A transdisciplinary approach to examining and confidence- boosting the experiences of Chinese teachers of Chinese in Finland

With the current rise of China as a political, cultural, and economic superpower, Chinese as a foreign and second language has gained popularity worldwide. Finland is also responding to this global wave, as is reflected by the increasing number of Chinese courses in formal and informal settings in the Nordic country. Yet not all actors involved in the promotion of Chinese seem to experience instruction in the language in the same way. This study investigates how Chinese teachers of the Chinese language, who represent the majority of the ‘workforce’ for instruction in this language in Finland, perceive Chinese language education and their role in it. We argue that there is a need for a paradigm shift in evaluating the teachers’ experiences. Specifically, we support a move away from perspectives that see culture as static and identity as singular. Using the “analysis of multivoiceness,” which was developed from dialogism (Aveling, Gillespie, & Cornish, 2014), the authors of this article identify a number of positions assumed/taken up by the teachers and others in their discourses. Finally, we propose a critical intercultural approach to Chinese teacher education or professional development based on transdisciplinarity, which relies on problem-solving that recognizes an important triad: educational contexts—teachers’ experiences—society (McGregor & Volckmann, 2011).Peer reviewe

Voiceless Teachers in Education : Intercultural Experiences and Perceptions of Chinese Immigrant Teachers in Finland

