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AbstractEpimedium is a Chinese herb known as “yin and yang fire,” first mentioned in the Compendium of Materia Medica. Many of the proprietary Chinese medicines used in clinical practice contain Epimedium as an ingredient, and its main active constituents include icariin, icaritin, and icariside II, among others. In addition to its traditional use in treating fatigue and sexual problems, modern research has confirmed that the main bioactive compounds in Epimedium have pharmacological effects such as antidepressant, antibacterial, antiviral, antioxidant, and anti-inflammatory properties, as well as inhibiting bone destruction, promoting bone growth, improving immune regulation and protecting the cardio-cerebral vascular system. With the continuous development of extraction and purification techniques, the development and use of bioactive compounds in Epimedium have significantly progressed, and the anticancer effect has received widespread attention. Since natural herbs have few side effects on the human body and do not easily develop drug resistance, they have long been the direction of research in cancer treatment. This review summarizes the latest research on the anticancer effects of Epimedium and its extracts, describes the bioactive compounds, pharmacological efficacy, and antitumor mechanism of Epimedium, and gives a new view on the administration and development of Epimedium. [ABSTRACT FROM AUTHOR]

The Chinese alligator (Alligator sinensis) is currently an endangered species due to a combination of factors, including climate change, anthropogenic activities, and habitat fragmentation. Captivity plays a crucial role in mitigating the decline of the Chinese alligator population. Currently, there is a lack of clarity regarding the influence of host development and captive conditions on the gut microbiota of Chinese alligators. The aim of the study was to investigate the gut bacterial communities of Chinese alligators and their surrounding environmental bacterial communities using 16S rRNA sequencing. The primary gut flora of Chinese alligators consists of Proteobacteria, Bacteroidetes, and Firmicutes. Proteobacteria is the most abundant and efficient settler in the gut, water, and sediment. PCoA and Adonis test revealed significant differences in bacterial communities across these habitats. Venn analysis revealed overlap in OTUs among the gut, water, and sediment, varying with growth stage and density stress. Different growth stages of Chinese alligator guts harbor distinct pathogenic bacteria, requiring attention. Density stress leads to an increase in pathogenic bacteria, a decrease in gut absorption efficiency. PICRUst2 predicts more abundant metabolic pathways related to gut function during high‐density stress, possibly linked to Roseburia. SourceTracker Analysis indicated that water bacteria have a greater impact on Chinese alligator gut bacteria than sediment, and density stress significantly affects the contribution of environmental microorganisms to the gut microbes of Chinese alligator. BugBase analysis identified water body microbes as the main source of "potentially pathogenic" phenotypes in the gut microbiota. RDA analysis found dissolved oxygen (DO) in water to be the most significant factor influencing water microorganisms, positively correlated with certain pathogenic strains. These findings enhance our understanding of the significance of microbial communities in the gut and surrounding aquatic environment of the Chinese alligator. Furthermore, they provide theoretical support for environmental regulation, disease control, and healthy breeding. [ABSTRACT FROM AUTHOR]

We propose the regularized linear programming discriminant (LPD) rule with folded concave penalty in the ultrahigh-dimensional regime. We use the local linear approximation (LLA) algorithm to redirect the model with folded concave penalty to a weighted ℓ1 model. The strong oracle property of the solution constructed by the one-step local linear approximation (LLA) algorithm is verified. In addition, we propose efficient and parallelizable algorithms based on feature space split to address the computational challenges due to ultrahigh dimensionality. The proposed feature-split algorithm is compared to existing methods by both numerical simulations and applications to real data examples. The numerical comparisons suggest that the proposed method works well for ultrahigh dimensions, while the linear programming solver and alternating direction method of multiplier (ADMM) algorithm may fail for such high dimensions. for this article are available online. [ABSTRACT FROM AUTHOR]

Aldo-keto reductase family 1 member C3 (AKR1C3) plays an important role in prostate cancer (PCa) progression, particularly in castration-resistant prostate cancer (CRPC). It is necessary to establish a genetic signature associated with AKR1C3 that can be used to predict the prognosis of PCa patients and provide important information for clinical treatment decisions. AKR1C3-related genes were identified via label-free quantitative proteomics of the AKR1C3-overexpressing LNCaP cell line. A risk model was constructed through the analysis of clinical data, PPI, and Cox-selected risk genes. Cox regression analysis, Kaplan–Meier (K–M) curves, and receiver operating characteristic (ROC) curves were used to verify the accuracy of the model, and two external datasets were used to verify the reliability of the results. Subsequently, the tumor microenvironment and drug sensitivity were explored. Moreover, the roles of AKR1C3 in the progression of PCa were verified in LNCaP cells. MTT, colony formation, and EdU assays were conducted to explore cell proliferation and drug sensitivity to enzalutamide. Migration and invasion abilities were measured using wound-healing and transwell assays, and qPCR was used to assess the expression levels of AR target genes and EMT genes. CDC20, SRSF3, UQCRH, INCENP, TIMM10, TIMM13, POLR2L, and NDUFAB1 were identified as AKR1C3-associated risk genes. These risk genes, established using the prognostic model, can effectively predict the recurrence status, immune microenvironment, and drug sensitivity of PCa. Tumor-infiltrating lymphocytes and several immune checkpoints that promote cancer progression were higher in high-risk groups. Furthermore, there was a close correlation between the sensitivity of PCa patients to bicalutamide and docetaxel and the expression levels of the eight risk genes. Moreover, through in vitro experiments, Western blotting confirmed that AKR1C3 enhanced SRSF3, CDC20, and INCENP expression. We found that PCa cells with a high expression of AKR1C3 have high proliferation ability and high migration ability and were insensitive to enzalutamide. AKR1C3-associated genes had a significant role in the process of PCa, immune responses, and drug sensitivity and offer the potential for a novel model for prognostic prediction in PCa. [ABSTRACT FROM AUTHOR]

The Population-based HIV Impact Assessment (PHIA) is an ongoing project that conducts nationally representative HIV-focused surveys for measuring national and regional progress toward UNAIDS' 90-90-90 targets, the primary strategy to end the HIV epidemic. We believe the PHIA survey offers a unique opportunity to better understand the key factors that drive the HIV epidemics in the most affected countries in sub-Saharan Africa. In this article, we propose a novel causal structural learning algorithm to discover important covariates and potential causal pathways for 90-90-90 targets. Existing constraint-based causal structural learning algorithms are quite aggressive in edge removal. The proposed algorithm preserves more information about important features and potential causal pathways. It is applied to the Malawi PHIA (MPHIA) dataset and leads to interesting results. For example, it discovers age and condom usage to be important for female HIV awareness; the number of sexual partners to be important for male HIV awareness; and knowing the travel time to HIV care facilities leads to a higher chance of being treated for both females and males. We further compare and validate the proposed algorithm using BIC and using Monte Carlo simulations, and show that the proposed algorithm achieves improvement in true positive rates in important feature discovery over existing algorithms. for this article are available online. [ABSTRACT FROM AUTHOR]

In this article, we propose a new projection test for linear hypotheses on regression coefficient matrices in linear models with high-dimensional responses. We systematically study the theoretical properties of the proposed test. We first derive the optimal projection matrix for any given projection dimension to achieve the best power and provide an upper bound for the optimal dimension of projection matrix. We further provide insights into how to construct the optimal projection matrix. One- and two-sample mean problems can be formulated as special cases of linear hypotheses studied in this article. We both theoretically and empirically demonstrate that the proposed test can outperform the existing ones for one- and two-sample mean problems. We conduct Monte Carlo simulation to examine the finite sample performance and illustrate the proposed test by a real data example. [ABSTRACT FROM AUTHOR]

