Protein–Energy Malnutrition: A Risk Factor for Various Ailments

The wheel of industrialization that spun throughout the last century resulted in urbanization coupled with modifications in lifestyles and dietary habits. However, the communities living in developing economies are facing many problems related to their diet and health. Amongst, the prevalence of nutritional problems especially protein–energy malnutrition (PEM) and micronutrients deficiencies are the rising issues. Moreover, the immunity or susceptibility to infect-parasitic diseases is also directly linked with the nutritional status of the host. Likewise, disease-related malnutrition that includes an inflammatory component is commonly observed in clinical practice thus affecting the quality of life. The PEM is treatable but early detection is a key for its appropriate management. However, controlling the menace of PEM requires an aggressive partnership between the physician and the dietitian. This review mainly attempts to describe the pathophysiology, prevalence and consequences of PEM and aims to highlight the importance of this clinical syndrome and the recent growth in our understanding of the processes behind its development. Some management strategies/remedies to overcome PEM are also the limelight of the article. In the nutshell, early recognition, prompt management, and robust follow up are critical for best outcomes in preventing and treating PEM.     

Properties and curing behavior of reactive blended allyl novolak with bismaleimide using dicumyl peroxide as a novel curing agent

For reducing the cure temperature and improving the thermal stability and mechanical properties, a thermosetting resin system composed of novolak and bismaleimide (BMI) was developed by reactive blending and using dicumyl peroxide (DCP) as a novel curing agent. Novolak was allylated and reacted with BMI to produce bismaleimide allylated novolak (BAN), and the effect of DCP on flexural, impact and heat distortion temperature of cured resin were investigated. On the basis of improved mechanical and thermal properties at 0.5% DCP contents, the curing behavior of DCP/BAN resin system was evaluated by DSC analysis. Ene, Diels‐Alder, homo‐polymerization and alternating copolymerization which occurred in DCP/BAN resin system were further verified using FTIR at sequential cure conditions from 140 to 200°C. Kissinger and Ozawa‐Flynn‐wall methods were used to optimize the process and curing reactions of DCP/BAN resin system. The results showed that the addition of 0.5% DCP in BAN reduced the curing temperature and time of the modified resin. For evaluating process ability of the modified system, composite samples using polyvinyl acetyl fiber were molded and tested for flexural properties. The resulting samples showed better flexural properties when compared with the composite made with neat BAN. The modified 0.5% DCP/BAN resin system with good mechanical properties and manufacturability can be used for making bulk molding compounds and fiber reinforced composites required in various commercial and aerospace applications. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41829.     

IoMT-Based Smart Monitoring Hierarchical Fuzzy Inference System for Diagnosis of COVID-19

The prediction of human diseases, particularly COVID-19, is an extremely challenging task not only for medical experts but also for the technologists supporting them in diagnosis and treatment. To deal with the prediction and diagnosis of COVID-19, we propose an Internet of Medical Things-based Smart Monitoring Hierarchical Mamdani Fuzzy Inference System (IoMTSM-HMFIS). The proposed system determines the various factors like fever, cough, complete blood count, respiratory rate, Ct-chest, Erythrocyte sedimentation rate and C-reactive protein, family history, and antibody detection (lgG) that are directly involved in COVID-19. The expert system has two input variables in layer 1, and seven input variables in layer 2. In layer 1, the initial identification for COVID-19 is considered, whereas in layer 2, the different factors involved are studied. Finally, advanced lab tests are conducted to identify the actual current status of the disease. The major focus of this study is to build an IoMT-based smart monitoring system that can be used by anyone exposed to COVID-19; the system would evaluate the user’s health condition and inform them if they need consultation with a specialist for quarantining. MATLAB-2019a tool is used to conduct the simulation. The COVID-19 IoMTSM-HMFIS system has an overall accuracy of approximately 83%. Finally, to achieve improved performance, the analysis results of the system were shared with experts of the Lahore General Hospital, Lahore, Pakistan.     

Rotational Effect on the Propagation of Waves in a Magneto-Micropolar Thermoelastic Medium

The present paper aims to explore how the magnetic field, ramp parameter, and rotation affect a generalized micropolar thermoelastic medium that is standardized isotropic within the half-space. By employing normal mode analysis and Lame’s potential theory, the authors could express analytically the components of displacement, stress, couple stress, and temperature field in the physical domain. They calculated such manners of expression numerically and plotted the matching graphs to highlight and make comparisons with theoretical findings. The highlights of the paper cover the impacts of various parameters on the rotating micropolar thermoelastic half-space. Nevertheless, the non-dimensional temperature is not affected by the rotation and the magnetic field. Specific attention is paid to studying the impact of the magnetic field, rotation, and ramp parameter of the distribution of temperature, displacement, stress, and couple stress. The study highlighted the significant impact of the rotation, magnetic field, and ramp parameter on the micropolar thermoelastic medium. In conclusion, graphical presentations were provided to evaluate the impacts of different parameters on the propagation of plane waves in thermoelastic media of different nature. The study may help the designers and engineers develop a structural control system in several applied fields.     

