The role of self-related information in the sense of agency.

Sense of agency (SoA) refers to the subjective experience of controlling one's actions and their subsequent consequences. The present study endeavors to investigate the impact of how different degrees of self-related stimuli as action outcomes on the sense of agency by observing the temporal binding effect. Results showed that self-related sound significantly altered temporal binding, notably influencing outcome binding. A post-hoc explanation model effectively elucidated the role of self-related information in the formation of the sense of agency.

Global Sensitivity Analysis of the Advanced ORYZA-N Model with Different Rice Types and Irrigation Regimes.

Identifying important parameters in crop models is critical for model application. This study conducted a sensitivity analysis of 23 selected parameters of the advanced rice model ORYZA-N using the Extended FAST method. The sensitivity analysis was applied for three rice types (single-season rice in cold regions and double-season rice (early rice and late rice) in subtropical regions) and two irrigation regimes (traditional flood irrigation (TFI) and shallow-wet irrigation (SWI)). This study analyzed the parameter sensitivity of six crop growth outputs at four developmental stages and yields. Furthermore, we compared the variation in parameter sensitivity on model outputs between TFI and SWI scenarios for single-season rice, early rice, and late rice. Results indicated that parameters RGRLMX, FRPAR, and FLV0.5 significantly affected all model outputs and varied over developmental stages. Water stress in paddy fields caused by water-saving irrigation had more pronounced effects on single-season rice than on double-season rice.

Evidence for Quantum Stripe Ordering in a Triangular Optical Lattice.

Understanding strongly correlated quantum materials, such as high-T_{c} superconductors, iron-based superconductors, and twisted bilayer graphene systems, remains as one of the outstanding challenges in condensed matter physics. Quantum simulation with ultracold atoms in particular optical lattices, which provide orbital degrees of freedom, is a powerful tool to contribute new insights to this endeavor. Here, we report the experimental realization of an unconventional Bose-Einstein condensate of ^{87}Rb atoms populating degenerate p orbitals in a triangular optical lattice, exhibiting remarkably long coherence times. Using time-of-flight spectroscopy, we observe that this state spontaneously breaks the rotational symmetry and its momentum spectrum agrees with the theoretically predicted coexistence of exotic stripe and loop-current orders. Like certain strongly correlated electronic systems with intertwined orders, such as high-T_{c} cuprate superconductors, twisted bilayer graphene, and the recently discovered chiral density-wave state in kagome superconductors AV_{3}Sb_{5} (A=K, Rb, Cs), the newly demonstrated quantum state, in spite of its markedly different energy scale and the bosonic quantum statistics, exhibits multiple symmetry breakings at ultralow temperatures. These findings hold the potential to enhance our comprehension of the fundamental physics governing these intricate quantum materials.

Revealing the infiltration process and retention mechanisms of surface applied free DNA tracer through soil under flood irrigation.

It has been recently demonstrated that free DNA tracers have the potential in tracing water flow and contaminant transport through the vadose zone. However, whether the free DNA tracer can be used in flood irrigation area to track water flow and solute/contaminant transport is still unclear. To reveal the infiltration process and retention mechanisms of surface applied free DNA tracer through soil under flood irrigation, we tested the fate and transport behavior of surface applied free DNA tracers through packed saturated sandy soil columns with a 10 cm water head mimicking flood irrigation. From the experimental breakthrough curves and by fitting a two-site kinetic sorption model (R2 = 0.83-0.91 and NSE = 0.79-0.89), adsorption/desorption rates could be obtained and tracer retention profiles could be simulated. Together these results revealed that 1) the adsorption of free DNA was dominantly to clay particles in the soil, which took up 1.96 % by volume, but took up >97.5 % by surface area and densely cover the surface of sand particles; and 2) at a pore water pH of 8.0, excluding the 4.9 % passing through and 3.1 % degradation amount, the main retention mechanisms in the experimental soil were ligand exchange (42.0 %), Van der Waals interactions (mainly hydrogen bonds), electrostatic forces and straining (together 44.7 %), and cation bridge (5.3 %). To our knowledge, this study is the first to quantify the contribution of each of the main retention mechanisms of free synthetic DNA tracers passing through soil. Our findings could facilitate the application of free DNA tracer to trace vadose zone water flow and solute/contaminant transport under flood irrigation and other infiltration conditions.

Stand transpiration and canopy conductance dynamics of Populus popularis under varying water availability in an arid area.

