**4.2 Results**

242 Trends in Electromagnetism – From Fundamentals to Applications

V.grad .

ρ

*T P T aT t C*

Governing equations for AMRR system have been developed throughout the years with the objective of to analytically or numerically describe the thermal behaviour at specific time and for a given set of boundary conditions. They consist of a system of two equations, one for the fluid and the other for the solid matrix. These equations are derived from the energy balance expression for each phase. Since they are coupled they must be solved simultaneously (Bouchekara, 2008). The model of an AMRR cycle has been developed in (Bouchekara, 2008). Fig. 16 illustrates the concept of an AMRR regenerator modelled using

The system of equations given by the energy balance (explained above) for both the magnetocaloric material and the fluid by neglecting the axial conduction (this approximation can be justified for different conditions: low thermal conductivity, very thin

( ) ( )

τ

(25)

for the time. Thus, the derivatives with

(26)

( )

To solve this system we use the finite difference method. We use a grid of elements that

respect to the time are calculated using forward formulas, and those with respect to the space are calculated using backward formulas. This gives a centered discretization scheme.

1, , , 1 (,)

12 3

( ) ( ) ( )

=+ +

1, (,) (,)

*i j i j i j*

*m mm m f*

*T AT AT* + −

= +

1 2 *i j i j i j i j*

*T AT AT AT*

*f f f f f fm*

. ( ) *f f ff f m f*

∂ ∂ + =− ∂ ∂

*T T m C T d t hS T T t x*

*m m m f m*

*T m C hS T T t*

∂ = −

∂

( )

+

range from 0 to L for the space and from 0 to

Thus the system (25) becomes:

∂ + = +Δ

*p*

∂ (24)

is defined as the thermal diffusivity of the fluid, thus :

if *p a C* = λ ρ

**4.1 Application to AMRR**

one dimensional (1D) approximation.

Fig. 16. Conceptual drawing of a 1D AMRR model.

plates, etc.) can be summarized by the following system of equations:

We will now apply the model developed earlier to a regenerator in the form of plates, as shown in Fig. 17(a). The equivalent cell of the whole regenerator is given in Fig. 17 (b). This cell has the same parameters as the regenerator except the width that is *eq p l Nl* = (where *eq l* represents the equivalent width, *Np* represents the number of plates and *l* is the width of one plate).

Fig. 17. (a) A regenerator in the form of plates, (b) Equivalent cell (plate + fluid).

The model parameters (for this simulation case) are shown in Table 2. The magnetocaloric material used is gadolinium, the coolant used is water and the magnetic field is generated by permanent magnets B = 1 T.

Table 2. The parameters used in the simulation.

Fig. 18 (a) shows the temperature evolution of both sides (hot and cold) of the material versus time. After a transient phase, the two curves reach their steady state. In addition, we note that the final value is greater than the initial MCE. From this curve we can extract the evolution of the temperature at the end of each cycle (Fig. 18 (b)). The small delay between the two curves of this figure is due to programming constraints, i.e. the magnetization phase has been introduced (programmed) before the demagnetization phase.

Magnetic Refrigeration Technology at Room Temperature 245

(a) Geometry of the first structure modeled by Flux 3D.

outside the cylinder). The opposite way works also; i.e. the material remains fixed and the magnet is connected to the linear motor. In this case, the magnetic behavior is the same as in

Y0 (mm)

Y0 (mm)

Fig. 19. Geometry and magnetic characteristics of the Structure A.

Fig. 20. Cylindre d'Halbach made of eight segments.

(b) Induction (T)

(c) Force (N)

the first case.

The projection of the geometry of the structure on the plane (oxy).

Y0=-50(mm)

Y0=0(mm)

(d) The distribution of the magnetic induction.

Fig. 18. Temperature profiles given by the AMRR numerical model.


*5.6. The Perspectives of Health Professionals and Patients on Racism in Healthcare: A Qualitative Systematic Review*

A qualitative systematic review of 23 articles, with a total of 1006 participants across the articles, looked at the perspectives of professionals and patients on racism. The authors found that healthcare providers perpetuated racism due to their unconscious (and sometimes conscious) biases toward patients. For example, providers professed less empathy toward racialized minority patients because they were less able to connect with patients of a different race than themselves, yet they often shifted blame for health disparities on minority patients behaviours as opposed to racism. The authors also found two major themes, generated through interviews with racialized minorities. These were: (1) alienation of minorities due to racial supremacism and lack of empathy, resulting in inadequate medical treatment; and (2) labelling of minority patients who were stereotyped as belonging to a lower socio-economic class and having negative behaviors. The findings of this study support the notion that experiences of racism in healthcare interactions contributes to inadequate medical service and treatment for racialized minorities, which can then lead to poor health outcomes [31].

#### *5.7.  The authors focused on this group because they report more incidents of racism than other racialized minorities. Pieterse et al. (2012) systematically reviewed 66 studies with total sample size of 18,140 across studies. Using a random effects model, the authors found a positive association between perceived racism and psychological distress (r = 0.20). As exposure to and appraised stressfulness of racist events increased, so did the likelihood of reporting mental distress. Moreover, effects for psychiatric symptoms and general distress were stronger than effects for life satisfaction and self-esteem. Thus, these

findings support the notion that racism ought to be viewed within the context of trauma in the field of mental health [32].


