Search

Aims Huanglongbing (citrus greening) is a plant disease putatively caused by the unculturable Gram-negative bacterium Candidatus Liberibacter asiaticus (CLas), and it has caused severe damage to citrus plantations worldwide. There are no definitive treatments for this disease, and conventional disease control techniques have shown limited efficacy. This work presents an in silico evaluation of using specifically targeting anti-microbial peptides (STAMPs) consisting of a targeting segment and an antimicrobial segment to inhibit citrus greening by inhibiting the BamA protein of CLas, which is an outer membrane protein crucial for bacterial viability. Methods and results Initially, a set of peptides with a high affinity toward BamA protein were screened and evaluated via molecular docking and molecular dynamics simulations and were verified in vitro via bio-layer interferometry (BLI). In silico studies and BLI experiments indicated that two peptides, HASP2 and HASP3, showed stable binding to BamA. Protein structures for STAMPs were created by fusing known anti-microbial peptides (AMPs) with the selected short peptides. The binding of STAMPs to BamA was assessed using molecular docking and binding energy calculations. The attachment of high-affinity short peptides significantly reduced the free energy of binding for AMPs, suggesting that it would make it easier for the STAMPs to bind to BamA. Efficacy testing in vitro using a closely related CLas surrogate bacterium showed that STAMPs had greater inhibitory activity than AMP alone. Conclusions In silico and in vitro results indicate that the STAMPs can inhibit CLas surrogate Rhizobium grahamii more effectively compared to AMPs, suggesting that STAMPs can achieve better inhibition of CLas, potentially via enhancing the site specificity of AMPs. [ABSTRACT FROM AUTHOR]

Earlier studies with montelukast (M) and telmisartan (T) have revealed their potential antiviral properties against SARS-CoV-2 wild-type (WT) but have not assessed their efficacy against emerging Variants of Concern (VOCs) such as Omicron. Our research fills this gap by investigating these drugs' impact on VOCs, a topic that current scientific literature has largely overlooked. We employed computational methodologies, including molecular mechanics and machine learning tools, to identify drugs that could potentially disrupt the SARS-CoV-2 spike RBD-ACE2 protein interaction. This led to the identification of two FDA-approved small molecule drugs, M and T, conventionally used for treating asthma and hypertension, respectively. Our study presents an additional potential use for these drugs as antivirals. Our results show that both M and T can inhibit not only the WT SARS-CoV-2 but also, in the case of M, the Omicron variant, without reaching cytotoxic concentrations. This novel finding fills an existing gap in the literature and introduces the possibility of repurposing these drugs for SARS-CoV-2 VOCs, an essential step in responding to the evolving global pandemic. [ABSTRACT FROM AUTHOR]

Bridge weigh-in-motion (BWIM) serves as a method to obtain the weight of passing vehicles from bridge responses. Most BWIM systems proposed so far rely on the measurement of bridge global vibration data, usually strain, to determine the vehicle load. However, because the bridge's global response is sensitive to all vehicles on the bridge, the global vibration-based BWIM techniques usually suffer from inaccuracy in the case where multiple vehicles are present on the bridge. In this paper, a data-driven approach is proposed to extract the passing vehicle's weight and driving speed from vertical acceleration at the bridge joint. As a type of local vibration, the impulse acceleration responses at a bridge joint can be recorded only during a short period when a vehicle is passing over the joint and are thus not sensitive to vehicles at other locations of the bridge. A field test is conducted at a bridge to prepare labeled training data for the use of a convolutional neural network. One accelerometer is installed on the bridge joint to record impulse acceleration, while the vehicle's weight and driving speed are obtained from a WIM station and a camera near the bridge, respectively. A network that detects the vehicle's passage as well as its passing lane is first proposed, followed by a 1-D convolutional neural network that uses the raw data of acceleration as the input to predict the vehicle's gross weight and driving speed. A comparison is made between the 1-D network and an updated 2-D network that uses the wavelet coefficients as the input matrix. The latter one shows better performance, indicating that it is important to choose the proper input data for the network to be trained. A transfer learning technique is used to test the feasibility of the proposed method. Results show that the proposed method can be extended with limited data to bridges other than the bridge where the network is trained. [ABSTRACT FROM AUTHOR]

Citrus greening, also known as Huanglongbing (HLB), is caused by the unculturable bacterium Candidatus Liberibacter spp. (e.g., CLas), and has caused a devastating decline in citrus production in many areas of the world. As of yet, there are no definitive treatments for controlling the disease. Antimicrobial peptides (AMPs) that have the potential to block secretion-dependent effector proteins at the outer-membrane domains were screened in silico. Predictions of drug-receptor interactions were built using multiple in silico techniques, including molecular docking analysis, molecular dynamics, molecular mechanics generalized Born surface area analysis, and principal component analysis. The efflux pump TolC of the Type 1 secretion system interacted with natural bacteriocin plantaricin JLA-9, blocking the β barrel. The trajectory-based principal component analysis revealed the possible binding mechanism of the peptides. Furthermore, in vitro assays using two closely related culturable surrogates of CLas (Liberibacter crescens and Rhizobium spp.) showed that Plantaricin JLA-9 and two other screened AMPs inhibited bacterial growth and caused mortality. The findings contribute to designing effective therapies to manage plant diseases associated with Candidatus Liberibacter spp. [ABSTRACT FROM AUTHOR]

Owing to the light weight and high fundamental frequency, timber floors exhibit impulse-like responses under human-induced excitation, which is different with the resonance-like responses for heavy concrete structures. The vibration serviceability of timber floors thus needs to be considered in a different manner. Many design codes for timber structures have required that the static displacement or dynamic response under human excitation should be limited within a threshold for the purpose of serviceability, while failing to provide appropriate method for predicting structural responses considering various affecting factors. Inspired by the idea of response spectrum, this paper proposed a design-oriented method for the peak acceleration prediction of high-frequency floors under human bouncing excitation. The prediction can be obtained for any desired confidence level. Statistical analysis shows that the acceleration responses are mostly dependent on structural fundamental frequency, structural damping ratio, and excitation frequency, which are considered in the proposed mathematical model. The application procedure and the experimental assessment of the proposed model are provided, showing the decent applicability of the proposed method. [ABSTRACT FROM AUTHOR]

Bouncing is a common human activity that is frequently observed in large-span structures such as sports stadiums and concert halls; this activity can cause vibration serviceability problems that must be considered at the structural design stage. Current design codes suggest methods for predicting structural responses under rhythmic bouncing excitations. However, these methods typically do not consider the interaction effect between the crowd and structure, which is highly significant, particularly for large groups of people. Such an effect can quantitatively be evaluated from the structural dynamic property changes attributable to the crowd. Using the random distribution of human model parameters given in a previous study, we propose an empirical formula to predict the frequency and damping ratio of the coupled system via statistical analysis. The structural dynamic properties are updated. A response spectrum method framework that employs the updated structural dynamic properties is proposed and validated through a series of experiments on crowd bouncing. The results show that the response spectrum method provides a reasonable prediction of the structural responses. Hence, this study provides an effective method for quantitatively considering the interaction effect when calculating structural responses at the design stage. [ABSTRACT FROM AUTHOR]

DNA originating from organellar genomes are regularly discovered in nuclear sequences during genome assembly. Nevertheless, such insertions are sometimes omitted during the process of nuclear genome assembly because the inserted DNA is assigned to organellar genomes, leading to a systematic underestimation of their frequency. With the rapid development of high-throughput sequencing technology, more inserted fragments from organelle genomes can now be detected. Therefore, it is necessary to be aware of the insertion events from organellar genomes during nuclear genome assembly to properly attribute the impact and rate of such insertions in the evolution of nuclear genomes. Here, we investigated the impact of intracellular gene transfer (IGT) from the plastome to the nuclear genome using genome assemblies that were refined through time with technological improvements from two model species, Arabidopsis thaliana and Oryza sativa. We found that IGT from the plastome to the nuclear genome is a dynamic and ongoing process in both A. thaliana and O. sativa, and mostly occurred recently, as the majority of transferred sequences showed over 95% sequence similarity with plastome sequences of origin. Differences in the plastome-to-nuclear genome IGT between A. thaliana and O. sativa varied among the different assembly versions and were associated with the quality of the nuclear genome assembly. IGTs from the plastome to nuclear genome occurred more frequently in intergenic regions, which were often associated with transposable elements (TEs). This study provides new insights into intracellular genome evolution and nuclear genome assembly by characterizing and comparing IGT from the plastome into the nuclear genome for two model plant species. [ABSTRACT FROM AUTHOR]