As a tree species of shelterbelts, Populus popularis maintains significant ecological functions in arid and semiarid areas. However, stand transpiration (T) and canopy conductance (gc) dynamics of P. popularis are unclear in arid irrigated areas with shallow groundwater fluctuations. To better understand the responses of T and gc to meteorological factors, soil water, and shallow groundwater in arid areas, we observed the environmental conditions and sap flow of P. popularis, and quantified T and gc in three growing seasons of 2018-2020 in a typical arid area of China. Results showed T and gc ranged from 0.18 to 6.11 mm day-1 and 2.26-12.54 mm s-1 in 2018-2020, respectively. Solar radiation and vapor pressure deficit (VPD) were major drivers of T at daily scales. It was consistently found that T exponentially decreased with increasing groundwater table depth (GTD) and decreasing reference evapotranspiration in three years. gc is primarily influenced by VPD and is positively related to soil water content in 0-30 cm soil layer (SWC0-30 cm). Moreover, low SWC0-30 cm and deepening GTD jointly decreased T and gc by 22.45 % and 30.41 %, respectively. The response of gc to VPD was susceptible to groundwater fluctuations, and the synergistic influences of VPD and GTD on gc could be well described by the logarithmic function, especially in 2019. The sensitivity of gc to VPD and its variations under different environmental conditions suggested that a flexible stomatal regulation of transpiration occurred in the observed P. popularis with the arid climate and shallow groundwater. These findings provided the essential basis for the water use strategy of P. popularis and stand water resources management in arid regions.

Acute psychosocial stress weakens the sense of agency in healthy adults.

The sense of agency (SoA) refers to the feeling of being in control of one's actions and the subsequent consequence of these actions. Emotional context seems to alter the strength of sense of agency. The present study explored the influence of acute psychosocial stress on the SoA by means of the Trier Social Stress Test (TSST). Self-assessment manikin (SAM) and objective physiological indicators (e.g. heart rate, electrodermal activity, and salivary cortisol levels) were utilized to evaluate the effect of the TSST. We also employed the temporal binding effect as an implicit assessment of the participant's SoA. The results indicated that the stress level of the experimental group after TSST was significantly higher than the control group, whilst the temporal binding scores of the experimental group decreased after TSST manipulation. In short, acute psychosocial stress with intense emotional arousal weakened the sense of agency.

The Functional Brain Network of Subcortical and Cortical Regions Underlying Time Estimation: An Functional MRI Study.

Time estimation is fundamental for human survival. There have been increasing studies suggesting that distributed brain regions, such as the basal ganglia, cerebellum and the parietal cortex, may contribute to a dedicated neural mechanism of time estimation. However, evidence on the specific function of the subcortical and cortical brain regions and the interplay of them is scare. In this work, we explored how the subcortical and cortical networks function in time estimation during a time reproduction task using functional MRI (fMRI). Thirty healthy participants performed the time reproduction task in both auditory and visual modalities. Results showed that time estimation in visual and auditory modality recruited a subcortical-cortical brain network including the left caudate, left cerebellum, and right precuneus. Besides, the superior temporal gyrus (STG) was found essential in the difference between time estimation in visual and auditory modality. Using psychophysiological interaction (PPI) analysis, we observed an increase in the connection between left caudate and left precuneus using the left caudate as the seed region in temporal reproduction task than control task. This suggested that the left caudate is the key region connecting and transmitting information to other brain regions in the dedicated brain network of time estimation.

Lignite bioorganic fertilizer enhanced microbial co-occurrence network stability and plant-microbe interactions in saline-sodic soil.

