In this paper, the resonant nonlinear Schrödinger’s equation is studied with four forms of nonlinearity and time-dependent coefficients. The trial solution method is employed to solve the governing ...equations. Solitons and singular periodic solutions are obtained. The constraint conditions naturally emerge from the solution structure that are needed for its existence.
Abstract
The adulteration of milk fat in dairy products with less expensive non-milk-based fats, vegetable oils and animal fats are a common occurrence in the dairy industry. In this study, some ...imported and local yogurt which is consumed widely in Sulaymaniyah Governorate was investigated for detecting foreign fat. Fat percent in all brands were less than recorded on their labels, among Iranian brands, Manizan has the lowest fat content, the same result was obtained for local brand (Halla). The Reichert Meissl (RM) number was varying among the imported and local brands, and it was 12.32 and 3.85 for Mersin and Pegah brands, respectively. The fatty acid (FA) composition of milk fat in yogurt samples was studied using GC-MS, and it was showed many differences in fatty acid profiles of yoghurt samples, the highest level of butyric acid (C4:0) appears in Jwanro brand, it is nearly absent in Halla brand. The amount of mono-unsaturated fatty acids (MUFA) in all unbranded samples yogurt are higher than that appear in the milk fat.
During the coronavirus disease (COVID-19) pandemic, different technologies, including telehealth, are maximised to mitigate the risks and consequences of the disease. Telehealth has been widely ...utilised because of its usability and safety in providing healthcare services during the COVID-19 pandemic. However, a systematic literature review which provides extensive evidence on the impact of COVID-19 through telehealth and which covers multiple directions in a large-scale research remains lacking. This study aims to review telehealth literature comprehensively since the pandemic started. It also aims to map the research landscape into a coherent taxonomy and characterise this emerging field in terms of motivations, open challenges and recommendations. Articles related to telehealth during the COVID-19 pandemic were systematically searched in the WOS, IEEE, Science Direct, Springer and Scopus databases. The final set included (n = 86) articles discussing telehealth applications with respect to (i) control (n = 25), (ii) technology (n = 14) and (iii) medical procedure (n = 47). Since the beginning of the pandemic, telehealth has been presented in diverse cases. However, it still warrants further attention. Regardless of category, the articles focused on the challenges which hinder the maximisation of telehealth in such times and how to address them. With the rapid increase in the utilization of telehealth in different specialised hospitals and clinics, a potential framework which reflects the authors’ implications of the future application and opportunities of telehealth has been established. This article improves our understanding and reveals the full potential of telehealth during these difficult times and beyond.
•State-of-the-art Literature Categorization for Telehealth utilization during COVID-19.•Challenges, motivations and recommended solutions are identified for Telehealth during COVID-19.•Different Applications of Telehealth during the COVID-19 pandemic.
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•Identified a multi-criteria requirements for COVID-19 vaccine distribution.•Augmented a new dataset paths for COVID-19 vaccine recipients.•Proposed a dynamic decision matrix of ...COVID-19 vaccine distribution.•Developed a dynamic distribution mechanism for COVID-19 vaccine doses.
The vaccine distribution for the COVID-19 is a multicriteria decision-making (MCDM) problem based on three issues, namely, identification of different distribution criteria, importance criteria and data variation. Thus, the Pythagorean fuzzy decision by opinion score method (PFDOSM) for prioritising vaccine recipients is the correct approach because it utilises the most powerful MCDM ranking method. However, PFDOSM weighs the criteria values of each alternative implicitly, which is limited to explicitly weighting each criterion. In view of solving this theoretical issue, the fuzzy-weighted zero-inconsistency (FWZIC) can be used as a powerful weighting MCDM method to provide explicit weights for a criteria set with zero inconstancy. However, FWZIC is based on the triangular fuzzy number that is limited in solving the vagueness related to the aforementioned theoretical issues.
This research presents a novel homogeneous Pythagorean fuzzy framework for distributing the COVID-19 vaccine dose by integrating a new formulation of the PFWZIC and PFDOSM methods.
The methodology is divided into two phases. Firstly, an augmented dataset was generated that included 300 recipients based on five COVID-19 vaccine distribution criteria (i.e., vaccine recipient memberships, chronic disease conditions, age, geographic location severity and disabilities). Then, a decision matrix was constructed on the basis of an intersection of the ‘recipients list’ and ‘COVID-19 distribution criteria’. Then, the MCDM methods were integrated. An extended PFWZIC was developed, followed by the development of PFDOSM.
(1) PFWZIC effectively weighted the vaccine distribution criteria. (2) The PFDOSM-based group prioritisation was considered in the final distribution result. (3) The prioritisation ranks of the vaccine recipients were subject to a systematic ranking that is supported by high correlation results over nine scenarios of the changing criteria weights values.
The findings of this study are expected to ensuring equitable protection against COVID-19 and thus help accelerate vaccine progress worldwide.
