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With the ongoing progress of geological survey work and the continuous accumulation of geological data, extracting accurate information from massive geological data has become increasingly difficult. To fully mine and utilize geological data, this study proposes a geological news named entity recognition (GNNER) method based on the bidirectional encoder representations from transformers (BERT) pre-trained language model. This solves the problems of traditional word vectors that are difficult to represent context semantics and the single extraction effect and can also help construct the knowledge graphs of geological news. First, the method uses the BERT pre-training model to embed words in the geological news text, and the dynamically obtained word vector is used as the model’s input. Second, the word vector is sent to a bidirectional long short-term memory model for further training to obtain contextual features. Finally, the corresponding six entity types are extracted using conditional random field sequence decoding. Through experiments on the constructed Chinese geological news dataset, the average F1 score identified by the model is 0.839. The experimental results show that the model can better identify news entities in geological news.

Monocyte-derived DCs (moDCs) have been implicated in the pathogenesis of autoimmunity, but the molecular pathways determining the differentiation potential of these cells remain unclear. Here, we report that microRNA-148a ( miR-148a ) serves as a critical regulator for moDC differentiation. First, miR-148a deficiency impaired the moDC development in vitro and in vivo. A mechanism study showed that MAFB, a transcription factor that hampers moDC differentiation, was a direct target of miR-148a . In addition, a promoter study identified that miR-148a could be transcriptionally induced by PU.1, which is crucial for moDC generation. miR-148a ablation eliminated the inhibition of PU.1 on MAFB. Furthermore, we found that miR-148a increased in monocytes from patients with psoriasis, and miR-148a deficiency or intradermal injection of antagomir-148a immensely alleviated the development of psoriasis-like symptoms in a psoriasis-like mouse model. Therefore, these results identify a pivotal role for the PU.1-miR-148a-MAFB circuit in moDC differentiation and suggest a potential therapeutic avenue for autoimmunity.

Socio-scientific issues have become increasingly important in Science-Technology-Society (STS) education as a means to make science learning more relevant to students' lives. This study used the e-waste issue as a context to investigate two aspects of socio-scientific decision-making: (1) the relationship between the nature of science (NOS) conceptualizations and decision-making; and (2) moral concerns involved in the process of decision-making. This study contributes to the field of socio-scientific issue research and STS education in the following ways. First, it is the first study that performed meta-analysis to seek the relationship between the NOS understanding and decision-making. This study concludes that valuable NOS conceptualizations that are highly related to the socio-scientific issue under investigation, rather than general NOS understanding, exert statistically significant influences on decision-making. Second, this study empirically examined the Multiple Responses Model (MRM), which enables the transfer of qualitative NOS responses into quantitative data, and hence, inferential statistics. The current study justifies the significance of unidimensionality to the application of the MRM. It addresses the limitations associated with the MRM and provides implications for future use of the MRM in other contexts. Finally, the study explores the role of moral concerns in socio-scientific decision-making. Eight participants engaged in interviews that were designed to elicit their reactions and feelings regarding the issue of exporting e-waste to poor countries. Qualitative analyses demonstrated that moral considerations were significant influences on decision-making. In addition, participants' action responses revealed that they were motivated to take action to help the environment. The study has implications for socio-scientific issue studies in other contexts and for teacher education programs that use socio-scientific issues to advance teachers' reasoning and discourse skills.

The metazoan meiofauna in the Chukchi Sea were collected from seven shallow water stations （depths rang- ing 46 to 52 m） and five deep sea stations （depths ranging between 393 and 2 300 m） during the 4th Chinese National Arctic Research Expedition in 2010. The results showed that abundance of meiofauna was higher in shallow water sediments （average of 2445 ind./（10 cm2）） than in deep sea sediments （407.06 ind./（10 cm2））. A UNIANOVA test for difference between the two different regions was highly significant （F=10h 15, p〈0.Ol）. Nematodes were numerically dominant, representing （96.6±4.6）% of the total meiofaunal abundance at the shallow water stations and （98.90±1.42）% at deep sea stations. The number of higher taxonomic groups and abundance of meiofauna were higher at Stas CC1, CC4, and R06 near the Bering Strait and the continent, than at the rest of the shallow water and deep sea stations. The primary factors causing the differences were concentrations of nutrients P and Si of bottom seawater （R=0.831, p〈0.003）, followed by depth （R=-0.655, p〈0.05） and sand fractions of sediments （R=0.632, p 〈0.05）. The numbers of meiofauna on the 65 lam and 32 llm sieves were significantly higher than those on the rest of the screens. Differences in numbers of meiofauna retained on screens with different mesh openings were highly significant among all sampling stations （F=31.60, p〈0.01）. The highest numbers of individuals on screens with 32 μm mesh openings were found at deep sea stations. The number of meiofauna in the top 6-1, 1-2, and 2-4 cm segments constituted 84.4% of the total and was significantly higher than those in the bottom 4-6 and 6-10 cm segments （F=15, p〈0.01）.

