The direct catalytic dehydrative amidation of β-hydroxycarboxylic acids with amines is described. A biphenyl-based diboronic acid anhydride with a B–O–B skeleton is shown to be an exceptionally effective catalyst for the reaction, providing β-hydroxycarboxylic amides in high to excellent yields with a low catalyst loading (minimum of 0.01 mol %, TON up to 7,500). This hydroxy-directed amidation shows excellent chemoselectivity and is applicable to gram-scale drug synthesis.

The biogenic production of hydrogen sulfide is a serious problem associated with wastewater treatment. The aim of this study was to investigate the inhibitory effect of nitrate on the dynamics of sulfate-reducing bacteria (SRB) community in a laboratory-scale wastewater reactor, originating from a denitrifying plant using activated sludge. For this purpose, denaturing gradient gel electrophoresis (DGGE) analysis targeting the dsrB (dissimilatory sulfite reductase) gene was used in combination with chemical analyses and measurement of oxidation and reduction potential (ORP). The reactors were initially dosed with 1.0 and 4.0 g/L potassium nitrate and anaerobically incubated for 490 h. Addition of 4.0 g/L nitrate to the reactor was associated with a prolonged inhibition (over 300 h, i.e., 12.5 days) of sulfate reduction and this was consistent with a rapid decrease in ORP associated with nitrate depletion. The DGGE analysis revealed that nitrate addition remarkably attenuated a distinct group of dsrB related to Desulfovibrio, whereas other dsrB groups were not influenced. Furthermore, another sulfate reduction by Syntrophobacter in the later stages of the incubation period occurred in both reactors (regardless of the nitrate concentration), suggesting that different SRB groups are associated with sulfate reduction at different stages of the wastewater treatment process.

The cell growth on H 2 and O 2 as the energy source and CO 2 as the sole carbon source in the autotrophic culture condition was tested for the gram-negative bacteria Paracoccus spp. The aerobic growth in the autotrophic condition was only observed in Paracoccus denitrificans NBRC13301 and P.pantotrophus NBRC102493. Both strains were sensitive to O 2 in particular the growth of P.pantotrophus was completely inhibited at the concentrations above 2% O 2. P.denitrificans grew until 15% O 2 however the optimum O 2 concentration was 5%. The growth characteristic of P.denitrificans was investigated by pH-controlled batch culture with supplying the gas mixture of H 2 , O 2 and CO 2. The specific growth rate was 0.12 h-1 at 5% O 2 , 30°C and pH7.0. The growth was much slower than other hydrogen-oxidizing bacteria however P.denitrificans accumulated biodegradable plastic, polyhydroxybutyrate, PHB with the content of 57.3% w/w in the cell under nitrogen limitation. Under DO limitation, the cell concentration increased to 25 g/L without accumulating PHB if NH 3 solution as the nitrogen source was fed sufficiently.

Cooperative intelligent transportation systems (ITS) are used by autonomous vehicles to communicate with surrounding autonomous vehicles and roadside units (RSU). Current C-ITS applications focus primarily on real-time information sharing, such as cooperative perception. In addition to realtime information sharing, self-driving cars need to coordinate their action plans to achieve higher safety and efficiency. For this reason, this study defines a vehicle's future action plan/path and designs a cooperative path-planning model at intersections using future path sharing based on the future path information of multiple vehicles. The notion is that when the RSU detects a potential conflict of vehicle paths or an acceleration opportunity according to the shared future paths, it will generate a coordinated path update that adjusts the speeds of the vehicles. We implemented the proposed method using the open-source Autoware autonomous driving software and evaluated it with the LGSVL autonomous vehicle simulator. We conducted simulation experiments with two vehicles at a blind intersection scenario, finding that each car can travel safely and more efficiently by planning a path that reflects the action plans of all vehicles involved. The time consumed by introducing the RSU is 23.0 % and 28.1 % shorter than that of the stand-alone autonomous driving case at the intersection.

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