• The problem of potential changes in propagation paths generated by different prevention strategies is addressed. • A multi-stage coordination model is proposed for reducing cascading failure impacts. • A double-layer optimization framework is proposed for solving the multi-stage coordination dispatch model. Blackout events caused by cascading failures have induced enormous losses in power systems. Good defense strategies are helpful for stopping cascading failures spread, which not only reduces system losses, but also improves the system's ability to cope with the cascading failures. However, the current studies mostly focus on single-stage defense strategy and lack coordination of preventive, emergency and restoration dispatch (CPERD) against cascading failures. This paper proposes a CPERD methodology to counteract cascading failures for resilience enhancement. We first analyze the propagation mechanism and the prediction method for the propagation paths of cascading failures. Second, we explore the necessity and feasibility of whole-process coordinated dispatch under cascading failures and design a CPERD model framework. Based on this framework, we further analyze the impact of whole-process coordinated dispatch on the propagation path of cascading failures. Third, preventive dispatch, emergency dispatch and restoration dispatch sub-models are separately modeled to minimize the dispatch cost. Since the model has the characteristics of multi-stage and multi-objective, a double-layer optimization framework and an improved particle swarm optimization algorithm are introduced to solve the CPERD problem. Finally, the IEEE 39-bus and IEEE 118-bus test systems are taken as examples for simulation analysis. The results show that whole-process coordinated dispatch can effectively reduce the final load loss and overall dispatch cost, and enhance power system resilience against cascading failures. [ABSTRACT FROM AUTHOR]

Most traditional methods have difficulty detecting landslide boundary accurately, and the existing methods based on deep learning often lead to insufficient training or overfitting due to insufficient samples. An end-to-end, semi-supervised adversarial network, which fully considers spectral and topographic features derived using unmanned aerial vehicle (UAV) photogrammetry, is proposed to extract landslides by semantic segmentation to address the abovementioned problem. In the generative network, a generator similar to pix2pix is introduced into the proposed adversarial nets to learn semantic features from UAV-photogrammetry-derived data by semi-supervised operation and a confrontational strategy to reduce the requirement of the number of labeled samples. In the discriminative network, DeepLabv3+ is improved by inserting multilevel skip connection architecture with upsampling operation to obtain the contextual information and retain the boundary information of landslides at all levels, and a topographic convolutional neural network is proposed to be inserted into the encoder to concatenate topographic features together with spectral features. Then, transfer learning with the pre-trained parameters and weights, shared with pix2pix and DeepLabv3+, is used to perform landslide extraction training and validation. In our experiments, the UAV-photogrammetry-derived data of a typical landslide located at Meilong gully in China are collected to test the proposed method. The experimental results show that our method can accurately detect the area of a landslide and achieve satisfactiory results based on several indicators including the Precision, Recall, F1 score, and mIoU, which are 13.07%, 15.65%, 16.96%, and 18.23% higher than those of the DeepLabV3+. Compared with state-of-the-art methods such as U-Net, PSPNet, and pix2pix, the proposed adversarial nets considering multidimensional information such as topographic factors can perform better and significantly improve the accuracy of landslide extraction. [ABSTRACT FROM AUTHOR]

Parallel restoration following blackouts can reduce economic and social losses. This paper aims to develop a parallel restoration method coordinating the partitioning scheme of the blackout system and restoration strategies of subsystems. The susceptible-infected-recovered model, i.e., a virus propagation model of complex networks, is used to decide the parallel restoration strategies online. Firstly, various types of viruses are used to represent different subsystems. The probability vector of virus infection is obtained according to the importance level of each bus. Secondly, an immunization strategy is developed based on the faulted buses in the blackout situation. According to the infection rate and the immunization strategy, the virus propagation direction will be changed based on real-time system conditions. The startup characteristics of units and the charging reactive power of restoration paths are considered as constraints to embed in the virus propagation process. Finally, the partitioning scheme and the restorative actions for subsystems are determined based on the infected results of viruses. The effectiveness of the proposed method is validated by case studies on the IEEE 39-bus and the IEEE 118-bus test systems. [ABSTRACT FROM AUTHOR]

• Proposes a multi-stage determination method for excavator working points that considers engine fuel consumption, hydraulic pump efficiency, and load fluctuation, overcoming limitations of traditional methods. • Introduces a comprehensive evaluation model for working point determination that integrates fuel consumption, hydraulic pump efficiency, and load variability, offering a more holistic approach. • Utilizes experimental data to inform the determination of engine working points, ensuring practical relevance and applicability. • Employs weight parameters to adjust the importance of fuel consumption and load fluctuation in the working point optimization process, allowing for tailored engine performance improvement under varying operational needs. In view of the problem that the traditional working point determination method only considers the engine fuel consumption and does not consider the hydraulic pump efficiency and load fluctuation in the process of the working point stability control of an excavator engine, a simple and feasible, experimental data-driven, multi-stage determination method of excavator working point based on the comprehensive evaluation model is proposed. In this paper, the comprehensive evaluation model of working point torque with weight parameters is established at different working stages under the rated speed in a phased way. The results show that this method can determine the working point torque at different working stages, and reduce engine fuel consumption and load fluctuation based on ensuring the efficiency of the hydraulic pump. The lowest engine fuel consumption can be reduced by 7.09%, and the lowest load fluctuation can be reduced by 17.8%. In addition, by modifying the weight parameters, we can emphasize the fuel consumption and load fluctuation of the engine according to their importance, to achieve the determination of working points under different requirements. This approach also provides a new idea for optimizing the working point of construction machinery. [ABSTRACT FROM AUTHOR]

In the research on energy-efficient networking methods for precision agriculture, a hot topic is the energy issue of sensing nodes for individual wireless sensor networks. The sensing nodes of the wireless sensor network should be enabled to provide better services with limited energy to support wide-range and multi-scenario acquisition and transmission of three-dimensional crop information. Further, the life cycle of the sensing nodes should be maximized under limited energy. The transmission direction and node power consumption are considered, and the forward and high-energy nodes are selected as the preferred cluster heads or data-forwarding nodes. Taking the cropland cultivation of ginseng as the background, we put forward a particle swarm optimization-based networking algorithm for wireless sensor networks with excellent performance. This algorithm can be used for precision agriculture and achieve optimal equipment configuration in a network under limited energy, while ensuring reliable communication in the network. The node scale is configured as 50 to 300 nodes in the range of 500 × 500 m2, and simulated testing is conducted with the LEACH, BCDCP, and ECHERP routing protocols. Compared with the existing LEACH, BCDCP, and ECHERP routing protocols, the proposed networking method can achieve the network lifetime prolongation and mitigate the decreased degree and decreasing trend of the distance between the sensing nodes and center nodes of the sensor network, which results in a longer network life cycle and stronger environment suitability. It is an effective method that improves the sensing node lifetime for a wireless sensor network applied to cropland cultivation of ginseng. [ABSTRACT FROM AUTHOR]

In 3D frequency domain seismic forward and inversion calculation, the huge amount of calculation and storage is one of the main factors that restrict the processing speed and calculation efficiency. The frequency domain finite-difference forward simulation algorithm based on the acoustic wave equation establishes a large bandwidth complex matrix according to the discretized acoustic wave equation, and then the frequency domain wave field value is obtained by solving the matrix equation. In this study, the predecessor's optimized five-point method is extended to a 3D seven-point finite-difference scheme, and then a perfectly matched layer absorbing boundary condition (PML) is added to establish the corresponding matrix equation. In order to solve the complex matrix, we transform it to the equivalent real number domain to expand the solvable range of the matrix, and establish two objective functions to transform the matrix solving problem into an optimization problem that can be solved using gradient methods, and then use conjugate gradient algorithm to solve the problem. Previous studies have shown that in the conjugate gradient algorithm, the product of the matrix and the vector is the main factor that affects the calculation efficiency. Therefore, this study proposes a method that transform bandwidth matrix and vector product problem into some equivalent vector and vector product algorithm, thereby reducing the amount of calculation and storage. [ABSTRACT FROM AUTHOR]

An energy-saving control strategy for wheel loaders is proposed in this paper to address the issue of high energy consumption during their operation. The strategy is based on the intelligent identification of working stages, allowing for staged power matching and resulting in reduced energy consumption. Each work stage of the loader is identified by matching it to the main pump pressure waveform and actuator pilot pressure waveform. Using a sliding time window method, pressure waveforms from each working stage are subjected to feature extraction. A bidirectional long short-term memory neural network (BILSTM) algorithm is then used to establish an intelligent recognition model. Based on work stage identification, an energy-saving control strategy based on power matching is proposed for the shoveling stage of the loader, and the Grey Wolf optimization (GWO)-PID algorithm is utilized for control parameter tuning. Finally, the effectiveness of the energy-saving control strategy based on work stage identification is verified through experiments. The research results indicate that the BILSTM recognition model outperforms other models with a recognition accuracy of 96.1%. The optimal time window width is 0.6 s, and the proposed energy-saving control strategy achieves a fuel-saving rate of 6.81%. This method provides feasibility for reducing energy consumption in construction machinery and achieving energy-saving and carbon-reduction goals. [ABSTRACT FROM AUTHOR]

