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Abstract An accumulating number of studies have highlighted the importance of interpersonal neural synchronization (INS) between interlocutors in successful verbal communications. The opportunities for communication across different language contexts are rapidly expanding, thanks to the frequent interactions among people all over the world. However, whether the INS changes in different language contexts and how language choice affects the INS remain scarcely explored. The study recruited twenty pairs of participants to communicate in the first language (L1), second language (L2) and interlingual contexts. Using functional near-infrared spectroscopy (fNIRS), we examined the neural activities of interlocutors and analyzed their wavelet transform coherence to assess the INS of dyads. Results showed that as compared to the resting state, stronger INS was observed at the left inferior temporal gyrus, middle temporal gyrus, pre-motor and supplementary motor cortex, dorsolateral prefrontal cortex, and inferior frontal gyrus in L1; at the left middle temporal gyrus, superior temporal gyrus, and inferior frontal gyrus in L2; at the left inferior temporal gyrus and inferior frontal gyrus in interlingual context. Additionally, INS at the left inferior frontal gyrus was significantly stronger in L2 than in L1. These findings reveal the differences of the INS in different language contexts and confirm the importance of language choice for the INS changes.

Abstract The hepatotoxicity of regorafenib is one of the most noteworthy concerns for patients, however the mechanism is poorly understood. Hence, there is a lack of effective intervention strategies. Here, by comparing the target with sorafenib, we show that regorafenib-induced liver injury is mainly due to its nontherapeutic target Eph receptor A2 (EphA2). EphA2 deficiency attenuated liver damage and cell apoptosis under regorafenib treatment in male mice. Mechanistically, regorafenib inhibits EphA2 Ser897 phosphorylation and reduces ubiquitination of p53 by altering the intracellular localization of mouse double minute 2 (MDM2) by affecting the extracellular signal-regulated kinase (ERK)/MDM2 axis. Meanwhile, we found that schisandrin C, which can upregulate the phosphorylation of EphA2 at Ser897 also has protective effect against the toxicity in vivo. Collectively, our findings identify the inhibition of EphA2 Ser897 phosphorylation as a key cause of regorafenib-induced hepatotoxicity, and chemical activation of EphA2 Ser897 represents a potential therapeutic strategy to prevent regorafenib-induced hepatotoxicity.

Recent advancements in DNA and RNA bioengineering have paved the way for developing stimuli-responsive nanostructures with remarkable potential across various applications. These nanostructures, crafted through sophisticated bioengineering techniques, can dynamically and precisely respond to both physiological and physical stimuli, including nucleic acids (DNA/RNA), adenosine triphosphate, proteins, ions, small molecules, pH, light, and temperature. They offer high sensitivity and specificity, making them ideal for applications such as biomarker detection, gene therapy, and controlled targeted drug delivery. In this review, we summarize the bioengineering methods used to assemble versatile stimuli-responsive DNA/RNA nanostructures and discuss their emerging applications in structural biology and biomedicine, including biosensing, targeted drug delivery, and therapeutics. Finally, we highlight the challenges and opportunities in the rational design of these intelligent bioengineered nanostructures.

BackgroundThe community characteristics of the gut microbiota are not well defined and are not as widely studied as the functions of individual bacteria. This study aims to investigate the community composition of intestinal flora in women of childbearing age by conducting cluster analysis of gut microbiota and analyzing the relationship between different clusters and immune status.MethodsA total of 45 women of childbearing age were recruited in the study, including 15 non-pregnant women and 30 women in late pregnancy, and stool samples were collected twice during the third trimester, specifically at 32 weeks and at full term. The gut microbiota data was analyzed using 16S rRNA amplicon sequencing. Partitioning Around Medoids algorithm was employed to assess microbial clustering patterns. Microbial network for each cluster was performed and plasm cytokines were measured to analyze the relationship between specific genera and immune state in clusters.ResultsThere were three distinct clusters of intestinal community composition in women of childbearing age. Cluster 1 (PAM_1) was characterized by a high abundance of Bacteroides, while cluster 2 (PAM_2) showed higher levels of Bifidobacterium and Blautia, along with a significantly increased Firmicutes to Bacteroidota ratio. Cluster 3 (PAM_3) displayed a high abundance of Escherichia-shigella. PAM_1 was the most dominant cluster in non-pregnant women, and this dominant cluster was also one of the main in late pregnancy. At full term, the majority of subjects retained the same cluster as at 32 weeks, while a few experienced a shift. The microbial correlation networks differed across the three clusters, with PAM_1 exhibiting higher modularity and fewer connections. Analysis of the correlation between genera and plasma cytokines showed significant differences in their associations with cytokines between pregnancy and nonpregnancy within the same cluster, and the same genera had different effects in different clusters.ConclusionWomen of childbearing age exhibit three distribution patterns of gut microbiota, and the intestinal clusters reshaped during late pregnancy in a small population. Different clusters may have diverse immunomodulatory effects in different physiological states. When studying the gut microbiome during pregnancy, it is crucial to consider the cluster differences within healthy women.

IntroductionNon-suicidal self-injury (NSSI) is highly prevalent in depression, and is associated with psychosocial factors, emotion dysregulation, and strategies of cognitive emotion regulation. However, the internal combination and interactions of these risk factors in depression remain unclear.MethodsData from 122 patients with depression, including 56 with NSSI and 66 without NSSI, were analyzed. Self-rating scales were used to assess psychosocial factors, emotion dysregulation, and cognitive regulation strategies. Sparse partial least squares discriminant analysis (sPLS-DA) was employed to explore internal combinations in each profile. A moderated mediation model was applied to examine their interactional relationship.ResultsThe results identified an NSSI-related psychosocial profile characterized by high neuroticism, childhood trauma, poor family functioning, and low psychological resilience. Emotion dysregulation, including high levels of alexithymia, anhedonia, and emotion regulation difficulties, mediated the association between this psychosocial profile and NSSI. The mediated effect was further moderated by maladaptive cognitive regulation strategies.LimitationsLack of sufficient information on NSSI frequency and severity. Relatively small sample size for discussing the impact of gender and age of depressive patients with NSSI.ConclusionThese findings hold important implications for the prevention, treatment, and rehabilitation of NSSI.

Chip-scale programmable optical signal processors are often used to flexibly manipulate the optical signals for satisfying the demands in various applications, such as lidar, radar, and artificial intelligence. Silicon photonics has unique advantages of ultra-high integration density as well as CMOS compatibility, and thus makes it possible to develop large-scale programmable optical signal processors. The challenge is the high silicon waveguides propagation losses and the high calibration complexity for all tuning elements due to the random phase errors. In this paper, we propose and demonstrate a programmable silicon photonic processor for the first time by introducing low-loss multimode photonic waveguide spirals and low-random-phase-error Mach-Zehnder switches. The present chip-scale programmable silicon photonic processor comprises a 1×4 variable power splitter based on cascaded Mach-Zehnder couplers (MZCs), four Ge/Si photodetectors, four channels of thermally-tunable optical delaylines. Each channel consists of a continuously-tuning phase shifter based on a waveguide spiral with a micro-heater and a digitally-tuning delayline realized with cascaded waveguide-spiral delaylines and MZSs for 5.68 ps time-delay step. Particularly, these waveguide spirals used here are designed to be as wide as 2 µm, enabling an ultralow propagation loss of 0.28 dB/cm. Meanwhile, these MZCs and MZSs are designed with 2-µm-wide arm waveguides, and thus the random phase errors in the MZC/MZS arms are negligible, in which case the calibration for these MZSs/MZCs becomes easy and furthermore the power consumption for compensating the phase errors can be reduced greatly. Finally, this programmable silicon photonic processor is demonstrated successfully to verify a number of distinctively different functionalities, including tunable time-delay, microwave photonic beamforming, arbitrary optical signal filtering, and arbitrary waveform generation.

