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The purpose of this paper is to investigate the dynamics of waste production in the product structure of a wire and cable manufacturing company that deals with a high-volume waste and proposes strategies that reduce product costs.

The methodology for this research is descriptive and expressive modeling in a way that theories of research have been extracted from literature and field studies have been done based on the company specialists’ views. The system dynamics has been used to analyze and model waste in a wire and cable firm.

Applying SD approach in the paper not only helps to identify the structure of producing the waste, which is complicated and dynamic, but also proposes ways to reduce them and illustrate the applied results. The second outcome shows that in the waste management there should be a digression in a managerial view to the systematic thought. In the other word as in the system dynamic approach, the expansion of the model boundary is one of the objectives to find appropriate solution. The behavior model showed that in the waste management the most effective way to reduce the waste is to buy qualified raw material which is out of the firm.

This paper not only shows that the system dynamic approach is appropriate for the waste management problems which are complicated and dynamic but also proved that in the waste management system the solutions are not always near or within the firm. They should be identified by a systematic approach.

The present article's primary purpose is the topic modeling of the global coronavirus publications in the last 50 years.

The present study is applied research that has been conducted using text mining. The statistical population is the coronavirus publications that have been collected from the Web of Science Core Collection (1970–2020). The main keywords were extracted from the Medical Subject Heading browser to design the search strategy. Latent Dirichlet allocation and Python programming language were applied to analyze the data and implement the text mining algorithms of topic modeling.

The findings indicated that the SARS, science, protein, MERS, veterinary, cell, human, RNA, medicine and virology are the most important keywords in the global coronavirus publications. Also, eight important topics were identified in the global coronavirus publications by implementing the topic modeling algorithm. The highest number of publications were respectively on the following topics: “structure and proteomics,” “Cell signaling and immune response,” “clinical presentation and detection,” “Gene sequence and genomics,” “Diagnosis tests,” “vaccine and immune response and outbreak,” “Epidemiology and Transmission” and “gastrointestinal tissue.”

The originality of this article can be considered in three ways. First, text mining and Latent Dirichlet allocation were applied to analyzing coronavirus literature for the first time. Second, coronavirus is mentioned as a hot topic of research. Finally, in addition to the retrospective approaches to 50 years of data collection and analysis, the results can be exploited with prospective approaches to strategic planning and macro-policymaking.

This study explores whether metacognitive strategy training can influence the lexical knowledge of L2 learners of the present study, and what they think about the use of metacognitive strategies in language learning classes. To do so, a 50-item multiple-choice vocabulary test, developed by the researchers based upon Nation’s (1990) levels of language proficiency, was employed to measure the learners’ vocabulary knowledge progress during the period of instruction. The instruction received by the experimental group was based on the Cognitive Academic Language Learning Approach (CALLA) Model, developed and validated by Chamot and O’Malley (1994). The findings revealed that the experimental group outperformed the control group in their endeavors for comprehending and producing vocabulary. This may be attributed to the fact that after this intervention, participants have developed their metacognitive awareness and their thinking skills. The study concludes with pedagogical implications and highlights avenues for future research.

