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To analyze the phenotype of the male reproductive system in the germline-specific conditional Foxj2 knock-in mouse model (Stra8-cre; Foxj2tg/+), identify a target gene of the transcription factor FOXJ2, and investigate the effect of the overexpression of Foxj2 on mouse spermatogenesis and its action mechanism.Based on the Cre-loxP recombination system, we generated a germline-specific conditional Foxj2 knock-in mouse model (Stra8-cre; Foxj2tg/+). We determined male fertility by counting the number of pups per litter and the fertilization rate after intracytoplasmic sperm injection (ICSI), observed the morphology of the testes and epididymides by HE staining, examined the sperm quality by computer assisted sperm analysis (CASA), detected the expression and localization of Cx43 in the testis by RT-qPCR, Western blot and immunohistochemistry, and verified the binding site of FOXJ2 to the Cx43 promoter using ChIP-PCR and dual luciferase reporter assay.The number of pups per litter and fertilization rate after ICSI were lower in the Stra8-cre; Foxj2tg/+ male mice than in the controls, and so were the size and weight of the testis. HE staining exhibited obvious exfoliation of germ cells and dramatically decreased spermatocytes and spermatids in the seminiferous tubules of the Stra8-cre; Foxj2tg/+ mice. Moreover, sperm concentration in the cauda epididymides was reduced, and the transcription and expression levels of Cx43 in the testis were increased. ChIP-PCR and dual luciferase reporter assay showed direct binding of FOXJ2 to the Cx43 promoter in the testis.Overexpressed FOXJ2 may lead to spermatogenic failure and subfertility in Stra8-cre; Foxj2tg/+ male mice by upregulating the expression of Cx43.

Spermatogenesis is a complex biological process that produces haploid spermatozoa and requires precise regulation by many tissue-specific factors. In this study, we explored the role and mechanism of Fork head box J2 (FOXJ2, which is highly expressed in spermatocytes) in the regulation of spermatogenesis using a germline-specific conditional Foxj2 knock-in mouse model (Stra8-Cre; Foxj2tg/tg mouse). Foxj2 overexpression in mouse testes led to spermatogenesis failure, which started at the initiation of meiosis, and resulted in male infertility. Lysosomes and autophagy-related genes were upregulated in Stra8-cre; Foxj2tg/tg mouse testes and the number of autolysosomes in the spermatocytes in Stra8-cre; Foxj2tg/tg mice was increased. Chromatin immunoprecipitation-PCR and Dual-luciferase reporter assays showed that Lamp2 (encoding lysosome‐associated membrane protein‐2) was a target of FOXJ2. Foxj2 overexpression increased the expression levels of Lamp2a and Hsc70 (70-kDa cytoplasmic heat shock protein) in the Stra8-cre; Foxj2tg/tg mouse testes. Our results suggested that Foxj2 overexpression in the germ cells of mouse testes affects chaperone-mediated autophagy by upregulating LAMP2A, leading to spermatogenesis failure at the initiation of meiosis, thus resulting in male infertility. Our findings provide a new insight into the function of FOXJ2 in spermatogenesis and the significance of autophagy regulation in spermatogenesis.

A 135 mW single-frequency distributed Bragg reflector fiber laser at 1.95 μm was obtained based on a Tm:YAG ceramic-derived all-glass fiber. The fiber laser achieved an optical signal-to-noise ratio of ∼ 77 dB. Moreover, the threshold and linewidth of the single-frequency laser were measured to be 15.4 mW and 4.5 kHz, respectively. In addition, the measured relative intensity noise was less than –140 dB⋅Hz−1 at frequencies of over 10 MHz. The results show that the as-drawn Tm:YAG ceramic-derived all-glass fiber is highly promising for ∼ 2 μm single-frequency fiber laser applications.

We report a case of Aspergillus aortitis following aortic valve surgery which resulted in a large pseudoaneurysm 6 weeks post-operatively. The patient presented with lung consolidation and haemoptysis which delayed diagnosis, intervention and led to an unfavourable outcome. We encourage clinicians to consider Aspergillus aortitis as a differential post aortic valve surgery.

