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The impacts of aging and process variations on the performance of VLSI systems is increasing with each process generation. The conventional way to counteract them are extensive guard bands, which are calculated at system design time. Hence, they are necessarily worst case guard bands, i.e., most often too pessimistic. Current research tries to mitigate this by means of in-situ performance measurement based adaptive voltage scaling (AVS). The performance measurement is typically determined by means of dedicated sensors or canary logic. The parametrization of such AVS systems relies on assumptions regarding the relative behavior of the sensor and the application logic. Most published approaches use manually gained empirical data for this purpose. However, an automatic calibration procedure is needed for the practical application of these approaches. We propose such an automated calibration procedure and evaluate it on multiple FPGAs to consider the effects of aging and process variation. Furthermore, we use two designs to cover leakage power and dynamic power dominated scenarios. We achieve average power savings of 67% for a leakage dominated design and 48% for a test case with dominant dynamic power. Furthermore, we investigate the limitations of AVS systems regarding their capability to counteract fast disturbances, e.g., voltage drop.

This paper considers data from centrifuge model tests on pile groups in silica sand involving lateral one-way cyclic loading. The influence of cyclic load amplitude, pile spacing within the pile group and number of cycles on the observed response are highlighted. Investigating the contribution of each pile on the lateral capacity shows leading row piles exhibit highest bending moments and attract larger loads due to ‘shadowing’ effects. Cyclic loading results in a subtle change of the load distribution within the pile group, with the load gradually shifting from the leading to the trailing piles as the number of cycles increases. The effect of cyclic loading on the initial stiffness of the p–y curves is more significant; initial stiffness reduces with increasing number of loading cycles at a rate that is higher in the leading row than in the trailing row. The changes in load distribution are quantified using simple analytical equations that may be used in design.

Approximate or inexact arithmetic is a promising approach towards lower power consumption for applications that can tolerate a certain amount of imprecision. As human perception is limited in its precision, this applies to image and audio processing. Beyond, other applications like neuronal networks or AI processing can benefit from such arithmetic as well, as they are inherently tolerant to a certain amount of inaccuracy. One of the most critical components of arithmetic circuits regarding power, delay, and area are multipliers. Various sophisticated approaches towards approximate multipliers are already published for ASICs. However, such ASIC approaches are under-performing in conjunction with the specific Lookup-Table (LUT)-based design of FPGAs. As FPGAs gain in importance for applications like signal processing, there is a substantial lack of approximate design methodology for FPGAs. We propose an approach towards approximate signal processing that is specifically tailored towards the LUT-based hardware of FPGAs. It allows for significant performance improvements while lowering the energy demands. While introducing an insignificant average relative error of just 0.14%, we achieve a 45.9% area reduction in terms of LUTs while decreasing the delay by 30.6% compared to the Xilinx Vivado multiplier IP core. Our proposed design is open source and available at https://github.com/niemann-c/approx-mult-for-fpga.

The frequency and severity of drought increase in many regions of the world, which emphasizes the need for sufficient research to better monitor and trigger management plans. An important role hereby plays hydrological drought, because it affects water supply and crop yields that are necessary to ensure food security. Typically, hydrological drought detection is based on in-situ observations of fluxes or storages at the surface. However, this neglects the fact that drought might occur in multiple storages with different timing and severity. The use of subsurface storage, e.g. groundwater, is rare because the available in-situ well level monitoring is irregularly distributed in space and time and access might be restricted, for example due to national security reasons or problems in converting them to storage estimates.The satellite mission Gravity Recovery and Climate Experiment (GRACE) and its successor GRACE-FO offer a great possibility to observe the total water storage, i.e. the sum of surface and subsurface storages, on a global scale from space. However, GRACE is restricted to monthly data on a spatial resolution of about 300 km and the vertical sum of the storages. Hydrological models present another possibility to derive global storage information with a finer spatial (~50km), temporal and vertical resolution than GRACE but they do not perfectly represent the reality because they are underlying assumptions and are affected by uncertainty of forcing data. Therefore, to enable downscaling of GRACE while improving the models realism, the GRACE measurements are assimilated into a hydrological model.In previous works we used a framework that assimilates GRACE into the WaterGAP Global Hydrological Model (WGHM) regionally or basin-wise. In this work we present a new framework that globally assimilates GRACE on a 4 degree grid with full uncertainty information from 2003 to 2018. The framework enables to assimilate about 95% of the global WGHM land surface except Greenland. With regard to vertical and spatial resolution the performance of model, observation and assimilation is compared. Global GRACE based drought indicators are applied and its development in the different compartments of surface water, soil and groundwater is analyzed to identify new insights into the propagation of drought. We expect that by including GRACE we derive new information especially for groundwater droughts, which might reveal time lags and a different severity as compared to surface water droughts for some regions.

