Miracle-dz/UniFAR-FTUs huggingface dataset:
Human hand as a powerless and multiplexed infrared light source for information decryption and complex signal generation

Significance The utilization of electricity-powered light sources as external stimuli is limited by the cost and energy loss. Here we demonstrate that the human hand can be used as a natural IR light source without the need of external power. As each finger can serve as an independent light source, the hand can also be utilized as a multiplexed IR light source. This work provides a different insight on using the hand in a functional system, such as the information encryption and complex signal generation systems demonstrated here, which will help move forward the effort in the integration of human components into various systems to increase the level of intelligence and achieve ultimate control of these systems. With the increasing pursuit of intelligent systems, the integration of human components into functional systems provides a promising route to the ultimate human-compatible intelligent systems. In this work, we explored the integration of the human hand as the powerless and multiplexed infrared (IR) light source in different functional systems. With the spontaneous IR radiation, the human hand provides a different option as an IR light source. Compared to engineered IR light sources, the human hand brings sustainability with no need of external power and also additional level of controllability to the functional systems. Besides the whole hand, each finger of the hand can also independently provide IR radiation, and the IR radiation from each finger can be selectively diffracted by specific gratings, which helps the hand serve as a multiplexed IR light source. Considering these advantages, we show that the human hand can be integrated into various engineered functional systems. The integration of hand in an encryption/decryption system enables both unclonable and multilevel information encryption/decryption. We also demonstrate the use of the hand in complex signal generation systems and its potential application in sign language recognition, which shows a simplified recognition process with a high level of accuracy and robustness. The use of the human hand as the IR light source provides an alternative sustainable solution that will not only reduce the power used but also help move forward the effort in the integration of human components into functional systems to increase the level of intelligence and achieve ultimate control of these systems.
Topological defects produce kinks in biopolymer filament bundles

Significance A common structural motif for stress-bearing intracellular structures and tissues is a network of filament bundles. When observed in optical microscopy, these bundles often show localized bends—kinks—in their contour even though the stress-free state of their constituent filaments is straight. Using a combination of analytical mechanics and large-scale, finite-element Brownian dynamics simulations, we show that the optically observable kinks are related to topological defects in the interior, nanoscale structure of the bundle. Moreover, the kinks are more compliant to bending than the rest of the bundle. As a result, defected bundle networks must contain a random distribution of soft hinges, which, being the most compliant elastic elements, control the low-energy excitations of these bundle networks. Bundles of stiff filaments are ubiquitous in the living world, found both in the cytoskeleton and in the extracellular medium. These bundles are typically held together by smaller cross-linking molecules. We demonstrate, analytically, numerically, and experimentally, that such bundles can be kinked, that is, have localized regions of high curvature that are long-lived metastable states. We propose three possible mechanisms of kink stabilization: a difference in trapped length of the filament segments between two cross-links, a dislocation where the endpoint of a filament occurs within the bundle, and the braiding of the filaments in the bundle. At a high concentration of cross-links, the last two effects lead to the topologically protected kinked states. Finally, we explore, numerically and analytically, the transition of the metastable kinked state to the stable straight bundle.
Impact of prenatal maternal cytokine exposure on sex differences in brain circuitry regulating stress in offspring 45 years later

Significance Clinical research and animal models have demonstrated a significant connection between maternal stress during pregnancy and sensitivity to stress in offspring, leading to increased susceptibility to neuropsychiatric disorders later in life. In a unique prenatal cohort that was followed for over four decades, we tested associations between pro- and anti-inflammatory markers in maternal prenatal sera and sex differences in neural responses to negative stress in the offspring in early midlife using functional MRI. Men and women exposed in utero to abnormal levels of pro-inflammatory cytokines and to an imbalance of pro- to anti-inflammatory influences showed dysregulation of stress response circuitry 45 y later, with sex-dependent effects. Stress is associated with numerous chronic diseases, beginning in fetal development with in utero exposures (prenatal stress) impacting offspring’s risk for disorders later in life. In previous studies, we demonstrated adverse maternal in utero immune activity on sex differences in offspring neurodevelopment at age seven and adult risk for major depression and psychoses. Here, we hypothesized that in utero exposure to maternal proinflammatory cytokines has sex-dependent effects on specific brain circuitry regulating stress and immune function in the offspring that are retained across the lifespan. Using a unique prenatal cohort, we tested this hypothesis in 80 adult offspring, equally divided by sex, followed from in utero development to midlife. Functional MRI results showed that exposure to proinflammatory cytokines in utero was significantly associated with sex differences in brain activity and connectivity during response to negative stressful stimuli 45 y later. Lower maternal TNF-α levels were significantly associated with higher hypothalamic activity in both sexes and higher functional connectivity between hypothalamus and anterior cingulate only in men. Higher prenatal levels of IL-6 were significantly associated with higher hippocampal activity in women alone. When examined in relation to the anti-inflammatory effects of IL-10, the ratio TNF-α:IL-10 was associated with sex-dependent effects on hippocampal activity and functional connectivity with the hypothalamus. Collectively, results suggested that adverse levels of maternal in utero proinflammatory cytokines and the balance of pro- to anti-inflammatory cytokines impact brain development of offspring in a sexually dimorphic manner that persists across the lifespan.
Global warming is causing a more pronounced dip in marine species richness around the equator

