Near infra-red optical materials from polymeric amorphous carbon synthesised by collisional plasma process

The synthesis of polymer-like amorphous carbon (a-C:H) thin-films by microwave excited collisional hydrocarbon plasma process is reported. Stable and highly aromatic a-C:H were obtained containing significant inclusions of poly(p-phenylene vinylene) (PPV). PPV confers universal optoelectronic properties to the synthesised material. That is a-C:H with tailor-made refractive index are capable of becoming absorption-free in visible (red) - near infrared wavelength range. Production of large aromatic hydrocarbon including phenyl clusters and/or particles is attributed to enhanced coagulation of elemental plasma species under collisional plasma conditions. Detailed structural and morphological changes that occur in a-C:H during the plasma synthesis are also described.Comment: 12 pages, 4 figure

How people know their risk preference

People differ in their willingness to take risks. Recent work found that revealed preference tasks (e.g., laboratory lotteries)—a dominant class of measures—are outperformed by survey-based stated preferences, which are more stable and predict real-world risk taking across different domains. How can stated preferences, often criticised as inconsequential “cheap talk,” be more valid and predictive than controlled, incentivized lotteries? In our multimethod study, over 3,000 respondents from population samples answered a single widely used and predictive risk-preference question. Respondents then explained the reasoning behind their answer. They tended to recount diagnostic behaviours and experiences, focusing on voluntary, consequential acts and experiences from which they seemed to infer their risk preference. We found that third-party readers of respondents’ brief memories and explanations reached similar inferences about respondents’ preferences, indicating the intersubjective validity of this information. Our results help unpack the self perception behind stated risk preferences that permits people to draw upon their own understanding of what constitutes diagnostic behaviours and experiences, as revealed in high-stakes situations in the real world

Widely used, short 16S rRNA mitochondrial gene fragments yield poor and erratic results in phylogenetic estimation and species delimitation of amphibians.

BACKGROUND The 16S mitochondrial rRNA gene is the most widely sequenced molecular marker in amphibian systematic studies, making it comparable to the universal CO1 barcode that is more commonly used in other animal groups. However, studies employ different primer combinations that target different lengths/regions of the 16S gene ranging from complete gene sequences (~ 1500 bp) to short fragments (~ 500 bp), the latter of which is the most ubiquitously used. Sequences of different lengths are often concatenated, compared, and/or jointly analyzed to infer phylogenetic relationships, estimate genetic divergence (p-distances), and justify the recognition of new species (species delimitation), making the 16S gene region, by far, the most influential molecular marker in amphibian systematics. Despite their ubiquitous and multifarious use, no studies have ever been conducted to evaluate the congruence and performance among the different fragment lengths. RESULTS Using empirical data derived from both Sanger-based and genomic approaches, we show that full-length 16S sequences recover the most accurate phylogenetic relationships, highest branch support, lowest variation in genetic distances (pairwise p-distances), and best-scoring species delimitation partitions. In contrast, widely used short fragments produce inaccurate phylogenetic reconstructions, lower and more variable branch support, erratic genetic distances, and low-scoring species delimitation partitions, the numbers of which are vastly overestimated. The relatively poor performance of short 16S fragments is likely due to insufficient phylogenetic information content. CONCLUSIONS Taken together, our results demonstrate that short 16S fragments are unable to match the efficacy achieved by full-length sequences in terms of topological accuracy, heuristic branch support, genetic divergences, and species delimitation partitions, and thus, phylogenetic and taxonomic inferences that are predicated on short 16S fragments should be interpreted with caution. However, short 16S fragments can still be useful for species identification, rapid assessments, or definitively coupling complex life stages in natural history studies and faunal inventories. While the full 16S sequence performs best, it requires the use of several primer pairs that increases cost, time, and effort. As a compromise, our results demonstrate that practitioners should utilize medium-length primers in favor of the short-fragment primers because they have the potential to markedly improve phylogenetic inference and species delimitation without additional cost

A simple self-reflection intervention boosts the detection of targeted advertising

Abstract Online platforms’ data give advertisers the ability to “microtarget” recipients’ personal vulnerabilities by tailoring different messages for the same thing, such as a product or political candidate. One possible response is to raise awareness for and resilience against such manipulative strategies through psychological inoculation. Two online experiments (total $$N= 828$$ N = 828 ) demonstrated that a short, simple intervention prompting participants to reflect on an attribute of their own personality—by completing a short personality questionnaire—boosted their ability to accurately identify ads that were targeted at them by up to 26 percentage points. Accuracy increased even without personalized feedback, but merely providing a description of the targeted personality dimension did not improve accuracy. We argue that such a “boosting approach,” which here aims to improve people’s competence to detect manipulative strategies themselves, should be part of a policy mix aiming to increase platforms’ transparency and user autonomy

The role of information search and its influence on risk preferences

According to the ‘Description–Experience gap’ (DE gap), when people are provided with the descriptions of risky prospects they make choices as if they overweight the probability of rare events; but when making decisions from experience after exploring the prospects’ properties, they behave as if they underweight such probability. This study revisits this discrepancy while focusing on information-search in decisions from experience. We report findings from a lab-experiment with three treatments: a standard version of decisions from description and two versions of decisions from experience: with and without a ‘history table’ recording previously sampled events. We find that people sample more from lotteries with rarer events. The history table proved influential; in its absence search is more responsive to cues such as a lottery’s variance while in its presence the cue that stands out is the table’s maximum capacity. Our analysis of risky choices captures a significant DE gap which is mitigated by the presence of the history table. We elicit probability weighting functions at the individual level and report that subjects overweight rare events in experience but less so than in description. Finally, we report a measure that allows us to compare the type of DE gap found in studies using choice patterns with that inferred through valuation and find that the phenomenon is similar but not identical across the two methods

