Semi-quantitative Information Research Articles

A facility for studying corrosion via in-situ Raman spectroscopy

Several in-core components in nuclear power systems are exposed to high-temperature water in the presence of radiation fields. The dynamic effect of radiation and water chemistry on material performance in these environments is not well understood partly due to significant experimental challenges. A facility consisting of a high temperature/pressure corrosion loop coupled with in-situ Raman spectroscopy has been commissioned to examine material behaviour in more realistic reactor conditions. The in-situ Raman component of the facility has been validated by conducting experiments with both pre-oxidized, and freshly abraded SS304L in water at 80 °C and 300 °C. Testing in water also revealed the detection limitations of the system. The assessment reported in this paper highlights the capabilities to perform degradation studies of key nuclear components by conducting in-situ characterization of materials exposed to high temperature water via Raman spectroscopy, thereby providing chemical, structural and semi-quantitative kinetic information.

IBRNet: Interpretable Belief Rule Network modeling method for fault diagnosis of redundant inertial navigation systems

With the increasing complexity of inertial navigation systems, especially with the incorporation of redundant inertial measurement units, fault diagnosis is facing new challenges. On one hand, it involves the effective integration of system mechanisms and angular increment data. On the other hand, it focuses on the interpretability of the fault diagnosis models and their corresponding diagnostic results. To address these issues, this article proposes a new belief rule network structure. It takes into account interpretability constraints during the optimization process. The proposed structure, called IBRNet, aims to achieve fault diagnosis of redundant measurement units. Specifically, the belief rule network is used to model semi-quantitative information, and interpretability is achieved through two components: parameter optimization based on interpretability constraints and interpretability analysis based on Kernel SHAP. Additionally, a fault diagnosis model based on IBRNet was established for the inertial measurement unit with 5-table redundancy. Experimental results show that the proposed IBRNet method can provide higher accuracy and interpretability compared to several existing methods.

Urine-based point-of-care testing for factor-Xa-inhibitors in acute ischemic stroke patients: a feasibility study.

Direct oral anticoagulants (DOACs) have become widely used in clinical practice for preventing thromboembolic events. Point-of-care testing methods, particularly those based on urine samples, offer a promising approach for rapid and accurate assessment of DOAC presence. This pilot study aims to evaluate the utility of a urine-based DOAC dipstick test as a point-of-care tool for identifying DOAB presence in acute ischemic stroke (AIS) or transient ischemic attack (TIA) patients. This prospective pilot study included patients with AIS/TIA eligible for DOAC-measurement. After exclusion of 3 patients, 23 patients with DOAC-intake (DOAC group; factor-Xa-inhibitors; n = 23) and 21 patients without DOAC-intake (control-group) remained for analyses. The urine-based DOAC dipstick test and parallel blood-based specific DOAC-level assessment were performed in all patients. Time-intervals of sampling urine/blood sampling and result of DOAC-test were recorded to analyze a potential time benefit based on dipstick evaluation. The urine-based DOAC dipstick test demonstrated high sensitivity (100%) and specificity (100%), correctly identifying all patients with anticoagulatory activity due to DOAC intake (i.e., anti-Xalevel ≥30 ng/mL). Moreover, the visual readout of the test provided semiquantitative information on drug-specific anti-Xa levels, showing a sensitivity of 83% and specificity of 93% to detect anti-Xa levels ≥120 ng/mL. The dipstick test exhibited a median time-benefit of 2:25 h compared to standard blood-based DOAC-level testing. The results of this pilot study underline the efficacy of urine-based point-of-care testing as a rapid and reliable method for assessing DOAC presence in patients with acute ischemic stroke. The value of this tool for clinical decision-making in stroke management needs to be established in future trials.Clinical Trial Registration: Clinicaltrails.org identifier [NCT06037200].

