Miracle-dz/UniFAR-FTUs huggingface dataset:
A metaphor is not like a simile: reading-time evidence for distinct interpretations for negated tropes

ABSTRACT Studies have suggested that metaphors (Lawyers are sharks) and similes (Lawyers are like sharks) have distinct representations: metaphors engender more figurative and abstract properties, whereas similes engender more literal properties. We investigated to what extent access to such representations occurs automatically, during on-line reading. In particular, we examined whether similes convey a more literal meaning by following the metaphors and similes with explanations that expressed either a figurative (dangerous) or a literal property (fish) of the vehicle. In a self-paced reading with a moving window paradigm, we presented participants with negated simile and metaphor main clauses (Lawyers are not (like) sharks) followed by explanations that also negated either a figurative (because lawyers are not dangerous) or a literal property of the vehicle (because lawyers are not fish). We found that vehicles (sharks) in metaphors were read significantly faster than those in similes. In addition, explanations negating a figurative property were read faster after metaphors, whereas explanations negating a literal property were read faster after similes. These results support the hypothesis that metaphors and similes rely on different interpretive processes, suggesting that similes access literal representations while metaphor access figurative ones in real time.
When security elites deal with politicians: rethinking practices from the perspective of security-politics relationships

ABSTRACT This article examines how security-politics relationships play out in the routines of security elites when confronted with political decisions pertaining to European security cooperation. To do so, the article reflects upon British debates about police and judicial cooperation in a post-Brexit Europe along with debates on the 2014 opt-out from Justice and Home Affairs. How security elites respond to political decisions is investigated from a sociological lens that mobilises lessons from Norbert Elias. The article thus shows how security elites play out distinct roles and conduct distinct types of work when embedded chains of interdependence with professionals of politics that define what legitimate security cooperation is; a neglected aspect in bureaucratic politics and practice turn literature, and Critical Security Studies. It also exposes how security elites fight for EU-led cooperation because of attributes seemingly drawn from lived experiences in EU cooperation and triggered by the constraints of the relationships in which they are situated. The article thus complements existing debates on practices and security professionals by building knowledge on security elites and their routines from the angle of security-politics relationships.
Cardiac TdP risk stratification modelling of anti-infective compounds including chloroquine and hydroxychloroquine

Hydroxychloroquine (HCQ), the hydroxyl derivative of chloroquine (CQ), is widely used in the treatment of rheumatological conditions (systemic lupus erythematosus, rheumatoid arthritis) and is being studied for the treatment and prevention of COVID-19. Here, we investigate through mathematical modelling the safety profile of HCQ, CQ and other QT-prolonging anti-infective agents to determine their risk categories for Torsade de Pointes (TdP) arrhythmia. We performed safety modelling with uncertainty quantification using a risk classifier based on the qNet torsade metric score, a measure of the net charge carried by major currents during the action potential under inhibition of multiple ion channels by a compound. Modelling results for HCQ at a maximum free therapeutic plasma concentration (free Cmax) of approximately 1.2 µM (malaria dosing) indicated it is most likely to be in the high-intermediate-risk category for TdP, whereas CQ at a free Cmax of approximately 0.7 µM was predicted to most likely lie in the intermediate-risk category. Combining HCQ with the antibacterial moxifloxacin or the anti-malarial halofantrine (HAL) increased the degree of human ventricular action potential duration prolongation at some or all concentrations investigated, and was predicted to increase risk compared to HCQ alone. The combination of HCQ/HAL was predicted to be the riskiest for the free Cmax values investigated, whereas azithromycin administered individually was predicted to pose the lowest risk. Our simulation approach highlights that the torsadogenic potentials of HCQ, CQ and other QT-prolonging anti-infectives used in COVID-19 prevention and treatment increase with concentration and in combination with other QT-prolonging drugs.
Olfactory Testing in Parkinson Disease and REM Behavior Disorder

Objective We sought to identify an abbreviated test of impaired olfaction amenable for use in busy clinical environments in prodromal (isolated REM sleep behavior disorder [iRBD]) and manifest Parkinson disease (PD). Methods Eight hundred ninety individuals with PD and 313 controls in the Discovery cohort study underwent Sniffin’ Stick odor identification assessment. Random forests were initially trained to distinguish individuals with poor (functional anosmia/hyposmia) and good (normosmia/super-smeller) smell ability using all 16 Sniffin’ Sticks. Models were retrained using the top 3 sticks ranked by order of predictor importance. One randomly selected 3-stick model was tested in a second independent PD dataset (n = 452) and in 2 iRBD datasets (Discovery n = 241, Marburg n = 37) before being compared to previously described abbreviated Sniffin’ Stick combinations. Results In differentiating poor from good smell ability, the overall area under the curve (AUC) value associated with the top 3 sticks (anise/licorice/banana) was 0.95 in the Development dataset (sensitivity 90%, specificity 92%, positive predictive value 92%, negative predictive value 90%). Internal and external validation confirmed AUCs ≥0.90. The combination of the 3-stick model determined poor smell, and an RBD screening questionnaire score of ≥5 separated those with iRBD from controls with a sensitivity, specificity, positive predictive value, and negative predictive value of 65%, 100%, 100%, and 30%. Conclusions Our 3-Sniffin’-Stick model holds potential utility as a brief screening test in the stratification of individuals with PD and iRBD according to olfactory dysfunction. Classification of Evidence This study provides Class III evidence that a 3-Sniffin’-Stick model distinguishes individuals with poor and good smell ability and can be used to screen for individuals with iRBD.
The Effects of Adverse Childhood Experiences and Gender on Developmental Trajectories of Internalizing and Externalizing Outcomes

