Low-energy structures of zinc borohydride Zn(BH4_4)2_2

We present a systematic study of the low-energy structures of zinc borohydride, a crystalline material proposed for the hydrogen storage purpose. In addition to the previously proposed structures, many new low-energy structures of zinc borohydride are found by utilizing the minima-hopping method. We identify a new dynamically stable structure which belongs to the $I4_122$ space group as the most stable phase of zinc borohydride at low temperatures. A low transition barrier between $I4_122$ and $P1$, the two lowest-lying phases of zinc borohydride is predicted, implying that a coexistence of low-lying phases of zinc borohydride is possible at ambient conditions. An analysis based on the simulated X-ray diffraction pattern reveals that the $I4_122$ structure exhibits the same major features as the experimentally synthesized zinc borohydride samples.Comment: Version accepted by Phys. Rev. B. Manuscript has 8 pages, 5 figures, 2 tables (with 6 pages, 5 figures, 2 tables in supplemental material

APMEC: An Automated Provisioning Framework for Multi-access Edge Computing

Novel use cases and verticals such as connected cars and human-robot cooperation in the areas of 5G and Tactile Internet can significantly benefit from the flexibility and reduced latency provided by Network Function Virtualization (NFV) and Multi-Access Edge Computing (MEC). Existing frameworks managing and orchestrating MEC and NFV are either tightly coupled or completely separated. The former design is inflexible and increases the complexity of one framework. Whereas, the latter leads to inefficient use of computation resources because information are not shared. We introduce APMEC, a dedicated framework for MEC while enabling the collaboration with the management and orchestration (MANO) frameworks for NFV. The new design allows to reuse allocated network services, thus maximizing resource utilization. Measurement results have shown that APMEC can allocate up to 60% more number of network services. Being developed on top of OpenStack, APMEC is an open source project, available for collaboration and facilitating further research activities

Low-Energy Polymeric Phases of Alanates

Low-energy structures of alanates are currently known to be described by patterns of isolated, nearly ideal tetrahedral [AlH$_4$] anions and metal cations. We discover that the novel polymeric motif recently proposed for LiAlH$_4$ plays a dominant role in a series of alanates, including LiAlH$_4$, NaAlH$_4$, KAlH$_4$, Mg(AlH$_4$)$_2$, Ca(AlH$_4$)$_2$ and Sr(AlH$_4$)$_2$. In particular, most of the low-energy structures discovered for the whole series are characterized by networks of corner-sharing [AlH$_6$] octahedra, forming wires and/or planes throughout the materials. Finally, for Mg(AlH$_4$)$_2$ and Sr(AlH$_4$)$_2$, we identify two polymeric phases to be lowest in energy at low temperatures.Comment: 9 pages, 8 figures, 2 tables, including supplemental materia

Aspergillus nidulans Septa Are Indispensable for Surviving Cell Wall Stress

Septation in filamentous fungi is a normal part of development, which involves the formation of cross-hyphal bulkheads, typically containing pores, allowing cytoplasmic streaming between compartments. Based on previous findings regarding septa and cell wall stress, we hypothesized that septa are critical for survival during cell wall stress. To test this hypothesis, we used known Aspergillus nidulans septation-deficient mutants (ΔsepH, Δbud3, Δbud4, and Δrho4) and six antifungal compounds. Three of these compounds (micafungin, Congo red, and calcofluor white) are known cell wall stressors which activate the cell wall integrity signaling pathway (CWIS), while the three others (cycloheximide, miconazole, and 2,3-butanedione monoxime) perturb specific cellular processes not explicitly related to the cell wall. Our results show that deficiencies in septation lead to fungi which are more susceptible to cell wall-perturbing compounds but are no more susceptible to other antifungal compounds than a control. This implies that septa play a critical role in surviving cell wall stress

Calmness of efficient solution maps in parametric vector optimization

The paper is concerned with the stability theory of the efficient solution map of a parametric vector optimization problem. Utilizing the advanced tools of modern variational analysis and generalized differentiation, we study the calmness of the efficient solution map. More explicitly, new sufficient conditions in terms of the Fréchet and limiting coderivatives of parametric multifunctions for this efficient solution map to have the calmness at a given point in its graph are established by employing the approach of implicit multifunctions. Examples are also provided for analyzing and illustrating the results obtained. © 2011 Springer Science+Business Media, LLC

Dynamic networks differentiate the language ability of children with cochlear implants