Advancing carotenoid Quantification: A new method for semi-quantitative assessment of β -Carotene and lycopene content in food extracts

Carotenoids, such as lycopene and β-carotene, have been widely recognized for their antioxidant properties and potential health benefits. Accurate quantification of carotenoids in plant extracts is essential for nutritional assessment, quality control, and research investigations. This study introduces an innovative method for quantifying lycopene and β-carotene, in plant extracts and aims to bridge the gap between complex and expensive carotenoid quantification techniques and the need for accessible methods that can be widely adopted. The primary difference between HPLC and HPTLC lies in the medium used for separation. HPLC employs a liquid phase within columns, while HPTLC utilizes a thin layer of adsorbent on a plate. This distinction impacts factors like equipment, cost, and analysis time. The VisionCats software, combined with the CAMAG Visualizer-2, allows the semi-quantification of metabolites using an image-based evaluation method enabling the simultaneous assessment of qualitative and semi-quantitative information from the HPTLC images.Sample preparation involves washing and drying the vegetal material, followed by dichloromethane extraction. HPTLC analysis is performed using the CAMAG Advanced Herbal System, and the validation studies include establishing calibration curves and determining the detection threshold and minimum quantification threshold for lycopene and β-carotene. Specificity and precision were evaluated to ensure accurate identification and repeatability of the method. Data analysis involves selecting the regression method based on the nature of the data and assessing the goodness of fit using the R2 value. The results showed distinct peaks corresponding to lycopene and β-carotene in the chromatograms of the plant extract samples. The visualizer-based method demonstrates good specificity and precision, with no interfering peaks observed and low relative standard deviation. The method shows promising results regarding specificity, precision, and reliability. It has the potential for broader implementation in carotenoid research and rapid monitoring of carotenoid content in various agricultural and food products, particularly in resource-limited settings. Further optimization and validation on a wider range of samples would enhance the applicability of this method in carotenoid research.Sample preparation involves washing and drying the vegetal material, followed by dichloromethane extraction. HPTLC analysis is performed using the CAMAG Advanced Herbal System, and the validation studies include establishing calibration curves and determining the detection threshold and minimum quantification threshold for lycopene and β-carotene. Specificity and precision were evaluated to ensure accurate identification and repeatability of the method. Data analysis involves selecting the regression method based on the nature of the data and assessing the goodness of fit using the R2 value. The results showed distinct peaks corresponding to lycopene and β-carotene in the chromatograms of the plant extract samples. The visualizer-based method demonstrates good specificity and precision, with no interfering peaks observed and low relative standard deviation. The method shows promising results regarding specificity, precision, and reliability. It has the potential for broader implementation in carotenoid research and for rapid screening and monitoring of carotenoid content in various agricultural and food products, particularly in resource-limited settings. Further optimization and validation on a wider range of samples would enhance the applicability of this method in carotenoid research.

The Task Matters: A Comprehensive Review and Proposed Literature Score of the Effects of Chemical and Physical Parameters on Embryo Developmental Competence.

To explore the effects of chemical and physical parameters on embryo developmental competence, we conducted a systematic search on PubMed for peer-reviewed original papers using specific keywords and medical subject heading terms. Studies of interest were selected from an initial cohort of 4141 potentially relevant records retrieved. The most relevant publications were critically evaluated to identify the effect of these parameters on embryo development. Moreover, we generated a literature score (LS) using the following procedure: (i) the number of studies favoring a reference group was expressed as a fraction of all analyzed papers; (ii) the obtained fraction was multiplied by 10 and converted into a decimal number. We identified and discussed six parameters (oxygen, temperature, humidity, oil overlay, light, pH). Moreover, we generated a LS according to five different comparisons (37 °C vs. <37 °C; 5% vs. 20% oxygen; 5-2% vs. 5% oxygen; humidity conditions vs. dry conditions; light exposure vs. reduced/protected light exposure). Only two comparisons (37 °C vs. <37 °C and 5% vs. 20% oxygen) yielded a medium-high LS (8.3 and 7, respectively), suggesting a prevalence of studies in favor of the reference group (37 °C and 5% oxygen). In summary, this review and LS methodology offer semi-quantitative information on studies investigating the effects of chemical and physical parameters on embryo developmental competence.

The Effect of Temperature on Molecular Structure of Medium-Rank Coal via Fourier Transform Infrared Spectroscopy.

