Predicted Research Articles

Crack propagation analysis and strength prediction of bonded joints based on XFEM-CZM coupling method

Crack propagation analysis and strength prediction of bonded joints based on XFEM-CZM coupling method

Which approach to modeling? Predicting infectious disease dynamics in epidemics

Disease outbreaks can be devastating to many nations. Interventions of all kinds are run alongside treatments or preventive measures. The effectiveness of the measures taken depends on the number of individuals who are susceptible, exposed, infectious or recovered. These in turn are a function of the nature of the disease: The mode of transmission, the risk of infection reproduction number and incubation period among others. Cases of epidemics are often difficult to contain owing to the fact that no one knows the dynamics of such diseases. In the absence of information the preparation and response to such disease is erratic and may entirely depend on predictions made. Epidemiologists and/or statisticians use the available data and parameterize the key indicators of a disease, do simulations so as to enable them make estimations. Wrong prediction or modeling may lead to huge variation in the predicted values and hence under-preparedness or over-preparedness. Both cases are costly. When properly done modeling can and has become extremely useful. This study reviews two approaches to modeling: The deterministic and the stochastic with merits and demerits of each discussed. The importance of modeling is also reviewed. It was found out that stochastic models are inevitably suitable when the population is small. For larger population the effect of randomness becomes negligible and hence deterministic approach which is relatively easier to model may be used. Stochastic model, as it was noticed, is also good in giving the range of the much desired numbers at every category of the disease. Key words: Disease modeling, deterministic, stochastic, risk of infection, infectiousness, basic reproduction number.

Sino-DPRK Relations and Chinese Perception toward North Korea’s Nuclear Issue: Meta-Analysis on Chinese Literature since 2012

This paper examined the perceptions of Chinese scholars on Sino-DPRK relations and North Korea’s nuclear issue through meta-analysis of arguments of 102 articles published from January 2012 to June 2020. As a result of a comprehensive investigation, this paper found six main tendencies on Chinese academic discourse. First, although Sino-DPRK relations became strained at times, most articles viewed it as a friendly alliance and a special relationship. Some also argue that it should be transformed into normal diplomatic relations between sovereign states. Second, while acknowledging North Korea’s role as a strategic buffer, Chinese scholars tend to believe that Pyongyang’s nuclear program not only threatens China’s national security and interests but also allows the United States to strengthen the South Korea-U.S. alliance and implement strategic deterrence against Beijing. Third, in many scholars’ predictions, the North’s nuclear weapons are likely to cause nuclear proliferation and an arms race in East Asia. Fourth, scholars claim that the North’s nuclear issue stem not only from the Cold War but also from the post-Cold War architecture on the Korean Peninsula. In this regard, some of them support the North’s nuclear development, emphasizing a Korean unification led by Pyongyang, a strategic balance between the two Koreas, and lessons from the Indian and Iraqi cases. Fifth, most papers find the root cause of Pyongyang’s nuclear development as being from U.S. military threats, yet the authors think situational changes made the North’s nuclear policy more entrenched. Sixth, the authors stressed Sino-U.S. cooperation is necessary to resolve nuclear issue, criticizing the lack of Washington’s sincerity. They expect Beijing to play an active role in this problem based on its special relationship with Pyongyang despite some limitations.

