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Abstract Background The utilization of long reads for single nucleotide polymorphism (SNP) phasing has become popular, providing substantial support for research on human diseases and genetic studies in animals and plants. However, due to the complexity of the linkage relationships between SNP loci and sequencing errors in the reads, the recent methods still cannot yield satisfactory results. Results In this study, we present a graph-based algorithm, GCphase, which utilizes the minimum cut algorithm to perform phasing. First, based on alignment between long reads and the reference genome, GCphase filters out ambiguous SNP sites and useless read information. Second, GCphase constructs a graph in which a vertex represents alleles of an SNP locus and each edge represents the presence of read support; moreover, GCphase adopts a graph minimum-cut algorithm to phase the SNPs. Next, GCpahse uses two error correction steps to refine the phasing results obtained from the previous step, effectively reducing the error rate. Finally, GCphase obtains the phase block. GCphase was compared to three other methods, WhatsHap, HapCUT2, and LongPhase, on the Nanopore and PacBio long-read datasets. The code is available from https://github.com/baimawjy/GCphase . Conclusions Experimental results show that GCphase under different sequencing depths of different data has the least number of switch errors and the highest accuracy compared with other methods.

Abstract Background Although early hemivertebra (HV) resection and short fusion (within 4 segments) have been successful in treating congenital HV, there is limited research comparing the outcomes of the shortest-segment fusion (2 segments) versus 3 or 4 segments, particularly in young children. To evaluate the efficacy of posterior hemivertebrectomy combined with two or more segments fusion in children under the age of 10 years with a solitary simple lower thoracic or lumbar HV (T8-L5). Methods This retrospective study included patients under the age of 10 with lower thoracic or lumbar solitary simple HV who underwent hemivertebra resection (HVR) and transpedicular short fusion and were divided into HV ± 1 group (2 segment fusion) and HV ± 2 group (3 or 4-segment fusion). The study recorded preoperative, postoperative (1 week), and the latest follow-up radiographic parameters and complications. The results of the coronal and sagittal planes were analyzed, and the main curve, segmental scoliosis curve, compensatory scoliosis curve, segmental kyphosis curve, and trunk shift were compared. Results The study included 35 patients (15 in the HV ± 1 group and 20 in the HV ± 2 group) with a mean age of 5.26 ± 2.31 years and a mean follow-up of 22.54 months (12–68). The mean preoperative Cobb angle was 32.66° ± 7.339° (HV ± 1) and 29.31°±6.642° (HV ± 2). The final Cobb angle was 10.99°± 7.837° (HV ± 1) and 8.22° ± 4.295° (HV ± 2). The main curve corrected by 72% (HV ± 1), 75% (HV ± 2) postoperatively and 67% (HV ± 1), 72% (HV ± 2) at the final follow-up (P > 0.05). There were no significant differences in the correction of the segmental scoliosis curve, compensatory scoliosis curve, segmental kyphosis curve, and trunk shift between the HV ± 1 and HV ± 2 groups (P > 0.05). The unplanned reoperation rate for HV in the thoracolumbar region (T11-L2) is significantly higher (P = 0.038). Conclusion In the context of solitary simple lower thoracic or lumbar HV (T8-L5), HV ± 1 segment fusion suffices and yields comparable correction outcomes in the midterm period when compared to HV ± 2. The reoperation rate exhibited a statistically significant increase in the thoracolumbar region.

Abstract Particulate organic nitrates (pON) significantly contribute to the mass of organic aerosol and influence the nitrogen oxides cycle in the atmosphere, but their evolution and lifetime remain uncertain. This study performed simultaneous measurements on the anthropogenically affected surface site and the mountain site on top of the polluted planetary boundary layer (PBL). After aging in the PBL, organic nitrate was converted from primary sources (decreased from 8.7% to 4.3%) to secondary sources (increased from 6.3% to 36.1%), spanning from the surface to the mountain. The evaporation of more volatile inorganic nitrate and the production of secondary organic nitrate during aging in the PBL contributed to the enhanced pON fraction over the top of PBL. The contribution of light absorption by brown carbon increased by 57% at the top of PBL compared to the surface, consistent with the higher fraction of nitrogenous organic aerosols over the mountain. The results provide field evidence that the nitrogenous organic aerosols (OA) may be preserved by adding into secondary OA and significantly contribute to the enhanced importance of brown carbon after aging during vertical transport in the PBL.

