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Mental illness usually involves a range of cognitive, behavioral, and affective symptoms associated with impaired occupational or social functioning. Duration of untreated psychosis (DUP) is considered as an important predictor and independent risk factor for the prognosis of patients with mental disorders, a longer DUP is associated with poor prognosis. Meanwhile, early intervention measures to shorten DUP have gradually attracted increasing attention from both domestic and international researchers. In this paper, the related studies on DUP were reviewed and analyzed, the concept, measurement tools, neurobiological mechanisms of DUP, the relationship between DUP and prognosis, and early intervention measures to shorten DUP were described, in order to provide ideas and reference for developing clinical intervention strategies for DUP.

Background The accuracy of data collection can be affected by bias in the understanding of the items between the developer and the target population during scale development. Objective To adjust the items of the Schizophrenia Help-seeking Motivation Scale using the cognitive interview. Methods A purposive sampling method was used to select 30 schizophrenia patients from a psychiatric hospital in Daqing City from December 2021 to January 2022 to attend three rounds of cognitive interviews. The interview data were collected, and coded using the Question Appraisal System (QAS-99) , and after the coding results were collated, the scale entries were adjusted by integrating respondent feedback and expert panel comments. Results During the 1st round of interview, interviewees raised doubts on 11 entries, among which three were due to wording, seven were due to vague expressions, two were due to lack of inadequate knowledge, and one was due to the difficulty in recalling. And some of the entries were revised after discussion. The results of the 2nd round of interview showed that one entry was assumed to be inappropriate and was revised after discussion. The 3rd round of interview continued until the interviewees were able to understand the entries correctly, and they thought that there was no need to further revise the entries. Conclusion The cognitive interview effectively solved the problem of understanding differences between the developer and schizophrenia patients in the development of the Schizophrenia Help-seeking Motivation Scale, thus improving the accuracy and applicability of the scale.

A number of previous studies have identified cognitive deficits in developmental dyscalculia (DD). Yet, most of these studies were in alphabetic languages, whereas few of them examined Chinese DD. Here, we conducted a study aiming to determine the cognitive factors associated with DD in Chinese children. Five candidate cognitive factors of DD--phonological retrieval, phonological awareness, visual-spatial attention, spatial thinking, and pattern understanding--were examined in the present study. A total of 904 Chinese children ages 8 to 11 years participated in this study. From the sample, 97 children were identified with DD through tests of arithmetic ability, and 93 age- and IQ-matched typically developing children were selected as controls. Logistic regression analysis revealed that phonological retrieval, pattern understanding, visual-spatial attention, and phonological awareness significantly predicted DD, whereas spatial thinking failed to do so. Results of logistic relative weights analysis showed that all five factors explained statistically significant amounts of variance in arithmetic scores. Phonological retrieval had the most influence on DD, followed by pattern understanding, visual--spatial attention, phonological awareness, and spatial thinking. These findings have important clinical implications for diagnosis and intervention of Chinese DD.

In order to rationalize the consumption of graphite tailing sand and reduce its pollution of the environment—with sodium silicate being a commonly used activator for improving the strength of concrete composites—in this study, the joint effects of sodium silicate (SS) and graphite tail sand (GT) on the strength and frost resistance of graphite tail sand high-performance mortar (GT-HPM) were investigated. Experiments were conducted to evaluate the bulk density, water absorption, compressive strength, speed of sound, and working performance status of GT-HPM before and after freezing and thawing at different SS dosages and different GT substitution rates. The microstructural properties of GT-HPM were also analyzed by X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), and scanning electron microscopy (SEM/EDS). The results showed that 4% SS doping improved the performance of GT-HPM more obviously. Moreover, with an increase in the GT substitution rate, the mechanical properties and frost resistance of GT-HPM increased firstly and then decreased, and the best performance of GT-HPM was obtained when the GT substitution rate was 20%. At 6% SS doping, the performance of GT-HPM gradually decreased with the increase in the graphite tailing sand substitution rate. FT-IR testing showed that there was no significant change with the type of hydration products used, and the Si–O–T absorption peak and average bond length of GT-4 were the largest. SS and GT promoted the generation of hydration products. Microstructural analysis showed that 4% SS promoted the hydration reaction; in addition, an appropriate amount of GT improved the pore structure of HPM, increased the strength and frost resistance, and provided fundamental insights for the subsequent comprehensive utilization of graphite tailing sand. [ABSTRACT FROM AUTHOR]

The logistics demands of industries represented by e-commerce have experienced explosive growth in recent years. Vehicle path-planning plays a crucial role in optimization systems for logistics and distribution. A path-planning scheme suitable for an actual scenario is the key to reducing costs and improving service efficiency in logistics industries. In complex application scenarios, however, it is difficult for conventional heuristic algorithms to ensure the quality of solutions for vehicle routing problems. This study proposes a joint approach based on the genetic algorithm and graph convolutional network for solving the capacitated vehicle routing problem with multiple distribution centers. First, we use the heuristic method to modularize the complex environment and encode each module based on the constraint conditions. Next, the graph convolutional network is adopted for feature embedding for the graph representation of the vehicle routing problem, and multiple decoders are used to increase the diversity of the solution space. Meanwhile, the REINFORCE algorithm with a baseline is employed to train the model, ensuring quick returns of high-quality solutions. Moreover, the fitness function is calculated based on the solution to each module, and the genetic algorithm is employed to seek the optimal solution on a global scale. Finally, the effectiveness of the proposed framework is validated through experiments at different scales and comparisons with other algorithms. The experimental results show that, compared to the single decoder GCN-based solving method, the method proposed in this paper improves the solving success rate to 100% across 15 generated instances. The average path length obtained is only 11% of the optimal solution produced by the GCN-based multi-decoder method. [ABSTRACT FROM AUTHOR]

