Modeling and forecasting car ownership based on socio-economic and demographic indicators in Turkey

Since car ownership is an important determinant to analyze car travel behavior especially in developing countries, this paper deals with modeling and forecasting car ownership in Turkey based on socio-economic and demographic indicators such as Gross Domestic Product(GDP) per capita, Gasoline Price (GP), car price and number of employees by using multiple nonlinear regression analysis. Although most of the studies on this subject prefer using annual data, we use monthly data for the analysis of car ownership since all explanatory variables and exchange rates used for the modeling are unstable and vary even in a short period in developing countries such as Turkey. Thus, it may be possible to reflect the effects of socio-economic and demographic indicators on car ownership more properly. During the modeling process, exponential and polynomial nonlinear regression models are set up and then tested to investigate their applicability for car ownership forecasting. Based on results of the Kolmogorov-Smirnov test, the polynomial models has been selected to forecast car ownership for the year 2035. In order to reveal the possible different trends of the independent variables in future, car ownership is forecasted along the scenarios which are related to the GDP per capita and GP. Results show that Turkey’s car ownership may vary between 230 and 325 per thousand capita in 2035 depending on economic achievements, global oil prices and national taxation policies. The lowest and the highest values of the car ownership may provide insight to car producers and transport planners in Turkey. Another significant result presented in this study is that car ownership rate will be substantially lower in Turkey than that in the European Union countries despite it has an increasing trend in the past two decades

The Antimicrobial Activity of Aliquidambar orientalis mill. Against Food Pathogens and Antioxidant Capacity of Leaf Extracts

Background: Medicinal plants are an important source of substances which are claimed to induce antimicrobial, antimutagenic and antioxidanteffects. Many plants have been used due to their antimicrobial treatments. Antimicrobial and antioxidant activities of L. orientalis have not beenreported to the present day. The aim of this work was to investigate of the antimicrobial and antioxidant potentials of different extracts from L.orientalis.Materials and Methods: The extracts were screened for antimicrobial activity against different food pathogens. These bacteria include 4 Grampositive and 3 Gram negative bacteria and one fungi. The leaf extracts of plant were tested by disc diffusion assay. The MIC was evaluated onplant extracts as antimicrobial activity. In addition to, the plant extracts were tested against the stable DPPH (2,2-diphenyl-1-picryl-hydrazylhydrate) free-radical.Results: The acetone, ethanol and methanol extracts of L. orientalis showed maximum inhibition zone of 12 mm against Yersinia enterocolitica,Listeria monocytogenes and Staphylococcus aureus. In addition to, the methanol extract displayed a strong antioxidant activity (trolox equivalent= 2.23 mM).Conclusion: L. orientalis extracts have antimicrobial, and antioxidant potential. Our results support the use of this plant in traditional medicineand suggest that some of the plant extracts possess compounds with good antibacterial properties that can be used as antibacterial agents in thesearch for new drugs.Key words: Antimicrobial activity; Antioxidant activity; L. orientalis

Glycosaminoglycan mimetric peptide nanofibers promote mineralization by osteogenic cells

Cataloged from PDF version of article.Bone tissue regeneration is accomplished by concerted regulation of protein-based extracellular matrix components, glycosaminoglycans (GAGs) and inductive growth factors. GAGs constitute a significant portion of the extracellular matrix and have a significant impact on regulating cellular behavior, either directly or through encapsulation and presentation of growth factors to the cells. In this study we utilized a supramolecular peptide nanofiber system that can emulate both the nanofibrous architecture of collagenous extracellular matrix and the major chemical composition found on GAGs. GAGs and collagen mimetic peptide nanofibers were designed and synthesized with sulfonate and carboxylate groups on the peptide scaffold. The GAG mimetic peptide nanofibers interact with bone morphogenetic protein-2 (BMP-2), which is a critical growth factor for osteogenic activity. The GAG mimicking ability of the peptide nanofibers and their interaction with BMP-2 promoted osteogenic activity and mineralization by osteoblastic cells. Alkaline phosphatase activity, Alizarin red staining and energy dispersive X-ray analysis spectroscopy indicated the efficacy of the peptide nanofibers in inducing mineralization. The multifunctional and bioactive microenvironment presented here provides osteoblastic cells with osteogenic stimuli similar to those observed in native bone tissue

Effects of DC-Field Excitation on the Incremental Inductance of a Variable Flux Reluctance Machine

This paper presents a method for the computation of the incremental inductances in a 12/10 variable flux reluctance machine using the hybrid analytical modeling coupled with a fixed-point nonlinear solver. The variation of incremental and apparent inductance with respect to the dc-field excitation is investigated for both zero and non-zero ac-field excitations. The results show that the difference between both inductance values is not negligible after 25 A/mm2 dc-current density for the investigated benchmark without the ac field. Moreover, when a non-zero ac field is introduced in addition to the dc-field, the apparent inductance becomes misleading not only under magnetic saturation but also under low excitation in the linear region of the saturation curve. The results obtained with the proposed nonlinear hybrid model are compared with the finite element method in terms of magnetic flux density distribution and incremental inductance value. The root-mean-square discrepancy of magnetic flux density distribution is found to be 37.6 mT. Furthermore, the discrepancy between incremental inductance results of the proposed method and the finite element model is calculated as 1.43%, while the proposed approach requires less post-processing and necessitates ten times less number of degrees-of-freedom

Convergence analysis of the fixed-point method with the hybrid analytical modeling for 2-D nonlinear magnetostatic problems