HEMŞİRELERDE OTONOMİ DÜZEYİNİN MESLEKİ BENLİK SAYGISINA ETKİSİ

Bu çalışmanın amacı, hemşirelerde otonomi düzeyinin mesleki benlik saygısına etkisinin incelenmesidir. Araştırma ilişkisel tarama modeli kullanılarak tanımlayıcı tipte yapılmıştır. Araştırma verileri bir il merkezinde yer alan dört kamu hastanesinde görev yapan ve çalışmaya katılmaya gönüllü olan 265 hemşireden elde edilmiştir. Verilerin toplanmasında, “Kişisel Bilgi Formu”, “Dempster Uygulama Davranışı Ölçeği (DUDÖ)” ve “Mesleki Benlik Saygısı Ölçeği (MBSÖ)” kullanılmıştır. Verilerin değerlendirilmesi tanımlayıcı istatistikler, pearson korelasyon analizi ve regresyon analizi kullanılarak yapılmıştır. Çalışmada hemşirelerin otonomisine ilişkin toplam puan ortalaması 45.91±8.234 ve mesleki benlik saygısı toplam puan ortalaması 97.00±20.097 olarak hesaplanmıştır. Hemşirelerde otonomiye ilişkin bağımsız davranış (t= 2.718, p= .007) alt boyutunun mesleki benlik saygısını anlamlı şekilde yordadığı, profesyonel davranış (t= 1.292, p= .198) ve karar verme (t= -.045, p= .964) alt boyutlarının ise yordamadığı belirlenmiştir. Araştırma sonucunda, hemşirelerin otonomisi ve mesleki benlik saygısı orta düzeyde belirlenmiştir. Hemşirelerde bağımsız davranışın mesleki benlik saygısını anlamlı şekilde yordadığı ortaya çıkmıştır. Bu sonuca göre, hemşirelerin mesleki benlik saygısını artırmak için mesleki otonomilerinin desteklenmesi ve uygulamalarında yeterli özerkliğin tanınması önemlidir.

공 던지기 로봇의 정책 예측 심층 강화학습

공 던지기 로봇의 정책 예측 심층 강화학습

코로나19 확산의 수요충격에 대비한 상장기업 현금소진위험 설명변수와 상장폐지 예측에 관한 실증연구

[연구목적] 본 연구에서는 코로나19 확산에 따른 수요충격 요인을 반영하여 상장기업의 현금소진위험을 설명하는 회계변수를 탐색하고, 추정한 현금소진위험이 기업의 극단적인 하방위험에 대해 유의미한 예측력이 있는지를 검증한다. [연구방법] 2001년부터 2019년까지 유가증권시장 및 코스닥시장에 상장된 비금융업종 23,558 기업/연 관측치를 대상으로 Probit 회귀분석을 통해 단기 현금소진 확률을 설명하는 주요 회계변수를 탐색하고, 상관관계 분석을 통해 추정 현금소진 확률과 미래 상장폐지율 간 관련성을 검증한다. 고위험 기업군에 대해서는 수요충격 시나리오별 민감도 분석을 수행하여 현금소진위험의 확대가능성을 점검한다. [연구결과] 연구 결과는 다음과 같다. 첫째, 현금소진위험은 현금보유비중이 낮고, 규모가 작은 기업일수록 높고, 재량적 발생액의 절대치와 장부가치대비시장가치가 큰 경우 높게 나타났다. 둘째, 현금소진위험의 추정확률은 미래 상장폐지율과 유의한 관련성이 있는 것으로 확인된다. 셋째, 재무건전성이 취약한 관리종목, 자본잠식기업, 투자주의 신용등급기업, 회사채 만기도래기업일수록 현금소진 확률이 더욱 위험한 수준으로 확인되며, 매출감소로 인한 수요충격이 클수록 현금소진위험은 더욱 증대되는 것으로 추정된다. [정책적 시사점] 본 연구에서는 현금소진위험을 설명할 수 있는 회계변수를 제시하고, 이를 활용하여 추정한 현금소진 확률이 미래 상장폐지 위험과도 유의한 관련성이 있음을 실증하였다. 코로나19 여파로 일시적인 현금경색 위기에 직면한 기업에 대해 구제의 필요성이 제기되는 가운데, 유동성 경색기업의 선별과 지원 소요 금액의 산출 등 관련 정책 대응 과정에 유의미한 판단 근거를 제시할 수 있다는 점에서 정책적 시사점이 있다.

Comprehensive rock burst prediction of deep hard rock based on in-situ stress and energy accumulation theory

Comprehensive rock burst prediction of deep hard rock based on in-situ stress and energy accumulation theory

Prediction of the employment ratio by industry using constrainted forecast combination

Prediction of the employment ratio by industry using constrainted forecast combination

Strength prediction of corrosion reinforced concrete columns strengthened with concrete filled steel tube under axial compression

Twenty-two corrosion-damaged columns were simulated through accelerated steel corrosion tests. Eight specimens were directly tested to failure under axial load, and the remaining specimens were tested after concrete-filled steel tube (CFST) strengthening. This study aimed to investigate the damage of RC columns after corrosion and their restoration and enhancement after strengthening. The research parameters included different corrosion degrees of RC columns, diameter-to-thickness ratio of steel tube and the strengthening concrete strength. Experimental results showed that CFST strengthening method could change the failure mode of corrosion-damaged RC columns from brittleness to ductility. In addition to the bearing capacity provided by the strengthening materials, it can also provide an extra 26.7% amplification because of the effective confinement provided by steel tubes. The influence of corrosion on reinforcement and concrete was quantitatively analysed and considered in the design formula. The proposed formula accurately predicted the bearing capacity of the strengthened columns with a maximum error of only 7.68%.