Fourier transform infrared spectroscopy (FTIR) was used to study the molecular structure of four medium- and low-temperature heat-treated medium-rank coals. The FTIR spectral parameters, which consist of CH2/CH3, aromaticity (fa), aromatic carbon rate (fC), aromatic hydrogen rate (fH), oxygen-containing (C-O) rate (IR), organic matter maturity (M), and the degree of aromatic condensation (Dc), indicate different characteristics, including changes in the aromatic hydrocarbon structure, fatty hydrocarbon structure, hydroxyl structure, and oxygen-containing functional groups of medium-rank coal. The results show that with the increase in heat treatment temperature, the sulfur content in coal gradually decreases, but the C/H ratio gradually increases. Meanwhile, the content of kaolinite and pyrite in coal gradually decreases, whereas the content of dolomite and hematite gradually increases. With the increase in heat treatment temperature, the relative content of ether oxygen hydroxyl groups in the hydroxyl structure significantly decreases, but the relative content of self-associated hydroxyl groups increases. The relative content of alkyl ether (C-O) in oxygen-containing functional groups gradually increases, whereas the relative content of aromatic nucleus C=C vibration presents a trend of first increasing and then decreasing. In addition, -CH2- is the majority in the structure of fatty hydrocarbons, and the absorption peak intensity of asymmetric -CH3 stretching vibration increases with the increase in heat-treated temperature. The structure of aromatic hydrocarbons mainly consists of four substituted benzene rings (except for R-303.15 K), in which the relative content of the trisubstituted benzene ring decreases with the increase in heat treatment temperature. With the increase in the heat-treated temperature of medium-rank coal, Dc, fH, fC, and fa show a trend of first increasing and then decreasing, M and IR reveal a trend of first decreasing and then increasing, and CH2/CH3 present a gradually decreasing trend. In conclusion, during the increase in the heat treatment temperature of medium-rank coal, the length of the fatty side chains in the fatty hydrocarbon structure becomes shorter, the number of branch chains continuously increases, and the maturity and condensation degree of organic matter first increases and then decreases. On this basis, further research on the effect of coal gasification suggests combining various technologies such as 13C NMR, XRD, and TG-MS to obtain semi-quantitative structural information of molecules in coal from different perspectives.

AgeSpectraAnalyst: A MATLAB based package to model zircon age distributions in silicic magmatic systems

In the last decade, improvements in the analytical precision achievable by zircon U-Pb geochronological techniques have allowed to resolve complexities of zircon crystallization histories in magmatic rocks to an unprecedented level. A number of studies have strived to link resolvable dispersion in zircon age spectra of samples from fossil magmatic systems to the physical parameters of their parent magma bodies. However, the methodologies developed have so far been limited to reproduce the effect of simple thermal histories on the final distribution of zircon ages. In this work we take a more nuanced approach, fine-tuning a thermodynamics-based zircon saturation model to predict the relative distribution of zircon ages in samples from silicic magma reservoirs experiencing open-system processes (e.g. heat/mass addition, mechanical mixing). Employing the MATLAB package (AgeSpectraAnalyst) presented in this contribution:•Users can forward model the effect that diverse thermal histories and mechanical mixing processes characteristic of silicic magma bodies have on zircon age distributions as measured by high-precision, chemical abrasion thermal ionization mass spectrometry (CA-ID-TIMS) U-Pb geochronology.•Zircon CA-ID-TIMS datasets from silicic magmatic systems can be easily compared with model output to gain semi-quantitative information on thermo-mechanical history of the system of interest.•We demonstrated (Tavazzani et al., in press) that distribution of high-precision zircon ages in crystallized remnants of shallow (∼ 250 MPa), silicic magma reservoirs can discriminate between systems that experienced catastrophic, caldera-forming eruptions and systems that underwent monotonic cooling histories.

