What roles do social media play in hurricane Ian, before, during and after the event

In recent years, natural disasters like wildfires, tsunamis, and floods have surged in both severity and frequency, causing widespread harm, including physical damage, loss of life, economic turmoil, and societal unrest. Among these disasters, hurricanes, defined by wind speeds surpassing 74 mph, pose a persistent threat, bringing hazards such as heavy rainfall and inland flooding. Hurricane Ian, one of the most significant in recent U.S. history, formed on September 23rd, hit Florida on September 28th, and dissipated on October 2nd, leaving widespread devastation. In the realm of disaster management, Location-Based Social Media (LBSM) has emerged as a crucial tool, aiding in early warnings, damage assessment, rescue coordination, and recovery evaluation. This thesis focuses on the analysis of English and Spanish tweets related to Hurricane Ian, covering the period from its formation to 50 days after its dissipation. The tweet datasets were divided into two categories: all tweets and the top 1% most shared tweets. Employing the Latent Dirichlet Allocation (LDA) model, the study unveiled prevalent themes within the tweets over different timeframes. Additionally, sentiment analysis was conducted on both English and Spanish tweet datasets, using the Valence Aware Dictionary and sEntimentReasoner (VADER) model for English tweets and Vader-multi for Spanish tweets. This aimed to capture the evolving sentiments of individuals and their emotional responses to various topics. The findings reveal Twitter's effectiveness as an early warning system and a valuable tool for risk assessment and recovery. Leading up to the hurricane's landfall, discussions mainly revolved around weather and disaster-related topics. During and after the hurricane, the focus shifted to disaster-related and situational topics. Sentiment analysis indicated a growing negativity as the storm approached, followed by a gradual return to less negative sentiments after the hurricane passed. This thesis emphasizes the significance of social media platforms as essential resources for rapid decision-making during crises, particularly when quick responses are imperative

Timing of infant formula introduction and risk of atopic diseases and being overweight during early childhood

Dietary exposure in early life, including formula feeding and early introduction of complementary foods, was considered as one of the main modifiable exposures associated with childhood allergy and obesity. During the past decades, the Chinese population has witnessed rapid economic development along with the unprecedented speed of industrialization and urbanization. Meanwhile, the consumption of infant formula has been increasing dramatically in recent decades worldwide, particularly in China. The observed remarkable growth in infant formula sales raises serious concern for child health. The research within this thesis focuses on the associations of feeding practice, especially the timing of infant formula introduction, with the development of atopic diseases and being overweight or obesity in young Chinese children. Our systematic review and meta-analysis found that relatively little high-quality evidence was identified to allow for definitive conclusions on the association between early cow’s milk or cow’s milk formula introduction and risk of allergic diseases. Our meta-analysis on this topic highlights the specific gaps in information for public recommendations regarding cow’s milk or cow’s milk formula feeding practice in an early stage of life, particularly before 3 months of age. Then, we performed the studies based on the Born in Guangzhou Cohort Study (BIGCS), a population-based birth cohort in Guangzhou, China. The results suggested that early infant formula introduction, particularly within the first 3 months of life, may increase the risk of eczema during the first year of life. Also, food introduction patterns containing early infant formula introduction were related to a higher risk of eczema by the age of 3 years regardless of whether complementary foods were introduced relatively early or late. Furthermore, the later introduction of infant formula between 4 to 6 months seems to be associated with the lower BMI, weight-for-age and weight-for-length z-scores both at 1 year and 3 years of age, compared with early introduction within the first 3 months. We also found that there may be a potential effect of early formula introduction on being persistently overweight from 1 year to 3 years old. The findings provide new evidence into the influence of formula feeding on early childhood health. The results need to be replicated in other cohorts to provide more robust evidence on the development of future health-related prevention guidelines for children

Online Bearing Remaining Useful Life Prediction Based on a Novel Degradation Indicator and Convolutional Neural Networks

In industrial applications, nearly half the failures of motors are caused by the degradation of rolling element bearings (REBs). Therefore, accurately estimating the remaining useful life (RUL) for REBs are of crucial importance to ensure the reliability and safety of mechanical systems. To tackle this challenge, model-based approaches are often limited by the complexity of mathematical modeling. Conventional data-driven approaches, on the other hand, require massive efforts to extract the degradation features and construct health index. In this paper, a novel online data-driven framework is proposed to exploit the adoption of deep convolutional neural networks (CNN) in predicting the RUL of bearings. More concretely, the raw vibrations of training bearings are first processed using the Hilbert-Huang transform (HHT) and a novel nonlinear degradation indicator is constructed as the label for learning. The CNN is then employed to identify the hidden pattern between the extracted degradation indicator and the vibration of training bearings, which makes it possible to estimate the degradation of the test bearings automatically. Finally, testing bearings' RULs are predicted by using a $\epsilon$-support vector regression model. The superior performance of the proposed RUL estimation framework, compared with the state-of-the-art approaches, is demonstrated through the experimental results. The generality of the proposed CNN model is also validated by transferring to bearings undergoing different operating conditions

Real transmission and reflection zeros of periodic structures with a bound state in the continuum

For lossless periodic structures with a proper symmetry, the transmission and reflection spectra often have peaks and dips that are truly $100\%$ and $0\%$, respectively. The full peaks and zero dips typically appear near resonant frequencies, and they are robust with respect to structural perturbations that preserve the required symmetry. However, current theories on the existence of full peaks and zero dips are incomplete and difficult to use. For periodic structures with a bound state in the continuum (BIC), we present a new theory on the existence of real transmission and reflection zeros that correspond to the zero dips in the transmission and reflection spectra. Our theory is relatively simple, complete, and easy to use. Numerical examples are presented to validate the new theory.Comment: 8 pages, 5 figure

