The impact of honors education on students’ academic and innovative achievements: a longitudinal study in China (2011–2021)

Honors education has ascended as an integral element within the sphere of global higher education, concentrating on fostering individuals who exhibit creativity and a history of innovative achievements. Despite its widespread adoption, there remains a scarcity of exhaustive longitudinal studies investigating its effects and associated variables. To address this shortcoming, this study deploys rigorous structural equation modeling (SEM) and linear regression analyses to meticulously examine a dataset comprising 319 students, who enrolled over a decade (2011–2021) in a prestigious honors college at a preeminent university in China. The primary objective is to discern the predictive efficacy of Chinese honors education selection criteria on students’ creative and academic accomplishments. This endeavor strives to clarify the complex interplay among students’ creative personalities, academic performance, creative achievements, and standardized college entrance exam scores. The findings emphasize that individuals who exhibit enhanced creative personality traits are predisposed to elevated levels of both innovation and academic attainment (β = 0.170, p  = 0.017). Additionally, a significant inverse relationship is observed between general learning aptitude and subsequent academic performance (β = −0.008, p = 0.023), while students pursuing science disciplines demonstrate superior innovation outcomes compared to their liberal arts counterparts (β = 0.125, p  = 0.048). Interestingly, neither gender nor general academic prowess exerts significant predictive power over collegiate innovation (β  = −0.002, p = 0.134). These empirical insights equip policymakers and scholars with nuanced perspectives on the determinants shaping students’ refined educational experiences, thereby inciting critical discourse concerning the refinement of selection criteria and the imperative of nurturing students’ creative proclivities

Distributed Learning over Networks with Graph-Attention-Based Personalization

In conventional distributed learning over a network, multiple agents collaboratively build a common machine learning model. However, due to the underlying non-i.i.d. data distribution among agents, the unified learning model becomes inefficient for each agent to process its locally accessible data. To address this problem, we propose a graph-attention-based personalized training algorithm (GATTA) for distributed deep learning. The GATTA enables each agent to train its local personalized model while exploiting its correlation with neighboring nodes and utilizing their useful information for aggregation. In particular, the personalized model in each agent is composed of a global part and a node-specific part. By treating each agent as one node in a graph and the node-specific parameters as its features, the benefits of the graph attention mechanism can be inherited. Namely, instead of aggregation based on averaging, it learns the specific weights for different neighboring nodes without requiring prior knowledge about the graph structure or the neighboring nodes' data distribution. Furthermore, relying on the weight-learning procedure, we develop a communication-efficient GATTA by skipping the transmission of information with small aggregation weights. Additionally, we theoretically analyze the convergence properties of GATTA for non-convex loss functions. Numerical results validate the excellent performances of the proposed algorithms in terms of convergence and communication cost.Comment: Accepted for publication in IEEE TSP; with supplementary details for the derivation

Distributed multi-view sparse vector recovery

In this paper, we consider a multi-view compressed sensing problem, where each sensor can only obtain a partial view of the global sparse vector. Here the partial view means that some arbitrary and unknown indices of the global vector are unobservable to that sensor and do not contribute to the measurement outputs. The sensors aim to collaboratively recover the global state vector in a decentralized manner. We formulatethis recovery problem as a bilinear optimization problem relying on a factored joint sparsity model (FJSM), in which the variables are factorized into a node-specific sparse local masking vector and the desired common sparse global vector. We first theoretically analyze the general conditions guaranteeing the global vector’s successful recovery. Then we propose a novel in network algorithm based on the powerful distributed alternating direction method of multipliers (ADMM), which can reconstruct the vectors and achieve consensus among nodes concerning the estimation of the global vector. Specifically, each node alternately updates the common global vector and its local masking vector, and then it transfers the estimated global vector to its neighboring nodes for further updates. To avoid potential divergence of the iterative algorithm, we propose an early stopping rule for theestimation of the local masking vectors and further conceive an estimation error-mitigation algorithm. The convergence of the proposed algorithms is theoretically proved. Finally, extensive simulations validate their excellent performance both in terms of the convergence and recovery accuracy

Case report: “Major fetal cardiac pathology associated with a novel CTNND1 mutation”

BackgroundThe p120-ctn protein, encoded by CTNND1, is involved in intercellular connections and regulates epithelial–mesenchymal transformation. CTNND1 mutations can lead to blepharocheilodontic syndrome (BCDS). Increasing evidence shows that although BCDS mainly manifests as craniofacial and oral deformities, it can also present as congenital heart disease, limb deformities, and neurodevelopmental disorders.Case descriptionWe report a prenatal case of a major cardiac malformation at 24+3 weeks of gestation. Ultrasound examination revealed a hypoplastic left ventricular, aortic coarctation, and a ventricular septal defect. Genetic analysis of the fetal tissues showed the presence of a novel mutation in CTNND1 (NM_001085458.2: c.566_c.567insG; p.Pro190fs*15), which may lead to premature termination of protein coding, while both the parents harbored wild-type CTNND1. To date, only 15 CTNND1 mutations have been reported in 19 patients worldwide, of which approximately 31% (6/19) had a cardiac phenotype.ConclusionTo the best of our knowledge, this is the first case report of fetal complicated cardiac malformations caused by this CTNND1 mutation. Our findings provide new clinical references for prenatal diagnosis and suggest an important role for CTNND1 in early cardiac development

Study on the Influence and Optimization of the Venturi Effect on the Natural Ventilation of Buildings in the Xichang Area

