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The arginine-vasopressin (AVP) hormone plays a pivotal role in regulating various physiological processes, such as hormone secretion, cardiovascular modulation, and social behavior. Recent studies have highlighted the V1a receptor as a promising therapeutic target. In-depth insights into V1a receptor-related pathologies, attained through in vivo imaging and quantification in both peripheral organs and the central nervous system (CNS), could significantly advance the development of effective V1a inhibitors. To address this need, we develop a novel V1a-targeted positron emission tomography (PET) ligand, [18F]V1A-2303 ([18F]8), which demonstrates favorable in vitro binding affinity and selectivity for the V1a receptor. Specific tracer binding in peripheral tissues was also confirmed through rigorous cell uptake studies, autoradiography, biodistribution assessments. Furthermore, [18F]8 was employed in PET imaging and arterial blood sampling studies in healthy rhesus monkeys to assess its brain permeability and specificity, whole-body distribution, and kinetic properties. Our research indicated [18F]8 as a valuable tool for noninvasively studying V1a receptors in peripheral organs, and as a foundational element for the development of next-generation, brain-penetrant ligands specifically designed for the CNS.

Previously, we reported that α-synuclein (α-syn) clusters synaptic vesicles (SV) Diao et al., 2013, and neutral phospholipid lysophosphatidylcholine (LPC) can mediate this clustering Lai et al., 2023. Meanwhile, post-translational modifications (PTMs) of α-syn such as acetylation and phosphorylation play important yet distinct roles in regulating α-syn conformation, membrane binding, and amyloid aggregation. However, how PTMs regulate α-syn function in presynaptic terminals remains unclear. Here, based on our previous findings, we further demonstrate that N-terminal acetylation, which occurs under physiological conditions and is irreversible in mammalian cells, significantly enhances the functional activity of α-syn in clustering SVs. Mechanistic studies reveal that this enhancement is caused by the N-acetylation-promoted insertion of α-syn’s N-terminus and increased intermolecular interactions on the LPC-containing membrane. N-acetylation in our work is shown to fine-tune the interaction between α-syn and LPC, mediating α-syn’s role in synaptic vesicle clustering.

Student dormitories play a pivotal role in the daily lives of university students in China, significantly influencing their academic, residential, and developmental experiences. However, there is a lack of a standardized framework to evaluate the service quality of these dormitories. This study aimed to develop a customized service quality evaluation index system specifically for Chinese university dormitories. The Delphi method and Analytic Hierarchy Process (AHP) were employed, involving 15 experts from Chinese universities. Two rounds of expert deliberation were conducted, starting with 28 initial indicators. The expert consultations resulted in the identification of six primary and 23 secondary indicators that form the service quality evaluation system. This framework is tailored to the specific needs of Chinese university dormitories and provides a solid technical foundation for future evaluations. It is expected to contribute to the improvement of dormitory management practices across China.

Abstract Background Hypoxia/reoxygenation (H/R) induces cardiomyocyte ferroptosis, a core remodeling event in myocardial ischemia/reperfusion injury. Methyltransferase-like 14 (METTL14) emerges as a writer of N6-methyladenosine (m6A) modification. This study was conducted to decipher the role of METTL14 in H/R-induced cardiomyocyte ferroptosis. Methods Mouse cardiomyocytes HL-1 were cultured and underwent H/R treatment. The degree of ferroptosis after H/R treatment was appraised by the cell counting kit-8 assay, assay kits (ROS/GSH/Fe2+), and Western blotting (GPX4/ACSL4). The intracellular expressions of METTL14, pri-miR-146a-5p, miR-146a-5p, or adaptor protein phosphotyrosine interacting with PH domain and leucine zipper 1 (APPL1) were examined by real-time quantitative polymerase chain reaction or Western blotting, with m6A quantification analysis and RNA immunoprecipitation to determine the total m6A level and the expression of pri-miR-146a-5p bound to DiGeorge critical region 8 (DGCR8) and m6A-modified pri-miR-146a-5p. The binding of miR-146a-5p to APPL1 was testified by the dual-luciferase assay. Results H/R treatment induced cardiomyocyte ferroptosis (increased ROS, Fe2+, and ACSL4 and decreased GSH and GPX4) and upregulated METTL14 expression. METTL14 knockdown attenuated H/R-induced cardiomyocyte ferroptosis. METTL14 induced the recognition of pri-miR-146a-5p by DGCR8 by increasing m6A modification on pri-miR-146a-5p, which promoted the conversion of pri-miR-146a-5p into miR-146a-5p and further repressed APPL1 transcription. miR-146a-5p upregulation or APPL1 downregulation limited the inhibitory effect of METTL14 downregulation on H/R-induced cardiomyocyte ferroptosis. Conclusion METTL14 promoted miR-146a-5p expression through the recognition and processing of pri-miR-146a-5p by DGCR8, which repressed APPL1 transcription and triggered H/R-induced cardiomyocyte ferroptosis.

Intuitionistic linguistic numbers (ILNs) describe expert evaluation information by representing semantic assessment values and reflecting the confidence level and hesitation of decision-makers. ILNs are widely used to handle uncertain and incomplete information. The Evaluation Based on Distance from Average Solution (EDAS) method selects the optimal solution based on the distance of each alternative from the average solution, making it suitable for multi-attribute decision-making with conflicting attributes. This study proposes a new scoring function for ILNs and develops an evaluation method combining ILNs with EDAS (IL-EDAS). Experts’ evaluations of each alternative’s indices are expressed using ILNs, and the EDAS method ranks the alternatives to select the optimal solution. We apply this method to assess innovation and entrepreneurship education capabilities in universities, and compare the results with those from other methods to verify their applicability and practicality.

Real-time semantic segmentation is a challenging task in computer vision, especially in complex scenes. In this study, a novel three-branch semantic segmentation model is designed, aiming to effectively use boundary information to improve the accuracy of semantic segmentation. The proposed model introduces the concept of containment control in a pioneering way, which treats image interior elements as well as image boundary elements as followers and leaders in containment control, respectively. Based on this, we utilize two learnable feature fusion matrices in the high-level semantic information stage of the model to quantify the fusion process of internal and boundary features. Further, we design a dedicated loss function to update the parameters of the feature fusion matrices based on the criterion of containment control, which enables fine-grained communication between target features. In addition, our model incorporates a Feature Enhancement Unit (FEU) to tackle the challenge of maximizing the utility of multi-scale features essential for semantic segmentation tasks through the meticulous reconstruction of these features. The proposed model proves effective on the publicly available Cityscapes and CamVid datasets, achieving a trade-off between effectiveness and speed.

