Muscle activity-driven green-oriented random number generation mechanism to secure WBSN wearable device communications

Wireless body sensor networks (WBSNs) mostly consist of low-cost sensor nodes and implanted devices which generally have extremely limited capability of computations and energy capabilities. Hence, traditional security protocols and privacy enhancing technologies are not applicable to the WBSNs since their computations and cryptographic primitives are normally exceedingly complicated. Nowadays, mobile wearable and wireless muscle-computer interfaces have been integrated with the WBSN sensors for various applications such as rehabilitation, sports, entertainment, and healthcare. In this paper, we propose MGRNG, a novel muscle activity-driven green-oriented random number generation mechanism which uses the human muscle activity as green energy resource to generate random numbers (RNs). The RNs can be used to enhance the privacy of wearable device communications and secure WBSNs for rehabilitation purposes. The method was tested on 10 healthy subjects as well as 5 amputee subjects with 105 segments of simultaneously recorded surface electromyography signals from their forearm muscles. The proposed MGRNG requires only one second to generate a 128-bit RN, which is much more efficient when compared to the electrocardiography-based RN generation algorithms. Experimental results show that the RNs generated from human muscle activity signals can pass the entropy test and the NIST random test and thus can be used to secure the WBSN nodes

Multi-focus image fusion based on non-negative sparse representation and patch-level consistency rectification

Most existing sparse representation-based (SR) fusion methods consider the local information of each image patch independently during fusion. Some spatial artifacts are easily introduced to the fused image. A sliding window technology is often employed by these methods to overcome this issue. However, this comes at the cost of high computational complexity. Alternatively, we come up with a novel multi-focus image fusion method that takes full consideration of the strong correlations among spatially adjacent image patches with NO need for a sliding window. To this end, a non-negative SR model with local consistency constraint (CNNSR) on the representation coefficients is first constructed to encode each image patch. Then a patch-level consistency rectification strategy is presented to merge the input image patches, by which the spatial artifacts in the fused images are greatly reduced. As well, a compact non-negative dictionary is constructed for the CNNSR model. Experimental results demonstrate that the proposed fusion method outperforms some state-of-the art methods. Moreover, the proposed method is computationally efficient, thereby facilitating real-world applications

Magnet bioreporter device for ecological toxicity assessment on heavy metal contamination of coal cinder sites

A novel magnet bioreporter device was developed in this research for soil toxicity assessment, via magnetic nanoparticles functionalized whole-cell bioreporters. The whole-cell bioreporter ADPWH-recA kept response capability to DNA damage after magnetic nanoparticles (MNPs) functionalization, and could be harvested from soil samples by permanent magnet to reduce the soil particle disturbance. Compared to conventional treatments applying bioreporter directly in soil-water mixture (SW-M treatment) or supernatant (SW-S treatment), MNPs functionalized bioreporter via the magnet device (MFB) treatment achieved high sensitivity to evaluate the toxicity and bioavailability of chromium contamination in soils from 10 mg/kg to 5000 mg/kg soil dry weight. The MNPs functionalized bioreporter also achieved high reproducibility with pH value from 5.0 to 9.0, salinity from 0% to 3% and temperature from 20 °C to 37 °C. A case study was carried out on the ecological toxicity assessment of heavy metal contamination at the coal cinder site via the magnet bioreporter device. The heavy metal toxicity declined with the increasing distance to the coal cinder point, and a significant accumulation of heavy metal toxicity was observed along the vertical distribution. No direct link was found between the pollution load index (PLI) and heavy metal toxicity, and the results suggested the bioreporter test monitored the toxicity of heavy metals in soils and was an important approach for ecological risk assessment. Magnet bioreporter device also offered the high throughput biological measurement and was feasible for in situ monitoring

