Earticle

본 연구는 오늘날 한국 청소년들이 겪는 학업 중압감의 실태를 파악하고 이의 성경적 상담을 통한 신앙지도에 관한 연구이다. 구체적으로는 어느 한 교회의 청소년부의 학생들과 학부모를 상담한 내용을 분석하여 그들의 경험과 문제에 맞는 성경적인 접근 방법을 모색하는 것이다. 한국교회의 성장이 둔화되고 있는 현 시점에서 내일의 주역인 청소년을 올바르게 신앙 지도하는 것은 아주 중요하다. 청소년들에 대한 학업의 압박감은 지역 교회에도 부정적인 영향을 미치고 있어서 많은 학생들이 주중에 있는 청소년 성경공부나 예배에 나오지 않게 되고 심지어는 상당수의 학생들이 주일 예배에도 참석을 못하고 학교를 가거나 학원을 간다. 크리스천 학부모들도 헌신된 몇몇 부모들을 제외하고는 이러한 학생들의 선택을 방조한다. 이는 지역 교회 청소년부의 약화 또는 붕괴로 연결된다. 더 안타까운 것은 이에 대해서 많은 교회들이 적극적으로 대처하지 못하고 있는 것이다. 대부분의 교회들은 줄어드는 청소년의 교회 출석에 대응하는 전도나 예배 프로그램에 초점을 맞추는 경향이다. 이러한 교회 안에 존재하는 청소년들에 대한 피상적인 접근 방식에 대하여, 이 논문은 교회 안의 청소년들도 학업의 압박과 스트레스로 고통 받고 있음을 인지하고 그들의 어려움을 성경적 상담의 방법을 통하여 성경적으로 이해하고 이들을 성경적으로 도울 수 있는 원리를 제안하고자 한다. 본 연구는 목회에서 상담이 차지하는 역할을 조명하고 이의 두드러진 특징과 과제들을 기술한다. 상담의 대상인 청소년의 특성, 가정, 학교, 사회, 교회 등의 환경적 특성을 알아보고 청소년이 직면한 문제점들을 알아본다. 이어서 청소년이 문제를 직면하고 스스로 해결하게 하는 방법을 설명하며 이를 위한 성경적 상담의 방법 L.K.S.D.(Love, Know, Speak, Do)를 구체적으로 적용함으로써 청소년의 마음의 변화를 시도하는 신앙지도 방법과 성공적인 상담사례를 예시한다.

The purpose of this study is to suggest the principles of Biblical counseling concerning the mental stresses prevalent in Korean students due to their severe academic pressures to prepare for admission to college. This dissertation will provide a case study of a youth group and their parents in a local church, and will analyze the results of counseling with them by using the principles of biblical counseling, developed to fit with their conditions. In Korean society, the college from which one graduate is more important than a different society can ever imagine. This emphasis on college results in overheated competitions in the entrance examination. Teenagers’ academic pressures and their consequent mental problems have raised a grievous concern in the multiple sectors of society, including the government, social institutions, and private parties. They have suggested and implemented various solutions. Despite these efforts, however, juvenile delinquency is steadily increasing and its character is getting worse. Furthermore, it becomes more difficult to find effective measures to this problem. Teenagers’ inordinate academic pressures also create a negative effect on local churches. Many youth group members quit weekday Bible studies and worship services. Some of them do not regularly attend Sunday worship service because they have to go to private tutoring centers. Christian parents, except for those who are devoted to Christian faith and practice, ignore their children’s decision not to go to church on Sunday. This trend gradually weakens youth group activities, and in some cases this even leads to the collapse of youth group in local churches. Unfortunately, many churches respond to this problem simplistically. Most churches focus on evangelism or changing worship liturgy in order to increase church attendance. Most of all churches are more interested in church attendance than in helping them in real life. Against this superficial approach to which churches may easily resort, this study suggests an alternative biblical principle by which churches may recognize that teenagers do suffer from inordinate academic pressures and mental stress, and they may understand the nature of their suffering and may receive by means of biblical counseling. Heart Model, one of biblical counselling, is adapted and analysed with a successful case study. It is practised with methods of L.K.S.D.(Love, Know, Speak, Do).

