Subnetwork Estimation for Spatial Autoregressive Models in Large-scale Networks

Large-scale networks are commonly encountered in practice (e.g., Facebook and Twitter) by researchers. In order to study the network interaction between different nodes of large-scale networks, the spatial autoregressive (SAR) model has been popularly employed. Despite its popularity, the estimation of a SAR model on large-scale networks remains very challenging. On the one hand, due to policy limitations or high collection costs, it is often impossible for independent researchers to observe or collect all network information. On the other hand, even if the entire network is accessible, estimating the SAR model using the quasi-maximum likelihood estimator (QMLE) could be computationally infeasible due to its high computational cost. To address these challenges, we propose here a subnetwork estimation method based on QMLE for the SAR model. By using appropriate sampling methods, a subnetwork, consisting of a much-reduced number of nodes, can be constructed. Subsequently, the standard QMLE can be computed by treating the sampled subnetwork as if it were the entire network. This leads to a significant reduction in information collection and model computation costs, which increases the practical feasibility of the effort. Theoretically, we show that the subnetwork-based QMLE is consistent and asymptotically normal under appropriate regularity conditions. Extensive simulation studies, based on both simulated and real network structures, are presented

Distributed Logistic Regression for Massive Data with Rare Events

Large-scale rare events data are commonly encountered in practice. To tackle the massive rare events data, we propose a novel distributed estimation method for logistic regression in a distributed system. For a distributed framework, we face the following two challenges. The first challenge is how to distribute the data. In this regard, two different distribution strategies (i.e., the RANDOM strategy and the COPY strategy) are investigated. The second challenge is how to select an appropriate type of objective function so that the best asymptotic efficiency can be achieved. Then, the under-sampled (US) and inverse probability weighted (IPW) types of objective functions are considered. Our results suggest that the COPY strategy together with the IPW objective function is the best solution for distributed logistic regression with rare events. The finite sample performance of the distributed methods is demonstrated by simulation studies and a real-world Sweden Traffic Sign dataset

Driving mechanism of consumer migration behavior under the COVID-19 pandemic

IntroductionChina is now in the post-period of COVID-19 epidemic prevention and control. While facing normalized epidemic prevention and control, consumers behavioral intention and decision-making will still be influenced by the epidemic's development and the implementation of specific epidemic prevention measures in the medium to long term. With the impact of external epidemic prevention environment and measures, consumers' channel behavior has changed. How to better promote channel integration by adopting consumers' channel migration behavior is important for channel coordination strategies.MethodsThis paper takes fresh product retailing under normal epidemic prevention and control as an example and examines the change in channel migration behavior. Based on the value-based adoption model (VAM), this paper discusses the influence of channel characteristics and channel switching costs on channel migration intention, the mediating effect of perceived value between various influencing factors and channel migration intention, and the moderating effect of channel switching cost on perceived value and channel migration intention. Thus, an empirical study was carried out with 292 samples to verify the hypotheses.ResultsThe results show that under normal epidemic prevention and control, the influencing factors in the VAM model have a significant impact on channel migration intention; perceived value plays a mediating role between various influencing factors and channel migration intention.DiscussionsThe COVID-19 pandemic has had a significant effect on daily life and purchasing behavior. In the context of this pandemic, we have confirmed that consumers will probably change to other retailers when the usefulness, entertainment, and cost meet their expectation for purchasing fresh products. Channel characteristics have versatile features, such as channel structure and supply chain mode, which affect consumer behaviors in different ways. The perceived value comes from expectations and experience. Retailers should try to keep their products fresh and provide consumers with a high-level shopping experience during sale

Trajectories of the Hippocampal Subfields Atrophy in the Alzheimer’s Disease: A Structural Imaging Study