ProAgent: Building Proactive Cooperative Agents with Large Language Models

Building agents with adaptive behavior in cooperative tasks stands as a paramount goal in the realm of multi-agent systems. Current approaches to developing cooperative agents rely primarily on learning-based methods, whose policy generalization depends heavily on the diversity of teammates they interact with during the training phase. Such reliance, however, constrains the agents' capacity for strategic adaptation when cooperating with unfamiliar teammates, which becomes a significant challenge in zero-shot coordination scenarios. To address this challenge, we propose ProAgent, a novel framework that harnesses large language models (LLMs) to create proactive agents capable of dynamically adapting their behavior to enhance cooperation with teammates. ProAgent can analyze the present state, and infer the intentions of teammates from observations. It then updates its beliefs in alignment with the teammates' subsequent actual behaviors. Moreover, ProAgent exhibits a high degree of modularity and interpretability, making it easily integrated into various of coordination scenarios. Experimental evaluations conducted within the Overcooked-AI environment unveil the remarkable performance superiority of ProAgent, outperforming five methods based on self-play and population-based training when cooperating with AI agents. Furthermore, in partnered with human proxy models, its performance exhibits an average improvement exceeding 10% compared to the current state-of-the-art method. For more information about our project, please visit~\url{https://pku-proagent.github.io}.Comment: v3 is the AAAI'24 camera ready version, which polished abstract and introduction based on the reviewers' comments, and enriched related works. 7 pages of main content, 2 pages of references, 2 figures and 1 tabl

The dynamic change of microbial communities in crude oil contaminated soils from oilfields in China

To study the biodegradability of microbial communities in crude oil contamination, crude oil-contaminated soil samples from different areas of China were collected. Using polyphasic approach, this study explored the dynamic change of the microbial communities during natural accumulation in oilfield and how the constructed bioremediation systems reshape the composition of microbial communities. The abundance of oil-degrading microbes was highest when oil content was 3%–8%. This oil content is potentially optimal for oil-degrading bacteria proliferate. During a ∼12 months natural accumulation, the quantity of oil-degrading microbes increased from 105 to 108 cells/g of soil. A typical sample of Liaohe (LH, oil-contaminated site near Liaohe river, Liaoning Province, China) was remediated for 50 days to investigate the dynamic change of microbial communities. The average FDA (a fluorescein diacetate approach) activities reached 0.25 abs/h·g dry soil in the artificially enhanced repair system, 32% higher than the 0.19 abs/h·g dry soil in natural circumstances. The abundance of oil-degrading microbes increased steadily from 0.001 to 0.068. During remediation treatment, oil content in the soil sample was reduced from 6.0% to 3.7%. GC-MS analysis indicated up to 67% utilization of C10–C20 normal paraffin hydrocarbons, the typical compounds that undergo microbial degradation

A whole-cell bioreporter assay for quantitative genotoxicity evaluation of environmental samples

Whole-cell bioreporters have emerged as promising tools for genotoxicity evaluation, due to their rapidity, cost-effectiveness, sensitivity and selectivity. In this study, a method for detecting genotoxicity in environmental samples was developed using the bioluminescent whole-cell bioreporter Escherichia coli recA::luxCDABE. To further test its performance in a real world scenario, the E. coli bioreporter was applied in two cases: i) soil samples collected from chromium(VI) contaminated sites; ii) crude oil contaminated seawater collected after the Jiaozhou Bay oil spill which occurred in 2013. The chromium(VI) contaminated soils were pretreated by water extraction, and directly exposed to the bioreporter in two phases: aqueous soil extraction (water phase) and soil supernatant (solid phase). The results indicated that both extractable and soil particle fixed chromium(VI) were bioavailable to the bioreporter, and the solid-phase contact bioreporter assay provided a more precise evaluation of soil genotoxicity. For crude oil contaminated seawater, the response of the bioreporter clearly illustrated the spatial and time change in genotoxicity surrounding the spill site, suggesting that the crude oil degradation process decreased the genotoxic risk to ecosystem. In addition, the performance of the bioreporter was simulated by a modified cross-regulation gene expression model, which quantitatively described the DNA damage response of the E. coli bioreporter. Accordingly, the bioluminescent response of the bioreporter was calculated as the mitomycin C equivalent, enabling quantitative comparison of genotoxicities between different environmental samples. This bioreporter assay provides a rapid and sensitive screening tool for direct genotoxicity assessment of environmental samples