Understanding the Catalytic Mechanism of Redox Mediators for Li-O2 Batteries Using Cyclic Voltammetry

Lithium-air batteries are appealing candidates for high-energy electric vehicle applications because they have a theoretical capacity 3 to 5 times higher than li-ion batteries. They are composed of a lithium anode and a porous conductive matrix (usually carbon-based), where oxygen is reduced during discharge and oxidized during charge. One of the major issues is the high overpotentials needed to recharge the battery due to the isolating nature of the solid discharge product, lithium peroxide.The use of redox mediators (RMs) for the discharge and charge reactions has gained popularity because it can increase energy efficiency and minimize electrolyte degradation. These molecules act as soluble catalysts: during the discharge, the RM molecule is reduced at the surface of the electrode; it then diffuses through the solution where it can react with solubilized oxygen to form big solid deposits of Li2O2. In the case of charge, the RM is oxidized at the free surface of the electrode that is not blocked by Li2O2, and then chemically reacts with it to release O2. Thus, RMs allow decoupling of the oxygen reduction reaction oxygen evolution reaction from the electron transfer (ET) reactions at the electrode, giving the charge transfer an alternative path to the electrically insulating Li2O2.1 Previous studies have mainly focused on the thermodynamic aspects governing the ability of a molecule to act as a successful RM. The principal parameter analysed is usually the standard potential of the electrochemical couple, although oftentimes it is poorly characterized using inadequate reference electrodes or assumed to be independent of the solvent, Li salt concentration and identity. Some attention has been given to the effect of solvation environments on the potential of iodide,2 but little has been said about other RMs.3 Since most ET reactions with RMs involve a significant change in the charge/size ratio of the molecule or ion, it is only natural that the driving force for this reaction will be dependent on the environment.The kinetics of the ET and of the reaction of RM with the target species (O2 in the case of discharge RM and Li2O2 in the case of charge) is another factor that has received almost no attention, and yet it is crucial for the operation of a Li-O2 battery. Some effort has been made to relate the kinetics of the catalysis to the standard potential of the RM or the ET kinetics,4 but there is no consensus regarding these effects. No rationalization of the effect of solvation environments such as ionic association or DN of the solvent on the kinetics has been established either.Cyclic voltammetry (CV) is a very useful tool to probe the kinetics both of electrochemical reactions and chemical reactions. It is possible to decouple the influence of these two types of processes by varying the scan rate. Furthermore, the effect of ionic association and solvation environment become easily identifiable in CVs. We show how these parameters affect simulated experiments, and how this can facilitate the understanding of the processes limiting the performance of a cell. Moreover, we can use this approach to extract semiquantitative information about the catalytic mechanism both for charge RM and discharge RM by comparing it with experimental data.To benchmark our simulations, the electrochemical behaviour of two typical RMs was studied. 2,5-di-tert-butyl-1,4-benzoquinone (DBBQ) and lithium iodide were used as discharge and charge redox mediator models, respectively. This way, we evidenced the effect of different solvents and of ionic association on CVs, and we showed that the effect of the chemical reaction between triiodide and Li₂O₂ becomes more important at slow scan rates (<1 mV/s). Using this approach, we were able to probe the timescales of the catalytic behaviour of triiodide and relate it to the performance of mediated lithium-oxygen batteries at different charge rates.The advantage of this approach is that it is easily generalizable to other kinds of RMs, without the need of following specific functional groups that depend on the structure of the molecule. This will allow for quantitative information to be obtained about the catalytic behaviour, and aid the understanding of catalytic mechanisms of Li-O2 batteries. Further implementation of this method will be aimed at establishing relationships between the catalytic and the thermodynamic parameters.

Content and form of original research articles in general major medical journals.

