Implications for South Koreas Foreign Policies

학위논문(석사)--서울대학교 대학원 :국제대학원 국제학과(국제지역학전공),2019. 8. 신성호.Although classical realism has a relatively long history as an international politics theory (and/or international relations theory), it has often been and is still widely misunderstood in several aspects. In particular, this thesis highlights the problems of i) overlooking the difference between classical realism and neorealism, especially due to the lack of attention to their metatheories, and ii) discounting the normative side of classical realism. The primary reason why these two misunderstandings are problematized here is because whilst realism continues to be the most widely accepted IR theory, its misunderstandings have resulted in substantive consequences, namely the marginalization of normative concerns in the international politics. Therefore, the thesis aims to vindicate classical realism as a normative international political theory by clarifying the common misunderstandings in the light of its metatheories. By exposing the metatheoretical differences between classical realism and neorealism, the thesis argues that, at their roots, they have more dissimilarities than similarities and that arguing in defense of classical realism as a normative theory is relevant and essential in the contemporary international relations and its discourse. Such relevance will be discussed in light of the implications the topic could have for South Koreas foreign policies.고전적 현실주의가 전세계적으로 오랫동안 국제관계, 혹은 국제정치이론으로서 받아들여지고 있었음에도 불구하고 잘못 이해, 인식되어 온 부분들이 있다. 특히, 본 논문에서는 i) 메타이론적 이해의 결여로 인해 고전적 현실주의와 신현실주의간의 차이가 간과되었던 점과ii) 고전적 현실주의의 규범이론으로서의 역할이 상대적으로 주목받지 못했던 점을 문제화한다. 이와 같은 이슈를 주목하는 이유는 현실주의가 가장 오랜 기간동안 적용 및 수용된 국제관계, 혹은 국제정치이론임에도 불구하고 현실주의, 특히 고전적 현실주의에 대한 포괄적인 이해가 부족하여 국제정치에서 규범적 논의의 주변화 등과 같은 실질적인 결과를 초래하였기 때문이다. 따라서, 본 논문은 고전적 현실주의와 신현실주의 각각의 메타이론을 설명함으로써 두 이론 간의 차이를 설명한 후, 고전적 현실주의의 국제정치규범이론으로서 갖는 역할을 주목하고자 한다. 또한, 이와 같은 논의가 현대 국제 관계에서 갖는 적합성과 중요성을 한국 대외정책에 주는 시사점에 비추어 논하고자 한다.I. Introduction 1 1. Study Background 1 2. Purpose of Research 2 II. Literature Review 4 III. Classical Realism vs. Neorealism 10 1. Background 10 2. Metatheories of Classical Realism and Neorealism 13 2.1. Ontology 17 2.2. Epistemology 23 2.3. Axiology 30 IV. Classical Realism as a Normative Theory 35 1. Practice and Prudence of Statesmen 36 2. National Interest and Universal Moral Principles 41 3. Ethics of Imperfection and Responsibility and the Lesser Evil 44 V. Implications for South Korea's Foreign Policies 48 1. Background 48 1.1. Theoretical Misunderstanding 48 1.2. Geopolitical Circumstances 53 2. Implications for Foreign Policies 55 VI. Conclusion 64 Bibliography 67 국문 초록 71Maste

