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The Asian corn borer, Ostrinia furnacalis (Guenée), emerges as a significant threat to maize cultivation, inflicting substantial damage upon the crops. Particularly, its larval stage represents a critical point characterised by significant economic consequences on maize yield. To manage the infestation of this pest effectively, timely and precise identification of its larval stages is required. Currently, the absence of techniques capable of addressing this urgent need poses a formidable challenge to agricultural practitioners. To mitigate this issue, the current study aims to establish models conducive to the identification of larval stages. Furthermore, this study aims to devise predictive models for estimating larval weights, thereby enhancing the precision and efficacy of pest management strategies. For this, 9 classification and 11 regression models were established using four feature datasets based on the following features geometry, colour, and texture. Effectiveness of the models was determined by comparing metrics such as accuracy, precision, recall, F1-score, coefficient of determination, root mean squared error, mean absolute error, and mean absolute percentage error. Furthermore, Shapley Additive exPlanations analysis was employed to analyse the importance of features. Our results revealed that for instar identification, the DecisionTreeClassifier model exhibited the best performance with an accuracy of 84%. For larval weight, the SupportVectorRegressor model performed best with R2 of 0.9742. Overall, these findings present a novel and accurate approach to identify instar and predict the weight of O. furnacalis larvae, offering valuable insights for the implementation of management strategies against this key pest.
Ignorable likelihood (IL) approaches are often used to handle missing data when estimating a multivariate model, such as a structural equation model. In this case, the likelihood is based on all available data, and no model is specified for the missing data mechanism. Inference proceeds via maximum likelihood or Bayesian methods, including multiple imputation without auxiliary variables. Such IL approaches are valid under a missing at random (MAR) assumption. Rabe-Hesketh and Skrondal (Ignoring non-ignorable missingness. Presidential Address at the International Meeting of the Psychometric Society, Beijing, China, 2015; Psychometrika, 2023) consider a violation of MAR where a variable A can affect missingness of another variable B also when A is not observed. They show that this case can be handled by discarding more data before proceeding with IL approaches. This data-deletion approach is similar to the sequential estimation of Mohan et al. (in: Advances in neural information processing systems, 2013) based on their ordered factorization theorem but is preferable for parametric models. Which kind of data-deletion or ordered factorization to employ depends on the nature of the MAR violation. In this article, we therefore propose two diagnostic tests, a likelihood-ratio test for a heteroscedastic regression model and a kernel conditional independence test. We also develop a test-based estimator that first uses diagnostic tests to determine which MAR violation appears to be present and then proceeds with the corresponding data-deletion estimator. Simulations show that the test-based estimator outperforms IL when the missing data problem is severe and performs similarly otherwise.
Unpredictability is a core but understudied dimension of adversities and has been receiving increasing attention recently. The effects of unpredictability on psychopathology and the underlying neural mechanisms, however, remain unclear. It is also unknown how unpredictability interacts with other dimensions of adversities in predicting brain development and psychopathology of youth.
Methods
We applied cluster robust standard errors to examine how unpredictability was associated with the developmental changes in resting-state functional connectivity (rsFC) of large-scale brain networks implicated in psychopathology, as well as the moderating role of deprivation, using data from the Adolescent Brain Cognitive Development (ABCD) study, which included four measurements from baseline (mean ± s.d. age, 119.13 ± 7.51 months; 2815 females) to 3-year follow-up (N = 5885).
Results
After controlling for threat, unpredictability was associated with a smaller increase in rsFC within default mode network (DMN) and a smaller decrease in rsFC between cingulo-opercular network (CON) and DMN. Neighborhood educational deprivation moderated the associations between unpredictability and changes in rsFC within DMN and fronto-parietal network (FPN), as well as between CON and DMN. A smaller decrease in rsFC between CON and DMN mediated the association between unpredictability and externalizing problems. Neighborhood educational deprivation moderated the indirect pathway from unpredictability to externalizing problems via a smaller decrease in CON-DMN rsFC.
Conclusions
Our findings shed light on the neural mechanisms underlying the associations between unpredictability and adolescents' psychopathology and the moderating role of deprivation, highlighting the significance of providing stable environment and abundant educational opportunities to facilitate optimal development.