• The generator startup process is modeled as the Markov Decision Process. • The Q-learning is applied in the planning of generator startup after blackout. • A new restoration strategy is proposed for the generator startup process. • The Upper Confidence Bound is used to optimize the selection of action of agent. With the expansion of the power system and the impact of natural disasters, blackouts are almost inevitable. A scientific restoration plan can effectively shorten the economic and social losses caused by blackouts. As the first step of power system restoration, the generator start-up process impacts the success rate and time consumption. Considering the diversity of constraints in the generator start-up process and the complexity of the topology, this paper proposes a planning method for the generator start-up process based on reinforcement learning. Q-learning is a model-free reinforcement learning algorithm that can cope well with complex environments and diverse constraints. First, the generator start-up problem is modeled as a Markov Decision Process, and the restoration operation and constraints are considered. Q-learning uses an artificial intelligence agent to plan the generator start-up process and guide operators. Second, different from the restoration methods of sequential restarting the generators, this paper presents a novel strategy for restoration by restoring the path of the subsequent generator while the current generator acquires cranking power. Then, the action selection mechanism is optimized by using the Upper Confidence Bound algorithm to address the shortcoming of low exploration effectiveness in the conventional Q-learning. Finally, the simulation results provide evidence of the excellent performance of the proposed method in terms of optimality and convergence. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the effect of ε‐polylysine hydrochloride (ε‐PLH) on the growth and thermal inactivation kinetics of Listeria monocytogenes in fish balls. Samples, supplemented with ε‐PLH (0, 150, or 300 ppm, w/w), were inoculated with a three‐strain cocktail of L. monocytogenes and incubated at constant temperatures of 3.4, 8, 12, or 16 °C for growth studies, or heated at 60, 62.5, 65, or 67.5 °C for thermal inactivation tests. The growth curves were fitted to the Huang primary model, and the Huang and Ratkowsky square‐root models (SRM) were used as the secondary models to evaluate the effect of temperature on bacterial growth. The survival during heating was analyzed with a log‐linear model. The results showed that, while the lag time of L. monocytogenes was affected by both ε‐PLH concentration and temperature, the specific growth rate was unaffected by ε‐PLH. Under the same temperature, a 10‐time in increase of the lag time would be expected for every 565 ppm in the increase of ε‐PLH concentration. Using the Ratkowsky SRM, the estimated nominal minimum growth temperature was –2.04 °C, while the minimum growth temperature was 0.29 °C when estimated with the Huang SRM. Validation at 10 °C showed that the Huang primary model, in combination with either the Huang or Ratkowsky SRM, could accurately predict the growth of L. monocytogenes. On the other hand, the thermal resistance of the pathogen was significantly reduced by increase in temperature or ε‐PLH. The thermal z value of L. monocytogenes was 5.78 °C, and the ε‐PLH z value was 1642 ppm. The results of this study showed that the combined application of ε‐PLH and temperature can be used to control L. monocytogenes in fish balls and to improve food safety and reduce risks to public health. [ABSTRACT FROM AUTHOR]

Clostridium perfringens is a major foodborne health hazard that can cause acute gastroenteritis in consumers, and is often associated with cooked meat and poultry products. Improper cooling after cooking may allow this pathogen to grow in a product, producing an enterotoxin that causes food poisoning. This study was conducted to evaluate the effect of common ingredients, including sodium tripolyphosphate (STPP), sodium lactate (NaL), and sodium chloride (NaCl), on the germination and outgrowth of C. perfringens spores in meat products. The growth/no growth test was conducted in Shahidi Ferguson Perfringens agar mixed with STPP (0–2500 ppm), NaL (0–4%), and NaCl (0–4%) in microplates. Turbidity measurements at 600 nm were compared before and after anaerobic incubation at 46 °C to evaluate growth and no growth conditions. The dichotomous responses were analyzed by logistic regression to develop a model for estimating the growth probability of C. perfringens . The probability model was used to define the threshold of growth (probability > 0.1 or 0.2) of C. perfringens and validated using inoculated ground beef under optimum temperature. Inoculated ground beef was mixed with different combinations of STPP, NaL, and NaCl to observe growth or no growth of C. perfringens , and the probability was calculated from the formulation. If the threshold of growth was set to 0.2, the accuracy of the growth and no growth predictions was 95.7%, with 4.3% over-prediction of growth events (fail-safe). The results from this study suggested that proper combinations of STPP, NaL, and NaCl could be used to control the growth of C. perfringens in cooked beef under the optimum temperature. The results may also suggest that proper combinations of STPP, NaL, and NaCl in cooked meat and poultry products could be used to prevent the growth of C. perfringens during cooling. [ABSTRACT FROM AUTHOR]

Thermal properties are necessary for the design and control of processes and storage facilities of food materials. This study proposes the measurement of thermal properties using easily constructed probes with specific heat capacity calculated, as opposed to the use of Differential Scanning Calorimeter (DSC) or other. These probes were constructed and used to measure thermal properties of white radish in the temperature range of 80–20°C and moisture content of 91–6.1% wb. Results showed thermal properties were within the range of 0.71–0.111 Wm-1 C-1 for thermal conductivity, 1.869×10−7–0.72×10−8 m2s-1 for thermal diffusivity and 4.316–1.977 kJ kg-1C-1for specific heat capacity. These results agree with reports for similar products studied using DSC and commercially available line heat source probes. Empirical models were developed for each property through linear multiple regressions. The data generated would be useful in modeling and control of its processing and equipment design. [ABSTRACT FROM AUTHOR]

Listeria monocytogenes is a potentially fatal foodborne pathogen that can be found in ready-to-eat seafood products, such as fresh salmon roe. Once contaminated, salmon roe must be decontaminated prior to human consumption. This study was conducted to determine the thermal inactivation kinetics of L. monocytogenes in raw salmon roe as affected by bacterial strain, temperature, and salt concentration. Three different strains of L. monocytogenes , including serotype 4b (F2365), 1/2b (F4260), and 1/2a (V7), were individually inoculated to salmon roe supplemented with salt (0–4.5%), and heated under different temperatures (57.5–65.0 °C) to evaluate the survival of the bacterium during heating and determine the D-values. Results showed that the thermal resistance (log D) of L. monocytogenes was significantly affected by bacterial strain, temperature, and salt and by their interactive effects, with strain F2365 being the most heat-resistant among all three strains tested. Salt added to salmon roe significantly increased the thermal resistance of the bacteria. For L. monocytogenes F2365, the z value of the bacterium in salmon roe was 5.99 °C, and its heat resistance increased with the level of salt in a linear manner. The results of kinetic analysis and the models obtained in this study may be used by the seafood industry to develop proper thermal processes to eliminate L. monocytogenes in raw salmon roe and to ensure microbial safety and prevent foodborne illness. [ABSTRACT FROM AUTHOR]

• Calcium silicate-based nanofibers are synthesized through seed-mediated hydrothermal method. • The structure of unstable nanofiber is Na 2 Ca 3 Si 2 O 8. • Nanofibers with defects have strong interactions with Ca2+ ions. • The flexural strength of mortar can be enhanced by adding the nanofibers. Despite many studies of nanomaterials have been reported on the enhancement of cement-based materials, such as the pozzolanic effect of nano silica and flexural enhancement of fibers, there rarely are reports of the nanomaterials with both pozzolanic effect and shape-based enhancement. In this paper, anisotropic nanofibers were synthesized based on calcium silicates through hydrothermal method. Seed-mediated growth was conducted while SiO 2 nanoparticles served as the seeds and pseudo-wollastonite was used as the precursor. Importantly, the addition of the nanofibers can greatly improve the 28d flexural strength from 7.12 MPa to 8.99 MPa of the cement-based materials, which provides a new approach to realize the high performance of cement-based materials. [ABSTRACT FROM AUTHOR]