Lignite-converted bioorganic fertilizer substantially improves soil physiochemical properties, but little is known about how lignite bioorganic fertilizer (LBF) affects soil microbial communities and how the changed microbial communities impact their stability, functions, and crop growth in saline-sodic soil. Therefore, a two-year field experiment was conducted in saline-sodic soil in the upper Yellow River basin, Northwest China. Three treatments, i.e., the control treatment without organic fertilizer (CK), the farmyard manure treatment (FYM) amended with 21 t ha-1 (same as local farmers) sheep manure, and the LBF treatment amended with the optimal rate of LBF (3.0 and 4.5 t ha-1), were designed in this study. The results showed that after two years of application of LBF and FYM, the percentage of aggregate destruction (PAD) was significantly reduced by 14.4 % and 9.4 %, respectively, while the saturated hydraulic conductivity (Ks) was obviously increased by 114.4 % and 99.7 %, respectively. The LBF treatment significantly increased the contributions of nestedness to total dissimilarity by 101.4 % and 156.2 % in bacterial and fungal communities, respectively. LBF contributed to the shift from stochasticity to variable selection in the assembly of the fungal community. The LBF treatment enriched the bacterial classes of Gammaproteobacteria, Gemmatimonadetes, and Methylomirabilia and fungal classes of Glomeromycetes and GS13, which were mainly driven by PAD and Ks. Additionally, the LBF treatment significantly increased the robustness and positive cohesions and decreased the vulnerability of the bacterial co-occurrence networks in both 2019 and 2020 in comparison with the CK treatment, indicating that the LBF treatment increased stability of bacterial community. The relative abundance of chemoheterotrophy and arbuscular mycorrhizae in the LBF treatment were 89.6 % and 854.4 % higher than those in the CK treatment, respectively, showing that the LBF enhanced sunflower-microbe interactions. The FYM treatment improved the functions mainly regarding sulfur respiration and hydrocarbon degradation by 309.7 % and 212.8 % in comparison with the CK treatment, respectively. The core rhizomicrobiomes in the LBF treatment showed strong positive connections with the stabilities of both bacterial and fungal co-occurrence networks, as well as the relative abundance and potential functions of chemoheterotrophy and arbuscular mycorrhizae. These factors were also linked to the growth of sunflowers. This study reveals that the LBF improved sunflower growth due to enhance microbial community stability and sunflower-microbe interactions through altering core rhizomicrobiomes in saline-sodic farmland.

Inflammation, metabolic dysregulation and environmental neurotoxins and risk of cognitive decline and impairment in midlife.

BACKGROUND: Age-related declines in cognitive function may begin in midlife. PURPOSE: To determine whether blood-based biomarkers of inflammation, metabolic dysregulation and neurotoxins are associated with risk of cognitive decline and impairment. METHODS: Baseline blood samples from the longitudinal Beaver Dam Offspring Study (2005-2008) were assayed for markers of inflammation, metabolic dysregulation, and environmental neurotoxins. Cognitive function was measured at baseline, 5-year (2010-2013) and 10-year (2015-2017) examinations. Participants without cognitive impairment at baseline and with cognitive data from at least one follow-up were included. Cox proportional hazards models were used to evaluate associations between baseline blood biomarkers and the 10-year cumulative incidence of cognitive impairment. Poisson models were used to estimate the relative risk (RR) of 5-year decline in cognitive function by baseline blood biomarkers. Models were adjusted for age, sex, education, and cardiovascular related risk factors. RESULTS: Participants (N = 2421) were a mean age of 49 years and 55% were women. Soluble vascular cell adhesion molecule-1 (sVCAM-1Tertile(T)3 vs T1-2 hazard ratio (HR) = 1.72, 95% confidence interval (CI) = 1.05,2.82) and hemoglobin A1C (HR = 1.75, 95% CI = 1.18,2.59, per 1% in women) were associated with the 10-year cumulative incidence of cognitive impairment. sVCAM-1 (RRT3 vs T1-2 = 1.45, 95% CI = 1.06,1.99) and white blood cell count (RR = 1.10, 95% CI = 1.02,1.19, per 103/µL) were associated with 5-year cognitive decline. CONCLUSIONS: Biomarkers related to inflammation and metabolic dysregulation were associated with an increased risk of developing cognitive decline and impairment. These results extend previous research in cognitive aging to early markers of cognitive decline in midlife, a time when intervention methods may be more efficacious.

An improved estimation of soil water and salt dynamics by considering soil bulk density changes under freeze/thaw conditions in arid areas with shallow groundwater tables.