Using data from the China Health and Retirement Longitudinal Study, this research investigates how post-retirement employment influences older people’s expenditure in urban China. By broadening the understanding of post-retirement employment behaviour from a consumer welfare perspective, this study expands the literature on retirement consumption and provides theoretical explanations, empirical insights and policy recommendations. The findings reveal that post-retirement employment behaviour reduces urban retirees’ household expenditure and has a more significant effect on men than on women, but this effect diminishes as consumption levels rise. Increasing income, promoting social participation and improving subjective health outcomes are all potential channels through which post-retirement employment can affect consumption. Further analysis shows two main reasons why post-retirement employment reduces older people’s expenditure: first, the increase in subjective health levels resulting from post-retirement employment reduces healthcare expenditure; second, post-retirement employment does not promote social participation and self-rated health for all consumption levels and all genders of retirees – it also decreases expenditure. Preliminary evidence suggests that internet use positively moderates the negative impact of post-retirement employment on older people’s expenditure. These findings provide policy implications for retirement policies and the promotion of the silver economy.
Todorokite is a common Mn oxide (with a tunnel structure) in the Earth surface environment, and can be obtained by hydrothermal treatment or refluxing process from precursor buserite with a layered structure. Several chemical reaction conditions for the phase transformation from Na-buserite to todorokite at atmospheric pressure were investigated, including temperature, pH, crystallinity of precursor Na-buserite, the amount of the interlayer Mg2+ of the Mg-buserite and clay minerals. The results showed that the conversion rate and crystallinity of todorokite decreased with falling temperature, and Mg-buserite could not be completely transformed to todorokite at lower temperatures (40°C). The poorly crystalline Na-buserite could be converted into todorokite more easily than highly crystalline Na-buserite. Todorokite can be prepared at pH 5–9, but the rate of conversion and crystallinity of todorokite did vary with pH in the order: neutral ≈ alkali > acidic. The conversion rate of todorokite decreased with decreasing interlayer Mg2+ content of the Mg-buserite. The presence of montmorillonite or goethite slowed the formation reaction of todorokite in the refluxing process, and the reaction time was prolonged when the amounts of those minerals were increased.
Compound bubbles with a liquid coating in another continuous immiscible bulk phase are ubiquitous in a wide range of natural and industrial processes. Their formation, rise and ultimate bursting at the air–liquid interface play crucial roles in the transport and fate of natural organic matter and contaminants. However, the dynamics of compound bubbles has not received considerable attention until recently. Here, inspired by our previous work (Yang et al., Nat. Phys., vol. 19, 2023, pp. 884–890), we investigate the entrainment of daughter oil droplets in bulk water produced by a bursting oil-coated bubble. We document that the size of the entrained daughter oil droplet is affected by the oil coating fraction and the bulk liquid properties. We rationalize this observation by balancing the viscous force exerted by the extensional flow produced by bubble bursting with the capillary force resisting the deformation of the oil coating, and considering the subsequent end-pinching process which finally entrains the daughter oil droplets. We propose a scaling analysis for the daughter oil droplet size that well captures the experimental results for a wide range of oil coating fractions and Ohnesorge numbers of the bulk liquid. In addition, we discuss the non-monotonic variation of daughter droplet size with the Ohnesorge number, and show the eventual absence of daughter droplets because of the strong viscous effect in the high-Ohnesorge-number regime. Our findings may advance the fundamental understanding of compound bubble bursting and provide guidance and modelling constraints for bubble-mediated contaminant transport in liquids.
The motion of a long gas bubble in a confined capillary tube is ubiquitous in a wide range of engineering and biological applications. While the understanding of the deposited thin viscous film near the tube wall in Newtonian fluids is well developed, the deposition dynamics in commonly encountered non-Newtonian fluids remains much less studied. Here, we investigate the dynamics of a confined bubble moving in shear-thinning fluids with systematic experiments, varying the zero-shear-rate capillary number $Ca_0$ in the range of $O(10^{-3}\unicode{x2013}10^2)$ considering the zero-shear-rate viscosity. The thickness of the deposited liquid film, the bubble speed and the bubble front/rear menisci are measured, which are further rationalized with the recent theoretical studies based on appropriate rheological models. Compared with Newtonian fluids, the film thickness decreases for both the carboxymethyl cellulose and Carbopol solutions when the shear-thinning effect dominates. We show that the film thickness follows the scaling law from Aussillous & Quéré (Phys. Fluids, vol. 12, no. 10, 2000, pp. 2367–2371) with an effective capillary number $Ca_e$, considering the characteristic shear rate in the film as proposed by Picchi et al. (J. Fluid Mech., vol. 918, no. A7, 2021, pp. 1–30). $Ca_e$ is calculated by the Carreau number and the power-law index from the Carreau–Yasuda rheological model. The shear-thinning effect also influences the bubble speed and delays the transition to the parabolic region in the bubble front and rear menisci. In particular, a high degree of undulations on the bubble surface results in an intricate rear viscosity distribution for the rear meniscus and the deviation between the experiments and theory may require a further investigation to resolve the axial velocity field. Our study may advance the fundamental understandings and engineering guidelines for coating processes involving thin-film flows and non-Newtonian fluids.