The Agrobacterium-mediated floral dip protocol is the most extensively used transformation method for a model plant Arabidopsis thaliana. Several useful methods for Agrobacterium tumefaciens-mediated ...transformations of Arabidopsis are existing, but they are time consuming and with low transformation efficiency. Here, we developed a transgenic Arabidopsis lines TET12p::TET12-RFP in a short period of time and enhanced transformation efficiency by using a modified transformation method by applying drought stress after floral dip. In this protocol, Agrobacterium cells carrying TET12p::TET12-RFP recombinant vectors were resuspended in a solution of 5% sucrose, 0.05% (v/v) silwet L-77 to transform female gametes of developing Arabidopsis inflorescences. Treated Arabidopsis were then applied with different levels of drought stresses to stimulate plants for the utilization of maximum plant energy in seed maturation process. The applied stresses achieved the fast maturation of already treated inflorescences while stopped the growing of newly arising untreated inflorescence, thus decreased the chances of wrong collection of untransformed seeds. Consequently, the collected seeds were mostly transgenic with a transformation frequency of at least 10%, thus the screening for positive transformants selection was more advantageous on a selective medium as compared to a classical floral dip method. Within 2-3 months, two hundred of individual transgenic plants were produced from just 10 infiltrated plants. This study concludes that application of drought stresses in a specific stage of plant is a beneficial strategy for achieving the transgenic Arabidopsis in a short period of time with high transformation efficiency.
This paper addresses solitons in nonlinear directional couplers in non-Kerr law media, with spatio-temporal dispersion. Both twin-core couplers as well as multiple-core couplers are studied. The ...nonlinearities studied are Kerr law, power law, parabolic law, dual-power law and log law. Bright, dark and singular soliton solutions of the governing equation are studied.
Many studies have recently developed real-time sign language recognition system (SLRS)-based DataGlove wearable electronic devices for deaf and dumb to assort hand gestures as having an identical ...meaning in spoken language. An evaluation and benchmarking of these systems are important towards understanding the most suitable for fulfilling all essential requirements. This process falls under the multi-criteria decision-making (MCDM) problem because of different issues, namely, multi-evaluation criteria, criteria importance and data variation. Therefore, the MCDM solution is necessary to solve complex problems. The latest MCDM method called the fuzzy decision by the opinion score method (FDOSM) and its extension are considered the most powerful and suitable methods. However, these methods still suffer from vagueness issues. According to the advantage of Pythagorean fuzzy numbers in solving such issues, this study extended FDOSM into Pythagorean fuzzy set based on the Interactive hybrid arithmetic mean (IHAM) operator (called PFDOSM-IHAM) to evaluate and benchmark effectively the real-time SLRS. The methodology is presented on the basis of the two phases. Firstly, a decision matrix is proposed on the basis of ‘performance evaluation criteria’ and ‘SLRS set’. Secondly, the development of the PFDOSM-IHAM method is provided considering the following two stages: data transformation and processing. The following results are presented. (1) Variations are observed in the individual benchmarking results of real-time SLRS depending on each decision maker. (2) The group benchmarking results indicate that the 29th real-time SLRS was the best, whereas the worst real-time SLRS was attributed to SLRS (6th). (3) In evaluation, the statistical test indicates that the benchmarked systems from PFDOSM-IHAM are undergoing a systematic ranking. (4) Comparative analysis confirmed the efficacy of the proposed PFDOSM-IHAM against of the other well-known MCDM methods running on Pythagorean fuzzy numbers.
In prediabetes, blood glucose levels are higher than normal; however, they remain below the diabetes threshold. Studies conducted on biomarkers for this disease result in controlling diabetes ...mellitus (DM) or reducing the risk of developing complications. Lipid profile parameters are considered important predictors of DM. Therefore, this study was conducted on three groups of normoglycemic (n=30), pre-diabetics (n=125), and diabetics (n=30) to recognize the predictive role of lipid parameters in the transition from pre-diabetes to diabetes. In this experiment, in addition to total cholesterol and triglycerides, very-low-density lipoprotein (VLDL), low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglyceride/HDL ratio, and fasting triglyceride-fasting blood glucose (FBG) index were measured. Based on the results, medians for total cholesterol, LDL, HDL, LDL/HDL ratio, cholesterol/HDL ratio, and LDL/HDL ratio did not differ significantly across the groups of normoglycemia, prediabetes, and diabetes. For triglyceride, the medians were significantly higher in pre-diabetes and also diabetes, compared to normoglycemia (i.e., 127.9 and 129.1 vs. 94.5 mg/dL, respectively
<0.001). Moreover, the same results were observed in the case of VLDL (i.e., 25.6 and 30.9 vs. 18.9 mg/dL, respectively). The triglyceride/HDL ratio significantly increased pre-diabetics and diabetics, compared to normoglycemic (2.72 and 2.67 vs. 2.18, respectively). Moreover, the median of the triglyceride-FBG index significantly had an increase in pre-diabetics and diabetics, compared to normoglycemic (8.89 and 9.38 vs. 8.22, respectively). The importance of triglyceride, VLDL, triglyceride/HDL ratio, and triglyceride-FBG index in distinguishing between pre-diabetes and normoglycemia was verified by a receiver operating characteristic curve analysis of the results. Logistic regression analysis confirmed the risk effects of the four parameters on pre-diabetes and diabetes. Therefore, triglyceride, VLDL, triglyceride-FBG index, and triglyceride/HDL ratio are considered promising biomarkers used to predict pre-diabetes and DM in the general population.
