This paper reports the design of two potential navigation systems for use in an unmanned surface vehicle (USV) named Springer.The approaches adopted are based on fuzzy multisensor data fusion (MSDF) and multiple model adaptive estimation (MMAE) algorithms with adaptive capabilities. A general description of the Springer USV is given along with details of its navigation sensor suite. Of particular interest are the three different types of electronic compass used to supply heading information. Using a system identification technique, state space models of the compasses are derived for use in a simulation study to compare the navigation systems. From the results presented, it is concluded the fuzzy MSDF algorithm is 'better than the MMAE methodology in terms of heading (yaw error) accuracy and robustness.

The selective destruction of tumour cells while sparing healthy tissues is one of the main challenges in cancer therapy. Antibody-drug conjugates (ADCs) are arguably the most rapidly expanding class of targeted cancer therapies. Efficient drug conjugation and release technologies are essential for the development of these new therapeutic agents. In response to the ever-increasing demand for efficient drug release systems, we have developed a new class of beta-galactosidase-cleavable linkers for ADCs. Within this framework, novel payloads comprising a galactoside linker, the monomethyl auristatin E (MMAE) and cysteine-reactive groups were synthesized, conjugated with trastuzumab and evaluated both in vitro and in vivo. The ADCs with galactoside linkers demonstrated superior therapeutic efficacy in mice compared to the marketed trastuzumab emtansine used for the treatment of breast cancer. (C) 2017 Elsevier Masson SAS. All rights reserved.