The discovery of chiral-induced spin selectivity (CISS) opens up the possibility to manipulate spin orientation without external magnetic fields and enables new spintronic device designs

Thickness‐dependent chemical and physical properties have gained tremendous interest since the emergence of two‐dimensional (2D) materials. Despite attractive prospects, the thickness‐controlled synthesis of ultrathin nanosheets remains an outstanding challenge. Here, a chemical vapor deposition (CVD) route is reported to controllably synthesize high‐quality PtSe2 nanosheets with tunable thickness and explore their thickness‐dependent electronic and magnetotransport properties. Raman spectroscopic studies demonstrate all Eg , A 1 g , A 2 u , and Eu modes are red shift in thicker nanosheets. Electrical measurements demonstrate the 1.7 nm thick nanosheet is a semiconductor with room temperature field‐effect mobility of 66 cm2 V−1 s−1 and on/off ratio of 106. The 2.3–3.8 nm thick nanosheets show slightly gated modulation with high field‐effect mobility up to 324 cm2 V−1 s−1 at room‐temperature. When the thickness is over 3.8 nm, the nanosheets show metallic behavior with conductivity and breakdown current density up to 6.8 × 105 S m–1 and 6.9 × 107 A cm−2, respectively. Interestingly, magnetoresistance (MR) studies reveal magnetic orders exist in this intrinsically non‐magnetic material system, as manifested by the thickness‐dependent Kondo effect, where both metal to insulator transition and negative MR appear upon cooling. Together, these studies suggest that PtSe2 is an intriguing system for both developing novel functional electronics and conducting fundamental 2D magnetism study., Ultrathin 2D PtSe2 nanosheets with various thickness are synthesized by a CVD method. The thickness dependent electrical and magnetoelectrical properties suggest that PtSe2 is an intriguing platform for both developing novel functional electronics and conducting fundamental 2D magnetism studies. The existence of magnetic order in this intrinsically non‐magnetic system will define a new class of magnetic material and stimulate further study.

In order to improve the downlink communication performance of the traditional LoRa wide area network (LoRaWAN), a LoRaWAN downlink routing control strategy based on the software defined networks (SDN) framework and the improved auto-regressive integrated moving average (ARIMA) model is proposed. The SDN architecture is used to monitor the network traffic, and the link bandwidth occupancy rate is calculated based on the monitored downlink traffic. Taking into account the impact of data volatility on the accuracy of the prediction results, the Savitzky–Golay (S–G) smoothing filter and the sliding window method are introduced for data pre-processing. Stationarity processing is carried out for the time series data in the window, and the ARIMA model is developed to predict the downlink bandwidth occupancy rate. The triangle module operator is then used to incorporate multiple path parameters to finally calculate the selectivity of different paths, and the optimal path for LoRaWAN downlink communication is then provided. Simulation and experimental results show that the root mean square error of the improved ARIMA prediction model is reduced by 87% compared with the standard ARIMA model. The proposed routing control strategy effectively reduces the service transmission delay and packet loss rate. In the LoRaWAN test environment, as the downlink load rate increases, the average link bandwidth occupancy rate of this solution increases by 12% compared with the traditional method.

Tourism consumption is not only an important means by which to improve residents’ sense of happiness but is also the main way to promote national economic development. In a traditional relational society such as China, it remains unclear how social network affects tourism consumption by households. Here, we evaluated the impact of the social network on tourism consumption by Chinese households using the data of 3254 samples from the China Family Panel Studies. The empirical results from the ordinary least square method showed that the social network promotes tourism consumption, which can be projected to increase by about 28% for every 1% increase in social network strength. This was further confirmed using the instrumental variable method to address the issue of endogenous social network formation, as well as other robustness checks. The impact of the social network on tourism consumption was heterogeneous. Compared with other residents, there were higher positive effects for high-income families, households with a head aged 35–44 years, urban families, and households in eastern China. The quantile regression results revealed that the impact of the social network was weakened with increasing tourism consumption by households. These results are crucial for policymakers, in that they could form good habits of tourism consumption and strengthen tourism market management, especially for the management of tourism negative events in the context of new media.