Accuracy improvement of classification model becomes main research objective in various fields. Selecting important features and removing outliers of a dataset are two effective solutions for improving model accuracy. Information Gain is one of the feature selection methods that can be considered as a solution for selecting important features of a dataset. Information Gain selects the variable that maximizes the information gain, which in turn minimizes the entropy and best splits the dataset into groups for effective classification. Aside of selecting important feature, removing outlier is also necessary for improving accuracy of the classification model. Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is one of the powerful outlier removal methods which can identify with significant accuracy the clusters of random shape and size in large databases corrupted with noise. Therefore, in this study, we propose the accuracy improvement of heart disease classification model using Information Gain and DBSCAN applied to various machine learning algorithms. One publicly available heart disease dataset (Cleveland) is utilized in this study to build the classification model. The results showed that after implementing Information Gain, the accuracy of the model applied to Gaussian Naïve Bayes, Logistic Regression, Multi-Layer Perceptron, Support Vector Machine, Decision Tree, Random Forest, and Extreme Gradient Boosting algorithms increases as much as 1.31% in average. The accuracy also increases when DBSCAN is applied to the model after utilizing Information Gain, with the number of improvements is around 0.62%.

Heart disease is a major cause of mortality in the world that is in dire need of accurate, interpretable predictive measures that could be utilized to manage it proactively. The writer of this paper proposes an Explainable AI (XAI) Ensemble Machine Learning model to predict heart disease using an 1,025 patient record dataset. To achieve methodological rigor and generalization, 5- Fold Stratified Cross-Validation (CV) was used to evaluate all models, such as LightGBM and Random Forest. LightGBM model was stable and better in performance as it had Mean CV Accuracy of ±0.9620 ±0.0178. Integration of XAI (SHAP/LIME) is the means of creating clinical trust; analysis has confirmed maximum heart rate (thalach) and type of chest pain (cp) as medically significant characteristics. This framework supports the sustainable smart city healthcare through a highly transparent decision-support system, which manages the resources in optimizing scalable public health programs.

본 연구에서는 근로자 집단 내 심장마비 고위험군 예측 모델 개발을 위해 Regularized Greedy Forest (RGF) 알고리즘을 활용하였다. 제안된 RGF 알고리즘은 대규모 복잡 데이터셋에 대한 처리 능력을 바탕으로, 전 통적인 CART, KNN, SVM 모델 대비 예측 정확도 및 신뢰성 측면에서 유의미한 성능 향상을 달성하였다. 분석 결과, 연령, 콜레스테롤 수치, 신체 활동 수준이 주요 심장마비 위험 요인으로 도출되었다. 본 연구는 직업 건강 영역에서 조기 개입 전략 수립 시 기계 학습 기법의 활용 가능성을 확인하고, 그 중요성을 강조한다.

This study introduces a predictive model using Regularized Greedy Forest (RGF) to identify high-risk heart attack candidates among workers. Heart disease risks are heightened by occupational stressors like stress and sedentary lifestyles. The RGF algorithm effectively handles complex datasets, surpassing traditional models like CART and KNN in prediction accuracy. The model highlights age, cholesterol, and physical activity as key risk factors, achieving an accuracy of 63.7% and an AUC of 65.1%. This research emphasizes machine learning's role in enhancing early intervention strategies in occupational health.

