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With the industrialization of the food industry and the advancement of production technology, along with the simultaneous modern fast-paced lifestyle and the growth of the central kitchen market, pre-made dishes have become an important choice for both the catering industry and households. Pre-made dishes made primarily with pork as the main ingredient have become an important component of the pre-made dishes market and the market share continues to grow steadily. The quality of pre-made pork dishes is closely linked to processing technology, storage techniques and quality control measures. This paper reviews the material characteristics, processing and quality control technologies of pre-made pork dishes and aims to guide for their high-quality development.

In order to investigate changes in flavor substances of lightly-pickled cucumbers during storage, volatile compounds were analyzed by electronic nose and gas chromatography-ion mobility spectrometry (GC-IMS). The results showed that flavor characteristics of lightly-pickled cucumbers changed obviously during storage. A total of 56 volatile organic compounds (VOCs) were detected by GC-IMS, including 10 alcohols, 30 aldehydes, 8 ketones, 5 esters, 1 furan, 1 acid, and 1 alkane. With the extension of storage period, the relative contents of aldehydes, alcohols and ketones decreased significantly, while the contents of esters increased significantly (P1), including cis-6-nonenal, nonenal, 1-penten-3-one, isobutyraldehyde, trans-2,cis-6-nonadienal, and trans-2-octenal. Among them, trans-2-octenal increased with the relative extension of storage time, which might be the main off-flavor compound for flavor deterioration. This study can provide a theoretical basis for flavor quality evaluation of lightly-pickled cucumbers during storage.

Premade meat and poultry dishes refer to the finished or semi-finished products that use meat and poultry materials as the main ingredients, which undergo pretreatments and stored, transported and sold under room temperature or cold chain conditions. Flavor is an important factor that determines consumers' willing for premade dish purchase. However, due to raw material characteristics, microbial metabolism, nutrients oxidation or degradation, inappropriate reheating, the premade meat and poultry dishes might generate some unpleasant off-flavors. The off-flavors might have strong negative impact on the sensory quality of premade dishes, which restricts the further development of the whole industry. The commonly seen off-flavor substances in premade meat and poultry dishes include hexanal with sour note, nonanal, octanal, decanal and (E,E)-2,4-decadienal with waxy and oily note, (E)-2-decenal with greasy fatty note, 3-methylbutyraldehyde and 2-methylbutyraldehyde with musty note, butyric acid with a strong cheesy note, 3-methylbutyric acid with sweaty note, dimethyl trisulfide, dimethyl sulphide with sulphurous note, and 1-octen-3-ol with earthy note etc. This paper reviews the main sources of premade meat and poultry dishes off-flavors, summarizes the off-flavors inhibiting and masking techniques applied in premade dish preparation. This study would provide practical guidance and reference for the innovation and development of the flavor quality control in premade dish industry.

Paper mulberry (Broussonetia papyrifera) is a high-quality silage protein feed material that can help address feed shortages and support livestock development. Although some studies have investigated the relationships between microbial communities and silage quality, these relationships and the underlying community assembly processes remain complex, requiring further research to clarify them. Additionally, limited research has explored the relationship between microbial community fermentation functions and silage quality. In this study, we aimed to explore B. papyrifera and wheat bran mixed silage quality driven by the characteristics of the microbial community. After 50 days of silage fermentation, high-quality and low-quality samples were selected from every mixing ratio (90:10, 80:20, and 65:35). The silage chemical composition, lignocellulose degradation enzyme activity, microbial community composition, and potential functions were used to explore the relevance between silage quality and the characteristics of the microbial community. The contents of hemicellulose, neutral detergent fiber, pH, and the activities of endoglucanase and exoglucanase were significantly affected by mixing ratios and silage quality grade. There were higher crude protein content, lignocellulose degrading enzyme activity, and lower pH, lignin, and acid detergent fiber in the mixing of 65:35 (BP65%) samples. The PERMANOVA results showed that mixing ratios had significant impacts on microbial community composition and bacterial fermentation functions. There was a higher bacterial diversity, lower fungal diversity, and better functional potentials for fermentation and lignocellulose degradation in BP65% high-quality silage. The dominant genera were Lactobacillus, Cladosporium, and Wallemia in all samples. The relative abundance of Clostridium, Rhodococcus, Turicibacter, Ralstonia, and Burkholderia was significantly higher in BP65% high-quality samples. There was a higher abundance of Wallemia in the BP65% samples than in other mixing ratios samples. Notably, silage quality showed a close relationship with Lactobacillus, Turicibacter, Romboutsia, Wallemia, and Pichia. In summary, 65:35 was a suitable mixing ratio for B. papyrifera and wheat bran silage, but high-quality silage still required the participation of multiple specific rare microbial taxa. The higher bacterial diversity and specific microbial taxa abundance could be critical for improving B. papyrifera silage quality. We expect that our findings will provide new insights into silage quality driven by the characteristics of the microbial community.

Abstract Immune microenvironment and immunotherapy have become the focus and frontier of tumor research, and the immune checkpoint inhibitors has provided novel strategies for tumor treatment. Malignant pleural effusion (MPE) is a common end-stage manifestation of lung cancer, malignant pleural mesothelioma and other thoracic malignancies, which is invasive and often accompanied by poor prognosis, affecting the quality of life of affected patients. Currently, clinical therapy for MPE is limited to pleural puncture, pleural fixation, catheter drainage, and other palliative therapies. Immunization is a new direction for rehabilitation and treatment of MPE. The effusion caused by cancer cells establishes its own immune microenvironment during its formation. Immune cells, cytokines, signal pathways of microenvironment affect the MPE progress and prognosis of patients. The interaction between them have been proved. The relevant studies were obtained through a systematic search of PubMed database according to keywords search method. Then through screening and sorting and reading full-text, 300 literatures were screened out. Exclude irrelevant and poor quality articles, 238 literatures were cited in the references. In this study, the mechanism of immune microenvironment affecting malignant pleural effusion was discussed from the perspectives of adaptive immune cells, innate immune cells, cytokines and molecular targets. Meanwhile, this study focused on the clinical value of microenvironmental components in the immunotherapy and prognosis of malignant pleural effusion.

IntroductionAccurate classification of single-trial electroencephalogram (EEG) is crucial for EEG-based target image recognition in rapid serial visual presentation (RSVP) tasks. P300 is an important component of a single-trial EEG for RSVP tasks. However, single-trial EEG are usually characterized by low signal-to-noise ratio and limited sample sizes.MethodsGiven these challenges, it is necessary to optimize existing convolutional neural networks (CNNs) to improve the performance of P300 classification. The proposed CNN model called PSAEEGNet, integrates standard convolutional layers, pyramid squeeze attention (PSA) modules, and deep convolutional layers. This approach arises the extraction of temporal and spatial features of the P300 to a finer granularity level.ResultsCompared with several existing single-trial EEG classification methods for RSVP tasks, the proposed model shows significantly improved performance. The mean true positive rate for PSAEEGNet is 0.7949, and the mean area under the receiver operating characteristic curve (AUC) is 0.9341 (p < 0.05).DiscussionThese results suggest that the proposed model effectively extracts features from both temporal and spatial dimensions of P300, leading to a more accurate classification of single-trial EEG during RSVP tasks. Therefore, this model has the potential to significantly enhance the performance of target recognition systems based on EEG, contributing to the advancement and practical implementation of target recognition in this field.