The objective of this study was to investigate the growth kinetics of Listeria monocytogenes in unsalted and salted (3%) salmon roe. Growth curves, developed using inoculated samples incubated at constant temperatures between 5 and 30 °C, were analyzed by curve-fitting to the Huang and Baranyi models using the USDA IPMP 2013. The experimental results showed that L. monocytogenes in salted samples exhibited approximately 40% longer lag times than the cells in unsalted samples under the same temperature condition, while the rates of bacterial growth were not affected by the addition of salt. The Ratkowsky square-root (RSR) model, Huang square-root (HSR) model, and an Arrhenius-type model were all shown suitable for evaluating the effect of temperature on specific growth rates. The estimated nominal minimum growth temperature in the RSR model was −0.5 °C, whereas the minimum growth temperature in HSR model was 2.57 °C. The HSR models may be more suitable for describing the temperature effect in salted salmon roe. The lag times of L. monocytogenes were found to change log-linearly with the specific growth rates. The mean h 0 in the Baranyi model was 0.742 in unsalted samples and 1.193 in salted samples, and did not appear to change with temperature in a systematic manner. In summary, kinetic models were developed for examining the effect of temperature on growth of L. monocytogenes in unsalted and salted salmon roe samples. The results may be used by the food industry and regulatory agencies to estimate the growth of L. monocytogenes in salmon roe, and to conduct risk assessments of this microorganism. [ABSTRACT FROM AUTHOR]

Abstract: Peanut butter has been implicated in multi-state outbreaks of salmonellosis in recent years. Studies have shown that Salmonella exhibited increased thermal resistance in peanut butter. However, little is known about the effect of product formulation on the kinetics of survival of Salmonella during thermal treatment. Therefore, the objective of this research was to compare the thermal resistance of Salmonella in four commercially available peanut butter and spread products, and evaluate the effect of product formulation on the survival of this pathogen during heating. Four peanut butter and spread samples, including Omega 3 (A), regular fat (B), reduced sugar (C), and reduced fat (D), inoculated with a 6-strain cocktail of Salmonella spp., were heated at 70, 75, 80, 85, and 90 °C. Experimental results showed that the highest thermal resistance of Salmonella was found in the samples with reduced fat, while the least in the samples with Omega 3 formulation. No significant difference in the bacterial thermal resistance was observed in the regular fat and reduced sugar formulations. The Weibull survival model was used to describe the survival curves. Results showed that the average exponent (shape factor) of the model ranged from 0.38 to 0.662, suggesting progressively decreased rate of inactivation during heating. The scale (rate) coefficients of the model increased linearly with temperature. The calculated minimum lethal temperature for Salmonella was 54.8, 59.8, 59.5, and 63.9 °C in samples A, B, C, and D, respectively. No tail effect was observed. The results of this study suggest that proper formulation of peanut butter and spread may enhance thermal inactivation of Salmonella. [Copyright &y& Elsevier]

Testing high-dimensional means has many applications in scientific research. For instance, it is of great interest to test whether there is a difference of gene expressions between control and treatment groups in genetic studies. This can be formulated as a two-sample mean testing problem. However, the Hotelling T 2 test statistic for the two-sample mean problem is no longer well defined due to singularity of the sample covariance matrix when the sample size is less than the dimension of data. Over the last two decades, the high-dimensional mean testing problem has received considerable attentions in the literature. This paper provides a selective overview of existing testing procedures in the literature. We focus on the motivation of the testing procedures, the insights into how to construct the test statistics and the connections, and comparisons of different methods. [ABSTRACT FROM AUTHOR]

A series of novel α,ω-bis(4-methylphenoxy) alkane functionalized cyclen ligands were synthesized by the nucleophilic substitution reaction of 1,4,7-tris( tert-butyloxycarbonyl)-1,4,7,10-tetraazacyclododecane and α,ω-bis(4-bromomethylphenoxy) alkanes. The corresponding dimeric Zn(II)-cyclen complexes were obtained by reaction of these ligands with Zn(ClO)·6HO. Ligands and complexes were characterized by FT-IR, H NMR, and elemental analysis. [ABSTRACT FROM AUTHOR]

Abstract: Estimating the kinematic vorticity numbers from rock fabrics presents many problems. In this paper we use numerical modeling to investigate the reliability of those widely-used vorticity analysis methods using rigid clasts. We use very simple flows (steady state, homogeneous, and having monoclinic symmetry) to represent plane-straining zones and transpressional zones and assume that the rotation of rigid clasts perfectly obeys the theory of . These are assumptions made in current vorticity analysis using rigid clasts. Even with these simple assumptions, our modeling shows that the current methods have intrinsic uncertainties so large that it is pointless to use the estimated vorticity numbers to constrain shear zone boundary conditions and kinematics. It is perfectly consistent with numerical modeling results if the currently reported vorticity numbers estimated from rigid clasts (in the range of 0.50–0.85) are all interpreted as being from natural shear zones with close-to-simple-shearing flows. The large uncertainties arise because the motion of rigid clasts is intrinsically a three dimensional problem. [Copyright &y& Elsevier]

Quasi-zero stiffness (QZS) metastructures with simple structures exhibit a high low-frequency vibration isolation performance, but the bearing capacity and working regions are limited due to the linear positive stiffness elements. In this study, a novel hyperbolic QZS metastructure coupled with nonlinear stiffness is designed by combining a pair of cosine-shaped beams and arc-shaped beams for low-frequency vibration isolation. Finite element models (FEM) and experimental analysis are utilized to examine the static characteristics of the metastructure, revealing a wide QZS region and significant load-bearing capacity. The metastructure can achieve effective vibration isolation properties through reasonably designing the unit cells. The influence of geometrical parameters on the QZS region is investigated to optimize and realize desirable QZS features. The dynamic equation and response of the vibration isolation system are determined using the harmonic balance method. Moreover, the corresponding displacement transmissibility is confirmed by numerical simulation. The results of the dynamic sweep frequency experiment further verify the validity of the theoretical analysis model. The hyperbolic QZS metastructure system possesses good vibration isolation performance due to the introduction and compensation of a nonlinear positive stiffness arc beam element. The proposed hyperbolic QZS metastructure provides a significant route for the stiffness compensation of metastructures. [Display omitted] • A novel hyperbolic quasi-zero stiffness metastructure is designed by combining cosine-shaped curved and arc-shaped beams. • The metastructure with QZS characteristics can enhance the structural load-bearing capacity and broden the QZS region. • The required positive, quasi-zero, and negative stiffness can be obtained by reasonably designing geometrical parameter. • The dynamic theoretical, numerical simulation, and experimentsal results verified the good vibration isolation performance. [ABSTRACT FROM AUTHOR]

Regulating the crystal morphology of low aspect ratio, short columnar α‐hemihydrate gypsum (α‐HH) is crucial due to its distinctive physical and chemical properties, which make it widely applicable. In this work, succinic acid, malic acid, and maleic acid were selected as the research objects, among which the number and spacing of carboxyl groups were the same, while the auxiliary functional groups were different. The adsorption energy, Mulliken charge population, electronic state density, and charge density difference of the three organic acids on the surfaces of α‐HH were calculated by well‐defined ab initio calculations. The results showed that the synergistic effect of ‐COOH groups is necessary for the effective crystallization of α‐HH. Organic acids interact with the Ca atoms on the crystal surface, as evidenced by their preferential adsorption on the top surface of α‐HH crystals (002). This interaction occurs through a double‐dentate chelation between the carboxyl oxygen atoms at both ends of the organic acid and the Ca atoms on the crystal surface, resulting in the formation of a six‐membered cyclic organic acid calcium complex. This complex hinders ion diffusion and the stacking of crystal surfaces, leading to a decrease in the growth rate along the c‐axis and promoting more extensive crystal development and larger crystal sizes. The work provides insight into the preparation of short prismatic α‐HH using organic acid crystallizing agents. [ABSTRACT FROM AUTHOR]

• We introduce fused folded concave penalized method to identify Parkinson's markers. • We construct markers from high-dimensional voxel level MRI data with small samples. • Proposed method identifies markers more accurately than other penalized approaches. • Proposed method had better classification accuracy/specificity/sensitivity. Brain MRI is a promising technique for Parkinson's disease (PD) biomarker development. Its analysis, however, is hindered by the high-dimensional nature of the data, particularly when the sample size is relatively small. This study introduces a folded concave penalized machine learning scheme with spatial coupling fused penalty (fused FCP) to build biomarkers for PD directly from whole-brain voxel-wise MRI data. The penalized maximum likelihood estimation problem of the model is solved by local linear approximation. The proposed approach is evaluated on synthetic and Parkinson's Progression Marker Initiative (PPMI) data. It achieves good AUC scores, accuracy in classification, and biomarker identification with a relatively small sample size, and the results are robust for different tuning parameter choices. On the PPMI data, the proposed method discovers over 80 % of large regions of interest (ROIs) identified by the voxel-wise method, as well as potential new ROIs. The fused FCP approach is compared with L1, fused-L1, and FCP method using three popular machine learning algorithms, logistic regression, support vector machine, and linear discriminant analysis, as well as the voxel-wise method, on both synthetic and PPMI datasets. The fused FCP method demonstrated better accuracy in separating PD from controls than L1 and fused-L1 methods, and similar performance when compared with FCP method. In addition, the fused FCP method showed better ROI identification. The fused FCP method can be an effective approach for MRI biomarker discovery in PD and other studies using high dimensionality data/low sample sizes. [ABSTRACT FROM AUTHOR]