Understanding the factors that shape the diversity, distribution, and function of denitrifying microbes is vital for managing nitrogen cycling in these ecosystems. This study explores the diversity, biogeographic distribution, assembly processes, interaction, and denitrification potential of the nirS-encoding microbial community (nirS denitrifier) in the Pearl River Estuary based on high-throughput and metagenomics sequencing dataset. The results of this study show that salinity is a crucial regulatory environmental factor that determines the spatial distribution, phylogenetic turnover, and co-occurrence patterns of nirS denitrifiers. Additionally, the dissolved organic carbon (DOC), suspended sediment concentration (SSC), and dissolved oxygen (DO) in water also significantly impact the biodiversity and abundance of nirS denitrifiers. Furthermore, our findings demonstrate that, in comparison to environmental factors, the ecological and evolutionary characteristics of nirS denitrifiers play a more prominent role in regulating their denitrification potential, suggesting that alterations in the microbial community within dynamic changes in estuarine water can profoundly affect its denitrification function. Our results indicate the significant roles of denitrification microbial structure and phylogenetic characteristics in maintaining their ecological functions. Future studies should continue to explore the interactions between microbial communities and environmental factors to further elucidate the denitrification process in estuaries and its implications for ecosystem health and water quality.

(1) Background: With the rapid development of cloud computing, large AI models, and other emerging technologies, the issue of heat dissipation in data centers has become increasingly prominent. This issue is often caused by inappropriate temperature distribution when using cold air to cool servers. Improving temperature distribution is key to optimizing the thermal performance of data centers. Previous solutions do not include installing adjustable underfloor deflectors under a raised floor while adjusting the aperture ratio of the floor grille and replacing the side of the floor grille located near the air-conditioning unit with a fan floor. (2) Methods: A 3D model of a data center was established, and its meshing and boundary conditions were set. The airflow inside the data center was analyzed using a CFD simulation to assess the temperature distribution resulting from two proposed solutions. (3) Results: Simulations and analyses showed that both options balanced the airflow close to and away from the conditioned side cabinets. This maximized the cooling capacity and improved temperature uniformity. The maximum temperature drop registered for the average cabinet’s out temperature was 2.81 °C. And by installing an adjustable underfloor deflector under the floor grille in rows O and N and adjusting the grille opening, the airflow to the cabinet near the air-conditioned side increased by 18.1%, and the airflow away from the air-conditioned side decreased by 5.1%. Similarly, replacing the Q-row floor grille with a fan floor resulted in a 4.9% increase in airflow to the cabinet near the air-conditioning side and a 3.8% decrease in airflow to the cabinet away from the air-conditioning side. (4) Conclusions: Airflow is a crucial factor that affects cabinet temperature. And balancing airflow between the front-end and rear-end cabinets is essential to make the best use of the cooling capacity and improve temperature distribution within data-center cabinets. This can be achieved by installing a fan floor and an underfloor deflector device in front of high-temperature cabinets located near air-conditioning units.

Generating continuous power by ionic thermoelectric material modules remains challenging. Here, the authors find the ionic thermoelectric material exhibiting bipolar thermopower property by manipulating the interactions between ions and electrodes.

There is an accumulating body of evidence implicating the muscarinic acetylcholine receptor 4 (M4) in schizophrenia and dementia with Lewy bodies, however, a clinically validated M4 positron emission tomography (PET) radioligand is currently lacking. As such, the aim of this study was to develop a suitable M4 PET ligand that allows the non-invasive visualization of M4 in the brain. Structure–activity relationship studies of pyrazol-4-yl-pyridine derivates led to the discovery of target compound 12 ― a subtype-selective positive allosteric modulator (PAM). The radiofluorinated analogue, [18F]12, was synthesized in 28 ± 10% radiochemical yield, >37 GBq/μmol and an excellent radiochemical purity >99%. Initial in vitro autoradiograms on rodent brain sections were performed in the absence of carbachol and showed moderate specificity as well as a low selectivity of [18F]12 for the M4-rich striatum. However, in the presence of carbachol, a significant increase in tracer binding was observed in the rat striatum, which was reduced by >60% under blocking conditions, thus indicating that orthosteric ligand interaction is required for efficient binding of [18F]12 to the allosteric site. Remarkably, however, the presence of carbachol was not required for high specific binding in the non-human primate (NHP) and human striatum, and did not further improve the specificity and selectivity of [18F]12 in higher species. These results pointed towards significant species-differences and paved the way for a preliminary PET study in NHP, where peak brain uptake of [18F]12 was found in the putamen and temporal cortex. In conclusion, we report on the identification and preclinical development of the first radiofluorinated M4 PET radioligand with promising attributes. The availability of a clinically validated M4 PET radioligand harbors potential to facilitate drug development and provide a useful diagnostic tool for non-invasive imaging.

The echo state network (ESN) is a recurrent neural network that has yielded state-of-the-art results in many areas owing to its rapid learning ability and the fact that the weights of input neurons and hidden neurons are fixed throughout the learning process. However, the setting procedure for initializing the ESN’s recurrent structure may lead to difficulties in designing a sound reservoir that matches a specific task. This paper proposes an improved pre-training method to adjust the model’s parameters and topology to obtain an adaptive reservoir for a given application. Two strategies, namely global random selection and ensemble training, are introduced to pre-train the randomly initialized ESN model. Specifically, particle swarm optimization is applied to optimize chosen fixed and global weight values within the network, and the reliability and stability of the pre-trained model are enhanced by employing the ensemble training strategy. In addition, we test the feasibility of the model for time series prediction on six benchmarks and two real-life datasets. The experimental results show a clear enhancement in the ESN learning results. Furthermore, the proposed global random selection and ensemble training strategies are also applied to pre-train the extreme learning machine (ELM), which has a similar training process to the ESN model. Numerical experiments are subsequently carried out on the above-mentioned eight datasets. The experimental findings consistently show that the performance of the proposed pre-trained ELM model is also improved significantly. The suggested two strategies can thus enhance the ESN and ELM models’ prediction accuracy and adaptability.

