Antecedents of Employees\u27 Knowledge Sharing Intentions: An Integrated Perspective of Interpersonal Trust and Conflicts

Facilitating knowledge sharing among employees across different units in an organization is crucial in terms of facilitating collaboration for developing competitive advantages. While a significant numbers of previous studies have examined the facilitating and inhibiting factors of knowledge sharing among employees in organizations, very few of them have empirically examined the individual effects of different types of interpersonal conflicts on interpersonal trust and, consequently, on their knowledge sharing intentions. Data collected from 224 employees of organizations in the manufacturing industry in Taiwan was analyzed to examine the proposed theoretical model using the technique of component-based structural equation modeling. The results indicate that both relationship and task conflicts have significant indirect effects on employees’ knowledge sharing intentions via interpersonal trust. The theoretical and practical implications of this work are discussed

Structural response reconstruction for non-proportionally damped systems in the presence of closely spaced modes

An approach of structural response reconstruction for non-proportionally damped systems is proposed in this paper, which is a time domain method based on the empirical mode decomposition method with intermittency criteria and modal superposition method. The state space method is employed for decoupling the dynamic system equation to obtain the complex mode shapes. Response reconstruction of the structural system in the presence of closely spaced modes is studied in detail. The key idea is to regard each set of closely spaced modes as an integral part. Two numerical examples are conducted to validate the effectiveness of the proposed method

Gene-induced Multimodal Pre-training for Image-omic Classification

Histology analysis of the tumor micro-environment integrated with genomic assays is the gold standard for most cancers in modern medicine. This paper proposes a Gene-induced Multimodal Pre-training (GiMP) framework, which jointly incorporates genomics and Whole Slide Images (WSIs) for classification tasks. Our work aims at dealing with the main challenges of multi-modality image-omic classification w.r.t. (1) the patient-level feature extraction difficulties from gigapixel WSIs and tens of thousands of genes, and (2) effective fusion considering high-order relevance modeling. Concretely, we first propose a group multi-head self-attention gene encoder to capture global structured features in gene expression cohorts. We design a masked patch modeling paradigm (MPM) to capture the latent pathological characteristics of different tissues. The mask strategy is randomly masking a fixed-length contiguous subsequence of patch embeddings of a WSI. Finally, we combine the classification tokens of paired modalities and propose a triplet learning module to learn high-order relevance and discriminative patient-level information.After pre-training, a simple fine-tuning can be adopted to obtain the classification results. Experimental results on the TCGA dataset show the superiority of our network architectures and our pre-training framework, achieving 99.47% in accuracy for image-omic classification. The code is publicly available at https://github.com/huangwudiduan/GIMP

Form factors of P→TP\to T transition within the light-front quark models

In this paper, we calculate the vector, axial-vector and tensor form factors of $P\to T$ transition within the standard light-front~(SLF) and covariant light-front~(CLF) quark models~(QMs). The self-consistency and Lorentz covariance of CLF QM with two types of correspondence schemes are investigated. The zero-mode effects and the spurious $\omega$-dependent contributions to the form factors of $P\to T$ transition are analyzed. Employing a self-consistent CLF QM, we present our numerical predictions for the vector, axial-vector and tensor form factors of $c\to (q,s)$~($q=u,d$) induced $D \to (a_2,K^*_2)$, $D_s \to (K^*_2,f'_{2})$, $\eta_c(1S) \to (D^*_2,D^*_{s2})$, $B_c \to (B^*_2,B^*_{s2})$ transitions and $b\to (q,s,c)$ induced $B \to (a_2,K^*_2,D^*_2)$, $B_s \to (K^*_2,f'_2,D^*_{s2})$, $B_c \to (D^*_2,D^*_{s2},\chi_{c2}(1P))$, $\eta_b(1S) \to (B^*_2,B^*_{s2})$ transitions. Finally, in order to test the obtained form factors, the semileptonic $B\to \bar{D}_2^*(2460)\ell^+\nu_\ell$~($\ell=e,\mu$) and $\bar{D}_2^*(2460)\tau^+\nu_{\tau}$ decays are studied. It is expected that our results for the form factors of $P\to T$ transition can be applied further to the relevant phenomenological studies of meson decays.Comment: 41 pages, 7figures. arXiv admin note: text overlap with arXiv:1908.0467

Correlation between diopters and refractive parameters among 5 to 12 years old school-age children of Lanzhou city

