• Title/Summary/Keyword: Functional Prediction

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Predicting Thermo-mechanical Characteristics from the 2nd Phase Fraction of Al-AlN Composites for LED Heat Sinks with FEM (유한요소해석을 이용한 방열용 Al-AlN 복합재의 제2상 분율에 따른 열-기계적 특성예측)

  • Yoon, Juil
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.17 no.5
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    • pp.137-142
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    • 2018
  • With the development of the electronic-materials industry, multi-functional metal-composite materials with high thermal conductivity and low thermal expansion must be developed for high reliability and high life expectancy. This paper is a preliminary study on the manufacturing technology of gas reaction control composite material, focusing on the prediction of the equivalent thermal properties of Al-AlN composite materials. Numerical equivalent property values are obtained by using finite element analysis and compared with theoretical formulas. Al-AlN composite materials should become the optimal composite material when the proportion of the reinforcing phase is less than 0.5.

INERTIAL PROXIMAL AND CONTRACTION METHODS FOR SOLVING MONOTONE VARIATIONAL INCLUSION AND FIXED POINT PROBLEMS

  • Jacob Ashiwere Abuchu;Godwin Chidi Ugwunnadi;Ojen Kumar Narain
    • Nonlinear Functional Analysis and Applications
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    • v.28 no.1
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    • pp.175-203
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    • 2023
  • In this paper, we study an iterative algorithm that is based on inertial proximal and contraction methods embellished with relaxation technique, for finding common solution of monotone variational inclusion, and fixed point problems of pseudocontractive mapping in real Hilbert spaces. We establish a strong convergence result of the proposed iterative method based on prediction stepsize conditions, and under some standard assumptions on the algorithm parameters. Finally, some special cases of general problem are given as applications. Our results improve and generalized some well-known and related results in literature.

Small CNN-RNN Engraft Model Study for Sequence Pattern Extraction in Protein Function Prediction Problems

  • Lee, Jeung Min;Lee, Hyun
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.8
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    • pp.49-59
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    • 2022
  • In this paper, we designed a new enzyme function prediction model PSCREM based on a study that compared and evaluated CNN and LSTM/GRU models, which are the most widely used deep learning models in the field of predicting functions and structures using protein sequences in 2020, under the same conditions. Sequence evolution information was used to preserve detailed patterns which would miss in CNN convolution, and the relationship information between amino acids with functional significance was extracted through overlapping RNNs. It was referenced to feature map production. The RNN family of algorithms used in small CNN-RNN models are LSTM algorithms and GRU algorithms, which are usually stacked two to three times over 100 units, but in this paper, small RNNs consisting of 10 and 20 units are overlapped. The model used the PSSM profile, which is transformed from protein sequence data. The experiment proved 86.4% the performance for the problem of predicting the main classes of enzyme number, and it was confirmed that the performance was 84.4% accurate up to the sub-sub classes of enzyme number. Thus, PSCREM better identifies unique patterns related to protein function through overlapped RNN, and Overlapped RNN is proposed as a novel methodology for protein function and structure prediction extraction.

The Usefulness of Myocardial SPECT for the Preoperative Cardiac Risk Evaluation in Noncardiac Surgery (비심장 수술 환자에서 수술 전후 심장사건의 위험도 평가를 위한 심근관류 SPECT의 유용성)

