Lateral Input Research Articles

Lateral line ablation by ototoxic compounds results in distinct rheotaxis profiles in larval zebrafish

The zebrafish lateral line is an established model for hair cell organ damage, yet few studies link mechanistic disruptions to changes in biologically relevant behavior. We used larval zebrafish to determine how damage via ototoxic compounds impact rheotaxis. Larvae were treated with CuSO4 or neomycin to disrupt lateral line function then exposed to water flow stimuli. Their swimming behavior was recorded on video then DeepLabCut and SimBA software were used to track movements and classify rheotaxis behavior, respectively. Lateral line-disrupted fish performed rheotaxis, but they swam greater distances, for shorter durations, and with greater angular variance than controls. Furthermore, spectral decomposition analyses confirmed that lesioned fish exhibited ototoxic compound-specific behavioral profiles with distinct changes in the magnitude, frequency, and cross-correlation between fluctuations in linear and angular movements. Our observations demonstrate that lateral line input is needed for fish to hold their station in flow efficiently and reveals that commonly used lesion methods have unique effects on rheotaxis behavior.

Dominant source areas shift seasonally from longitudinal to lateral contributions in a montane headwater stream

Montane ecoregions are important vehicles for downstream hydrologic function, but their dynamics are relatively understudied compared to alpine and subalpine catchments in the western United States. Montane catchments experience shifts in precipitation inputs seasonally, which results in spatiotemporal differences in source area contributions to the stream. We collected hydrometric and geochemical data between 2018 and 2021 from a 2.65 km2 semi-arid headwater catchment in the Front Range of Colorado, USA. Using a combined approach of hydrometric monitoring, geochemical characterization, and end-member mixing analysis (EMMA), we assess hydrologic connectivity between areas with high upslope accumulation and the stream. Within our study area, high upslope accumulation area corresponded to alluvial/ colluvial fans wherein we focused instrumentation and water sample collection. Using observed rainfall, and multiyear measurements of groundwater levels, soil moisture, and streamflow, we observed distinct hydrologic seasons within our catchment characterized by snowmelt during the spring, rainstorms during the summer, and a return to baseflow during the fall. Within this framework, we found that source areas to streamflow shift with longitudinal distance downstream, and among hydrologic seasons. Notably, our EMMA results indicate that contributions from upstream source areas become less important than lateral inputs from spring snowmelt into the fall return to baseflow. This was most pronounced at the upper catchment where upstream contributions to streamflow decreased up to 33.3% between spring and fall. These results suggest that streamflow is maintained by local source areas contributing laterally and vertically. Our results reflect dynamic shifts in hydrologic connectivity in space and in time, which are increasingly important to land and water resource management given rapid climate changes within the western United States.

Integration of Robust Control with Reinforcement Learning for Safe Autonomous Vehicle Motion

This paper presents a control design framework for the integration of robust control and reinforcement learning-based (RL) control agent. The proposed integration method is applied for motion control of autonomous road vehicles, providing safe motion. In the integrated motion control, longitudinal and lateral dynamics are incorporated. The high-performance motion of the vehicle, e.g., high-velocity motion, path following, and reduction of lateral acceleration, through the RL-based control agent is achieved. The training through Proximal Policy Optimization during episodes is performed. Safe motion with guaranteed performances, i.e., keeping limits on lateral error, through the robust control and the supervisor is achieved. The robust control is designed through the H∞ method, and in the supervisor, a constrained quadratic programming task is performed. As a result, lateral and longitudinal control inputs of the vehicle are calculated by the integrated control system. The effectiveness of the proposed control method using simulation scenarios and test scenarios on a small-scaled test vehicle is illustrated.

Litter inputs and standing stocks in riparian zones and streams under secondary forest and managed and abandoned cocoa agroforestry systems.

