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Marine fisheries are a critical component of the marine economy. Examining the changes in the economic resilience of marine fisheries allows for identifying potential development risks and supports informed decision-making to optimize growth patterns and mitigate risks. This study applied the CRITIC-based combined weights model to calculate China’s Marine Fisheries Economic Resilience (MFER). It investigated the temporal and spatial evolution of MFER and analyzed the influencing factors using the Geographical Detector and a Two-way fixed-effects model. Furthermore, the future development trends of MFER were predicted using the Markov chain. The results show that the overall MFER in China’s coastal provinces increased steadily from 2001 to 2020. Second, MFER exhibits a clear pattern, with low-value regions improving and high-value areas shifting toward medium- and low-value provinces. Fourth, the trajectory of the MFER center is moving from north to south, with high-value regions expanding in the same direction. Fourth, factors such as EDL, TEC, SPE, and SYS positively impact MFER, while OPE has a negative effect. Finally, the results of the Markov chain indicate that the current development state of MFER is relatively stable, with evidence of club convergence. However, the probability of maintaining the current development level is gradually decreasing. Based on these findings, provide suggestions for the preservation of marine economic security.

Rock mass may be exposed to high temperature and cooled by water in fire, geothermal resource exploitation and deep underground engineering, which affects the safety of these engineering. In this study, cracked straight through Brazilian disc (CSTBD) specimen was used to study the fracture properties of granite treated with different water-cooling time from 25 °C to 800 °C. A camera was used to record the fracture process of the specimen, the evolution of strain at the specimen surface was obtained by using digital image correlation technology, and the morphological characteristics of fracture surface were observed by using scanning electron microscopy. The results show that water-cooling time has some effects on fracture properties of granite, but its effect is less than the temperature. With the increase of water-cooling time, the mode I fracture toughness decreases first, then increases and finally decreases at the same temperature, and the fracture toughness ranges from 0.419 MPa m1/2 to 0.567 MPa m1/2 at 400 °C. The crack tip opening displacement (CTOD), crack propagation path and fracture surface are related to the energy released during the specimen failure. When the temperature is 25 °C or 200 °C, the energy released is large and the fracture surface is relatively flat with irregular sharp edges, the main cracks are straight lines. At 600 °C, the main crack is zigzag, the CTOD and the maximum principal strain in order can reach 0.143 mm and 0.731 %. This study can help to understand the effect of water-cooling time on engineering rock mass.

Background Direct evidence for the relationship between a large prostate (≥80 ml) and androgen receptor/PSA signal remains lacking in benign prostatic hyperplasia (BPH). Our aim is to identify whether the cause of a large prostate is related to progesterone receptor (PGR) androgen receptor (AR), oestrogen receptor α, β (ERα,β) and prostate-specific antigen (PSA).Materials and methods Surgical specimens of BPH in plasmakinetic resection of the prostate (PKRP) with three groups of different prostate-sizes with mean volumes of 25.97 ml, 63.80 ml, and 122.37 ml were collected for immunohistochemical analysis of the tissue microarray with PGR, AR, PSA and ERs. Rats were castrated and treated with testosterone replacement to explore androgen and PGR, AR and ERs expression levels in the prostate. Quantitative real-time reverse transcription polymerase chain reaction (Rt-PCR) for mRNA detection of above genes was conducted.Results Immunoblotting, Rt-PCR and immunohistochemistry assays showed that PGR, PSA, AR, ERα expression levels were positively correlated with prostate size and that ERβ expression levels were negatively correlated with prostate volume. Animal experiments have shown that prostate volume is decreased in castrated rats with decreased PGR, AR, ERα and increased ERβ expression levels.Conclusion PGR, AR, ERs signals can be regarded as important factors for large-sized prostates in BPH patients (≥100 ml).