BackgroundThe hippocampus and hippocampal subfields have been found to be diversely affected in Alzheimer’s Disease (AD) and early stages of Alzheimer’s disease by neuroimaging studies. However, our knowledge is still lacking about the trajectories of the hippocampus and hippocampal subfields atrophy with the progression of Alzheimer’s disease.ObjectiveTo identify which subfields of the hippocampus differ in the trajectories of Alzheimer’s disease by magnetic resonance imaging (MRI) and to determine whether individual differences on memory could be explained by structural volumes of hippocampal subfields.MethodsFour groups of participants including 41 AD patients, 43 amnestic mild cognitive impairment (aMCI) patients, 35 subjective cognitive decline (SCD) patients and 42 normal controls (NC) received their structural MRI brain scans. Structural MR images were processed by the FreeSurfer 6.0 image analysis suite to extract the hippocampus and its subfields. Furthermore, we investigated relationships between hippocampal subfield volumes and memory test variables (AVLT-immediate recall, AVLT-delayed recall, AVLT-recognition) and the regression model analyses were controlled for age, gender, education and eTIV.ResultsCA1, subiculum, presubiculum, molecular layer and fimbria showed the trend toward significant volume reduction among four groups with the progression of Alzheimer’s disease. Volume of left subiculum was most strongly and actively correlated with performance across AVLT measures.ConclusionThe trend changes in the hippocampus subfields and further illustrates that SCD is the preclinical stage of AD earlier than aMCI. Future studies should aim to associate the atrophy of the hippocampal subfields in SCD with possible conversion to aMCI or AD with longitudinal design

COVID-19 Shock and the Time-Varying Volatility Spillovers Among the Energy and Precious Metals Markets: Evidence From A DCC-GARCH-CONNECTEDNESS Approach

The outbreak of the COVID-19 epidemic intensified the volatility of commodity markets (the energy and precious metals markets), which created a significant negative impact on the volatility spillovers among these markets. It may also have triggered a new volatility risk contagion. In this paper, we introduce the DCC-GARCH-CONNECTEDNESS approach to explore the volatility spillover level and multi-level spillover structure characteristics among the commodity markets before and during the COVID-19 epidemic in order to clarify the new volatility risk contagion patterns across the markets. The results implied several conclusions. (i) The COVID-19 epidemic has significantly improved the total volatility spillover level of the energy and precious metals markets and has enhanced the risk connectivity among the markets. (ii) The COVID-19 epidemic has amplified the volatility of the crude oil market, making it the main volatility spillover market, namely the source of volatility risk contagion. (iii) The COVID-19 epidemic outbreak enhanced the external risk absorption capacity of the natural gas and silver markets, and the absorption level of the external volatility spillover improved significantly. Furthermore, the risk absorption capacity of the gold market weakened, while the gold market has remained the endpoint of external volatility risk during the epidemic and has acted as a risk stabilizer. (iv) The volatility spillover among markets has clear time-varying characteristics and a positive connectedness with the severity of the COVID-19 epidemic. As the severity of the COVID-19 epidemic increases, the volatility risk connectivity among the markets rapidly increases

Systems-Mapping of Herbal Effects on Complex Diseases Using the Network-Perturbation Signatures

The herbs have proven to hold great potential to improve people's health and wellness during clinical practice over the past millennia. However, herbal medicine for the personalized treatment of disease is still under investigation owing to the complex multi-component interactions in herbs. To reveal the valuable insights for herbal synergistic therapy, we have chosen Traditional Chinese Medicine (TCM) as a case to illustrate the art and science behind the complicated multi-molecular, multi-genes interaction systems, and how the good practices of herbal combination therapy are applicable to personalized treatment. Here, we design system-wide interaction map strategy to provide a generic solution to establish the links between diseases and herbs based on comprehensive testing of molecular signatures in herb-disease pairs. Firstly, we integrated gene expression profiles from 189 diseases to characterize the disease-pathological feature. Then, we generated the perturbation signatures from the huge chemical informatics data and pharmacological data for each herb, which were represented the targets affected by the ingredients in the herb. So that we could assess the effects of herbs on the individual. Finally, we integrated the data of 189 diseases and 502 herbs, yielding the optimal herbal combinations for the diseases based on the strategy, and verifying the reliability of the strategy through the permutation testing and literature verification. Furthermore, we propose a novel formula as a candidate therapeutic drugs of rheumatoid arthritis and demonstrate its therapeutic mechanism through the systematic analysis of the influencing targets and biological processes. Overall, this computational method provides a systematic approach, which blended herbal medicine and omics data sets, allowing for the development of novel drug combinations for complex human diseases

