Testing the Soil Carbon Saturation Theory: Maximal Carbon Stabilization and Soil Organic Matter Stability as a Function of Organic Carbon Inputs

Soil carbon (C) stocks and fluxes represent significant components of the global C cycle. Application of the soil C saturation theory can help identify soils with large C storage potentials and estimate rates and durations needed to reach maximal soil C storage. The goal of my dissertation was to test the soil C saturation theory by estimating C saturation levels of fine soil particles and quantifying changes in soil organic matter (SOM) stability as fine soil particles approach C saturation. Current model using least-squares linear regression generally underestimates C the maximal amount of soil C stabilization in fine soil particles. Using an analysis of published data, I proposed two alternative methods (boundary line analysis and the organic C loading method) to improve estimates, and found that while the organic C loading method is better since it incorporated mineral specific surface areas which would influence C saturation, it requires information about soil mineralogy and further tests to determine whether the monolayer-equivalent C loading indeed represents a maximal C stabilization potential. Laboratory batch sorption experiment of dissolved organic matter onto soil minerals generated organo-mineral complexes with a range of organic C loadings. These organo-mineral complexes, as well as silt+clay fractions physically isolated from soil samples from three long-term agroecosystem field experiments with differing fertilizer and manure addition treatments, were used to test for differences in SOM stability as a function of organic C loading. Biological, chemical, and thermal test of SOM stability showed little change or the increase trend of SOM stability with increasing organic C inputs, which do not support the notion of the soil C saturation theory that SOM stability decreases as organic C inputs increase. This observation of SOM stability is likely due to the fact that most samples did not exhibit C saturation behavior. The results show that most soils are likely well below C saturation, and further studies of the driving factors (e.g., chemical composition of organic C inputs, mineralogy, and organo-mineral binding types and strength) is needed to determine maximal C loadings and estimate the maximal soil C storage potentials

Biological Invasion and Coexistence in Intraguild Predation

Invasion of an exotic species initiated by its local introduction is considered subject to intraguild predation (IGP). Mathematically, the system dynamics is described by three nonlinear diffusion-reaction equations in two spatial dimensions. The key factors that determine successful invasion are investigated by means of extensive numerical simulations. The results reveal high asymmetry. An exotic species can invade successfully if it acted as the top predator and engaged in IGP, and the IGP interactions of the postinvasion web will be kept. While the exotic species were introduced as the intraguild prey (IGprey), they invade and spread through patchy invasion which corresponds to the invasion at the edge of extinction. Increase of the IGprey's dispersal rate and decrease of the IGpredator's may make the IGprey invade. But the interactions of the postinvasion web will change from IGP to competition, which is absolutely different from the first case. Finally, the common existence of IGP was explored once again from the perspective of biological invasion

Dissolve of Living Space: Living Space Under the Development of Metaverse

According to our vision, in the future, after the use of the metaverse becomes popular, we will spend a lot of time working, living and playing in the metaverse. The space needed in reality will be reduced by the use of the metaverse, and public buildings will be retained or not depending on the nature of the building. Because the focus of human life shifts from reality to the metaverse, energy and material consumption will also be reduced, and environmental problems can be properly alleviated. The nature in the real city will also be expanded by the reduction of the land needed by human beings. Therefore, the spread of the metaverse not only changes the living space of humans, but also brings more natural space back to the city. We began studying the actual environment in the midst of the project, concentrating on the influence of human activities on the current environment. According to our findings, human travel and industrial emissions are the leading contributors of global warming and natural catastrophes. This also makes us consider what the metaverse may offer to humanity and our globe, and the influence it can have on the environment can already be predicted

Vertical distributions of soil microbial biomass carbon: a global dataset

Soil microbial biomass carbon (SMBC) is important in regulating soil organic carbon (SOC) dynamics along soil profiles by mediating the decomposition and formation of SOC. The dataset (VDMBC) is about the vertical distributions of SOC, SMBC, and soil microbial quotient (SMQ = SMBC/SOC) and their relations to environmental factors across five continents. Data were collected from literature, with a total of 289 soil profiles and 1040 observations in different soil layers compiled. The associated environment data collectd include climate, ecosystem types, and edaphic factors. We developed this dataset by searching the Web of Sciene and the China National Knowledge Infrastructure from the year of 1970 to 2019. All the data in this dataset met two creteria: 1) there were at least three mineral soil layers along a soil profile, and 2) SMBC was measured using the fumigation extraction method. The data in tables and texts were obtained from literature directly, and the data in figures were extracted by using the GetData Graph digitizer software version 2.25. When climate and soil properties were not available from publications, we obtainted the data from the World Weather Information Service (https://worldweather.wmo.int/en/home.html) and SoilGrids at a spatial resolution of 250 meters (version 0.5.3, https://soilgrids.org). The units of all the variables were converted to the standard international units or commonly used ones and the values were transformed correspondingly. For example, the value of soil organic matter (SOM) was converted to SOC by using the equation (SOC = SOM × 0.58). This dataset can be used in predicting global SOC changes along soil profiles by using the multi-layer soil carbon models. It can also be used to analyse how soil microbial biomass changes with plant roots as well as the composition, structure, and functions of soil microbial communities along soil profiles at large spatial scales. This dataset offers opportunities to improve our prediction of SOC dynamics under global changes and to advance our understanding of the environmental controls