Abstract Objective The aim of this study was to establish a preoperative model to predict the outcome of primary debulking surgery (PDS) for advanced ovarian cancer (AOC) patients by combing Suidan predictive model with HE4, CA125, CA153 and ROMA index. Methods 76 AOC Patients in revised 2014 International Federation of Gynecology and Obstetrics (FIGO) stage III-IV who underwent PDS between 2017 and 2019 from Yunnan Cancer Hospital were included. Clinical data including the levels of preoperative serum HE4, CA125, CA153 and mid-lower abdominal CT-enhanced scan results were collected. The logistics regression analysis was performed to find factors associated with sub-optimal debulking surgery (SDS). The receiver operating characteristic curve was used to evaluate the predictive performances of selected variables in the outcome of primary debulking surgery. The predictive index value (PIV) model was constructed to predict the outcome of SDS. Results Optimal surgical cytoreduction was achieved in 61.84% (47/76) patients. The value for CA125, HE4, CA153, ROMA index and Suidan score was lower in optimal debulking surgery (ODS) group than SDS group. Based on the Youden index, which is widely used for evaluating the performance of predictive models, the best cutoff point for the preoperative serum HE4, CA125, CA153, ROMA index and Suidan score to distinguish SDS were 431.55 pmol/l, 2277 KU/L, 57.19 KU/L, 97.525% and 2.5, respectively. Patients with PIV≥5 may not be able to achieve optimal surgical cytoreduction. The diagnostic accuracy, NPV, PPV and specificity for diagnosing SDS were 73.7%, 82.9%, 62.9% and 72.3%, respectively. In the constructed model, the AUC of the SDS prediction was 0.770 (95% confidence interval: 0.654-0.887), P

The Tibetan medicinal fruit E’seguo originates from two species, Malus toringoides (Rehd.) Hughes and Malus transitoria (Batal.) Schneid, both unique to the Hengduan Mountains. These species are predominantly found in high-altitude regions of Ganzi Prefecture, Sichuan Province, particularly in the Xianshui River and Yalong River basins. Malus toringoides (Rehd.) Hughes is far more abundant in both resource quantity and distribution compared to Malus transitoria (Batal.) Schneid. However, the nutritional and medicinal differences between the two remain unclear, which significantly impacts the development and utilization of E’seguo resources. This study aimed to measure the mineral content, nutritional components, and medicinal properties of E’seguo from 12 different regions of Ganzi Prefecture to explore the quality differences between these two species and across different regions. ICP-MS (Inductively Coupled Plasma Mass Spectrometry) was used to determine the mineral content, ultraviolet-visible spectrophotometry and potentiometric titration to analyze nutritional indicators, and HPLC (High-Performance Liquid Chromatography) to measure the medicinal components L-malic acid and 2-O-β-D-glucopyranosyl-L-ascorbic acid (AA-2βG). Results indicate that Malus transitoria (Batal.) Schneid contains higher levels of K, Ca, Zn, Mg, and Cu compared to Malus toringoides (Rehd.) Hughes, which has higher Fe and Mn content. Malus toringoides (Rehd.) Hughes from the Kangding and Litang regions showed the highest mineral content, with mineral elements primarily influencing polysaccharide levels, according to Mantel analysis. Nutritional and medicinal analyses revealed that Malus toringoides (Rehd.) Hughes outperformed Malus transitoria (Batal.) Schneid in all metrics except for the sugar-acid ratio. Given the mineral content and taste, Malus transitoria (Batal.) Schneid is better suited for consumption, while Malus toringoides (Rehd.) Hughes has superior medicinal properties, making it more appropriate for medicinal use. In the Malus transitoria (Batal.) Schneid regions, both Luhuo and Daofu are in the Xianshui River basin, with Daofu County producing the higher quality fruit. Among the nine Malus toringoides (Rehd.) Hughes regions, the M10 (Tuoba Township, Ganzi County) near the Yalong River had the highest overall score, followed by M7 (Yade Township, Luhuo County) and M6 (Keke, Xiala Tuo Town, Luhuo County), both of which are near the Xianshui River. In summary, Malus transitoria (Batal.) Schneid generally has higher mineral content, but Malus toringoides (Rehd.) Hughes has larger fruit and higher medicinal value, making the latter more suitable as a medicinal resource. At the same time, the medicinal quality of Xianshui River fruit was higher in the two watersheds of Malus toringoides (Rehd.) Hughes.