During the past decade, the demographic changes brought about by international mobility have diversified education in Finland. One type of diversification is the increasing number of teachers of immigrant background. However, how immigrant teachers experience the Finnish educational system has not yet been amongst the topics of full-scale academic research (Nishimura-Sahi, Wallin & Eskola, 2017). There is an emerging need to address this research gap by giving voice to immigrant teachers who are rarely heard. This doctoral thesis sets out to investigate the experiences and perceptions of immigrant teachers working in Finland, taking Chinese immigrant teachers of the Chinese language as a case study. The findings of this PhD study are presented in the form of three academic publications and an extended summary. The first article looks into the social discourses on Finnish education in general and Chinese language education in particular, that could potentially influence immigrant Chinese teachers’ presumptions and expectations about being a Chinese language teacher in Finland. The first article forms the background of the doctoral study. The second article and the third article examine the intercultural experiences and the perceptions of Chinese immigrant teachers in Finland. The second article reveals the multiple facets of immigrant teachers’ experiences which are connected to how the teachers perceive their positions in Finland. The third article examines the teachers’ cross-national comparisons on Chinese language education, which also reveal how the teachers perceive their positions in comparison with colleagues working in another context. The findings in all of the three publications suggest a strong link between experiences, perceptions and intercultural imaginations, as well as constructed discourses. The findings of this doctoral study lead to both theoretical and practical implications. Theoretically, a new model for understanding the experiences of immigrant teachers was developed. This model takes into account the multiple facets of immigrant teachers’ experiences, the power relations in the context under review and their influence on intercultural imagination and discourses. Practically, the findings suggested that 1) stakeholders should listen to the needs and concerns of immigrant teachers and provide equal treatment to all kinds of teachers; 2) regular continued professional development training plays a very important role in helping teachers to update their subject knowledge and teaching skills, but also in providing opportunities for all types of teachers to learn together; 3) intercultural teacher education and training should also help the teachers to become aware of the ongoing discourses, and reflect critically on their own cultural assumptions.Viime vuosikymmenen aikana lisääntynyt kansainvälinen liikkuvuus on vaikuttanut väestörakenteen muutokseen, joka puolestaan on vaikuttanut koulutuksen moninaistumiseen. Yksi huomattava muutos on lisääntynyt maahanmuuttajataustaisten opettajien määrä. Aikaisempi tutkimus maahanmuuttajataustaisista opettajista ja heidän kokemuksistaan suomalaisessa koulutusjärjestelmässä on vähäistä (Nishimura-Sahi, Wallin and Eskola, 2017). Erityisen tärkeää on antaa näille opettajille mahdollisuus kertoa näistä kokemuksista ja tuoda esille heidän käsityksiään suomalaisesta koulutusjärjestelmästä. Tämä väitöskirjatutkimus on tapaustutkimus Suomessa työskentelevistä maahanmuttajataustaisista opettajista, esimerkkinä kiinalaiset opettajat. Ensimmäisessä artikkelissa tarkastellaan keskustelua suomalaisesta koulutusjärjestelmästä, erityisesti kiinan kielen opetuksen näkökulmasta. Tämä sosiaalinen diskurssi voi mahdollisesti vaikuttaa maahanmuuttajataustaisten kiinalaisten opettajien oletuksiin ja käsityksiin siitä, millainen kiinan kielen opettajan tulee olla Suomessa. Ensimmäinen artikkeli on johdatus väitöskirjatyöhön. Toisessa ja kolmannessa artikkelissa tarkastellaan Suomessa työskentelevien kiinalaisten maahanmuuttajaopettajien kokemuksia ja käsityksiä opettamisesta Suomessa. Toinen artikkeli tuo esille maahanmuuttajaopettajien moninaisia kokemuksia, jotka liittyvät siihen, miten opettajat kokevat oman asemansa suomalaisessa työelämässä. Kolmannessa artikkelissa tarkastellaan opettajien kansallisia rajoja ylittäviä kokemuksia kiinan kielen opettamisesta ja, kuinka nämä opettajat arvioivat omaa asemaansa Suomessa verrattuna kollegoihin, jotka työskentelvät eri kontekstissa. Kaikkien kolmen yksittäisten tutkimusten (artikkelien) tulokset viittaavat vahvaan yhteyteen kokemusten, käsitysten ja kulttuurienvälisten mielikuvien sekä niiden ympärille muodostuneiden diskurssien välillä. Tämä tutkimus on merkittävä sekä teoreettisesta että käytännän työn kehittämisen näkökulmasta. Tutkimuksen pohjalta on luotu malli, joka auttaa maahanmuuttajataustaisten opettajien kokemusten analysoinnissa. Tämä malli ottaa huomioon maahanmuuttajaopettajien moninaiset kokemukset, valtasuhteet, jotka synnyttävät näitä diskursseja ja niiden vaikutukset interkulttuuristen mielikuvien rakentumiselle. Tutkimuksen tulokset osoittavat, että 1) eri sidosryhmien tulisi kuunnella maahanmuuttajaopettajien kokemuksia ja huolenaiheita sekä kohdella tasa-arvoisesti eri taustoista tulevia opettajia; 2) säännöllisellä opettajijen täydennyskoulutuksella on erittäin tärkeä rooli, jotta opettajat pystyvät päivittämään sekä kontekstiosaamista että opetustaitojaan, mutta myös tarjota mahdollisuuksia erilaisille opettajille oppia yhdessä; 3) Interkulttuurisen opettajankoulutuksen tulisi myös auttaa opettajia tunnistamaan meneillään olevia diskursseja ja pohtimaan kriittisesti omia kulttuurisia oletuksiaan

“They have it better there” : Chinese Migrant Teachers’ Beliefs, Imaginaries and Ideologies in Cross-national Comparisons

This paper was written in response to a growing need to address the perceptions and experiences of teachers of migrant background. Based on a critical intercultural theoretical perspective, which moves beyond typical ‘culture shock’ and ‘adaptation’ models of understanding and explaining migrants’ experiences, this paper makes use of the concepts of teacher beliefs, ideologies and imaginaries (Holliday, 2010) in considering how Finland-based Chinese migrant teachers perceive the position of being teachers of Chinese in Finland and Australia. Analysis of data from group discussions during a teacher training workshop indicates that these teachers constructed a “utopia” (Australia) and “dystopia” (Finland) Chinese language teaching, and reveals that multiple factors have influenced these migrant teachers’ perceptions and experiences. Findings provide information for e.g. teacher educators and stakeholders to better understand and support migrant teachers from various linguistic and cultural backgrounds.Peer reviewe