Background: Early evaluation of prognosis in cardiogenic shock (CS) is crucial for tailored treatment selection. Both lactate clearance and lactate levels are considered useful prognostic biomarkers in patients with CS. However, there is yet no literature comparing the 6-hour lactate clearance rate (Δ6Lac) with lactate levels measured at admission (L1) and after 6 h (L2) to predict 30-day mortality in CS. Methods: In this observational cohort study, 95 patients with CS were treated at Department of Intensive Care Unit, Yiwu Central Hospital between January 2020 and December 2022. Of these, 88 patients met the eligibility criteria. The lactate levels were measured after admission (L1) as the baseline lactate value, and were measured after 6 h (L2) following admission. The primary endpoint of the study was survival rate at 30 days. A receiver operating characteristic curve was used for data analysis. Univariate and multivariate Cox regression analyses were performed based on Δ6Lac. Kaplan–Meier (KM) survival curves were generated to compare the 30-day survival rates among L1, L2, and Δ6Lac. Results: The Δ6Lac model showed the highest area under the curve value (0.839), followed by the L2 (0.805) and L1 (0.668) models. The Δ6Lac model showed a sensitivity of 84.2% and specificity of 75.4%. The L1 and L2 models had sensitivities of 57.9% each and specificities of 89.9% and 98.6%, respectively. The cut-off values for Δ6Lac, L1, and L2 were 18.2%, 6.7 mmol/L, and 6.1 mmol/L, respectively. Univariate Cox regression analysis revealed a significant association between Δ6Lac and 30-day mortality. After adjusting for five models in multivariate Cox regression, Δ6Lac remained a significant risk factor for 30-day mortality in patients with CS. In our fifth multivariate Cox regression model, Δ6Lac remained a risk factor associated with 30-day mortality (hazard ratio [HR]=5.14, 95% confidence interval [CI]: 1.48 to 17.89, P=0.010) as well as L2 (HR=8.42, 95% CI: 1.26 to 56.22, P=0.028). The KM survival curve analysis revealed that L1 >6.7 mmol/L (HR=8.08, 95% CI: 3.23 to 20.20, P 6.1 mmol/L (HR=25.97, 95% CI: 9.76 to 69.15, P

Abstract N-Hydroxyapiosporamide (N-hydap), a marine product derived from a sponge-associated fungus, has shown promising inhibitory effects on small cell lung cancer (SCLC). However, there is limited understanding of its metabolic pathways and characteristics. This study explored the in vitro metabolic profiles of N-hydap in human recombinant cytochrome P450s (CYPs) and UDP-glucuronosyltransferases (UGTs), as well as human/rat/mice microsomes, and also the pharmacokinetic properties by HPLC–MS/MS. Additionally, the cocktail probe method was used to investigate the potential to create drug-drug interactions (DDIs). N-Hydap was metabolically unstable in various microsomes after 1 h, with about 50% and 70% of it being eliminated by CYPs and UGTs, respectively. UGT1A3 was the main enzyme involved in glucuronidation (over 80%), making glucuronide the primary metabolite. With a favorable bioavailability of 24.0%, N-hydap exhibited a higher distribution in the lungs (26.26%), accounting for its efficacy against SCLC. Administering N-hydap to mice at normal doses via gavage did not result in significant toxicity. Furthermore, N-hydap was found to affect the catalytic activity of drug metabolic enzymes (DMEs), particularly increasing the activity of UGT1A3, suggesting potential for DDIs. Understanding the metabolic pathways and properties of N-hydap should improve our knowledge of its drug efficacy, toxicity, and potential for DDIs. Graphical Abstract

Abstract Orphan diseases, exemplified by T-cell prolymphocytic leukemia, present inherent challenges due to limited data availability and complexities in effective care. This study delves into harnessing the potential of machine learning to enhance care strategies for orphan diseases, specifically focusing on allogeneic hematopoietic cell transplantation (allo-HCT) in T-cell prolymphocytic leukemia. The investigation evaluates how varying numbers of variables impact model performance, considering the rarity of the disease. Utilizing data from the Center for International Blood and Marrow Transplant Research, the study scrutinizes outcomes following allo-HCT for T-cell prolymphocytic leukemia. Diverse machine learning models were developed to forecast acute graft-versus-host disease (aGvHD) occurrence and its distinct grades post-allo-HCT. Assessment of model performance relied on balanced accuracy, F1 score, and ROC AUC metrics. The findings highlight the Linear Discriminant Analysis (LDA) classifier achieving the highest testing balanced accuracy of 0.58 in predicting aGvHD. However, challenges arose in its performance during multi-class classification tasks. While affirming the potential of machine learning in enhancing care for orphan diseases, the study underscores the impact of limited data and disease rarity on model performance.

