Sequence-Dependent Nanofiber Structures of Phenylalanine and Isoleucine Tripeptides

The molecular design of short peptides to achieve a tailor-made functional architecture has attracted attention during the past decade but remains challenging as a result of insufficient understanding of the relationship between peptide sequence and assembled supramolecular structures. We report a hybrid-resolution model to computationally explore the sequence–structure relationship of self-assembly for tripeptides containing only phenylalanine and isoleucine. We found that all these tripeptides have a tendency to assemble into nanofibers composed of laterally associated filaments. Molecular arrangements within the assemblies are diverse and vary depending on the sequences. This structural diversity originates from (1) distinct conformations of peptide building blocks that lead to different surface geometries of the filaments and (2) unique sidechain arrangements at the filament interfaces for each sequence. Many conformations are available for tripeptides in solution, but only an extended β-strand and another resembling a right-handed turn are observed in assemblies. It was found that the sequence dependence of these conformations and the packing of resulting filaments are determined by multiple competing noncovalent forces, with hydrophobic interactions involving Phe being particularly important. The sequence pattern for each type of assembly conformation and packing has been identified. These results highlight the importance of the interplay between conformation, molecular packing, and sequences for determining detailed nanostructures of peptides and provide a detailed insight to support a more precise design of peptide-based nanomaterials.     

Reduction of temperature influence in stress measurement using surface SH‐wave acoustoelasticity

Stress measurements are required to prevent collapse accidents of structures. Surface SH‐wave acoustoelasticity can measure principal stress difference nondestructively and easily. Currently, surface SH‐wave acoustoelasticity can measure with high precision using a T‐type surface SH‐wave sensor in ideal environments such as in the laboratory. However, in actual environments, it cannot be measured with high precision due to change in the temperature of the specimen. In this paper, temperature dependence of surface SH‐wave acoustoelastic constants was verified to investigate the influence of specimen temperature on surface SH‐wave acoustoelasticity. In addition, the measuring system of surface SH‐wave acoustoelasticity using a cross T‐type surface SH‐wave sensor to reduce the influence of specimen temperature was developed.     

Alcoholism detection based on Hu moment invariants of event-related potentials

Diagnostic efforts to identify alcoholism are frequently subjective; however, recent technological advances have allowed the automated assessment of objective signals. To improve the performance of the automated classification of patients with alcohol dependence (AD) and controls, we analyzed features of event-related potentials (ERPs) in 72 subjects with AD and 42 controls while the subjects underwent three different visual oddball tasks. In addition to such commonly used morphological features (MFs) as time-domain amplitude and latency components as well as discrete wavelet transform coefficient entropies (WEs), we analyzed Hu moment invariants (HMIs) in this study. Smaller P3 and P2 amplitudes, longer latencies, lower WE values, and lower HMI values were observed for AD subjects relative to those observed for controls. We used a Naïve Bayes algorithm to compare classification accuracies among MFs, WEs, HMIs, combinations of MFs/WEs, and combinations of all three characteristics. We found that HMIs improved the classification accuracy by 17%. Our findings demonstrated that a combined feature analysis of ERPs obtained during a visual oddball task can be a useful and discriminative tool for diagnostic purposes in alcoholism and that HMIs show promise for improving the objective diagnosis of alcoholism and similar diseases.     

Peaks Over Thresholds Modeling With Multivariate Generalized Pareto Distributions

When assessing the impact of extreme events, it is often not just a single component, but the combined behavior of several components which is important. Statistical modeling using multivariate generalized Pareto (GP) distributions constitutes the multivariate analogue of univariate peaks over thresholds modeling, which is widely used in finance and engineering. We develop general methods for construction of multivariate GP distributions and use them to create a variety of new statistical models. A censored likelihood procedure is proposed to make inference on these models, together with a threshold selection procedure, goodness-of-fit diagnostics, and a computationally tractable strategy for model selection. The models are fitted to returns of stock prices of four UK-based banks and to rainfall data in the context of landslide risk estimation. Supplementary materials and codes are available online.     

