Analyzing Research and Development(R&D)trends is important because it can influence future decisions regarding R&D direction.In typical trend analysis,topic or technology taxonomies are employed to compute the...Analyzing Research and Development(R&D)trends is important because it can influence future decisions regarding R&D direction.In typical trend analysis,topic or technology taxonomies are employed to compute the popularities of the topics or codes over time.Although it is simple and effective,the taxonomies are difficult to manage because new technologies are introduced rapidly.Therefore,recent studies exploit deep learning to extract pre-defined targets such as problems and solutions.Based on the recent advances in question answering(QA)using deep learning,we adopt a multi-turn QA model to extract problems and solutions from Korean R&D reports.With the previous research,we use the reports directly and analyze the difficulties in handling them using QA style on Information Extraction(IE)for sentence-level benchmark dataset.After investigating the characteristics of Korean R&D,we propose a model to deal with multiple and repeated appearances of targets in the reports.Accordingly,we propose a model that includes an algorithm with two novel modules and a prompt.A newly proposed methodology focuses on reformulating a question without a static template or pre-defined knowledge.We show the effectiveness of the proposed model using a Korean R&D report dataset that we constructed and presented an in-depth analysis of the benefits of the multi-turn QA model.展开更多
Obesity is recognized as the second highest risk factor for cancer. The pathogenic mechanisms underlying tobaccorelated cancers are well characterized and efective programs have led to a decline in smoking and related...Obesity is recognized as the second highest risk factor for cancer. The pathogenic mechanisms underlying tobaccorelated cancers are well characterized and efective programs have led to a decline in smoking and related cancers, but there is a global epidemic of obesity without a clear understanding of how obesity causes cancer. Obesity is heterogeneous, and approximately 25% of obese individuals remain healthy(metabolically healthy obese, MHO), so which fat deposition(subcutaneous versus visceral, adipose versus ectopic) is "malignant"? What is the mechanism of carcinogenesis? Is it by metabolic dysregulation or chronic inflammation? Through which chemokines/genes/signaling pathways does adipose tissue influence carcinogenesis? Can selective inhibition of these pathways uncouple obesity from cancers? Do all obesity related cancers(ORCs) share a molecular signature? Are there common(overlapping) genetic loci that make individuals susceptible to obesity, metabolic syndrome, and cancers? Can we identify precursor lesions of ORCs and will early intervention of high risk individuals alter the natural history? It appears unlikely that the obesity epidemic will be controlled anytime soon; answers to these questions will help to reduce the adverse efect of obesity on human condition.展开更多
Specific research foci:(1) Mouse models of gamma-herpes virus-68(γHV-68) and polyomavirus(Py V) infections during neonatal versus adult life.(2) For human papilloma virus(HPV)-positive oropharyngeal carcinoma(OPC)—(...Specific research foci:(1) Mouse models of gamma-herpes virus-68(γHV-68) and polyomavirus(Py V) infections during neonatal versus adult life.(2) For human papilloma virus(HPV)-positive oropharyngeal carcinoma(OPC)—(a) Asking the question: Is oral sex a powerful carcinogen?(b) Examining the evidence for the vertical transmission of HPV infection.(c) Examining the relationship between HPV and Epstein–Barr virus(EBV) infections and nasopharyngeal cancer(NPC) in West European, East European, and East Asian countries.(d) Examining the association between HPVpositive OPC and human leukocyte antigen(HLA).(3) For non-smoking East Asian female lung adenocarcinoma—(a) Examining the incidence trends of HPV-positive OPC and female lung adenocarcinoma according to birth cohorts.(b) Examining the association between female lung adenocarcinoma and HPV.(c) Examining the associations of lung adenocarcinoma with immune modulating factors.(4) For triple-negative breast carcinoma(TNBC) in East Asians—(a) Examining the association between TNBC and HPV.(b) Examining the unique epidemiological characteristics of patients with TNBC. A summary "epidemiological" model tying some of these findings together.展开更多
How to restore the destroyed forest after forest fire is a key question that man must face. This paper reviewed the research situation and history on the forest restoration burned blanks and summed up the research met...How to restore the destroyed forest after forest fire is a key question that man must face. This paper reviewed the research situation and history on the forest restoration burned blanks and summed up the research methods used into four scales: seed-bank scale, community scale, ecosystem scale and landscape scale. The new technologies such as GIS & Remote Sensing used to vegetation restoration were also summarized. The strategies and developing trend of vegetation restoration research on burned blanks were discussed.展开更多
基金the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(NRF-2019R1G1A1003312)the Ministry of Education(NRF-2021R1I1A3052815).
