Dairy Manure as a Potential Feedstock for Cost-Effective Cellulosic Bioethanol

This study investigated sulfite pretreatment to overcome recalcitrance of lignocelluloses (SPORL) pretreatment and subsequent enzymatic digestibility of undigested dairy manure to preliminarily assess its potential use as an inexpensive feedstock for cellulosic bioethanol production. The sulfite pretreatment was carried out in a factorial analysis using 163 to 197 °C for 3 to 37 min with 0.8% to 4.2% sulfuric acid combined with 2.6% to 9.4% sodium sulfite. These treatments were compared with other standard pretreatments of dilute acid, and hot and cold alkali pretreatments. This comparative study showed that the sulfite pretreatment, through its combined effects of hemicellulose and lignin removal and lignin sulfonation, is more effective than the diluted acid and alkali pretreatments to improve the enzymatic digestibility of dairy manure

Phenomena identification Ranking Table (PIRT) study for suppression containment of small modular reactor using new methodology

The Phenomena Identification and Ranking Table (PIRT) is a significant method for analyzing the safety of nuclear reactors. It helps researchers identify important phenomena within the reactor, enabling a focused and appropriate simplification of accident scenarios during the study. However, traditional PIRT methods often rely on experts' subjective opinions to rank phenomena’ importance and knowledge level, potentially distorting the PIRT results. This paper proposes a new PIRT method inspired by literature evaluation techniques used in the medical and healthcare field, which can be more objective. This new method utilizes a literature evaluation framework instead of relying solely on expert judgments, resulting in a more objective assessment of the phenomena’ importance and knowledge level. This study applies the new method to a simplified small modular reactor with a suppression containment system. Following a Loss of Coolant Accident (LOCA), the suppression containment can effectively suppress temperature and pressure increases, ensuring containment integrity. Relevant PIRT tables and a knowledge-level structure are obtained using the new method

Geochemical characteristics of natural gases from different petroleum systems in the Longgang gas field, Sichuan Basin, China

Located in the Sichuan Basin, China, the Longgang gas field consists of three vertically developed petroleum systems with the Triassic Leikoupo Formation as a dividing interface. There is one marine petroleum system below the interface and one continental petroleum system above it. The marine petroleum system is composed of coal measures, the main source rock in the Longtan Formation, and marine reef reservoirs in the Changxing and Feixianguan formations. The continental petroleum system can also be subdivided into two sets. One is the Xujiahe petroleum system sourced from the Xujiahe coal measures in the Upper Triassic formation. The other is a Jurassic petroleum system that is sourced from Jurassic lacustrine black shales. The gas pools in the marine system contain H2S gas. The gases are very dry and the δ13C1 and δ13C2 values display less negative values with an average of −29.2 and −25.0‰, respectively. The gases are humic origin generated at highly to over mature stages from coal measures of the Longtan Formation. The natural gas in the continental petroleum system does not contain H2S. The natural gases from the Xujiahe petroleum system are mainly wet gases with a few dry gases, and belong to typical humic type sourced from coal measures of the Xujiahe Formation. All the gases from this Jurassic petroleum system are wet gases and the alkane gases show more negative carbon isotopic values typical of sapropels. These are derived from the lower Jurassic lacustrine black mudstone. The three sets of petroleum systems in the Longgang gas field are vertically well separated. Each system has its own source rock, and there are no gases from other sources despite multiple tectonic events in the past. The reservoirs had been in a relatively stable tectonic condition with excellent seals by cap rocks during the gas accumulation period

Nature‐inspired K+‐sensitive imaging probes for biomedical applications

Abstract In living systems, potassium ion (K+) plays a vital role in a variety of physiological functions, whose dyshomeostasis has been seen as a biomarker of many diseases. Consequently, real‐time monitoring of K+ dynamics would benefit disease diagnosis and offer insight into the pathogenic mechanisms as well as the progression of diseases. By learning from K+‐specific substances in nature, such as ionophores, ion channels and DNA G‐quadruplex, this perspective introduces the ingenious designs, imaging functionalities, and response principles of K+‐sensitive probes. Furthermore, the recent advances in K+ probes for disease diagnosis, especially for brain disorders and tumors, are briefly summarized. Finally, we highlight the current challenges and future perspectives of K+‐sensitive probes for biomedical applications

The origin of gas in the Changxing–Feixianguan gas pools in the Longgang gas field in the Sichuan Basin, China

In this paper, the origin of natural gas in the formations of the Changxing–Feixianguan within the Longgang gas field was studied in detail using geochemical methods. The gas discovered has a very high dryness coefficient, yet low ethane and other less heavy hydrocarbons content. Apart from a small amount of N2 and CO2 gasses it generally contains H2S. In the field location, the Changxing–Feixianguan formations itself does not have a hydrocarbon generation potential. Nearing the edge of the Kaijiang-Liangping Trough, there developed the Dalong Formation. However, it also has a very low TOC content in the area of the Longgang gas field, and it cannot act as an effective source rock. The geochemistry of natural gas is much different from the gasses generated by the Silurian and Cambrian source rocks. Therefore, it is impossible that the gas in the Longgang gas field is from the Silurian and Cambrian source rocks. Gas reservoirs generally contain bitumen which is considered a product of crude oil cracking. The carbon isotope fractionation between the bitumen and methane is not distinct, and it indicates that the gas is not directly from oil cracking. The carbon of methane and ethane has isotopically less negative value, which is considered to be in a high-overmature coal-formed gas, mainly from the Longtan Formation coal measures. In comparison to the gas from high overmature stage obtained from the Xujiahe coal measure source rock in the Western Sichuan Depression. The methane in the Longgang gas field has abnormal less negative carbon isotopic value. It is due to the superposition of these two factors together: higher evolution of source rocks and mixing of gas degassing from the water. It is not caused by TSR that most researchers believed at present because the methane carbon isotopic values have no relationship with H2S content