Polymer-derived ultra-high-temperature ceramic (UHTC) nanocomposites have attracted growing attention due to the increasing demands for advanced thermal structure components in aerospace. Herein, hafnium carbide (HfC) whiskers are successfully fabricated in carbon fiber preforms via the polymer-derived ceramic (PDC) method. A novel carbon nanotube (CNT) template growth mechanism combined with the PDC method is proposed in this work, which is different from the conventional vapor–liquid–solid (VLS) mechanism that is commonly used for polymer-derived nanostructured ceramics. The CNTs are synthesized and proved to be the templates for fabricating the HfC whiskers, which are generated by the released low-molecular-weight gas such as CO, CO2, and CH4 during the pyrolysis of a Hf-containing precursor. The formed products are composed of inner single crystal HfC whiskers that are measured to be several tens of micrometers in length and 100–200 nm in diameter and outer HfC/HfO2 particles. Our work not only proposes a new strategy to prepare the HfC whiskers, but also puts forward a new thinking of the efficient utilization of a UHTC polymer precursor.

A hyperspectral image (HSI) has also highly correlated and redundant data, in addition to abundant spatial and spectral information. Only the spectral characteristics were usually utilized to perform the HSI classification in most previous studies, which leads to unsatisfactory accuracy and precision. The combination of Principal Component Analysis (PCA), Local Binary Pattern (LBP) and Back Propagation Neural Network (BPNN) (PCA-LBP-BPNN) was used to propose a novel classification method. More specifically, PCA was first used to reduce the dimensionality of HSIs for obtaining independent spectral bands sensitive to the classified objects. LBP was then adopted to extract the spatial texture features. Finally, the feature vectors were formed by fusing spatial–spectral features and input into BPNN for HSI classification. Three key parameters including the number of principal components (p) and the neurons in the hidden layer (l) as well as the learning rate (r) were optimally selected to improve the classification accuracy. Three publicly available hyperspectral datasets including Pavia University (PU), Salinas (Sa) and Botswana (Bo) were selected to validate the performance by comparing the kNN (k-Nearest Neighbor), SVM (Support Vector Machine) and Contextual Deep Convolutional Neural Network (CDCNN). The overall accuracy of PCA-LBP-BPNN reached 93.67%, 98.09% and 92.97%, respectively, for the three datasets. The method had a satisfying performance than kNN, SVM and CDCNN for the PU and Sa, but it had lower accuracies than kNN and CDCNN for the Bo due to extremely similar spectral responses. PCA-LBP-BPNN generally has satisfactory practicability and robustness in adapting to different hyperspectral datasets.

Online monitoring and real-time feedback on inclusions in molten metal are essential for metal quality control. However, existing methods for detecting aluminum melt inclusions face challenges, including interference, prolonged processing times, and latency. This paper presents the design and development of an online monitoring system for molten metal inclusions. Initially, the system facilitates real-time adjustment of signal acquisition parameters through a multiplexer. Subsequently, it employs a detection algorithm capable of swiftly extracting pulse peaks, with this task integrated into our proprietary host computer software to ensure timely detection and data visualization. Ultimately, we developed a monitoring device integrated with this online monitoring system, enabling the online monitoring of the aluminum alloy filtration process. Our findings indicate that the system can accurately measure the size and concentration of inclusions during the filtration process in real time, offering enhanced detection speed and stability compared to the industrial LiMCA CM (liquid metal cleanliness analyzer continuous monitoring) standard. Furthermore, our evaluation of the filtration process demonstrates that the effectiveness of filtration significantly improves with the increase in inclusion sizes, and the synergistic effect of combining CFF (ceramic foam filter) and MCF (metallics cartridge filter) filtration methods exceeds the performance of the CFF method alone. This system thus provides valuable technical support for optimizing filtration processes and controlling inclusion quality.

Traditional methods for assessing the cleanliness of liquid metal are characterized by prolonged detection times, delays, and susceptibility to variations in sampling conditions. To address these limitations, an online cleanliness-analyzing system grounded in the method of the electrical sensing zone has been developed. This system facilitates real-time, in situ, and quantitative analysis of inclusion size and amount in liquid metal. Comprising pneumatic, embedded, and host computer modules, the system supports the continuous, online evaluation of metal cleanliness across various metallurgical processes in high-temperature environments. Tests conducted with gallium liquid at 90 °C and aluminum melt at 800 °C have validated the system’s ability to precisely and quantitatively detect inclusions in molten metal in real time. The detection procedure is stable and reliable, offering immediate data feedback that effectively captures fluctuations in inclusion amount, thereby meeting the metallurgical industry’s demand for real-time analyzing and control of inclusion cleanliness in liquid metal. Additionally, the system was used to analyze inclusion size distribution during the hot-dip galvanizing process. At a zinc melt temperature of 500 °C, it achieved a detection limit of 21 μm, simultaneously providing real-time data on the size and amount distribution of inclusions. This represents a novel strategy for the online monitoring and quality control of zinc slag throughout the hot-dip galvanizing process.

To address the most significant environmental challenges, the quest for high-performance gas sensing materials is crucial. Among numerous two-dimensional materials, this study investigates the gas-sensitive capabilities of monolayer As, Sb, and Bi materials. To compare the gas detection abilities of these three materials, we employ first-principles calculations to comprehensively study the adsorption behavior of NO and NO2 gas molecules on the material surfaces. The results indicate that monolayer Bi material exhibits reasonable adsorption distances, substantial adsorption energies, and significant charge transfer for both NO and NO2 gases. Therefore, among the materials studied, it demonstrates the best gas detection capability. Furthermore, monolayer As and Sb materials exhibit remarkably high capacities for adsorbing NO and NO2 gas molecules, firmly interacting with the gas molecules. Gas adsorption induces changes in the material’s work function, suggesting the potential application of these two materials as catalysts.

The interfacial incompatibility of the poly (ethylene oxide)-based electrolytes hinder the longevity and further practice of all-solid-state batteries. Herein, we present a productive additive 1-Fluoroadamantane facilitating to the distinct performance of the poly (ethylene oxide)-based electrolytes. Attributed to the strong molecular interaction, the coordination of the Li+-EO is reduced and the ‘bonding effect’ of anion is improved. Thus, the Li + conductivity is promoted and the electrochemical window is widened. The diamond building block C10H15− strengthens the stability of the solid polymer electrolytes. Importantly, the 1-Fluoroadamantane mediates the generation of LiF in the interfaces, which fosters the interfacial stability, contributing to the long-term cycling. Hence, the symmetric cell (Li/Li) exhibits a long-term lithium plating/stripping for over 2,400 h. The 4.3 V LiNi0.8Mn0.1Co0.1O2/Li all-solid-state battery with the 1-Fluoroadamantane-poly (ethylene oxide) improved electrolyte delivers 600 times, with an impressive capacity retention of 84%. Also, the cell presents high capacity of 210 mA·h/g, and 170 mA·h/g at 0.1 C and 0.3 C respectively, rivalling the liquid electrolytes.