As a classical formula of traditional Chinese medicine (TCM), Lingguizhugan Decoction (LGZGD) has been used for treating heart failure (HF) because it has an efficiency of yang-warming and fluid-dispersing. However, the pharmacodynamic material basis of LGZGD responsible for the therapeutic benefits is not well understood.The aim of this study was to elucidate the pharmacodynamic material basis of LGZGD by an integrated approach.Following oral administration of LGZGD in mice, ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS/MS) was used to identify prototype substances. A heart failure (HF) model was established, followed by an untargeted metabolomics study to determine potential targets of LGZGD. The network pharmacology method was performed to screen substances that interacted with potential targets of LGZGD treating HF. Molecular docking technology was applied to further screen substances based on binding energy. Cell viability assays were conducted to verify pharmacodynamic effects of selected substances.In all, forty-two prototype substances were identified in the blood, urine, and fecal samples of mice. A total of fifty-five differential metabolites were identified using heart tissue untargeted metabolomics. Twenty-five substances of LGZGD were screened relating to thirty-three targets treating HF. Twenty-two substances were filtered according to their binding energy using molecular docking technology. Cell experiments revealed cinnamaldehyde, glycyrrhetinic acid, kaempferol, daidzein, caffeic acid, and catechin could significantly improve the survival rate of H9c2 cells, which might be the pharmacodynamic material basis of LGZGD.A scientific approach that integrated in vivo substances identification, metabolomics, network pharmacology, molecular docking, and cell pharmacodynamic assay has been developed to study the pharmacodynamic material basis of LGZGD in the treatment of HF.

Background This study examined the short-term and long-term mortality of community- and hospital-acquired hypernatraemia in a large cohort of general hospitalised patients, and the impact of delayed serum sodium correction in hypernatraemic patients. Methods Adult patients admitted to Mayo Clinic Rochester from 2011 to 2013 were examined. The patients with admission serum sodium ≥138 mEq/L and at least 2 serum sodium measurements during hospitalisation were included. Hypernatraemia was defined as serum sodium ≥143 mEq/L. The patients were categorised into three groups based on serum sodium at admission and during hospitalisation: (a) normal serum sodium, (b) community-acquired hypernatraemia and (c) hospital-acquired hypernatraemia. Outcomes included hospital mortality and 1-year mortality after hospital discharge amongst hospital survivors. Results Of 25 781 eligible patients, 45% had normal serum sodium, 20% had community-acquired hypernatraemia and 35% had hospital-acquired hypernatraemia. In adjusted analysis, odds ratios (ORs) of community- and hospital-acquired hypernatraemia for hospital mortality were 4.91 (95% CI 3.47-6.94) and 4.11 (95% CI 2.94-5.73), whereas hazard ratio (HR) for 1-year mortality was 1.76 (95% CI 1.56-1.98) and 1.61 (95% CI 1.45-1.79), respectively. Hospital-acquired hypernatraemia had a higher hospital mortality but not 1-year mortality than community-acquired hypernatraemia. In patients with community-acquired hypernatraemia, 36% remained hypernatraemic by hospital day 3. Hospital mortality (OR 3.01; 95% CI 2.71-5.83) and 1-year mortality (HR 1.51; 95% CI 1.26-1.81) were significantly increased in patients with persistent hypernatraemia, compared with those with serum sodium correction into optimal range of 138-142 mEq/L. Conclusion Hypernatraemia, regardless of acquisition origin, is associated with elevated short-term and long-term mortality. Hospital-acquired hypernatraemia was more common and had a higher short-term mortality than community-acquired hypernatraemia. Failure to correct hypernatraemia by hospital day 3 is associated with increased mortality.

Supervised learning based object detection frameworks demand plenty of laborious manual annotations, which may not be practical in real applications. Semi-supervised object detection (SSOD) can effectively leverage unlabeled data to improve the model performance, which is of great significance for the application of object detection models. In this paper, we revisit SSOD and propose Instant-Teaching, a completely end-to-end and effective SSOD framework, which uses instant pseudo labeling with extended weak-strong data augmentations for teaching during each training iteration. To alleviate the confirmation bias problem and improve the quality of pseudo annotations, we further propose a co-rectify scheme based on Instant-Teaching, denoted as Instant-Teaching$^*$. Extensive experiments on both MS-COCO and PASCAL VOC datasets substantiate the superiority of our framework. Specifically, our method surpasses state-of-the-art methods by 4.2 mAP on MS-COCO when using $2\%$ labeled data. Even with full supervised information of MS-COCO, the proposed method still outperforms state-of-the-art methods by about 1.0 mAP. On PASCAL VOC, we can achieve more than 5 mAP improvement by applying VOC07 as labeled data and VOC12 as unlabeled data.