As a member of cyclic nucleotide phosphodiesterase (PDE) enzyme family, PDE10A is in charge of the degradation of cyclic adenosine (cAMP) and guanosine monophosphates (cGMP). While PDE10A is primarily expressed in the medium spiny neurons of the striatum, it has been implicated in a variety of neurological disorders. Indeed, inhibition of PDE10A has proven to be of potential use for the treatment of central nervous system (CNS) pathologies caused by dysfunction of the basal ganglia–of which the striatum constitutes the largest component. A PDE10A-targeted positron emission tomography (PET) radioligand would enable a better assessment of the pathophysiologic role of PDE10A, as well as confirm the relationship between target occupancy and administrated dose of a given drug candidate, thus accelerating the development of effective PDE10A inhibitors. In this study, we designed and synthesized a novel 18F-aryl PDE10A PET radioligand, codenamed [18F]P10A-1910 ([18F]9), in high radiochemical yield and molar activity via spirocyclic iodonium ylide-mediated radiofluorination. [18F]9 possessed good in vitro binding affinity (IC50 = 2.1 nmol/L) and selectivity towards PDE10A. Further, [18F]9 exhibited reasonable lipophilicity (logD = 3.50) and brain permeability (Papp > 10 × 10−6 cm/s in MDCK-MDR1 cells). PET imaging studies of [18F]9 revealed high striatal uptake and excellent in vivo specificity with reversible tracer kinetics. Preclinical studies in rodents revealed an improved plasma and brain stability of [18F]9 when compared to the current reference standard for PDE10A-targeted PET, [18F]MNI659. Further, dose–response experiments with a series of escalating doses of PDE10A inhibitor 1 in rhesus monkey brains confirmed the utility of [18F]9 for evaluating target occupancy in vivo in higher species. In conclusion, our results indicated that [18F]9 is a promising PDE10A PET radioligand for clinical translation.

Based on the hourly temperature and precipitation data from China national meteorological stations and regional automatic weather stations in Shenyang, the relationship between extreme hourly precipitation (ExHP) and urban heat island Intensity (UHII) is analyzed. Results show that the UHII is higher at night and in the early morning. The ExHP events mostly occur at night in summer when the UHII is relatively high. The spatial distribution of UHII in Shenyang is consistent with the economic development and the transportation density. Denser population and transportation, and high-rise buildings in the urban center contribute to higher UHII. There are three types of ExHP, namely the abrupt-type ExHP, the growing-type ExHP and the continuous-type ExHP. The overall variation characteristics of the three types of ExHP are relatively consistent. Their UHII values are positive and relatively stable in 6–12 h before the start of ExHP. The UHII begins to increase dramatically about 6 h before the ExHP, but decreases obviously and turn negative after the precipitation begins. Before the abrupt ExHP, the UHII is relatively high and can rapidly return to positive after the ending of ExHP. The UHII of the abrupt-type ExHP is remarkably larger than that of the growing-type and continuous-type ExHP. The UHII before and after the abrupt-type ExHP differs greatly. Before the abrupt ExHP, the UHII is high in the center and low at both ends, and the high-value areas of UHII are mainly located in the urban area. After the abrupt-type EXHP, the UHII drops and turn negative in the whole area. The UHII is obviously increasing with urbanization. The diurnal variation of UHII is enormous, which is higher at night than during the daytime. The increasing UHII can cause abnormal air pressure in cities and villages. The air in the lower atmospheric layer of the city can be heated and expanded, hence resulting in lower local air pressure. Then, the lower air pressure can promote the convergence and upward movement of air, hence facilitating the establishment of UHII circulation. This phenomenon is particularly distinct at night, which is conducive to the occurrence of ExHP events.

Primary liver cancer (PLC), including hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC), and other rare tumours, is the second leading cause of cancer-related mortality. It has been a major contributor to the cancer burden worldwide. Of all primary liver cancer, HCC is the most common type. Over the past few decades, chemotherapy, immunotherapy and other therapies have been identified as applicable to the treatment of HCC. However, evidence suggests that chemotherapy resistance is associated with higher mortality rates in liver cancer. The tumour microenvironment (TME), which includes molecular, cellular, extracellular matrix(ECM), and vascular signalling pathways, is a complex ecosystem. It is now increasingly recognized that the tumour microenvironment plays a pivotal role in PLC prognosis, progression and treatment response. Cancer cells reprogram the tumour microenvironment to develop resistance to chemotherapy drugs distinct from normal differentiated tissues. Chemotherapy resistance mechanisms are reshaped during TME reprogramming. For this reason, TME reprogramming can provide a powerful tool to understand better both cancer-fate processes and regenerative, with the potential to develop a new treatment. This review discusses the recent progress of tumour drug resistance, particularly tumour microenvironment reprogramming in tumour chemotherapy resistance, and focuses on its potential application prospects.

In recent decades, anthropogenic industrial-based activities (i.e., energy production and its conveyance) has led to the emission of deleterious greenhouse gases such as CO2, H2S, and NO2 as an important environmental concern. Membrane-based gas separation processes have been currently of paramount attention in critical industrial applications such as purification, biogas recovery, water treatment, gas processing and H2 recovery. Polymeric nanocomposite membranes (PNM) have illustrated indisputable potential of utilization to mitigate the release of gaseous pollutants to the ecosystem and reduce their hazardous environmental effects. Incorporation of novel nanoparticles including activated carbon, nanofibers and carbon nanotubes have revolutionized the efficiency of polymeric membranes for gas separation. This review paper aims to present disparate applications of polymeric nanocomposite membranes for mitigating the emission of toxic/acidic gases to environment. Moreover, performance, applications and challenges towards the use of nanocomposite membranes are reviewed comprehensively and future perspectives towards their development in industrial applications are recommended. Finally, prevalent nanocomposite membranes for the separation of various gaseous mixtures are presented.

Deep learning is a type of high-level learning that has received widespread attention in research on higher education; however, learning scenarios as an important variable have been ignored to some extent in past studies. This study aimed to explore the learning state of engineering students in three learning scenarios: theoretical learning, experimental learning, and engineering practice. Samples of engineering university students in China were recruited online and offline; the students filled in the engineering Education-Study Process Questionnaire, which was revised from the R-SPQ-2F. The results of clustering analysis showed four types of learning approaches in the three scenarios: typical deep learning, typical shallow learning, deep-shallow learning, and free learning. Engineering learners in different learning scenarios tended to adopt different learning approaches and showed gender differences. Due to factors such as differences in culture and choice of learning opportunities, the deep and shallow learners demonstrated excellent learning performance, which is in sharp contrast with the “learning failure” exhibited by such students abroad.