Longitudinal measurement invariance of the Child Problematic Trait Inventory in older Chinese children

The Child Problematic Traits Inventory (CPTI) is a newly developed informant-rated instrument to measure psychopathic traits during early childhood. The aim of this study was to examine the longitudinal measurement invariance of the CPTI in a group of Chinese schoolchildren. Mothers of 585 children aged 8 to 12 years (50% girls) completed the CPTI twice with one-year interval. Confirmatory factor analyses showed that the CPTI had strict invariance (i.e., equality of factor patterns, loadings, intercepts, and item uniqueness) across time. Furthermore, the internal consistencies for the CPTI subscales were good at both time points and the stability coefficients over time were moderate. Findings suggest that, in children aged 8 to 12 years old, changes in CPTI scores across time can be attributed to actual changes in the child’s psychopathic personality

Quantitative structural analysis of hemifacial microsomia mandibles in different age groups

IntroductionThis study aims to quantitively analyze mandibular ramus and body deformities, assessing the asymmetry and progression in different components.MethodsThis is a retrospective study on hemifacial microsomia children. They were divided into mild/severe groups by Pruzansky-Kaban classification and into three age groups (<1 year,1–5 years, 6–12 years old). Linear and volumetric measurements of the ramus and the body were collected via their preoperative imaging data to compare between the different sides and severities, using independent and paired tests, respectively. The progression of asymmetry was assessed by changes in affected/contralateral ratios with age using multi-group comparisons.ResultsTwo hundred and ten unilateral cases were studied. Generally, the affected ramus and body were significantly smaller than those on the contralateral side. Linear measurements on the affected side were shorter in the severe group. Regarding affected/contralateral ratios, the body was less affected than the ramus. Progressively decreased affected/contralateral ratios of body length, dentate segment volume, and hemimandible volume were found.DiscussionThere were asymmetries in mandibular ramus and body regions, which involved the ramus more. A significant contribution to progressive asymmetry from the body suggests treatment focus in this region

Dielectric barrier discharge-based defect engineering method to assist flash sintering

Oxygen vacancy OV plays an important role in a flash sintering (FS) process. In defect engineering, the methods of creating oxygen vacancy defects include doping, heating, and etching, and all of them often have complex processes or equipment. In this study, we used dielectric barrier discharge (DBD) as a new defect engineering technology to increase oxygen vacancy concentrations of green billets with different ceramics (ZnO, TiO2, and 3 mol% yttria-stabilized zirconia (3YSZ)). With an alternating current (AC) power supply of 10 kHz, low-temperature plasma was generated, and a specimen could be treated in different atmospheres. The effect of the DBD treatment was influenced by atmosphere, treatment time, and voltage amplitude of the power supply. After the DBD treatment, the oxygen vacancy defect concentration in ZnO samples increased significantly, and a resistance test showed that conductivity of the samples increased by 2–3 orders of magnitude. Moreover, the onset electric field (E) of ZnO FS decreased from 5.17 to 0.86 kV/cm at room temperature (RT); while in the whole FS, the max power dissipation decreased from 563.17 to 27.94 W. The defect concentration and conductivity of the green billets for TiO2 and 3YSZ were also changed by the DBD, and then the FS process was modified. It is a new technology to treat the green billet of ceramics in very short time, applicable to other ceramics, and beneficial to regulate the FS process