Are collapse models testable with quantum oscillating systems? The case of neutrinos, kaons, chiral molecules

Collapse models provide a theoretical framework for understanding how classical world emerges from quantum mechanics. Their dynamics preserves (practically) quantum linearity for microscopic systems, while it becomes strongly nonlinear when moving towards macroscopic scale. The conventional approach to test collapse models is to create spatial superpositions of mesoscopic systems and then examine the loss of interference, while environmental noises are engineered carefully. Here we investigate a different approach: We study systems that naturally oscillate --creating quantum superpositions-- and thus represent a natural case-study for testing quantum linearity: neutrinos, neutral mesons, and chiral molecules. We will show how spontaneous collapses affect their oscillatory behavior, and will compare them with environmental decoherence effects. We will show that, contrary to what previously predicted, collapse models cannot be tested with neutrinos. The effect is stronger for neutral mesons, but still beyond experimental reach. Instead, chiral molecules can offer promising candidates for testing collapse models.Comment: accepted by NATURE Scientific Reports, 12 pages, 1 figures, 2 table

Punishing the individual or the group for norm violation [version 2; peer review: 2 approved]

Background: It has recently been proposed that a key motivation for joining groups is the protection from consequences of negative behaviours, such as norm violations. Here we empirically test this claim by investigating whether cooperative decisions and the punishment of associated fairness-based norm violations are different in individuals vs. collectives in economic games. / Methods: In the ultimatum game, participants made or received offers that they could reject at a cost to their outcome, a form of social punishment. In the dictator game with third-party punishment, participants made offers to a receiver while being observed by a punisher, or could themselves punish unfair offers. / Results: Participants made lower offers when making their decision as part of a group as compared to alone. This difference correlated with participants’ overall mean offers: those who were generally less generous were even less so in a group, suggesting that the collective structure was compatible with their intention. Participants were slower when punishing vs not punishing an unfair offer. Importantly here, they were slower when deciding whether to punish or not to punish groups as compared to individuals, only when the offer concerned them directly in second party punishment. Participants thus take more time to punish others, and to make their mind on whether to punish or not when facing a group of proposers. / Conclusions: Together, these results show that people behave differently in a group, both in their willingness to share with others and in their punishment of norm violations. This could be explained by the fact that being in a collective structure allows to share responsibility with others, thereby protecting from negative consequences of norm violations

Punishing the individual or the group for norm violation [version 1; peer review: awaiting peer review]

Background: It has recently been proposed that a key motivation for joining groups is the protection from consequences of negative behaviours, such as norm violations. Here we empirically test this claim by investigating whether cooperative decisions and the punishment of associated fairness-based norm violations are different in individuals vs. collectives in economic games. Methods: In the ultimatum game, participants made or received offers that they could reject at a cost to their outcome, a form of social punishment. In the dictator game with third-party punishment, participants made offers to a receiver while being observed by a punisher, or could themselves punish unfair offers. Results: Participants made lower offers when making a collective rather than an individual decision. This difference correlated with participants’ overall mean offers: those who were generally less generous were even less so in a group, suggesting that the collective structure was compatible with their intention. Participants were slower when punishing vs not punishing an unfair offer. Importantly here, they were slower when deciding whether to punish groups as compared to individuals, only when the offer concerned them directly in second party punishment. Participants thus seem reluctant to punish others, and even more so when facing a group of proposers. Conclusions: Together, these results show that people behave differently in a group, both in their willingness to share with others and in their punishment of norm violations. This could be explained by the fact that being in a collective structure allows to share responsibility with others, thereby protecting from negative consequences of norm violations

The white matter connectome as an individualized biomarker of language impairment in temporal lobe epilepsy.