고분자 전해질막 연료전지 시스템 고장 반응 및 심각도 기반 고장진단 방법

학위논문(박사) -- 서울대학교대학원 : 공과대학 기계항공공학부(멀티스케일 기계설계전공), 2021.8. 박진영.최근 들어 지속 가능하며 오염 없는 수소 사회에 대한 관심이 증가하고 있다. 수소는 우주에 가장 많은 물질이며 또한 쉽게 제조할 수 있다. 친환경 기술 개발과 더불어 수소 사회가 실현 된다는 가정하에, 수소에너지를 전기에너지로 변환시켜 주는 장치가 반드시 필요하다. 고분자 전해질막 연료전지 시스템은 산소와 수소의 전기화학반응을 이용하여 전기를 발전시키는 시스템이며, 다른 변환 장치에 비해 많은 장점을 가지고 있다. 또한, 가장 널리 사용되고 있는 장치이기도 하다. 다만, 연료전지의 상용화와 보급에 있어 내구성과 신뢰성은 아직 부족하여 극복해야 할 문제로 언급되고 있다. 이러한 내구성과 신뢰성 증진을 위해서는 고장 진단 기술이 반드시 필요하다. 연료전지는 운전 조건에 따라 그 성능과 내구성이 크게 영향을 받기 때문에 시스템에 발생한 문제를 빠르게 진단하여 장치를 보호하는 것이 중요하기 때문이다. 본 연구에서는 먼저 연료전지 시스템에 고장 발생시 그 영향을 관찰하였다. 일차적으로는 연료전지 스택에 반응의 공급 혹은 냉각이 원활히 이루어지지 않는 상황에서의 변화를 실험적으로 관찰하였다. 이어, 연료전지 시스템을 제작하여 연료 공급 시스템, 공기 공급 시스템, 열 관리 시스템에서 발생할 수 잇는 고장 시나리오를 설정하였다. 고장 시나리오는 연료전지 스택 혹은 시스템 전체에 미칠 수 있는 영향을 그 심각도에 따라 분류하였다. 마지막으로 고장을 인가하고 제어 및 계측 신호의 변화 양상을 관찰 및 분석하였다. 다음으로, 본 연구에서는 이러한 연료전지 시스템 고장을 진단할 수 있는 방법을 제안하였다. 고장의 심각도에 따라 변화 반응의 크기와 속도가 다르다는 점에 착안하여, 치명적 고장, 심각한 고장, 사소한 고장을 각각 진단하는 뉴럴 네트워크 기반 알고리즘을 개발하고, 이를 심각도 기반 고장 진단 알고리즘이라 명명하였다. 각각의 뉴럴 네트워크에 입력하는 계측 잔차 값의 이동 평균 시간과 이를 나누는 분산의 배수 값을 조절함으로 서, 진단 알고리즘의 민감도와 강건성을 동시에 달성할 수 있다는 장점을 갖는다. 또한 고장 실험 없이 고장 시 예상되는 제어 및 계측 신호 값의 증감을 테이블화 하는 것만으로도 본 알고리즘을 개발할 수 있다는 장점을 갖는다. 이러한 방법으로 개발 된 심각도 기반 고장 진단 알고리즘에 고장실험 데이터를 입력한 결과 고장을 성공적으로 진단하는 것을 확인하였다. 이어서, 본 연구에서는 내부 전류 분포를 예측할 수 있는 모델 개발법을 제안하였다. 지금까지의 연료전지 내부 전류 분포 연구는 실험 기반으로, 혹은 모델기반으로 각각 이루어져 왔다. 다만 두가지 접근 방법 모두 필연적으로 한계점을 가진다. 이러한 한계를 뉴럴 네트워크를 도입하여 극복하고자 하였다. 분할 연료전지를 이용하여 압력, 온도, 유량 및 가습도가 변하는 다양한 운전 조건에서의 전류 분포 정보를 습득하였고, 이를 뉴럴 네트워크 모델에 학습시켰다. 그 결과 제한된 데이터만으로 모델을 개발하고, 다양한 운전조건에서 전류 밀도 분포를 예측 할 수 있음을 확인하였다. 이러한 접근법은 상용 연료전지의 개발 과정에서 효율적으로 활용될 것이라 생각한다. 마지막으로, 본 연구에서는 열화 및 고장 발생에 따른 내부 전류 분포를 예측할 수 있는 모델 개발법을 제안하고 검증하였다. 연료전지는 시간이 지나면 필연적으로 열화 한다는 특성을 가지고 있다. 따라서 열화에 따른 전류 분포 변화 특성을 이해하고 예측하는 작업은 중요하다. 하여, 가속 열화 기법을 도입하여 열화에 따른 내부 전류 분포 변화를 먼저 관찰하였다. 또한 가속 열화 시험 중간에 운전 온도 상승, 당량비 증감, 가습도 저하와 같은 고장을 인가하여 전류 분포 변화 정보를 추가적으로 습득하였다. 이러한 정보를 바탕으로 열화 및 열화 진행 상태에서의 고장 발생 시, 전류밀도 분포를 예측하는 뉴럴 네트워크 기반 모델을 개발하였다. 그 결과 모델을 이용하여 효율적이면서도 정확한 전류 밀도 분포 예측이 가능함을 확인하였다.In recent years, interest in hydrogen society has grown from the viewpoint of a sustainable clean energy society. Hydrogen is the most abundant element in the universe and can be easily produced. When hydrogen becomes a commonly used fuel, an energy conversion device is needed. A polymer electrolyte membrane fuel cell (PEMFC) system is the most widely distributed device so far, with many advantages among many devices. However, there still are some barriers to overcome for the commercialization of the PEMFC system; reliability and durability. In order to improve the reliability and durability of the fuel cell system, fault diagnosis technology is essentially required. Since the performance and durability of the PFMFC highly depend on operating conditions, faults in the system should be correctly detected in the early stage for its protection. Firstly, fault responses of a PEMFC stack and PEMFC system are investigated in this study. A response of 1 kW PEMFC stack under insufficient reactant supply or failure thermal management is investigated. Next, probable fault scenarios in a 1 kW class PEMFC system are established. The fault scenarios in air providing system, fuel providing system and thermal management system are classified depending on their fault severity to the stack or the entire system. Responses of control and sensing signals are investigated and analyzed under each fault scenario. Secondly, a fault diagnostic method for the PEMFC system is suggested in this study. Considering that response time and magnitude differ depending on fault severity, three neural networks that diagnose the critical fault, significant fault and minor fault, respectively, are developed. The neural networks together work as a severity-based fault diagnosis algorithm. The algorithm can achieve both sensitivity and robustness by adjusting the moving average time and standard deviation multiplication value that divides the residual data. The residual data is acquired from the control and sensing signals during the system