The spatial and seasonal distributions of stable carbon and nitrogen isotopes (δ13C and δ15N) in dominant zooplankton groups were investigated in Jiaozhou Bay. Zooplankton δ13C values ranged from −22.89‰ to −15.86‰, and δ15N values ranged from 3.18‰ to 13.57‰, respectively. The δ13C and δ15N values generally followed the order of small zooplankton < large calanoids < small Sagitta < large Sagitta. Spatial distribution patterns of zooplankton δ13C and δ15N values varied in different seasons. Our results suggested that the spatial variation of δ13C was mainly controlled by terrigenous organic matter (OM) input and phytoplankton biomass, but water temperature may have played a key role in the seasonal variation of δ13C. In spring, the high phytoplankton biomass might increase the δ13C value of small zooplankton in the inner bay. During other seasons, the δ13C values of zooplankton generally increased from the inner bay to the outer bay, which might be associated with the influence of 13C-depleted terrigenous OM carried by the river discharge. Small zooplankton stable isotope values were significantly correlated with that of particulate organic matter (POM). The influence of anthropogenic nutrient input on isotopic baseline can be cascaded to the zooplankton, and the effect might be weak at higher trophic levels. The Bayesian standard ellipse areas of dominant zooplankton groups were generally smallest in the winter, suggesting a narrow niche width during that time. The niche partition between small zooplankton, large calanoids, and Sagitta was most distinct in winter, and followed by summer. The relative trophic level of Sagitta ranged from 2.23 to 4.01, which generally declined from the inner bay to the outer bay during the spring, autumn, and winter seasons. High anthropogenic nutrient loading might reduce the difference in trophic niches among zooplankton groups. This study provided detailed information on the distribution of zooplankton δ13C and δ15N in a coastal bay, which will be useful for understanding the anthropogenic influence on the ecosystem structure and function.

In this study, the northward-moving tropical cyclones (TCs) that influence Northeast China (NEC) in July–September are identified based on the distance between the TC center and the boundaries of NEC. Then, based on a machine learning algorithm named hierarchical agglomerative clustering, the tracks of northward-moving TCs that influence NEC are classified into the eastern-track type and the turning type. In NEC, the precipitation induced by eastern-track type TCs gradually decreases from east to west, and the precipitation induced by turning-type TCs gradually decreases from south to north. For eastern-track type TCs, negative Niño3 sea surface temperature (SST) anomalies in preceding January–March can induce cyclonic circulation anomalies and positive vorticity anomalies over the Philippine Sea during subsequent July–September, which favors the genesis of TCs. Moreover, the westerly anomaly in the subtropical western north Pacific and the strengthening of cyclonic steering flow over the Philippines jointly steer the TCs to move northward along the northerly airflow on the west of the western Pacific subtropical high, which favors the genesis of eastern-track type TCs. For turning-type TCs, the positive SST anomalies in the West Wind Drift area during preceding May–July cause positive vorticity anomalies from the northern Philippines to Taiwan from July to September. The cyclonic steering flow over the Philippines and the anticyclonic steering flow over the Sea of Japan lead the TCs to move northwestwards and then turn to northeast, which is conducive to the genesis of turning type northward-moving TCs. Finally, the results of numerical experiments have confirmed these findings.

The development of techniques capable of orchestrating the assembly of living cells into multicellular ensembles with synergistic and function is challenge. Here, the authors construct algal or algal/bacterial cells-based core shell-like structure based on aqueous two-phase system for synergic photosynthetic H2 production.

The E46K α-synuclein mutation causes familial Parkinson’s disease. Here, the authors present the cryo-EM structure of N-terminally acetylated E46K α-synuclein fibrils and find that it is distinct from other known α-synuclein fibril structures.

To clarify the precipitation forecast skills of climate forecast operations in the flood season in Liaoning Province of China, this study examines the forecast accuracies of China’s national and provincial operational climate prediction products and the self-developed objective prediction methods and climate model products by Shenyang Regional Climate Center (SRCC) in the flood season in Liaoning. Furthermore, the forecast accuracies of the main influencing factors on the precipitation in the flood season of Liaoning are assessed. The results show that the SRCC objective methods have a relatively high accuracy. The European Centre for Medium-Range Weather Forecasts (ECMWF) sub-seasonal forecast initialized at the sub-nearest time has the best performance in June. The National Climate Center (NCC) Climate System Model sub-seasonal forecast initialized at the sub-nearest time, and the ECMWF seasonal and sub-seasonal forecasts initialized at the nearest time, perform the best in July. The NCC sub-seasonal forecast initialized at the sub-nearest time has the best performance in August. For the accuracy of the SRCC objective method, the more significant the equatorial Middle East Pacific sea surface temperature (SST) anomaly is, the higher the evaluation score of the dynamic–analogue correction method is. The more significant the North Atlantic SST tripole is, the higher the score of the hybrid downscaling method is. For the forecast accuracy of the main influencing factors of precipitation, the tropical Atlantic SST and the north–south anti-phase SST in the northwest Pacific can well predict the locations of the southern vortex and the northern vortex in early summer, respectively. The warm (clod) SST in China offshore has a good forecast performance on the weak (strong) southerly wind in midsummer in Northeast China. The accuracy of using the SST in the Nino 1+2 areas to predict the north–south location of the western Pacific subtropical high is better than that of using Kuroshio SST. The accuracy of predicting northward-moving typhoons from July to September by using the SST in the west-wind-drift area is better than using the SST in the Nino 3 area. The above conclusions are of great significance for improving the short-term climate prediction in Liaoning.

The COVID-19 pandemic has posed a significant challenge to global public health. In response, the search for specific antiviral drugs that can effectively treat the disease caused by the SARS-CoV-2 virus has become a priority. While significant progress has been made in this regard, much work remains to address this ongoing crisis effectively. Favipiravir is an antiviral drug initially developed for the treatment of influenza and has received approval for emergency use for COVID-19 in many countries. A better understanding of the biodistribution and pharmacokinetics of Favipiravir in vivo would facilitate the development and translation of clinical antiviral drugs for COVID-19. Herein, we report the evaluation of [18F]Favipiravir in naive mice, transgenic mice models of Alzheimer’s disease, and nonhuman primates (NHP) with positron emission tomography (PET). The [18F]Favipiravir was obtained in an overall decay-corrected radiochemical yield of 29% with a molar activity of 25 GBq/µmol at the end of synthesis (EOS). PET imaging in naive mice, transgenic mice models of Alzheimer’s disease, and nonhuman primates revealed a low initial brain uptake, followed by a slow washout of [18F]Favipiravir in vivo. The [18F]Favipiravir was eliminated by a combination of hepatobiliary and urinary excretion. The low brain uptake was probably attributed to the low lipophilicity and low passive permeability of the drug. We hope this proof-of-concept study will provide a unique feature to study antiviral drugs using their corresponding isotopologues by PET.

Fault localization is indeed tedious and costly work during software maintenance. Studies indicate that combining both structural features and behavior characteristics of programs can be beneficial for improving the efficiency of fault locating. In this paper, we proposed a framework, called Mulr4FL, for fault localization using a multivariate logistic regression model that combined both static and dynamic features collected from the program under debugging. Firstly, the hybrid metrics data set, with both program structural features and behavior characteristics combined, is constructed by static program analyzing and dynamically tracing that runs with a designed metrics set. Meanwhile, the fault information of the legacy program is also obtained from the bug tracking system. Secondly, Bivariate logistic analysis is performed to filter the metrics that are significantly related to faults, and then with the selected metrics and their measurements, a multivariate logistic regression model was constructed and trained. Finally, based on the trained logistic model, we conduct the multivariate logistic analysis on the features of the evolved software and predict the buggy class methods. An empirical study was conducted based on a set of benchmarks that are used widely in program debugging research. The results indicate that the Mulr4FL can significantly improve the effectiveness of locating faults in contrast to 5 baseline techniques.

