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Aflatoxin B1 (AFB1) contamination poses a fatal risk to human beings and urgently needs highly sensitive detection for environmental monitoring and food safety. However, the existing challenges are the unsatisfied sensitivity of the immunoassay methods and the complex matrix effect. Rolling circle amplification (RCA) is a promising method for nucleic acid isothermal amplification due to its high specificity and sensitivity. Herein, we constructed a general RCA-based point-of-care test method (RCA−POCT). With biotinylated antibodies, streptavidin, and biotinylated RCA primers, we realized the signal transduction and preliminary signal amplification. In this way, the fluorescent signal of the immunocomplex on the microwells was greatly enhanced. Under optimal conditions, we recorded sensitive detection limits for aflatoxin B1 (AFB1) of 1.94, 16.3, and 37.7 fg/mL (femtogram per microliter), and wide linear ranges with 5 × 10−6 to 5, 5 × 10−5 to 5, and 5 × 10−5 to 5 ng/mL in the irrigation water, field soil, and peanut samples, respectively. Satisfactory recovery, specificity, repeatability, and reproducibility were observed. The RCA−POCT was validated by comparing it to the HPLC method. This work provides a general RCA-assisted detection method for AFB1 in the environment and food. [ABSTRACT FROM AUTHOR]

In a previous study, rice bread was prepared using a combination of rice–wheat mixed flour. To investigate the impact of the partial adoption of extruded rice flour (ERF) on mixed flour (MF) and mixed dough (MD), the effects of adding ERF on the pasting, mixing characteristics, texture, and water retention of the MF and MD were examined by a rapid visco analyzer (RVA), Mixolab, texture profile analysis (TPA), and a low-field nuclear magnetic resonance analyzer (LF-NMR). The PV, TV, BD, FV, and SV of the MF declined as the incorporated amount of ERF increased. There was no significant difference in the PT at the 5–15% addition level (p < 0.05), but it showed an increasing trend at the 20–30% level (p < 0.05). The incorporation of ERF led to a significant increase in the water absorption (WA) of the MD, while the DT, ST, C2, C3, C4, and C5 exhibited a declining trend. The texture analysis revealed a significant decrease in the dough hardness with the addition of ERF, with a 55% reduction in the hardness of the 30% improved mixed dough (IMD), and the cohesiveness increased significantly (p < 0.05). The IMD was mainly composed of weakly bound water. The content of weakly bound water increased with the ERF amount. [ABSTRACT FROM AUTHOR]

To overcome the limitations of the sparrow search algorithm and the challenges of dynamic obstacle avoidance in mobile robots, an integrated method combining the enhanced sparrow search algorithm with the dynamic window approach is introduced. First, logistic–tent chaotic mapping is utilized for the initialization of the sparrow population, thereby achieving a uniform distribution of the sparrow population and simultaneously enhancing the exploratory capability of the algorithm. The implementation of the elite reverse learning strategy aims to diversify the sparrow population, thus improving the quality of initial solutions and the algorithm's search accuracy. Additionally, the position update dynamic self-adaptive adjustment strategy is adopted to enhance the optimization capability of the algorithm by refining the position update formulas for both producers and scroungers. By combining the Lévy flight strategy and the optimal position perturbation strategy, the algorithm's efficacy in escaping local optima can be improved. Second, an adaptive velocity adjustment strategy is presented for the dynamic window approach and optimized for its evaluation function to enhance the safety of the path. Third, the enhanced sparrow search algorithm is integrated with the dynamic window approach to tackle the problems of the non-smooth global path and inadequate dynamic obstacle avoidance capability. Both simulation and experimental results show the superiority of the enhanced sparrow search algorithm in comparison to other algorithms in terms of the path length, total rotation angle, and algorithm execution time. Notably, in comparison to the basic sparrow search algorithm, there is a decrease in average path lengths by 15.31% and 11.92% in the improved sparrow search algorithm. The integrated algorithm not only crafts local paths rooted in global paths but also adeptly facilitates real-time dynamic obstacle evasion, ensuring the robot's safe arrival at its destination. [ABSTRACT FROM AUTHOR]

