Characterization,design and modeling of on-chip interleaved transformers in CMOS RFICs

This paper discusses the impacts of key geometrical parameters on the performance of interleaved transformers in CMOS radio frequency integrated circuits (RFICs). It also presents a compact circuit model for the transformer based on the “2-π” model of on-chip spiral inductors. All the RLC circuit elements can be calculated from the transformer’s geometrical and process parameters. Verification with accurately calibrated electromagnetic (EM) simulation data demonstrates accurate performance prediction and good scalability for a wide range of transformers’ layout.     

Biological denitrification in microbial fuel cells

Microbial fuel cells (MFCs) that remove carbon as well as nitrogen compounds out of wastewater are of special interest for practice. We developed a MFC in which microorganisms in the cathode performed a complete denitrification by using electrons supplied by microorganisms oxidizing acetate in the anode. The MFC with a cation exchange membrane was designed as a tubular reactor with an internal cathode and was able to remove up to 0.146 kg NO(3-)-N m(-3) net cathodic compartment (NCC) d(-1) (0.080 kg NO(3-)-N m(-3) total cathodic compartment d(-1) (TCC)) at a current of 58 A m(-3) NCC (32 A m(-3) TCC) and a cell voltage of 0.075 V. The highest power output in the denitrification system was 8 W m(-3) NCC (4 W m(-3) TCC) with a cell voltage of 0.214 V and a current of 35 A m(-3) NCC. The denitrification rate and the power production was limited bythe cathodic microorganisms, which only denitrified significantly at a cathodic electrode potential below 0 V versus standard hydrogen electrode (SHE). This is, to our knowledge, the first study in which a MFC has both a biological anode and cathode performing simultaneous removal of an organic substrate, power production, and complete denitrification without relying on H2-formation or external added power.     

Cyanogenic potential of randomly sampled fresh and processed cassava on retail sale in Singapore

A random sample of fresh cassava roots and cassava products, purchased at various retail outlets in Singapore during 2016–2017, had total cyanogenic potential (CNp–expressed as mean ± standard deviation, mg kg⁻¹ HCN, fresh weight basis) as follows: fresh roots (n = 66) from three SE Asian countries, 59.0 ± 19.2; peeled chilled root pieces from Malaysia (20 × 1-kg packs), 38.5 ± 16.5; cassava flour from Indonesia (8 × 1-kg packs), 11.7 ± 8.2; dried Indonesian chips for home frying (5 × 250 g packs), 61.6 ± 16.5; one pack (120 g) of Malaysian ready-to-eat (RTE) chips, 17.1 ± 3.2. CNp in all flour and RTE chips was below 20 mg kg⁻¹. The majority of fresh roots (59.1%) and packs of dried chips (80%), and 15% of packs of peeled chilled root parenchyma, exceeded the Codex Alimentarius limit (50 mg kg⁻¹) for ‘sweet’ (boil-and-eat) cassava.     

Trade-offs between mobility restrictions and transmission of SARS-CoV-2

In their response to the COVID-19 outbreak, governments face the dilemma to balance public health and economy. Mobility plays a central role in this dilemma because the movement of people enables both economic activity and virus spread. We use mobility data in the form of counts of travellers between regions, to extend the often-used SEIR models to include mobility between regions. We quantify the trade-off between mobility and infection spread in terms of a single parameter, to be chosen by policy makers, and propose strategies for restricting mobility so that the restrictions are minimal while the infection spread is effectively limited. We consider restrictions where the country is divided into regions, and study scenarios where mobility is allowed within these regions, and disallowed between them. We propose heuristic methods to approximate optimal choices for these regions. We evaluate the obtained restrictions based on our trade-off. The results show that our methods are especially effective when the infections are highly concentrated, e.g. around a few municipalities, as resulting from superspreading events that play an important role in the spread of COVID-19. We demonstrate our method in the example of the Netherlands. The results apply more broadly when mobility data are available.