A unified econophysics explanation for the power-law exponents of stock market activity

We survey a theory (first sketched in Nature in 2003, then fleshed out in the Quarterly Journal of Economics in 2006) of the economic underpinnings of the fat-tailed distributions of a number of financial variables, such as returns and trading volume. Our theory posits that they have a common origin in the strategic trading behavior of very large financial institutions in a relatively illiquid market. We show how the fat-tailed distribution of fund sizes can indeed generate extreme returns and volumes, even in the absence of fundamental news. Moreover, we are able to replicate the individually different empirical values of the power-law exponents for each distribution: 3 for returns, 3/2 for volumes, 1 for the assets under management of large investors. Large investors moderate their trades to reduce their price impact; coupled with a concave price impact function, this leads to volumes being more fat-tailed than returns but less fat-tailed than fund sizes. The trades of large institutions also offer a unified explanation for apparently disconnected empirical regularities that are otherwise a challenge for economic theory.     

UA62784 Is a cytotoxic inhibitor of microtubules, not CENP-E

A recent screen for compounds that selectively targeted pancreatic cancer cells isolated UA62784. We found that UA62784 inhibits microtubule polymerization in?vitro. UA62784 interacts with tubulin dimers ten times more potently than colchicine, vinblastine, or nocodazole. Competition experiments revealed that UA62784 interacts with tubulin at or near the colchicine-binding site. Nanomolar doses of UA62784 promote the accumulation of mammalian cells in mitosis, due to aberrant mitotic spindles, as shown by immunofluorescence and live cell imaging. Treatment of cancerous cell lines with UA62784 is lethal, following activation of apoptosis signaling. By monitoring mitotic spindle perturbations and apoptosis, we found that the effects of UA62784 and of some known microtubule-depolymerizing drugs are additive. Finally, high content screening of H2B-GFP HeLa cells revealed that low doses of UA62784 and vinblastine potentiate each other to inhibit proliferation.     

Strength statistics and the distribution of earthquake interevent times

The Weibull distribution is often used to model the earthquake interevent times distribution (ITD). We propose a link between the earthquake ITD on single faults with the Earth’s crustal shear strength distribution by means of a phenomenological stick–slip model. For single faults or fault systems with homogeneous strength statistics and power-law stress accumulation we obtain the Weibull ITD. We prove that the moduli of the interevent times and crustal shear strength are linearly related, while the time scale is an algebraic function of the scale of crustal shear strength. We also show that logarithmic stress accumulation leads to the log-Weibull ITD. We investigate deviations of the ITD tails from the Weibull model due to sampling bias, magnitude cutoff thresholds, and non-homogeneous strength parameters. Assuming the Gutenberg–Richter law and independence of the Weibull modulus on the magnitude threshold, we deduce that the interevent time scale drops exponentially with the magnitude threshold. We demonstrate that a microearthquake sequence from the island of Crete and a seismic sequence from Southern California conform reasonably well to the Weibull model.     

Supported Au Nanoparticles-Catalyzed Regioselective Dehydrogenative Disilylation of Allenes by Dihydrosilane

Supported Au nanoparticles on TiO₂ catalyze the unprecedented dehydrogenative disilylation of monosubstituted and 1,1-disubstituted allenes by Et₂SiH₂ exclusively on the terminal double bond in a stereoselective manner. Treatment of the disilylation products with H₂O, in a one-pot operation also catalyzed by Au/TiO₂, leads to 3-alkylidene-1,2,5-oxadisilolanes, an unknown class of heterocyclic compounds, which are excellent scaffolds for the stereoselective synthesis of alkenes under Hiyama-type cross-coupling conditions.     

Middle school students’ reasoning about data and context through storytelling with repurposed local data

Publicly-available datasets, though useful for education, are often constructed for purposes that are quite different from students’ own. To investigate and model phenomena, then, students must learn how to repurpose the data. This paper reports on an emerging line of research that builds on work in data modeling, exploratory data analysis, and storytelling to examine and support students’ data repurposing. We ask: What opportunities emerge for students to reason about the relationship between data, context, and uncertainty when they repurpose public data to explore questions about their local communities? And, How can these opportunities be supported in classroom instruction and activity design? In two exploratory studies, students were asked to pose questions about their communities, use publicly-available data to investigate those questions, and create visual displays and written stories about their findings. Across both enactments, opportunities for reasoning emerged especially when students worked to reconcile (1) their own knowledge and experiences of the context from which data were collected with details of the data provided; and (2) their different emerging stories about the data with one another. We review how these opportunities unfolded within each enactment at the level of group and classroom, with attention to facilitator support.     

