The Internal Circadian Clock Increases Hunger and Appetite in the Evening Independent of Food Intake and Other Behaviors

Objective: Despite the extended overnight fast, paradoxically, people are typically not ravenous in the morning and breakfast is typically the smallest meal of the day. Here we assessed whether this paradox could be explained by an endogenous circadian influence on appetite with a morning trough, while controlling for sleep/wake and fasting/feeding effects. Design and Methods We studied 12 healthy non-obese adults (6 male; age, 20–42 year) throughout a 13-day laboratory protocol that balanced all behaviors, including eucaloric meals and sleep periods, evenly across the endogenous circadian cycle. Participants rated their appetite and food preferences by visual analog scales. Results: There was a large endogenous circadian rhythm in hunger, with the trough in the biological morning (8 AM) and peak in the biological evening (8 PM; peak-to-trough amplitude=17%; P=0.004). Similarly phased significant endogenous circadian rhythms were present in appetite for sweets, salty and starchy foods, fruits, meats/poultry, food overall, and for estimates of how much food participants could eat (amplitudes 14–25%; all P < 0.05). Conclusions: In people who sleep at night, the intrinsic circadian evening peak in appetite may promote larger meals before the fasting period necessitated by sleep. Furthermore, the circadian decline in hunger across the night would theoretically counteract the fasting-induced hunger increase that could otherwise disrupt sleep

PassGAN: A Deep Learning Approach for Password Guessing

State-of-the-art password guessing tools, such as HashCat and John the Ripper, enable users to check billions of passwords per second against password hashes. In addition to performing straightforward dictionary attacks, these tools can expand password dictionaries using password generation rules, such as concatenation of words (e.g., "password123456") and leet speak (e.g., "password" becomes "p4s5w0rd"). Although these rules work well in practice, expanding them to model further passwords is a laborious task that requires specialized expertise. To address this issue, in this paper we introduce PassGAN, a novel approach that replaces human-generated password rules with theory-grounded machine learning algorithms. Instead of relying on manual password analysis, PassGAN uses a Generative Adversarial Network (GAN) to autonomously learn the distribution of real passwords from actual password leaks, and to generate high-quality password guesses. Our experiments show that this approach is very promising. When we evaluated PassGAN on two large password datasets, we were able to surpass rule-based and state-of-the-art machine learning password guessing tools. However, in contrast with the other tools, PassGAN achieved this result without any a-priori knowledge on passwords or common password structures. Additionally, when we combined the output of PassGAN with the output of HashCat, we were able to match 51%-73% more passwords than with HashCat alone. This is remarkable, because it shows that PassGAN can autonomously extract a considerable number of password properties that current state-of-the art rules do not encode.Comment: This is an extended version of the paper which appeared in NeurIPS 2018 Workshop on Security in Machine Learning (SecML'18), see https://github.com/secml2018/secml2018.github.io/raw/master/PASSGAN_SECML2018.pd

Measuring Strategic Uncertainty in Coordination Games

Lecture on the first SFB/TR 15 meeting, Gummersbach, July, 18 - 20, 2004This paper explores predictability of behavior in coordination games with multiple equilibria. In a laboratory experiment we measure subjects' certainty equivalents for three coordination games and one lottery. Attitudes towards strategic uncertainty in coordination games are related to risk aversion, experience seeking, gender and age. From the distribution of certainty equivalents among participating students we estimate probabilities for successful coordination in a wide range of coordination games. For many games success of coordination is predictable with a reasonable error rate. The best response of a risk neutral player is close to the global-game solution. Comparing choices in coordination games with revealed risk aversion, we estimate subjective probabilities for successful coordination. In games with a low coordination requirement, most subjects underestimate the probability of success. In games with a high coordination requirement, most subjects overestimate this probability. Data indicate that subjects have probabilistic beliefs about success or failure of coordination rather than beliefs about individual behavior of other players

Shaping point- and mirror-symmetric proto-planetary nebulae by the orbital motion of the central binary system

