Invalid Assumptions Research Articles

A Food for All Seasons: Stability of Food Preferences in Gorillas across Testing Methods and Seasons.

Simple SummaryWe assessed food preferences in three adult male zoo-housed gorillas over a period of 20 months. We used paired-choice tasks on a computer touchscreen and we also presented food pairings by hand using PVC tubes and compared the stability of preferences across methods and seasons. In addition, we assessed whether preferences were stable across offerings within a session. To further validate the use of images on touchscreens to assess food preferences, we showed that these gorillas chose images of highly preferred food items when these images were paired with images of their less preferred foods. These tests can help us understand the stability of animals’ preferences and whether preferences are dependent on the larger test context.Decisions about which foods to use during training and enrichment for captive animals may be based on invalid assumptions about individuals’ preferences. It is important to assess the stability of food preferences given that one-time preferences are often used to inform which items are offered over a longer period of time. Presenting preference assessments using images of food items allows control over factors such as size, scent, and inadvertent cueing but requires validation. We presented three male gorillas with choices between randomly selected pairs of actual food items from their morning meal using PVC feeders. We also presented the gorillas with two-alternative forced-choice tests between images of these foods on a touchscreen computer. Ranked preferences were correlated across method and seasons. Furthermore, gorillas selected images of preferred over less preferred foods in a validation task on the touchscreen. However, selections of some food items changed within sessions, suggesting that preference may be relative to other contextual factors. Researchers should assess how choices affect subsequent preferences to understand whether animals demonstrate absolute preferences for particular food items, or prefer variety.

An EEG Classification-Based Method for Single-Trial N170 Latency Detection and Estimation.

Event-related potentials (ERPs) can reflect the high-level thinking activities of the brain. In ERP analysis, the superposition and averaging method is often used to estimate ERPs. However, the single-trial ERP estimation can provide researchers with more information on cognitive activities. In recent years, more and more researchers try to find an effective method to extract single-trial ERPs, because most of the existing methods have poor generalization ability or suffer from strong assumptions about the characteristics of ERPs, resulting in unsatisfactory results under the condition of a very low signal-to-noise ratio. In this paper, an EEG classification-based method for single-trial ERP detection and estimation was proposed. This study used a linear generated EEG model containing templates of ERP local descriptors which include amplitude and latency, and this model can avoid the invalid assumption about ERPs taken by other methods. The purpose of this method is not to recover the whole ERP waveform but to model the amplitude and latency of ERP components. This method afterwards examined the three machine learning models including logistic regression, neural network, and support vector machine in the EEG signal classification for ERP detection and selected the best performed MLPNN model for detection. To get the utmost out of information produced in the classification process, this study also used extra information to propose a new optimization model, with which outperformed detection results were obtained. Performance of the proposed method is evaluated on simulated N170 and real P50 data sets, and the results show that the model is more effective than the Woody filter and the SingleTrialEM algorithm. These results are also consistent with the conclusion of sensory gating, which demonstrated good generalization ability.

Screw-controlled strength of BCC non-dilute and high-entropy alloys

The impressive mechanical properties of single phase BCC High Entropy Alloys (HEAs) has renewed interest in understanding the mechanisms controlling strength in BCC alloys. Theory and simulation of strengthening of screw dislocations in HEAs shows that screw dislocations become spontaneously kinked along their length to lower the total energy due to solute/screw interactions. Dislocation motion then mainly occurs via two mechanisms, lateral kink migration and breaking of cross-kinks due to kink formation on different glide planes. Existing kink migration models, in spite of successes in capturing some experiments, are based on several invalid assumptions. Here, a new theory for the kink migration in HEAs is developed based on recent understanding in dilute alloys, leading to a fully derived analytical model for the kink migration energy barrier as a function of applied stress and kink spacing. Results emerge to be quantitatively close to those presented in recent theory by Maresca and Curtin but are on much firmer theoretical basis. A revised version of the Maresca-Curtin screw strengthening theory that incorporates the new kink migration model is compared to experiments on non-dilute Fe-Si, Nb-Mo, and Nb-W alloys and shows broad agreement as a function of temperature and composition, establishing the quantitative accuracy of the new theory.

