More on minors of Hermitian (quasi-)Laplacian matrix of the second kind for mixed graphs

A mixed graph $M_{G}$ is the graph obtained from an unoriented simple graph $G$ by giving directions to some edges of $G$, where $G$ is often called the underlying graph of $M_{G}$. In this paper, we introduce two classes of incidence matrices of the second kind of $M_{G}$, and discuss the determinants of these two matrices for rootless mixed trees and unicyclic mixed graphs. Applying these results, we characterize the explicit expressions of various minors for Hermitian (quasi-)Laplacian matrix of the second kind of $M_{G}$. Moreover, we give two sufficient conditions that the absolute values of all the cofactors of Hermitian (quasi-)Laplacian matrix of the second kind are equal to the number of spanning trees of the underlying graph $G$.Comment: 16 pages,7 figure

Characterizing random-singlet state in two-dimensional frustrated quantum magnets and implications for the double perovskite Sr2_2CuTe1−x_{1-x}Wx_{x}O6_6

Motivated by experimental observation of the non-magnetic phase in the compounds with frustration and disorder, we study the ground state of the spin-$1/2$ square-lattice Heisenberg model with randomly distributed nearest-neighbor $J_1$ and next-nearest-neighbor $J_2$ couplings. By using the density matrix renormalization group (DMRG) calculation on cylinder system with circumference up to $10$ lattice sites, we identify a disordered phase between the N\'eel and stripe magnetic phase with growing $J_2 / J_1$ in the presence of strong randomness. The vanished spin-freezing parameter indicates the absent spin glass order. The large-scale DMRG results unveil the size-scaling behaviors of the spin-freezing parameter, the power-law decay of average spin correlation, and the exponential decay of typical spin correlation, which all agree with the corresponding behavior in the one-dimensional random singlet (RS) state and characterize the RS nature of this non-magnetic state. The DMRG simulation also opens new insight and opportunities for characterizing a class of non-magnetic states in two-dimensional frustrated magnets with disorder. We also compare with existing experiments and suggest more measurements for understanding the spin-liquid-like behavior in the double perovskite Sr$_2$CuTe$_{1-x}$W$_{x}$O$_6$.Comment: 11 pages,10 figure

Transmissive fiber Bragg grating-based delay line interferometer for RZ-OOK to NRZ-OOK format conversion

We propose a return-to-zero on-off keying (RZ-OOK) to non-return-to-zero (NRZ) OOK conversion scheme based on a transmissive phase-modulated fiber Bragg grating (PM-FBG). The PM-FBG has a spectrum similar to the combination of a delay line interferometer and a narrow band optical filter, which is designed and synthesized using numerical optimization algorithm. The coupling strength of the PM-FBG is almost uniform and the grating period varies along the fiber length according to the optimization method. The designed PM-FBG has been fabricated using advanced ultraviolet laser inscription technique. Experimental results show that such a PM-FBG can perform RZ-OOK to NRZ-OOK format conversion successfully

Graph Neural Network Recommendation Model Integrating User Preferences

Aiming at the problem that knowledge graph-driven graph neural network recommendation algorithm cannot learn the user and item representations at the same time,a graph neural network recommendation model that integrates user preferences is proposed.The model learns user and item representations from user’s perspective and entity’s perspective respectively.Firstly,the user’s perspective spreads user preferences in the knowledge graph based on user historical interaction records and enhances user representation.Secondly,the entity perspective gathers neighbor information of candidate entities through graph convolu-tional network to enrich the representation of the entity.At the same time,a hybrid layer is designed to capture high-level connectivity and hybrid hierarchical information from both the width and depth aspects to enhance the item representation.The enhanced user representation vector and item representation vector are input to the prediction function to predict the interaction probability.Finally,the fixed-size sampling method and phased training strategy are used to optimize the model.The click-through rate prediction experiment is conducted on the MovieLens-1M data set,and the results show that,compared with the benchmark methods RippleNet and KGCN,its AUC increases by 1.7% and 2.3% respectively

GlueGen: Plug and Play Multi-modal Encoders for X-to-image Generation

Text-to-image (T2I) models based on diffusion processes have achieved remarkable success in controllable image generation using user-provided captions. However, the tight coupling between the current text encoder and image decoder in T2I models makes it challenging to replace or upgrade. Such changes often require massive fine-tuning or even training from scratch with the prohibitive expense. To address this problem, we propose GlueGen, which applies a newly proposed GlueNet model to align features from single-modal or multi-modal encoders with the latent space of an existing T2I model. The approach introduces a new training objective that leverages parallel corpora to align the representation spaces of different encoders. Empirical results show that GlueNet can be trained efficiently and enables various capabilities beyond previous state-of-the-art models: 1) multilingual language models such as XLM-Roberta can be aligned with existing T2I models, allowing for the generation of high-quality images from captions beyond English; 2) GlueNet can align multi-modal encoders such as AudioCLIP with the Stable Diffusion model, enabling sound-to-image generation; 3) it can also upgrade the current text encoder of the latent diffusion model for challenging case generation. By the alignment of various feature representations, the GlueNet allows for flexible and efficient integration of new functionality into existing T2I models and sheds light on X-to-image (X2I) generation.Comment: ICCV 202