Low molecular weight glutenin subunits (LWM-GSs) play a crucial role in determining wheat flour processing quality. In this work, 35 novel LMW-GS genes (32 active and three pseudogenes) from three Aegilops umbellulata (2n = 2x = 14, UU) accessions were amplified by allelic-specific PCR. We found that all LMW-GS genes had the same primary structure shared by other known LMW-GSs. Thirty-two active genes encode 31 typical LMW-m-type subunits. The MZ424050 possessed nine cysteine residues with an extra cysteine residue located in the last amino acid residue of the conserved C-terminal III, which could benefit the formation of larger glutenin polymers, and therefore may have positive effects on dough properties. We have found extensive variations which were mainly resulted from single-nucleotide polymorphisms (SNPs) and insertions and deletions (InDels) among the LMW-GS genes in Ae. umbellulata. Our results demonstrated that Ae. umbellulata is an important source of LMW-GS variants and the potential value of the novel LMW-GS alleles for wheat quality improvement.
The joint effects of stimulus quality and semantic context in visual word recognition were examined with event-related potential (ERP) recordings. In one-character Chinese word recognition, we manipulated stimulus quality at two degradation levels (highly vs. slightly degraded) and semantic context at two priming levels (semantically related vs. unrelated). In a prime–target–probe trial flow, ERPs were recorded to the target character which was presented in either high or slight degradation and which was preceded by either a semantically related or unrelated prime character. The target character was then followed by a probe character which was either identical to or different from the target character. Subjects were instructed to make target–probe matching judgments. The ERP results demonstrated a degradation by priming interaction, with larger N400 semantic priming effects for slightly degraded targets. Moreover, the degradation effects were observed on the P200, N250, and N400. These findings provided evidence for the cascaded model of visual word recognition such that the visual processing cascaded into the semantic stage and thus interacted on the N400 amplitude. The results were compared to an earlier study with a null ERP degradation by priming interaction. The ramifications of these results for models of visual word recognition are discussed.
The orogenic process and crustal growth of the Changning–Menglian Palaeo-Tethys orogenic belt in the southeastern Tibetan Plateau is not fully understood. Triassic Caojian rhyolites and granites occur extensively in this orogenic belt and represent important constraints for this issue. This study aims to examine the relationships between the Triassic Caojian rhyolites and granites and to gain a better understanding of their possible petrogenesis. The study used zircon U–Pb geochronology, trace element analyses and Sr–Nd–Hf isotope data to better understand the relationships and possible origin of the rhyolites and granites. Recent zircon U–Pb ages indicated that the Caojian rhyolites were emplaced at 227.2 Ma, whereas age estimates for Caojian granites were slightly older (233.4–236.9 Ma). The Caojian rhyolites are enriched in large-ion lithophile elements and high-field-strength elements, with elevated FeOtot/MgO and Ga/Al ratios. However, they are significantly depleted in Ba, Sr, Eu, P and Ti. These geochemical characteristics indicate that they have an A-type affinity. Furthermore, the Caojian granites comprise biotite monzogranites and granodiorites and show unfractionated composition. Mineralogically, the Caojian granites were found to contain diagnostic I-type minerals such as hornblende. Geochemical data suggest that the petrogenesis of the Triassic Caojian rhyolites is characterized by rejuvenation of crystal mush represented by the Triassic Caojian granites. The necessary thermal input was supplied by mafic magma. This magmatic evolution was likely related to lithospheric delamination and upwelling of the asthenosphere during the Mid- to Late Triassic, forming post-collisional I-type granites and A-type volcanics in the Changning–Menglian Palaeo-Tethys orogenic belt.
There have been growing uses of semantic networks in the past decade, such as leveraging large-scale pre-trained graph knowledge databases for various natural language processing (NLP) tasks in engineering design research. Therefore, the paper provides a survey of the research that has employed semantic networks in the engineering design research community. The survey reveals that engineering design researchers have primarily relied on WordNet, ConceptNet, and other common-sense semantic network databases trained on non-engineering data sources to develop methods or tools for engineering design. Meanwhile, there are emerging efforts to mine large scale technical publication and patent databases to construct engineering-contextualized semantic network databases, e.g., B-Link and TechNet, to support NLP in engineering design. On this basis, we recommend future research directions for the construction and applications of engineering-related semantic networks in engineering design research and practice.