Information-theoretic approach in allometric scaling relations of DNA and proteins.

Allometric scaling relations can be observed in between molecular parameters. Hence, we looked for presence of such relation among sizes (i.e., lengths) of proteins and genes. Protein lengths exist in the literature as the number of amino acids. They can also be derived from the mRNA lengths. Here, we looked for allometric scaling relation by using such data and simultaneously, the data was compared with the sizes of genes and proteins that were obtained from our modified information-theoretic approach. Results implied presence of scaling relation in the calculated results. This was expected due to the implemented modification in the information-theoretic calculation. Relation in the literature-based data was lacking high goodness of fit value. It could be due to physical factors and selective pressures, which ended up in deviations of the literature-sourced values from those in the model. Genome size is correlated with cell size. Intracellular volume, which is related to the DNA size, would require certain number of proteins, the sizes of which can therefore be correlated with the protein sizes. Cell sizes, genome sizes, and average protein and gene sizes, along with the number of proteins, namely the expression levels of the genes, are the physical factors, and the molecular factors influence those physical factors. The selective pressures on those can act through the connection between those physical factors and limit the dynamic ranges. Biological measures could be prone to such forces and are likely to deviate from expected models, regardless of the validity of assumptions, unless those are also implemented in the models. Yet, present discrepancies could be pointing at the need for model improvement, data imperfection, invalid assumptions, etc. Still, current work highlights possible use of information-theoretic approach in allometric scaling relations' studies.

Issues in clustering algorithm consistency in fixed dimensional spaces. Some solutions for k-means

Kleinberg introduced an axiomatic system for clustering functions. Out of three axioms, he proposed, two (scale invariance and consistency) are concerned with data transformations that should produce the same clustering under the same clustering function. The so-called consistency axiom provides the broadest range of transformations of the data set. Kleinberg claims that one of the most popular clustering algorithms, k-means does not have the property of consistency. We challenge this claim by pointing at invalid assumptions of his proof (infinite dimensionality) and show that in one dimension in Euclidean space the k-means algorithm has the consistency property. We also prove that in higher dimensional space, k-means is, in fact, inconsistent. This result is of practical importance when choosing testbeds for implementation of clustering algorithms while it tells under which circumstances clustering after consistency transformation shall return the same clusters. Two types of remedy are proposed: gravitational consistency property and dataset consistency property which both hold for k-means and hence are suitable when developing the mentioned testbeds.

Conditional copula models for correlated survival endpoints: Individual patient data meta-analysis of randomized controlled trials.

Correlations among survival endpoints are important for exploring surrogate endpoints of the true endpoint. With a valid surrogate endpoint tightly correlated with the true endpoint, the efficacy of a new drug/treatment can be measurable on it. However, the existing methods for measuring correlation between two endpoints impose an invalid assumption: correlation structure is constant across different treatment arms. In this article, we reconsider the definition of Kendall's concordance measure (tau) in the context of individual patient data meta-analyses of randomized controlled trials. According to our new definition of Kendall's tau, its value depends on the treatment arms. We then suggest extending the existing copula (and frailty) models so that their Kendall's tau can vary across treatment arms. Our newly proposed model, a joint frailty-conditional copula model, is the implementation of the new definition of Kendall's tau in meta-analyses. In order to facilitate our approach, we develop an original R function condCox.reg(.) and make it available in the R package joint.Cox (https://CRAN.R-project.org/package=joint.Cox). We apply the proposed method to a gastric cancer dataset (3288 patients in 14 randomized trials from the GASTRIC group). This data analysis concludes that Kendall's tau has different values between the surgical treatment arm and the adjuvant chemotherapy arm (p-value<0.001), whereas disease-free survival remains a valid surrogate at individual level for overall survival in these trials.

