Rationality as the Rule of Reason

The demands of rationality are linked both to our subjective normative perspective (given that rationality is a person-level concept) and to objective reasons or favoring relations (given that rationality is non-contingently authoritative for us). In this paper, I propose a new way of reconciling the tension between these two aspects: roughly, what rationality requires of us is having the attitudes that correspond to our take on reasons in the light of our evidence, but only if it is competent. I show how this view can account for structural rationality on the assumption that intentions and beliefs as such involve competent perceptions of downstream reasons, and explore various implications of the account

CASTNet: Community-Attentive Spatio-Temporal Networks for Opioid Overdose Forecasting

Opioid overdose is a growing public health crisis in the United States. This crisis, recognized as "opioid epidemic," has widespread societal consequences including the degradation of health, and the increase in crime rates and family problems. To improve the overdose surveillance and to identify the areas in need of prevention effort, in this work, we focus on forecasting opioid overdose using real-time crime dynamics. Previous work identified various types of links between opioid use and criminal activities, such as financial motives and common causes. Motivated by these observations, we propose a novel spatio-temporal predictive model for opioid overdose forecasting by leveraging the spatio-temporal patterns of crime incidents. Our proposed model incorporates multi-head attentional networks to learn different representation subspaces of features. Such deep learning architecture, called "community-attentive" networks, allows the prediction of a given location to be optimized by a mixture of groups (i.e., communities) of regions. In addition, our proposed model allows for interpreting what features, from what communities, have more contributions to predicting local incidents as well as how these communities are captured through forecasting. Our results on two real-world overdose datasets indicate that our model achieves superior forecasting performance and provides meaningful interpretations in terms of spatio-temporal relationships between the dynamics of crime and that of opioid overdose.Comment: Accepted as conference paper at ECML-PKDD 201

Floquet engineering of the Lifshitz phase transition in the Hubbard model

Within the Floquet theory of periodically driven quantum systems, we demonstrate that an off-resonant high-frequency electromagnetic field can induce the Lifshitz phase transition in periodical structures described by the one-dimensional repulsive Hubbard model with the nearest and next-nearest neighbor hopping. The transition changes the topology of electron energy spectrum at the Fermi level, transforming it from the two Fermi-points to the four Fermi-points, what facilitates the emergence of the superconducting fluctuations in the structure. Possible manifestations of the effect and conditions of its experimental observability are discussed

Algorithm engineering for optimal alignment of protein structure distance matrices

Protein structural alignment is an important problem in computational biology. In this paper, we present first successes on provably optimal pairwise alignment of protein inter-residue distance matrices, using the popular Dali scoring function. We introduce the structural alignment problem formally, which enables us to express a variety of scoring functions used in previous work as special cases in a unified framework. Further, we propose the first mathematical model for computing optimal structural alignments based on dense inter-residue distance matrices. We therefore reformulate the problem as a special graph problem and give a tight integer linear programming model. We then present algorithm engineering techniques to handle the huge integer linear programs of real-life distance matrix alignment problems. Applying these techniques, we can compute provably optimal Dali alignments for the very first time

Convergent algorithms for protein structural alignment

<p>Abstract</p> <p>Background</p> <p>Many algorithms exist for protein structural alignment, based on internal protein coordinates or on explicit superposition of the structures. These methods are usually successful for detecting structural similarities. However, current practical methods are seldom supported by convergence theories. In particular, although the goal of each algorithm is to maximize some scoring function, there is no practical method that theoretically guarantees score maximization. A practical algorithm with solid convergence properties would be useful for the refinement of protein folding maps, and for the development of new scores designed to be correlated with functional similarity.</p> <p>Results</p> <p>In this work, the maximization of scoring functions in protein alignment is interpreted as a Low Order Value Optimization (LOVO) problem. The new interpretation provides a framework for the development of algorithms based on well established methods of continuous optimization. The resulting algorithms are convergent and <it>increase the scoring functions at every iteration</it>. The solutions obtained are critical points of the scoring functions. Two algorithms are introduced: One is based on the maximization of the scoring function with Dynamic Programming followed by the continuous maximization of <it>the same </it>score, with respect to the protein position, using a smooth Newtonian method. The second algorithm replaces the Dynamic Programming step by a fast procedure for computing the correspondence between C<it>α </it>atoms. The algorithms are shown to be very effective for the maximization of the STRUCTAL score.</p> <p>Conclusion</p> <p>The interpretation of protein alignment as a LOVO problem provides a new theoretical framework for the development of convergent protein alignment algorithms. These algorithms are shown to be very reliable for the maximization of the STRUCTAL score, and other distance-dependent scores may be optimized with same strategy. The improved score optimization provided by these algorithms provide means for the refinement of protein fold maps and also for the development of scores designed to match biological function. The LOVO strategy may be also used for more general structural superposition problems such as flexible or non-sequential alignments. The package is available on-line at http://www.ime.unicamp.br/~martinez/lovoalign.</p