Background and aims Pulmonary artery aneurysm is a rare disease. A 59-year-old Chinese female was diagnosed with idiopathic pulmonary aneurysm with pulmonary regurgitation. She had a past medical history of hemoptysis and systemic lupus erythematosus. Methods She underwent a successful total pulmonary artery and valve replacement with an Avalus-Gelweave conduit. Results The postoperative echocardiogram showed a 7 mm Hg peak gradient across the prosthetic valve. The patient's postoperative recovery was uncomplicated. Conclusions A bioprosthetic aortic valve can be used in a pulmonary position to achieve a good gradient and avoid long term anticoagulation therapy.

RNAi interference (RNAi) is an evolutionarily conserved post-transcriptional gene silencing mechanism and has been well recognized as an important antiviral immunity in eukaryotes. Numerous viruses have been shown to encode viral suppressors of RNAi (VSRs) to antagonize antiviral RNAi. Hepatitis C virus (HCV) is a medically important human pathogen that causes acute and chronic hepatitis. In this study, we screened all the nonstructural proteins of HCV and found that HCV NS2 could suppress RNAi induced either by small hairpin RNAs (shRNAs) or small interfering RNAs (siRNAs) in mammalian cells. Moreover, we demonstrated that NS2 could suppress RNAi via its direct interaction with double-stranded RNAs (dsRNAs) and siRNAs, and further identified that the cysteine 184 of NS2 is required for the RNAi suppression activity through a serial of point mutation analyses. Together, our findings uncovered that HCV NS2 can act as a VSR in vitro, thereby providing novel insights into the life cycle and virus-host interactions of HCV.

Background: Cardiorenal interconnections are complex and may in part be mediated by the extent of intravascular volume expansion. The impact of subclinical volume excess on outcomes in heart failure (HF) patients with chronic kidney disease (CKD) has not been examined previously. Objectives: To assess the impact of volume-kidney interactions on outcomes in clinically “euvolemic” chronic HF patients (NYHA class II) with coexisting CKD. Methods: Plasma volume (PV) was prospectively measured in 110 stable HF patients with different degrees of renal function using a standardized radiolabeled albumin indicator-dilution technique. To examine the interactive roles of volume expansion and biomarkers of CKD, the cohort was dichotomized by median PV and then further stratified by cohort median serum creatinine, eGFR, and BUN, and analyzed for outcomes of HF-related mortality and 1st hospitalization. Results: PV was expanded above normal in 76% of the cohort. Over 1.5 years of follow-up, sCr and BUN above and eGFR below cohort median stratified higher risks for the composite endpoint only in ambulatory HF patients with a severe degree of PV expansion (median PV expansion ≥+26%; p = 0.02). With less expansion (p = 0.578). The percentage of subjects experiencing composite outcome events was, however, comparable for both greater and lesser degrees of PV expansion in HF patients with stable clinical status. Conclusions: In clinically stable chronic HF patients with coexisting CKD, substantial subclinical PV expansion is common even when patients are considered clinically to be euvolemic, and, importantly, the extent of PV expansion impacts outcomes including early HF mortality. Better kidney function appears to mitigate the effects of excess PV expansion, while less volume expansion appears to limit the risk of worse renal function as reflected by clinical biomarkers of renal function. Thus, the extent of volume expansion impacts the capacity of standard clinical biomarkers of CKD to differentiate outcome risk in ambulatory chronic (NYHA class II) HF patients.

This study investigated the role of insulin-like growth factor-1/insulin-like growth factor-1 receptor (IGF-1/IGF-1R) in the genesis and progression of diabetic kidney disease (DKD) in a streptozotocin (STZ)-induced mouse diabetes model. We showed elevated IGF-1 expression in the DKD kidneys after 16 wk of diabetic onset. Intraperitoneal administration of IGF-1R inhibitor (glycogen synthase kinase-3β, GSK4529) from week 8 to week 16 postdiabetes induction ameliorated urinary albumin excretion and kidney histological changes due to diabetes, including amelioration of glomerulomegaly, inflammatory infiltration, and tubulointerstitial fibrosis. The GSK4529 treatment also attenuated alterations in renal tubular expression of E-cad and matrix protein fibronectin. Moreover, renal fibrosis in DKD (without treatment) was associated with Snail1 overexpression that was effectively prevented by IGF-1R inhibition. Further experiments in cultured renal epithelial cells (NRK) showed that IGF-1 silencing reproduced in vivo effects of IGF-1R inhibition with markedly attenuated Snail1 expression and near normalization of the Ecad1 and fibronectin expression pattern. Further Snail1 silencing prevented high-glucose-induced changes without affecting IGF-1 expression, consistent with Snail1 acting downstream to IGF-1. The antifibrotic effects were also shown with benazepril or insulin treatment but to a much lesser degree. In summary, in STZ-induced diabetic mice, activation of IGF-1 in diabetic kidneys induces fibrogenesis through Snail1 upregulation. The diabetes-related histological and functional changes, as well as fibrogenesis, can be attenuated by IGF-1/IGF-1R inhibition.