• A MCTS-based method for online deciding the generator startup sequence is proposed. • A constraint about the robustness of restoration scheme is proposed. • The restoration scheme can be adjusted online according to the unexpected faults. Generator startup is a critical step for the power system restoration following blackouts. Most strategies for the startup sequence of generators are obtained by offline methods, which probably are ineffective in the real situation: some devices unexpectedly fail to be restarted. To deal with the uncertainties, this paper proposed a novel method for online decision-making of the startup sequence of generators. First, the framework of online decision making is presented. The principles of online decision-making of the generator startup sequence are analyzed. Second, an optimization model for determining the generator startup sequence is developed to maximize the generating capacity. Then, the Monte Carlo tree search algorithm (MCTS) is applied to online decide the generator to be restored in the next step according to the real-time situation. To make it more suitable for system restoration, MCTS is modified: the upper confidence bounds for trees, the default policy, backpropagation, and the final decision making are improved. The restoration paths related to the selected generator are obtained by a graphic theoretic algorithm. Except commonly used constraints on generator startup and the path restoration, this paper considers the hot start of generators to propose a constraint about the robustness of the restoration scheme. Finally, the feasible strategy with the maximum generating capacity is selected online for application. Case studies on the IEEE 39-bus test system and an actual power system in Hebei, China, demonstrated the effectiveness of this method. [ABSTRACT FROM AUTHOR]

The objective of this study was to determine the kinetic parameters and apply Markov Chain Monte Carlo (MCMC) simulation to predict the growth of Clostridium perfringens from spores in cooked ground chicken meat during dynamic cooling. Inoculated samples were exposed to various cooling conditions to observe dynamic growth. A combination of 4 cooling profiles was used in one-step inverse analysis with the Baranyi model as the primary model and the cardinal parameters model as the secondary model. Six kinetic parameters of the Baranyi model and the cardinal parameters model, including Q 0 , Y max , μ opt , T min , T opt , and T max , were estimated. The estimated T min , T opt , and T max were 14.8, 42.9, and 50.5 °C, respectively, with a μ opt of 5.25 h−1 and maximum cell density of 8.4 log CFU/g. Correlation analysis showed that both Q 0 and Y max are weakly correlated to other parameters, while the remaining parameters are mostly mildly to strongly correlated with each other. Although it may be difficult to estimate highly correlated parameters using a single temperature profile, one-step analysis with multiple different temperature profiles helped estimate them successfully. The estimated parameters were used as the prior information to construct the posterior distribution for Bayesian analysis. MCMC simulation was used to predict the bacterial growth using different dynamic temperature profiles for validation of the accuracy of the predictive models. The MCMC simulation results showed that the Bayesian analysis produced more accurate predictions of bacterial growth during cooling than the deterministic method. With Bayesian analysis, the root-mean-square-error (RMSE) of prediction was only 0.1 log CFU/g with all residual errors within ±0.25 log CFU/g. Therefore, Bayesian analysis is recommended for predicting the growth of C. perfringens in cooked meat during cooling. • One-step dynamic method is used to study the growth of C. perfringens. • Markov Chain Monte Carlo simulation was used for Bayesian stochastic analysis. • Bayesian analysis was compared with deterministic modeling. • Bayesian analysis was proven to produce more accurate predictions. [ABSTRACT FROM AUTHOR]

Staphylococcus aureus is a common foodborne pathogen that is ubiquitous in nature. Consumption of contaminated foods, such as dairy products, can lead to food poisoning caused by heat-stable staphylococcal toxins that are not easily destroyed during pasteurization. The objective of this study was to investigate the growth kinetics of S. aureus and background microorganisms in camel milk stored at different temperatures between 8 and 43°C using one-step kinetic analysis to estimate the kinetic parameters from the observed growth curves. The growth of S. aureus showed apparent lag, exponential, and stationary phases, whereas no or negligible lag phase was observed for background microorganisms. Data analysis showed that the estimated minimum, optimum, and maximum growth temperatures were 5.9, 42.0, and 49.2°C for S. aureus , and 3.0, 38.6, and 49.2°C for the background microorganisms, respectively. The estimated optimum specific growth rate was higher for S. aureus (1.24 h−1) than for background microorganisms (0.995 h−1). This study found that camel milk may inhibit the growth of S. aureus , as it exhibits a lower specific growth rate than that in cow milk or cooked potato. It also has a longer lag phase than that in cow milk at comparable temperature ranges. This unique property is probably related to the presence of some antimicrobial compounds naturally occurring in camel milk. Validation of kinetic parameters and models showed that the root mean square error of prediction was only 0.5 log cfu/mL for S. aureus and background microorganisms, suggesting that the models are reasonably accurate. These models can be used for conducting risk assessments of S. aureus and predicting the general microbiological shelf life of camel milk to prevent foodborne staphylococcal poisoning. [ABSTRACT FROM AUTHOR]

MucA and MucB are critical negative modulators of sigma factor AlgU and regulate the mucoid conversion of Pseudomonas aeruginosa. Previous studies have revealed that lipid signals antagonize MucA-MucB binding. Here we report the crystal structure of MucB in complex with the periplasmic domain of MucA and polyethylene glycol (PEG), which unveiled an intermediate state preceding the MucA-MucB dissociation. Based on the biochemical experiments, the aliphatic side chain with a polar group was found to be of primary importance for inducing MucA cleavage. These results provide evidence that the hydrophobic cavity of MucB is a primary site for sensing lipid molecules and illustrates the detailed control of conformational switching within MucA-MucB in response to lipophilic effectors. Tao Li et al. report crystal structure of MucA-MucB complex and identify a cavity region of MucB that binds PEG molecule. They further show that this hydrophobic cavity of MucB is a primary site for sensing lipid molecules and that lipid A stimulates MucB to release MucA for AlgW cleavage, helping to understand the regulation mechanism of alginate biosynthesis. [ABSTRACT FROM AUTHOR]

This study was performed to evaluate the hypolipidemic and anti‐atherogenic activities of the crude polysaccharides extracted from abalone viscera (AVCP). The major functional groups of purified polysaccharides were analyzed by infrared spectroscopy (IR). Male Kunming mice (SPF) were divided into six groups and were treated with normal diet or high‐fat diet with AVCP or Xuezhikang (hypotensive drug) for 5 weeks. Physicochemnical analysis of AVCP showed the presence of 60.4% polysaccharides, 17.9% protein, 6.0% fat and 10.9% moisture. The IR analysis of AVP showed the presence of functional groups of sugar moiety and sulfate groups. The results demonstrated that AVCP not only led to significant reduction of total cholesterol (TC), triglycerides (TG), low‐density lipoprotein cholesterol (LDL‐C), and increase of high‐density lipoprotein cholesterol (HDL‐C) in plasma, but also to significant increments of malondialdehyde (MDA) and superoxide dismutase (SOD) activities. However, AVCP played no role in mice weight. Furthermore, the results of the photomicrograph of liver tissue showed that AVCP reduced lipid droplets and prevented the disordered structure of the liver. The results suggested that AVCP exhibited significantly hypolipidemic and anti‐atherogenic activities. [ABSTRACT FROM AUTHOR]

There are works have reported the crystal structures and mechanical properties of ferrite cement (C4AF) at the atomic scale with deviation owing to the omission of the Coulomb interaction effect (Ueff) between 3d electrons of Fe in C4AF. In this work, the DFT+U method was used to evaluate its effect on their electronic structures and mechanical properties of C4AF with two different phases I2mb (C4AF‐I) and Pnma (C4AF‐P). The FeO bonds of the two phases are all weaker and display Ueff due to the presence of Fe ions. The mechanical properties of C4AF calculated using DFT+U method significantly differ from those obtained without considering Ueff, in which the former shows lower inferior mechanical properties than the latter. This work presents a comparative study the effect of Coulomb interaction to the internal electronic structures and mechanical properties, which will pave the way for designing high hydration reaction cement and high toughness materials. [ABSTRACT FROM AUTHOR]

