Search

Purpose This study aims to reveal the topic structure and evolutionary trends of health informatics research in library and information science. Design/methodology/approach Using publications in Web of Science core collection, this study combines informetrics and content analysis to reveal the topic structure and evolutionary trends of health informatics research in library and information science. The analyses are conducted by Pajek, VOSviewer and Gephi. Findings The health informatics research in library and information science can be divided into five subcommunities: health information needs and seeking behavior, application of bibliometrics in medicine, health information literacy, health information in social media and electronic health records. Research on health information literacy and health information in social media is the core of research. Most topics had a clear and continuous evolutionary venation. In the future, health information literacy and health information in social media will tend to be the mainstream. There is room for systematic development of research on health information needs and seeking behavior. Originality/value To the best of the authors’ knowledge, this is the first study to analyze the topic structure and evolutionary trends of health informatics research based on the perspective of library and information science. This study helps identify the concerns and contributions of library and information science to health informatics research and provides compelling evidence for researchers to understand the current state of research.

Background. Hypoxia is regarded as a key factor in promoting the occurrence and development of ovarian cancer. In ovarian cancer, hypoxia promotes cell proliferation, epithelial to mesenchymal transformation, invasion, and metastasis. Long non-coding RNAs (lncRNAs) are extensively involved in the regulation of many cellular mechanisms, i.e., gene expression, cell growth, and cell cycle. Materials and Methods. In our study, a hypoxia-related lncRNA prediction model was established by applying LASSO-penalized Cox regression analysis in public databases. Patients with ovarian cancer were divided into two groups based on the median risk score. The survival rate was analyzed in the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets, and the mechanisms were investigated. Results. Through the prognostic analysis of DElncRNAs (differentially expressed long non-coding RNAs), a total of 5 lncRNAs were found to be closely associated with OS (overall survival) in ovarian cancer patients. It was evaluated through Kaplan–Meier analysis that low-risk patients can live longer than high-risk patients (TCGA: p = 1.302 e − 04 ; ICGC: 1.501e − 03). The distribution of risk scores and OS status revealed that higher risk score will lead to lower OS. It was evaluated that low-risk group had higher immune score ( p = 0.0064 ) and lower stromal score ( p = 0.00023 ). Conclusion. It was concluded that a hypoxia-related lncRNA model can be used to predict the prognosis of ovarian cancer. Our designed model is more accurate in terms of age, grade, and stage when predicting the overall survival of the patients of ovarian cancer.

