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Large stocks of soil organic carbon (SOC) have accumulated in the Northern Hemisphere permafrost region, but their current amounts and future fate remain uncertain. By analyzing dataset combining >2700 soil profiles with environmental variables in a geospatial framework, we generated spatially explicit estimates of permafrost-region SOC stocks, quantified spatial heterogeneity, and identified key environmental predictors. We estimated that Pg C are stored in the top 3 m of permafrost region soils. The greatest uncertainties occurred in circumpolar toe-slope positions and in flat areas of the Tibetan region. We found that soil wetness index and elevation are the dominant topographic controllers and surface air temperature (circumpolar region) and precipitation (Tibetan region) are significant climatic controllers of SOC stocks. Our results provide first high-resolution geospatial assessment of permafrost region SOC stocks and their relationships with environmental factors, which are crucial for modeling the response of permafrost affected soils to changing climate.

Abstract Background Cutibacterium acnes is part of the anaerobic skin microbiome and resides in deeper skin layers. The organism is an agent of surgical site infections (SSI) in shoulder surgery. We hypothesized that prolonged skin preparation with an agent that penetrates deeply into the skin would be beneficial. Thus, we compared two classes of antiseptics, each combined with alcohol, each applied with two different contact times. Methods Using a cross-over arrangement, shoulders of 16 healthy volunteers were treated for 2.5 min (standard) or 30 min (prolonged) with alcohol-based chlorhexidine (CHG-ALC) or alcohol-based povidone-iodine (PVP-I-ALC). Skin sites were sampled before, immediately after, and 3 h after treatment, using a standardized cup-scrub technique. Results Aerobic skin flora was reduced more effectively by PVP-I-ALC than by CHG-ALC after 2.5 min application and immediate sampling (reduction factor [RF] 2.55 ± 0.75 vs. 1.94 ± 0.91, p = 0.04), but not after prolonged contact times and 3-h sampling. Coagulase-negative staphylococci were completely eliminated after PVP-I-ALC application, but still recovered from 4 of 32 samples after CHG-ALC application. Anaerobic flora was reduced more effectively by PVP-I-ALC than CHG-ALC after standard (RF 3.96 ± 1.46 vs. 1.74 ± 1.24, p

Abstract Past work shows that processing information in relation to the self improves memory which is known as the self‐reference effect in memory. Other work suggests that transcranial direct current stimulation (tDCS) can also improve memory. Given recent research on self‐reference context memory effects (improved memory for contextual episodic details associated with self‐referential processing), we were interested in examining the extent stimulation might increase the magnitude of the self‐reference context memory effect. In this investigation, participants studied objects superimposed on different background scenes in either a self‐reference or other‐reference condition while receiving either active or sham stimulation to the dorsal medial prefrontal cortex (dmPFC), a cortical region known to support self‐reference context memory effects. Participants then completed a memory test that assessed item memory (have you seen this object before?) and context memory (with which background scene was this object paired?). Results showed a self‐reference context memory effect driven by enhanced memory for stimuli processed in the self‐reference compared to the other‐reference condition across all participants (regardless of stimulation condition). tDCS, however, had no effect on memory. Specifically, stimulation did not increase the magnitude of the self‐reference context memory effect under active compared to sham stimulation. These results suggest that stimulation of the dmPFC at encoding may not add to the memory benefits induced by self‐referential processing suggesting a boundary condition to tDCS effects on memory.

Skin-like tactile sensors provide robots with rich feedback related to the force distribution applied to their soft surface. The complexity of interpreting raw tactile information has driven the use of machine learning algorithms to convert the sensory feedback to the quantities of interest. However, the lack of ground truth sources for the entire contact force distribution has mainly limited these techniques to the sole estimation of the total contact force and the contact center on the sensor's surface. The method presented in this article uses a finite element model to obtain ground truth data for the three-dimensional force distribution. The model is obtained with state-of-the-art material characterization methods and is evaluated in an indentation setup, where it shows high agreement with the measurements retrieved from a commercial force-torque sensor. The proposed technique is applied to a vision-based tactile sensor, which aims to reconstruct the contact force distribution purely from images. Thousands of images are matched to ground truth data and are used to train a neural network architecture, which is suitable for real-time predictions.