This paper presents the convergence analysis of the fixed-point method (FPM) to model the nonlinear magnetic characteristics of a 2-D magnetostatic problem. In this study, FPM is used as the iterative nonlinear solver of the hybrid analytical modeling (HAM) technique for the accurate computation of the magnetic field distribution. The benchmark consists of a stator with excitation windings, an airgap, and a slotless mover. The relative errors between two successive iterations are calculated using different error estimators: the attraction force on the mover, the Fourier coefficients defined in the airgap, the magnetic flux density, and the magnetic scalar potential distributions. The effect of the number of mesh elements and harmonics on the accuracy and computational cost of the model is investigated for different levels of magnetic saturation. It is observed that the maximum rate of change in the relative difference of attraction force during the iterations is found to be 0.52 under the magnetic saturation. In addition, the absolute error of the attraction force between the developed hybrid model with FPM and the finite element method (FEM) is achieved to be 0.18%, while HAM has approximately three times less number of degrees-of-freedom compared to FEM

Bone-Like Mineral Nucleating Peptide Nanofibers Induce Differentiation of Human Mesenchymal Stem Cells into Mature Osteoblasts

Cataloged from PDF version of article.A bone implant should integrate to the tissue through a bone-like mineralized interface, which requires increased osteoblast activity at the implant-tissue boundary. Modification of the implant surface with synthetic bioinstructive cues facilitates on-site differentiation of progenitor stem cells to functional mature osteoblasts and results in subsequent mineralization. Inspired by the bioactive domains of the bone extracellular matrix proteins and the mussel adhesive proteins, we synthesized peptide nanofibers to promote bone-like mineralization on the implant surface. Nanofibers functionalized with osteoinductive collagen I derived Asp-Gly-Glu-Ala (DGEA) peptide sequence provide an advantage in initial adhesion, spreading, and early commitment to osteogenic differentiation for mesenchymal stem cells (hMSCs). In this study, we demonstrated that this early osteogenic commitment, however, does not necessarily guarantee a priority for maturation into functional osteoblasts. Similar to natural biological cascades, early commitment should be further supported with additional signals to provide a long-term effect on differentiation. Here, we showed that peptide nanofibers functionalized with Glu-Glu-Glu (EEE) sequence enhanced mineralization abilities due to osteoinductive properties for late-stage differentiation of hMSCs. Mussel-inspired functionalization not only enables robust immobilization on metal surfaces, but also improves bone-like mineralization under physiologically simulated conditions. The multifunctional osteoinductive peptide nanofiber biointerfaces presented here facilitate osseointegration for long-term clinical stability. © 2014 American Chemical Society

Magnetodynamic finite element analysis coupled with a vector hysteresis model applied to a variable flux reluctance machine

This article presents an extended magnetodynamic finite element modeling technique for 2-D time-dependent electromechanical problems with soft-magnetic laminated steels. The proposed modeling technique includes magnetic vector hysteresis, eddy-current, and excess field components in the system of equations instead of obtaining them in the post-processing. A transient finite element solver is coupled with the Jiles-Atherton vector hysteresis model, while the dynamic components, i.e. eddy current and excess field, are modeled in a weak formulation. The proposed method is experimentally verified using a laminated transformer core similar to TEAM problem 32. It is demonstrated that the proposed magnetodynamic model with vector hysteresis characteristics calculates the flux linkage and iron loss more accurately than magnetostatic and magnetodynamic models coupled with the single-valued magnetization curve. The proposed method estimates the iron loss with a discrepancy of less than 15 % up to an excitation frequency of 1500 Hz when it is compared to the transformer core measurements. Later, the experimentally verified magnetodynamic model is employed to model a 48 V, 5 kW variable flux reluctance machine with 16 Nm peak torque under various excitation levels. The machine is tested in laboratory conditions utilizing a field-oriented control algorithm in motor mode at 1000 rpm rotor speed. The average percentage error of the magnetodynamic model with vector hysteresis characteristics is found to be 14 % compared to the iron loss measurements while the magnetodynamic and magnetostatic models coupled with the single-valued curve exhibit 25 % and 45 % average percentage errors, respectively

Assessment of proportion of hidden patients having symptoms of overactive bladder and why has it been hidden in female outpatients admitted to hospital

Purpose: To determine the proportion of patients with undetected symptoms of overactive bladder by using the overactive bladder-validated 8 (OAB-V8) screening questionnaire and investigate these symptoms were undetected in female patients who were hospitalized. Methods: We invited 2,250 female patients hospitalized in the Aegean region of Turkey to answer a self-administered questionnaire. The questionnaire included questions on evidence of lower urinary tract symptoms (OAB-V8), relevant medical history, and demographic data. Patients with a total OAB-V8 score ≥ 8 were defined as having OAB symptoms. Results: The proportion of patients with OAB symptoms in this study was 40.6%. Nearly 57% of the patients with OAB symptoms had not been previously admitted to any hospital for lower urinary tract symptoms (LUTS). The two most common reasons why women with OAB symptoms did not admit themselves to a hospital because of LUTS were as follows: "I did not think I had a disease" and "The symptoms did not bother me," with a response rate of 74.7%. The mean OAB-V8 scores of the patients with these two responses were significantly lower than those of the other patients (P < 0.001). Conclusions: This is the first study to demonstrate a significant proportion of women with undetected OAB symptoms. The main reasons the women did not admit themselves to a hospital were their unawareness of the disease and because the LUTS were not bothersome. Public awareness programs on this disease may resolve this problem. © 2016 Korean Continence Society

Query Answering in Ontologies under Preference Rankings

We present an ontological framework, based on preference rankings, that allows users to express their preferences between the knowledge explicitly available in the ontology. Using this formalism, the answers for a given query to an ontology can be ranked by preference, allowing users to retrieve the most preferred answers only. We provide a host of complexity results for the main computational tasks in this framework, for the general case, and for EL and DL-Litecore as underlying ontology languages