**4.1 Dynamic reservation versus static reservation**

There are several reasons for designing multi-tier cellular networks. One is to provide services for mobile terminals with different mobility and traffic patterns. The required performance measures can be met if the traffic and mobility patterns can be classified into more homogeneous parts and treated separately. Consider a system where there are two mobility classes. If the cell radii are optimized for low-mobility terminals, then the high-mobility terminals will have to make a lot of handovers during a communication session. On the other hand, if the optimization is made regarding the handover performance of high-mobility terminals, then the traffic load in each cell may exceed acceptable limits.

In multi-tier cellular networks, different layers offer the designer the opportunity of class based optimization. In case of a two-tier network we consider three or seven micro-cells overlaid by one large macro-cell offered calls from two mobility classes (Fig. 8). High-mobility 10 Will-be-set-by-IN-TECH

In queuing priority schemes, new calls and handover calls are all accepted whenever there are idle channels for that type of calls. When no idle channels are accessible, calls may be queued or blocked (i.e cleared from the system). Queueing priority schemes can be divided into three groups: new call queuing schemes (Chang et al., 1999), handover call queuing schemes (Yoon & Kwan, 1993); (Tian & Ji, 2001); (Agrawal et al., 1996), and all calls queuing schemes (Yoon &

Computational analysis has shown that waiting positions do not change the advantage of dynamic reservation strategy. Fig. 7 displays two pairs of curves: one pair is the same as in Fig. 6, the second one relates to a case with three waiting positions. Of course, the revenue is

Fig. 7. Waiting positions do not change the advantage of dynamic reservation strategy. One pair of curves is the same as in Figure 6, the other pair relates to the case with three waiting

There are several reasons for designing multi-tier cellular networks. One is to provide services for mobile terminals with different mobility and traffic patterns. The required performance measures can be met if the traffic and mobility patterns can be classified into more homogeneous parts and treated separately. Consider a system where there are two mobility classes. If the cell radii are optimized for low-mobility terminals, then the high-mobility terminals will have to make a lot of handovers during a communication session. On the other hand, if the optimization is made regarding the handover performance of high-mobility terminals, then the traffic load in each cell may exceed acceptable limits.

In multi-tier cellular networks, different layers offer the designer the opportunity of class based optimization. In case of a two-tier network we consider three or seven micro-cells overlaid by one large macro-cell offered calls from two mobility classes (Fig. 8). High-mobility

growing, but the preference of dynamic reservation keeps the place.

**3.3 On queueing effect**

positions.

**4. Two-tier network**

**4.1 Dynamic reservation versus static reservation**

Kwan, 1993); (Chang et al., 1999).

Fig. 8. A macro-cell covering (a) three and (b) seven micro-cells.

calls of intensity *A* are served by macro-cell only. Low-mobility calls of intensity *B* are served by the micro-cells as first choice and, if the reservation strategy admits it, by the macro-cell as second choice. Arriving calls are served as follows. The mobility class of the call is identified. High-mobility calls of intensity *A* are served by macro-cell only. Low-mobility calls of intensity *B* are served by the appropriate micro-cell as first choice, and if reservation strategy allows it by macro-cell as second choice. In both cases, our optimization criteria is the same: to maximize the revenue when each served A-call costs *K* units and each served B-call costs one unit (*K >* 1). When calls reach the macro-cell level, they are no longer

Fig. 9. A two-tier cellular network call flow model.

differentiated according to their mobility classes. Therefore, the calls of the high mobility class terminals and the overflowed handover calls from micro-cells are treated identically. New calls from micro-cells may not use the guard (reserved) channels upon their arrival. If no non-guard channel is available, then new calls are blocked. High mobility calls are blocked if all macro-cell channels are busy. Fig. 9 shows schematically how calls are served and what order is followed when serving them. As above in the case of single-tier network we compare two reservation strategies:

a) Dynamic reservation: The cutoff priority scheme is to reserve a number of channel for high-mobility calls in the macro-cell. Whenever a channel is released, it is returned to the common pool of channels.

........................................................................ ...................... .. ..... ..... ......... .....

New calls Low Mobility

to 0.025%.

Micro-cells

........................................................................................................... ...................... .. ........ .. ... .... .....

Overflow

........................................................................................................................................................................................................................................................

New calls High Mobility

Fig. 11. An illustration of channel rearrangement.

........................................................................ ...................... .. ....... .. ........ ... ....

