Analyzing Norm Violations in Live-Stream Chat

Toxic language, such as hate speech, can deter users from participating in online communities and enjoying popular platforms. Previous approaches to detecting toxic language and norm violations have been primarily concerned with conversations from online forums and social media, such as Reddit and Twitter. These approaches are less effective when applied to conversations on live-streaming platforms, such as Twitch and YouTube Live, as each comment is only visible for a limited time and lacks a thread structure that establishes its relationship with other comments. In this work, we share the first NLP study dedicated to detecting norm violations in conversations on live-streaming platforms. We define norm violation categories in live-stream chats and annotate 4,583 moderated comments from Twitch. We articulate several facets of live-stream data that differ from other forums, and demonstrate that existing models perform poorly in this setting. By conducting a user study, we identify the informational context humans use in live-stream moderation, and train models leveraging context to identify norm violations. Our results show that appropriate contextual information can boost moderation performance by 35\%.Comment: 17 pages, 8 figures, 15 table

De Pulchritudine non est Disputandum? A cross-cultural investigation of the alleged intersubjective validity of aesthetic judgment

Since at least Hume and Kant, philosophers working on the nature of aesthetic judgment have generally agreed that common sense does not treat aesthetic judgments in the same way as typical expressions of subjective preferences—rather, it endows them with intersubjective validity, the property of being right or wrong regardless of disagreement. Moreover, this apparent intersubjective validity has been taken to constitute one of the main explananda for philosophical accounts of aesthetic judgment. But is it really the case that most people spontaneously treat aesthetic judgments as having intersubjective validity? In this paper, we report the results of a cross-cultural study with over 2,000 respondents spanning 19 countries. Despite significant geographical variations, these results suggest that most people do not treat their own aesthetic judgments as having intersubjective validity. We conclude by discussing the implications of our findings for theories of aesthetic judgment and the purpose of aesthetics in general.info:eu-repo/semantics/acceptedVersio

Regulation of BRCA1 stability through the tandem UBX domains of isoleucyl-tRNA synthetase 1

Aminoacyl-tRNA synthetases possess unique domains. In this study the structure of the vertebrate IARS1 and EARS1 complex reveals that vertebrate IARS1 protects the DNA repair factor BRCA1 from proteolytic degradation via its UBX-fold domain. Aminoacyl-tRNA synthetases (ARSs) have evolved to acquire various additional domains. These domains allow ARSs to communicate with other cellular proteins in order to promote non-translational functions. Vertebrate cytoplasmic isoleucyl-tRNA synthetases (IARS1s) have an uncharacterized unique domain, UNE-I. Here, we present the crystal structure of the chicken IARS1 UNE-I complexed with glutamyl-tRNA synthetase 1 (EARS1). UNE-I consists of tandem ubiquitin regulatory X (UBX) domains that interact with a distinct hairpin loop on EARS1 and protect its neighboring proteins in the multi-synthetase complex from degradation. Phosphomimetic mutation of the two serine residues in the hairpin loop releases IARS1 from the complex. IARS1 interacts with BRCA1 in the nucleus, regulates its stability by inhibiting ubiquitylation via the UBX domains, and controls DNA repair function

