ARQ Protocols in Cognitive Decode-and-Forward Relay Networks: Opportunities Gain

In this paper, two novel automatic-repeat-request (ARQ) based protocols were proposed, which exploit coop- eration opportunity inherent in secondary retransmission to create access opportunities. If the signal was not decoded correctly in destination, another user can be acted as a relay to reduce retransmission rounds by relaying the signal. For comparison, we also propose a Direct ARQ Protocol. Specif- ically, we derive the exact closed-form outage probability of three protocols, which provides an effective means to evalu- ate the effects of several parameters. Moreover, we propose a new metric to evaluate the performance improvement for cognitive networks. Finally, Monte Carlo simulations were presented to validate the theory analysis, and a comparison is made among the three protocols

On mountain pass theorem and its application to periodic solutions of some nonlinear discrete systems

We obtain a new quantitative deformation lemma, and then gain a new mountain pass theorem. More precisely, the new mountain pass theorem is independent of the functional value on the boundary of the mountain, which improves the well known results (\cite{AR,PS1,PS2,Qi,Wil}). Moreover, by our new mountain pass theorem, new existence of nontrivial periodic solutions for some nonlinear second-order discrete systems is obtained, which greatly improves the result in \cite{Z04}.Comment: 11 page

Chemically Modified Cellulosic Materials as Multi-Functional Agents in Polymer Composites

Comparative flame retardancy of micro wood fiber plastic composites (WPCs) with fire retardants (1,2-bis(pentabromophenyl) ethane, metal hydroxides and nanoclay) was studied. The fire additives (1,2-bis(pentabromophenyl) ethane as well as magnesium hydroxide) obviously enhanced the fire retarding properties of WPCs. Especially, 1,2-bis(pentabromophenyl) ethane significantly reduced the total heat release as well as heat release rate. In addition, a synergistic effect of 1,2-bis(pentabromophenyl) and nanoclay was achieved for the enhanced fire retarding performance of WPCs. A copolymer of cellulose nanocrystals (CNCs) and poly(N-vinylcaprolactam) (PVCL) (PVCL-g-CNCs) for use as thermally-responsive polymers with low critical solution temperatures (LCSTs) was synthesized via atom transfer radical polymerization (ATRP). The rod like morphology of CNCs was well preserved after the grafting modification. The dynamic rheology measurement confirmed the thermally induced phase transition behavior of PVCL-g-CNCs aqueous suspensions (1.0 wt%) with the LCST value at 36 oC. The surface of CNCs was modified with poly(butyl acrylate) (PBA) and poly(methyl methacrylate) (PMMA) through ATRP technique. The successful grafting modification led to the increased thermal stability of modified CNCs (MCNCs). The increase in Young’s modulus of more than 25-fold and in tensile strength of about 3 times for 7 wt% MCNCs/PBA-co-PMMA nanocomposites was achieved compared to those of neat PBA-co-PMMA. A micro-phase separated morphology (PBA- soft domains, and PMMA- as well as CNCs- hard domains) of MCNCs/PBA-co-PMMA nanocomposites was also observed. In addition, the interfacial miscibility and phase separated morphology of PMMA-g-CNCs (PMCNCs)/PBA-co-PMMA nanocomposites were further studied. The 10 wt% PMCNCs/PBA-co-PMMA nanocomposites showed increases in Young’s modulus of more than 20-fold and in tensile strength of about 3-fold when compared to those of neat PBA-co-PMMA. Morphological analysis indicated the presence of microphase separation in PMCNCs/PBA-co-PMMA nanocomposites. Therefore, the surface modification of CNCs played a crucial role in reinforcing mechanical performance, controlling interfacial miscibility and tuning phase morphology of the nanocomposites