Sexual Dysfunction in Jordanian Diabetic Women

OBJECTIVE—To estimate the prevalence of female sexual dysfunction (FSD) in diabetic and nondiabetic Jordanian women

Coupling effects in QD dimers at sub-nanometer interparticle distance

Currently, intensive research efforts focus on the fabrication of meso-structures of assembled colloidal quantum dots (QDs) with original optical and electronic properties. Such collective features originate from the QDs coupling, depending on the number of connected units and their distance. However, the development of general methodologies to assemble colloidal QD with precise stoichiometry and particle-particle spacing remains a key challenge. Here, we demonstrate that dimers of CdSe QDs, stable in solution, can be obtained by engineering QD surface chemistry, reducing the surface steric hindrance and favoring the link between two QDs. The connection is made by using alkyl dithiols as bifunctional linkers and different chain lengths are used to tune the interparticle distance from few nm down to 0.5 nm. The spectroscopic investigation highlights that coupling phenomena between the QDs in dimers are strongly dependent on the interparticle distance and QD size, ultimately affecting the exciton dissociation efficiency. [Figure not available: see fulltext.]

Hard-boiled Ecologies: Ross Macdonald’s Environmental Crime Fiction

Although Ross Macdonald’s position in the annals of great American hardboiled crime writers is unquestioned, what often been overlooked in the study of his works are the underlying environmental preoccupations that frequently serve as the background to, or context for, crime. This context of ecological violence is forcefully manifested in two of Macdonald’s later Archer novels The Underground Man (1971) and Sleeping Beauty (1973). This essay scrutinizes the environmental imperatives of Macdonald’s work, arguing that the damage and destruction inflicted upon the environment in these two texts becomes symbiotically connected to the broader, morally fraught social milieu of the city

Room-Temperature Inter-Dot Coherent Dynamics in Multilayer Quantum Dot Materials

The full blossoming of quantum technologies requires the availability of easy-to-prepare materials where quantum coherences can be effectively initiated, controlled, and exploited, preferably at ambient conditions. Solid-state multilayers of colloidally grown quantum dots (QDs) are highly promising for this task because of the possibility of assembling networks of electronically coupled QDs through the modulation of sizes, inter-dot linkers, and distances. To usefully probe coherence in these materials, the dynamical characterization of their collective quantum mechanically coupled states is needed. Here, we explore by two-dimensional electronic spectroscopy the coherent dynamics of solid-state multilayers of electronically coupled colloidally grown CdSe QDs and complement it by detailed computations. The time evolution of a coherent superposition of states delocalized over more than one QD was captured at ambient conditions. We thus provide important evidence for inter-dot coherences in such solid-state materials, opening up new avenues for the effective application of these materials in quantum technologies

Comprehensive structural classification of ligand binding motifs in proteins

Comprehensive knowledge of protein-ligand interactions should provide a useful basis for annotating protein functions, studying protein evolution, engineering enzymatic activity, and designing drugs. To investigate the diversity and universality of ligand binding sites in protein structures, we conducted the all-against-all atomic-level structural comparison of over 180,000 ligand binding sites found in all the known structures in the Protein Data Bank by using a recently developed database search and alignment algorithm. By applying a hybrid top-down-bottom-up clustering analysis to the comparison results, we determined approximately 3000 well-defined structural motifs of ligand binding sites. Apart from a handful of exceptions, most structural motifs were found to be confined within single families or superfamilies, and to be associated with particular ligands. Furthermore, we analyzed the components of the similarity network and enumerated more than 4000 pairs of ligand binding sites that were shared across different protein folds.Comment: 13 pages, 8 figure