Natural ventilation is a way to reduce the energy consumption of building operations and improve the indoor living environment comfort. The venturi cap is designed with a roof, grille and wind deflector to intensify the natural ventilation of buildings. The structural parameters of the venturi cap were designed using an orthogonal design. Fluid analysis software was used for numerical simulation, and variance analysis was used to study the importance of seven influence factors: the width of the roof opening, the roof slope, the height of the wind deflector, the horizontal width of the wind deflector, the angle of the wind deflector, the angle of the grille, and the spacing of the grille slices. The results show that the most significant influencing factor is the width of the roof opening, while significant influence factors include the angle of the grille and the horizontal width of the wind deflector. Additionally, the optimum parameter combination for ventilation performance at the research level was put forward, with the proposed combination achieving a volume flow rate of 5.507 m3/s. The average temperature of the horizontal plane at a height of 1.2 m above the ground was 3.002 K lower than that without a venturi cap, which provides a reference for the optimization of indoor ventilation design in buildings in the Xichang area

Design and Application of a Solar Mobile Pond Aquaculture Water Quality-Regulation Machine Based in Bream Pond Aquaculture.

Bream pond aquaculture plays a very important role in China's aquaculture industry and is the main source of aquatic products. To regulate and control pond water quality and sediment, a movable solar pond aquaculture water quality regulation machine (SMWM) was designed and used. This machine is solar-powered and moves on water, and its primary components are a solar power supply device, a sediment lifting device, a mechanism for walking on the water's surface and a control system. The solar power supply device provides power for the machine, and the water walking mechanism drives the machine's motion on the water. The sediment lifting device orbits the main section of the machine and affects a large area of the pond. Tests of the machine's mechanical properties revealed that the minimum illumination necessary for the SMWM to function is 13,000 Lx and that its stable speed on the water is 0.02-0.03 m/s. For an illumination of 13,000-52,500 Lx, the sediment lifting device runs at 0.13-0.35 m/s, and its water delivery capacity is 110-208 m(3)/h. The sediment lifting device is able to fold away, and the angle of the suction chamber can be adjusted, making the machine work well in ponds at different water depths from 0.5 m to 2 m. The optimal distance from the sediment lifting device to the bottom of the pond is 10-15 cm. In addition, adjusting the length of the connecting rod and the direction of the traction rope allows the SMWM to work in a pond water area greater than 80%. The analysis of water quality in Wuchang bream (Parabramis pekinensis) and silver carp (Hypophthalmichthys molitrix) culture ponds using the SMWM resulted in decreased NH3(+)-N and available phosphorus concentrations and increased TP concentrations. The TN content and the amount of available phosphorus in the sediment were reduced. In addition, the fish production showed that the SMWM enhanced the yields of Wuchang bream and silver carp by more than 30% and 24%, respectively. These results indicate that the SMWM may be suitable for Wuchang bream pond aquaculture in China and that it can be used in pond aquaculture for regulating and controlling water quality

Non-coding RNAs identification and regulatory networks in pathogen-host interaction in the microsporidia congenital infection

Abstract Background The interaction networks between coding and non-coding RNAs (ncRNAs) including long non-coding RNA (lncRNA), covalently closed circular RNA (circRNA) and miRNA are significant to elucidate molecular processes of biological activities and interactions between host and pathogen. Congenital infection caused by vertical transmission of microsporidia N. bombycis can result in severe economic losses in the silkworm-feeding industry. However, little is known about ncRNAs that take place in the microsporidia congenital infection. Here we conducted whole-transcriptome RNA-Seq analyses to identify ncRNAs and regulatory networks for both N. bombycis and host including silkworm embryos and larvae during the microsporidia congenital infection. Results A total of 4,171 mRNAs, 403 lncRNA, 62 circRNAs, and 284 miRNAs encoded by N. bombycis were identified, among which some differentially expressed genes formed cross-talk and are involved in N. bombycis proliferation and infection. For instance, a lncRNA/circRNA competing endogenous RNA (ceRNA) network including 18 lncRNAs, one circRNA, and 20 miRNAs was constructed to describe 14 key parasites genes regulation, such as polar tube protein 3 (PTP3), ricin-B-lectin, spore wall protein 4 (SWP4), and heat shock protein 90 (HSP90). Regarding host silkworm upon N. bombycis congenital infection, a total of 14,889 mRNAs, 3,038 lncRNAs, 19,039 circRNAs, and 3,413 miRNAs were predicted based on silkworm genome with many differentially expressed coding and non-coding genes during distinct developmental stages. Different species of RNAs form interacting network to modulate silkworm biological processes, such as growth, metamorphosis and immune responses. Furthermore, a lncRNA/circRNA ceRNA network consisting of 140 lncRNAs, five circRNA, and seven miRNAs are constructed hypothetically to describe eight key host genes regulation, such as Toll-6, Serpin-6, inducible nitric oxide synthase (iNOS) and Caspase-8. Notably, cross-species analyses indicate that parasite and host miRNAs play a vital role in pathogen-host interaction in the microsporidia congenital infection. Conclusion This is the first comprehensive pan-transcriptome study inclusive of both N. bombycis and its host silkworm with a specific focus on the microsporidia congenital infection, and show that ncRNA-mediated regulation plays a vital role in the microsporidia congenital infection, which provides a new insight into understanding the basic biology of microsporidia and pathogen-host interaction