Testing the oil price efficiency using various measures of long-range dependence

In this paper, we empirically examine the application of a host of techniques employed to measure price efficiency through long-range dependence using prices of monthly oil contracts. Using a series of methods, we analyse the volatility (daily absolute returns) of WTI and Brent oil prices for nine different contracts with maturity, ranging from 1 to 9 months, during the sample period of 1990-2017. We use bootstrapping to compute the confidence interval of the parameter of long-range dependence. Our results indicate that on an average, there is no long-range dependence in the volatility of oil price contracts at least at the 10-percent level of significance. Moreover, our results of rolling estimates suggest that the normality assumption does not affect the results considerably, and the results are robust to different rolling window sizes. While the results of the efficiency index suggest that the efficiency of oil returns vary with time, the futures contracts for Brent oil are found to be less efficient compared to WTI oil. The long-term futures contracts are more efficient than short-term contracts.     

Prediction of Long-Term Treatment Response to Selective Serotonin Reuptake Inhibitors (SSRIs) Using Scalp and Source Loudness Dependence of Auditory Evoked Potentials (LDAEP) Analysis in Patients with Major Depressive Disorder

Background: Animal and clinical studies have demonstrated that the loudness dependence of auditory evoked potentials (LDAEP) is inversely related to central serotonergic activity, with a high LDAEP reflecting weak serotonergic neurotransmission and vice versa, though the findings in humans have been less consistent. In addition, a high pretreatment LDAEP appears to predict a favorable response to antidepressant treatments that augment the actions of serotonin. The aim of this study was to test whether the baseline LDAEP is correlated with response to long-term maintenance treatment in patients with major depressive disorder (MDD). Methods: Scalp N1, P2 and N1/P2 LDAEP and standardized low resolution brain electromagnetic tomography-localized N1, P2, and N1/P2 LDAEP were evaluated in 41 MDD patients before and after they received antidepressant treatment (escitalopram (n = 32, 10.0 ± 4.0 mg/day), sertraline (n = 7, 78.6 ± 26.7 mg/day), and paroxetine controlled-release formulation (n = 2, 18.8 ± 8.8 mg/day)) for more than 12 weeks. A treatment response was defined as a reduction in the Beck Depression Inventory (BDI) score of >50% between baseline and follow-up. Results: The responders had higher baseline scalp P2 and N1/P2 LDAEP than nonresponders (p = 0.017; p = 0.036). In addition, changes in total BDI score between baseline and follow-up were larger in subjects with a high baseline N1/P2 LDAEP than those with a low baseline N1/P2 LDAEP (p = 0.009). There were significantly more responders in the high-LDAEP group than in the low-LDAEP group (p = 0.041). Conclusions: The findings of this study reveal that a high baseline LDAEP is associated with a clinical response to long-term antidepressant treatment.     

Qualification of an ultrasonic flow meter as a transfer standard for measurements at Reynolds numbers up to 4×106 between NMIJ and PTB

The quality of any laboratory intercomparison depends to a large extent on the performance of the used flow meter. To find a flow meter that is capable of reaching a reproducibility better than 0.05% requires bounding all involved influence quantities down to the required level. The present paper describes the efforts performed while qualifying a time-of-flight ultrasonic flow meter as a transfer standard. It was determined that the most relevant influence quantity besides the flow profile within the bulk flow is the effect caused by the transducer pockets in the meter body. By taking advantage of a specially designed window chamber, it was possible to determine the magnitude of the errors introduced by the transducer pockets and to define, based on the findings, a procedure to perform a bilateral comparison between the hot water calibration facilities of the Physikalisch-Technische Bundesanstalt and the National Institute of Advanced Industrial Science and Technology. The results of the bilateral comparison are presented.     

