DNA barcoding approaches have been successfully applied for estimating diet composition. However, an accurate quantification in the diets of herbivores remains to be achieved. In the current study, we present a novel methodology that reveals the relationship between the actual proportions (by mass) of each herbage species in the diets and the relative proportions of the ITS2 gene sequences obtained from faecal samples to evaluate the diet composition of sheep in a meadow steppe. Nine common and twelve rare species of plants were employed for formulating six diets, along with the addition of feed supplements for improving the growth performance of sheep. Faecal samples were collected for DNA analysis over the period spanning days 7–12. A significant positive correlation (Spearman’s ρ = 0.389) was obtained between the actual proportions (by mass) of the herbage in the diet provided and the relative abundance of ITS2 sequences obtained from the faecal samples. A significant regression coefficient was found between the relative abundance of all common species and their respective herbage mass proportions. The accuracy of the relation equations, evaluated by utilizing the similarity coefficient, showed 84.69% similarity between the actual diet composition and the correct percentage. Taken together, the current study has provided empirical evidence for the accuracy and applicability of ITS2 as a DNA barcode for obtaining quantitative information about the diet composition of sheep grazing in species-rich grasslands.

Immunological castration can be an alternative to traditional surgical castration. The active immunization against GnRH or kisspeptin has a castrating effect. To date, the fusion protein vaccine of combination with GnRH and kisspeptin have not been studied. Thus, the present study will develop a GnRH6-kisspeptin vaccine by genetic engineering method and investigate its immunocastration effect in male rats. Twenty 20-day-old male rats were randomly divided into two groups: the control group (n=10) and the immunization group (n=10). The initial immunization took place at week 0 followed by three booster doses administered intervals. The control group received an equivalent dose of white oil adjuvant. Orbital blood samples were collected at various time points following the initial immunization, at 0, 2, 4, 6, 8, 10 and 12 weeks, respectively. The entire left testis was weighed and its volume measured at week 12. Samples from the right testis were obtained for histological analysis. Serum levels of GnRH and kisspeptin antibodies, as well as testosterone levels were determined using ELISA. The results showed that the serum levels of GnRH and kisspeptin antibody titres of the immunized rats were significantly higher compared to the control group (P<0.05). Additionally, the testosterone concentration was effectively reduced following the intensified immunization. The testes of the immunized group exhibited a reduction in size and a significant decrease in the number of spermatogonia in the testicular tissue compared to the control group (P<0.05). These data indicate that the recombinant GnRH6-kisspeptin protein effectively induced immunological castration in rats.

We consider the system $\dot {x}=(A+ P(t,\epsilon )) x, x\in \mathbb {R}^{3}, $ where $A, P$ are both three-dimensional skew symmetric matrices, A is a constant matrix with eigenvalues $\pm i\unicode{x3bb} $ and 0, $P(t,\epsilon )$ is $C^{m}(m=0,1)$-smooth in $\epsilon $ and analytic quasi-periodic with respect to t with basic frequencies $\omega =(1,\alpha )$, with $\alpha $ being irrational, and $\epsilon $ is a small parameter. Under some non-resonant conditions about the basic frequencies and the eigenvalues of the constant matrix and without any non-degeneracy condition, it is proved that for many sufficiently small parameters, this system can be reduced to a rotation system. Furthermore, if the basic frequencies satisfy that $ 0\leq \beta (\alpha ) < r,$ where $\beta (\alpha )=\limsup \nolimits _{n\rightarrow \infty } {\ln q_{n+1}}/{q_{n}},$ $q_{n}$ is the sequence of denominations of the best rational approximations for $\alpha \in \mathbb {R} \setminus \mathbb {Q},$ r is the initial radius of analytic domain, it is proved that for many sufficiently small parameters, this system can be reduced to a constant system.

The Early-Middle Jurassic impression/compression macroflora and the palynoflora from the Qaidam Basin in the northeastern Qinghai-Xizang (Tibetan) Plateau have been well studied; however, fossil wood from this region has not been previously documented systematically. Here, we describe an anatomically well-preserved fossil wood specimen from the Lower Jurassic Huoshaoshan Formation at the Dameigou section in northern Qinghai Province, northwestern China. This fossil exhibits typical Metapodocarpoxylon Dupéron-Laudoueneix et Pons anatomy with usually araucarian radial tracheid pits and variable cross-field pits, representing a new record for Metapodocarpoxylon in the Qaidam Basin. This discovery indicates that trees with this type of wood anatomy were not confined to northern Gondwana but also grew in more northerly regions in Laurasia. The wood displays distinct growth rings, with abundant, well-formed earlywood and narrow latewood. This observation, along with previous interpretations based on macroflora, palynoflora and sedimentological data, suggests that a warm and humid climate with mild seasonality prevailed in the region during the Early Jurassic.