Abstract Spin waves, collective dynamic magnetic excitations, offer crucial insights into magnetic material properties. Rare‐earth iron garnets offer an ideal spin‐wave (SW) platform with long propagation length, short wavelength, gigahertz frequency, and applicability to magnon spintronic platforms. Of particular interest, thulium iron garnet (TmIG) has attracted huge interest recently due to its successful growth down to a few nanometers, observed topological Hall effect, and spin‐orbit torque‐induced switching effects. However, there is no direct spatial measurement of its SW properties. This work uses diamond nitrogen‐vacancy (NV) magnetometry in combination with SW electrical transmission spectroscopy to study SW transport properties in TmIG thin films. NV magnetometry allows probing spin waves at the sub‐micrometer scale, seen by the amplification of the local microwave magnetic field due to the coupling of NV spin qubits with the stray magnetic field produced by the microwave‐excited spin waves. By monitoring the NV spin resonances, the SW properties in TmIG thin films are measured as a function of the applied magnetic field, including their amplitude, decay length (≈50 µm), and wavelength (0.8–2 µm). These results pave the way for studying spin qubit‐magnon interactions in rare‐earth magnetic insulators, relevant to quantum magnonics applications.

Abstract Mott insulator VO2 exhibits an ultrafast and reversible semiconductor‐to‐metal transition (SMT) near 340 K (67 °C). In order to fulfill the multifunctional device applications, effective transition temperature (Tc) tuning as well as integrated functionality in VO2 is desired. In this study, multifunctionalities including tailorable SMT characteristics, ferromagnetic (FM) integration, and magneto‐optical (MO) coupling, have been demonstrated via metal/VO2 nanocomposite designs with controlled morphology, i.e., a two‐phase Ni/VO2 pillar‐in‐matrix geometry and a three‐phase Au/Ni/VO2 particle‐in‐matrix geometry. Evident Tc reduction of 20.4 to 54.9 K has been achieved by morphology engineering. Interestingly, the Au/Ni/VO2 film achieves a record‐low Tc of 295.2 K (22.2 °C), slightly below room temperature (25 °C). The change in film morphology is also correlated with unique property tuning. Highly anisotropic magnetic and optical properties have been demonstrated in Ni/VO2 film, whereas Au/Ni/VO2 film exhibits isotropic properties because of the uniform distribution of Au/Ni nanoparticles. Furthermore, a strong MO coupling with enhanced magnetic coercivity and anisotropy is demonstrated for both films, indicating great potential for optically active property tuning. This demonstration opens exciting opportunities for the VO2‐based device implementation towards smart windows, next‐generation optical‐coupled switches, and spintronic devices.

Habitat fragmentation affects the survival of wildlife and is a main threat to biodiversity. Corridors are frequently used to alleviate habitat fragmentation. However, corridors are costly and often ineffective in practice. Endangered species in montane regions are particularly affected by habitat fragmentation and therefore require economic and efficient conservation strategies. We propose a stepping stone strategy (SSS) to deal with habitat fragmentation threatening an endangered primate, the black-and-white snub-nosed monkeys (Rhinopithecus bieti). We selected the southern range of R. bieti as the study area, which covers 3,580 km2. We evaluated the habitat status and formulated an SSS based on the dispersal ability of an adult male R. bieti. Six sustainable habitat patches and 340 natural stepping stones were detected. Thirteen artificial stepping stones are needed to establish weak connectivity of habitats. Forty-four stepping stones are proposed as key stepping stones for attaining strong connectivity. The SSS is projected to incur substantially less pecuniary investment than the corridor strategy (0.06 million versus 5.65 million, USD). We conclude that 5 steps are needed for the SSS: (a) assessing the status of habitats to plan restorative intervention activities, (b) designing artificial stepping stones to weakly link sustainable habitats, (c) proposing corridors to allow for a stable connection between sustainable habitats, (d) identifying key stepping stones to establish small protected area, and (e) recovery of fragmented habitat and reinstatement of sustainable habitat. Our study suggests that SSS is a cost-effective and practical way for maintaining connectivity and supporting habitat recovery for endangered wildlife in montane regions.

As a mixed-methods research in economics and psychology, this study aimed to analyze the influence from the intergenerational succession on the financialization level including asset financialization and revenue financialization, and further test the moderating effect of the heirs’ typical growing experience according to The Imprinting Theory, based on the 2009–2020 annual data of listed family enterprises of China. There were two key findings. First, the effect of Chinese family enterprises’ intergenerational succession on asset financialization was positively significant while the effect on revenue financialization was not significant, indicating that the financialization behavior has not brought about effective financial profits. Second, among the heirs’ typical growing experiences, their parents’ entrepreneurial experience during their childhood, oversea study experience, and MBA education experience had the significantly positive moderating effects on the influence from intergeneration succession to asset financialization level of Chinese family enterprises, which was an important internal mechanism for the heirs to promote the financialization process of family enterprises.

