Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of government science and technology policies with a focus on biotechnology research on commercial agricultural innovation in China

Purpose - The Chinese Government has used a number of policies to encourage commercial agribusiness firms to do more innovation. These include public sector agricultural research and development (R&D), public sector biotechnology research and innovation, subsidies for commercial research, encouraging foreign firms to invest in China as minority shareholders in joint ventures, and allowing commercial companies to raise money on the stock market. The purpose of this paper is to assess whether these policies were effective in stimulating innovations by commercial firms in China. Design/methodology/approach - This study estimates the impact of public biotech research and other policies by employing an econometric model of patenting by commercial firms. It uses a unique data set collected from commercial agribusiness firms for the years 2001, 2004, 2005, and 2006. Addition data were collected from public research institutes and universities and patent data from the Derwent Innovations Index database. It employs four count data models for the empirical analysis. Findings - This study finds a positive impact of public biotechnology (measured by the number of biotech patents of government research institutes and public universities) on commercial innovation measured by the number of patents granted to the commercial firms. As expected the firm’s research expenditure and having their own R&D center (as opposed to contracting R&D or no R&D investment at all) have a positive and statistically significant effect on the number of patents granted. The impacts of public R&D investment spending have no statistically significant effect on commercial innovation. Multi-national firms and publicly traded firms have fewer patents than their counterparts suggesting that policies to encourage multi-nationals and financing through stock markets had no impact on innovation. Originality/value - This study is one of the first studies to untangle the relationship between government policies and innovation by commercial agricultural research output and public R&D investment and biotechnology. The main findings suggest that simply increasing research money to public research does not increase commercial innovations, but moving resources to the development patentable biotech does improve commercial research productivity. The results also suggest that policies to increase commercial research will also increase innovation. These could include strengthening the legal framework and institutional resources for public institutes to the protection and enforcement of intellectual properties.
Streamflow Response to Climate Variability and Land‐Cover Changes in the River Beça Watershed, Northern Portugal

This work analyses changes in the River Beça basin streamflow, an area with a typically Mediterranean climate, since the second half of the last century, evaluating trends in annual, monthly and extreme streamflow in the River Beça basin and relating them to precipitation variability and changes in land use and vegetation. Annual streamflow and precipitation are highly irregular, both in intra and inter annual terms. During the period analysed, which covers the last six decades, a consistent negative trend was observed, both in mean annual streamflow and amount of annual precipitation. The results also demonstrate that precipitation greatly influences streamflow dynamics, accounting for around 85% of the variability observed in mean annual streamflow. In addition, the results show that the changes detected in land use/cover may have affected the water discharg‐ es of the river, although it is difficult to evaluate the magnitude of impact. The findings demonstrate that the impacts of climate variability and land use/cover change on streamflow are challenging and crucial to the management of water resources in Mediterranean river basins.
The effects of early low dose exposures to the Environmental Estrogen Bisphenol A on the Development of Childhood Asthma

Abbreviations: BALF: Broncho Alveolar Lavage Fluid; BBzP, di-n-butyl phthalate and butylbenzyl phthalate; BPA: Bisphenol A; BW: Body Weight; ER: Estrogen Receptor; IP: Intraperitoneal; FEV1: Forced Expiratory Volume in the fi rst second of expiration; Intraperitoneal; MBzP, Monobenzyl phthalate; NHANES: National Health and Nutrition Examination Survey; OVA: Ovalbumin; PN: Post Natal; PND: Post Natal Day
Normal forms with exponentially small remainder and Gevrey normalization for vector fields with a nilpotent linear part

We explore the convergence/divergence of the normal form for a singularity of a vector field on $\C^n$ with nilpotent linear part. We show that a Gevrey-$\alpha$ vector field $X$ with a nilpotent linear part can be reduced to a normal form of Gevrey-$1+\alpha$ type with the use of a Gevrey-$1+\alpha$ transformation. We also give a proof of the existence of an optimal order to stop the normal form procedure. If one stops the normal form procedure at this order, the remainder becomes exponentially small.
Stability of exfoliated Bi2Sr2DyxCa1-xCu2O8+δ studied by Raman microscopy