• The virtual reward model is firstly suggested in the reinforcement learning (RL) algorithm, making the optimum CFD study of AF-PCHE based on RL algorithm feasible. • The thermal hydraulics performance of AF-PCHE from reinforcement learning is significantly improved. • The Q-learning algorithm converges faster than that of DQN with a small number of optimum parameters. • The comprehensive performance of the heat exchanger derived from the DQN optimum algorithm is better than that of Q-learning algorithm. As the Gen IV nuclear reactors, the lead-based reactor employs the S-CO 2 Brayton cycle. As the intermediate heat exchangers, high or low temperature regenerators and precoolers, the thermal hydraulic characteristics of the PCHEs directly affect the efficiency of S-CO 2 power cycle efficiency. In this work, two reinforcement learning algorithms, namely the Q-learning and DQN are used to optimize the key geometric parameters that affects the thermal hydraulics performance of the airfoil fin PCHE (AF-PCHE) with the S-CO 2 as the working fluid. Furthermore, the thermal hydraulic performance of the optimal designs derived from these two reinforcement learning algorithms is compared with that of the original design. The results demonstrate that the two reinforcement learning algorithms significantly improve the optimization efficiency of AF-PCHE design. Specifically, the ΔQ/ΔP of the optimized AF-PCHEs are improved by 173.89% and 189.38%, respectively. In addition, the Nu/Eu of optimized AF-PCHEs are increased by 129.15% and 141.94%, respectively. [ABSTRACT FROM AUTHOR]

A patient's comprehension and memory of conversations with their providers plays an important role in their healthcare. Adult breast cancer patients whose legal sex was female and who underwent treatment at the Center for Reconstructive Surgery at The University of Texas MD Anderson Cancer Center were asked to indicate which breast reconstruction procedures they discussed with their surgeon. We focused on the three most frequent responses: (a) participants who remembered discussing implant-based, tissue-based, and combination procedures; (b) participants who remembered only an implant-based option being discussed; and (c) participants who remember only a tissue-based option being discussed. We used multinomial logistic regression models to explore the psychosocial factors associated with patients' recollections of their breast reconstruction options after discussions with their reconstructive surgeons, controlling for medical factors that impact surgical decision-making. Our analyses identified body mass index, body image investment, and body image as statistically significantly associated with the reconstructive options that a participant recalls discussing with their surgeon. Our findings highlight body image investment and body image as important psychological factors that may influence what patients remember from consultations about breast reconstruction options. [ABSTRACT FROM AUTHOR]

Breast cancer (BC) is one of the leading causes of cancer-related deaths in women. The purpose of this study is to identify key molecular markers related to the diagnosis and prognosis of early breast cancer (EBC). The data of mRNA, lncRNA and DNA methylation were downloaded from The Cancer Genome Atlas (TCGA) dataset for identification of differentially expressed mRNAs (DEmRNAs), differentially expressed lncRNAs (DElncRNAs) and DNA methylation analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyzes were used to identify the biological functions of DEmRNAs. The correlation analysis between DNA methylation and DEmRNAs was carried out. Then, diagnostic analysis and prognostic analysis of identified DEmRNAs and DElncRNAs were also performed in the TCGA database. Subsequently, methylation state verification for identified DEmRNAs was performed in the GSE32393 dataset. In addition, real-time polymerase chain reaction (RT-PCR) in vitro verification of genes was performed. Finally, AC093110.1 was overexpressed in human BC cell line MCF-7 to verify cell proliferation and migration. In this study, a total of 1633 DEmRNAs, 750 DElncRNAs and 8042 differentially methylated sites were obtained, respectively. In the Venn analysis, 11 keys DEmRNAs (ALDH1L1, SPTBN1, MRGPRF, CAV2, HSPB6, PITX1, WDR86, PENK, CACNA1H, ALDH1A2 and MME) were we found. ALDH1A2, ALDH1L1, HSPB6, MME, MRGPRF, PENK, PITX1, SPTBN1, WDR86 and CAV2 may be considered as potential diagnostic gene biomarkers in EBC. Strikingly, CAV2, MME, AC093110.1 and AC120498.6 were significantly actively correlated with survival. Methylation state of identified DEmRNAs in GSE32393 dataset was consistent with the result in TCGA. AC093110.1 can affect the proliferation and migration of MCF-7. ALDH1A2, ALDH1L1, HSPB6, MME, MRGPRF, PENK, PITX1, SPTBN1, WDR86 and CAV2 may be potential diagnostic gene biomarkers of EBC. Strikingly, CAV2, MME, AC093110.1 and AC120498.6 were significantly actively correlated with survival. The identification of these genes can help in the early diagnosis and treatment of EBC. In addition, AC093110.1 can regulate SPTBN1 expression and play an important role in cell proliferation and migration, which provides clues to clarify the regulatory mechanism of EBC. [ABSTRACT FROM AUTHOR]

A novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified as the cause of the COVID-19 pandemic that originated in China in December 2019. Although extensive research has been performed on SARS-CoV-2, the binding behavior of spike (S) protein and receptor binding domain (RBD) of SARS-CoV-2 at different environmental conditions have yet to be studied. The objective of this study is to investigate the effect of temperature, fatty acids, ions, and protein concentration on the binding behavior and rates of association and dissociation between the S protein and RBD of SARS-CoV-2 and the hydrophobic aminopropylsilane (APS) biosensors using biolayer interferometry (BLI) validated with molecular dynamics simulation. Our results suggest three conditions—high ionic concentration, presence of hydrophobic fatty acids, and low temperature—favor the attachment of S protein and RBD to hydrophobic surfaces. Increasing the temperature within an hour from 0 to 25 °C results in S protein detachment, suggesting that freezing can cause structural changes in the S protein, affecting its binding kinetics at higher temperature. At all the conditions, RBD exhibits lower dissociation capabilities than the full-length S trimer protein, indicating that the separated RBD formed stronger attachment to hydrophobic surfaces compared to when it was included in the S protein. [ABSTRACT FROM AUTHOR]

The vibration caused by human excitation has become a key factor at the structural design stage of large-span structures including footbridges, sport stadia, and high-rise buildings. As the structures tend to become slenderer and lighter, the mass of the crowd is not negligibly small compared with the mass of the structure. In such cases, the crowd and the structure form a coupling system through a mechanism known as human–structure interaction (HSI). Researchers found that the structural responses with and without HSI are different. However, the interaction effect on the structural responses has rarely been quantitatively evaluated from the perspective of human system parameters. In this paper, a novel method using a physical principle to predict jumping-induced structural responses is proposed, in which the structural response is expressed as the multiplication of a series of transfer functions representing human system and structural dynamic properties. Structural responses of a large-span concrete structure under jumping excitation are predicted using the proposed method and identified human system parameters. Comparison with measured responses shows satisfactory agreement. The proposed method provides a solution to consider HSI effect on the calculation of structural responses in the vibration serviceability design for large-span structures. [ABSTRACT FROM AUTHOR]

Summary: The effects from passing vehicle's load on bridge are divided into two categories: static effect and dynamic effect. The static effect usually indicates the pseudo‐static responses of the bridge caused by the vehicle gross weight while the dynamic effect means dynamic responses due to vehicle and bridge dynamic properties and bridge pavement roughness. Both effects need to be properly evaluated because the vehicle static weight is a governing factor in determining bridge's fatigue life while the dynamic part of the vehicle load tends to amplify the bridge responses. In this paper, a method based on an extended Kalman filter is proposed to identify vehicle static and dynamic load only from responses recorded by portable accelerometers, together with their transverse position, which affects the identification of the loads. Even though only accelerometers are employed as sensors, the bridge vertical acceleration can capture the dynamic load components and the inclination obtained from the projection of the gravitational acceleration in the longitudinal direction can capture the low‐frequency component. The feasibility of the proposed method is proved through numerical simulation and an experimental test on a bridge. This paper makes full use of three‐axis accelerometers to estimate vehicle's static and dynamic load considering the vehicle's passing route, thus solving the nonlinear problem caused by vehicle's transverse position. Moreover, the proposed method eliminates the need of using other devices like displacement sensor or strain gauges to obtain low‐frequency components. [ABSTRACT FROM AUTHOR]