Significance We use distribution data on 48,661 species to show that marine biodiversity has been responding to climate warming at a global scale. We show that marine species richness levels off or declines in latitudinal bands with average annual sea surface temperatures exceeding 20 °C. This results in a dip in species richness around the equator that has become more pronounced as the climate has warmed, especially for pelagic species. Previous studies have either only predicted such effects or have provided data at regional scales or for limited numbers of taxa. The latitudinal gradient in species richness, with more species in the tropics and richness declining with latitude, is widely known and has been assumed to be stable over recent centuries. We analyzed data on 48,661 marine animal species since 1955, accounting for sampling variation, to assess whether the global latitudinal gradient in species richness is being impacted by climate change. We confirm recent studies that show a slight dip in species richness at the equator. Moreover, richness across latitudinal bands was sensitive to temperature, reaching a plateau or declining above a mean annual sea surface temperature of 20 °C for most taxa. In response, since the 1970s, species richness has declined at the equator relative to an increase at midlatitudes and has shifted north in the northern hemisphere, particularly among pelagic species. This pattern is consistent with the hypothesis that climate change is impacting the latitudinal gradient in marine biodiversity at a global scale. The intensification of the dip in species richness at the equator, especially for pelagic species, suggests that it is already too warm there for some species to survive.
Accurate modeling of DNA conformational flexibility by a multivariate Ising model

Significance The deformability of DNA is strongly sequence-dependent. Accurate prediction of the deformability could be a major step for understanding indirect readout in numerous processes involving protein–DNA binding. At the base-pair level, DNA deformability is typically described by nearest-neighbor-coupled harmonic oscillators. However, DNA can also adopt different transiently stable substates that also depend on neighbors. We have developed a model that combines a harmonic coupled oscillator description with an Ising model to include also all possible substates of a DNA duplex. It gives not only an improved prediction of the equilibrium distribution of DNA helical variables, but also predicts indirect readout contributions to protein–DNA binding in better agreement with experiment than a unimodal harmonic model. The sequence-dependent structure and deformability of DNA play a major role for binding of proteins and regulation of gene expression. So far, most efforts to model DNA flexibility are based on unimodal harmonic stiffness models at base-pair resolution. However, multimodal behavior due to distinct conformational substates also contributes significantly to the conformational flexibility of DNA. Moreover, these local substates are correlated to their nearest-neighbor substates. A description for DNA elasticity which includes both multimodality and nearest-neighbor coupling has remained a challenge, which we solve by combining our multivariate harmonic approximation with an Ising model for the substates. In a series of applications to DNA fluctuations and protein–DNA complexes, we demonstrate substantial improvements over the unimodal stiffness model. Furthermore, our multivariate Ising model reveals a mechanical destabilization for adenine (A)-tracts to undergo nucleosome formation. Our approach offers a wide range of applications to determine sequence-dependent deformation energies of DNA and to investigate indirect readout contributions to protein–DNA recognition.
Energy efficiency in mechanical pulping – definitions and considerations

Abstract Production of mechanical pulps requires high specific electrical energy compared to many other attrition processes. In Scandinavia, the lowest specific refining energy for production of thermomechanical pulp is around 1800 kWh/t for newsprint quality, which is roughly 60 times higher than for crushing of stone to a similar size distribution. The high specific energy demand for refining has naturally motivated large efforts in the search for improved efficiency. It is always practical to be able to quantify improvements in efficiency for comparison of process designs and of different machine types. However, there is no commonly accepted definition of efficiency for mechanical pulping processes. In published work within mechanical pulping, energy efficiency has been presented in different ways. In this paper, we discuss definitions of energy efficiency and aspects that ought to be considered when energy efficiency is presented. Although focus of this work is on energy efficiency for refiner processes, the principles can be applied to other types of mechanical pulping processes such as stone groundwood.
Learning to Engage in Interactive Digital Art