Objective To explore the composition of culturable bacteria in platelets through bacterial culturomics and verify the results of culturomics and metagenomics to improve the detection rate of bacteria in platelets. Methods Platelet samples from 6 healthy people were collected. Eight kinds of culture media were placed in aerobic conditions and 12 kinds of culture media were placed in anaerobic conditions for large-scale culture and isolation of bacteria in platelets. The isolated single colony was identified by 16S rRNA gene sequencing. The bacterial abundance of healthy human platelet microbiome was analyzed by metagenomic sequencing, and the cultivable bacterial species in platelets was confirmed based on metagenomic and culturomics results. Results A total of 90 strains of bacteria belonging to 3 phylums, 5 classes, 5 orders, 7 families, 9 genus and 23 species were isolated from 6 platelet samples by culturomics. Among them, the strains with more monoclonal clones at the species level were Brevundimonas aurantiaca (16.7%), Bacillus sp. Y1 (15.6%), Cutibacterium acnes (14.4%) and Brevibacillus brevis (13.3%). The platelet samples sequenced by mNGS showed that the abundance values of Proteobacteria, Firmicutes and Actinobacteria were high. The bacteria detected by both culturomics and metagenomic sequencing methods were as follows: Firmicutes: Bacillus sp. Y1, B. thuringiensis, B. cereus, B. mobilis, B. velezensis, Staphylococcus epidermidis, and Brevibacillus brevis; Actinobacteria: Cutibacterium acnes; Proteobacteria: Escherichia coli and Delftia tsuruhatensis. Conclusion The mutual validation of culturomics and metagenomics has identified some bacteria, proving that bacteria exist in platelets.

Abstract Background Auriculocondylar syndrome (ARCND) is a rare congenital craniofacial developmental malformation syndrome of the first and second pharyngeal arches with external ear malformation at the junction between the lobe and helix, micromaxillary malformation, and mandibular condylar hypoplasia. Four subtypes of ARCND have been described so far, that is, ARCND1 (OMIM # 602483), ARCND2 (ARCND2A, OMIM # 614669; ARCND2B, OMIM # 620458), ARCND3 (OMIM # 615706), and ARCND4 (OMIM # 620457). Methods This study reports a case of ARCND2 resulting from a novel pathogenic variant in the PLCB4 gene, and summarizes PLCB4 gene mutation sites and phenotypes of ARCND2. Results The proband, a 5‐day‐old male neonate, was referred to our hospital for respiratory distress. Micrognathia, microstomia, distinctive question mark ears, as well as mandibular condyle hypoplasia were identified. Trio‐based whole‐exome sequencing identified a novel missense variant of NM_001377142.1:c.1928C>T (NP_001364071.1:p.Ser643Phe) in the PLCB4 gene, which was predicted to impair the local structural stability with a result that the protein function might be affected. From a review of the literature, only 36 patients with PLCB4 gene mutations were retrieved. Conclusion As with other studies examining familial cases of ARCND2, incomplete penetrance and variable expressivity were observed within different families' heterozygous mutations in PLCB4 gene. Although, motor and intellectual development are in the normal range in the vast majority of patients with ARCND2, long‐term follow‐up and assessment are still required.

A high-efficiency Nd:LuVO4 laser, pumped by a fiber-coupled laser diode at 916 nm, was successfully demonstrated. Employing a recycling-pumping architecture, an output power of 12.1 W at 1,343.2 nm was achieved with an incident pump power of 20 W, resulting in a slope efficiency of 62.1% and an optical conversion efficiency of 60.5%. Furthermore, the beam quality factor was measured to be approximately 1.1 at the maximum output level.

In this paper, we demonstrated an efficient degenerate middle infrared (mid-IR) ZGP-OPO that is pumped by an electro-optically Q-switched diode-pumped Tm:YAP laser. The Tm:YAP laser, operating at a repetition rate of 1 kHz, produced a peak pulse energy of 9.66 mJ at 1.94 μm and a minimum pulse width of 25 ns. Utilizing the Tm:YAP laser as the pump source, a peak average output power of 3.14 W at 3.88 μm was achieved in the degenerate ZGP-OPO with an incident Tm power of 9.4 W, resulting in a slope efficiency of 62.7% and an optical conversion efficiency of 33.4%. The minimum pulse width was measured at 21 ns, leading to a peak power of 149.5 kW. Additionally, the beam quality factor of the degenerate mid-IR ZGP-OPO was evaluated to be approximately 2.7 at the maximum output power level.

Objective To explore the influence of common methods of reducing non-viral nucleic acid on the abundance of plasma virus group. Methods Three kinds of library construction, five kinds of centrifugation conditions, two kinds of filters, four kinds of enzymes and four concentrations of chloroform were used to treat plasma samples added quantitatively 2.16 mL of pseudorabies virus(PRV) and 2.16 mL of porcine parvovirus(PPV). A total of 21.6 mL of plasma samples were processed, including 54 samples. Subsequently, nucleic acid was extracted, mitochondrial DNA(mtDNA) and two viruses were quantitated, the library of the next generation sequencing was constructed, Illumina NovaSeq 6000 was used for the next generation sequencing. The sequencing data were compared with Kraken Py 2.0 software, and the species annotation analysis was conducted. The corresponding species classification information of each segment was obtained to analyze the impact of different reducing non-viral nucleic acid methods on the relative abundance of microorganisms and two indicator viruses. Results After sequencing by Illumina NovaSeq 6000, 306.27 GB raw data and 193.17 GB clean data were obtained, with Q20>90%, Q30>85%, Error Rate of 0.03%, and average GC Content of 45.02%. The DNA library construction process significantly increased the proportion of microbial sequences and the PRV abundance [(91.8±0.5)%](P

Electrical tomography sensors have been widely used for pipeline parameter detection and estimation. Before they can be used in formal applications, the sensors must be calibrated using enough labeled data. However, due to the high complexity of actual measuring environments, the calibrated sensors are inaccurate since the labeling data may be uncertain, inconsistent, incomplete, or even invalid. Alternatively, it is always possible to obtain partial data with accurate labels, which can form mandatory constraints to correct errors in other labeling data. In this paper, a semi-supervised fuzzy clustering algorithm is proposed, and the fuzzy membership degree in the algorithm leads to a set of mandatory constraints to correct these inaccurate labels. Experiments in a dredger validate the proposed algorithm in terms of its accuracy and stability. This new fuzzy clustering algorithm can generally decrease the error of labeling data in any sensor calibration process.

Objective. To evaluate the influence of screw-tightening methods on the immediate and long-term stability of dental implant screw joints. Methodology. A total of 150 implants of three different implant systems with different diameters were used in this study. Each group was divided into three subgroups (n = 5), according to the tightening methods (A—tightening with recommended torque and retorque after 10 min; B—tightening with recommended torque, then loosening and immediate retorque; C—tightening with recommended torque only once). The operating time of tightening the assemblies was recorded. Ten minutes later, the immediate removal torque (IRT) (Ncm) was measured. After retightening the assemblies, a dynamic load between 20 and 200 N was applied for 105 cycles, and the postloading removal torque (PRT) (Ncm) was measured. Scanning electron microscopy (SEM) was used to observe the surface topography of the screws. Results. For different types of implants, the IRTs were 11.92 ± 1.04–34.12 ± 0.36 Ncm for method A, 11.64 ± 0.57–33.96 ± 0.29 Ncm for method B, and 10.30 ± 0.41–31.62 ± 0.52 Ncm for method C, and the IRTs of methods A and B were 6.28%–21.58% higher than that of method C (P≤0.046). The PRTs were 4.08 ± 0.77–29.86 ± 0.65 Ncm for method A, 4.04 ± 0.40–29.60 ± 0.36 Ncm for method B, and 2.98 ± 0.26–26.38 ± 0.59 Ncm for method C, and the PRTs of methods A and B were 11.77%–44.87% higher than that of method C (P≤0.016). The removal torque loss rates of methods A (12.49% ± 0.99%–65.88% ± 4.83%) and B (12.84% ± 0.96%–65.35% ± 1.95%) were 3.04%–7.74% lower than that of method C (16.58% ± 0.56%–71.10% ± 1.58%) (P≤0.017). The operating time of method A was much longer than those of methods B and C (P

