103 research outputs found

    Film-through large perovskite grains formation via a combination of sequential thermal and solvent treatment

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    Organic–inorganic halide perovskites have recently attracted strong research interest for fabrication of high-performance, lowcost photovoltaic devices. Recently, we reported a highly reproducible procedure to fabricate high-performance organic–inorganic halide perovskite solar cells. This procedure, based on a onestep, solvent-induced, fast deposition-crystallization method, involves the use of sec-butyl alcohol as a new solvent to induce the CH3NH3PbI3 fast crystallization deposition. In the present study, we propose a reproducible fabrication method to prepare both flat and large-grain perovskite film by adding a pre-annealing step to strengthen the perovskite nucleation, aiming to facilitate the excess CH3NH3I and solvent removal in the sec-butyl alcohol soaking process, in which all films with thickness between 420 nm and 1µm performed uniformly. The best performing planar device obtained with this procedure had an efficiency of 17.2% under AM 1.5G illumination and an average power conversion efficiency of 16.2 ± 0.5%. We also analyzed the efficiency of halide perovskite planar solar cells as a function of the perovskite film thickness; the efficiency dropped only slightly to 15.7% when the perovskite film thickness was increased to 1µm

    Target-Barrier Coverage Improvement in an Insecticidal Lamps Internet of UAVs

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    Insecticidal lamps Internet of things (ILs-IoT) has attracted considerable attention for its applications in pest control to achieve green agriculture. However, ILs-IoTs cannot provide a perfect solution to the migratory pest outbreak if the ILs are fixed on the ground. In this paper, we embed ILs in unmanned aerial vehicles (UAVs) as the mobile nodes, which can be rapidly landed on the ground to kill agricultural pests, and the Internet of UAVs (IoUAV) is introduced to extend the application of ILs-IoTs. To take full advantage of the IL-IoUAVs, we formulate the problem of target-barrier coverage and investigate how to minimise the number of IL-UAVs in constructing the target-barrier coverage. The target-barrier coverage is introduced utilizing the realistic probabilistic sensing model of IL-UAVs, based on which we study how to guarantee the target-barrier coverage while minimizing the number of IL-UAVs needed. The problem is solved by an optimal algorithm to merge multiple target-barriers. Evaluation results show the efficiency of our designed algorithms for constructing target-barrier coverage

    In situ electron paramagnetic resonance spectroscopy using single nanodiamond sensors

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    An ultimate goal of electron paramagnetic resonance (EPR) spectroscopy is to analyze molecular dynamics in place where it occurs, such as in a living cell. The nanodiamond (ND) hosting nitrogen-vacancy (NV) centers will be a promising EPR sensor to achieve this goal. However, ND-based EPR spectroscopy remains elusive, due to the challenge of controlling NV centers without well-defined orientations inside a flexible ND. Here, we show a generalized zero-field EPR technique with spectra robust to the sensor's orientation. The key is applying an amplitude modulation on the control field, which generates a series of equidistant Floquet states with energy splitting being the orientation-independent modulation frequency. We acquire the zero-field EPR spectrum of vanadyl ions in aqueous glycerol solution with embedded single NDs, paving the way towards \emph{in vivo} EPR

    Hybridization alters the gut microbial and metabolic profile concurrent with modifying intestinal functions in Tunchang pigs

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    IntroductionHybridization has been widely used among Chinese wild boars to improve their growth performance and maintain meat quality. Most studies have focused on the genetic basis for such variation. However, the differences in the gut environment between hybrid and purebred boars, which can have significant impacts on their health and productivity, have been poorly understood.MethodsIn the current study, metagenomics was used to detect the gut microbial diversity and composition in hybrid Batun (BT, Berkshire × Tunchang) pigs and purebred Tunchang (TC) pigs. Additionally, untargeted metabolomic analysis was used to detect differences in gut metabolic pathways. Furthermore, multiple molecular experiments were conducted to demonstrate differences in intestinal functions.ResultsAs a result of hybridization in TC pigs, a microbial change was observed, especially in Prevotella and Lactobacillus. Significant differences were found in gut metabolites, including fatty acyls, steroids, and steroid derivatives. Furthermore, the function of the intestinal barrier was decreased by hybridization, while the function of nutrient metabolism was increased.DiscussionEvidences were shown that hybridization changed the gut microbiome, gut metabolome, and intestinal functions of TC pigs. These findings supported our hypothesis that hybridization altered the gut microbial composition, thereby modifying the intestinal functions, even the host phenotypes. Overall, our study highlights the importance of considering the gut microbiome as a key factor in the evaluation of animal health and productivity, particularly in the context of genetic selection and breeding programs

    Atomically Dispersed Pd on Nanodiamond/Graphene Hybrid for Selective Hydrogenation of Acetylene

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    An atomically dispersed palladium (Pd) catalyst supported onto a defective nanodiamond-graphene (ND@G) is reported here for selective hydrogenation of acetylene in the presence of abundant ethylene. The catalyst exhibits remarkable performance for the selective conversion of acetylene to ethylene: high conversion (100%), ethylene selectivity (90%), and good stability (i.e., steady for at least 30 hours). The unique struc-ture of the catalyst (i.e., atomically dispersion of Pd atoms on graphene through Pd-C bond anchoring) ensure the facile desorption of ethylene against the over-hydrogenation of ethylene to undesired ethane, which is the key for the outstanding selectivity of the catalyst

    Survival outcomes of stage I colorectal cancer:development and validation of the ACEPLY model using two prospective cohorts

