irradiation, attributed to effective acceptor removal in the gain layer. Sets of thin sensors were produced by two different producers on different substrates, with different gain layer doping profiles and thicknesses (45, 50 and 80 um). Their performance in terms of gain/collected charge and leakage current was compared before and after irradiation with neutrons and pions up to the equivalent fluences of 5e15 cm-2. Transient Current Technique and charge collection measurements with LHC speed electronics were employed to characterize the detectors. The thin LGAD sensors were shown to perform much better than sensors of standard thickness (~300 um) and offer larger charge collection with respect to detectors without gain layer for fluences <2e15 cm-2. Larger initial gain prolongs the beneficial performance of LGADs. Pions were found to be more damaging than neutrons at the same equivalent fluence, while no significant difference was found between different producers. At very high fluences and bias voltages the gain appears due to deep acceptors in the bulk, hence also in thin standard detectors

A connection between stress and development in the multicelular prokaryote Streptomyces coelicolor

Morphological changes leading to aerial mycelium formation and sporulation in the mycelial bacterium Streptomyces coelicolor rely on establishing distinct patterns of gene expression in separate regions of the colony. sH was identified previously as one of three paralogous sigma factors associated with stress responses in S. coelicolor. Here, we show that sigH and the upstream gene prsH (encoding a putative antisigma factor of sH) form an operon transcribed from two developmentally regulated promoters, sigHp1 and sigHp2. While sigHp1 activity is confined to the early phase of growth, transcription of sigHp2 is dramatically induced at the time of aerial hyphae formation. Localization of sigHp2 activity using a transcriptional fusion to the green fluorescent protein reporter gene (sigHp2–egfp) showed that sigHp2 transcription is spatially restricted to sporulating aerial hyphae in wild-type S. coelicolor. However, analysis of mutants unable to form aerial hyphae (bld mutants) showed that sigHp2 transcription and sH protein levels are dramatically upregulated in a bldD mutant, and that the sigHp2–egfp fusion was expressed ectopically in the substrate mycelium in the bldD background. Finally, a protein possessing sigHp2 promoter-binding activity was purified to homogeneity from crude mycelial extracts of S. coelicolor and shown to be BldD. The BldD binding site in the sigHp2 promoter was defined by DNase I footprinting. These data show that expression of sH is subject to temporal and spatial regulation during colony development, that this tissue-specific regulation is mediated directly by the developmental transcription factor BldD and suggest that stress and developmental programmes may be intimately connected in Streptomyces morphogenesis

Characterization of the seismic environment at the Sanford Underground Laboratory, South Dakota

An array of seismometers is being developed at the Sanford Underground Laboratory, the former Homestake mine, in South Dakota to study the properties of underground seismic fields and Newtonian noise, and to investigate the possible advantages of constructing a third-generation gravitational-wave detector underground. Seismic data were analyzed to characterize seismic noise and disturbances. External databases were used to identify sources of seismic waves: ocean-wave data to identify sources of oceanic microseisms, and surface wind-speed data to investigate correlations with seismic motion as a function of depth. In addition, sources of events contributing to the spectrum at higher frequencies are characterized by studying the variation of event rates over the course of a day. Long-term observations of spectral variations provide further insight into the nature of seismic sources. Seismic spectra at three different depths are compared, establishing the 4100-ft level as a world-class low seismic-noise environment.Comment: 29 pages, 16 figure

Dark Matter Capture in the First Stars: a Power Source and Limit on Stellar Mass

The annihilation of weakly interacting massive particles can provide an important heat source for the first (Pop. III) stars, potentially leading to a new phase of stellar evolution known as a "Dark Star". When dark matter (DM) capture via scattering off of baryons is included, the luminosity from DM annihilation may dominate over the luminosity due to fusion, depending on the DM density and scattering cross-section. The influx of DM due to capture may thus prolong the lifetime of the Dark Stars. Comparison of DM luminosity with the Eddington luminosity for the star may constrain the stellar mass of zero metallicity stars; in this case DM will uniquely determine the mass of the first stars. Alternatively, if sufficiently massive Pop. III stars are found, they might be used to bound dark matter properties.Comment: 19 pages, 4 figures, 3 Tables updated captions and graphs, corrected grammer, and added citations revised for submission to JCA

Antioxidant and cytotoxic potential of selected plant species of the boraginaceae family

Antioxidant activity is one of the most important properties of plant extracts. Antioxidants from natural sources have been intensively studied in the last few decades. The antioxidant contents of medicinal plants may contribute to the protection of diseases. Bioactive components of plants have a potential role in chemoprevention and inhibition of different phases of the malignant transformation process. Therefore, plant extracts and essential oils are in the focus of research, and in recent decades have been tested on a large number of malignant cell lines. The aim of this study was to examine antioxidant and cytotoxic potential of selected plant species from the Boraginaceae family. Determination of antioxidant activity was performed by ammonium-thiocyanate method. Testing citotoxic activity was performed by MTT test on cancer cell lines: HEP 2c (human larynx carcinoma), RD (human cell line-rhabdomyosarcoma) and L2OB (mouse tumor fibroblast line). The best antioxidant activity showed ethanol, acetone and chloroform extracts of Anchusa officinalis, Echium vulgare and Echium italicum. The tested extracts showed an inhibitory effect on cancer cells, but chloroform and acetone extracts of all three plant had the most effective effect on L2OB cells. Isolation of individual active components from this plants and their testing for cancer cells would be of great importance for this field of research