Goal-oriented dynamic test generation

ContextMemory safety errors such as buffer overflow vulnerabilities are one of the most serious classes of security threats. Detecting and removing such security errors are important tasks of software testing for improving the quality and reliability of software in practice.ObjectiveThis paper presents a goal-oriented testing approach for effectively and efficiently exploring security vulnerability errors. A goal is a potential safety violation and the testing approach is to automatically generate test inputs to uncover the violation.MethodWe use type inference analysis to diagnose potential safety violations and dynamic symbolic execution to perform test input generation. A major challenge facing dynamic symbolic execution in such application is the combinatorial explosion of the path space. To address this fundamental scalability issue, we employ data dependence analysis to identify a root cause leading to the execution of the goal and propose a path exploration algorithm to guide dynamic symbolic execution for effectively discovering the goal.ResultsTo evaluate the effectiveness of our proposed approach, we conducted experiments against 23 buffer overflow vulnerabilities. We observed a significant improvement of our proposed algorithm over two widely adopted search algorithms. Specifically, our algorithm discovered security vulnerability errors within a matter of a few seconds, whereas the two baseline algorithms failed even after 30 min of testing on a number of test subjects.ConclusionThe experimental results highlight the potential of utilizing data dependence analysis to address the combinatorial path space explosion issue faced by dynamic symbolic execution for effective security testing.     

Study of haze emission efficiency based on new co-opetition data envelopment analysis

As haze intensifies in China, controlling haze emission has become the country's top priority for environmental protection. Because haze moves across different regions, it is necessary to develop a data envelopment analysis (DEA) model underpinned by both competition and cooperation to evaluate the haze emission efficiency in different provinces. This study innovatively adopts the spatial econometrics to construct the co-opetition matrices of Chinese provinces, then builds the co-opetition DEA model to evaluate the haze emission efficiency of them, and finally uses the haze data of 2015 as an example to assess the applicability of the model. The results of the study include the following: First, compared with the traditional CCR (A. Charnes & W. W. Cooper & E. Rhodes) model, this study constructs the co-opetition DEA cross-efficiency model that integrates haze's feature of cross-border moving; thus, it is more in line with the reality of haze emission and movement. Second, compared with the efficiency value gained from the CCR model, the haze emission efficiency values for Tianjin and Guangdong, two decision-making units, register greater variance when using the DEA model. The reason might lie in that they have a different spatial transportation relationship with their surrounding provinces. Third, the haze emission efficiency of provinces, according to the evaluation based on the co-opetition DEA method, varies greatly: Those with high efficiency are mostly inland provinces with slow economic growth and adverse climatic conditions, whereas many of the provinces with low efficiency are located in the relatively prosperous East China. The specific co-opetition DEA model constructed in this study enriches the research on the DEA model, which can be applied to the emission efficiency evaluation of similar pollutants around the world and can contribute empirical support to the haze reducing efforts of the government with its empirical results.     

Thermally-induced phase transformations in KNNS-BNKZ lead-free piezoceramics

Promising piezoelectric properties have been reported in potassium sodium niobate-based ceramics by introducing Bi_0.5(Na_0.82K_0.18)_0.5ZrO₃ (BNKZ) into K_0.48Na_0.52Nb_0.95Sb_0.05O₃ (KNNS) solid solutions in order to control the polymorphic phase transformation temperatures. In the present study, synchrotron x-ray powder diffraction (SXPD) was employed in combination with dielectric and ferroelectric measurements in order to clarify the influence of BNKZ on the phase transition temperatures of (1-x)KNNS-(x)BNKZ ceramics (with x = 0 to 0.05). The results, presented in terms of temperature-dependent SXPD patterns, dielectric permittivity and thermal depolarisation characteristics, confirmed that polymorphic phase transformation temperatures all shifted in a systematic manner with increasing BNKZ content. Broadening of the phase transition regions was also observed with increasing BNKZ content, leading to improvements in thermal stability of the ferroelectric properties. Microstructural examination of the KNNS-BNKZ ceramics revealed the presence of core-shell microstructures; this was correlated with the presence of weak shoulders on the diffraction peaks.