Shear Modulus of a Carbonate Sand–Silt Mixture with THF Hydrate

The maximum shear modulus (Gmax) is an important factor determining soil deformation, and it is closely related to engineering safety and seafloor stability. In this study, a series of bender element tests was carried out to investigate the Gmax of a hydrate-bearing carbonate sand (CS)–silt mixture. The soil mixture adopted a CS:silt ratio of 1:4 by weight to mimic the fine-grained deposit of the South China Sea (SCS). Tetrahydrofuran (THF) was used to form the hydrate. Special specimen preparation procedures were adopted to form THF hydrate inside the intraparticle voids of the CS. The test results indicate that hydrate contributed to a significant part of the skeletal stiffness of the hydrate-bearing CS–silt mixture, and its Gmax at 5% hydrate saturation (Sh) was 4–6 times that of the host soil mixture. Such stiffness enhancement at a low Sh may be related to the cementation hydrate morphology. However, the Gmax of the hydrate-bearing CS–silt mixture was also sensitive to the effective stress for an Sh ranging between 5% and 31%, implying that the frame-supporting hydrate morphology also plays a key role in the skeletal stiffness of the soil mixture. Neither the existing cementation models nor the theoretical frame-supporting (i.e., Biot–Gassmann theory by Lee (BGTL)), could alone provide a satisfactory prediction of the test results. Thus, further theoretical study involving a combination of cementation and frame-supporting models is essential to understand the effects of complicated hydrate morphologies on the stiffness of soil with a substantial amount of intraparticle voids

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

Annual analysis of the photovoltaic direct-expansion heat pump assisted by double condensing equipment for secondary power generation

Thermoelectric generation (TEG) converts heat directly into electricity based on temperature difference. Many studies on combining TEG with photovoltaics to convert waste heat into electricity to increase overall power generation have been conducted. However, through previous research, if TEG was installed between the cooling and PV, it will hinder PV heat dissipation and cause electricity deterioration, which could not be compensated by TEG output. To ensure the PV cooling and meanwhile realize thermoelectric conversion, a photovoltaic direct-expansion double-condensing heat pump system based on TEG assisted by micro-channel heat pipes and water-cooling condenser is proposed. Experiments & mathematical model are carried out & verified. The regional weather conditions at different latitudes and altitudes are adopted to predict the system performance on a year basis. From the results, the electrical efficiency is improved due to the additional TEG power output. With a higher ambient temperature in Hongkong, the heating capacity is higher, but the compressor consumption also increases. With better irradiation and a lower ambient temperature, Garze has brilliant electrical performance, the COPPVT & NEER are the highest at 9.9 monthly & 8.0 annually. Furthermore, the operating costs and CO2emissions of this system are just 1/4–1/3 and 1/3–1/2 of gas boiler, indicating significant potential for energy-savings & emission reduction

Shear Modulus of a Carbonate Sand–Silt Mixture with THF Hydrate

The maximum shear modulus (Gmax) is an important factor determining soil deformation, and it is closely related to engineering safety and seafloor stability. In this study, a series of bender element tests was carried out to investigate the Gmax of a hydrate-bearing carbonate sand (CS)–silt mixture. The soil mixture adopted a CS:silt ratio of 1:4 by weight to mimic the fine-grained deposit of the South China Sea (SCS). Tetrahydrofuran (THF) was used to form the hydrate. Special specimen preparation procedures were adopted to form THF hydrate inside the intraparticle voids of the CS. The test results indicate that hydrate contributed to a significant part of the skeletal stiffness of the hydrate-bearing CS–silt mixture, and its Gmax at 5% hydrate saturation (Sh) was 4–6 times that of the host soil mixture. Such stiffness enhancement at a low Sh may be related to the cementation hydrate morphology. However, the Gmax of the hydrate-bearing CS–silt mixture was also sensitive to the effective stress for an Sh ranging between 5% and 31%, implying that the frame-supporting hydrate morphology also plays a key role in the skeletal stiffness of the soil mixture. Neither the existing cementation models nor the theoretical frame-supporting (i.e., Biot–Gassmann theory by Lee (BGTL)), could alone provide a satisfactory prediction of the test results. Thus, further theoretical study involving a combination of cementation and frame-supporting models is essential to understand the effects of complicated hydrate morphologies on the stiffness of soil with a substantial amount of intraparticle voids