In this work, we study the problem of learning a single model for multiple domains. Unlike the conventional machine learning scenario where each domain can have the corresponding model, multiple domains (i.e., applications/users) may share the same machine learning model due to maintenance loads in cloud computing services. For example, a digit-recognition model should be applicable to hand-written digits, house numbers, car plates, etc. Therefore, an ideal model for cloud computing has to perform well at each applicable domain. To address this new challenge from cloud computing, we develop a framework of robust optimization over multiple domains. In lieu of minimizing the empirical risk, we aim to learn a model optimized to the adversarial distribution over multiple domains. Hence, we propose to learn the model and the adversarial distribution simultaneously with the stochastic algorithm for efficiency. Theoretically, we analyze the convergence rate for convex and non-convex models. To our best knowledge, we first study the convergence rate of learning a robust non-convex model with a practical algorithm. Furthermore, we demonstrate that the robustness of the framework and the convergence rate can be further enhanced by appropriate regularizers over the adversarial distribution. The empirical study on real-world fine-grained visual categorization and digits recognition tasks verifies the effectiveness and efficiency of the proposed framework., Comment: accepted by AAAI'19

Multimaterial fibers which integrate novel materials and/or structures into fiber configuration aim at developing multiple functionalities and high performance. Here, we demonstrate a kind of multimaterial fibers with crystalline GeSe core and K9 glass cladding by the molten core drawing method. The as-drawn fibers undergo a change in electrical conductivity when externally illuminated by an 808 nm HeNe laser. Furthermore, the Seebeck coefficient of the fibers is comparable with bulk GeSe, while the resistance is 3–4 magnitude lower than that. The results show that the GeSe core fibers have promising applications in optical switch and thermoelectric conversion field.

Background: Resistance to docetaxel is a major obstacle to effective treatment of breast cancer. Exosomal microRNAs (miRNAs) have recently been introduced in cell-to-cell transmission of chemoresistance between heterogeneous populations of tumor cells with diverse drug sensitivity. However, a systematic evaluation of the exosomal miRNA signature remains largely unclear. Method: miRNA expression profiles in exosomes from docetaxel-resistant (D/exo) and parental sensitive breast cancer cells (S/exo) were assessed using microarray. Bioinformatics analysis was performed to predict target genes of the dysregulated miRNAs and to uncover their potential roles in chemoresistance formation. Signaling pathways, gene ontology terms, transcription factors, protein-protein interactions, and hub genes were also constructed. Results: The selected exosomal miRNAs could modulate target genes responsible for MAPK, TGF-beta, Wnt, mTOR, and PI3K/Akt signaling pathways. Function enrichment analysis revealed the involvement of target genes in transcription regulation, protein phosphorylation, kinase activity, and protein binding. Enriched transcription factors including SP1, SP4, and EGR1 were obtained and a protein-protein interaction network was established. The hub genes for up-expressed and down-expressed exosomal miRNAs such as CCND1 and PTEN were identified. Conclusion: This bioinformatics study provides a comprehensive view of the function of dysregulated exosomal miRNAs, and may help us to understand exosome-mediated resistance transmission and overcome docetaxel resistance in future breast cancer therapy.

A new method, which originates from the continuous-time dynamics stability theory in the control field, is proposed for the optimal control computation. By introducing a virtual dimension, the variation time, an infinite-dimensional dynamic system that describes the variation motion of variables is derived from the optimal control problem based on the Lyapunov principle. The optimal solution is its stable equilibrium point and will be obtained in an asymptotically evolving way. Through this method, the intractable optimal control problems are transformed to the initial-value problems and they may be solved with mature ordinary differential equation numerical integration methods. Especially, the deduced dynamic system is globally stable, so any initial value may evolve to an extremal solution ultimately.

