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The purpose of this paper is to evaluate the photochromic performance of photochromic compounds in polymer matrices.

The poly(methyl methacrylate) (PMMA) and epoxy resin doped with photochromic spirobenzopyran were prepared and the effects of ultraviolet (UV) irradiation were studied using spectrophotometer. The reversible reaction was effected using white light. Photochemical fatigue resistance of these films was also studied.

Irradiation of colourless 1′,3′,3′‐trimethyl‐6‐nitrospiro[2H‐1‐benzopyran‐2,2′‐indoline] spiropyran (SP) doped in PMMA and epoxy resin with UV light (366 nm) results in the formation of an intense purple‐red coloured zwitterionic photomerocyanine (PMC). The reverse reaction was photochemically induced by irradiation with white light. Photocolouration of SP doped in PMMA follows a first‐order rate equation (k=0.0011 s⁻¹), while that doped in epoxy resin deviates from linearity. It was found that photobleaching follows a first‐order equation in both matrices. The photobleaching rate constant of PMC in both matrices is the same and equals 0.0043 s⁻¹. Spirobenzopyran doped in PMMA shows better fatigue resistance than that doped in epoxy resin.

The PMMA and epoxy resin polymers doped with photochromic spirobenzopyran described in the present paper were prepared and studied. The principle of study established can be applied to any type of polymer or to any type of photochromic compounds.

The photochromic materials developed can be used for different applications, such as coatings and holography.

The method developed may be used to enhance the performance of photochromic materials.

Gamma-aminobutyric acid (GABA) is a four-carbon and nonprotein amino acid, made by various microorganisms, especially lactic acid bacteria (LAB) and probiotics. GABA has various physiological roles, for instance, insomnia, depression, hypotensive activity as well as diuretic effects. The production of GABA-based foods is a favorable result from GABA’s biological and functional properties. The purpose of this study is to investigate different methods of improving GABA production in probiotics and LAB to select the superlative method and bacterial strain.

In this review paper, all articles from five electronic databases containing Google Scholar, Web of Science, PubMed, Scopus and Science Direct were considered from 2000 to January 11, 2023, with keywords “Optimization” OR “Enhance” OR “Increase” AND “Gamma-aminobutyric acid” OR “GABA” AND “Probiotics” OR “Lactic acid bacteria” and selected according to the purpose of the study.

It seems that among all the investigated methods, an effective fermentation procedure with optimal conditions including fermentation medium, 5 L; glutamic acid, 295 g/L; incubation temperature, 32°C; inoculum, 10% (v/v); and agitation, 100 rpm, after 48 h of fermentation led to producing 205,800 mg/L of GABA from the effective bacterial strain Lactobacillus brevis NCL912.

With a simple but optimized fermentation, L. brevis NCL912 can be used for the efficient GABA production in the pharmacy and food factories.

To gain a better and more comprehensive understanding, this study aims to investigate the literature to explore the two popular diets’ health benefits and concerns. Google Scholar and PubMed were used to search for available and relevant nutrition and health articles that pertain to the benefits and concerns of plantogenic and ketogenic diets. Search terms like low carbohydrate, diet, ketogenic, vegetarian and chronic diseases were used. Information was obtained from review articles and original research articles and checked for accuracy. Ketogenic diets have been used for a long time for convulsion in children and now reappeared for weight loss purposes.

Ketogenic and plantogenic (plant-based) diets have been adopted today by many professionals and the public.

Ketogenic diets have been used for a long time for convulsion in children and now reappeared for weight loss purposes. Plantogenic diets also have been practiced for many years for religious, health and environmental reasons. Compared to plantogenic diets, ketogenic diets lack long-term evidence of its potential benefits and harm.

Maybe Lacto-ovo vegetarian and pesco-vegetarian (eat fish but not meats) diets are OK. However, for strict plantogenic diets (total plantogenic/vegan diet), the risk of mineral or vitamin deficiency is present (Melina et al., 2016). Of particular concern is dietary vitamin B12, which is obtained mostly from animal sources (Melina et al., 2016). A long-term deficiency of vitamin B12 can lead to macrocytic anemia and cause neuro and psychological effects (Obeid et al., 2019). Also, omega-3 fatty acids may be deficient in such a diet and probably need to be supplemented on those who follow the total plantogenic diet (Melina et al., 2016). Other deficiencies of concern would be zinc, iron, calcium, vitamin D and iodine (Melina et al., 2016). Another disadvantage is that many junk foods could be easily classified within the plantogenic diet, such as sugar, cakes, French fries, white bread and rice, sugar-sweetened beverages and sweets in general. These items are related to higher weight gain and, consequently, to a higher incidence of diabetes and other chronic diseases (Schulze et al., 2004; Malik et al., 2006; Fung et al., 2009).

