This exploratory study aims to identify the main characteristics and relationships between artificial intelligence (AI) and broadband development in Asia and the Pacific. Broadband networks are the foundation and prerequisite for the development of AI. But what types of broadband networks would be conducive are not adequately discussed so far. Furthermore, in addition to broadband networks, other factors, such as income level, broadband quality, and investment, are expected to influence the uptake of AI in the region. The findings are synthesized into a set of policy recommendations at the end of the article, which highlights the need for regional cooperation through an initiative, such as the Asia-Pacific Information Superhighway (AP-IS). 

Over the past decade, Ontario has seen a renewal in efforts to stimulate economic growth by investing in infrastructures. In this paper, we analyze the impact of public infrastructure investment on economic performance in this province. We use a multivariate dynamic time series methodological approach, based on the use of vector autoregressive models to estimate the elasticities and marginal products of six different types of public infrastructure assets on private investment, employment and output. We find that all types of public investment crowd in private investment while investment in highways, roads, and bridges crowds out employment. We also find that all types of public investment, with the exception of highways, roads and bridges, have a positive effect on output. The relatively large range of results estimated for the impact of each of the different public infrastructure types suggests that a targeted approach to the design of infrastructure investment policy is required. Infrastructure investment in transit systems and health facilities display the highest returns for output and the largest effects on employment and labor productivity. In terms of the nature of the empirical results presented here it would be important to highlight the fact that investments in health infrastructures as well as investments in education infrastructures are of great relevance. This is a pattern consistent with the mounting international evidence on the importance of human capital for long term economic performance.

Helical deep hole drilling is a process frequently used in industrial applications to produce bores with a large length to diameter ratio. For better cooling and lubrication, the deep drilling oil is fed directly into the bore hole via two internal cooling channels. Due to the inaccessibility of the cutting area, experimental investigations that provide information on the actual machining and cooling behavior are difficult to carry out. In this paper, the distribution of the deep drilling oil is investigated both experimentally and simulatively and the results are evaluated. For the Computational Fluid Dynamics (CFD) simulation, two different turbulence models, i.e. the RANS k-ω-SST and hybrid SAS-SST model, are used and compared. Thereby, the actual used deep drilling oil is modelled instead of using fluid dynamic parameters of water, as is often the case. With the hybrid SAS-SST model, the flow could be analyzed much better than with the RANS k-ω-SST model and thus the processes that take place during helical deep drilling could be  simulated with realistic details. Both the experimental and the simulative results show that the deep drilling oil movement is almost exclusively generated by the tool rotation. At the tool’s cutting edges and in the flute, the flow velocity drops to zero for the most part, so that no efficient cooling and lubrication could take place there. In addition, cavitation bubbles form and implode, concluding in the assumption that the process heat is not adequately dissipated and the removal of chips is adversely affected, which in turn can affect the service life of the tool and the bore quality. The carried out investigations show that the application of CFD simulation is an important research instrument in machining technology and that there is still great potential in the area of tool and process optimization.

To investigate the possible role of arbuscular mycrrhizal fungi (AMF) in alleviating the negative effects of salinity on Stevia rebaudiana (Bert.), the regenerated plantlets in tissue culture was transferred to pots in greenhouse and inoculated with Glomus intraradices. Salinity caused a significant decrease in chlorophyll content, photosynthesis efficiency and enhanced the electrolyte leakage. The use of AMF in salt –affected plants resulted in improved all above mentioned characteristics. Hydrogen peroxide and malondialdehyde (MDA) contents increased in salt stressed plants while a reduction was observed due to AMF inoculation. CAT activity showed a significant increase up to 2 g/l and then followed by decline at 5 g/l NaCl in both AMF and non-AMF treated stevia, however, AMF inoculated plants maintained lower CAT activity at all salinity levels (2 and 5 g/l). Enhanced POX activities in salt- treated stevia plants were decreased by inoculation of plants with AMF. The addition of NaCl to stevia plants also resulted in an enhanced activity of SOD whilst, AMF plants maintained higher SOD activity at all salinity levels than those of non-AMF inoculated plants. AMF inoculation was capable of alleviating the damage caused by salinity on stevia plants by reducing oxidative stress and improving photosynthesis efficiency. 

Numerical study of subcooled and saturated flow boiling in the curved and helically  coiled tubes in presence of phase change is one of the challenging area of CFD studies. In this paper, the CFD modeling of the nucleate and convective flow boiling in the small helically coiled tube at low vapor quality (up to the 18.93 percent) region is studied. A proper Eulerian-based mathematical model is used for interphase exchange forces and heat transfer between two phases in CFD modeling using Bulk boiling model. The results show that, the inner and the bottom wall of the helically coiled tube have the lowest and the highest heat transfer coefficient, respectively. The effect of change in coil diameter, helical pitch and tube diameter is investigated on the counters of vapor volume fraction. It is seen that at low vapor quality flows, the heat transfer coefficient is enhanced by decreasing in coil diameter, tube diameter and increasing in coil pitch of helically coiled tube.