  • Lim, Seok-Tae;Lee, Dong-Soo;Kang, Won-Jun;Chung, June-Key;Lee, Myung-Chul
    • The Korean Journal of Nuclear Medicine
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    • v.33 no.3
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    • pp.273-281
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    • 1999
  • Purpose: We investigated whether myocardial SPECT had additional usefulness to clinical, functional or surgical indices for the preoperative evaluation of cardiac risks in noncardiac surgery. Materials and Methods: 118 patients (M: F=66: 52, $62.7{\pm}10.5$ years) were studied retrospectively. Eighteen underwent vascular surgeries and 100 nonvascular surgeries. Rest T1-20l/ stress Tc-99m-MIBI SPECT was performed before operation and cardiac events (hard event: cardiac death and myocardial infarction; soft event: ischemic ECG change, congestive heart failure and unstable angina) were surveyed through perioperative periods ($14.6{\pm}5.6$ days). Clinical risk indices, functional capacity, surgery procedures and SPECT findings were tested for their predictive values of perioperative cardiac events. Results: Perioperative cardiac events occurred in 25 patients (3 hard events and 22 soft events). Clinical risk indices, surgical procedure risks and SPECT findings but functional capacity were predictive of cardiac events. Reversible perfusion decrease was a better predictor than persistent decrease, Multivariate analysis sorted out surgical procedure risk (p=0.0018) and SPECT findings (p=0.0001) as significant risk factors. SPECT could re-stratify perioperative cardiac risks in patients ranked with surgical procedures. Conclusion : We conclude that myocardial SPECT provides additional predictive value to surgical type risks as well as clinical indexes or functional capacity for the prediction of preoperative cardiac events in noncardiac surgery.

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Models for Predicting Five Jang Biological Ages with Clinical Biomarkers (임상 생체지표를 이용한 오장생체나이 추정 모델)

  • Kim, Tae-Hee;Kim, Seok;Bae, Chul-Young;Kang, Young-Gon;Cho, Kyung-Hee;Kwon, Su-Kyung;Park, Mei-Hua
    • The Journal of the Society of Korean Medicine Diagnostics
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    • v.15 no.2
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    • pp.175-190
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    • 2011
  • Objectives: Even though there has been no consensus on the concept of viscera organ between the oriental and western medicine, we tried to investigate the correlation between clinical biomarkers of five Jang and chronological age and develop the models for predicting five Jang biological ages by statistical analysis. Methods: We obtained data from about 120,000 subjects who visited health promotion centers for health promotion and disease prevention from January 2004 to June 2009. Participants were included if they were over 20 years old, and excluded if reported to have cardiovascular disease or other serious medical illness such as cancer, malignant hypertension, uncontrolled diabetes, cardiopulmonary insufficiency, liver disease, pancreatic disease or renal disease. Among the clinical biomarkers obtained, we selected the biomarkers which were associated with the function of 5 Jang in previous studies, or showed statistically significant correlation with age. Multiple regression models were used for building prediction models of biological age after adjusting for potential confounders for men and women, respectively. Pearson correlation coefficient was calculated to examine the linear relationship between age and various biomarkers, and multiple regression analysis was used for building the prediction models of five Jang biological ages for men and women, respectively. All statistical data analysis was performed by using SPSS Version 12.0 software and statistical significance was obtained if p<0.05. Results: For males, the best models were developed using 12, 2, 8, 3, and 4 biomarkers for predicting biological ages of heart, lung, liver, pancreas, and kidney, respectively (R2 = 0.57, 0.43, 0.11, 0.24, and 0.93, respectively). Similar to males, for the females, 10, 2, 8, 3, and 4 biomarkers were selected as the models respectively (R2 = 0.76, 0.44, 0.14, 0.38, and 0.89, respectively). Conclusions: As we have developed for the first time the models for predicting five Jang biological ages with common clinical biomarkers, it is expected that these models may be used as clinical supplementary tools in the evaluation of aging status and functional decline of five Jang according to age in health promotion centers and private clinics. At the same time, it is considered that the use as objective tools to evaluate aging status and functional decline of each Jang.