BACKGROUND: The pea leafminer, Liriomyza huidobrensis, is one of the most important insect pests on vegetables and ornamentals. The survival and egg‐laying behavior of leafminers are markedly affected by the environment temperature. However, the mechanisms underlying the relationship between egg‐laying and temperature are still largely unknown. RESULTS: Here, we find that leafminers have evolved an adaptive strategy to overcome the stress from high or low temperature by regulating oviposition‐punching plasticity. We further show that this oviposition‐punching plasticity is mediated by the expression of pyx in the ovipositor when subjected to disadvantageous temperature. Specifically, down‐regulation of pyx expression in leafminers under low temperature stress led to a significant decrease in the swing numbers of ovipositor and puncture area of the egg spot, and consequently the lower amount of egg‐laying compared to leafminers at ambient temperature. Conversely, activation of pyx expression under high temperature stress increased the swing numbers and puncture area, still resulting in a reduction of egg‐laying amount. CONCLUSION: Thereby, leafminers are able to coordinate pyx channel expression level and accordingly depress the oviposition. Our study uncovers a molecular mechanism underlying the adaptive strategy in insects that can avoid disadvantageous temperature for reproducing offspring. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

The load-bearing capacity of a building is influenced by the strength of the concrete. However, when faced with complex environments, ordinary concrete is not always adequate. The strength of concrete can be enhanced by incorporating additives into it. At this point, the study of adding basalt fiber (BF) and nano-SiO2 (NS) to concrete is pretty advanced. Still, research on the incorporation of nano-TiC (NT) into concrete is limited. In order to study the effect of NT, BF, and NS on the strength of concrete, in this paper, these materials were incorporated into concrete and NSF concrete was made by semi-dry mixing. And the concrete was analyzed for slump, compressive strength, splitting tensile strength, flexural strength, and modulus of elasticity. The optimization of the mechanical characteristics of concrete was conducted using response surface methodology (RSM), and the microstructure of concrete was used for analysis by scanning electron microscopy (SEM). To develop a thirst function optimization model based on NSF concrete, parallel experiments were used to verify the accuracy of the optimization results. The research findings show that NS, NT, and BF reduced the slump of concrete. Adding NT, NS, and BF in moderate amounts can enhance the mechanical characteristics of the concrete. The material's optimal proportions for mixing were 0.85% for NT, 0.11% for BF, and 1.94% for NS. The optimized concrete has a maximum error of 9.03% in compressive strength, 9.30% in split tensile strength, and 9.82% in flexural strength. [ABSTRACT FROM AUTHOR]

While genetic and environmental factors have been shown as predictors of children's reading ability, the interaction effects of identified genetic risk susceptibility and the specified environment for reading ability have rarely been investigated. The current study assessed potential gene–environment (G×E) interactions on reading ability in 1477 school-aged children. The gene–environment interactions on character recognition were investigated by an exploratory analysis between the risk single-nucleotide polymorphisms (SNPs), which were discovered by previous genome-wide association studies of developmental dyslexia (DD), and parental education (PE). The re-parameterized regression analysis suggested that this G×E interaction conformed to the strong differential susceptibility model. The results showed that rs281238 exhibits a significant interaction with PE on character recognition. Children with the "T" genotype profited from high PE, whereas they performed worse in low PE environments, but "CC" genotype children were not malleable in different PE environments. This study provided initial evidence for how the significant SNPs in developmental dyslexia GWA studies affect children's reading performance by interacting with the environmental factor of parental education. [ABSTRACT FROM AUTHOR]

The size tunable color of colloidal semiconductor quantum dots (QDs) is probably the most elegant illustration of the quantum confinement effect. As explained by the simple "particle‐in‐a‐box" model, the transition energies between the levels increase when the "box" becomes smaller. To investigate quantum confinement effects, typically a well‐defined narrow size distribution of the nanoparticles is needed. In this contribution, how coherent electronic two‐dimensional spectroscopy (2DES) can directly visualize the quantum size effect in a sample with broad size distribution of QDs is demonstrated. The method is based on two features of the 2DES – the ability to resolve inhomogeneous broadening and the capability to reveal correlations between the states. In QD samples, inhomogeneous spectral broadening is mainly caused by the size distribution and leads to elongated diagonal peaks of the spectra. Since the cross peaks correlate the energies of two states, they allow drawing conclusions about the size dependence of the corresponding states. It is also found that the biexciton binding energy changes between 3 and 8 meV with the QD size. Remarkably, the size dependence is non‐monotonic with a clear minimum. [ABSTRACT FROM AUTHOR]