Dynamic deflection monitoring of high-speed railway bridges with the optimal inclinometer sensor placement

Dynamic deflection monitoring is an essential and critical part of structural health monitoring for high-speed railway bridges. Two critical problems need to be addressed when using inclinometer sensors for such applications. These include constructing a general representation model of inclination-deflection and addressing the ill-posed inverse problem to obtain the accurate dynamic deflection. This paper provides a dynamic deflection monitoring method with the placement of optimal inclinometer sensors for high-speed railway bridges. The deflection shapes are reconstructed using the inclination-deflection transformation model based on the differential relationship between the inclination and displacement mode shape matrix. The proposed optimal sensor configuration can be used to select inclination-deflection transformation models that meet the required accuracy and stability from all possible sensor locations. In this study, the condition number and information entropy are employed to measure the ill-condition of the selected mode shape matrix and evaluate the prediction performance of different sensor configurations. The particle swarm optimization algorithm, genetic algorithm, and artificial fish swarm algorithm are used to optimize the sensor position placement. Numerical simulation and experimental validation results of a 5-span high-speed railway bridge show that the reconstructed deflection shapes agree well with those of the real bridge.

A Study of the Prediction on the Possibility of Socially Responsible Values of Artificial Intelligence Speakers Applying Machine Learning Algorithms

A Study of the Prediction on the Possibility of Socially Responsible Values of Artificial Intelligence Speakers Applying Machine Learning Algorithms

Improving efficiency of a square cyclone separator using a dipleg – a CFD-based analysis

The present study is mainly focused on proposing an effective way to improve the efficiency of a square cyclone separator. For this purpose, a dipleg is attached under the square cyclone to investigate its effect on the performance of square cyclone. A three-dimensional Computational Fluid Dynamics (CFD) simulation is done by solving the Reynolds-Averaged Navier-Stokes equations with the Reynolds stress model (RSM) turbulence model and applying the Eulerian-Lagrangian two-phase method. The turbulent dispersion of particles is predicted by the application of the Discrete Random Walk (DRW) model. The numerical results demonstrate that using dipleg although produced an increase in pressure drop but it positively enhances the separation efficiency of the square cyclone. Using dipleg significantly increases the separation efficiency of square cyclone especially at higher inlet velocity. This can be more obvious when using dipleg which is minimized the 50% cut size of square cyclone about 26.3%.

Short-term Efficacy and Predictive Index of Anlotinib Hydrochloride Capsule on Advanced Non-small Cell Lung Cancer

Short-term Efficacy and Predictive Index of Anlotinib Hydrochloride Capsule on Advanced Non-small Cell Lung Cancer

Desarrollo de correlaciones para determinar el potencial a licuefacción mediante la aplicación del ensayo de penetración estática de piezocono (CPTu) en una cámara de calibración (CC).

El objetivo principal de este proyecto fue desarrollar correlaciones para determinar el potenciala licuefacción de depósitos de arenas sueltas empleando el ensayo de penetración estáticade piezocono CPTu; para ello fue necesario determinar el comportamiento de ensayos (CPTu)en la cámara de calibración (CC) del Laboratorio de Mecánica de Suelos y Rocas (IBF) en elInstituto Tecnológico de Karlruhe, además determinar la resistencia a licuefacción por mediode ensayos triaxiales cíclicos no drenados para muestras de arena, plantear una correlaciónentre la densidad relativa de almacenamiento (ID) de la muestra, la resistencia de punta(qc) del CPTu y la resistencia al flujo (CRR) de los ensayos triaxiales y por último compararla correlación experimental obtenida con correlaciones existentes de la literatura. Con esteproyecto se concluyó que en la región de bajas densidades de almacenamiento y bajasresistencias en punta una buena similitud, esto al comparar las correlaciones para los materialesexperimentales estudiados por el IBF con correlaciones provenientes de la literatura. Ahora bien,para densidades altas y, por lo tanto, mayores resistencias en punta, las curvas de correlaciónpara los materiales experimentales fueron más planas que en referencias bibliográficas; enotras palabras, la resistencia a licuefacción de los materiales experimentales en esta área esmenor de lo que habrían predicho las curvas de la literatura. Así pues, no es posible aplicardirectamente los resultados de este proyecto a otros sitios de estudio; ya que los materialesde las correlaciones realizadas (Kali4) y otros suelos difieren en aspectos como la mineralogía(criterios geológicos), la granulometría y la forma de partícula (criterios de composición); loscuales influyen sobre la susceptibilidad a la licuación.