Background Neurogenic bladder (NB) following suprasacral spinal cord injury (SSCI) is an interstitial disease with the structural remodeling of bladder tissue and matrix over-deposition. Circular RNAs (circRNAs) are involved in fibrotic disease development through their post-transcriptional regulatory functions. This study aimed to use transcriptome high-throughput sequencing to investigate the process of NB and bladder fibrosis after SSCI. Methods Spinal cord transection at the T10–T11 level was used to construct the SSCI model in rats (10–week–old female Wistar rats, weighing 200 ± 20 g). The bladders were collected without (sham group) and with (SSCI 1–3 groups) NB status. Morphological examination was conducted to assess the extent of bladder fibrosis. Additionally, RNA sequencing was utilized to determine mRNAs and circRNAs expression patterns. The dynamic changes of differentially expressed mRNAs (DEMs) and circRNAs (DECs) in different periods of SSCI were further analyzed. Results Bladder weight, smooth muscle cell hypertrophy, and extracellular matrix gradually increased after SSCI. Compared with the sham group, 3,255 DEMs and 1,339 DECs, 3,449 DEMs and 1,324 DECs, 884 DEMs, and 1,151 DECs were detected in the SSCI 1–3 groups, respectively. Specifically, circRNA3621, circRNA0617, circRNA0586, and circRNA4426 were significant DECs common to SSCI 1–3 groups compared with the sham group. Moreover, Gene Ontology (GO) enrichment suggested that inflammatory and chronic inflammatory responses were the key events in NB progression following SSCI. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment associated with the “Chemokine signaling pathway”, the “IL-17 signaling pathway”, and the “TGF-beta signaling pathway” suggests their potential involvement in regulating biological processes. The circRNA–miRNA–mRNA interaction networks of DECs revealed rno-circ-2239 (micu2) as the largest node, indicating that the rno-circ-2239–miRNA–mRNA–mediated network may play a critical role in the pathogenesis of SSCI-induced NB. Conclusions This study offers a comprehensive outlook on the possible roles of DEMs and DECs in bladder fibrosis and NB progression following SSCI. These findings have the potential to serve as novel biomarkers and therapeutic targets.

Abstract Nephrotoxicity has become prominent due to the increase in the clinical use of nilotinib, a second‐generation BCR‐ABL1 inhibitor in the first‐line treatment of Philadelphia chromosome‐positive chronic myeloid leukemia. To date, the mechanism of nilotinib nephrotoxicity is still unknown, leading to a lack of clinical intervention strategies. Here, it is found that nilotinib could induce glomerular atrophy, renal tubular degeneration, and kidney fibrosis in an animal model. Mechanistically, nilotinib induces intrinsic apoptosis by specifically reducing the level of BCL2 like 1 (Bcl‐XL) in both vascular endothelial cells and renal tubular epithelial cells, as well as in vivo. It is confirmed that chloroquine (CQ) intervenes with nilotinib‐induced apoptosis and improves mitochondrial integrity, reactive oxygen species accumulation, and DNA damage by reversing the decreased Bcl‐XL. The intervention effect is dependent on the alleviation of the nilotinib‐induced reduction in ubiquitin specific peptidase 13 (USP13) and does not rely on autophagy inhibition. Additionally, it is found that USP13 abrogates cell apoptosis by preventing excessive ubiquitin‒proteasome degradation of Bcl‐XL. In conclusion, the research reveals the molecular mechanism of nilotinib's nephrotoxicity, highlighting USP13 as an important regulator of Bcl‐XL stability in determining cell fate, and provides CQ analogs as a clinical intervention strategy for nilotinib's nephrotoxicity.

Summary: Large biosynthetic gene cluster (BGC) cloning is important for discovering natural product-based drugs and remains challenging in high GC content microorganisms (e.g., Actinobacteria). Here, we present an in vitro CRISPR-Cas12a-mediated protocol for direct cloning of large DNA fragments. We describe steps for crRNA design and preparation, genomic DNA isolation, and CRISPR-Cas12a cleavage and capture plasmid construction and linearization. We then detail target BGC and plasmid DNA ligation and transformation and screening for positive clones.For complete details on the use and execution of this protocol, please refer to Liang et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Social networks are becoming increasingly popular and significant. One of the most distinctive features of these networks is their dynamic nature, which means that they change over time. Consequently, the community structure on these platforms also changes with time, making the detection of community structure a crucial area of research. Specifically, there is still a lack of understanding of how social networks and communities evolve over time. In this paper, we reveal that individual changing topics (i.e., individual temporal semantics) are a vital factor that drives community evolution. A novel dynamic community detection model is proposed, which takes into account natural evolutionary features. The model first partitions social networks into snapshots. It then detects the community structure at each snapshot by utilizing individual changing topics and information from the previous snapshot. Finally, the evolution of users’ interested topic distributions and topic distributions of communities are identified. The model is compared with five state-of-the-art baselines on two real datasets, and the experimental results demonstrate that our model outperforms all baselines.

Speech Emotion Recognition (SER) is a common aspect of human-computer interaction and has significant applications in fields such as healthcare, education, and elder care. Although researchers have made progress in speech emotion feature extraction and model identification, they have struggled to create an SER system with satisfactory recognition accuracy. To address this issue, we proposed a novel algorithm called F-Emotion to select speech emotion features and established a parallel deep learning model to recognize different types of emotions. We first extracted the emotion features from speech and calculated the F-Emotion value for each feature. These values were then used to determine the combination of speech emotion features that was optimal for speech emotion recognition. Next, a parallel deep learning model was established with the speech emotion feature combination as input to train and test for each type of emotion. Finally, decision fusion was applied to the parallel output results to obtain an overall recognition result. These analyses were conducted on two datasets, RAVDESS and EMO-DB, with the accuracy of speech emotion recognition reaching 82.3% and 88.8%, respectively. The results demonstrate that the F-Emotion algorithm can effectively analyze the correspondence between speech emotion features and emotion types. The MFCC feature best describes emotions of neutrality, happiness, fear, and surprise, and Mel best describes emotions of anger and sadness. The parallel deep learning model mechanism can improve the accuracy of speech emotion recognition.