Comment on “Separability of completely symmetric states in a multipartite system”

In their interesting paper [Phys. Rev. A 99, 032312 (2019)], Chen et al. consider the completely symmetric (CS) states, which are invariant under any index permutation. They proved that the CS states are separable if and only if they are a convex combination of real symmetric pure product states in Theorem 14, and claimed that any CS state in a two-qutrit system is separable in Theorem 20. We point out that their proof of Theorem 20 is flawed because of invalid assumptions. Furthermore, we present a sufficient and necessary condition for the separability of the CS states in two-qutrit systems.

Errors Related to General Relativity, Repulsive Gravitation and the Question of Black Holes

Galileo and Newton considered gravity to be independent of temperature, while Einstein claimed that the weight of metal will increase as temperature increases. Further, Maxwell maintained that charge is unrelated to gravity. Experiments show, however, that the weight of a metal piece is reduced as its temperature increases. Thus, charge-initiated repulsive gravitation exists. In fact, repulsive gravity has been demonstrated by the use of a charged capacitor hovering over Earth. Further, it is expected that a piece of heated metal would fall more slowly than a feather in a vacuum. Einstein developed an invalid notion of gravitational mass, and failed to establish the unification of gravitation and electromagnetism since he overlooked repulsive gravitation. Moreover, photons are a combination of the gravitational wave and the electromagnetic wave. For electromagnetic energy is invalid, and is in conflict with the Einstein equation. The non-linear Einstein equation has no bounded dynamic solution, Space-time singularity theorems are based on an invalid implicit assumption that all the couplings have a unique sign. Since gravity is no longer always attractive, the existence of black holes is questionable. The fact that Penrose was awarded the 2020 Nobel Prize in Physics for the derivation of black holes is due to that the Nobel Prize Committee for Physics did not sufficiently understand the physics of general relativity. A distinct characteristic of Penrose's work, as usual, is that it is not verifiable.

Psychotropic Polypharmacy in the US Pediatric Population: A Methodologic Critique and Commentary.

Background: Psychotropic concomitant medication use for the treatment of youth with emotional and behavioral disorders has grown significantly in the U.S. over the past 25 years. The use of pharmacy claims to analyze these trends requires the following: age of the selected population, overlapping days of use, and precision of the outcome itself. This review will also address the gaps in reporting of pediatric psychotropic polypharmacy.Methods: An electronic literature search was undertaken for the period 2000 through 2020 using keywords such as “pediatric,” “concomitant,” “polypharmacy,” “multiple medications,” and “concurrent psychotropic”; Relevant references in textbooks were also used. Only English language and U.S. studies were included, resulting in 35 inter-class studies.Results: Studies were organized into seven groups according to data sources and clinical topics: (1) population surveys; (2a) multi-state publicly insured populations; (2b) single/two state studies; (3) privately insured populations; (4) diagnosed populations; (5) foster care populations; (6) special settings. Across 20 years it is apparent that pediatric psychotropic polypharmacy affects substantially more children and adolescents today than had been the case. As many as 300,000 youth now receive 3 or more classes concomitantly. The duration of concomitant use is relatively long, e.g., 69–89% of annual medicated days. Finally, more adverse event reports were associated with 3-class compared with 2-class drug regimens.Discussion: Factors that contribute to the growth of pediatric psychotropic polypharmacy include: (1) predominance of the biological model in psychiatric practice; (2) invalid assumptions on efficacy of combinations, (3) limited professional awareness of metabolic and neurological adverse drug events, and (4) infrequent use of appropriate deprescribing.Conclusion: A review of publications documenting U.S. pediatric psychotropic polypharmacy written over the last 20 years supports the need to standardize the methodologies used. The design of population-based studies should maximize information on the number of youth receiving regimens of 3-, 4-, and 5 or more concomitant classes and the duration of such use. Next, far more post-marketing research is needed to address the effectiveness, safety and tolerability of complex drug regimens prescribed for youngsters.