Nothing at Stake in Knowledge

Many philosophers hold that stakes affect ordinary knowledge ascriptions. Here’s a version of a pair of cases aimed at supporting this: Bob and his wife are driving home on Friday and considering whether to stop at the bank to deposit a check. The lines at the bank are very long and so Bob considers coming back on Saturday. In the low stakes version, nothing of importance hinges on whether the check is deposited; in the high stakes version, it is very important that the check be deposited. Bob’s wife asks whether the bank will be open on Saturday. Bob says he drove past the bank last Saturday, and it was open. However, his wife points out that banks sometimes change their hours. Bob says “I know the bank will be open tomorrow”. In the low stakes case, many philosophers maintain that Bob does indeed know that the bank will be open; in the high stakes case, these philosophers maintain that Bob is ignorant – his statement that he knows the bank will be open tomorrow is false. These philosophers also maintain that this pattern of judgments is what we would expect from competent speakers confronted with this and similar cases (e.g., Cohen, 1999, 2013; DeRose, 1992, 2009; Fantl and McGrath, 2002; Nagel, 2008; Rysiew, 2001; Stanley, 2005). Though many philosophers agree that stakes play a role in ordinary knowledge ascriptions, there is disagreement about what explains this. One view, epistemic contextualism, holds that “to know” is a context sensitive verb and that the truth conditions for knowledge ascriptions can vary across conversational contexts (e.g., DeRose, 2009). For instance, Bob’s statement “I know the bank will be open tomorrow” can be true in low stakes contexts and false in high stakes contexts. Another view, interest-relative invariantism, denies that “to know” is a context sensitive verb and that the truth conditions for knowledge ascriptions vary according to conversational contexts. Instead, cases like the Bank cases show that practical factors—i.e., stakes—play a distinctive role in determining whether the knowledge relation obtains (e.g., Stanley, 2005). Yet another alternative, which we’ll call classical invariantism, denies that “to know” is a context sensitive verb and that practical factors, such as stakes, play a direct role in determining whether the knowledge relation obtains. Instead, stakes affect knowledge ascriptions only by affecting our assessment of factors that have traditionally been taken to constitute or be necessary for knowledge, such as e.g., belief, quality of evidence, etc. (e.g., Bach, 2005; Weatherson, 2005; Ganson, 2007; Nagel, 2008). If this is right, then the role of stakes in knowledge ascriptions fails to motivate such surprising views as epistemic contextualism or interest-relative invariantism. Naturally, epistemic contextualists and interest-relative invariantists deny this, claiming that even when the factors that have traditionally been taken to constitute or be necessary for knowledge are held fixed, stakes continue to play a role in ordinary knowledge ascriptions (e.g., DeRose, 2009; Lawlor, 2013). So we see a dispute over what best explains the role of stakes in ordinary knowledge ascriptions. It is thus extremely surprising that a wide range of empirical evidence suggests that ordinary knowledge ascriptions fail to display any sensitivity to stakes (e.g., Buckwalter, 2010; Buckwalter and Schaffer, 2015; Feltz and Zarpentine, 2010; May, Sinnott-Armstrong, Hull, and Zimmerman, 2010; Turri, forthcoming; though see e.g., Pinillos, 2012; Pinillos and Simpson, 2014; Sripada and Stanley, 2012). If stakes really do not play any role in ordinary knowledge ascriptions, one of the main motivations for epistemic contextualism and interest relative invariantism would be undermined. Perhaps these different explanations of the role of stakes in ordinary knowledge ascription are born out of nothing more than a myth (Schaffer and Knobe, 2009). If so, classical invariantism about knowledge might be best supported—not because it provides the best explanation of the role of stakes in ordinary knowledge ascriptions, but rather because the failure of stakes to play a role in ordinary knowledge ascription would undercut an important motivation for its two competitors, epistemic contextualism and interest-relative invariantism. These radical alternatives to classical invariantism, lacking evidence in support of one of their important motivations, should perhaps then fall. Classical invariantism would stand. In the remainder of this article, we’ll disarm an important motivation for epistemic contextualism and interest-relative invariantism. We’ll accomplish this by presenting a stringent test of whether there is a stakes effect on ordinary knowledge ascription. Having shown that, even on a stringent way of testing, stakes fail to impact ordinary knowledge ascription, we will conclude that we should take another look at classical invariantism. Here is how we will proceed. Section 1 lays out some limitations of previous research on stakes. Section 2 presents our study and concludes that there is little evidence for a substantial stakes effect. Section 3 responds to objections. The conclusion clears the way for classical invariantism

Azimuthal anisotropy of charged jet production in root s(NN)=2.76 TeV Pb-Pb collisions

We present measurements of the azimuthal dependence of charged jet production in central and semi-central root s(NN) = 2.76 TeV Pb-Pb collisions with respect to the second harmonic event plane, quantified as nu(ch)(2) (jet). Jet finding is performed employing the anti-k(T) algorithm with a resolution parameter R = 0.2 using charged tracks from the ALICE tracking system. The contribution of the azimuthal anisotropy of the underlying event is taken into account event-by-event. The remaining (statistical) region-to-region fluctuations are removed on an ensemble basis by unfolding the jet spectra for different event plane orientations independently. Significant non-zero nu(ch)(2) (jet) is observed in semi-central collisions (30-50% centrality) for 20 <p(T)(ch) (jet) <90 GeV/c. The azimuthal dependence of the charged jet production is similar to the dependence observed for jets comprising both charged and neutral fragments, and compatible with measurements of the nu(2) of single charged particles at high p(T). Good agreement between the data and predictions from JEWEL, an event generator simulating parton shower evolution in the presence of a dense QCD medium, is found in semi-central collisions. (C) 2015 CERN for the benefit of the ALICE Collaboration. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Peer reviewe