Shear Modulus of a Carbonate Sand–Silt Mixture with THF Hydrate

The maximum shear modulus (Gmax) is an important factor determining soil deformation, and it is closely related to engineering safety and seafloor stability. In this study, a series of bender element tests was carried out to investigate the Gmax of a hydrate-bearing carbonate sand (CS)–silt mixture. The soil mixture adopted a CS:silt ratio of 1:4 by weight to mimic the fine-grained deposit of the South China Sea (SCS). Tetrahydrofuran (THF) was used to form the hydrate. Special specimen preparation procedures were adopted to form THF hydrate inside the intraparticle voids of the CS. The test results indicate that hydrate contributed to a significant part of the skeletal stiffness of the hydrate-bearing CS–silt mixture, and its Gmax at 5% hydrate saturation (Sh) was 4–6 times that of the host soil mixture. Such stiffness enhancement at a low Sh may be related to the cementation hydrate morphology. However, the Gmax of the hydrate-bearing CS–silt mixture was also sensitive to the effective stress for an Sh ranging between 5% and 31%, implying that the frame-supporting hydrate morphology also plays a key role in the skeletal stiffness of the soil mixture. Neither the existing cementation models nor the theoretical frame-supporting (i.e., Biot–Gassmann theory by Lee (BGTL)), could alone provide a satisfactory prediction of the test results. Thus, further theoretical study involving a combination of cementation and frame-supporting models is essential to understand the effects of complicated hydrate morphologies on the stiffness of soil with a substantial amount of intraparticle voids

Atmospheric Oxidation Capacity and Its Impact on the Secondary Inorganic Components of PM_2.5 in Recent Years in Beijing: Enlightenment for PM_2.5 Pollution Control in the Future

In recent years, the concentrations of PM2.5 in urban ambient air in China have been declining; however, the strong atmospheric oxidation capacity (AOC) represents challenges to the further reduction of PM2.5 concentration and the continuous improvement of ambient air quality in China in the future, since the overall AOC is still at a high level. For this paper, based on ground observation data recorded in Beijing from 2016 to 2019, the variation in AOC was characterized according to the concentration of odd oxygen (OX = O3 + NO2). The concentrations of the primary and secondary components of PM2.5 were analyzed using empirical formulas, the correlation between AOC and the concentrations of secondary PM2.5 and the secondary inorganic components (SO42−, NO3−, NH4+, and SNA) in Beijing were explored, the impact of atmospheric photochemical reaction activity on the generation of atmospheric secondary particles was evaluated, and the impact of atmospheric oxidation variations on PM2.5 concentrations and SNA in Beijing was investigated. The results revealed that OX concentrations reached their peak in 2016 and reached their lowest point in 2019. The OX concentrations followed a descending seasonal trend of summer, spring, autumn, and winter, along with a spatial descending trend from urban observation stations to suburban stations and background stations. The degree of photochemical activity and the magnitude of the AOC have a large influence on the production of atmospheric secondary particles. When the photochemical reaction was more active and the AOC was stronger, the mass concentrations of the secondary generated PM2.5 fraction were higher and accounted for a higher proportion of the total PM2.5 mass concentrations. In the PM2.5 fraction, SNA accounted for 50.7% to 94.4% of the total mass concentrations of water-soluble inorganic ions in the field observations. Higher concentrations of the atmospheric oxidant OX in ambient air corresponded to a higher sulfur oxidation ratio (SOR) and nitrogen oxidation ratio (NOR), suggesting that the increase in AOC could promote the increase of PM2.5 concentration. Based on a relationship analysis of SOR, NOR, and OX, it was inferred that the relationship between OX and SOR and the relationship between OX and NOR were both nonlinear. Therefore, when establishing PM2.5 control strategies in Beijing in the future, the impact of the AOC on PM2.5 generation should be fully considered, and favorable measures should be taken to properly regulate the AOC, which would be more effective when carrying out further control measures regarding PM2.5 pollution