당뇨 환자에서 기계학습을 이용한 생리학적 지표 및 위험요인이 심혈관계 예후에 미치는 영향에 대한 검증

학위논문 (박사) -- 서울대학교 대학원 : 의과대학 의학과, 2020. 8. 구본권.Background and Objectives: Current European Society of Cardiology and European Association for Cardio-Thoracic Surgery guidelines recommend fractional flow reserve (FFR) measurement as a standard invasive method to identify the ischemia-causing coronary lesions. However, patients after therapeutic procedures still suffer adverse cardiovascular events even after deferral of revascularization according to FFR, potentially due to the presence of microvascular dysfunction that may cause ischemia or foster the progression of obstructive disease. Coronary microvascular dysfunction (CMD) is more frequently observed in patients with diabetes mellitus (DM) and is a major determinant of long-term adverse outcome. Since comprehensive physiologic assessment enables the evaluation of microvascular function which could not be fully demonstrated by angiography, we sought to investigate the prognostic implication of invasive physiologic index-defined CMD in patients with DM and coronary artery disease (part I). Increasing evidence showed that machine learning can provide tools to assist physicians during diagnosis and treatment of diverse clinical conditions, including myocardial infarction. Therefore, we sought to study using machine learning algorithms with an expanded sample size, to validate the physiologic indices and find out the valuable risk factors for cardiovascular outcomes in patients with DM and coronary artery disease (part II). Methods: Part 1: Two hundred and eighty-three patients with available FFR and index of microcirculatory resistance (IMR) were selected from the 3V FFR-FRIENDS study. Patients were classified according to the presence of DM and CMD into group A (DM-, CMD-), group B (DM-, CMD+), group C (DM+, CMD-), and group D (DM+, CMD+). Primary outcome was a major adverse cardiac event (MACE, a composite of cardiac death, myocardial infarction and ischemia-driven revascularization) at 2 years. Part 2: Seven hundred and fourteen patients (235 patients with DM) with deferred coronary revascularization according to FFR (>0.80) were included. This registry hitherto is the biggest cohort whose patients were fully assessed by comprehensive physiologic indices. Comprehensive physiologic evaluation, including coronary flow reserve (CFR), IMR and FFR, was performed at the time of revascularization deferral. The median values of CFR (2.88), FFR (0.88) and IMR (17.85) were used to classify high or low CFR, FFR, and IMR groups. Information gains of variables with 5,000-permutation resampling, minimal depth and Boruta algorithms were used for feature selection. Furthermore, prognostic models were compared using c-index. In this part, patient-oriented composite outcome (POCO) at 5 years, including all-cause death, any myocardial infarction, and any revascularization, was the primary outcome. Results: Part 1: DM population showed significantly higher risk of MACE compared with non-DM population (HR 4.88, 95% CI 1.54-15.48, p=0.003). MACE at 2-year among four groups were 2.2%, 2.0%, 7.0%, and 18.5%, respectively. Group D showed significantly higher risk of MACE compared with group A (HR 8.98, 95% CI 2.15-37.41, p=0.003). The multivariable regression analysis showed the presence of DM and CMD was an independent predictor of 2-year MACE (HR 11.24, 95% CI 2.53-49.88, p=0.002) and integrating CMD into a model with DM increased discriminant ability (C-index 0.683 vs. 0.710, p=0.010, integrated discrimination improvement 0.015, p=0.040). Part 2: Compared with non-DM population, DM population showed a higher risk of POCO at 5 years (HR 2.49, 95% CI 1.64-3.78, p<0.001). Low CFR group had a higher risk of POCO than high CFR group (HR 3.22, 95% CI 1.74-5.97, p<0.001) only in DM population. In contrast, CFR values could not differentiate the risk of POCO in non-DM population. There was a significant interaction between CFR and the presence of DM regarding the