Soil bulk density (BD) is a parameter dependent on soil texture, compositions of soil minerals and organic matter and the extent of soil compaction. Seasonal freeze/thaw in arid areas with shallow groundwater tables (AASGT) may significantly change BD and hence soil hydrothermal properties and water holding capacity. Therefore, quantifying soil bulk density changes (BDC) under freeze/thaw conditions can improve estimates of soil water-salt dynamics in AASGT. In this study, we conducted field experiments to investigate the soil water-salt dynamics under freeze/thaw conditions from three typical land-use types (i.e., farmland, woodland, and natural land) in the upper Yellow River basin, China. We proposed a method to estimate BDC, which can better describe the soil water-salt dynamics during the freeze/thaw period. Our results showed marked BDC occurred in all layers within the 0-100 cm profile in natural land, while mainly at the 20-80 cm profile in farmland. During the freezing period, BD in farmland and natural land first decreased rapidly and then remained relatively stable until the thawing period started. After that, BD gradually increased during the thawing period. The largest BDC in farmland and natural land were 0.48 g cm-3 (occurring at the 30-40 cm layer) and 0.43 g cm-3 (occurring at the 80-90 cm layer), respectively, close to 30 % of their initial values. The differences in BDC between the three land-use types were mainly owing to their differences in groundwater table depth, initial soil salt concentration, soil texture, and surface coverage conditions. Moreover, in farmland and natural land, ignoring BDC resulted in different degrees of overestimation or underestimation in soil water content, water fluxes, and soil hydrothermal properties in the selected soil layers. This study demonstrates that considering BDC can improve the accuracy of soil water-salt dynamics estimation in AASGT under freeze/thaw conditions.

Intrinsic Anomalous Hall Effect in a Bosonic Chiral Superfluid.

The anomalous Hall effect has had a profound influence on the understanding of many electronic topological materials but is much less studied in their bosonic counterparts. We predict that an intrinsic anomalous Hall effect exists in a recently realized bosonic chiral superfluid, a p-orbital Bose-Einstein condensate in a 2D hexagonal boron nitride optical lattice [Wang et al., Nature (London) 596, 227 (2021)NATUAS0028-083610.1038/s41586-021-03702-0]. We evaluate the frequency-dependent Hall conductivity within a multi-orbital Bose-Hubbard model that accurately captures the real experimental system. We find that in the high frequency limit, the Hall conductivity is determined by finite loop current correlations on the s-orbital residing sublattice, the latter a defining feature of the system's chirality. In the opposite limit, the dc Hall conductivity can trace its origin back to the noninteracting band Berry curvature at the condensation momentum, although the contribution from atomic interactions can be significant. We discuss available experimental probes to observe this intrinsic anomalous Hall effect at both zero and finite frequencies.

University-industry collaboration: The impact of postdoctoral workstations on labor investment efficiency.

This paper investigates whether managers use knowledge transferred from university-industry collaboration when making investment decisions on labor. To establish causality, we use a difference-in-difference method based on the staggered establishment of postdoctoral workstations in Chinese firms. We find that postdoctoral workstations enable managers to improve labor investment efficiency and thus help mitigate over- and under-investment problems in labor, and the higher the operational quality of the workstation, the more significant the increase in investment efficiency. This finding is robust to utilizing the event study approach, placebo test, propensity score matching, instrumental variable, and entropy balancing. Brain gain and knowledge transfer effects between universities and industries are two plausible mechanisms. Furthermore, the main effect is more pronounced for firms located closer to prestigious universities, firms are non-state-owned enterprises, human-capital-intensive, have political connections, and without national fellows' lead. Our findings suggest that brain gain in firms does not merely increase or reduce labor investments Per se, but rather inspires managers to maintain optimal labor levels through knowledge transfer processes.

Body Temperature Enhanced Adhesive, Antibacterial, and Recyclable Ionic Hydrogel for Epidermal Electrophysiological Monitoring.

Hydrogel-based epidermal electrodes attract widespread attention in health monitoring and human-machine interfaces for their good biocompatibility, skin-matched Young's modulus, and stable in situ electrophysiological recording performance. However, it is difficult to make the exact conformal attachment between skin and electrodes because of the hair, wrinkles, as well as complex, curved contours of the skin. This also results in signal distortion and large noise. Here, a body temperature enhanced skin-adhesive epidermal electrode is proposed based on non-covalent cross-linked network ionic hydrogel. The ionic hydrogel is fabricated by the polyvinyl alcohol, branched polyethyleneimine, and calcium chloride (CaCl2 ), which demonstrates impressive performances including ultra-stretchability of 1291%, great adhesion to skin and other non-biological materials, stable conductivity of 3.09 S m-1 , recyclability, and outstanding antibacterial ability, simultaneously. Specifically, the adhesion of the ionic hydrogel behaves as temperature-sensitive and could be enhanced by body temperature. Furthermore, the ionic hydrogel is utilized as epidermal electrodes, which display seductive capability to record multifarious electrophysiological signals with high signal-to-noise ratio and ultra-low detection limit, including electrocardiogram, electromyogram, and electroencephalogram. The as-proposed body temperature enhanced skin-adhesive ionic hydrogel brings intelligent functions and broadens the way for epidermal electronics, promoting the development of healthcare electronics.