Microbial electrosynthesis (MES) is a promising technology through which carbon dioxide is converted into chemicals via bioelectrochemcal reaction. In this study, a natural loofah sponge (LS) was directly converted into a 3D macroporous carbon cathode through carbonization. The LS was codecorated with polydopamine and Mo 2 C (Mo 2 C/N-doped LS). Results revealed that the acetate production rate of MES with Mo 2 C/N-doped LS increased by 2.5 times compared with that of carbon felt. The maximum acetate concentration of 6.08 g L−1 and 64% of coulomb efficiency (CE) were obtained in MES with Mo 2 C/N-doped LS. Electrochemistry, scanning electron microscopy, and microbial community analyses showed that Mo 2 C/N-doped LS contributed to biofilm formation and improved the enrichment of electrochemically active bacteria. Thus, this study introduced a promising method for the fabrication of 3D cathodes with a high electrocatalytic activity from low-cost sustainable natural materials to improve MES efficiency. [Display omitted] • LS provided a high specific area for microbial attachment. • LS was widely available and could easily produce 3D electrodes for MES. • Mo 2 C/N-doped LS was beneficial to direct and indirect electron transfer rate. • The acetate production rate of Mo 2 C/N-doped LS increased by 2.5 times. • The maximum acetate concentration of 6.08 g L−1 and CE of 64% were obtained. [ABSTRACT FROM AUTHOR]

Human-robot collaboration (HRC) in assembly is becoming increasingly popular in the field of intelligent manufacturing. However, safety concerns remain the most critical issue to be addressed. The complex assembly environment and the individual differences of workers make it challenging to ensure safety effectively. Furthermore, the concept of human-centric manufacturing also places higher requirements on safety and efficiency of HRC assembly. The application of digital twin (DT) technology has bolstered the cognitive and decision-making capabilities in the context of HRC assembly. This technological advancement provides essential support for addressing safety concerns in HRC assembly processes guided by a human-centric approach. A personalised safety detection method for HRC assembly based on DT technology is proposed. This approach involves personalised modelling and simulation of real objects within the HRC process, establishing a collision detection model based on skeleton points. Subsequently, human motion prediction methods drive safety monitoring between humans and robots. Ultimately, personalised safety warning strategies are applied to ensure the safety of the assembly process. [ABSTRACT FROM AUTHOR]

Simple Summary: Muscle growth is essential for the economic sustainability of the swine industry. Gaining a deeper understanding of pig muscle development is crucial for improving both the quantity and quality of pork production. This study employed RNA-seq technology to conduct a transcriptomic analysis of the longissimus dorsi muscle (LD) in three different pig breeds with varying body sizes and growth rates: Tibetan pigs (TP), Wujin pigs (WJ), and large white pigs (LW). Significant differences in gene expression were observed among the different breeds. We identified that myosin light chain 4 (MYL4) plays a role in influencing muscle growth. Experimental validation confirmed that MYL4 promotes skeletal muscle cell proliferation and inhibits degradation. These findings reveal the molecular mechanisms that control muscle growth and provide valuable insights for improving pig breeding practices, ultimately enhancing the efficiency and quality of meat production. Muscle growth stands as a pivotal economic trait within pig production, governed by a complex interplay of multiple genes, each playing a role in its quantitative manifestation. Understanding the intricate regulatory mechanisms of porcine muscle development is crucial for enhancing both pork yield and quality. This study used the GSE99749 dataset downloaded from the GEO database, conducting a detailed analysis of the RNA-seq results from the longissimus dorsi muscle (LD) of Tibetan pigs (TP), Wujin pigs (WJ) and large white pigs (LW) at 60 days of gestation, representing diverse body sizes and growth rates. Comparative analyses between TPvsWJ and TPvsLW, along with differential gene expression (DEG) analysis, functional enrichment analysis, and protein–protein interaction (PPI) network analysis, revealed 1048 and 1157 significantly differentially expressed genes (p < 0.001) in TPvsWJ and TPvsLW, respectively. With stricter screening criteria, 37 DEGs were found to overlap between the 2 groups. PPI analysis identified MYL5, MYL4, and ACTC1 as the three core genes. This article focuses on exploring the MYL4 gene. Molecular-level experimental validation, through overexpression and interference of the MYL4 gene combined with EDU staining experiments, demonstrated that overexpression of MYL4 significantly promoted the proliferation of porcine skeletal muscle satellite cells (PSMSC), while interference with MYL4 inhibited their proliferation. Furthermore, by examining the effects of overexpressing and interfering with the MYL4 gene on the muscle hypertrophy marker Fst gene and the muscle degradation marker FOXO3 gene, the pivotal role of the MYL4 gene in promoting muscle growth and preventing muscle degradation was further confirmed. These findings offer a new perspective on the molecular mechanisms behind porcine muscle growth and development, furnishing valuable data and insights for muscle biology research. [ABSTRACT FROM AUTHOR]

The consideration of inherent uncertainties of the human-structure coupled system during serviceability assessment has become a consensus in recent years. The uncertainties from human body and structures are coupled and propagate together through the human-structure interaction (HSI) effect. However, how each random source affects the system output under rhythmic motion remains unclear and lacks investigation. In this paper, a method for uncertainty quantification and global sensitivity analysis for large-span floors under crowd bouncing is introduced. Both the uncertainties from the structure and the human body are considered through an HSI analytical model. The Kullback–Leibler (K-L) divergence indices and probability density evolution method (PDEM) are adopted for the uncertainty analysis. Dynamic properties and vibration responses of four structures with different characteristics are investigated. Parametric analysis of structural modal mass, damping ratio, and natural frequency is carried out for general insights and a quick method identifying the important variables is proposed. The influence on dynamic reliability after eliminating unimportant variables is investigated. It is found that a bouncing crowd has limited influence on structural frequency regardless of the structural characteristics but may significantly increase the structural damping ratio and its variability. The human body damping ratio and the human body frequency are the main influential parameters for the structural damping ratio in most cases. The structural acceleration responses under crowd bouncing are with large variability, which needs to be considered during the calculation. The mass, frequency, damping ratio of human body, the mass, and the damping ratio of structure are unimportant for acceleration responses in most cases, while the frequency of bouncing activity and structure are important in most cases. The importance of biomechanical load factors heavily depends on the structural frequency and the structural damping ratio. The reliability results only considering the suggested important variables are accurate enough for the engineering practice. [ABSTRACT FROM AUTHOR]

Model‐Based Systems Design (MBSD) formalizes the application of system modeling. However, it is still difficult for designers to implement MBSD in practice. One of the challenges is to make the field of design more unified, as different MBSD methodologies focus on specific areas, and various designers from different areas use ambiguous terms. Moreover, the failure of some products originates in undiscovered couplings of functions in the design stage. Axiomatic Design (AD) provides a scientific foundation for system design. In order to reduce ambiguity and alleviate functional couplings, this paper integrates AD with the MBSD and proposes a unified systems design approach, called Axiomatic Model‐Based Systems Design (A‐MBSD). A‐MBSD uses four pillars: (a) the fundamental framework of AD; (b) the Independence Axiom; (c) a new behavior domain (BD); and (d) an A‐MBSD modeling profile. Finally, the design of a Forest Fire Satellite Monitoring and Control System demonstrates that the proposed approach can improve unity and alleviate the coupling of functions in a system design. [ABSTRACT FROM AUTHOR]