Approximately 1700 Pg of soil carbon (C) are stored in the northern circumpolar permafrost zone, more than twice as much C than in the atmosphere. The overall amount, rate, and form of C released to the atmosphere in a warmer world will influence the strength of the permafrost C feedback to climate change. We used a survey to quantify variability in the perception of the vulnerability of permafrost C to climate change. Experts were asked to provide quantitative estimates of permafrost change in response to four scenarios of warming. For the highest warming scenario (RCP 8.5), experts hypothesized that C release from permafrost zone soils could be 19-45 Pg C by 2040, 162-288 Pg C by 2100, and 381-616 Pg C by 2300 in CO2 equivalent using 100-year CH4 global warming potential (GWP). These values become 50 % larger using 20-year CH4 GWP, with a third to a half of expected climate forcing coming from CH4 even though CH4 was only 2.3 % of the expected C release. Experts projected that two-thirds of this release could be avoided under the lowest warming scenario (RCP 2.6). These results highlight the potential risk from permafrost thaw and serve to frame a hypothesis about the magnitude of this feedback to climate change. However, the level of emissions proposed here are unlikely to overshadow the impact of fossil fuel burning, which will continue to be the main source of C emissions and climate forcing. © 2013 The Author(s).

The article is devoted to the search for ways to reduce carbon dioxide emissions in the technological operation of plowing. Ways to reduce CO2 emissions were determined on the basis of computational experiments conducted using a mathematical model of an arable unit compiled according to the efficiency criterion - the minimum integral emission of carbon dioxide. Integral CO2 emission, in addition to direct and indirect CO2 emissions over the life cycle of the arable unit, includes CO2, which could be absorbed from the atmosphere by the crop lost due to the influence of the parameters of the unit. The influence of the parameters of the tractor and the unit on the emission of carbon dioxide during its manufacture, technical and production operation is analyzed. Computational experiments were conducted to identify the influence of some external factors (field area, seasonal load volume, etc.) on the efficiency of the arable unit.

The article discusses the questions of optimization of parameters and operating modes of the tractor as a part of the arable unit by various criteria of optimization. The following parameters have been chosen for consideration. These are minimum total energy costs, taking into account the energy of the lost crop; minimum emission of carbon dioxide into the atmosphere; minimum fuel consumption per 1 ha of crops; maximum performance; maximum traction efficiency of the tractor. The optimal weight of the tractor, the power of its engine, the width of the sowing unit and its working speed were determined by carrying out computational experiments with a change in the resistivity of the sowing complex. It was revealed that the optimal parameters of the tractor and the sowing unit do not coincide according to all optimization criteria with an increase in the specific resistance of the soil to the working bodies of the seeder, the optimal value of the tractor weight and the power of its engine grow. The optimal weight of the tractor should be 120 kN with the possibility of loading up to 150 kN, it is desirable to have a two-level engine of 500 and 600 hp. The working width of the seeder must be able to change from 14 to 18 m.

The article deals with issues related to the reduction of carbon dioxide emissions into the atmosphere during the operation of sowing machine and tractor units. To identify ways to reduce CO2 emissions, computational experiments were conducted using a mathematical model of sowing units compiled according to the efficiency indicator. This is the integral emission of carbon dioxide as the sum of CO2 in the manufacture, maintenance, repair, control of the unit, when burning fuel and the amount of CO2 not absorbed from the atmosphere during the formation of the grain crop due to its losses from improperly selected equipment and its parameters. The influence of a number of factors on the integral emission of CO2 is investigated. These are the area of the treated area or field, the specific resistance of the planter, the volume of seasonal load on the unit, the annual load of the tractor in hours, the physical and mechanical properties of the soil, the pressure in the tires of the wheel propulsion engines, etc. Effective values of factors for reducing the emission of carbon dioxide by the sowing unit are revealed. The use of the totality of all the recommendations received will reduce the emission of carbon dioxide into the atmosphere by the aggregate during the technological operation of direct sowing of grain crops by 600-650 kg/ha.