본 논문에서는 여러 곳에서 통용되고 있는 기존의 CW(continuous-wave) 레이더 송수신모델을 수정한 송수신모델을 제안한다. 최근 에 심장박동과 호흡을 검출하기 위해 기존신호모델을 기반으로 CW(continuous-wave) 레이더에 대한연구가 진행 되고 있다. 그러나 이 통용되고 있는 수신모델은 인체 공학적으로 개념과 일치하지 않기 때문에 이모델을 근거로 실험을 할 경우 실제 개발되는 시스템 성능을 정확하게 예측할수 없다. 본 논문에서는 인체 공학상 개념과 일치하는 수정된 CW(continuous-wave) 레이더 송수신모델을 제안하고 가운시안 잡음rhk 다중경로 환경에서 심장박동 및 호흡검출에 대한 시뮬레이션을 수행하고 이를 기존수신모델과의 심장박 동과 호흡검출에 대한 성능을 비교 분석한다.

In this paper, new signal model for bio-signal detection, i.e heart beat and respiration, using CW radar. Most research on this similar topic are based on the conventional signal model which is not correct in envisaging reflected signal from the human body. The system developed based on this conventional model can not predict exact performance of the system. So in this paper modified signal model for bio-radar is proposed and then simulation for detecting heartbeat and respiration signal in AWGN, multipath environment. The detection performance difference between two signal models are discussed.the modified

Purpose: The purpose of this study was to construct and test a hypothetical model of exercise behavior in patients with Heart Failure (HF) based on the Information-Motivation-Behavioral skills (IMB) model, and the IMB model including depression (IMBD). Methods: Data collection was conducted from February 1 to March 15, 2019. A total of 306 patients who were diagnosed with HF and were receiving outpatient treatment at the D University hospital and S hospital located in B city were included in the final analysis. The collected data were analyzed using SPSS 24.0 and AMOS 25.0 program. Results: The IMB model (x 2 /df=2.45, SRMR=.07, RMSEA=.07, GFI=.98, AGFI=.94, TLI=.93, CFI=.97) and IMBD model (x 2 /df=0.79, SRMR=.02, RMSEA=.003, GFI=.99, AGFI=.97, TLI=.98, CFI=.97) were a good fit for the data. In the exercise behavior IMB model, exercise behavior was explained by 55.1% by information, personal motivation, and behavioral skills. In the exercise behavior IMBD model, exercise behavior was explained by 60.4% by information, personal motivation, behavioral skills, and depression. Conclusion: The IMBD model showed high predictive power of exercise behavior. Therefore, in order to improve HF patients’ exercise behavior, it is necessary to identify and manage patients who experience depression. The development and application of integrated interventions to provide appropriate information, motivation, and confidence in exercise can be an effective strategy in increasing exercise compliance, and ultimately contribute to improving the health outcomes of patients with HF.

감정을 정확히 예측하는 것은 환자중심의 의료디바이스 개발 및 감성관련 산업에서 매우 중요한 이슈이다. 감정 예측에 관한 많은 연구 중 감정 예측에 심박 변동성과 뉴로-퍼지 접근법을 적용한 연구는 없다. 본 연구는 HRV를 이용한 ANFEP(Adaptive Neuro Fuzzy system for Emotion Prediction)을 제안한다. ANFEP의 핵심 기능은 인공 신경망과 퍼지 시스템을 통합해 예측 모델을 학습하는 ANFIS(Adaptive Neuro-Fuzzy Inference System)에 기반한다. 제안 모형의 검증을 위해 50명의 실험자를 대상으로 청각자극으로 감정을 유발하고, 심박변이도를 구하여 ANFEP 모형에 입력하였다. STDRR 과 RMSSD를 입력으로 하고 입력변수 당 2개의 소속함수로 하는 ANFEP모형이 가장 좋은 결과를 나타났다. 제안한 감정예 측 모형을 선형회귀 분석, 서포트 벡터 회귀, 인공신경망, 랜덤 포레스트와 비교한 결과 본 제안모형이 가장 우수한 성능을 보였다. 연구 결과는 보다 적은 입력으로 신뢰성 높은 감정인식이 가능함을 입증했고, 이를 활용해 보다 정확하고 신뢰성 높은 감정인식 시스템 개발에 대한 연구가 필요하다.