Plantogenic diets were concluded to have sustainable health benefits for humans and the environment over ketogenic diets, which could be used but under professional follow-up only.

Blood lipid and lipoprotein abnormalities are common among patients with diabetes. The study aimed to assess dietary fat intake and its association with blood lipids among patients with Type 2 diabetes mellitus (T2DM) considering sex differences.

A cross-sectional observational study was conducted with patients (207 males and 197 females) with T2DM. The daily food intake and its contents of fat and fat types were assessed through face-to-face interview. Anthropometric measurements, glycated hemoglobin (HbA1c), triglyceride, total cholesterol (TC), high-density lipoprotein (HDL) cholesterol and low-density lipoprotein (LDL) cholesterol were initially recorded.

The results revealed that TC, LDL and HDL cholesterol levels were significantly higher in females than in males. However, the TC: HDL ratio was significantly higher in males than in females. The results also showed that the daily intake of saturated fatty acid (SFA) slightly exceeded the daily recommended allowance. However, the monounsaturated fatty acid + polyunsaturated fatty acid/SFA (MUFA + PUFA/SFA) ratio was within the recommended ratio. In addition, this study found that the main sources of SFA and cholesterol intake were milk and milk products. A significant association between high fat intake and HbA1c levels was observed (r = 0.234, p < 0.001).

As it is a cross-sectional observational study, this study has the natural limitation where it can only demonstrate an association.

The types of dietary fat intake may contribute to blood lipid abnormalities and differences effects may exist among male and female. Studies on the effect of daily fat intake and its types on blood lipids in patients with diabetes, in particular Saudi patients with diabetes are limited. This study focused on the amount and type of the consumed fat among male and female Saudi patients with T2DM and studied the relationship between the type of consumed fat and blood lipid profiles.

This paper aims to identify, prioritise and explore the relationships between the various barriers that are hindering the machine learning (ML) adaptation for analysing accident data information in the Indian petroleum industry.

The preferred reporting items for systematic reviews and meta-analysis (PRISMA) is initially used to identify key barriers as reported in extant literature. The decision-making trial and evaluation laboratory (DEMATEL) technique is then used to discover the interrelationships between the barriers, which are then prioritised, based on three criteria (time, cost and relative importance) using complex proportional assessment (COPRAS) and multi-objective optimisation method by ratio analysis (MOORA). The Delphi method is used to obtain and analyse data from 10 petroleum experts who work at various petroleum facilities in India.

The findings provide practical insights for management and accident data analysts to use ML techniques when analysing large amounts of data. The analysis of barriers will help organisations focus resources on the most significant obstacles to overcome barriers to adopt ML as the primary tool for accident data analysis, which can save time, money and enable the exploration of valuable insights from the data.

This is the first study to use a hybrid three-phase methodology and consult with domain experts in the petroleum industry to rank and analyse the relationship between these barriers.

For Internet celebrities, self-disclosure (SD) is a crucial step in building relationships with their followers who perceive this communication as para-social interaction (PSI), which facilitates socialization among followers. Normative commitment (NC) is critical for creating bonds among community members that are strengthened through socialization. However, research on the predictive relationships among SD, PSI and NC has been insufficient. This paper aims to investigate the effects of two facets of Internet celebrity SDs (i.e. private life and opinion) and two facets of PSI (i.e. companionship and following) on NC. The mediating role of PSI on the effects of SD on NC was also analyzed.

People who follow at least one Internet celebrity on a social networking site were recruited to participate in this study, and 494 valid questionnaires were collected for examination. The collected data were analyzed using structural equation modeling (SEM).

The results revealed that both private-life and opinion SDs have positive effects on companionship and following PSI, which consequently influence NC. A mediation test revealed that companionship and following PSI mediate the effects of private-life and opinion SD on NC. This study's findings also revealed that NC is influenced more by following PSI than it is by companionship PSI. Furthermore, opinion SD was determined to be the more influential factor in following PSI, whereas private-life SD was the more influential factor in companionship PSI.