In minimally invasive surgery, surgical instruments with a wrist joint have better flexibility. However, the bending motion of the wrist joint causes a coupling motion between the end-effector and wrist joint, affecting the accuracy of the movement of the surgical instrument. Aiming at this problem, a new gear train decoupling method is proposed in the paper, which can automatically compensate for the coupled motion in real-time. Based on the performance tests of the instrument prototype, a series of decoupling effects tests are carried out. The test results show that the surgical instrument has excellent decoupling ability and stable performance.
We explored the genetic architecture of metabolic risk factors of cardiovascular diseases (CVDs) and their clustering in Chinese boys and girls. Seven metabolic traits (body mass index [BMI], waist circumference [WC], systolic blood pressure [SBP], diastolic blood pressure [DBP], total cholesterol [TC], triglyceride [TG], and uric acid [UA]) were measured in a sample of 1016 twins between 8 and 17 years of age, recruited from the Qingdao Twin Registry. Cholesky, independent pathway, and common pathway models were used to identify the latent genetic structure behind the clustering of these metabolic traits. Genetic architecture of these metabolic traits was largely similar in boys and girls. The highest heritability was found for BMI (a2 = 0.63) in boys and TC (a2 = .69) in girls. Three heritable factors, adiposity (BMI and WC), blood pressure (SBP and DBP), and metabolite factors (TC, TG, and UA), which formed one higher-order latent phenotype, were identified. Latent genetic, common environmental, and unique environmental factors indirectly impacted the three factors through one single latent factor. Our results suggest that there is one latent factor influencing several metabolic traits, which are known risk factors of CVDs in young Chinese twins. Latent genetic, common environmental, and unique environmental factors indirectly imposed on them. These results inform strategies for gene pleiotropic discovery and intervening of CVD risk factors during childhood and adolescence.
We investigate the phased evolution and variation of the South Asian monsoon and resulting weathering intensity and physical erosion in the Himalaya–Karakoram Mountains since late Pliocene time (c. 3.4 Ma) using a comprehensive approach. Neodymium and strontium isotopic compositions and single-grain zircon U–Pb age spectra reveal the sources of the deposits in the east Arabian Sea, and show a combination of sources from the Himalaya and the Karakoram–Kohistan–Ladakh Mountains, with sediments from the Indian Peninsula such as the Deccan Traps or Craton. We interpret shifts in the sediment sources to have been forced by sea-level changes that correlate with South Asian monsoon rainfall variation since late Pliocene time. We collected 908 samples from the International Ocean Discovery Program Hole U1456A, which was drilled in the east Arabian Sea. Time series of hematite content and grain size of the sediments were examined downcore. We found South Asian monsoon precipitation and weathering intensity experienced three phases from late Pliocene time. Lower monsoon precipitation, with a lower variability and strong weathering intensity, occurred during 3.4–2.4 Ma; an increased and more variable South Asian monsoon rainfall, along with strengthened but fluctuating weathering intensity, occurred at 1.8–1.1 Ma; and a reduced rainfall with lower South Asian monsoon precipitation variability and moderate weathering intensity marked the period 1.1–0.1 Ma. Maximum entropy spectral analysis and wavelet transform show that there were orbital-dominated cycles of periods c. 100 and c. 41 ka in these proxy-based time series. We propose that the monsoon, sea level, global temperature and insolation together forced the weathering and erosion in SW Asia.
The Arsenic (+3 oxidation state) methyltransferase (AS3MT) gene has been identified as a top risk gene for schizophrenia in several large-scale genome-wide association studies. A variable number tandem repeat (VNTR) of this gene is the most significant expression quantitative trait locus, but its role in brain activity in vivo is still unknown.
Methods
We first performed a functional magnetic resonance imaging (fMRI) scan of 101 healthy subjects during a memory span task, trained all subjects on an adaptive memory span task for 1 month, and finally performed another fMRI scan after the training. After excluding subjects with excessive head movements for one or more scanning sessions, data from 93 subjects were included in the final analyses.
