Pitching a business idea to investors: How new venture founders use micro-level rhetoric to achieve narrative plausibility and resonance

For entrepreneurial narratives to be effective, they need to be judged as plausible and have to resonate with an audience. Prior research has, however, not examined or explained how entrepreneurs try to meet these criteria. In this paper, we addressed this question by analysing the micro-level arguments underpinning the pitch narratives of entrepreneurs who joined a business incubator. We discerned four previously unidentified rhetorical strategies that these entrepreneurs used to achieve narrative plausibility and resonance. Our findings further suggest that temporality and product development status may shape how entrepreneurs use these strategies. By outlining these aspects of entrepreneurial rhetoric, we contribute to opening up the black box of narrative resonance and plausibility and advance work on the role of rhetoric in entrepreneurship

The formation of organizational reputation

In this article, we review four decades of research on the formation of organizational reputation. Our review reveals six perspectives that have informed past studies: a game theoretic, a strategic, a macro-cognitive, a micro-cognitive, a cultural-sociological, and communicative one. We compare and contrast the different assumptions about what reputation is and how it forms that characterize these perspectives, and we discuss the implications of these differences for our theoretical understanding of stability and change, control and contestation, and the micro-macro relationship in the complex process of reputation formation

Differential gaze behavior towards sexually preferred and non-preferred human figures

The gaze pattern associated with image exploration is a sensitive index of our attention, motivation and preference. To examine whether an individual’s gaze behavior can reflect his/her sexual interest, we compared gaze patterns of young heterosexual men and women (M = 19.94 years, SD = 1.05) while viewing photos of plain-clothed male and female figures aged from birth to sixty years old. Our analysis revealed a clear gender difference in viewing sexually preferred figure images. Men displayed a distinctive gaze pattern only when viewing twenty-year-old female images, with more fixations and longer viewing time dedicated to the upper body and waist-hip region. Women also directed more attention at the upper body on female images in comparison to male images, but this difference was not age-specific. Analysis of local image salience revealed that observers’ eye-scanning strategies could not be accounted for by low-level processes, such as analyzing local image contrast and structure, but were associated with attractiveness judgments. The results suggest that the difference in cognitive processing of sexually preferred and non-preferred figures can be manifested in gaze patterns associated with figure viewing. Thus, eye-tracking holds promise as a potential sensitive measure for sexual preference, particularly in men

Deep Learning-Based Natural Language Processing in Radiology:The Impact of Report Complexity, Disease Prevalence, Dataset Size, and Algorithm Type on Model Performance

In radiology, natural language processing (NLP) allows the extraction of valuable information from radiology reports. It can be used for various downstream tasks such as quality improvement, epidemiological research, and monitoring guideline adherence. Class imbalance, variation in dataset size, variation in report complexity, and algorithm type all influence NLP performance but have not yet been systematically and interrelatedly evaluated. In this study, we investigate these factors on the performance of four types [a fully connected neural network (Dense), a long short-term memory recurrent neural network (LSTM), a convolutional neural network (CNN), and a Bidirectional Encoder Representations from Transformers (BERT)] of deep learning-based NLP. Two datasets consisting of radiologist-annotated reports of both trauma radiographs (n = 2469) and chest radiographs and computer tomography (CT) studies (n = 2255) were split into training sets (80%) and testing sets (20%). The training data was used as a source to train all four model types in 84 experiments (Fracture-data) and 45 experiments (Chest-data) with variation in size and prevalence. The performance was evaluated on sensitivity, specificity, positive predictive value, negative predictive value, area under the curve, and F score. After the NLP of radiology reports, all four model-architectures demonstrated high performance with metrics up to > 0.90. CNN, LSTM, and Dense were outperformed by the BERT algorithm because of its stable results despite variation in training size and prevalence. Awareness of variation in prevalence is warranted because it impacts sensitivity and specificity in opposite directions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10916-021-01761-4