Abstract Background As the main cause of cancer death, lung cancer imposes seriously health and economic burdens on individuals, families, and the health system. In China, there is no national study analyzing the hospitalization expenditures of different payment methods by lung cancer inpatients. Based on the 2010–2016 database of insured urban resident lung cancer inpatients from the China Medical Insurance Research Association (CHIRA), this paper aims to investigate the characteristics and cost of hospitalized lung cancer patient, to examine the differences in hospital expenses and patient out-of-pocket (OOP) expenses under four medical insurance payment methods: fee-for-service (FFS), per-diem payments, capitation payments (CAP) and case-based payments, and to explore the medical insurance payment method that can be conducive to controlling the cost of lung cancer. Method This is a 2010–2016, 7-year cross-sectional study. CHIRA data are not available to researchers after 2016. The Medical Insurance Database of CHIRA was screened using the international disease classification system to yield 28,200 inpatients diagnosed with lung cancer (ICD-10: C34, C34.0, C34.1, C34.2, C34.3, C34.8, C34.9). The study includes descriptive analysis and regression analysis based on generalized linear models (GLM). Results The average patient age was 63.4 years and the average length of hospital stay (ALOS) was 14.2 day; 60.7% of patients were from tertiary hospitals; and 45% were insured by FFS. The per-diem payment had the lowest hospital expenses (RMB7496.00/US$1176.87), while CAP had the lowest OOP expenses (RMB1328.18/US$208.52). Compared with FFS hospital expenses, per-diem was 21.3% lower (95% CI = -0.265, -0.215) and case-based payment was 8.4% lower (95% CI = -0.151, -0.024). Compared with the FFS, OOP expenses, per-diem payments were 9.2% lower (95% CI = -0.130, -0.063) and CAP was 15.1% lower (95% CI = -0.151, -0.024). Conclusion For lung cancer patients, per-diem payment generated the lowest hospital expenses, while CAP meant patients bore the lowest OOP costs. Policy makers are suggested to give priority to case-based payments to achieve a tripartite balance among medical insurers, hospitals, and insured members. We also recommend future studies comparing the disparities of various diseases for the cause of different medical insurance schemes.

Abstract Objectives We investigated both the metabolic differences and interictal/ictal discharges of the anterior nucleus of the thalamus (ANT) in patients with epilepsy to clarify the relationship between the ANT and the epileptic network. Methods Nineteen patients with drug‐resistant epilepsy who underwent stereoelectroencephalography were studied. Metabolic differences in ANT were analyzed using [18F] fluorodeoxyglucose–positron emission tomography with three‐dimensional (3D) visual and quantitative analyses. Interictal and ictal discharges in the ANT were analyzed using visual and time‐frequency analyses. The relationship between interictal discharge and metabolic differences was analyzed. Results We found that patients with temporal lobe epilepsy (TLE) showed significant metabolic differences in bilateral ANT compared with extratemporal lobe epilepsy in 3D visual and quantitative analyses. Four types of interictal activities were recorded from the ANT: spike, high‐frequency oscillation (HFO), slow‐wave, and α‐rhythmic activity. Spike and HFO waveforms were recorded mainly in patients with TLE. Two spike patterns were recorded: synchronous and independent. In 83.3% of patients, ANT was involved during seizures. Three seizure onset types of ANT were recorded: low‐voltage fast activity, rhythmic spikes, and theta band discharge. The time interval of seizure onset between the seizure onset zone and ANT showed two patterns: immediate and delayed. Interpretation ANT can receive either interictal discharges or ictal discharges which propagate from the epileptogenic zones. Independent epileptic discharges can also be recorded from the ANT in some patients. Metabolic anomalies and epileptic discharges in the ANT indicate that the ANT plays a role in the epileptic network in most patients with epilepsy, especially TLE.

Abstract As a power electronic converter with bidirectional energy transmission, the Dual Active Bridge (DAB) has a broad application prospect in the electrical power distribution system of hybrid‐electric flight. For the DAB application in the electrical power distribution system, high efficiency and high reliability are envisaged due to the mission‐critical nature of the application. A new pulse width modulation optimization control strategy is proposed, which is based on the feedback temperature fluctuations of the GaN (Gallium Nitride) power transistors, to improve the lifetime of the whole circuit. The complete topology and simulations of the DAB converter are carried out in PLECS. Detailed simulation results manifest the precise lifetime of the GaN power transistors and verify the accuracy of the new optimization control strategy. Meanwhile, Insulated Gate Bipolar Translator is set as a control group to compare the lifetime of conventional silicon‐based power devices with the GaN power transistor. Hardware In Loop platform test is built to further validate the proposed method.

This paper summarizes the research progress on the types of interactions between proteins and polyphenols and their effects on protein characteristics, and prospects the future foods with the coexistence of polyphenols and proteins.

Abstract Background Peritoneal dialysis (PD) is an effective and successful renal replacement therapy. The baseline peritoneal solute transfer rate (PSTR) is related to local membrane inflammation and may be partially genetically determined. Herein, we focused on vascular endothelial growth factor (VEGF) and its receptor, kinase insert domain containing receptor (KDR). Methods This study recruited 200 PD patients from Renji Hospital in Shanghai, China. We analysed the association between the polymorphisms of VEGF and KDR and the 4-hour dialysate-to-plasma ratio for creatinine (4 h D/P Cr), which was measured between one and three months after initiating PD. Results The CC genotype in VEGF rs3025039 and the AA genotype in KDR rs2071559 were both positively associated with a fast baseline PSTR (VEGF rs3025039 CC vs. TT + TC: 0.65 ± 0.12 vs. 0.61 ± 0.11; P = 0.029; KDR rs2071559 AA vs. GA + GG: 0.65 ± 0.12 vs. 0.62 ± 0.12; P = 0.039). Conclusion Baseline PSTR was partly determined by VEGF and KDR gene polymorphisms.

The accuracy of Monte Carlo (MC) simulations in estimating the computed tomography radiation dose is highly dependent on the accuracy of CT scanner model. A system was developed to observe the 3D model intuitively and to calculate the X-ray energy spectrum and the bowtie (BT) filter model more accurately in Monte Carlo N-particle (MCNP). Labview's built-in Open Graphics Library (OpenGL) was used to display basic surfaces, and constructive solid geometry (CSG) method was used to realize Boolean operations. The energy spectrum was calculated by simulating the process of electronic shooting and the BT filter model was accurately modeled based on the calculated shape curve. Physical data from a study was used as an example to illustrate the accuracy of the constructed model. RMSE between the simulation and the measurement results were 0.97% and 0.74% for two filters of different shapes. It can be seen from the comparison results that to obtain an accurate CT scanner model, physical measurements should be taken as the standard. The energy spectrum library should be established based on Monte Carlo simulations with modifiable input files. It is necessary to use the three-segment splicing modeling method to construct the bowtie filter model.

BackgroundsThe coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a global threat since 2020. The emergence of the Omicron variant in 2021, which replaced Delta as the dominant variant of concern, has had a significant adverse impact on the global economy and public health. During this period, Zhejiang Province implemented dynamic zeroing and focused on preventing imported cases. This study aimed to gain clear insight into the characteristics of imported COVID-19 cases in Zhejiang Province.MethodsWe conducted a systematic molecular epidemiological analysis of 146 imported cases between July 2021 and November 2022 in Zhejiang Province. Virus samples with cycle threshold (Ct) value less than 32 were performed next generation sequencing. Basing the whole genome sequence obtained after quality control and assembly of reads, the whole genome variation map and phylogenetic tree were constructed and further analyzed.ResultsOur study identified critical months and populations for surveillance, profiled the variation of various lineages, determined the evolutionary relationships among various lineages of SARS-CoV-2, and compared the results in Zhejiang with those obtained worldwide during this period.ConclusionThe continuous molecular epidemiological surveillance of imported cases of COVID-19 in Zhejiang Province during 2021 to 2022 is consistent with the global epidemic trend.