Abstract Background Craniofacial microsomia (CFM) is a common congenital malformation with unknown pathogenesis. Although few cases have been reported, it is suggested that variants of the SF3B2 gene may lead to CFM. We herein report the case of a neonate with CFM exhibiting rare features of airway obstruction. Methods Trio whole‐exome sequencing and Sanger validation were performed on the proband and her parents. Candidate gene mutations were analyzed using the Genome Aggregation Database (gnomAD) for normal frequency distributions. The Human Splicing Finder (HSF) and Rare Disease Data Center (RDDC) RNA splicer algorithms predicted the variant's harmfulness, verified by a Minigene assay. Results The proband had a heterozygous SF3B2 variant, NM_006842.3:c.777+1G>A. The patient's father also carried this variant and exhibited facial abnormalities. The variant was not in gnomAD, and HSF and RDDC RNA splicers indicated donor site disruption. The minigene assay suggested that two mRNA products were produced, leading to a premature termination codon. Conclusion For this family, the pathogenesis of CFM may have been caused by an SF3B2 splicing variant. Affected family members exhibited varying degrees of malformation, indicating that CFM has phenotypic heterogeneity. This finding expands the phenotype and variant spectrum of SF3B2, enriches neonatal CFM research, and provides a possible guide to genetic counseling.

Time-of-Flight imaging is one of the quintessential techniques in three-dimensional reconstruction. However, depth missing is a common problem in Time-of-Flight imaging, which can be classified into structure-based depth loss and large-area one according to various reasons. Large-area depth loss generally occurs due to close-range overexposure resulting in limited dynamic range in depth sensing. Compared to structure-based depth loss, the recovery of large-area depth missing is more challenging and has been rarely studied. In this paper, a large-area depth recovery framework guided by polarization cues is proposed stemmed from a solid physical basic concerning depth and polarization, to realize high dynamic range in applications. Inspired by RGB-D system and shape-from-polarization technique, a dual camera system is utilized including infrared Time-of-Flight camera and visible polarized camera. A physical model between depth map and polarization cues, specifically depth-gradient and degree-of-polarization, is investigated and established. Based on the physical basics, a corresponding polarization-guided depth recovery algorithm with statistical analysis and image processing approach is introduced. Experimental results towards different targets demonstrate the effectiveness of the proposed method qualitatively and quantitatively, accompanied with outcome analysis and detailed discussions about strengths and future works, which indicates a great potential for the applications of high-quality three-dimensional reconstruction and depth sensing.

Abstract The objective of this study was to investigate the performance and emissions of a diesel engine fueled by coal-based diesel fuels and their blends with oxygenated fuel polyoxymethylene dimethyl ethers (PODEn). First, coal-based Fischer–Tropsch (FT) diesel fuel was blended with hydrogenated diesel fuel at three volume ratios of 40%/60%, 50%/50%, and 60%/40%, denoted as T6W4, T5W5, and T4W6, respectively. Then, PODEn were added into the T4W6 fuel with the volume ratios of 10%, 20%, and 30% to evaluate its effects on the performance and emissions of a coal-based diesel engine. The results showed that the output torques and powers of the three coal-based diesel blends were slightly lower than those of the petroleum diesel fuel. The brake specific fuel consumption (BSFC) of the coal-based diesel fuels was almost the same as that of the petroleum diesel fuel. The brake thermal efficiencies (BTE) of the coal-based diesel blends were slightly lower than that of the petroleum diesel fuel, and the maximum reduction was 1.59%. The pollutant emissions of T5W5 were the closest to those of petroleum diesel fuel. The nitrogen oxides (NOx) emissions of T4W6 were lower, with a maximum decrease of 11.18% compared with the petroleum diesel. The carbon monoxide (CO) and hydrocarbon (HC) emissions of T6W4 were the highest, with maximum increases of 36.79% and 29.05%, respectively. The smoke emissions of T4W6 and T6W4 were higher than those of petroleum diesel fuel. Adding PODEn into T4W6 lowered the engine power and torque but increased the BSFC and BTE. The output torque and power of the diesel engine were further reduced when PODEn were blended with T4W6, with the maximum reductions of 17.76% and 16.96%, respectively. With an increase in the PODEn blending ratio, BSFC and BTE increased gradually, and the maximum increase in the BTE was 1.57%. Blending PODEn with the fuel effectively improved the emission characteristics of the coal-based diesel fuels. The NOx emissions increased slightly, but the emissions of HC, CO, and smoke were reduced significantly, with maximum reductions of 24.42%, 31.67%, and 82.35%, respectively.

In this paper, we introduce a new statistical methodology for updating the flexibility level of the traditional distributions. The newly developed method is called, the logarithmic-U family of distributions. For the logarithmic-U distributions, the estimation of the parameters via the maximum likelihood method is discussed. Some mathematical properties of the logarithmic-U distributions are also derived. By using the logarithmic-U method, an updated version of the Weibull model, namely, the logarithmic Weibull distribution is introduced. A simulation study for the logarithmic Weibull distribution is provided. Finally, the practical illustration of the logarithmic Weibull distribution is shown by analyzing two data sets taken from the engineering sector. The first data set represents the fracture toughness of Al2O3 material. Whereas, the second data set represents the fatigue fracture of Kelvar 373/epoxy. The practical applications show that the proposed logarithmic Weibull distribution is very competent for analyzing data sets in engineering and other related sectors.

The alpine grassland ecosystem is a biodiversity hotspot of plants on the Qinghai-Tibetan Plateau, where rapid climate change is altering the patterns of plant biodiversity along elevational and seasonal gradients of environments. However, how belowground microbial biodiversity changes along elevational gradient during the growing season is not well understood yet. Here, we investigated the elevational distribution of soil prokaryotic communities by using 16S rRNA amplicon sequencing along an elevational gradient between 3,200 and 4,200 m, and a seasonal gradient between June and September in the Qinghai-Tibetan alpine grasslands. First, we found soil prokaryotic diversity and community composition significantly shifted along the elevational gradient, mainly driven by soil temperature and moisture. Species richness did not show consistent elevational trends, while those of evenness declined with elevation. Copiotrophs and symbiotic diazotrophs declined with elevation, while oligotrophs and AOB increased, affected by temperature. Anaerobic or facultatively anaerobic bacteria and AOA were hump-shaped, mainly influenced by moisture. Second, seasonal patterns of community composition were mainly driven by aboveground biomass, precipitation, and soil temperature. The seasonal dynamics of community composition indicated that soil prokaryotic community, particularly Actinobacteria, was sensitive to short-term climate change, such as the monthly precipitation variation. At last, dispersal limitation consistently dominated the assembly process of soil prokaryotic communities along both elevational and seasonal gradients, especially for those of rare species, while the deterministic process of abundant species was relatively higher at drier sites and in drier July. The balance between deterministic and stochastic processes in abundant subcommunities might be strongly influenced by water conditions (precipitation/moisture). Our findings suggest that both elevation and season can alter the patterns of soil prokaryotic biodiversity in alpine grassland ecosystem of Qinghai-Tibetan Plateau, which is a biodiversity hotspot and is experiencing rapid climate change. This work provides new insights into the response of soil prokaryotic communities to changes in elevation and season, and helps us understand the temporal and spatial variations in such climate change-sensitive regions.