Digital Transformation of Industrial Organizations: Toward an Integrated Framework

ABSTRACT Industrial organizations are responding to new risks and opportunities originating from exponentially growing and disruptive digital technologies, by taking company-wide digital transformation initiatives. However, the key enablers of such digital transformation initiatives that facilitate operational performance outcomes in industrial organizations demand further investigation. Therefore, drawing on the sociotechnical system theory (STS), the objective of this study is to explore the digital transformation enablers and their impact on performance outcomes. Research data was collected from four leading industrial organizations that engaged in digital transformation programmes. Our results indicate that leadership, structures, and culture are the key enablers of digital transformation that help industrial organizations to achieve performance outcomes (i.e. collaboration, customer-centricity, and agility). By providing an empirically grounded integrated framework with future research propositions, this study contributes to the existing literature on digital transformation and sociotechnical system theory. MAD statement This article aims to make a difference by exploring industrial digital transformation in order to identify the key enablers and performance outcomes. We highlight the need for alignment and joint optimization of social and technical systems to effectively capitalize on the digital transformation initiatives. Moreover, we call for urgent attention to the development of leaders, as well as the further identification of supportive digital transformation leadership competencies. Competent leaders assume a central role in correcting outdated and invalid assumptions, conceptualizing new ideas, and reinforcing cultural values. Furthermore, we elaborate the necessity of cultural transformation in industrial organizations for impactful digital transformation. Lastly, our findings confirm the significance of organizational structure in digital transformation and simultaneously warn that too little is happening.

Finite element model updating of composite with adhesive jointed structure under built-up internal stress

Highly complex engineering structures such as the body-in-white of a car consist of hundreds of different parts that are assembled using various types of joints such as welded and adhesive joints. The finite element method has been used extensively in various engineering fields to predict and analyze the dynamic behavior of assembled structures. However, despite the use of well-characterized individual subcomponent models, the predicted results frequently differ from measured results. This is believed to be because of the invalid assumptions of the joint model such as the material properties and other uncertainties associated with the assembly. This study investigated the use of a model updating method (MSC Nastran SOL 200) to identify the invalid assumptions and uncertainties in adhesive jointed composite structures and to minimize the difference between predicted and measured results. Results revealed that the stresses built-up in a structure during the assembly process are permanently retained in the structure after the adhesive is completely cured and that they cause a local stress stiffening effect, which is believed to affect the resonance frequencies of the structure. Introducing the effect of the stresses as an updating parameter in the model updating process increases the prediction accuracy.

Membrane permeability of small molecules from unbiased molecular dynamics simulations.

Permeation of many small molecules through lipid bilayers can be directly observed in molecular dynamics simulations on the nano- and microsecond timescale. While unbiased simulations provide an unobstructed view of the permeation process, their feasibility for computing permeability coefficients depends on various factors that differ for each permeant. The present work studies three small molecules for which unbiased simulations of permeation are feasible within less than a microsecond, one hydrophobic (oxygen), one hydrophilic (water), and one amphiphilic (ethanol). Permeabilities are computed using two approaches: counting methods and a maximum-likelihood estimation for the inhomogeneous solubility diffusion (ISD) model. Counting methods yield nearly model-free estimates of the permeability for all three permeants. While the ISD-based approach is reasonable for oxygen, it lacks precision for water due to insufficient sampling and results in misleading estimates for ethanol due to invalid model assumptions. It is also demonstrated that simulations using a Langevin thermostat with collision frequencies of 1/ps and 5/ps yield oxygen permeabilities and diffusion constants that are lower than those using Nosé-Hoover by statistically significant margins. In contrast, permeabilities from trajectories generated with Nosé-Hoover and the microcanonical ensemble do not show statistically significant differences. As molecular simulations become more affordable and accurate, calculation of permeability for an expanding range of molecules will be feasible using unbiased simulations. The present work summarizes theoretical underpinnings, identifies pitfalls, and develops best practices for such simulations.

On the interference from agar in chemical exchange saturation transfer MRI parameter optimization in model solutions.

