A Latent Factor Approach for Social Network Analysis

Social network data consist of entities and the relation of information between pairs of entities. Observations in a social network are dyadic and interdependent. Therefore, making appropriate statistical inferences from a network requires specifications of dependencies in a model. Previous studies suggested that latent factor models (LFMs) for social network data can account for stochastic equivalence and transitivity simultaneously, which are the two primary dependency patterns that are observed social network data in real-world social networks. One particular LFM, the additive and multiplicative effects network model (AME) accounts for the heterogeneity of second-order dependencies at the actor level. However, all current latent variable models have not considered the heterogeneity of third-order dependencies, actor-level transitivity for example. Failure to model third-order dependency heterogeneity may result in worse fits to local network structures, which in turn may result in biased parameter inferences and may negatively influence the goodness-of-fit and prediction performance of a model. Motivated by such a gap in the literature, this dissertation proposes to incorporate a correlation structure between the sender and receiver latent factors in the AME to account for the distribution of actor-level transitivity. The proposed model is compared with the existing AME in both simulation studies real-world data. Models are evaluated via multiple goodness-of-fit techniques, including mean squared error, parameter coverage rate, information criteria, receiver-operation curve (ROC) based on K-fold cross-validation or full data, and posterior predictive checking. This work may also contribute to the literature of goodness-of-fit methods to network models, which is an area that has not been unified. Both the simulation studies and real-world data analyses showed that adding the correlation structure provides a better fit as well as higher prediction accuracy to network data. The proposed method has equal or similar performance to the AME when the underlying correlation is zero, with regard to mean-squared error of probability of ties and widely applicable information criteria. The present study did not find any significant impact of the correlation term on the node-level covariate’s coefficient estimation. Future studies include investigating more types of covariates, subgroup related covariate effects is an example

A Comparative Research on Competitiveness of Information Industry of China vs. Korea

This paper explores the competitiveness of information industry of China and Korea by means of comparative research based on the analysis of statistic data and the definition of items denoting the competitiveness. Consequently, we analyze the competitive and complementary relation of information industry of China vs. Korea, and put forward a co-operation project of China-Korea information industry ultimately

Digital LLRF system for TRIUMF ISIS buncher

The ISIS buncher system at TRIUMF operates at frequencies of 23MHz, 46MHz, and 4.6MHz. The 23MHz and 46MHz signals drive two buncher cavities, while the 4.6MHz signal drives the 5:1 selector. The previous analog-digital hybrid system has been replaced with a new digital LLRF system due to occasional drifts in the setpoints of the control loops during operation. The reference signal for the LLRF system is obtained from the pickup signal of the cyclotron's cavity, ensuring that all frequencies are synchronized with it. In the event of a spark occurring in the cyclotron's cavity, the LLRF system may lose its reference signal. To address this, a phase-locked loop with a track and hold function is designed to maintain the frequency when the reference signal is absent. The 4.6MHz frequency is derived by dividing the 23MHz reference signal frequency by 5. Designing the divide-by-5 circuitry posed specific challenges in a binary system. The LLRF system is built upon TRIUMF's versatile digital LLRF hardware system, with firmware optimized specifically for the ISIS buncher system. This paper will delve into the details of the hardware and firmware.Comment: Poster presented at LLRF Workshop 2023 (LLRF2023, arXiv: 2310.03199

Kaposi’s sarcoma-associated herpesvirus seropositivity is associated with type 2 diabetes mellitus: A case–control study in Xinjiang, China

Objective: To assess the potential relationship between Kaposi’s sarcoma-associated herpesvirus (KSHV) infection and type 2 diabetes mellitus (DM-2) in Xinjiang, China. Methods: A case–control study of consecutively included DM-2 patients and normal controls was conducted among the Uygur and Han populations in Xinjiang Uygur Autonomous Region, China. Blood samples were collected and KSHV seroprevalence, antibody titers, and viral load were investigated. Logistic regression analysis and multiple linear regression analysis were applied to explore determinants of the main outcome measures. Results: A total of 324 patients with DM-2 and 376 normal controls were included. The seroprevalence of KSHV was 49.1% (95% confidence interval (CI) 43.6–54.5%) for diabetic patients and 23.7% (95% CI 19.4– 28.0%) for the control group. After adjusting for variables of ethnicity, sex, body mass index, occupation, educational level, marital status, age, and smoking and alcohol consumption habits, the association between DM-2 and KSHV infection still existed (odds ratio (OR) 2.94, 95% CI 2.05–4.22), and the risk of KSHV infection increased with glucose concentration (OR 1.35, 95% CI 1.21–1.51). KSHV was more likely to express both the latent and lytic antigens in diabetic patients (latent: OR 3.27, 95% CI 2.25–4.75; lytic: OR 3.99, 95% CI 2.68–5.93). Antibody titers and viral load increased in patients with higher blood glucose levels (p \u3c 0.001). Conclusions: Patients with DM-2 have an elevated risk of KSHV infection. Both antibody titers and viral load increased with blood glucose levels