Given a set of data objects, the fuzzy c-means (FCM) partitional clustering algorithm is favored due to easy implementation, rapid response, and feasible optimization. However, FCM fails to reflect either the importance degree of the individual data objects or that of the clusters. Numerous variants of FCM have been proposed to address these issues. However, most of them cannot effectively apply the available information on data objects or clusters. In this paper, a double-constraint fuzzy clustering algorithm is proposed to reflect the importance degrees of both individual data objects and clusters. By incorporating double constraints into each data object and cluster, the objective function of FCM is reformulated and its realization equation is mathematically conducted. Consequently, the clustering accuracy of FCM is improved by applying the available information on both data objects and clusters. Especially, the proposed algorithm effectively addresses the limitations inherent in the existing variants of FCM. The experimental results validate the effectiveness, implementation, and robustness of the new fuzzy clustering algorithm.

BackgroundLead exposure induces microglial cell death, of which the mechanism is unclear. Ferroptosis is a new death form and its role in microglia death has not been reported. ObjectiveTo investigate the role of ferroptosis in microglia following lead exposure in order to provide a theoretical basis for the mechanism of lead neurotoxicity. MethodsMicroglial cell line BV-2 cells were co-cultured with 0, 10, 20 and 40 μmol·L−1 lead acetate for 24 h. The 40 μmol·L−1 lead acetate group with iron chelator (DFO) was named the 40+DFO group. Changes in BV-2 cell morphology after lead exposure were observed under an inverted microscope; tissue iron kit and glutathione kit were used to detect intracellular iron and glutathione (GSH) respectively; flow cytometry was applied to detect lipid reactive oxygen species (lipid ROS) immunofluorescence intensity. Western blotting and qPCR were adopted to detect the expressions of glutathione peroxidase 4 (GPX4), solute carrier family 7 member 11 (SLC7A11), transferrin receptor 1 (TFR-1), divalent metal transporter 1 (DMT1), ferroportin 1 (FPN1) protein and mRNA. ResultsCompared with the control group, the number of BV-2 cells decreased with increasing doses of lead and the cells showed a large, round amoeboid shape. The intracellular levels of iron of BV-2 cells were (1.08±0.04), (1.29±0.03), and (1.72±0.10) mg·g−1 (calculated by protein, thereafter) in the 10, 20, and 40 μmol·L−1 lead acetate groups, respectively, significantly higher than that in the control group (P

Long-lasting zinc metal electrodes are crucial in developing commercial zinc-based batteries. Here, the authors investigate the different morphology evolution between the stripping and plating process and propose electrochemical protocols to prolong the lifespan of zinc anodes.

Although target detection based on electroencephalogram (EEG) signals has been extensively investigated recently, EEG-based target detection under weak hidden conditions remains a problem. In this paper, we proposed a rapid serial visual presentation (RSVP) paradigm for target detection corresponding to five levels of weak hidden conditions quantitively based on the RGB color space. Eighteen subjects participated in the experiment, and the neural signatures, including P300 amplitude and latency, were investigated. Detection performance was evaluated under five levels of weak hidden conditions using the linear discrimination analysis and support vector machine classifiers on different channel sets. The experimental results showed that, compared with the benchmark condition, (1) the P300 amplitude significantly decreased (8.92 ± 1.24 μV versus 7.84 ± 1.40 μV, p = 0.021) and latency was significantly prolonged (582.39 ± 25.02 ms versus 643.83 ± 26.16 ms, p = 0.028) only under the weakest hidden condition, and (2) the detection accuracy decreased by less than 2% (75.04 ± 3.24% versus 73.35 ± 3.15%, p = 0.029) with a more than 90% reduction in channel number (62 channels versus 6 channels), determined using the proposed channel selection method under the weakest hidden condition. Our study can provide new insights into target detection under weak hidden conditions based on EEG signals with a rapid serial visual presentation paradigm. In addition, it may expand the application of brain–computer interfaces in EEG-based target detection areas.

The performances of rechargeable batteries are detrimentally affected by low temperatures (e.g., < 0 °C). Here, the authors report a few-layer Bi2Se3 material capable of improving battery cycling performances when operational temperatures are shifted from +25 °C to −20 °C.

BackgroundGinseng-containing traditional medicine preparations (G-TMPs) in combination with fluoropyrimidine-based chemotherapy (FBC) are well-known treatments for advanced gastric cancer (AGC), with a superior efficacy to FBC alone. However, evidence regarding their efficacy remains limited. The purpose of this meta-analysis is to evaluate the efficacy and safety of G-TMPs in combination with FBC for the treatment of AGC.MethodsEight electronic databases were searched for randomized controlled trials (RCTs) using G-TMPs with FBC for the treatment of AGC. The primary outcome included the tumor response, while the secondary outcomes included the quality of life (QoL), proportions of peripheral blood lymphocytes, adverse drug reactions (ADRs), and levels of cancer biomarkers. The quality of evidence for each outcome was assessed using GRADE profilers.ResultsA total of 1,960 participants were involved in the 26 RCTs included. Patients treated with FBC plus G-TMPs had better objective response (risk ratio [RR] = 1.23, 95% confidence interval [CI]: 1.13 to 1.35, p < 0.00001) and disease control (RR = 1.13, 95% CI: 1.08 to 1.19, p < 0.00001) rates than those treated with FBC alone. Additionally, the combination group had a better QoL, higher proportions of CD3+ T cells, CD4+ T cells, and natural killer cells, as well as a higher CD4+/CD8+ T-cell ratio. Furthermore, lower levels of CA19-9, CA72-4, and CEA were confirmed in the combination treatment group. In addition, G-TMPs reduced the incidence of ADRs during chemotherapy.ConclusionIn combination with FBC, G-TMPs can potentially enhance efficacy, reduce ADRs, and improve prognosis for patients with AGC. However, high-quality randomized studies remain warranted.Systematic review registrationPROSPERO Number: CRD42021264938.

BackgroundIn recent years, an increasing number of patients with age-related macular degeneration (AMD) have received acupuncture treatment, but there has been no systematic review to evaluate the effect of acupuncture on patients with AMD.PurposeThis meta-analysis aims to review the clinical efficacy of acupuncture in the treatment of AMD.MethodsRandomized controlled trials up to September 4, 2022 were searched in the following databases: PubMed, Ovid Medline, Embase, Cochrane Library, The Chinese National Knowledge Infrastructure Database, VIP, Wanfang, and SINOMED. Two reviewers independently performed literature screening and data extraction. RevMan 5.4 was used for the meta-analysis.ResultsNine of the 226 articles were finally included. A total of 508 AMD patients (631 eyes) were enrolled, including 360 dry eyes and 271 wet eyes. The results showed that acupuncture alone or as an adjunct therapy improved both the clinical efficacy and best-corrected visual acuity (BCVA) of AMD patients and reduced their central macular thickness. The certainty of the evidence ranged from "low" to "very low".ConclusionThere is no high-quality evidence that acupuncture is effective in treating patients with AMD; patients with dry AMD may benefit from acupuncture treatment. Considering the potential of acupuncture treatment for AMD, it is necessary to conduct a rigorously designed randomized controlled trials to verify its efficacy.

