A comparison of effective factors in creating delays from the contractors’ and the employers’ point of view in construction of schools in Tehran

Time is one of the most fundamental factors in investment projects which are directly or indirectly affecting other factors. Since the reconstruction of Iran's schools as one of the Executive agencies, dedicates a large portion of Iran's annual credit to itself, paying attention to the effective factors in the delay in timely delivery of the organization's projects can result in increasing productivity and its performance. The purpose of this study is to identify factors in the delay of the organization's projects in Tehran province from the employer and the contractor's perspective. In the meantime, the qualitative information by using face-to-face interview with the experts and experts of both parties were collected as well quantitative information which has been prepared through a questionnaire. The results of two groups have identified factors like   high inflation in Iran , low affordability of the contractors, delay in financial demands of the contractors by an employer, offering lower prices by contractors, weaknesses in the management of financial resources and lack of familiarity of the contractors with the principles of engineering and workshop management. Also, each group has pointed out factors as effective reasons which are at a low priority of the other group. Identifying these categories of factors can help every researcher to find the claim causing factors in doing the projects by  this organization

Coupling Machine Learning and Crop Modeling Improves Crop Yield Prediction in the US Corn Belt

This study investigates whether coupling crop modeling and machine learning (ML) improves corn yield predictions in the US Corn Belt. The main objectives are to explore whether a hybrid approach (crop modeling + ML) would result in better predictions, investigate which combinations of hybrid models provide the most accurate predictions, and determine the features from the crop modeling that are most effective to be integrated with ML for corn yield prediction. Five ML models (linear regression, LASSO, LightGBM, random forest, and XGBoost) and six ensemble models have been designed to address the research question. The results suggest that adding simulation crop model variables (APSIM) as input features to ML models can decrease yield prediction root mean squared error (RMSE) from 7 to 20%. Furthermore, we investigated partial inclusion of APSIM features in the ML prediction models and we found soil moisture related APSIM variables are most influential on the ML predictions followed by crop-related and phenology-related variables. Finally, based on feature importance measure, it has been observed that simulated APSIM average drought stress and average water table depth during the growing season are the most important APSIM inputs to ML. This result indicates that weather information alone is not sufficient and ML models need more hydrological inputs to make improved yield predictions

Comparative Evaluation of Dexmedetomidine and Bupivacaine Combination versus Bupivacaine Alone On the Analgesic Effect of Ilioinguinal Nerve Block in Pediatric Patients Undergoing Inguinal Herniorrhaphy

Introduction: Elective inguinal herniorrhaphy is one of the most prevalent surgical procedures in pediatric age group. |Postoperative pain is prevalent in children undergoing inguinal hernia repair. This study was aimed to compare the analgesic effect of dexmedetomidine with bupivacaine combination versus bupivacaine alone for ilioinguinal nerve block in children undergoing inguinal herniorrhaphy.Materials and Methods: In this prospective randomized study, we studied 60 ASA class I and II patients with the age between 6 months to 6 years scheduled for unilateral inguinal herniorrhaphy. With the help of a computer-generated list, our patients were assigned randomly to two groups of 30 patients. Group A, received 5cc bupivacaine 0.25%, and group B received 5cc bupivacaine 0.25% with dexmedetomidine 0.3 μg/ kg. Statistical analysis was performed using SPSS. The t-student and Mann-Whitney tests were used to compare the variables between groups. The values were considered significant if P < 0.05.Results: There was no significant difference in blood pressure (systolic or diastolic) and heart rate between the two groups (P=0.624, P=0.784 and P=0.167, respectively).  Analgesia duration was significantly longer in bupivacaine with dexmedetomidine group in comparison to bupivacaine alone group (P=0.008). However, there were no significant difference in frequency of analgesic consumption (P = 0.175) and total dose of analgesic consumption (P = 0.634) in the first 24 h between the two groups. One patient in group B developed bradycardia.Conclusion: The use of dexmedetomidine, as an adjuvant to bupivacaine prolongs the length and the analgesic efficacy of the ilioinguinal nerve block after inguinal herniorrhaphy in pediatric age group

Tumor Hypoxia Imaging Agents in Nuclear Medicine

Hypoxia is due to imbalance in oxygen supply and oxygen demand compromising biological functions of cells. Since tumor hypoxia results in angiogenesis, apoptosis, metastasis, tumor aggressiveness and treatment failure, in vivo measurement is required. Nuclear imaging can provide information about tissue oxygen levels. 2-nitroimidazole containing compounds selectively accumulate in hypoxic cells. They have been radiolabeled with 18F, 123/124I, and 99mTc and used in clinical trial stages using PET and SPECT techniques. 62/64Cu-ATSM is a non-imidazole imaging agent, which is trapped in hypoxic cells. There is a great interest in the development of 99mTc-labeled 2-nitroimidazole compounds. Though novel compounds based on molecular mechanisms of hypoxia would be developed in future.HighlightsTumor hypoxia results in angiogenesis, apoptosis, metastasis, tumor aggressiveness, and treatment failure.Nuclear imaging can provide information about tissue oxygen levels.2-nitroimidazole compounds selectively accumulate in hypoxic cells.At present a few PET radiopharmaceuticals as hypoxia imaging agents are in clinical trial stages