Nanometer thick cuprates are an appealing platform for devices as well as exploring the roles of dimensionality, disorder, and free carrier density in these compounds. To this end we have produced exfoliated crystals of Bi2Sr2CaCu2O8 on oxidized silicon substrates. The exfoliated crystals were characterized via Atomic Force and polarized Raman microscopies. Proper procedures for production, handling and monitoring of these thin oxides are described. Subtle differences between the exfoliated and bulk crystals are also discussed.
Does Money Matter in the IS Curve? The Case of the UK

Narrow and broad money measures (including Divisia aggregates) have been found to have explanatory power for UK output in backward-looking specifications of the IS curve. In this paper, we explore whether or not real balances enter into a forward-looking IS curve for the UK. To do this, we test for additive separability between consumption and money over a sizeable part of the post-Exchange Rate Mechanism period using non-parametric methods. A main finding is that the UK data seem to be broadly consistent with additive separability for the more recent period from 1999 to 2007.
UNTYING THE KNOT: HOW EINSTEIN FOUND HIS WAY BACK TO FIELD EQUATIONS DISCARDED IN THE ZURICH NOTEBOOK

Sometimes the most obvious questions are the most fruitful ones. The Zurich Notebook is a case in point. The notebook shows that Einstein already considered the field equations of general relativity about three years before he published them in November 1915. In the spring of 1913 he settled on different equations, known as the “ Entwurf ” field equations after the title of the paper in which they were first published (Einstein and Grossmann 1913). By Einstein’s own lights, this move compromised one of the fundamental principles of his theory, the extension of the principle of relativity from uniform to arbitrary motion. Einstein had sought to implement this principle by constructing field equations out of generally-covariant expressions. 1 The Entwurf field equations are not generally covariant. When Einstein published the equations, only their covariance under general linear transformations was assured. This raises two obvious questions. Why did Einstein reject equations of much broader covariance in 1912-1913? And why did he return to them in November 1915?
Role of Inflammatory Cytokines in Insulin Resistance Among Chronic Hepatitis C Patients

Insulin resistance plays an essential role in the pathogenesis of diabetes associated with HCV. High levels of inflammatory cytokines have been found in HCV-infected patients. The aim of the study was to investigate the association of HCV infection with impaired glucose metabolism and to highlight the role of inflammatory cytokines as an initial mechanism involved in insulin resistance development in HCV infection. It included 3 groups of patients: Group I: 50 HCV patients with DM. Group II: 50 HCV patients without DM and Group III: 25 patients with DM alone as control subjects. Insulin resistance was evaluated using the (HOMA - IR) index. We measured the levels of fasting insulin, CRP and two of the inflammatory cytokines of the innate immunity (TNF-α and IL-6 by ELISA). It was found that insulin resistance, CRP and IL6 in group (I) were significantly higher when compared to group (II) and (III) with P-value < 0.001. CRP in group (II) was significantly higher when compared to group (III) with P-value < 0.05. Serum level of (TNF-α) in group (I) was significantly higher when compared to group (II) with P-value < 0.05 and group (III) with P-value < 0.001 as well as in group (II) it was significantly higher when compared to group (III) with P-value < 0.001. CRP, IL-6 and TNF-α had statistically significant positive direct correlation to insulin resistance. In conclusion there was a strong relationship between inflammatory cytokines and the occurrence of insulin resistance in chronic HCV patients with type 2 diabetes mellitus.
Control Strategies for a Multiple Degree of Freedom Prosthetic Hand

Some of the traditional methods used to control a conventional prosthetic device are described alongside the current state of new control techniques and how they may progress. The review includes implantable myoelectric sensors and describes the potential of connecting directly to the peripheral nervous system. Control methods are then deduced for each technique, where the application is a six degrees of freedom hand having integral slip, force and temperature sensors.
Regional Body-Wave Discrimination Research