Since the implementation of the Basel III Accord, expected shortfall (ES) has gained increasing attention from regulators as a complement to value-at-risk (VaR). The problem of elicitability for ES makes jointly modeling VaR and ES a popular method to study ES. In this article, we develop model averaging for joint VaR and ES regression models that selects the two weight vectors by minimizing a jackknife criterion. We show the large sample properties of the estimators under potential model misspecification with increasing dimension of parameters and the asymptotic optimality of the selected weights in the sense of minimizing the out-of-sample excess final prediction error. Simulation studies and three empirical analyses reveal good finite sample performance.

In this paper, on–off switching digitization of a W-band variable gain power amplifier (VGPA) with above 60 dB dynamic range is introduced for large-scale phased array. Digitization techniques of on–off switching modified stacking transistors with partition are proposed to optimize configuration of control sub-cells. By the proposed techniques, gain control of a radio frequency variable gain amplifier (VGA) could be highly customized for both coarse and fine switching requirements instead of using additional digital-to-analog converters to tune the overall amplifier bias. The designed VGA in 130 nm SiGe has achieved switchable gain range from −46.4 to 20.6 dB and power range from −25.0 to 15.7 dBm at W band. The chip size of the fabricated VGPA is about 0.31 mm × 0.1 mm.

Model selection (MS) and model averaging (MA) are two popular approaches when many candidate models exist. Theoretically, the estimation risk of an oracle MA is not larger than that of an oracle MS because the former is more flexible, but a foundational issue is this: Does MA offer a substantial improvement over MS? Recently, seminal work by Peng and Yang (2022) has answered this question under nested models with linear orthonormal series expansion. In the current paper, we further respond to this question under linear nested regression models. A more general nested framework, heteroscedastic and autocorrelated random errors, and sparse coefficients are allowed in the current paper, giving a scenario that is more common in practice. A remarkable implication is that MS can be significantly improved by MA under certain conditions. In addition, we further compare MA techniques with different weight sets. Simulation studies illustrate the theoretical findings in a variety of settings.

The Northwest Tibet region is defined by several terranes, magmatic belts, basins and sutures, which were primarily shaped by the tectonic activities associated with Proto-, Palaeo- and Neo-Tethys Oceans. However, the basement nature and Precambrian tectonic evolution of the Northwest Tibet region, particularly within the Tashikuergan-Tianshuihai terrane, remain largely unknown. The Hongliutan area, located in the northeastern part of the Tashikuergan-Tianshuihai terrane, contains a critical sequence of Precambrian metamorphic rock strata. Detailed petrological, geochronological, and geochemical analyses of these metamorphic rocks – including plagioclase schist, quartz schist, amphibolite and nearby leucogranite – reveal the intricate processes of tectonic evolution within the Tianshuihai unit. Combining these findings with previous geochronological results is crucial for re-evaluating the nature of the Tashikuergan-Tianshuihai basement and its Precambrian tectonic evolution of the Tashikuergan-Tianshuihai basement. Our results reveal the following: (1) the leucogranite and amphibolite, identified as Cambrian igneous rocks, display distinct geochemical signatures indicative of a continental arc origin. These include calc-alkaline characteristics, enrichment in Th, U, Pb, Zr and Hf and depletion in Ba, Nb, Sr and Ti. Their εNd(t) values, close to zero, further support this tectonic setting, with the leucogranite and amphibolite formed at 506 and 522 Ma, respectively. (2) The plagioclase schist and quartz schist are interpreted to be Neoproterozoic volcaniclastic rocks that formed in a rifted (passive) continental margin setting. The quartz schist is particularly rich in detrital zircons, displaying a broad spectrum of 207Pb/206Pb ages, ranging from 901 to 3364 Ma. (3) A significant subset of detrital zircons within the quartz schist exhibits oscillatory zoning, high Th/U ratios and sharp-edged, anhedral-to-subhedral crystal forms, suggesting a derivation from proximal or deep-seated terranes. The concordant U–Pb zircon ages of 2468 and 974 Ma from the quartz schist, along with the 978 Ma age from the inherited zircons in the amphibolite, and the 1.2–2.1 Ga T2DM(Nd) from leucogranite and metamorphic rocks, collectively suggest that the Tianshuihai unit is likely underpinned by a Palaeoproterozoic basement that indicates Neoproterozoic reworking.

Therefore, our findings suggest the presence of a continuous, northwest-southeast trending Palaeoproterozoic basement underlying the entire Tashikuergan-Tianshuihai terrane. An alternative scenario posits that the ancient basement, currently beneath the Tashikuergan terrane, could extend into the Tianshuihai region, potentially indicating a Cambrian continental margin arc interspersed with remnants of older terranes.