ﺗ مّ د ﻣ ﺞ ا ﺳ ﺗ ر ا ﺗ ﯾ ﺟ ﯾ ﺎ ت ﻣ ﺎ و ر ا ء ا ﻟ ﻣ ﻌ ر ﻓ ﯾ ﺔ (MS) ، ا ﻟ ﺗ ﻲ ﺗ ﻌ ﺗ ﺑ ر ا ﻟ ﻔ ﺋ ﺔ ا ﻟ ﻔ ر ﻋ ﯾ ﺔ ا ﻟ ر ﺋ ﯾ ﺳ ﯾ ﺔ ﻻ ﺳ ﺗ ر ا ﺗ ﯾ ﺟ ﯾ ﺎ ت ﺗ ﻌ ﻠّ م ا ﻟ ﻠّ ﻐ ﺔ ﻓ ﻲ ﻣ ﻧ ﺎ ھ ﺞ ﺗ ﻌ ﻠّ م ا ﻟ ﻠّ ﻐ ﺔ ا ﻷ ﺟ ﻧ ﺑ ﯾ ﺔ ﻟ ﺗ ﺳ ﮭ ﯾ ل ا ﻟ ﺗ ﻔ ﻛ ﯾ ر ا ﻟ ﻌ ﺎ ﻟ ﻲ و ا ﻟ ﺗ ﺧ ط ﯾ ط ا ﻟ ذ ا ﺗ ﻲ و ا ﻟ ﺗ ﻌ ﻠّ م ا ﻟ ﻣ ﺳ ﺗ ﻘِّل و ا ﻟ ﺗ ﻌ ﻠ م ا ﻷ ﻓ ﺿ ل ﻓ ﻲ ﻧ ﮭ ﺎ ﯾ ﺔ ا ﻟ ﻣ ط ﺎ ف . و ﻓ ﻘًﺎ ﻟ ذ ﻟ ك ، ﺗ ﻌ دّ ھ ذ ه ا ﻟ دّر ا ﺳ ﺔ ﻣ ﺣ ﺎ و ﻟ ﺔً ﻟ ﻺ ﺟ ﺎ ﺑ ﺔ ﻋ ﻣ ﺎ إ ذ ا ﻛ ﺎ ن ا ﻟ ﺗ د ر ﯾ ب ﻋ ﻠ ﻰ ا ﺳ ﺗ ر ا ﺗ ﯾ ﺟ ﯾ ﺔ ﻣ ﺎ و ر ا ء ا ﻟ ﻣ ﻌ ر ﻓ ﻲ ﯾ ﻣ ﻛ ن أ ن ﯾ ؤ ﺛّ ر ﻋ ﻠ ﻰ ا ﻟ ﻣ ﻌ ر ﻓ ﺔ ا ﻟ ﻣُﻌ ﺟ ﻣ ﯾ ﺔ ﻟ ﻠ ﻣ ﺗ ﻌ ﻠ ﻣ ﯾ ن و ﻣ ﺎ ذ ا ﯾ ﻔ ﻛّر ﻓ ﯾ ﮫ ا ﻟ ﻣ ﺗ ﻌ ﻠّ ﻣ و ن ﺣ ول ﺗ د ر ﯾ س ا ﺳ ﺗ ر ا ﺗ ﯾ ﺟ ﯾ ﺎ ت ﻣ ﺎ و ر ا ء ا ﻟ ﻣ ﻌ ر ﻓ ﯾ ﺔ . و ﻟ ﻠ ﻘ ﯾ ﺎ م ﺑ ذ ﻟ ك ، ﺗ مّ ا ﺳ ﺗ ﺧ د ا م ا ﺧ ﺗ ﺑ ﺎ ر ﻣ ﻛ و ن ﻣ ن 50 ﻋ ﻧ ﺻ ر اً ﻣ ﺗ ﻌ د د ا ﻻ ﺧ ﺗ ﯾ ﺎ ر ا ت ا ﻟّ ذ ي ﺗ مّ ﺗ ط و ﯾ ر ه ﺑ و ا ﺳ ط ﺔ ا ﻟ ﺑ ﺎ ﺣ ﺛ ﯾ ن ا ﺳ ﺗ ﻧ ﺎ دًا إ ﻟ ﻰ ﻣ ﺳ ﺗ و ﯾ ﺎ ت ا ﻟ ﻛ ﻔ ﺎ ء ة ا ﻟ ﻠ ﻐ و ﯾ ﺔ ﻟ د ى ا ﻟ ﺷ ﻌ ب (Nation) (1990 م ( ، ﻟ ﻘ ﯾ ﺎ س ﺗ ط وّ ر ﻣ ﻌ ر ﻓ ﺔ ا ﻟ ﻣ ﻔ ر د ا ت أ ﺛ ﻧ ﺎ ء ﻓ ﺗ ر ة اﻟ ﺗد ر ﯾ س . ا ﺳ ﺗ ﻧ د ت ا ﻟ ﺗ ﻌ ﻠ ﯾ ﻣ ﺎ ت ا ﻟ ﺗ ﻲ ﺗ ﻠ ﻘّﺗ ﮭ ﺎ ا ﻟ ﻣ ﺟ ﻣ و ﻋ ﺔ ا ﻟ ﺗ ﺟ ر ﯾ ﺑ ﯾ ﺔ إ ﻟ ﻰ ﻧ ﻣ و ذ ج ﻣ ﻧ ﮭ ﺞ ا ﻟ ﺗ ﻌ ﻠ م ا ﻟ ﻣ ﻌ ر ﻓ ﻲ ا ﻷ ﻛ ﺎ د ﯾ ﻣ ﻲ ) CALLA ( ا ﻟ ذّي أ ﻋ دّه و و ا ﻓ ق ﻋﻠ ﯾ ﮫ ﺷﺎ ﻣو ت وأ وﻣﺎﻟ ﻲ ) 1994 ( . ﻛ ﺷ ﻔ ت ا ﻟ ﻧ ﺗ ﺎ ﺋ ﺞ أ نّ ا ﻟ ﻣ ﺟ ﻣ و ﻋ ﺔ ا ﻟ ﺗ ﺟ ر ﯾ ﺑ ﯾ ﺔ ﺗ ﻔ و ﻗ ت ﻋ ﻠ ﻰ ا ﻟ ﻣ ﺟ ﻣ و ﻋ ﺔ ا ﻟ ﺗ ﺣ ﻛ ﻣ ﯾ ﺔ ﺑ ﺎ ﻟ ﻧّﺳ ﺑ ﺔ ﻟ ﻔ ﮭ م و إ ﻧ ﺗ ﺎ ج ا ﻟ ﻣ ﻔ ر د ا ت . ﻣن اﻟ ﻣﻣﮑن أ ن ﯾﻌود ذ ﻟ ك إ ﻟ ﻰ ﺣ ﻘ ﯾ ﻘ ﺔ أ نّ ا ﻟ ﻣ ﺗ ﻌ ﻠ ﻣ ﯾ ن ﺑ ﻌ د ھ ذ ا ا ﻟ ﻌ ﻼ ج ﯾ ﻣ ﻛ ﻧ ﮭ م ا ﻟ ﺗ ﻔ ﻛ ﯾ ر أ ﻛ ﺛ ر و ر ا ء ا ﻟ ﻣ ﻌ ر ﻓ ﯾ ﺔ و ﺗ ط و ﯾ ر ﺗ ﻘ دّم ﺗ ﻔ ﻛ ﯾ ر ھ م . ﺗ ﺧ ﺗ ﺗ م ا ﻟ دّر ا ﺳ ﺔ ﺑ ذ ﮐ ر ﺑ ﻌ ض ا ﻵ ﻓ ﺎ ق ا ﻟ ﺗ ر ﺑ و ﯾّﺔ و ﺗ ﺳ ﻠ ﯾ ط ا ﻟ ﺿّو ء ﻋ ﻠ ﻰ ﺑ ﻌ ض ا ﻟ ﺳّﺑ ل ﻟ ﻠ ﺑ ﺣ ث ﻓ ﻲ ا ﻟ ﻣ ﺳ ﺗ ﻘ ﺑ ل .