Bouncing, which refers to the up-and-down movement of the human body with both feet remaining on the ground, is one of the most common human-induced dynamic loads for civil structures such as sports stadiums and concert halls. Although researchers have focused on the modeling of bouncing-induced loads, studies on the excitation source (the bouncing person) have not gained much attention. The spring-mass-damper model with a pair of internal biomechanical forces is the simplest model to represent a bouncing person. The model parameters, such as stiffness and damping, though very important for application and for HSI (Human Structure Interaction) analysis, have been rarely reported. This study utilized the particle filter (a step-by-step system identification method) to identify human SMD (Spring-Mass-Damper) model parameters from measured bouncing forces obtained by a wireless insole system. A total of 173 continuous bouncing force signals were recorded and divided into 6800 bouncing cycles, from which the SMD model parameters were identified. The results indicated that human natural frequency and high-order biomechanical load factors have a linear trend against the bouncing frequency, while the damping ratio and first-order BLF (Biomechanical Load Factor) share a parabolic relation. For each model parameter, a skew normal distribution was fitted, and the fitting parameters were found to be dependent on the bouncing frequency range. The influence of HSI on the model parameters was also experimentally investigated, indicating that a vibrating surface leads to a lower human natural frequency and a higher damping ratio value. • Particle filter is used to identify SMD model parameters for a bouncing person. • This is a parameter identification problem with unknown excitation. • Results are given for all recorded bouncing cycles. • The dependence of human system parameters on the bouncing frequency is analyzed. • Influence from human-structure-interaction is experimentally investigated. [ABSTRACT FROM AUTHOR]

The overuse of antibiotics has caused an increased prevalence of drug-resistant bacteria. Bacterial resistance in E. coli is regulated via production of β-lactam-hydrolyzing β-lactamases enzymes. Escherichia coli O104: H4 is a multi-drug resistant strain known to resist β-lactam as well as several other antibiotics. Here, we report a molecular dynamic simulation–combined docking approach to identify, screen, and verify active pharmacophores against enterohemorrhagic Escherichia coli (EHEC). Experimental studies revealed a boronic acid cyclic monomer (BACM), a non-β-lactam compound, to inhibit the growth of E. coli O104: H4. In vitro Kirby Bauer disk diffusion susceptibility testing coupled interaction analysis suggests BACM inhibits E. coli O104:H4 growth by not only inhibiting the β-lactamase pathway but also via direct inhibition of the penicillin-binding protein. These results suggest that BACM could be used as a lead compound to develop potent drugs targeting beta-lactam resistant Gram-negative bacterial strains. Key messages: • An in silico approach was reported to identify pharmacophores against E. coli O104: H4. • In vitro studies revealed a non-β-lactam compound to inhibit the growth of E. coli O104: H4. • This non-β-lactam compound could be used as a lead compound for targeting beta-lactam strains. [ABSTRACT FROM AUTHOR]

Highlights • An augmented Kalman filter estimates dynamic tire forces from vehicle responses. • Smartphones are used to record vehicle body responses. • Numerical examples with observability and sensitivity analysis prove the feasibility of the study. • A field measurement validates the proposed method. Abstract Bridge modal parameters, including modal mass, are important factors that directly affect the bridge responses under various excitations. To identify these parameters, the simultaneous measurement of the bridge excitation and its corresponding bridge responses is typically required. However, traditional methods of exciting a bridge using a hammer or a shaker have the limitations of small impact energy, narrow frequency range, and other site-specific difficulties. However, the vehicle-induced load, which excites the bridge through the vehicle-bridge interaction, can be used in bridge parameter identification if the vehicle-bridge contact force is estimated well. In this paper, an algorithm is proposed to estimate the dynamic components of the vertical tire contact forces by measuring the vehicle body acceleration and angular velocity at selected locations on an ordinary vehicle. A Kalman filter with augmented tire forces in the system state vector is employed. Observability and sensitivity analyses provide the method's theoretical foundation. Numerical examples for different road roughness conditions demonstrate that the proposed algorithm has good accuracy and robustness against noise and modelling error. A commercial light vehicle was used in the conduct of field measurement to validate the proposed method. The estimated dynamic tire forces are in good agreement with reference measurements. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • The acetate production rate with fluidized GAC was 2.8 times that of control. • Fluidized GAC provide a high electrode surface and a favorable mass transport. • Fluidized GAC likely promoted the enrichment of electrochemically active bacteria. • Fluidized GAC electrode is a promising strategy to improve MES efficiency. Abstract The electricity-driven bioreduction of carbon dioxide to multi-carbon organic compounds, particularly acetate, has been achieved in microbial electrosynthesis (MES). MES performance can be limited by the amount of cathode surface area available for biofilm formation and slow substrate mass transfer. Here, a fluidized three-dimensional electrode, containing granular activated carbon (GAC) particles, was constructed via MES. The volumetric acetate production rate increased by 2.8 times through MES with 16 g L−1 GAC (0.14 g L−1 d-1) compared with that of the control (no GAC), and the final acetate concentration reached 3.92 g L−1 within 24 days. Electrochemical, scanning electron microscopy, and microbial community analyses suggested that GAC might improve the performance of MES by accelerating direct and indirect (via H 2) electron transfer because GAC could provide a high electrode surface and a favorable mass transport. This study attempted to improve the efficiency of MES and presented promising opportunities for MES scale-up. [ABSTRACT FROM AUTHOR]

A bridge's natural frequencies are important dynamic properties reflecting the structural condition of the bridge. Numerous studies have been conducted in the field to extract a bridge's natural frequencies from responses of passing vehicles. The bridge frequency peaks are, however, not easily observed, because pavement roughness often influences the spectra of vehicle responses. In this research, a method that extracts the fundamental frequency of a bridge from the responses of an ordinary vehicle with its parameters calibrated in advance is proposed. The method is based on the idea that the vehicle passing across a bridge is excited by two sources, i.e., pavement roughness and bridge vibration. The excitation inputs to the vehicle, i.e., displacement inputs at the front and rear tire locations, are estimated from vehicle responses using a particle filter method. The estimated displacement inputs at the front and rear tires are then subtracted from each other after shifting by a wheel–base distance to eliminate the roughness influence, which commonly appears in both signals. The signal after the subtraction contains only the bridge vibration influence and is used to extract the fundamental frequency of the bridge. This indirect method of bridge frequency extraction is investigated through numerical simulations. A field measurement was also conducted, and it showed that the bridge's fundamental frequency was successfully extracted with a good accuracy for several driving-speed cases. [ABSTRACT FROM AUTHOR]

Background/Aims: This study aims to explore the effects of microRNA-214-5p (miR-214-5p) on the invasion and migration of Hepatocellular Carcinoma cells (HCC). Methods: Hepatocellular Carcinoma tissues and adjacent normal tissues from 44 hepatocellular carcinoma patients were prepared for this study. The HepG2 and BEL-7402 cells were transfected with miR-214-5p mimic and inhibitor. qRT-PCR was performed to detect the expressions of miR-214-5p. Transwell assays were used to detect the invasion and migration assays in HepG2 and BEL-7402 cells. A dual-luciferase reporter assay was conducted to examine the effect of miR-214-5p on Wiskott-Aldrich Syndrome Like (WASL/ N-WASP). Western blot and qRT-PCR were used to measure the expressions of the E-cadherin, N-cadherin and Vimentin proteins. Transwell chamber assays were performed to detect cell invasion and migration. Results: Compared with normal tissues, HCC tissues demonstrated significantly lower expression of miR-214-5p. Overexpression of miR-214-5p significantly inhibited the migration and invasion of HCC cells and inhibition of miR-214-5p promoted the migration and invasion. Additionally, miR-214-5p suppressed the epithelial-mesenchymal transition (EMT). Further study showed WASL was a putative target gene of miR-214-5p. Up-regulating the expression of WASL could reverse the inhibition effect of miR-214-5p on invasion and migration. Conclusion: Our data suggested that miR-214-5p inhibited the invasion and migration of HepG2 and BEL-7402 by targeting WASL in Hepatocellular carcinoma. [ABSTRACT FROM AUTHOR]

Change propagation potentially affects many aspects of a SysML-based system model during the iterative process of Model-Based Systems Engineering (MBSE). However, few authors have addressed the implication of engineering change and its impact. To address having a successful change process, this article analyzes and explicitly represents different scenarios of how a system model is changed from a formal perspective, i.e., how a system model should be changed, and how model elements should be added, deleted or modified in response to design changes. A workflow is introduced to guide the change process taking change propagation into account. Second, change impact relationships among requirements, behaviors, and structures of the system model are formalized by an ontology to make the semantics both human-understandable and machine-readable. Reasoning rules are defined as well in order to improve automation of the change process. Finally, an experiment using a water distiller system showed that the identification of change impact information could help designers complete the change in less time and with higher quality. [ABSTRACT FROM AUTHOR]