operation. The severity-based fault diagnosis algorithm can be developed using a tabularized expected fault response without experimental data. As a result, the developed algorithm successfully diagnosed all the considered fault scenarios. Thirdly, a local current distribution prediction method is suggested in this study. Local current distribution studies have been conducted experimentally or numerically. Both approaches had limitations. In order to overcome the limitations, a neural network-based local current distribution prediction model is developed. Current distribution data is collected under various pressure, temperature, reactant stoichiometric ratio and relative humidity conditions. The model is developed with the data and successfully predicted local current distribution. Using the model, the effect of the operating parameters is investigated. Lastly, a local current distribution prediction model under degradation and fault is suggested in this study. The performance of the fuel cell inevitably decreases over time. With the degradation, local current distribution also changes. Therefore, understanding and predicting the current distribution changes are important. An accelerated stress test (AST) is applied to the fuel cell for fast degradation. With the AST, current distribution data is collected. Also, fault data under elevated temperature, reduced humidity and varying cathode stoichiometric ratio condition are collected. With the collected data, local current distribution model based on a neural network is developed. As a result, the model predicted the current distribution under degradation and fault with high accuracy. In summary, a fault response of PEMFC is investigated from the viewpoint of the system and local current distribution. A severity-based fault diagnosis algorithm is suggested and validated with the PEMFC system fault experimental data. Also, local current distribution prediction algorithm is suggested and successively predicted the current distribution under PEMFC degradation and faults.Chapter 1. Introduction 1 1.1 Background of study 1 1.2 Literature survey 7 1.2.1 PEMFC fault diagnosis technology 7 1.2.2 PEMFC local current distribution 11 1.3 Objective and scopes 19 Chapter 2. Fault response of PEMFC system 22 2.1 Introduction 22 2.2 Fault response of 1 kW stack 23 2.2.1 Experimental setup description 23 2.2.2 Fault response of stack 29 2.3 Fault response of 1 kW PEMFC system 34 2.3.1 PEMFC system description 34 2.3.2 Fault scenarios 44 2.3.3 Fault response of PEMFC system 52 2.4 Summary 63 Chapter 3. Severity-based fault diagnostic method for PEMFC system 64 3.1 Introduction 64 3.2 Fault residual patterns 68 3.2.1 Input values 68 3.2.2 Normal state 69 3.2.3 Faul residual pattern table 72 3.3 Fault diagnosis algorithm development 79 3.3.1 Severity-based fault diagnosis concept 79 3.3.2 Algorithm development 82 3.4 Results and discussion 88 3.5 Summary 105 Chapter 4. Current distribution prediction with neural network 106 4.1 Introduction 106 4.2 Experimental setup 108 4.2.1 Experimental apparatus 108 4.2.2 Experimental conditions 113 4.3 Model development 116 4.3.1 Neural network model 116 4.3.2 Data conditioning 119 4.3.3 Model training 122 4.4 Results and discussion 127 4.4.1 Model accuracy 127 4.4.2 Effects of parameters on current distribution 129 4.4.3 Effects of parameters on standard deviations 133 4.4.3 Uniform current distribution 134 4.5 Summary 138 Chapter 5. Current distribution prediction under degradation and fault 139 5.1 Introduction 139 5.2 Accelerated stress test 140 5.3 Experimental setup 143 5.3.1 Experimental apparatus 143 5.3.2 Experimental conditions 148 5.4 Current distribution characteristics 152 5.4.1 Local current distribution change with accelerated stress test 152 5.4.2 Local current distribution change under faults 156 5.5 Model development 161 5.5.1 Neural network models 161 5.5.2 Data conditioning 166 5.5.3 Model training 169 5.6 Prediction results 171 5.7 Summary 176 Chapter 6. Concluding remarks 177 References 180 Abstract (in Korean) 197박

