An implementation of the coupled perturbed Kohn-Sham equations: perturbation due to nuclear displacements

The Coupled Perturbed Kohn-Sham equations have been implemented in the Amsterdam Density Functional program package. Our implementation differs from previous ones in many ways. This program uses density fitting to calculate the Coulomb and exchange integrals. Further, all matrix elements of the Fock type matrix and its derivatives are calculated by numerical integration. The frozen core approximation is also implemented. Our implementation is approximately 10 times faster than a finite difference algorithm, and the absolute CPU times also compare favorably with other reported implementations.     

Generalized ordering-search for learning directed probabilistic logical models

Recently, there has been an increasing interest in directed probabilistic logical models and a variety of formalisms for describing such models has been proposed. Although many authors provide high-level arguments to show that in principle models in their formalism can be learned from data, most of the proposed learning algorithms have not yet been studied in detail. We introduce an algorithm, generalized ordering-search, to learn both structure and conditional probability distributions (CPDs) of directed probabilistic logical models. The algorithm is based on the ordering-search algorithm for Bayesian networks. We use relational probability trees as a representation for the CPDs. We present experiments on a genetics domain, blocks world domains and the Cora dataset. Editors: Stephen Muggleton, Ramon Otero, Simon Colton.     

Citywide: Supporting Interactive Digital Experiences Across Physical Space

The Citywide project is exploring ways in which technology can provide people with rich and engaging digital experiences as they move through physical space, including historical experiences, performances and games. This paper describes some initial results and experiences with this project based upon two prototype demonstrators. In the first, we describe an application in which a search party explores an archaeological site, uncovering enacted scenes within the virtual world that are of a historical relevance to their particular physical location. In the second, we describe a museum experience where participants explore an outdoors location, hunting for buried virtual artifacts that they then bring back to a museum for a more detailed study. Our demonstrators employ a varied set of devices, including mobile wireless interfaces for locating hotspots of virtual activity when outdoors, to give different experiences of the virtual world depending upon location, task, available equipment and accuracy of tracking. We conclude by discussing some of the potential advantages of using an underlying shared virtual world to support interactive experiences across extended physical settings.     

Automated formal analysis and verification: an overview

This paper provides an overview of various existing approaches to automated formal analysis and verification. The most space is devoted to the approach of model checking, including its basic principles as well as the different techniques that have been proposed for dealing with the state space explosion problem in model checking. This paper, however, includes a brief discussion of theorem proving and static analysis too. All of the discussed approaches are introduced mostly on an informal level, with an attempt to provide the reader with their basic ideas and references to works where more details can be found.     

A continuous-time delta-sigma modulator for 802.11a/b/g WLAN implemented with a hierarchical bottom-up optimization methodology

This paper presents a 3rd-order continuous-time Delta-Sigma modulator with a resolution of 10 bits for a 10 MHz signal bandwidth. It is designed in a standard 0.18 μm CMOS technology and consumes only 6 mW. After the design/selection of the topologies for the integrators, comparator and D/A converters, optimal sizing of the complete modulator was ensured by using a hierarchical bottom-up, multi-objective evolutionary design methodology. With this methodology, a set of Pareto-optimal modulator designs is generated by using Pareto-optimal performance solutions of the hierarchically decomposed lower-level subblocks. From the generated Pareto-optimal design set, a final optimal design is chosen that complies with the specifications for the 802.11a/b/g WLAN standard and has minimal power consumption.     

Susceptible Workload Evaluation and Protection using Selective Fault Tolerance

Low power fault tolerance design techniques trade reliability to reduce the area cost and the power overhead of integrated circuits by protecting only a subset of their workload or their most vulnerable parts. However, in the presence of faults not all workloads are equally susceptible to errors. In this paper, we present a low power fault tolerance design technique that selects and protects the most susceptible workload. We propose to rank the workload susceptibility as the likelihood of any error to bypass the logic masking of the circuit and propagate to its outputs. The susceptible workload is protected by a partial Triple Modular Redundancy (TMR) scheme. We evaluate the proposed technique on timing-independent and timing-dependent errors induced by permanent and transient faults. In comparison with unranked selective fault tolerance approach, we demonstrate a) a similar error coverage with a 39.7% average reduction of the area overhead or b) a 86.9% average error coverage improvement for a similar area overhead. For the same area overhead case, we observe an error coverage improvement of 53.1% and 53.5% against permanent stuck-at and transition faults, respectively, and an average error coverage improvement of 151.8% and 89.0% against timing-dependent and timing-independent transient faults, respectively. Compared to TMR, the proposed technique achieves an area and power overhead reduction of 145.8% to 182.0%.     