How ChatGPT is Solving Vulnerability Management Problem

Recently, ChatGPT has attracted great attention from the code analysis domain. Prior works show that ChatGPT has the capabilities of processing foundational code analysis tasks, such as abstract syntax tree generation, which indicates the potential of using ChatGPT to comprehend code syntax and static behaviors. However, it is unclear whether ChatGPT can complete more complicated real-world vulnerability management tasks, such as the prediction of security relevance and patch correctness, which require an all-encompassing understanding of various aspects, including code syntax, program semantics, and related manual comments. In this paper, we explore ChatGPT's capabilities on 6 tasks involving the complete vulnerability management process with a large-scale dataset containing 78,445 samples. For each task, we compare ChatGPT against SOTA approaches, investigate the impact of different prompts, and explore the difficulties. The results suggest promising potential in leveraging ChatGPT to assist vulnerability management. One notable example is ChatGPT's proficiency in tasks like generating titles for software bug reports. Furthermore, our findings reveal the difficulties encountered by ChatGPT and shed light on promising future directions. For instance, directly providing random demonstration examples in the prompt cannot consistently guarantee good performance in vulnerability management. By contrast, leveraging ChatGPT in a self-heuristic way -- extracting expertise from demonstration examples itself and integrating the extracted expertise in the prompt is a promising research direction. Besides, ChatGPT may misunderstand and misuse the information in the prompt. Consequently, effectively guiding ChatGPT to focus on helpful information rather than the irrelevant content is still an open problem

Synergistic strategy with hyperthermia therapy based immunotherapy and engineered exosomes−liposomes targeted chemotherapy prevents tumor recurrence and metastasis in advanced breast cancer

Advanced breast cancer with recurrent and distal organ metastasis is aggressive and incurable. The current existing treatment strategies for advanced breast cancer are difficult to achieve synergistic treatment of recurrent tumors and distant metastasis, resulting in poor clinical outcomes. Herein, a synergistic therapy strategy composed of biomimetic tumor-derived exosomes (TEX)-Liposome-paclitaxel (PTX) with lung homing properties and gold nanorods (GNR)-PEG, was designed, respectively. GNR-PEG, with well biocompatibility, cured recurrent tumors effectively by thermal ablation under the in situ NIR irradiation. Meanwhile, GNR-mediated thermal ablation activated the adaptive antitumor immune response, significantly increased the level of CD8+ T cells in lungs and the concentration of serum cytokines (tumor necrosis factor-α, interlekin-6, and interferon-γ). Subsequently, TEX-Liposome-PTX preferentially accumulated in lung tissues due to autologous tumor-derived TEX with inherent specific affinity to lung, resulting in a better therapeutic effect on lung metastasis tumors with the assistance of adaptive immunotherapy triggered by GNR in vivo. The enhanced therapeutic efficacy in advanced breast cancer was a combination of thermal ablation, adaptive antitumor immunotherapy, and targeted PTX chemotherapy. Hence, the synergistic strategy based on GNR and TEX-Liposome provides selectivity to clinical treatment of advanced breast cancer with recurrent and metastasis

Monitoring activity at the Daguangbao mega-landslide (China) using Sentinel-1 TOPS time series interferometry