The relevance of the problem under study is due to the need to substantiate the sufficient number of tractors used for various technological operations, depending on the volume of works performed, and taking into account their influence on the crop yield. The purpose is to develop the mathematical model of machine and tractor units used in technological operations by formalizing the vague concept of optimal agrotechnical timing of technological operations and calculating the optimal number of tractors to perform works by the total energy costs. The main research method is mathematical modeling of operations performed by machine-tractor units based on the system analysis and computational experiments and using the energy mathematical model. The article describes a criterion for optimizing the tractor parameters, dependences of the energy mathematical model of the unit. The results of computational experiments showed that for each operation there is an optimal number of tractors and tractor units minimizing the minimum total energy costs. Calculations were carried out when treating 1000 hectares with various tractors. It was revealed that the total energy consumption differs by 2 or more times. The required number of tractors depends on their main parameters, propeller parameters and other factors. It was revealed that with an increase in the volume of works, the required optimal number of tractors increases. The method for substantiating the required optimal number of tractors in technological operations will improve operations of tractors used by large agricultural producers, reduce the total energy costs for cultivating up to 12–16 thousand MJ/ha.

The topic is relevant due to the need to improve basic measurements of tractors, considering a major contribution they make to crop production, not only during separate technological operations, but also during a whole sequence of technological operations performed. The paper analyzes the limits to which the basic measurements of tractors (weight and engine power), which are used to perform a combination of technological operations requiring different energy consumption, can be altered and to identify practical limits to perform a combination of low and high energy-consuming activities. The key research method used is mathematical modeling based on system analysis and computational experiments that are carried out using models of implements during various technological operations. The results of calculations analyzed for technological operations that differ in the amount of energy consumed suggest that for each of the groups of technological operations that require similar amount of energy (soil resistivity per meter of working width, kN/m), there are fairly stable values of the basic measurements of tractors. A reasonable weight for tractors to perform operations such as harrowing, continuous cultivation of soil with a resistivity of 1 to 4 kN/m is 35-60 kN. For soil preparation with a resistivity of 4 to 8 kN/m it is 100-120 kN, for plowing with a resistivity from 10 to 16.25 kN/m – equal to 160 kN, for tillage with subsoilers with a resistivity from 8 to 16 kN/m – equal to 240 kN. Once put to practice, the findings will lead to a decrease in total energy consumption to 10,000 MJ/ha. The amount of saved energy costs depends on the type of technological operation, the parameters of tractors used, the characteristics of agricultural implements, soil properties, etc.

The article presents the results of a study to identify the optimal value of the annual load on one tractor using direct sowing technology. The optimal annual load on one tractor is directly associated with the power provision to agriculture and, indirectly, with its productivity. The article analyzes the dependence of the annual tractor load in ploughland per ha on various factors of the tractor-operator-instrument-fieldsoil-crop system: on tractor parameters; unit; environment and it is concluded that the optimal annual load on one tractor depends on them. The method of choosing various agricultural enterprises power supply should be connected with the natural and climatic conditions of their production activities, accepted technologies for cultivating crops, soil types, field sizes, etc. It was revealed that in Russia the optimal energy supply of agriculture with the power of tractor engines, using the zero tillage technology, is in the range from 2.4 to 2.8 hp/ha.

