Structure and Bonding of Ni(C₆H_4-nF_n)(CO)₂ (C₆H₄=benzyne, n=1-4) Complexes

Ghiasi, Reza,Hashemian, Saeedeh,Irajee, Oranoos Korean Chemical Society 2011 대한화학회지 Vol.55 No.2

Ni$(C_6H_{4-n}F_n)(CO)_2$ ($C_6H_4$=benzyne, n=1-4) 착물의 전자구조 및 성질을 혼성 밀도 함수 B3LYP 이론을 이용하여 조사하였다. Benzyne 고리에 대한 방향족 성질과 벤젠핵과 무관한 화학적이동(NICS)을 분석하였다. 일-, 이- 및 삼-플루오르화 착물 중에서 3-F, 3, 6-F, 및 4-H는 각기 가장 안정한 이성질체였다. 고리 중심 상단의 여러 점에서 계산한 NICS 수치는 이들 착물의 상대 에너지에 의해 구한 값들과 일치하였다. 분자-내-원자(AIM) 분석에서 얻어진 Ni-C 결합거리는 모든 화학종에 대한 고리 임계점의 전자밀도(${\rho}_{rcp}$)와 좋은 상관성을 보였다. The electronic structure and properties of Ni$(C_6H_{4-n}F_n)(CO)_2$ ($C_6H_4$=benzyne, n=1-4) complexes have been investigated using hybrid density functional B3LYP theory. Both aromatic natures and nucleus independent chemical shift (NICS) of the benzyne rings have been analyzed. Among mono-, di-, and tri-fluorinated complexes, 3-F, 3,6-F, and 4-H are the most stable isomers, respectively. NICS values calculated at the several points above the ring centers are consistent with those based on the relative energies of the complexes. The atoms in molecules (AIM) analysis indicates that Ni-C bond distance is well correlated with the electron density of a ring critical point (${\rho}_{rcp}$) in all species.

New composite traits for joint improvement of milk and fertility trait in Holstein dairy cow

Ghiasi, Heydar,Piwczynski, Dariusz,Sitkowska, Beata,Gonzalez-Recio, Oscar Asian Australasian Association of Animal Productio 2021 Animal Bioscience Vol.34 No.8

Objective: The objective of this study was to define a new composite trait for Holstein dairy cows and evaluate the possibility of joint improvement in milk and fertility traits. Methods: A data set consisting 35,882 fertility related records (days open [DO], calving interval [CI], and number of services per conception [NSC], and total milk yield in each lactation [TMY]) was collected from 1998 to 2016 in Polish Holstein-Friesian breed herds. In this study TMY, DO, CI, and lactation length of each cow was used to obtain composite milk and fertility traits (CMF). Results: Moderate heritability (0.15) was estimated for composite trait that was higher than heritability of female fertility related traits: DO 0.047, CI 0.042, and NSC 0.014, and slightly lower than heritability of TMY 0.19. Favourable genetic correlations (-0.87) were estimated between CMF with TMY. Spearman rank correlation coefficients between breeding value of CMF with DO, CI, and TMY were high (>0.94) but with NSC were moderate (0.64). Selection on CMF caused favourable correlated genetic gains for DO, CI, and TMY. Different selection indices with different emphasis on fertility and milk production were constructed. The amount of correlated genetic gains obtained for DO and total milk production according to selection in CMF were higher than of genetic gains obtained for DO and TMY in selection indices with different emphasis on milk and fertility. Conclusion: The animal selection only based on a composite trait - CMF proposed in current study would simultaneously lead to favourable genetic gains for both milk and fertility related traits. In this situation CMF introduced in current study can be used to overcome to limitations of selection index and CMF could be useful for countries that have problems in recording traits, especially functional traits.