AIM: To investigate the epidemiological status of refractive state among school-age children of 5 to 12 years in Chengguan district of Lanzhou city, and to analyze the correlation with axial length(AL), horizontal and vertical corneal refractive power(K1, K2), anterior chamber depth(ACD)and corneal diameter(W-W). <p>METHODS: The value of AL, K1, K2, ACD and W-W of 813 school-age children(1626 eyes)aged 8.46±2.30 years old(5-12 years)were measured by IOL-Master, refractive error was measured by computer refractor. The eyes were divided into 5 groups according to different mean spherical equivalent(SE)diopter: high myopia, moderate myopia, low myopia, emmetropia and hyperopia. The correlation between diopter and different refractive parameters of different ages and different diopter groups were analyzed respectively, the SPSS 19.0 was used for the statistical analysis.<p>RESULTS: There were statistically significant difference(<i>P</i><0.05)in uncorrected visual acuity and refractive state among the different groups of 5-12 years school-age children, the prevalence of myopia tended to increase with the age. There were statistically significant difference in AL and ACD among the different age groups(<i>P</i><0.05), AL and ACD increased with the age. There were statistically significant difference in AL among three myopic groups(<i>P</i><0.05). There were statistically significant difference in ACD between low myopia and moderate myopia, low myopia and high myopia(<i>P</i><0.05). There were statistically significant difference in corneal refractive power and corneal diameter between low myopia and high myopia, moderate myopia and high myopia(<i>P</i><0.05). SE was negatively correlated with AL(<i>r</i>=-0.764, <i>P</i><0.01)and ACD(<i>r</i>=-0.498, <i>P</i><0.01), but had week correlation with corneal refractive power or corneal diameter.<p>CONCLUSION: The increase of AL plays an important role in the changes of refractive among school-age children of 5-12 years, AL is the main morphological variable related to myopia. Meanwhile, refractive changes may be affected by corneal refractive power(K1, K2), ACD and corneal diameter(W-W). 7-8 years old can be regarded as the main phase from emmetropization to myopization of school-age children

Anomalous quantum transport in 2D asymptotic quasiperiodic system

Quasiperiodic systems extend the concept of Anderson transition to the quasi-random and low-dimensional realm, exhibiting intricate behaviors even in the one-dimension, while their investigation in higher dimensions remains less explored. Here, we delve into a series of two-dimensional lattice models of Hall systems with asymptotically incommensurate flux, and reveal the impact of asymptotic incommensurability together with relaxation on transport phenomena. Specifically, we demonstrate anomalous bulk transport with universal scaling characteristics in the wave-packet dynamics and conductivity, and predict novel interplay effects involving asymptotic incommensurability, temperature, and relaxation, leading to unprecedented multiple anisotropic metal-insulator transitions. The asymptotic quasiperiodicity also leads to the quantized anisotropic edge tunneling transport. Our work enriches the universal quantum transport phenomena, and add to the fundamental mechanisms underlying the metal-insulator transitions driven by incommensurability in higher dimensions, potentially opening a new avenue for exploring novel transport physics in quasiperiodic systems.Comment: 5+6 pages. 4+6 figure

Controlled-NOT gate based on the Rydberg states of surface electrons

Due to the long coherence time and efficient manipulation, the surface electron (SE) provides a perfect two-dimensional platform for quantum computation and quantum simulation. In this work, a theoretical scheme to realize the controlled-NOT (CNOT) gate is proposed, where the two-qubit system is encoded on the four-level Rydberg structure of SE. The state transfer is achieved by a three-level structure with an intermediate level. By simultaneously driving the SE with two external electromagnetic fields, the dark state in the electromagnetically induced transparency (EIT) effect is exploited to suppress the population of the most dissipative state and increase the robustness against dissipation. The fidelity of the scheme is 0.9989 with experimentally achievable parameters

An improved state space method for force identification based on function interpolation in the presence of large noise

The conventional state space method for force identification has the disadvantage of large discretization error with a low sampling frequency. This paper presents an improved method based on the function interpolation of the external force in time domain. Two types of the interpolation functions are investigated, one is the linear interpolation, and the other type is the sigmoid curve interpolation. Gauss integration method is used for integration computation. Numerical studies show that both of the improved methods based on the two types of interpolation function are more accurate especially when the sampling is long and/or with a low sampling frequency. In addition, the proposed method is also extended for the case of high noise level. The key idea is to divide the time step of measured responses into several smaller time steps to form an overdetermined equation of the inverse force identification. Then, the least square algorithm is adopted, which helps to reduce the effect of the high random noise to improve the accuracy of identified solution