Controlling the Shadow Trade

From tackling illicit flows of small arms to combating nuclear smuggling, the shadow trade has become a central target of attempts to control the means of violence. This article argues that much of this practice and literature is framed in unhelpful terms that posit two distinct worlds, an upperworld and underworld, that separates illicit flow networks from the familiar world of state security policy. This implies that the possibilities for controlling the shadow trade are limited or require expansive and expensive controls. The article then examines the formation of illicit flow networks, drawing on examples including narcotics, small arms, nuclear materials, nuclear technology, major conventional arms, dual use technologies, and chemical weapons precursors; and finds that state and hybrid actors rather than extensive private networks are constitutive of illicit networks in many ways. It concludes by reclaiming hope for controlling the means of violence in this hybridity.

Non Classical Design in MOSFETs for Improving OTA gain-bandwidth trade off

In this paper, gain-bandwidth (GB) trade-off associated with analog device/circuit design due to conflicting requirements for enhancing gain and cutoff frequency is examined. It is demonstrated that the use of a nonclassical source/drain (S/D) profile (also known as underlap channel) can alleviate the GB trade-off associated with analog design. Operational transconductance amplifier (OTA) with 60 nm underlap S/D MOSFETs achieve 15 dB higher open loop voltage gain along with three times higher cutoff frequency as compared to OTA with classical nonunderlap S/D regions. Underlap design provides a methodology for scaling analog devices into the sub-100 nm regime and is advantageous for high temperature applications with OTA, preserving functionality up to 540 K. Advantages of underlap architecture over graded channel (GC) or laterally asymmetric channel (LAC) design in terms of GB behavior are demonstrated. Impact of transistor structural parameters on the performance of OTA is also analyzed. Results show that underlap OTAs designed with spacer-to-straggle ratio of 3.2 and operated below a bias current of 80 microamps demonstrate optimum performance. The present work provides new opportunities for realizing future ultra wide band OTA design with underlap DG MOSFETs in silicon-on-insulator (SOI) technology. Index Terms—Analog/RF, double gate, gain-bandwidth product, .

Bad Faith in European Trade Mark Law

Analyses how the European Court of Justice has interpreted the EU law rules against the registration of a trade mark or Community trade mark by an applicant in bad faith. Reviews case law from the UK courts, Office of Harmonisation in the Internal Market and Community courts on the role of bad faith as a moral standard. Considers case law on the narrow interpretation of bad faith in view of other EU provisions limiting trade marks.

The relationship between agricultural intensification and biological control: experimental tests across Europe

Agricultural intensification can affect biodiversity and related ecosystem services such as biological control, but large-scale experimental evidence is missing. We examined aphid pest populations in cereal fields under experimentally reduced densities of (1) ground-dwelling predators (-G), (2) vegetation-dwelling predators and parasitoids (-V), (3) a combination of (1) and (2) (-G-V),compared with open-fields (control), in contrasting landscapes with low vs. high levels of agricultural intensification (AI), and in five European regions. Aphid populations were 28%, 97%, and 199% higher in -G, -V, and -G -V treatments, respectively, compared to the open fields, indicating synergistic effects of both natural-enemy groups. Enhanced parasitoid : host and predator : prey ratios were related to reduced aphid population density and population growth. The relative importance of parasitoids and vegetation-dwelling predators greatly differed among European regions, and agricultural intensification affected biological control and aphid density only in some regions. This shows a changing role of species group identity in diverse enemy communities and a need to consider region-specific landscape management.

Agricultural intensification and biodiversity partitioning in European landscapes comparing plants, carabids, and birds

Effects of agricultural intensification (AI) on biodiversity are often assessed on the plot scale, although processes determining diversity also operate on larger spatial scales. Here, we analyzed the diversity of vascular plants, carabid beetles, and birds in agricultural landscapes in cereal crop fields at the field (n = 1350), farm (n = 270), and European-region (n = 9) scale. We partitioned diversity into its additive components alpha, beta, and gamma, and assessed the relative contribution of beta diversity to total species richness at each spatial scale. AI was determined using pesticide and fertilizer inputs, as well as tillage operations and categorized into low, medium, and high levels. As AI was not significantly related to landscape complexity, we could disentangle potential AI effects on local vs. landscape community homogenization. AI negatively affected the species richness of plants and birds, but not carabid beetles, at all spatial scales. Hence, local AI was closely correlated to beta diversity on larger scales up to the farm and region level, and thereby was an indicator of farm-and region-wide biodiversity losses. At the scale of farms (12.83-20.52%) and regions (68.34-80.18%), beta diversity accounted for the major part of the total species richness for all three taxa, indicating great dissimilarity in environmental conditions on larger spatial scales. For plants, relative importance of alpha diversity decreased with AI, while relative importance of beta diversity on the farm scale increased with AI for carabids and birds. Hence, and in contrast to our expectations, AI does not necessarily homogenize local communities, presumably due to the heterogeneity of farming practices. In conclusion, a more detailed understanding of AI effects on diversity patterns of various taxa and at multiple spatial scales would contribute to more efficient agri-environmental schemes in agroecosystems.