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Many foods naturally contain dietary Cr, but lost during processing and cooking. Type 2 diabetes mellitus (T2DM) has been associated with poor glycemic control and low Cr status. The objectives of the current study were to evaluate the dietary Cr intake and its relationship with diabetes risk factors in moderately obese subjects with T2DM.

Thirty‐six subjects (age: 26–65 years) were recruited through local advertisements. Subjects were taking stable doses of oral antidiabetic medication(s) excluding concomitant insulin. Subjects had HbA1c ≥7 per cent, persistent impaired glucose control (2 hour glucose >200 mg dL⁻¹) and at least a one‐year history of T2DM. Demographic characteristics, blood pressure, body mass index (BMI), family and medical history were recorded. Three‐day dietary intakes were collected and evaluated for Cr and nutrient content using Nutritionist V software. Plasma glucose, circulating insulin and lipid profile were analyzed. Homeostatic model assessment insulin resistance (IR), beta cell function (BCF) and derived ratios were calculated. Morning void urinary chromium levels were also measured.

It was observed that mean dietary Cr intake of adults (30 mcg) was below the suggested recommended daily intake (RDI) of 120 mcg day⁻¹. These estimates correspond to approximately 16.4 μg Cr per 1000 Kcals. A significant correlation was observed between dietary Cr and fasting insulin (p<0.05), total‐C (p<0.05), LDL‐C (p<0.01), triglycerides (p<0.05), BCF (p<0.05), TG/HDL‐C ratio (p<0.01), HOMA BCF (p<0.05) and with atherogenic index in plasma (p<0.05).

In this study, the consumption of chromium is less than the RDI. Overall the results suggest that the US diets are inadequate in the essential metal chromium. Further studies are required to explore the relationship of Cr absorption with dietary Cr intake and risk factors in T2DM.

Development in microcomputer systems has led to their use for a three‐dimensional magnetic field calculation. It caused a great progress in numerical methods used for a magnetic field analysis in electric machines and devices. Determination of the calculations quality may be achieved by comparing with the measurements. For this purpose real objects or simplified models can be used.

The impedance boundary condition is widely used in order to reduce a multiple region electromagnetic field problem to a magnetic field problem analyzed in a nonconducting region only. It is obvious that the solution to the latter problem is much easier to obtain than those for conducting regions. There are several versions of the impedance boundary condition formulation which depend mainly on the choice of a field state variable and the solution technique applied.

NOT for a long time have books and libraries featured in the correspondence columns of The Times and other newspapers as regularly as they have in 1960. Earlier in the year Sir Alan Herbert's lending rights' scheme had a good run, and we have clearly not yet heard the last of it. Indeed, a Private Member's bill on the subject is to have its second reading in Parliament on December 9th. More recently, the Herbert proposals have had a by‐product in the shape of bound paperbacks, and a correspondence ensued which culminated in Sir Allen Lane's fifth‐of‐November firework banning hard‐covered Penguins for library use.

This research paper adopts the fundamental tenets of advanced technologies in industry 4.0 to monitor the structural health of concrete beam members using cost-effective non-destructive technologies. In so doing, the work illustrates how a coalescence of low-cost digital technologies can seamlessly integrate to solve practical construction problems.

A mixed philosophies epistemological design is adopted to implement the empirical quantitative analysis of “real-time” data collected via sensor-based technologies streamed through a Raspberry Pi and uploaded onto a cloud-based system. Data was analysed using a hybrid approach that combined both vibration-characteristic-based method and linear variable differential transducers (LVDT).

The research utilises a novel digital research approach for accurately detecting and recording the localisation of structural cracks in concrete beams. This non-destructive low-cost approach was shown to perform with a high degree of accuracy and precision, as verified by the LVDT measurements. This research is testament to the fact that as technological advancements progress at an exponential rate, the cost of implementation continues to reduce to produce higher-accuracy “mass-market” solutions for industry practitioners.

Accurate structural health monitoring of concrete structures necessitates expensive equipment, complex signal processing and skilled operator. The concrete industry is in dire need of a simple but reliable technique that can reduce the testing time, cost and complexity of maintenance of structures. This was the first experiment of its kind that seeks to develop an unconventional approach to solve the maintenance problem associated with concrete structures. This study merges industry 4.0 digital technologies with a novel low-cost and automated hybrid analysis for real-time structural health monitoring of concrete beams by fusing several multidisciplinary approaches into one integral technological configuration.

Rural communities around the world are searching for solutions to upkeep, restore and improve local services that are deteriorating. They are exploring the potential of a digital transition along with the opportunities and threats created by new patterns of mobility and closer links with urban areas. The expansion of information and communication technologies (ICT)-enhanced applications enables rural communities to improve their quality of life. The concept of smart village is primarily about how rural communities make the best use of both ICT and social innovation by responding to the ongoing and emerging challenges. Therefore, the aim of this paper is to investigate strategies for adoption of smart villages along with the challenges faced.