Global hydrological models simulate water storages and fluxes of the water cycle which is important for e.g. water management decisions and drought/flood predictions. However, the models include many uncertainties due to the model inputs (e.g. climate forcing data), model parameters, and model structure resulting in disagreements with observations. To reduce these uncertainties, the models are typically calibrated against in-situ discharge observations or GRACE-derived total water storage anomalies (TWSA) are integrated into the model by data assimilation.In this study, we introduce a framework for jointly assimilating multiple observations into the WaterGAP 2.2d model over the Mississippi River Basin for 2003-2018. We do not only assimilate GRACE-derived TWSA but also in-situ discharge observations from gauge stations. In addition, we vary the number as well as the location of the considered discharge stations to derive information about e.g. the influence of assimilating down- or upstream stations.Our results show a strong influence of the GRACE data and that the assimilation of multiple discharge stations resembles the results of a traditional calibration approach. We expect the most downstream stations to have a larger impact on the assimilation results than the more upstream stations (as the downstream stations already include the information of the upstream stations). The gained insights of this study show a great potential to better assess and understand the global freshwater system and become even more relevant in view of the Surface Water and Ocean Topography (SWOT) satellite. SWOT will be launched in 2022 and is expected to allow the derivation of discharge observations globally for rivers wider than 50-100m.

WaterGAP is a global hydrological model that quantifies human use of groundwater and surface water as well as water flows and water storage and thus water resources on all land areas of the Earth. Since 1996, it has served to assess water resources and water stress both historically and in the future, in particular under climate change. It has improved our understanding of continental water storage variations, with a focus on overexploitation and depletion of water resources. In this paper, we describe the most recent model version WaterGAP 2.2d, including the water use models, the linking model that computes net abstractions from groundwater and surface water and the WaterGAP Global Hydrology Model WGHM. Standard model output variables that are freely available at a data repository are explained. In addition, the most requested model outputs, total water storage anomalies, streamflow and water use, are evaluated against observation data. Finally, we show examples of assessments of the global freshwater system that can be done with WaterGAP2.2d model output.

Context. Long-term deep brain stimulation (DBS) studies in rodents are of crucial importance for research progress in this field. However, most stimulation devices require jackets or large head-mounted systems which severely affect mobility and general welfare influencing animals’ behavior. Objective. To develop a preclinical neurostimulation implant system for long-term DBS research in small animal models. Approach. We propose a low-cost dual-channel DBS implant called software defined implantable platform (STELLA) with a printed circuit board size of Ø13 × 3.3 mm, weight of 0.6 g and current consumption of 7.6 µA/3.1 V combined with an epoxy resin-based encapsulation method. Main results. STELLA delivers charge-balanced and configurable current pulses with widely used commercial electrodes. While in vitro studies demonstrate at least 12 weeks of error-free stimulation using a CR1225 battery, our calculations predict a battery lifetime of up to 3 years using a CR2032. Exemplary application for DBS of the subthalamic nucleus in adult rats demonstrates that fully-implanted STELLA neurostimulators are very well-tolerated over 42 days without relevant stress after the early postoperative phase resulting in normal animal behavior. Encapsulation, external control and monitoring of function proved to be feasible. Stimulation with standard parameters elicited c-Fos expression by subthalamic neurons demonstrating biologically active function of STELLA. Significance. We developed a fully implantable, scalable and reliable DBS device that meets the urgent need for reverse translational research on DBS in freely moving rodent disease models including sensitive behavioral experiments. We thus add an important technology for animal research according to ‘The Principle of Humane Experimental Technique’—replacement, reduction and refinement (3R). All hardware, software and additional materials are available under an open source license.