Soils and other unconsolidated deposits in the northern circumpolar permafrost region store large amounts of soil organic carbon (SOC). This SOC is potentially vulnerable to remobilization following soil warming and permafrost thaw, but SOC stock estimates were poorly constrained and quantitative error estimates were lacking. This study presents revised estimates of permafrost SOC stocks, including quantitative uncertainty estimates, in the 0–3 m depth range in soils as well as for sediments deeper than 3 m in deltaic deposits of major rivers and in the Yedoma region of Siberia and Alaska. Revised estimates are based on significantly larger databases compared to previous studies. Despite this there is evidence of significant remaining regional data gaps. Estimates remain particularly poorly constrained for soils in the High Arctic region and physiographic regions with thin sedimentary overburden (mountains, highlands and plateaus) as well as for deposits below 3 m depth in deltas and the Yedoma region. While some components of the revised SOC stocks are similar in magnitude to those previously reported for this region, there are substantial differences in other components, including the fraction of perennially frozen SOC. Upscaled based on regional soil maps, estimated permafrost region SOC stocks are 217 ± 12 and 472 ± 27 Pg for the 0–0.3 and 0–1 m soil depths, respectively (±95% confidence intervals). Storage of SOC in 0–3 m of soils is estimated to 1035 ± 150 Pg. Of this, 34 ± 16 Pg C is stored in poorly developed soils of the High Arctic. Based on generalized calculations, storage of SOC below 3 m of surface soils in deltaic alluvium of major Arctic rivers is estimated as 91 ± 52 Pg. In the Yedoma region, estimated SOC stocks below 3 m depth are 181 ± 54 Pg, of which 74 ± 20 Pg is stored in intact Yedoma (late Pleistocene ice- and organic-rich silty sediments) with the remainder in refrozen thermokarst deposits. Total estimated SOC storage for the permafrost region is ∼1300 Pg with an uncertainty range of ∼1100 to 1500 Pg. Of this, ∼500 Pg is in non-permafrost soils, seasonally thawed in the active layer or in deeper taliks, while ∼800 Pg is perennially frozen. This represents a substantial ∼300 Pg lowering of the estimated perennially frozen SOC stock compared to previous estimates.

Together with lectures and labs, case studies assist students in acquiring content knowledge, process skills, and an understanding of the context and application of science to their daily lives. Cases make the process of scientific learning more genuine and rigorous, bringing alive classroom learning and helping students apply concepts to understand contemporary societal challenges. (Contains 5 tables and 2 figures.)

High-latitude terrestrial ecosystems are key components in the global carbon cycle. The Northern Circumpolar Soil Carbon Database (NCSCD) was developed to quantify stocks of soil organic carbon (SOC) in the northern circumpolar permafrost region (a total area of 18.7 × 106 km2). The NCSCD is a geographical information system (GIS) data set that has been constructed using harmonized regional soil classification maps together with pedon data from the northern permafrost region. Previously, the NCSCD has been used to calculate SOC storage to the reference depths 0–30 cm and 0–100 cm (based on 1778 pedons). It has been shown that soils of the northern circumpolar permafrost region also contain significant quantities of SOC in the 100–300 cm depth range, but there has been no circumpolar compilation of pedon data to quantify this deeper SOC pool and there are no spatially distributed estimates of SOC storage below 100 cm depth in this region. Here we describe the synthesis of an updated pedon data set for SOC storage (kg C m−2) in deep soils of the northern circumpolar permafrost regions, with separate data sets for the 100–200 cm (524 pedons) and 200–300 cm (356 pedons) depth ranges. These pedons have been grouped into the North American and Eurasian sectors and the mean SOC storage for different soil taxa (subdivided into Gelisols including the sub-orders Histels, Turbels, Orthels, permafrost-free Histosols, and permafrost-free mineral soil orders) has been added to the updated NCSCDv2. The updated version of the data set is freely available online in different file formats and spatial resolutions that enable spatially explicit applications in GIS mapping and terrestrial ecosystem models. While this newly compiled data set adds to our knowledge of SOC in the 100–300 cm depth range, it also reveals that large uncertainties remain. Identified data gaps include spatial coverage of deep (> 100 cm) pedons in many regions as well as the spatial extent of areas with thin soils overlying bedrock and the quantity and distribution of massive ground ice. An open access data-portal for the pedon data set and the GIS-data sets is available online at http://bolin.su.se/data/ncscd/. The NCSCDv2 data set has a digital object identifier (doi:10.5879/ECDS/00000002).