How to Better Reduce Confirmation Bias? The Fit Between Types of Counter-Argument and Tasks

Confirmation bias is a driver of problematic decision making. People search information supporting current beliefs and ignore real critical evidence. Counter-argument i.e. providing evidences opposite to preferred beliefs was shown to have an effect on reducing confirmation bias. This study advances past studies by separating counter-arguments into two types and examining their effects in different stock investment contexts. We attempt to show that different types of counter-arguments are needed under different decisional contexts

A novel dynamics model of fault propagation and equilibrium analysis in complex dynamical communication network

International audienceTo describe failure propagation dynamics in complex dynamical communication networks, we propose an efficient and compartmental standard-exception-failure propagation dynamics model based on the method of modeling disease propagation in social networks. Mathematical formulas are derived and differential equations are solved to analyze the equilibrium of the propagation dynamics. Stability is evaluated in terms of the balance factor G and it is shown that equilibrium where the number of nodes in different states does not change, is globally asymptotically stable if G≥1. The theoretical results derived are verified by numerical simulations. We also investigate the effect of some network parameters, e.g. node density and node movement speed, on the failure propagation dynamics in complex dynamical communication networks to gain insights for effective measures of control of the scale and duration of the failure propagation in complex dynamical communication networks

The Variant of Designated Verifier Signature Scheme with Message Recovery

In this work, we introduce a strong Designated Verifier Signature (DVS) scheme that incorporates a message recovery mechanism inspired by the concept of the Universal Designated Verifier Signature (UDVS) scheme. It is worth noting that Saeednia's strong designated verifier signature scheme fails to guarantee the privacy of the signature, making it unsuitable for certain applications such as medical record certificates or voting systems. To overcome this limitation, we extend Lee's strong designated verifier signature with a message recovery scheme to develop a universal designated verifier signature scheme. This universal designated verifier scheme is crafted to safeguard the privacy of signature holders, ensuring that only designated verifiers can authenticate the true signer and recover the messages.Comment: 11 page

Contingencies of Self-Worth on Positive and Negative Events and Their Relationships to Depression

Previous studies have found that the relationship between contingencies of self-worth (CSW) and depression was generally weak. We posited that this is partly because previous studies assumed CSW on positive and negative events as the same construct (one-dimensional CSW), which should be better conceptualized as two distinctive dimensions (two-dimensional CSW) in explaining depression. A total of 393 undergraduates from Taiwan completed the measures regarding one-dimensional CSW, two-dimensional CSW, and depression. After dividing CSW of seven classic domains into two dimensions of positive and negative CSW, the results of confirmatory factor analyses showed that the two-dimensional CSW model had better model fit than the one-dimensional model in all domains. Furthermore, relative to using one-dimensional CSW as a predictor of depression, the variance accounted for largely increased when positive and negative CSW entered simultaneously in the regression equation. The results suggest that CSW on positive and negative events should be seen as two dimensions and this perspective may largely increase the explanatory power of CSW in explaining mental health

Bis(μ-adamantane-1,3-dicarboxyl­ato-κ4 O 1,O 1′:O 3,O 3′)bis­[aqua­(3-carboxy­adam­antane-1-carboxyl­ato-κO 1)(1,10-phen­an­throline-κ2 N,N′)erbium(III)] dihydrate

The asymmetric unit of the binuclear centrosymmetric title compound, [Er2(C12H14O4)2(C12H15O4)2(C12H8N2)2(H2O)2]·2H2O, contains one ErIII atom, one coordinated water mol­ecule, one 1,10-phenanthroline (phen) ligand, two differently coordinated adamantane-1,3-dicarboxyl­ate (H2L) ligands and one lattice water mol­ecule. The ErIII ion is eight-coordinated by four O atoms from bridging L 2−, one O atom from HL −, one O atom from the coordinated water and two N atoms from a phen ligand. Extensive O—H⋯O hydrogen-bonding inter­actions result in the formation of chains which are further linked into a layer-like network by π–π stacking inter­actions centroid–centroid distance = 3.611 (3) Å] between adjacent phen ligands belonging to neighbouring chains. The carboxy group of the HL − ligand is equally disordered over two positions

TPA3D: Triplane Attention for Fast Text-to-3D Generation

Due to the lack of large-scale text-3D correspondence data, recent text-to-3D generation works mainly rely on utilizing 2D diffusion models for synthesizing 3D data. Since diffusion-based methods typically require significant optimization time for both training and inference, the use of GAN-based models would still be desirable for fast 3D generation. In this work, we propose Triplane Attention for text-guided 3D generation (TPA3D), an end-to-end trainable GAN-based deep learning model for fast text-to-3D generation. With only 3D shape data and their rendered 2D images observed during training, our TPA3D is designed to retrieve detailed visual descriptions for synthesizing the corresponding 3D mesh data. This is achieved by the proposed attention mechanisms on the extracted sentence and word-level text features. In our experiments, we show that TPA3D generates high-quality 3D textured shapes aligned with fine-grained descriptions, while impressive computation efficiency can be observed