We present 3D hydrodynamical simulations of a jet launched from the secondary star of a binary system inside a proto-planetary nebula. The secondary star moves around the primary in a close eccentric orbit. From the gasdynamic simulations we compute synthetic [NII] 6583 emission maps. Different jet axis inclinations with respect to the orbital plane, as well as different orientations of the flow with respect to the observer are considered. For some parameter combinations, we obtain structures that show point- or mirror-symmetric morphologies depending on the orientation of the flow with respect to the observer. Furthermore, our models can explain some of the emission distribution asymmetries that are summarized in the classification given by Soker & hadar (2002).Comment: 15 pages, 3 figures, 2 tables, Accepted in Apj Letter

Differentially Private Exponential Random Graphs

We propose methods to release and analyze synthetic graphs in order to protect privacy of individual relationships captured by the social network. Proposed techniques aim at fitting and estimating a wide class of exponential random graph models (ERGMs) in a differentially private manner, and thus offer rigorous privacy guarantees. More specifically, we use the randomized response mechanism to release networks under $\epsilon$-edge differential privacy. To maintain utility for statistical inference, treating the original graph as missing, we propose a way to use likelihood based inference and Markov chain Monte Carlo (MCMC) techniques to fit ERGMs to the produced synthetic networks. We demonstrate the usefulness of the proposed techniques on a real data example.Comment: minor edit

Birth and early evolution of a planetary nebula

The final expulsion of gas by a star as it forms a planetary nebula --- the ionized shell of gas often observed surrounding a young white dwarf --- is one of the most poorly understood stages of stellar evolution. Such nebulae form extremely rapidly (about 100 years for the ionization) and so the formation process is inherently difficult to observe. Particularly puzzling is how a spherical star can produce a highly asymmetric nebula with collimated outflows. Here we report optical observations of the Stingray Nebula which has become an ionized planetary nebula within the past few decades. We find that the collimated outflows are already evident, and we have identified the nebular structure that focuses the outflows. We have also found a companion star, reinforcing previous suspicions that binary companions play an important role in shaping planetary nebulae and changing the direction of successive outflows.Comment: 9 pages + 3 figures. To appear in Nature, 2 April 199

Impact of Sleep and Circadian Disruption on Energy Balance and Diabetes: A Summary of Workshop Discussions

A workshop was held at the National Institute for Diabetes and Digestive and Kidney Diseases with a focus on the impact of sleep and circadian disruption on energy balance and diabetes. The workshop identified a number of key principles for research in this area and a number of specific opportunities. Studies in this area would be facilitated by active collaboration between investigators in sleep/circadian research and investigators in metabolism/diabetes. There is a need to translate the elegant findings from basic research into improving the metabolic health of the American public. There is also a need for investigators studying the impact of sleep/circadian disruption in humans to move beyond measurements of insulin and glucose and conduct more in-depth phenotyping. There is also a need for the assessments of sleep and circadian rhythms as well as assessments for sleep-disordered breathing to be incorporated into all ongoing cohort studies related to diabetes risk. Studies in humans need to complement the elegant short-term laboratory-based human studies of simulated short sleep and shift work etc. with studies in subjects in the general population with these disorders. It is conceivable that chronic adaptations occur, and if so, the mechanisms by which they occur needs to be identified and understood. Particular areas of opportunity that are ready for translation are studies to address whether CPAP treatment of patients with pre-diabetes and obstructive sleep apnea (OSA) prevents or delays the onset of diabetes and whether temporal restricted feeding has the same impact on obesity rates in humans as it does in mice

Single-mode sapphire fiber Bragg grating

We present here the inscription of single-mode waveguides with Bragg gratings in sapphire. The waveguide Bragg gratings have a novel multi-layer depressed cladding design in the 1550 nm telecommunications waveband. The Bragg gratings have a narrow bandwidth (<0.5 nm) and have survived annealing at 1000{\deg}C. The structures are inscribed with femtosecond laser direct writing, using adaptive beam shaping with a non-immersion objective. A single-mode sapphire fiber Bragg grating is created by writing a waveguide with a Bragg grating within a 425 {\mu}m diameter sapphire optical fiber, providing significant potential for accurate remote sensing in ultra-extreme environments.Comment: Submitted to Optica 12 November 202