Sensitive, intelligent point-of-care test (iPOCT) methods for small molecules like aflatoxin B1 (AFB1) are urgently needed for food and the environment. The challenge remains of surface control in iPOCT. Herein, we developed an electrochemical sensor based on the DNA pyramid (DNP), combining a smartphone, app, and mobile electrochemical workstations to detect AFB1. The DNP's structure can reduce local overcrowding and entanglement between neighboring probes, control the density and orientation of recognition probes (antibodies), produce uniform and orientational surface assemblies, and improve antigen–antibody-specific recognition and binding efficiency. Simultaneously, the hollow structure of the DNP enhances the electron transfer capacity and increases the sensitivity of electrochemical detection. In this work, the biosensor based on DNP was first combined with electrochemical (Ec) iPOCT to simultaneously achieve ordered interface modulation of recognition probes and intelligent detection of AFB1. Under optimal conditions, we found a detection limit of 3 pg/mL and a linear range of 0.006–30 ng/mL (R2 = 0.995). Further, using peanut, soybean, corn, and lake water as complex matrices, it recorded recoveries of 82.15–100.53%, excellent selectivity, acceptable stability, and good reproducibility. Finally, this Ec iPOCT provides consistent results compared to the high-performance liquid chromatography-tandem mass spectrometry method. [ABSTRACT FROM AUTHOR]

In the complex and ever-changing manufacturing environment, maintaining the long-term steady and efficient work of the assembly line is the ultimate goal pursued by relevant enterprises, the foundation of which is a balanced load. Therefore, this paper carries out research on the two-sided assembly line balance problem (TALBP) for load balancing. At first, a mathematical programming model is established with the objectives of optimizing the line efficiency, smoothness index, and completion time smoothness index of the two-sided assembly line (TAL). Secondly, a deep reinforcement learning algorithm combining distributed proximal policy optimization (DPPO) and the convolutional neural network (CNN) is proposed. Based on the distributed reinforcement learning agent structure assisted by the marker layer, the task assignment states of the two-sided assembly and decisions of selecting tasks are defined. Task assignment logic and reward function are designed according to the optimization objectives to guide task selection and assignment. Finally, the performance of the proposed algorithm is verified on the benchmark problem. [ABSTRACT FROM AUTHOR]

As an indispensable part of the automobile factory transmission system, the transmission assembly line has a high level of automation and can play as a pioneer in the digital transformation of production. However, for the transmission production process, especially the front and middle case, there are many problems, such as a low degree of informatization, low efficiency of information transmission, and lack of a platform for rapid information release and sharing. This leads to the difficulty of timely discovery and feedback of exceptional events, resulting in low assembly efficiency. Therefore, this paper constructs its cyber–physical system (CPS) with the help of the Internet of Things (IoT) technologies, such as physical identification, information collection, and transmission. It contributes to improving the intelligent level of transmission of front and middle case assembly, strengthening the close integration, interaction, and collaboration between a large amount of assembly data and the physical entity of the assembly process, realizing the real-time monitoring of the transmission front and middle case assembly process, timely discovering, provide feedback, and dealing with exceptional events. In addition, scientific and effective adjustment strategies based on the data can be provided. Ultimately, the assembly efficiency of the transmission front and middle case is improved, ensuring the stability of the assembly line. [ABSTRACT FROM AUTHOR]

AlGaN/GaN high-electron-mobility transistors (HEMTs) with two different gate–drain distances (30 μm and 10 μm) were exposed to 1 MeV, 0.6 MeV, and 0.4 MeV protons at a fluence of 2.16 × 1012 cm−2. The gate–channel electron density and low-field mobility were obtained by measuring the capacitance–voltage characteristics and current–voltage characteristics. After proton irradiation, the gate–channel low-field electron mobility of the AlGaN/GaN HEMT with a 30 μm gate–drain distance increases and that with a 10 μm gate–drain distance decreases. It is studied and found that the mobility behavior is related to the polarization Coulomb field scattering, and the proton irradiation influences the intensity of the polarization Coulomb field scattering by changing the polarization/strain distribution in the barrier layer. The different gate–drain distances correspond to different variation trends of scattering intensity. The effect of 1 MeV protons on the barrier layer is smaller compared with 0.6 MeV and 0.4 MeV protons, so the mobility variation is smaller. [ABSTRACT FROM AUTHOR]

