Prediction Possibility in the Fractal Overlap Model of Earthquakes

The two-fractal overlap model of earthquake shows that the contact area distribution of two fractal surfaces follows power law decay in many cases and this agrees with the Guttenberg-Richter power law. Here, we attempt to predict the large events (earthquakes) in this model through the overlap time-series analysis. Taking only the Cantor sets, the overlap sizes (contact areas) are noted when one Cantor set moves over the other with uniform velocity. This gives a time series containing different overlap sizes. Our numerical study here shows that the cumulative overlap size grows almost linearly with time and when the overlapsizes are added up to a pre-assigned large event (earthquake) and then reset to `zero' level, the corresponding cumulative overlap sizes grows upto some discrete (quantised) levels. This observation should help to predict the possibility of `large events' in this (overlap) time series.Comment: 6 pages, 6 figures. To be published as proc. NATO conf. CMDS-10, Soresh, Israel, July 2003. Eds. D. J. Bergman & E. Inan, KLUWER PUB

Design of domestic photovoltaics manufacturing systems under global constraints and uncertainty

As global political discourse is taking place where the need for a cleaner energy mix is constantly highlighted, manufacturing strategies are becoming more relevant. Thus, the photovoltaics system design is a crucial aspect related with the overall sustainability. In fact, various countries are considering the potential to locally manufacture different elements of the photovoltaics (PV) value chain and the strategies to incentivize a local manufacturing base. This paper develops a mathematical programming approach for the optimal design of a PV manufacturing value chain considering diverse criteria linked to economic and environmental performance such as minimum sustainable price, transportation capacity, among others, and considering uncertainty. In addition, the proposed methodology involves the dependence over time of supply chain variables and economic parameters such as inflation, electricity cost, and weighted average cost of capital, to determine the manufacturing system topology under uncertain conditions. Our results highlight the importance of planning models to develop markets policies related to supply chains, production level changes and imposed tariffs all while involving uncertainty in economic parameters, which is an improvement compared to planning models that use deterministic formulations. Finally, the proposed methodology and results can encourage decision-making considering probable variations in different parameters

Thermal Conductivity of Periclase (MgO) from First Principles

We combine first-principles calculations of forces with the direct nonequilibrium molecular dynamics method to determine the lattice thermal conductivity k of periclase (MgO) up to conditions representative of the Earth's core-mantle boundary (136 GPa, 4100 K). We predict the logarithmic density derivative a = (partial derivative lnk/partial derivative ln rho)(Tau) = 4.6 +/- 1.2 and that k = 20 +/- 5 Wm(-1) K-1 at the core-mantle boundary, while also finding good agreement with extant experimental data at much lower pressures

Lymphotoxin is an autocrine growth factor for Epstein-Barr virus-infected B cell lines.