BackgroundThe effect of primary site on cardiovascular mortality (CVM) post-radiotherapy (RT) in patients with limited-stage small cell lung cancer (LS-SCLC) remains unclear.MethodsWe screened the Surveillance, Epidemiology, and End Results (SEER) database between 1988 and 2013. We used cumulative incidence function (CIF) curves to compare CVM incidences, and performed Cox proportional hazards and Fine-Gray competing risk analyses to identify independent risk factors of CVM. Propensity score matching (PSM) analysis was conducted.ResultsAmong enrolled 4,824 patients (median age 57 years old, 49.2% were male), CVM accounts for 10.0% of all deaths after 5 years since cancer diagnosis. Hazard ratios (HRs) for CVM were 1.97 (95% CI: 1.23–3.16, P = 0.005) for main bronchus (MB) patients, 1.65 (95% CI: 1.04–2.63, P = 0.034) for lower lobe (LL) patients and 1.01 (95% CI: 0.40–2.59, P = 0.977) for middle lobe (ML) patients compared to upper lobe (UL) patients. CIF curves showed that the cumulative CVM incidence was greater in the re-categorized MB/LL group compared to UL/ML group both before PSM (P = 0.005) and after PSM (P = 0.012). Multivariate regression models indicated that MB/LL was independently associated with an increased CVM risk, before PSM (HRCox: 1.79, 95% CI: 1.23–2.61, P = 0.002; HRFine−Gray: 1.71, 95% CI: 1.18–2.48, P = 0.005) and after PSM (HRCox: 1.88, 95% CI: 1.20–2.95, P = 0.006; HRFine−Gray: 1.79, 95% CI: 1.15–2.79, P = 0.010).ConclusionsMB/LL as the primary site is independently associated with an increased CVM risk post-RT in patients with LS-SCLC.

Abstract Lung cancer is one of the most common malignant tumours worldwide. however, emerging immunotherapy and targeted therapies continue to show limited efficacy. In the search for new targets for lung cancer treatment, exosomes have become a major focus of research. Exosomes play an important role in the tumour microenvironment (TME) of lung cancer and affect invasion, metastasis, and treatment responses. This review describes our current understanding of the release of exosomes derived from different cells in the TME, the effects of exosomes on T/Tregs, myeloid-derived suppressor cells, tumour-associated macrophages, dendritic cells, and natural killer cells, and the role of exosomes in the endothelial–mesenchymal transition, angiogenesis, and cancer-associated fibroblasts. In particular, this review focuses on the potential clinical applications of exosomes in the lung cancer microenvironment and their prognostic and diagnostic value.

The interactions between water molecules, electrode materials and anions are essential yet challenging for aqueous dual ion batteries. Here, the authors demonstrate the voltage manipulation of dual ion batteries through matching intercalation energy and solvation energy of different anions.

Abstract To study the influence of diesel fuel blended with polyoxymethylene dimethyl ethers (PODEn), a new alternative fuel with a high oxygen content and large cetane number, on the combustion characteristics, fuel economies, and emission characteristics of heavy-duty diesel engines that meet China VI emission standards, relevant tests were conducted on a supercharged intercooled high-pressure common-rail diesel engine. The PODEn were blended with diesel fuel at three different ratios (volume fractions of 10%, 20%, and 30%). The test results showed that the PODEn could optimize the combustion process of diesel engines that met the China VI emission standards, effectively improve the thermal efficiencies of diesel engines, and reduce the emissions of hydrocarbon (HC), carbon monoxide (CO), and soot. With an increase in the PODEn blending ratio, the peak values of the in-cylinder pressure, average in-cylinder temperature, and instantaneous heat release rate gradually decreased, and each peak progressively moved forward. As the start of combustion gradually moved forward, the combustion duration was shortened by 0.7–2.8°CA, the heat release process became more concentrated, and the effective thermal efficiency was increased by up to 2.57%. The effective fuel consumption gradually increased, yet the equivalent effective fuel consumption gradually decreased, with the largest drop being as high as 4.55%. The nitrogen oxides (NO x ) emission increased slightly, and the emissions of HC, CO, and soot gradually decreased. The emissions of CO and soot declined significantly under high-speed and high-load conditions, with the highest reductions reaching 66.2% and 76.3%, respectively.

BackgroundPatients with Bell's Stage II/III necrotizing enterocolitis (NEC) may have more severe presentations, higher rates of death, and more long-term complications than those with Bell's Stage I NEC, so the purpose of this article was to construct a nomogram model to distinguish Bell's stage II/III NEC early from Bell's Stage I NEC, which is critical in the clinical management of NEC.Patients and MethodsA total of 730 NEC newborns diagnosed from January 2015 to January 2021 were retrospectively studied. They were randomly divided into training and validation groups at the ratio of 7:3. A nomogram model for predicting NEC was developed based on all the independent risk factors by multivariate regression analysis. The model's performance was mainly evaluated through three aspects: the area under the curve (AUC) to verify discrimination, the Hosmer–Lemeshow test and calibration curve to validate the consistency, and decision curve analysis (DCA) to determine the clinical effectiveness.ResultsPredictors included in the prediction model were gestational age (GA), birth weight (BW), asphyxia, septicemia, hypoglycemia, and patent ductus arteriosus (PDA). This nomogram model containing the above-mentioned six risk factors had good discrimination ability in both groups, and the AUCs were 0.853 (95% CI, 0.82–0.89) and 0.846 (95% CI, 0.79–0.90), respectively. The calibration curve and DCA confirmed that the nomogram had good consistency and clinical usefulness.ConclusionsThis individual prediction nomogram based on GA, BW, asphyxia, septicemia, hypoglycemia, and PDA served as a useful tool to risk-stratify patients with NEC, and can help neonatologists early distinguish Bell's stage II/III NEC early from Bell's Stage I NEC.

The immune system has evolved since the birth of humans. However, immune-related diseases have not yet been overcome due to the lack of expected indicators and targeting specificity of current medical technology, subjecting patients to very uncomfortable physical and mental experiences and high medical costs. Therefore, the requirements for treatments with higher specificity and indicative ability are raised. Fortunately, the discovery of and continuous research investigating circular RNAs (circRNAs) represent a promising method among numerous methods. Although circRNAs wear regarded as metabolic wastes when discovered, as a type of noncoding RNA (ncRNA) with a ring structure and wide distribution range in the human body, circRNAs shine brilliantly in medical research by virtue of their special nature and structure-determined functions, such as high stability, wide distribution, high detection sensitivity, acceptable reproducibility and individual differences. Based on research investigating the role of circRNAs in immunity, we systematically discuss the hotspots of the roles of circRNAs in immune-related diseases, including expression profile analyses, potential biomarker research, ncRNA axis/network construction, impacts on phenotypes, therapeutic target seeking, maintenance of nucleic acid stability and protein binding research. In addition, we summarize the current situation of and problems associated with circRNAs in immune research, highlight the applications and prospects of circRNAs in the treatment of immune-related diseases, and provide new insight into future directions and new strategies for laboratory research and clinical applications.

Most current automatic summarization methods are for English texts. The distinction between words in Chinese text is large, the types of parts of speech are many and complex, and polysemy or ambiguous words appear frequently. Therefore, compared with English text, Chinese text is more difficult to extract useful feature words. Due to the complex syntax of Chinese, there are currently relatively few automatic summarization methods for Chinese text. In the past, only the important sentences in the original text can be selected and simply arranged to obtain a summary with chaotic sentences and insufficient coherence. Meanwhile, because Chinese short text usually contains more redundant information and the sentence structure is not neat, we propose a topic-based automatic summary method for Chinese short text. Firstly, a key sentence selection method is proposed combining topic words and TF-IDF to obtain the score of each text corresponding to the topic in the original text data. Then the sentence with the highest score as the topic sentence of the topic is selected. Considering that the short text of Weibo may contain a lot of irrelevant information and sometimes even lack some important components of topic, three retouching mechanisms are proposed to improve the conciseness, richness and readability of topic sentence extraction results. We validate our approach on natural disaster and social hot event datasets from Sina Weibo. The experimental results show that the polished topic summary not only reflects the exact relationship between topic sentences and natural disasters or social hot events, but also has rich semantic information. More importantly, we can almost grasp the basic elements of natural disaster or social hot event from the topic sentence, so as to help the government guide disaster relief or meet the needs of users for quickly obtaining information of social hot events.