Acute flaccid myelitis (AFM) is a polio-like disease that results in paralysis in previously healthy persons. Although the definitive cause of AFM remains unconfirmed, enterovirus D68 (EV-D68) is suspected based on 2014 data demonstrating an increase in AFM cases concomitant with an EV-D68 outbreak. We examined the prevalence in children and the molecular evolution of EV-D68 for 2009–2018 in Philadelphia, Pennsylvania, USA. We detected widespread EV-D68 circulation in 2009, rare detections in 2010 and 2011, and then biennial circulation, only in even years, during 2012–2018. Prevalence of EV-D68 significantly correlated with AFM cases during this period. Finally, whole-genome sequencing revealed early detection of the B1 clade in 2009 and continued evolution of the B3 clade from 2016 to 2018. These data reinforce the need to improve surveillance programs for nonpolio enterovirus to identify possible AFM triggers and predict disease prevalence to better prepare for future outbreaks.

Abstract Background Analysis of mixed microbial communities using metagenomic sequencing experiments requires multiple preprocessing and analytical steps to interpret the microbial and genetic composition of samples. Analytical steps include quality control, adapter trimming, host decontamination, metagenomic classification, read assembly, and alignment to reference genomes. Results We present a modular and user-extensible pipeline called Sunbeam that performs these steps in a consistent and reproducible fashion. It can be installed in a single step, does not require administrative access to the host computer system, and can work with most cluster computing frameworks. We also introduce Komplexity, a software tool to eliminate potentially problematic, low-complexity nucleotide sequences from metagenomic data. A unique component of the Sunbeam pipeline is an easy-to-use extension framework that enables users to add custom processing or analysis steps directly to the workflow. The pipeline and its extension framework are well documented, in routine use, and regularly updated. Conclusions Sunbeam provides a foundation to build more in-depth analyses and to enable comparisons in metagenomic sequencing experiments by removing problematic, low-complexity reads and standardizing post-processing and analytical steps. Sunbeam is written in Python using the Snakemake workflow management software and is freely available at github.com/sunbeam-labs/sunbeam under the GPLv3.

In the early summer (June) of 2022, the spatial mean precipitation in northeast China (NEC) was 62% higher than normal and broke the historical record since 1951. Based on the precipitation data of 245 meteorological stations in NEC and the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis, this paper analyzes the role of large-scale circulation and sea-surface temperature (SST) associated with anomalous precipitation over NEC in June using singular value decomposition (SVD), correlation analysis, regression analysis, and composite analysis methods, and further investigates the possible cause of the abnormal precipitation in June 2022. Results show that the northeast China cold vortex (NCCV) accompanying the blocking high in the Okhotsk Sea (BHOS) has been the primary mid-to-high latitude atmospheric circulation pattern affecting NEC precipitation in June since 2001. This circulation pattern is closely related to the tripole SST pattern over the North Atlantic (NAT) in March. In June 2022, the NAT SST anomaly in March stimulates eastward-propagating wave energy, resulting in the downstream anomalous circulation pattern in which the NCCV cooperates with the BHOS in the mid-high latitudes of East Asia. Under this background atmospheric circulation favorable for precipitation, the Kuroshio region SST anomaly in June led to a more northward and stronger anomalous anticyclone in the northwestern Pacific through local air–sea interaction, which provides more sufficient water vapor for NEC, resulting in unprecedented precipitation in June 2022.

Understanding changes in extreme hourly precipitation is critical to urban planners for building more sustainable and resilient cities. In this study, we use satellite nighttime light data, urban land area data, population, and economic data to objectively classify urban and rural stations. Based on the hourly precipitation data from national meteorological stations in 1974–2020 and from regional automatic weather stations in 2005–2020 in Shenyang (China), the spatio-temporal distribution characteristics of the thresholds, maximums, intensities, and frequencies of extreme hourly precipitation (ExHP) in urban and rural areas are analyzed and compared. The results show that the large-value centers of ExHP thresholds, maximums, and intensities are mainly concentrated in urban areas. Both the frequency and intensity of ExHP at urban stations are obviously larger than those at rural stations, and the peaks mainly appear at night for stations of both two types. From 1974 to 2020, the average frequency and intensity of ExHP at urban stations both show increasing trends, with the increasing rate being much higher than those at rural stations. In terms of temporal variation, precipitation events of the abrupt type are the most frequent, accounting for 48.6% of the total, followed by the growing type (42.7%) and continuous type (8.7%). ExHP events of the abrupt type are mostly concentrated in Kangping County and Faku County of Northern Shenyang, but rarely occur in Xinmin City. ExHP events of the growing type are mainly found in Xinmin City and the municipal district of Shenyang. For urban stations, the ExHP frequency decreases in the early stage of urbanization, while increasing evidently during the rapid urbanization stage. However, the situation is just the opposite for rural stations. This indicates that the rapid urbanization in Shenyang has a certain impact on the increase in ExHP.

D number theory removes the constraints of mutual exclusion and completeness in the frame of discernment of DS evidence theory, and is therefore widely used to deal with uncertain and incomplete information. EDAS (evaluation based on distance from average solution) selects the optimal solution according to the distance from each solution to the average. This method is very suitable for solving issues of multiple attribute decision making (MADM) with conflicting attributes. In this study, we propose an evaluation method that combines D numbers with the EDAS method. D number theory is used to express the evaluation of the alternatives for experts. Then, we use the SCRI (stepwise comparison and replacement integration) method of D numbers for data integration, and finally the EDAS method is used to select the optimal one by sorting the alternatives. We apply this method to address the user experience evaluation problems of platforms that offer online live courses and compare the evaluation results with other methods to verify the applicability and practicability of the method.

Phosphatidylethanolamine-binding-protein (PEBP) domain-containing proteins play important roles in multiple developmental processes of plants; however, functions of few members in the PEBP gene family have been elucidated in rice and other crops. In this study, we found that twenty OsPEBPs genes identified in rice are not evenly distributed on the chromosomes. Four colinear pairs are identified, suggesting the duplication of OsPEBPs during evolution. The OsPEBPs are classified into six subgroups by phylogenetic analysis. The structure of all the OsPEBP genes and encoded proteins are similar. The 262 PEBP domain-containing proteins from crops are divided into six groups. The number of colinear pairs varies between rice and other crops. More than thirty cis-acting elements in the promoter region of OsPEBPs are discovered. Expression profiles of OsPEBP genes are differential. Most of the OsPEBPs expression can be regulated by NaCl, ABA, JA, and light, indicating that OsPEBPs may be involved in the control of the response to the environmental signals. These results lay sound foundation to further explore their functions in development of rice and crops.