Ebola virus (EBOV) is a non-segmented, negative-sense RNA virus (NNSV) in the family Filoviridae, and is recognized as one of the most lethal pathogens in the planet. For RNA viruses, cellular or virus-encoded RNA helicases play pivotal roles in viral life cycles by remodelling viral RNA structures and/or unwinding viral dsRNA produced during replication. However, no helicase or helicase-like activity has ever been found to associate with any NNSV-encoded proteins, and it is unknown whether the replication of NNSVs requires the participation of any viral or cellular helicase. Here, we show that despite of containing no conserved NTPase/helicase motifs, EBOV VP35 possesses the NTPase and helicase-like activities that can hydrolyse all types of NTPs and unwind RNA helices in an NTP-dependent manner, respectively. Moreover, guanidine hydrochloride, an FDA-approved compound and inhibitor of certain viral helicases, inhibited the NTPase and helicase-like activities of VP35 as well as the replication/transcription of an EBOV minigenome replicon in cells, highlighting the importance of VP35 helicase-like activity during EBOV life cycle. Together, our findings provide the first demonstration of the NTPase/helicase-like activity encoded by EBOV, and would foster our understanding of EBOV and NNSVs.

Nucleation of Y-Al-O, Y-Ti-O, and Y-Zr-O enriched nano-clusters (NCs) in nano-structured ferric alloys were comparatively investigated using first-principles calculations. Formation of various possible cluster configurations was energetically evaluated with respect to individually dissolved solute atoms, to explore the preferential precipitation and growth sequence of the NCs. Key results include the following observations. During the earliest nucleation stages, Y-Zr-O NCs are always the most energy favored to form in the supersaturated bcc-Fe based matrix, followed by Y-Ti-O and Y-Al-O NCs. All the three type NCs follow the same nucleation path that begins from the O-O pairs. Y has the strongest thermodynamic driving force to precipitate with the O-O pairs. The most stable six-atomic cluster configuration is predicted as –[2Y-3O-X]–. The (O-Y)-cores may constitute the stable nuclei of larger NCs which grow consistently by attracting extra solutes available nearby.

The Dirac mode in the hollow core photonic crystal fibers (HC-PCFs) traditionally rely on high refractive index glasses with a high air-filling factor. In this paper, the Dirac mode was observed in the modified honeycomb lattice HC-PCFs, which breaks the constraint of refractive index, and can be realized in pure silica glasses for the first time. The band structure of the modified honeycomb lattice was calculated to elaborate the formation process of the Dirac point. The Dirac mode in the HC-PCFs was established at the Dirac frequency outside the bandgaps. In addition, the relationship between the Dirac frequency and the air-filling fraction and the refractive index were also analyzed. This design provides a modified honeycomb lattice HC-PCFs with substantially reduced fabrication effort and expands the application of Dirac mode in the conventional silica-based optical fiber devices.

A new kind of erbium-doped solid-core photonic bandgap fiber (ED-SC-PBGF) for amplification of orbital angular momentum (OAM) modes is proposed and investigated. The configurations of annular erbium-doped profile with special design and multi pump modes are used to amplify the signal modes evenly. Using an optimized ED-SC-PBGF pumped with l = 1 and 2 modes, differential mode gains of 0.9 dB and gain of more than 20 dB can be achieved for l = 1 and 2 OAM signal modes across the full C-band. This OAM-in-fiber amplification techniques would have potential application in ultra-long distance and high capacity OAM optical communication systems and other systems that utilize high power OAM light.

The authority of journals is usually a key indicator in guiding people to choose important journals, and the journal ranking is a common way to distinguish the journals' authority. The common ranking methods or models are based on citation data, such as the impact factor (IF), the PageRank algorithm, and the hyperlink-induced topic search algorithm. In this paper, we present a new model, named the reputation analysis of citation behavior (RACB) model, which not only considers the number of citations but also considers the reputation of inter-citation behavior. First, the model fits the function relation of the citation desire index (CDI) based on the citation data of the most reputable journal (named the top journal in the remainder of this paper). Then, the CDI values of the target journals are calculated by using the function relation of the top journal. An improved gray correlation analysis is used to describe the deviation between the CDI and the actual citation rate, named the random citation rate, indicating the inter-citation reputation value of the target journals. Finally, a case study showed that the ranking result of the RACB model has a high similarity with the IF values of 2017, which indicates that the ranking results of the RACB model that considered journal reputation evaluations are more reasonable than those of the traditional PageRank algorithm. This paper proposes a new method of journal ranking from the perspective of reputation evaluation, which can rank the journals more reasonably. It encourages researchers to cite articles more fairly in order to avoid a situation in which the low reputation of the citation behavior affects the quality of the journal that published the article.