Vacuum induction-melting gas atomization (VIGA) is considered a widely applied method to prepare metal powders. However, the nozzle clogging problem in the VIGA process seriously affects the continuity of production and greatly increases the economic and time costs. In the atomization initial stage, the existence of unsteady state atomization mainly results in the nozzle clogging challenge. To understand the formation mechanism of nozzle clogging, a computational fluid dynamics (CFD) model was established to simulate the influence of unsteady state atomization sequence on the primary atomization of alloy melt. Typically, there are two kinds of sequence including starting the gas before pooling the alloy (namely, GA) and pouring the alloy before opening the gas (AG). The movement trajectory of the alloy melt droplet at the end of the delivery-tube was clarified. Based on CFD simulation, the atomization sequence of AG and GA was precisely controlled in the atomization pressure range of 2.5 MPa, 3.5 MPa, and 4.5 MPa to address the nozzle clogging issue. In the GA process, relatively finer powder was obtained at 3.5 MPa without nozzle clogging occurring. In contrast, the AG process greatly reduces the probability of nozzle clogging at 2.5–4.5 MPa, the final prepared powder is coarser. The predicted results of industrial experiments and numerical simulations are consistent. This study provides theoretical support for understanding the formation mechanism of nozzle clogging during the VIGA process.

Abstract Quantum annealing, which involves quantum tunnelling among possible solutions, has state-of-the-art applications not only in quickly finding the lowest-energy configuration of a complex system, but also in quantum computing. Here we report a single-crystal study of the frustrated magnet α-CoV2O6, consisting of a triangular arrangement of ferromagnetic Ising spin chains without evident structural disorder. We observe quantum annealing phenomena resulting from time-reversal symmetry breaking in a tiny transverse field. Below ~ 1 K, the system exhibits no indication of approaching the lowest-energy state for at least 15 hours in zero transverse field, but quickly converges towards that configuration with a nearly temperature-independent relaxation time of ~ 10 seconds in a transverse field of ~ 3.5 mK. Our many-body simulations show qualitative agreement with the experimental results, and suggest that a tiny transverse field can profoundly enhance quantum spin fluctuations, triggering rapid quantum annealing process from topological metastable Kosterlitz-Thouless phases, at low temperatures.

Objective The jet noise generated by the main circuit breaker switching valve of high-speed railway EMU is excessively high, which seriously affects passenger comfort. Therefore, it is essential to study effective noise reduction measures. Method Field experiments are conducted to measure the jet noise of the switching valve, revealing a noise level as high as 96 dB with noticeable intermittency and pulsation. Using LES (large eddy simulation), a mathematical model for simulating the jet noise of the switching valve is established. Four different nozzle shapes are selected, and their flow velocity distribution nephograms are computed. The calculated jet flow results are imported into LMS.Virtual.Lab software, and the acoustic boundary element method is employed to simulate the jet noise fields of the four nozzles. The simulated 1/3-octave frequency spectrum values for them are compared with experimentally measured values. Finally, four existing industrial mufflers and a developed new structural composite material muffler are selected and tested for their noise reduction effectiveness on the switching valve. Result & Conclusion Generated by main circuit breaker disconnection, the jet noise of the switching valve is closely related to the shape of the exhaust port and falls into the mid-to-high-frequency noise range. All five mufflers can significantly reduce the jet noise from the switching valve, with the new structural composite material muffler demonstrating the best noise reduction effect, achieving a reduction of up to 20 dB.

Chilled meat is favored by consumers because of its fresh, low price and high nutritive value. However, it is susceptible for microbial contamination in slaughtering, processing, marketing and other links, as well as the change of its color, odor and other qualities, which results in short shelf life, even losing its edible value and other problems of chilled meat, restricting the further development of the fresh meat industry. Therefore, the preservative preservation technology is particularly important in China's meat food, and it has a wide range of application prospects in the development of meat food industry. This paper describes the main reasons for the corruption and deterioration of chilled meat, including microbial contamination, lipid oxidation and discoloration of myoglobin. Besides, it elaborates on chemical preservation technologies such as organic acids, microbial metabolites and physical preservation technologies such as packaging technology, irradiation technology, etc., and their anticorrosion mechanisms. In addition to enumerating the status quo of its application in the preservation of meat, analyzing the advantages of preservation technology and its limitations in the development, and making future research proposals for the development of meat food. In addition, it lists the current status of its application in meat preservation, analyzes the advantages of the preservation technology and its limitations in application, and makes prospects for future preservation technologies, with a view to providing a certain theoretical basis for the further in-depth research on the preservation technology for the preservation of the preservation of cold meat as well as the preservation of fresh meat.

The phospholipid bilayer nanodiscs (LNDs), as a rapidly-developing tool in recent years, provide a natural bio-memebrane environment to maintain the native conformation and functions of membrane proteins as well as a versatile delivery vehicle for a variety of hydrophobic and hydrophilic drugs. We have seen unprecedented advantages of phospholipid bilayer nanodiscs in membrane protein structure characterization, biochemical and physiological studies of membrane proteins, membrane environment studies, drug discovery & development, and drug delivery. Many previous reviews have been mainly focused on the advantages of nanodiscs in membrane protein researches, but few have touched upon the importance and potential application of nanodiscs in pharmaceutical industries. This review will provide general description of the structural characteristics, advantages, classification, and applications of phospholipid nanodiscs, with particular focus on nanodisc-enabled membrane protein drug discovery & development as well as drug delivery.