A total of 58 (eight known and 50 new) species of the subgenus Stegana (Steganina) from China were surveyed and (re)described: S. (S.) bacilla Chen & Aotsuka, 2004, S. (S.) belokobylskiji Sidorenko, 1997, S. (S.) hirticeps Wang, Gao, & Chen, 2013, S. (S.) izu Sidorenko, 1997, S. (S.) kanmiyai Okada & Sidorenko, 1992, S. (S.) masanoritodai Okada & Sidorenko, 1992, S. (S.) maymyo Sidorenko, 1997, stat. rev., S. (S.) nigripes Zhang & Chen, 2015, S. (S.) alafoliacea Zhang & Chen, sp. nov., S. (S.) baoxing Li & Chen, sp. nov., S. (S.) bibarbata Li & Chen, sp. nov., S. (S.) bimai Cui & Chen, sp. nov., S. (S.) cinereipecta Zhang & Chen, sp. nov., S. (S.) cardua Cui & Chen, sp. nov., S. (S.) cordhirsuta Wang & Chen, sp. nov., S. (S.) cornuta Li & Chen, sp. nov., S. (S.) cucullata Li & Chen, sp. nov., S. (S.) cultella Cui & Chen, sp. nov., S. (S.) curvitabulata Cui & Chen, sp. nov., S. (S.) daiya Cui & Chen, sp. nov., S. (S.) dendrophila Zhang & Chen, sp. nov., S. (S.) flabella Li & Chen, sp. nov., S. (S.) flavipes Li & Chen, sp. nov., S. (S.) formosa Zhang & Chen, sp. nov., S. (S.) fusca Li & Chen, sp. nov., S. (S.) fuscipes Li & Chen, sp. nov., S. (S.) glaucopalpula Cui & Chen, sp. nov., S. (S.) haba Zhang & Chen, sp. nov., S. (S.) hirticlavata Cui & Chen, sp. nov., S. (S.) iaspidea Zhang & Chen, sp. nov., S. (S.) idiasta Cui & Chen, sp. nov., S. (S.) kanda Cui & Chen, sp. nov., S. (S.) labao Li & Chen, sp. nov., S. (S.) lancang Li & Chen, sp. nov., S. (S.) latifoliacea Wang & Chen, sp. nov., S. (S.) liusanjieae Li & Chen, sp. nov., S. (S.) magniflava Cui & Chen, sp. nov., S. (S.) mailangang Li & Chen, sp. nov., S. (S.) marenubila Cui & Chen, sp. nov., S. (S.) menghai Zhang & Chen, sp. nov., S. (S.) menglian Li & Chen, sp. nov., S. (S.) minutiflava Li & Chen, sp. nov., S. (S.) multiprocera Li & Chen, sp. nov., S. (S.) nayun Li & Chen, sp. nov., S. (S.) nigridentata Wang & Chen, sp. nov., S. (S.) nigripalpula Cui & Chen, sp. nov., S. (S.) otphylla Cui & Chen, sp. nov., S. (S.) radiciflava Zhang & Chen, sp. nov., S. (S.) rava Cui & Chen, sp. nov., S. (S.) sciophila Li & Chen, sp. nov., S. (S.) septencolorata Li & Chen, sp. nov., S. (S.) serrata Zhang & Chen, sp. nov., S. (S.) silvestrella Zhang & Chen, sp. nov., S. (S.) simola Cui & Chen, sp. nov., S. (S.) yani Li & Chen, sp. nov., S. (S.) yixiang Zhang & Chen, sp. nov., S. (S.) zaduo Cui & Chen, sp. nov., and S. (S.) zhuoma Cui & Chen, sp. nov. We also provided a complete list of Chinese Steganina species together with their geographical distributions. In addition, the majority of currently available DNA barcode (partial sequence of the mitochondrial cytochrome c oxidase subunit I (COI) gene) sequences of this subgenus (435 sequences of 102 spp.) were employed in a molecular analysis for species delimitation. Taken together, morphology- and molecular-based species delimitation results reached a consensus for an overwhelming majority of these Steganina species (98 of 102 spp.).

Companies in platform-based business markets have widely embraced freemium business models, in which profit is primarily determined by a minority of paying customers. However, the key challenge of these models is transitioning participants from free users to paying consumers. To encourage paid consumption, companies often rely on product differentiation such as providing consumers who pay for products or services with enhanced features. Product differentiation can be broadly classified into two categories: taste differentiation and quality differentiation. The authors demonstrate that extending the magnitude of taste differentiation is an effective differentiation strategy. Quality differentiation, however, is a double-edged sword and should be used with care. Increasing product differentiation leads to greater perceived value of the service, but undermines fairness perceptions.

Deep neural networks (DNNs) have been widely adopted in many fields, and they greatly promote the Internet of Health Things (IoHT) systems by mining health-related information. However, recent studies have shown the serious threat to DNN-based systems posed by adversarial attacks, which has raised widespread concerns. Attackers maliciously craft adversarial examples (AEs) and blend them into the normal examples (NEs) to fool the DNN models, which seriously affects the analysis results of the IoHT systems. Text data is a common form in such systems, such as the patients’ medical records and prescriptions, and we study the security concerns of the DNNs for textural analysis. As identifying and correcting AEs in discrete textual representations is extremely challenging, the available detection techniques are still limited in performance and generalizability, especially in IoHT systems. In this paper, we propose an efficient and structure-free adversarial detection method, which detects AEs even in attack-unknown and model-agnostic circumstances. We reveal that sensitivity inconsistency prevails between AEs and NEs, leading them to react differently when important words in the text are perturbed. This discovery motivates us to design an adversarial detector based on adversarial features, which are extracted based on sensitivity inconsistency. Since the proposed detector is structure-free, it can be directly deployed in off-the-shelf applications without modifying the target models. Compared to the state-of-the-art detection methods, our proposed method improves adversarial detection performance, with an adversarial recall of up to 99.7% and an F1-score of up to 97.8%. In addition, extensive experiments have shown that our method achieves superior generalizability as it can be generalized across different attackers, models, and tasks.

The electronic structure and optical properties of the two stable CsPbCl3 main phases (P4/mbm, Amm2) and the six most stable anion substitution structures under stress.

A Ni–Fe based perovskite oxide catalyzes the oxygen evolution reaction (OER), coupled with changes in local composition and structure identified by virtue of an epitaxial thin film geometry.

