有機薄膜太陽電池における材料の界面と結晶性に関する研究

学位の種別: 課程博士審査委員会委員 : (主査)東京大学教授 橋本 和仁, 東京大学教授 竹谷 純一, 東京大学特任教授 松尾 豊, 東京大学講師 猪熊 泰英, 理化学研究所チームリーダー 伹馬 敬介University of Tokyo(東京大学

An Ultra-wideband Off-axis Reflector Lens

The paper describes the design, fabrication and characterization of an ultra-wideband off-axis reflector lens operating between 6.8 GHz and 16.8 GHz. The lens is constructed using a single layer metasurface, consisting of a single ring with two equal openings. The design achieves an efficiency greater than 80% polarization conversion and a cross-polarization gain of 10 dB at the center frequency. The experimental results are in good agreement with the numerical simulations

Global Proteomic Analysis of the Resuscitation State of Vibrio parahaemolyticus Compared With the Normal and Viable but Non-culturable State

Vibrio parahaemolyticus is a common pathogen which has become a major concern of seafood products. The bacteria in the viable but non-culturable (VBNC) state are unable to form colonies on growth media, but under appropriate conditions they can regain culturability. In this study, V. parahaemolyticus was induced into VBNC state at low temperature and oligotrophic condition, and was resuscitated to culturable state. The aim of this study is to explore the comparative proteomic profiles of the resuscitation state compared with the VBNC state and the exponential phase of V. parahaemolyticus using isobaric tags for relative and absolute quantitation (iTRAQ) technique. The differentially expressed proteins (DEPs) were subjected to GO functional annotations and KEGG pathway analysis. The results indicated that a total of 429 proteins were identified as the significant DEPs in the resuscitation cells compared with the VBNC cells, including 330 up-regulated and 99 down-regulated DEPs. Meanwhile, the resuscitation cells displayed 25 up-regulated and 36 down-regulated DEPs (total of 61 DEPs) in comparison with the exponential phase cells. The remarkable DEPs including ribosomal proteins, ABC transporters, outer membrane proteins and flagellar proteins. GO annotation showed that the 429 DEPs were classified into 37 GO terms, of which 17 biological process (BP) terms, 9 cellular component (CC) terms and 11 molecular function (MF) terms. The up-regulated proteins presented in all GO terms except two terms of developmental process and reproduction. The 61 DEPs were assigned to 23 GO terms, the up- and down-regulated DEPs were both mainly involved in cellular process, establishment of localization, metabolic process and so on. KEGG pathway analysis revealed that the 429 DEPs were assigned to 35 KEGG pathways, and the pathways of ribosome, glyoxylate and dicarboxylate metabolism were significantly enriched. Moreover, the 61 DEPs located in 26 KEGG pathways, including the significantly enriched KEGG pathways of ABC transporters and two-component system. This study would contribute to a better understanding of the molecular mechanism underlying the resuscitation of the VBNC state of V. parahaemolyticus

Aligning Large Language Models with Human: A Survey

Large Language Models (LLMs) trained on extensive textual corpora have emerged as leading solutions for a broad array of Natural Language Processing (NLP) tasks. Despite their notable performance, these models are prone to certain limitations such as misunderstanding human instructions, generating potentially biased content, or factually incorrect (hallucinated) information. Hence, aligning LLMs with human expectations has become an active area of interest within the research community. This survey presents a comprehensive overview of these alignment technologies, including the following aspects. (1) Data collection: the methods for effectively collecting high-quality instructions for LLM alignment, including the use of NLP benchmarks, human annotations, and leveraging strong LLMs. (2) Training methodologies: a detailed review of the prevailing training methods employed for LLM alignment. Our exploration encompasses Supervised Fine-tuning, both Online and Offline human preference training, along with parameter-efficient training mechanisms. (3) Model Evaluation: the methods for evaluating the effectiveness of these human-aligned LLMs, presenting a multifaceted approach towards their assessment. In conclusion, we collate and distill our findings, shedding light on several promising future research avenues in the field. This survey, therefore, serves as a valuable resource for anyone invested in understanding and advancing the alignment of LLMs to better suit human-oriented tasks and expectations. An associated GitHub link collecting the latest papers is available at https://github.com/GaryYufei/AlignLLMHumanSurvey.Comment: work in progres

FollowBench: A Multi-level Fine-grained Constraints Following Benchmark for Large Language Models

The ability to follow instructions is crucial for Large Language Models (LLMs) to handle various real-world applications. Existing benchmarks primarily focus on evaluating pure response quality, rather than assessing whether the response follows constraints stated in the instruction. To fill this research gap, in this paper, we propose FollowBench, a Multi-level Fine-grained Constraints Following Benchmark for LLMs. FollowBench comprehensively includes five different types (i.e., Content, Situation, Style, Format, and Example) of fine-grained constraints. To enable a precise constraint following estimation on diverse difficulties, we introduce a Multi-level mechanism that incrementally adds a single constraint to the initial instruction at each increased level. To assess whether LLMs' outputs have satisfied every individual constraint, we propose to prompt strong LLMs with constraint-evolution paths to handle challenging open-ended instructions. By evaluating ten closed-source and open-source popular LLMs on FollowBench, we highlight the weaknesses of LLMs in instruction following and point towards potential avenues for future work. The data and code are publicly available at https://github.com/YJiangcm/FollowBench.Comment: 19 pages, 9 figures, 14 table