Introduction Despite the favourable efficacy of antiretroviral therapy (ART), HIV/AIDS continues to impose significant disease burdens worldwide. This study aims to systematically review published prognostic prediction models for survival outcomes of treatment experienced people living with HIV (TE-PLHIV), to describe their characteristics, compare their performance and assess the risk of bias and real-world clinical utility.Methods and analysis Studies will be identified through a comprehensive search in PubMed, EMBASE, Scopus, the Cochrane Library, and OpenGrey databases. Two reviewers will independently conduct a selection of eligible studies, data extraction and critical appraisal. Included studies will be systematically summarised using appropriate tools designed for prognostic prediction modelling studies. Where applicable, evidence will be summarised with meta-analyses.Ethics and dissemination Ethical approval is not required because only available published data will be analysed. The results of this work will be published in a peer-reviewed journal.Systematic review registration PROSPERO registration number CRD42023412118.

The correlation between formaldehyde (FA) exposure and prevalence of asthma has been widely reported. However, the underlying mechanism is still not fully understood. FA exposure at 2.0 mg/m3 was found to exacerbate asthma in OVA-induced murine models. IFN-γ, the cytokine produced by T helper 1 (Th1) cells, was significantly induced by FA in serum and bronchoalveolar lavage fluid (BALF) of asthmatic mice, which was different from cytokines secreted by other Th cells. The observation was also confirmed by mRNA levels of Th marker genes in CD4+ T cells isolated from BALF. In addition, increased production of IFN-γ and expression of T-bet in Jurkat T cells primed with phorbol ester and phytohaemagglutinin were also observed with 100 μM FA treatment in vitro. Upregulated STAT1 phosphorylation, T-bet expression and IFN-γ production induced by FA was found to be restrained by STAT1 inhibitor fludarabine, indicating that FA promoted Th1 commitment through the autocrine IFN-γ/STAT1/T-bet pathway in asthma. This work not only revealed that FA could bias Th lineage commitment to exacerbate allergic asthma, but also identified the signaling mechanism of FA-induced Th1 differentiation, which may be utilized as the target for development of interfering strategies against FA-induced immune disorders.

Neutralization slag (NS) of copper smelting is a waste residue mainly composed of calcium sulfate, which is produced during the process of metal smelting. The large accumulation and storage of NS poses a significant threat to the environment. Therefore, it is imperative to explore a new economically and environmentally friendly approach for recycling NS. This study proposes a method for preparing a new eco-friendly geopolymer material by utilizing NS. A geopolymer with satisfactory mechanical properties was created by employing a hybrid solid activator consisting of CaO-Na2SiO3. The effects of hybrid solid alkali activators calcium oxide (CaO)/sodium silicate (Na2SiO3) ratio on the hydration properties of the NS-based geopolymer were studied, and its curing mechanism was discussed. The results show that, when the hybrid solid activator CaO/Na2SiO3 ratio was 3:1, the maximum 28 d compressive strength of the geopolymer reached 27.8 MPa. The solid activator at a suitable ratio can accelerate the hydration reaction, form higher amounts of C-A-S-H gel and ettringite, reduce the proportion of harmful macropores in the geopolymer, and improve the microstructure of the geopolymer. Toxicity characteristic leaching procedure (TCLP) test confirmed that the NS-based geopolymer had a solidification effect on heavy metals. The leaching concentration of elemental Pb from the neutralised slag feedstock was 7.241 mg/L, while the lowest concentration was 0.286 mg/L in the NS based geopolymer. As a green cementitious material, the NS-based geopolymer is expected to be applied in engineering practice.