Metamaterials with low-frequency band gap have always been the focus of research. For this reason, many researchers have proposed many structural design schemes. In this paper, an innovative star-shaped hybrid metamaterial structure is proposed. Based on Bloch's theorem and finite element method, a dynamic model of the proposed structure is established, the band gap characteristics of the proposed structure are analyzed, and the generation mechanism of band gap is discussed with the mode shape of specific frequency. Then, the propagation characteristics of elastic wave in the proposed structure are analyzed by using the dispersion surface and group velocity images, and the attenuation region of vibration transmission in the finite periodic structure is consistent with the frequency range of band gap. Finally, the relationship between band gap and structure parameters is explored. The results show that the proposed structure has good band gap characteristics in the frequency range of 1000 Hz, the lowest frequency of band gap reaches 60.207 Hz, and the total band gap width accounts for 54.463%. This research opens up an ideological route for the design of low frequency metamaterial structures.

Chlamydia psittaci is the pathogen of psittacosis and infects a wide range of birds and even humans. Human infection occurs most commonly in those with a history of contact with birds or poultry. We describe a case of psittacosis in a human immunodeficiency virus infected patient in Zhejiang Province for the first time. C. psittaci infection was confirmed by nested polymerase chain reaction (PCR) and Real-Time PCR. Phylogenetic analysis revealed that the sequences from the patient’s samples clustered with genotype A in the same branch. Our study highlights the possibility of diagnosing psittacosis in patients with a chronic disease such as HIV-infected patients, and should increase awareness and surveillance of psittacosis in China.

ObjectiveBy studying the surgical outcome of deep brain stimulation (DBS) of different target nuclei for patients with refractory epilepsy, we aimed to explore a clinically feasible target nucleus selection strategy.MethodsWe selected patients with refractory epilepsy who were not eligible for resective surgery. For each patient, we performed DBS on a thalamic nucleus [anterior nucleus of the thalamus (ANT), subthalamic nucleus (STN), centromedian nucleus (CMN), or pulvinar nucleus (PN)] selected based on the location of the patient's epileptogenic zone (EZ) and the possible epileptic network involved. We monitored the clinical outcomes for at least 12 months and analyzed the clinical characteristics and seizure frequency changes to assess the postoperative efficacy of DBS on the different target nuclei.ResultsOut of the 65 included patients, 46 (70.8%) responded to DBS. Among the 65 patients, 45 underwent ANT-DBS, 29 (64.4%) responded to the treatment, and four (8.9%) of them reported being seizure-free for at least 1 year. Among the patients with temporal lobe epilepsy (TLE, n = 36) and extratemporal lobe epilepsy (ETLE, n = 9), 22 (61.1%) and 7 (77.8%) responded to the treatment, respectively. Among the 45 patients who underwent ANT-DBS, 28 (62%) had focal to bilateral tonic-clonic seizures (FBTCS). Of these 28 patients, 18 (64%) responded to the treatment. Out of the 65 included patients, 16 had EZ related to the sensorimotor cortex and underwent STN-DBS. Among them, 13 (81.3%) responded to the treatment, and two (12.5%) were seizure-free for at least 6 months. Three patients had Lennox–Gastaut syndrome (LGS)-like epilepsy and underwent CMN-DBS; all of them responded to the treatment (seizure frequency reductions: 51.6%, 79.6%, and 79.5%). Finally, one patient with bilateral occipital lobe epilepsy underwent PN-DBS, reducing the seizure frequency by 69.7%.SignificanceANT-DBS is effective for patients with TLE or ETLE. In addition, ANT-DBS is effective for patients with FBTCS. STN-DBS might be an optimal treatment for patients with motor seizures, especially when the EZ overlaps the sensorimotor cortex. CMN and PN may be considered modulating targets for patients with LGS-like epilepsy or occipital lobe epilepsy, respectively.

Objective: To establish a new animal model of intervertebral disc degeneration (IDD) by axial compression on lumbar spine of rabbits and to investigate the changes of microcirculation in bony endplates during the progress of IDD. Methods: 32 New Zealand white rabbits were equally divided into 4 groups as follows: Control group with no operation and compression, Sham operation group with apparatus placement only, 2-week compression group and 4-week compression group with the devices installed and compressed for their preset duration. All groups of rabbits underwent MRI, histological evaluation, disc height index measurement and Microfil contrast agent perfusions to examine the ratio of endplate microvascular channels. Results: The new animal model of IDD was successfully established after axial compression for 4 weeks. The MRI grades for the 4-week compression group was 4.63 ± 0.52 and significantly different to the sham operation group (P

In this paper, novel two-dimensional single-phase three-ligament, four-ligament and six-ligament chiral structure models are proposed. The advantage is that it is easy to manufacture with few components, has good sound insulation and vibration damping performance, and is more practical. The dispersion information of the structure is calculated by combining Bloch's theorem and the finite element method. By varying the geometric parameters of the new structural single-cell and simulating the vibration transmission of the finite period structure to check the vibration suppression capability of the optimized structure. Three combined structures were constructed to compare their energy band properties with the base structure. The wave propagation characteristics within the combined structure are also analyzed by comprehensive means. It is shown that the optimized structure has a significantly lower bandgap down to below 1 kHz and a significantly wider bandgap width up to 3.6 kHz. The combined structure can open up a wider omnidirectional bandgap for multi-frequency and broadband vibration attenuation. The flexibility of the structure combination gives it a large potential for use, providing a new solution for broadband and multi-frequency vibration and noise reduction, while plane wave analysis provides theoretical support for structural optimization.

The approach of dynamic tracking and counting for obscured citrus based on machine vision is a key element to realizing orchard yield measurement and smart orchard production management. In this study, focusing on citrus images and dynamic videos in a modern planting mode, we proposed the citrus detection and dynamic counting method based on the lightweight target detection network YOLOv7-tiny, Kalman filter tracking, and the Hungarian algorithm. The YOLOv7-tiny model was used to detect the citrus in the video, and the Kalman filter algorithm was used for the predictive tracking of the detected fruits. In order to realize optimal matching, the Hungarian algorithm was improved in terms of Euclidean distance and overlap matching and the two stages life filter was added; finally, the drawing lines counting strategy was proposed. ln this study, the detection performance, tracking performance, and counting effect of the algorithms are tested respectively; the results showed that the average detection accuracy of the YOLOv7-tiny model reached 97.23%, the detection accuracy in orchard dynamic detection reached 95.12%, the multi-target tracking accuracy and the precision of the improved dynamic counting algorithm reached 67.14% and 74.65% respectively, which were higher than those of the pre-improvement algorithm, and the average counting accuracy of the improved algorithm reached 81.02%. The method was proposed to effectively help fruit farmers grasp the number of citruses and provide a technical reference for the study of yield measurement in modernized citrus orchards and a scientific decision-making basis for the intelligent management of orchards.