The aim of this study was to determine whether reinforcement learning could increase user engagement in interactive art installations. Building on a physical interactive art installation called The Plants [1] by Playable Streets, reinforcement learning was integrated into a web application adapted from the physical interactive art piece. The original installation consisted of real plants that visitors could touch to produce sounds. A digital model and interface was developed to simulate the physical installation. A user study was conducted with 178 participants. Three modes were examined: the original settings of the installation as designed by the artist; a predetermined fixed schedule of consistently changing sound banks; and a reinforcement learning mode, where an agent changes the interactive behaviours to maximise user engagement. User engagement was estimated by comparing the number of touches by an individual over successive time intervals. From the trial, it was found that reinforcement learning was able to improve average engagement levels of users by nearly 27%. However, reinforcement learning was not able to increase the average duration users interacted with the installation.
Data-centric disambiguation for data transformation with programming-by-example

Programming-by-example (PBE), can be a powerful tool to reduce manual work in repetitive data transformation tasks. However, few examples often leave ambiguity and may cause undesirable data transformation by the system. This ambiguity can be resolved by allowing the user to directly edit the synthesized programs; however, this is difficult for non-programmers. Here, we present a novel approach: data-centric disambiguation for data transformation, where users resolve the ambiguity in data transformation by examining and modifying the output rather than the program. The key idea is to focus on the given set of data the user wants to transform instead of pursuing the synthesized program’s generality or completeness. Our system provides visualization and interaction methods that allow users to efficiently examine and fix the transformed outputs, which is much simpler than understanding and modifying the program itself. The user study suggests that our system can successfully help non-programmers to more easily and efficiently process data.
Automatic Indonesian Sentiment Lexicon Curation with Sentiment Valence Tuning for Social Media Sentiment Analysis

A novel Indonesian sentiment lexicon (SentIL -- Sentiment Indonesian Lexicon) is created with an automatic pipeline; from creating sentiment seed words, adding new words with slang words, emoticons, and from the given dictionary and sentiment corpus, until tuning sentiment value with tagged sentiment corpus. It begins by taking seed words from WordNet Bahasa that mapped with sentiment value from English SentiWordNet. The seed words are enriched by combining the dictionary-based method with words’ synonyms and antonyms, and corpus-based methods with word embedding for word similarity that trained in positive and negative sentiment corpus from online marketplaces review and Twitter data. The valence score of each lexicon is recalculated based on its relative occurrence in the corpus. We also add some famous slang words and emoticons to enrich the lexicon. Our experiment shows that the proposed method can provide an increase of 3.5 times lexicon number as well as improve the accuracy of 80.9% for online review and 95.7% for Twitter data, and they are better than other published and available Indonesian sentiment lexicons.
Increasing the User Experience in Autonomous Driving through different Feedback Modalities

Within the ongoing process of defining autonomous driving solutions, experience design may represent an important interface between humans and the autonomous vehicle. This paper presents an empirical study that uses different ways of unimodal communication in autonomous driving to communicate awareness and intent of autonomous vehicles. The goal is to provide recommendations for feedback solutions within holistic autonomous driving experiences. 22 test subjects took part in four autonomous, simulated virtual reality shuttle rides and were presented with different unimodal feedback in the form of light, sound, visualisation, text and vibration. The empirical study showed that, compared to a no-feedback baseline ride, light, and visualisation were able to create a positive user experience.
Rapid Assisted Visual Search: Supporting Digital Pathologists with Imperfect AI

Designing useful human-AI interaction for clinical workflows remains challenging despite the impressive performance of recent AI models. One specific difficulty is a lack of successful examples demonstrating how to achieve safe and efficient workflows while mitigating AI imperfections. In this paper, we present an interactive AI-powered visual search tool that supports pathologists in cancer assessments. Our evaluation with six pathologists demonstrates that it can 1) reduce time needed with maintained quality, 2) build user trust progressively, and 3) learn and improve from use. We describe our iterative design process, model development, and key features. Through interviews, design choices are related to the overall user experience. Implications for future human-AI interaction design are discussed with respect to trust, explanations, learning from use, and collaboration strategies.
Titanium Doping and Its Effect on the Morphology of Three-Dimensional Hierarchical Nb3O7(OH) Nanostructures for Enhanced Light-Induced Water Splitting