Abstract Background Telemedicine has experienced rapid growth in recent years, aiming to enhance medical efficiency and reduce the workload of healthcare professionals. During the COVID-19 pandemic in 2019, it became especially crucial, enabling remote screenings and access to healthcare services while maintaining social distancing. Online consultation platforms have emerged, but the demand has strained the availability of medical professionals, directly leading to research and development in automated medical consultation. Specifically, there is a need for efficient and accurate medical dialogue summarization algorithms to condense lengthy conversations into shorter versions focused on relevant medical facts. The success of large language models like generative pre-trained transformer (GPT)-3 has recently prompted a paradigm shift in natural language processing (NLP) research. In this paper, we will explore its impact on medical dialogue summarization. Methods We present the performance and evaluation results of two approaches on a medical dialogue dataset. The first approach is based on fine-tuned pre-trained language models, such as bert-based summarization (BERTSUM) and bidirectional auto-regressive Transformers (BART). The second approach utilizes a large language models (LLMs) GPT-3.5 with inter-context learning (ICL). Evaluation is conducted using automated metrics such as ROUGE and BERTScore. Results In comparison to the BART and ChatGPT models, the summaries generated by the BERTSUM model not only exhibit significantly lower ROUGE and BERTScore values but also fail to pass the testing for any of the metrics in manual evaluation. On the other hand, the BART model achieved the highest ROUGE and BERTScore values among all evaluated models, surpassing ChatGPT. Its ROUGE-1, ROUGE-2, ROUGE-L, and BERTScore values were 14.94%, 53.48%, 32.84%, and 6.73% higher respectively than ChatGPT’s best results. However, in the manual evaluation by medical experts, the summaries generated by the BART model exhibit satisfactory performance only in the “Readability” metric, with less than 30% passing the manual evaluation in other metrics. When compared to the BERTSUM and BART models, the ChatGPT model was evidently more favored by human medical experts. Conclusion On one hand, the GPT-3.5 model can manipulate the style and outcomes of medical dialogue summaries through various prompts. The generated content is not only better received than results from certain human experts but also more comprehensible, making it a promising avenue for automated medical dialogue summarization. On the other hand, automated evaluation mechanisms like ROUGE and BERTScore fall short in fully assessing the outputs of large language models like GPT-3.5. Therefore, it is necessary to research more appropriate evaluation criteria.

Abstract In this paper, a novel algorithm is presented for warhead recognition in the defense of ballistic missiles. The range profiles from the warheads of interest in typical illumination directions form a dataset. First, each range profile in the dataset is compared to the range profile of the target under observation, and the most similar range profile is found. Then, the observed target is considered as a warhead if the deviation of its range profile from the most similar range profile is less than or equal to a threshold. The threshold is chosen such that the detection rate is a constant. The simulation results verify the effectiveness of the proposed algorithm. Since the threshold is automatically calculated according to the detection rate, this algorithm has a larger applicability than the current methods based on range-profile matching.

AbstractTricyrtis xianjuensis Li, Chen & Ma 2014 is a rare and endangered species endemic to Zhejiang province, with fewer than 200 individuals in the wild. In our present study, the complete chloroplast genome of T. xianjuensis was assembled by using high-throughput sequencing data, and its genomic features were described and comparative genomic analyses within Liliaceae family were performed. The complete chloroplast genome of T. xianjuensis was 155,748 bp in length, exhibiting a GC content of 37.3%. This genome structure contained two inverted repeats (IRs), as well as a small single-copy (SSC) and a large single-copy (LSC) region. The IR region measured 26,371 bp, while the SSC and LSC regions were 17,729 bp and 85,277 bp in length, respectively. A total of 137 genes were identified, including 85 protein-coding genes, 38 tRNA genes, eight rRNA genes, and six pseudogenes. Phylogenic analysis revealed T. xianjuensis shared a clade with T. formosana Baker 1879 and T. macropoda Miq. 1867, with a support rate of 100%. The assembly and analysis of T. xianjuensis chloroplast genome provided an insight into further studies on the conservation genetics of this endangered species.

A two-photon near infrared (NIR) fluorescence turn-on sensor with high selectivity and sensitivity for Zn2+ detection has been developed. This sensor exhibits a large Stokes' shift (∼300 nm) and can be excited from 900 to 1000 nm, with an emission wavelength of ∼785 nm, making it ideal for imaging in biological tissues. The sensor's high selectivity for Zn2+ over other structurally similar cations, such as Cd2+, makes it a promising tool for monitoring zinc ion levels in biological systems. Given the high concentration of zinc in thrombi, this sensor could provide a useful tool for in vivo thrombus imaging.

The extracellular matrix (ECM) is a complex three-dimensional structure composed of proteins, glycans, and proteoglycans, constituting a critical component of the tumor microenvironment. Complex interactions among immune cells, extracellular matrix, and tumor cells promote tumor development and metastasis, consequently influencing therapeutic efficacy. Hence, elucidating these interaction mechanisms is pivotal for precision cancer therapy. T lymphocytes are an important component of the immune system, exerting direct anti-tumor effects by attacking tumor cells or releasing lymphokines to enhance immune effects. The ECM significantly influences T cells function and infiltration within the tumor microenvironment, thereby impacting the behavior and biological characteristics of tumor cells. T cells are involved in regulating the synthesis, degradation, and remodeling of the extracellular matrix through the secretion of cytokines and enzymes. As a result, it affects the proliferation and invasive ability of tumor cells as well as the efficacy of immunotherapy. This review discusses the mechanisms underlying T lymphocyte-ECM interactions in the tumor immune microenvironment and their potential application in immunotherapy. It provides novel insights for the development of innovative tumor therapeutic strategies and drug.

