A Study of the Comparison between Artificial Neural Networks, Logistic Regression and Similarity Weighted Instance-based Learning in Modeling and Predicting Trends in Deforestation

The change in forest cover plays a vital role in ecosystem services, atmospheric carbon balance, and, thus, climate change. In this study, land use maps for the periods 1984 and 2012, derived from Landsat TM satellite imagery, were used. The goal of this study is comparison of three procedures of artificial neural network, logistic regression, and similarity weighted instance-based learning (SIM Weight) to predict spatial trend of forest cover change. The SimWeight considers the nearest instances in the variable space, which are computed based on past changes and the relative importance of the driving variables. The LogReg approach, on the other hand, is a type of generalized linear model that assumes that the current land use pattern reflects the processes of land use in the past. Artificial Neural Network is a nonparametric algorithm that is capable of fitting complex nonlinear functions to find the relations between past changes and their driving variables. Such approaches are expected to produce better fitting between the change potential and their complex relationships with their driving variables. Artificial neural networks in comparison with logistic regression and SimWeight have higher accuracy and less error in modeling and predicting of forest changes

Examining the Relationship between Sleep Quality and Academic Performance with the Degree of Dependence on Smartphone during the Coronavirus Pandemic

Background and Objective: After the outbreak of the coronavirus disease 2019 (COVID-19) pandemic in Iran, to pre-vent the spread of coronavirus, it was decided for classes to be held virtually. Even though this decision reduced the spread of the virus, the students were exposed to smartphone addiction, which is believed to have high comorbidity with psychological problems. The current study aims to examine the relationship between sleep quality and academic per-formance with the degree of dependence on smartphone during the COVID-19 pandemic. Materials and Methods: The current research was a cross-sectional study with 254 adolescent students participating in virtual classes. This study was conducted in 2020-2021. The participants filled out the following questionnaires online: Pittsburgh Sleep Quality Index (PSQI), smartphone addiction scale (SAS), and Educational Performance Test (EPT). The data were analyzed using SPSS software, descriptive statistics [frequency, pearson correlation, mean, standard deviation (SD)], and inferential statistics (simultaneous regression) (P < 0.05). Results: There was a significant correlation between components of addiction to the Internet and the study’s variables. The results of correlation analysis showed that there was a significant correlation between Internet addiction and academic performance (Pearson correlation = -0.57, P = 0.01) and between Internet addiction and sleep quality (Pearson correlation = 0.47, P = 0.01). Conclusion: According to the results, it can be concluded that after the COVID-19 pandemic and virtual education, Internet addiction could be a risk factor for decreasing sleep quality and academic performance in students

The Relationship between Spiritual Health and Public Health Aspects among Patients with Breast Cancer

For downloading the full-text of this article please click here.Background and Objective: Spiritual well-being is one of the fundamental concepts in chronic diseases and is considered an important approach to improve public health among individuals. Given the importance of spiritual well-being and its role in the promotion of mental health, the present study was conducted with the aim of evaluating spiritual well-being and mental health in patients with breast cancer who visited a center for cancer control at the University of Medical Sciences.Method: This cross-sectional study was conducted on 122 patients with breast cancer in 2015. The data were collected through self-administered 20-item Paloutzian &amp; Ellison’s Spiritual Well-Being Scale and a 28-item questionnaire of mental health after determining their validity and reliability. The collected data were then analyzed using ANOVA and Pearson correlation and linear regression.Results: The results show that most patients had moderate spiritual health (37.8%), and most of them suffered mild mental health problems. (50 percent). Furthermore, there was a significant relationship between mental health and demographic characteristics (Marital status, education, income, physical activity). There was also a significant relationship between mental health and spiritual health.Conclusion: According to the findings, to prevent mental suffering among patients with breast cancer, promoting spiritual health of patients should be regarded as one of the priorities of health care professionals.For downloading the full-text of this article please click here

Harnessing the Power of Smart and Connected Health to Tackle COVID-19:IoT, AI, Robotics, and Blockchain for a Better World