Cocoa is an important tropical tree crop that is mainly cultivated in agroforestry systems (AFS). This system, known as cabruca in northeastern Brazil, holds promise to reconcile biodiversity conservation and economic development. However, since cocoa AFS alters forest structure composition, it can affect litter dynamics in riparian zones and streams. Thus, our objective was to determine litter inputs and standing stocks in riparian zones and streams under three types of forest: managed cocoa AFS, abandoned cocoa AFS, and secondary forest. We determined terrestrial litter fall (TI), vertical (VI) and lateral (LI) litter inputs to streams, and litter standing stocks on streambeds (BS) in the Atlantic Forest of northeastern Brazil. Litter was collected every 30 days from August 2018 to July 2019 using custom-made traps. The litter was dried, separated into four fractions (leaves, branches, reproductive organs, and miscellaneous material) and weighed. Terrestrial litter fall was similar in all forests, ranging from 89 g m-2 month-1 in secondary forest (SF) to 96 g m-2 month-1 in abandoned cocoa AFS (AC). Vertical input were higher in AC (82 g m-2 month-1) and MC (69 g m-2 month-1) than in SF (40 g m-2 month-1), whereas lateral input were higher in MC (43 g m-2 month-1) than in AC (15 g m-2 month-1) and SF (24 g m-2 month-1). Standing stocks followed the order SF > AC > MC, corresponding to 425, 299 and 152 g m-2. Leaves contributed most to all litter fractions in all forests. Reproductive plant parts accounted for a larger proportion in managed AFS. Branches and miscellaneous litter were also similar in all forests, except for higher benthic standing stocks of miscellaneous litter in the SF. Despite differences in the amounts of litter inputs and standing stocks among the forests, seasonal patterns in the abandoned AFS (AC) were more similar to those of the secondary forest (SF) than the managed AFS, suggesting potential of abandoned AFS to restore litter dynamics resembling those of secondary forests.

Temporal-spatial distribution and ecological evaluation of macroinvertebrate functional feeding groups in Yongding River Basin

We investigated community structure of macroinvertebrate, water environment factors, hydrological factors at 23 sampling sites of the Yongding River basin from spring 2017 (April) to autumn 2017 (November). We analyzed the composition, spatial and temporal distribution of the macroinvertebrate functional feeding groups, as well as their responses to changes in riverine habitat. A total of 78 macroinvertebrate species were identified, with 52, 50 and 53 macroinvertebrate species in spring, summer and autumn respectively. The dominant functional feeding groups were gather-collectors, followed by predators, while the proportion of scrapers, filter-collectors and shredders were extremely low. Dominant species in the three seasons were all gather-collectors, including Orthocladius, Rheotanytarsus, Cricotopus in spring, Glyptotendipes in summer, and Polypedilum, Chironomus, Orthocladius in autumn. Results of redundancy analysis showed that the functional feeding groups of macroinvertebrate community structure were mainly influenced by water temperature, flow velocity, salinity, and total phosphorus in spring, by total phosphorus, dissolved oxygen, conductivity and flow capacity in summer, and by total phosphorus and dissolved oxygen in autumn. Total phosphorus had positive correlation with gather-collectors in all three seasons, indicating that the functional feeding groups of macroinvertebrates were affected by water pollution. The evaluation based on the metrics of functional feeding groups showed that: 1) in terms of material cycle, primary productivity of Guishui River were significantly higher than other regions, and that in autumn were significantly higher than other seasons. The secondary productivity and decomposition capacity of Yanghe River were significantly higher than other regions, and those in spring were significantly higher than other seasons. The autotrophy/heterotrophy of Yanghe River was significantly lower than other regions, and that in spring were significantly higher than other seasons. 2) The longitudinal transport capacity of Sanggan River was significantly higher than other regions, and that in autumn was significantly higher than other seasons. 3) The lateral input capacity of Guishui River was significantly higher than other regions, and that in summer was significantly higher than other seasons.