Optimization-based method for structural damage detection with consideration of uncertainties- a comparative study

Ghiasi, Ramin,Ghasemi, Mohammad Reza Techno-Press 2018 Smart Structures and Systems, An International Jou Vol.22 No.5

In this paper, for efficiently reducing the computational cost of the model updating during the optimization process of damage detection, the structural response is evaluated using properly trained surrogate model. Furthermore, in practice uncertainties in the FE model parameters and modelling errors are inevitable. Hence, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The current work builds a framework for Probability Based Damage Detection (PBDD) of structures based on the best combination of metaheuristic optimization algorithm and surrogate models. To reach this goal, three popular metamodeling techniques including Cascade Feed Forward Neural Network (CFNN), Least Square Support Vector Machines (LS-SVMs) and Kriging are constructed, trained and tested in order to inspect features and faults of each algorithm. Furthermore, three wellknown optimization algorithms including Ideal Gas Molecular Movement (IGMM), Particle Swarm Optimization (PSO) and Bat Algorithm (BA) are utilized and the comparative results are presented accordingly. Furthermore, efficient schemes are implemented on these algorithms to improve their performance in handling problems with a large number of variables. By considering various indices for measuring the accuracy and computational time of PBDD process, the results indicate that combination of LS-SVM surrogate model by IGMM optimization algorithm have better performance in predicting the of damage compared with other methods.

Assessment the effect of pile intervals on settlement and bending moment raft analysis of piled raft foundations

Ghiasi, Vahed,Moradi, Mobin Techno-Press 2018 Geomechanics & engineering Vol.16 No.2

Application the pile group foundation to reduce overall settlement of the foundation and also avoid a very fruitful settlement of foundations, inconsistent was carried out. In such a case, in event that the Foundation, not as a mere pile group, which as a system consisting of a broad foundation with pile Group, economic design criteria will be provided in spite of high safety. A new approach in the design of the Foundation can be introduced as the piles are just a tool to improve the parameters of soil hardness; that it can work with detachable piles from raft. Centralized arrangement of piles as the most optimal layout of piles in reducing inconsistent settlement, which is the lowest value of resulting layout in this differential settlement. Using the combination of piles connected and disconnected to form the raft, bending moment created in the raft is reduced. It also concentrated arrangements have greatest effect in reducing amount of moment applied to the raft.

Tumour Suppressive Effects of WEE1 Gene Silencing in Breast Cancer Cells

Ghiasi, Naghmeh,Habibagahi, Mojtaba,Rosli, Rozita,Ghaderi, Abbas,Yusoff, Khatijah,Hosseini, Ahmad,Abdullah, Syahrilnizam,Jaberipour, Mansooreh Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.11

Background: WEE1 is a G2/M checkpoint regulator protein. Various studies have indicated that WEE1 could be a good target for cancer therapy. The main aim of this study was to asssess the tumor suppressive potential of WEE1 silencing in two different breast cancer cell lines, MCF7 which carries the wild-type p53 and MDA-MB468 which contains a mutant type. Materials and Methods: After WEE1 knockdown with specific shRNAs downstream effects on cell viability and cell cycle progression were determined using MTT and flow cytometry analyses, respectively. Real-time PCR and Western blotting were conducted to assess the effect of WEE1 inhibition on the expression of apoptotic (p53) and anti-apoptotic (Bcl2) factors and also a growth marker (VEGF). Results: The results showed that WEE1 inhibition could cause a significant decrease in the viability of both MCF7 and MDA-MB-468 breast cancer cell lines by more than 50%. Interestingly, DNA content assays showed a significant increase in apoptotic cells following WEE1 silencing. WEE1 inhibition also induced upregulation of the apoptotic marker, p53, in breast cancer cells. A significant decrease in the expression of VEGF and Bcl-2 was observed following WEE1 inhibition in both cell lines. Conclusions: In concordance with previous studies, our data showed that WEE1 inhibition could induce G2 arrest abrogation and consequent cell death in breast cancer cells. Moreover, in this study, the observed interactions between the pro- and anti-apoptotic proteins and decrease in the angiogenesis marker expression confirm the susceptibility to apoptosis and validate the tumor suppressive effect of WEE1 inhibition in breast cancer cells. Interestingly, the levels of the sensitivity to WEE1 silencing in breast cancer cells, MCF7 and MDA-MB468, seem to be in concordance with the level of p53 expression.