In this work, a newly designed superheated steam dryer (SSD) bearing exhaust heat recovery unit (RD) was fabricated. The dryer was designed for the superheated steam (SS) to be generated by foodstuff being dried, and the latent heat of the exhaust SS was recovered by microtube radiators and exploited to heat the RD unit. The system was then applied in Kelp drying, in which the drying kinetics was analyzed and fitted with mathematical models. The energy efficiency by the system was further evaluated and compared with hot air (HA)-drying. The results showed that the Kelp drying process in SSD could be described by two stages: heat-upstage (stage I) and superheated steam stage (stage II). While in stage I, different heat-up times of 10, 15, and 20 min were required to generate superheated steam at temperatures of 110-150°C, in stage II, the moisture content in Kelp was decreased to approximately 50 ± 5% (wet basis) within 60, 50, and 30 min at 110, 130, and 150°C, respectively. Moreover, the Midilli and Kucuk model best described Kelp drying curve in both stages, whereas the logarithmic model best fitted with that in stage II. Finally, the energy efficiency for SSD-RD was in the range of 1.127-1.425 kWh/kgwater compared with 2.406-2.508 kWh/kgwater for HA operating under the same conditions, demonstrating that the SSD-RD was able to reduce the energy input by at least 46.14%. [ABSTRACT FROM AUTHOR]

The critical role of the G protein-coupled receptor 1 (GPER1), a member of the seven-transmembrane G protein-coupled receptor family, in the functional regulation of oocytes accumulated abundant theories in the early research on model animals. However, the full-length cDNA encoding GPER1 and its role in the folliculogenesis has not been illustrated in crocodilians. 0.5, 3, and 12 months old Alligator sinensis cDNA samples were used to clone the full-length cDNA encoding GPER1. Immunolocalization and quantitative analysis were performed using Immunofluorescence technique, RT-PCR and Western blot. Simultaneously, studies on GPER1 's promoter deletion and cis-acting transcriptional regulation mechanism were conducted. Immunolocalization staining for the germline marker DDX4 and GPER1 demonstrated that DDX4-positive oocytes were clustered tightly together within the nests, whereas scarcely any detectable GPER1 was present in the oocytes nest in Stage I. After that, occasionally GPER1-positive immunosignal was observed in oocytes and somatic cells additional with the primordial follicles, and it was mainly located at the granulosa cells or thecal cells within the early PFs in the Stage III. The single mutation of the putative SP1 motif, double mutating of Ets / SP1 and SP1 / CRE binding sites all depressed promoter activities. This result will help to investigate the role of GPER1 in the early folliculogenesis of A. sinensis. • The full-length cDNA encoding G protein-coupled receptor 1 has been cloned in Alligator sinensis. • The folliculogenesis of Alligator sinensis might be related to estrogen signaling via G protein-coupled receptor 1. • The up-regulation of G protein-coupled receptor 1 expression might be mediated by the SP1 cis-acting elements. [ABSTRACT FROM AUTHOR]

Staphylococcus aureus is a food‐borne pathogen that quickly forms biofilm on meat contact surfaces and thus poses a serious threat to the safety of the meat industry. This study evaluated the attachment, survival, and growth of S. aureus biofilm with exposure to environmental factors in the meat industry by simulated ready‐to‐eat (RTE) cooked beef product contamination scenarios. The results indicated that the meat‐borne S. aureus biofilm formation dynamic could be divided into four different phases: initial adhesion (4–12 h), exponential (12–24 h), slow growth (1–3 days), and stationary (3–7 days). Meat‐borne S. aureus has strong adhesion and biofilm formation ability, and its biofilm exhibits persistence, high‐intensity metabolic activity, aerotaxis, and strain heterogeneity. This study has also demonstrated that in the long‐term existence of meat‐borne S. aureus biofilm on stainless steel and plexiglass surfaces (>7 days, 7.2–8.8 log CFU/cm2), expose to RTE cooked beef products, may cause it to become high‐risk contaminated food. Meat‐borne S. aureus that forms a dense and rough concave‐convex in the shape of biofilm architecture was observed by scanning electron microscopy, consisting of complex components and adhesion of living and dead cells. This was further confirmed by the meat‐borne S. aureus biofilm on the stainless steel surface by attenuated total reflectance Fourier transformed infrared spectroscopy, and the dominant peaks in biofilm spectra were mainly associated with proteins, polysaccharides, amino acid residues, and phospholipids (>50%). These findings may help in the identification of the main sources of contamination within the meat industry and the subsequent establishment of strategies for biofilm prevention and removal. Practical Application: This study revealed the meat‐borne S. aureus biofilm formation mechanism and found that it exhibited strong colonization and biofilm‐forming ability, which can persist on the contact surfaces of ready‐to‐eat beef products. These initial findings could provide information on the behavior of meat‐borne S. aureus biofilm attached to meat contact surfaces under conditions commonly encountered in meat environments, which help to support the determination of the main sources of contamination within the meat industry and the subsequent establishment of strategies for biofilm prevention and removal. It was also helpful in controlling biofilm contamination and improving meat safety to minimize it. [ABSTRACT FROM AUTHOR]

Dark channel prior (DCP) has advantages in image enhancement and image haze removal and is explored to detect highway visibility according to the physical relationship between transmittance and extinction coefficient. However, there are three major error sources in calculating transmittance. The first is that sky regions do not satisfy the assumptions of DCP algorithm. So the optimization algorithms combined with region growing and coefficient correction method are proposed. When extracting atmospheric brightness, different values lead to the second error. Therefore, according to different visibility conditions, a multimode classification method is designed. Image blocky effect causes the third error. Then guided image filtering is introduced to obtain accurate transmittance of each pixel of image. Next, according to the definition meteorological optical visual range and the relationship between transmittance and extinction coefficient of Lambert-Beer’s Law, accurate visibility value can be calculated. A comparative experimental system including visibility detector and video camera was set up to verify the accuracy of these optimization algorithms. Finally, a large number of highway section videos were selected to test the validity of DCP method in different models. The results indicate that these detection visibility methods are feasible and reliable for the smooth operation of highways. [ABSTRACT FROM AUTHOR]

In this work, a novel total non-ionic polystyrene-polyurethane (PS-PU) composite latex was synthesized with polymerizable polyethylene glycol ether. Contrary to traditional styrene-butyl acrylate latex (St-BA), PS-PU has a smaller size and superior dispersion stability, and it is stable in saturated Ca(OH)2 even after 72 h. In fresh-mixed mortars, PS-PU showed a little adverse effect on workability and insignificant air entrainment, with little defoamer consumption. The retardation effect of PS-PU is also much milder than traditional St-BA. As for strength, PS-PU showed a less adverse effect on early and late age compressive strength, but its effect on flexural strength is not as pronounced as St-BA at high dosages (4% and 6%). The different behavior in cementitious materials between PS-PU and St-BA can be reasoned from their different adsorption behavior and surface charge properties, as the results from characterizations suggest. The non-ionic nature of PS-PU made it less prone to destabilization and adsorption, which turned out as the aforementioned behavior in cementitious systems. The difference can further be ascribed to the difference in their polymeric structure and properties. [ABSTRACT FROM AUTHOR]

