UNSUPERVISED PART OF SPEECH TAGGING FOR PERSIAN

Abstract In this paper we present a rather novel unsupervised method for part of speech (below POS) disambiguation which has been applied to Persian. This method known as Iterative Improved Feedback (IIF) Model, which is a heuristic one, uses only a raw corpus of Persian as well as all possible tags for every word in that corpus as input. During the process of tagging, the algorithm passes through several iterations corresponding to n-gram levels of analysis to disambiguate each word based on a previously defined threshold. The total accuracy of the program applying in Persian texts has been calculated as 93 percent, which seems very encouraging for POS tagging in this language

Comparing the performance of Organic-inorganic hybrid tandem multijunction solar cells of different organic bulk thicknesses

In this study, J-V curves of a-Si:H/PCPDTBT:PC70BM hybrid tandem solar cells were simulated using a modified drift-diffusion model, and the influence of the thickness of the organic blend layer was investigated. The results of the simulations were compared with experimental data from literature.It is shown that as the thickness of the blend layer increases, the fill factor and the voltage corresponding to maximum power point decrease whereas the maximum power point and the short circuit current density of solar cell increase up to thicknesses of 60 nm and 138 nm respectively. Finally, the modified organic solar cell was used as second sub-cell and the power conversion efficiency increased from 1.90% to 2.1% in simulation

Sulfur dioxide emissions in Iran and environmental impacts of sulfur recovery plant in Tabriz Oil Refinery

Background: Combustion of fossil fuels contributes to sulfur dioxide (SO2) emissions. To deal with this issue, the government of Iran has appointed the oil refineries to upgrade their installations and produce high quality fuels. Thus, this study investigated the status of SO2 emissions in Iran and the capability of advanced technologies to control SO2 emissions. Methods: The status of SO2 emissions was reviewed and discussed through national online reports. Meanwhile, the environmental impacts of sulfur recovery and tail gas treatment (TGT) plant (STP) were assessed by applying rapid impact assessment matrix (RIAM) for implementation and nonimplementation alternatives in Tabriz Oil Refinery Company (TORC). Results: SO2 emissions have been increased by 2.1 times during 2004-2014 in Iran. Power plants and transportation play a significant role in this regard and overall contribute 82% of emissions. Among the other fossil fuels, fuel oil and gasoil account for 95% of SO2 emissions. Based on the environmental impact assessments (EIAs), sulfur recovery management and enhancing sulfur removal efficiency from flue gas up to 99.9% are two main positive environmental aspects of STP project that would enable TORC to prevent 87 600 tons of SO2 emissions, annually. Nevertheless, flue gas and sour gas streams which have been determined as probable pollution sources of process, should be managed through proper monitoring framework. Conclusion: The increasing trend of SO2 emissions and significant role of fuel oil and gasoil has required Iranian oil refineries to enhance the quality of fuels by employing clean and cost-effective technologies. Keywords: Air pollution, Fossil fuels, Oil and gas industry, Environmental assessment, Tabri

Effects of “FIRST2ACT” Model on Knowledge and Practical Skills of Difficult Airway Management in Nurse Anesthesia Students: An Interventional Study

Introduction: An important part of anesthesia management is opening and maintaining the patient’s airway. Failure to establish and maintain a safe airway for patients during anesthesia is a life-threatening condition. Despite advances in science and technology, difficult airway management is far from ideal. Providing a simulated environment for critical situations seems to be the best way to better educate and prevent medical errors. This study aimed to compare the effect of the FIRST2ACT (Feedback Incorporating Review and Simulation Techniques to Act on Clinical Trend) model on knowledge and practical skills of difficult airway management and respiratory accidents between the intervention and control groups.Methods: This study was a quasi-experimental intervention with before and after design. Sampling was done by census method and the participants were third and fourth-year nurse anesthesia students (n=62). The students were randomly allocated to an intervention group (n=31) educated and practicing based on the FIRST2ACT model and a control group (n=31). The intervention consisted of five stages: developing core knowledge, assessment, simulation, reflective review, and performance feedback, all based on the FIRST2ACT model. Theoretical and practical skills were examined in the participants. Data collection tools included a questionnaire and a checklist.Results: The results showed that after applying the FIRST2ACT model, the intervention group scored higher than the control group in both theoretical knowledge (17.87±1.43 vs. 12.67±1.35) and practical skills (134.28±3.21 vs. 81.58±8.55). This difference in results between the two groups was statistically significant (P˂0.001).Conclusion: It can be concluded that using this model was effective to improve the knowledge and practical skills of nurse anesthesia students in the field of difficult airway management and respiratory accidents during anesthesia

Metallic Nanoparticles for the Modulation of Tumor Microenvironment; A New Horizon

