The evolution of the electronics industry on Batam Island (Riau Islands Province,Indonesia): an evolutionary trajectory contributing to regional resilience?

While extensively studied in the 1990s, research on the electrical and electronics (E&E) industry in Singapore and the proximate areas of Indonesia has dwindled. Focusing on the E&E sector in the island of Batam (Riau Islands Province, Indonesia), we examine the industry’s recent evolution, in particular its ‘robustness’—its durability and capacity to adapt to adverse events. As to the explanatory factors accounting for its robustness, we evaluate the role of agency as opposed to conventional approaches that focus on structure. Our findings show that, in Batam, the E&E industry’s robustness has started to suffer. While there is evidence that structural factors are at work, we argue that agency in the form of institutionally-embedded perspectives and behaviour of actors at the sub-national level also plays a role. Because the promotion of economic diversification through investment in new sectors is easier and more lucrative than upgrading and deepening of firm capabilities in existing sectors, agents privilege the former at the cost of the latter. At the end of the day, regional resilience is undermined, rather than reinforced as evinced by the recent atrophy of Batam’s E&E industry.     

Comparison of surface and borehole locations of induced seismicity

Monitoring of induced microseismic events has become an important tool in hydraulic fracture diagnostics and understanding fractured reservoirs in general. We compare microseismic event and their uncertainties using data sets obtained with surface and downhole arrays of receivers. We first model the uncertainties to understand the effect of different acquisition geometries on location accuracy. For a vertical array of receivers in a single monitoring borehole, we find that the largest part of the final location uncertainty is related to estimation of the backazimuth. This is followed by uncertainty in the vertical position and radial distance from the receivers. For surface monitoring, the largest uncertainty lies in the vertical position due to the use of only a single phase (usually P‐wave) in the estimation of the event location. In surface monitoring results, lateral positions are estimated robustly and are not sensitive to the velocity model. In this case study, we compare event location solutions from two catalogues of microseismic events; one from a downhole array and the second from a surface array of 1C geophone. Our results show that origin time can be reliably used to find matching events between the downhole and surface catalogues. The locations of the corresponding events display a systematic shift consistent with a poorly calibrated velocity model for downhole dataset. For this case study, locations derived from surface monitoring have less scatter in both vertical and horizontal directions.     

Present climate and climate change over North America as simulated by the fifth-generation Canadian regional climate model

The fifth-generation Canadian Regional Climate Model (CRCM5) was used to dynamically downscale two Coupled Global Climate Model (CGCM) simulations of the transient climate change for the period 1950–2100, over North America, following the CORDEX protocol. The CRCM5 was driven by data from the CanESM2 and MPI-ESM-LR CGCM simulations, based on the historical (1850–2005) and future (2006–2100) RCP4.5 radiative forcing scenario. The results show that the CRCM5 simulations reproduce relatively well the current-climate North American regional climatic features, such as the temperature and precipitation multiannual means, annual cycles and temporal variability at daily scale. A cold bias was noted during the winter season over western and southern portions of the continent. CRCM5-simulated precipitation accumulations at daily temporal scale are much more realistic when compared with its driving CGCM simulations, especially in summer when small-scale driven convective precipitation has a large contribution over land. The CRCM5 climate projections imply a general warming over the continent in the 21st century, especially over the northern regions in winter. The winter warming is mostly contributed by the lower percentiles of daily temperatures, implying a reduction in the frequency and intensity of cold waves. A precipitation decrease is projected over Central America and an increase over the rest of the continent. For the average precipitation change in summer however there is little consensus between the simulations. Some of these differences can be attributed to the uncertainties in CGCM-projected changes in the position and strength of the Pacific Ocean subtropical high pressure.     

Prediction of magnitude of the largest potentially induced seismic event

We propose a method for determining the possible magnitude of a potentially largest induced seismic event derived from the Gutenberg–Richter law and an estimate of total released seismic moment. We emphasize that the presented relationship is valid for induced (not triggered) seismicity, as the total seismic moment of triggered seismicity is not bound by the injection. The ratio of the moment released by the largest event and weaker events is determined by the constants a and b of the Gutenberg–Richter law. We show that for a total released seismic moment, it is possible to estimate number of events greater than a given magnitude. We determine the formula for the moment magnitude of a probable largest seismic event with one occurrence within the recurrence interval (given by one volumetric change caused by mining or injecting). Finally, we compare theoretical and measured values of the moment magnitudes of the largest induced seismic events for selected geothermal and hydraulic fracturing projects.     