Aim To analyze the expression and distribution of Small Integrin-Binding LIgand N-linked Glycoproteins ( SIBLINGs) in reparative dentin (RepD). Methodology Cavities on the mesial surfaces of rat molars were prepared to expose the pulp, and a calcium hydroxide agent was applied to cap the exposed pulp. The molars with pulp capping were extracted at postoperative 1, 2, and 4 weeks. The immunolocalization of four SIBLINGs, dentin matrix protein 1 ( DMP1), dentin sialoprotein ( DSP), bone sialoprotein ( BSP), and osteopontin ( OPN) in RepD, was analyzed in comparison with reactionary dentin (ReaD) and primary dentin ( PD). Results At two weeks after operation, the region of the exposed pulp formed a layer of reparative dentin bridge sealing the communication between the cavity and pulp chamber. Dentinal tubules in RepD were more irregular in shape and fewer in number than PD. At postoperative 2 and 4 weeks, RepD had lower levels of DMP1 and DSP than PD. BSP and OPN were present in RepD, but not in PD. RepD showed certain similarities to ReaD in the expression of SIBLINGs. Conclusions The reduced levels of DMP1 and DSP may be associated with the decreased number of dentinal tubules in RepD. The expression of BSP and OPN in RepD indicates that the odontoblast-like cells were attempting to produce a hard tissue at a very rapid pace. These findings suggest that in response to the surgical injury, the newly differentiated odontoblast-like cells altered their synthesis of the dentinogenesis-related proteins and produced a hard tissue that is an intermediate between dentin and bone. [ABSTRACT FROM AUTHOR]

During preparation stages of ready-to-eat (RTE) foods, they can be cross-contaminated with Listeria monocytogenes which could result to outbreaks of foodborne listeriosis. In this study, the effects of gloves, cutting boards and cleaning methods on the transmission of L. monocytogenes during the processing of salmon sashimi were investigated. Subsequently, an improved particle swarm algorithm optimized BP neural network prediction model (CLPSO-BP) was developed based on Lévy flight and chaotic mapping. After processing contaminated salmons with gloves, we found that the surfaces of the gloves contained a significant amount of L. monocytogenes (5.24 log CFU/g), and 10.69% of the bacteria were subsequently transferred to uninfected salmon after being processed with the same gloves. Contamination of the processing tools with L. monocytogenes was reduced by up to 3 log CFU/g and the transfer rate was reduced by up to 50% after cleaning with room temperature water and detergent. In contrast, no bacteria were found after wiping the surfaces of the tools 70 °C hot water and detergent. The mean squared error (MSE) for the CLPSO-BP modeling tests was 0.1003, indicating accurate predictions. Overall, choosing an appropriate cleaning method and changing gloves regularly can help to avoid cross-contamination when processing RTE foods. • Sufficient independent tests were conducted to determine the range of transfer rates. • CLPSO-BP model has been developed to predict cross-contamination scenarios. • The improved PSO algorithm yields accurate results with small sample sizes. [ABSTRACT FROM AUTHOR]

Abstract: The Xiaotian-Mozitan fault (XMF) located north of the Dabie orogenic belt separates the North Dabie complex to the south from the Beihuaiyang low-grade metamorphic rocks to the north. It comprises several NW-striking ductile shear zones and brittle faults. The brittle faults obviously overprinted on the ductile shear zones and promoted the development of the volcanic basins in early Cretaceous to the north, which suggests that the brittle faults were normal faults formed in early Cretaceous during doming of the Dabie orogenic belt. The ductile shear zone superposed on the north Dabie gray gneiss, and it is an important channel where the Dabie HP–UHP rocks exhumed. For obtaining new structural constraint on exhumation of the HP–UHP rocks, we present here experimental results on the microstructure, quartz C-axis fabrics and the microprobe analyses of phengite. The ductile shear zone was determined to be formed at a temperature of 600–650°C and pressure of 1.1 GPa by the mineral deformation, microprobe analyses and geobarometry of Si-in-phengite of the mylonite, the results suggest that the mylonite now exposed on the surface experienced an upper amphibolite-facies metamorphism in the lower crust. The mineral stretching lineation varies from horizontal in the east segment to sub-dip in the west. Shear sense indicators from outcrop and thin sections of orientated specimen and quartz C-axis fabrics suggest that the XMF is a sinistral normal fault. The kinematics analysis of the ductile shear zone indicates that the exhumation of Dabie HP–UHP rocks is the results of a SE-directed extrusion and an anticlockwise rotation around its eastern pivot simultaneously. [Copyright &y& Elsevier]

Based on the abundant and low-cost zinc-based acrylate resins, C/ZnO composites were fabricated via one-step carbonization at 700 °C in a N 2 atmosphere for 2 h. Zinc-based acrylate resins, which were synthesized by free-radical polymerization of butyl acrylate (BA), acrylic acid (AA) and vinyl acetate (VAc) and dehydration condensation of Zn(OH) 2 , provided a common source for carbon and ZnO. These materials demonstrate enhanced electromagnetic wave absorption (EMWA) behavior with tunable microwave absorption bands at 2–18 GHz, which is related to the molar ratio (mol%) of Zn(OH) 2 to acrylate monomers in zinc-based acrylate resins. Remarkably, the 0.11 mol% C/ZnO composite exhibits outstanding absorption properties: the minimum reflection loss (RL min) at 16.7 wt% loading of −34.66 dB is observed at 3.0 mm and 10.32 GHz, and an RL min of −24.83 dB is observed at a small thickness of 1.5 mm with an effective absorption bandwidth (EAB) of 3.61 GHz. Moreover, the EAB (RL ≤ −10 dB) from the C band to Ku band is achieved by simply adjusting the thickness of the absorbers, which are superior to the other hybrids of organic carbon and ZnO. These results provide a new strategy for the preparation of carbon-based composites containing metal oxides and their application in high-performance microwave absorption. [Display omitted] • Zinc-based acrylate resins were first applied as precursors to prepare C/ZnO composites for electromagnetic absorption. • Effective adsorption of C/ZnO composites could be tuned by adjusting the molar ratio of Zn(OH) 2 to acrylate monomers. • An RL min value at 16.7 wt% loading of -34.66 dB (10.32 GHz) at 3.0 mm and EAB of 3.61 GHz at 1.5 mm were achieved. • The EMWA mechanism of the C/ZnO composites was investigated in detail. [ABSTRACT FROM AUTHOR]

In the field of non-destructive testing (NDT), the detection of surface cracks using permanent magnetic field perturbation (PMFP) testing has emerged as a novel approach. It is particularly well-suited for detecting ferromagnetic materials due to its capability to identify open cracks, facilitated by a compact and straightforward probe structure. However, the existing rigid PMFP probes pose challenges in terms of shape-conforming, resulting in large lift-off fluctuations during sweeping, and are prone to wear and tear. Furthermore, their suitability is limited when inspecting specimens with various specifications and irregular shapes. To address these issues, this paper proposes a novel PMFP detection method based on the magnetization of a Flexible Magnetic Sheet (FMS). For further optimization, the machining of a through-slot in the FMS, with the magnetic sensor embedded within, serves to capture the magnetic field perturbation. This configuration is employed for the detection of surface defects. Compared to the conventional PMFP method that relies on rigid permanent magnetization, its flexibility makes the proposed method offer notable advantages such as streamlined processing, lightweight construction, and inherent adaptability to various shapes. Moreover, compared to the traditional PMFP structure where the sensor is placed beneath the permanent magnet, the through-plot FMS design exhibits a larger and more uniform magnetic field. Consequently, this feature significantly improves the signal-to-noise ratio by approximately 30%. The flexible testing method has a high application value and can effectively detect rectangular slots of size 1 mm * 1 mm* 12.5 mm and flat-bottom holes of size Φ2mm* 0.5 mm in pipeline testing. [Display omitted] • Based on FMS magnetization, a flexible probe is proposed to optimize the adaptability of conventional PMFP testing. • Enhanced magnetization field and signal-to-noise ratio by machining through-slots in the FMS. • The proposed flexible probe structure effectively addresses the issues of fit and array scanning in pipeline testing. [ABSTRACT FROM AUTHOR]

Summary: Type II toxin‐antitoxin (TA) systems modulate many essential cellular processes in prokaryotic organisms. Recent studies indicate certain type II antitoxins also transcriptionally regulate other genes, besides neutralizing toxin activity. Herein, we investigated the diverse transcriptional repression properties of type II TA antitoxin PaHigA from Pseudomonas aeruginosa. Biochemical and functional analyses showed that PaHigA recognized variable pseudopalindromic DNA sequences and repressed expression of multiple genes. Furthermore, we presented high resolution structures of apo‐PaHigA, PaHigA‐PhigBA and PaHigA‐Ppa2440 complex, describing how the rearrangements of the HTH domain accounted for the different DNA‐binding patterns among HigA homologues. Moreover, we demonstrated that the N‐terminal loop motion of PaHigA was associated with its apo and DNA‐bound states, reflecting a switch mechanism regulating HigA antitoxin function. Collectively, this work extends our understanding of how the PaHigB/HigA system regulates multiple metabolic pathways to balance the growth and stress response in P. aeruginosa and could guide further development of anti‐TA oriented strategies for pathogen treatment. [ABSTRACT FROM AUTHOR]