Pallidal deep brain stimulation (DBS) is an important option for patients with severe dystonias, which are thought to arise from a disturbance in striatal control of the globus pallidus internus (GPi). The mechanisms of GPi-DBS are far from understood. Although a disturbance of striatal function is thought to play a key role in dystonia, the effects of DBS on cortico-striatal function are unknown. We hypothesised that DBS, via axonal backfiring, or indirectly via thalamic and cortical coupling, alters striatal function. We tested this hypothesis in the dtsz hamster, an animal model of inherited generalised, paroxysmal dystonia. Hamsters (dystonic and non-dystonic controls) were bilaterally implanted with stimulation electrodes in the GPi. DBS (130 Hz), and sham DBS, were performed in unanaesthetised animals for 3 h. Synaptic cortico-striatal field potentials, as well as miniature excitatory postsynaptic currents (mEPSC) and firing properties of medium spiny striatal neurones were recorded in brain slice preparations obtained immediately after EPN-DBS. The main findings were as follows: a. DBS increased cortico-striatal evoked responses in healthy, but not in dystonic tissue. b. Commensurate with this, DBS increased inhibitory control of these evoked responses in dystonic, and decreased inhibitory control in healthy tissue. c. Further, DBS reduced mEPSC frequency strongly in dystonic, and less prominently in healthy tissue, showing that also a modulation of presynaptic mechanisms is likely involved. d. Cellular properties of medium-spiny neurones remained unchanged. We conclude that DBS leads to dampening of cortico-striatal communication, and restores intrastriatal inhibitory tone.

BackgroundDeep brain stimulation (DBS) of the globus pallidus internus (GPi) is considered to be the most relevant therapeutic option for patients with severe dystonias, which are thought to arise from a disturbance in striatal control of the GPi, possibly resulting in thalamic disinhibition. The mechanisms of GPi-DBS are far from understood. Hypotheses range from an overall silencing of target nuclei (due to e.g. depolarisation block), via differential alterations in thalamic firing, to disruption of oscillatory activity in the β-range. Although a disturbance of striatal function is thought to play a key role in dystonia, the effects of DBS on cortico-striatal function are unknown.ObjectiveWe hypothesised that DBS, via axonal backfiring, or indirectly via thalamic and cortical coupling, alters striatal network function. We aimed to test this hypothesis in the dtsz-hamster, an animal model of inherited generalised, paroxysmal dystonia.MethodsHamsters (dtsz-dystonic and non-dystonic controls) were bilaterally implanted with stimulation electrodes targeting the entopeduncular nucleus (EPN, equivalent of human GPi). DBS (130 Hz), and sham DBS, were performed in unanaesthetised animals for 3 hours. Synaptic cortico-striatal field potential responses, as well as miniature excitatory postsynaptic currents (mEPSC) and firing properties of medium spiny striatal neurons were subsequently recorded in brain slice preparations obtained from these animals immediately after EPN-DBS, to gauge synaptic responsiveness of cortico-striatal projections, their inhibitory control, and striatal neuronal excitability.ResultsDBS increased cortico-striatal responses in slices from control, but not dystonic animals. Inhibitory control of these responses, in turn, was differentially affected: DBS increased inhibitory control in dystonic, and decreased it in healthy tissue. A modulation of presynaptic mechanisms is likely involved, as mEPSC frequency was reduced strongly in dystonic, and less prominently in healthy tissues, while cellular properties of medium-spiny neurons remained unchanged.ConclusionDBS leads to dampening of cortico-striatal communication with restored inhibitory tone.

Remote sensing data are essential for monitoring the Earth’s surface waters, especially since the amount of publicly available in-situ data is declining. Satellite altimetry provides valuable information on the water levels and variations of lakes, reservoirs and rivers. In combination with satellite imagery, the derived time series allow the monitoring of lake storage changes and river discharge. However, satellite altimetry is limited in terms of its spatial resolution due to its measurement geometry, only providing information in the nadir direction beneath the satellite’s orbit. In a case study in the Mississippi River Basin (MRB), this study investigates the potential and limitations of past and current satellite missions for the monitoring of basin-wide storage changes. For that purpose, an automated target detection is developed and the extracted lake surfaces are merged with the satellites’ tracks. This reveals that the current altimeter configuration misses about 80% of all lakes larger than 0.1 km2 in the MRB and 20% of lakes larger than 10 km2, corresponding to 30% and 7% of the total water area, respectively. Past altimetry configurations perform even more poorly. From the larger water bodies represented by a global hydrology model, at least 91% of targets and 98% of storage changes are captured by the current altimeter configuration. This will improve significantly with the launch of the planned Surface Water and Ocean Topography (SWOT) mission.

The Right-Hand Resonant Instability (RHI) is one of several electromagnetic ion/ion beam instabilities responsible for the formation of parallel magnetized collisionless shocks and the generation of ultra-low frequency (ULF) waves in their foreshocks. This instability has been observed for the first time under foreshock-relevant conditions in the laboratory through the repeatable interaction of a preformed magnetized background plasma and a super-Alfvenic laser-produced plasma. This platform has enabled unprecedented volumetric measurements of waves generated by the RHI, revealing filamentary current structures in the transverse plane. These measurements are made in the plasma rest frame with both high spatial and temporal resolution, providing a perspective that is complementary to spacecraft observations. Direct comparison of data from both the experiment and the Wind spacecraft to 2D hybrid simulations demonstrates that the waves produced are analogous to the ULF waves observed upstream of the terrestrial bow shock.