Chemical exchange saturation transfer (CEST) MRI is currently set to become part of clinical routine as it enables indirect detection of low concentrated molecules and proteins. Recently, intermediate to fast exchanging functional groups of glucose and its derivatives, glutamate and dextran, have gained attention as promising CEST contrast agents. To increase the specificity of CEST MRI for certain functional groups, the presaturation module is commonly optimized. At an early stage, this is performed in well-defined model solutions, in which, for instance, the relaxation times are adjusted to mimic in vivo conditions. This often involves agar, assuming the substance would not yield significant CEST effects by itself, which the current study proves to be an invalid assumption. Model solutions at different pH values and concentrations of agar were investigated at different temperatures at a 9.4 T human whole body MR scanner. High power presaturation of around 4 μT, optimal for investigating intermediate to fast exchanging groups, was applied. Postprocessing included spatiotemporal corrections for B0 and spatial corrections for B1+ . CEST effects of up to 3 % of the bulk water signal were observed. From pH, concentration and temperature dependency, it was concluded that the observed behavior reflects a CEST effect of agar. It was also shown how to remove this undesirable contribution from CEST MRI data. It was concluded that if agar is involved in the CEST MRI parameter optimization process, its contribution to the observed effects has to be taken into account. CEST agent concentration must be sufficiently high to be able to neglect the contribution of agar, or a control sample at matched pH is necessary for correction. Experiments on pure agarose showed reduced CEST effects compared with agar but did not provide a neutral baseline either.

Heterogenous Trip Distance-Based Route Choice Behavior Analysis Using Real-World Large-Scale Taxi Trajectory Data

Most early research on route choice behavior analysis relied on the data collected from the stated preference survey or through small-scale experiments. This manuscript focused on the understanding of commuters’ route choice behavior based on the massive amount of trajectory data collected from occupied taxicabs. The underlying assumption was that travel behavior of occupied taxi drivers can be considered as no different than the well-experienced commuters. To this end, the DBSCAN algorithm and Akaike information criterion (AIC) were first used to classify trips into different categories based on the trip length. Next, a total of 9 explanatory variables were defined to describe the route choice behavior, and and the path size (PS) logit model was then built, which avoided the invalid assumption of independence of irrelevant alternatives (IIA) in the commonly seen multinomial logit (MNL) model. The taxi trajectory data from over 11,000 taxicabs in Xi’an, China, with 40 million trajectory records each day were used in the case study. The results confirmed that commuters’ route choice behavior are heterogenous for trips with varying distances and that considering such heterogeneity in the modeling process would better explain commuters’ route choice behaviors, when compared with the traditional MNL model.

369-OR: [1,2-13C2]-L-Glutamine Mass Isotopomers Map Hepatic Mitochondrial Metabolism without Tracer Interference