The title of an article is the main entrance for reading the full article. The aim of our work therefore is to examine differences of title content and form between original research articles and its changes over time. Using PubMed we examined title properties of 500 randomly chosen original research articles published in the general major medical journals BMJ, JAMA, Lancet, NEJM and PLOS Medicine between 2011 and 2020. Articles were manually evaluated with two independent raters. To analyze differences between journals and changes over time, we performed random effect meta-analyses and logistic regression models. Mentioning of results, providing any quantitative or semi-quantitative information, using a declarative title, a dash or a question mark were rarely used in the title in all considered journals. The use of a subtitle, methods-related items, such as mentioning of methods, clinical context or treatment increased over time (all p < 0.05), while the use of phrasal tiles decreased over time (p = 0.044). Not a single NEJM title contained a study name, while the Lancet had the highest usage of it (45%). The use of study names increased over time (per year odds ratio: 1.13 (95% CI: [1.03‒1.24]), p = 0.008). Investigating title content and form was time-consuming because some criteria could only be adequately evaluated by hand. Title content changed over time and differed substantially between the five major medical journals. Authors are advised to carefully study titles of journal articles in their target journal prior to manuscript submission.

Advancements in portable instruments based on affinity-capture-migration and affinity-capture-separation for use in clinical testing and life science applications

The shift from testing at centralized diagnostic laboratories to remote locations is being driven by the development of point-of-care (POC) instruments and represents a transformative moment in medicine. POC instruments address the need for rapid results that can inform faster therapeutic decisions and interventions. These instruments are especially valuable in the field, such as in an ambulance, or in remote and rural locations. The development of telehealth, enabled by advancements in digital technologies like smartphones and cloud computing, is also aiding in this evolution, allowing medical professionals to provide care remotely, potentially reducing healthcare costs and improving patient longevity. One notable POC device is the lateral flow immunoassay (LFIA), which played a major role in addressing the COVID-19 pandemic due to its ease of use, rapid analysis time, and low cost. However, LFIA tests exhibit relatively low analytical sensitivity and provide semi-quantitative information, indicating either a positive, negative, or inconclusive result, which can be attributed to its one-dimensional format. Immunoaffinity capillary electrophoresis (IACE), on the other hand, offers a two-dimensional format that includes an affinity-capture step of one or more matrix constituents followed by release and electrophoretic separation. The method provides greater analytical sensitivity, and quantitative information, thereby reducing the rate of false positives, false negatives, and inconclusive results. Combining LFIA and IACE technologies can thus provide an effective and economical solution for screening, confirming results, and monitoring patient progress, representing a key strategy in advancing diagnostics in healthcare.

An interpretable method for inertial platform fault diagnosis based on combination belief rule base

As a key component of navigation equipment, the inertial platform needs high reliability, so an accurate and interpretable method for fault diagnosis is necessary. The belief rule base (BRB) has strong interpretability and its ability to process semi-quantitative information. However, the high complexity of inertial platforms leads to the existence of multiple indicators for use in fault diagnosis, which leads to the combinatorial explosion of rules problem in BRB. Considering this problem, an interpretable method for inertial platform fault diagnosis based on combination BRB is proposed here. This paper provides two main contributions: 1) A BRB optimization method considering the correlation coefficient is proposed, which maintains the interpretability of sub-BRBs in the combination BRB, and 2) a method is proposed to calculate the sub-BRB weights based on the precision of the sub-BRBs and the occurrence times of repeated indicators, thus ensuring that the fusion process is explainable when the ER algorithm is used for the fusion of sub-BRBs. The proposed method ensures the interpretability of the final result during fault diagnosis while maintaining the reliability of the inertial platform. Finally, the effectiveness of the proposed method is verified against state-of-the-art methods using actual operation data from an inertial platform.

A novel optimization method for belief rule base expert system with activation rate

Although the belief rule base (BRB) expert system has many advantages, such as the effective use of semi-quantitative information, objective description of uncertainty, and efficient nonlinear modeling capability, it is always limited by the problem of combinatorial explosion. The main reason is that the optimization of a BRB with many rules will consume many computing resources, which makes it unable to meet the real-time requirements in some complex systems. Another reason is that the optimization process will destroy the interpretability of those parameters that belong to the inadequately activated rules given by experts. To solve these problems, a novel optimization method for BRB is proposed in this paper. Through the activation rate, the rules that have never been activated or inadequately activated are pruned during the optimization process. Furthermore, even if there is a complete data set and all rules are activated, the activation rate can also be used in the parallel optimization process of the BRB expert system, where the training data set is divided into some subprocesses. The proposed method effectively solves the combinatorial explosion problem of BRB and can make full use of quantitative data without destroying the original interpretability provided by experts. Case studies prove the advantages and effectiveness of the proposed method, which greatly expands the application fields of the BRB expert system.