The rapid development of electromagnetic technology has been widely used in many fields. For example, the transmission of electromagnetic waves in extreme environments (such as sandstorms and haze) and the monitoring of particle composition in the atmosphere by using electromagnetic wave technology. The properties of particles, such as particle electrification, will affect electromagnetic wave scattering and directly affect the signal transmission quality and monitoring results. Based on the scattering characteristics of electromagnetic waves of charged particles, the effects of different particle composition, different electric quantity, different humidity and different particle numbers on electromagnetic wave propagation are studied in this paper. The multiple scattering of electromagnetic waves by the random distribution of multiple particles is studied, and the Maxwell equation is converted into the Foldy–Lax multiple scattering equation, and the numerical solution is carried out. The influence of charged particle clusters on the electromagnetic scattering is analyzed. The simulation and experiment show that the charge of particles has a great influence on the electromagnetic scattering near some frequencies. [ABSTRACT FROM AUTHOR]

Ochratoxin A (OTA) poses a severe health risk to livestock along the food chain. Moreover, according to the International Agency for Research on Cancer, it is also categorized as being possibly carcinogenic to humans. The lack of intelligent point-of-care test (POCT) methods restricts its early detection and prevention. This work establishes a smartphone-enabled point-of-care test for OTA detection via a fluorescent lateral flow assay within 6 min. By using a smartphone and portable reader, the assay allows for the recording and sharing of the detection results in a cloud database. This intelligent POCT provided (iPOCT) a linearity range of 0.1–3.0 ng/mL and a limit of detection (LOD) of 0.02 ng/mL (0.32 µg/kg in wheat). By spiking OTA in blank wheat samples, the recoveries were 89.1–120.4%, with a relative standard deviation (RSD) between 3.9–9.1%. The repeatability and reproducibility were 94.2–101.7% and 94.6–103.4%, respectively. This work provides a promising intelligent POCT method for food safety. [ABSTRACT FROM AUTHOR]

Microplastic pollution is a global problem that has attracted extensive attention and has become a very hot topic in the scientific community. Overall, this indication suggests that nanoplastics may negatively affect the efflux capacity of ABC transporters and may lead to the accidental accumulation of organic pollutants that coexist in aquatic organisms. The result highlights microplastic pollution in Zhanjiang Bay before and after the typhoon and provides theoretical support for future studies on microplastic pollution in coastal water ecosystems and the effects of typhoons on distributions of microplastics. I Aedes aegypti i L. did not affect its survival rate, and at all life stages, the average weight of mosquitoes eating PS microspheres was higher than that of the control group. [Extracted from the article]

Diabetic retinopathy (DR) is one of the most common and serious microvascular complications of diabetes. Although current treatments can control the progression of DR to a certain extent, there is no effective treatment for early DR. Apart from vascular endothelial growth factor, it has been noted that the apelin/APJ system contributes to the pathogenesis of DR. We used a high-fat diet/streptozotocin-induced type 2 diabetic mouse model. The mice were divided into a lentivirus control group (LV-EGFP), an apelin-overexpression group (LV-Apelin+), and an apelin-knockdown group (LV-Apelin−), all of which were administrated intravitreal injections. LV-Apelin+ ameliorated the loss of pericytes in DR mice, whereas LV-Apelin− aggravated the loss of pericytes. Similarly, LV-Apelin+ reduced the leakage of retinal vessels, whereas LV-Apelin− exacerbated it. The genes and signaling pathway related to cell adhesion molecules were downregulated, whereas the cell–cell tight junctions and anti-apoptotic genes were upregulated in response to apelin overexpression. However, the alterations of these same genes and signaling pathways were reversed in the case of apelin knockdown. Additionally, LV-Apelin+ increased ZO-1 and occludin levels, whereas LV-Apelin− decreased them. Our results suggest that apelin can reduce vascular leakage by protecting pericytes, which offers a promising new direction for the early treatment of DR. [ABSTRACT FROM AUTHOR]

