Leveraging trans-ethnic genetic risk scores to improve association power for complex traits in underrepresented populations.

Trans-ethnic genome-wide association studies have revealed that many loci identified in European populations can be reproducible in non-European populations, indicating widespread trans-ethnic genetic similarity. However, how to leverage such shared information more efficiently in association analysis is less investigated for traits in underrepresented populations. We here propose a statistical framework, trans-ethnic genetic risk score informed gene-based association mixed model (GAMM), by hierarchically modeling single-nucleotide polymorphism effects in the target population as a function of effects of the same trait in well-studied populations. GAMM powerfully integrates genetic similarity across distinct ancestral groups to enhance power in understudied populations, as confirmed by extensive simulations. We illustrate the usefulness of GAMM via the application to 13 blood cell traits (i.e. basophil count, eosinophil count, hematocrit, hemoglobin concentration, lymphocyte count, mean corpuscular hemoglobin, mean corpuscular hemoglobin concentration, mean corpuscular volume, monocyte count, neutrophil count, platelet count, red blood cell count and total white blood cell count) in Africans of the UK Biobank (n = 3204) while utilizing genetic overlap shared in Europeans (n = 746 667) and East Asians (n = 162 255). We discovered multiple new associated genes, which had otherwise been missed by existing methods, and revealed that the trans-ethnic information indirectly contributed much to the phenotypic variance. Overall, GAMM represents a flexible and powerful statistical framework of association analysis for complex traits in underrepresented populations by integrating trans-ethnic genetic similarity across well-studied populations, and helps attenuate health inequities in current genetics research for people of minority populations.

Economical bluetooth low energy-based telemetry system with combined data processing method for long-term laboratory animal monitoring for biological rhythm research.

A telemetry system based on Bluetooth Low Energy (BLE) was constructed to simultaneously collect locomotor activity and physiological signals of small animal cohorts for circadian rhythm experiments; it consists of miniature transmitters and mobile phone with customized App. The continuous sampling signals obtained from the 3-axis acceleration and temperature sensors in the transmitters are sent to the mobile phone in real-time through Internet of Things (IoT) for temporary storage and then imported into the computer for summary and rhythm analysis by the general open-source mathematical software. Unlike expensive and complicated commercial telemetry systems with industrial wireless standards, no special data receivers and software are needed. In our validation experiment, six rats were divided into two groups under natural dark and light-dark cycles. For two consecutive weeks, the transmitter mounted on the head of the rat-recorded locomotor activity, skin temperature, and ambient temperature of each rat at a frequency of 6 Hz. After processing with Local Weighted Regression Scatter Smoothing (LOWESS) and Fast Fourier Transform (FFT) filtering, single cosinor and multi-components cosinor were then used to assess and characterize the circadian rhythm. The results showed that the rhythm values of the two groups of rats coincided with the corresponding light-dark cycle, and that the system was robust to data loss and error from BLE communication failures. Therefore, the proposed system provides a light-weight framework for long-term circadian rhythm monitoring in free-moving rodents to further simplify and promote experimental chronobiology animal studies.

Piezoelectric Transducers for Structural Health Monitoring of Joint Structures in Cylinders: A Wave-Based Design Approach.

Joint structures, such as riveting, hinges, and flanges, are widely used in complex mechanical systems. A small unexpected change of a joint can lead to complicated wave-scattering in its connected waveguides. The conversion between wave modes can be used to quantify the variation of the connection status of joints. This gives rise to the challenge of exciting and sensing only one specific wave mode in practice. In this paper, transmitted wave amplitudes of a flange joint are first calculated by the wave finite element method (WFEM) to study the quantitative relationship between the local stiffness changes of the damaged site and the wave-mode conversion. Wave-mode piezoelectric transducers are subsequently designed for torsional, longitudinal, and flexural waves in cylindrical waveguides. The idea is to use the distribution and interconnection of the piezoelectric materials to cancel the charge contributed from the non-targeting waves. We conducted numerical simulations to demonstrate the selective coupling features of the designed wave transducers and found difference of several orders of magnitude in voltages between targeting wave mode and other wave modes. Four selected wave transducers were then extended to monitor the connection status of the flange. The wave-scattering features in the simulation and WFEM were verified to be in good agreement.

Market segmentation and industry overcapacity considering input resources and environmental costs through the lens of governmental intervention.

The problems with China's regional industrial overcapacity are often influenced by local governments. This study constructs a framework that includes the resource and environmental costs to analyze overcapacity using the non-radial direction distance function and the price method to measure industrial capacity utilization and market segmentation in 29 provinces in China from 2002 to 2014. The empirical analysis of the spatial panel econometric model shows that (1) the industrial capacity utilization in China's provinces has a ladder-type distribution with a gradual decrease from east to west and there is a severe overcapacity in the traditional heavy industry areas; (2) local government intervention has serious negative effects on regional industry utilization and factor market segmentation more significantly inhibits the utilization rate of regional industry than commodity market segmentation; (3) economic openness improves the utilization rate of industrial capacity while the internet penetration rate and regional environmental management investment have no significant impact; and(4) a higher degree of openness and active private economic development have a positive spatial spillover effect, while there is a significant negative spatial spillover effect from local government intervention and industrial structure sophistication. This paper includes the impact of resources and the environment in overcapacity evaluations, which should guide sustainable development in emerging economies.