Abstract FRET-based sensors are utilized for real-time measurements of cellular tension. However, transfection of the sensor gene shows low efficacy and is only effective for a short period. Reporter mice expressing such sensors have been developed, but sensor fluorescence has not been measured successfully using conventional confocal microscopy. Therefore, methods for spatiotemporal measurement of cellular tension in vivo or ex vivo are still limited. We established a reporter mouse line expressing FRET-based actinin tension sensors consisting of EGFP as the donor and mCherry as the acceptor and whose FRET ratio change is observable with confocal microscopy. Tension-induced changes in FRET signals were monitored in the aorta and tail tendon fascicles, as well as aortic smooth muscle cells isolated from these mice. The pattern of FRET changes was distinctive, depending on tissue type. Indeed, aortic smooth muscle cells exhibit different sensitivity to macroscopic tensile strain in situ and in an isolated state. This mouse strain will enable novel types of biomechanical investigations of cell functions in important physiological events.

Abstract Pyrophosphate (PPi) anions are crucial in numerous biological and ecological processes involved in energy conversion, enzymatic reactions, and metabolic regulation along with adenosine. They are also significant biological markers for various processes related to diseases. Fluorescent PPi sensors would enable visual and/or biological detection in convenient settings. However, the current availability of commercial sensors has been limited to costly enzymes that are not compatible for imaging. Sensor development has also encountered challenges such as poor selectivity and stability and limited practical applications. In this review, we analyze the situation of PPi sensing via commercial kits and focus on sensors that use metal complexes. We address their designs, sensing mechanisms, selectivities, and detection limits. Finally, we discuss limitations and perspectives for PPi detection and imaging.

Given the development of insects’ resistance and deteriorative ecological environment, the discovery of insecticides with a new mode of action has been proven to be an important tool for comprehensive pest management. Herein, a novel anthranilic diamides containing 3,5-dichloropyridylpyrazole group were designed and synthesized. Their insecticidal potency was assayed against beet armyworm (Spodoptera exigua). Moreover, the structure-activity relationship of these new compounds was also discussed. Of them, compound 15g exhibited potential insecticidal activity. Because of the excellent efficacy against a series of Lepidoptera and low toxicity to mammals, compound 15g, namely tetrachlorantraniliprole, has been developed and launched into the market as an insecticide.

In this work, a novel heterojunction composite Ag2S/KTaxNb1-xO3 was designed and synthesized through a combination of hydrothermal and precipitation procedures. The Ta/Nb ratio of the KTaxNb1-xO3 and the Ag2S content were optimized. The best 0.5% Ag2S/KTa0.5Nb0.5O3 (KTN) sample presents an enhanced photocatalytic performance in ammonia synthesis than KTN and Ag2S. Under simulated sunlight, the NH3 generation rate of 0.5% Ag2S/KTN reaches 2.0 times that of pure KTN. Under visible light, the reaction rate ratio of the two catalysts is 6.0. XRD, XPS, and TEM analysis revealed that Ag2S was intimately decorated on the KTN nanocubes surface, which promoted the electron transfer between the two semiconductors. The band structure investigation indicated that the Ag2S/KTN heterojunction established a type-II band alignment with intimate contact, thus realizing the effective transfer and separation of photogenerated carriers. The change in charge separation was considered as the main reason for the enhanced photocatalytic performance. Interestingly, the Ag2S/KTN composite exhibited higher NH3 generation performance under the combined action of ultrasonic vibration and simulated sunlight. The enhanced piezo-photocatalytic performance can be ascribed that the piezoelectric effect of KTN improved the bulk separation of charge carriers in KTN. This study not only provides a potential catalyst for photocatalytic nitrogen fixation but also shows new ideas for the design of highly efficient catalysts via semiconductor modification and external field coupling.

Under operating conditions, bearings have a substantial service life with short failure time periods, which leads to unbalanced dataset and greatly affects the accuracy of deep learning model fault diagnosis. To address this problem, a fault diagnosis method of rolling bearing unbalanced dataset based on two-step transfer learning is proposed in this paper. First, a small amount of data in the source and target domains is used to generate the transition dataset by conditional gradient penalized generative adversarial network (CWGAN-GP). Then, the constructed convolutional neural network model is migrated twice between the source domain dataset, the transition dataset, and the target domain dataset. Finally, a small amount of data from the target domain is used to fine-tune the transferred model to obtain the final fault diagnosis model. The experimental results show that the method has a good diagnostic recognition effect on rolling bearing spalling class faults with unbalanced dataset under different working conditions.