An effective method for classification with missing values

Classification is one of the most important tasks in machine learning with a huge number of real-life applications. In many practical classification problems, the available information for making object classification is partial or incomplete because some attribute values can be missing due to various reasons. These missing values can significantly affect the efficacy of the classification model. So it is crucial to develop effective techniques to impute these missing values. A number of methods have been introduced for solving classification problem with missing values. However they have various problems. So, we introduce an effective method for imputing missing values using the correlation among the attributes. Other methods which consider correlation for imputing missing values works better either for categorical or numeric data, or designed for a particular application only. Moreover they will not work if all the records have at least one missing attribute. Our method, Model based Missing value Imputation using Correlation (MMIC), can effectively impute both categorical and numeric data. It uses an effective model based technique for filling the missing values attribute wise and reusing then effectively using the model. Extensive performance analyzes show that our proposed approach achieves high performance in imputing missing values and thus increases the efficacy of the classifier. The experimental results also show that our method outperforms various existing methods for handling missing data in classification.     

Preparation and characterization of PPRC/EPDM thermoplastic vulcanizates: A comparative study

Thermoplastic vulcanizates (TPVs) of polypropylene random copolymer (PPRC) with ethylene–propylene diene monomer rubber (EPDM) were prepared through in situ and ex situ compatibilization techniques. Silanized silica as nanofiller was incorporated in the ex situ compatibilized TPVs. Mechanical properties were measured for different formulated TPVs with increasing loading of EPDM from 10 to 30 phr. A comparative data is generated to discuss the effect of two compatibilization techniques and addition of silica filler in the TPVs. The degradation studies were also carried out to check the stability of the blends under harsh ultraviolet environment. The in situ compatibilized TPVs provided better overall mechanical properties. Moreover, it is worth mentioning that the properties of ex situ compatiblized TPVs were enhanced by incorporation of silanized silica filler. Silanized silica filler helped in reducing the die swell significantly. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 46726.     

A comprehensive survey of network coding in vehicular ad-hoc networks

Network coding is a data processing technique in which the flow of digital data is optimized in a network by transmitting a composite of two or more messages to make the network more robust. Network coding has been used in traditional and emerging wireless networks to overcome the communications issues of these networks. It also plays an important role in the area of vehicular ad-hoc networks (VANETs) to meet the challenges like high mobility, rapidly changing topology, and intermittent connectivity. VANETs consist of network of vehicles in which they communicate with each other to ensure road safety, free flow of traffic, and ease of journey for the passengers. It is now considered to be the most valuable concept for improving efficiency and safety of future transportation. However, this field has a lot of challenges to deal with. This paper presents a comprehensive survey of network coding schemes in VANETs. We have classified different applications like content distribution, multimedia streaming, cooperative downloading, data dissemination, and summarized other key areas of VANETs in which network coding schemes are implemented. This research work will provide a clear understanding to the readers about how network coding is implemented in these schemes in VANETs to improve performance, reduce delay, and make the network more efficient.     

Green Adeptness in the Synthesis and Stabilization of Copper Nanoparticles: Catalytic,Antibacterial, Cytotoxicity,and Antioxidant Activities

Copper nanoparticles (CuNPs) are of great interest due to their extraordinary properties such as high surface-to-volume ratio, high yield strength, ductility, hardness, flexibility, and rigidity. CuNPs show catalytic, antibacterial, antioxidant, and antifungal activities along with cytotoxicity and anticancer properties in many different applications. Many physical and chemical methods have been used to synthesize nanoparticles including laser ablation, microwave-assisted process, sol-gel, co-precipitation, pulsed wire discharge, vacuum vapor deposition, high-energy irradiation, lithography, mechanical milling, photochemical reduction, electrochemistry, electrospray synthesis, hydrothermal reaction, microemulsion, and chemical reduction. Phytosynthesis of nanoparticles has been suggested as a valuable alternative to physical and chemical methods due to low cytotoxicity, economic prospects, environment-friendly, enhanced biocompatibility, and high antioxidant and antimicrobial activities. The review explains characterization techniques, their main role, limitations, and sensitivity used in the preparation of CuNPs. An overview of techniques used in the synthesis of CuNPs, synthesis procedure, reaction parameters which affect the properties of synthesized CuNPs, and a screening analysis which is used to identify phytochemicals in different plants is presented from the recent published literature which has been reviewed and summarized. Hypothetical mechanisms of reduction of the copper ion by quercetin, stabilization of copper nanoparticles by santin, antimicrobial activity, and reduction of 4-nitrophenol with diagrammatic illustrations are given. The main purpose of this review was to summarize the data of plants used for the synthesis of CuNPs and open a new pathway for researchers to investigate those plants which have not been used in the past.

Open image in new window

Graphical abstract Proposed Mechanism for Antibacterial activity of copper nanoparticles.

     

Quantum secret sharing protocol through noisy channel with application in visual cryptography

This study presents a quantum secret sharing (QSS) protocol designed using Grover's search algorithm in a noisy environment. The proposed protocol utilizes Grover's three-particle quantum state. The proposed scheme is divided into secret information sharing and eavesdropping checking. The dealer prepares an encoded state by encoding the classical information as a marked state and shares the states' qubits between three participants. Using the amplitude-damping noise and the phase-damping noise as conventional noisy channels, it can be demonstrated that secret information can be conveyed between participants with some information lost. The security analysis shows the scheme is stringent against malicious participants or eavesdroppers. The simulation analysis is done on the cloud platform IBM-QE thereby showing the practical feasibility of the scheme. Finally, an application of the proposed scheme is demonstrated in visual cryptography using the GNEQR representation of images.