Seagrasses inhabiting the intertidal zone experience periodically repeated cycles of air exposure and rehydration. However, little is known about the photoprotective mechanisms in photosystem (PS)II and PSI, as well as changes in carbon utilization upon air exposure. The photoprotective processes upon air exposure in Halophila beccarii Asch., an endangered seagrass species, were examined using the Dual-PAM-100 and non-invasive micro-test technology. The results showed that air exposure enhanced non-photochemical quenching (NPQ) in both PSII and PSI, with a maximum increase in NPQ and Y(ND) (which represents the fraction of overall P700 that is oxidized in a given state) of 23 and 57%, respectively, resulting in intensive thermal energy dissipation of excess optical energy. Moreover, cyclic electron transport driven by PSI (CEF) was upregulated, reflected by a 50 and 22% increase in CEF and maximum electron transport rate in PSI to compensate for the abolished linear electron transport with significant decreases in pmfLEF (the proton motive force [pmf]) attributable solely to proton translocation by linear electron flow [LEF]). Additionally, H+ fluxes in mesophyll cells decreased steadily with increased air exposure time, exhibiting a maximum decrease of six-fold, indicating air exposure modified carbon utilization by decreasing the proton pump influxes. These findings indicate that efficient heat dissipation and CEF confer daily air exposure tolerance to the intertidal seagrass H. beccarii and provide new insights into the photoprotective mechanisms of intertidal seagrasses. This study also helps explain the extensive distribution of H. beccarii in intertidal zones.

Rapid urbanization leads to an accelerating decline of seagrass beds. The status of seagrass beds along the entire coastline of a rapidly urbanizing area, Guangdong Province, was examined to document the change in seagrass beds and to explore the determinants of seagrasses characteristics and their plasticity. Thirteen seagrass beds were newly discovered with a total area as 679.04 ha, whereas eleven known seagrass beds have decreased from 972.55 ha to 858.67 ha with seven of them having disappeared in recent decade primarily due to exacerbated construction of artificial shorelines and beach dams, increased nutrient inputs from fish caging and shrimp pond culture, oyster culture, mangrove planting and shellfish collection. The leaf nitrogen content of Halophila ovalis, which dominated the largest beds, increased from (2.09 ± 0.24)% in 2011 to (3.39 ± 0.18)% in 2017, indicating enhanced eutrophication. The optimum seawater dissolved inorganic nitrogen and dissolved inorganic phosphorus levels for Halophila beccarii were 40 μmol/L and 2.5 μmol/L, respectively. The standing stock and plant dimensions of H. beccarii were positively correlated with sediment mud content. Longer, wider leaves, and greater aboveground and belowground biomass were observed at lower salinities, indicating that H. beccarii prefers hyposaline habitats. High shoot density could induce intraspecific competition followed by self-thinning in H. beccarii, leading to reduced leaf area, aboveground and belowground biomass, and root length. Thus, long-term monitoring of seagrass beds along the rapidly urbanizing coastline of Guangdong Province is needed to unravel the mechanisms of decline and to develop effective management strategies.

In order to solve the problem that the flatness error contour curve of the guideway mounting surface on machine tools can not be intuitive description, a novel method is proposed in this paper. The principle is to divide the measured surface with a certain length into several short surfaces with overlapping region, and the segmented surfaces are measured respectively, then the flatness error contours of the segmented surfaces can be obtained, finally, the segmented flatness error contours are spliced together to reconstruct the flatness error contour of the entire surface. On this basis, the detection instrument is designed, the detection principle is given, the benchmark plate is customized to identify the starting position and ending position of measurement, the reference surface and the measured surface are measured respectively in combination with the detection instrument and the benchmark plate. Then, an algorithm is developed to convert the distance difference between the reference surface and the measured surface into the flatness error contours of segmented surfaces. Next, using the geometric relationship between overlapping region of segmented flatness error contours, an algorithm is studied which can splice these segmented flatness error contours and reconstruct the flatness error contour of the entire surface. Meanwhile, mathematical models of the algorithms are established, and the measurement experiment is carried out. The results demonstrate that this method can reconstruct the flatness error contour of long surface accurately.

High-speed machining is a key technology for greatly improving productivity and reducing production costs. Angular contact ball bearing is the key component of ball screw feed system. Predictive analysis of bearings thermal behavior is significant to ensure the working accuracy of machine tools. Due to the continuous dynamic changes under actual working conditions, it is difficult to predict and model of the bearings heating characteristics. This paper develops a comprehensive calculation method for predicting the thermodynamic characteristics on high speed feed shaft bearings. Based on quasi-static model and thermal dynamic model, Monte Carlo optimization algorithm is used to inverse the temperature field experimental temperature data. The real heating characteristics of heat source are comprehensively predicted and analyzed, so as to accurately predict the bearing thermal dynamic performances of feed shaft bearings. The research work in this paper lays a strong foundation for the thermal error modeling and thermodynamic analysis of the ball screw feed system of machine tools.

Seagrass beds provide nursery habitats for marine species. Seagrass leaves, in particular, are used as spawning grounds and as a food source for fish and invertebrates, but direct evidence of spawning in seagrass leaves is rare. It is also very challenging to identify eggs through morphological analysis, since the eggs of many marine species appear similar. To accurately identify the eggs on the leaves of the dominant seagrass species in the South China Sea, and evaluate seasonal contribution of seagrass leaves as a food source, DNA barcoding and stable isotope technique were conducted. Interestingly, Monetaria annulus was found to spawn on the leaf sheath of Thalassia hemprichii in Li’an gang, Hainan Island. This choice of oviposition site might increase embryo survival compared to the other parts of the seagrass leaves. Meanwhile, the eggs of Stethojulis trilineata were deposited on the entire leaf of Halophila ovalis in Liusha Bay, Guangdong Province. The small fingernail-shaped leaves of H. ovalis might be beneficial for S. trilineata to lay eggs as they are closer to the sediment surface than other seagrass leaves. Based on the stable carbon and nitrogen isotope analyses, the primary food source of M. annulus in summer and in winter were particulate organic matter and seagrass, respectively. The results suggest that seagrass leaves are not only important for fish and invertebrates as a spawning site, but also as a food source. The findings of the present study may support the urgent requirement of the conservation of seagrass beds for sustaining the productivity of marine fisheries.