Pseudorapidity and transverse-momentum distributions of charged particles in proton-proton collisions at root s=13 TeV

The pseudorapidity (eta) and transverse-momentum (p(T)) distributions of charged particles produced in proton-proton collisions are measured at the centre-of-mass energy root s = 13 TeV. The pseudorapidity distribution in vertical bar eta vertical bar <1.8 is reported for inelastic events and for events with at least one charged particle in vertical bar eta vertical bar <1. The pseudorapidity density of charged particles produced in the pseudorapidity region vertical bar eta vertical bar <0.5 is 5.31 +/- 0.18 and 6.46 +/- 0.19 for the two event classes, respectively. The transverse-momentum distribution of charged particles is measured in the range 0.15 <p(T) <20 GeV/c and vertical bar eta vertical bar <0.8 for events with at least one charged particle in vertical bar eta vertical bar <1. The evolution of the transverse momentum spectra of charged particles is also investigated as a function of event multiplicity. The results are compared with calculations from PYTHIA and EPOS Monte Carlo generators. (C) 2015 CERN for the benefit of the ALICE Collaboration. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Peer reviewe

대장내시경 영상에서 유의미한 정보를 제공하는 새로운 형태의 시각화된 대장내시경 요약 보고서

학위논문(박사)--서울대학교 대학원 :공과대학 협동과정 바이오엔지니어링전공,2019. 8. Kim, Sungwan.Colorectal cancer is one of the most important diseases in which early diagnosis can make a significant difference. Colonoscopy is the most commonly used method for early diagnosis of colorectal cancer. Recently, studies have been actively conducted to obtain more information from colonoscopy images by applying image processing methods, where polyp detection is an important factor for the early diagnosis of colorectal cancer. Since the size and shape of the polyps are variable, it is not easy to find them with human eye due to the nature of the colon wall that continues to move. So, this study intends to develop a system that could automatically detect polyps by applying image processing and machine learning methods to colonoscopy images. In addition, it is also anticipated to provide various useful information to clinicians performing colonoscopy. In this study, 7 meaningful information that can be useful for clinicians are defined and extracted with respect to time information. This information is classified as bleeding, instruments, polypectomy, residue, inflated, non-inflated, and no-fold. Next, the directions of the colonoscopy scope are also classified. It is extremely important to determine the time-location of the cecum, i.e., the cecal intubation time, since the reaching the appendix orifice is a major factor in determining whether a colonoscopy has been successfully performed. If the direction of the colonoscopy scope is classified, the cecal intubation time can be calculated as the insertion movement phase. Also, the withdrawal movement phase can be automatically calculated. All the results from the above processes are visualized for efficient delivery and organized as a summary report. The proposed novel summary report of colonoscopy with timeline visualization provides meaningful and formulated colonoscopy video information Under the Institutional Review Board (IRB) approval of Seoul National University Hospital, 113 colonoscopy video were collected. Support Vector Machine (SVM) model