1H-Indene과 Mono-sila-1H-Indene의 구조와 방향족성에 대한 이론적 연구

Ghiasi, Reza,Monnajemi, Majid 대한화학회 2006 대한화학회지 Vol.50 No.4

Hybrid DFT 계산 방법을 이용하여 1H-Indene과 Mono-sila-1H-indene 분자의 구조와 특성에 관한 이론적 연구를 수행하였다. 이 분자들의 방향족성 특성 연구를 위하여 MO, 비등방성 자기 민감도 등을 계산하였다. 1H-Indene과 Mono-sila-1H-indene 분자들에 대한 X8-X9 결합의 상대적인 안정도와 특성을 이해하기 위하여 NBO 계산을 수행하였다. 그 결과, 8, 9 위치의 Si 원자들이 C 원자들로 치환되었을 때, p orbital의 기여도가 증가하였다. 이러한 결과는 X8-X9 결합 길이는 하이브리드 오비탈의 p 오비탈 기여도에 크게 영향받는 사실을 보여준다. NBO계산을 통하여 X8-X9로부터 *X8-X9 결합 오비탈로의 비편재화에 기인하는 정량적인 에너지 안정화 세기를 결정하였다. MO 분석 결과 연구 대상 분자들의 방향족성은 3개의 비편재화된 pMO와 2개의 비편재화된 sMO에 의해서 주로 영향 받는다는 사실을 알 수 있었다. The electronic structure and properties of the 1H-indene and mono-sila-1H-indene series have been investigated using basis set of 6-31G(d, p) and hybrid density functional theory. Basic measures of aromatic character derived from structure, molecular orbitals, a variety of magnetic criteria (magnetic isotropic and anisotropic susceptibilities) are considered. Energetic criteria suggest that In(Si7) enjoy conspicuous stabilization. However, by magnetic susceptibility isotropic this system are among the least aromatic of the family: Within their isomer series, In(Si4) is the most aromatic using this criteria. Natural bond orbital (NBO) analysis method was performed for the investigation of the relative stability and the nature of the 8-9 bonds in 1H-indene and mono-sila-1H-indene compounds. The results explained that how the p character of natural atomic hybrid orbital on X8 and X9 (central bond) is increased by the substitution of the C8 and C9 by Si. Actually, the results suggested that in these compounds, the X8-X9 bond lengths are closely controlled by the p character of these hybrid orbitals and also by the nature of C-Si bonds. The magnitude of the molecular stabilization energy associated to delocalization from X8-X9 and to * X8-X9 bond orbital were also quantitatively determined. Molecular orbital (MO) analysis further reveal that all structure has three delocalized MOs and two delocalized MOs and therefore exhibit the aromaticity.

Densified biocoal from woodchips: Is it better to do torrefaction before or after densification?

Ghiasi, B.,Kumar, L.,Furubayashi, T.,Lim, C.J.,Bi, X.,Kim, C.S.,Sokhansanj, S. Applied Science Publishers 2014 APPLIED ENERGY Vol.134 No.-

Torrefied biomass represents a high quality renewable energy commodity that can be used to substitute fossil fuels such as coal. However, densification processes such as pelletisation is necessary to improve the tradability of ''low-dense'' torrefied biomass. In this work, two process pathways were assessed for energy and mass balance in making torrefied pellets from softwood chips and qualities of the resulting torrefied pellets were compared. Pathway I involve drying the wood chips, torrefaction, grinding followed by densification. In pathway II, wood chips were dried, ground, densified and finally torrefied. The results showed that it was difficult to bind the torrefied biomass particles and a binding agent was necessary to enable their effective pelletisation with reasonable energy consumption. In contrary, pelletization of raw materials was possible without using binding agents and when the ''raw wood pellets'' were torrefied, the pellets surprisingly stayed intact and had several promising properties such as higher energy/carbon value, reduced moisture content and higher stability in water. In addition, the pathway II was more efficient in terms of overall energy and material balance.