文摘Analyzing Research and Development(R&D)trends is important because it can influence future decisions regarding R&D direction.In typical trend analysis,topic or technology taxonomies are employed to compute the popularities of the topics or codes over time.Although it is simple and effective,the taxonomies are difficult to manage because new technologies are introduced rapidly.Therefore,recent studies exploit deep learning to extract pre-defined targets such as problems and solutions.Based on the recent advances in question answering(QA)using deep learning,we adopt a multi-turn QA model to extract problems and solutions from Korean R&D reports.With the previous research,we use the reports directly and analyze the difficulties in handling them using QA style on Information Extraction(IE)for sentence-level benchmark dataset.After investigating the characteristics of Korean R&D,we propose a model to deal with multiple and repeated appearances of targets in the reports.Accordingly,we propose a model that includes an algorithm with two novel modules and a prompt.A newly proposed methodology focuses on reformulating a question without a static template or pre-defined knowledge.We show the effectiveness of the proposed model using a Korean R&D report dataset that we constructed and presented an in-depth analysis of the benefits of the multi-turn QA model.
文摘Obesity is recognized as the second highest risk factor for cancer. The pathogenic mechanisms underlying tobaccorelated cancers are well characterized and efective programs have led to a decline in smoking and related cancers, but there is a global epidemic of obesity without a clear understanding of how obesity causes cancer. Obesity is heterogeneous, and approximately 25% of obese individuals remain healthy(metabolically healthy obese, MHO), so which fat deposition(subcutaneous versus visceral, adipose versus ectopic) is "malignant"? What is the mechanism of carcinogenesis? Is it by metabolic dysregulation or chronic inflammation? Through which chemokines/genes/signaling pathways does adipose tissue influence carcinogenesis? Can selective inhibition of these pathways uncouple obesity from cancers? Do all obesity related cancers(ORCs) share a molecular signature? Are there common(overlapping) genetic loci that make individuals susceptible to obesity, metabolic syndrome, and cancers? Can we identify precursor lesions of ORCs and will early intervention of high risk individuals alter the natural history? It appears unlikely that the obesity epidemic will be controlled anytime soon; answers to these questions will help to reduce the adverse efect of obesity on human condition.
文摘Specific research foci:(1) Mouse models of gamma-herpes virus-68(γHV-68) and polyomavirus(Py V) infections during neonatal versus adult life.(2) For human papilloma virus(HPV)-positive oropharyngeal carcinoma(OPC)—(a) Asking the question: Is oral sex a powerful carcinogen?(b) Examining the evidence for the vertical transmission of HPV infection.(c) Examining the relationship between HPV and Epstein–Barr virus(EBV) infections and nasopharyngeal cancer(NPC) in West European, East European, and East Asian countries.(d) Examining the association between HPVpositive OPC and human leukocyte antigen(HLA).(3) For non-smoking East Asian female lung adenocarcinoma—(a) Examining the incidence trends of HPV-positive OPC and female lung adenocarcinoma according to birth cohorts.(b) Examining the association between female lung adenocarcinoma and HPV.(c) Examining the associations of lung adenocarcinoma with immune modulating factors.(4) For triple-negative breast carcinoma(TNBC) in East Asians—(a) Examining the association between TNBC and HPV.(b) Examining the unique epidemiological characteristics of patients with TNBC. A summary "epidemiological" model tying some of these findings together.
文摘How to restore the destroyed forest after forest fire is a key question that man must face. This paper reviewed the research situation and history on the forest restoration burned blanks and summed up the research methods used into four scales: seed-bank scale, community scale, ecosystem scale and landscape scale. The new technologies such as GIS & Remote Sensing used to vegetation restoration were also summarized. The strategies and developing trend of vegetation restoration research on burned blanks were discussed.