Abstract Background In the last decade, Genome-wide Association studies (GWASs) have contributed to decoding the human genome by uncovering many genetic variations associated with various diseases. Many follow-up investigations involve joint analysis of multiple independently generated GWAS data sets. While most of the computational approaches developed for joint analysis are based on summary statistics, the joint analysis based on individual-level data with consideration of confounding factors remains to be a challenge. Results In this study, we propose a method, called Coupled Mixed Model (CMM), that enables a joint GWAS analysis on two independently collected sets of GWAS data with different phenotypes. The CMM method does not require the data sets to have the same phenotypes as it aims to infer the unknown phenotypes using a set of multivariate sparse mixed models. Moreover, CMM addresses the confounding variables due to population stratification, family structures, and cryptic relatedness, as well as those arising during data collection such as batch effects that frequently appear in joint genetic studies. We evaluate the performance of CMM using simulation experiments. In real data analysis, we illustrate the utility of CMM by an application to evaluating common genetic associations for Alzheimer’s disease and substance use disorder using datasets independently collected for the two complex human disorders. Comparison of the results with those from previous experiments and analyses supports the utility of our method and provides new insights into the diseases. The software is available at https://github.com/HaohanWang/CMM .

Abstract Background The current understanding of the genetic basis of complex human diseases is that they are caused and affected by many common and rare genetic variants. A considerable number of the disease-associated variants have been identified by Genome Wide Association Studies, however, they can explain only a small proportion of heritability. One of the possible reasons for the missing heritability is that many undiscovered disease-causing variants are weakly associated with the disease. This can pose serious challenges to many statistical methods, which seems to be only capable of identifying disease-associated variants with relatively stronger coefficients. Results In order to help identify weaker variants, we propose a novel statistical method, Constrained Sparse multi-locus Linear Mixed Model (CS-LMM) that aims to uncover genetic variants of weaker associations by incorporating known associations as a prior knowledge in the model. Moreover, CS-LMM accounts for polygenic effects as well as corrects for complex relatednesses. Our simulation experiments show that CS-LMM outperforms other competing existing methods in various settings when the combinations of MAFs and coefficients reflect different scenarios in complex human diseases. Conclusions We also apply our method to the GWAS data of alcoholism and Alzheimer’s disease and exploratively discover several SNPs. Many of these discoveries are supported through literature survey. Furthermore, our association results strengthen the belief in genetic links between alcoholism and Alzheimer’s disease.

Abstract Background Genome-wide Association Studies (GWAS) have contributed to unraveling associations between genetic variants in the human genome and complex traits for more than a decade. While many works have been invented as follow-ups to detect interactions between SNPs, epistasis are still yet to be modeled and discovered more thoroughly. Results In this paper, following the previous study of detecting marginal epistasis signals, and motivated by the universal approximation power of deep learning, we propose a neural network method that can potentially model arbitrary interactions between SNPs in genetic association studies as an extension to the mixed models in correcting confounding factors. Our method, namely Deep Mixed Model, consists of two components: 1) a confounding factor correction component, which is a large-kernel convolution neural network that focuses on calibrating the residual phenotypes by removing factors such as population stratification, and 2) a fixed-effect estimation component, which mainly consists of an Long-short Term Memory (LSTM) model that estimates the association effect size of SNPs with the residual phenotype. Conclusions After validating the performance of our method using simulation experiments, we further apply it to Alzheimer’s disease data sets. Our results help gain some explorative understandings of the genetic architecture of Alzheimer’s disease.