risk of POCO (interaction p=0.025). Independent predictors of POCO at 5 years were low CFR and family history of coronary artery disease in DM population, and percent diameter stenosis and multi-vessel disease in non-DM population. Among all angiographic and physiologic parameters, CFR showed the highest information gain. In DM population, CFR, consistently, was the most important feature followed by Age and FFR using Minimal Depth algorithm. Moreover, CFR was the valuable features to predict POCO using Boruta algorithm in DM population. In DM population, adding clinical risk factors (c-index 0.75 0.65-0.85, p=0.500) or clinical risk factors and invasive parameters together (c-index 0.75, 95%CI 0.65-0.85, p=0.535) into features from Boruta (c-index 0.73, 95% CI 0.63-0.83) did not show a better discriminant ability. Conclusions: The patients with DM and CMD were associated with increased risk of cardiovascular events. Integration of CMD improved risk stratification to predict the occurrence of MACE. The importance of risk factors for cardiovascular outcomes is different according to the presence of DM. CFR consistently was the important prognostic factor in patients with DM regardless of methods. Machine learning could help find out the most effective combination with acceptable numbers of features for better outcome prediction.배경 및 목적: 유럽심장학회 (European Society of Cardiology) 및 유럽심장외과협회 (European Society of Cardio-Thoracific Academy) 지침에서 관상동맥 허혈 진단을 위한 침습적 표준 방법으로 분획혈류예비력 (FFR, Fractal Flow Reserve) 측정을 권고하고 있음. 그러나 표준지침으로 치료받은 일부 환자들은 여전히 심혈관 사건을 겪음. 이는 잠재적으로 허혈을 유발하거나 폐쇄성 질환의 진행을 촉진할 수 있는 미세혈관 기능장애 때문임. 이런 미세기능장애는 관상동맥 조영술로 평가할 수 없음. 관상동맥미세혈관기능장애는 당뇨환자에서 더 자주 생기고 장기 예후의 주요 위험요인임. 종합적인 생리학적 평가로 미세혈관 기능의 평가가 가능하기 때문에 당뇨 및 관상동맥질환이 있는 환자에서 대한 침습적 생리지표로 정의한 미세혈관 장애가 예후에 미치는 영향을 조사하고자 본 연구의 Part 1을 시행하였음. 또 샘플 크기가 확장된 본 연구의 Part 2에서는 기계학습을 이용하여 당뇨 환자에서 생리학적 지표 및 위험요인이 심혈관계 예후에 미치는 영향을 검증하고자 시행하였음. 방법: 본 연구의 첫번째 부분은 3V FFR-FRIENS study에서 사용 가능한 FFR 및 index of microcirculatory resistance (IMR)가 있는 환자 283명이 선택됨. CMD (coronary microvascular dysfunction)는 IMR≥25U로 정의함. 환자는 DM과 CMD에 따라 그룹 A(DM-, CMD-), 그룹 B(DM-, CMD+), 그룹 C(DM+, CMD-), 그룹 D(DM+, CMD+)로 분류됨. 이 선행 연구에서 1차 평가변수는 2년의 major adverse cardiac event (MACE, 심장사, 심근경색 및 허혈성 기반 혈관재개통술)로 정의함. 두번째 부분은 Korea-Japan-Spain registry에서 FFR (>0.80)에 따라 관상동맥 재개통술이 지연되고 관상동맥혈류예비력(CFR, coronary flow reserve), IMR을 포함한 종합적인 생리학적 평가가 이루어진 환자 714명(DM을 가진 환자 235명)이 선택됨. CFR, IMR, FFR의 높은 그룹 또는 낮은 그룹을 분류하는데 중간값 CFR(2.88), FFR(0.88), IMR(17.85)이 사용됨. 이 부분의 1차 평가변수는 POCO (patient-oriented composite outcome) 5년 내의 모든 원인 사망, 심근경색, 모든 혈관재개통술로 정의함. 결과: 첫 부분에서 당뇨 환자들은 비당뇨환자에 비해 MACE의 위험성이 높음(HR 4.88, 95% CI 1.54-15.48, p=0.003). 4개 그룹의 2년 MACE는 각각 2.2%, 2.0%, 7.0%, 18.5%. 그룹 D는 그룹 A에 비해 MACE의 위험도가 현저히 높음(HR 8.98, 95% CI 2.15-37.41, p=0.003). 다변량 회귀 분석에서 2년 MACE의 독립적인 예측인자는 CMD를 동반한 당뇨환자 (HR 11.24, 95% CI 2.53-49.88, p=0.002). CMD를 당뇨에 추가했을때 예측 능력이 향상됨(C-index 0.683 vs 0.710, p=0.010). 두번째 부분에서, 비당뇨군과 비교했을 때, 당뇨군은 5년 POCO의 위험성이 더 높음(HR 2.49, 95% CI 1.64-3.78, p<0.001). 당뇨군에서 낮은 CFR 그룹은 높은 CFR 그룹보다 POCO의 위험이 높음(HR 3.22, 95% CI 1.74-5.97, p<0.001). CFR 값은 비당뇨군에서 POCO의 위험을 구별할 수 없음. POCO의 위험성을 예측함에 있어서 CFR과 당뇨 사이에 유의한 상호작용이 있었다(interaction p=0.025). 5년 POCO에 대한 독립적인 예측 인자는 당뇨군에서 낮은 CFR과 관상동맥 가족력, 비당뇨군에서 관상동맥 질환의 percent diameter stenosis와 다혈관 질환임. 당뇨군에서 POCO를 예측함에 있어서 다른 요인에 비해 CFR은 가장 많은 정보를 가지고 있었음. "Minimum Depth" 알고리즘을 사용했을 때 CFR은 가장 중요한 예측요인이고 "Boruta" 알고리즘을 사용했을 때 의미 있는 요인으로 나타남. 당뇨군에서 임상적 위험 인자(c-index 0.75 0.65-0.85, p=0.500) 혹은 임상적 시술적 위험인자(c-index 0.75, 95%CI 0.65-0.85, p=0.535)를 동시에 Boruta 알고리즘에서 선택되어진 위험인자로 구성된 모델(c-index 0.73, 95% CI 0.63-0.83)에 추가하였을 때 모델의 예측력은 유의하게 높아지지 않았음. 결론: CMD를 동반한 당뇨는 심혈관 질환 위험의 증가와 관련이 있음. 당뇨환자에서 CMD의 추가는 MACE발생의 예측력을 높임. 관상동맥 생리학적 지표와 위험 인자들이 예후에 미치는 역할은 당뇨여부에 따라 다름. 어떤 방법을 사용하는지 불구하고 CFR은 예후를 예측하는 중요한 지표임. 기계학습은 가장 효과적이고 효율적인 변수조합을 찾아 예후를 더 잘 예측할 수 있음.Introduction 2 First Part 4 Methods 4 Results 7 Second Part 10 Methods 10 Results 16 Discussion 19 Conclusions 26 References 28 국문초록 58Docto