Subsurface Lateral Flows Buffer Riparian Water Stress Against Snow Drought

AbstractIn the Sierra Nevada, CA, the Mediterranean climate exposes montane forests to water stress during the summer drought. Normally, spring snowmelt alleviates summer water stress, especially in riparian ecosystems that receive subsurface lateral inputs from groundwater. However, snow drought could potentially eliminate these beneficial effects. This research investigates how subsurface lateral redistribution mediates hillslope‐scale vegetation responses to snow drought. We apply a spatially‐distributed ecohydrologic model (Regional Hydro‐Ecologic Simulation System (RHESSys)) to a snow‐dominated watershed in the Sierra Nevada. We incorporate observed sap flow data along a hillslope to estimate relative differences in water stress for upslope and riparian sites, and constrain RHESSys drainage parameter uncertainty. Our model results show that subsurface lateral inputs buffer riparian water stress against snow drought. For all drought types, both upslope and riparian sites experience substantial losses of net primary productivity (NPP), and on average upslope sites are more adversely affected (upslope loss of NPP = 45% vs. riparian = 28%). Dry droughts from a lack of rain or snow induce substantial loss of biomass for upslope and riparian trees because of low annual precipitation, but a small snowpack retained during cold, dry years slightly alleviates these effects and delays water stress by 2 weeks in riparian areas and 3 weeks upslope. While riparian forests are often buffered against drought stress, our study also shows that riparian forests can suffer from water stress. We found 21% of drought scenarios where riparian trees experience greater water stress than upslope trees that were mostly associated with wet and warm snow droughts.

Zebrafish (Danio rerio) shoaling in light and dark conditions involves a complex interplay between vision and lateral line

We know little about how - or even if in some species – fish shoal in darkness. We hypothesized that ‘dark shoaling’ occurs in zebrafish and therefore must depend upon lateral line sensory input. Shoaling in groups of five adult zebrafish was analyzed with motion tracking software. We measured average inter-individual distance, time near the arena wall (thigmotaxis zone) and total distance traveled under normal room light, and in near-complete darkness (infrared light at 850 nm). These observations were repeated in fish treated with cobalt chloride (CoCl2), which ablates lateral line function. In untreated controls, dark shoaling was reduced compared to in light, but nonetheless still present. Elimination of lateral line sensory input by CoCl2 treatment similarly reduced, but did not eliminate, shoaling under both light and dark. Our findings indicate that normal zebrafish shoaling in light or dark requires both visual and lateral line inputs, with neither alone sufficient for normal shoaling.

Application of concentration and 2-dimensional stable isotope measurements of methane to constrain sources and sinks in a seasonally stratified freshwater lake

Methane (CH4) emissions from aquatic systems have recently been comprised to account for up to 50% of global CH4 emissions, with lakes representing one of the largest CH4 sources within this pool. However, there is large uncertainty associated with CH4 emissions from freshwater environments to the atmosphere, because of a lack of understanding in the spatial and temporal dynamics of CH4 sources and sinks, as well as underlying mechanisms and processes. In this study, we investigated the concentrations and stable carbon (δ13C-CH4) and hydrogen (δ2H-CH4) isotope composition of CH4 in a small eutrophic lake (Lake Willersinnweiher) with seasonal stratification and its spatial and temporal variation. We found that while supersaturation of CH4 in the entire water column was present throughout the whole year, the isotopic composition of CH4 in sediment and water column varied depending on lake stratification, physiochemical conditions, and lake depth. During the stratification period, isotopic characteristics of pelagic surface water CH4 differed from littoral and sedimentary CH4, suggesting likely mixing of CH4 from different sources including vertical and lateral input as well as groundwater input and potentially oxic methane production in the mixed surface water layer. Aerobic CH4 oxidation indicated by a strong increase in both δ13C-CH4 and δ2H-CH4 values at the bottom of the oxycline was found to significantly reduce upward migrating CH4 released at the sediment-water interface. In the sediment, stable isotope characteristics of CH4 showed an increasing dominance of the acetoclastic CH4 formation pathway from the pelagic towards the littoral area. Furthermore, the occurrence of sulfate-dependent anaerobic methane oxidation in the sediment was suggested by an increase in δ13C-CH4 and δ2H-CH4 values. During the mixing period, the isotopic CH4 composition of the water column was distinctively less negative than during the stratification period potentially resulting from a greater impact of groundwater CH4 input compared to the stratification period. Our findings implicate that the application of concentrations and dual isotope measurements of CH4 is a promising approach for constraining CH4 sinks and sources in Lake Willersinnweiher and potentially other small lakes to clearly disentangle the complex CH4 dynamics in lakes both spatially and seasonally.