Distribution of the Amphipod Diporeia in Lake Superior: The Ring of Fire

Diporeia, formerly the dominant benthic macroinvertebrate in the Great Lakes, remains a keystone species in Lake Superior. Little is known, however, about fine scale amphipod distributions, especially as influenced by the production, transport and transformation of energy resources. Here, we document the distribution and abundance of Diporeia along 19 transects around the lake's perimeter. Regions of elevated density, averaging 958 ± 408 Diporeia/m² (mean ± S.D.) were observed along all transects, typically within slope habitat (depth of 30–125 m). Waters shoreward (shelf habitat, < 30 m) and lakeward (profundal habitat, > 125 m) of these regions supported significantly lower densities, averaging 239 ± 178/m² and 106 ± 59/m², respectively. Amphipods within regions of elevated density, termed here the Ring of Fire, account for two-thirds of the lakewide population while occupying only one-quarter of the benthic habitat. The Ring of Fire, observed lakewide as a band averaging 14.2 ± 9.4 km in width, is characterized as a region of transitional sediment deposition with gentle slope, proximate to nearshore locations of elevated primary production. Within the Ring of Fire exceptionally high densities are found in the south central region, where the Keweenaw Current and slope bathymetries serve to funnel production from adjoining regions of high production. Density measurements for the 173 stations sampled here are used to estimate lakewide Diporeia standing stock (22.5–37.7 trillion individuals, 4.4–7.4 Gg dry weight, 2.1–3.5 Gg C), individual and biomass density (274–460/m², 0.05–0.09 g DW/m², 0.03–0.04 gC/m²) and areal (0.02–0.03 g C/m²/yr) and total (1.6–2.6 Gg C/yr) production.     

SARS-CoV-2 Infection Dysregulates Cilia and Basal Cell Homeostasis in the Respiratory Epithelium of Hamsters

Similar to many other respiratory viruses, SARS-CoV-2 targets the ciliated cells of the respiratory epithelium and compromises mucociliary clearance, thereby facilitating spread to the lungs and paving the way for secondary infections. A detailed understanding of mechanism involved in ciliary loss and subsequent regeneration is crucial to assess the possible long-term consequences of COVID-19. The aim of this study was to characterize the sequence of histological and ultrastructural changes observed in the ciliated epithelium during and after SARS-CoV-2 infection in the golden Syrian hamster model. We show that acute infection induces a severe, transient loss of cilia, which is, at least in part, caused by cilia internalization. Internalized cilia colocalize with membrane invaginations, facilitating virus entry into the cell. Infection also results in a progressive decline in cells expressing the regulator of ciliogenesis FOXJ1, which persists beyond virus clearance and the termination of inflammatory changes. Ciliary loss triggers the mobilization of p73⁺ and CK14⁺ basal cells, which ceases after regeneration of the cilia. Although ciliation is restored after two weeks despite the lack of FOXJ1, an increased frequency of cilia with ultrastructural alterations indicative of secondary ciliary dyskinesia is observed. In summary, the work provides new insights into SARS-CoV-2 pathogenesis and expands our understanding of virally induced damage to defense mechanisms in the conducting airways.     

Group Study of Simulated Driving fMRI Data by Multiset Canonical Correlation Analysis

In this work, we apply a novel statistical method, multiset canonical correlation analysis (M-CCA), to study a group of functional magnetic resonance imaging (fMRI) datasets acquired during simulated driving task. The M-CCA method jointly decomposes fMRI datasets from different subjects/sessions into brain activation maps and their associated time courses, such that the correlation in each group of estimated activation maps across datasets is maximized. Therefore, the functional activations across all datasets are extracted in the order of consistency across different dataset. On the other hand, M-CCA preserves the uniqueness of the functional maps estimated from each dataset by avoiding concatenation of different datasets in the analysis. Hence, the cross-dataset variation of the functional activations can be used to test the hypothesis of functional-behavioral association. In this work, we study 120 simulated driving fMRI datasets and identify parietal-occipital regions and frontal lobe as the most consistently engaged areas across all the subjects and sessions during simulated driving. The functional-behavioral association study indicates that all the estimated brain activations are significantly correlated with the steering operation during the driving task. M-CCA thus provides a new approach to investigate the complex relationship between the brain functions and multiple behavioral variables, especially in naturalistic tasks as demonstrated by the simulated driving study.