A Novel Non-Volatile Inverter-based CiM: Continuous Sign Weight Transition and Low Power on-Chip Training

In this work, we report a novel design, one-transistor-one-inverter (1T1I), to satisfy high speed and low power on-chip training requirements. By leveraging doped HfO2 with ferroelectricity, a non-volatile inverter is successfully demonstrated, enabling desired continuous weight transition between negative and positive via the programmable threshold voltage (VTH) of ferroelectric field-effect transistors (FeFETs). Compared with commonly used designs with the similar function, 1T1I uniquely achieves pure on-chip-based weight transition at an optimized working current without relying on assistance from off-chip calculation units for signed-weight comparison, facilitating high-speed training at low power consumption. Further improvements in linearity and training speed can be obtained via a two-transistor-one-inverter (2T1I) design. Overall, focusing on energy and time efficiencies, this work provides a valuable design strategy for future FeFET-based computing-in-memory (CiM)

ZHENG-Omics Application in ZHENG Classification and Treatment: Chinese Personalized Medicine

With the hope to provide an effective approach for personalized diagnosis and treatment clinically, traditional chinese medicine (TCM) is being paid increasing attention as a complementary and alternative medicine. It performs treatment based on ZHENG (TCM syndrome) classification, which could be identified clinical special phenotypes by symptoms and signs of patients even if they have a different disease. However, it caused controversy because ZHENG classification only depends on observation, knowledge, and clinical experience of TCM practitioners, which lacks objectivity and repeatability. Although researchers and scientists of TCM have done some work with a lot of beneficial methods, the results could not reach satisfactory with the shortcomings of generalizing the entire state of the body or ignoring the patients' feelings. By total summary, mining, and integration of existing researches, the present paper attempts to introduce a novel macro-microconcept of ZHENG-omics, with the prospect of bright future in providing an objective and repeatable approach for Chinese personalized medicine in an effective way. In this paper, we give the brief introduction and preliminary validation, and discuss strategies and system-oriented technologies for achieving this goal

Pre‐symptomatic transmission of novel coronavirus in community settings

We used contact tracing to document how COVID‐19 was transmitted across 5 generations involving 10 cases, starting with an individual who became ill on January 27. We calculated the incubation period of the cases as the interval between infection and development of symptoms. The median incubation period was 6.0 days (interquartile range, 3.5‐9.5 days). The last two generations were infected in public places, 3 and 4 days prior to the onset of illness in their infectors. Both had certain underlying conditions and comorbidity. Further identification of how individuals transmit prior to being symptomatic will have important consequences.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163478/2/irv12773.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163478/1/irv12773_am.pd

Association of C-Reactive Protein/Albumin Ratio With Mortality in Patients With Traumatic Brain Injury: A Systematic Review and Meta-Analysis

Objective: This study examines the C-reactive protein (CRP)/albumin ratio (CAR) as an inflammation-based prognostic score for predicting mortality in patients with Traumatic Brain Injury (TBI). Methods: We systematically searched the electronic databases PubMed, Embase, and Cochrane up to February 2024. Our inclusion criteria encompassed studies investigating CAR-predicted mor- tality in patients with TBI. We calculated the Odds Ratio (OR) and associated 95 % confidence intervals (95 % CI) using a random-effects model. Quality assessment of the included studies was appraised using a Newcastle–Ottawa scale. Results: A total of five studies comprising 1040 patients were included in this meta-analysis. The pooled results indicated that CAR was associated with mortality in patients with TBI (OR = 1.88, 95 % CI: 1.05–3.36, P \u3c 0.0001). The findings of subgroup analysis indicated that the relationship between CAR and mortality in patients with TBI did not vary with the severity of the condition. Conclusions: CAR emerges as a valuable prognostic tool for mortality in patients with TBI, underscoring its potential role in early risk stratification and management strategies

Integrated Optical Vortex Microcomb

The explorations of physical degrees of freedom with infinite dimensionalities, such as orbital angular momentum and frequency of light, have profoundly reshaped the landscape of modern optics with representative photonic functional devices including optical vortex emitters and frequency combs. In nanophotonics, whispering gallery mode microresonators naturally support orbital angular momentum of light and have been demonstrated as on-chip emitters of monochromatic optical vortices. On the other hand, whispering gallery mode microresonators serve as a highly efficient nonlinear optical platform for producing light at different frequencies - i.e., microcombs. Here, we interlace the optical vortices and microcombs by demonstrating an optical vortex comb on an III-V integrated nonlinear microresonator. The angular-grating-dressed nonlinear microring simultaneously emits spatiotemporal light springs consisting of 50 orbital angular momentum modes that are each spectrally addressed to the frequency components (longitudinal whispering gallery modes) of the generated microcomb. We further experimentally generate optical pulses with time-varying orbital angular momenta by carefully introducing a specific intermodal phase relation to spatiotemporal light springs. This work may immediately boost the development of integrated nonlinear/quantum photonics for exploring fundamental optical physics and advancing photonic quantum technology.Comment: To appear in Nature Photonic