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Image enhancement is a vital process that serves as a tool for improving the quality of a lot of real-life applications. Fractional calculus can be utilized in enhancing images using fractional order kernels, adding more controllability to the system, due to the flexible choice of the fractional order parameter, which adds extra degrees of freedom. The proposed system merges two fractional order kernels which helps in image enhancement techniques, and the contribution of this work is based on the study of how to optimize this process. The optimization of the two fractional kernels was done using the neural network optimization algorithm (NNA) to utilize the best order for the two kernels. In this paper, three fractional kernels are studied to highlight the performance of image enhancement using fractional kernels against different metrics. Furthermore, three different combinations of two kernels are combined and studied to enhance the metrics score by utilizing two different fractional orders for each kernel. Various optimization algorithms are used to obtain the optimum fractional order for both single and combined kernels. Using the constrained NNA, the evaluation metrics of the image enhancement show a 33% increase in measure of enhancement metric (EME), 21% increase in contrast, and 4% increase in average gradient compared to the best-achieved metrics by the literature while keeping the similarity metric above 0.75. [ABSTRACT FROM AUTHOR]

Smoking has been recognized by the World Health Organization (WHO) as the fifth highest threat to humanity. Smoking, a leading disease promoter, is a major risk factor for non-communicable diseases (NCDs) such as cancer, cardiovascular disease, diabetes, and chronic respiratory diseases. NCDs account for 63% of all deaths worldwide. Passive smoking is also a health risk. Globally, more than a third of all people are regularly exposed to harmful smoke. Air pollution is a common global problem in which pollutants emitted into the atmosphere undergo a series of physical or chemical reactions to produce various oxidation products, which are often referred to as secondary pollutants. Secondary pollutants include ozone (O3), sulfur trioxide (SO3), nitrogen dioxide (NO2), and respirable particulate matter (PM). It is worth mentioning that third-hand smoke (THS), formed by the reaction of nicotine with second-hand smoke (SHS) caused by indoor O3 or nitrous acid (HONO), is a major indoor secondary pollutant that cannot be ignored. As a form of indoor air pollution that is relatively difficult to avoid, THS exists in any corner of the environment where smokers live. In this paper, we summarize the important research progress on the main components, detection, and toxicity of THS and look forward to future research directions. Scientific understanding of THS and its hazards will facilitate smoking bans in indoor and public places and raise public concern for how to prevent and remove THS. [ABSTRACT FROM AUTHOR]

An in silico design of a new metallo‐organic electride, containing metal‐nitrogen bonds, namely, Li4EPc, with high non‐linear optical (NLO) properties (βtotal = 6.382 × 104 au) is presented. Density functional theory (DFT)‐based computation has revealed the thermodynamic stability of Li42+ cluster encapsulated in EPc host moiety where EPc is an extended phthalocyanine system. Natural bond orbital (NBO) analysis is performed to study the bonding nature of the aforementioned species. We have also performed atoms in molecules (AIM) analysis to confirm the presence of an isolated electron at the interstitial tetrahedral hollow formed by three‐dimensional Li42+ cluster attached with EPc ligand. Linear and NLO properties of the designed electride have been analyzed by polarizability (α¯) and first hyperpolarizability calculations (βtotal). Frequency dependent first hyperpolarizability, second harmonic generation (SHG), electro‐optic Pockel's effect (EOPE) have also been computed. Furthermore, we report the hydrogen adsorption potential of each Li atom in Li4EPc system. The result shows that two H2 molecules can be adsorbed per lithium atom leading to a total of eight H2 molecules adsorbed by Li42+ cluster through physisorption process. This work provides a new insight into designing a stable metallo‐organic electride (Li4EPc) with high NLO response which also can be used as an efficient hydrogen storage material. [ABSTRACT FROM AUTHOR]