Brain Tumor Rehabilitation: Symptoms, Complications, and Treatment Strategy

Brain tumors are receiving increasing attention in cancer rehabilitation due to their high rate of neurological deterioration. Motor dysfunction, cognitive deterioration, and emotional problems are commonly present in patients with brain tumors. Other medical complications, such as seizures, headache, and dysphagia are also common. An individualized multidisciplinary rehabilitation intervention is necessary to treat functional impairment due to the tumor itself and/or treatment-related dysfunction. Herein, we discuss rehabilitation treatment strategies in relation to the neurological and functional complications that commonly occur in patients with brain tumors.ope

Medical Help-Seeking Strategies for Perinatal Women With Obstetric and Mental Health Problems and Changes in Medical Decision Making Based on Online Health Information: Path Analysis

BACKGROUND: Previous studies have revealed that most pregnant women rarely discuss informal information found on the internet with health professionals and have frequently expressed concerns for medical experts' reactions to the online information they shared, as well as the lack of time to consult the medical experts in general. To date, little information is available on the effect of individual differences in utilizing medical help-seeking strategies on their medical decisions during the perinatal period. OBJECTIVE: The objectives of this study were (1) to determine associations among perinatal women's medical help-seeking strategies, changes in medical decision making, and online health information utilization with a focus on the mediating effect of self-efficacy in perinatal health literacy on the intent to consult health professionals, and (2) to clarify these associations in perinatal women with two different medical problems: obstetric and mental health. METHODS: A total of 164 perinatal women aged 24 to 47 years (mean 34.64, SD 3.80) repeatedly completed the Problem Solving in Medicine and Online Health Information Utilization questionnaires to examine the moderating effect of two types of medical problems on their decision-making processes. To validate the hypothesized relationships in the proposed conceptual model encompassing obstetric and mental health problem-solving models, path analyses were performed. RESULTS: This study found that some perinatal women, who use an online informal medical help-seeking (OIMH) strategy, would be more likely to change their medical decisions based only on internet-based information without consulting health professionals (P<.001), compared to other women using different medical help-seeking strategies. Particularly, this concern is significantly prevalent when encountering obstetric problems during the perinatal period (obstetric problem-solving: P<.001; mental health problem-solving: P=.02). Furthermore, perinatal women with mental health issues using the OIMH strategy showed a significant difference in intent to consult health professionals based on online health information when the medical problem they had to solve was different (obstetric problem-solving: P=.94; mental health problem-solving: P=.003). CONCLUSIONS: Despite the positive mediating effects of perinatal women's enhanced health literacy on the intent to discuss personal medical issues with health professionals based on online health information, the strategy used is of fundamental importance for understanding their help-seeking and decision-making processes during the perinatal period. Beyond a short consultation to steer patients quickly and authoritatively towards an obstetric doctor's choice of action, it is recommended in this study that obstetricians attempt to provide their patients with needed context for the information found online. To fully explain this information with an open mind, they should actively develop or support information and communications technology (ICT)-based health information services.ope

Motor Recovery after Seizure Induced by Repetitive Transcranial Magnetic Stimulation