ObjectiveThe distributed white matter network underlying language leads to difficulties in extracting clinically meaningful summaries of neural alterations leading to language impairment. Here we determine the predictive ability of the structural connectome (SC), compared with global measures of white matter tract microstructure and clinical data, to discriminate language impaired patients with temporal lobe epilepsy (TLE) from TLE patients without language impairment.MethodsT1- and diffusion-MRI, clinical variables (CVs), and neuropsychological measures of naming and verbal fluency were available for 82 TLE patients. Prediction of language impairment was performed using a robust tree-based classifier (XGBoost) for three models: (1) a CV-model which included demographic and epilepsy-related clinical features, (2) an atlas-based tract-model, including four frontotemporal white matter association tracts implicated in language (i.e., the bilateral arcuate fasciculus, inferior frontal occipital fasciculus, inferior longitudinal fasciculus, and uncinate fasciculus), and (3) a SC-model based on diffusion MRI. For the association tracts, mean fractional anisotropy was calculated as a measure of white matter microstructure for each tract using a diffusion tensor atlas (i.e., AtlasTrack). The SC-model used measurement of cortical-cortical connections arising from a temporal lobe subnetwork derived using probabilistic tractography. Dimensionality reduction of the SC was performed with principal components analysis (PCA). Each model was trained on 49 patients from one epilepsy center and tested on 33 patients from a different center (i.e., an independent dataset). Randomization was performed to test the stability of the results.ResultsThe SC-model yielded a greater area under the curve (AUC; .73) and accuracy (79%) compared to both the tract-model (AUC: .54, p < .001; accuracy: 70%, p < .001) and the CV-model (AUC: .59, p < .001; accuracy: 64%, p < .001). Within the SC-model, lateral temporal connections had the highest importance to model performance, including connections similar to language association tracts such as links between the superior temporal gyrus to pars opercularis. However, in addition to these connections many additional connections that were widely distributed, bilateral and interhemispheric in nature were identified as contributing to SC-model performance.ConclusionThe SC revealed a white matter network contributing to language impairment that was widely distributed, bilateral, and lateral temporal in nature. The distributed network underlying language may be why the SC-model has an advantage in identifying sub-components of the complex fiber networks most relevant for aspects of language performance

A cyber-kill-chain based taxonomy of crypto-ransomware features

In spite of being just a few years old, ransomware is quickly becoming a serious threat to our digital infrastructures, data and services. Majority of ransomware families are requesting for a ransom payment to restore a custodian access or decrypt data which were encrypted by the ransomware earlier. Although the ransomware attack strategy seems to be simple, security specialists ranked ransomware as a sophisticated attack vector with many variations and families. Wide range of features which are available in different families and versions of ransomware further complicates their detection and analysis. Though the existing body of research provides significant discussions about ransomware details and capabilities, the all research body is fragmented. Therefore, a ransomware feature taxonomy would advance cyber defenders’ understanding of associated risks of ransomware. In this paper we provide, to the best of our knowledge, the first scientific taxonomy of ransomware features, aligned with Lockheed Martin Cyber Kill Chain (CKC) model. CKC is a well-established model in industry that describes stages of cyber intrusion attempts. To ease the challenge of applying our taxonomy in real world, we also provide the corresponding ransomware defence taxonomy aligned with Courses of Action matrix (an intelligence-driven defence model). We believe that this research study is of high value for the cyber security research community, as it provides the researchers with a means of assessing the vulnerabilities and attack vectors towards the intended victims

High-speed detection of DNA translocation in nanopipettes

We present a high-speed electrical detection scheme based on a custom-designed CMOS amplifier which allows the analysis of DNA translocation in glass nanopipettes on a microsecond timescale. Translocation of different DNA lengths in KCl electrolyte provides a scaling factor of the DNA translocation time equal to p = 1.22, which is different from values observed previously with nanopipettes in LiCl electrolyte or with nanopores. Based on a theoretical model involving electrophoresis, hydrodynamics and surface friction, we show that the experimentally observed range of p-values may be the result of, or at least be affected by DNA adsorption and friction between the DNA and the substrate surface

Unexpected benefits: reflections on virtual relationship building within public involvement during the Covid-19 pandemic

The Covid-19 pandemic reduced research collaborations with public contributors and prevented face-to-face interaction. The formation of Researcher Coffee Mornings within the Wessex region aimed to continue relationships between the research community and public through the pandemic. Researcher Coffee Mornings were regular Zoom meetings run by public involvement staff at University Hospital Southampton NHS Foundation Trust, UK. They were created to provide pastoral support and ‘check-ins’ between staff and public contributors during the Covid-19 pandemic. Reorganisation, implemented by public involvement staff but led by public contributors, meant that the events evolved over time. The Researcher Coffee Mornings were a means to share updates about research with the public. They were a safe space for involvement staff, researchers and the public to exchange knowledge and share experiences. This article highlights the intended and unexpected benefits of investing in relationships. We reflect on these benefits through the perspectives of the public involvement staff, public contributors and researchers. Investing in relationships has brought value to everyone involved. By demonstrating the benefits of providing regular, inclusive spaces for relationship building between the research community and public contributors, we hope to encourage others to invest in relationship building in their settings, to improve public involvement practices