Research And Implementation Of Drug Target Interaction Confidence Measurement Method Based On Causal Intervention

The identification and discovery of drug-target Interaction (DTI) is an important step in the field of Drug research and development, which can help scientists discover new drugs and accelerate the development process. KnowledgeGraph and the related knowledge graph Embedding (KGE) model develop rapidly and show good performance in the field of drug discovery in recent years. In the task of drug target identification, the lack of authenticity and accuracy of the model will lead to the increase of misjudgment rate and the low efficiency of drug development. To solve the above problems, this study focused on the problem of drug target link prediction with knowledge mapping as the core technology, and adopted the confidence measurement method based on causal intervention to measure the triplet score, so as to improve the accuracy of drug target interaction prediction model. By comparing with the traditional Softmax and Sigmod confidence measurement methods on different KGE models, the results show that the confidence measurement method based on causal intervention can effectively improve the accuracy of DTI link prediction, especially for high-precision models. The predicted results are more conducive to guiding the design and development of followup experiments of drug development, so as to improve the efficiency of drug development.Comment: 8 pages,11 figure

Development of a miner personal dust continuous monitor based on the principle of oscillating balance

An accurate measurement of coal mine dust concentration is an important prerequisite for effective dust control. Traditional offline filter sampling gravimetric methods need a long measuring period and cumbersome operations, while direct-reading light absorption/scattering measurement methods are susceptible to environmental conditions and dust properties. To overcome the above-mentioned problems, a miner personal dust continuous monitor based on the principle of oscillating balance was developed. The finite element simulation method was used to explore the effects of different characteristics of the oscillating element on the response frequency and mass sensitivity of the oscillation system. The optimal gradient optimization algorithm was used to design the material and shape of the oscillating element. An oscillating tube with highly stable elastic modulus was fabricated. Its frequency temperature coefficient is 3×10−5 Hz/℃, which is minimally affected by temperature, ensuring the accurate measurement of the oscillation frequency when the external ambient temperature conditions vary. An oscillating balance mass sensor was developed. A digital self-excited oscillation closed-loop control circuit was designed to realize the automatic control of resonant frequency and real-time output. The oscillating balance mass sensor had a mass sensitivity of approximately 1 mg/Hz and a mass detection limit of 2 μg. Finally, a miner personal dust continuous monitor based on the principle of oscillating balance was developed for the first time in China by integrating the respiratory dust sampler, the total dust sampler, the heating tube, the mass sensor, the air pump, the flow rate controller, and the temperature, humidity and pressure sensors. The detection limit of this instrument is 0.035 mg/m3 in terms of the average dust mass concentration. The instrument can provide continuous monitoring information, including the real-time total dust or respirable dust concentration and the cumulative occupational exposure concentration of the day. This instrument was applied to dust measurement in an underground coal mine. Its measurement results were compared with those from the instrument using traditional filter sampling gravimetric method, with a relative error of approximately 5%. This instrument has the capability of rapid and accurate measurement of coal mine dust. It has the potential to be an alternative of offline filter sampling weighing methods and direct-reading dust monitors based on optical principles

Convergence analysis of environmental efficiency from the perspective of environmental regulation: evidence from China

The aim of this paper is to analyze the impact of environmental regulation on regional environmental efficiency convergence using the fixed effects model and threshold regression model. The results show that the differences in environmental efficiency have a convergence trend in China, as well as in the eastern, central and western regions. The effect of environmental regulation on regional environmental efficiency is inhibition first and then promotion, research and development investment and outward foreign direct investment have a positive transmission effect; when environmental regulation intensity exceeds a certain threshold, the growth rate of environmental efficiency in the central and western regions will be significantly higher than that in the eastern regions

Genetic variants in the vitamin D pathway genes VDBP and RXRA modulate cutaneous melanoma disease-specific survival

Single nucleotide polymorphisms (SNPs) in the vitamin D pathway genes have been implicated in cutaneous melanoma (CM) risk, but their role in CM disease-specific survival (DSS) remains obscure. We comprehensively analyzed the prognostic roles of 2669 common SNPs in the vitamin D pathway genes using data from a published genome-wide association study (GWAS) at The University of Texas M.D. Anderson Cancer Center (MDACC) and then validated the SNPs of interest in another GWAS from the Nurses' Health Study and Health Professionals Follow-up Study. Among the 2669 SNPs, 203 were significantly associated with DSS in MDACC dataset (P C was associated with a better DSS [combined hazards ratio (HR) = 0.66]; and the same for RXRA rs7850212 C > A (combined HR = 0.38), which were further confirmed by the Fine and Gray competing-risks regression model. Further bioinformatics analyses indicated that these loci may modulate corresponding gene methylation status