Rhizosphere bacterial community structures and their determining drivers have been studied in a variety of marine and freshwater ecosystems for a range of plant species. However, there is still limited information about the influence of habitat on microbial communities in seagrass beds. This study aimed to determine which factors (habitat and plant species) have crucial roles on the rhizospheric bacteria associated with two tropical seagrass species (Thalassia hemprichii and Enhalus acoroides) that are dominant at Xincun Bay and Tanmen Harbor in Hainan Island, South China. Using Illumina HiSeq sequencing, we observed substantial differences in the bacterial richness, diversity, and relative abundances of taxa between the two habitats, which were characterized differently in sediment type and nutrient status. Rhizospheric bacteria from sandy sediment at the eutrophic Xincun Bay were dominated by Desulfobacteraceae and Helicobacteraceae, which are primarily involved in sulfate cycling, whereas rhizosphere microbes from the reef flat at oligotrophic Tanmen Harbor were dominated by Vibrionaceae and Woeseiaceae, which may play important roles in nitrogen and carbon fixing. Additionally, we speculated that host-specific effects of these two seagrass species may be covered under nutrient-rich conditions and in mixed community patches, emphasizing the importance of the nutrient status of the sediment and vegetation composition of the patches. In addition, our study confirmed that Proteobacteria was more adapted to the rhizosphere environment than to low-carbon conditions that occurred in bulk sediment, which was primarily dominated by well-known fermentative bacteria in the phylum Firmicutes.

Streptococcus thermophilus plays important roles in the dairy industry and is widely used as a dairy starter in the production of fermented dairy products. The genomes of S. thermophilus strains CS5, CS9, CS18, and CS20 from fermented milk in China were sequenced and used for biodiversity analysis. In the present study, the phylogenetic analysis of all 34 S. thermophilus genomes publicly available including these four strains reveals that the phylogenetic reconstruction does not match geographic distribution as strains isolated from the same continent are not even clustered on the nearby branches. The core and variable genes were also identified, which vary among strains from 0 to 202. CS9 strain contained 127 unique genes from a variety of distantly related species. It was speculated that CS9 had undergone horizontal gene transfer (HGT) during the long evolutionary process. The safety evaluation of these four strains indicated that none of them contains antibiotic resistance genes and that they are all sensitive to multiple antibiotics. In addition, the strains do not contain any pathogenic virulence factors or plasmids and thus can be considered safe. Furthermore, these strains were investigated in terms of their technological properties including milk acidification, exopolysaccharide (EPS) and γ-aminobutyric acid (GABA) production, and in vitro survival capacity in the gastrointestinal tract. CS9 possesses a special eps gene cluster containing significant traces of HGT, while the eps gene clusters of CS5, CS18, and CS20 are almost the same. The monosaccharide compositional analysis indicated that crude EPS-CS5, EPS-CS9, EPS-CS18, and EPS-CS20 contain similar monosaccharide compositions with different ratios. Furthermore, CS9 was one of a few GABA-producing strains that could ferment glutamate to produce GABA, which is beneficial for improving the acid tolerance of the strain. CS18 has the most potential for the production of fermented food among these four strains because of its fast growth rate, rapid acidifying capacity, and stronger acid and bile salt resistance capacity. This study focused on the genome analysis of the four new S. thermophilus strains to investigate the diversity of strains and provides a reference for selecting excellent strains by use of the genome data.

We report a simple realization of a compact linear electroacoustic field effect transistor (EA-FET) constructed by coupling a membrane-type acoustic metamaterial with a piezoelectric shunt circuit. As analogous to the electroelectronic field effect transistor, the proposed EA-FET is a four-terminal device in which the sound flux is regulated by the external electric field. The core function of the EA-FET relies on the electrical-elasticity-control mechanism stemming from the inside mechanical and electrical interactions. The effectiveness of the EA-FET concept is proved by investigating the intrinsic output and transfer properties and the sound transmission characteristics. The continuous and rapid regulation of sound flux, as well as the acoustic binary encoding via an EA-FET sample, were demonstrated experimentally. As an essential analog acoustic functional device, the EA-FET could play a significant role in engineering the integration of analog acoustic circuits, and it may be adapted to build distributed information processing systems.

D numbers theory is an extension of Dempster–Shafer evidence theory. It eliminates the constraints of mutual exclusion and completeness under the frame of discernment of Dempster–Shafer evidence theory, so it has been widely used to deal with uncertainty modelling, but if it cannot effectively deal with the problem of missing information, sometimes unreasonable conclusions will be drawn. This paper proposes a new type of integration representation of D numbers, which compares the data of multiple evaluation items horizontally, and can reasonably fill in missing information. We apply this method to the user experience evaluation problem of online live course platform to verify the effectiveness of this method.

Abstract Research on the human microbiome has yielded numerous insights into health and disease, but also has resulted in a wealth of experimental artifacts. Here, we present suggestions for optimizing experimental design and avoiding known pitfalls, organized in the typical order in which studies are carried out. We first review best practices in experimental design and introduce common confounders such as age, diet, antibiotic use, pet ownership, longitudinal instability, and microbial sharing during cohousing in animal studies. Typically, samples will need to be stored, so we provide data on best practices for several sample types. We then discuss design and analysis of positive and negative controls, which should always be run with experimental samples. We introduce a convenient set of non-biological DNA sequences that can be useful as positive controls for high-volume analysis. Careful analysis of negative and positive controls is particularly important in studies of samples with low microbial biomass, where contamination can comprise most or all of a sample. Lastly, we summarize approaches to enhancing experimental robustness by careful control of multiple comparisons and to comparing discovery and validation cohorts. We hope the experimental tactics summarized here will help researchers in this exciting field advance their studies efficiently while avoiding errors.

Mycobacterium chelonae is a rapidly growing nontuberculous mycobacterium that is a common cause of nosocomial infections. Here we describe investigation of a possible nosocomial transmission of M. chelonae at the Hospital of the University of Pennsylvania (HUP). M. chelonae strains with similar high-level antibiotic resistance patterns were isolated from two patients who developed post-operative infections at HUP in 2017, suggesting a possible point source infection. The isolates, along with other clinical isolates from other patients, were sequenced using the Illumina and Oxford Nanopore technologies. The resulting short and long reads were hybrid assembled into draft genomes. The genomes were compared by quantifying single nucleotide variants in the core genome and assessed using a control dataset to quantify error rates in comparisons of identical genomes. We show that all M. chelonae isolates tested were highly dissimilar, as indicated by high pairwise SNV values, consistent with environmental acquisition and not a nosocomial point source. Our control dataset determined a threshold for evaluating identity between strains while controlling for sequencing error. Finally, antibiotic resistance genes were predicted for our isolates, and several single nucleotide variants were identified that have the potential to modulated drug resistance.