Psychological Factors Shaping Public Responses to COVID-19 Digital Contact Tracing Technologies in Germany

The COVID-19 pandemic has seen one of the first large-scale uses of digital contact tracing to track a chain of infection and contain the spread of a virus. The new technology has posed challenges both for governments aiming at high and effective uptake and for citizens weighing its benefits (e.g., protecting others’ health) against the potential risks (e.g., loss of data privacy). Our cross-sectional survey with repeated measures across four samples in Germany ([Formula: see text] ) focused on psychological factors contributing to the public adoption of digital contact tracing. We found that public acceptance of privacy-encroaching measures (e.g., granting the government emergency access to people’s medical records or location tracking data) decreased over the course of the pandemic. Intentions to use contact tracing apps—hypothetical ones or the Corona-Warn-App launched in Germany in June 2020—were high. Users and non-users of the Corona-Warn-App differed in their assessment of its risks and benefits, in their knowledge of the underlying technology, and in their reasons to download or not to download the app. Trust in the app’s perceived security and belief in its effectiveness emerged as psychological factors playing a key role in its adoption. We incorporate our findings into a behavioral framework for digital contact tracing and provide policy recommendations

How to detect high-performing individuals and groups: Decision similarity predicts accuracy

Distinguishing between high- and low-performing individuals and groups is of prime importance in a wide range of high-stakes contexts. While this is straightforward when accurate records of past performance exist, these records are unavailable in most real-world contexts. Focusing on the class of binary decision problems, we use a combined theoretical and empirical approach to develop and test a approach to this important problem. First, we use a general mathematical argument and numerical simulations to show that the similarity of an individual's decisions to others is a powerful predictor of that individual's decision accuracy. Second, testing this prediction with several large datasets on breast and skin cancer diagnostics, geopolitical forecasting, and a general knowledge task, we find that decision similarity robustly permits the identification of high-performing individuals and groups. Our findings offer a simple, yet broadly applicable, heuristic for improving real-world decision-making systems

Self-reported practices and emotions in prescribing opioids for chronic, noncancer pain: A cross-sectional study of German physicians

Background: The pressure on physicians when a patient seeks pain relief and their own desire to be self-effective may lead to the prescription of strong opioids for chronic noncancer pain (CNCP). This study, via physician self-reporting, aims to identify and measure (i) physician adherence to national opioid prescribing guidelines and (ii) physician emotions when a patient seeks a dosage increase of the opioid. Methods: Within a cross-sectional survey—conducted as part of a randomized controlled online intervention trial (ERONA)—600 German physicians were queried on their opioid prescribing behavior (choice and formulation of opioid, indications) for CNCP patients and their emotions to a case vignette describing a patient seeking an opioid dosage increase without signs of objective deterioration. Results: The prescription of strong opioids in this study was not always in accordance with current guidelines. When presented with a scenario in which a patient sought to have their opioid dose increased, some physicians reported negative feelings, such as either pressure (25%), helplessness (25%), anger (23%) or a combination. The risk of non-guideline-compliant prescribing behavior using the example of ultrafast-acting fentanyl for CNCP was increased when negative emotions were present (OR: 1.7; 95%-CI: 1.2–2.6; p = 0.007) or when sublingual buprenorphine was prescribed (OR: 15.4; 95%-CI: 10.1–23.3; p < 0.001). Conclusions: Physicians’ emotional self-awareness represents the first step to identify such direct reactions to patient requests and to ensure a responsible, guideline-based opioid prescription approach for the long-term well-being of the patient

Assessing Optical and Electrical Properties of Highly Active IrO_x Catalysts for the Electrochemical Oxygen Evolution Reaction via Spectroscopic Ellipsometry

Efficient water electrolysis requires highly active electrodes. The activity of corresponding catalytic coatings strongly depends on material properties such as film thickness, crystallinity, electrical conductivity, and chemical surface speciation. Measuring these properties with high accuracy in vacuum-free and non-destructive methods facilitates the elucidation of structure–activity relationships in realistic environments. Here, we report a novel approach to analyze the optical and electrical properties of highly active oxygen evolution reaction (OER) catalysts via spectroscopic ellipsometry (SE). Using a series of differently calcined, mesoporous, templated iridium oxide films as an example, we assess the film thickness, porosity, electrical resistivity, electron concentration, electron mobility, and interband and intraband transition energies by modeling of the optical spectra. Independently performed analyses using scanning electron microscopy, energy-dispersive X-ray spectroscopy, ellipsometric porosimetry, X-ray reflectometry, and absorption spectroscopy indicate a high accuracy of the deduced material properties. A comparison of the derived analytical data from SE, resonant photoemission spectroscopy, X-ray absorption spectroscopy, and X-ray photoelectron spectroscopy with activity measurements of the OER suggests that the intrinsic activity of iridium oxides scales with a shift of the Ir 5d t2g sub-level and an increase of p–d interband transition energies caused by a transition of μ1-OH to μ3-O species