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The random forest algorithm was applied to study the nuclear binding energy and charge radius. The regularized root-mean-square of error (RMSE) was proposed to avoid overfitting during the training of random forest. RMSE for nuclides with Z, N>7 is reduced to 0.816 MeV and 0.020 0 fm compared with the six-term liquid drop model and a three-term nuclear charge radius formula, respectively. Specific interest is in the possible (sub) shells among the superheavy region, which is important for searching for new elements and the island of stability. The significance of shell features estimated by the so-called shapely additive explanation method suggests (Z, N)=(92, 142) and (98, 156) as possible subshells indicated by the binding energy. Because the present observed data is far from the N=184 shell, which is suggested by mean-field investigations, its shell effect is not predicted based on present training. The significance analysis of the nuclear charge radius suggests Z=92 and N=136 as possible subshells. The effect is verified by the shell-corrected nuclear charge radius model.

The microscopic mechanism of the energy transfer in cyclotrimethylene trinitramine (RDX) is of particular importance for the study of the energy release process in high-energy materials. In this work, an effective vibrational Hamiltonian based on normal modes (NMs) has been introduced to study the energy transfer process of RDX. The results suggest that the energy redistribution in RDX can be characterized as an ultrafast process with a time scale of 25 fs, during which the energy can be rapidly localized to the –NNO2 twisting mode (vNNO2), the N–N stretching mode (vN–N), and the C–H stretching mode (vC–H). Here, the vNNO2 and vN–N modes are directly related to the cleavage and dissociation of the N–N bond in RDX and, therefore, can be referred to as "active modes." More importantly, we found that the energy can be rapidly transferred from the vC–H mode to the vNNO2 mode due to their strong coupling. From this perspective, the vC–H mode can be regarded as an "energy collector" that plays a pivotal role in supplying energy to the "active modes." In addition, the bond order analysis shows that the dissociation of the N–N bonds of RDX follows a combined twisting and stretching path along the N–N bond. This could be an illustration of the further exothermic decomposition triggered by the accumulation of vibrational energy. The present study reveals the microscopic mechanism for the vibrational energy redistribution process of RDX, which is important for further investigation of the energy transfer process in high-energy materials. [ABSTRACT FROM AUTHOR]

Grapholita molesta (Busck) (Lepidoptera: Tortricidae) is a globally significant fruit pest traditionally managed using chemical insecticides such as lambda-cyhalothrin. However, repeated applications have led to the development of resistance in field populations. The mechanisms and fitness costs associated with lambda-cyhalothrin resistance in G. molesta remain poorly understood. In this study, we established a lambda-cyhalothrin-resistant strain (RS) of G. molesta through continuous selection with lambda-cyhalothrin in the laboratory for 21 generations, resulting in a 249.6-fold increase in resistance. Bioassay data from the F1 progeny (F1RS and F1SR) of reciprocal crosses between RS and susceptible strain (SS) showed similar degrees of dominance (0.40 for F1RS and 0.32 for F1SR). Significant differences between observed and expected mortalities of backcross individuals suggested that resistance to lambda-cyhalothrin is polygenic. Compared to the SS strain, the RS strain exhibited significantly prolonged periods of larval, prepupal, and pupal stages, as well as a significant decrease in larval weight. In addition, the RS strain showed significant reductions in fecundity, cumulative flight distance, maximum flight distance, cumulative flight time, maximum flight time, and average flight speed. These results suggest that resistance to lambda-cyhalothrin in G. molesta is autosomal, incompletely dominant, and polygenic. Life-history traits such as fecundity and flight capacity were significantly reduced in RS strains compared with the SS strain. These findings provide valuable insights for mitigating lambda-cyhalothrin resistance development and promoting sustainable control of G. molesta in the field. [ABSTRACT FROM AUTHOR]

Wireless communication capability is vital for remote transmission between unmanned aerial vehicle (UAV) coordination systems, but the communication link between highly dynamic UAV systems is unstable and severely disturbed due to its rapidly time-varying channel. Current channel estimation methods suffer from insufficient inter-symbol interference (ISI) and inter-carrier interference (ICI) suppression and inadequate noise filtering. Therefore, a collaborative channel estimation network (CoCENet) is proposed in this paper, and it can restrain the channel interference by capturing the amplitude–phase and time–frequency correlation at the same time. Moreover, CoCENet applies a multi-scale fusion strategy to optimize the purity of the estimated outcome. Our experiment results demonstrate that CoCENet has preferable performance in terms of the suppression of channel interference and noise in rapidly time-varying UAV systems in a complex environment without stationarity assumption. At a signal-to-noise ratio (SNR) of −10 dB, the mean square error (MSE) of CoCENet is improved by 1.7–2.3 dB compared to existing methods, and at a SNR of 20 dB, the MSE is improved by 1.1–2.2 dB. [ABSTRACT FROM AUTHOR]