Ultra-high frequency (UHF) signal detection is one of the most effective methods for spatial orientation and partial discharge fault diagnosis. However, when the background noise, especially Gaussian white noise and narrow-band interference, is very high, or the detection region is remote, location accuracy may decrease. To improve this, a location system based on the improved higher-order cumulant time delay estimation (TDE) method combined with energy accumulation is proposed. In the system, the UHF waves are received by a four-antenna array. Improved fourth-order cumulants with a smoothed coherence transform (SCOT) window are used in the TDE, by which Gaussian white noise and narrow-band interference can be efficiently suppressed. The energy accumulation algorithm is applied to the cross-correlation results, by which the accuracy of TDE can be enhanced. The applicability of the proposed localization algorithm is evaluated by simulation and experiment. The simulation results show that the improved fourth-order cumulant TDE-parameter accumulation algorithm is superior in accuracy to traditional location methods. In the experimental measurements, two partial discharge measurement points located in a complex electromagnetic environment are tested. The results illustrate that the proposed method can effectively suppress Gaussian white and narrow-band noise, and the location results can satisfy accuracy requirements when the measurement point is within 70 m. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has severely impacted healthcare systems worldwide. This study investigated cardiologists' opinions on how the COVID-19 pandemic impacted clinical practice patterns in atrial fibrillation (AF). A multicenter clinician survey, including demographic and clinical questions, was administered to 300 cardiologists from 22 provinces in China, in April 2022. The survey solicited information about their treatment recommendations for AF and their perceptions of how the COVID-19 pandemic has impacted their clinical practice patterns for AF. The survey was completed by 213 cardiologists (71.0%) and included employees in tertiary hospitals (82.6%) and specialists with over 10 years of clinical cardiology practice (53.5%). Most respondents stated that there were reductions in the number of inpatients and outpatients with AF in their hospital during the pandemic. A majority of participants stated that the pandemic had impacted the treatment strategies for all types of AF, although to different extents. Compared with that during the assumed non-pandemic period in the hypothetical clinical questions, the selection of invasive interventional therapies (catheter ablation, percutaneous left atrial appendage occlusion) was significantly decreased (all p < 0.05) during the pandemic. There was no significant difference in the selection of non-invasive therapeutic strategies (the management of cardiovascular risk factors and concomitant diseases, pharmacotherapy for stroke prevention, heart rate control, and rhythm control) between the pandemic and non-pandemic periods (all p > 0.05). The COVID-19 pandemic has had a profound impact on the clinical practice patterns of AF. The selection of catheter ablation and percutaneous left atrial appendage occlusion was significantly reduced, whereas pharmacotherapy was often stated as the preferred option by participating cardiologists. [ABSTRACT FROM AUTHOR]

In this paper, the electrostatic discharge of solar arrays in spacecraft energy systems is taken as the research object. The influence and internal mechanism of external electromagnetic radiation on electrostatic discharge is studied. Meanwhile, the charging and discharging test platform of spacecraft solar arrays under a strong field is first established. Then, the influence of irradiation field strength, electron beam energy and beam density on electrostatic discharge of solar arrays is analyzed and summarized. The results show that during the irradiation process of solar arrays using a high-energy electron beam under vacuum conditions, the higher the electron beam energy and the beam current density, the higher the discharge frequency of the solar array. When the intensity of the external electromagnetic radiation field increases, the discharge frequency also increases. Under the action of external radiation field with the same peak field strength, the larger the gap, the smaller the discharge frequency. With the increase in the field strength, the potential difference of each part of the solar array becomes smaller, and the peak of the discharge current decreases. The research results can provide technical reference for electrostatic protection of spacecraft solar arrays. [ABSTRACT FROM AUTHOR]

A micro/nano surface structure can produce specific properties, such as super hydrophilicity, low reflectance property, etc. A femtosecond laser-induced periodic surface structure is an important manufacturing process for the micro/nano structure. This research investigated the effects of scanning intervals and laser power on the surface morphology, wetting properties, and reflectance properties of LIPSS based on a silicon wafer. The results showed that the laser power had a significant effect on the surface morphology and wettability of silicon. With the increase of laser power, the surface roughness, etching depth and surface hydrophilicity increased. However, the laser power had little effect on the surface reflectance. The scanning interval had a great influence on the wettability and reflectance property of silicon. With the decrease of the scanning interval, the surface hydrophobicity and reflectance of silicon first decrease and then remain basically stable from 10 μm. [ABSTRACT FROM AUTHOR]