**1. Introduction**

Honey is an economically important food product worldwide. It is prized by many cultures for its pleasing aroma and flavor, and high nutritional value and potential healing properties. Given its many valuable nutritional and culinary properties, the price of natural honey is much higher than that of syrup, such as refined corn syrup (CS), rice syrup (RS), beet syrup (BS) and maltose syrup (MS). In the honey market, it is common for some merchants to attempt to take economic advantage of the differences in price by diluting honey with these less expensive sugar syrups [1,2]. Honey adulteration not only affects the quality of the honey but also harms the bee-keeping industry by negatively impacting sales and product reputation [3]. Therefore, there is an urgent need to develop effective methods for the detection of sugar syrup-adulterated honey in order to reassure consumers and ensure fair competition.

Several review papers have summarized recent studies dealing with honey adulteration, and a number of different analytical techniques are currently employed for the detection of syrup in adulterated honey [3–6]. These methodologies include common analytical techniques such as thin-layer chromatography (TLC) [7], stable carbon isotopic ratio analysis (SCIRA) [8], gas chromatography (GC) [9], high-performance anion exchange chromatography (HPAEC) [10], high-performance liquid chromatography (HPLC) [11,12] and high-performance liquid chromatography/quadrupole time of flight mass spectrometry (HPLC-Q-TOF) [3], among other emerging technologies [13–15]. Although these techniques offer detailed and accurate results, the processes are time-consuming and expensive and can only be performed in well-equipped laboratories by highly trained analysts.

**Citation:** Yan, S.; Sun, M.; Wang, X.; Shan, J.; Xue, X. A Novel, Rapid Screening Technique for Sugar Syrup Adulteration in Honey Using Fluorescence Spectroscopy. *Foods* **2022**, *11*, 2316. https://doi.org/ 10.3390/foods11152316

Academic Editor: M. Carmen Seijo

Received: 1 July 2022 Accepted: 27 July 2022 Published: 3 August 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

Some advanced spectroscopic techniques have also been used for detecting honey adulteration, such as infrared spectroscopy (IR) [16,17], Raman spectroscopy (RP) [18], inductively coupled plasma optical emission spectroscopy (ICP-OES) [19] and nuclear magnetic resonance (NMR) [4,20,21], which are rapid and relatively easy but must be used in conjunction with multivariate analysis. However, the shortcoming of these methods is that they require a high level of expertise to set the chemometric models necessary to distinguish pure honey from its adulterated counterparts. Although adulteration is a global issue for the honey market, the levels and types of adulteration vary between regions. In developed nations and affluent cities, the quality of honey is generally good, and adulteration is less pervasive, since honey quality can be rigorously monitored by well-equipped testing agencies and inspectors with analytical expertise. However, in less developed regions, the regulatory infrastructure often lacks advanced analytical equipment and experts, resulting in widespread honey adulteration and often large quantities of glucose–fructose syrup [3]. There is therefore a critical need for the honey market to develop a cost-effective, simple, rapid and easy-to-use screening method for monitoring the adulteration of honey.

Fluorescence spectroscopy, a common analytical technique with relatively low-cost instrumentation that is ubiquitous in biological, food science and toxicology labs, offers several advantages for the characterization of chemical constituents, such as high sensitivity and specificity [22]. Several early studies successfully used fluorescence spectroscopy to distinguish the geographical and botanical origins of honey samples through front-face and synchronous fluorescence spectroscopy [23–26]. Fluorescence spectroscopy, in combination with chemometrics, has also been used to discriminate between true and artificial honey samples produced by feeding bee colonies with sucrose [22,27]. However, few studies have been reported on the detection of multiple adulterant sugar syrups in honey using fluorescence spectroscopy.

In the process of finding the fluorescence emission spectra of honey and different sugar syrups, we found a significant difference in the intensity of the frequency doubled peak (FDP) between honey and sugar syrup samples. The second-order diffraction of the monochromator produces the FDP. When the monochromator is set to transmit 740 nm, a small fraction of 370 nm excitation light will also be transmitted through the emission monochromator. Due to the chemical differences between syrup and honey [28], the FDP intensity at 740 nm can be influenced by different honey and sugar samples and may serve as a potential indicator to distinguish honey from sugar syrups.

We envisioned that, based on the differences in fluorescence spectra between honey and syrup, a rapid, low-cost and easy-to-use syrup-adulterated honey screening approach could be developed. In this study, we report the first application, to our knowledge, of fluorescence spectroscopy in combination with FDP intensity data for rapid screening of sugar syrup adulterants in commercial and spiked honey samples. By using the apex wavelength of characterized emission spectra in conjunction with FDP intensities as profiles, we show that natural honey from different botanical origins can be readily distinguished from honey adulterated with a range of different syrups without the need for multivariate analysis. Our findings represent a critical and clear step toward the application of common fluorescence spectroscopy in the screening for honey adulteration.