Adverse Childhood Experiences (ACEs) are linked to problematic outcomes, but it remains unclear how ACEs affect developmental patterns of harmful behavior, and whether this varies by gender. This study examined these relationships among 868 youth participating in the Longitudinal Studies of Child Abuse and Neglect. Group-based trajectory models identified five trajectories of internalizing and six trajectories of externalizing outcomes. Multinomial logistic regression models examined the relationships between ACEs, gender, and the interaction between the two on trajectory group membership. Higher ACEs were associated with elevated internalizing and externalizing trajectories, and boys who experienced higher ACEs were at a heightened risk of exhibiting elevated externalizing trajectories. Findings shed light on the importance of gender in developmental responses to victimization and adversity.
Unmanned surface vessel obstacle avoidance with prior knowledge‐based reward shaping

Autonomous obstacle avoidance control of unmanned surface vessels (USVs) in complex marine environments is always fundamental for its scientific search and detection. Traditional methods usually model USV motion and environments in a mathematical way that needs perceptual information. Unfortunately, it is difficult to provide sufficient perceptual information due to complex marine environments, resulting in inaccurate modeling. Reinforcement learning has recently enjoyed increasing popularity in the problem of obstacle avoidance since it can settle problems by partially observable environment information. However, the autonomous USV obstacle avoidance using reinforcement learning is still facing the challenge of designing appropriate reward functions under complex marine environments. To address these issues, we propose a prior knowledge‐based USV reinforcement learning obstacle avoidance algorithm. In this algorithm, an actor‐critic network is used as the main architecture of the algorithm, and prior knowledge‐based reward shaping used to design relevant reward function for USV obstacle avoidance. A standard USV based on a visual sensor is designed, and the state input of the algorithm is through USV's front vision sensor. We conducted simulation experiments and results prove that our algorithm can effectively converge, and USV achieves high velocity and low collision rate in the complex marine environment.
Characterising electrospun nanofibre adsorbents for bioprocessing

Biopharmaceutical manufacturing is one of largest sectors in the world and purification steps are expensive. Packed-bed resins are widely used, but are limited by diffusion mass transfer. Convective mass transfer media offer improved productivities using high flowrates. Electrospun nanofibres are a non-woven with an open structure and high surface area. Cellulose acetate was electrospun into reproducible adsorbents and activation methodologies were evaluated. Aldehyde activation caused degradation. Epoxy, carboxyl and cyanuric chloride activations were successful and recommended for cellulose nanofibres. Compressing cellulose acetate nanofibres improved mechanical strength. Functionalisation to diethylaminoethyl and carboxyl adsorbents showed the highest DBC10% values at the lowest compression load of 1 MPa at 20 and 27 mg /mL, respectively. However, at this load the DBC decreased for increasing flowrate, whereas, the DBCs of higher loads were consistent. Glucose isomerase is an important industrial enzyme used as a sweetener in the drinks industry. Immobilised glucose isomerase by epoxy activation showed similar initial activities in static and dynamic assays, which represented batch and flowthrough process, respectively. The activity of free enzyme was notably higher in the static assay than the immobilised, but the poorer mixing in the dynamic assay reduced its activity. The retained activity of nanofibre-immobilised glucose isomerase in the dynamic assay supports its application to flowthrough reactors. Protein A chromatography is an expensive stage in antibody manufacture and was immobilised by cyanuric chloride and spacer arms. For comparison, an aldehyde activation was developed with glycidol modification, which was preferred to that of cyanuric chloride, recording equilibrium and DBC10% capacities of 4.37 and 2.99 mg/mL, respectively. The versatility of electrospun cellulose adsorbents are characterised in protein binding and biocatalysis applications, showing static and dynamic operations. The continued development of nanofibres into largescale systems and a whole process context will reveal their full benefits to bioprocessing.
A Critique of Keum-Bae Cho's Proof that $\mathrm{P} \subsetneq \mathrm{NP}$