Non-destructive estimation of the cation composition of natural carbonates by micro-Raman spectroscopy

Carbonates play a crucial role in the water and carbon cycles of both geochemical and cosmochemical environments. As carbonates do not exist homogeneously with other minerals in rocks and sands of various sizes, an analytical method that simultaneously satisfies non-destructivity and high spatial resolution has been desired. Further, the ability of semi-quantitative analysis with carbonates-selectivity and without any pre-treatments is added, for its applicability would be extended to remote sensing for deep sea and outer spaces. Here, we focused on the application of micro-Raman spectroscopy, where the vibrational wavenumbers of the translational (T) and librational (L) modes of carbonates are sensitively related to their cation composition. By comparing the semi-quantitative information obtained by X-ray fluorescence spectroscopy, it was found that these vibrational wavenumbers are approximately linearly related to the cation composition. Consequently, a conversion matrix was proposed to estimate the cation composition from the T and L mode vibrational wavenumbers. This method is universally applicable to any cation composition in carbonates, with no background information on the analyte required. To improve the accuracy, conversion matrices were further optimized to three solid-solution series of carbonates. It is worth noting that the proposed conversion matrices are free from matrix effects and do not depend on the total amount of carbonate in a sample. Therefore, the proposed method provides a useful analytical basis for remote sensing of the cation composition of carbonates, both in terrestrial and extra-terrestrial environments.

Cybersecurity Status Assessment of Cloud Manufacturing Systems Based on Semiquantitative Information

The network security status assessment (NSSA) method can evaluate the network security status of cloud manufacturing systems (CMSs), which is of great significance to reduce the network security risk and loss of CMSs. At present, the NSSA of CMSs suitable for semiquantitative and uncertain information conditions is commonly used, which has certain limitations and low accuracy. This paper proposes an NSSA method for CMSs based on semiquantitative information. First, through the detailed analysis of the influencing factors of the network security status of the CMSs, the security evaluation indicators were selected, and the evaluation framework containing multilevel indicators was established by combining semiquantitative information. Second, the evaluation level was established according to the data distribution and the properties of the indicators. Third, a process of data fusion reasoning based on an evidential reasoning algorithm is designed, and a strong reference fusion case is given. Finally, the effectiveness of the proposed security state assessment algorithm in the NSSA of CMSs was verified and analyzed by simulation experiments. The experimental results show that the proposed method can make full use of semiquantitative information and uncertain information to evaluate the network security status of CMSs, and the evaluation results can reflect the actual security status of CMSs.

Estimation of the Quality of the Diet of Mexican University Students Using DQI-I

The quality of diet can be measured using diet quality indices, based on knowledge of associations between diet and health. The objective of this work was to evaluate whether the International Diet Quality Index is suitable for use as a diet quality index in populations of Mexican university girls. A cross-sectional nutritional survey was conducted at the University of Chihuahua (Mexico), collecting semi-quantitative nutritional information and socio-economic and lifestyle data from a representative sample of 400 women. Mean (Standard Deviation (SD)) age was 21.43 years (SD: 3.72); 59.1% were normal weight, 26.6% overweight, 15.3% obesity. The Diet Quality Index-International (DQI-I) was developed according to the method of Kim et al. (2003) and focused on major aspects of a high-quality diet (variety, adequacy, moderation and overall balance). The total score of Diet Quality Index-International reached 53.86% (SD: 11.43), indicating that the general diet of Mexican women a poor-quality diet. Adequacy scored highest, followed by moderation and variety. Overall balance scored the lowest. Variety: 26.3 % consumed less than 4 food groups daily, only 12.8% take more than 1 serving from each food group, and 50.6% consumed only one source of protein daily. Regarding adequacy, a large proportion of the population reported an intake of proteins, vitamin C, calcium, iron, and fruit greater than 50% of recommendation; the vegetables, fiber and grain groups were less 50%. Poor scores were obtained for total fat and SFA consumption (moderation). No statistically significant differences are observed for any of the variables under study and score of the Diet Quality Index-International: body mass index, weight, physical activity level, education level of father and mother, location of lunch, breakfast considered important, knowledge of nutrition, which allows us to consider a relatively uniform population in its eating habits. These people are close to a Westernized diet, and an intervention in nutritional education would be advisable to improve the intake of unprocessed foods, consume a greater variety of protein sources and significantly reduce consumption of sugary foods and soft drinks. Due to different methodological and cultural factors, the proposed Diet Quality Index-International dietary assessment method does not seem to be useful in the assessment of diet quality in the Mexican university population, so further research is needed to develop a diet quality index adapted to the Mexican population.