SUMMARY: Plant trichomes are an excellent model for studying cell differentiation and development, providing crucial defenses against biotic and abiotic stresses. There is a well‐established inverse relationship between trichome density and aphid prevalence, indicating that higher trichome density leads to reduced aphid infestations. Here we present the cloning and characterization of a dominant quantitative trait locus, HIC (hirsute cotton), which significantly enhances cotton trichome density. This enhancement leads to markedly improved resistance against cotton aphids. The HIC encodes an HD‐ZIP IV transcriptional activator, crucial for trichome initiation. Overexpression of HIC leads to a substantial increase in trichome density, while knockdown of HIC results in a marked decrease in density, confirming its role in trichome regulation. We identified a variant in the HIC promoter (−810 bp A to C) that increases transcription of HIC and trichome density in hirsute cotton compared with Gossypium hirsutum cultivars with fewer or no trichomes. Interestingly, although the −810 variant in the HIC promoter is the same in G. barbadense and hirsute cotton, the presence of a copia‐like retrotransposon insertion in the coding region of HIC in G. barbadense causes premature transcription termination. Further analysis revealed that HIC positively regulates trichome density by directly targeting the EXPANSIN A2 gene, which is involved in cell wall development. Taken together, our results underscore the pivotal function of HIC as a primary regulator during the initial phases of trichome formation, and its prospective utility in enhancing aphid resistance in superior cotton cultivars via selective breeding. [ABSTRACT FROM AUTHOR]

BackgroundAs an excellent nondestructive testing technology, cold neutron radiography is widely employed to image materials of interest in many basic and application research fields. One of key components of such device is the neutron sensitive scintillation screen. Normally, these screens are made up of scintillation or phosphor powder mixed with/without neutron sensing isotopes, such as 6LiF:ZnS(Ag) and Gd2O2S:Tb. Uniform scintillation screens are very difficult to make a trade-off between spatial resolution and neutron detection efficiency. Recently a new type of micro-structural scintillation screens has been proposed, which is expected to have higher spatial resolution while maintaining higher neutron detection efficiency. Following this idea, a scintillation screen has been proposed, developed, and studied by our group.PurposeThis study aims to develop a new type of scintillation screens based on a glass capillary array filled with scintillation powders to achieve high spatial resolution and neutron detection efficiency.MethodsFirst of all, a neutron sensing scintillation screen was made by filling very fine grinded Gd2O2S:Tb phosphor powder into glass capillary arrays. Three main steps, i.e. the phosphor powder grinding, the particle size screening, and the vacuum suction filtration process, were taken making such screens. Then, photographs of Gd2O2S:Tb phosphor before and after grinding were taken with a scanning electron microscope (SEM) to examine the filling efficiency of scintillation powder in the glass capillary arrays. Finally, experimental test of spatial resolution of such scintillation screens was carried out by using an optical system to read out the scintillation light emitted by the screen, and a Siemens Star neutron test target to characterize the screens' spatial resolution with cold neutrons.ResultsX-ray luminescence spectra show that the grinding process reduces the light yield of the phosphor. The filling efficiency of scintillation powder in the glass capillary arrays is up to 70%. The cold neutron imaging system with developed scintillation screen achieves spatial resolution of about 300 μm@CTF=3% by experimental test.ConclusionsAlthough the new neutron sensing scintillation screen is still under-developing and there are still some problems to be overcome, cold neutron imaging scintillation screen based on glass capillary array filled with Gd2O2S:Tb phosphor, proposed in this study, can be used to achieve high spatial resolution and neutron detection efficiency with advantages of low cost and simple fabrication process.

