Dissociation of processes in belief: Source recollection, statement familiarity, and the illusion of truth.

Reports 4 experiments concerning the effect of repetition on rated truth (the illusory-truth effect). Statements were paired with differentially credible sources (true vs false). Old trues would be rated true on 2 bases, source recollection and statement familiarity. Old falses, however, would be rated false if sources were recollected, leaving the unintentional influence of familiarity as their only basis for being rated true. Even so, falses were rated truer than new statements unless sources were especially memorable. Estimates showed the contributions of the 2 influences to be independent; the intentional influence of recollection was reduced if control was impaired, but the unintentional influence of familiarity remained constant. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Biexciton emission and crystalline quality of ZnO nano-objects

The design of cost-effective standards for the quality of nano-objects is currently a key issue toward their massive use for optoelectronic applications. The observation by photoluminescence of narrow excitonic and biexcitonic emission lines in semiconductor nanowires is usually accepted as evidence for high structural quality. Here, we perform time-resolved cathodoluminescence experiments on isolated ZnO nanobelts grown by chemical vapor deposition. We observe narrow emission lines at low temperature, together with a clear biexciton line. Still, drastic alterations in both the CL intensity and lifetime are observed locally along the nano-object. We attribute these to non-radiative recombinations at edge dislocations, closing basal plane stacking faults, inhomogeneously distributed along the NB length. This leads us to the conclusion that the observation of narrow excitonic and biexcitonic emission lines is far from sufficient to grade the quality of a nano-object.     

Effect of Curd Washing Level on Proteolysis and Functionality of Low-Moisture Mozzarella Cheese Made with Galactose-Fermenting Culture

Abstract: The effect of curd washing on functional properties of low-moisture mozzarella cheese made with galactose-fermenting culture was investigated. A total of 4 curd washing levels (0%, 10%, 25%, 50% wt/wt) were used during low-moisture mozzarella cheese manufacture, and cheeses were stored for 63 d at 4 °C and the influence of curd washing on proteolysis and functionality of low-moisture mozzarella cheese were examined. Curd washing had a significant effect on moisture and ash contents. In general, moisture contents increased and ash contents decreased with increased curd washing levels. Low-moisture mozzarella cheese made with 10% curd washing levels showed higher proteolysis, meltability, and stretchability during storage than other experimental cheeses. In general, galactose contents decreased during storage; however, cheeses made with 25% and 50% curd washing levels had lower galactose contents than those with control or 10%. L*-values (browning) decreased and proteolysis increased in low-moisture mozzarella cheeses during storage.     

Effects of extended dry storage of powdered infant milk formula on susceptibility of Enterobacter sakazakii to hot water and ionizing radiation

Infant milk formula has been identified as a potential source of Enterobacter sakazakii, which has been implicated in neonatal meningitis and necrotizing enterocolitis. This study was undertaken to determine whether the length of E. sakazakii storage in powdered infant milk formula (PIMF) affected the ability of the pathogen to survive subsequent reconstitution of the powder with hot water or treatment with gamma radiation. Five E. sakazakii strains were mixed individually with PIMF and kept for up to 12 months at 25 degrees C. After storage PIMF was reconstituted with water at 60 to 100 degrees C or was exposed to < or = 5 kGy of gamma radiation. Without any treatment secondary to drying, E. sakazakii counts decreased < 1 log/g after 1 month but decreased about 4 log/g during storage for 8 to 12 months. Dry storage decreased thermal resistance but increased resistance of E. sakazakii to ionizing radiation in PIMF. Reconstitution of contaminated powder with water at 70 degrees C after 1 month of dry storage reduced E. sakazakii viability slightly, > 2 log/g, and after powder was stored for 12 months all E. sakazakii strains were eliminated. In contrast, desiccation substantially increased the resistance of E. sakazakii strains to ionizing radiation. Although the D-value for E. sakazakii IMF1 following overnight storage in PIMF was 0.98 kGy, > 4 kGy was required to kill 1.5 log/g of the same strain that had survived 12 months in dry PIMF. Results suggested that low-dose irradiation will more effectively eliminate E. sakazakii from PIMF if the treatment is applied shortly after PIMF manufacture.     

