Correlations Between Human Mobility and Social Interaction Reveal General Activity Patterns

A day in the life of a person involves a broad range of activities which are common across many people. Going beyond diurnal cycles, a central question is: to what extent do individuals act according to patterns shared across an entire population? Here we investigate the interplay between different activity types, namely communication, motion, and physical proximity by analyzing data collected from smartphones distributed among 638 individuals. We explore two central questions: Which underlying principles govern the formation of the activity patterns? Are the patterns specific to each individual or shared across the entire population? We find that statistics of the entire population allows us to successfully predict 71\% of the activity and 85\% of the inactivity involved in communication, mobility, and physical proximity. Surprisingly, individual level statistics only result in marginally better predictions, indicating that a majority of activity patterns are shared across {our sample population}. Finally, we predict short-term activity patterns using a generalized linear model, which suggests that a simple linear description might be sufficient to explain a wide range of actions, whether they be of social or of physical character

Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm

NLP tasks are often limited by scarcity of manually annotated data. In social media sentiment analysis and related tasks, researchers have therefore used binarized emoticons and specific hashtags as forms of distant supervision. Our paper shows that by extending the distant supervision to a more diverse set of noisy labels, the models can learn richer representations. Through emoji prediction on a dataset of 1246 million tweets containing one of 64 common emojis we obtain state-of-the-art performance on 8 benchmark datasets within sentiment, emotion and sarcasm detection using a single pretrained model. Our analyses confirm that the diversity of our emotional labels yield a performance improvement over previous distant supervision approaches.Comment: Accepted at EMNLP 2017. Please include EMNLP in any citations. Minor changes from the EMNLP camera-ready version. 9 pages + references and supplementary materia

Measure of Node Similarity in Multilayer Networks

The weight of links in a network is often related to the similarity of the nodes. Here, we introduce a simple tunable measure for analysing the similarity of nodes across different link weights. In particular, we use the measure to analyze homophily in a group of 659 freshman students at a large university. Our analysis is based on data obtained using smartphones equipped with custom data collection software, complemented by questionnaire-based data. The network of social contacts is represented as a weighted multilayer network constructed from different channels of telecommunication as well as data on face-to-face contacts. We find that even strongly connected individuals are not more similar with respect to basic personality traits than randomly chosen pairs of individuals. In contrast, several socio-demographics variables have a significant degree of similarity. We further observe that similarity might be present in one layer of the multilayer network and simultaneously be absent in the other layers. For a variable such as gender, our measure reveals a transition from similarity between nodes connected with links of relatively low weight to dis-similarity for the nodes connected by the strongest links. We finally analyze the overlap between layers in the network for different levels of acquaintanceships.Comment: 12 pages, 4 figure

Chemically modified PTFE particles as solid lubricant additive for the fixation on substrate surfaces

During the irradiation of high molecular weight poly(tetrafluoroethylene) (PTFE) in presence of oxygen perfluoroalkyl(peroxy) radicals and functional groups are formed which allow chemical coupling reactions (cc = chemical compatibilized) with oils and plastics. Contrary to the well-known inert properties of perfluorinated organic compounds high-effective additives can be produced by radiation modification and subsequent chemical compatibilization of such substances with olefinically unsaturated groups of oils/lubricants. By the irradiation process high molecular weight PTFE degrades by C-C and C-F bond scission to lower molecular weight PTFE microparticles which possess perfluoroalkyl(peroxy) radicals. These radicals are used for the chemical compatibilization reaction with olefinically unsaturated groups base oils. The tribological properties and the dispersion stability of the resulting oil-PTFE-cc (cc = chemical compatibilized) dispersions are significantly enhanced in comparison to physical mixture of oil and PTFE micropowder. These oil-PTFE-cc-dispersions show primarily anti-wear (AW) properties. The use of reactive groups (e.g. phosphite groups) in the oil gives the dispersions extreme pressure (EP) properties additionally. This article demonstrates the usefulness of the oil-PTFE-cc-dispersions in rolling bearings using phosphite-modified PTFE products as additive in lubricants (FE-8 test). The investigations are completed by the examination of roller elements by SEM/EDX analysis. A model is shown to explain the effect of phosphite groups on oxidic/hydrolytic metal surfaces