Genetic variation and relationships of eighteen Chinese indigenous pig breeds

Chinese indigenous pig breeds are recognized as an invaluable component of the world's pig genetic resources and are divided traditionally into six types. Twenty-six microsatellite markers recommended by the FAO (Food and Agriculture Organization) and ISAG (International Society of Animal Genetics) were employed to analyze the genetic diversity of 18 Chinese indigenous pig breeds with 1001 individuals representing five types, and three commercial breeds with 184 individuals. The observed heterozygosity, unbiased expected heterozygosity and the observed and effective number of alleles were used to estimate the genetic variation of each indigenous breed. The unbiased expected heterozygosity ranged between 0.700 (Mashen) and 0.876 (Guanling), which implies that there is an abundant genetic variation stored in Chinese indigenous pig breeds. Breed differentiation was shown by fixation indices (FIT, FIS, and FST). The FST per locus varied from 0.019 (S0090) to 0.170 (SW951), and the average FST of all loci was 0.077, which means that most of the genetic variation was kept within breeds and only a little of the genetic variation exists between populations. The Neighbor-Joining tree was constructed based on the Nei DA (1978) distances and one large cluster with all local breeds but the Mashen breed, was obtained. Four smaller sub-clusters were also found, which included two to four breeds each. These results, however, did not completely agree with the traditional type of classification. A Neighbor-Joining dendrogram of individuals was established from the distance of – ln(proportions of shared alleles); 92.14% of the individuals were clustered with their own breeds, which implies that this method is useful for breed demarcation. This extensive research on pig genetic diversity in China indicates that these 18 Chinese indigenous breeds may have one common ancestor, helps us to better understand the relative distinctiveness of pig genetic resources, and will assist in developing a national plan for the conservation and utilization of Chinese indigenous pig breeds

Distinguishing Smilax glabra and Smilax china rhizomes by flow-injection mass spectrometry combined with principal component analysis

Flow-injection mass spectrometry (FIMS) coupled with a chemometric method is proposed in this study to profile and distinguish between rhizomes of Smilax glabra (S. glabra) and Smilax china (S. china). The proposed method employed an electrospray-time-of-flight MS. The MS fingerprints were analyzed using principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) with the aid of SIMCA software. Findings showed that the two kinds of samples perfectly fell into their own classes. Further predictive study showed desirable predictability and the tested samples were successfully and reliably identified. The study demonstrated that the proposed method could serve as a powerful tool for distinguishing between S. glabra and S. china

Case report: Supratherapeutic tacrolimus concentrations with nirmatrelvir/ritonavir in a lung transplant patient: a case report using Rifampin for reversal

Paxlovid (nirmatrelvir/ritonavir) is an antiviral drug used to treat COVID-19, nirmatrelvir, a SARS-CoV-2 main protease inhibitor, works by inhibiting viral replication in the early stages, and ritonavir is a strong cytochrome P450 (CYP) 3A inhibitor that helps the nirmatrelvir reach and maintain the therapeutic concentrations. Paxlovid has a potential risk of drug interaction by elevating the plasma concentration of other drugs metabolized by CYP3A, like tacrolimus. This report examines the case of a 57-year-old female lung transplant patient self-administered Paxlovid for 5 days without discontinuing tacrolimus. She presented to the hospital with symptoms of headache, dizziness, palpitations, abdominal distension, nausea, vomiting, and diarrhea. The patient presented with tacrolimus toxicity and the blood concentration of tacrolimus was measured at 106 ng/mL. Urgent medical intervention was initiated, and Rifampin was administered to induce enzyme activity and rapidly decrease the concentration of tacrolimus. By adjusting the tacrolimus dosage, the final concentration was brought within the appropriate range. Clinical pharmacists should prioritize medication education for transplant patients to prevent severe drug interactions and minimize the impact on the patient’s overall well-being

IL21R and PTH May Underlie Variation of Femoral Neck Bone Mineral Density as Revealed by a Genome-wide Association Study

Bone mineral density (BMD) measured at the femoral neck (FN) is the most important risk phenotype for osteoporosis and has been used as a reference standard for describing osteoporosis. The specific genes influencing FN BMD remain largely unknown. To identify such genes, we first performed a genome-wide association (GWA) analysis for FN BMD in a discovery sample consisting of 983 unrelated white subjects. We then tested the top significant single-nucleotide polymorphisms (SNPs; 175 SNPs with p < 5 × 10−4) for replication in a family-based sample of 2557 white subjects. Combing results from these two samples, we found that two genes, parathyroid hormone (PTH) and interleukin 21 receptor (IL21R), achieved consistent association results in both the discovery and replication samples. The PTH gene SNPs, rs9630182, rs2036417, and rs7125774, achieved p values of 1.10 × 10−4, 3.24 × 10−4, and 3.06 × 10−4, respectively, in the discovery sample; p values of 6.50 × 10−4, 5.08 × 10−3, and 5.68 × 10−3, respectively, in the replication sample; and combined p values of 3.98 × 10−7, 9.52 × 10−6, and 1.05 × 10−5, respectively, in the total sample. The IL21R gene SNPs, rs8057551, rs8061992, and rs7199138, achieved p values of 1.51 × 10−4, 1.53 × 10−4, and 3.88 × 10−4, respectively, in the discovery sample; p values of 2.36 × 10−3, 6.74 × 10−3, and 6.41 × 10−3, respectively, in the replication sample; and combined p values of 2.31 × 10−6, 8.62 × 10−6, and 1.41 × 10−5, respectively, in the total sample. The effect size of each SNP was approximately 0.11 SD estimated in the discovery sample. PTH and IL21R both have potential biologic functions important to bone metabolism. Overall, our findings provide some new clues to the understanding of the genetic architecture of osteoporosis. © 2010 American Society for Bone and Mineral Research