Monitoring the world for potential nuclear explosions requires identifying them by their expected seismic signatures and discriminating them from earthquakes and other sources of seismic waves. Large events (approximately m{sub b} > 4.0) can often be successfully identified by the M{sub s}:m{sub b} discriminant. In order to monitor small events (approximately m{sub b}, < 4.0) short-period regional waveform data recorded within 2000 km will be needed because of poor signal-to-noise at large distances and/or long-periods. Many studies have shown that short-period (0.5-10 Hz) regional body wave phases (e.g. Pn, Pg, Sn, Lg and coda) have excellent discrimination power down to very small magnitudes when used at various nuclear tests sites. In order to broaden the application of these regional body wave techniques, we are developing size-, distance- and location-based corrections to apply to the regional data to allow wider data comparison and better discrimination performance. Building on prior work (e.g. Taylor et al. 1999, Rodgers and Walter, 2000), we are developing a revised Magnitude and Distance Amplitude Correction (MDAC) procedure. The procedure makes use of the very stable moment magnitude determinations from regional coda envelopes (see Mayeda et al, this Symposium) to provide an independent size estimate. Using a Brunemore » (1970) style omega-squared source spectral model, we parameterize the source in terms of apparent stress and its scaling with moment. For the distance corrections we parameterize in terms of geometrical spreading, and frequency-dependent attenuation. In addition there are constants associated with velocities, densities and a phase- and frequency-dependent site effect. Using this relatively simple model we can remove much of the magnitude and distance trends from the regional data. We use a grid-search technique to explore the model space with more emphasis on removing the magnitude and distance trends than in fitting the observable spectra perfectly. Two-dimensional path effects are currently corrected by kriging the MDAC residuals but they could also be addressed through location-dependent attenuation models if available. Using earthquake and explosion data from the Nevada Test Site and India we show that the revised MDAC correction and kriging of the residuals can significantly improve phase and spectral ratio discrimination performance. In addition by correcting the regional amplitudes we allow maximum flexibility in exploring and creating new combinations of regional phases which may have even better discrimination potential. Finally the corrected regional amplitudes provide critical information on the detection of regional phases, which is another important factor in the overall estimation of discrimination capability. « less
Mixture Simultaneous Factor Analysis for Capturing Differences in Latent Variables Between Higher Level Units of Multilevel Data

Given multivariate data, many research questions pertain to the covariance structure: whether and how the variables (e.g., personality measures) covary. Exploratory factor analysis (EFA) is often used to look for latent variables that might explain the covariances among variables; for example, the Big Five personality structure. In the case of multilevel data, one might wonder whether or not the same covariance (factor) structure holds for each so-called data block (containing data of 1 higher level unit). For instance, is the Big Five personality structure found in each country or do cross-cultural differences exist? The well-known multigroup EFA framework falls short in answering such questions, especially for numerous groups or blocks. We introduce mixture simultaneous factor analysis (MSFA), performing a mixture model clustering of data blocks, based on their factor structure. A simulation study shows excellent results with respect to parameter recovery and an empirical example is included to illustrate the value of MSFA.
Improved redshifts for SDSS quasar spectra

A systematic investigation of the relationship between different redshift estimation schemes for more than 91000 quasars in the Sloan Digital Sky Survey (SDSS) Data Release 6 (DR6) is presented. The publicly available SDSS quasar redshifts are shown to possess systematic biases of Dz/(1+z)>=0.002 (600km/s) over both small (dz~0.1) and large (dz~1) redshift intervals. Empirical relationships between redshifts based on i) CaII H & K host galaxy absorption, ii) quasar [OII] 3728, iii) [OIII] 4960,5008 emission, and iv) cross-correlation (with a master quasar template) that includes, at increasing quasar redshift, the prominent MgII 2799, CIII] 1908 and CIV 1549 emission lines, are established as a function of quasar redshift and luminosity. New redshifts in the resulting catalogue possess systematic biases a factor of ~20 lower compared to the SDSS redshift values; systematic effects are reduced to the level of Dz/(1+z)<10^-4 (30km/s) per unit redshift, or <2.5x10^-5 per unit absolute magnitude. Redshift errors, including components due both to internal reproducibility and the intrinsic quasar-to-quasar variation among the population, are available for all quasars in the catalogue. The improved redshifts and their associated errors have wide applicability in areas such as quasar absorption outflows, quasar clustering, quasar-galaxy clustering and proximity-effect determinations.
Hydrogen sulfide initiated corrosion in concrete sewers - a conceptual approach for prediction