New calls Low Mobility

........................................................................................................... ...................... .. .. ... .. ...... ... ...

Overflow

Call Admission Control in Cellular Networks 123

Fig. 12. Dependence of revenue on channel rearrangement from macro-cell to micro-cell.

of arrangement could be implemented by modern DSP techniques.

channels in the second tier. In Fig. 13.b some kind of a homogeneous single tier network is depicted: each call has access to 9 channels equally distributed between streams. Such kind

Fig. 14 depicts the loss probability curves for these two schemes. Case (a) relates to pure loss system, case (b) relates to scheme with one waiting positions per stream. What is surprising? In case (a), beginning with a loss probability as low as 0.56% (less than 1%), it is advantageous to use the equally distributed scheme. Therefore, the traditional two-tier network could be recommended here at a very low call rates. Table 1 contains more detailed data on loss probability. When a single waiting position is added, the advantage of the equally distributed scheme increases even more and the cross point of curves occurs at the loss probability equal

........................................................................................................... .. ... ....... .... ... ... . ..........................

Take-Back

N1 N2

........................................................................ ...................... .. ..........

L1 L2 L3

... ...... ...

........................................................................................................... ...................... .. ...... ...... ... ... ......

N

........................................................................................................... .... ... .... ... ...... ... .......................... ........................................................................................................................................................................................................................................................

New calls High Mobility

...................... .. ..... ...... ... ... .....

...................... .. .. ... .. ...... ... ....

Macro-cell

b) Static reservation: Divide all macro-cell channels allocated to a cell into two groups: one for the common use by all calls and the other for high-mobility calls only (the rigid division-based CAC scheme).

Fig. 10. Dependence of the revenue on the reserved number of channels for two-tier networks: (a) Three micro-cells and one macro-cell, (b) Seven micro-cells and one macro-cell.

Numerical results for two two-tier network examples are obtained. They are not qualitatively different from the results of the one-tier model discussed above. Fig. 10.a (three micro-cells and one macro-cell) and Fig. 10.b (seven micro-cells and one macro-cell) show that the dynamic reservation strategy gives the higher maximum revenue in both cases if the reserved number of channels *R* is properly chosen. The parameters are as follows: *A* = high-mobility call flow, *B* = low-mobility call flow, *N*1 = number of micro-cell channels for each cell, *N*2 = number of micro-cell channels.

**Conclusion:** In case of two-tier network, the results of numerical analysis confirm that the optimal strategy is dynamic reservation.


**1. Introduction**

Crop pollution by fungal toxins is a global issue that causes massive annual economic losses. Large territorial areas of China are located in temperate and subtropical zones, o ffering favorable climatic conditions for the growth and reproduction of toxic fungi [1]. Zearalenone (ZEN) of *Fusarium* [2] and ochratoxin A (OTA) of *Aspergillus* and *Penicillium* [3] exhibited the most extensive distribution and strongest toxicity among the more than 400 toxic fungi discovered thus far [4]. Numerous studies have reported on the reproduction, genetic, and immune toxicities of ZEN, which causes nausea, vomiting, and diarrhea in humans and animals [5]. Animal toxicological experiments and clinical studies have demonstrated the strong nephrotoxicity, immunotoxicity, and carcinogenicity of OTA [6,7].

Ozone, as a strong oxidant, can attack the double bond in organic compounds through molecules and free radicals in a liquid system [8–10]. In addition, ozone exhibits acceptable permeability and can

automatically decompose into oxygen without generating toxic residues [11]. Hence, ozonation is a fungal toxin degradation technology with promising potential, and has been the focus of numerous studies in recent decades. Xu et al. discussed the reduction of ZEN in corn flour by ozone treatment, and four ozonation products were identified by a method involving the use of ultra-performance liquid chromatography-tandem mass spectrometry [12]. Inan et al. degraded aflatoxin B1 (AFB1) in sliced and ground pimiento by 33 and 66 mg/L ozone and obtained degradation rates of 80% and 93%, respectively [13]. Zorlugenc et al. treated AFB1 in dry figs by ozone gas and ozonated water for 180 min, and the degradation rates of AFB1 were 95.21% and 88.62%, respectively [14]. These studies proved the strong degradation capability of ozonated gas and ozone water for fungal toxins.