AbstractImpatiens huangyanensis Jin and Ding 2002 is a plant species with very small populations, and it distributes only in Huangyan, Zhejiang Province, China. In this study, the complete chloroplast genome of I. huangyanensis was assembled by using high-throughput Illumina paired-end sequences. Its genomic feature was determined, and comparative genomic analysis of the genus Impatiens was performed. The results revealed that the full-length chloroplast genome of I. huangyanensis was 152,156 bp with a GC content of 36.8%. The chloroplast genome contains a typical quadripartite structure, comprising two copies of inverted repeats (IRs), a small single-copy (SSC) region, and a large single-copy (LSC) region. The sequence lengths of IR, SSC, and LSC were 25,756 bp, 17,662 bp, and 82,982 bp, respectively. The chloroplast genome consisted of 134 genes, including 84 protein-coding genes, 37 transfer RNA genes, eight ribosomal RNA genes, and five pseudogenes. Phylogenic results indicated I. huangyanensis shared a clade with I. davidii Franchet 1883, I. macrovexilla Chen 2000, I. fanjingshanica Chen 1999, and I. piufanensis Hook 1908, with a support rate of 100%. Our study provided insight into further studies on the conservation genetics of I. huangyanensis.

Abstract Lumbar hernia is a rare lateral abdominal wall hernia. Various surgical repair strategies have been recorded, but there is currently no unified standard. A Chinese surgeon recently revealed a novel technique for treating primary lumbar hernia called retroperitoneal totally endoscopic prosthetic repair (R-TEP). We have made a further exploration of this method and successfully used it in the treatment of secondary lumbar hernia. We successfully performed R-TEP on three patients with lumbar hernias. All patients were female with an average age of 64 years (51–71 years). Two patients each had a primary upper lumbar hernia, while one patient had a secondary lumbar hernia. With a mean operative time of 77 min (60–105 min), all operations were performed successfully. The average visual analogue scale (VAS) was 1.3 points (1–2 points) on the second day following surgery. The mean postoperative hospital stay was 2.3 days (2–3 days). No postoperative complications occurred. During a mean follow-up period of 19 months (10–24 months), there was no recurrence of the hernia, chronic pain or mesh infection. Therefore, R-TEP is safe and effective for both primary and secondary lumbar hernia. Anti-adhesive coated meshes are not required, making this a cost-effective procedure that is worthy of recommendation.

AbstractLuisia hancockii Rolfe 1896 is an epiphytic orchid species. In our present study, the whole chloroplast genome sequence of L. hancockii was de novo assembled by using high-throughput Illumina reads, and phylogenetic analysis was conducted within species of subtribe Aeridinae. The complete chloroplast genome sequence of L. hancockii was 146,243 bp in length, with a typical quadripartite structure, and its large single-copy, small single-copy, and inverted repeat were 84,441 bp, 11,412 bp, and 25,195 bp long, respectively. The GC content of the whole chloroplast genome was 36.6%, while the GC contents of LSC, SSC, and IR were 33.8%, 27.5%, and 43.3%, respectively. The chloroplast genome consisted of 129 genes, including 74 protein-coding genes, eight rRNAs, 38 tRNAs, and nine pseudogenes. Phylogenic tree was generated using the best model GTR + R, and the results showed that L. hancockii was sister to Holcoglossum and Vanda species, with a support of 100%.

Abstract To generate arbitrary shape magnetic field waveforms for advanced scientific research, a reconfigurable pulsed high magnetic field facility (PHMFF) was developed at Wuhan National Pulsed High Magnetic Field Centre (WHMFC). First, the basic elements of PHMFF are introduced, and a ternary physical model composed of energy storage unit, magnet, transmission circuits and other auxiliary units is summarised to describe various magnetic field systems. Second, in order to realise the reconfiguration of magnetic field systems based on detailed elements, the control system with the ability of dynamic construction and control sequence reconfiguration is designed. On this basis, the PHMFF has been realised and various magnetic field systems are constructed to produce arbitrary shape magnetic field waveforms, such as half‐sine, ultra‐high, flat‐top and repetitive field pulses, which not only enhances the capability and efficiency of PHMFF, but also makes more scientific research possible in pulsed magnetic fields. So far, a peak magnetic field of 94.8 T, a flat‐top magnetic field of 64 T/10 ms and a repetitive magnetic field waveform of 20 T/60 Hz have been achieved, and some experiments and studies on the physical properties of materials have been carried out at WHMFC.

Explosive percolation (EP) has received significant research attention due to its rich and anomalous phenomena near criticality. In our recent study [Phys. Rev. Lett. 130, 147101 (2023)0031-900710.1103/PhysRevLett.130.147101], we demonstrated that the correct critical behaviors of EP in infinite dimensions (complete graph) can be accurately extracted using the event-based method, with finite-size scaling behaviors still described by the standard finite-size scaling theory. We perform an extensive simulation of EPs on hypercubic lattices ranging from dimensions d=2 to 6, and find that the critical behaviors consistently obey the standard finite-size scaling theory. Consequently, we obtain a high-precision determination of the percolation thresholds and critical exponents, revealing that EPs governed by the product and sum rules belong to different universality classes. Remarkably, despite the mean of the dynamic pseudocritical point T_{L} deviating from the infinite-lattice criticality by a distance determined by the d-dependent correlation-length exponent, T_{L} follows a normal (Gaussian) distribution across all dimensions, with a standard deviation proportional to 1/sqrt[V], where V denotes the system volume. A theoretical argument associated with the central-limit theorem is further proposed to understand the probability distribution of T_{L}. These findings offer a comprehensive understanding of critical behaviors in EPs across various dimensions, revealing a different dimension-dependence compared to standard bond percolation.