This paper is useful for understanding the influence mechanism of the SD of Internet celebrities on PSI and NC.

This study aims to examine the effects of industrial production (IP), inflation and investment on suicide mortality in Turkey as a developing country over the 1988–2018 period.

Fourier cointegration test and dynamic ordinary least square regression were used in this study.

IP and investment have a statistically significant and negative impact on suicide mortality, whereas inflation has a statistically significant and positive effect on suicide mortality.

The results of this study have important implications for policymakers and potentially the creation and implementation of suicide prevention policies. Not only do investment promotion, IP and disinflation policies in developing countries have a significant effect on economic growth but they also have a substantial impact on mental health.

Although previous studies have investigated the impact of economic growth and unemployment on suicide deaths in Turkey, no research has probed the effect of economic factors, except for unemployment and gross domestic product, on suicide. Thus, given the hidden unemployment and informal sector in developing economies, it is vital to examine the impact of IP, inflation and investment on mental health.

Generation Z will be the leading consumer group in the future. Using convenience stores, the study provides an in-depth analysis on Gen Z’s current experience and future expectations from retail stores. The study further highlights the differences between Gen Z’s perception of convenience stores across three different regions – the USA, South Korea and Japan.

This study conducted a series of in-depth, semi-structured interviews with 36 Gen Z participants from the USA (12), South Korea (11) and Japan (13). All interviews were first coded based on a preselected list of themes and were further coded with new themes that emerged from exploratory coding.

Each regional cohort varied in terms of how they experienced and what they expected from convenience stores. US participants showed negative or utilitarian attitudes toward convenience stores, whereas South Korean participants had a positive, personal attachment to them. In comparison, Japanese participants had a relatively neutral attitude. However, all three groups showed a common preference for smart technology and health concerns surrounding convenience store foods.

Convenience store chains should consider the cultural nuances when designing future services. The chains should further strive to remove the health concerns about the foods provided at the stores and design smart technologies that enhance user experience.

The present study broadens the knowledge in this budding consumer segment where current research is limited. It further sheds light on the variance among Gen Zers across different cultural contexts.

The intelligent agent object (IAO) system is a multi‐paradigm development environment which can be used to create intelligent agent systems for manufacturing or other domains. The IAO system was developed from the rule‐based object (RBO) system which is a programming environment integrating both the rule‐based and object‐oriented paradigms. Propagation‐oriented programming, access‐oriented programming and group‐oriented programming are among the extensions included in the IAO system. Its most unusual contribution is the propagation‐oriented programming paradigm which is not found in most systems. A key application is the messenger inferencing structure which is a user‐extendable framework supporting multiple knowledge representation, meta‐inference control, and distributed inference. This allows the IAO system to go beyond predicate logic based production rule programming. New developments are also introduced for access‐oriented programming. The IAO system can be used to develop integrated manufacturing systems such as the prototype automated guided vehicle planning and control system, which is briefly described.

The purpose of this study is to explore the latest approaches in integrating artificial intelligence and analytics (AIA) in energy smart grid projects. Empirical results are synthesized to highlight their relevance from a technology and project management standpoint, identifying several lessons learned that can be used for planning highly integrated and automated smart grid projects.

A systematic literature review leads to selecting 108 research articles dealing with smart grids and AIA applications. Keywords are based on the following research questions: What is the growth trend in Smart Grid projects using intelligent systems and data analytics? What business value is offered when AI-based methods are applied? How do applications of intelligent systems combine with data analytics? What lessons can be learned for Smart Grid and AIA projects?

The 108 selected articles are classified according to the following four research issues in smart grids project management: AIA integrated applications; AI-focused technologies; analytics-focused technologies; architecture and design methods. A broad set of smart grid functionality is reviewed, seeking to find commonality among several applications, including as follows: dynamic energy management; automation of extract, transform and load for Supervisory Control And Data Acquisition (SCADA) systems data; multi-level representations of data; the relationship between the standard three-phase transforms and modern data analytics; real-time or short-time voltage stability assessment; smart city architecture; home energy management system; building energy consumption; automated fault and disturbance analysis; and power quality control.

Given the diversity of issues reviewed, a more capability-focused research agenda is needed to further synthesize empirical findings for AI-based smart grids. Research may converge toward more focus on business rules systems, that may best support smart grid design, proof development, governance and effectiveness. These AIA technologies must be further integrated with smart grid project management methodologies and enable a greater diversity of renewable and non-renewable production sources.