Electron beam irradiation (EBI) is the process of irradiating products by using the electron beam generated by an electron accelerator. This technology is characterized by high energy utilization, simple operation, and safe use. EBI is a safe and e ffective green-processing technology. Researchers have explored the application of EBI in agricultural products and food storage, crop breeding, radiation sterilization, radiation pest control, and other emerging fields such as radiation chemical and radiation material engineering [15,16]. The degradation of fungal toxins in foods based on EBI has recently been discussed. Stepanik et al. investigated the degradation of deoxynivalenol (DON) in three production intermediates in distillers dried grain and solubles by using a dose of EBI treatment [17]. Wang et al. discussed the degradation of AFB1 by EBI and found that 8.6 kGy of EBI was adequate to completely degrade 5 ng/g AFB1 [18]. The mechanism of action was similar to that of γ-ray [19]. Water molecules were activated and ionized after EBI, generating hydroxyl radicals and hydration molecules. Hydroxyl radicals further destroy the molecular structure of the toxin.

Few studies on the degradation of ZEN and OTA by ozone and EBI are available presently, although numerous studies have focused on the degradation of AFB1 [20]. The e ffects of ozone and EBI on the degradation of ZEN and OTA cannot be easily understood due to the di fferent structures of ZEN and OTA from AFB1, thereby limiting the applications of ozone and EBI in ZEN- and OTA-contaminated foods. The influences of ozone concentration, sample concentration, treatment time, and radiation dose in acetonitrile and methanol systems on the degradation rates of ZEN and OTA were discussed on the basis of previous studies on DON [21] and AFB1 [22] degradation by ozone and EBI. The present study provides theoretical and practical bases for OTA and ZEN degradation in food by ozone and EBI in the future.


*4.4. Paeoniflorin*

Paeoniflorin is a monoterpene glucoside extracted from the root of the *Paeonia Lactiflora*. Paeoniflorin shows anti-inflammatory properties and it is already used in traditional Chinese medicine for a wide range of pathologies [110,111]. Moreover, paeoniflorin shows immunomodulatory e ffects on microglial cells through the enhancement of the suppressor of cytokine signaling 3 (SOCS3) pathways [112]. Zhu et al. demonstrated, in an in vitro study on BV2 microglial cells exposed to high concentrations of glucose, that treatment with paeoniflorin reduces the expression of metalloproteinases-9 (MMP-9) through the inhibition of p38/NF-κB. In addition, paeoniflorin activates SOCS3, which blocks the TLR-4 pathway [112,113]. The repression of TLR-4 determines the reduction of HMGB1 mediated inflammation in retinal microglial cells [114].


**6. Conclusions**

444 Polyurethane

PGU40

PGU-Cel-20

**Figure 12.** IR spectra PGU20-cellulose 1 – initial PGU20-cellulose; 2 – PGU after contact with natural

microbial medium, 3 – PGU after contact with aggressive microbial medium.

**Table 3.** IR spectra of PGU40 and PGU-cellulose-20 after biodestruction

System Initial Natural Aggressive

New hydroxylcontaining polyurethane networks (polyglucanurethane) with various urethane group content were obtained based on microbial exopolysaccharide xanthan and latent blocked polyisocyanate using environment friendly technique. Obtained polyglukaneurethanes possess advanced thermal and chemical (both alkali and acid) resistance. Thermal resistance of PGU grows with increasing of urethane group amount. Were as with growth of urethane group content in the system the amount of absorbed water declines.

Study of properties of polyglucanuretanes reveals their ability to quantitative extraction of phenol and bivalent metal ions from water solution, while controlling sorption properties of the material with polysaccharide cross-linking degree. According to electron spectroscopy and EPR data the main mechanism of ion capture by polyglucanurethane consists in formation of "polymer-metal ion" chelate complexes.

Biodestruction research demonstrate that polyglucanurethane degradation in aggressive microbial media occurs via polysaccharide fragmentation due to urethane bonds cleavage. On the contrary microbial association that was isolated from pollution-free chernozem disintegrate the polysaccharide chains predominantly.

But both in aggressive microbial association and in natural microbial association that was isolated from pollution-free soil the direct relation was observed between destruction process intensity and percentage of polysaccharide OH-group substitution in PGU. The lower percentage of OH-groups was substituted, the more intensive destruction process was observed.