This paper proposes a fundamental investigation of coal gangue and fly ash impact on B. pasteurii to enhance the properties of backfill materials. The goal is to obtain effective microbial mineralization and potential mechanical properties of coal gangue and fly ash as backfill materials and to mitigate the impact of the most common binders used in the backfill material of mines. Micro-scale mineralization was performed with B. pasteurii bacteria using microbially induced carbonate precipitation (MICP) technology to clarify solid waste impact on B. pasteurii and to bind coal gangue and fly ash. Several tests were carried out to analyze the behavior of B. pasteurii, especially when it coexists with these two waste materials separately. In such cases, it was possible to observe a reduction in mineralization initiation time with respect to the natural mineralization of the MICP technology. Moreover, at the macro-scale, the new mineralized backfilling material shows good workability in the fresh state, whereas the strength at 28 days is 5.34 times higher than that obtained with non-mineralized coal gangue and fly ash.

Engineered crystal architectures from DNA have become a foundational goal for nanotechnological precise arrangement. Here, the authors systematically investigate the structures of 36 immobile Holliday junction sequences and identify the features allowing the crystallisation of most of them, while 6 are considered fatal.

Abstract Self-assembled photonic systems with well-organized spatial arrangement and engineered optical properties can be used as efficient energy materials and as effective biomedical agents. The lessons learned from natural light-harvesting antennas have inspired the design and synthesis of a series of biomimetic photonic complexes, including those containing strongly coupled dye aggregates with dense molecular packing and unique spectroscopic features. These photoactive components provide excellent features that could be coupled to multiple applications including light-harvesting, energy transfer, biosensing, bioimaging, and cancer therapy. Meanwhile, nanoscale DNA assemblies have been employed as programmable and addressable templates to guide the formation of DNA-directed multi-pigment complexes, which can be used to enhance the complexity and precision of artificial photonic systems and show the potential for energy and biomedical applications. This review focuses on the interface of DNA nanotechnology and biomimetic photonic systems. We summarized the recent progress in the design, synthesis, and applications of bioinspired photonic systems, highlighted the advantages of the utilization of DNA nanostructures, and discussed the challenges and opportunities they provide. Graphical Abstract

While cervical total artificial disc replacement potentially preserves motion of the natural intervertebral disc (IVD), problems also arise involving alterations of the spinal biomechanics. A major challenge lies in restoring mechanics of the natural IVD with appropriate kinematics and biomimetic configuration. A biomimetic artificial IVD model is designed and fabricated using a 3D braided fibrous scaffold and a self‐healable hydrogel matrix. The artificial IVD is characterized by 3D four‐directional fibrous structure resembling natural annulus fibrosus and self‐healable hydrogel‐mimicking natural nucleus pulposus. In the compression tests, the artificial IVD exhibits reasonable mechanical behaviors and desired viscoelastic behaviors similar to the natural IVD. After fatigue loading of 5 million cycles, the artificial IVDs become stiffer, whereas the mechanical values remain within the reasonable range. Finite‐element analysis of the artificial IVD from mesoscale and macroscale analysis indicates the coherent load transfer through both the interconnections within the fiber mesh and the fiber–matrix interface, and the entire IVD shows a stress profilometry similar to natural IVD. In conclusion, a biomimetic prototype of artificial IVD with nature‐mimicking mechanics and structure is fabricated. The presence of interwoven fibrous mesh, hydrogel confinement, and proper interfacial adhesion is all essential for scalable production of the IVD.

ObjectiveThe COVID-19 pandemic has challenged the health system worldwide. This study aimed to assess how China’s hierarchical medical system (HMS) coped with COVID-19 in the short-and medium-term. We mainly measured the number and distribution of hospital visits and healthcare expenditure between primary and high-level hospitals during Beijing’s 2020–2021 pandemic relative to the 2017–2019 pre-COVID-19 benchmark period.MethodsHospital operational data were extracted from Municipal Health Statistics Information Platform. The COVID-19 period in Beijing was divided into five phases, corresponding to different characteristics, from January 2020 to October 2021. The main outcome measures in this study include the percentage change in inpatient and outpatient emergency visits, and surgeries, and changing distribution of patients between different hospital levels across Beijing’s HMS. In addition, the corresponding health expenditure in each of the 5 phases of COVID-19 was also included.ResultsIn the outbreak phase of the pandemic, the total visits of Beijing hospitals declined dramatically, where outpatient visits fell 44.6%, inpatients visits fell 47.9%; emergency visits fell 35.6%, and surgery inpatients fell 44.5%. Correspondingly, health expenditures declined 30.5% for outpatients and 43.0% for inpatients. The primary hospitals absorbed a 9.51% higher proportion of outpatients than the pre-COVID-19 level in phase 1. In phase 4, the number of patients, including non-local outpatients reached pre-pandemic 2017–2019 benchmark levels. The proportion of outpatients in primary hospitals was only 1.74% above pre-COVID-19 levels in phases 4 and 5. Health expenditure for both outpatients and inpatients reached the baseline level in phase 3 and increased nearly 10% above pre-COVID-19 levels in phases 4 and 5.ConclusionThe HMS in Beijing coped with the COVID-19 pandemic in a relatively short time, the early stage of the pandemic reflected an enhanced role for primary hospitals in the HMS, but did not permanently change patient preferences for high-level hospitals. Relative to the pre-COVID-19 benchmark, the elevated hospital expenditure in phase 4 and phase 5 pointed to hospital over-treatment or patient excess treatment demand. We suggest improving the service capacity of primary hospitals and changing the preferences of patients through health education in the post-COVID-19 world.

To achieve multi-frequency vibration suppression and wave propagation modulation, eight branching ligament structures for wind models are proposed. Using lattice theory, dynamical model and finite element release method, the structures are verified to have multi-frequency bandgaps. By attaching a solid disc at the center of the model, the bandgap coverage of the structure is improved and the bandgap frequency is reduced. The modal analysis shows that the vibration of branch ligaments and border ligaments has a suppression effect on elastic waves. The phase constant surface, phase velocity and wave propagation direction plots at specific frequencies are calculated to verify the directional and regional nature of wave propagation. And the good correspondence of group velocity and wave propagation finite element simulation results at specific frequencies. Finally, the calculated bandgap frequency range is compared with the vibration transfer function, and the two agree well. And the stress cloud diagram also shows that the optimized structure has an excellent vibration suppression capability. The innovatively designed structure has the combined advantages of light weight, ease of fabrication, wide frequency and low frequency vibration control, while the integrated in-plane wave analysis provides the theoretical basis for structural optimization.

