Relationship between transactional, transformational leadership styles, emotional intelligence and job performance

Claims about the significant relationship or the positive influence of emotional intelligence on performance are numerous, in both the commercial and scientific literatures. However, despite the intense interest of the media and business consultants in the field of emotional intelligence or EI, and its increasingly popular use in organizations, there is little empirical evidence to support these claims. In this study, we investigated the relationships between EI, leadership styles among 192 managers. Emotional intelligence was evaluated employing the Schutte emotional intelligence scale and while the Bass and Avolve leadership styles scale was also adapted. Finally, job performance was measured by immediate managers. Results showed that emotional intelligence was positively correlated with emotion in job performance. Surprisingly, it also appears that transformational leadership style was correlated with job performance. These results suggest that emotional intelligence may provide an interesting new way of enhancing productivity through job performance

Analgesic Efficacy of Dexamethasone and Dexmedetomidine as an Adjuvant to Bupivacaine Infiltration in Unilateral Cleft Lip Surgery: A Randomized, Double-Blinded Study

Background: In the majority of cases, the treatment method for Cleft lip is surgery. Providing adequate pain control during and after surgery for children, is too important. Also, different methods are used for pain relief like analgesic prescription and nerve block and different adjuvants can be added to anesthetics to reduce pain. Aims: This trial was aimed to compare the analgesic effect of Bupivacaine with or without dexmedetomidine or dexamethasone for cleft lip surgery. Methods: This study is a prospective, double-blinded, randomized trial which conducted on 75 pediatrics, aged between 3 to 10 months, who needed unilateral cleft lip surgery. Patients were divided into 3 groups (n=25 in each group). Children in group A, were given a combination of bupivacaine and 0.5 µg/kg of dexmedetomidine, those in group B, 0.1 mg/kg of dexamethasone as an adjuvant to bupivacaine, and in group C, plain 1 cc of bupivacaine 0.5% was injected in the operation site. Outcomes were assessed via FLACC and WATCHA scores. Results: The mean age among children was 4.3 ±1.29 months and mean weight was 6.3± 1.09 kg. Pain score and frequency of analgesic request intra and post-operation in group A was lower than others (p<0.0001). Also, FLACC and WATCHA scores were significantly lower in group A (p<0.0001) and parental and surgeon satisfaction was higher in group A (p<0.05). Conclusion: Our study showed that, dexmedetomidine as an adjuvant to bupivacaine 0.5% is more effective to improve the analgesia, in children who underwent unilateral cleft lip surgery

A review of application of multi-criteria decision making methods in construction

Construction is an area of study wherein making decisions adequately can mean the difference between success and failure. Moreover, most of the activities belonging to this sector involve taking into account a large number of conflicting aspects, which hinders their management as a whole. Multi-criteria decision making analysis arose to model complex problems like these. This paper reviews the application of 22 different methods belonging to this discipline in various areas of the construction industry clustered in 11 categories. The most significant methods are briefly discussed, pointing out their principal strengths and limitations. Furthermore, the data gathered while performing the paper are statistically analysed to identify different trends concerning the use of these techniques. The review shows their usefulness in characterizing very different decision making environments, highlighting the reliability acquired by the most pragmatic and widespread methods and the emergent tendency to use some of them in combination

Optimized ensemble learning and its application in agriculture

It has been shown that combining multiple machine learning base learners, results in better prediction accuracy, given that the base learners are diverse enough. Assuming each of the base learners as a decision-maker, a committee of decision-makers is able to make better decisions as long as they are not very similar to each other i.e. they are diverse. More importantly, it is crucial to figure out the best way to combine these base learners in order to maximize the committee’s prediction accuracy. Many well-known ensemble creation methods such as Basic Ensemble Model (BEM), Generalized Ensemble Model (GEM), stacked generalization, etc. have been proposed to address the ensemble creation problem. However, considering the ensemble as the linear combination of the base learners’ predictions, those models consider the base model construction and the weighted aggregation to be independent steps. We designed a framework that can find optimal ensemble weights as well as hyperparameter combinations and result in better ensemble performance. Although extensive studies have applied sophisticated machine learning (ML) models on ecological problems, especially crop yield prediction, the use of ensemble models has been limited. We developed several ensemble frameworks to address the corn yield prediction problem. We have shown that an ensemble of some individual models can outperform the individual models. In addition, we have shown that a hybrid ML-simulation crop modeling framework could further improve the quality of yield predictions as the ML ensembles benefit significantly from the agricultural information and insights derived from simulation crop models. Lastly, we have designed sophisticated ensemble frameworks from the convolutional neural network – deep neural network (CNN-DNN) base learners. The promising predictions made by this model prove its performance and its dominance over the state-of-the-art models found in the literature

Relationship among transactional and transformational leadership style, emotional intelligence and job performance of bank managers in Semnan Province, Iran