Because human lymphotoxin (LT) was originally isolated from a lymphoblastoid cell line, we investigated the role of this molecule in three newly established Epstein-Barr virus (EBV)-infected human B cell lines. These lines were derived from acute lymphoblastic leukemia (Z-6), myelodysplastic syndrome (Z-43), and acute myelogenous leukemia (Z-55) patients who had a prior EBV infection. Each lymphoblastoid cell line had a karyotype that was different from that of the original parent leukemic cells, and all expressed B cell, but not T cell or myeloid surface markers. In all three lines, rearranged immunoglobulin heavy chain joining region (JH) bands were found, and the presence of EBV DNA was confirmed by Southern blotting. Z-6, Z-43, and Z-55 cell lines constitutively produced 192, 48, and 78 U/ml LT, respectively, as assessed by a cytotoxicity assay and antibody neutralization. Levels of tumor necrosis factor (TNF) were undetectable. Scatchard analysis revealed that all the cell lines expressed high-affinity TNF/LT receptors with receptor densities of 4197, 1258, and 1209 sites/cell on Z-6, Z-43, and Z-55, respectively. Furthermore, labeled TNF binding could be reversed by both unlabeled TNF, as well as by LT. Studies with p60 and p80 receptor-specific antibodies revealed that the three lines expressed primarily the p80 form of the TNF receptor. When studied in a clonogenic assay, exogenous LT stimulated proliferation of all three cell lines in a dose-dependent fashion at concentrations ranging from 25 to 500 U/ml. Similar results were obtained with [3H]TdR incorporation. Monoclonal anti-LT neutralizing antibodies at concentrations of 25-500 U/ml inhibited cellular multiplication in a dose-dependent manner. It is interesting that in spite of a common receptor, TNF (1,000 U/ml) had no direct effect on Z-55 cell growth, whereas it partially reversed the stimulatory effect of exogenous LT. In addition, TNF inhibited Z-6 and Z-43 cell proliferation, and its suppressive effect was reversed by exogenous LT. Both p80 and p60 forms of soluble TNF receptors suppressed the lymphoblastoid cell line proliferation and their inhibitory effect was partially reversed by LT. Our data suggest that (a) LT is an autocrine growth factor for EBV-transformed lymphoblastoid B cell lines; and (b) anti-LT antibodies, soluble TNF/LT receptors, and TNF itself can suppress the growth of lymphoblastoid cells, probably by modulating or competing with LT.(ABSTRACT TRUNCATED AT 400 WORDS

HardIDX: Practical and Secure Index with SGX

Software-based approaches for search over encrypted data are still either challenged by lack of proper, low-leakage encryption or slow performance. Existing hardware-based approaches do not scale well due to hardware limitations and software designs that are not specifically tailored to the hardware architecture, and are rarely well analyzed for their security (e.g., the impact of side channels). Additionally, existing hardware-based solutions often have a large code footprint in the trusted environment susceptible to software compromises. In this paper we present HardIDX: a hardware-based approach, leveraging Intel's SGX, for search over encrypted data. It implements only the security critical core, i.e., the search functionality, in the trusted environment and resorts to untrusted software for the remainder. HardIDX is deployable as a highly performant encrypted database index: it is logarithmic in the size of the index and searches are performed within a few milliseconds rather than seconds. We formally model and prove the security of our scheme showing that its leakage is equivalent to the best known searchable encryption schemes. Our implementation has a very small code and memory footprint yet still scales to virtually unlimited search index sizes, i.e., size is limited only by the general - non-secure - hardware resources

Modeling startle eyeblink electromyogram to assess fear learning

Pavlovian fear conditioning is widely used as a laboratory model of associative learning in human and nonhuman species. In this model, an organism is trained to predict an aversive unconditioned stimulus from initially neutral events (conditioned stimuli, CS). In humans, fear memory is typically measured via conditioned autonomic responses or fear-potentiated startle. For the latter, various analysis approaches have been developed, but a systematic comparison of competing methodologies is lacking. Here, we investigate the suitability of a model-based approach to startle eyeblink analysis for assessment of fear memory, and compare this to extant analysis strategies. First, we build a psychophysiological model (PsPM) on a generic startle response. Then, we optimize and validate this PsPM on three independent fear-conditioning data sets. We demonstrate that our model can robustly distinguish aversive (CS+) from nonaversive stimuli (CS-, i.e., has high predictive validity). Importantly, our model-based approach captures fear-potentiated startle during fear retention as well as fear acquisition. Our results establish a PsPM-based approach to assessment of fear-potentiated startle, and qualify previous peak-scoring methods. Our proposed model represents a generic startle response and can potentially be used beyond fear conditioning, for example, to quantify affective startle modulation or prepulse inhibition of the acoustic startle response