Background: Tracers should be maximally descriptive with minimal interference to the metabolic system of interest. Divergent concepts of in vivo hepatic metabolism (e.g., anaplerosis) may have emerged, in part, from invalid assumptions and/or perturbations associated with common tracers. Aim: We evaluated three common substrate tracers for intrahepatic metabolism vis-à-vis a novel independent [1,2-13C2]-L-glutamine strategy. Methods: Overnight fasted Sprague-Dawley rats underwent primed, continuous infusions of reported tracer rates for lactate, propionate, acetate or glutamine. Plasma/freeze-clamped livers were obtained at 0, 5, 15, 30, 60, and 120 min. Plasma/tissue isotopomers were subject to steady state and kinetic Mass Isotopomer MultiOrdinate Spectral Analysis (MIMOSA) and reported relative to citrate synthase (CS). Results: In contrast to glutamine infusion, plasma insulin ([i]) glucose concentration ([g]), and/or plasma glucose turnover (Ra) were increased by acetate ([i] = 1.5 fold, p = 0.015; [g] = 129 mg/dl, p=0.021), lactate ([i]= 2.03 fold, p = 0.0001; [g] = 156mg/dl, p = 0.0001, Ra = 7.2 mg/kg/min, p=0.006), and propionate ([i]= 1.7 fold, p = 0.0013; [g] = 165 mg/dl, p = 0.0001, Ra = 7.8 mg/kg/min, p = 0.0017). [1,2-13C2]-L-glutamine quickly reached isotopic equilibrium without impacting mitochondrial metabolite concentration or glutamate anaplerosis. Transaminase exchange (Vx) was &amp;gt;&amp;gt;CS. PEPCK was 1.6 x CS with pyruvate only accounting for 76% of anaplerosis (remainder from propionate and glutamate anaplerosis). PK was less than CS while ATP citrate lyase (ACLy) was 18% of CS. Conclusion: Direct in vivo measurements of pyruvate cycling rates were low relative to CS while ACLy, IDH exchange, and non-pyruvate anaplerosis contributed substantially to hepatic metabolism. [1,2-13C2]-L-glutamine MIMOSA delivered an unencumbered, direct assessment of hepatic mitochondrial metabolism. Disclosure S. Siebel: None. R.L. Cardone: None. A. Abulizi: None. R. Raaisa: None. R.M. Williams: None. R. Sehgal: None. G. Butrico: None. G. Cline: None. D.L. Rothman: None. G.F. Mason: None. R. Kibbey: None. Funding National Institutes of Health (2K12DK094714-06, R01DK108283)

Improving finite element modelling of the dynamic behaviour of a car trunk lid with modal based updating method

Predicted results of a finite element model used to develop physical test structures are often found to be not in a good agreement with the experimental results due to the invalid assumptions made in the finite element modelling. This study will focus on improving the correlation level between the finite element model and experimental model of a car trunk lid with the presence of resistance spot welded joints using modal based updating method. The natural frequencies and mode shapes computed from the updated finite element model of the car trunk lid are compared with the corresponding experimental results. HyperWorks and Leuven Measurement System (LMS) test are used for the modelling and modal testing. MSC Nastran SOL200 is used to identify potential updating parameters and to improve the initial finite element model in the light of corresponding experimental results which are obtained from modal testing. The comparison of the results showed that the total error of 58.59 per cent predicted from the initial finite element model of the trunk lid has been successfully reduced to 3.62 per cent. In conclusion, modal based updating has been successfully used to improve the correlation level between the initial finite element model and the physical model of the trunk lid.

Response of microbial community and net nitrogen turnover to modify climate change in Alpine meadow

In order to investigate the effect of climate change on the functional role of microbial community, we studied links between microbial community structure and the net ammonification and nitrification rates in a space for time climate change experiment. Abundance of bacteria and fungi as well as the induced climate change effects varied with seasons. The highest PLFA concentrations were found in frozen soils of the climate change treatment in which organic carbon (C) and nitrogen (N) substrates accumulated. It indicated that frozen soil can be the hot moment for soil microbial community. We found that climate change significantly increased total PLFA concentrations while decrease F:B ratio in July. It suggested that climate change could increase growth of bacteria more than that of fungi, and thus changed the soil microbial community structure. On the other hand, net N turnover itself was largely negative (i.e. illustrating net immobilization and the high N retention capacity). Since the ability of net rates of N turnover to predict plant N availability is relying on the (invalid) assumption that plants poorly compete for mineral N against soil microbes, this might be related to the strong plant-soil-microbe carbon-nitrogen interactions in the investigated soil, and unfortunately climate change would enhance the interaction. Therefore, net N mineralization has its limitation to deeply study the microbial N turnover in N biogeochemistry cycles.