Crime issues have been attracting widespread attention from citizens and managers of cities due to their unexpected and massive consequences. As an effective technique to prevent and control urban crimes, the data-driven spatial–temporal crime prediction can provide reasonable estimations associated with the crime hotspot. It thus contributes to the decision making of relevant departments under limited resources, as well as promotes civilized urban development. However, the deficient performance in the aspect of the daily spatial–temporal crime prediction at the urban-district-scale needs to be further resolved, which serves as a critical role in police resource allocation. In order to establish a practical and effective daily crime prediction framework at an urban police-district-scale, an "online" integrated graph model is proposed. A residual neural network (ResNet), graph convolutional network (GCN), and long short-term memory (LSTM) are integrated with an attention mechanism in the proposed model to extract and fuse the spatial–temporal features, topological graphs, and external features. Then, the "online" integrated graph model is validated by daily theft and assault data within 22 police districts in the city of Chicago, US from 1 January 2015 to 7 January 2020. Additionally, several widely used baseline models, including autoregressive integrated moving average (ARIMA), ridge regression, support vector regression (SVR), random forest, extreme gradient boosting (XGBoost), LSTM, convolutional neural network (CNN), and Conv-LSTM models, are compared with the proposed model from a quantitative point of view by using the same dataset. The results show that the predicted spatial–temporal patterns by the proposed model are close to the observations. Moreover, the integrated graph model performs more accurately since it has lower average values of the mean absolute error (MAE) and root mean square error (RMSE) than the other eight models. Therefore, the proposed model has great potential in supporting the decision making for the police in the fields of patrolling and investigation, as well as resource allocation. [ABSTRACT FROM AUTHOR]

Featured Application: With the increasing demand for customization, the engineer-to-order (ETO) production strategy plays an increasingly important role in today's manufacturing industry. The most important phase of ETO production is assembly. Project scheduling and workforce allocation have an impact on the efficiency and cost of the assembly of ETO products and the two problems are interrelated. To the best of our knowledge, this is the only work about project scheduling and workforce allocation in the ETO assembly process. The method proposed in this work can improve the efficiency of the ETO assembly system and has been successfully applied at the Shanghai Electric Power Plant Equipment Company, which is a joint venture between Shanghai Electric Company and Siemens. The engineer-to-order (ETO) production strategy plays an important role in today's manufacturing industry. This paper studies integrated multi-project scheduling and hierarchical workforce allocation in the assembly process of ETO products. The multi-project scheduling problem involves the scheduling of tasks of different projects under many constraints, and the workforce allocation problem involves assigning hierarchical workers to each task. These two problems are interrelated. The task duration depends on the number of hierarchical workers assigned to the task. We developed a mathematical model to represent the problem. In order to solve this issue with the minimization of the makespan as the objective, we propose a hybrid algorithm combining particle swarm optimization (PSO) and Tabu search (TS). The improved PSO is designed as the global search process and the Tabu search is introduced to improve the local searching ability. The proposed algorithm is tested on different scales of benchmark instances and a case that uses industrial data from a collaborating steam turbine company. The results show that the solution quality of the hybrid algorithm outperforms the other three algorithms proposed in the literature and the experienced project manager. [ABSTRACT FROM AUTHOR]

The extracellular polysaccharide (EPS) matrix embedding microbial cells and soil particles plays an important role in the development of biological soil crusts (BSCs), which is widely recognized as beneficial to soil fertility in dryland worldwide. This study examined the EPS-producing bacterial strains YL24-1 and YL24-3 isolated from sandy soil in the Mu Us Desert in Yulin, Shaanxi province, China. The strains YL24-1 and YL24-3 were able to efficiently produce EPS; the levels of EPS were determined to be 257.22 μg/mL and 83.41 μg/mL in cultures grown for 72 h and were identified as Sinorhizobium meliloti and Pedobacter sp., respectively. When the strain YL24-3 was compared to Pedobacter yulinensis YL28-9T using 16S rRNA gene sequencing, the resemblance was 98.6% and the strain was classified as Pedobacter sp. using physiological and biochemical analysis. Furthermore, strain YL24-3 was also identified as a subspecies of Pedobacter yulinensis YL28-9T on the basis of DNA–DNA hybridization and polar lipid analysis compared with YL28-9T. On the basis of the EPS-related genes of relevant strains in the GenBank, several EPS-related genes were cloned and sequenced in the strain YL24-1, including those potentially involved in EPS synthesis, assembly, transport, and secretion. Given the differences of the strains in EPS production, it is possible that the differences in gene sequences result in variations in the enzyme/protein activities for EPS biosynthesis, assembly, transport, and secretion. The results provide preliminary evidence of various contributions of bacterial strains to the formation of EPS matrix in the Mu Us Desert. [ABSTRACT FROM AUTHOR]