Concrete corrosion caused by hydrogen sulfide in sewer networks is a major economical problem. Resent studies have provided new knowledge of the absorption of hydrogen sulfide on concrete surfaces and of the subsequent oxidation to sulfuric acid. In this paper the information from these studies was combined to simulate concrete corrosion in a gravity sewer located downstream from a force main. The concrete corrosion on this section of gravity sewer was highly dependent on the concentration of active biomass on the concrete surface and in a worst case scenario a corrosion rate of 7 mm year -1 was predicted. The model simulations also revealed that the concrete corrosion process can be described using saturation type kinetics even though the removal of hydrogen sulfide from the sewer gas phase follows n th order kinetics.
Optical backscattering is correlated with phytoplankton carbon across the Atlantic Ocean

Phytoplankton are an important component of the oceanic carbon cycle. Yet, due to methodological constraints, the carbon biomass of phytoplankton is poorly characterized. To address this limitation, we have explored the bio‐optical relationship between in situ measurements of the particle backscattering coefficient at 470 nm, bbp(470), and the phytoplankton carbon concentration for cells with diameter less than 20 µm (Cf). We found a significant relationship between bbp(470) and Cf for Atlantic oceanic waters with chlorophyll‐a concentrations less than 0.4 mg m−3 (or bbp(470) < 0.003 m−1). This relationship could be used to estimate Cf from data collected by in situ autonomous platforms and from remote sensing of ocean color.
Investigation of the summer Kara Sea circulation employing a variational data assimilation technique

[1] The summer circulations and hydrographic fields of the Kara Sea are reconstructed for mean, positive and negative Arctic Oscillation regimes employing a variational data assimilation technique which provides the best fit of reconstructed fields to climatological data and satisfies dynamical and kinematic constraints of a quasi-stationary primitive equation ocean circulation model. The reconstructed circulations agree well with the measurements and are characterized by inflow of 0.63, 0.8, 0.51 Sv through Kara Gate and 1.18, 1.1, 1.12 Sv between Novaya Zemlya and Franz Josef Land, for mean climatologic conditions, positive and negative AO indexes, respectively. The major regions of water outflow for these regimes are the St. Anna Trough (1.17, 1.21, 1.34 Sv) and Vilkitsky/Shokalsky Straits (0.52, 0.7, 0.51 Sv). The optimized velocity pattern for the mean climatological summer reveals a strong anticyclonic circulation in the central part of the Kara Sea (Region of Fresh Water Inflow, ROFI zone) and is confirmed by ADCP surveys and laboratory modeling. This circulation is well pronounced for both high and low AO phases, but in the positive AO phase it is shifted approximately 200 km west relatively to its climatological center. During the negative AO phase the ROFI locaion is close to its climatological position. The results of the variational data assimilation approach were compared with the simulated data from the Hamburg Shelf Ocean Model (HAMSOM) and Naval Postgraduate School 18 km resolution (NPS-18) model to validate these models.
New Optimization Methods for Modern Machine Learning

