This paper presents the first reported design of a balanced nonreciprocal bandpass filter with both common-mode (CM) and differential-mode (DM) reflectionless characteristics. The nonreciprocal behavior is achieved using a time-modulated resonator, which isolates in-band backward interference signals, thereby protecting preceding circuits from their negative effects. To solve the negative effects of reflected waves of the reflection-based CM noise suppression and reflection-based DM stopband attenuation, CM and DM reflectionless structures are integrated at both the input and output ports, ensuring reflectionless operation for both CM and DM signals. Meanwhile, the implementation of DM reflectionless characteristics effectively addresses the issue of reflection zero degradation typically observed in time-modulated resonator-based nonreciprocal filters. The proposed filter exclusively transmits differential forward signals, which will greatly improve the anti-interference ability and stability of the balanced RF circuits. To validate the concept experimentally, a 1.5-GHz microstrip prototype is designed, simulated, fabricated, and characterized.

It was found that a significant number of patients with major depressive disorder (MDD) did not respond to the treatment, leading to high ongoing costs and disease burden. The main objective of this study was to find neurobiological indicators that can predict the effectiveness of antidepressant treatment using diffusion tensor imaging (DTI). A group of 103 patients who were experiencing their first episode of MDD were included in the study. After 2 weeks of SSRI treatment, the group of patients was split into two categories: ineffectiveand effective. The FMRIB Software Library (FSL) was used for diffusion data preprocessing to obtain tensor-based parameters such as FA, MD, AD, and RD. Tract-Based Spatial Statistical (TBSS) voxel-wise statistical analysis of the tensor-based parameters was carried out using the TBSS procedure in FSL. We conducted an investigation to determine if there were notable variations in neuroimaging attributes among the three groups. Compared to HC, the effective group showed significantly higher AD and MD values in the left CgH. Correlating neuroimaging characteristics and clinical manifestations revealed a significant positive correlation between CgH-l FA and clinical 2-week HAMD-17 total scores and a significant positive correlation between CgH-r FA and clinical 2-week HAMD-17 total scores. Functional damage to the cingulum bundle in the hippocampal region may predispose patients to MDD and predict antidepressant treatment outcomes. More extensive multicenter investigations are necessary to validate these MRI findings that indicate treatment effectiveness and assess their potential significance in practical therapeutic decision-making.

Assessing fit in common factor models solely through the lens of mean and covariance structures, as is commonly done with conventional goodness-of-fit (GOF) assessments, may overlook critical aspects of misfit, potentially leading to misleading conclusions. To achieve more flexible fit assessment, we extend the theory of generalized residuals (Haberman & Sinharay, 2013), originally developed for models with categorical data, to encompass more general measurement models. Within this extended framework, we propose several fit test statistics designed to evaluate various parametric assumptions involved in common factor models. The examples include assessing the distributional assumptions of latent variables and the functional form assumptions of individual manifest variables. The performance of the proposed statistics is examined through simulation studies and an empirical data analysis. Our findings suggest that generalized residuals are promising tools for detecting misfit in measurement models, often masked when assessed by conventional GOF testing methods.

American silk moth, Antheraea polyphemus Cramer 1775 (Lepidoptera: Saturniidae), native to North America, has potential significance in sericulture for food consumption and silk production. To date, the phylogenetic relationship and divergence time of A. polyphemus with its Asian relatives remain unknown. To end these issues, two mitochondrial genomes (mitogenomes) of A. polyphemus from the USA and Canada respectively were determined. The mitogenomes of A. polyphemus from the USA and Canada were 15,346 and 15,345 bp in size, respectively, with only two transitions and five indels. The two mitogenomes both encoded typical mitochondrial 37 genes. No tandem repeat elements were identified in the A+T-rich region of A. polyphemus. The mitogenome-based phylogenetic analyses supported the placement of A. polyphemus within the genus Antheraea, and revealed the presence of two clades for eight Antheraea species used: one included A. polyphemus, A. assamensis Helfer, A. formosana Sonan and the other contained A. mylitta Drury, A. frithi Bouvier, A. yamamai Guérin-Méneville, A. proylei Jolly, and A. pernyi Guérin-Méneville. Mitogenome-based divergence time estimation further suggested that the dispersal of A. polyphemus from Asia into North America might have occurred during the Miocene Epoch (18.18 million years ago) across the Berling land bridge. This study reports the mitogenome of A. polyphemus that provides new insights into the phylogenetic relationship among Antheraea species and the origin of A. polyphemus.