Evaluation of drift-velocity closure relationships for highly viscous liquid-air slug flow in horizontal pipes through 3D CFD modelling

In the past 50 years, several correlations have been developed in order to predict the drift velocity of a liquid-air slug-flow system inside horizontal pipelines. However, a great portion of these correlations is based on either very limited experimental data in terms of fluid properties and operating conditions or on often invalid assumptions. Considering this, the present study assesses the accuracy and validity of seven of the most common non-complex drift velocity correlations through the development of a 3D-Computational Fluid Dynamics (CFD) model using the commercial software Star-CCM+. For this assessment, 13 experimental measurements from the literature were used to validate the CFD model, and 11 case-studies were proposed in order to expand the range of analysis to high-viscosity fluids (μ > 0.3 Pa·s) often found in industrial settings. The two-phase system was modelled with an Eulerian-Eulerian approach, coupled with the Volume of Fluid (VOF) method. Three VOF parameters were calibrated in order to obtain the best configurations for different viscosity ranges. The results indicated that the CFD model offers an excellent prediction of the drift velocity given than the average absolute relative error obtained was 6%, even considering highly viscous fluids (μ ~ 6.86 Pa·s). The model allowed to confirm that the slug units and gas bubbles do not behave symmetrically in the axial direction and therefore, a 3-D approach substantially improves the accuracy of the model when compared with some 2-D models developed previously. The correlations that showed the highest predicting capabilities were Jeyachandra’s 2012 correlation and Livinus’ 2018 correlation. These two studies considered the combined effect of the Viscosity and Eötvös Numbers, indicating that both parameters significantly influence the drift velocity. In addition, a new correlation was developed by the fitting of the CFD results for all the case-studies proposed. This new correlation slightly improves the prediction achieved by other authors as the overall average error obtained (18%) is 4% lower than the one found for the correlations of Livinus (2018) and Jeyachandra (2012) and around 11% and 6% lower for the high-viscosity range (Nvis > 0.1) when compared to those two correlations, respectively.

Swearword strength in subtitled and dubbed films: A reception study

Abstract In this paper we present the results of the first empirical reception study on the comparative strength of swearwords in two audiovisual translation (AVT) modes. We test the assumption/hypothesis that swearwords are perceived as stronger in writing (i.e. subtitles) than in spoken language (i.e. dubbing), which has led to the long-held translation practice of toning down or deleting swearwords more in subtitles than in dubbing. By means of an online survey, participants were asked to a) rate the psychological distance between the connotative meanings of swearwords embedded in ten film clips on a four-point strength scale, and b) comment on their ratings in open-ended text boxes. The results of various types of quantitative analysis show that our participants do not rate swearwords in subtitles higher than in dubbed clips. The qualitative analysis identified contextual factors (genre/director of film, participating characters and their relationship, setting and linguistic context) as well as viewer characteristics (gender, swearing habits and reactions to swearing) as main determinants of swearword strength. The convention of toning down or deleting swearwords more in subtitles than in dubbed audiovisual products thus seems to be based on an invalid assumption and ought to be abandoned altogether.

Classification of ALS Point Clouds Using End-to-End Deep Learning

Deep learning, referring to artificial neural networks with multiple layers, is widely used for classification tasks in many disciplines including computer vision. The most popular type is the Convolutional Neural Network (CNN), commonly applied to 2D image data. However, CNNs are difficult to adapt to irregular data like point clouds. PointNet, on the other hand, has enabled the derivation of features based on the geometric distribution of a set of points in nD-space utilising a neural network. We use PointNet on multiple scales to automatically learn a representation of local neighbourhoods in an end-to-end fashion, which is optimised for semantic labelling on 3D point clouds acquired by Airborne Laser Scanning (ALS). The results are comparable to those using manually crafted features, suggesting a successful representation of these neighbourhoods. On the ISPRS 3D Semantic Labelling benchmark, we achieve 80.6% overall accuracy, a mid-field result. Investigation on a bigger dataset, namely the 2011 ALS point cloud of the federal state of Vorarlberg, shows overall accuracies of up to 95.8% over large-scale built-up areas. Lower accuracy is achieved for the separation of low vegetation and ground points, presumably because of invalid assumptions about the distribution of classes in space, especially in high alpine regions. We conclude that the method of the end-to-end system, allowing training on a big variety of classification problems without the need for expert knowledge about neighbourhood features can also successfully be applied to single-point-based classification of ALS point clouds.