The objective of this study was to develop a dynamic model for predicting the growth of Listeria monocytogenes in pasteurized cow milk under fluctuating temperature conditions during storage and temperature abuse. Six dynamic temperature profiles that simulated random fluctuation patterns were designed to change arbitrarily between 4 and 30°C. The growth data collected from 3 independent temperature profiles were used to determine the kinetic parameters and construct a growth model combining the primary and secondary models using a 1-step dynamic analysis method. The results showed that the estimated minimum growth temperature and maximum cell concentration were 0.6 ± 0.2°C and 7.8 ± 0.1 log cfu/mL (mean ± standard error), with the root mean square error (RMSE) only 0.3 log cfu/mL for model development. The model and the associated kinetic parameters were validated using the data collected under both dynamic and isothermal conditions, which were not used for model development, to verify the accuracy of prediction. The RMSE of prediction was approximately 0.3 log cfu/mL for fluctuating temperature profiles, and it was between 0.2 and 1.1 log cfu/mL under certain isothermal temperatures (2–30°C). The resulting model and kinetic parameters were further validated using 3 growth curves at 4, 7, and 10°C arbitrarily selected from ComBase (www.combase.cc). The RMSE of prediction was 0.8, 0.4, and 0.5 log cfu/mL, respectively, for these curves. The validation results indicated the predictive model was reasonably accurate, with relatively small RMSE. The model was then used to simulate the growth of L. monocytogenes under a variety of continuous and square-wave temperature profiles to demonstrate its potential application. The results of this study showed that the model developed in this study can be used to predict the growth of L. monocytogenes in contaminated milk during storage. [ABSTRACT FROM AUTHOR]

Kelp is an aquatic product that must be dried after harvest to prevent spoilage. This study tested a novel system for drying kelp. It utilized superheated steam for heating and could recover the latent heat of the exhausted steam, for further drying of the product. The system was tested in four drying modes, including single-face radiation drying mode (SRDM), double-face radiation drying mode (DRDM), single-face conduction drying mode (SCDM), and combined conduction and radiation drying mode (CCRDM). A one-dimensional semi-empirical mathematical model was used to predict the change in the moisture content and temperature of kelp during drying in each of the four drying modes. The drying characteristics of standardized kelp samples in each drying mode were investigated and the efficiency of heat recovery was assessed and compared. The change in moisture content and surface temperature of kelp during drying in each of the four drying modes was also predicted. The results showed that the drying characteristic of the kelp differed significantly depending on the drying mode. The CCRDM was determined as the optimal drying method and exhibited the best drying characteristics, including the highest kelp surface temperature, shortest drying time, and fastest drying rate. Compared to SRDM, DRDM and SCDM, CCRDM recovered, 83.3, 79.5, and 4.5% more energy from the system, and was the most energy efficient among 4 operation modes. Compared with changes in moisture, the changes in the surface temperature of kelp were more accurately predicted during drying. [ABSTRACT FROM AUTHOR]

Square billet is an important industrial raw material. Due to the large amount of oxidation skin on the surface after continuous casting process, it needs surface grinding treatment. Meanwhile, the billet surface is prone to stress concentrations and cracks in the crystallization zone, so it is easy to break and cause accidents in the subsequent process. However, the poor surface condition of the reground billet, such as the large roughness and fluctuations in the shape, makes it difficult to be tested by traditional methods. In this paper, the relationship between the excitation frequency of alternative current magnetic flux leakage (AC-MFL) and the fluctuation of magnetic field generated by uneven surface is studied, and the high-frequency AC leakage field formation is restated. Furthermore, a flexible probe integrating parallel cables (PC) magnetizer and receiving coils is proposed, which can realize the profiling testing and reduce the influence of the undulating surface. Finally, the wavelet transform is used to reconstruct signals, which increases the average signal-to noise ratio (SNR) from 7.25 dB to 11.89 dB. [ABSTRACT FROM AUTHOR]

A novel dimeric gadolinium(III) complex, bis(4-Gd-DTPA-aminophenyl)adamantane ( 5 ), was successfully synthesized using bis(4-aminophenyl)adamantane to link two Gd-DTPA units. All the intermediates and bis(4-Gd-DTPA-aminophenyl)adamantane ( 5 ) have been characterized by 1 H NMR, 13 C NMR, ES-API-MS, HR-ESI-MS, FT-IR and elemental analysis (EA). The longitudinal relaxivity of bis(4-Gd-DTPA-aminophenyl)adamantane is 8.43 mM −1  Gd −1  s −1 at 0.43 T (32 °C, pH 7.0), and 4.89 mM −1  Gd −1  s −1 at 3.0 T (32 °C, pH 7.4). The T 1 -weighted imaging in vitro showed that bis(4-Gd-DTPA-acetylaminophenyl)adamantane can enhance the contrast of images distinctly. But most of all, the kinetic inertness of bis(4-Gd-DTPA-aminophenyl)adamantane ( 5 ) was comparable to that of [Gd(DTPA)(H 2 O)] 2− (Magnetvist®). Moreover, cytotoxicity tests indicated that the bis(4-Gd-DTPA-acetylaminophenyl)adamantane exhibited low toxicity to healthy liver cells (L-02 cells). These results demonstrate that the Gd(III) complex 5 may be a promising MRI contrast agent candidate. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the growth kinetics of S. aureus and different concentrations of background microbiota in Chinese-style braised beef (CBB). A one-step analysis method was applied to develop predictive model to describe the simultaneous growth and interaction of S. aureus with different concentrations of background microbiota in CBB. The results show that a one-step method successfully models the growth of S. aureus and background microbiota in CBB and the competing interactions between the two. In sterile CBB, the estimated minimum growth temperatures (T min,S) and the maximum growth concentrations (Y max,S) were 8.76 °C and 9.58 log CFU/g for S. aureus. Under competition, the growth of background microbiota was not affected by S. aureus , the estimated T min,B and Y max,B was 4.46 °C and 9.94 log CFU/g. The background microbiota in CBB did not affect the growth rate of S. aureus (α 1 = 1.04), but had an inhibitory effect on the number of S. aureus (α 2 = 0.69) at the later growth stage. The Root Mean Square Error (RMSE) of the modeling data was 0.34 log CFU/g, with 85.5% of the residual errors within ±0.5 log CFU/g of experimental observations. The one-step analysis and dynamic temperatures (8 °C–32 °C) verification indicated that the RMSE of prediction was <0.5 log CFU/g for both S. aureus and background microbiota. This study demonstrates that microbial interaction models are a useful and promising tool for predicting and evaluating the spatiotemporal population dynamics of S. aureus and background microbiota in CBB products. • A growth prediction model for S. aureus in sterile CBB was developed. • Interaction models of S. aureus and background microbiota in CBB were developed. • A one-step analysis method was used to estimate kinetic parameters. • The applicability and accuracy of the model were verified under dynamic temperature. [ABSTRACT FROM AUTHOR]

Key message : Using bulk segregant analysis (BSA) coupling with RNA-seq and DNA markers identified a potentially novel nitrogen-dependent lesion mimic gene Ndhrl1 on 2BS in wheat. Abstract: Lesion mimic (LM) refers to hypersensitive reaction-like (HRL) traits that appear on leaf tissue in the absence of plant pathogens. In a wheat line P7001, LM showed up on the leaves under the 0 g nitrogen (N) treatment, but disappeared when sufficient N was supplied, suggesting that LM is N-responsive and N dosage dependent. Using BSA strategy together with RNA-seq and DNA markers, we identified an N-dependent LM gene ( Ndhrl1) and mapped it to the short arm of chromosome 2B using an F recombinant inbred population developed from the cross of P7001 × P216. The putative gene was delimited into an interval of 8.1 cM flanked by the CAPS/dCAPS markers 7hrC9 and 7hr2dc14, and co-segregated with the dCAPS marker 7hrdc2. This gene is most likely a novel gene for LM in wheat based on its chromosomal location. Further analysis of RNA-seq data showed that plant-pathogen interaction, nitrogen metabolism, zeatin biosynthesis and plant hormone signal transduction pathways were significantly differentially expressed between LM and non-LM lines. [ABSTRACT FROM AUTHOR]