Transport and Loss of Ring Current Electrons Inside Geosynchronous Orbit During the 17 March 2013 Storm.

Ring current electrons (1-100 keV) have received significant attention in recent decades, but many questions regarding their major transport and loss mechanisms remain open. In this study, we use the four-dimensional Versatile Electron Radiation Belt code to model the enhancement of phase space density that occurred during the 17 March 2013 storm. Our model includes global convection, radial diffusion, and scattering into the Earth's atmosphere driven by whistler-mode hiss and chorus waves. We study the sensitivity of the model to the boundary conditions, global electric field, the electric field associated with subauroral polarization streams, electron loss rates, and radial diffusion coefficients. The results of the code are almost insensitive to the model parameters above 4.5 R E R E, which indicates that the general dynamics of the electrons between 4.5 R E and the geostationary orbit can be explained by global convection. We found that the major discrepancies between the model and data can stem from the inaccurate electric field model and uncertainties in lifetimes. We show that additional mechanisms that are responsible for radial transport are required to explain the dynamics of ≥40-keV electrons, and the inclusion of the radial diffusion rates that are typically assumed in radiation belt studies leads to a better agreement with the data. The overall effect of subauroral polarization streams on the electron phase space density profiles seems to be smaller than the uncertainties in other input parameters. This study is an initial step toward understanding the dynamics of these particles inside the geostationary orbit

A Rule-Based Approach to Analyzing Database Schema Objects with Datalog

Database schema elements such as tables, views, triggers and functions are typically defined with many interrelationships. In order to support database users in understanding a given schema, a rule-based approach for analyzing the respective dependencies is proposed using Datalog expressions. We show that many interesting properties of schema elements can be systematically determined this way. The expressiveness of the proposed analysis is exemplarily shown with the problem of computing induced functional dependencies for derived relations. The propagation of functional dependencies plays an important role in data integration and query optimization but represents an undecidable problem in general. And yet, our rule-based analysis covers all relational operators as well as linear recursive expressions in a systematic way showing the depth of analysis possible by our proposal. The analysis of functional dependencies is well-integrated in a uniform approach to analyzing dependencies between schema elements in general.Comment: Pre-proceedings paper presented at the 27th International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2017), Namur, Belgium, 10-12 October 2017 (arXiv:1708.07854

When Does Paternalistic Control Positively Relate to Job Satisfaction and Citizenship Behavior in Taiwan?:The Role of Follower Expectation

Although prior research predicts mainly that followers expect leaders to exert less paternalistic control (such as emphasis on discipline, didactic instruction, and belittling followers), we argue that such an expectation may not be stable overtime or across settings. Based on the connectionist perspectives of implicit leadership theories, we propose a follower expectation model of paternalistic control, in which followers compare their perceived with expected levels of paternalistic control. Two inconsistent conditions—insufficient and excessive control—are identified, and the consistency between perceived and expected paternalistic control is predicted to relate to favorable follower outcomes. We examine this model by conducting two daily experience sampling studies in Taiwan. Our findings indicate that insufficient control is as unfavorable as excessive control in lowering followers’ job satisfaction and citizenship behavior, and this pattern is particularly salient in terms of emphasis on discipline and the belittling of followers. A supplemental, qualitative analysis additionally demonstrated the conditions under which the expectation–perception consistency regarding belittling followers relates to favorable follower responses. (PsycInfo Database Record (c) 2023 APA, all rights reserved

Germ cells commit somatic stem cells to differentiation following priming by PI3K/Tor activity in the Drosophila testis

How and when potential becomes restricted in differentiating stem cell daughters is poorly understood. While it is thought that signals from the niche are actively required to prevent differentiation, another model proposes that stem cells can reversibly transit between multiple states, some of which are primed, but not committed, to differentiate. In the Drosophila testis, somatic cyst stem cells (CySCs) generate cyst cells, which encapsulate the germline to support its development. We find that CySCs are maintained independently of niche self-renewal signals if activity of the PI3K/Tor pathway is inhibited. Conversely, PI3K/Tor is not sufficient alone to drive differentiation, suggesting that it acts to license cells for differentiation. Indeed, we find that the germline is required for differentiation of CySCs in response to PI3K/Tor elevation, indicating that final commitment to differentiation involves several steps and intercellular communication. We propose that CySC daughter cells are plastic, that their fate depends on the availability of neighbouring germ cells, and that PI3K/Tor acts to induce a primed state for CySC daughters to enable coordinated differentiation with the germline

Spanning Properties of Theta-Theta Graphs

We study the spanning properties of Theta-Theta graphs. Similar in spirit with the Yao-Yao graphs, Theta-Theta graphs partition the space around each vertex into a set of k cones, for some fixed integer k > 1, and select at most one edge per cone. The difference is in the way edges are selected. Yao-Yao graphs select an edge of minimum length, whereas Theta-Theta graphs select an edge of minimum orthogonal projection onto the cone bisector. It has been established that the Yao-Yao graphs with parameter k = 6k' have spanning ratio 11.67, for k' >= 6. In this paper we establish a first spanning ratio of $7.82$ for Theta-Theta graphs, for the same values of $k$. We also extend the class of Theta-Theta spanners with parameter 6k', and establish a spanning ratio of $16.76$ for k' >= 5. We surmise that these stronger results are mainly due to a tighter analysis in this paper, rather than Theta-Theta being superior to Yao-Yao as a spanner. We also show that the spanning ratio of Theta-Theta graphs decreases to 4.64 as k' increases to 8. These are the first results on the spanning properties of Theta-Theta graphs.Comment: 20 pages, 6 figures, 3 table