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    BACKGROUND: Approximately 10% of stage I colorectal cancer (CRC) patients experience unfavorable clinical outcomes after surgery. However, little is known about the subset of stage I patients who are predisposed to high risk of recurrence or death. Previous evidence was limited by small sample sizes and lack of validation. METHODS: We aimed to identify early indicators and develop a risk stratification model to inform prognosis of stage I patients by employing two large prospective cohorts. Prognostic factors for stage II tumors, including T stage, number of nodes examined, preoperative carcinoma embryonic antigen (CEA), lymphovascular invasion, perineural invasion (PNI), and tumor grade were investigated in the discovery cohort, and significant findings were further validated in the other cohort. We adopted disease-free survival (DFS) as the primary outcome for maximum statistical power and recurrence rate and overall survival (OS) as secondary outcomes. Hazard ratios (HRs) were estimated from Cox proportional hazard models, which were subsequently utilized to develop a multivariable model to predict DFS. Predictive performance was assessed in relation to discrimination, calibration and net benefit. RESULTS: A total of 728 and 413 patients were included for discovery and validation. Overall, 6.7% and 4.1% of the patients developed recurrences during follow-up. We identified consistent significant effects of PNI and higher preoperative CEA on inferior DFS in both the discovery (PNI: HR = 4.26, 95% CI: 1.70–10.67, p = 0.002; CEA: HR = 1.46, 95% CI: 1.13–1.87, p = 0.003) and the validation analysis (PNI: HR = 3.31, 95% CI: 1.01–10.89, p = 0.049; CEA: HR = 1.58, 95% CI: 1.10–2.28, p = 0.014). They were also significantly associated with recurrence rate. Age at diagnosis was a prominent determinant of OS. A prediction model on DFS using Age at diagnosis, CEA, PNI, and number of LYmph nodes examined (ACEPLY) showed significant discriminative performance (C-index: 0.69, 95% CI:0.60–0.77) in the external validation cohort. Decision curve analysis demonstrated added clinical benefit of applying the model for risk stratification. CONCLUSIONS: PNI and preoperative CEA are useful indicators for inferior survival outcomes of stage I CRC. Identification of stage I patients at high risk of recurrence is feasible using the ACEPLY model, although the predictive performance is yet to be improved. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-022-02693-7

    Glycolysis-Related Gene Expression Profiling Screen for Prognostic Risk Signature of Pancreatic Ductal Adenocarcinoma

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    Objective: Pancreatic ductal adenocarcinoma (PDAC) is highly lethal. Although progress has been made in the treatment of PDAC, its prognosis remains unsatisfactory. This study aimed to develop novel prognostic genes related to glycolysis in PDAC and to apply these genes to new risk stratification.Methods: In this study, based on the Cancer Genome Atlas (TCGA) PAAD cohort, the expression level of glycolysis-related gene at mRNA level in PAAD and its relationship with prognosis were analyzed. Non-negative matrix decomposition (NMF) clustering was used to cluster PDAC patients according to glycolytic genes. Prognostic glycolytic genes, screened by univariate Cox analysis and LASSO regression analysis were established to calculate risk scores. The differentially expressed genes (DEGs) in the high-risk group and the low-risk group were analyzed, and the signal pathway was further enriched to analyze the correlation between glycolysis genes. In addition, based on RNA-seq data, CIBERSORT was used to evaluate the infiltration degree of immune cells in PDAC samples, and ESTIMATE was used to calculate the immune score of the samples.Results: A total of 319 glycolysis-related genes were retrieved, and all PDAC samples were divided into two clusters by NMF cluster analysis. Survival analysis showed that PDAC patients in cluster 1 had shorter survival time and worse prognosis compared with cluster 2 samples (P < 0.001). A risk prediction model based on 11 glycolysis genes was constructed, according to which patients were divided into two groups, with significantly poorer prognosis in high-risk group than in low-risk group (P < 0.001). Both internal validation and external dataset validation demonstrate good predictive ability of the model (AUC = 0.805, P < 0.001; AUC = 0.763, P < 0.001). Gene aggregation analysis showed that DEGs highly expressed in high-risk group were mainly concentrated in the glycolysis level, immune status, and tumor cell proliferation, etc. In addition, the samples in high-risk group showed immunosuppressed status and infiltrated by relatively more macrophages and less CD8+T cell.Conclusions: These findings suggested that the gene signature based on glycolysis-related genes had potential diagnostic, therapeutic, and prognostic value for PDAC

    High energy Millihertz quasi-periodic oscillations in 1A 0535+262 with Insight-HXMT challenge current models

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    We studied the millihertz quasi-periodic oscillation (mHz QPO) in the 2020 outburst of the Be/X-ray binary 1A 0535+262 using Insight-HXMT data over a broad energy band. The mHz QPO is detected in the 27-120 keV energy band. The QPO centroid frequency is correlated with the source flux, and evolves in the 35-95 mHz range during the outburst. The QPO is most significant in the 50-65 keV band, with a significance of ~ 8 sigma, but is hardly detectable (<2 sigma) in the lowest (1-27 keV) and highest (>120 keV) energy bands. Notably, the detection of mHz QPO above 80 keV is the highest energy at which mHz QPOs have been detected so far. The fractional rms of the mHz QPO first increases and then decreases with energy, reaching the maximum amplitude at 50-65 keV. In addition, at the peak of the outburst, the mHz QPO shows a double-peak structure, with the difference between the two peaks being constant at ~0.02 Hz, twice the spin frequency of the neutron star in this system. We discuss different scenarios explaining the generation of the mHz QPO, including the beat frequency model, the Keplerian frequency model, the model of two jets in opposite directions, and the precession of the neutron star, but find that none of them can explain the origin of the QPO well. We conclude that the variability of non-thermal radiation may account for the mHz QPO, but further theoretical studies are needed to reveal the physical mechanism.Comment: 13 pages, 7 figures. Accepted for publication in MNRA
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