The escalating concern over global warming has garnered significant international attention, with carbon emission intensity emerging as a crucial barrier to sustainable economic development across various regions. While previous studies have largely focused on annual scales, this study introduces a novel examination of Tianjin’s quarterly carbon emission intensity and its influencing factors from 2012 to 2022 using quarterly data and the Logarithmic Mean Divisia Index (LMDI) model. The analysis considers the carbon emission effects of thermal power generation, the power supply structure, power intensity effects, and economic activity intensity. The results indicate a general decline in Tianjin’s carbon emission intensity from 2012 to 2020, followed by an increase in 2021 and 2022. This trend, exhibiting significant seasonal fluctuations, revealed the highest carbon emission intensity in the first quarter (an average of 1.4093) and the lowest in the second quarter (an average of 1.0019). Economic activity intensity emerged as the predominant factor influencing carbon emission intensity changes, particularly notable in the second quarter (an average of −0.0374). Thermal power generation and electricity intensity effects were significant in specific seasons, while the power supply structure’s impact remained relatively minor yet stable. These findings provide essential insights for formulating targeted carbon reduction strategies, underscoring the need to optimize energy structures, enhance energy efficiency, and account for the seasonal impacts of economic activity patterns on carbon emissions.

The cocrystallization of 1,3,5,7-tetranitro-1,3,5,7-tetrazolidine (HMX) with cyclopentanone was achieved via a controlled cooling method, followed by comprehensive characterization that confirmed the α-configuration of HMX within the cocrystal. The enthalpy of dissolution of HMX in cyclopentanone was assessed across a range of temperatures using a C-80 Calvert microcalorimeter, revealing an endothermic dissolution process. Subsequently, the molar enthalpy of dissolution was determined, and kinetic equations describing the dissolution rate were derived for temperatures of 303.15, 308.15, 313.15, 318.15, and 323.15 K as follows: dα⁄dt = 10−2.46(1 − α)0.35, dα⁄dt = 10−2.19(1 − α)0.79, dα⁄dt = 10−1.76(1 − α)1.32, dα⁄dt = 10−1.86(1 − α)0.46, and dα⁄dt = 10−2.02(1 − α)0.70, respectively. Additionally, molecular dynamics (MD) simulations investigated the intermolecular interactions of the HMX/cyclopentanone cocrystallization process, demonstrating a transformation of HMX from β- to α-conformation within the cyclopentanone environment. Theoretical calculations performed at the ωB97XD/6-311G(d,p) level affirmed that α-HMX exhibited stronger binding affinity toward cyclopentanone compared to β-HMX, corroborating experimental findings. A comprehensive understanding of the dissolution behavior of HMX in cyclopentanone holds significant implications for crystal growth methodologies and cocrystallization processes. Such insights are pivotal for optimizing HMX dissolution processes and offer valuable perspectives for developing and designing advanced energetic materials.

Accurate and precise rigid registration between head-neck computed tomography (CT) and cone-beam computed tomography (CBCT) images is crucial for correcting setup errors in image-guided radiotherapy (IGRT) for head and neck tumors. However, conventional registration methods that treat the head and neck as a single entity may not achieve the necessary accuracy for the head region, which is particularly sensitive to radiation in radiotherapy. We propose ACSwinNet, a deep learning-based method for head-neck CT-CBCT rigid registration, which aims to enhance the registration precision in the head region. Our approach integrates an anatomical constraint encoder with anatomical segmentations of tissues and organs to enhance the accuracy of rigid registration in the head region. We also employ a Swin Transformer-based network for registration in cases with large initial misalignment and a perceptual similarity metric network to address intensity discrepancies and artifacts between the CT and CBCT images. We validate the proposed method using a head-neck CT-CBCT dataset acquired from clinical patients. Compared with the conventional rigid method, our method exhibits lower target registration error (TRE) for landmarks in the head region (reduced from 2.14 ± 0.45 mm to 1.82 ± 0.39 mm), higher dice similarity coefficient (DSC) (increased from 0.743 ± 0.051 to 0.755 ± 0.053), and higher structural similarity index (increased from 0.854 ± 0.044 to 0.870 ± 0.043). Our proposed method effectively addresses the challenge of low registration accuracy in the head region, which has been a limitation of conventional methods. This demonstrates significant potential in improving the accuracy of IGRT for head and neck tumors.