A New Model for Network Security Situation Assessment of the Industrial Internet

To address the problem of network security situation assessment in the Industrial Internet, this paper adopts the evidential reasoning (ER)algorithm and belief rule base (BRB) method to establish an assessment model. First, this paper analyzes the influencing factors of the Industrial Internet and selects evaluation indicators that contain not only quantitative data but also qualitative knowledge. Second, the evaluation indicators are fused with expert knowledge and the ER algorithm. According to the fusion results, a network security situation assessment model of the Industrial Internet based on the ER and BRB method is established, and the projection covariance matrix adaptive evolution strategy (P-CMA-ES) is used to optimize the model parameters. This method can not only utilize semiquantitative information effectively but also use more uncertain information and prevent the problem of combinatorial explosion. Moreover, it solves the problem of the uncertainty of expert knowledge and overcomes the problem of low modeling accuracy caused by insufficient data. Finally, a network security situation assessment case of the Industrial Internet is analyzed to verify the effectiveness and superiority of the method. The research results show that this method has strong applicability to the network security situation assessment of complex Industrial Internet systems. It can accurately reflect the actual network security situation of Industrial Internet systems and provide safe and reliable suggestions for network administrators to take timely countermeasures, thereby improving the risk monitoring and emergency response capabilities of the Industrial Internet.

A Liquid Launch Vehicle Safety Assessment Model Based on Semi-Quantitative Interval Belief Rule Base

As the propulsion part of a space launch vehicle and nuclear weapon missile, the health status of the liquid rocket determines whether the space launch vehicle and nuclear weapon missile can function normally. Therefore, it is of great significance to evaluate the health status of the liquid rocket. As the structure of the liquid rocket is becoming increasingly sophisticated, subjective judgment alone can no longer meet the needs of the actual system. As an expert system and a gray-box model, the belief rule base (BRB) can process both qualitative and quantitative information. The expert knowledge base is used in the safety assessment of a liquid rocket. However, in practical applications, the traditional BRB model still has two problems, which are that (1) when there are too many premise attributes, it easily leads to the explosion of combination rules, and (2) the reliability of rules is not considered in the process of model reasoning. Therefore, this paper proposes the BRB model with intervals (intervals-BRB) on the basis of traditional BRB. The interval-BRB retains the advantage of the traditional BRB, which can handle semi-quantitative information. In addition, the proposed model changes the reference point of the prerequisite attribute to the reference interval and changes the rule combination. This solves the problem of the traditional BRB explosive combination rule. The ER-rule (evidential reasoning rule) is introduced into the reasoning procedure, and the weight of the rule and the reliability of the rule are considered at the same time, which solves the shortcoming of the traditional BRB, which does not consider the reliability of the rule in reasoning. Finally, the CMAES optimization algorithm is used to optimize the initial model to obtain better performance. Finally, the model is verified by the actual data set of a liquid rocket, and the experimental results show that the model can achieve good experimental results.