Data-driven neural word embeddings (NWEs), grounded in distributional semantics, can capture various ranges of linguistic regularities, which can be further enriched by incorporating structured knowledge resources. This work proposes a novel post-processing approach for injecting semantic relationships into the vector space of both static and contextualized NWEs. Current solutions to retrofitting (RF) word embeddings often oversimplify the integration of semantic knowledge, neglecting the nuanced differences between relationships, which may result in suboptimal performance. Instead of applying multi-thresholding to distance boundaries in metric learning, we compute taxonomic similarity to dynamically adjust these boundaries during the semantic specialization of word embeddings. Benchmark evaluations on both static and contextualized word embeddings demonstrate that our dynamic-fitting (DF) approach produces SOTA correlation results of 0.78 and 0.76 on SimLex-999 and SimVerb-3500, respectively, highlighting the effectiveness of incorporating multiple semantic relationships in refining vector semantics. Our approach also outperforms existing RF methods in both supervised and unsupervised semantic relationships recognition tasks. It achieves top accuracy scores for hypernymy detection on the BLESS, WBLESS, and BIBLESS datasets (0.97, 0.89, and 0.83, respectively) and an F1 score of over 0.60 on four types of semantic relationship classification in the shared Subtask-2 of CogALex-V, surpassing all participant systems. In the analogy reasoning task of the Bigger Analogy Test Set, our approach outperforms existing RF methods on inferring relational similarity. These consistent improvements across various lexical semantics tasks suggest that our DF approach can effectively integrate distributional semantics with symbolic knowledge resources, thereby enhancing the representation capacity of word embeddings in downstream applications.

Nutrition intervention is an effective way to improve flesh qualities of fish. The effect of feed supplementation with glutamate (Glu) on flesh quality of gibel carp (Carassius gibelio) was investigated. In trial 1, the fish (initial weight: 37.49 ± 0.08 g) were fed two practical diets with 0 and 2% Glu supplementation. In trial 2, the fish (37.26 ± 0.04 g) were fed two purified diets with 0 and 3% Glu supplementation. The results after feeding trials showed that dietary Glu supplementation increased the hardness and springiness of muscle, whether using practical or purified diets. Glu-supplemented diets increased the thickness and density of myofibres and collagen content between myofibres. Furthermore, Glu promoted muscle protein deposition by regulating the IGF-1-AKT-mTOR signalling pathway, and enhanced the myofibre hypertrophy by upregulating genes related to myofibre growth and development (mef2a, mef2d, myod, myf5, mlc, tpi and pax7α). The protein deposition and myofibre hypertrophy in turn improved the flesh texture. In addition, IMP content in flesh increased when supplementing Glu whether to practical or to purified diet. Metabolomics confirmed that Glu promoted the deposition of muscle-flavoured substances and purine metabolic pathway most functioned, echoed by the upregulation of key genes (ampd, ppat and adsl) in purine metabolism. The sensory test also clarified that dietary Glu improved the flesh quality by enhancing the muscle texture and flavour. Conclusively, dietary Glu supplementation can improve the flesh quality in this fish, which can further support evidence from other studies more generally that improve flesh quality of cultured fish.

Automatic precision herbicide application offers significant potential for reducing herbicide use in turfgrass weed management. However, developing accurate and reliable neural network models is crucial for achieving optimal precision weed control. The reported neural network models in previous research have been limited by specific geographic regions, weed species, and turfgrass management practices, restricting their broader applicability. The objective of this research was to evaluate the feasibility of deploying a single, robust model for weed classification across a diverse range of weed species, considering variations in species, ecotypes, densities, and growth stages in bermudagrass turfgrass systems across different regions in both China and the United States. Among the models tested, ResNeXt152 emerged as the top performer, demonstrating strong weed detection capabilities across 24 geographic locations and effectively identifying 14 weed species under varied conditions. Notably, the ResNeXt152 model achieved an F1 score and recall exceeding 0.99 across multiple testing scenarios, with a Matthews correlation coefficient (MCC) value surpassing 0.98, indicating its high effectiveness and reliability. These findings suggest that a single neural network model can reliably detect a wide range of weed species in diverse turf regimes, significantly reducing the costs associated with model training and confirming the feasibility of using one model for precision weed control across different turf settings and broad geographic regions.

