Periodicities in the occurrence of aurora as indicators of solar variability

A compilation of records of the aurora observed in China from the Time of the Legends (2000 - 3000 B.C.) to the mid-18th century has been used to infer the frequencies and strengths of solar activity prior to modern times. A merging of this analysis with auroral and solar activity patterns during the last 200 years provides basically continuous information about solar activity during the last 2000 years. The results show periodicities in solar activity that contain average components with a long period (approx. 412 years), three middle periods (approx. 38 years, approx. 77 years, and approx. 130 years), and the well known short period (approx. 11 years)

IT\u27S ALL ABOUT BALANCE: PROPENSITY SCORE MATCHING IN THE CONTEXT OF COMPLEX SURVEY DATA

Many research studies aim to draw causal inferences using data from large, nationally representative survey samples, and many of these studies use propensity score matching to make those causal inferences as rigorous as possible given the non-experimental nature of the data. However, very few applied studies are careful about incorporating the survey design with the propensity score analysis, which may mean that the results don’t generate population inferences. This may be because few methodological studies examine how to best combine these methods. Furthermore, even fewer of the methodological studies incorporate different non-response mechanisms in their analysis. This study examines methods for how to handle survey weights in propensity score matching analyses of survey data, under diferent non-response mechanisms. Based on the results from Monte Carlo simulations implemented on synthetic data as well as a data based application we developed suggestions regarding the implementation of propensity score methods to make causal inferences relevant to the target population of a sample survey. Our main conclusions are: (1) whether the survey weights are incorporated in the estimation of the propensity score does not impact estimation of the population treatment effect, as long as good population balance is achieved across confounders, (2) survey weights must be taken into account in the outcome analysis and (3) transfer of survey weights (i.e., matched comparison units are assigned the sampling weight of the treated unit they have been matched to) can be benefcial under certain non-response mechanisms

Optimization of Protein-Protein Interaction Measurements for Drug Discovery Using AFM Force Spectroscopy

Increasingly targeted in drug discovery, protein-protein interactions challenge current high throughput screening technologies in the pharmaceutical industry. Developing an effective and efficient method for screening small molecules or compounds is critical to accelerate the discovery of ligands for enzymes, receptors and other pharmaceutical targets. Here, we report developments of methods to increase the signal-to-noise ratio (SNR) for screening protein-protein interactions using atomic force microscopy (AFM) force spectroscopy. We have demonstrated the effectiveness of these developments on detecting the binding process between focal adhesion kinases (FAK) with protein kinase B (Akt1), which is a target for potential cancer drugs. These developments include optimized probe and substrate functionalization processes and redesigned probe-substrate contact regimes. Furthermore, a statistical-based data processing method was developed to enhance the contrast of the experimental data. Collectively, these results demonstrate the potential of the AFM force spectroscopy in automating drug screening with high throughput

Salient Object Detection via Integrity Learning

Albeit current salient object detection (SOD) works have achieved fantastic progress, they are cast into the shade when it comes to the integrity of the predicted salient regions. We define the concept of integrity at both the micro and macro level. Specifically, at the micro level, the model should highlight all parts that belong to a certain salient object, while at the macro level, the model needs to discover all salient objects from the given image scene. To facilitate integrity learning for salient object detection, we design a novel Integrity Cognition Network (ICON), which explores three important components to learn strong integrity features. 1) Unlike the existing models that focus more on feature discriminability, we introduce a diverse feature aggregation (DFA) component to aggregate features with various receptive fields (i.e.,, kernel shape and context) and increase the feature diversity. Such diversity is the foundation for mining the integral salient objects. 2) Based on the DFA features, we introduce the integrity channel enhancement (ICE) component with the goal of enhancing feature channels that highlight the integral salient objects at the macro level, while suppressing the other distracting ones. 3) After extracting the enhanced features, the part-whole verification (PWV) method is employed to determine whether the part and whole object features have strong agreement. Such part-whole agreements can further improve the micro-level integrity for each salient object. To demonstrate the effectiveness of ICON, comprehensive experiments are conducted on seven challenging benchmarks, where promising results are achieved

Spin Alignment of Vector Mesons in Non-central A+A Collisions

We discuss the consequence of global polarization of the produced quarks in non-central heavy-ion collisions on the spin alignment of vector mesons. We show that the alignment is quite different for different hadronization scenarios. These results can be tested directly by measuring the vector mesons' alignment through angular distributions of the decay products with respect to the reaction plane. Such angular distributions will give rise to azimuthal anisotropy $v_2$ of the decay products in the collision frame. Constraints provided by the data on the azimuthal anisotropy of hadron spectra at RHIC points to a quark recombination scenario of hadronization.Comment: 6 pages in latex with two postscript figure