Cancer is one of the most critical human challenges which endangers many people’s lives every year with enormous direct and indirect costs worldwide. Unfortunately, despite many advanced treatments used in cancer clinics today, the treatments are deficiently encumbered with many side effects often encountered by clinicians while deploying general methods such as chemotherapy, radiotherapy, surgery, or a combination thereof. Due to their low clinical efficacy, numerous side effects, higher economic costs, and relatively poor acceptance by patients, researchers are striving to find better alternatives for treating this life-threatening complication. As a result, Metal nanoparticles (Metal NPs) have been developed for nearly 2 decades due to their important therapeutic properties. Nanoparticles are quite close in size to biological molecules and can easily penetrate into the cell, so one of the goals of nanotechnology is to mount molecules and drugs on nanoparticles and transfer them to the cell. These NPs are effective as multifunctional nanoplatforms for cancer treatment. They have an advantage over routine drugs in delivering anticancer drugs to a specific location. However, targeting cancer sites while performing anti-cancer treatment can be effective in improving the disease and reducing its complications. Among these, the usage of these nanoparticles (NPs) in photodynamic therapy and sonodynamic therapy are notable. Herein, this review is aimed at investigating the effect and appliances of Metal NPs in the modulation tumor microenvironment which bodes well for the utilization of vast and emerging nanomaterial resources

Theory of hard photoproduction

The present theoretical knowledge about photons and hard photoproduction processes, i.e. the production of jets, light and heavy hadrons, quarkonia, and prompt photons in photon-photon and photon-hadron collisions, is reviewed. Virtual and polarized photons and prompt photon production in hadron collisions are also discussed. The most important leading and next-to-leading order QCD results are compiled in analytic form. A large variety of numerical predictions is compared to data from TRISTAN, LEP, and HERA and extended to future electron and muon colliders. The sources of all relevant results are collected in a rich bibliography.Comment: Habilitationsschrift, scheduled for publication in Rev. Mod. Phys., 126 pages, 61 figure

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Scenario-based simulation and debriefing sessions can potentially improve non-technical skills in nurse anesthetist students of Iran; A quasi-experimental study

Background: Technical skills refer to all practical abilities necessary for surgery or anesthesia. Non-technical skills (Task management, Team-working, Situation-awareness, and Decision-making) are abilities accelerate the individuals' adaptability in critical anesthetic situations. Simulation (a type of unreal simulated education similar to the real situation in which the learner can achieve clinical experiences using human models) and debriefing sessions (a method of education in which the learners have a discussion about what they have learned during simulation) are educational protocols for non-technical skills improvement. Thus, in the current quasi-experimental study, we aimed to investigate the effects of scenario-based simulation and debriefing sessions on the development of non-technical skills among nurse anesthetist students (Hamadan, Iran). Methods: Nurse anesthetist students (n = 60) were categorized into control (n = 30) and test (n = 30) groups. Anesthesia induction was simulated by an anesthesiologist for students in a practice hall. Immediately, debriefing sessions were held to improve non-technical skills. A week later, the Anaesthetists' Non-Technical Skills (ANTS) checklist was hired, and non-technical skills were scored. Collected data were analyzed (SPSS v.16.0) and represented as Mean ± SD. P-value < 0.05 was also considered a significant level. Results: Significantly (p < 0.05), following simulation and debriefing interventions, non-technical skills were improved, including Task management (mean ANTS score: 11.13 ± 2.87 and 14.53 ± 2.20 in control and test, respectively), Team-working (mean ANTS score: 10.42 ± 3.20 and 14.93 ± 2.19 in control and test, respectively), and Situation-awareness (mean ANTS score: 9.62 ± 4.30 and 13.20 ± 2.86 in control and test, respectively) skills. Besides, Decision-making skills represented no significant (p = 0.299) alteration after the intervention (mean ANTS score: 5.81 ± 2.75 and 4.73 ± 2.55 in control and test, respectively). Conclusions: Scenario-based simulation training and debriefing sessions, as the proposed educational curriculum, can promote non-technical skills during anesthesia induction in nurse anesthetist students leading to improvement of patient safety and prevention of medical profession errors

A New Technique for Quantitative Determination of Dexamethasone in Pharmaceutical and Biological Samples Using Kinetic Spectrophotometric Method

Dexamethasone is a type of steroidal medications that is prescribed in many cases. In this study, a new reaction system using kinetic spectrophotometric method for quantitative determination of dexamethasone is proposed. The method is based on the catalytic effect of dexamethasone on the oxidation of Orange G by bromate in acidic media. The change in absorbance as a criterion of the oxidation reaction progress was followed spectrophotometrically. To obtain the maximum sensitivity, the effective reaction variables were optimized. Under optimized experimental conditions, calibration graph was linear over the range 0.2–54.0 mg L−1. The calculated detection limit (3sb/m) was 0.14 mg L−1 for six replicate determinations of blank signal. The interfering effect of various species was also investigated. The present method was successfully applied for the determination of dexamethasone in pharmaceutical and biological samples satisfactorily