Manganese (Mn) is a crucial trace element that actively participates in a diverse array of physiological processes. Mn is maintained at appropriate levels in the body by absorption and excretion by the body. Dysregulation of Mn homeostasis can lead to a variety of diseases, especially the accumulation of Mn in the brain, resulting in toxic side effects. We reviewed the metabolism and distribution of Mn at multiple levels, including organ, cellular and sub-cell levels. Mitochondria are the main sites of Mn metabolism and energy conversion in cells. Enhanced Mn superoxide dismutase activity reduces mitochondrial oxidative stress and inhibits cancer development. In addition, Mn enhances anti-cancer immune responses through the cGAS–STING pathway. We introduced various delivery vectors for Mn delivery to cancer sites for Mn supplementation and anti-cancer immunity. This review aims to provide new research perspectives for the application of Mn in the prevention and treatment of human diseases, especially by enhancing anti-cancer immune responses to inhibit cancer progression.

The previous study indicated that ubiquitination is involved in the freezing tolerance of hydrated seeds. Parthenolide (PN), inducing the ubiquitination of MDM2, an E3 ring-finger ubiquitin ligase, adversely affects the freezing tolerance of hydrated lettuce seeds. Therefore, a proteomics analysis was conducted to identify PN's targets in hydrated seeds exposed to cooling conditions. Several pathways, including oxidative phosphorylation (KEGG00190), amino sugar and nucleotide sugar metabolism (KEGG00520), and biosynthesis of nucleotide sugars (KEGG01250), were enriched in the PN treatment under slow-cooling conditions (3°C h−1, P < 0.05). Among the proteins in oxidative phosphorylation, the expression of NADH dehydrogenases and ATP synthases (ATPsyn) decreased in PN treatment. In contrast, uncoupling proteins increased after PN treatment, which led to the dissociation of the electron transport chain from ATP synthesis. Treatments with rotenone, dicoumarol, and oligomycin (i.e., oxidative phosphorylation inhibitors) decreased the survival rate of hydrated seeds under freezing conditions, which indicated that energy metabolism was related to the freezing tolerance of hydrated seeds. The predicted interactions between PN and MDM2-like proteins of Lactuca indicated that LsMDM2-5 forms two potential hydrogen bonds with PN. Furthermore, based on AlphaFold predictions and yeast 2-hybrid results, MDM2-5 might interact directly with NADH2. The knockdown of MDM2-5 by RNAi caused a higher level of NADH2 and ATPsyn and a higher freezing tolerance of hydrated seeds. This indicated that MDM2 played negative roles in regulating ATP synthesis and freezing tolerance of hydrated seeds.

The collapse of an initially spherical cavitation bubble near a free surface leads to the formation of two jets: a downward jet into the liquid, and an upward jet penetrating the free surface. In this study, we examine the surprising interaction of a bubble trapped in a stable cavitating vortex ring approaching a free surface. As a result, a single fast and tall liquid jet forms. We find that this jet is observed only above critical Froude numbers ($Fr$) and Weber numbers ($We$) when ${Fr}^2 (1.6-2.73/{We}) > 1$, illustrating the importance of inertia, gravity and surface tension in accelerating this novel jet and thereby reaching heights several hundred times the radius of the vortex ring. Our experimental results are supported by numerical simulations, revealing that the underlying mechanism driving the vortex ring acceleration is the disruption of the equilibrium of high-pressure regions at the front and rear of the vortex ring caused by the free surface. Quantitative analysis based on the energy relationships elucidates that the velocity ratio between the maximum velocity of the free-surface jet and the translational velocity of the vortex ring is relatively stable yet is attenuated by surface tension when the jet is mild.

Differential item functioning (DIF) analysis is an important step in establishing the validity of measurements. Most traditional methods for DIF analysis use an item-by-item strategy via anchor items that are assumed DIF-free. If anchor items are flawed, these methods will yield misleading results due to biased scales. In this article, based on the fact that the item’s relative change of difficulty difference (RCD) does not depend on the mean ability of individual groups, a new DIF detection method (RCD-DIF) is proposed by comparing the observed differences against those with simulated data that are known DIF-free. The RCD-DIF method consists of a D-QQ (quantile quantile) plot that permits the identification of internal references points (similar to anchor items), a RCD-QQ plot that facilitates visual examination of DIF, and a RCD graphical test that synchronizes DIF analysis at the test level with that at the item level via confidence intervals on individual items. The RCD procedure visually reveals the overall pattern of DIF in the test and the size of DIF for each item and is expected to work properly even when the majority of the items possess DIF and the DIF pattern is unbalanced. Results of two simulation studies indicate that the RCD graphical test has Type I error rate comparable to those of existing methods but with greater power.