Results
The VNTR was significantly associated with both baseline brain activation and training-induced changes in multiple regions including the prefrontal cortex and the anterior and posterior cingulate cortex. Additionally, it was associated with baseline brain activation in the striatum and the parietal cortex. All these results were corrected based on the family-wise error rate method across the whole brain at the peak level.
Conclusions
This study sheds light on the role of AS3MT gene variants in neural plasticity related to memory span training.
Exosomes derived from hepatocellular carcinoma (HCC) cells are nanovesicles and are involved in the occurrence and development of HCC, they also serve as important carriers and drug targets of nanodrug delivery systems. The external shape and internal structure of exosomes are important indexes of identification, and isolated intact morphology is crucial to biological function integrity. However, given their susceptibility to various influencing factors, the external shape and internal structure of exosomes derived from HCC cells remain incompletely studied. In this study, exosomes purified from HCC cells were isolated at different centrifugation speeds and examined via multiple electron microscopy (EM) techniques. The results demonstrate that exosomes possess a nearly spherical shape and bilipid membranous vesicle with a concave cavity structure containing electron-dense and coated vesicles, suggesting the possible existence of subpopulations of exosomes with specific functions. The exosomes isolated at ultracentrifugation (UC) speed (≥110,000×g) presented irregular and diverse external morphologies, indicating the effect on the integrity of the exosomes. Transforming growth factor signaling bioactive substances (TGF-β1, S100A8, and S100A9) can be found in exosomes by performing Western blotting, showing that the internal content is associated with metastasis of HCC. These findings show that EMelectron microscopy and UC speed can affect exosome characteristics, including external shape, internal structure, and content of bioactive substances. The electron-dense and coated vesicles that had been discovered in exosomes might become new additional morphological features, which could help to improve the interpretation of experimental results and widen our understanding of exosome morphology.
Previous studies of amyloid diseases reported that the aggregating proteins share a similar conserved peptide sequence which can form the cross-β-sheet-containing nanostructures like nanofilaments. The template-assisted self-assembly (TASA) of peptides on inorganic substrates with different hydrophilicity could be an alternative approach to shed light on the fibrillization mechanism of proteins/peptides in vivo. To figure out the effect of interfaces on amyloid aggregation, we herein employed in situ atomic force microscopy (AFM) to investigate the self-assembling of a Parkinson disease-related core peptide sequence (TGV-9) on a hydrophobic liquid–solid interface via real-time observation of the dynamic fibrillization process. The results show that TGV-9 forms one-dimensional nanostructures on the surface of highly ordered pyrolytic graphite (HOPG) with three preferred growth orientations, which are consistent with the atomic lattice of HOPG, indicating an epitaxial growth or TASA. Conversely, the nanostructures formed in bulk solution can be free-standing nanofilaments, and the fibrillization mechanism is different from that on HOPG. These results could not only deepen the understanding of the protein/peptide aggregation mechanism but also benefit for the early diagnosis and clinic treatment of related diseases.
Combinational creativity is a significant element of design in supporting designers to generate creative ideas during the early phases of design. There exists three driven approaches to combinational creativity: problem-, similarity- and inspiration-driven. This study provides further insights into the three combinational creativity driven approaches, exploring which approach could lead to ideas that are more creative in the context of practical product design. The results from a case study reveal that the problem- driven approach could lead to more creative and novel ideas or products compared with the similarity- and inspiration-driven approach. Products originating from the similarity- and inspiration-driven approach are at comparable levels. This study provides better understanding of combinational creativity in practical design. It also delivers benefits to designers in improving creative idea generation, and supports design researchers in exploring future ideation methods and design support tools employing the concept of 'combination'.
This study proposes two multimodal frameworks to classify pathological voice samples by combining acoustic signals and medical records. In the first framework, acoustic signals are transformed into static supervectors via Gaussian mixture models; then, a deep neural network (DNN) combines the supervectors with the medical record and classifies the voice signals. In the second framework, both acoustic features and medical data are processed through first-stage DNNs individually; then, a second-stage DNN combines the outputs of the first-stage DNNs and performs classification. Voice samples were recorded in a specific voice clinic of a tertiary teaching hospital, including three common categories of vocal diseases, i.e. glottic neoplasm, phonotraumatic lesions, and vocal paralysis. Experimental results demonstrated that the proposed framework yields significant accuracy and unweighted average recall (UAR) improvements of 2.02–10.32% and 2.48–17.31%, respectively, compared with systems that use only acoustic signals or medical records. The proposed algorithm also provides higher accuracy and UAR than traditional feature-based and model-based combination methods.