Background: Cochlear implantation (CI) in prelingually deafened children has been shown to be an effective intervention for developing language and reading skill. However, there is a substantial proportion of the children receiving CI who struggle with language and reading. The current study–one of the first to implement electrical source imaging in CI population was designed to identify the neural underpinnings in two groups of CI children with good and poor language and reading skill. Methods: Data using high density electroencephalography (EEG) under a resting state condition was obtained from 75 children, 50 with CIs having good (HL) or poor language skills (LL) and 25 normal hearing (NH) children. We identified coherent sources using dynamic imaging of coherent sources (DICS) and their effective connectivity computing time-frequency causality estimation based on temporal partial directed coherence (TPDC) in the two CI groups compared to a cohort of age and gender matched NH children. Findings: Sources with higher coherence amplitude were observed in three frequency bands (alpha, beta and gamma) for the CI groups when compared to normal hearing children. The two groups of CI children with good (HL) and poor (LL) language ability exhibited not only different cortical and subcortical source profiles but also distinct effective connectivity between them. Additionally, a support vector machine (SVM) algorithm using these sources and their connectivity patterns for each CI group across the three frequency bands was able to predict the language and reading scores with high accuracy. Interpretation: Increased coherence in the CI groups suggest overall that the oscillatory activity in some brain areas become more strongly coupled compared to the NH group. Moreover, the different sources and their connectivity patterns and their association to language and reading skill in both groups, suggest a compensatory adaptation that either facilitated or impeded language and reading development. The neural differences in the two groups of CI children may reflect potential biomarkers for predicting outcome success in CI children

HW-FlowQ: A Multi-Abstraction Level HW-CNN Co-design Quantization Methodology

Model compression through quantization is commonly applied to convolutional neural networks (CNNs) deployed on compute and memory-constrained embedded platforms. Different layers of the CNN can have varying degrees of numerical precision for both weights and activations, resulting in a large search space. Together with the hardware (HW) design space, the challenge of finding the globally optimal HW-CNN combination for a given application becomes daunting. To this end, we propose HW-FlowQ, a systematic approach that enables the co-design of the target hardware platform and the compressed CNN model through quantization. The search space is viewed at three levels of abstraction, allowing for an iterative approach for narrowing down the solution space before reaching a high-fidelity CNN hardware modeling tool, capable of capturing the effects of mixed-precision quantization strategies on different hardware architectures (processing unit counts, memory levels, cost models, dataflows) and two types of computation engines (bit-parallel vectorized, bit-serial). To combine both worlds, a multi-objective non-dominated sorting genetic algorithm (NSGA-II) is leveraged to establish a Pareto-optimal set of quantization strategies for the target HW-metrics at each abstraction level. HW-FlowQ detects optima in a discrete search space and maximizes the task-related accuracy of the underlying CNN while minimizing hardware-related costs. The Pareto-front approach keeps the design space open to a range of non-dominated solutions before refining the design to a more detailed level of abstraction. With equivalent prediction accuracy, we improve the energy and latency by 20% and 45% respectively for ResNet56 compared to existing mixed-precision search methods

Accelerated diffusion-weighted imaging for lymph node assessment in the pelvis applying simultaneous multislice acquisition: A healthy volunteer study

To evaluate the feasibility of accelerated simultaneous multislice diffusion weighted sequences (SMS-DWI) for lymph node detection in the abdominopelvic region. Sequences were evaluated regarding the number and depiction of lymph nodes detected with SMS-DWI compared with conventional diffusion weighted sequences, the most suitable SMS- acceleration factor, signal-to-noise ratio (SNR), and the overall acquisition time (TA).Eight healthy volunteers (4 men, 4 women; age range 21-39 years; median age 25 years) were examined in the pelvic region at 3T using a conventional DWI sequence and a SMS DWI sequence with different acceleration factors (AF: 2-3). Moreover, a SMS DWI sequence with AF 3 and higher slice resolution was applied. For morphological correlation of the lymph nodes and as a reference standard, an isotropic 3-dimensional T2-weighted fast-spin-echo sequence with high sampling efficiency (SPACE) was acquired. Two radiologists reviewed each DWI sequence and assessed the number of lymph nodes and the overall image quality. For each DWI sequence, SNR, SNR efficiency per time, contrast to noise (CNR), and ADC values were calculated. Values were statistically compared using a Wilcoxon test (P < .05).Overall, scan time of SMS-DWI with AF2 (AF3) decreased by 46.9% (57.2%) with respect to the conventional DWI. Compared with the SPACE sequence, the detection rate was 89.6% for conventional DWI, 69.4% for SMS-DWI with AF2, and 59.9% for SMS-DWI with AF3. The highly resolved SMS-DWI with AF3 leads to a scan time reduction of 46.9% and detection rate of 83.0%. SNR and CNR were lower in the accelerated sequences (up to 51.0%, P < .001) as compared with the conventional DWI. SNR efficiency decreased to 19.3% for AF2 and to 31.3% for AF3. In the highly resolved dataset, an SNR efficiency reduction of 51.2% was found.This study showed that lymph node detection in the abdominopelvic region with accelerated SMS-DWI sequences is feasible whereby an AF of 2 represents the best compromise between image quality, SNR, CNR, TA, and detection rate