Personality and Risk-Perception Profiles with Regard to Subjective Wellbeing and Company Management: Corporate Managers during the Covid-19 Pandemic.

This study examined the role of the Big Five personality traits and risk perception profiles among a sample of corporate managers concerning their subjective wellbeing (SWB) and corporate management practices during the Covid-19 pandemic. Two hundred and fifty-five chief executive officers (CEOs) and chief financial officers (CFOs) of companies listed on the main market of the Warsaw Stock Exchange (WSE) in Poland participated in the study by completing the Satisfaction with Life Scale, Positive and Negative Affect Scale, Ten-Item Personality Inventory, Stimulation-Instrumental Risk Inventory, and a business survey on the Covid-19 pandemic's impact on company management. Latent profile analysis revealed the existence of diverse profiles among the participants regarding personality traits and risk perception, which were variously related to their SWB and managerial practices during the pandemic. It seems that individual differences in personality traits and risk perception not only matter for the individual life satisfaction of managers but may also translate into effective company management in times of crisis. The results of our study may be an adjunct to understanding underlying sources of managerial biases in corporate management as well as to developing more effective methods of psychological counseling of corporate managers, a topic that remains still a highly understudied research area.

Differential pulse voltammetry and chronoamperometry as analytical tools for epinephrine detection using a tyrosinase-based electrochemical biosensor.

The main goal of the presented study was to design a biosensor-based system for epinephrine (EP) detection using a poly-thiophene derivative and tyrosinase as a biorecognition element. We compared two different electroanalytical techniques to select the most prominent technique for analyzing the neurotransmitter. The prepared biosensor system exhibited good parameters; the differential pulse (DPV) technique presented a wide linear range (1-20 µM and 30-200 µM), with a low detection limit (0.18 nM and 1.03 nM). In the case of chronoamperometry (CA), a high signal-to-noise ratio and lower reproducibility were observed, causing a less broad linear range (10-200 µM) and a higher detection limit (125 nM). Therefore, the DPV technique was used for the calculation of sensitivity (0.0011 µA mM-1 cm-2), stability (49 days), and total surface coverage (4.18 × 10-12 mol cm-2). The biosensor also showed very high selectivity in the presence of common interfering species (i.e. ascorbic acid, uric acid, norepinephrine, dopamine) and was successfully applied for EP determination in a pharmaceutical sample.

Managerial overconfidence in capital structure decisions and its link to aggregate demand: An agent-based model perspective.

OBJECTIVE: This study aims to connect two strands of the psychology and economics literature, i.e., behavioural finance and agent-based macroeconomics, to assess the impact of managerial overconfidence at the micro and macro levels of the economy as a whole. METHOD: We build a macroeconomic stock-flow consistent agent-based model that is calibrated for the specific case of Poland to explore whether the overconfidence of top corporate managers in the context of their initial capital structure decisions is detrimental for the firms being managed in this way, the financial market dynamics, and the selected macroeconomic indicators. We model heterogeneous firms with different capital structure decision criteria depending on their degree of managerial overconfidence. Our model also includes a complete macroeconomic closure with aggregated households, capital producers, banking, and a public sector. RESULTS: We find that firms with overconfident managers outperform in terms of investment and size but are also more fragile, thereby making them more likely to default. Finally, we run policy shocks and show that while investors' flight to liquidity creates financial turmoil and increases the probability of default. CONCLUSIONS: This paper contributes to the knowledge base by linking behavioural corporate finance and agent-based macroeconomics. In general, the excess overconfidence on the micro level, either an increase in the proportion of overconfident firms or a higher degree of overconfidence among managers, has a strong destabilizing impact on the economy as a whole on the macro level.

Enzymatic Platforms for Sensitive Neurotransmitter Detection.

A convenient electrochemical sensing pathway was investigated for neurotransmitter detection based on newly synthesized silole derivatives and laccase/horseradish-peroxidase-modified platinum (Pt)/gold (Au) electrodes. The miniature neurotransmitter's biosensors were designed and constructed via the immobilization of laccase in an electroactive layer of the Pt electrode coated with poly(2,6-bis(3,4-ethylenedioxythiophene)-4-methyl-4-octyl-dithienosilole) and laccase for serotonin (5-HT) detection, and a Au electrode modified with the electroconducting polymer poly(2,6-bis(selenophen-2-yl)-4-methyl-4-octyl-dithienosilole), along with horseradish peroxidase (HRP), for dopamine (DA) monitoring. These sensing arrangements utilized the catalytic oxidation of neurotransmitters to reactive quinone derivatives (the oxidation process was provided in the enzymes' presence). Under the optimized conditions, the analytical performance demonstrated a convenient degree of sensitivity: 0.0369 and 0.0256 µA mM-1 cm-2, selectivity in a broad linear range (0.1-200) × 10-6 M) with detection limits of ≈48 and ≈73 nM (for the serotonin and dopamine biosensors, respectively). Moreover, the method was successfully applied for neurotransmitter determination in the presence of interfering compounds (ascorbic acid, L-cysteine, and uric acid).

Surface topography analysis with application of roughness area dependence method.

At the moment the root mean square roughness (Rq) is the most commonly used parameter for quantitative description of surface properties. However, this parameter has one main disadvantage: for its calculation only height variations of surface profile are used which are then represented by a single number. To eliminate this restriction authors of the paper have developed a surface analysis method which is based on roughness calculation in the function of gradually increasing dimensions of a sampling area. By setting proper measurement parameters and further data processing, from Rq dependence on sampling area plot size there is a possibility to obtain more useful, additional information about specific surface properties than using the single roughness value. Roughness area dependence plots, obtained from AFM images, were analyzed to study the influence of different growth parameters on surface properties of GaN layers and AlGaN/GaN heterostructures grown on sapphire and silicon substrates by Metal Organic Chemical Vapor Deposition (MOVPE) epitaxy. Although the method was used to characterize the semiconductor material in micrometer range, it can be applied also for any topography imaging technique in wide scale ranges.