Lateral septum inputs to nucleus accumbens mediates stress induced suppression of natural reward seeking

Stress alters the level of reward evaluation and seeking. However, the neural circuitry mechanisms underlying stress induced effects on natural reward seeking remain unclear. Here we report a septal-accumbens pathway that mediates the effects of acute stress on reward seeking suppression. We first established the sucrose oral self-administration paradigm and measured the effects of acute stress on reward seeking behavior after 21 days of abstinence. Both forced swimming stress and foot shock stress significantly suppressed the natural reward seeking. Among a variety of brain regions, intermediolateral septum (LSi) appear as a strong stress-responsive area containing abundant c-Fos positive cells; chemogenetic inactivation of LSi reinstated the reward seeking behavior. To elucidate the downstream targets receiving LSi projections, we combined pathway-specific retro-labeling and chemogenetic manipulation to confirm the involvement of LSi-nucleus accumbens (NAc) rather than the Ventral tegmental area (VTA) in mediating the observed behavioral responses. In conclusion, the septal-accumbal projection constitute a discrete circuit dictating the stress evoked alterations on reward seeking and may implicate in treatment of stress induced anhedonia.

The legacy of forest logging on organic matter inputs and storage in tropical streams

AbstractRiparian forests play an important role in stream ecosystems, as they support biodiversity, reduce water erosion, and provide litter that fuels aquatic biota. However, they are affected by great array of anthropogenic threats (e.g., fire, logging, and organic pollution), which alter species composition and their physical structure. Although forest recovery after disturbance such as logging can take decades, the legacy of forest clear‐cut logging on key processes in tropical riparian ecosystems is mostly unknown. Here, we investigated how litter inputs (leaves, twigs, and reproductive parts) and storage, key processes for carbon and nutrient recycling and for forest and stream biota, are influenced by riparian vegetation undergoing succession (after 28 years from logging) through the comparison of reference and logged forest sites in the Cerrado biome. Litterfall was overall similar between forest types, but litterfall of twigs was twofold higher at logged than reference sites. Similarly, litter inputs from the bank to the stream (i.e., lateral inputs) and streambed storage were 50–60% higher at logged than reference sites. The higher litterfall observed in logged forests could be related to higher proportion of tree species that are characteristic of primary and secondary successional stages, including fast‐growing and liana species, which often are more productive and common in anthropogenic areas. Our results showed that the legacy impact of clear‐cut logging, even if residual woody vegetation is maintained in riparian buffers, can shift the type, quantity, and seasonality of litter subsidies to tropical streams. This knowledge should be considered within the context of management and conservation of communities and ecosystem processes in the forest‐stream interfaces.Abstract in Portuguese is available with online material.

Stream metabolism sources a large fraction of carbon dioxide to the atmosphere in two hydrologically contrasting headwater streams

AbstractHeadwater streams are control points for carbon dioxide (CO2) emissions to the atmosphere, with relative contributions to CO2 emission fluxes from lateral groundwater inputs widely assumed to overwhelm those from in‐stream metabolic processes. We analyzed continuous measurements of stream dissolved CO2 and oxygen (O2) concentrations during spring and early summer in two Mediterranean headwater streams from which we evaluated the contribution of in‐stream net ecosystem production (NEP) to CO2 emission. The two streams exhibited contrasting hydrological regimes: one was non‐perennial with relatively small groundwater inflows, while the other was perennial and received significant lateral groundwater inputs. The non‐perennial stream exhibited strong inverse coupling between instantaneous and daily CO2 and O2 concentrations, and a strong correlation between aerobic ecosystem respiration (ER) and gross primary production (GPP) despite persistent negative NEP. At the perennial stream, the CO2–O2 relationship varied largely over time, ER and GPP were uncorrelated, and NEP, which was consistently negative, increased with increasing temperature. Mean NEP contribution to CO2 emission was 51% and 57% at the non‐perennial and perennial stream, respectively. Although these proportions varied with assumptions about metabolic stoichiometry and groundwater CO2 concentration, in‐stream CO2 production consistently and substantially contributed to total atmospheric CO2 flux in both streams. We conclude that in‐stream metabolism can be more important for driving C cycling in some headwater streams than previously assumed.