A comparison of effective factors in creating delays from the contractors’ and the employers’ point of view in construction of schools in Tehran

Time is one of the most fundamental factors in investment projects which are directly or indirectly affecting other factors. Since the reconstruction of Iran's schools as one of the Executive agencies, dedicates a large portion of Iran's annual credit to itself, paying attention to the effective factors in the delay in timely delivery of the organization's projects can result in increasing productivity and its performance. The purpose of this study is to identify factors in the delay of the organization's projects in Tehran province from the employer and the contractor's perspective. In the meantime, the qualitative information by using face-to-face interview with the experts and experts of both parties were collected as well quantitative information which has been prepared through a questionnaire. The results of two groups have identified factors like   high inflation in Iran , low affordability of the contractors, delay in financial demands of the contractors by an employer, offering lower prices by contractors, weaknesses in the management of financial resources and lack of familiarity of the contractors with the principles of engineering and workshop management. Also, each group has pointed out factors as effective reasons which are at a low priority of the other group. Identifying these categories of factors can help every researcher to find the claim causing factors in doing the projects by  this organization

A comparison of effective factors in creating delays from the contractors’ and the employers’ point of view in construction of schools in Tehran

Time is one of the most fundamental factors in investment projects which are directly or indirectly affecting other factors. Since the reconstruction of Iran's schools as one of the Executive agencies, dedicates a large portion of Iran's annual credit to itself, paying attention to the effective factors in the delay in timely delivery of the organization's projects can result in increasing productivity and its performance. The purpose of this study is to identify factors in the delay of the organization's projects in Tehran province from the employer and the contractor's perspective. In the meantime, the qualitative information by using face-to-face interview with the experts and experts of both parties were collected as well quantitative information which has been prepared through a questionnaire. The results of two groups have identified factors like   high inflation in Iran , low affordability of the contractors, delay in financial demands of the contractors by an employer, offering lower prices by contractors, weaknesses in the management of financial resources and lack of familiarity of the contractors with the principles of engineering and workshop management. Also, each group has pointed out factors as effective reasons which are at a low priority of the other group. Identifying these categories of factors can help every researcher to find the claim causing factors in doing the projects by  this organization

Maize Yield and Nitrate Loss Prediction with Machine Learning Algorithms

Pre-season prediction of crop production outcomes such as grain yields and N losses can provide insights to stakeholders when making decisions. Simulation models can assist in scenario planning, but their use is limited because of data requirements and long run times. Thus, there is a need for more computationally expedient approaches to scale up predictions. We evaluated the potential of five machine learning (ML) algorithms as meta-models for a cropping systems simulator (APSIM) to inform future decision-support tool development. We asked: 1) How well do ML meta-models predict maize yield and N losses using pre-season information? 2) How many data are needed to train ML algorithms to achieve acceptable predictions?; 3) Which input data variables are most important for accurate prediction?; and 4) Do ensembles of ML meta-models improve prediction? The simulated dataset included more than 3 million genotype, environment and management scenarios. Random forests most accurately predicted maize yield and N loss at planting time, with a RRMSE of 14% and 55%, respectively. ML meta-models reasonably reproduced simulated maize yields but not N loss. They also differed in their sensitivities to the size of the training dataset. Across all ML models, yield prediction error decreased by 10-40% as the training dataset increased from 0.5 to 1.8 million data points, whereas N loss prediction error showed no consistent pattern. ML models also differed in their sensitivities to input variables. Averaged across all ML models, weather conditions, soil properties, management information and initial conditions were roughly equally important when predicting yields. Modest prediction improvements resulted from ML ensembles. These results can help accelerate progress in coupling simulation models and ML toward developing dynamic decision support tools for pre-season management

Performance of Local Anesthesia with Lidocaine among Opium Addicts and Non-Addicts; a Case Control Study

Introduction: Compared to ordinary people, addicts usually have a lower pain threshold. The current work attempts to compare the performance of local analgesia with lidocaine among opium addicts and non-addicts.Methods: In this case-control study, opium addicts and healthy patients with skin laceration referring to emergency departments of two educational hospitals were compared regarding the response to local anesthesia with lidocaine, as well as side effects.Results: 197 cases with the mean age of 43.44 ± 20.12 years were studied (72.1% male). 98 (49.8%) cases were addicts and 99 (50.2%) were healthy people. Two groups were similar regarding age (p = 0.281), sex (p = 0.666), and wound size (p = 0.272). The amount of pain reduction 5 (df =1.5, F=0.38, p = 0.88) and 10 (df =1.5, F=0.58, p = 0.72) minutes after lidocaine injection was not different between the groups. Subgroup analysis based on sex and age of patient did not show any differences between the groups (p > 0.1 for all analysis). The mean duration of analgesia was 16.4 ± 5.37 minutes in addicts and 16.95±1.79 in control group (p = 0.334).Conclusion: Lidocaine, as a commonly used local anesthetic agents, does not show different effects in addicts and non-addicts in repairing skin laceration