This study examined the relationship between emotional intelligence, leadership styles and Job performance. Data from 192 managers of banks indicated significant positive effects of emotional intelligence on job performance (r=.55, P.05). A factorial analysis of variance (ANOVA) was used to determine the influence of level of education, age, and management experience on job performance. The results of this research indicated that the level of education, age, and management experience had no significant effects on bank managers’ job performance. The findings of the study revealed that there is a significant difference in managers’ job performance in terms of type of bank (t=2.45,P.05; =1.29,P>.05; and t=1.87,P>.05 respectively)

Performance optimization of water distribution network using meta-heuristic algorithms from the perspective of leakage control and resiliency factor (case study: Tehran water distribution network, Iran)

In the context of sustainable development and considering water distribution networks (WDNs) as vital infrastructure systems, designing a resilient and efficient network to deliver water demand to consumption nodes while adhering to engineering standards is of utmost importance. This study specifically focused on the complex structure of the north-west Tehran's WDN, encompassing 1124 pipes totaling 92552 m in length, along with four gravity reservoirs and 988 nodes. Genetic Algorithm (GA) and Nonlinear Programming (NLP) were employed as optimization techniques to enhance the WDN by minimizing leakage and improving its resilience. The study involved determining leakage coefficients for nodes using measured data and GA. Subsequently, the WDN was optimized by defining an objective function, constraints, and decision variables using both GA and NLP. The results demonstrated the superiority of GA in terms of pressure reduction, achieving a significant decrease of 23.7%. Additionally, GA outperformed NLP in enhancing the resiliency index, underscoring its effectiveness in optimizing the network's performance and ensuring its robustness against potential disruptions

An ERP Selection Framework in Constructor Companies using Fuzzy AHP Approach

The success in ERP implementation is definitely based on selecting an appropriate system which is more aligned with enterprise culture, infrastructure and requirements, and that's why ERP selection, the process and impressive criteria have been increasingly attended in recent years. The constructor companies are strongly affected by ERP systems. A successful implementation will improve their productivity and promote their performance considerably. However, it is a challenge for decision-makers to identify the real needs, define the criteria, select the acceptable vendor and purchase the most appropriate system. This study is developed to present a Fuzzy AHP-based framework for selecting ERP systems in constructor companies. In this study, the impressive criteria have been collected by reviewing previous studies and researches, a questionnaire was used to assess and define the criteria and sub-criteria’s priority. Afterward, another questionnaire was used to compare the alternatives regarding to each criteria. Eventually, the Fuzzy Analytic Hierarchical Process was used to select a system which is more aligned with the organization’s requirements and strategie

The Effectiveness of Cognitive-Behavioral Therapy on Coping Styles and Quality of Life of Depressed Women

Depression is the most common psychiatric disorder. Its prevalence in women is twice that of men, which seriously affects the mental health of this group. Therefore, it is very important to adopt treatment methods to reduce it. For this reason, the aim of this study was to investigate the effectiveness of cognitive behavioral therapy on coping styles and quality of life of depressed women. This research was a semi-experimental method of pre-test and post-test design with a control group. The statistical population of the study was made up of all women who referred to counseling centers in Mashhad city in 2017, who scored higher than 13 in the Beck depression test. 30 of them were selected as a sample by purposive sampling method and then randomly divided into two control and experimental groups (15 people in the experimental group - 15 people in the control group). Beck depression inventory (BDI-II), the Coping Inventory for Stressful Situations (CISS) and World Health Organization quality of life (WHOQOL-BREF) were used to collect data. Data were analyzed by multivariate analysis of covariance. The findings showed that there is a significant difference between the two experimental and control groups in the post-test stage in emotional and avoidant coping styles (P<0.05). However, there was no significant difference between the two groups in the problem-oriented coping style (P<0.05). Also, the results in the quality of life section show a significant difference between the two groups in the variables of social, psychological, physical and environmental quality of life (P<0.05). As a result, it can be said that cognitive behavioral therapy can be used as an efficient treatment method to reduce emotional and avoidant coping styles in depressed patients in the clinical environment. Also, the use of this treatment method increases the level of quality of life in these patients

A Comparison of Competitive Anxiety and Perceived Overtraining in Athletes with and without Anabolic Steroids Consumption

The aim of the present study was to compare competitive anxiety and perceived overtraining in athletes with and without anabolic steroids consumption. The statistical population included all athletes of team and individual sport fields in Tehran city in 2016. 251 male athletes with and without anabolic steroids consumption were selected using multi-stage cluster sampling method. Athletes had mean age (24 ± 6) years and exercise history (3 ± 1) years. Data were collected using competitive anxiety and perceived overtraining questionnaires. The findings were analyzed by multivariate analysis of variance (MANOVA) and independent t test and showed that athletes without the consumption of anabolic steroids had higher cognitive and physical anxiety than those athletes who consumed anabolic steroids, but there was no significant difference between the two groups in self-confidence. Also, given the perceived overtraining variable, the group who did not use anabolic steroids had a higher level of overtraining. The results indicated that one of the main reasons why athletes use anabolic steroids is their benefits which reduce the negative states and improve the mental and physical performance. That is why these steroids prevail among athletes every day