Personel İş Zekası Sistemi ve Veri Madenciliği ile Personel Memnuniyetinin Ölçülmesi

Veri madenciliği uygulamaları ve iş zekası sistemleri verileri anlamlandırarak bilgiye dönüştürülmesinde ve kuruluşlara karar verme süreçlerinde yardımcı olmak için kullanılır. Çalışmada bir devlet kurumunun personel verileri üzerinde iş zekası ve veri madenciliği süreçleri gerçekleştirilerek verilerin yönetimini sağlamak ve dinamik analizler ile stratejik öngörülerin yapılabilmesi amaçlanmıştır. İş zekası süreçlerinin uygulanmasında Microsoft iş zekası araçlarından SSIS (SQL Server Integration Service), SSAS (SQL Server Analysis Service) ve Power BI kullanılmıştır. Öncelikle veri yapısı modellendirilmiş olup ETL (Extract-Transform-Load) sürecinden geçirilerek anlamlı hale getirilen veri, veri ambarına SSIS programı ile aktarılmıştır. Daha sonra SSAS programı ile OLAP veri küpü oluşturulmuştur. Son olarak da OLAP küpü veri kaynağı olarak belirlenip zengin görsel araçlara sahip olan ve veri analizini çok daha etkili hale getiren Power BI iş zekası aracı kullanılarak çeşitli görsellerle veri analizi gerçekleştirilmiştir. Böylece, karar vericilerin veri analizini etkin bir şekilde yapabilecekleri bir karar destek sistemi geliştirilmiştir. Çalışmada kümeleme analizi yöntemlerinden biri olan K-Means algoritması ve birliktelik kurallarından kurallarından Apriori algoritması ile bir devlet kurumundaki İç Kontrol Sistemi anketi verileri kullanılarak personel memnuniyet analizi yapılmıştır. Veri madenciliği aracı olarak ise içerisinde bulundurduğu bir çok algoritma sayesinde verilerden bilgi çıkarımı yapılabilmesine olanak sağlayan ve açık kaynak kodlu bir araç olması sebebi ile WEKA kullanılmıştır. Kümeleme analizi sonucunda oluşan farklı personel grupları detaylı incelenerek bu gruplara nasıl yaklaşılması gerektiği ve nasıl hitap edilmesi gerektiği belirlenmiştir. Her grubun memnuniyet durumunun farklılaşan noktaları belirlenerek, stratejiler ve uygulama faaliyetleri bu grubun ihtiyacına göre planlanmıştır. Apriori algoritması, personelin İç Kontrol Sistemi anket sorularına vermiş olduğu cevaplar arasında anlamlı ilişkileri bulmak, bu ilişkilerden faydalanarak personelin çalıştığı birimden memnuniyetini karşılaştırarak anlamlı sonuçlar elde etmek ve çalışılan birimden memnun olmama nedenlerini keşfetmek için kullanılmıştır. Böylece İç Kontrol Sistemi anketi verilerinden anlamlı ve yararlı bilgiler elde etmek ve bu bilgiler ışığında personel karar destek planlama faaliyetlerinde destek olmak amaçlanmıştır.