Estimation of groundwater storage from seismic data using deep learning

Convolutional neural networks can provide a potential framework to characterize groundwater storage from seismic data. Estimation of key components, such as the amount of groundwater stored in an aquifer and delineate water table level, from active-source seismic data are performed in this study. The data to train, validate and test the neural networks are obtained by solving wave propagation in a coupled poroviscoelastic–elastic media. A discontinuous Galerkin method is applied to model wave propagation, whereas a deep convolutional neural network is used for the parameter estimation problem. In the numerical experiment, the primary unknowns estimated are the amount of stored groundwater and water table level, while the remaining parameters, assumed to be of less of interest, are marginalized in the convolutional neural network-based solution. Results, obtained through synthetic data, illustrate the potential of deep learning methods to extract additional aquifer information from seismic data, which otherwise would be impossible based on a set of reflection seismic sections or velocity tomograms.     

A comparative analysis of three habitat suitability models for commercial yield estimation of Tapes philippinarum in a North Adriatic coastal lagoon (Sacca di Goro, Italy)

Habitat Suitability (HS) models have been extensively used by conservation planners to estimate the spatial distribution of threatened species and of species of commercial interest. In this work we compare three HS models for the estimation of commercial yield potential and the identification of suitable sites for Tapes philippinarum rearing in the Sacca di Goro lagoon (Italy) on the basis of six environmental factors. The habitat suitability index (HSI) is based on expert opinion while the habitat suitability conditional (HSC) is calibrated on observational data. The habitat suitability mixed (HSM) model is a two-part model combining expert knowledge and regression analysis: the first component of the model uses logistic regression to identify the areas in which clams are likely to be present; the second part applies the same parameter-specific suitability functions of the HSI model only in the areas previously identified as productive by the logistic component. The HS models were validated on an independent data set and estimates of potential yield of the Goro lagoon were compared. The effectiveness of the three approaches is then discussed in terms of predicted yield and identification of suitable sites for farming.     

Chlorinated compounds and polybrominated diphenyl ethers (PBDEs) in mussels (Mytilus galloprovincialis) collected from Apulia Region coasts

This project was carried out to assess the levels and spatial distribution of organochlorine compounds in the coastal marine environment, using mussels as bioindicators to evaluate the coastal water quality. Levels of polychlorobiphenils (PCB), chlorinated pesticides (DDT isomers, HCH isomers, Aldrin, Dieldrin, alfa-Endosulfan, Hexachlorobenzene, Pentachlorobenzene) and polybrominated diphenyl ethers (PBDEs) were determined in tissues from mussels (Mytilus galloprovincialis) collected along the Apulia Region coasts (Mediterranean Sea). Results indicate that contamination by organochlorine compounds is higher in mussels sampled in the Ionian Sea than in those from the Adriatic Sea, with PCB levels up to seven times higher in mussels from Ionian than from the Adriatic Sea. Although PCB levels were above the maximum values indicated by both European Community (EC) and National regulation in several sample sites, the PCB concentrations were particularly high in some stations, suggesting that these locations require a much specific attention. Conversely, results on the mussel contamination by PBDEs highlight their ubiquitous environmental distribution, and underline the need to establish the maximum level for these compounds in foodstuff, according to European Regulations.     

Amplified exchange rate by tidal forcing of a piecewise-linear Helmholtz bay

Sea-level and current measurements have been performed in the Mok Bay, a tidal embayment in the Dutch Wadden Sea, situated on the island of Texel, the Netherlands. Characteristic for this estuary is its nonuniform hypsometry. Oscillations in both water level and inflow of the estuary were observed, with characteristic frequencies of 31 and 48 cycles per day. The significant change in basin shape between low and high water is the cause for the existence of these two frequencies of resonance. Due to its semi-enclosed nature, the basin could at both tidal phases be characterized as a Helmholtz resonator, albeit of different dimensions. Depth measurements were performed to find these characteristic dimensions of the estuary, allowing the determination of its theoretical Helmholtz frequencies. These estimates match to within 10% with the observed frequencies, and this deviation can partly be explained. Although sea level oscillations at these frequencies have small amplitude (of order 1 cm), the accompanying oscillatory flow at the entrance is of similar magnitude as the tidal flow. The water level measurements (spanning only 8 days of data) were therefore modeled using a piecewise-uniform hypsometry that approximates the real hypsometric curve well. The simplified semi-analytical piecewise-linear viscous Helmholtz model captures the observed combination of tidal and eigenoscillations well. However, despite its simplicity, this model is able to display nonlinear behavior for certain parameter values. This is because of the intrinsic nonlinearity that accompanies the matching of the low and high water phases. In the setting studied here, bifurcations up to period 13 were found. This nonlinear type of response may be of importance in facilitating an extra exchange of sediments and nutrients between the Bay and the sea.