In this paper, a nine degree-of-freedom dynamic model of the ball screw feed system considering the contact nonlinearity between balls and raceways is established to analyze the vibration characteristics. The position relationship between raceway centers for the ball screw and bearings is determined by using the homogeneous coordinate transformation, and then the restoring force functions along the axial and lateral directions are derived. The dynamic equations of the feed system are solved by using Newmark method, and the proposed model is verified by the experimental method. Furthermore, the effect of the excitation amplitude on the axial vibration of the feed system is investigated by the frequency-amplitude curve and 3-D frequency spectrum. With the increase of excitation amplitude, the dynamic response of the feed system exits the softening, hardening type nonlinearity and jump phenomenon. Additionally, the effects of the initial contact angle, length of screw shaft and number of loaded balls on the axial vibration of the feed system in the resonance region are discussed. The results show that the dynamic model established in this paper is suitable for improving the machining accuracy and stability of the ball screw feed system.

In this paper, we propose an in-fiber Mach–Zehnder temperature sensor based on a dual-core fiber with an eccentric core and a central core. The latter one is beside a fluidic channel embedded in the fiber. The effective refractive index of the guided mode in the central core could be influenced by the glycerol–water solution filled in the fluidic channel. Thus, the transmitted spectrum of the sensor is shifted as a function of temperature. By monitoring the selected spectral dip shifts, an experimental sensitivity of 2.77 nm/°C is obtained in the range of 25 to 40 °C for a solution length of 15 cm. To further improve the temperature sensitivity, the solution length is increased up to 29.5 cm, and a higher sensitivity of 5.69 nm/°C is achieved in the same temperature range. The experimental results agree well with the theoretical ones. The proposed sensor has good robustness and stability, which makes it promising for applications of high precision temperature monitoring.

The Li-ion battery is of paramount importance to electric vehicles (EVs). Propelled by the rapid growth of the EV industry, the performance of the battery is continuously improving. However, Li-ion batteries are susceptible to the working temperature and only obtain the optimal performance within an acceptable temperature range. Therefore, a battery thermal management system (BTMS) is required to ensure EVs’ safe operation. There are various basic methods for BTMS, including forced-air cooling, liquid cooling, phase change material (PCM), heat pipe (HP), thermoelectric cooling (TEC), etc. Every method has its unique application condition and characteristic. Furthermore, based on basic BTMS, more hybrid cooling methods adopting different basic methods are being designed to meet EVs’ requirements. In this work, the hybrid BTMS, as a more reliable and environmentally friendly method for the EVs, will be compared with basic BTMS to reveal its advantages and potential. By analyzing its cost, efficiency and other aspects, the evaluation criterion and design suggestions are put forward to guide the future development of BTMS.

The purpose of this paper is investigating the characteristics of dynamic contact and dynamic stiffness of the single nut ball screw pair (SNBSP). Then a new sensorless method is proposed to extract the SNBSP dynamic contact stiffness of a mass production CNC machine tool feed system. First of all, the transformation relationship between each coordinate system of SNBSP is established. Secondly, the dynamic model of all ball–raceway contact pairs is established. Based on this, a dynamic contact stiffness model is established. The dynamic contact parameters are obtained by the numerical method. It is found that the influence of screw speed on screw and nut raceway normal force distribution are opposite. This will affect the variations of dynamic contact stiffness. It is also clear that the effect of axial load on dynamic stiffness is significant. Then, an effective method is proposed to estimate the dynamic contact stiffness of a mass production CNC machine tool feed system without any external sensors. The axial force of feed system is estimated by using torque current of servo motor. Current signals can be obtained through FANUC Open CNC API Specifications (FOCAS) library functions, and then dynamic contact stiffness can be calculated through the stiffness model without external sensors. Finally, a feed system dynamic model is built, and the contact model and sensorless stiffness estimating method are verified by experiments in this dynamic system.

Material extrusion (ME), an extrusion-based rapid prototyping technique, has been extensively studied to manufacture final functional products, whose forming quality is significantly influenced by the melt flow behavior (MFB) inside the extrusion liquefier. Applied vibration has a great potential to improve the MFB, and thereby promote the forming quality of the built product. To reveal the mechanism, a dynamic model of the melt flow behavior (DMMFB) is established based on fluid dynamics, Tanner nonlinear constitutive equation and Newton’s power law equation. The MFB, i.e., pressure drop, shear stress and apparent viscosity, is investigated without and with different vibration applied. The corresponding finite element analysis (FEA) is then carried out. From the comparison between DMMFB and FEA results, it is concluded that the proposed model is reliable. When vibration is applied onto the extrusion liquefier, the time-domain MFB will change periodically. Its effective value decreases significantly, and further decreases with the increase of vibration frequency or amplitude. This paper provides the theoretical basis to improve the MFB by applied vibration, and thereby to enhance the forming quality of ME products.

In the research of dynamic load identification, the method of obtaining kernel function matrix is usually rather cumbersome. To solve this problem, an explicit dynamic load identification algorithm based on the Wilson-θ (DLIAEW) method is proposed to easily obtain the kernel function matrix as long as the parameters of the system are known. To aim at the ill-posed problem in the inverse problem, this paper improves the Tikhonov regularization, proposes an improved regularization algorithm (IRA), and introduces the U-curve method to determine the regularization parameters. In the numeric simulation investigation of a four dofs vibrating system, effects of the sampling frequency and the noise level on the regularization parameters and the identification errors of impact and harmonic loads for the IRA are discussed in comparison with the Tikhonov regularization. Finally, the experiments of a cantilever beam excited by impact and harmonic loads are carried out to verify the advantages of the IRA.

With the increasingly wide application of fused filament fabrication (FFF) technique, the built products are inevitably exposed to dynamic mechanical loading and vibration. However, there has been no systematic study in the literature on understanding and characterization of dynamic mechanical performance for FFF products. In this paper, the dynamic characteristics of FFF plates are quantified, with the effect of different extrusion width taken into account. A dynamic model of the built plate with cantilever boundary conditions is established, and the inherent characteristics are predicted. Modal tests are then performed on these samples to obtain the measured data. Through the comparison between predictions and measurements, the theoretical model is validated. Different extrusion width makes the material properties of the plates different, resulting in different dynamic characteristics. The scanning electron microscopy (SEM) analysis on the samples confirms that the dynamic characteristic is deteriorated as the extrusion width decreases. This present work provides theoretical basis and technical support for further research in improving the dynamic performance of FFF products and helps extend the applications of this technique.