Progress on error propagation and correction of long-range rockets in disturbing gravity field

Disturbing gravity field is becoming an important factor leading to impact error of long-range rockets. In this paper, the influence mechanism of deflection of the vertical and spatial disturbing gravity on inertial navigation and guidance system are firstly introduced, respectively. Then, the navigation error propagation methods due to disturbing gravity field are reviewed. The fast assignment models of disturbing gravity field, which are available for compensating navigation errors in engineering, are also summarized. After that, the unpowered trajectory error propagation methods and the corresponding guidance correction strategies, as well as potential directions for future efforts, are discussed.

Perspectives on hiPSC-Derived Muscle Cells as Drug Discovery Models for Muscular Dystrophies

Muscular dystrophies are a heterogeneous group of inherited diseases characterized by the progressive degeneration and weakness of skeletal muscles, leading to disability and, often, premature death. To date, no effective therapies are available to halt or reverse the pathogenic process, and meaningful treatments are urgently needed. From this perspective, it is particularly important to establish reliable in vitro models of human muscle that allow the recapitulation of disease features as well as the screening of genetic and pharmacological therapies. We herein review and discuss advances in the development of in vitro muscle models obtained from human induced pluripotent stem cells, which appear to be capable of reproducing the lack of myofiber proteins as well as other specific pathological hallmarks, such as inflammation, fibrosis, and reduced muscle regenerative potential. In addition, these platforms have been used to assess genetic correction strategies such as gene silencing, gene transfer and genome editing with clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9), as well as to evaluate novel small molecules aimed at ameliorating muscle degeneration. Furthermore, we discuss the challenges related to in vitro drug testing and provide a critical view of potential therapeutic developments to foster the future clinical translation of preclinical muscular dystrophy studies.

Exploring language learning and corrective feedback in an eTandem project

Many studies about eTandem and language learning stem from learners in Western institutions of higher education. Unfortunately, there is a lack of research investigating the telecollaboration regarding language development between learners in the East and the West. Against this backdrop, a small-scale, six-week Chinese-English eTandem project focusing on learners’ language learning processes and experiences was undertaken between nine Chinese university students learning English in China and nine British university students learning Chinese in the UK. Multiple datasets were collected from learners’ diaries, synchronous Skype communication recordings, email exchanges, interviews and a post-project survey. This paper reports the main language error types made by Chinese L2 learners of English and error correction strategies provided by eTandem partners of competent L1 English speakers, along with how Chinese participants responded to the corrections. A thorough analysis of the research data indicated three types of linguistic errors in written tasks made by Chinese L2 learners of English: grammatical, lexical and idiomatic expressions. Another finding was that, although explicit written correction was the most commonly used strategy in email exchanges, learners preferred explanations with examples. In addition to previously established gains of eTandem learning, such as authentic communication, forging friendship and promoting intercultural awareness, positive responses to competent L1 partners’ error corrections was another major benefit indicated in our data. Our study pinpoints the importance of both pre-project training of participants on error-correction strategies with examples and how to respond to partner feedback in future eTandem projects.

Preventing dataset shift from breaking machine-learning biomarkers

Machine learning brings the hope of finding new biomarkers extracted from cohorts with rich biomedical measurements. A good biomarker is one that gives reliable detection of the corresponding condition. However, biomarkers are often extracted from a cohort that differs from the target population. Such a mismatch, known as a dataset shift, can undermine the application of the biomarker to new individuals. Dataset shifts are frequent in biomedical research, e.g., because of recruitment biases. When a dataset shift occurs, standard machine-learning techniques do not suffice to extract and validate biomarkers. This article provides an overview of when and how dataset shifts break machine-learning–extracted biomarkers, as well as detection and correction strategies.

Teachers' Error Correction Strategies of Students' Writing at Senior High School in Pekanbaru

The purpose of this study was to explore error correction strategies of students’ writing used by English teachers at first grade students of Senior High School in Pekanbaru. There were three questions contained in this study. Firstly, what are strategies that English teachers used in correcting student’s writing. Secondly, how did English teachers implement the error corection strategies. Thirdly, factors influenced the implementation of the strategies. This study used qualitative descriptive research. The data were collected from English teachers and three students of each selected school (SMAN 7 Pekanbaru, SMA Plus Binabangsa Pekanbaru, and SMA Muhammadiyah 1 Pekanbaru) by using observations, interviews, and document analysis. The text used in this study was descriptive text. Result of the data analysis showed that English teachers used self-corection, peer-correction, and teacher-correction in correctiong students’ writing. In teacher-correction, they also used one-to-one correction and correction code to improve students’ writing. To implement error correction strategies, English teachers used familiar theme, tried to improve students’ vocabularies, and applied the process of writing. Then, there were some factors influenced English teacher implement error correction strategies. Those factors mostly because students had insufficient vocabularies and the other factors was English teachers did not have enough time in correcting students’ writing. In conclusion, these findings implied the teachers should try to use an effective error correction strategies, like one-to-one correction strategy in order to get good results for the students.