The pursuit of information sharing: Expressing task conflicts as debates vs. disagreements increases perceived receptivity to dissenting opinions in groups

Ministry of Education, Singapore under its Academic Research Funding Tier

Sequential change in olfaction and (non) motor symptoms: the difference between anosmia and non-anosmia in Parkinson’s disease

IntroductionHyposmia is a common prodrome in patients with Parkinson’s disease (PD). This study investigates whether olfactory changes in PD differ according to the degree of olfactory dysfunction and whether there are changes in motor and non-motor symptoms.MethodsThe 129 subjects with PD were divided into two groups: anosmia and non-anosmia. All cases were reassessed within 1–3 years after the initial assessment. The assessment included the MDS-Unified PD Rating Scale (MDS-UPDRS), the University of Pennsylvania Smell Identification Test (UPSIT), Beck’s Depression Inventory-II (BDI-II), Montreal Cognitive Assessment (MoCA), and equivalence dose of daily levodopa (LEDD). The generalized estimating equation (GEE) model with an exchangeable correlation structure was used to analyze the change in baseline and follow-up tracking and the disparity in change between these two groups.ResultsThe anosmia group was older and had a longer disease duration than the non-anosmia group. There was a significant decrease in UPSIT after follow-up in the non-anosmia group (β = −3.62, p < 0.001) and a significant difference in the change between the two groups (group-by-time effect, β = 4.03, p < 0.001). In the third part of the UPDRS motor scores, there was a tendency to increase the score in the non-anosmia group compared to the anosmia group (group-by-time effect, β = −4.2, p < 0.038). There was no significant difference in the group-by-time effect for UPDRS total score, LEDD, BDI-II, and MoCA scores.DiscussionIn conclusion, this study found that olfactory sensation may still regress in PD with a shorter disease course without anosmia, but it remains stable in the anosmia group. Such a decline in olfaction may not be related to cognitive status but may be associated with motor progression

Spontaneous Arrangement of Two-way Flow in Water Bridge

By revisiting the century-old problem of water bridge, we demonstrate that it is in fact dynamic and comprises of two coaxial currents that carry different charges and flow in opposite directions. Initially, the inner flow is facilitated by the cone jet that is powered by H+ and flows out of the anode beaker. The negative cone jet from cathode is established later and forced to take the outer route. This spontaneous arrangement of two-way flow is revealed by the use of chemical dyes, e.g., fluorescein and FeCl3, carbon powder, and the Particle Image Velocimetry. These two opposing flows are found to carry non-equal flux that results in a net transport of water to the cathode beaker. By combining the above information and taking into account the counter flow to equate the water level from the connecting pipe, we can estimate the cross section and flow speed of these co-axial flows as a function of time and applied voltage.Comment: 5 pages, 5 figure

Deep Learning of Phase Transitions for Quantum Spin Chains from Correlation Aspects

Using machine learning (ML) to recognize different phases of matter and to infer the entire phase diagram has proven to be an effective tool given a large dataset. In our previous proposals, we have successfully explored phase transitions for topological phases of matter at low dimensions either in a supervised or an unsupervised learning protocol with the assistance of quantum information related quantities. In this work, we adopt our previous ML procedures to study quantum phase transitions of magnetism systems such as the XY and XXZ spin chains by using spin-spin correlation functions as the input data. We find that our proposed approach not only maps out the phase diagrams with accurate phase boundaries, but also indicates some new features that have not observed before. In particular, we define so-called relevant correlation functions to some corresponding phases that can always distinguish between those and their neighbors. Based on the unsupervised learning protocol we proposed [Phys. Rev. B 104, 165108 (2021)], the reduced latent representations of the inputs combined with the clustering algorithm show the connectedness or disconnectedness between neighboring clusters (phases), just corresponding to the continuous or disrupt quantum phase transition, respectively.Comment: 18 pages, 21 figure