Tobacco smoke is an environmental pollutant that can cause follicle destruction and oocyte dysfunction. Thirdhand smoke (THS) is residual tobacco smoke existing in the environment long after cigarettes have been extinguished, which can react with other environmental compounds to produce secondary pollutants. THS contains a variety of toxic and harmful chemicals, such as nicotine and 1‐(N‐methyl‐N‐nitrosamino)‐1‐(3‐pyridinyl)‐4‐butanal (NNA), a logical biomarker of THS exposure. The health hazards of THS exposure and its components have been researched in recent years. In this review, we have summarized research progress on the effects of THS exposure on organs in mice and humans especially on the reproductive system. This review may help evaluate the health risks of THS, in particular reproduction and offspring health. We hope this review will guide public health education on the dangers of THS exposure and promotion of healthy living habits. Living in a harmful environment is closely related to decreased fertility rate. The health hazards of thirdhand smoke (THS) exposure, a new way of passive smoking, have been researched in a few studies. This article mainly reviews the effects of THS exposure and its components on reproductive system, which provides a certain theoretical basis for the research of human reproductive health. Further research is necessary to enhance our knowledge of the potential molecular mechanisms of THS. [ABSTRACT FROM AUTHOR]

Smoking has been recognized by the World Health Organization (WHO) as the fifth highest threat to humanity. Smoking, a leading disease promoter, is a major risk factor for non-communicable diseases (NCDs) such as cancer, cardiovascular disease, diabetes, and chronic respiratory diseases. NCDs account for 63% of all deaths worldwide. Passive smoking is also a health risk. Globally, more than a third of all people are regularly exposed to harmful smoke. Air pollution is a common global problem in which pollutants emitted into the atmosphere undergo a series of physical or chemical reactions to produce various oxidation products, which are often referred to as secondary pollutants. Secondary pollutants include ozone (O3), sulfur trioxide (SO3), nitrogen dioxide (NO2), and respirable particulate matter (PM). It is worth mentioning that third-hand smoke (THS), formed by the reaction of nicotine with second-hand smoke (SHS) caused by indoor O3 or nitrous acid (HONO), is a major indoor secondary pollutant that cannot be ignored. As a form of indoor air pollution that is relatively difficult to avoid, THS exists in any corner of the environment where smokers live. In this paper, we summarize the important research progress on the main components, detection, and toxicity of THS and look forward to future research directions. Scientific understanding of THS and its hazards will facilitate smoking bans in indoor and public places and raise public concern for how to prevent and remove THS.

With the development of science and technology, the application of the Internet of Things (IOT) is becoming more and more widespread. Applying BP neural network algorithms (NNA) to the IOT system will help improve the performance of the IOT system. The research purpose of this paper is to solve the problems of long-parameter measurement cycle and untimely feedback of the existing IOT online measurement system. In this paper, a multi-parameter (MP) IOT online measurement system based on BP NNA is designed, and a simulation test experiment is performed. The MP online measurement IOT system based on the BP NNA completes the parameter collection, analysis, and display through the perception layer, network transmission layer, and application layer. The core is that the system application layer adds the BP NNA to optimize real-time acquisition parameters, processing to reduce parameter measurement time. It can be known from algorithm simulation experiments that the online measurement system based on the BP NNA proposed in this paper uses the BP NNA to predict the absolute error value of the final moisture content and the measured moisture content within 0.3, and the absolute error of the moisture content value in actual production. It is acceptable in the range of 0.5, which speeds up data collection time. This system has a very good effect on improving the feedback adjustment speed of the manufacturing process system. [ABSTRACT FROM AUTHOR]

The advancement in communication and sensor technologies makes it possible to develop low-cost circuitry networks to sense and transmit the state of surroundings called Wireless Sensor Networks (WSNs). However, due to their severe computation and energy constraints, WSN's have unique design challenges. Energy-efficient cluster-based routing and security are still receiving immense interest from the researchers today. The most appropriate approach to prolonging WSN's performance parameters is clustering. Effective CH selection algorithm and optimized routing protocol are important for designing efficient solutions for WSNs to overcome the limitations in clustering algorithms such as reduced cluster head (CH) lifetime. In this paper, a Neural Network optimization algorithm using a fuzzy type-2 based clustering approach is proposed to extend the lifetime of the network. The proposed approach has been tested in terms of the number of alive nodes per round, network lifetime, and stability period of the network. Simulation outcomes show that the proposed protocol outperforms competitive clustering algorithms in terms of energy consumption, stability duration and lifetime of the network. [ABSTRACT FROM AUTHOR]