CrossBind: Collaborative cross-modal identification of protein nucleic-acid-binding residues

Accurate identification of protein nucleic-acid-binding residues poses a significant challenge with important implications for various biological processes and drug design. Many typical computational methods for protein analysis rely on a single model that could ignore either the semantic context of the protein or the global 3D geometric information. Consequently, these approaches may result in incomplete or inaccurate protein analysis. To address the above issue, in this paper, we present CrossBind, a novel collaborative cross-modal approach for identifying binding residues by exploiting both protein geometric structure and its sequence prior knowledge extracted from a large-scale protein language model. Specifically, our multi-modal approach leverages a contrastive learning technique and atom-wise attention to capture the positional relationships between atoms and residues, thereby incorporating fine-grained local geometric knowledge, for better binding residue prediction. Extensive experimental results demonstrate that our approach outperforms the next best state-of-the-art methods, GraphSite and GraphBind, on DNA and RNA datasets by 10.8/17.3% in terms of the harmonic mean of precision and recall (F1-Score) and 11.9/24.8% in Matthews correlation coefficient (MCC), respectively.We release the code at https://github.com/BEAM-Labs/CrossBind.</p

CrossBind: Collaborative cross-modal identification of protein nucleic-acid-binding residues

Accurate identification of protein nucleic-acid-binding residues poses a significant challenge with important implications for various biological processes and drug design. Many typical computational methods for protein analysis rely on a single model that could ignore either the semantic context of the protein or the global 3D geometric information. Consequently, these approaches may result in incomplete or inaccurate protein analysis. To address the above issue, in this paper, we present CrossBind, a novel collaborative cross-modal approach for identifying binding residues by exploiting both protein geometric structure and its sequence prior knowledge extracted from a large-scale protein language model. Specifically, our multi-modal approach leverages a contrastive learning technique and atom-wise attention to capture the positional relationships between atoms and residues, thereby incorporating fine-grained local geometric knowledge, for better binding residue prediction. Extensive experimental results demonstrate that our approach outperforms the next best state-of-the-art methods, GraphSite and GraphBind, on DNA and RNA datasets by 10.8/17.3% in terms of the harmonic mean of precision and recall (F1-Score) and 11.9/24.8% in Matthews correlation coefficient (MCC), respectively.We release the code at https://github.com/BEAM-Labs/CrossBind.</p

A Pectic Polysaccharide from <i>Codonopsis pilosula</i> Alleviates Inflammatory Response and Oxidative Stress of Aging Mice via Modulating Intestinal Microbiota-Related Gut–Liver Axis

Aging is a biological process that leads to the progressive deterioration and loss of physiological functions in the human body and results in an increase in morbidity and mortality, and aging-related disease is a major global problem that poses a serious threat to public health. Polysaccharides have been shown to delay aging by reducing oxidative damage, suppressing inflammatory responses, and modulating intestinal microbiota. Our previous studies have shown that polysaccharide CPP-1 extracted from the root of Codonopsis pilosula possesses noticeable anti-oxidant activity in vitro. Thus, in our study, we tested the anti-aging effect of CPP-1 in naturally aging mice (in vivo). Eighteen C57/BL mice (48-week-old, male) were divided into a control group, high-dose CPP-1 group (20 mg/mL), and low-dose CPP-1 group (10 mg/mL). We discovered that CPP-1 can exert a reparative effect on aging stress in the intestine and liver, including alleviating inflammation and oxidative damage. We revealed that CPP-1 supplementation improved the intestinal microbiota composition and repaired the intestinal barrier in the gut. Furthermore, CPP-1 was proved to modulate lipid metabolism and repair hepatocyte injury in the liver by influencing the enterohepatic axis associated with the intestinal microbiota. Therefore, we concluded that CPP-1 prevents and alleviates oxidative stress and inflammatory responses in the intestine and liver of aging mice by modulating the intestinal microbiota-related gut–liver axis to delay aging