Discovery of Deleterious nsSNPs on the Genes related to the Lipid Metabolism and Prediction of Changes on Biological Function in Korean Native Chicken (한국 재래닭에서 지질대사 관련 유전자에 존재하는 유해성 nsSNP 발굴 및 생물학적 기능 예측)

  • Oh, Jae-Don;Shin, Dong-Hyun;Shin, Sang-Soo;Yoon, Chang;Song, Ki-Duk
    • Korean Journal of Poultry Science
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    • v.43 no.4
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    • pp.263-272
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    • 2016
  • In this study, we aimed to identify the nonsynonymous single nucleotide polymorphisms (nsSNPs) located in lipid metabolism-related genes because lipids are an important factor affecting the taste and flavor of meat, and they predict the functional consequences. The results showed that we identified 139 common nsSNPs in all five Korean native chicken (KNC) lines from the 81 genes related to lipid metabolism. Furthermore, sorting intolerant from tolerant (SIFT) and polymorphism phenotyping v2 (Polyphen-2) analyses predicted that among the genes, 14 nsSNPs of nine genes might be deleterious. Protein domain prediction of the nine genes revealed that all deleterious nsSNPs identified in this study were located outside the functional domain. This observation suggests that the common deleterious nsSNPs might be dispensable and have a minor effect on the traits of the KNCs.

Prediction of Pathway and Toxicity on Dechlorination of PCDDs by Linear Free Energy Relationship (다이옥신의 환원적 탈염화 분해 경로와 독성 변화예측을 위한 LFER 모델)

  • Kim, Ji-Hun;Chang, Yoon-Seok
    • Journal of Korean Society of Environmental Engineers
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    • v.31 no.2
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    • pp.125-131
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    • 2009
  • Reductive dechlorination of polychlorinated dibenzo-p-dioxins (PCDDs) and its toxicity change were predicted by the linear free energy relationship (LFER) model to assess the zero-valent iron (ZVI) and anaerobic dechlorinating bacteria (ADB) as electron donors in PCDDs dechlorination. Reductive dechlorination of PCDDs involves 256 reactions linking 76 congeners with highly variable toxicities, so is challenging to assess the overall effect of this process on the environmental impact of PCDD contamination. The Gibbs free energies of PCDDs in aqueous solution were updated to density functional theory (DFT) calculation level from thermodynamic results of literatures. All of dechlorination kinetics of PCDDs was evaluated from the linear correlation between the experimental dechlorination kinetics of PCDDs and the calculated thermodynamics of PCDDs. As a result, it was predicted that over 100 years would be taken for the complete dechlorination of octachlorinated dibenzo-p-dioxin (OCDD) to non-chlorinated compound (dibenzo-p-dioxin, DD), and the toxic equivalent quantity (TEQ) of PCDDs could increase to 10 times larger from initial TEQ with the dechlorination process. The results imply that the single reductive dechlorination using ZVI or ADB is not suitable for the treatment strategy of PCDDs contaminated soil, sediment and fly ash. This LFER approach is applicable for the prediction of dechlorination process for organohalogen compounds and for the assessment of electron donating system for treatment strategies.

Quality Prediction of Eggs Treated in Combination with Gamma Irradiation and Chitosan Coating Using Response Surface Methodology

  • Lee, Kyung-Heang;Jung, Samooel;Ham, Jun-Sang;Lee, Jun-Heon;Lee, Soo-Kee;Jo, Cheo-Run
    • Journal of Animal Science and Technology
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    • v.53 no.3
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    • pp.253-259
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    • 2011
  • The aim of this work was to determine the method and predict the optimum conditions for egg quality stored for 7 days when combination treatments of irradiation and chitosan coating were applied using response surface methodology (RSM). A central composite design was chosen for the RSM in this study and the factors were irradiation dose (0~2 kGy) and concentration of chitosan coating material (0~2%). Performance of the irradiation and chitosan coating were evaluated by analyzing the egg quality and functional property factors. The predicted maximum level of Haugh units and foaming ability calculated by a developed model were 74.19 at 0 kGy of irradiation with coating by 0.96% chitosan solution and 50.83 mm at 2.0 kGy with 1.01%, respectively. The predicted minimum value of foam stability and 2-thiobarbituric acid reactive substances (TBARS) value were 2.97 mm at 0.39 kGy with 0.21% and 0.54 mg malonaldehyde/kg egg yolk at 0 kGy with 0.90% of chitosan solution, respectively. Results clearly showed that gamma irradiation negatively affected the Haugh unit and TBARS but positively affected the foaming capacity. The estimated value from the developed model by RSM was verified by no statistical difference with observed value. Therefore, RSM can be a good tool for optimization and prediction of egg quality when 2 or more treatments are combined. However, one should decide the target quality first to achieve a successful implementation of this technology.