Apparent shifts in the microplankton community in response to zinc and iron enrichments in the Northeastern Subarctic Pacific

The offshore Gulf of Alaska—in the northeastern subarctic Pacific—is a high-nitrate, low-chlorophyll (HNLC) oceanic region where concentrations of dissolved iron (DFe) and zinc (DZn) are of the order ~0.1 nmol kg−1 in surface waters. At the average winter mixed layer depth of ~120 m, DFe and DZn are of the orders ~0.1–0.2 nmol kg−1 and ~1–2 nmol kg−1, respectively. Vertical supply of Fe to surface waters is therefore limited, with phytoplankton blooms driven by episodic atmospheric and lateral inputs of Fe. In contrast, DZn is presumably replenished through seasonal vertical mixing, though maintained at low levels in surface waters, even in winter, implying that removal processes are in operation. Previous supplementation experiments have demonstrated that phytoplankton biomass (chl-a), growth, and drawdown of nitrate (NO3-) are stimulated strongly by Fe but only minimally, if at all, by Zn alone. Using on-deck bioassay incubations of surface waters, we confirm that the addition of Fe stimulates significant increases in chl-a and large diatoms, and drawdown of NO3- and silicic acid [Si(OH)4]. Associated drawdown of DZn and dissolved cadmium (DCd) indicated Zn stress in the control and +Fe treatment. Supplementation with Zn alone had no significant impact on NO3- and commonly monitored pigments such as chl-a and fucoxanthin. However, in the +Zn treatment, DFe and coccolithophore abundance were significantly lower, and the concentration of particulate organic carbon (POC) and that of the pigments alloxanthin and chlorophyll c1+2 were significantly higher than those in control incubations. Our experiment corroborates previously observed relationships between DZn and alloxanthin and chlorophyll c across the subarctic north Pacific and Bering Sea and could help to explain the low or undetectable concentrations of alloxanthin frequently observed in this region. Alloxanthin is a pigment specific to the cryptophytes, either within free-living cells or within functional plastids retained by mixotrophic protists. Both cryptophytes and mixotrophic ciliates, such as Laboea sp. and Strombidium spp., make a variable but significant contribution to phytoplankton biomass in this area. In the absence of Fe supply to surface waters, Zn could play a hitherto unsuspected role in shaping plankton communities in the HNLC Gulf of Alaska.

Deep learning for screening primary osteopenia and osteoporosis using spine radiographs and patient clinical covariates in a Chinese population.

PurposeMany high-risk osteopenia and osteoporosis patients remain undiagnosed. We proposed to construct a convolutional neural network model for screening primary osteopenia and osteoporosis based on the lumbar radiographs, and to compare the diagnostic performance of the CNN model adding the clinical covariates with the image model alone.MethodsA total of 6,908 participants were collected for analysis, including postmenopausal women and men aged 50–95 years, who performed conventional lumbar x-ray examinations and dual-energy x-ray absorptiometry (DXA) examinations within 3 months. All participants were divided into a training set, a validation set, test set 1, and test set 2 at a ratio of 8:1:1:1. The bone mineral density (BMD) values derived from DXA were applied as the reference standard. A three-class CNN model was developed to classify the patients into normal BMD, osteopenia, and osteoporosis. Moreover, we developed the models integrating the images with clinical covariates (age, gender, and BMI), and explored whether adding clinical data improves diagnostic performance over the image mode alone. The receiver operating characteristic curve analysis was performed for assessing the model performance.ResultsAs for classifying osteoporosis, the model based on the anteroposterior+lateral channel performed best, with the area under the curve (AUC) range from 0.909 to 0.937 in three test cohorts. The models with images alone achieved moderate sensitivity in classifying osteopenia, in which the highest AUC achieved 0.785. The performance of models integrating images with clinical data shows a slight improvement over models with anteroposterior or lateral images input alone for diagnosing osteoporosis, in which the AUC increased about 2%–4%. Regarding categorizing osteopenia and the normal BMD, the proposed models integrating images with clinical data also outperformed the models with images solely.ConclusionThe deep learning-based approach could screen osteoporosis and osteopenia based on lumbar radiographs.