BackgroundAn increasing number of studies have focused on the role of gut microbiota in the treatment of ADHD, but its related molecular mechanisms are not yet clear, and there is still room for development of studies targeting this area. This study analyzes publications from 2012 to 2021 in a comprehensive and multi-faceted visualization, with the aim of grasping the existing research profile and guiding scholars to make more in-depth studies.MethodsThe 1,677 articles and 298 review articles on gut microbiota in ADHD were retrieved from the Web of Science Core Collection. CiteSpace, VOSviewer, Microsoft Excel 2019, Scimago Graphica, Bibliometrix and Pajek metrics software were used for visualization and analysis of the included literature.ResultsOn August 3, 2022, a total of 1975 English-language articles on gut microbiota in ADHD were retrieved from Web of Science Core Collection (WoSCC) from January 2012 to December 2021, with a steady upward trend in the number of articles published in this field over the decade. The top three countries in terms of the number of articles published are the United States, China, and Spain. Meanwhile, CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS CSIC, UNIV OF CALIFORNIA SYSTEM, and UDICE FRENCH RESEARCH UNIV have made significant contributions in this field. In the analysis of the published journals, PLoS One was not only the first in terms of number of articles published but also the most cited. Wang J was the most prolific author and CAPORASO JG ranked first in terms of co-cited authors. In addition, “Diet rapidly and reproducibly alters the human gut microbiome,” published by David LA et al., has the highest citation frequency in this field. The most frequently occurring keyword was “gut microbiota.”ConclusionThe results of this paper clarify the current status of research on gut microbiota in ADHD. Based on the research on the mechanism of gut microbiota in other diseases, there is reason to believe that the exploration of gut microbiota in ADHD must be increasingly mature. And the study speculates that future research may focus on “nutrition supplements,” “lipid metabolism,” and “gut brain axis.” It is imperative to promote a closer international cooperation among scholars in this field.

BackgroundIdentifying high-risk groups of non-suicidal self-injury (NSSI) with multiple risk factors and different functional subtypes contribute to implementing person-centered interventions.MethodsWe investigated NSSI profiles among a sample of 258 psychiatric inpatients aged 18–25 years. All participants completed well-validated measures of internal personal and external environmental characteristics. One-hundred and ninety patients reported a lifetime history of NSSI and completed an additional NSSI assessment. A k-means cluster analysis was conducted to extract characteristics of risk factors and functional subtypes. Independent sample t-test, analysis of variance and χ2 test were used to test the difference of demographic statistical factors, risk factors and functional scores among groups with different frequency of NSSI.ResultsThe clustering of risk factors analyses supported 4-clusters. The proportion of repeat NSSI patients was the highest (67.1%) in the group with unfavorable personal and unfavorable environmental characteristics. Functional subtype clustering analyses supported 5-clusters. Among patients with repeated NSSI, those with depression were mainly accompanied by the “Sensation Seeking” subtype (39.7%), bipolar disorder mainly supported the “Anti-suicide” subtype (37.9%), and eating disorders were mostly “Social Influence” subtype (33.3%). There was an interaction between functional subtypes and mental disorders.LimitationsAll participants were in treatment in a psychiatric service and the results may not be generalizable to a community sample. The data included retrospective self-report which may be inaccurate due to recall bias.ConclusionIt is necessary to identify high-risk groups of NSSI who with unfavorable personal and environmental characteristics and clinical interventions need to consider the heterogeneity of patients’ functional subtypes of NSSI.

Artificial systems to control the transport of molecules across biomembranes can be useful for biosensing or drug delivery. Here, the authors assemble a DNA channel enabling the precisely timed, stimulus-controlled transport of functional proteins across bilayer membranes.

Abstract QTc interval prolongation is one of the most common antipsychotic-induced side effects which could lead to ventricular tachycardia or Torsade de Pointes, even cardiac arrest. There is very limited understanding on the genetic factors that associated with antipsychotic-induced QTc interval change. We conducted a genome-wide association study (GWAS) of antipsychotic-induced QTc interval change among patients with schizophrenia. A total of 2040 patients with schizophrenia were randomly assigned to six groups (olanzapine, risperidone, quetiapine, aripiprazole, ziprasidone, and first-generation antipsychotics; first-generation antipsychotics including haloperidol or perphenazine were also assigned randomly) and received 6-week antipsychotic treatment. We identified two novel loci (rs200050752 in ATAD3B and rs186507741 in SKIL) that were associated with antipsychotic-induced QTc interval change at a genome-wide significance level. The combination of polygenic risk score (PRS), based the GWAS of myocardial infarction from BioBank Japan project, and clinical data (sex, heart rate and QTc interval at baseline) could be applied to predict whether patients with schizophrenia have QTc interval prolongation (10 ms was applied as threshold, P

Abstract Papillary thyroidal carcinoma (PTC) is a common endocrine cancer that plagues people across the world. The potential roles of long non-coding RNAs (lncRNAs) in PTC have gained increasing attention. In this study, we aimed to explore whether lncRNA ROR affects the progression of PTC, with the involvement of tescalcin (TESC)/aldehyde dehydrogenase isoform 1A1 (ALDH1A1)/βIII-tubulin (TUBB3)/tensin homolog (PTEN) axis. PTC tumor and adjacent tissues were obtained, followed by measurement of lncRNA ROR and TESC, ALDH1A1, and TUBB3 expression. Interactions among lncRNA ROR, TESC, ALDH1A1, TUBB3, and PTEN were evaluated by ChIP assay, RT-qPCR, or western blot analysis. After ectopic expression and depletion experiments in PTC cells, MTT and colony formation assay, Transwell assay, and flow cytometry were performed to detect cell viability and colony formation, cell migration and invasion, and apoptosis, respectively. In addition, xenograft in nude mice was performed to test the effects of lncRNA ROR and PTEN on tumor growth in PTC in vivo. LncRNA ROR, TESC, ALDH1A1, and TUBB3 were highly expressed in PTC tissues and cells. Overexpression of lncRNA ROR activated TESC by inhibiting the G9a recruitment on the promoter of TESC and histone H3-lysine 9me methylation. Moreover, TESC upregulated ALDH1A1 expression to increase TUBB3 expression, which then reduced PTEN expression. Overexpression of lncRNA ROR, TESC, ALDH1A1 or TUBB3 and silencing of PTEN promoted PTC cell viability, colony formation, migration, and invasion while suppressing apoptosis. Moreover, overexpression of lncRNA ROR increased tumor growth by inhibiting PTEN in vivo. Taken together, the current study demonstrated that lncRNA ROR mediated TESC/ALDH1A1/TUBB3/PTEN axis, thereby facilitating the development of PTC.

Summary The redox‐sensitive transcriptional regulator SoxR is conserved in bacteria. Its role in mediating protective response to various oxidative stresses in Escherichia coli and related enteric bacteria has been well established. However, functions and regulatory mechanisms of SoxR in filamentous Streptomyces, which produce half of known antibiotics, are unclear. We report here that SoxR pleiotropically regulates antibiotic production, morphological development, primary metabolism and thiol‐oxidative stress response in industrially important species Streptomyces avermitilis. SoxR stimulated avermectin production by directly activating ave structural genes. Four genes (sav_3956, sav_4018, sav_5665 and sav_7218) that are homologous to targets of S. coelicolor SoxR are targeted by S. avermitilis SoxR. A consensus 18‐nt SoxR‐binding site, 5′‐VSYCNVVMHNKVKDGMGB‐3′, was identified in promoter regions of sav_3956, sav_4018, sav_5665, sav_7218 and target ave genes, leading to prediction of the SoxR regulon and confirmation of 11 new targets involved in development (ftsH), oligomycin A biosynthesis (olmRI), primary metabolism (metB, sav_1623, plcA, nirB, thiG, ndh2), transport (smoE) and regulatory function (sig57, sav_7278). SoxR also directly activated three key developmental genes (amfC, whiB and ftsZ) and promoted resistance of S. avermitilis to thiol‐oxidative stress through activation of target trx and msh genes. Overexpression of soxR notably enhanced antibiotic production in S. avermitilis and S. coelicolor. Our findings expand our limited knowledge of SoxR and will facilitate improvement of methods for antibiotic overproduction in Streptomyces species.

