The mechanistic view of computation contends that computational explanations are mechanistic explanations. Mechanists, however, disagree about the precise role that the environment – or the so-called “contextual level” – plays for computational (mechanistic) explanations. We advance here two claims: (i) Contextual factors essentially determine the computational identity of a computing system (computational externalism); this means that specifying the “intrinsic” mechanism is not sufficient to fix the computational identity of the system. (ii) It is not necessary to specify the causal-mechanistic interaction between the system and its context in order to offer a complete and adequate computational explanation. While the first claim has been discussed before, the second has been practically ignored. After supporting these claims, we discuss the implications of our contextualist view for the mechanistic view of computational explanation. Our aim is to show that some versions of the mechanistic view are consistent with the contextualist view, whilst others are not.
A crucial challenge in measuring how text represents an entity is the need to associate each representative expression with a relevant entity to generate meaningful results. Common solutions to this problem are usually based on proximity methods that require a large corpus to reach reasonable levels of accuracy. We show how such methods for the association between an entity and a representation yield a high percentage of false positives at the expression level and low validity at the document level. We introduce a solution that combines syntactic parsing, semantic role labeling logic, and a machine learning approach—the role-based association method. To test our method, we compared it with prevalent methods of association on the news coverage of two entities of interest—the State of Israel and the Palestinian Authority. We found that the role-based association method is more accurate at the expression and the document levels.
Sulfated saccharides are an essential part of extracellular matrices, and they are involved in a large number of interactions. Sulfated saccharide matrices in organisms accumulate heavy metal ions in addition to other essential metal ions. Accumulation of heavy metal ions alters the function of the organisms and cells, resulting in severe and irreversible damage. The effect of the sulfation pattern of saccharides on heavy metal binding preferences is enigmatic because the accessibility to structurally defined sulfated saccharides is limited and because standard analytical techniques cannot be used to quantify these interactions. We developed a new strategy that combines enzymatic and chemical synthesis with surface chemistry and label‐free electrochemical sensing to study the interactions between well‐defined sulfated saccharides and heavy metal ions. By using these tools we showed that the sulfation pattern of hyaluronic acid governs their heavy metal ions binding preferences.
The present invention relates to the use of pomegranate oil and fractions thereof for preventing and treating neurodegenerative diseases. Particularly, the present invention relates to emulsions of the pomegranate oil or fractions thereof for the prevention and treatment of brain diseases, including Creutzfeldt-Jacob disease (CJD) and multiple sclerosis (MS).
Over the last two decades, carbon based materials and especially carbon nanotubes (CNTs), were the subject of many studies, mainly due to their unique electrical, optical and mechanical properties (Ouyang et al., 2002; Dresselhaus et al., 2003; Dresselhaus et al., 1995). CNTs can combine electrical conductivity with wide absorption spectra, and can be produced in large scale (Danafar et al., 2009) [4]. These properties enable to realize CNTs in simple, low-cost detector. Here we present a proof-of-concept for such a detector operating at the short-wave infrared (SWIR) regime. We use a simple spray technique, which allows creating a large matrix of CNT bundles. Semiconducting quantum dots (QDs) were adsorbed on top of the CNTs, enhancing the sensitivity to the infrared regime. This regime is important for numerous applications in the civil, medical, defense and security fields. Controlled coupling between the QDs and the CNT matrix generates gate-like electro-optical response when light is absorbed. This proof-of-concept for a detector in the SWIR region is presented for large surfaces and substrates, while the responsivity and detectivity of the detector in a range of frequencies and wavelengths was evaluated.
This paper presents a Simplified Metastatistical Extreme Value formulation (SMEV) able to model hydro- meteorological extremes emerging from multiple underlying processes. The formulation explicitly includes the average intensity and probability of occurrence of the processes allowing to parsimoniously model changes in these quantities to quantify changes in the probability of occurrence of extremes. SMEV allows (a) frequency analyses of extremes emerging from multiple underlying processes and (b) computationally efficient analyses of the sensitivity of extreme quantiles to changes in the characteristics of the underlying processes; moreover, (c) it provides a robust framework for explanatory models, nonstationary frequency analyses, and climate projections. The methodology is applied to daily precipitation data from long recording stations in the eastern Mediter- ranean, using Weibull distributions to model daily precipitation amounts generated by two classes of synoptic systems. At-site application of SMEV provides spatially consistent estimates of extreme quantiles, in line with regional GEV estimates and generally characterized by reduced uncertainties. The sensitivity of extreme quan- tiles to changes and uncertainty in the intensity and yearly occurrences of events generated by different synoptic classes is examined, and an application of SMEV for the projection of future extremes is provided.
Localization of rectal tumors is a challenge in minimally invasive surgery due to the lack of tactile sensation. We had developed liposomal indocyanine green (Lip-ICG) for localization of rectal tumor. In this study we evaluated the effects of liposome size and lipid PEGylation on imaging. We used an endoscopically-guided orthotopic exptl. rectal cancer model in which tumor fluorescence was determined at different time points after i.v. (i.v.) administration of Lip-ICG and PEGylated liposomes (PEG-Lip-ICG). Signal intensity was measured by tumor-to-background ratio (TBR), or normalized TBR (compared to TBR of free ICG). Fluorescence microscopy of tumor tissue was performed to determine fluorescence localization within the tissue and blood vessels. Liposomes of 60 nm showed an increased TBR compared with free ICG at 12 h after i.v. injection: normalized TBR (nTBR) = 3.11 vs. 1, resp. (p = 0.006). Larger liposomes (100 nm and 140 nm) had comparable signal to free ICG (nTBR = 0.98 ± 0.02 and 0.78 ± 0.08, resp.), even when addnl. time points were examined (0.5, 3 and 24 h). PEG-Lip- ICG were more efficient than Lip-ICG (TBR = 4.2 ± 0.18 vs. 2.5 ± 0.12, p < 0.01) presumably because of reduced uptake by the reticulo-endothelial system. ICG was found outside the capillaries in tumor margins. We conclude that size and lipid modification impact imaging intensity.