Research on Lateral and Longitudinal Coordinated Control of Distributed Driven Driverless Formula Racing Car under High-Speed Tracking Conditions

Aiming at the problem that it is difficult to ensure the trajectory tracking accuracy and driving stability of the distributed driven driverless formula racing car under high-speed tracking conditions, a lateral and longitudinal coordinated control strategy is proposed. Based on the adaptive model predictive control theory, the lateral motion controller is designed, and the prediction time domain of the controller is changed in real time according to the change of vehicle speed. Based on the sliding mode variable structure control theory, a longitudinal motion controller is designed to accurately track the desired vehicle speed. Considering the coupling between the lateral and longitudinal controls, the lateral controller inputs the longitudinal speed and displacement of the vehicle, using the feedback mechanism to update the prediction model in real time, the longitudinal controller takes the front wheel angle as the input, the driving torque is redistributed through the differential drive control, and the lateral and longitudinal coordinated control is carried out to improve the trajectory tracking accuracy and driving stability. The typical working conditions are selected for co-simulation test verification. The results show that the lateral and longitudinal coordinated control strategy can effectively improve the vehicle trajectory tracking control accuracy and driving stability.

Complementing ERA5 and E-OBS with high-resolution river discharge over Europe

The 0.5° resolution of many global observational or quasi-observational datasets is not sufficient for the evaluation of current state-of-the-art regional climate models or the forcing of ocean model simulations over Europe. While higher resolved products are available for meteorological data, e.g. ERA5 reanalysis and the E-OBS vs 22 (EOBS22) datasets, they lack crucial information at the land-ocean boundary. ERA5 is frequently used to force regional climate models (RCMs) or ocean models and both datasets are commonly used as reference datasets for the evaluation of RCMs. Therefore, we extended both datasets with high-resolution river discharge for the period 1979–2018. On the one hand, our discharge data close the water cycle at the land-ocean interface so that the discharges can be used as lateral freshwater input for ocean models applied in the European region. On the other hand, the data can be used to identify trends in discharge that are induced by recent climate change as ERA5 and EOBS22 are rather independent datasets. The experimental setup to generate the discharges was chosen in a way that it could be easily adapted in a climate or Earth system modelling framework. Consequently, the recently developed 5 Min. horizontal resolution version of the hydrological discharge (HD) model was used to simulate discharge. It has already been applied in multiple climate modelling studies and is coupled within several global and regional Earth system models. As the HD model currently does not regard direct human impacts of the river runoff, it is well suited to investigate climate change-related discharge trends. In order to calculate the necessary gridded input fields for the HD model from ERA5 and EOBS22 data, we used the HydroPy global hydrological model. For both experiments, we found that the general behavior of discharge is captured well for many European rivers, which is consistent to earlier results. For the EOBS22 based discharges, a widespread low bias in simulated discharge occurs, which is likely caused by the missing undercatch correction in the underlying precipitation data. The analysis of trends over Southeastern Europe was hampered by missing data in EOBS22 after 2004. Using both experiments, we identified consistent trend patterns in various discharge statistics, with increases in low flow characteristics over Northern Europe and general drying trends over Central and Southern Europe. In summary, we introduced an experimental setup that is useful to generate high-resolution river runoff data consistent with the meteorological forcing for historical periods and future scenarios from any climate model data instead of having to rely on observed time series.

Groundwater discharge as a driver of methane emissions from Arctic lakes

Lateral CH4 inputs to Arctic lakes through groundwater discharge could be substantial and constitute an important pathway that links CH4 production in thawing permafrost to atmospheric emissions via lakes. Yet, groundwater CH4 inputs and associated drivers are hitherto poorly constrained because their dynamics and spatial variability are largely unknown. Here, we unravel the important role and drivers of groundwater discharge for CH4 emissions from Arctic lakes. Spatial patterns across lakes suggest groundwater inflows are primarily related to lake depth and wetland cover. Groundwater CH4 inputs to lakes are higher in summer than in autumn and are influenced by hydrological (groundwater recharge) and biological drivers (CH4 production). This information on the spatial and temporal patterns on groundwater discharge at high northern latitudes is critical for predicting lake CH4 emissions in the warming Arctic, as rising temperatures, increasing precipitation, and permafrost thawing may further exacerbate groundwater CH4 inputs to lakes.