(1) Background: Cytoplasmic male sterility (CMS) is important for exploiting heterosis. Soybean (Glycine max L.) has a low outcrossing rate that is detrimental for breeding sterile lines and producing hybrid seeds. Therefore, the molecular mechanism controlling the outcrossing rate should be elucidated to increase the outcrossing rate of soybean CMS lines; (2) Methods: The male–sterile soybean lines JLCMS313A (with a high outcrossing rate; HL) and JLCMS226A (with a low outcrossing rate; LL) were used for a combined analysis of the transcriptome (RNA–seq) and the targeted phenol metabolome; (3) Results: The comparison between HL and LL detected 5946 differentially expressed genes (DEGs) and 81 phenolic metabolites. The analysis of the DEGs and differentially abundant phenolic metabolites identified only one common KEGG pathway related to flavonoid biosynthesis. The qRT–PCR expression for eight DEGs was almost consistent with the transcriptome data. The comparison of the cloned coding sequence (CDS) regions of the SUS, FLS, UGT, and F3H genes between HL and LL revealed seven single nucleotide polymorphisms (SNPs) only in the F3H CDS. Moreover, five significant differentially abundant phenolic metabolites between HL and LL were associated with flavonoid metabolic pathways. Finally, on the basis of the SNPs in the F3H CDS, one derived cleaved amplified polymorphic sequence (dCAPS) marker was developed to distinguish between HL and LL soybean lines; (4) Conclusions: The flavonoid biosynthesis pathway may indirectly affect the outcrossing rate of CMS sterile lines in soybean.

Aeolian sand (AS) and recycled coarse aggregate (RCA) can be reasonably utilized as green materials for concrete modification. The paucity of natural sand and gravel in the construction industry is anticipated to be remedied by the use of these two eco-friendly concrete ingredients. This is incredibly important for environmental protection. Study on the damage law of self-compacting concrete with the addition of AS and RCA (ARSCC) under severely cold conditions is of great significance for the promotion and implementation of this material. In this study, 12 groups of ARSCC specimens were prepared for freeze–thaw cycle experiments, with AS substitution rates of 0, 20%, 40%, and 60% as well as RCA replacement rates of 0, 25%, and 50%. Then, the degradation mechanism of ARSCC freeze–thaw damage was discussed from both macroscopic and microscopic perspectives via mass loss rate (Wn), relative dynamic modulus of elasticity (Pn), bubble spacing factor, and SEM analysis. Finally, the response surface method was utilized to determine the damage variable. A freeze–thaw damage model for ARSCC was developed based on the Weibull distribution and Grey theories. The results showed that the Pn could reflect the evolution law of the internal structure of ARSCC. Appropriate addition of AS to fill the large, harmful pores in RCA would inhibit freeze–thaw damage of ARSCC. The optimum substitution rates of AS and RCA were determined to be 20–40% and 25–50%, respectively. In addition, the values obtained from theoretical damage modeling and experiments were in good agreement. The acquired damage model had the potential to predict ARSCC damage under freeze–thaw cycles.

Strain engineering is an effective way to adjust the sensing properties of two-dimensional materials. In this paper, lateral heterojunctions (LHSs) based on arsenic and antimony have been designed along the armchair (AC) or zigzag (ZZ) edges. The adsorption and sensing characteristics of As/Sb LHSs to NO2 before and after applying different types of strain are calculated by first principles. The band gaps of all As/Sb heterostructures are contributed by As-p and Sb-p orbitals. In addition, the adsorption energy of As/Sb ZZ-LHS with −4% compression strain is the largest. Furthermore, its work function changes significantly before and after the adsorption of NO2. Meanwhile, strong orbital hybridizations near the Fermi level are observed and a new state is yielded after applying compressive strain. These results indicate that the As/Sb LHS with ZZ interface under −4% compression strain possesses the best sensing properties to NO2. This work lays the foundation for the fabrication of high-performance NO2 gas sensors. High-performance gas sensors can be used to track and regulate NO2 exposure and emission, as well as to track NO2 concentrations in the atmosphere and support the assessment of air quality.

Gangue-cemented paste backfill is one kind of paste backfill that is composed of cement, fly ash, and gangue, which is widely used in mining operation for controlling the strata movement and guaranteeing the safety of workplace. The knowledge of thermal conductivity of mine backfill is vital for understanding the thermal interaction of backfill with surrounding rock mass and therefore contributing to geothermal energy extraction with backfill technology in deep mines. Thermal conductivity of gangue-cemented paste backfill is investigated through laboratory tests in this article. The influences of mix proportion parameters and water saturation degree on the thermal conductivity of gangue-cemented paste backfill were analyzed. The results showed that thermal conductivity of gangue-cemented paste backfill markedly increased with the water/binder ratio from 0.35 to 0.55, while cement amount ranging from 4% to 12% had nearly no influence on the thermal conductivity. Meanwhile, the linear positive correlation was notable between thermal conductivity and water saturation degree of gangue-cemented paste backfill, which was interpreted from the perspective of component. The series model was found more reliable for predicting thermal conductivity of gangue-cemented paste backfill by importing the thermal conductivity and volume fraction of continuous paste and dispersed gangue separately. This study would provide a new insight into the design of backfill considering the thermal conductivity and lay a foundation for the efficient geothermal energy extraction in deep mines.

Private Set Intersection (PSI), which is a hot topic in recent years, has been extensively utilized in credit evaluation, medical system and so on. However, with the development of big data era, the existing traditional PSI cannot meet the application requirements in terms of performance and scalability. In this work, we proposed two secure and effective PSI (SE-PSI) protocols on scalable datasets by leveraging deterministic encryption and Bloom Filter. Specially, our first protocol focuses on high efficiency and is secure under a semi-honest server, while the second protocol achieves security on an economic-driven malicious server and hides the set/intersection size to the server. With experimental evaluation, our two protocols need only around 15 and 24 seconds respectively over one million-element datasets. Moreover, as a novelty, a multi-round mechanism is proposed for the two protocols to improve the efficiency. The implementation demonstrates that our two-round mechanism can enhance efficiency by almost twice than two basic protocols.

ROP is an important index to evaluate the efficiency of oil and gas drilling. In order to accurately predict the ROP of an oilfield in Xinjiang working area, a ROP prediction model based on the historical drilling data of this working area was established based on stacking ensemble learning. This model integrates the K-nearest neighbor algorithm and support vector machine algorithm by stacking ensemble strategy and uses genetic algorithm to optimize model parameters, forming a new method of ROP prediction suitable for this oilfield. The prediction results show that the accuracy of ROP prediction by this method is up to 92.5%, and the performance is stable, which can provide reference for the optimization of drilling parameters in this oilfield and has specific guiding significance for improving the efficiency of drilling operations.