# **The Effects of Mycotoxins on Human and Animal Health A Special Focus on the Cellular and Molecular Mechanisms Responsible for Mycotoxin Toxicity**

Edited by Daniela Eliza Marin and Ionelia Taranu Printed Edition of the Special Issue Published in *Toxins*

www.mdpi.com/journal/toxins


**4. Particle fabrication**

Traditionally, implantable medical devices for neurostimulation have been built with CMOS processes (like other electronic devices). This approach is not scalable to nano-sized products that are needed for noninvasive access. Most of the magnetic particle literature was contributed in the field of bioassays, where particle uniformity is not critical. However, for medical applications (e.g., magnetic particle imaging), lack of particle uniformity is often a limiting factor [21].

**Figure 2.** Example of template-guided shape-engineered synthesis of magnetic particles. Particles are made via sequential processing of polycarbonate track etched (PCTE) membrane films. PCTE films have pores extending through the thickness of the film. Templates (A) are first partially sealed on one surface with a conductive layer (B), followed by deposition of a polymer (e.g. poly-lactic-co-glycolic acid) shell inside the pores of the PCTE (C). Selectively etching the partially sealing conductive layer (D) and replacing it with a completely sealing conductive layer (E) allows for deposition of a conformal gold layer (F), after which a payload (e.g. liquid-crystal-magnetic composite) can be deposited by vacuum impregnation into the sealed pores of the PCTE film (G). Deposition of a final sealing layer (H), followed by selective etching of the conductive sealing layer (I) and removal of PCTE film (J) results in free-floating particles.

We have used template-guided methods to build shape-engineered highly uniform magnetizable particles with features important for transport and effectiveness [22] (**Figure 2**). For example, different sections of the particles can be built with aspect ratios that favor a particular magnetization direction. With appropriate use of precessing magnetic fields, the particles can be drilled through tissue [14]. The template-guided methods are also economical: it is possible to fabricate micromolar quantities of particles for less than \$20 in raw materials. We have evaluated nanoscale spintronic devices for voltage sensing and stimulation, which have very tight tolerances. Transitioning these devices in their current morphologies to templateguided manufacturing (with tolerances of a few nm) may be challenging and may require device redesign.


**4. Discussion**

The research showed the Tmax increase in the summer season in Pozna ´n over the last 50 years. The results are consistent with previous studies conducted in Pozna ´n [27,38] and other Polish cities [27,39], as well as in the rest of Europe [38,40,41].

The observed increase in Tmax translated into an increase in the number of hot days and heat waves. Of the exceptionally hot summer seasons in Pozna ´n, one should especially mention the summers of 1992, 1994, 2006 and 2015. Similar results were also obtained in other regions of Poland [42–44]. As Sulikowska et al. [27] have shown, the summer of 2015 was exceptionally hot in Poland, especially in the southwest of the country.

In the city districts, there was a great diversification of thermal conditions during the summer season and during the analysed heat waves. The highest air temperature was recorded in heavily transformed areas, i.e., in the developed city centre or industrial and commercial and public areas, while natural areas such as forests and areas near water bodies were characterised by the lowest air temperature. On this basis, within the city, one may distinguish areas with favourable biometeorological conditions during heat waves, such as green wedges, where the air temperature was significantly lower than in the centre and the air temperature differences were several degrees. A similar distribution of areas with highest and lowest temperatures was determined by Majkowska et al. [33] by analysing the urban heat island in Pozna ´n, and Walawender [32], who analysed the urban heat island in Kraków based on satellite images.

In the course of daily air temperature in Pozna ´n, the greater difference between the individual measuring points in the early hours, which gradually decreased during the day, was clearly visible. These differences are due to numerous shadowing effects of urban space and slower heating of the artificial surfaces [11,45–47] and faster cooling of natural areas, especially in clear and windless weather [11].

The research conducted using satellite images showed different variations in air temperature in the city area on the days analysed. On the first day, the average air temperature differences in the studied area were 2.8 ◦C, while on the second day they were smaller and amounted to 1.5 ◦C. On the second day, there was also less variation in air temperature within the various types of land use. No significant impact of the city's development on thermal conditions on 11 August 2015 was caused by the exchange of air masses.

This situation was a consequence of the passage of a weather front, while on 12 July 2010 the anticyclonic weather caused tropical air to hold for a few days. When stable pressure systems hold for a longer time, this leads to intensification of thermal conditions in highly transformed areas, which results in deterioration of biometeorological conditions and poses risks to human health and life. This highlights the significant role of atmospheric circulation in shaping weather conditions that can be modified by local factors. Similar results were obtained by Półrolniczak et al. [48], who demonstrated that the greatest intensity of the urban heat island is at night, especially during anti-cyclone circulation.