Prediction of Time to Recurrence and Influencing Factors for Gastric Cancer in Iran

  • Roshanaei, Ghodratollah;Ghannad, Masoud Sabouri;Safari, Maliheh;Sadighi, Sanambar
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.6
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    • pp.2639-2642
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    • 2012
  • Background: The patterns of gastric cancer recurrence vary across societies. We designed the current study in an attempt to evaluate and reveal the outbreak of the recurrence patterns of gastric cancer and also prediction of time to recurrence and its effected factors in Iran. Materials and Methods: This research was performed from March 2003 to February 2007. Demographic characteristics, clinical and pathological diagnosis and classification including pathologic stage, tumor grade, tumor site and tumor size in of patients with GC recurrent were collected from patients' data files. To evaluate of factors affected on the relapse of the GC patients, gender, age at diagnosis, treatment type and Hgb were included in the research. Data were analyzed using Kaplan-Meier and logistic regression models. Results: After treatment, 82 patients suffered recurrence, 42, 33 and 17 by the ends of first, second and third years. The mean ( SD) and median ( IQR) time to recurrence in patients with GC were 25.5 (20.6-30.1) and 21.5 (15.6-27.1) months, respectively. The results of multivariate analysis logistic regression showed that only pathologic stage, tumor grade and tumor site significantly affected the recurrence. Conclusions: We found that pathologic stage, tumor grade and tumor site significantly affect on the recurrence of GC which has a high positive prognostic value and might be functional for better follow-up and selecting the patients at risk. We also showed time to recurrence to be an important factor for follow-up of patients.

Prediction of Non-Genotoxic Carcinogenicity Based on Genetic Profiles of Short Term Exposure Assays

  • Perez, Luis Orlando;Gonzalez-Jose, Rolando;Garcia, Pilar Peral
    • Toxicological Research
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    • v.32 no.4
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    • pp.289-300
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    • 2016
  • Non-genotoxic carcinogens are substances that induce tumorigenesis by non-mutagenic mechanisms and long term rodent bioassays are required to identify them. Recent studies have shown that transcription profiling can be applied to develop early identifiers for long term phenotypes. In this study, we used rat liver expression profiles from the NTP (National Toxicology Program, Research Triangle Park, USA) DrugMatrix Database to construct a gene classifier that can distinguish between non-genotoxic carcinogens and other chemicals. The model was based on short term exposure assays (3 days) and the training was limited to oxidative stressors, peroxisome proliferators and hormone modulators. Validation of the predictor was performed on independent toxicogenomic data (TG-GATEs, Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System, Osaka, Japan). To build our model we performed Random Forests together with a recursive elimination algorithm (VarSelRF). Gene set enrichment analysis was employed for functional interpretation. A total of 770 microarrays comprising 96 different compounds were analyzed and a predictor of 54 genes was built. Prediction accuracy was 0.85 in the training set, 0.87 in the test set and increased with increasing concentration in the validation set: 0.6 at low dose, 0.7 at medium doses and 0.81 at high doses. Pathway analysis revealed gene prominence of cellular respiration, energy production and lipoprotein metabolism. The biggest target of toxicogenomics is accurately predict the toxicity of unknown drugs. In this analysis, we presented a classifier that can predict non-genotoxic carcinogenicity by using short term exposure assays. In this approach, dose level is critical when evaluating chemicals at early time points.