Large Language Models Converge on Brain-Like Word Representations

One of the greatest puzzles of all time is how understanding arises from neural mechanics. Our brains are networks of billions of biological neurons transmitting chemical and electrical signals along their connections. Large language models are networks of millions or billions of digital neurons, implementing functions that read the output of other functions in complex networks. The failure to see how meaning would arise from such mechanics has led many cognitive scientists and philosophers to various forms of dualism -- and many artificial intelligence researchers to dismiss large language models as stochastic parrots or jpeg-like compressions of text corpora. We show that human-like representations arise in large language models. Specifically, the larger neural language models get, the more their representations are structurally similar to neural response measurements from brain imaging.Comment: Work in proces

Acoustic pharyngometry - A new method to facilitate oral appliance therapy

Background There is lack of reliable and accurate methods to predict treatment outcomes of oral appliance (OA) treatment. Acoustic pharyngometry (AP) is a non-invasive technique to evaluate the volume and minimal cross-sectional area of the upper airway, which may prove useful to locate the optimal position of OAs. Objective This retrospective study aimed to evaluate the effect of applying AP to OA treatment of patients with obstructive sleep apnoea (OSA). Methods All patients (n = 244) treated with OAs following an AP protocol at two dental clinics between 2013 and 2018 were invited to participate. A total of 129 patients accepted the invitation, and 120 patients (75 men, 45 women) were included in the analyses. Mean baseline age, BMI and apnoea hypopnea index (AHI) were 59.1 ± 0.9 years, 27.8 ± 0.4 and 21.9 ± 1.1, respectively. Mean follow-up time was 318 ± 24 days. Results AHI at follow-up was 6.4 ± 0.7, resulting in a treatment success rate of 86.7% (≥50% reduction of baseline AHI). The number of failures ( 5 hours usage per night, when worn. Conclusion The AP protocol applied seems to contribute to the excellent effect of OA treatment in this study. Further research on the application of AP in OA treatment is necessary in order to clarify its possible beneficial contribution to improving OA therapy.publishedVersio

Neutron radiography as a tool for revealing root development in soil: capabilities and limitations

Neutron Radiography (NR) is a valuable non-invasive tool to study in situ root development in soil. However, there is a lacuna of quantitative information on its capabilities and limitations. We combined neutron radiography with image analysis techniques to quantify the neutron absorption coefficients (Σ) of various root-growth media for a range of water contents (θ) in the presence and absence of plant roots with various rooting systems. Plants were grown in aluminium containers (170 × 150 × 12mm) and were imaged using NR, as well as X-Ray radiography and an optical scanner. Sandy soil was the best medium for NR because it supported plant growth at θ that gave a good contrast for root visualisation. After correction for neutron scattering, we obtained a linear correlation between Σ and soil θ. The minimum detectable root thickness in neutron radiographs was found to be 0.2mm in these containers. Combining NR with X-Ray radiography could provide information on soil structure in addition to revealing root structure and developmen

Realtime implementation of a particle filter with integrated voice activity detector for acoustic speaker tracking

Abstract-In noisy and reverberant environments, the problem of acoustic source localisation and tracking (ASLT) using an array of microphones presents a number of challenging difficulties. One of the main issues when considering real-world situations involving human speakers is the temporally discontinuous nature of speech signals: the presence of silence gaps in the speech can easily misguide the tracking algorithm, even in practical environments with low to moderate noise and reverberation levels. This work focuses on a realtime implementation of the ASLT algorithm proposed in [1], which circumvents this problem by integrating measurements from a voice activity detector (VAD) within the tracking algorithm framework. The algorithm is here optimized for low computational complexity, and is implemented on a PC based real-time system. The resulting computational load is calculated and is presented along with real measurements of the true execution speed for the considered algorithm implementation. The results show that the algorithm is suitable for implementation in currently existing low-power embedded systems

Search for Higgs bosons decaying into new spin-0 or spin-1 particles in four-lepton final states with the ATLAS detector with 139 fb−1 of pp collision data at √s = 13 TeV

Searches are conducted for new spin-0 or spin-1 bosons using events where a Higgs boson with mass 125 GeV decays into four leptons (ℓ = e, μ). This decay is presumed to occur via an intermediate state which contains two on-shell, promptly decaying bosons: H → XX/ZX → 4ℓ, where the new boson X has a mass between 1 and 60 GeV. The search uses pp collision data collected with the ATLAS detector at the LHC with an integrated luminosity of 139 fb−1 at a centre-of-mass energy s√ = 13 TeV. The data are found to be consistent with Standard Model expectations. Limits are set on fiducial cross sections and on the branching ratio of the Higgs boson to decay into XX/ZX, improving those from previous publications by a factor between two and four. Limits are also set on mixing parameters relevant in extensions of the Standard Model containing a dark sector where X is interpreted to be a dark boson