An accurate prediction of emotion is a very important issue for the sake of patient-centered medical device development and emotion-related psychology fields. Although there have been many studies on emotion prediction, no studies have applied the heart rate variability and neuro-fuzzy approach to emotion prediction. We propose ANFEP(Adaptive Neuro Fuzzy System for Emotion Prediction) HRV. The ANFEP bases its core functions on an ANFIS(Adaptive Neuro-Fuzzy Inference System) which integrates neural networks with fuzzy systems as a vehicle for training predictive models. To prove the proposed model, 50 participants were invited to join the experiment and Heart rate variability was obtained and used to input the ANFEP model. The ANFEP model with STDRR and RMSSD as inputs and two membership functions per input variable showed the best results. The result out of applying the ANFEP to the HRV metrics proved to be significantly robust when compared with benchmarking methods like linear regression, support vector regression, neural network, and random forest. The results show that reliable prediction of emotion is possible with less input and it is necessary to develop a more accurate and reliable emotion recognition system.

직접증명과 주요사실이 가지는 직접적 연관성이 다름으로 인하여 간접증거를 통해 사건의 사실을 인정하는 경우가 종종 있는데, 이는 법관이 사실의 ‘조각’을 맞추는 과정에서 주관적 요소가 개입될 가능성이 매우 높다. 즉, 이는 재판에서 경험칙을 어떻게 규제할 것인가의 문제로 이어진다. 논리적 추론의 적용과정에 서 쉽게 나타나는 법관의 주관적 추단성을 어떻게 간접증거와 동질성을 입증할 것인가이다. 이는 이러한 증거들 간의 고리를 형성할 수 있는가가 재판실무에서 난제이다. 또한 간접증거이든 직접증거이든 모두 증거로 인증되는데, 법관의 주 관적 사실의 확신에 대하여 어떻게 고려하여야 할 것인지도 문제된다. 이러한 관점에서 본 연구는 심정의 객관화를 통한 간접증명의 유형을 검토한 다. 첫째, 경험칙에서의 심정의 객관화의 규범화가 최종추정력이나 증거보충력 등에서 어떠한 문제가 있는지를 검토할 필요가 있다. 둘째, 당사자가 법원에 이 러한 심정의 객관화를 보충적으로 증명력으로서 인정해줄 수 있는지이다. 본고에서는 실무에서 나타나는 전형적인 의료소송사례에서 어떠한 간접증명 방식이 사용되는지 분석하고, 의료소송에서 어떠한 간접증명 방식이 가장 효과 적인지를 검토한다. 증명문제는 구체적이어야 하고 필수적인 것이다. 즉, 간접사 실과 주요사실은 관련성을 가지고 있어야 하며, 이러한 관련성에 대해 판사의 경험칙이 적용되기 마련인데 의료소송에서 어떻게 적용되는지 검토한다.

Different from the direct relationship between direct evidence and the main facts, the process of using the indirect evidence to determine the case facts is often complicated and complicated. It is also very easy that judges mix subjective and random factors under the process of the reconstruction of factual “fragment”. How to regulate the subjective arbitrariness in the application process of the rule of thumb and logical inference, how to prove the indirectness between indirect evidences and form a complete chain of evidence, which become difficult point of trial practice. At the same time, whether it is an indirect proof or a direct proof, it is a complete proof that the judge’s conviction of the facts should be sufficient to satisfy the judge. In this regard, how to evaluate the final proof the indirect proof to determine whether the proof standard is met, and how to clearly show the proof process to the party so that it convinced the judgment is also worthy of attention. Based on this, this paper proposes a medium to achieve heart Objectification -indirect proof model. On the one hand, It is to standardize the application of the rule of thumb, clarify the final presumptive power, and to make up for the lack of application of the evidence chain and the evidence loop, thereby maximally suppressing the subjective randomness of the fact-finding and standardizing the application of the indirect proof method; On the one hand, it provides the possibility for the parties to communicate with the court in time to ensure that the parties fully exercise their proof right. The indirect proof model can be roughly divided into four types: simple evidence loop, complex evidence chain, evidence loop and comprehensive type. Based on the concept clarification of various models and the prototype display, this article demonstrates how to perform module operations based on typical medical litigation cases appearing in practice. At the same time, it is indirectly proved that the maximal utility of the model requires the surrounding system—proof subject must be specific and necessary, the indirect facts and the main facts must be related, and the type of the rule of thumb should be perfected. Only the interaction of the various systems, Indirect proof that the model can be applied correctly.