A new free-living marine nematode species Hopperia sinensis sp. nov. from mangrove forests of Fujian Province, China, is identified and illustrated. Hopperia sinensis sp. nov. is characterized by its cephalic setae 2.4–2.8 μm long or 17%–20% head diameter, and amphids of 2.25–2.5 turns. Lateral differentiation appears with larger, more irregularly distributed dots behind 3–5 transverse rows of dots posterior to amphid. Buccal cavity is consisted of a shallow and weakly sclerotized cup-shaped portion with strongly sclerotized walls of 18–21 μm deep. There are three sclerotized and size-equally pointed teeth at the junction between the two parts. Spicules of 41–45 μm long are slightly curved with broadband velum and central strips at the proximal end. The gubernacula, with apparent lateral guiding pieces, are formed by one central tubular piece that is weakly sclerotized with 11–16 μm long dorso-caudally directed apophyses. There are 13–14 fine tubular precloacal supplements. Conico-cylindrical tail gradually tapers till pointed tail tip. Female is similar to male, but have a longer body and tail. Ovaries are opposed and outstretched, with anterior ovary to the left and posterior ovary to the right of the intestine. A pictorial key to all the valid known species in genus Hopperia is given.

A vision-based scheme for object recognition and transport with a mobile robot is proposed in this paper. First, camera calibration is experimentally performed with Zhenyou Zhang’s method, and a distance measurement method with the monocular camera is presented and tested. Second, Kalman filtering algorithm is used to predict the movement of a target with HSI model as the input and the seed filling algorithm as the image segmentation approach. Finally, the motion control of the pan-tilt camera and mobile robot is designed to fulfill the tracking and transport task. The experiment results demonstrate the robust object recognition and fast tracking capabilities of the proposed scheme.

We consider the semilinear heat equation with globally Lipschitz non-linearity involving gradient terms in a bounded domain of ℝn. In this paper, we obtain explicit bounds of the cost of approximate controllability, i.e., of the minimal norm of a control needed to control the system approximately. The methods we used combine global Carleman estimates, the variational approach to approximate controllability and Schauder’s fixed point theorem.

背景：適當的流程改善可以有效提升醫療照護品質亦可增加病人滿意度。現況調查發現照護流程不完善導致個管師術前收案率低、病人入住時間過長、術前相關衛教認知不足、常規手術取消率高。目的：藉由病人流概念檢視整體照護流程進行改善及對策擬定，提升照護品質。解決方法：為提供完善照護流程，故擬定因應對策：（1）制定骨科個管師標準收案流程，以提高術前收案率；（2）建置關節置換專區將病人集中管理照護，以降低病人入住病室時間；（3）製作膝望護照、拍攝術前須知及居家環境準備影片和拍攝殺菌澡衛教影片，以提升病人術前衛教遵從性及降低手術排程取消率。結果：經改善後，個管師術前收案完成率由27.8%提升至84.6%；入住病室時間由73分鐘縮短至41分鐘；衛教遵從率由83.0%提升至100%；手術排程取消率由11.1%降至0%。結論：本專案運用病人流概念檢視人工膝關節置換術照護流程，藉由專案改善措施落實照護流程標準化，進而提升整體醫療照護品質。

Rotating machinery is widely applied in various types of industrial applications. As a promising field for reliability of modern industrial systems, early fault diagnosis (EFD) techniques have attracted increasing attention from both academia and industry. EFD is critical to provide appropriate information for taking necessary maintenance actions and thereby prevent severe failures and reduce financial losses. A massive amounts of research work has been conducted in last two decades to develop EFD techniques. This paper reviews and summarizes the research works on EFD of gears, rotors, and bearings. The main purpose of this paper is to serve as a guidemap for researchers in the field of early fault diagnosis. After a brief introduction of early fault diagnosis techniques, the applications of EFD of rotating machine are reviewed in two aspects: fault frequency-based methods and artificial intelligence-based methods. Finally, a summary and some new research prospects are discussed.

Nitric oxide (NO) has been implicated in a variety of physiological and pathological processes. Monitoring cellular levels of NO requires a sensor to feature adequate sensitivity, transient recording ability and biocompatibility. Herein we report a single-atom catalysts (SACs)-based electrochemical sensor for the detection of NO in live cellular environment. The system employs nickel single atoms anchored on N-doped hollow carbon spheres (Ni SACs/N-C) that act as an excellent catalyst for electrochemical oxidation of NO. Notably, Ni SACs/N-C shows superior electrocatalytic performance to the commonly used Ni based nanomaterials, attributing from the greatly reduced Gibbs free energy that are required for Ni SACs/N-C in activating NO oxidation. Moreover, Ni SACs-based flexible and stretchable sensor shows high biocompatibility and low nanomolar sensitivity, enabling the real-time monitoring of NO release from cells upon drug and stretch stimulation. Our results demonstrate a promising means of using SACs for electrochemical sensing applications. The monitoring of nitric oxide is important to a number of disease states and biomedical applications. Here, the authors report on a single nickel atom catalyst based sensor for detecting nitric oxide production from cells.