Deep Transfer Learning for the Multilabel Classification of Chest X-ray Images.

Chest X-ray (CXR) is widely used to diagnose conditions affecting the chest, its contents, and its nearby structures. In this study, we used a private data set containing 1630 CXR images with disease labels; most of the images were disease-free, but the others contained multiple sites of abnormalities. Here, we used deep convolutional neural network (CNN) models to extract feature representations and to identify possible diseases in these images. We also used transfer learning combined with large open-source image data sets to resolve the problems of insufficient training data and optimize the classification model. The effects of different approaches of reusing pretrained weights (model finetuning and layer transfer), source data sets of different sizes and similarity levels to the target data (ImageNet, ChestX-ray, and CheXpert), methods integrating source data sets into transfer learning (initiating, concatenating, and co-training), and backbone CNN models (ResNet50 and DenseNet121) on transfer learning were also assessed. The results demonstrated that transfer learning applied with the model finetuning approach typically afforded better prediction models. When only one source data set was adopted, ChestX-ray performed better than CheXpert; however, after ImageNet initials were attached, CheXpert performed better. ResNet50 performed better in initiating transfer learning, whereas DenseNet121 performed better in concatenating and co-training transfer learning. Transfer learning with multiple source data sets was preferable to that with a source data set. Overall, transfer learning can further enhance prediction capabilities and reduce computing costs for CXR images.

Identifying the Posture of Young Adults in Walking Videos by Using a Fusion Artificial Intelligent Method.

Many neurological and musculoskeletal disorders are associated with problems related to postural movement. Noninvasive tracking devices are used to record, analyze, measure, and detect the postural control of the body, which may indicate health problems in real time. A total of 35 young adults without any health problems were recruited for this study to participate in a walking experiment. An iso-block postural identity method was used to quantitatively analyze posture control and walking behavior. The participants who exhibited straightforward walking and skewed walking were defined as the control and experimental groups, respectively. Fusion deep learning was applied to generate dynamic joint node plots by using OpenPose-based methods, and skewness was qualitatively analyzed using convolutional neural networks. The maximum specificity and sensitivity achieved using a combination of ResNet101 and the naïve Bayes classifier were 0.84 and 0.87, respectively. The proposed approach successfully combines cell phone camera recordings, cloud storage, and fusion deep learning for posture estimation and classification.

Rapid screening of microalgae by a 96-hole air-flowing device.

In this study, a 96-hole air-flowing device (96HAFD) was established for high-throughput screening of three mutant Chlorella strains under air aeration. 96HAFD was first tested for the confirmation of homogeneous air aeration cultivation environment at 1.2 L min-1 for algal screening based on the results of t test (p < 0.05) in the verification of consistency experiment. Then the data of dynamic growth characteristics of three mutant Chlorella strains indicated the good agreement in three screening devices including 96HAFD, flask and tube air-flowing cultivation devices by linear regression analysis between the 96HAFD and tube (R2 = 0.9904), 96HAFD and flask (R2 = 0.9904). At last, the 96HAFD was verified more efficient and reliable in fast screening single algal colony strains when compared with flask and tube air-flowing cultivation devices, because 96HAFD was confirmed have better performances in adaptation to the aeration cultivation circumstance and growing faster in a short period, in addition, 96HAFD had the less percentage of water loss per day (0.11%) than that of flask aeration device (2-3%) and tube aeration device (5-6.5%), which reduced negative effect caused by the water evaporation in the aeration cultivation to make the whole growing system more stable.

Modeling and assessing water and nutrient balances in a tile-drained agricultural watershed in the U.S. Corn Belt.

