Baseline characteristics of climate, permafrost, and land cover from Samoylov Island, Lena River Delta, Siberia

Samoylov Island is centrally located within the Lena River Delta at 72° N, 126° E and lies within the Siberian zone of continuous permafrost. The landscape on Samoylov Island consists mainly of late Holocene river terraces with polygonal tundra, ponds and lakes, and an active floodplain. The island has been the focus of numerous multidisciplinary studies since 1993, which have focused on climate, land cover, ecology, hydrology, permafrost and limnology. This paper aims to provide a framework for future studies by describing the characteristics of the island's meteorological parameters (temperature, radiation and snow cover), soil temperature, and soil moisture. The land surface characteristics have been described using high resolution aerial images in combination with data from ground-based observations. Of note is that deeper permafrost temperatures have increased between 0.3 to 1.3 °C over the last five years. However, no clear warming of air and active layer temperatures is detected since 1998, though winter air temperatures during recent years have not been as cold as in earlier years.

Meteorological observations and eddy covariance raw data from polygonal tundra in the Lena River Delta, Siberia

We present the first ecosystem-scale methane flux data from a northern Siberian tundra ecosystem covering the entire snow-free period from spring thaw until initial freeze-back. Eddy covariance measurements of methane emission were carried out from the beginning of June until the end of September in the southern central part of the Lena River Delta (72°22' N, 126°30' E). The study site is located in the zone of continuous permafrost and is characterized by Arctic continental climate with very low precipitation and a mean annual temperature of -14.7°C. We found relatively low fluxes of on average 18.7 mg/m**2/d, which we consider to be because of (1) extremely cold permafrost, (2) substrate limitation of the methanogenic archaea, and (3) a relatively high surface coverage of noninundated, moderately moist areas. Near-surface turbulence as measured by the eddy covariance system in 4 m above the ground surface was identified as the most important control on ecosystem-scale methane emission and explained about 60% of the variance in emissions, while soil temperature explained only 8%. In addition, atmospheric pressure was found to significantly improve an exponential model based on turbulence and soil temperature. Ebullition from waterlogged areas triggered by decreasing atmospheric pressure and near-surface turbulence is thought to be an important pathway that warrants more attention in future studies. The close coupling of methane fluxes and atmospheric parameters demonstrated here raises questions regarding the reliability of enclosure-based measurements, which inherently exclude these parameters.

Nanotechnology in food industry II: risk assessment and legislation

Currently, there is increasing use of nanomaterials in the food industry thanks to the many advantages offered and make the products that contain them more competitive in the market. Their physicochemical properties often differ from those of bulk materials, which require specialized risk assessment. This should cover the risks to the health of workers and consumers as well as possible environmental risks. The risk assessment methods must go updating due to more widespread use of nanomaterials, especially now that are making their way down to consumer products. Today there is no specific legislation for nanomaterials, but there are several european dispositions and regulations that include them. This review gives an overview of the risk assessment and the existing current legislation regarding the use of nanotechnology in the food industry.

Real-time depth camera tracking with CAD models and ICP

In recent years, depth cameras have been widely utilized in camera tracking for augmented and mixed reality. Many of the studies focus on the methods that generate the reference model simultaneously with the tracking and allow operation in unprepared environments. However, methods that rely on predefined CAD models have their advantages. In such methods, the measurement errors are not accumulated to the model, they are tolerant to inaccurate initialization, and the tracking is always performed directly in reference model's coordinate system. In this paper, we present a method for tracking a depth camera with existing CAD models and the Iterative Closest Point (ICP) algorithm. In our approach, we render the CAD model using the latest pose estimate and construct a point cloud from the corresponding depth map. We construct another point cloud from currently captured depth frame, and find the incremental change in the camera pose by aligning the point clouds. We utilize a GPGPU-based implementation of the ICP which efficiently uses all the depth data in the process. The method runs in real-time, it is robust for outliers, and it does not require any preprocessing of the CAD models. We evaluated the approach using the Kinect depth sensor, and compared the results to a 2D edge-based method, to a depth-based SLAM method, and to the ground truth. The results show that the approach is more stable compared to the edge-based method and it suffers less from drift compared to the depth-based SLAM.

Avaliação de atrativos para monitoramento de drosophila suzukii em pomar comercial de framboesa.

Drosophila suzukii (Diptera: Drosophilidae), conhecida como drosófila da asa manchada (SWD) ou suzuki, é uma praga quarentenária nativa da Ásia em expansão mundial na atualidade. Em 2008, SWD foi coletada nos EUA (Califórnia) e, desde então, registrada em outros estados americanos (WALSH et al. 2011) e também na Europa (CINI et al. 2012). No Brasil, a praga foi detectada no ano de 2014 ocasionando danos na ordem de 30% em cultivos de morango no Estado do Rio Grande do Sul (SANTOS, 2014a). Os danos são causados pela alimentação das larvas em frutos ainda fixos às plantas, e pela introdução de patógenos no local da oviposição. O fruto atacado entra em colapso exibindo intensa perda de líquidos. Entre os hospedeiros da SWD estão as fruteiras que produzem frutos de epiderme fina como, por exemplo, os pequenos frutos: morango, framboesa, amora-preta e o mirtilo. Em se tratando de uma espécie recentemente introduzida no Brasil, poucas são as informações sobre a eficiência de atrativos para monitoramento das populações. O vinagre de maçã tem sido usado em vários estudos científicos, sendo até sugerido como atrativo para o monitoramento da espécie no Brasil (SANTOS, 2014b). Apesar disto, a atratividade é apontada como de curta duração e de baixa seletividade. Assim, Santos (2016) recomenda, em substituição ao vinagre de maçã, o uso de um atrativo à base de fermento biológico, açúcar e água, o qual tem se mostrado promissor e seletivo para monitoramento de SWD. Nos 24 EUA, após extensa avaliação laboratorial e de campo, foram isolados componentes químicos essenciais da atratividade de D. Suzukii, os quais estão sendo produzidos e comercializados em forma de dispenser, com os nomes comerciais de Pherocon® SWD e Scentry® SWD. Como inexistem informações sobre a eficiência e a seletividade de tais produtos para o monitoramento da suzuki no Brasil, foi planejado o presente estudo, cujo objetivo foi o de avaliar a captura e a seletividade de atrativos e de misturas no monitoramento de D. suzukii em pomar de framboesa no município de Vacaria, RS.