PM2.5 was sampled from January 2017 to May 2018 at an urban, suburban, industrial, and rural sites in Xining. The annual mean of PM2.5 was highest at the urban site and lowest at the rural site, with an average of 51.5 ± 48.9 and 26.4 ± 17.8 μg·m−3, respectively. The average PM2.5 concentration of the industrial and suburban sites was 42.8 ± 27.4 and 37.2 ± 23.7 μg·m−3, respectively. All sites except for the rural had concentrations above the ambient air quality standards of China (GB3095-2012). The highest concentration of PM2.5 at all sites was observed in winter, followed by spring, autumn, and summer. The concentration of major constituents showed statistically significant seasonal and spatial variation. The highest concentrations of organic carbon (OC), elemental carbon (EC), water-soluble organic carbon (WSOC), and water-soluble inorganic ions (WSIIs) were found at the urban site in winter. The average concentration of F− was higher than that in many studies, especially at the industrial site where the annual average concentration of F− was 1.5 ± 1.7 μg·m−3. The range of sulfur oxidation ratio (SOR) was 0.1–0.18 and nitrogen oxidation ratio (NOR) was 0.02–0.1 in Xining. The higher SO42−/NO3− indicates that coal combustion has greater impact than vehicle emissions. The results of the potential source contribution function (PSCF) suggest that air mass from middle- and large-scale transport from the western areas of Xining have contributed to the higher level of PM2.5. On the basis of the positive matrix factorization (PMF) model, it was found that aerosols from salt lakes and dust were the main sources of PM2.5 in Xining, accounting for 26.3% of aerosol total mass. During the sandstorms, the concentration of PM2.5 increased sharply, and the concentrations of Na+, Ca2+ and Mg2+ were 1.13–2.70, 1.68–4.41, and 1.15–5.12 times higher, respectively, than annual average concentration, implying that aerosols were mainly from dust and the largest saltwater lake, Qinghai Lake, and many other salt lakes in the province of Qinghai. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) was utilized to study the surface components of PM2.5 and F− was found to be increasingly distributed from the surface to inside the particles. We determined that the extremely high PM2.5 concentration appears to be due to an episode of heavy pollution resulting from the combination of sandstorms and the burning of fireworks. [ABSTRACT FROM AUTHOR]

Sensitive and point-of-care detection of small toxic molecules plays a key role in food safety. Aflatoxin, a typical small toxic molecule, can cause serious healthcare and economic issues, thereby promoting the development of sensitive and point-of-care detection. Although ELISA is one of the official detection methods, it cannot fill the gap between sensitivity and point-of-care application because it requires a large-scale microplate reader. To employ portable readers in food safety, Pt-catalysis has attracted increasing attention due to its portability and reliability. In this study, we developed a sensitive point-of-care aflatoxin detection (POCAD) method via a portable handheld barometer. We synthesized and characterized Au@PtNPs and Au@PtNPs conjugated with a second antibody (Au@PtNPs-IgG). A competitive immunoassay was established based on the homemade monoclonal antibody against aflatoxins. Au@PtNPs-IgG was used to catalyze the production of O2 from H2O2 in a sealed vessel. The pressure of O2 was then recorded by a handheld barometer. The aflatoxin concentration was inversely proportional to the pressure recorded via the barometer reading. After optimization, a limit of detection of 0.03 ng/mL and a linear range from 0.09 to 16.0 ng/mL were achieved. Recovery was recorded as 83.1%–112.0% along with satisfactory results regarding inner- and inter-assay precision (relative standard deviation, RSD < 6.4%). Little cross-reaction was observed. Additionally, the POCAD was validated by high-performance liquid chromatography (HPLC) by using peanut and corn samples. The portable POCAD exhibits strong potential for applications in the on-site detection of small toxic molecules to ensure food safety. [ABSTRACT FROM AUTHOR]

Many chemical plant explosion accidents occur along with the development of the chemical industry. Meanwhile, the interaction and influence of various factors significantly increase the uncertainty of the evolution process of such accidents. This paper presents a framework to dynamically evaluate chemical plant explosion accidents. We propose twelve nodes to represent accident evolution and establish a Bayesian network model for chemical plant explosion accidents, combining historical data with expert experience to support the prevention, management, and real-time warning. Hypothetical scenarios and catastrophic explosion scenarios were analyzed by setting different combinations of states for nodes. Moreover, the impacts of factors such as factory type, material form, accident equipment, the emergency response on casualty and property loss are evaluated. We find that sensitivity of property loss and casualties to factory type and ongoing work are less significant; the equipment factors result in more casualties than that from personnel factors; the impact of emergency response on the accident results is significant; equipment safety management and personnel safety training are the most important measures to prevent chemical plant explosion risks. [ABSTRACT FROM AUTHOR]