This study presents a simple method that allows us to modify the composition, morphological, and surface properties of three-dimensional hierarchical Nb3O7(OH) superstructures, resulting in strongly enhanced photocatalytic H2 production. The superstructures consist of highly ordered nanowire networks and self-assemble under hydrothermal conditions. The presence of titanium affects the morphology of the superstructures, resulting in increased surface areas for higher doping levels. Up to 12 at. % titanium is incorporated into the Nb3O7(OH) crystal lattice via substitution of niobium at its octahedral lattice sites. Further titanium excess results in the formation of niobium-doped TiO2 plates, which overgrow the surface of the Nb3O7(OH) superstructures. Photoluminescence spectroscopy indicates fewer charge recombination processes near the surface of the nanostructures with an increasing titanium concentration in the crystal lattice. The combination of larger surface areas with fewer quenching sites at the c.
Exploring Smartphone Keyboard Interactions for Experience Sampling Method driven Probe Generation

Keyboard interaction patterns on a smartphone is the input for many intelligent emotion-aware applications, such as adaptive interface, optimized keyboard layout, automatic emoji recommendation in IM applications. The simplest approach, called the Experience Sampling Method (ESM), is to systematically gather self-reported emotion labels from users, which act as the ground truth labels, and build a supervised prediction model for emotion inference. However, as manual self-reporting is fatigue-inducing and attention-demanding, the self-report requests are to be scheduled at favorable moments to ensure high fidelity response. We, in this paper, perform fine-grain keyboard interaction analysis to determine suitable probing moments. Keyboard interaction patterns, both cadence, and latency between strokes, nicely translate to frequency and time domain analysis of the patterns. In this paper, we perform a 3-week in-the-wild study (N = 22) to log keyboard interaction patterns and self-report details indicating (in)opportune probing moments. Analysis of the dataset reveals that time-domain features (e.g., session length, session duration) and frequency-domain features (e.g., number of peak amplitudes, value of peak amplitude) vary significantly between opportune and inopportune probing moments. Driven by these analyses, we develop a generalized (all-user) Random Forest based model, which can identify the opportune probing moments with an average F-score of 93%. We also carry out the explainability analysis of the model using SHAP (SHapley Additive exPlanations), which reveals that the session length and peak amplitude have strongest influence to determine the probing moments.
Critiquing for Music Exploration in Conversational Recommender Systems

Dialogue-based conversational recommender systems allow users to give language-based feedback on the recommended item, which has great potential for supporting users to explore the space of recommendations through conversation. In this work, we consider incorporating critiquing techniques into conversational systems to facilitate users’ exploration of music recommendations. Thus, we have developed a music chatbot with three system variants, which are respectively featured with three different critiquing techniques, i.e., user-initiated critiquing (UC), progressive system-suggested critiquing (Progressive SC), and cascading system-suggested critiquing (Cascading SC). We conducted a between-subject study (N=107) to compare these three types of systems with regards to music exploration in terms of user perception and user interaction. Results show that both UC and SC are useful for music exploration, while users perceive higher diversity of recommendations with the system that offers Cascading SC and perceive more serendipitous with the system that offers Progressive SC. In addition, we find that the critiquing techniques significantly moderate the relationships between some interaction metrics (e.g., number of listened songs, number of dialogue turns) and users’ perceived helpfulness and serendipity during music exploration.
Stress Management Training using Biofeedback guided by Social Agents

Coping with stress is critical to mental health. Prolonged mental stress is the psychological and physiological response to a high frequency of or continuous stressors, which has a negative impact on health. This paper presents a virtual stress management training using biofeedback derived from the cardiovascular response of the heart rate variability (HRV) with an interactive social agent as biofeedback trainer. The evaluation includes both, a subject-matter expert interview and an experiment with 71 participants. In the experiment, we compared our novel stress management training to a stress management training using stress diaries. The results indicate that our social agent-based stress management training using biofeedback significantly decreased the self-assessed stress levels immediately after the training, as well as in a socially stressful task. Moreover, we found a significant correlation between stress level and the assessment of one’s performance in a socially stressful task. Participants that received our training assessed their performance higher than participants getting stress diaries. Taken this together, our novel virtual stress management training with an interactive social agent as a trainer can be evaluated as a valid method for learning techniques on how to cope with stressful situations.
Author Reply: Aligning Social Relations With Faces, Words, and Emotions

How do facial movements and verbal statements relate to emotional processes? A familiar answer is that the primary phenomenon is an internally located emotion that may then get expressed on the face and represented in words. In this view, emotion’s social functions and effects are indirect consequences of prior intrapsychic states or events. By contrast, my target article argued that facial and verbal activity are constituents rather than consequences of the dynamic production of fundamentally relational emotions. This article clarifies this alternative position and evaluates potential counterarguments.