不同于直接证据与主要事实所具有直接联系，利用间接证据认定案件事实的过程 往往繁琐复杂，法官对事实“碎片”的重构也极易混杂主观随意性的因素。如何规制 经验法则、逻辑推论在适用过程极易出现的主观臆断性，如何证成间接证据之间具 有同向性并形成了完整的证据链条，成为审判实务的难点。同时，无论是间接证 明，还是直接证明，均属于完全证明，即法官对事实的确信，均应足以令法官达到 确信即可。对此，如何评估该间接证明的最终推定力进而判断是否达到证明标准， 又如何将证明过程清晰地展示给当事人从而使其信服判决等问题同样值得关注。 据此，本文提出了实现心证客观化的介质——间接证明模型。一方面，以期借此 使得经验法则的适用规范化、最终推定力明晰化以及弥补证据链、证据环的适用缺 失，从而最大程度上抑制事实认定者的主观随意性，规范间接证明方式的适用；另 一方面，为当事人与法院的及时交流沟通提供可能，以保证当事人充分行使其证明 权。 间接证明模型可粗略分为简单证据环、复杂证据链、证据环以及综合型四种类 型。在对各种模型进行概念明晰以及原型展示的基础上，本文以实务中出现的典型 医疗诉讼案例为素材演示了如何进行模块操作。同时，间接证明模型最大效用的发 挥尚需周边制度——证明主题须具体与必要、间接事实与主要事实须具有关联性、 经验法则的类型化构建——的完善，只有各个制度的相互配合，间接证明模型才能 得以正确适用。

Purpose: This descriptive study aimed to investigate heart rate variability (HRV) according to sex and to elucidate the influence of negative emotion such as levels of stress, anxiety and depression on HRV among Korean college students based on a neurovisceral integration model. Methods: A descriptive study design was used. Eighty-six healthy college students participated in the study. Resting HRV and standing HRV on orthostatic stimulation were measured for 5 minutes during 4-6 p.m. in the afternoon. Levels of stress, anxiety and depression were assessed using the Global assessment of recent stress, State-Trait Anxiety Inventory and Beck Depression Index, respectively. Results: Out of the 86 students, 47 (54.7%) were men and 39 (45.3%) were women. Root mean square of the differences between adjacent RR intervals (RMSSD) and normalized high frequency (nHF) on standing HRV were significantly lower in men than in women (p=.005, p=.019, respectively). Male gender (β=0.30, p=.013), higher level of stress (β=-0.36, p=.009) and lower level of depression (β=0.30, p=.044) exerted a significant influence on decreased nHF in the multiple regression analysis. Conclusion: We suggest that men are more vulnerable to having reduced vagal activity on HRV than women. Since male gender, higher level of stress and lower level of depression level influenced decreased vagal activity, strategies are needed to improve stress and depression rather than anxiety especially for men, which contribute to promoting HRV to prevent cardiac health diseases.

『장자』의 장인은 이상적 존재를 상징한다. 『장자』에 묘사되어 있는 장인의 삶에 토대해 서 장자적 삶의 방식을 구성하는 것이 본고의 목적이다. 본고에서는 먼저 『장자』에 心과 氣 라는 두 개의 상이한 소통방식이 존재함을 보인다. 이후, 장자의 양가적 기술관에도 이 두 가지 소통방식이 반영되어 있음을 밝히고, 이 기반위에서 장자가 말하는 장인의 삶을 구성 해낸다. 구체적으로 장인의 삶을 기술수행 이전, 기술수행과정과 이후의 셋으로 나누고, 각 단계의 특성을 심과 기의 소통방식을 통해 설명해낸다. 각 단계마다 소통방식에 차이가 있 고, 이런 차이점이 장자적 삶의 복합적 양상을 만들어낸다.