As COVID-19 hounds the world, the common cause of finding a swift solution to manage the pandemic has brought together researchers, institutions, governments, and society at large. The Internet of Things (IoT), Artificial Intelligence (AI) &#x2014; including Machine Learning (ML) and Big Data analytics &#x2014; as well as Robotics and Blockchain, are the four decisive areas of technological innovation that have been ingenuity harnessed to fight this pandemic and future ones. While these highly interrelated smart and connected health technologies cannot resolve the pandemic overnight and may not be the only answer to the crisis, they can provide greater insight into the disease and support frontline efforts to prevent and control the pandemic. This paper provides a blend of discussions on the contribution of these digital technologies, propose several complementary and multidisciplinary techniques to combat COVID-19, offer opportunities for more holistic studies, and accelerate knowledge acquisition and scientific discoveries in pandemic research. First, four areas where IoT can contribute are discussed, namely, i) tracking and tracing, ii) Remote Patient Monitoring (RPM) by Wearable IoT (WIoT), iii) Personal Digital Twins (PDT), and iv) real-life use case: ICT/IoT solution in Korea. Second, the role and novel applications of AI are explained, namely: i) diagnosis and prognosis, ii) risk prediction, iii) vaccine and drug development, iv) research dataset, v) early warnings and alerts, vi) social control and fake news detection, and vii) communication and chatbot. Third, the main uses of robotics and drone technology are analyzed, including i) crowd surveillance, ii) public announcements, iii) screening and diagnosis, and iv) essential supply delivery. Finally, we discuss how Distributed Ledger Technologies (DLTs), of which blockchain is a common example, can be combined with other technologies for tackling COVID-19

Efficient and green pathway for one-pot synthesis of spirooxindoles in the presence of CuO nanoparticles

In this research, a new, green and eco-friendly method for the synthesis of spirooxindole derivatives was presented. The reaction was performed at room temperature in the presence of catalytic amounts (4 mol.%) of CuO nanoparticles and products were obtained in high to excellent yields. Low-cost high-efficiency reusable catalyst, short reaction times at room temperature, high to excellent yield and easy purification of products are the main advantages to this protocol. The pronounced advantages of catalyst are expected to create a new pathway for the synthesis of spirooxindoles

Assessing Germination Response of Wheat and Wild Oat to Different Levels of ZnO Nanoparticles

Introduction: These days, researchers are trying to develop an efficient production technology based on the innovative techniques to increase seedling vigour and plant establishment through physical seed treatments. Seed germination is an important phenomenon in modern agriculture because it is a thread of life of plants that guarantees its survival. Nanotechnology has emerged as an innovative technology for the elaboration and use of new nanomaterials in the industry and many fields of research. It opens up a wide array of opportunities in various fields like medicine, pharmaceuticals, electronics and agriculture. Nanotechnology has the potential to protect plants, monitor plant growth, detect plant and animal diseases, increase global food production, enhance food quality, and reduce waste for “sustainable intensification”(Chandra Rath et al, 2017). Zinc (Zn) is an essential nutrient required by all living organisms. It has been considered as an essential micronutrient for metabolic activities in plants and animals. Zinc has important functions in the synthesis of auxin or indole acetic acid (IAA) from tryptophan as well as in biochemical reactions required for formation of chlorophyll and carbohydrates. It also regulates the functions of stomata by retaining potassium content of protective cells. The crop yield and quality of produce can be affected by deficiency of Zn (Pandey et al., 2006). Zinc oxide (nano-ZnO) is commonly used metal oxide engineered nanoparticle. It is used in a range of applications such as sunscreens and other personal care products, electrodes and biosensors, photocatalysis and solar cells. Seed is an important stage of plant life history. Most invasive plants primarily rely on seedling recruitment for population establishment and persistence. Rapid spread of many invasive plants is frequently correlated with special seed traits. Seed trait variations exist not only among species but also within species. Seed traits variations within a species are essential for seedling establishment at different habitats (Grundy et al., 1996). Germination of various plants has a different response to nanoparticles. Application of nanoparticles that have a positive effect on germination and growth of crop and a negative effect on weed can be useful in weed control. Materials and Methods: In order to study the effect of different concentrations of ZnO on germination characteristics of wild oat and two genotypes of wheat, an experiment was conducted with a factorial arrangement based on completely randomized design with four replications in research laboratory of Ilam University. The experimental treatments were plant genotypes (wild oat and Behrang and Sivand genotypes of wheat) and different concentrations of ZnO (0, 10, 100 and 500 ppm). Germination of seeds was determined by placing 30 seed in a 9-cm-diam Petri dish containing two layers of Whatman No. 1 filter paper, moistened with 5 ml of distilled water or a treatment solution. The treatments of ZnO were applied in Agar complex. After treatment, the dishes were sealed with paraffin tape, and placed in the dark in an incubator at 25 °C. The number of seeds germinated was counted every day. Seedling and radicle length, seedling and radicle dry weight and germination rate were measured. Data were subjected to two-way analysis of variance (ANOVA) and the difference between treatment means was separated using Duncan test. A significance level of 95% was applied by SAS 9.2. Results and Discussion: The results showed that the simple and interaction effects of genotype and ZnO had a significant effect (P ≤ 0.01) on all studied traits. The plumule length of both wheat genotypes was increased to 100 ppm ZnO concentration and then was decreased. The plumule length of oat wild was increased by increasing ZnO concentration. Increase in ZnO concentration to 10 ppm caused a significant increment in the radical length of sivand genotype and wild oat, and the trait was reduced after mentioned concentration. The radical length of behrang genotype was declined as ZnO concentration increased. The applied ZnO treatments caused a significant reduction and increase in plumule dry weight of behrang genotype and wild oat, respectively, whereas they had an insignificant effect on plumule dry weight of sivand genotype. Increased ZnO concentration negatively influenced the plumule dry weight of wild oat and behrang genotype and positively affected the plumule dry weight for sivand genotype. Germination rate and percentage of the both wheat genotypes were not affected by nanoparticle, but, increased ZnO concentration caused a significant increment in these traits in wild oat. Conclusion: Overall, the results illustrated that application of ZnO nanoparticle in wheat agroecosystems can lead to a higher germination rate and growth of wild oat compared to wheat, and is not recommended