Several applications, from water resource management to the prediction of extreme events, require a realistic representation of the global water cycle. Global hydrological models simulate continental water fluxes and individual storages. However, they poorly reproduce observations of discharge and total water storage anomalies (TWSA). To improve the realism of the simulations, TWSA derived from the Gravity Recovery and Climate Experiment (GRACE) mission are usually assimilated into hydrological models.However, while assimilating GRACE-TWSA yields more realistic TWSA simulations, it is not clear how it affects the simulation of individual storages and fluxes. Therefore, assimilating discharge, in-situ or derived from satellite-altimetry, has been suggested to improve simulated discharge which is especially important for ungauged parts of basins.In this study, we jointly assimilate GRACE-TWSA and discharge observations and, for the first time, simultaneously calibrate the model parameters in order to improve the simulation skills of the model beyond the observational time frame. For this, we couple the WaterGAP 2.2d model with the Parallel Data Assimilation Framework and apply an Ensemble Kalman Filter for the Mississippi River Basin from 2003 to 2016. Furthermore, we compare our results to single-data assimilation and validate them against discharge observations that were not used for calibration/assimilation. Additionally, we analyze the effect of the calibrated parameters on the model’s realism.

Freshwater availability is of vital importance for humans, freshwater biota and ecosystem functions. In the past decades, global hydrological models (GHMs) were developed to improve understanding of the global freshwater situation in a globalized word, by filling gaps in observational coverage and assessing scenarios of the future under consideration of different socioeconomic developments and climate change. The Water Global Assessment and Prognosis (WaterGAP) model was one of the first GHMs developed to evaluate freshwater resources and their use for both historical and future conditions. It consists of five water use models (for irrigation, domestic, cooling of thermal power plants, manufacturing, and livestock sectors) and the WaterGAP Global Hydrology Model (WGHM). Recently, the latest model version, WaterGAP 2.2d, was finalized, containing a number of enhancements and revisions such as a river storage-based flow velocity approach, improvements in modelling groundwater recharge in dry environments and integration of historical development of irrigated areas.This presentation provides an overview about the WaterGAP 2.2d scheme and features, assesses global freshwater resources (runoff and streamflow) and water balance components, and provides insights to evaluation results against observed streamflow, GRACE total water storage and the AQUASTAT database.

State of the art global hydrological models (GHMs) are able to assess continental water storages and fluxes. Different current GHMs provide conflicting estimates of e.g. evapotranspiration or discharge, resulting in differing water availability or climate change impact estimates. The Global Calibration and Data Assimiliation project (GlobalCDA) aims at enhancing our understanding of global freshwater resources by combining state-of-the-art hydrological modelling with new data assimilition and calibration methods using multiple geodetic and remote sensing data.This study is part of the hydrological model development efforts within GlobalCDA and analyzes the effect of the adaptation and implementation of an existing dynamic floodplain model (Adam, 2017) into WaterGAP2.2d, a state-of-the-art GHM. The implemented floodplain model approach combines the modeling of a two-way river-floodplain interaction, downstream water transport within river and floodplain and flood-plain-groundwater interactions. The effect of information on the water level of surface water bodies on the model results is assessed using the Amazon basin as study area. Observed river discharge is used to assess the changes in model efficiency as floodplains and other wetlands have a strong impact on river discharge dynamics. This study shows the value of the modeling of large floodplains and wetlands for an improved estimation of terrestrial water cycle components.

Global-scale gradient-based groundwater models are a new endeavor for hydrologists who wish to improve global hydrological models (GHMs). In particular, the integration of such groundwater models into GHMs improves the simulation of water flows between surface water and groundwater and of capillary rise and thus evapotranspiration. Currently, these models are not able to simulate water table depth adequately over the entire globe. Unsatisfactory model performance compared to well observations suggests that a higher spatial resolution is required to better represent the high spatial variability of land surface and groundwater elevations. In this study, we use New Zealand as a testbed and analyze the impacts of spatial resolution on the results of global groundwater models. Steady-state hydraulic heads simulated by two versions of the global groundwater model G3 M, at spatial resolutions of 5 arc-minutes (9 km) and 30 arc-seconds (900 m), are compared with observations from the Canterbury region. The output of three other groundwater models with different spatial resolutions is analyzed as well. Considering the spatial distribution of residuals, general patterns of unsatisfactory model performance remain at the higher resolutions, suggesting that an increase in model resolution alone does not fix problems such as the systematic overestimation of hydraulic head. We conclude that (1) a new understanding of how low-resolution global groundwater models can be evaluated is required, and (2) merely increasing the spatial resolution of global-scale groundwater models will not improve the simulation of the global freshwater system.