A quantitative research methodology was adopted in this research. A web-based questionnaire survey was conducted to collect data. In total, 110 fully completed and useable questionnaires were received. Statistical analyses were undertaken using the Statistical Package for Social Sciences (SPSS).

The results indicate that lack of budget, lack of clear strategies for development of sustainable “smart villages”, lack of collaboration between stakeholders and lack of knowledge related to “smart villages” are the most debated challenges for implementing smart village agenda. Whereas smart energy, smart healthcare, smart transport, smart education and smart water are the top five most important smart village strategies.

Despite the novel insights provided by this study, it has some limitations. Given that the research reported in this paper is based on literature review and small-scale survey, results presented are only tentative and not generalisable. The findings of this paper are limited to the UK context only. Although generalisability outside of this context may be limited, the authors infer that the results are relevant to other comparable developed countries.

Research on smart village development is rare. This paper presents a theoretical basis on the concept of smart villages. It adds to the rich insight that goes into the understanding and awareness of the current smart village strategies along with the key challenges organisations encounter when implementing smart village initiatives. This research has implications towards informing professionals and policymakers on key lessons learnt during the implementation of smart village strategies. Also, this paper contributes to the academic debate on smart village development and provides useful recommendations to both policymakers and practitioners.

The purpose of this paper is to propose that the grey tolerance rough set (GTRS) and construct the GTRS-based classifiers.

The authors use grey relational analysis to implement a relationship-based similarity measure for tolerance rough sets.

The proposed classification method has been tested on several real-world data sets. Its classification performance is comparable to that of other rough-set-based methods.

The authors design a variant of a similarity measure which can be used to estimate the relationship between any two patterns, such that the closer the relationship, the greater the similarity will be.

It is challenging to derive an appropriate tolerance relation for tolerance rough set-based classifiers (TRSCs). The traditional tolerance rough set employs a simple distance function to determine the tolerance relation. However, such a simple function does not take into account criterion weights and the interaction among criteria. Further, the traditional tolerance relation ignores interdependencies concerning direct and indirect influences among patterns. This study aimed to incorporate interaction and interdependencies into the tolerance relation to develop non-additive grey TRSCs (NG-TRSCs).

For pattern classification, this study applied non-additive grey relational analysis (GRA) and the decision-making trial and evaluation laboratory (DEMATEL) technique to solve problems arising from interaction and interdependencies, respectively.

The classification accuracy rates derived from the proposed NG-TRSC were compared to those of other TRSCs with distinctive features. The results showed that the proposed classifier was superior to the other TRSCs considered.

In addition to pattern classification, the proposed non-additive grey DEMATEL can further benefit the applications for managerial decision-making because it simplifies the operations for decision-makers and enhances the applicability of DEMATEL.

This paper contributes to the field by proposing the non-additive grey tolerance rough set (NG-TRS) for pattern classification. The proposed NG-TRSC can be constructed by integrating the non-additive GRA with DEMATEL by using a genetic algorithm to determine the relevant parameters.

Meteorin like-peptide (Metrnl) modulates energy hemostasis and relieves inflammation and oxidative stress. This study aims to investigate the relationship between Metrnl levels and inflammatory cytokines, oxidative stress biomarkers and body composition parameters in obese type 2 diabetic patients.

This analytical cross-sectional study was carried out between August 2020 and March 2021on 93 people (n = 32 obese type 2 diabetic patients, n = 31 healthy obese, n = 30 healthy normal weight). Serum Metrnl levels were measured by enzyme-linked immunosorbent assay. Serum levels of interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), high-sensitivity C-reactive protein (hs-CRP), malondialdehyde and total antioxidant capacity were measured using standard methods. Body composition was assessed by bioelectrical impedance analysis. p-Value less than 0.05 was considered significant.

Serum Metrnl levels were lower in obese diabetic patients than in healthy normal-weight subjects (82.5 [72.4–94.5] ng/mL compared to 154 [129–189] ng/mL). The difference in Metrnl levels between the two groups was significant (p < 0.001). The difference in Metrnl levels between the two groups was significant. Moreover, a significant correlation between Metrnl level and both TNF-a and hs-CRP was detected (p = 0.006 and p < 0.001, respectively) and the correlation between Metrnl and IL-6 was borderline (p = 0.051). A negative correlation was revealed between Metrnl level and anthropometric measurements and body composition (p < 0.05) with the exception of fat-free mass and skeletal muscle mass.

To discover sufficient evidence for the therapeutic function of Metrnl and its use as a prognostic biomarker in the management of type 2 diabetes mellitus, future clinical studies are needed to highlight other factors influencing Metrnl serum levels.