This research aimed to visualize and analyze the co-word network and thematic clusters of the intellectual structure in the field of linked data during 1900–2021.

This applied research employed a descriptive and analytical method, scientometric indicators, co-word techniques, and social network analysis. VOSviewer, SPSS, Python programming, and UCINet software were used for data analysis and network structure visualization.

The top ranks of the Web of Science (WOS) subject categorization belonged to various fields of computer science. Besides, the USA was the most prolific country. The keyword ontology had the highest frequency of co-occurrence. Ontology and semantic were the most frequent co-word pairs. In terms of the network structure, nine major topic clusters were identified based on co-occurrence, and 29 thematic clusters were identified based on hierarchical clustering. Comparisons between the two clustering techniques indicated that three clusters, namely semantic bioinformatics, knowledge representation, and semantic tools were in common. The most mature and mainstream thematic clusters were natural language processing techniques to boost modeling and visualization, context-aware knowledge discovery, probabilistic latent semantic analysis (PLSA), semantic tools, latent semantic indexing, web ontology language (OWL) syntax, and ontology-based deep learning.

This study adopted various techniques such as co-word analysis, social network analysis network structure visualization, and hierarchical clustering to represent a suitable, visual, methodical, and comprehensive perspective into linked data.

Lot-sizing is among the most important problems in the production and inventory management field. The purpose of this paper is to move one step forward in the direction of the real environment of the dynamic, multi-period, lot-sizing problem. For this purpose, a two-warehouse inventory system, imperfect quality and supplier capacity are simultaneously taken into consideration, where the aim is minimization of the system costs.

The problem is formulated in a novel continuous nonlinear programming model. Because of the high complexity of the lot-sizing model, invasive weed optimization (IWO), as a population-based metaheuristic algorithm, is proposed to solve the problem. The designed IWO benefits from an innovative encoding–decoding procedure and a heuristic operator for dispersing seeds. Moreover, sequential unconstrained minimization technique (SUMT) is used to improve the efficiency of the IWO.

Taking into consideration a two-warehouse system along with the imperfect quality items leads to model nonlinearity. Using the proposed hybrid IWO and SUMT (SUIWO) for solving small-sized instances shows that SUIWO can provide satisfactory solutions within a reasonable computational time. In comparison between SUIWO and a parameter-tuned genetic algorithm (GA), it is found that when the size of the problem increases, the superiority of SUIWO to GA to find desirable solutions becomes more tangible.

Developing a continuous nonlinear model for the concerned lot-sizing problem and designing a hybrid IWO and SUMT based on a heuristic encoding–decoding procedure are two main originalities of the present study.

The purpose of this paper is to examine the level of cardinal welfare based on Sen’s index using both Pareto and non-Pareto states besides evaluating the effective factors on the welfare changes according to a fuzzy least-squares regression model.

The social welfare functions express the optimal social allocations in the public economics. Therefore, they can be applied as a tool to represent the difference of utility allocations among consumers. There are various criteria on the literature pertaining to the social welfare functions such as those of Dasgupta et al. (1970), Sheshinski (1972), Sen (1974), Yitzhaki (1979), Shorrocks (1983), Kakwani (1984), Dagum (1990, 1993), Mukhopadhaya (2003), and Mukhopadhaya and Rao (2001). The Sen’s welfare function because of strong theoretical basis and enjoying the welfare axioms is more celebrated among others so that it is a function of individual utilities resulting from the individual’s social positions.

The findings indicate that the welfare level has increased by about 4.8 percent during the period 2002-2007; by nearly 3.1 percent during 1997-2001 and mature to 2.7 percent from 1992 to 1996 such that the period 1997-2007 has had the highest level of social welfare improvement in Iran. The results obtained from the fuzzy regression show that the unemployment rate, inflation rate and Gini coefficient variables have an adverse relation with the cardinal welfare in both Pareto and non-Pareto cases, while the literacy rate and government expenditures have a positive relation with the welfare index. The findings also imply that there is a positive relationship between economic growth and welfare level in Iran.

I verify that this manuscript is an original study.

This paper aims to update with information about edible coating on minimally processed and fresh fruits, focussing on the composition, active ingredients, antimicrobial concentration and their effect on ripening rate, phytonutrients retention and shelf-life of fruits. In future, the data will be helpful for the processors to select the best coating material and its effective concentration for different fresh and minimally processed fruits.

Major scientific information was collected from Scopus, Web of Science, Mendeley and Google Scholar. Several key words such as postharvest, edible coating, phytonutrients, shelf-life enhancement, bioactive compounds, minimally processed fruits and antimicrobial compounds were used to find the data. Relevant information was collected by using 90 recent research and review articles.

The main findings of this comprehensive review are to improve the quality of fruits, to meet the next-generation food security needs. However, in the process of achieving the goal of improving quality of food produce, embrace of synthetic, non-biodegradable packaging materials have increased, creating serious pollution problem. Amidst several alternatives for replacement of synthetic packaging, the option of biodegradable films and coatings showed promising results.

The paper represents recent information about the edible coating used for the enhancement of shelf-life of fresh and minimally processed fruits.