Abstract Background Mesenchymal stem cells (MSCs) are pluripotent mesenchymal cells present in various adult tissues. MSCs secrete exosomes as regulators of the tumor niche, with involvement in tumorigenesis and metastasis. The regulatory role of microRNAs (miRs or miRNAs) in MSCs via targeting cyclin E1 (CCNE1) or cyclin E2 (CCNE2) has been extensively reported. Since exosomes are considered as protective and enriched sources of shuttle miRNAs, we hypothesized that exosomal transfer of miR-144 from bone marrow-derived MSCs (BMMSCs) would affect the development of non-small cell lung cancer (NSCLC) cells by targeting CCNE1 and CCNE2. Methods We first quantified the levels of miR-144, CCNE1, and CCNE2 in NSCLC tissues and cell lines and then undertook gain- and loss-of-function studies of miR-144, CCNE1, and CCNE2 to investigate their roles in the biological characteristics of NSCLC in vitro. NSCLC cells (A549) were exposed to exosomes derived from MSCs, and cell proliferation and colony formation rate were determined using in vitro assays. Finally, effects of BMMSC-derived exosomal miR-144 on tumor development were studied in vivo. Results In NSCLC tissues and cell lines, miR-144 was expressed poorly and CCNE1 and CCNE2 were expressed highly. Artificially elevating miR-144 inhibited cell proliferation, colony formation, and the number of S phase-arrested cells in NSCLC by downregulating CCNE1 and CCNE2. Additionally, BMMSC-derived exosomal miR-144 led to restrained NSCLC cell proliferation and colony formation. These inhibitory effects of BMMSC-derived exosomes carrying miR-144 on NSCLC were confirmed by experiments in vivo. Conclusion Collectively, these findings revealed inhibitory effects of BMMSC-derived exosomal miR-144 on NSCLC progression, which were mediated by downregulation of CCNE1 and CCNE2.

BackgroundIrinotecan is a first-line agent in the systematic treatment of colorectal cancer (CRC). Adjusting the dose of irinotecan according to the uridine diphosphate glucuronosyltransferase (UGT) 1A1 genotype reflects the principle of individualized and precision medicine, and may improve the chemotherapy response and survival of CRC.MethodsTo summarize the feasibility, efficacy and safety of high dose irinotecan in CRC patients with UGT1A1 wild-type or heterozygous alleles, PubMed, EMBASE, MEDLINE and the Cochrane Central Register of Controlled Trials online databases were searched from the date of creation to October 22, 2021.ResultsA total of 1,186 related literatures were searched, and 14 studies were included for review according to the inclusion criteria. The results indicated that the maximum tolerated dose of irinotecan in CRC patients with UGT1A1 wild-type or heterozygous variant was significantly higher than the conventional recommended dose. Chemotherapy based on high dose irinotecan improved the clinical efficacy in mCRC patients with UGT1A1*28 wild-type and heterozygous variant, and the toxicity was tolerated, as reflected in most studies.ConclusionsWe are optimistic about the application of high dose irinotecan for mCRC patients with UGT1A1*28 wild-type or heterozygous variant, which will provide a relatively clear direction for future research and certain norms for clinical practice.

BackgroundTraditional medicine preparations (TMPs) combined with chemotherapy is widely used for patients with advanced pancreatic cancer (APC); however, its efficacy and safety are still unclear. The purpose of this meta-analysis was to evaluate the clinical efficacy and safety of TMPs combined with chemotherapy for the treatment of APC.MethodsA systematic search of eight electronic databases for randomized controlled trials (RCTs) was conducted from inception to October 15, 2021. Tumor response was identified as primary outcome, whereas quality of life (QoL), cancer biomarkers, and adverse drug reactions (ADRs) were identified as secondary outcomes. Quality of the evidence for each outcome was evaluated by GRADE profiler.ResultsIn total, 31 RCTs involving 1,989 individuals were included. This meta-analysis showed that TMPs combined with chemotherapy significantly improved the objective response rate (ORR) (RR=1.64, 95% CI [1.43 to 1.88], p

KNL1 (kinetochore scaffold 1) has attracted much attention as one of the assembly elements of the outer kinetochore, and the functions of its different domains have been gradually revealed, most of which are associated with cancers, but few links have been made between KNL1 and male fertility. Here, we first linked KNL1 to male reproductive health and the loss-function of KNL1 resulted in oligospermia and asthenospermia in mice (an 86.5% decrease in total sperm number and an 82.4% increase in static sperm number, respectively) through CASA (computer-aided sperm analysis). Moreover, we introduced an ingenious method to pinpoint the abnormal stage in the spermatogenic cycle using flow cytometry combined with immunofluorescence. Results showed that 49.5% haploid sperm was reduced and 53.2% diploid sperm was increased after the function of KNL1 was lost. Spermatocytes arrest was identified at the meiotic prophase I of spermatogenesis, which was induced by the abnormal assembly and separation of the spindle. In conclusion, we established an association between KNL1 and male fertility, providing a guide for future genetic counseling regarding oligospermia and asthenospermia, and a powerful method for further exploring spermatogenic dysfunction by utilizing flow cytometry and immunofluorescence.

Copper (Cu(Ⅱ)) pollution has a hazardous effect on human health. However, designing new adsorbents with prominent properties is a tremendous challenge in effectively removing Cu(Ⅱ) ions from the environment. In this study, new adsorbent—MnFe2O4/multi-wall carbon nanotubes (MMWCNTs), with excellent magnetic properties were synthesized and then systematically characterized. Introducing MnFe2O4 addressed the challenge of separating the nano-adsorbent from the liquid medium. Batch adsorption experiment results indicated that effective adsorption occurred in a relatively neutral range (pH=6–8). The adsorption behaviors were consistent with the pseudo-second-order model and the Freundlich model. The maximum adsorption capacity reached 46.41 mg/g at 308 K. The adsorption thermodynamics revealed the endothermic character of adsorption by MMWCNTs, and increasing the temperature benefitted the adsorption process. Furthermore, many surface functional groups of MMWCNTs facilitated adsorption performance. Compared with the MWCNTs before modified, the adsorbent had a nearly tenfold improvement from 3.4% to 34.8% in the removal efficiency of Cu(Ⅱ) ions. These results demonstrated that MMWCNTs are a suitable, efficient adsorbent that can be used in natural water bodies for adsorbing Cu(Ⅱ) ions.