The spring-mass-damper (SMD) model with a pair of internal biomechanical forces is the simplest model for a walking pedestrian to represent his/her mechanical properties, and thus can be used in human-structure-interaction analysis in the vertical direction. However, the values of SMD stiffness and damping, though very important, are typically taken as those measured from stationary people due to lack of a parameter identification methods for a walking pedestrian. This study adopts a step-by-step system identification approach known as particle filter to simultaneously identify the stiffness, damping coefficient, and coefficients of the SMD model's biomechanical forces by ground reaction force (GRF) records. After a brief introduction of the SMD model, the proposed identification approach is explained in detail, with a focus on the theory of particle filter and its integration with the SMD model. A numerical example is first provided to verify the feasibility of the proposed approach which is then applied to several experimental GRF records. Identification results demonstrate that natural frequency and the damping ratio of a walking pedestrian are not constant but have a dependence of mean value and distribution on pacing frequency. The mean value first-order coefficient of the biomechanical force, which is expressed by the Fourier series function, also has a linear relationship with pacing frequency. Higher order coefficients do not show a clear relationship with pacing frequency but follow a logarithmic normal distribution. [ABSTRACT FROM AUTHOR]

Passing vehicles cause bridge deformation and vibration. Overloaded vehicles can result in fatigue damage to, or even failure of, the bridge. The bridge response is related to the properties of the passing vehicles, particularly the vehicle weight. Therefore, a bridge weigh-in-motion system for estimating vehicle parameters is important for evaluating the bridge condition under repeated load. However, traditional weigh-in-motion methods, which involve the installation of strain gauges on bridge members and calibration with known weight truck, are often costly and time-consuming. In this paper, a method for the identification of moving vehicle parameters using bridge acceleration responses is investigated. A time-domain method based on the Bayesian theory application of a particle filter is adopted. The bridge pavement roughness is estimated in advance using vehicle responses from a sensor-equipped car with consideration of vehicle-bridge interaction, and it is utilized in the parameter estimation. The method does not require the calibration. Numerical simulations demonstrate that the vehicle parameters, including the vehicle weight, are estimated with high accuracy and robustness against observation noise and modeling error. Finally, this method is validated through field measurement. The resulting estimate of vehicle mass agrees with the measured value, demonstrating the practicality of the proposed method. [ABSTRACT FROM AUTHOR]

• A large-scale renewable energy system is studied, which remedies the lack of existing studies for the study of arc faults in wind and energy storage systems. • A new arc fault detection scheme is proposed based on a time-frequency domain threshold comparison of voltages. • An advanced decomposition algorithm, variational mode decomposition (VMD), is proposed for the feature extraction. • The proposed scheme is demonstrated to be superior and applicable based on two systems of different scales. As the main new energy, the wind-solar-storage hybrid system is widely used because of its excellent complementarity. However, due to the complexity of the system, series DC arc faults are prone to occur. This paper presents a method for series DC arc fault detection and location in wind-solar-storage hybrid system, which works mainly on the principle of threshold comparison in the time-frequency domain. Therein, an algorithm called variational mode decomposition (VMD) is employed. The voltage signal of the identical DC load under different operating conditions is decomposed by VMD, and the time-frequency domain characteristics of the normal operating conditions are used as thresholds. The series DC arc faults in different subsystems are detected and located by comparing the time-frequency domain features under different operating conditions with the threshold features. Compared with classical decomposition algorithms, Empirical Mode Decomposition (EMD) and Wavelet Transform (WT), the results show that VMD can eliminate the influence of noise and extract the fault signals of different systems more accurately, ensuring the precise localization of series DC arc faults. [ABSTRACT FROM AUTHOR]

This work aims to provide a comprehensive in-depth analysis of the life cycle environmental and economic performance of some key global supply chains for torrefied wood pellets (TWP) used as bulk fuel, including their contribution to the bio-economy of the region where they are produced, and the effects of carbon accounting and carbon tax policies on the TWP trade. TWPs produced in British Columbia (BC), the western-most province of Canada, are taken as a specific example, with the results compared with pellets produced in other Canadian provinces, Southeast US and Vietnam. It is found that BC has comparative advantages in TWP production, benefiting from abundant biomass resources, availability of low-carbon electricity, existence of a well-developed forest product industry, and accessibility to international markets. The suitability of different domestic and overseas markets is assessed. In Canada, there is great potential demand for BC TWPs in the provinces of Alberta and Saskatchewan. In the Asia-Pacific region and Europe, BC pellets are not cost-competitive compared with pellets from Vietnam and Southeast US, due to higher production costs arising in part from BC's high carbon tax. However, BC producers have supply advantages over producers in Vietnam and the Southeast US in the province's abundant biomass and clean electricity supply. Transforming production from conventional to torrefied pellets can increase the contribution of the industry to the regional economy. The carbon accounting and carbon tax policies in different countries/regions will impact the TWP trade, and merit further study. • Several key global torrefied wood pellet (TWP) supply chains are compared. • BC has comparative advantages in TWP production compared with other Canadian provinces. • The domestic overseas markets of BC TWPs are identified. • The contributions of TWP to the regional bio-economy are identified. • The effects of carbon accounting and carbon tax policies on TWP trade are discussed. [ABSTRACT FROM AUTHOR]

This paper presents a modified half-sine-squared load model of the jumping impulses for a single person. The model is based on a database of 22,921 experimentally measured single jumping load cycles from 100 test subjects. Threedimensional motion capture technology in conjunction with force plates was employed in the experiment to record jumping loads. The variation range and probability distribution of the controlling parameters for the load model such as the impact factor, jumping frequency and contact ratio, are discussed using the experimental data. Correlation relationships between the three parameters are investigated. The contact ratio and jumping frequency are identified as independent model parameters, and an empirical frequency-dependent function is derived for the impact factor. The feasibility of the proposed load model is established by comparing the simulated load curves with measured ones, and by comparing the acceleration responses of a single-degree-of-freedom system to the simulated and measured jumping loads. The results show that a realistic individual jumping load can be generated by the proposed method. This can then be used to assess the dynamic response of assembly structures. [ABSTRACT FROM AUTHOR]

• A KF-based method is adopted to extract 191 vehicle-induced modal loads from a real bridge during its operation. • The extracted loads are used to propose a response spectrum model for the vibration design under vehicle dynamic excitation. • Factors affecting the shape and value of the response spectrum model are analyzed and considered. • The proposed model is validated in a field test. The load exerted from passing vehicles is a combination of the static moving load and dynamic load owing to the uneven bridge deck, which leads to bridge vibration. Vehicle-induced bridge vibration has a negative influence on many aspects, including driving safety and pedestrian comfort. Therefore, an efficient and accurate approach to predict bridge vibration due to the passage of vehicles is needed in the design stage. In this study, a response spectrum model is proposed to predict the bridge root-mean-square (RMS) acceleration response caused by a single-vehicle passage. The vehicle dynamic loads were extracted from a field test by employing a Kalman filter-based method. The extracted vehicle dynamic loads were then used to derive a mathematical model of the vehicle-induced loads. The proposed response spectrum model consisted of four parts: 0–2 Hz, 2–5 Hz, 5–7 Hz, and 7 Hz. A mathematical representation of each part was provided for different confidence levels. Additionally, the pavement roughness, mode shapes, and driving speeds affecting the shape of the design spectrum are discussed, and modification factors are suggested. Moreover, the procedure for applying the proposed response model for bridge vibration prediction under a vehicle passage is presented. The validation from field tests shows that the proposed method has decent applicability for the prediction of bridge vibration levels induced by passing vehicles. [ABSTRACT FROM AUTHOR]

The correct affiliations are listed below: Affiliation 1: Department of Breast Center, The Fourth Hospital of Hebei Medical University, 169 Tianshan Street, Shijiazhuang, Hebei 050011, People's Republic of China Affiliation 2: Gland Surgery, Shijiazhuang People's Hospital, Shijiazhuang, People's Republic of China Furthermore, Affiliation 1 was omitted for Wenshan Zhang. Correction to: I Scientific Reports i https://doi.org/10.1038/s41598-022-05486-3, published online 07 February 2022 In the original version of this Article, Affiliation 1 and 2 were not listed in the correct order. [Extracted from the article]