Semi-supervised co-clustering on attributed heterogeneous information networks

trueThe embargo period should be 2 years -- not sure why under the drop down I can only select one year. Please validate.</p

PrivGraph: Differentially Private Graph Data Publication by Exploiting Community Information

Graph data is used in a wide range of applications, while analyzing graph data without protection is prone to privacy breach risks. To mitigate the privacy risks, we resort to the standard technique of differential privacy to publish a synthetic graph. However, existing differentially private graph synthesis approaches either introduce excessive noise by directly perturbing the adjacency matrix, or suffer significant information loss during the graph encoding process. In this paper, we propose an effective graph synthesis algorithm PrivGraph by exploiting the community information. Concretely, PrivGraph differentially privately partitions the private graph into communities, extracts intra-community and inter-community information, and reconstructs the graph from the extracted graph information. We validate the effectiveness of PrivGraph on six real-world graph datasets and seven commonly used graph metrics.Comment: To Appear in the 32nd USENIX Security Symposiu

Experimental study on dynamic deformation properties of muck soil under low frequency cyclic loading

A series of dynamic triaxial tests were performed to investigate the dynamic deformation properties of the muck soil, in the Pearl River Delta region of Shenzhen, China, under different consolidation ratios, loading frequencies and cyclic stress with SPAX-2000 triaxial testing system. The results showed that the initial stress-strain hysteresis curve of the muck soil under the low-frequency cyclic loading developed rapidly and the curve shape changes from sparse to tight and to slightly sparse. The cumulative plastic strain of muck soil increased nonlinearly with the dynamic stress amplitude, and there was a critical dynamic stress. As the dynamic stress amplitude reached its critical value, the strain increased sharply and the soil microstructure was destroyed. There was a frequency threshold between 0.25 Hz and 0.5 Hz, and the cumulative plastic strain development mode was from stable model to over-destructive model. The stiffness of the muck decreased gradually, and the plastic deformation increased as the number of cycles increased. Therefore, the lower the loading frequency developed, the greater the plastic deformation would be. The dynamic elastic modulus decreased as the plastic deformation increased, while the dynamic elastic modulus increased as the consolidation stress increased. Moreover, the empirical formulas of dynamic elastic modulus and plastic strain index were established with the consolidation stress ratio as the parameter, and the validity was verified by experimental data

Primordial magnetic field as a common solution of nanohertz gravitational waves and Hubble tension

The origin of interstellar and intergalactic magnetic fields is largely unknown, and the primordial magnetic fields (PMFs) produced by, e.g., phase transitions of the early Universe are expected to provide seeds for those magnetic fields. The PMFs affect the evolution of the Universe at an early time, resulting in a series of phenomena. In this work, we show that the PMF-induced turbulence can give rise to nanohertz (nHz) gravitational waves reported by several pulsar timing arrays, including NANOGrav, PPTA, EPTA, and CPTA. Using the nHz gravitational wave data, we obtain the constraints on the characteristic magnetic field strength ($B_{\rm ch}^* \sim \mathcal{O}(1)~\rm{\mu G}$) and coherent length scale ($\ell_{\rm ch}^* \sim \mathcal{O}(1)~\rm{pc}$) of PMFs, assuming a generation temperature of approximately the QCD temperature ($\sim 100$ MeV). In addition, the PMFs which evolve to the recombination era can induce baryon density inhomogeneities, and then alter the ionization process. This naturally results in an alleviation of the tension of the Hubble parameter $H_0$ and the matter clumpiness parameter $S_8$ between early and late-time measurements. Assuming an evolution form of $B_{\rm ch}\sim \ell_{\rm ch}^{-\alpha}$ from the epoch of the production of PMFs to the epoch of recombination, we find $0.91<\alpha<1.08$ (95\% credible region).Comment: 7 pages, 4 figure

Flexible PVDF-TrFE Nanocomposites with Ag-decorated BCZT Heterostructures for Piezoelectric Nanogenerator Applications

Flexible piezoelectric nanogenerators are playing an important role in delivering power to next-generation wearable electronic devices due to their high-power density and potential to create self-powered sensors for the Internet of Things. Among the range of available piezoelectric materials, poly(vinylidene fluoride-trifluoroethylene) (PVDF-TrFE)-based piezoelectric composites exhibit significant potential for flexible piezoelectric nanogenerator applications. However, the high electric fields that are required for poling cannot be readily applied to polymer composites containing piezoelectric fillers due to the high permittivity contrast between the filler and matrix, which reduces the dielectric strength. In this paper, novel Ag-decorated BCZT heterostructures were synthesized via a photoreduction method, which were introduced at a low level (3 wt %) into the matrix of PVDF-TrFE to fabricate piezoelectric composite films. The effect of Ag nanoparticle loading content on the dielectric, ferroelectric, and piezoelectric properties was investigated in detail, where a maximum piezoelectric energy-harvesting figure of merit of 5.68 × 10-12 m2/N was obtained in a 0.04Ag-BCZT NWs/PVDF-TrFE composite film, where 0.04 represents the concentration of the AgNO3 solution. Modeling showed that an optimum performance was achieved by tailoring the fraction and distribution of the conductive silver nanoparticles to achieve a careful balance between generating electric field concentrations to increase the level of polarization, while not degrading the dielectric strength. This work therefore provides a strategy for the design and manufacture of highly polarized piezoelectric composite films for piezoelectric nanogenerator applications.</p