Robust Connectivity With Multiple Directional Antennas for Vehicular Communications

For critical vehicular communication services, such as traffic safety and traffic efficiency, it is advisable to design systems with robustness as the main criteria, possibly at the price of reduced peak performance and efficiency. We describe a simple, low-cost method for combining the output of L directional (i.e., not omnidirectional) antennas to the input of a single-port receiver with the aim to guarantee robustness, i.e., to minimize the probability that K consecutive packets arriving from the worst-case angle-of-arrival are decoded incorrectly. To minimize complexity, the combining network does not estimate or use channel state information. The combining network consists of L-1 analog phase shifters whose phases are affine functions of time. For a general Lłe K and when the packet error probability decays exponentially with the received SNR, the optimum slopes of the affine functions can be computed by solving an optimization problem that depends on the antenna far-field functions. We provide analytical solutions for the special case of L=2 and 3 antennas, which turns out to be independent of the antenna far-field functions and placement on a vehicle. In an experimental setup consisting of two monopole antennas mounted on the roof of a Volvo XC90, the proposed combining method is shown to give significant performance gains, compared to using any one of the antennas

A Simple Method for Robust Vehicular Communication with Multiple Nonideal Antennas

For critical vehicular communication services, such as traffic safety and traffic efficiency, it is advisable to design systems with robustness as the main criteria, possibly at the price of reduced peak performance and efficiency. We describe a simple, low-cost method for combining the output of L nonideal (i.e., nonisotropic) antennas to the input signal to a single-port receiver with the aim to guarantee robustness, i.e., to minimize the probability that K consecutive packets arriving from the worst-case angle-of-arrival are decoded incorrectly. To minimize complexity, the combining network does not estimate or use channel state information (complex channel gains, noise levels, etc.). The combining network consists of L-1 analog phase shifters whose phases are affine functions of time. For a general L\ua0and the case when the packet error probability decays exponentially with the received SNR, the optimum slopes of the affine functions can be computed by solving an optimization problem that depends on the antenna far field functions. We provide an analytical solution for the special case of L\ua0= 2 antennas, which turns out to be independent of the antenna patterns. In an experimental setup consisting of two monopole antennas mounted on the roof of a Volvo XC90, the proposed combining method is shown to give significant performance gains compared to using just one of the antennas

"Open Innovation" and "Triple Helix" Models of Innovation: Can Synergy in Innovation Systems Be Measured?

The model of "Open Innovations" (OI) can be compared with the "Triple Helix of University-Industry-Government Relations" (TH) as attempts to find surplus value in bringing industrial innovation closer to public R&D. Whereas the firm is central in the model of OI, the TH adds multi-centeredness: in addition to firms, universities and (e.g., regional) governments can take leading roles in innovation eco-systems. In addition to the (transversal) technology transfer at each moment of time, one can focus on the dynamics in the feedback loops. Under specifiable conditions, feedback loops can be turned into feedforward ones that drive innovation eco-systems towards self-organization and the auto-catalytic generation of new options. The generation of options can be more important than historical realizations ("best practices") for the longer-term viability of knowledge-based innovation systems. A system without sufficient options, for example, is locked-in. The generation of redundancy -- the Triple Helix indicator -- can be used as a measure of unrealized but technologically feasible options given a historical configuration. Different coordination mechanisms (markets, policies, knowledge) provide different perspectives on the same information and thus generate redundancy. Increased redundancy not only stimulates innovation in an eco-system by reducing the prevailing uncertainty; it also enhances the synergy in and innovativeness of an innovation system.Comment: Journal of Open Innovations: Technology, Market and Complexity, 2(1) (2016) 1-12; doi:10.1186/s40852-016-0039-

HAX-1 overexpression, splicing and cellular localization in tumors

<p>Abstract</p> <p>Background</p> <p>HAX-1 has been described as a protein potentially involved in carcinogenesis and especially metastasis. Its involvement in regulation of apoptosis and cell migration along with some data indicating its overexpression in cancer cell lines and tumors suggests that HAX-1 may play a role in neoplastic transformation. Here we present the first systematic analysis of HAX-1 expression in several solid tumors.</p> <p>Methods</p> <p>Using quantitative RT-PCR, we have determined the mRNA levels of <it>HAX1 </it>splice variant I in several solid tumors. We have also analyzed by semiquantitative and quantitative RT-PCR the expression of five <it>HAX-1 </it>splice variants in breast cancer samples and in normal tissue from the same individuals. Quantitative PCR was also employed to analyze the effect of estrogen on <it>HAX1 </it>expression in breast cancer cell line. Immunohistochemical analysis of HAX-1 was performed on normal and breast cancer samples.</p> <p>Results</p> <p>The results reveal statistically important <it>HAX1 </it>up-regulation in breast cancer, lung cancer and melanoma, along with some minor variations in the splicing pattern. HAX-1 up-regulation in breast cancer samples was confirmed by immunohistochemical analysis, which also revealed an intriguing HAX-1 localization in the nuclei of the tumor cells, associated with strong ER status.</p> <p>Conclusion</p> <p>HAX-1 elevated levels in cancer tissues point to its involvement in neoplastic transformation, especially in breast cancer. The connection between HAX-1 nuclear location and ER status in breast cancer samples remains to be clarified.</p

Extensive neuroadaptive changes in cortical gene-transcript expressions of the glutamate system in response to repeated intermittent MDMA administration in adolescent rats

<p>Abstract</p> <p>Background</p> <p>Many studies have focused on the implication of the serotonin and dopamine systems in neuroadaptive responses to the recreational drug 3,4-methylenedioxy-metamphetamine (MDMA). Less attention has been given to the major excitatory neurotransmitter glutamate known to be implicated in schizophrenia and drug addiction. The aim of the present study was to investigate the effect of repeated intermittent MDMA administration upon gene-transcript expression of the glutamate transporters (EAAT1, EAAT2-1, EAAT2-2), the glutamate receptor subunits of AMPA (GluR1, GluR2, GluR3), the glutamate receptor subunits of NMDA (NR1, NR2A and NR2B), as well as metabotropic glutamate receptors (mGluR1, mGluR2, mGluR3, mGluR5) in six different brain regions. Adolescent male Sprague Dawley rats received MDMA at the doses of 3 × 1 and 3 × 5 mg/kg/day, or 3× vehicle 3 hours apart, every 7^thday for 4 weeks. The gene-transcript levels were assessed using real-time PCR validated with a range of housekeeping genes.</p> <p>Results</p> <p>The findings showed pronounced enhancements in gene-transcript expression of GluR2, mGluR1, mGluR5, NR1, NR2A, NR2B, EAAT1, and EAAT2-2 in the cortex at bregma +1.6. In the caudate putamen, mRNA levels of GluR3, NR2A, and NR2B receptor subunits were significantly increased. In contrast, the gene-transcript expression of GluR1 was reduced in the hippocampus. In the hypothalamus, there was a significant increase of GluR1, GluR3, mGluR1, and mGluR3 gene-transcript expressions.</p> <p>Conclusion</p> <p>Repeated intermittent MDMA administration induces neuroadaptive changes in gene-transcript expressions of glutamatergic NMDA and AMPA receptor subunits, metabotropic receptors and transporters in regions of the brain regulating reward-related associative learning, cognition, and memory and neuro-endocrine functions.</p