Urban dirty bomb attacking is a type of unconventional terrorism threatening the urban security all through the world. In this paper, a Bayesian network of urban dirty bomb attacking is established to analyze the risk of urban dirty bomb attacking. The impacts of factors such as occurrence time, location, wind fields, the size of dirty bomb, emergency response and defense approaches on casualty from both direct blast and radiation-caused cancers are examined. Results show that sensitivity of casualty from cancers to wind fields are less significant; the impact of emergency response on the direct casualty from blast is not large; the size of the dirty bomb results in more casualties from cancers than that from bomb explosions; Whether an attack is detected by the police is not that related to normal or special time, but significantly depends on the attack location; Furthermore, casualty from cancers significantly depends on the location, while casualty from blast is not considerably influenced by the attacking location; patrol and surveillance are less important than security check in terms of controlling the risk of urban dirt bomb, and security check is the most effective approach to decreasing the risk of urban dirty bomb. [ABSTRACT FROM AUTHOR]

Based on polyimide (PI), epoxy resin (EP), polytetrafluoroethylene (PTFE) typical dielectric materials used in spacecraft, a research platform for charge-discharge experiment under strong field was established. The influence of irradiation field strength, beam energy, dielectric thickness, etc., on electrostatic discharge characters of dielectric materials were studied and summarized. The results show that with the increase of field strength, the frequency of induced electrostatic discharge increases, the accumulated charge on the dielectric surface decreases, and the dielectric surface potential decreases; Under the same conditions, PI has the lowest discharge frequency and the highest surface dynamic balance potential. The thicker the dielectric material, the lower the discharge frequency, the higher the surface dynamic equilibrium potential; The shape and size of the background electrodes also affect the discharge frequency. When the area is the same, the sharper the electrode edge, the higher the discharge frequency. When the shape is the same, the larger the grounding area, the higher the discharge frequency. By proposing the induced discharge test method, the function mechanism of spatial environmental factors on the electrostatic discharge of typical dielectric materials are obtained. Comparative analysis on electrostatic properties of different dielectric materials can provide data reference and technical support for spacecraft electrostatic safety and protection.

This study established an immunoaffinity column for selective extraction of aflatoxins in agri-products. Specifically, the immunoaffinity column was developed by covalently coupling monoclonal antibody 1C11 against aflatoxins to amino-silica gel microparticles and then packing these into a cartridge. The extraction conditions were thoroughly optimized in terms of loading, washing and eluting solutions. Under the optimal conditions, the immunoaffinity column had a capacity of 200 ng of aflatoxins. The detection limits (S/N = 3) for aflatoxin G₁, B₁, G₂ and B₂ were 0.03, 0.07, 0.05 and 0.09 μg·kg⁻¹, and the corresponding quantification limits (S/N = 10) were 0.10, 0.25, 0.18 and 0.30 μg·kg⁻¹, respectively. The recoveries of aflatoxins in samples were 90.1%-104.4% and RSDs were <4.4%. The developed method was further applied to the determination of aflatoxins in peanut, vegetable oil and tea samples, and the results indicated that peanut (26.9%), vegetable oils (28.0%) and tea (5.3%) samples were contaminated with aflatoxins, with levels ranging from 0.49 to 20.79 μg·kg⁻¹.

In our previous study, we found that acute anterior uveitis (AAU) could be induced in wild-type mice (C3H/HeN), but it could not be induced in TLR4 gene-deficient mice (C3H/HeJ), we concluded that the translocation of transcription factor nuclear factor-κB (NF-κB) may play an important role. In this study, we examined the concentration of different cytokines in the aqueous humor of C3H/HeN mice and C3H/HeJ mice with the aim of exploring the role of different cytokines in the lipopolysaccharide (LPS) and TLR4-mediated signal transduction in the development of AAU.

Chemical contaminants in food have caused serious health issues in both humans and animals. Microarray technology is an advanced technique suitable for the analysis of chemical contaminates. In particular, immuno-microarray approach is one of the most promising methods for chemical contaminants analysis. The use of microarrays for the analysis of chemical contaminants is the subject of this review. Fabrication strategies and detection methods for chemical contaminants are discussed in detail. Application to the analysis of mycotoxins, biotoxins, pesticide residues, and pharmaceutical residues is also described. Finally, future challenges and opportunities are discussed.