Symbiotic integration of agricultural activities is widespread but quantitative assessments of the environmental benefits are scarce. To explore the potential benefits of applying the industrial symbiosis approach in agriculture and horticulture, a detailed case study is reported of a potential Eco-Industrial Park (EIP) including three activities: dairy farming, greenhouse cultivation of vegetables, and mushroom growing. These activities are widespread world-wide but, to enable quantitative assessment, the specific EIP studied is located in the Canadian province of British Columbia (BC). The activities are linked by anaerobic digestion of dairy manure to produce biogas and digestate. Biogas replaces natural gas to supply heat to the farms and carbon dioxide (CO 2) to the greenhouse. Digestate is separated into a liquid fertilizer and a solid substrate; the former replaces chemical fertilizers and the latter can be utilized as cow bedding and growing medium for plants and mushrooms. Mushroom growing emits CO 2 which is conventionally ventilated but can be used for stimulating plant growth in the greenhouse. Life Cycle Assessment (LCA) is used to quantify the environmental benefits of the EIP compared to conventional independent farms. Non-renewable energy consumption, greenhouse gas emissions, aquatic acidification, respiratory effects from organic emissions, and human toxicity can be reduced by 50%–90% and aquatic eutrophication and respiratory effects from inorganic emissions can be reduced by more than 10%. Such EIPs can also alleviate nutrient management problems in regions with intensive livestock farming. • An LCA model of EIP linking AD of dairy manure, greenhouse and mushroom operations. • Exchange of by-products enhances energy and material self-sufficiency. • Digestate utilisation within the EIP improves nutrient management. • Reductions of ∼60% achievable in non-renewable energy use and global warming potential. • Reductions of 10%–90% achievable across five other life cycle impact categories. [ABSTRACT FROM AUTHOR]

The synchronization factor is an index to evaluate the level of consistency for crowd motion under rhythmic guidance, which is important for crowd load modeling as well as structural vibration monitoring. Most of the existing synchronization factors were defined based on the time history of the crowd movement over a long period of time, failing to consider the time-dependent characteristics of intra-subject variability. Moreover, these factors were generally based on the data that can only be measured under laboratory conditions, making them difficult to be applied on the monitoring of structures subjected to crowd excitation in real engineering practice. In this regard, this paper proposed a novel time-dependent synchronization factor for a crowd in rhythmic motion. By using multiple object tracking technology, the head movements of each person in the crowd were measured as the basis for calculating the newly proposed time-dependent synchronization factor, which is defined as the ratio between a representative value of the crowd movement time history and the average of the same values for each person in the crowd. A series of experiments were organized to study the characteristics and the applicability of the synchronization factor, whose relation with structural responses was clearly observed in the laboratory experiments as well as in a real structure. The results demonstrated that the newly proposed time-dependent synchronization factor is effective when applied on the intelligent operation and maintenance of the engineering structures. • A time-dependent synchronization factor describing the crowd rhythmic motion was first defined. • The algorithms for crowd head detection and crowd head tracking were trained and proposed. • The properties of the time-dependent synchronization factors for crowd motion were studied from an experimental test. • The relation between the factor and the structural responses was found through laboratory tests. • The feasibility of using the proposed factor for intelligent monitoring was tested in a real sport grandstand. [ABSTRACT FROM AUTHOR]

The Chinese urban regeneration movement underscores a "people-oriented" paradigm, aimed at addressing urban challenges stemming from rapid prior urbanization, while striving for high-quality and sustainable urban development. At the community level, fostering quality through a socially sustainable perspective (SSP) is a pivotal strategy for people-oriented urban regeneration. Nonetheless, explorations of community quality assessments grounded in an SSP have been notably scarce in recent scholarly discourse. This study pioneers a multidimensional quantitative model (MQM) for gauging community quality, leveraging diverse geospatial data sources from the SSP framework. The MQM introduces an evaluative framework with "Patency, Convenience, Comfort, and Safety" as primary indicators, integrating multi-sourced data encompassing the area of interest (AOI), Point of Interest (POI), Weibo check-ins, and Dianping data. The model's efficacy is demonstrated through a case study in the Gusu district, Suzhou. Furthermore, semantic analysis of the Gusu district's street view photos validates the MQM results. Our findings reveal the following: (1) AI-based semantic analysis accurately verifies the validity of MQM-generated community quality measurements, establishing its robust applicability with multi-sourced geospatial data; (2) the community quality distribution in Gusu district is notably correlated with the urban fabric, exhibiting lower quality within the ancient town area and higher quality outside it; and (3) communities of varying quality coexist spatially, with high- and low-quality communities overlapping in the same regions. This research pioneers a systematic, holistic methodology for quantitatively measuring community quality, laying the groundwork for informed urban regeneration policies, planning, and place making. The MQM, fortified by multi-sourced geospatial data and AI-based semantic analysis, offers a rigorous foundation for assessing community quality, thereby guiding socially sustainable regeneration initiatives and decision making at the community scale. [ABSTRACT FROM AUTHOR]

In accordance with the actual production circumstances of enterprises, a scheduling problem model is designed for open-shop environments, considering AGV transport time. A Q-learning-based method is proposed for the resolution of such problems. Based on the characteristics of the problem, a hybrid encoding approach combining process encoding and AGV encoding is applied. Three pairs of actions are constituted to form the action space. Decay factors and a greedy strategy are utilized to perturb the decision-making of the intelligent agent, preventing it from falling into local optima while simultaneously facilitating extensive exploration of the solution space. Finally, the proposed method proved to be effective in solving the open-shop scheduling problem considering AGV transport time through multiple comparative experiments. [ABSTRACT FROM AUTHOR]

Microbial electrosynthesis (MES) is an electrochemical reduction technology that converts carbon dioxide (CO 2) efficiently into chemicals by electrically driving microorganisms attached to electrodes. However, due to the limited solubility of CO 2 and hydrogen (H 2), low mass transfer efficiency affects the performance of MES. In this study, fillers were introduced into the MES system and combined with a vertical or horizontal cathode. Through the barrier and shearing effect of fillers, it realized the reduction of bubbles volume, the increase of gas residence time and the optimization of mass transfer rate, thereby providing a sufficient substrate supply for the biocatalyst. The results showed that MES with horizontal cathode and 4 series of fillers generated the highest acetate production rate (0.18 gL−1 day−1), which was 1.6 times that of the control group. Furthermore, the acetate concentration reached 5.28 ± 0.2 g L−1 within 30 days. Scanning electron microscope and microbial community analyses showed that the filler was beneficial to the growth of biofilm on cathodes and fillers, and improved the enrichment of Acetobacterium. The presence of fillers significantly enhanced the performance of MES and demonstrated the potential as a new and simple strategy for the MES reactor improvement. [Display omitted] • Fillers provided the barrier and shearing effect for MES. • The placement of different electrodes further improved the shearing performance. • Fillers realized the reduction of bubbles volume, the increase of gas residence time. • Fillers provided a sufficient substrate supply for the biocatalyst. • The acetate production rate of 4 fillers-horizontal cathode increased by 1.6 times. [ABSTRACT FROM AUTHOR]

Background: Microbial electrosynthesis (MES) is a biocathode-driven process, in which electroautotrophic microorganisms can directly uptake electrons or indirectly via H2 from the cathode as energy sources and CO2 as only carbon source to produce chemicals. Results: This study demonstrates that a hydrogen evolution reaction (HER) catalyst can enhance MES performance. An active HER electrocatalyst molybdenum carbide (Mo2C)-modified electrode was constructed for MES. The volumetric acetate production rate of MES with 12 mg cm−2 Mo2C was 0.19 ± 0.02 g L−1 day−1, which was 2.1 times higher than that of the control. The final acetate concentration reached 5.72 ± 0.6 g L−1 within 30 days, and coulombic efficiencies of 64 ± 0.7% were yielded. Furthermore, electrochemical study, scanning electron microscopy, and microbial community analyses suggested that Mo2C can accelerate the release of hydrogen, promote the formation of biofilms and regulate the mixed microbial flora. Conclusion: Coupling a HER catalyst to a cathode of MES system is a promising strategy for improving MES efficiency. [ABSTRACT FROM AUTHOR]