Despite the low incidence, seizures induced by repetitive transcranial magnetic stimulation (rTMS) have been studied as they may cause neurological and functional regression. Seizures may predict poor outcomes in stroke patients, with no reports of improved neurological status after seizures. This is the first Korean report of a seizure induced by rTMS, and the first report in the literature of prompt motor recovery following a seizure induced by highfrequency rTMS of the primary motor cortex in a stroke patient. A 43-year-old man with left hemiplegia due to infarction in the right basal ganglia was enrolled 10 sessions of rTMS (each session consisted of 15 trains, with each train consisting of 5 seconds of stimulation at 20 Hz and 90% of resting motor threshold for each session followed by 55 seconds of rest). The self-limited seizure occurred within 5 seconds after the 10th session. It lasted for 60 seconds, with generalized tonic features in all four extremities and the trunk and loss of consciousness followed by prompt improvement in left hand muscle strength and coordination. Though the seizure is known to usually cause neurologic regression, this case showed neurologic improvement after rTMS even after the rTMS-induced seizure.ope

Movement-Related Potentials Associated with Motor Timing Errors as Determined by Internally Cued Movement Onset

Objective: Accurate motor timing is critical for efficient motor control of behaviors; however, the effect of motor timing abilities on movement-related neural activities has rarely been investigated. The current study aimed to examine the electrophysiological correlates of motor timing errors. Methods: Twenty-two healthy volunteers performed motor timing tasks while their electroencephalographic and electromyographic (EMG) activities were simultaneously recorded. The average of intervals between consecutive EMG onsets was calculated separately for each subject. Motor timing error was calculated as an absolute discrepancy value between the subjects' produced and given time interval. A movement-related potential (MRP) analysis was conducted using readings from Cz electrode. Results: Motor timing errors and MRPs were significantly correlated. Our principal finding was that only Bereitschaftpotential (BP) and motor potential (MP), not movement monitoring potential, were significantly attenuated in individuals with motor timing errors. Motor timing error had a significant effect on the amplitude of the late BP and MP. Conclusion: The findings provide electrophysiological evidence that motor timing errors correlate with the neural processes involved in the generation of self-initiated voluntary movement. Alterations in MRPs reflect central motor control processes and may be indicative of motor timing deficits.ope

Which Visual Modality Is Important When Judging the Naturalness of the Agent (Artificial Versus Human Intelligence) Providing Recommendations in the Symbolic Consumption Context?

This study aimed to explore how the type and visual modality of a recommendation agent's identity affect male university students' (1) self-reported responses to agent-recommended symbolic brand in evaluating the naturalness of virtual agents, human, or artificial intelligence (AI) and (2) early event-related potential (ERP) responses between text- and face-specific scalp locations. Twenty-seven participants (M = 25.26, SD = 5.35) whose consumption was more motivated by symbolic needs (vs. functional) were instructed to perform a visual task to evaluate the naturalness of the target stimuli. As hypothesized, the subjective evaluation showed that they had lower attitudes and perceived higher unnaturalness when the symbolic brand was recommended by AI (vs. human). Based on this self-report, two epochs were segmented for the ERP analysis: human-natural and AI-unnatural. As revealed by P100 amplitude modulation on visual modality of two agents, their evaluation relied more on face image rather than text. Furthermore, this tendency was consistently observed in that of N170 amplitude when the agent identity was defined as human. However, when the agent identity was defined as AI, reversed N170 modulation was observed, indicating that participants referred more to textual information than graphical information to assess the naturalness of the agent.ope

Postoperative Delirium

Delirium can be defined as an 'acute brain dysfunction.' Compared to dementia, which is a disease that deteriorates the brain function chronically, delirium shows very similar symptoms but is mostly ameliorated when the causative factors are normalized. Due to the heterogeneity in etiologies and symptoms, people including health care workers often mistake delirium for dementia or other psychiatric disorders. Delirium has attracted global interest increasingly and a vast amount of research on its management has been conducted. Experts in the field have constantly suggested that systematic intervention should be implemented through a team-based multicomponent approach aimed to reduce the incidence and duration of delirium. Surgery involves many health care workers with different expertise who are not familiar with delirium. For a team-based approach on the management of delirium, it is vital that all medical personnel concerned have a common understanding of delirium and keep in constant communication. Postoperative delirium is a common complication and exerts an enormous burden on patients, their families, hospitals, and public resources. To alleviate this burden, this article aimed to review general features and the latest evidence-based knowledge of delirium with a focus on postoperative delirium.ope

A Chatbot for Perinatal Women's and Partners' Obstetric and Mental Health Care: Development and Usability Evaluation Study