Identifying the key processes and primary sources of water and nutrient losses is essential for water quantity and quality management in watersheds. This is especially true in the U.S. Corn Belt, which has been recognized as the primary region contributing nutrient loads to the Great Lakes and the Gulf of Mexico. A SWAT (Soil and Water Assessment Tool) model simulation was set up in an agricultural watershed with about 50% tile drainage area in the U.S. Corn Belt to study the water and nutrient balance components for the whole watershed and the corn-soybean rotation system. The SWAT model was improved to consider additional nitrogen and phosphorus loss paths from the soil. The model was comprehensively calibrated and validated for simulating monthly stream flow, total suspended solids (TSS), nutrient loads (including total Kjeldahl nitrogen (TKN), nitrate and nitrite nitrogen (NOx-N), total phosphorus (TP) and orthophosphate phosphorus (orthoP)), actual evapotranspiration (ETa), leaf area index (LAI) and annual crop yields in the watershed from 2011 to 2019. Results showed the model performance was very good for simulating the stream flow, TSS and ETa, and acceptable for nutrient loads, LAI and crop yields. ETa, surface runoff, lateral soil flow, tile drainage and percolation respectively accounted for 65%, 15%, 2%, 8% and 9% of the precipitation. Fertilizer was the main source of nitrogen and phosphorus input to the watershed, and harvested crops were the main paths removing nutrients. Surface runoff, tile drainage and percolation each contributed about 30% of total nitrogen losses to water, with surface runoff being dominated by organic nitrogen while tile drainage and percolation were dominated by nitrate nitrogen. Phosphorus losses were mainly through surface runoff, which resulted in 66% of the total losses and was dominated by organic phosphorus and soluble phosphorus. Representing about 49% of the watershed area, the corn-soybean rotation system contributed 83% and 88% of the total nitrogen and phosphorus inputs, respectively, to the watershed, as well as 64% and 46% of the nitrogen and phosphorus losses to the water system, respectively. The non-growing season (October to the next April) was identified as the critical period resulting in water and nutrient losses due to low evapotranspiration and plant uptake. Targeted management strategies for reducing nutrient loads in key hydrological paths were suggested.

Exploring Volatile Organic Compounds in Breath for High-Accuracy Prediction of Lung Cancer.

(1) Background: Lung cancer is silent in its early stages and fatal in its advanced stages. The current examinations for lung cancer are usually based on imaging. Conventional chest X-rays lack accuracy, and chest computed tomography (CT) is associated with radiation exposure and cost, limiting screening effectiveness. Breathomics, a noninvasive strategy, has recently been studied extensively. Volatile organic compounds (VOCs) derived from human breath can reflect metabolic changes caused by diseases and possibly serve as biomarkers of lung cancer. (2) Methods: The selected ion flow tube mass spectrometry (SIFT-MS) technique was used to quantitatively analyze 116 VOCs in breath samples from 148 patients with histologically confirmed lung cancers and 168 healthy volunteers. We used eXtreme Gradient Boosting (XGBoost), a machine learning method, to build a model for predicting lung cancer occurrence based on quantitative VOC measurements. (3) Results: The proposed prediction model achieved better performance than other previous approaches, with an accuracy, sensitivity, specificity, and area under the curve (AUC) of 0.89, 0.82, 0.94, and 0.95, respectively. When we further adjusted the confounding effect of environmental VOCs on the relationship between participants' exhaled VOCs and lung cancer occurrence, our model was improved to reach 0.92 accuracy, 0.96 sensitivity, 0.88 specificity, and 0.98 AUC. (4) Conclusion: A quantitative VOCs databank integrated with the application of an XGBoost classifier provides a persuasive platform for lung cancer prediction.

Modeling the effects of temperature on the migration and transformation of nitrate during riverbank filtration using HYDRUS-2D.

Riverbank filtration is a natural aquifer-based process. The nitrogen dynamics in a riverbank filtration system are affected by many factors, including temperature, water quality, and travel time, which cannot be quantified easily. In this study, a field experiment was conducted to investigate nitrogen transport during riverbank filtration. The HYDRUS-2D software package was used to investigate and quantify the factors that affect the fate of nitrogen. The effects of temperature, water quality, and travel time on nitrate transport were considered. The model was calibrated and validated using field experimental data from the river water and groundwater during riverbank filtration at different periods. The results showed that HYDRUS-2D adequately simulated nitrate transport during riverbank filtration. The denitrification rate constant exhibited a positive exponential relationship with temperature. An empirical formula describing this relationship in riverbank filtration was developed and validated. In addition, the denitrification rate can be quantified within a specified temperature data range under field conditions. Compared with indoor experimental conditions, for the same temperature, there was a 10-fold increase in the denitrification rate constant under field conditions. The results showed that most of the nitrate removal occurred in the riparian zone at high temperatures during riverbank filtration. We concluded that the fate of nitrate in the riparian zone is strongly controlled by groundwater temperature. Travel time also plays an important role in nitrate removal during riverbank filtration.