A reinforcement learning backstepping‐based control design for a full vehicle active Macpherson suspension system

This paper presents a reinforcement learning backstepping-based control scheme for the design of a full vehicle active suspension system such that both the superior ride comfort and stabilization are achieved. It is well known that the traditional backstepping control scheme is suitable to solve higher order nonlinear system based on the strict-feedback form; however, the disadvantage of the procedure requires computing the derivatives of virtual control signals, which is a very complex task. Therefore, a reinforcement learning scheme using the deep deterministic policy gradient (DDPG) control strategy is developed to replace the process of finding virtual control force in backstepping method. It not only avoids the complexity of analytically calculating the derivatives of the virtual control signals, but also retains the systems robustness when there exist random disturbances from road irregularities. To verify the performance of the proposed active suspension control scheme, the random road unevenness profiles according to ISO 8608 is considered as vertical and lateral disturbance input excitation of a full-vehicle suspension system. Compared with conventional passive suspension system and backstepping control scheme, the proposed approach can be demonstrated to not only effectively improve ride comfort under random road excitation, but also improve the transient response and robustness.

Numerical analysis of midwinter infiltration along the soil-rock interface: A pathway for enhanced bedrock recharge

Shallow bedrock aquifers are prevalent across the Northern Hemisphere and can be the primary source of freshwater for many communities. Cryospheric impacts from climate warming are particularly concerning for bedrock aquifers where recharge is dominated by winter precipitation. For the management and protection of fractured rock groundwater supplies, the processes influencing infiltration and recharge under warmer winter conditions require a greater understanding. As such, a numerical investigation was undertaken with the objective of testing a conceptual model of midwinter infiltration and recharge near a granitic Canadian Shield bedrock outcrop using data collected over an unseasonably warm and rainy winter in eastern Ontario, Canada. Additional objectives were to determine if infiltration and recharge would be limited through frozen soils without an outcrop and to explore the hydrologic implications of an additional midwinter snowmelt event. Results supported the concept that outcrops provide preferential infiltration along the soil-rock interface at outcrop margins, which enables localized bedrock recharge under frozen conditions. To simulate soil moisture content near the outcrop, bedrock runoff was needed as additional lateral input in the lower soil profile (75 cm). The amount of runoff required as input was controlled by the hydraulic conductivity of the soil-rock interface. In the absence of an outcrop, limited midwinter infiltration occurs due to reduced permeabilities of frozen soils from repeated early winter rainfall and snowmelt events. Additional midwinter melt events can likely increase bedrock recharge, but the associated decline in snow depth deepens soil frost which delays further infiltration and increases surface runoff. Simulations suggest winter is becoming a more active time for bedrock recharge where outcrops are present, but wetter conditions have implications for frozen soil permeability. Findings extend to similar seasonally frozen bedrock environments which are relied on as a source of freshwater and are rapidly changing under a warming climate.

Magnitude and Origin of CO2 Evasion From High‐Latitude Lakes

AbstractLakes evade significant amounts of carbon dioxide (CO2) to the atmosphere; yet the magnitude and origin of the evasion are still poorly constrained. We quantified annual CO2 evasion and its origin (in‐lake net ecosystem production vs. lateral inputs from terrestrial ecosystems) in 14 high‐latitude lakes through high‐frequency estimates of open water CO2 flux and ecosystem metabolism and inorganic carbon mass‐balance before and after ice breakup. Annual CO2 evasion ranged from 1 to 25 g C m−2 yr−1 of which an average of 57% was evaded over a short period at ice‐breakup. Annual internal CO2 production ranged from −6 to 21 g C m−2 yr−1, of which at least half was produced over winter. The contribution of internal versus external source contribution to annual CO2 evasion varied between lakes, ranging from fully internal to fully external with most lakes having over 75% of the evasion sustained through a single source. Overall, the study stresses the large variability in magnitude and control of CO2 evasion and suggests that environmental change impacts on CO2 evasion from high‐latitude lakes are not uniform.

Valve control of a hydraulically interconnected suspension system to improve vehicle handling qualities

This paper deals with the control of a hydraulically interconnected suspension system to improve the handling performance of the vehicle. A seven-degrees-of-freedom MATLAB/Simulink vehicle model and an Adams/Car model are used for simulation purposes. A Simscape model for analysing the hydraulic subsystem is also employed. It was observed that the yaw rate and roll responses of the vehicle are influenced to a large extent by the flow control valve opening values. The handling performance of the vehicle was investigated by the control of the orifice valves and their adjustment according to the lateral acceleration inputs. Considerable improvements were obtained in the handling qualities without sacrificing the ride responses, compared to the responses of a passive interconnected suspension.