Flexible job shops motivated by small batches and multiple orders require the collaboration of machines and automated guided vehicles (AGVs) scheduling to boost shop floor flexibility and productivity. The joint scheduling of machines and AGVs can better achieve global optimization. However, joint scheduling requires two NP hard problems to be solved simultaneously. Therefore, this paper employs a multi-AGV flexible job shop scheduling problem (MA-FJSP) with an effective hybrid algorithm. First of all, a model is established with the objectives of minimizing the makespan, the total AGV running time and the total machine load. To solve the MA-FJSP, high-quality initialization methods and improved elite strategies are designed to improve global convergence in the proposed algorithm. In addition, a problem-knowledge-based neighborhood search is integrated to improve its exploitation capability. At last, a series of comparative experimental studies were performed to exam the effectiveness of the improved algorithm. The results demonstrate that the solutions gained by the proposed algorithm perform well in respect of convergence, diversity and distribution. [ABSTRACT FROM AUTHOR]

Patterned diamond-like carbon (DLC) coatings were deposited on a Si (100) substrate using the filtered cathodic vacuum arc technique. The effects of the patterning and of the coating thickness on tribological behavior of DLC coating were investigated using a ball-on-disk tribometer under dry and oil-lubrication conditions. The results suggest that 1 mm2 patterned structures delimited by 100-μm grooves can enhance the tribological properties. The coefficients of friction of the tested patterned films were 0.123 and 0.067 under dry and oil lubrication conditions, respectively, 10% and 21% lower than the coefficients of friction of the continuous DLC films with the same thickness. Raman spectroscopy measurements showed graphitized wear particles for both the continuous and patterned DLC films, but the debris of patterned DLC films having a greater degree of graphitization under dry sliding. The grooves of the patterned coatings could serve as a lubricant reservoir and trap the wear debris, which was beneficial for the tribological properties. The effect of the thickness of the patterned DLC films on their tribology behavior was also investigated. The 0.4-μm-thick patterned samples exhibited the lowest coefficients of friction of 0.105 and 0.058 under dry and oil lubrication conditions, respectively, while the 0.8-μm-thick patterned samples showed the lowest specific wear rate. In addition, the coefficients of friction of the patterned samples increased with an increase in the film thickness under oil lubrication conditions. • Patterned diamond-like carbon coatings were deposited on a Si substrate. • Patterned film showed lower coefficient of friction than continuous films. • The patterned structure could trap the wear debris and reserve the lubricant. • The 0.4-μm-thick patterned samples exhibited the lowest coefficients. [ABSTRACT FROM AUTHOR]

• RVE for thermoplastic composites is developed considering the elastic–plastic behavior of matrix material. • Cohesive zone model is applied to study the effect of interface debonding. • Randomness of micro-structural configuration changes the failure process of thermoplastic composites. Based on the multi-scale progressive homogenization theory, a micromechanical model is proposed that can predict the plastic deformation of thermoplastic fiber-reinforced composites. By developing microscopic representative volume elements (RVEs) that include three materials phases: fiber, matrix and fiber–matrix interface, the effect of elastic–plastic material behaviors and interface debonding on the mechanical properties of thermoplastic composites can be considered. Employing this model, the deformation and failure process of carbon fiber reinforced PEEK composite is studied, considering the effects of random size and distribution of carbon fiber, as well as the ratio of interface debonding. It can be found that the yielding strength is most sensitive to the proportion of interface debonding compared to Young's modulus and ultimate strength. Interface debonding has the most significant impact on the mechanical performances of thermoplastic composites by introducing a higher degree of plastic deformation into the polymer matrix and changing the evolution path of material damage. [ABSTRACT FROM AUTHOR]

Integrated process planning and scheduling (IPPS) is important for modern manufacturing companies to achieve manufacturing efficiency and improve resource utilization. Meanwhile, multiple objectives need to be considered in the realistic decision-making process for manufacturing systems. Based on the above realistic manufacturing system requirements, it becomes increasingly important to develop effective methods to deal with multi-objective IPPS problems. Therefore, an improved NSGA-II (INSGA-II) algorithm is proposed in this research, which uses the fast non-dominated ranking method for multiple optimization objectives as an assignment scheme for fitness. A multi-layer integrated coding method is adopted to address the characteristics of the integrated optimization model, which involves many optimization parameters and interactions. Elite and mutation strategies are employed during the evolutionary process to enhance population diversity and the quality of solutions. An external archive is also used to store and update the Pareto solution. The experimental results on the Kim test set demonstrate the effectiveness of the proposed INSGA-II algorithm. [ABSTRACT FROM AUTHOR]

Clarifying the pattern of the urban greenhouse gas (GHG) budget and its influencing factors is the basis of promoting urban low-carbon development. This paper takes Beijing and Shenzhen—the capital city and the most rapidly developing city in China, respectively—as case studies, comprehensively accounts their GHG budgets from 2005 to 2020, and investigates and compares the factors affecting their GHG budgets. The total GHG emissions in Beijing were lowest in 2005 (160.3 TgCO2 equivalents) and peaked at 227.7 TgCO2 equivalents in 2019, and then decreased to 209.1 TgCO2 equivalents in 2020. Meanwhile, the total GHG emissions in Shenzhen gradually increased from 36.0 TgCO2 equivalents in 2005 to 121.4 TgCO2 equivalents in 2019, and then decreased to 119.1 TgCO2 equivalents in 2020. The energy activity sector was the greatest contributor to GHG emissions in this period, accounting for 82.5% and 76.0% of the total GHG emissions in Beijing and Shenzhen, respectively. The carbon sink of the ecosystems of these two cities could absorb only small parts of their emissions, and the neutralization rates of sinks ranged from 1.7% to 2.3% in Beijing and from 0.3% to 1.5% in Shenzhen. The enhancement of population, economic product, and consumption increased the greenhouse gas emissions in both cities. A 1% increase in population size, per capita GD (gross domestic product), and residential consumption level would increase total GHG emissions by 0.181%, 0.019%, and 0.030% in Beijing, respectively. The corresponding increases in Shenzhen would be 0.180%, 0.243%, and 0.172%, respectively. The household size had opposite effects on the two cities, i.e., a 1% increase in household size would increase GHG emissions by 0.487% in Shenzhen but reduce them by 2.083% in Beijing. Each 1% increase in secondary industry and energy intensity would reduce GHG emissions by 0.553% and 0.110% in Shenzhen, respectively, which are more significant reductions than those in Beijing. [ABSTRACT FROM AUTHOR]

With the completion of the draft assembly of the giant panda genome sequence, RNA sequencing technology has been widely used in genetic research on giant pandas. We used RNA‐seq to examine black and white hair follicle samples from adult pandas. By comparison with the giant panda genome, 75 963 SNP loci were labeled, 2426 differentially expressed genes (DEGs) were identified, and 2029 new genes were discovered, among which 631 were functionally annotated. A cluster analysis of the DEGs showed that they were mainly related to the Wnt signaling pathway, ECM–receptor interaction, the p53 signaling pathway, and ribosome processing. The enrichment results showed that there were significant differences in the regulatory networks of hair follicles with different colors during the transitional stage of hair follicle resting growth, which may play a regulatory role in melanin synthesis during growth. In conclusion, our results provide new insights and more data support for research on the color formation in giant pandas. [ABSTRACT FROM AUTHOR]