Outlier Detection Based on Multivariable Panel Data and K-Means Clustering for Dam Deformation Monitoring Data

A dam is a super-structure widely used in water conservancy engineering fields, and its long-term safety is a focus of social concern. Deformation is a crucial evaluation index and comprehensive reflection of the structural state of dams, and thus there are many research papers on dam deformation data analysis. However, the accuracy of deformation data is the premise of dam safety monitoring analysis, and original deformation data may have some outliers caused by manual errors or instruments aging after long-time running. These abnormal data have a negative impact on the evaluation of dam structural safety. In this study, an analytical method for detecting outliers of dam deformation data was established based on multivariable panel data and K-means clustering theory. First, we arranged the original spatiotemporal monitoring data into the multivariable panel data format. Second, the correlation coefficients between the deformation signals of different measuring points were studied based on K-means clustering theory. Third, the outlier detection rules were established through the changes of the correlation coefficients. Finally, the proposed model was applied to the Jinping-I Arch Dam in China which is the highest dam in the world, and results indicate that the detection method has high accuracy detection ability, which is valuable in dam safety monitoring applications

Spatial distribution, ecological risk and health risk assessment of heavy metals in agricultural soil from Ankang basin, Shaanxi Province

In order to assess the heavy metal pollution features, ecological dangers, and health risk status posed to human beings by soils in the Ankang Basin, a study was conducted. This involved the collection of 38 surface soil samples, followed by the determination of elemental levels of arsenic, mercury, copper, cadmium, lead, chromium, nickel, and zinc. The concentrations of arsenic, mercury, copper, cadmium, lead, chromium, nickel, and zinc were quantified through the collection of 38 surface soil samples. The data obtained from the study was subjected to analysis and evaluation utilizing various academic methodologies, including the geo-accumulation index method, potential ecological risk assessment method, human health risk assessment model, and Monte Carlo simulation method. The findings indicated that the concentrations of the eight heavy metals in the soil above the background levels, with only Cadmium (Cd) marginally surpassing the threshold set for controlling soil pollution risks. The ground accumulation index revealed a higher degree of soil pollution with mercury, cadmium, copper, and zinc components. According to the possible ecological risk index, the presence of mercury and cadmium elements poses significant ecological hazards. The geographical distribution analysis suggests that these risks mostly stem from the combined impacts of human activities and the topographical and geomorphological characteristics of the river valley. The findings of the human health risk assessment indicated that the non-carcinogenic risk fell within acceptable limits. Additionally, it was observed that the carcinogenic risk associated with arsenic, mercury, cadmium, and nickel was comparatively greater for children as compared to adults. The results of the Monte Carlo simulations indicate that the non-carcinogenic hazards have a negligible effect on human health. However, it was seen that arsenic and nickel have a greater likelihood of presenting a substantial carcinogenic risk to humans, particularly in relation to the pediatric population, hence exerting a more pronounced impact on their health. In general, it is observed that conventional deterministic risk assessments tend to overstate the potential health risks associated with a given situation. Conversely, the utilization of Monte Carlo simulations has been found to effectively mitigate uncertainties in health risk assessments. It has been observed that children exhibit a higher vulnerability to both carcinogenic and non-carcinogenic health impacts resulting from exposure to heavy metals present in soil, in comparison to adults. It is recommended that residents prioritize the surveillance of soil heavy metals in relation to potential impacts on human health

Development of a Hybrid Intelligent Process Model for Micro-Electro Discharge Machining Using the TTM-MDS and Gaussian Process Regression

This paper proposed a hybrid intelligent process model, based on a hybrid model combining the two-temperature model (TTM) and molecular dynamics simulation (MDS) (TTM-MDS). Combined atomistic-continuum modeling of short-pulse laser melting and disintegration of metal films [Physical Review B, 68, (064114):1–22.], and Gaussian process regression (GPR), for micro-electrical discharge machining (micro-EDM) were also used. A model of single-spark micro-EDM process has been constructed based on TTM-MDS model to predict the removed depth (RD) and material removal rate (MRR). Then, a GPR model was proposed to establish the relationship between input process parameters (energy area density and pulse-on duration) and the process responses (RD and MRR) for micro-EDM machining. The GPR model was trained, tested, and tuned using the data generated from the numerical simulations. Through the GPR model, it was found that micro-EDM process responses can be accurately predicted for the chosen process conditions. Therefore, the hybrid intelligent model proposed in this paper can be used for a micro-EDM process to predict the performance

Cascade Direct Yaw Moment Control for an Independent Eight In-Wheel Motor-Driven Autonomous Vehicle

Unstructured off-road environments with complex terrain obstacles and pavement properties bring obvious challenges for special purpose autonomous vehicle control. A cascade direct yaw moment control strategy (CDYC), which contains a main loop and a servo loop, is proposed to enhance the accuracy and stability of an independent eight in-wheel motor-driven autonomous vehicle with rear-wheel steering (8WD/RWS). In the main loop, double PID controllers are designed to generate the desired drive moment and yaw rate. In the servo loop, the quadratic programming (QP) algorithm with the tire force boundaries optimally allocates the demanded yaw moment to individual wheel torques. The 8WD/RWS prototype is virtually established using TruckSim and serves as the control object for co-simulation. The proposed cascade controller is verified by simulations in customized off-road driving scenarios. The simulation results show that the proposed control architecture can effectively enhance the path-tracking ability and handling stability of the 8WD/RWS, as to ensure the maneuverability and control stability under extreme off-road conditions