Effects of water table and fertilization management on nitrogen loading to groundwater

Groundwater contamination by nitrate associated with fertilization practices is a ubiquitous environmental issue, and consequently of world-wide concern. Controlling this contamination requires an ability to measure and predict nitrate loading from unsaturated zone to saturated zone. A field experiment was conducted in an intensively irrigated agricultural area in Dianchi catchment of Kunming, China. Two celery (Apium graveolens) crop sites with different water table depths (Site A is 2.0 m below the soil surface; Site B is 0.5 m below the soil surface) were selected for the experiment. Both of sites were applied fertilizers at two different rates, one the highest traditionally used by farmers in the region (about 4800 kg N/ha per year, HF) and the other three-eighth of the farmer (1800 kg N/ha per year, LF). The results showed that fertilization practices impacted few effects on the balance and dynamic of water in the plant-soil-aeration zone-saturated zone system. However, groundwater table controlled vertical infiltration recharge and evaporation-transpiration rate. The vertical infiltration recharge and the evaporation-transpiration rate were averagely 0.514 and 5.897 mm/d at Site B with a water table depth of 0.5 m below the soil surface, 0.335 and 6.420 mm/d at Site A with a water table depth of 2.0 m below the soil surface, respectively. Nitrate concentrations of soil water near groundwater table under HF subplot were much higher than that under LH subplot. High fertilization rate consequently resulted in great nitrogen (including nitrate, nitrite and ammonium) loadings from aeration zone to groundwater. At Site B, nitrogen loadings were 316.03 and 223.89 kg/ha a under HF and LF, respectively. Nitrate was the dominant nitrogen component entering groundwater. Little ammonium and less nitrite transported into groundwater. Shallow water table made nitrate entering groundwater more easily and consequently determined the NO(3)(-) loading from vadose zone. For the same fertilization rate, nitrate loading to groundwater under Site B were much higher than those under Site A, with 47.11 kg NO(3)-N/ha a under Site A-HF and 311.73 kg NO(3)-N/ha a under Site B-HF. To avert or minimize the potential of groundwater nitrogen contamination in irrigated agricultural areas should determine and minimize the amounts of applied fertilizer by optimizing them to match crop requirements and environmental protection. (c) 2005 Elsevier B.V. All rights reserved

Structure and mass transportation model of slow-release organic carbon-source material for groundwater in situ denitrification

Based on the theories of organic polymer and chemical kinetics, the structure and mass transportation model of slow-release organic carbon-source (SOC) material was developed in this study to reveal and predict the carbon release mechanisms of polymer carbon source, which was feasible for in situ denitrification in nitrate-contaminated groundwater. Composed of polyvinyl alcohol (PVA) and starch, the SOC material formed the interlocking/disperse-phase structure. PVA performed as continuous phase and skeleton, whereas the starch or cellulose behaved as release component. Carbon release process was identified in two stages: solid-phase (inner) and interface (gel layer) diffusion. Solid-phase diffusion was affected by material porous medium parameters, for example, distance between the crosslinking points and starch free energy. The interface diffusion depended mostly on the groundwater dynamics and interface energy distribution. The interface diffusion was found as the limiting step of carbon release process, and the carbon release coefficient corresponded to kD,I as static coefficient and kC,I as dynamic coefficient. As the key indicator to evaluate carbon release capacity, kD,I and kC,I represented appropriate boundary conditions and interface properties. Sensitivity analysis showed that the key parameters of the carbon release model were the distance between the crosslinking points and the free energy of polymer, influenced by regulation of preparation technique, raw material composition and additive dosage