Sub 200 fs pulse generation from a graphene mode-locked fiber laser

Ultrafast fiber lasers with short pulses and broad bandwidth are in great demand for a variety of applications, such as spectroscopy, biomedical diagnosis and optical communications. In particular sub-200fs pulses are required for ultrafast spectroscopy with high temporal resolution. Graphene is an ideal ultra-wide-band saturable absorber. We report the generation of 174fs pulses from a graphene-based fiber lase

Who needs nature? The influence of employee speciesism on nature-based need satisfaction and subsequent work behavior

Scholars have long upheld the notion that exposure to nature benefits individuals. Recently, organizational researchers have theorized that these benefits extend to the workplace, leading to calls for organizations to incorporate contact with nature into employees’ jobs. However, it is unclear whether the effects of nature are strong enough to meaningfully impact employee performance, thereby justifying organizations’ investments in it. In this research, we draw on self-determination theory to develop a theoretical model predicting that exposure to nature at work satisfies employees’ psychological needs (i.e., needs for autonomy, relatedness, and competence), and positively affects their subsequent task performance and prosocial behavior. In addition, we theorize that the effects of nature on need satisfaction are weaker in employees higher on speciesism (i.e., the belief that humans are superior to other forms of life). We test these predictions with a mixed-method approach comprised of an online experiment in the United States (Study 1), a field experiment in Hong Kong (Study 2), a multi-wave, multi-source field study in Taiwan (Study 3), and a multi-wave, multi-source field study (with objective performance scores) in New Zealand (Study 4). Overall, our findings largely support our theoretical model

Graphene Q-switched, tunable fiber laser

We demonstrate a wideband-tunable Q-switched fiber laser exploiting a graphene saturable absorber. We get ~2us pulses, tunable between 1522 and 1555nm with up to~40nJ energy. This is a simple and low-cost light source for metrology, environmental sensing and biomedical diagnostics

Deep learning data augmentation for Raman spectroscopy cancer tissue classification.

Recently, Raman Spectroscopy (RS) was demonstrated to be a non-destructive way of cancer diagnosis, due to the uniqueness of RS measurements in revealing molecular biochemical changes between cancerous vs. normal tissues and cells. In order to design computational approaches for cancer detection, the quality and quantity of tissue samples for RS are important for accurate prediction. In reality, however, obtaining skin cancer samples is difficult and expensive due to privacy and other constraints. With a small number of samples, the training of the classifier is difficult, and often results in overfitting. Therefore, it is important to have more samples to better train classifiers for accurate cancer tissue classification. To overcome these limitations, this paper presents a novel generative adversarial network based skin cancer tissue classification framework. Specifically, we design a data augmentation module that employs a Generative Adversarial Network (GAN) to generate synthetic RS data resembling the training data classes. The original tissue samples and the generated data are concatenated to train classification modules. Experiments on real-world RS data demonstrate that (1) data augmentation can help improve skin cancer tissue classification accuracy, and (2) generative adversarial network can be used to generate reliable synthetic Raman spectroscopic data

Resting-state EEG power and coherence vary between migraine phases

© 2016, The Author(s). Background: Migraine is characterized by a series of phases (inter-ictal, pre-ictal, ictal, and post-ictal). It is of great interest whether resting-state electroencephalography (EEG) is differentiable between these phases. Methods: We compared resting-state EEG energy intensity and effective connectivity in different migraine phases using EEG power and coherence analyses in patients with migraine without aura as compared with healthy controls (HCs). EEG power and isolated effective coherence of delta (1–3.5 Hz), theta (4–7.5 Hz), alpha (8–12.5 Hz), and beta (13–30 Hz) bands were calculated in the frontal, central, temporal, parietal, and occipital regions. Results: Fifty patients with episodic migraine (1–5 headache days/month) and 20 HCs completed the study. Patients were classified into inter-ictal, pre-ictal, ictal, and post-ictal phases (n = 22, 12, 8, 8, respectively), using 36-h criteria. Compared to HCs, inter-ictal and ictal patients, but not pre- or post-ictal patients, had lower EEG power and coherence, except for a higher effective connectivity in fronto-occipital network in inter-ictal patients (p <.05). Compared to data obtained from the inter-ictal group, EEG power and coherence were increased in the pre-ictal group, with the exception of a lower effective connectivity in fronto-occipital network (p <.05). Inter-ictal and ictal patients had decreased EEG power and coherence relative to HCs, which were “normalized” in the pre-ictal or post-ictal groups. Conclusion: Resting-state EEG power density and effective connectivity differ between migraine phases and provide an insight into the complex neurophysiology of migraine