Evolutionary Intelligence and Deep Learning Enabled Diabetic Retinopathy Classification Model

Diabetic Retinopathy (DR) has become a widespread illness among diabetics across the globe. Retinal fundus images are generally used by physicians to detect and classify the stages of DR. Since manual examination of DR images is a time-consuming process with the risks of biased results, automated tools using Artificial Intelligence (AI) to diagnose the disease have become essential. In this view, the current study develops an Optimal Deep Learning-enabled Fusion-based Diabetic Retinopathy Detection and Classification (ODL-FDRDC) technique. The intention of the proposed ODL-FDRDC technique is to identify DR and categorize its different grades using retinal fundus images. In addition, ODL-FDRDC technique involves region growing segmentation technique to determine the infected regions. Moreover, the fusion of two DL models namely, CapsNet and MobileNet is used for feature extraction. Further, the hyperparameter tuning of these models is also performed via Coyote Optimization Algorithm (COA). Gated Recurrent Unit (GRU) is also utilized to identify DR. The experimental results of the analysis, accomplished by ODL-FDRDC technique against benchmark DR dataset, established the supremacy of the technique over existing methodologies under different measures.     

A Comparative Study of Superconductivity and Thermally Activated Flux Flow of YBa2Cu3O7-δ and YBa2Cu3O7-δ/La1-x-yPrxCayMnO3 Bilayers

Journal of Superconductivity and Novel Magnetism - YBa2Cu3O7-δ/La1-x-yPrxCayMnO3 (YBCO/LPCMO) (x?~?0.31, y?~?0.35) bilayers with fixed ferromagnetic layer thickness...     

Multi-Fidelity High-Throughput Optimization of Electrical Conductivity in P3HT-CNT Composites

Combining high-throughput experiments with machine learning accelerates materials and process optimization toward user-specified target properties. In this study, a rapid machine learning-driven automated flow mixing setup with a high-throughput drop-casting system is introduced for thin film preparation, followed by fast characterization of proxy optical and target electrical properties that completes one cycle of learning with 160 unique samples in a single day, a > 10 ×  improvement relative to quantified, manual-controlled baseline. Regio-regular poly-3-hexylthiophene is combined with various types of carbon nanotubes, to identify the optimum composition and synthesis conditions to realize electrical conductivities as high as state-of-the-art 1000 S cm⁻¹. The results are subsequently verified and explained using offline high-fidelity experiments. Graph-based model selection strategies with classical regression that optimize among multi-fidelity noisy input-output measurements are introduced. These strategies present a robust machine-learning driven high-throughput experimental scheme that can be effectively applied to understand, optimize, and design new materials and composites.     

Cognitive Bidirectional Buffer-Aided DF Relay Networks: Protocol design and Power Allocation

In this paper, we consider bidirectional decode-and-forward buffer-aided relay selection and transmission power allocation schemes for underlay cognitive radio relay networks. First, a low complexity delay-constrained bidirectional relaying protocol is proposed. The proposed protocol maximizes the single-hop normalized sum of the primary network (PN) and secondary network (SN) rates and controls the maximum packet delay caused by physical layer buffering at relays. Second, optimal transmission power expressions that maximize the single-hop normalized sum rate are derived for each possible transmission mode. Simulation results are provided to evaluate the performance of the proposed relaying protocol and transmission power allocation scheme and compare their performance with that of the optimal scenario. Additionally, the impacts of several system parameters including maximum buffer size, interference threshold, maximum packet delay and number of relays on the network performance are also investigated. The results reveal that the proposed bidirectional relaying protocol and antenna transmission power allocation schemes introduce a satisfactory performance with much lower complexity compared to the optimal relay selection and power allocation schemes and provide an application dependent delay-controlling mechanism. It is also found that the network performance degrades as the delay constraint is more restricted until it matches the performance of conventional unbuffered relaying with delay constraints of three. Additionally, findings show that using buffer-aided relaying significantly enhances the SN performance while slightly weakens the performance of the PN.     

Population dynamics of Salmonella spp. and Shigella spp. in ready-to-eat Mediterranean vegetable salads

This study evaluated the behavior of Salmonella and Shigella (5–6 log CFU/g) in tomato–cucumber (TC) salad without additives (control), TC with 1.0% lemon juice and 0.5% salt, TC with 10% wt/wt tahini, coleslaw, and toum sauce at 4, 10, or 24°C for 5 days. At 4°C, both pathogens survived well in all salads, with a 0.2–1.6 log CFU/g reduction after 5 days (except for toum sauce with >3.5 log CFU/g reduction after 4 days). At 10°C, Salmonella in the different TC salads remained constant, whereas Shigella numbers significantly increased by 1.0–1.7 log CFU/g after 5 days. Yet, both pathogens significantly decreased by 1.2–1.4 log CFU/g in coleslaw after 5 days and by >3.5 log CFU/g in toum sauce after 3 days. At 24°C, Salmonella significantly increased in TC salad without additives by 1.4 log CFU/g after 5 days and were below the detection level in the other types of salad after 5 days. However, Shigella numbers significantly increased by 1.0 log CFU/g in TC with tahini, but they significantly declined by 1.9–2.9 log CFU/g in TC salads after 5 days, and the pathogen was not detected in coleslaw and toum sauce after 4 days.