Background: Exposure to heavy metals has been considered harmful and can cause cognitive deficits in preschool children. Objective: To investigate the possible mediation effect of neurotransmitters on the relationship of heavy metal exposure with neurobehaviour. Methods: The levels of blood heavy metals and neurotransmitters, along with the neurobehavioural scores, were determined in preschool children. Multiple linear regression was used to assess the relationship between heavy metals, neurotransmitters, and neurobehavioural scores. Furthermore, the mediating role of neurotransmitters was investigated. Results: An interquartile range (IQR) increase in lead (6.10 μg/L) was associated with a decrease of 8.52%, 30.06%, and 20.10% for Glutamic acid (Glu), Glycine (Gly), and gamma-aminobutyric acid (GABA), respectively. An IQR increase in arsenic (19.37 μg/L) was associated with an increase of 6.32% and 2.09% for Gly and GABA, respectively. Further, an IQR increase in zinc (15.58 μg/L) was associated with an increase of 1.44% for Ser, whereas the IQR increase was associated with a decrease of 2.14%, 2.24%, and 1.89% for Glu, Gly, and GABA, respectively. An IQR increase in selenium (38.75 μg/L) was associated with an increase of 1.88% for GABA. Moreover, both Glu and Gly decreased by 2.87% for an IQR increase in manganese (16.92 μg/L). An IQR increase in mercury (15.22 μg/L) was associated with a decrease of 2.43% for Ser, but the IQR increase was associated with an increase of 4.99% and 3.09% for Gly and GABA, respectively. It was found that Glu and Serine (Ser) have a significant linear relationship with conduct score and impulsivity-hyperactivity index, and that there was a significant linear relationship between Ser and the learning disability index. GABA and conduct score and attention-deficit hyperactivity disorder (ADHD) index have a significant linear relationship. There is a significant linear relationship between Gly and conduct, anxiety, ADHD, and impulsivity-hyperactivity index. The results of the mediating effect analysis indicated that Ser, Glu, Gly, and GABA have a specific mediating effect between blood heavy metals and neurobehaviour. Conclusion: We showed the mediating effect of neurotransmitters. The current study may provide valuable information regarding the prevention and management of metal-related neurological disorders in preschool children.

BackgroundAstragalus-containing traditional Chinese medicine (TCM) is widely used as adjunctive treatment to platinum-based chemotherapy (PBC) in patients with advanced gastric cancer (AGC) in China. However, evidence regarding its efficacy remains limited. This study aimed to evaluate the efficacy and safety of Astragalus-containing TCM combined with PBC in AGC treatment.MethodsWe searched for literature (up to July 19, 2020) in eight electronic databases. The included studies were reviewed by two researchers. The main outcomes were the objective response rate (ORR), disease control rate (DCR), survival rate, quality of life (QOL), adverse drug reactions (ADRs), and peripheral blood lymphocyte levels. The effect estimate of interest was the risk ratio (RR) or mean difference (MD) with 95% confidence intervals (CIs). Trial sequential analysis (TSA) was used to detect the robustness of the primary outcome and to calculate the required information size (RIS). Certainty of the evidence was assessed using the GRADE profiler.ResultsResults based on available literature showed that, compared with patients treated with PBC alone, those treated with Astragalus-containing TCM had a better ORR (RR: 1.24, 95% CI: 1.15–1.34, P < 0.00001), DCR (RR: 1.10, 95% CI: 1.06–1.14, P < 0.00001), 1-year survival rate (RR: 1.41, 95% CI: 1.09–1.82, P = 0.009), 2-year survival rate (RR: 3.13, 95% CI: 1.80–5.46, P < 0.0001), and QOL (RR: 2.03, 95% CI: 1.70–2.43, P < 0.00001 and MD: 12.39, 95% CI: 5.48–19.30, P = 0.0004); higher proportions of CD3+ T cells and CD3+ CD4+ T cells; higher ratio of CD4+/CD8+ T cells; nature killer cells; and lower incidence of ADRs. Subgroup analysis showed that both oral and injection administration of Astragalus-containing TCM increased tumor response. Whether treatment duration was ≥8 weeks or

Point processes are important in extreme value theory due to their equivalent formulations of two popular models in various applications: the block maxima models and the peak-over-threshold model. Point processes in a metric space provide tools to analyze heavy-tailed phenomena that appear in the research of extremal behaviors of functional data. To facilitate these applications of point processes, the equivalence between the weak convergence of point processes and the MO-convergence is established in the paper.

Aerosol optical depth (AOD) observations have been widely used to generate wide-coverage PM2.5 retrievals due to the adverse effects of long-term exposure to PM2.5 and the sparsity and unevenness of monitoring sites. However, due to non-random missing and nighttime gaps in AOD products, obtaining spatiotemporally continuous hourly data with high accuracy has been a great challenge. Therefore, this study developed an automatic geo-intelligent stacking (autogeoi-stacking) model, which contained seven sub-models of machine learning and was stacked through a Catboost model. The autogeoi-stacking model used the automated feature engineering (autofeat) method to identify spatiotemporal characteristics of multi-source datasets and generate extra features through automatic non-linear changes of multiple original features. The 10-fold cross-validation (CV) evaluation was employed to evaluate the 24-hour and continuous ground-level PM2.5 estimations in the Beijing-Tianjin-Hebei (BTH) region during 2018. The results showed that the autogeoi-stacking model performed well in the study area with the coefficient of determination (R2) of 0.88, the root mean squared error (RMSE) of 17.38 µg/m3, and the mean absolute error (MAE) of 10.71 µg/m3. The estimated PM2.5 concentrations had an excellent performance during the day (8:00–18:00, local time) and night (19:00–07:00) (the cross-validation coefficient of determination (CV-R2): 0.90, 0.88), and captured hourly PM2.5 variations well, even in the severe ambient air pollution event. On the seasonal scale, the R2 values from high to low were winter, autumn, spring, and summer, respectively. Compared with the original stacking model, the improvement of R2 with the autofeat and hyperparameter optimization approaches was up to 5.33%. In addition, the annual mean values indicated that the southern areas, such as Shijiazhuang, Xingtai, and Handan, suffered higher PM2.5 concentrations. The northern regions (e.g., Zhangjiakou and Chengde) experienced low PM2.5. In summary, the proposed method in this paper performed well and could provide ideas for constructing geoi-features and spatiotemporally continuous inversion products of PM2.5.

Abstract While traditional three‐layer structure supercapacitors are under mechanical manipulations, the high‐stress region concentrates, inevitably causing persistent structural problems including interlayer slippage, crease formation, and delamination of the electrode–electrolyte interface. Toward this, an all‐polymeric, all‐elastic and non‐laminated supercapacitor with high mechanical reliability and excellent electrochemical performance is developed. Specifically, a polypyrrole electrode layer is in situ integrated into a silk fibroin‐based elastic supramolecular hydrogel film with extensive hydrogen and covalent bonds, where a non‐laminate device is realized with structural elasticity at the device level. The non‐laminate configuration can avoid slippage and delamination, while the elasticity can preclude crease formation. Furthermore, under more severe mechanical damage, the supercapacitors can restore the electrochemical performance through non‐autonomous self‐healing capabilities, where the supramolecular design of host–guest interactions in the hydrogel matrix results in a superior self‐healing efficiency approaching ≈95.8% even after 30 cutting/healing cycles. The all‐elastic supercapacitor delivers an areal capacitance of 0.37 F cm−2 and a volumetric energy density of 0.082 mW h cm−3, which can well‐maintain the specific capacitance even at −20 °C with over 85.2% retention after five cut/healing cycles.