Investigating the contribution of different sizes of pore spaces to the permeability of heterogeneous carbonate rocks using Markov Chain Monte Carlo and lattice-Boltzmann simulation

Ghiasi-Freez Javad,Ziaii Mansour,Moradzadeh Ali 한국자원공학회 2020 Geosystem engineering Vol.23 No.4

Different sizes of pore spaces play different roles in fluid flow properties of rocks. The advantages of image analysis were employed to study the effect of different sizes of pore spaces, including micropores (10–50 µm), mesopores (50–100 µm) and macropores (>100 µm), on their contribution in the permeability of carbonates. First, all of the original binarized photomicrographs were subdivided into three images each contains one class of pores. Then, the three-dimensional digital models of the images were reconstructed using Markov Chain Monte Carlo method. Then, the models were integrated using a superposition operation. Finally, the lattice Boltzmann method was used to estimate the permeability of each model. The results show: (1) higher percentage of macropores provides higher permeability, while growth of micropores percentage has insignificant effect on flow properties due to lack of pores connectivity; (2) In spite of negligible permeability of micropores lonely, they can improve the carbonate rock permeability in cooperation with the meso- and macropores; (3) the estimated permeability from the superposed digital models were closer to the reality compared with the not-processed models, which were reconstructed without pore differentiation.

Design Sensor-less PID Filter Controller for First Order Delays System

Hootan Ghiasi,Farzin Piltan,Mohammad Reza Avazpour,Mohammad Hadi Mazloom,Amirzubir Sahamijoo,Nasri B. Sulaiman 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.4

The dynamics of a first order delay system is highly nonlinear, time variant, uncertain and coupling effects. The main objectives to control of first order delay system are time response and acceleration measurements. The problem of acceleration measurements can be reduced, based on design sensor-less Proportional-Integral-Derivative (PID) filter controller in this research. Assuming unstructured uncertainties and structure uncertainties can be defined into one term and considered as an uncertainty and external disturbance, the problem of computation burden and large number of parameters can be solved to some extent. To solve the uncertainties acceleration measurements play an important role. In order to design sensor-less PID filter controller, an accurate PD surface and the derivative of PD surface plays important role. To design an accurate PD surface, stable and tuning surface slope is needed to form the structure of main PID controller. In this algorithm, the derivative of PD surface computes the second derivation of error. Regarding to this method, the challenge of system uncertainties and time response have been solved based on sensor-less acceleration linear filter controller. As this point if s = K1e + e + K2Σe is chosen as desired surface, if the dynamic of first order delay is derived to surface then the linearization can be realized. Because, when the system dynamic is on the surface is used the derivative of surface S = K1e + e + K2e is equal to the zero that is a decoupled and linearized closed-loop systems dynamics. Linearization and decoupling by the above method can be obtained in spite of the quality of the first order delay dynamic model.

An intelligent health monitoring method for processing data collected from the sensor network of structure

Ramin Ghiasi,Mohammad Reza Ghasemi 국제구조공학회 2018 Steel and Composite Structures, An International J Vol.29 No.6

Rapid detection of damages in civil engineering structures, in order to assess their possible disorders and as a result produce competent decision making, are crucial to ensure their health and ultimately enhance the level of public safety. In traditional intelligent health monitoring methods, the features are manually extracted depending on prior knowledge and diagnostic expertise. Inspired by the idea of unsupervised feature learning that uses artificial intelligence techniques to learn features from raw data, a two-stage learning method is proposed here for intelligent health monitoring of civil engineering structures. In the first stage, Nystrőm method is used for automatic feature extraction from structural vibration signals. In the second stage, Moving Kernel Principal Component Analysis (MKPCA) is employed to classify the health conditions based on the extracted features. In this paper, KPCA has been implemented in a new form as Moving KPCA for effectively segmenting large data and for determining the changes, as data are continuously collected. Numerical results revealed that the proposed health monitoring system has a satisfactory performance for detecting the damage scenarios of a three-story frame aluminum structure. Furthermore, the enhanced version of KPCA methods exhibited a significant improvement in sensitivity, accuracy, and effectiveness over conventional methods.