Determination of Optimal Leadership Styles through Knowledge Management: A Case from the Automotive Industry

This study proposed a model to examine the impact of various leadership styles on knowledge management. This case study identified the best leadership style, which can affect the key factors of the knowledge management success. The statistical population was composed of all staff of the Pars Khodro Company headquarters in Iran, in which 226 people were accordingly chosen as the sample. The required data for examining research hypotheses were also collected using questionnaire. Results revealed the impact of leadership styles on knowledge management. The transformational leadership style was consequently found to have a positive and significant impact on the knowledge management key success factors, in contrast with other leadership styles including self-management, pragmatic, conservative and structure-based

Evaluation of Echocardiography Results after Severe Mitral Valve Regurgitation Repair Surgery

BACKGROUND AND OBJECTIVE: Severe mitral valve regurgitation, which occurs primarily or secondary to various cardiovascular diseases, has undergone surgery and valve replacement and artificial valve insertion from several years ago. Within the last few years, severe mitral valve regurgitation has undergone repair surgery. This study was conducted to determine the results of mitral valve repair surgery. METHODS: This cross-sectional study was conducted among 210 patients who had undergone surgery with the diagnosis of severe mitral valve regurgitation. Transesophageal Echocardiography (TEE) was performed for all patients before surgery, and echocardiography was performed one week after surgery and six months later and the results were evaluated in terms of regurgitation in three mild, moderate and severe cases. FINDINGS: The mean age of patients with secondary mitral regurgitation was 43 – 85 years. In patients with secondary mitral regurgitation, 143 (83%) patients did not have mitral regurgitation, 27 (15%) patients had mild mitral regurgitation and 3 patients had moderate to severe mitral regurgitation, whereas in patients with primary mitral regurgitation, 30 (81%) patients did not have mitral regurgitation, 5 (14%) patients had mild mitral regurgitation and 2 (5%) patients had moderate to severe mitral regurgitation. CONCLUSION: The results of the study showed that mitral valve repair with primary or secondary etiology had good results and can replace artificial valve in the future

Safety Technology Adoption: Predicting Intention to Use Car Dashcams in an Emerging Country

This study investigates the factors that affect the user's intention to use dashcam in Malaysia. This study examines the quantitative relationship of intrinsic as well as extrinsic factors such as personal innovativeness, perceived uniqueness, perceived usefulness, perceived ease of use, attitude, perceived behavioral control, social influence, price value, and trust to the purchase intention of dashcam. Purposive sampling technique was employed to collect responses from 232 respondents based on two criteria: first, individuals who have experienced driving on the road and have a car; and second, individuals who not yet adopt or purchase the dashcam. The data were analyzed using SmartPLS (version 3.3.2). No relationship between personal innovativeness and perceived usefulness was found, in contrast to a significant relationship the former and perceived ease of use. Furthermore, perceived uniqueness was found significant to both perceived usefulness and perceived ease of use. Consistent with the literature, both perceived usefulness and perceived ease of use were identified as factors influencing attitude. However, perceived usefulness did not affect intention. Perceived behavioral control, social influence, attitude, and trust significantly affected the behavioral intention to use the dashcam in Malaysia. This study attempts to integrate and adapt two technology adoption models, namely the Combined Technology Acceptance Model and Theory Planned Behavior and extension of Unified Theory of Acceptance and Use of Technology, also extends the model with personal innovativeness, perceived uniqueness, and trust to fulfil the study's objectives as well

Prediction of the treatment response in ovarian cancer: a ctDNA approach.

Ovarian cancer is the eighth most commonly occurring cancer in women. Clinically, the limitation of conventional screening and monitoring approaches inhibits high throughput analysis of the tumor molecular markers toward prediction of treatment response. Recently, analysis of liquid biopsies including circulating tumor DNA (ctDNA) open new way toward cancer diagnosis and treatment in a personalized manner in various types of solid tumors. In the case of ovarian carcinoma, growing pre-clinical and clinical studies underscored promising application of ctDNA in diagnosis, prognosis, and prediction of treatment response. In this review, we accumulate and highlight recent molecular findings of ctDNA analysis and its associations with treatment response and patient outcome. Additionally, we discussed the potential application of ctDNA in the personalized treatment of ovarian carcinoma. ctDNA-monitoring usage during the ovarian cancer treatments procedures

Podoschistus scutellaris (Hym.: Ichneumonidae, Poemeniinae): a genus and species new to Iran

Two species of the subfamily Poemeniinae (Hym.: Ichneumonidae) were collected and identified from Mazandaran province, Iran during 2016 using Malaise traps. Podoschistus scutellaris and Neoxorides collaris are reported for the first time from Iran and Mazandaran province, respectively. Their diagnostic morphological characters and distribution within and outside Iran are provided

Positive effect of low dose vitamin D supplementation on growth of fetal bones: A randomized prospective study

The effect of vitamin D supplementation on growth of fetal bones during pregnancy is unclear. The aim of this study was to assess the effect of low dose vitamin D supplementation during pregnancy on bony anthropometric aspects of the fetus. In this prospective randomized trial, 140 patients were divided into two equally matched groups according to age, 25(OH)D level, exercise, and dietary intake. Then 1000 IU per day vitamin D supplement was given to the intervention group while the control group received placebo. Then crown-rump length (CRL) and femur length (FL) during the first trimester and humerus and femur lengths as well as their proximal metaphyseal diameter (PMD), midshaft diameter (MSD) and distal metaphyseal diameter (DMD) in the second and third trimester were measured using ultrasonography technique. Finally, no significant difference was observed for CRL (p = 0.93). Although FL was not statistically significant in the first trimester (p = 0.54), its measurement in the intervention group and the control group in the second (28.87 ± 2.14 vs. 26.89 ± 2.08; p ≤0.001) and the third (65.31 ± 2.17 vs. 62.85 ± 1.94; p ≤0.001) trimesters was significantly different. Femoral PMD, MSD, and DMD measurement increased more in the intervention group in comparison with the control group with P values <0.05. HL measurement in the intervention group and the control group in the second (28.62 ± 1.94 vs. 27.23 ± 2.08; p ≤0.001) and the third (61.29 ± 2.84 vs. 59.85 ± 1.79; p ≤0.001) trimesters revealed significant differences. Humeral PMD, MSD, and DMD measurement increased in the intervention group in comparison with the control group with P values <0.001 for all. It is suggested to prescribe low dose vitamin D (1000 IU per day) from early pregnancy with possible increment in length and diameter of femur and humerus bones of the fetus

Prediction of strain values in reinforcements and concrete of a RC frame using neural networks

The level of strain in structural elements is an important indicator for the presence of damage and its intensity. Considering this fact, often structural health monitoring systems employ strain gauges to measure strains in critical elements. However, because of their sensitivity to the magnetic fields, inadequate long-term durability especially in harsh environments, difficulties in installation on existing structures, and maintenance cost, installation of strain gauges is not always possible for all structural components. Therefore, a reliable method that can accurately estimate strain values in critical structural elements is necessary for damage identification. In this study, a full-scale test was conducted on a planar RC frame to investigate the capability of neural networks for predicting the strain values. Two neural networks each of which having a single hidden layer was trained to relate the measured rotations and vertical displacements of the frame to the strain values measured at different locations of the frame. Results of trained neural networks indicated that they accurately estimated the strain values both in reinforcements and concrete. In addition, the trained neural networks were capable of predicting strains for the unseen input data set