Aim: Not all the neonates respond with improvement in oxygenation following inhaled nitric oxide treatment (iNO) treatment. The aim of this study was to assess the independent risk factors associated with non-response to iNO during the 2 weeks of postnatal treatment in neonates diagnosed with persistent pulmonary hypertension (PPHN).Materials and Methods: This retrospective cohort study included all newborns with PPHN who received iNO treatment for more than 24 h. Demographic, obstetric, perinatal data and clinical complications were extracted from the hospitalization records. Subjects were divided into two groups according to their response to iNO inspiration during the first 24 h of iNO treatment. No response was defined as an increase in SpO2 < 5% or the inability to sustain saturation levels in the first 24 h of iNO treatment. For descriptive statistics, χ2 and t-test analysis were used to compare categorical and continuous variables between the two groups. To evaluate independent risk factors of non-responsiveness to iNO treatment, binary logistic regression analysis were performed.Results: A total of 75 newborns were included in the study. Sixty-two cases were in the responders group, and 13 cases were in the non-responders group. Univariate analysis showed that asphyxia, neonatal respiratory distress syndrome (NRDS), pulmonary surfactant administration, meconium aspiration syndrome (MAS), the severity of pulmonary hypertension (PH), and high-frequency oscillatory ventilation (HFOV) therapy were the high-risk factors affecting the response to iNO treatment in the newborns with PPHN. The binary logistic regression analysis indicated that asphyxia and NRDS incidence were independent predictors of non-responsiveness to iNO treatment [asphyxia: OR 4.193, 95% CI 1.104–15.927, P = 0.035; NRDS: OR 0.154, 95% CI 0.036–0.647, P = 0.011]. The patients in the non-responders group had shorter iNO inspiration followed by MV duration, supplemental oxygen and hospital stay, and higher mortality. There were no significant differences in IVH, PVL, and BPD between two groups.Conclusion: In the newborns with PPHN, asphyxia and NRDS resulted as the independent risk factors of non-responsiveness to iNO therapy. Asphyxia in the newborns with PPHN is detrimental to the response to iNO treatment, while NRDS is beneficial.

Rolling bearings are some of the most crucial components in rotating machinery systems. Rolling bearing failure may cause substantial economic losses and even endanger operator lives. Therefore, the accurate remaining useful life (RUL) prediction of rolling bearings is of tremendous research importance. Health indicator (HI) construction is the critical step in the data-driven RUL prediction approach. However, existing HI construction methods often require extraction of time-frequency domain features using prior knowledge while artificially determining the failure threshold and do not make full use of sensor information. To address the above issues, this paper proposes an end-to-end HI construction method called a multi-scale convolutional autoencoder (MSCAE) and uses LSTM neural networks for RUL prediction. MSCAE consists of three convolutional autoencoders with different convolutional kernel sizes in parallel, which can fully exploit the global and local information of the vibration signals. First, the raw vibration data and labels are input into MSCAE, and then, MSCAE is trained by minimizing the composite loss function. After that, the vibration data of the test bearings are fed into the trained MSCAE to extract HI. Finally, RUL prediction is performed using the LSTM neural network. The superiority of the HI extracted by MSCAE was verified using the PHM2012 challenge dataset. Compared to state-of-the-art HI construction methods, RUL prediction using MSCAE-extracted HI has the highest prediction accuracy.

Agrostis capillaris is a cool-season turf grass species that is found worldwide in temperate countries, and a good Pb phytostabilizer. In this study, the entire chloroplast genome sequence of A. capillaris was determined by Illumina sequencing. The complete chloroplast genome was circular and composed of 136,396 bp nucleotides with a GC content of about 38.5%. There were a large single-copy region (LSC, 81,659bp), a small single-copy region (SSC, 12,593bp), and a pair of reverse repeat regions (IRs, 42,144bp) in the chloroplast genome. In total, the A. capillaris chloroplast genome contained 144 genes, including 96 protein-coding genes, 40 tRNA genes, and 8 rRNA genes. Phylogenetic analysis revealed that A. capillaris was closely related to A. gigantean. The sequence data of A. capillaris chloroplast genome could provide useful genetic information for the studies on phylogenetic and evolutionary of Agrostidinae.

Abstract Aqueous rechargeable metal‐ion batteries (ARMBs) represent one of the current research frontiers due to their low cost, high safety, and other unique features. Evolving to a practically useful device, the ARMBs must be adaptable to various ambient, especially the cold weather. While much effort has been made on organic electrolyte batteries operating at low temperatures, the study on low‐temperature ARMBs is still in its infancy. The challenge mainly comes from water freezing at subzero temperatures, resulting in dramatically retarded kinetics. Here, the freezing behavior of water and its effects on subzero performances of ARMBs are first discussed. Then all strategies used to enhance subzero temperature performances of ARMBs by associating them with battery kinetics are summarized. The subzero temperature performances of ARMBs and organic electrolyte batteries are compared. The final section presents potential directions for further improvements and future perspectives of this thriving field.

Efficient electrogeneration of hydrogen peroxide (H2O2) is critical for treatment of refractory pollutants by the electro-Fenton process. An effective strategy is developed by combining a flow-through reactor with a polytetrafluoroethylene (PTFE)-modified graphite felt cathode. In this design, anodic oxygen is directly used for efficient H2O2 generation at the modified cathode. Experimental results show that the modified cathode with the optimum PTFE content can produce 29.6 mg/L of H2O2, which is 16 times higher than the unmodified graphite felt cathode for a flow rate of 3 mL/min. Maximum H2O2 production, up to 30.7 mg/L, was obtained under the following conditions: 120 mA, 3 mL/min, initial pH 13, no external aeration.

In the process of constructing engineered neural tissues, we often use mixed primary neural cells, which contain microglia in the cell culture. However, the role that microglia play in the construction of engineered neural tissue has not been well studied. Here, we generated three-dimensional (3D) engineered neural tissues by silk fibroin/collagen composite scaffolds and primary mixed cortical cells. We depleted microglial cells by magnetic separation. Then, we analyzed the neural growth, development, mature and synapse-related gene, and protein expressions compared with the control engineered neural tissues with the microglia-depleted engineered neural tissues. We found that the engineered neural tissues constructed by magnetic separation to remove microglia showed a decrease in the number of synaptic proteins and mature neurons. These findings link microglia to neuron and synaptic maturation and suggest the importance of microglia in constructing engineered neural tissues in vitro.

Abstract Rechargeable Zn‐based batteries (RZBs) have attracted much attention and been regarded as one of the most promising candidates for next‐generation energy storage featured with high safety, low costs, environmental friendliness, and satisfactory energy density. The aqueous electrolyte system exhibits great potential to power the future wearable electronics. Apart from the achievements of high capacity cathode and stable electrolyte, the anode suffers from problems of dendrite growth, hydrogen evolution, and passivation with limited attention. The dendrite formation strongly restricts the battery lifespan. Therefore, strategies focused on dendrite suppression are carefully categorized and summarized in this review, including crystallographic orientation manipulation, electric field control, ion flux regulation, and mechanical shield. Each strategy and the detailed approaches are critically dissected. Finally, remaining challenges are emphasized in this review, expecting to supply further research with potential directions to fulfill the high performance of the Zn anodes.

The growing popularity of unmanned aerial vehicle (UAV) attracts significant research interests and applications including low-altitude and airborne vehicles. Since there is no declared spectrum allocated to UAV communications, opportunistic transmission has been commonly considered as an important way for supporting UAV communications. When sharing the same spectrum with other users such as satellites and mobile base stations, accurate spectrum sensing and allocation are of critical importance for UAV communications to avoid serious interference. As the UAVs can constantly move to different locations with various spectrum environments, the spectrum decision may be invalid only in a short period, leading to require fast spectrum sensing. Furthermore, an UAV needs to predict possible temporal and spatial vacations of the spectrum. In this case, the spectrum prediction has a high dimensional state space which is notoriously difficult to solve. In this paper, some other issues such as how to determine the spectrum processing time and how to detect the primary signals with high priority to avoid interference, are also discussed. Finally, a fast spectrum sensing algorithm is proposed to improve the energy detection performance by optimizing the error estimation and a constant ratio of missed detection. Our proposed algorithm does not require high computational capability and can achieve relatively accurate sensing in low signal-to-noise ratio scenarios.