Abstract Rational design of efficient bifunctional electrocatalysts is highly imperative but still a challenge for overall water splitting. Herein, we construct novel freestanding Mo-doped NiCoP nanosheet arrays by the hydrothermal and phosphation processes, serving as bifunctional electrocatalysts for overall water splitting. Notably, Mo doping could effectively modulate the electronic structure of NiCoP, leading to the increased electroactive site and improved intrinsic activity of each site. Furthermore, an electrochemical activation strategy is proposed to form Mo-doped (Ni,Co)OOH to fully boost the electrocatalytic activities for oxygen evolution reaction. Benefiting from the unique freestanding structure and Mo doping, Mo-doped NiCoP and (Ni,Co)OOH show the remarkable electrochemical performances, which are competitive among current researches. In addition, an overall water splitting device assembled by both electrodes only requires a cell voltage of 1.61 V to reach a current density of 10 mA cm−2. Therefore, this work opens up new avenues for designing nonprecious bifunctional electrocatalysts by Mo doping and in situ electrochemical activation.

We demonstrate the highly sensitive and fast response/recovery gas sensors for detecting isopropanol (IPA), in which the Au-nanoparticles-modified ZnO (Au@ZnO) nanofilms act as the active layers. The data confirm that both the response and the response/recovery speed for the detection of IPA are significantly improved by adding Au nanoparticles on the surface of ZnO nanofilms. The gas sensor with an Optimum Au@ZnO nanofilm exhibits the highest responses of 160 and 7 to the 100 and 1 ppm IPA at 300 °C, which indicates high sensitivity and a very low detecting limit. The sensor also exhibits a very short response/recovery time of 4/15 s on the optimized Au@ZnO nanofilm, which is much shorter than that of the sensor with a pure ZnO nanofilm. The mechanisms of the performance improvement in the sensors are discussed in detail. Both the electronic sensitization and the chemical sensitization of the ZnO nanofilms are improved by the modified Au nanoparticles, which not only regulate the thickness of the depletion layer but also increase the amount of adsorbed oxygen species on the surfaces. This work proposes a strategy to develop a highly sensitive gas sensor for real-time monitoring of IPA.

Pollination success is essential for hybrid oilseed rape (OSR, Brassica napus) seed production, and the pollination method has some influences on the OSR plant growth traits. In order to explore the roles of different pollination methods, four pollination methods of “unmanned agricultural aerial system” (UAAS), “natural wind + UAAS” (NW+UAAS), “honeybee” (HB), and “no pollinators” (NP) were set in a hybrid OSR field to investigate their effects on OSR plant traits and rapeseed yields in this study. The control check (CK) area with natural wind (NW) pollination was set as a reference for comparison. The experiments were conducted continuously for 20 days during the OSR plant early to full-bloom stage. The results based on the evaluated OSR plants showed that the growth traits and the rapeseed yields exhibited some differences under different pollination methods. The average plant height under NP pollination was maximum, which was 231.52 cm, while the average plant heights under the other pollination methods exhibited nearly no difference. Except for the HB pollination, the average first-branch heights of the evaluated plants all exceeded 100 cm under the other pollination methods. The average once branch quantity of all the evaluated plants under different pollination methods was 5–7. The average number of effective siliques per plant varied greatly. The average quantity of effective siliques in each OSR plant was about 160 under UAAS, NW+UAAS, and NW pollination, about 100 under HB pollination, and only 2.12 under NP pollination. The thousand-rapeseed weight was 7.32 g under HB pollination, which was the highest of all of the pollination areas. In terms of rapeseed yield, the average rapeseed yields per plant were all more than 10 g, except for the one under NP pollination; the yield per hectare was highest under NW+UAAS pollination, reaching 4741.28 kg, and the yield under NP pollination was lowest, which was only 360.39 kg. The research results provide technical support for supplementary pollination in hybrid OSR seed production.

Transition metal nitrides such as titanium nitride (TiN) possess exceptional mechanical-, chemical-, and thermal-stability and have been utilized in a wide variety of applications ranging from super-hard, corrosion-resistive, and decorative coatings to nanoscale diffusion barriers in semiconductor devices. Despite the ongoing interest in these robust materials, there have been limited reports focused on engineering high-aspect ratio TiN-based nanocomposites with anisotropic magnetic and optical properties. To this end, we explored TiN–Fe thin films with self-assembled vertical structures integrated on Si substrates. We showed that the key physical properties of the individual components (e.g., ferromagnetism from Fe) are preserved, that vertical nanostructures promote anisotropic behavior, and interactions between TiN and Fe enable a special magneto-optical response. This TiN–Fe nanocomposite system presents a new group of complex multifunctional hybrid materials that can be integrated on Si for future Si-based memory, optical, and biocompatible devices.