When latent variables are used as outcomes in regression analysis, a common approach that is used to solve the ignored measurement error issue is to take a multilevel perspective on item response modeling (IRT). Although recent computational advancement allows efficient and accurate estimation of multilevel IRT models, we argue that a two-stage divide-and-conquer strategy still has its unique advantages. Within the two-stage framework, three methods that take into account heteroscedastic measurement errors of the dependent variable in stage II analysis are introduced; they are the closed-form marginal MLE, the expectation maximization algorithm, and the moment estimation method. They are compared to the naïve two-stage estimation and the one-stage MCMC estimation. A simulation study is conducted to compare the five methods in terms of model parameter recovery and their standard error estimation. The pros and cons of each method are also discussed to provide guidelines for practitioners. Finally, a real data example is given to illustrate the applications of various methods using the National Educational Longitudinal Survey data (NELS 88).

Diagnostic classification models (DCMs) have seen wide applications in educational and psychological measurement, especially in formative assessment. DCMs in the presence of testlets have been studied in recent literature. A key ingredient in the statistical modeling and analysis of testlet-based DCMs is the superposition of two latent structures, the attribute profile and the testlet effect. This paper extends the standard testlet DINA (T-DINA) model to accommodate the potential correlation between the two latent structures. Model identifiability is studied and a set of sufficient conditions are proposed. As a byproduct, the identifiability of the standard T-DINA is also established. The proposed model is applied to a dataset from the 2015 Programme for International Student Assessment. Comparisons are made with DINA and T-DINA, showing that there is substantial improvement in terms of the goodness of fit. Simulations are conducted to assess the performance of the new method under various settings.

Time limits are imposed on many computer-based assessments, and it is common to observe examinees who run out of time, resulting in missingness due to not-reached items. The present study proposes an approach to account for the missing mechanisms of not-reached items via response time censoring. The censoring mechanism is directly incorporated into the observed likelihood of item responses and response times. A marginal maximum likelihood estimator is proposed, and its asymptotic properties are established. The proposed method was evaluated and compared to several alternative approaches that ignore the censoring through simulation studies. An empirical study based on the PISA 2018 Science Test was further conducted.

With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational speed. This study introduces a novel “divide- and-conquer” parallel algorithm built on the Wasserstein posterior approximation concept, aiming to enhance computational speed while maintaining accurate parameter estimation. This algorithm enables drawing parameters from segmented data subsets in parallel, followed by an amalgamation of these parameters via Wasserstein posterior approximation. Theoretical support for the algorithm is established through asymptotic optimality under certain regularity assumptions. Practical validation is demonstrated using real-world data from the Programme for International Student Assessment. Ultimately, this research proposes a transformative approach to managing educational big data, offering a scalable, efficient, and precise alternative that promises to redefine traditional practices in educational assessments.

Diagnostic classification models (DCMs) are important statistical tools in cognitive diagnosis. In this paper, we consider the issue of their identifiability. In particular, we focus on one basic and popular model, the DINA model. We propose sufficient and necessary conditions under which the model parameters are identifiable from the data. The consequences, in terms of the consistency of parameter estimates, of fulfilling or failing to fulfill these conditions are illustrated via simulation. The results can be easily extended to the DINO model through the duality of the DINA and DINO models. Moreover, the proposed theoretical framework could be applied to study the identifiability issue of other DCMs.

In this paper, we simulate the process of two-dimensional axisymmetric fluid–structure coupling of a droplet impacting on a flexible disk. The effects of dimensionless disk stiffness (K = 0.1–1000), Weber number (We = 1–500) and contact angle (θ = 130° and 60°) on the dynamics of the droplet impacting on the flexible disk are analysed. The results indicate that there are five typical impact modes for a hydrophobic surface (θ = 130°) and four typical impact modes for a hydrophilic surface (θ = 60°) within the range of considered parameters. The analysis of spreading factor reveals that a part of the energy is transferred to the substrate, which is manifested as a weakening of the droplet spreading, when the substrate deforms downwards due to the droplet impact; the squeezing of the droplet causes a tendency to flow from the centre of the droplet to the edge, which is manifested as an enhancement of the droplet spreading, when the substrate recovers from the downward deformation. The effect of the substrate flexibility on the maximum spreading factor depends on the competition of the two mechanisms above. Based on this, a modified scaling law of βmax has been proposed by introducing the effective Weber number (Wem). The analysis of impact force demonstrates that the peak of the impact force is related to the deflection of the flexible substrate which is different from that of a rigid wall; and three typical processes of impact force variation have been summarised. In addition, unlike the rigid substrate scenario, there is an energy interaction between the droplet and the flexible substrate after impact occurs, which is classified as three typical energy transformation processes.