A roadmap towards a circular and sustainable bioeconomy through waste valorization

Municipal solid waste and food supply chain waste are globally generated in large quantities from various sectors including various stages of food supply chains, municipalities, open markets and catering services. A prevailing priority in the EU is to stimulate the transition towards a circular economy that fosters the promotion of sustainable and resource-efficient policies for long-term socio-economic and environmental benefits. Common practices for waste management include landfill disposal, anaerobic digestion, composting and wastewater treatment. Recently, new technologies have been introduced to produce value-added products from agricultural residues and food processing side streams. Integrated and holistic approaches for organic waste utilization as industrial feedstocks will boost the transition towards the bio-economy era. The establishment of circular economy would expand and diversify the market outlets of bio-based products. This review provides an overview of the current methods on waste and by-product streams bioconversion to develop biorefinery concepts.     

Valorization of By-Products from Palm Oil Mills for the Production of Generic Fermentation Media for Microbial Oil Synthesis

This study demonstrates the production of a generic nutrient-rich feedstock using by-product streams from palm oil production that could be used as a substitute for commercial fermentation supplements. Solid-state fermentations of palm kernel cake (PKC) and palm-pressed fiber (PPF) were conducted in tray bioreactors and a rotating drum bioreactor by the fungal strain Aspergillus oryzae for the production of crude enzymes. The production of protease was optimized (319.3 U/g) at an initial moisture content of 55 %, when PKC was used as the sole substrate. The highest free amino nitrogen (FAN) production (5.6 mg/g) obtained via PKC hydrolysis using the crude enzymes produced via solid-state fermentation was achieved at 50 °C. Three initial PKC concentrations (48.7, 73.7, and 98.7 g/L) were tested in hydrolysis experiments, leading to total Kjeldahl nitrogen to FAN conversion yields up to 27.9 %. Sequential solid-state fermentation followed by hydrolysis was carried out in the same rotating drum bioreactor, leading to the production of 136.7 U/g of protease activity during fermentation and 196.5 mg/L of FAN during hydrolysis. Microbial oil production was successfully achieved with the oleaginous yeast strain Lipomyces starkeyi DSM 70296 cultivated on the produced PKC hydrolysate mixed with commercial carbon sources, including glucose, xylose, mannose, galactose, and arabinose.     

Micellisation and gelation of diblock copolymers of ethylene oxide and propylene oxide in aqueous solution, the effect of P-block length

The aqueous solution properties of five diblock copolymers prepared by sequential anionic copolymerisation (i.e. E₁₀₂P₃₇, E₁₀₄P₅₂, E₉₂P₅₅, E₁₀₄P₆₀ and E₉₈P₇₃ where E denotes oxyethylene and P denotes oxypropylene) were studied across a wide range of concentration. The techniques used to study micellisation and micellar properties in dilute solution were static and dynamic light scattering, surface tension, and eluent gel-permeation chromatography. The gelation of concentrated solutions was also investigated. As expected, the critical micelle concentration (CMC) was lowered and the association number of the micelles was increased by an increase in P-block length. In contrast, the critical gel concentration was unchanged, consistent with the constant E-block length leading to micelles with essentially identical E-block fringes. Comparison of the CMCs of the diblock copolymers with those of triblock E_mP_nE_m copolymers with the same P-block length shows the diblock copolymers to micellise more efficiently. A similar comparison of the CMCs of the diblock copolymers with those of E_mB_n copolymer (B denotes oxybutylene) shows the hydrophobicity of a P unit to be one-sixth that of a B unit. The possibility is explored of correlating the limiting association number of a spherical micelle with the hydrophobe block length of its constituent copolymer. Of the five copolymers, only dilute solutions of E₉₈P₇₃ were predominantly micellar at both room temperature and body temperature, and this copolymer must be a prime candidate in any consideration of the potential application of E_mP_n copolymers in the solubilisation and controlled release of drugs.     

Spatial Modeling of Precipitation Based on Data-Driven Warping of Gaussian Processes

Modeling and forecasting spatiotemporal patterns of precipitation is crucial for managing water resources and mitigating water-related hazards. Globally valid spatiotemporal models of precipitation are not available. This is due to the intermittent nature, non-Gaussian distribution, and complex geographical dependence of precipitation processes. Herein we propose a data-driven model of precipitation amount which employs a novel, data-driven (non-parametric) implementation of warped Gaussian processes. We investigate the proposed warped Gaussian process regression (wGPR) using (i) a synthetic test function contaminated with non-Gaussian noise and (ii) a reanalysis dataset of monthly precipitation from the Mediterranean island of Crete. Cross-validation analysis is used to establish the advantages of non-parametric warping for the interpolation of incomplete data. We conclude that wGPR equipped with the proposed data-driven warping provides enhanced flexibility and—at least for the cases studied– improved predictive accuracy for non-Gaussian data.