Maxwell Equations Derived from Coulomb’ Law vs. Maxwell-type Gravity Derived from Newton’s Law

A Universal Mathematical Field Theory (UMFT) is established and states that the combination of the operations of both gradient and divergence of vector fields, such as electric field and velocity field, create the curl of an axial vector field, such as magnetic field. Utilizing UMFT, Extended-Maxwell equations and the equation of Lorentz force are derived from the combination of Coulomb’s law and velocity of source mathematically, and new effects are predicted. For a source moving with non-spatially-varying velocity Extended-Maxwell equations reduce to Maxwell equations. This derivation mathematically explains how a moving electric charge creates magnetic field, and shows that there is no magnetic monopole charge. The duality between the Newton’s law and the Coulomb’s law leads us to derive Maxwell-type gravitational equations and Lorentz-type gravitational force by combining UMFT, the Newton’s law and velocity of gravitational source, denoted as Gravito-electromagnetic, which is dual of Electromagnetics. The benefits of the duality are that the effects and phenomena of Electromagnetics may be directly converted to that of gravity. The Gravito-Electromagnetics are employed to study the accelerating expansion of the universe, rotation curve, virial theorem, and gravitation radiation.

Farmacocinética poblacional de fenitoína en pacientes adultos

La fenitoína (DPH) es un antiepiléptico considerado de primera elección en el tratamiento de las crisis focales y convulsiones tónico-clónicas. DPH presenta elevada unión a proteínas plasmáticas, un comportamiento cinético no lineal dependiente de la dosis, elevada variabilidad cinética interindividual y un estrecho margen terapéutico; estas características aconsejan su monitorización para optimizar su balance eficacia/toxicidad. El objetivo de este trabajo fue la caracterización de la farmacocinética de DPH en población adulta. Concentraciones en estado de equilibrio de DPH procedentes de 215 pacientes adultos fueron utilizadas para desarrollar un modelo farmacocinético poblacional (PopPK) aplicando una metodología de efectos mixtos no lineales con el programa NONMEM v.7.3. La cinética de DPH fue descrita adecuadamente mediante un modelo monocompartimental con absorción de orden cero y cinética de eliminación no lineal ajustada a la ecuación de Michaelis-Menten. Edad, peso, magnitud de dosis y comedicación con ácido valproico han mostrado influencia sobre la velocidad de eliminación de DPH, reduciendo su variabilidad de forma considerable. Se ha obtenido un modelo PopPK preliminar que ha mostrado una adecuada capacidad descriptiva y predictiva en población adulta en un amplio rango de dosis (50-800 mg/día). No obstante, se precisa su aplicación en el contexto clínico para confirmar su validez.

Present Analysis and Trend Prediction of Shape/ Performance Collaborative Control for High-End Cold Rolling Foils

Present Analysis and Trend Prediction of Shape/ Performance Collaborative Control for High-End Cold Rolling Foils

Logistic regression combined with ROC curve model to predict risk of critically ill-patients with COVID-19

Objective: To build a model to predict critically ill-patients with coronavirus disease 2019 (COVID-19), and provide a new idea for the rapid identification of clinical progression in the early stage of critically ill-patients Methods: A retrospective analysis of the general data of 152 general patients and 323 critically ill-patients diagnosed with COVID-19 from Jan 17th, 2020 to Feb 25th, 2020 in Wuhan Third Hospital was carried out;At the same time, the differences in fever, blood routine, liver and kidney function, coagulation function, C-reactive protein (CRP), and nucleic acid reagent testing results from the day of admission were statistically analyzed Factors with statistical significance were included in a multivariate logistic regression analysis to obtain independent relevant factors that affect the critical ill-patients with COVID-19 Then a prediction model was built based on these factors and its accuracy was evaluated by the receiver operating characteristic (ROC) curve Results: The sensitivities of age, fever, neutrophil ratio, lymphocyte ratio, serum creatinine (Scr) and combined diagnosis were 0 664, 0 671, 0 607, 0 669, 0 302 and 0 710, respectively;The specificities were 0 669, 0 585, 0 795, 0 685, 0 895 and 0 802, respectively;The area under the curve (AUC) were 0 725, 0 628, 0 721, 0 681, 0 590 and 0 795, respectively;The AUC of combined diagnosis was higher than that of single diagnosis (P < 0 05) Conclusion: The logistic regression and combined with ROC curve model based on multi-factors, including age, fever status, neutrophil ratio, lymphocyte ratio, and Scr, can play a good role in predicting the occurrence of critically ill-patients with COVID-19, which is worthy of further promotion and application

A Population-Based Risk Prediction Model for Patients with COVID-19

In the ongoing COVID-19 pandemic, with “second waves” in many countries, there is an urgent need for precise disease-severity prediction tools. The