Brightness and Darkness as Perceptual Dimensions

A common-sense assumption concerning visual perception states that brightness and darkness cannot coexist at a given spatial location. One corollary of this assumption is that achromatic colors, or perceived grey shades, are contained in a one-dimensional (1-D) space varying from bright to dark. The results of many previous psychophysical studies suggest, by contrast, that achromatic colors are represented as points in a color space composed of two or more perceptual dimensions. The nature of these perceptual dimensions, however, presently remains unclear. Here we provide direct evidence that brightness and darkness form the dimensions of a two-dimensional (2-D) achromatic color space. This color space may play a role in the representation of object surfaces viewed against natural backgrounds, which simultaneously induce both brightness and darkness signals. Our 2-D model generalizes to the chromatic dimensions of color perception, indicating that redness and greenness (blueness and yellowness) also form perceptual dimensions. Collectively, these findings suggest that human color space is composed of six dimensions, rather than the conventional three

Searching for unity: Real-world versus item-based visual search in age-related eye disease

When studying visual search, item-based approaches using synthetic targets and distractors limit the real-world applicability of results. Everyday visual search can be impaired in patients with common eye diseases like glaucoma and age-related macular degeneration. We highlight some results in the literature that suggest assessment of real-word search tasks in these patients could be clinically useful

Tip-surface forces, amplitude, and energy dissipation in amplitude-modulation (tapping mode) force microscopy

Amplitude-modulation (tapping mode) atomic force microscopy is a technique for high resolution imaging of a wide variety of surfaces in air and liquid environments. Here by using the virial theorem and energy conservation principles we have derived analytical relationships between the oscillation amplitude, phase shift, and average tip-surface forces. We find that the average value of the interaction force and oscillation and the average power dissipated by the tip-surface interaction are the quantities that control the amplitude reduction. The agreement obtained between analytical and numerical results supports the analytical method.This work has been supported by the Dirección General de Investigación Científica y Técnica (PB98-0471) and the European Union (BICEPS, BIO4-CT-2112). A. S. P. acknowledges financial support from the Comunidad Autónoma de Madrid.Peer reviewe

Electrically controlled long-distance spin transport through an antiferromagnetic insulator

Spintronics uses spins, the intrinsic angular momentum of electrons, as an alternative for the electron charge. Its long-term goal is in the development of beyond-Moore low dissipation technology devices. Recent progress demonstrated the long-distance transport of spin signals across ferromagnetic insulators. Antiferromagnetically ordered materials are however the most common class of magnetic materials with several crucial advantages over ferromagnetic systems. In contrast to the latter, antiferromagnets exhibit no net magnetic moment, which renders them stable and impervious to external fields. In addition, they can be operated at THz frequencies. While fundamentally their properties bode well for spin transport, previous indirect observations indicate that spin transmission through antiferromagnets is limited to short distances of a few nanometers. Here we demonstrate the long-distance, over tens of micrometers, propagation of spin currents through hematite (\alpha-Fe2O3), the most common antiferromagnetic iron oxide, exploiting the spin Hall effect for spin injection. We control the spin current flow by the interfacial spin-bias and by tuning the antiferromagnetic resonance frequency with an external magnetic field. This simple antiferromagnetic insulator is shown to convey spin information parallel to the compensated moment (N\'eel order) over distances exceeding tens of micrometers. This newly-discovered mechanism transports spin as efficiently as the net magnetic moments in the best-suited complex ferromagnets. Our results pave the way to ultra-fast, low-power antiferromagnet-insulator-based spin-logic devices that operate at room temperature and in the absence of magnetic fields

The influence of annealings on structure and microhardness of Fe-Mo-V-Nb-C steel processed by high-pressure torsion

The influence of high-pressure torsion on microstructure, microhardness and thermal stability of lowcarbon steel Fe-0,1Mo-0,6Mn-0,8Cr-0,2Ni-0,3Si-0,2Cu-0,1V-0,06Nb-0,09C, (wt.%) was investigated. It was shown that ultrafine-grained structure formed by high-pressure torsion possesses a high microhardness (H[mu]=7,0 GPa) and high thermal stability up to the temperature of 400°С