On the assumption that the craftsmen of Zhuangzi represent an ideal model of life, this paper organized the way of life of Zhuangzi. First of all, this paper identifies the existence of a communication method called 心(xin, mind) and 氣(qi, vital energy) in Zhuangzi. Afterwards, it reveals that these two modes of communication can be read from the perspective of Zhuangzi's technology, and on this basis it constructs Zhuangzi's artisanal life. Specifically, the artisan's life can be divided into three parts: before the technology performance process, the technology performance process itself, and after the technology performance process. And the characteristics of each step are explained by the concept of xin (心) and qi (氣).

본 연구에서는 가정에서도 임산부가 손쉽게 태아의 심장 소리를 측정할 수 있는 소형 초음파 측정기의 프로토 타입 모델을 설계 제작 하였다. 태아의 심장 박동은 내장된 블루투스 스피커를 통해 확인 할 수 있다. 심장 박동 주파수 에 따라 led의 색깔이 다양하게 표출된다. 초음파 진동자, 블루투스 스피커와 스마트폰이 연동된다. 간단한 심장박동 측정을 통해 태아에 발생 될 수 있는 이상 징후를 미연에 발견할 수 있음을 확인 하였다. 소아와 성인의 경우에도 급성으 로 발생되는 심근경색, 심부전등과 같은 심장 이상 징후 발견을 통해 돌연사를 미연에 방지 하는 용도로 유용하게 사용 할 수 있다.

In the paper, A prototype Fetal Heart Monitor, mini – size, was designed and produced for pre-mothers to measure the rate and rhythm of their features’s heart at home.Pre-mothers could listen fetal heart rhythm through an inner bluetooth speaker ant the monitor. LED colors show the frequency of fetal heart rate variability on the monitor. All measured health information ,by ultrasonic resonator and bluetooth speaker, is linked to a mother’s smart phone. A test verified this simple measuring device helps users discover the symptoms of fetal health. Patients using at home devices usefully prevent sudden cardiac death and myocardial infraction by discovering symptoms.

We present a mathematical model of left heart governed by the partial differential equations. This heart is coupled with a lumped model of the whole circulatory system governed by the ordinary differential equations. The immersed boundary method is used to investigate the intracardiac blood flow and the cardiac valve motions of the normal circulation in humans. We investigate the intraventricular velocity field and the velocity curves over the mitral ring and across outflow tract. The pressure and flow are also measured in the left and right heart and the systemic and pulmonary arteries. The simulation results are comparable to the existing measurements.

We investigated the energistics of the physiological heart model by comparing predictive indexes of the myocardial oxygen consumption (MOC), such as tension-time index (R), tension-time or force-time inteual (FTI), rate-pressure product (RPP), pressure-work index, and systolic pressure-volume area (PVA) when using the electro-hydraulic left ventricular device (LVAD). We developed the model of LVAD incorporated the closed-loop cardiovascular system with a baroreceptor which can control heart rate and time-varying elastance of left and right ventricles. On considering the benefit of the LVAD, the effects of various operation modes, especially timing of assistance, were evaluated using this coupled computer model. Overall results of the computer simulation shows that our LVAD can unload the ischemic (less contractile) heart by decreasing the MU and increasing coronary flow. Because the pump ejection at the end diastolic phase of the natural heart may increase the afterload of the left ventricle, the control scheme of our LVAD must prohibit ejecting at this time. Since the increment of coronary flow is proportional to the peak aortic pressure after ventricle contraction, the LVAD must eject immediately following the closure of the aortic valve to increase oxygen availability.