Offline Bengali writer verification by PDF-CNN and siamese net

© 2018 IEEE. Automated handwriting analysis is a popular area of research owing to the variation of writing patterns. In this research area, writer verification is one of the most challenging branches, having direct impact on biometrics and forensics. In this paper, we deal with offline writer verification on complex handwriting patterns. Therefore, we choose a relatively complex script, i.e., Indic Abugida script Bengali (or, Bangla) containing more than 250 compound characters. From a handwritten sample, the probability distribution functions (PDFs) of some handcrafted features are obtained and input to a convolutional neural network (CNN). For such a CNN architecture, we coin the term 'PDFCNN', where handcrafted feature PDFs are hybridized with auto-derived CNN features. Such hybrid features are then fed into a Siamese neural network for writer verification. The experiments are performed on a Bengali offline handwritten dataset of 100 writers. Our system achieves encouraging results, which sometimes exceed the results of state-of-The-Art techniques on writer verification

Effects of electromagnetic field of 33 and 275 kV influences on physiological, biochemical and antioxidant system changes of leaf mustard (Brassica chinensis)

The effects of electromagnetic fields (EMF) from 33 and 275 kV high voltage transmission line on biochemical and antioxidant system changes in mustard leaf (Brassica chinensis) were investigated under field condition. Mustard leaves were exposed to EMF from power lines at distances of 0, 3, 6, 9, 10, 12, 15, 18, 20, 21, 30, 40, 50 and 60 m away from the 33 kV power line and at 0, 10, 20, 30, 40, 50, 60 and 70 m away from the 275 kV transmission lines. The effects of EMF from 33 kV power lines on leaf mustard planted at different distances from the line showed that leaf mustard planted within 20 m from the line had significantly (p< 0.05) higher protein, soluble protein, soluble nitrogen and chlorophyll contents due to the higher EMF strength which decreased with increasing distance from the line. Higher EMF strength nearer to the 275 kV power line resulted in higher peroxidase enzymatic activity, and chlorophyll content. Protein electrophoretic profile obtained from sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS PAGE) analysis revealed no drastic alterations in the leaf mustard protein profiles. This suggests that electromagnetic field could be used as a tool to promote mustard growth via photosynthesis once the right EMF strength and duration of exposure has been established through future studies.Keywords: Mustard, electromagnetic field, biochemical marker

Microcredit Effect on Agricultural Productivity: A Comparative Analysis of Rural Farmers in Ogun State, Nigeria

This study examines the effect of access to credit on the productivity of rural farming households in Ogun State, Nigeria. Data were collected, with the use of well structured questionnaire, from 240 small-scale rural farmers, who were categorized into users and non-users of micro-credit based on their statement, through multi-stage sampling technique. Descriptive statistics, budgetary technique and multiple regression analysis, involving the use of ordinary least square (OLS) method of estimation, were employed in analyzing data for this study. The results revealed that total cost per hectare of credit user farmers is higher (N41,632.53) than that of non-credit user farmers (N32,667.79), indicating misallocation of resources by credit-user farmers. Again, profit per hectare of credit users farmer is greater (N44,466.59) than that of non-credit users (N27,833.03), suggesting that, access to credit could lead to improved farmers' productivity and higher income in form of revenue and profit. Regression analysis showed that only fertilizer and farm size, both being positive, affect credit users farmer's output, whereas, planting material, agrochemical, farm size and fixed inputs affects non-credit users farmer's output. R2 values suggested that variation in output by the two categories of farmers is explained by 57 and 52 percent of explanatory variables in their production functions, respectively. F-value of 9.84 and 10.11 recorded for the two categories of farmers respectively, and being significant at 1 percent each, led to the rejection of the hypothesis of inputs having no significant effect on output. It is thus concluded that credit could bring about higher productivity and profit in agricultural production, hence, this study recommends that existing banks should be encouraged to have more rural outlets, while there should be federal government policy of empowering rural farmers to have access to more agricultural lands.Keywords: Micro-credit, Productivity; Rural-farmers; Ogun State, Nigeri

Interaction Between Autonomic Tone and the Negative Chronotropic Effect of Adenosine in Humans

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72287/1/j.1540-8159.1999.tb00412.x.pd