A method for identifying the cause of inefficient salt-doping in organic semiconductors

Doping to enhance the electrical conductivity of organic semiconductors is not without its challenges: The efficacy of this process depends on many factors and it is not always clear how to remedy poor doping. In the case of doping with salts, one of the possible causes of poor doping is a limited yield of integer charge transfer resulting in the presence of both cations and anions in the film. The charge of such ions can severely limit the electrical conductivity, but their presence is not easily determined. Here we introduce a set of simple conductivity measurements to determine whether poor doping in the case where the dopant is a salt is due to limited integer charge transfer. By tracking how the conductivity changes over time when applying a bias voltage for an extended amount of time we can pinpoint whether unwanted ions are present in the film. Firstly, we introduce the principle of this approach by performing numerical simulations that include the movement of ions. We show that the conductivity can increase or decrease depending on the type of ions present in the film. Next, we show that the movement of these dopant ions causes a build-up of space-charge, which makes the current-voltage characteristic non-linear. Next, we illustrate how this approach may be used in practice by doping a fullerene derivative with a series of organic salts. We thus provide a tool to make the optimization of doping more rational.

Prognostic indicators in critically ill poisoned patients: development of a risk-prediction nomogram

OBJECTIVES

The prognosis of acutely poisoned patients is a significant concern for clinical toxicologists. In this study, we sought to determine the clinical and laboratory findings that can contribute to predicting the medical outcomes of poisoned patients admitted to intensive care units (ICUs).

METHODS

This retrospective study was performed from January 2009 to January 2016 in the ICU of Vali-e-Asr Hospital in Birjand, Iran. We included all patients with the diagnosis of acute poisoning admitted to the ICU. Demographic data, laboratory results, the Sequential Organ Failure Assessment (SOFA), and acute physiology score + age points + chronic health points (APACHE) II, and the Simplified Acute Physiology Score (SAPS) II, and outcome were collected. Univariate analysis (Mann-Whitney or t-test), multiple logistic regression, receiver operating characteristics (ROC) curve analysis, and Pearson's correlation test were performed using SPSS, STATA/SE 13.0, and Nomolog software programs.

RESULTS

The multiple logistic regression analysis revealed that five factors were significant for predicting mortality including age (OR 95% CI: 1.1[1.05-1.12], p<0.001), Glasgow Coma Score (GCS) (OR 95% CI: 0.71[0.6-0.84], p<0.001), white blood cell (WBC) count (OR 95% CI: 1.1[1.01-1.12], p=0.04), serum sodium (Na) (OR 95% CI: 1.08[1.01-1.15], p=0.02), and creatinine levels (Cr) (OR 95% CI: 1.86 [1.23-2.81], p=0.003). We generated a five-variable risk-prediction nomogram which could both predict mortality risk and identify high-risk patients.

CONCLUSIONS

Age, GCS, WBC, serum creatinine, and sodium levels are the best prognostic factors for mortality in poisoned patients admitted to the ICU. The APACHE II score can discriminate between non-survivors and survivors. The nomogram developed in the current study can provide a more precise, quick, and simple analysis of risks, thereby enabling the users to predict mortality and identify high-risk patients.

Prognostic indicators in critically ill poisoned patients: development of a risk-prediction nomogram

Objectives The prognosis of acutely poisoned patients is a significant concern for clinical toxicologists. In this study, we sought to determine the clinical and laboratory findings that can contribute to predicting the medical outcomes of poisoned patients admitted to intensive care units (ICUs). Methods This retrospective study was performed from January 2009 to January 2016 in the ICU of Vali-e-Asr Hospital in Birjand, Iran. We included all patients with the diagnosis of acute poisoning admitted to the ICU. Demographic data, laboratory results, the Sequential Organ Failure Assessment (SOFA), and acute physiology score + age points + chronic health points (APACHE) II, and the Simplified Acute Physiology Score (SAPS) II, and outcome were collected. Univariate analysis (Mann-Whitney or t-test), multiple logistic regression, receiver operating characteristics (ROC) curve analysis, and Pearson's correlation test were performed using SPSS, STATA/SE 13.0, and Nomolog software programs. Results The multiple logistic regression analysis revealed that five factors were significant for predicting mortality including age (OR 95% CI: 1.1[1.05-1.12], p<0.001), Glasgow Coma Score (GCS) (OR 95% CI: 0.71[0.6-0.84], p<0.001), white blood cell (WBC) count (OR 95% CI: 1.1[1.01-1.12], p=0.04), serum sodium (Na) (OR 95% CI: 1.08[1.01-1.15], p=0.02), and creatinine levels (Cr) (OR 95% CI: 1.86 [1.23-2.81], p=0.003). We generated a five-variable risk-prediction nomogram which could both predict mortality risk and identify high-risk patients. Conclusions Age, GCS, WBC, serum creatinine, and sodium levels are the best prognostic factors for mortality in poisoned patients admitted to the ICU. The APACHE II score can discriminate between non-survivors and survivors. The nomogram developed in the current study can provide a more precise, quick, and simple analysis of risks, thereby enabling the users to predict mortality and identify high-risk patients.