Objectives: The objective of this study is to demonstrate the cardioprotective effects of Salvia Miltiorrhiza Radix (SMR) on the pressure overload (PO)-induced heart failure (HF) by transverse aortic constriction (TAC) in C57BL/6 mice through possible antioxidant effects. Methods: The mortality, body and heart weights, antioxidant defense system of the heart and histopathology of heart were analyzed. The obtained results were compared with resveratrol, in which potent cardioprotective effects on TAC mice model were already proved at a dose level of 10 mg/kg by antioxidant effects, as reference in this experiment. Results: Significant increases of mortalities, heart weights, and hypertrophic, lytic and focal fibrotic histological changes in the left ventricles were found with defects of heart antioxidant defense systems - the increases of heart cortex MDA contents, decreases of GSH contents, SOD and CAT activities in TAC control mice as compared with sham vehicle control mice, respectively. However, these HF signs induced by TAC surgery through PO and destroys heart antioxidant defense systems were significantly and dose-dependently inhibited by 14 days continuous oral treatment of SMR 500, 250 and 125 mg/kg, similar to those of resveratrol 10 mg/kg in SMR 125 mg/kg. Conclusions: The results obtained in this study propose that oral administration of SMR potently alleviates PO-induced HF by TAC, through augmentation of heart antioxidant defense system.

Background/Aims: Angiotensin II in the failing heart initially helps to maintain cardiac output and blood pressure, but ultimately accelerates its deterioration. In this study, we established a model of arrhythmia-induced heart failure (HF) in zebrafish and investigated the role of renin-angiotensin-aldosterone system (RAAS) modulation by using an angiotensin II type 1 receptor blocker, fimasartan, through the assessment of cellular and physiologic responses, morbidity, and mortality. Methods: HF was induced in zebrafish larvae by exposure to 20 μM terfenadine. Morphologic, physiologic, and functional parameters were assessed in the presence or absence of fimasartan treatment. Results: Zebrafish exposed to terfenadine showed marked dilatation of the ventricle and reduced systolic function. Treatment with terfenadine was associated with 10-fold higher expression of atrial natriuretic peptide (p < 0.001 vs. vehicle), increased p53 mRNA expression, and chromatin fragmentation in the TUNEL assay, all of which were significantly reduced by fimasartan treatment. Moreover, fimasartan improved fractional shortening (terfenadine + fimasartan 16.9% ± 3.1% vs. terfenadine + vehicle 11.4% ± 5.6%, p < 0.05) and blood flow (terfenadine + fimasartan 479.1 ± 124.1 nL/sec vs. terfenadine + vehicle 273.0 ± 109.0 nL/sec, p < 0.05). Finally, treatment with fimasartan remarkably reduced mortality (terfenadine + fimasartan 36.0% vs. terfenadine + vehicle 96.0%, p < 0.001). Conclusions: Fimasartan effectively protected against the progression of HF in zebrafish by improving hemodynamic indices, which improved survival. A reduction in apoptotic cell death and an improvement in hemodynamics may be the mechanisms behind these effects. Further human studies are warranted to evaluate the possible role of fimasartan in the treatment of HF.

Objectives: The importance of the prediction of coronary heart disease (CHD) has been recognized in Korea; however, few studies have been conducted in this area. Therefore, it is necessary to develop a method for the prediction and classification of CHD in Koreans. Methods: A model for CHD prediction must be designed according to rule-based guidelines. In this study, a fuzzy logic and decision tree (classification and regression tree [CART])-driven CHD prediction model was developed for Koreans. Datasets derived from the Korean National Health and Nutrition Examination Survey VI (KNHANES-VI) were utilized to generate the proposed model. Results: The rules were generated using a decision tree technique, and fuzzy logic was applied to overcome problems associated with uncertainty in CHD prediction. Conclusions: The accuracy and receiver operating characteristic (ROC) curve values of the propose systems were 69.51% and 0.594, proving that the proposed methods were more efficient than other models.