was used to classify colonoscopy images into 7 types. The mean, variance, skewness, correlation, contrast, Laplacian energy, energy of gradient, and scale invariant feature transform values were used as feature of SVM and performed with 5-cross validation. Inflated, non-inflated, and no-fold frames were applied to polygon detection algorithms learned by SVM. Here, the same features as above are used, and gray-level co-occurrence matrix values are used. Moreover, the motion vector was calculated by the Horn-Schunk algorithm in order to detect the direction of the colonoscopy scope. Based on this value, the convolutional neural network deep learning technique was used to classify the insertion and withdrawal phases. Finally, all of the above information was quantified as time information and visualized as a summary report of colonoscopy video (SRCV). For 113 colonoscopy images, the mean accuracy and sensitivity of the seven categories were 93.7% and 87.4%, respectively. The accuracy in polyp detection was 82.1% and the positive predicted value was 39.3%. The classification of the direction of the colonoscopy scope was trained and evaluated by convolutional neural network (CNN) using a total of 328,927 image frames with an overall average accuracy of 95.6%. The recall and precision for the entry movement were 95.8% and 97.6%, respectively and the recall rate and precision for the recall movement were 94.6% and 96.9%, respectively. At the value t = 30 sec obtained from the study, the position of the cecum was detected with an accuracy of 96.7%. In this study, image processing methods and machine learning methods have been applied to colonoscopy images to quantify and visualize the direction of the scope and 7 meaningful information as type of timeline. Through the results of this study, it is expected to contribute to the improvement of quality of medical service by assisting in the detection of polyps and re-observing colonoscopy images or sharing information with other clinicians and other hospitals.대장암은 조기 진단이 매우 중요한 질병 중 하나이며, 대장암을 조기 진단하기 위해 가장 많이 사용되는 대표적인 방법은 대장내시경 이다. 오늘날, 영상 처리 기술을 적용하여 대장내시경 영상에서 더욱 많은 정보들을 획득하고자 하는 연구가 활발히 진행되고 있다. 가장 대표적인 연구로서, 대장암의 조기 진단에 중요한 요소인 용종 검출이 있다. 용종은 크기와 모양이 각기 다르며, 계속해서 움직이는 대장 내벽의 특성상 육안으로 발견하기가 쉽지 않다. 이러한 이유로, 본 연구에서는 용종 발견을 돕기 위하여 대장내시경 영상에 영상처리 기술과 기계학습 기술을 적용하여 자동으로 용종을 검출할 수 있는 시스템을 개발하고자 한다. 뿐만 아니라, 대장내시경 영상에서 임상의에게 도움이 될 수 있는 유의미한 정보를 다수 추출하여 제공하고자 한다. 본 연구에서는 대장내시경 영상에서 임상의에게 도움이 될 수 있는 유의미한 정보를 7가지로 정의하고, 이를 추출하여 시간 정보로 정형화 하고자 한다. 7가지 유의미한 정보는 Bleeding, instruments, polypectomy, residue, inflated, non-inflated, no-fold 로 분류된다. 두 번째로, 대장내시경 스코프의 진행 방향을 분류하고자 한다. 맹장 도달 여부는 대장내시경이 성공적으로 수행 되었는지를 판단하기 위한 주요한 요소이기 때문에, 맹장의 위치, 즉 맹장도달시간 (Cecal intubation time)을 파악하는 것은 임상적으로 큰 의미가 있다. 따라서, 대장내시경 스코프의 진행 방향을 분류하고, 이를 바탕으로 진입 단계와 후퇴 단계를 구분함과 동시에 맹장도달시간을 자동으로 계산할 수 있다면, 대장내시경 영상을 시간정보로 자동 정형화하여 제공할 수 있을 것이다. 서울대학교 병원의 의학연구윤리심의위원회 (Institutional Review Board, IRB) 승인 하에, 113명의 대장내시경 영상 데이터를 수집하였다. 대장내시경 영상을 7가지 종류로 분류하기 위해서 Support Vector Machine (SVM) 모델이 사용되었다. Mean, variance, skewness, correlation, contrast, energy of laplacian, energy of gradient, 그리고 scale invariant feature transform 값들이 SVM의 feature로 사용되었으며, 5-cross validation으로 수행되었다. Inflated, non-inflated, no-fold 프레임들에 대하여, SVM으로 학습된 용종 검출 알고리즘이 각각 적용 되었다. 여기에서도 위와 같은 feature들이 사용되었으며, 추가로 gray-level co-occurrence matrix 값이 사용되었다. 