Obesity and endocrine-related cancer: The important role of IGF-1

Obesity is increasingly becoming a global epidemic of concern and is considered a risk factor for several endocrine-related cancers. Moreover, obesity is associated with cancer development and poor prognosis. As a metabolic abnormality, obesity leads to a series of changes in insulin, IGF-1, sex hormones, IGFBPs, and adipokines. Among these factors, IGF-1 plays an important role in obesity-related endocrine cancers. This review describes the role of obesity in endocrine-related cancers, such as prostate cancer, breast cancer and pancreatic cancer, focusing on the mechanism of IGF-1 and the crosstalk with estrogen and adipokines. In addition, this review briefly introduces the current status of IGF-1R inhibitors in clinical practice and shows the prospect of IGF-1R inhibitors in combination with other anticancer drugs

Multi-site, Multi-domain Airway Tree Modeling (ATM'22): A Public Benchmark for Pulmonary Airway Segmentation

Open international challenges are becoming the de facto standard for assessing computer vision and image analysis algorithms. In recent years, new methods have extended the reach of pulmonary airway segmentation that is closer to the limit of image resolution. Since EXACT'09 pulmonary airway segmentation, limited effort has been directed to quantitative comparison of newly emerged algorithms driven by the maturity of deep learning based approaches and clinical drive for resolving finer details of distal airways for early intervention of pulmonary diseases. Thus far, public annotated datasets are extremely limited, hindering the development of data-driven methods and detailed performance evaluation of new algorithms. To provide a benchmark for the medical imaging community, we organized the Multi-site, Multi-domain Airway Tree Modeling (ATM'22), which was held as an official challenge event during the MICCAI 2022 conference. ATM'22 provides large-scale CT scans with detailed pulmonary airway annotation, including 500 CT scans (300 for training, 50 for validation, and 150 for testing). The dataset was collected from different sites and it further included a portion of noisy COVID-19 CTs with ground-glass opacity and consolidation. Twenty-three teams participated in the entire phase of the challenge and the algorithms for the top ten teams are reviewed in this paper. Quantitative and qualitative results revealed that deep learning models embedded with the topological continuity enhancement achieved superior performance in general. ATM'22 challenge holds as an open-call design, the training data and the gold standard evaluation are available upon successful registration via its homepage.Comment: 32 pages, 16 figures. Homepage: https://atm22.grand-challenge.org/. Submitte

Comparative Proteomics Analyses Reveal the virB of B. melitensis Affects Expression of Intracellular Survival Related Proteins

BACKGROUND: Brucella melitensis is a facultative, intracellular, pathogenic bacterium that replicates within macrophages. The type IV secretion system encoded by the virB operon (virB) is involved in Brucella intracellular survival. However, the underlying molecular mechanisms, especially the target proteins affected by the virB, remain largely unclear. METHODOLOGY/PRINCIPAL FINDINGS: In order to define the proteins affected by virB, the proteomes of wild-type and the virB mutant were compared under in vitro conditions where virB was highly activated. The differentially expressed proteins were identified by MALDI-TOF-MS. Forty-four down-regulated and eighteen up-regulated proteins which exhibited a 2-fold or greater change were identified. These proteins included those involved in amino acid transport and metabolism, lipid metabolism, energy production, cell membrane biogenesis, translation, post-translational modifications and protein turnover, as well as unknown proteins. Interestingly, several important virulence related proteins involved in intracellular survival, including VjbR, DnaK, HtrA, Omp25, and GntR, were down-regulated in the virB mutant. Transcription analysis of virB and vjbR at different growth phase showed that virB positively affect transcription of vjbR in a growth phase dependent manner. Quantitative RT-PCR showed that transcription of these genes was also affected by virB during macrophage cell infection, consistent with the observed decreased survival of the virB mutant in macrophage. CONCLUSIONS/SIGNIFICANCE: These data indicated that the virB operon may control the intracellular survival of Brucella by affecting the expression of relevant proteins

Roadmap on commercialization of metal halide perovskite photovoltaics

Perovskite solar cells (PSCs) represent one of the most promising emerging photovoltaic technologies due to their high power conversion efficiency. However, despite the huge progress made not only in terms of the efficiency achieved, but also fundamental understanding of the relevant physics of the devices and issues which affect their efficiency and stability, there are still unresolved problems and obstacles on the path toward commercialization of this promising technology. In this roadmap, we aim to provide a concise and up to date summary of outstanding issues and challenges, and the progress made toward addressing these issues. While the format of this article is not meant to be a comprehensive review of the topic, it provides a collection of the viewpoints of the experts in the field, which covers a broad range of topics related to PSC commercialization, including those relevant for manufacturing (scaling up, different types of devices), operation and stability (various factors), and environmental issues (in particular the use of lead). We hope that the article will provide a useful resource for researchers in the field and that it will facilitate discussions and move forward toward addressing the outstanding challenges in this fast-developing field