The genus Streptomyces comprises the most important chitin decomposers in soil and revealing their chitinolytic machinery is beneficial for the conversion of chitinous wastes. Streptomyces sp. SCUT-3, a chitin-hydrolyzing and a robust feather-degrading bacterium, was isolated previously. The potential chitin-degrading enzymes produced by SCUT-3 were analyzed in the present study. Among these enzymes, three chitinases were successfully expressed in Pichia pastoris at comparatively high yields of 4.8 U/mL (SsExoChi18A), 11.2 U/mL (SsExoChi18B), and 17.8 U/mL (SsEndoChi19). Conserved motifs and constructive 3D structures of these three exo- and endochitinases were also analyzed. These chitinases hydrolyzed colloidal chitin to chitin oligomers. SsExoChi18A showed apparent synergic effects with SsEndoChi19 in colloidal chitin and shrimp shell hydrolysis, with an improvement of 29.3 % and 124.9 %, respectively. Compared with SsExoChi18B and SsEndoChi19, SsExoChi18A exhibited the strongest antifungal effects against four plant pathogens by inhibiting mycelial growth and spore germination. This study provided good candidates for chitinous waste-processing enzymes and antifungal biocontrol agents. These synergic chitin-degrading enzymes of SCUT-3 are good targets for its further genetical modification to construct super chitinous waste-degrading bacteria with strong abilities to hydrolyze both protein and chitin, thereby providing a direction for the future path of the chitinous waste recycling industry.

When the volume fraction of hydrogen is below 20% and above 25%, aluminium and nickel wires inhibit and promote the hydrogen explosion.

Tumor recurrence caused by metastasis is a major cause of death for patients.

Antimonide-based ternary III-V nanowires (NWs) provide a tunable bandgap over a wide range, and the GaAsSb material system has prospective applications in the 1.3-1.55 μm spectral range of optical communications. In this paper, GaAs/Ga(As)Sb/GaAs single quantum well (SQW) NWs were grown on Si(111) substrates by molecular beam epitaxy (MBE). In addition, the morphologies and tunable wavelengths of the GaAs/Ga(As)Sb/GaAs SQWs were adjusted by interrupting the Ga droplets and changing the growth temperatures and V/III ratios. The four morphologies of the GaAs/Ga(As)Sb/GaAs SQW NWs were observed by scanning electron microscopy (SEM). The microscale lattice structure related to the incorporation of Sb in GaAs/Ga(As)Sb/GaAs SQWs was studied by Raman spectroscopy. The crystal quality of the GaAs/Ga(As)Sb/GaAs SQW NWs was researched by X-ray diffraction (XRD) and transmission electron microscopy (TEM). In addition, the optical properties of the GaAs/Ga(As)Sb/GaAs SQWs were investigated by photoluminescence (PL) spectroscopy. The PL spectra showed the peak emission wavelength range of ∼818 nm (GaAs) to ∼1628 nm (GaSb) at 10 K. This study provides an approach to enhance the effective control of the morphology, structure and wavelength of quantum well or core-shell NWs.

Study of the double effect of EA with different densities on an ethylene explosion explained by experiment and simulation for the first time.

Al2O3 particles are introduced into a La3Si6N11:Ce3+ PiG film to form a composite color converter for realizing high-brightness laser lighting.

Multi-Panda Tracking (MPT) is a video-based tracking task for panda individuals, which is conducive to the observation and measurement of distribution and status of pandas. Different from tracking general objects such as pedestrians and vehicles, MPT is extremely challenging due to the indistinguishable appearances and diversified postures of pandas. In this case, existing tracking methods cannot appropriately tackle with the excessive occlusion between different panda individuals, hence suffering from identity switch, missing and inaccurate detections. To address these problems, we propose a simple yet effective MPT framework in the tracking-by-detection paradigm, which is benefited both from a short-term prediction filtering module and a discriminative feature learning network. In particular, the short-term prediction filtering module introduces similarity learning to enhance the temporal consistency among detections, which is capable of supplementing the missing detections and discarding false positive detections. Besides, the discriminative feature learning network leverages a two-branch network to learn both local and global discriminative features, so as to distinguish different panda individuals with a very similar appearance with a subtle difference. To evaluate the proposed method, we annotate a large-scale MPT dataset, named PANDA2021, which is particularly challenging due to the similar appearance and dramatic occlusion between panda individuals. Experiments on PANDA2021 demonstrate that the proposed MPT method significantly outperforms the competing methods. Moreover, experimental results on pedestrian tracking dataset MOT16 further demonstrate that the proposed MPT method achieves comparative performance with competing methods.