Modern machine learning systems pose several new statistical, scalability, privacy and ethical challenges. With the advent of massive datasets and increasingly complex tasks, scalability has especially become a critical issue in these systems. In this thesis, we focus on fundamental challenges related to scalability, such as computational and communication efficiency, in modern machine learning applications. The underlying central message of this thesis is that classical statistical thinking leads to highly effective optimization methods for modern big data applications. The first part of the thesis investigates optimization methods for solving large-scale nonconvex Empirical Risk Minimization (ERM) problems. Such problems have surged into prominence, notably through deep learning, and have led to exciting progress. However, our understanding of optimization methods suitable for these problems is still very limited. We develop and analyze a new line of optimization methods for nonconvex ERM problems, based on the principle of variance reduction. We show that our methods exhibit fast convergence to stationary points and improve the state-of-the-art in several nonconvex ERM settings, including nonsmooth and constrained ERM. Using similar principles, we also develop novel optimization methods that provably converge to second-order stationary points. Finally, we show that the key principles behind our methods can be generalized to overcome challenges in other important problems such as Bayesian inference. The second part of the thesis studies two critical aspects of modern distributed machine learning systems — asynchronicity and communication efficiency of optimization methods. We study various asynchronous stochastic algorithms with fast convergence for convex ERM problems and show that these methods achieve near-linear speedups in sparse settings common to machine learning. Another key factor governing the overall performance of a distributed system is its communication efficiency. Traditional optimization algorithms used in machine learning are often ill-suited for distributed environments with high communication cost. To address this issue, we dis- cuss two different paradigms to achieve communication efficiency of algorithms in distributed environments and explore new algorithms with better communication complexity.
ON SUMS OF SQUARES OF PELL-LUCAS NUMBERS

In this paper we prove several formulas for sums of squares of even Pell-Lucas numbers, sums of squares of odd Pell-Lucas numbers, and sums of products of even and odd PellLucas numbers. These sums have nice representations as products of appropriate Pell and Pell-Lucas numbers with terms from certain integer sequences.
Acer pseudoplatanus L., Acer platanoides L. and Betula pendula Roth. as bioindicators of urban pollution in Sofia.

Acer pseudoplatanus L. , Acer platanoides L. and Betula pendula Roth. have been studied under the urban pollution in Sofia during 3 years period. The aim of the study was, by statistical multifactorial analysis, to assess the value changes in morphological parameters of species under air pollution and potential for species usage as bioindicators in observed regions. The statistical analysis includes 3 morphological parameters: linear growth of the annual twigs, number of leaves on these twigs and area of leaves. The variation of the parameters in specimens from the polluted areas compared to the control in the most of cases is of a statistical significance. As an indicator only for pollution could be used Betula pendula and as a specific one: Acer platanoides – in urban pollution, mainly of industrial type (Thermo-Electric Power Station) and Acer pseudoplatanus – in road traffic pollution in combination with drought. The linear growth of the annual twigs (Acer pseudoplatanus) as well as the linear growth of the annual twigs and leaf area (Acer platanoides, Betula pendula) have a priority as bioindicators of pollution in the studied regions.
Synthesis of carbon quantum dots from cabbage with down- and up-conversion photoluminescence properties: excellent imaging agent for biomedical applications

Carbon quantum dots (CQD) with down and up-conversion photoluminescence (PL) properties have been synthesized through low-temperature carbonization in a facile one step green method from cabbage as the natural source of carbon. The physiochemical and optical properties of the resultant CQD were performed using transmission electron microscopy, confocal laser scanning microscopy and various spectroscopic methods. The CQD with a quantum yield of 16.5% demonstrated excellent solubility and stability in aqueous media, superior resistance to photo bleaching, consistent PL within a biological pH range, excitation-dependent down conversion and excitation-independent up-conversion PL along with large stock shift behaviour. The purified CQD exhibited low cytotoxicity at higher concentration (500 μg ml−1) during the cell viability experiment against HaCaT cell, an immortalized non-tumerogenic human keratinocyte cell. Subsequently, CQD treated cells displayed three distinguished blue, green and red colours under a confocal microscope during in vitro imaging. Due to the advantages of green synthesis, high biocompatibility, excellent optical properties, low cytotoxicity and good cellular imaging outcome, the cabbage derived CQD showed considerable promise in biomedical applications.