If we live in media, then our knowledge of our social lives must, at least partly, come from those media. It is in this context that I analyze www.facebook.com/peace, a page that claims to show “how many new friendships formed just yesterday” between Facebook users from the opposing sides of three different protracted conflicts. However, the numbers seem unfeasible, leading to a series of attempts to try and evaluate them independently, as well as to ask Facebook if they could explain them. This article presents these failed efforts to verify the numbers published by Facebook, and the subsequent conclusion that they are, technically speaking, bullshit, and more specifically, social media bullshit. It is in reaching this conclusion that the article contributes to theoretical discussions around data, social media, and knowledge.
If we live in media, then our knowledge of our social lives must, at least partly, come from those media. It is in this context that I analyze www.facebook.com/peace, a page that claims to show “how many new friendships formed just yesterday” between Facebook users from the opposing sides of three different protracted conflicts. However, the numbers seem unfeasible, leading to a series of attempts to try and evaluate them independently, as well as to ask Facebook if they could explain them. This paper presents these failed efforts to verify the numbers published by Facebook, and the subsequent conclusion that they are, technically speaking, bullshit, and more specifically, social media bullshit. It is in reaching this conclusion that the article contributes to theoretical discussions around data, social media, and knowledge.
Abstract In this work, the electronic structure and spectroscopic properties of lumiflavin are calculated using various quantum chemical methods. The excitation energies for ten singlet and triplet states as well as the analysis of the electron density difference are assessed using various wave function-based methods and density functionals. The relative order of singlet and triplet excited states is established on the basis of the coupled cluster method CC2. We find that at least seven singlet excited states are required to assign all peaks in the UV/Vis spectrum. In addition, we have studied the solvatochromic effect on the excitation energies and found differential effects except for the first bright excited state. Vibrational frequencies as well as IR, Raman and resonance Raman intensities are simulated and compared to their experimental counterparts. We have assigned peaks, assessed the effect of anharmonicity, and confirmed the previous assignments in case of the most intense transitions. Finally, we have studied the NMR shieldings and established the effect of the solvent polarity. The present study provides data for lumiflavin in the gas phase and in implicit solvent model that can be used as a reference for the protein-embedded flavin simulations and assignment of experimental spectra.
The conjecture that, as in bulk semiconductors, hot multiexcitons in nanocrystals cool rapidly to the lowest available energy levels is tested here by recording the effects of a single cold “spectator” exciton on the relaxation dynamics of a subsequently deposited hot counterpart. Results in CdSe/CdS nanodots show that a preexisting cold “spectator exciton” allows only half of the photoexcited electrons to relax directly to the band-edge. The rest are blocked in an excited quantum state due to conflicts in spin orientation. The latter fully relax in this sample only after ∼25 ps as the blocked electrons spins flip, prolonging the temporal window of opportunity for harvesting the retained energy more than 100 fold! Common to all quantum-confined nanocrystals, this process will delay cooling and impact the spectroscopic signatures of hot multiexcitons in all envisioned generation scenarios. How the spin-flipping rate scales with particle size and temperature remains to be determined.
An efficient and general method for the chemoselective synthesis of unsymmetrical gem-diborylalkanes is reported. This method is based on a novel late-stage desymmetrization via nucleophilic “trifluorination”, providing chiral gem-diborylalkanes bearing a trifluoroborate group. The reaction offers a highly modular and diastereoselective approach to synthesize gem-diborylcyclopropanes. The utility of the gem-diborylalkane building blocks was demonstrated by selective post-functionalization of the trifluoroborate group. These functionalizations include inter- and intra- Pd-catalyzed Suzuki−Miyaura coupling reactions.
Linear-scaling implementations of density functional theory (DFT) reach their intended efficiency regime only when applied to systems having a physical size larger than the range of their Kohn–Sham density matrix (DM). This causes a problem since many types of large systems of interest have a rather broad DM range and are therefore not amenable to analysis using DFT methods. For this reason, the recently proposed stochastic DFT (sDFT), avoiding exhaustive DM evaluations, is emerging as an attractive alternative linear-scaling approach. This review develops a general formulation of sDFT in terms of a (non)orthogonal basis representation and offers an analysis of the statistical errors (SEs) involved in the calculation. Using a new Gaussian-type basis-set implementation of sDFT, applied to water clusters and silicon nanocrystals, it demonstrates and explains how the standard deviation and the bias depend on the sampling rate and the system size in various types of calculations. We also develop a basis-set embedded-fragments theory, demonstrating its utility for reducing the SEs for energy, density of states and nuclear force calculations. Finally, we discuss the algorithmic complexity of sDFT, showing it has CPU wall-time linear-scaling. The method parallelizes well over distributed processors with good scalability and therefore may find use in the upcoming exascale computing architectures. This article is categorized under: Electronic Structure Theory \textgreater Ab Initio Electronic Structure Methods Structure and Mechanism \textgreater Computational Materials Science Electronic Structure Theory \textgreater Density Functional Theory