Background: To motivate people to adopt medical chatbots, the establishment of a specialized medical knowledge database that fits their personal interests is of great importance in developing a chatbot for perinatal care, particularly with the help of health professionals. Objective: The objectives of this study are to develop and evaluate a user-friendly question-and-answer (Q&A) knowledge database-based chatbot (Dr. Joy) for perinatal women's and their partners' obstetric and mental health care by applying a text-mining technique and implementing contextual usability testing (UT), respectively, thus determining whether this medical chatbot built on mobile instant messenger (KakaoTalk) can provide its male and female users with good user experience. Methods: Two men aged 38 and 40 years and 13 women aged 27 to 43 years in pregnancy preparation or different pregnancy stages were enrolled. All participants completed the 7-day-long UT, during which they were given the daily tasks of asking Dr. Joy at least 3 questions at any time and place and then giving the chatbot either positive or negative feedback with emoji, using at least one feature of the chatbot, and finally, sending a facilitator all screenshots for the history of the day's use via KakaoTalk before midnight. One day after the UT completion, all participants were asked to fill out a questionnaire on the evaluation of usability, perceived benefits and risks, intention to seek and share health information on the chatbot, and strengths and weaknesses of its use, as well as demographic characteristics. Results: Despite the relatively higher score of ease of learning (EOL), the results of the Spearman correlation indicated that EOL was not significantly associated with usefulness (ρ=0.26; P=.36), ease of use (ρ=0.19; P=.51), satisfaction (ρ=0.21; P=.46), or total usability scores (ρ=0.32; P=.24). Unlike EOL, all 3 subfactors and the total usability had significant positive associations with each other (all ρ>0.80; P<.001). Furthermore, perceived risks exhibited no significant negative associations with perceived benefits (ρ=-0.29; P=.30) or intention to seek (SEE; ρ=-0.28; P=.32) or share (SHA; ρ=-0.24; P=.40) health information on the chatbot via KakaoTalk, whereas perceived benefits exhibited significant positive associations with both SEE and SHA. Perceived benefits were more strongly associated with SEE (ρ=0.94; P<.001) than with SHA (ρ=0.70; P=.004). Conclusions: This study provides the potential for the uptake of this newly developed Q&A knowledge database-based KakaoTalk chatbot for obstetric and mental health care. As Dr. Joy had quality contents with both utilitarian and hedonic value, its male and female users could be encouraged to use medical chatbots in a convenient, easy-to-use, and enjoyable manner. To boost their continued usage intention for Dr. Joy, its Q&A sets need to be periodically updated to satisfy user intent by monitoring both male and female user utterances.ope

Psychopathology, Temperament, and Character Factors of Adults with Childhood Attention-Deficit Hyperactivity Symptoms

Objectives：The objective of this study is to find out the differences in psychopathology, temperament, and character factorsbetween young adults with and without childhood attention-deficit hyperactivity disorder (ADHD) symptoms. Methods：The subjects consisted of 314 university students (male=72, female=242) in Gongju. They were divided into childhoodADHD group (N=54) and normal group (N=260) to the Wender-Utah Rating Scale. Participants were assessed using KoreanAdult ADHD Scale, Beck Depression Inventory-II, Beck Anxiety Inventory, Kimberly Young’s Internet Addiction Test, BarrattImpulsiveness Scale, Paranoia Scale, Korean-Schizotypal Ambivalence Scale, Lubben Social Network Scale, andTemperament and Character Inventory-Revised. Descriptive statistics, t-test, chi-square, spearman correlation, and stepwise multipleregression were applied to analyze the data. Results：Participants with childhood ADHD symptoms had high level of adult ADHD symptoms (p<.001), impulsiveness(p=.001), depression (p<.001), anxiety (p<.001), internet addiction (p<.001), paranoia tendency (p<.001) and low level of selfesteem(p<.001) compared to normal group. Self-directedness (p<.001) was lower, Harm avoidance (p=.001) and Self-transcendence(p=.029) were higher in the childhood ADHD group. In correlation and stepwise multiple regression, childhood ADHDsymptoms were significantly associated with cooperativeness (r=-0.515 and β=-0.547, p<.001 respectively). Conclusion：This result showed that young adults with childhood ADHD symptoms had various forms of psychopathologyand childhood ADHD symptoms were influenced by character such as cooperativeness. Therefore, more thorough evaluation regardingchildhood ADHD symptoms is needed.ope