Direct Laser Metal Deposition (DLMD) Additive Manufacturing (AM) of Inconel 718 Superalloy: Elemental, Microstructural and Physical Properties Evaluation

In this study, Direct Laser Metal Deposition (DLMD) technique is adopted for the additive manufacturing (AM) of Inconel 718 Superalloy. A 1 kW fiber laser with a coaxial nozzle head is used. The effects of scanning speed (2.5 and 5 mm/s) as well as powder feed rate (17.94 and 28.52 g/min) on the process were investigated. Characteristics of the 3D printed wall specimens such as the geometrical dimensions (width and height), microstructure observations, and the microhardness were obtained. To study the stability of the 3D manufactured walls, the height stability was considered for the investigation. Optical microscopy (OM), field emission electron microscopy (FE-SEM), energy dispersive X-ray spectroscopy (EDS), and mapping analysis were performed to derive the microstructural features of the additively manufactured parts (AMP). Vickers microhardness test is used to evaluate the hardness distributions of AMP. Catchment concept of the powder in DLMD process is used for explaining different trends of the process. Results indicated that, by decreasing the scanning speed, the width and height of the deposited layer increase. The average width of AMP directly depends on scanning speed and the powder feed rate. Scanning speed has a reverse effect on the height stability; that is, the lower the scanning speed, the larger the stability. Microstructural results showed that because of the solidification process, the alloying elements will be accumulated in the grain boundaries. The non-uniform cooling rate and non-steady solidification rates of molten area in additive manufacturing process, the microhardness values of the AMP following a fluctuated trend

Potentials of greenhouse gas emission reduction through energy efficiency improvement in Iran's petrochemical sector

Reducing energy consumption and increasing energy efficiency is a key strategy to mitigate greenhouse gases (GHGs) in the petrochemical sector, both because of the high share of energy-related emissions and because of the economic attractiveness in terms of return on investment. This paper aims to calculate the GHG mitigation potentials of the energy reduction projects in Iran's petrochemical sector. firstly, we estimated the trend of GHG emissions until 2035 using data collected from the petrochemical complexes in Iran. Then, by assessing the energy audits and other studies, we calculated the energy consumption reduction potentials as well as their costs and benefits for petrochemical complexes. Finally, we modelled the energy supply and demand of the petrochemical sector in LEAP software to evaluate the mitigation potentials of the energy reduction projects. The results show that a 6.7 % emission reduction in the existing petrochemical complexes can be achieved with a capital of about 160 million dollars. The net present value of the projects will be about 2 billion dollars, and the cost of carbon reduction will be −60.7 dollars per ton. The results of this research can be used for policymakers to plan the mitigation pathway of the sector since the revenues obtained from the energy conservation measures can be used to fund capital-intensive GHG mitigation projects