How Uneven Elementary School Education Quality Leads to Social Stratification in Beijing, China

Studies on (un)evenly distributed compulsory elementary education range from inter-regions, urban-rural areas, social classes and inter-schools. The purpose of this study is to examine stratifications derived from uneven compulsory elementary education quality in Beijing, mainly about inter-school and inter- social class comparisons. Key schools, which will be illustrated in detail later, break the balance among schools, leading to many social issues, such as education stratification among students from different socio-economic classes, and among schools. Also with the unique context of Beijing, School District System adds up to problems caused by uneven compulsory elementary education quality across eight counties in Beijing City. This study is divided into three parts, the first part is the stratification in schools, mainly about their financial statistics which reflects the financial power. Financial data for two elementary schools, one key school and one ordinary one, in Haidian County demonstrates key schools attracts more money, either from parents or government. The second part is education stratification among students. To reveal that families’ socio-economic status plays a role in students’ education choices, I use hedonic pricing model to analyze school quality’s influence on real estate market in Beijing City. Further, broad survey centering on parents’ opinions in Beijing City could provide better understanding of the status quo of compulsory elementary education stratification among students. It is the goal of this study to provide planners, policy makers, and future researchers some insights on the socio-economic impact of key schools in Beijing

On the stability and instability of Kelvin-Stuart cat's eyes flows

Kelvin-Stuart vortices are classical mixing layer flows with many applications in fluid mechanics, plasma physics and astrophysics. We prove that the whole family of Kelvin-Stuart vortices is nonlinearly stable for co-periodic perturbations, and linearly unstable for multi-periodic or modulational perturbations. This verifies a long-standing conjecture since the discovery of the Kelvin-Stuart cat's eyes flows in the 1960s. Kelvin-Stuart cat's eyes also appear as magnetic islands which are magnetostatic equilibria for the 2D ideal MHD equations in plasmas. We prove nonlinear stability of Kelvin-Stuart magnetic islands for co-periodic perturbations, and give the first rigorous proof of the coalescence instability, which is important for magnetic reconnection.Comment: 122 page

Adaptive Fuzzy Sliding Mode Controller for Attitude Coordinated Control in Spacecraft Formation

The attitude coordinated control problem of a spacecraft formation in leader-follower approach is considered in this paper. An adaptive fuzzy sliding mode control scheme is designed to achieve tracking and synchronization in spacecraft formation in the presence of model uncertainties and external disturbances. The proposed control law consists of two parts: equivalent control and switching control. In order to attenuate high-frequency chattering caused by the switching control, the adaptive fuzzy control is utilized to approximate the sign function of the switching control. Moreover, fuzzy rules are employed to smooth the switching control based on the sliding surface.Lyapunov theory is applied to proof the stability of the closedloop system. Finally, simulation results and comparative analysisare carried out to demonstrate the effectiveness of the proposed method

Fuzzy Authorization for Cloud Storage

It is widely accepted that OAuth is the most popular authorization scheme adopted and implemented by industrial and academic world, however, it is difficult to adapt OAuth to the situation in which online applications registered with one cloud party intends to access data residing in another cloud party. In this thesis, by leveraging Ciphertext-Policy Attribute Based Encryption technique and Elgamal-like mask over the protocol, we propose a reading authorization scheme among diverse clouds, which is called fuzzy authorization, to facilitate an application registered with one cloud party to access to data residing in another cloud party. More importantly, we enable the fuzziness of authorization thus to enhance the scalability and flexibility of file sharing by taking advantage of the innate connections of Linear Secret-Sharing Scheme and Generalized Reed Solomon code. Furthermore, by conducting error checking and error correction, we eliminate operation of satisfying a access tree. In addition, the automatic revocation is realized with update of TimeSlot attribute when data owner modifies the data. We prove the security of our schemes under the selective-attribute security model. The protocol flow of fuzzy authorization is implemented with OMNET++ 4.2.2 and the bi-linear pairing is realized with PBC library. Simulation results show that our scheme can achieve fuzzy authorization among heterogeneous clouds with security and efficiency.1 yea

Predictors of Pathology Smartphone Use: Reward Processing, Depressive Symptoms, and Self-Control

The widespread adoption of smartphones that allow us to work, engage with friends and family, and pursue leisure activities has been associated with the emergence of pathological smartphone use wherein individuals experience anxiety and depressive symptoms when separated from their devices and may be more likely to engage in risky behavior while using their phone. Consistent with the broader literature on behavioral addictions, smartphone pathology is associated with increased depressive symptoms and decreased self-control. The current study builds upon a foundation of evidence from studies of pathological technology use including video games, the Internet, and social media to explore the association between the neural correlates of reward processing and smartphone pathology, depressive symptoms, and self-control. Our findings reveal that greater levels of smartphone pathology are associated with decreased neural activity related to the processing of both gains and losses when the individual is the agent of choice in a simple gambling task. Additionally, we replicate the association between depressive symptoms, self-control and smartphone pathology; and further demonstrate that reward processing represents a unique predictor of pathology beyond any shared association with depressive symptoms and self-control