Background: For early detection and postoperative monitoring of upper tract urothelial carcinoma (UTUC), the traditional detection method was limited to its invasiveness and insufficient sensitivity. We aim to use urine tumour DNA (utDNA) for detecting minimal residual disease (MRD), early diagnosis and perioperative monitoring in UTUC. Method: We previously established a utDNA multidimensional bioinformatic valuation model, named utLIFE, using low‐coverage whole‐genome sequencing and targeted deep sequencing. This prospective cohort enrolled 93 patients diagnosed with UTUC without metastasis. We collected morning urine samples on the day of surgery and the discharge day after the operation for utLIFE testing. In addition, we also enrolled 80 healthy controls to further validate the specificity of the utLIFE model in the study. Results: The utLIFE of preoperative samples could discriminate UTUC with high specificity (96.25%, 77/80), and high sensitivity (96.77%, 90/93) regardless of stage and grade. The sensitivity of utLIFE was significantly higher than urine cytology (p < 0.001) and fluorescence in situ hybridisation (FISH) (p < 0.001) (N = 19), especially in early‐stage and low‐grade UTUC. Postoperative utLIFE scores were significantly decreased compared with those of preoperative samples (79 vs. 36, p < 0.001), indicating its association with tumour burden. For special pathology types, utLIFE performed less well in sensitivity and perioperative alteration. Conclusion: In conclusion, we established a bioinformatic utDNA valuation model, utLIFE, which was validated to be a rapid and noninvasive approach with high sensitivity for early detection and MRD monitoring for UTUC. [ABSTRACT FROM AUTHOR]

Extreme learning machines (ELMs), single hidden-layer feedforward neural networks, are renowned for their speed and efficiency in classification and regression tasks. However, their generalization ability is often undermined by the random generation of hidden layer weights and biases. To address this issue, this paper introduces a Hierarchical Learning-based Chaotic Crayfish Optimization Algorithm (HLCCOA) aimed at enhancing the generalization ability of ELMs. Initially, to resolve the problems of slow search speed and premature convergence typical of traditional crayfish optimization algorithms (COAs), the HLCCOA utilizes chaotic sequences for population position initialization. The ergodicity of chaos is leveraged to boost population diversity, laying the groundwork for effective global search efforts. Additionally, a hierarchical learning mechanism encourages under-performing individuals to engage in extensive cross-layer learning for enhanced global exploration, while top performers directly learn from elite individuals at the highest layer to improve their local exploitation abilities. Rigorous testing with CEC2019 and CEC2022 suites shows the HLCCOA's superiority over both the original COA and nine renowned heuristic algorithms. Ultimately, the HLCCOA-optimized extreme learning machine model, the HLCCOA-ELM, exhibits superior performance over reported benchmark models in terms of accuracy, sensitivity, and specificity for UCI breast cancer diagnosis, underscoring the HLCCOA's practicality and robustness, as well as the HLCCOA-ELM's commendable generalization performance. [ABSTRACT FROM AUTHOR]

Simple Summary: Establishing a cellular steatosis model is crucial for studying liver lipid deposition in poultry. This study used leghorn male hepatoma (LMH) cells to investigate the effects of oleic acid (OA), sodium oleate (SO), palmitic acid (PA), sodium palmitate (SP), and their pairwise combinations on steatosis development. Subsequently, RNA-seq was employed to comprehensively analyze alterations in gene expression within cells under various steatosis-inducing conditions. In primary chicken embryonic liver cells and liver tissue, the optimal conditions for inducing steatosis identified in this study can also induce steatosis effectively. Overall, this study found that a combination of SO and PA efficiently induces steatosis in various chicken liver cell types and chicken embryonic liver tissues. Research on hepatic steatosis in animal husbandry has been a prominent area of study. Developing an appropriate in vitro cellular steatosis model is crucial for comprehensively investigating the mechanisms involved in liver lipid deposition in poultry and for identifying potential interventions to address abnormalities in lipid metabolism. The research on the methods of in vitro liver steatosis in chickens, particularly the effects of different fat mixtures, is still lacking. In this study, LMH cells were utilized to investigate the effects of OA, SO, PA, SP, and their pairwise combinations on steatosis development, with the aim of identifying the optimal conditions for inducing steatosis. Analysis of triglyceride (TG) content in LMH cells revealed that OA and SP had limited efficacy in increasing TG content, while a combination of SO and PA in a 1:2 ratio exhibited the highest TG content. Moreover, Oil Red O staining results in LMH cells demonstrated that the combination treatment had a more pronounced induction effect compared to 0.375 mM SO. Additionally, RNA-seq analysis showed that 0.375 mM SO significantly influenced the expression of genes associated with fatty acid metabolism compared to the control group, whereas the combination of SO and PA led to an enrichment of key GO terms associated with programmed cell death. These findings suggest that varying conditions of cellular steatosis could lead to distinct disruptions in gene expression. The optimal conditions for inducing steatosis in LMH cells were also tested on chicken embryonic liver cells and embryos. TG detection and Oil Red O staining assays showed that the combination of SO and PA successfully induced steatosis. However, the gene expression pattern differed from that of LMH cells. This study lays the foundations for further investigations into avian hepatic steatosis. [ABSTRACT FROM AUTHOR]