In this paper we critique Keum-Bae Cho's proof that $\mathrm{P} \subsetneq \mathrm{NP}$. This proof relates instances of 3-SAT to indistinguishable binomial decision trees and claims that no polynomial-time algorithm can solve 3-SAT instances represented by these trees. We argue that their proof fails to justify a crucial step, and so the proof does not establish that $\mathrm{P} \subsetneq \mathrm{NP}$.
A High-Quality Authenticatable Visual Secret Sharing Scheme Using SGX

Visual cryptography scheme (VCS) is a secret-sharing scheme which encrypts images as shares and can decrypt shares without digital devices. Although a participant can reveal the secret image by merely stacking a sufficient number of shares, the visual quality of recovered images is reduced, and malicious adversaries can cheat participants by giving faked shares. The paper presents a novel VCS called T-VCS (trusted VCS) which consists of two main components: a high-quality VCS and an enhanced verification scheme of shares based on the emerging Intel Software Guard eXtensions (SGX). While providing highquality recovery, T-VCS keeps the size of the shares the same as the original secret image. We use SGX to act as a trusted third party (TTP) to verify the validity of the shares in an attested enclave without degrading the image quality. The experimental results show that T-VCS can achieve a balance among contrast, share size, and verification efficiency.
Multi-task Learning for Cross-Lingual Sentiment Analysis

This paper presents a cross-lingual sentiment analysis of news articles using zero-shot and few-shot learning. The study aims to classify the Croatian news articles with positive, negative, and neutral sentiments using the Slovene dataset. The system is based on a trilingual BERT-based model trained in three languages: English, Slovene, Croatian. The paper analyses different setups using datasets in two languages and proposes a simple multi-task model to perform sentiment classification. The evaluation is performed using the few-shot and zero-shot scenarios in single-task and multi-task experiments for Croatian and Slovene.
NOX-arme Steinkohlefeuerung für Grossdampferzeuger

Primary measures on the combustion side offer great potential for NO x reduction. For the tangential firing of a 110 MW power plant unit, this has been demonstrated by the attainment of NO x emission rates between 200 and 300 mg/m 3 (s.t.p.). A special air gradation principle forms the basis of the combustion system. An economic evaluation demonstrates that this kind of combustion system conversion is worthwhile today from the economic point of view, even with steam generators already equipped with selective catalytic reduction equipment. In addition, the paper presents simulation results for a corresponding combustion system of a new large steam generator.
Facial Expression Recognition Based on Attention Mechanism

At present, traditional facial expression recognition methods of convolutional neural networks are based on local ideas for feature expression, which results in the model’s low efficiency in capturing the dependence between long-range pixels, leading to poor performance for facial expression recognition. In order to solve the above problems, this paper combines a self-attention mechanism with a residual network and proposes a new facial expression recognition model based on the global operation idea. This paper first introduces the self-attention mechanism on the basis of the residual network and finds the relative importance of a location by calculating the weighted average of all location pixels, then introduces channel attention to learn different features on the channel domain, and generates channel attention to focus on the interactive features in different channels so that the robustness can be improved; finally, it merges the self-attention mechanism and the channel attention mechanism to increase the model’s ability to extract globally important features. The accuracy of this paper on the CK+ and FER2013 datasets is 97.89% and 74.15%, respectively, which fully confirmed the effectiveness and superiority of the model in extracting global features.
AFI-Net: Attention-Guided Feature Integration Network for RGBD Saliency Detection

This article proposes an innovative RGBD saliency model, that is, attention-guided feature integration network, which can extract and fuse features and perform saliency inference. Specifically, the model first extracts multimodal and level deep features. Then, a series of attention modules are deployed to the multilevel RGB and depth features, yielding enhanced deep features. Next, the enhanced multimodal deep features are hierarchically fused. Lastly, the RGB and depth boundary features, that is, low-level spatial details, are added to the integrated feature to perform saliency inference. The key points of the AFI-Net are the attention-guided feature enhancement and the boundary-aware saliency inference, where the attention module indicates salient objects coarsely, and the boundary information is used to equip the deep feature with more spatial details. Therefore, salient objects are well characterized, that is, well highlighted. The comprehensive experiments on five challenging public RGBD datasets clearly exhibit the superiority and effectiveness of the proposed AFI-Net.
Toxic Mechanisms of Five Heavy Metals: Mercury, Lead, Chromium, Cadmium, and Arsenic