Waste from crustaceans has adverse effects on the environment. In this respect, shrimp waste was valorized for producing chitosan nanoparticles as a source for eco-friendly nano-nitrogen fertilizer. ...The application of nano-nitrogen fertilizers is a valuable alternative approach in agriculture due to its potential for reducing the application of mineral nitrogen fertilizers and increasing yield quality and quantity, thereby helping to reduce the worldwide food shortage. Chitosan nanoparticles were foliar sprayed at three volumes (0, 7, and 14 L/ha) and compared with mineral nitrogen fertilizer (M-N) sprayed at three volumes (0, 120, and 240 kg N/ha) and their combination on two wheat cultivars (Misr-1 and Gemaiza-11) during two consecutive seasons (2019/2020 and 2020/2021) in order to evaluate the agronomic response. The synthesized chitosan nanoparticles displayed characteristic bands of both Nan-N and urea/chitosan from 500–4000 cm−1. They are stable and have a huge surface area of 73.21 m2 g−1. The results revealed significant differences among wheat cultivars, fertilization applications, individual or combined, and their interactions for yield-contributing traits. Foliar application of nano-nitrogen fertilizer at 14 L/ha combined with mineral fertilizer at 240 kg/ha significantly increased total chlorophyll content by 41 and 31% compared to control; concerning plant height, the two cultivars recorded the tallest plants (86.2 and 86.5 cm) compared to control. On the other hand, the heaviest 1000-grain weight (55.8 and 57.4 g) was recorded with treatment of 120 kg Mn-N and 14 L Nan-N/ha compared to the control (47.6 and 45.5 g). The Misr-1 cultivar achieved the highest values for grain yield and nitrogen (1.30 and 1.91 mg/L) and potassium (9.87 and 9.81 mg/L) in the two studied seasons when foliarly sprayed with the combination of 120 kg Mn-N/ha + 14 L Nan-N/ha compared to the Gemaiza-11 cultivar. It can be concluded that Misr-1 exhibited higher levels of total chlorophyll content, spike length, 100-grain weight, grain yield in kg/ha, and nitrogen and potassium. However, Gemaiza-11 displayed higher biomass and straw yield values, plant height, and sodium concentration values. It could be economically recommended to use the application of 120 kg Mn-N/ha + 14 L Nan-N/ha on the Misr-1 cultivar to achieve the highest crop yield.
•Intelligence-integrated concept is proposed to identify the most appropriate CP for corresponding prioritised patients with COVID-19.•ABO compatibility is assessed after classifying donors into the ...four blood types.•Contracted patient decision matrix in-between‘serological/protein biomarkers and the PaO2/FiO2’ and ‘patients list’.•Proposed a novel subjective and objective decision by opinion score method (SODOSM)’.•Contracted CP-decision matrix in-between serological/protein bio-markers criteria and ‘CPs tested list’.
People who have recently recovered from the threat of deteriorating coronavirus disease-2019 (COVID-19) have antibodies to the coronavirus circulating in their blood. Thus, the transfusion of these antibodies to deteriorating patients could theoretically help boost their immune system. Biologically, two challenges need to be surmounted to allow convalescent plasma (CP) transfusion to rescue the most severe COVID-19 patients. First, convalescent subjects must meet donor selection plasma criteria and comply with national health requirements and known standard routine procedures. Second, multi-criteria decision-making (MCDM) problems should be considered in the selection of the most suitable CP and the prioritisation of patients with COVID-19.
This paper presents a rescue framework for the transfusion of the best CP to the most critical patients with COVID-19 on the basis of biological requirements by using machine learning and novel MCDM methods.
The proposed framework is illustrated on the basis of two distinct and consecutive phases (i.e. testing and development). In testing, ABO compatibility is assessed after classifying donors into the four blood types, namely, A, B, AB and O, to indicate the suitability and safety of plasma for administration in order to refine the CP tested list repository. The development phase includes patient and donor sides. In the patient side, prioritisation is performed using a contracted patient decision matrix constructed between ‘serological/protein biomarkers and the ratio of the partial pressure of oxygen in arterial blood to fractional inspired oxygen criteria’ and ‘patient list based on novel MCDM method known as subjective and objective decision by opinion score method’. Then, the patients with the most urgent need are classified into the four blood types and matched with a tested CP list from the test phase in the donor side. Thereafter, the prioritisation of CP tested list is performed using the contracted CP decision matrix.
An intelligence-integrated concept is proposed to identify the most appropriate CP for corresponding prioritised patients with COVID-19 to help doctors hasten treatments.
The proposed framework implies the benefits of providing effective care and prevention of the extremely rapidly spreading COVID-19 from affecting patients and the medical sector.
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