Applications and limitations of portable density meter measurements of Na-Ca-Mg-K-Cl-SO4 brines

Knowledge of brine density and mineral saturation states under different temperatures contributes to understanding Earth systems, including dissolution and crystallization of chemical sediments, mixing water bodies with variable density, and mineral resource development and evolution. However, these interpretations often rely on geochemical measurements with low accuracies at high salinities. Here, we test the utility of density measurments to advance understanding of brine geochemistry. We demonstrate the accuracy and limits of determining a brine's density and halite saturation state at multiple temperatures with rapid and relatively inexpensive portable density meter measurements. Density measurements at different temperatures are used to create samples' equations of state, which are used to extrapolate measurements. This methodology presents multiple opportunities. We use brine samples from around the world to show that density and equation of state data provide semi-quantitative information about sample composition and temperature-sensitive mineral precipitation. Importantly, density measurements can be used to evaluate error-prone geochemical measurements. We illustrate applications with brine samples from the Bonneville Salt Flats, a landscape in Utah, USA, that is valued for mineral resources and recreation opportunities. We developed system-scale equations of state for these saline pan samples and their halite-saturated counterparts. We evaluated methodological limitations with duplication tests and by determining if diurnal fluctuations in salinity and halite saturation in a shallow pool's brine and shallow groundwater in contact with a halite crust were detectable. Average daily changes in halite saturation of shallow pool brine of approximately 3 kg m−3 were clearly detected, while diurnal halite saturation fluctuations in the shallow halite crust brine of 0.4 to 0.7 kg m−3 were near method limits. Because of their accuracy, low cost, and applications, portable density meter measurements of brines are invaluable in studying brine systems.

Formation of melanoidins and development of characterization techniques during thermal pretreatment of organic solid waste: A critical review

Melanoidins are Maillard products produced in the thermal pretreatment of organic solid waste represented by food waste and sludge. Their effect on anaerobic fermentation is related to energy recovery efficiency. Based on the researches of melanoidins in food field, this review paper aims to improve the understanding of melanoidins in waste treatment and anaerobic fermentation. The formation mechanism of melanoidins is complex, and the molecular weight and structure are not systematic and standardized. During the Maillard reaction process, the basic characteristics of melanoidins are affected by the type of reactants, temperature, pH and the presence of metal ions. In addition, the physicochemical and biological properties of melanoidin itself involve the mechanism explanation of melanoid behavior. Antioxidant, antimicrobial and metal chelating abilities are related to the inhibition or promotion of melanoidins in anaerobic fermentation, but the specific mechanism (such as cytotoxicity or the effect on interspecific electron transfer) still needs to be further explored. Finally, the characterization of melanoidins can provide more accurate semi-quantitative information with the development of analytical technology. The colorimetric method, ultraviolet/visible (UV/Vis) spectrophotometry, excitation-emission matrix joint region integration method and parallel factor analysis method developed from the color and structure characteristics of melanoidins have become the commonly used characterization techniques. In this review, the formation mechanism and influencing factors of melanoidins from organic solid waste by thermal pretreatment were investigated, the characteristics and characterization techniques of melanoidins were reviewed, and the possible ways of melanoidins affecting high quality products were put forward, which provided a reference for the efficient utilization of organic solid waste by thermal pretreatment coupled with anaerobic fermentation.

Lateral Flow Microimmunoassay (LFµIA) for the Reliable Quantification of Allergen Traces in Food Consumables.

Quality assurance and food safety are of great concern within the food industry because of unknown quantities of allergens often present in food. Therefore, there is an ongoing need to develop rapid, sensitive, and easy to use methods that serve as an alternative to mass spectrometry and enzyme-linked immunosorbent assay (ELISA) for monitoring food safety. Lateral flow immunoassay is one of the most used point-of-need devices for clinical, environmental, and food safety applications. Compared to traditional methods, it appears to be a simple and fast alternative for detecting food allergens. However, its reliability is frequently questioned due to the lack of quantitative information. In this study, a lateral flow microimmunoassay (LFµIA) is presented that integrates up to 36 spots in microarray format in a single strip, providing semi-quantitative information about the level of allergens, positive and negative controls, internal calibration, and hook effect. The LFµIA has been evaluated for the on-site simultaneous and reliable quantification of almond and peanut allergens as a proof of concept, demonstrating high sensitivity (185 and 229 µg/kg, respectively), selectivity (77%), and accuracy (RSD 5-25%) when analyzing commercial allergen-suspicious food consumables.