The industrial activities of the last century have caused massive increases in human exposure to heavy metals. Mercury, lead, chromium, cadmium, and arsenic have been the most common heavy metals that induced human poisonings. Here, we reviewed the mechanistic action of these heavy metals according to the available animal and human studies. Acute or chronic poisonings may occur following exposure through water, air, and food. Bioaccumulation of these heavy metals leads to a diversity of toxic effects on a variety of body tissues and organs. Heavy metals disrupt cellular events including growth, proliferation, differentiation, damage-repairing processes, and apoptosis. Comparison of the mechanisms of action reveals similar pathways for these metals to induce toxicity including ROS generation, weakening of the antioxidant defense, enzyme inactivation, and oxidative stress. On the other hand, some of them have selective binding to specific macromolecules. The interaction of lead with aminolevulinic acid dehydratase and ferrochelatase is within this context. Reactions of other heavy metals with certain proteins were discussed as well. Some toxic metals including chromium, cadmium, and arsenic cause genomic instability. Defects in DNA repair following the induction of oxidative stress and DNA damage by the three metals have been considered as the cause of their carcinogenicity. Even with the current knowledge of hazards of heavy metals, the incidence of poisoning remains considerable and requires preventive and effective treatment. The application of chelation therapy for the management of metal poisoning could be another aspect of heavy metals to be reviewed in the future.
Life in a Droplet: Microbial Ecology in Microscopic Surface Wetness

While many natural and artificial surfaces may appear dry, they are in fact covered by thin liquid films and microdroplets invisible to the naked eye known as microscopic surface wetness (MSW). Central to the formation and the retention of MSW are the deliquescent properties of hygroscopic salts that prevent complete drying of wet surfaces or that drive the absorption of water until dissolution when the relative humidity is above a salt-specific level. As salts are ubiquitous, MSW occurs in many microbial habitats, such as soil, rocks, plant leaf, and root surfaces, the built environment, and human and animal skin. While key properties of MSW, including very high salinity and segregation into droplets, greatly affect microbial life therein, it has been scarcely studied, and systematic studies are only in their beginnings. Based on recent findings, we propose that the harsh micro-environment that MSW imposes, which is very different from bulk liquid, affects key aspects of bacterial ecology including survival traits, antibiotic response, competition, motility, communication, and exchange of genetic material. Further research is required to uncover the fundamental principles that govern microbial life and ecology in MSW. Such research will require multidisciplinary science cutting across biology, physics, and chemistry, while incorporating approaches from microbiology, genomics, microscopy, and computational modeling. The results of such research will be critical to understand microbial ecology in vast terrestrial habitats, affecting global biogeochemical cycles, as well as plant, animal, and human health.
Tooth Microwear Texture in the Eastern Atlantic Harbour Seals (Phoca vitulina vitulina) of the German Wadden Sea and Its Implications for Long Term Dietary and Ecosystem Changes

Marine mammals are increasingly threatened in their habitat by various anthropogenic impacts. This is particularly evident in prey abundance. Understanding the dietary strategies of marine mammal populations can help predict implications for their future health status and is essential for their conservation. In this study we provide a striking example of a new dietary proxy in pinnipeds to document marine mammal diets using a dental record. In this novel approach, we used a combination of 49 parameters to establish a dental microwear texture (DMTA) as a dietary proxy of feeding behaviour in harbour seals. This method is an established approach to assess diets in terrestrial mammals, but has not yet been applied to pinnipeds. Our aim was to establish a protocol, opening DMTA to pinnipeds by investigating inter- and intra-individual variations. We analysed the 244 upper teeth of 78 Atlantic harbour seals (Phoca vitulina vitulina). The specimens were collected in 1988 along the North Sea coast (Wadden Sea, Germany) and are curated by the Zoological Institute of Kiel University, Germany. An increasing surface texture roughness from frontal to distal teeth was found and related to different prey processing biomechanics. Ten and five year old individuals were similar in their texture roughness, whereas males and females were similar to each other with the exception of their frontal dentition. Fall and summer specimens also featured no difference in texture roughness. We established the second to fourth postcanine teeth as reference tooth positions, as those were unaffected by age, sex, season, or intra-individual variation. In summary, applying indirect dietary proxies, such as DMTA, will allow reconstructing dietary traits of pinnipeds using existing skeletal collection material. Combining DMTA with time series analyses is a very promising approach to track health status in pinniped populations over the last decades. This approach opens new research avenues and could help detect dietary shifts in marine environments in the past and the future.
Fungal Toxins and Host Immune Responses

Fungi are ubiquitous organisms that thrive in diverse natural environments including soils, plants, animals, and the human body. In response to warmth, humidity, and moisture, certain fungi which grow on crops and harvested foodstuffs can produce mycotoxins; secondary metabolites which when ingested have a deleterious impact on health. Ongoing research indicates that some mycotoxins and, more recently, peptide toxins are also produced during active fungal infection in humans and experimental models. A combination of innate and adaptive immune recognition allows the host to eliminate invading pathogens from the body. However, imbalances in immune homeostasis often facilitate microbial infection. Despite the wide-ranging effects of fungal toxins on health, our understanding of toxin-mediated modulation of immune responses is incomplete. This review will explore the current understanding of fungal toxins and how they contribute to the modulation of host immunity.