Digital Technology-driven Business Model Innovations: A Bibliometric Analysis

With the advent of the data age, digital technology has been widely used in business model innovation. To understand the current research situation in the field of digital technology-driven business model innovation and reveal the knowledge structure, research hotspots, and development trends in this research field, this paper adopts statistical analysis, co-citation analysis, cluster analysis and other methods to carry out bibliometric analysis and knowledge mapping on the relevant literature included in the Web of Science database. The research results show that customer relationship management, digital economy and financial service system, sustainable development and digital service innovation, and the competition and cooperation mechanism of enterprises are hot topics in this field. Moreover, digital platform, firm performance, and value creation are the main research directions in the future

Self-Actuated, Thermo-Responsive Hydrogel Valves for Lab on a Chip

An easy to fabricate, thermally-actuated, self-regulated hydrogel valve for flow control in pneumatically driven, microfluidic systems is described. This microvalve takes advantage of the properties of the hydrogel, poly(N-isopropylacrylamide), as well as the aqueous fluid itself to realize flow control. The valve was designed for use in a diagnostic system fabricated with polycarbonate and aimed at the detection of pathogens in oral fluids at the location of the sample collection. The paper describes the construction and characterization of the hydrogel valves and their application for flow control, sample and reagent metering, sample distribution into multiple analysis paths, and the sealing of a polymerase chain reaction (PCR) reactor to suppress bubble formation. The hydrogel-based flow control is electronically addressable, does not require any moving parts, introduces minimal dead volume, is leakage and contaminant free, and is biocompatible

Secure Analysis of Multi-Antenna Cooperative Networks with Residual Transceiver HIs and CEEs

In this paper, we investigate the secure performance of multi-antenna decode-and-forward (DF) relaying networks where the Nakagami-m fading channel is taken into account. In practice, the joint impact of residual transceiver hardware impairments (HIs) and channel estimation errors (CEEs) on the outage probability and intercept probability is taken into account. Considering HIs and CEEs, an optimal transmit antenna selection (OTAS) scheme is proposed to enhance the secure performance and then a collaborative eavesdropping scheme is proposed. Additionally, we present main channel capacity and intercept capacity of the multi-antenna DF relaying networks. More specifically, we derive exact closed-form expressions for the outage and intercept probabilities. To obtain useful insights into implications of parameters on the secure performance, the asymptotic behaviors for the outage probability are examined in the high signal-to-noise ratio (SNR) regime and the diversity orders are obtained and discussed. Simulation results confirm the analytical derivations and demonstrate that: 1) As the power distribution coefficient increases, OP decreases, while IP increases; 2) There exist error floors for the outage probability at high SNRs, which is determined by CEEs; 3) The secure performance can be improved by increasing the number of source antennas and artificial noise quantization coefficient, while as the number of eavesdropping increases, the security performance of the system is reduced; 4) There is a trade-off between the outage probability and intercept probability

The Minimum-Norm Least Squares Solutions to Quaternion Tensor Systems

In this paper, we investigate the minimum-norm least squares solution to a quaternion tensor system A1*NX1=C1,A1*NX2+A2*NX3=C2,E1*NX1*MF1+E1*NX2*MF2+E2*NX3*MF2=D by using the Moore–Penrose inverses of block tensors. As an application, we discuss the quaternion tensor system A*NX=C,E*NX*MF=D for minimum-norm least squares reducible solutions. To illustrate the results, we present an algorithm and a numerical example