The Daguangbao mega-landslide (China), induced by the 2008 Wenchuan earthquake (Mw = 7.9), with an area of approximately 8 km2, is one of the largest landslides in the world. Experts predicted that the potential risk and instability of the landslide might remain for many decades, or even longer. Monitoring the activity of such a large landslide is hence critical. Terrain Observation by Progressive Scans (TOPS) mode from the Sentinel-1 satellite provides us with up-to-date high-quality Synthetic Aperture Radar (SAR) images over a wide ground coverage (250 × 250 km), enabling full exploitation of various InSAR applications. However, the TOPS mode introduces azimuth-dependent Doppler variations to radar signals, which requires an additional processing step especially for SAR interferometry. Sentinel-1 TOPS data have been widely applied to earthquakes, but the performance of TOPS data-based time series analysis requires further exploitation. In this study, Sentinel-1 TOPS data were employed to investigate landslide post-seismic activities for the first time. To deal with the azimuth-dependent Doppler variations, a processing chain of TOPS time series interferometry approach was developed. Since the Daguangbao landslide is as a result of the collapse of a whole mountain caused by the 2008 Mw 7.9 Wenchuan earthquake, the existing Digital Elevation Models (DEMs, e.g. SRTM and ASTER) exhibit height differences of up to approximately 500 m. Tandem-X images acquired after the earthquake were used to generate a high resolution post-seismic DEM. The high gradient topographic errors of the SRTM DEM (i.e. the differences between the pre-seismic SRTM and the actual post-seismic elevation), together with low coherence in mountainous areas make it difficult to derive a precise DEM using the traditional InSAR processing procedure. A re-flattening iterative method was hence developed to generate a precise TanDEM-X DEM in this study. The volume of the coseismic Daguangbao landslide was estimated to be of 1.189 ± 0.110 × 109 m3 by comparing the postseismic Tandem-X DEM with the preseismic SRTM DEM, which is consistent with the engineering geological survey result. The time-series results from Sentinel-1 show that some sectors of the Daguangbao landslide are still active (and displaying four sliding zones) and exhibiting a maximum displacement rate of 8 cm/year, even eight years after the Wenchuan earthquake. The good performance of TOPS in this time series analysis indicates that up-to-date high-quality TOPS data with spatiotemporal baselines offer significant potential in terms of future InSAR applications.This work was supported by the National Natural Science Foundation of China under Grant No. 41474003. The research stay of Dr. Tomás at Newcastle University was funded by the Ministry of Education, Culture and Sport within the framework of Project PRX14/00100. Additional funding was obtained from the Spanish Government under projects TIN2014-55413-C2-2-P and ESP2013-47780-C2-2-R. Part of this work is also supported by the UK Natural Environmental Research Council (NERC) through the Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET, ref.: come30001) and the LICS and CEDRRiC projects (ref. NE/K010794/1 and NE/N012151/1, respectively), the ESA-MOST DRAGON-3 projects (ref. 10607 and 10665), the ESA-MOST DRAGON-4 project (ref. 32244) and the Open Fund from the Key Laboratory of Earth Fissures Geological Disaster, Ministry of Land and Resources (ref.: gla2013001)

Machine-learning prediction of BMI change among doctors and nurses in North China during the COVID-19 pandemic

ObjectiveThe COVID-19 pandemic has become a major public health concern over the past 3 years, leading to adverse effects on front-line healthcare workers. This study aimed to develop a Body Mass Index (BMI) change prediction model among doctors and nurses in North China during the COVID-19 pandemic, and further identified the predicting effects of lifestyles, sleep quality, work-related conditions, and personality traits on BMI change.MethodsThe present study was a cross-sectional study conducted in North China, during May-August 2022. A total of 5,400 doctors and nurses were randomly recruited from 39 COVID-19 designated hospitals and 5,271 participants provided valid responses. Participants’ data related to social-demographics, dietary behavior, lifestyle, sleep, personality, and work-related conflicts were collected with questionnaires. Deep Neural Network (DNN) was applied to develop a BMI change prediction model among doctors and nurses during the COVID-19 pandemic.ResultsOf participants, only 2,216 (42.0%) individuals kept a stable BMI. Results showed that personality traits, dietary behaviors, lifestyles, sleep quality, burnout, and work-related conditions had effects on the BMI change among doctors and nurses. The prediction model for BMI change was developed with a 33-26-20-1 network framework. The DNN model achieved high prediction efficacy, and values of R2, MAE, MSE, and RMSE for the model were 0.940, 0.027, 0.002, and 0.038, respectively. Among doctors and nurses, the top five predictors in the BMI change prediction model were unbalanced nutritional diet, poor sleep quality, work-family conflict, lack of exercise, and soft drinks consumption.ConclusionDuring the COVID-19 pandemic, BMI change was highly prevalent among doctors and nurses in North China. Machine learning models can provide an automated identification mechanism for the prediction of BMI change. Personality traits, dietary behaviors, lifestyles, sleep quality, burnout, and work-related conditions have contributed to the BMI change prediction. Integrated treatment measures should be taken in the management of weight and BMI by policymakers, hospital administrators, and healthcare workers