In eukaryotes, polyadenylation (poly(A)) is an essential process during mRNA maturation. Identifying the cis-determinants of poly(A) signal (PAS) on the DNA sequence is the key to understand the mechanism of translation regulation and mRNA metabolism. Although machine learning methods were widely used in computationally identifying PAS, the need for tremendous amounts of annotation data hinder applications of existing methods in species without experimental data on PAS. Therefore, cross-species PAS identification, which enables the possibility to predict PAS from untrained species, naturally becomes a promising direction. In our works, we propose a novel deep learning method named Poly(A)-DG for cross-species PAS identification. Poly(A)-DG consists of a Convolution Neural Network-Multilayer Perceptron (CNN-MLP) network and a domain generalization technique. It learns PAS patterns from the training species and identifies PAS in target species without re-training. To test our method, we use four species and build cross-species training sets with two of them and evaluate the performance of the remaining ones. Moreover, we test our method against insufficient data and imbalanced data issues and demonstrate that Poly(A)-DG not only outperforms state-of-the-art methods but also maintains relatively high accuracy when it comes to a smaller or imbalanced training set.

Abstract Designing and constructing bifunctional electrocatalysts is vital for water splitting. Particularly, the rational interface engineering can effectively modify the active sites and promote the electronic transfer, leading to the improved splitting efficiency. Herein, free‐standing and defect‐rich heterogeneous MoS2/NiS2 nanosheets for overall water splitting are designed. The abundant heterogeneous interfaces in MoS2/NiS2 can not only provide rich electroactive sites but also facilitate the electron transfer, which further cooperate synergistically toward electrocatalytic reactions. Consequently, the optimal MoS2/NiS2 nanosheets show the enhanced electrocatalytic performances as bifunctional electrocatalysts for overall water splitting. This study may open up a new route for rationally constructing heterogeneous interfaces to maximize their electrochemical performances, which may help to accelerate the development of nonprecious electrocatalysts for overall water splitting.

Abstract As a critical transcription factor, Six1 plays an important role in the regulation of myogenesis and muscle development. However, little is known about its regulatory mechanism associated with muscular protein synthesis. The objective of this study was to investigate the effects of overexpression ofSix1 on the expression of key protein metabolism-related genes in duck myoblasts. Through an experimental model where duck myoblasts were transfected with a pEGFP-duSix1 construct, we found that overexpression of duckSix1 could enhance cell proliferation activity and increase mRNA expression levels of key genes involved in the PI3K/Akt/mTOR signaling pathway, while the expression of FOXO1, MuRF1and MAFbx was not significantly altered, indicating thatSix1 could promote protein synthesis in myoblasts through up-regulating the expression of several related genes. Additionally, in duck myoblasts treated with LY294002 and rapamycin, the specific inhibitors ofPI3K and mTOR, respectively, the overexpression of Six1 could significantly ameliorate inhibitive effects of these inhibitors on protein synthesis. Especially, the mRNA expression levels of mTOR and S6K1 were observed to undergo a visible change, and a significant increase in protein expression of S6K1 was seen. These data suggested that Six1plays an important role in protein synthesis, which may be mainly due to activation of the mTOR signaling pathway.

Background: Follistatin (FST), a secreted glycoprotein, is intrinsically linked to muscle hypertrophy. To explore the function of duck FST in myoblast proliferation and differentiation, the pEGFP-FST eukaryotic expression vector was constructed and identified. The biological activities of this vector were analyzed by transfecting pEGFP-FST into cultured duck myoblasts using Lipofectamine™ 2000 and subsequently determining the mRNA expression profiles of FST and myostatin (MSTN). Results: The duck pEGFP-FST vector was successfully constructed and was confirmed to have high liposome-mediated transfection efficiency in duck myoblasts. Additionally, myoblasts transfected with pEGFP-FST had a higher biological activity. Significantly, the overexpression of FST in these cells significantly inhibited the mRNA expression of MSTN (a target gene that is negatively regulated by FST). Conclusions: The duck pEGFP-FST vector has been constructed successfully and exhibits biological activity by promoting myoblast proliferation and differentiation in vitro.