Identification and evaluation of human errors esing human factor analysis and classification system based on fuzzy hierarchy theory: a case study in the cement industry

Introduction: Human factors studies have shown that about 80% of the root causes of major accidents have effected on safety, the environment or ergonomics are related to the human error. The purpose of this study was to identify human errors using the HFACS method and the FAHP theory in cement industry. Methods: The present study was a retrospective study carried out in one cement industry of fars provience. At first, the RCA analysis of 95 incidents occurred during the past six years was prepared. Then, by integrating the human factors analysis and classification system technique) HFACS( and the theory of fuzzy analytic hierarchy process) FAHP( by 4 safety engineers of the factory was analyzed. Results: The results of this study showed that the highest errors were related to the first level with the weight of 0.272, that was, the errors caused by unsafe acts, at this level of the subgroup of "skill-based error" with the weight of 0.269, the 2nd level of the sub-group of "industrial environment" with the weight of 0.155 , the 3rd subgroup of "inadequate supervision" with the weight of 0.352 and the 4th sub-category of "resource management" with the weight of 0.393 had the highest impact on the levels. Conclusion: The results show that errors have various causes, including individual, activity, situational, and organizational errors that require careful planning and management to eliminate or reduce these errors. This error reduction, according to safety expert theory, health and environment of the cement plant, including the promotion and effectiveness of staff training, safety guidelines, improvement of staff performance monitoring, identification, evaluation and elimination of high-risk risks, improvement of management and equipment systems, changing safety attitudes, as well as enhancing safety attitudes. Awareness can help reduce the likelihood of human error in the organization.

Epidemiological and clinical profiles of acute poisoning in patients admitted to the intensive care unit in eastern Iran (2010 to 2017)

BACKGROUND

Acute poisoning is a common chief complaint leading to emergency department visits and hospital admissions in developing countries such as Iran. Data describing the epidemiology of different poisonings, characteristics of the clinical presentations, and the predictors of outcome are lacking. Such data can help develop more efficient preventative and management strategies to decrease morbidity and mortality related to these poisonings. This manuscript describes the epidemiology of acute poisoning among patients admitted to the intensive care unit (ICU) in Birjand, Iran.

METHODS

This retrospective, cross-sectional study was conducted to characterize acute poisonings managed in the ICU during a 7-year period from March 2010 to March 2017 in a single center in Birjand, Iran. Patient characteristics, suspected exposure, the route of exposure, and outcome data were collected from hospital medical records.

RESULTS

During the study period, 267 (64% male and 36% female) patients met inclusion criteria. Pharmaceutical medication (36.6%), opioids (26.2%) followed by pesticides (13.9%) were the most common exposures 38.2% of these cases were identified as suicide attempts. There were different frequencies in terms of xenobiotic exposure in relation to gender (p = 0.04) and the survival (p = 0.001). There was a significant difference between various xenobiotics identified as the cause of poisoning (p = 0.001). Mortality rate in our study was 19.5%. The incidence of outcomes was significantly higher in patients poisoned with opioids, pesticides, benzodiazepines, and tricyclic antidepressants (p < 0.05). The median length of hospital stay was higher in pesticide-poisoned patients (p = 0.04).

CONCLUSION

Opioids and pesticides were the most common exposures. The mortality rate of the poisoned patients in the ICU was proportionately high. The mortality rate due to opioid poisoning is a major concern and the most significant cause death due to poisoning in the region. Further monitoring and characterization of acute poisoning in Birjand, Iran is needed. These data can help develop educational and preventative programs to reduce these exposures and improve management of exposures in the prehospital and hospital settings.