Bidirectional correlation between gastroesophageal reflux disease and sleep problems: a systematic review and meta-analysis

Objectives Gastroesophageal reflux disease (GERD) and sleep problems are highly prevalent among the general population. Both them are associated with a variety of psychiatric disorders such as depression and anxiety, which is highlighting an underexplored connection between them. This meta-analysis aims to explore the association between sleep problems and GERD. Methods We conducted a comprehensive search on PubMed, Cochrane Library, Embase, and Web of Science, using Medical Subject Headings (MeSH) and keywords, covering articles from the inception of the databases until August 2023. Stata statistical software, version 14.0, was utilized for all statistical analyses. A fixed-effects model was applied when p > 0.1 and I2 ≤ 50%, while a random-effects model was employed for high heterogeneity (p 50%). Funnel plots and Egger’s test were used to assess publication bias. Results Involving 22 studies, our meta-analysis revealed that insomnia, sleep disturbance, or short sleep duration significantly increased the risk of GERD (OR = 2.02, 95% CI [1.64–2.49], p < 0.001; I2 = 66.4%; OR = 1.98, 95% CI [1.58–2.50], p < 0.001, I2 = 50.1%; OR = 2.66, 95% CI [2.02–3.15], p < 0.001; I2 = 62.5%, respectively). GERD was associated with an elevated risk of poor sleep quality (OR = 1.47, 95% CI [1.47–1.79], p < 0.001, I2 = 72.4%), sleep disturbance (OR = 1.47, 95% CI [1.24–1.74], p < 0.001, I2 = 71.6%), or short sleep duration (OR = 1.17, 95% CI [1.12–1.21], p < 0.001, I2 = 0). Conclusion This meta-analysis establishes a bidirectional relationship between four distinct types of sleep problems and GERD. The findings offer insights for the development of innovative approaches in the treatment of both GERD and sleep problems

Superconductivity at 32K and anisotropy in Tl0.58Rb0.42Fe1.72Se2 crystals

Single crystals of Tl0.58Rb0.42Fe1.72Se2 are successfully grown with the superconducting transition temperatures Tconset=32K and Tczero=31.4K. The Hall coefficient exhibits a multi-band behavior, which is very similar to that of all other Fe-based superconductors. We found that the susceptibility at the normal state decreases with decreasing the temperature, indicating a strong antiferromagnetic (AFM) spin fluctuation at the normal state, which might be related to the superconductivity (SC). We also determined the upper critical fields in ab-plane and along c-axis. The anisotropy of the superconductivity determined by the ratio of Hc2ab and Hc2c is estimated to 5.0, which is larger than that in (Ba,K)Fe2As2 and BaFe2-xCoxAs2, but smaller than that in cuprate superconductors.Comment: 4 pages, 4 figure

You Do (Not) Belong Here: Detecting DPI Evasion Attacks with Context Learning

As Deep Packet Inspection (DPI) middleboxes become increasingly popular, a spectrum of adversarial attacks have emerged with the goal of evading such middleboxes. Many of these attacks exploit discrepancies between the middlebox network protocol implementations, and the more rigorous/complete versions implemented at end hosts. These evasion attacks largely involve subtle manipulations of packets to cause different behaviours at DPI and end hosts, to cloak malicious network traffic that is otherwise detectable. With recent automated discovery, it has become prohibitively challenging to manually curate rules for detecting these manipulations. In this work, we propose CLAP, the first fully-automated, unsupervised ML solution to accurately detect and localize DPI evasion attacks. By learning what we call the packet context, which essentially captures inter-relationships across both (1) different packets in a connection; and (2) different header fields within each packet, from benign traffic traces only, CLAP can detect and pinpoint packets that violate the benign packet contexts (which are the ones that are specially crafted for evasion purposes). Our evaluations with 73 state-of-the-art DPI evasion attacks show that CLAP achieves an Area Under the Receiver Operating Characteristic Curve (AUC-ROC) of 0.963, an Equal Error Rate (EER) of only 0.061 in detection, and an accuracy of 94.6% in localization. These results suggest that CLAP can be a promising tool for thwarting DPI evasion attacks.Comment: 12 pages, 12 figures; accepted to ACM CoNEXT 202