During the perinatal period, the bovine mammary epithelial cells of dairy cows exhibit vigorous metabolism and produce large amounts of reactive oxygen species (ROS). The resulting redox balance disruption leads to oxidative stress, one of the main causes of mastitis. Puerarin (PUE) is a natural flavonoid in the root of PUE that has attracted extensive attention as a potential antioxidant. This study first investigated whether PUE could reduce oxidative damage and mastitis induced by hydrogen peroxide (H2O2) in bovine mammary epithelial cells in vitro and elucidated the molecular mechanism. In vitro, BMECs (Bovine mammary epithelial cells) were divided into four treatment groups: Control group (no treatment), H2O2 group (H2O2 stimulation), PUE + H2O2 group (H2O2 stimulation before PUE rescue) and PUE group (positive control). The growth of BMECs in each group was observed, and oxidative stress-related indices were detected. Fluorescence quantitative PCR (qRT–PCR) was used to detect the expression of tightly linked genes, antioxidant genes, and inflammatory factors. The expression of p65 protein was detected by Western blot. In vivo, twenty cows with an average age of 5 years having given birth three times were divided into the normal dairy cow group, normal dairy cow group fed PUE, mastitis dairy cow group fed PUE, and mastitis dairy cow group fed PUE (n = 5). The contents of TNF-α, IL-6, and IL-1β in milk and serum were detected. In BMECs, the results showed that the PUE treatment increased the activities of glutathione (GSH), superoxide dismutase (SOD), catalase (CAT), and total antioxidant capacity (T-AOC); ROS and malondialdehyde (MDA) levels were reduced. Thus, PUE alleviated H2O2-induced oxidative stress in vitro. In addition, the PUE treatment eliminated the inhibition of H2O2 on the expression of oxidation genes and tight junction genes, and the enrichment degree of NRF-2, HO-1, xCT, and tight junctions (claudin4, occludin, ZO-1 and symplekin) increased. The PUE treatment also inhibited the expression of NF-κB-associated inflammatory factors (IL-6 and IL-8) and the chemokine CCL5 in H2O2-induced BMECs. In vivo experiments also confirmed that feeding PUE can reduce the expression of inflammatory factors in the milk and serum of lactating dairy cows. In conclusion, PUE can effectively reduce the oxidative stress of bovine mammary epithelial cells, enhance the tight junctions between cells, and play an anti-inflammatory role. This study provides a theoretical basis for PUE prevention and treatment of mastitis and oxidative stress. The use of PUE should be considered as a feed additive in future dairy farming. [ABSTRACT FROM AUTHOR]

In the context of increasing urbanization and worsening environmental pollution, nonpoint source pollution during high-frequency rainfall has become a major ecological problem that endangers residents in cities. This study takes Shenzhen as an example. On the basis of a large number of soil sample test data, and combined with relevant environmental variables, it has drawn the high-resolution, high-precision spatial distribution maps of soil attributes within the city. In addition, this paper combines the revised universal soil loss equation and the GeoDetector model to evaluate the supply capacity of nonpoint source reduction services in the city's ecological space and the main driving factors of spatial distribution characteristics for different types of land. The study found that increasing soil point density and combining environmental variables can help improve the accuracy of spatial mapping for soil attributes. The ME, MSE, ASE, RMSE, and RMSSE of spatial mapping all meet the accuracy evaluation criteria and are better than many existing studies; the spatial distribution characteristics of soil attributes and nonpoint source reduction services show significant differences among the whole city, secondary administrative regions, and different types of land; the GeoDetector results show that among the three main types of land use (forested land, industrial land, and street town residential land), topographic factors, habitat-quality factors, and ecosystem types have the greatest impact on the spatial differentiation characteristics of nonpoint source reduction services. Among climate factors, only precipitation factors have the greatest impact on the spatial differentiation characteristics of services. Facing the above factors, the q-values calculated by the GeoDetector are all higher than 10%. The results of this study can provide information for making better decisions on regional ecological system management and soil protection and on restoration work aimed at improving nonpoint source reduction services. [ABSTRACT FROM AUTHOR]

The pituitary gland is a key participant in the hypothalamic–pituitary–gonadal axis, as it secretes a variety of hormones and plays an important role in mammalian reproduction. Gonadotrophin-releasing hormone(GnRH) signaling molecules can bind to GnRH receptors on the surfaces of adenohypophysis gonadotropin cells and regulate the expression of follicle-stimulating hormone(FSH) and luteinizing hormone(LH) through various pathways. An increasing number of studies have shown that noncoding RNAs mediate the regulation of GnRH signaling molecules in the adenohypophysis. However, the expression changes and underlying mechanisms of genes and noncoding RNAs in the adenohypophysis under the action of GnRH remain unclear. In the present study, we performed RNA sequencing (RNA-seq) of the rat adenohypophysis before and after GnRH treatment to identify differentially expressed mRNAs, lncRNAs, and miRNAs. We found 385 mRNAs, 704 lncRNAs, and 20 miRNAs that were significantly differentially expressed in the rat adenohypophysis. Then, we used a software to predict the regulatory roles of lncRNAs as molecular sponges that compete with mRNAs to bind miRNAs, and construct a GnRH-mediated ceRNA regulatory network. Finally, we enriched the differentially expressed mRNAs, lncRNA target genes, and ceRNA regulatory networks to analyze their potential roles. Based on the sequencing results, we verified that GnRH could affect FSH synthesis and secretion by promoting the competitive binding of lncRNA-m23b to miR-23b-3p to regulate the expression of Calcium/Calmodulin Dependent Protein Kinase II Delta(CAMK2D). Our findings provide strong data to support exploration of the physiological processes in the rat adenohypophysis under the action of GnRH. Furthermore, our profile of lncRNA expression in the rat adenohypophysis provides a theoretical basis for research on the roles of lncRNAs in the adenohypophysis. [ABSTRACT FROM AUTHOR]

Methane (CH4) microseepage from petroleum basins is a significant contributor to the atmospheric CH4 budget. However, research about CH4 migration and release mechanism is still very limited. This work seeks to theorize and verify the migration and release mechanism of CH4 microseepage via field measurement and physical simulation, which, to the best of our knowledge, has not been reported in literature. Fluxes of CH4 microseepage from Dawanqi oilfield were measured, and three manifestations of release were observed, namely, continuous, flat, and episodic. Based on field observations, bench-scale physical simulation of CH4 migration through geological features of the oilfield was further conducted for 290 days. The results show that CH4 migration is mainly driven by buoyancy and diffusion. In continuous release, CH4 migration is mainly driven by buoyancy. In flat release, CH4 migration is dominated by diffusion. At low pressure, CH4 migrates upward slowly. As buoyancy increases, CH4 eventually break through the capillary pressure of the pore throat, causing spikes in CH4 concentrations in the layers above and reproducing episodic release observed during field measurement. Via field observation and verification by physical simulation, this work theorizes the migration mechanism of CH4 microseepage and its correlation with release types observed and confirms that counterbalance of buoyancy force and capillary pressure plays a critical role in episodic release of CH4 from oilfield. The findings of this study shed light on the migration mechanism and release manifestations of CH4 microseepage under different geological conditions and improve accuracy of estimating the flux of CH4 microseepage into atmosphere. [ABSTRACT FROM AUTHOR]

Human-robot collaboration (HRC) combines the robot's mechanical properties and predictability with human experience, logical thinking, and strain capabilities to alleviate production efficiency. However, ensuring the safety of the HRC process in-real time has become an urgent issue. Digital twin extends functions of virtual models in the design phase of the physical counterpart in the production phase through virtual-real interactive feedback, data fusion analysis, advanced computational features, etc. This paper proposes an HRC safety control framework and corresponding method based on the digital twin. In the design phase, virtual simulation and virtual reality technology are integrated to construct virtual twins of various HRC scenarios for testing and analyzing potential safety hazards. In the production phase, the safety distance between humans and robots of the HRC scene is monitored and calculated by an iterative algorithm according to machine vision and a convolutional neural network. Finally, the virtual twin is driven based on real-scene data, real-time online visual monitoring, and optimization of the HRC's overall process. A case study using ABB-IRB1600 is presented to verify the feasibility of the proposed approach. [ABSTRACT FROM AUTHOR]

The distributed manufacturing mode is an important paradigm of networked development in the context of globalization. The integration of process planning and shop scheduling in distributed discrete manufacturing system can fully use the production system's flexibility, which is helpful to further enhance the anti-risk ability of enterprises, improve production efficiency, and reduce production costs. This paper established the mathematical model of the distributed integrated process planning and scheduling (DIPPS) in heterogeneous manufacturing environment and designed a high-dimensional integrated encoding to deal with the coupling problem of multiple sub-problems of the DIPPS. Based on this encoding method, an improved genetic algorithm (IGA) is proposed to solve the DIPPS problem. According to the characteristics of the DIPPS, a hierarchical crossover operator with three sub-crossover operations is designed to expand the search dimension of the IGA. The mutation operators are planned to maintain population variety. Finally, five sets of experiments are planned to test the viability of the suggested approach for resolving the DIPPS problem. The outcomes demonstrate that the IGA algorithm outperforms competing algorithms in various scale jobs and factories. [ABSTRACT FROM AUTHOR]