다음으로, 대장내시경 스코프의 진행 방향을 검출하기 위해서 Horn-Schunk 알고리즘으로 모션 벡터를 계산하였고, 이 값을 바탕으로 합성곱 신경망 딥러닝 기법을 통해 진입 운동, 후퇴 단계가 분류 되었다. 마지막으로, 위의 모든 정보들은 시간 정보로 정형화 된 다음, 대장내시경 요약보고서 (Summary report of colonoscopy video, SRCV)로 시각화 되어 평가 되었다. 113명의 대장내시경 영상에 대하여, 7가지 분류에 대한 평균 정확도는 93.7%, 민감도는 87.4% 였으며, 용종의 검출 정확도는 82.1%, 양성예측치는 39.3%를 획득 하였다. 대장내시경 스코프의 진행 방향에 대한 분류는 112명의 환자 영상으로부터 총 328,927개의 이미지 프레임을 사용하여 CNN에 의해 학습, 평가되었으며, 전체 평균 정확도는 95.6% 였다. 진입 운동에 대한 재현율과 정밀도는 각각 95.8%, 97.6% 였으며, 후퇴 운동에 대한 재현율과 정밀도는 각각 94.6%, 96.9% 였다. 연구를 통해 얻어진 값 t = 30초 에서, 맹장의 위치는 96.7%의 정확도로 검출 되었다. 본 연구에서는 대장내시경 영상에 영상처리 기술 및 머신러닝 기술을 적용하여, 용종, 7가지 유의미한 정보와 스코프의 진행방향에 대한 정보를 시간 정보로 정형화 하고, 의사 및 환자에게 효율적으로 전달 될 수 있도록 시각화하여 제공하였다. 본 연구의 결과물을 통하여, 용종 검출을 보조하고 대장내시경 영상을 재관측 하거나 다른 의료진, 타 의료기관에 공유하는 경우에 정보를 효율적으로 전달하며, 의료 서비스의 품질 향상에 기여하고자 한다.1. Introduction 1 1.1. Colonoscopy Diagnosis and Colorectal Cancer 1 1.2. Colonoscopy Video Structuring 9 1.2.1. Video Storage Process 9 1.2.2. Video Type Classification 12 1.2.3. Colonoscope Direction Classification 15 1.3. Objectives and Scope 18 2. Materials and Methods 21 2.1. Colonoscopy Data Acquisition 21 2.1.1. Study Design and Population 21 2.1.2. Colonoscopy Procedure 23 2.1.3. Acquisition of Colonoscopy Video 24 2.1.4. Sample Size Calculation and Statistical Analysis 25 2.2. Informative Frame Classification 27 2.3. Type Classification 33 2.3.1. Overview 33 2.3.2. Hierarchical Classification 37 2.3.3. Polyp Detection 40 2.4. Colonoscope Direction Classification 43 2.4.1. Overview 43 2.4.2. Motion Vector Calculation 45 2.4.3. Scopes Movement Classification 49 2.4.4. Cecum Time-location Detection 53 2.5. Focus Group Interview 56 3. Results 57 3.1. Clinical Analysis 57 3.1.1. Characteristic of patients and colonoscopy quality assessment 57 3.1.2. Polyp Characteristics 59 3.2. Informative Frame Classification 61 3.3. Type Classification 62 3.3.1. Hierarchical Classification 62 3.3.2. Polyp Detection 64 3.3.3. Type Classification Visualization and Summary Report 69 3.4. Colonoscope Direction Classification 71 3.4.1. Scopes Movement Classification 71 3.4.2. Cecum Time-location Detection 75 3.4.3. Colonoscope Direction Visualization and Summary Report 78 3.5. System Usability Scale 81 4. Discussion 83 4.1. Type Classification and Polyp Detection 83 4.2. Colonoscope Direction Classification and Cecum Time-location Detection 88 4.3. Future Work 92 5. Conclusion 94 References 96 Abstract in Korean 112 Acknowledgement 115Docto

Ag2Se micropatterns via viscoelastic flow-driven phase separation

A novel approach to prepare micropatterns of metal chalcogenides is proposed by employing viscoelastic flow-driven patterning. A consecutive process involving deposition of the Se precursor on a pattern of a crystalline polymer, chemical reduction of the precursor into amorphous Se (a-Se), and short-time thermal annealing above the melting temperature of the patterned polymer generated regular patterns of a-Se. This work demonstrates patterns of periodic lines and circles which is driven by the viscoelastic polymer flow and the phase separation of Se from the polymer. Additional thermal annealing facilitated the lateral growth of trigonal-Se (t-Se) nanowires from the Se patterns. The growing t-Se nanowires eventually meet each other to produce a 2D network structure. Chemical transformation of the Se into Ag2Se generated metal chalcogenide network structures.close2