Connected mobile and embedded devices including tablets, smartphones, and smartwatches but also IoT sensors and actuators as well as medical implants are subject to a rapid development in terms of their numbers and computing power. However, these devices have energy limitations, e.g., due to limited energy supplies. In order for networked devices to be able to manage their energy, they can offload tasks to other devices. However, they need to estimate the energy demand to execute the tasks in order to take offloading decisions. This paper proposes energy models for estimating the energy consumption for task processing derived from practical measurements for exemplary tasks. The task-processing energy consumption models are implemented in the OMNeT++ simulator to allow simulative, accurate task-offloading investigations.

Bone defects can be the result of physiological atrophy, diseases, or medical intervention. Bone regeneration under electrical stimulation has been proven to be a promising approach in cell experiments. However, there is a lack of evidence of the respective effect in animal trials. This is limited because there are no fully implantable stimulators at hand. Therefore, the aim of our present study is the description of requirements and design of an implantable electrical stimulator for bone regeneration experiments.

Significance Using a compilation of 14C and pollen data of lake sediment records from over 632 sites globally, we identified the timings of first increase in lake sedimentation. Changes in lake sediment rates at this time are closely linked to increased sediment supply from hillslope erosion. The analysis on the relative roles of the driving factors indicated that a significant portion of the Earth’s surface shifted to human-driven soil erosion already 4,000 y ago following land deforestation. The long-term perspective afforded by this synthesis provides evidence that human beings are a geological force that have altered lateral soil and sediment transfers globally well before the great acceleration in human activity post-World War II and before the start of the Industrial Revolution., Accelerated soil erosion has become a pervasive feature on landscapes around the world and is recognized to have substantial implications for land productivity, downstream water quality, and biogeochemical cycles. However, the scarcity of global syntheses that consider long-term processes has limited our understanding of the timing, the amplitude, and the extent of soil erosion over millennial time scales. As such, we lack the ability to make predictions about the responses of soil erosion to long-term climate and land cover changes. Here, we reconstruct sedimentation rates for 632 lakes based on chronologies constrained by 3,980 calibrated 14C ages to assess the relative changes in lake-watershed erosion rates over the last 12,000 y. Estimated soil erosion dynamics were then complemented with land cover reconstructions inferred from 43,669 pollen samples and with climate time series from the Max Planck Institute Earth System Model. Our results show that a significant portion of the Earth surface shifted to human-driven soil erosion rate already 4,000 y ago. In particular, inferred soil erosion rates increased in 35% of the watersheds, and most of these sites showed a decrease in the proportion of arboreal pollen, which would be expected with land clearance. Further analysis revealed that land cover change was the main driver of inferred soil erosion in 70% of all studied watersheds. This study suggests that soil erosion has been altering terrestrial and aquatic ecosystems for millennia, leading to carbon (C) losses that could have ultimately induced feedbacks on the climate system.

We have developed a solid state probe for an absolute irradiance calibration of the Thomson scattering system on the Large Plasma Device (LAPD), based on Raman scattering off silica. Measurements performed with a triple-grating spectrometer have investigated the intensities of a pulsed laser beam Raman scattered off crystalline and amorphous silica over a range of temperatures of relevance to the LAPD (299 - 498 K). The data were compared with Rayleigh and Raman scattering intensities in gaseous nitrogen. The measurements show that Raman scattering off quartz allows rapid and accurate alignment and calibration of Thomson scattering systems in plasma physics experiments that cannot be calibrated using conventional methods.

Mach–Zehnder electrooptic intensity modulators (EOM) provide efficient intensity modulation in optical systems and can be used to shape laser pulses. It is necessary to avoid a low extinction ratio—which can cause a significant prepulse—by maintaining a low base modulation. The EOM’s modulation can be modeled by its nonlinear transfer function and is dependent on environmental conditions. A feedback algorithm was devised to regulate the EOM’s base intensity output and account for these dynamic environmental conditions. The field programmable gate array-based control algorithm interlaces a set of diagnostic pulses between the laser’s main pulses to map the transfer function. After mapping, the algorithm utilizes curve fitting to accurately target the minimum of the EOM’s transfer function and maintain the EOM’s highest possible extinction ratio. Testing demonstrated the effectiveness of the algorithm in maintaining a high extinction ratio in response to both the temperature and temporal drift of the transfer function.