**3. Ex vivo models**

Using *in vitro* models for studying nanoparticle mediated toxicity comes with the set of challenges as discussed in the previous section. Animal models like rodents or zebrafish embryos are ideal alternatives for studying toxicity induced by NPs, however, there are various limitations including the cost of maintenance, biosafety etc. One also needs to follow appropriate ethical guidelines and have a moral compass to ensure whether inducing pain or sacrificing the animal can be avoided by alternate studies.

*Ex vivo* studies where tissue slices are cultured outside the host organism, experiments on fertilized eggs, organs on chip studies are more reliant than *in vitro* studies which are often based on monolayer culture of cells. The following section will briefly describe the prominent ex vivo models.

In Vitro*,* In Vivo *and* Ex Vivo *Models for Toxicity Evaluation of Nanoparticles: Advantages… DOI: http://dx.doi.org/10.5772/intechopen.111806*

#### **3.1 Precision cut tissue slices**

In precision cut tissue slices, tissues are collected from a model organism or human biopsy samples for testing the effects of nanoparticle treatment. This approach provides a more comparable biological scenario rather than using immortalized or primary cells cultured in monolayer. As the organ tissues provide a better biological replica of the effect of nanoparticle in the biological system as a whole. Predominantly, this method has been used to study aerosol effects or nanocarriers developed for treating lung disorders [93–96]. Using liver cut slices to study hepatotoxicity is also common [97–100].

One of the major challenges of this method involves the penetration of nanocarriers into the organ slices. In a biological system, like our body, circulatory system ensures the uptake/delivery of nanocarriers. Without this in the organ slices which also has several physical barriers makes it difficult for the passive entry of NPs. As seen in some studies, the NPs are seen around the surface of the tissue slices [101]. Besides this, sometimes slicing a tissue induces inflammation around the cut region. This is unfavorable while studying toxicity effects. An inflamed tissue could introduce bias into the experimental outcomes. Inflammation could activate cells and induce necrosis or apoptosis which will interfere with toxicity results for nanoparticle testing.

#### **3.2 Organ-on-a-chip**

A 3D culture with multiple kinds of cell population sufficiently supported with extra cellular matrix and growth factors is better than monolayer culture in terms of nanotoxicology analysis. However, these kinds of system are considered to be static and does not mimic vascular perfusion or the sheer stress in biological systems. Recently, microfluidics have been integrated to 3D culture of different population to generate micro physiological systems called organ-on-a-chip. A very simplistic model of organ-on-a-chip will have a single type of cell lined over the microfluidic channel with a continuous flow of media. In advanced models like lung-on-a chip, blood brain barrier-on-a chip or blood retinal barrier-on-a-chip model, multiple types of cells are used with microfluidic channel mimicking biological processes like breathing, blinking [102–115] etc.

These devices employ different perfusion rates and with the kind of material used, introduce mechanical strains which mimics biological circulation events like breathing, heartbeat, peristalsis, blinking, twitching etc. By using transparent materials for channel construction, the device also allows live visualization. As compared to conventional *in vitro* techniques, this provides a better physiological parallel with intricate designs to replicate organ architecture. Recently, there have been studies to develop multiple organ on a chip interconnected devices which could essentially be called body-on-chip to develop a model of whole organism rather than studying the effects on individual organs [116]. With intricate designs to carefully recreate biological systems, this could to a larger extent eliminate animal based testing.

Fluorescently labeled PEGylated gold nanoparticles were tested on tumor on a chip model which provided better insights into the circulation, elimination and uptake of nanoparticles in tumor microenvironment [117, 118]. Similarly Organ-ona-Chip model are used in understanding the effects of shape of NP on its toxicity [119]. Understanding the effect of flow rates, especially while NP mediated targeted therapy for crossing BBB [120], the underlying changes in toxicity profile introduced by surface modifications of the particle [121] etc. are few of the recent advances in NP mediated research which has recently been revolutionized by Organ-on-a-Chip models. Specifically focusing on toxicity studies, lung-on-a-chip models have provided better insights into pulmonary toxicity of nanoparticles, specifically, TiO2, Silica NPs [108, 122] etc. Also, the effect of NPs on crossing placental membrane has been evaluated using Organ-on-a-Chip model. In one such model, placental membrane integrity and maternal immune cell response were negatively challenged by TiO2 NPs [123]. These models also enable the researchers to evaluate toxicity of NPs in both static and mobile conditions as opposed to static conditions in *in vitro* studies [124].

One major disadvantage of the devices is the use of precursors which adsorbs drugs while testing. This reduces the amount of drugs available for interacting with the cells of interest. The widely used material polydimethylsiloxane (PDMS) [125] is known to adsorb certain drugs which is a disadvantage to the application. Polysulphone based materials are considered to be an alternative for PDMS. However, they lack transparency and are difficult to tune the mechanical properties. If careful considerations are introduced while designing the architecture and appropriate precursor materials are chosen, organ-on-chip can be a lot desired application for nanoparticle toxicity analysis (**Figure 5**).

#### **3.3 Chick chorioallantoic membrane (CAM) assay**

Angiogenesis and neovascularization is a characteristic trait of multiple disorders including cancer and retinopathies. Preventing the formation of new leaky vasculature is thus critical in treating these disorders. NPs developed as potential therapeutic options thus need to be evaluated for their anti-angiogenic properties. Evaluating this on developing chick embryos is both cost and time effective other than the simplicity of the model [127–130]. Briefly, the assay is performed by making a hole in the eggshell and inserting a membrane which delivers the NPs of choice. At the end of study, the eggs are opened, and the blood vessels are quantified using bright field imaging. One of the major advantages of this method is its reproducibility and simplicity to conduct in small scale laboratories.

#### *3.3.1 Ex-vivo tumor models on CAM*

Cancer cells of human origin are transplanted to CAM that covers chicken embryo. After 3 days of transplantation, a tumor with host species features will be developed. The tumor features multiple cell type of human origin, with rich vasculature and extracellular matrix. In terms of tumor microenvironment and cell types, this model is a closer approximation to *in vivo* models compared to 3D organoid studies. Also, the tumor formation process is rapid and eliminates longer waiting period as compared to rodents. Also, immune compromised animals are costlier in contrast to chick embryos which poses naturally underdeveloped immune system in early developmental stages. Besides these advantages, the rich nutrients present in chick embryo encourages effective angiogenesis in the tumor model. This facilitates drug and nanoparticle testing and monitoring of reduction of micro blood vessels and other tumor characteristics (**Figure 6**).

#### *3.3.2 Anti-angiogenesis studies for retinopathies*

These are studies where implants are prepared and investigated on its ability to sustainably deliver therapeutic agents in ocular regions. Neovascularization and

In Vitro*,* In Vivo *and* Ex Vivo *Models for Toxicity Evaluation of Nanoparticles: Advantages… DOI: http://dx.doi.org/10.5772/intechopen.111806*

#### **Figure 5.**

*The lung/liver-on-a-chip platform. (a) A photograph of the chip system comprising the pump main unit with four pump heads, the PEEK chip, and the reservoir plate. (b) a schematic view of the chip comprising four circuits is shown; each circuit includes two compartments to house the lung and liver tissues, respectively. The cross-section schemas of the plates show the path of the tubes and channels and the relative depth of each well. (c) a close-up view of the two compartments showing the groove pattern on the bottom of the wells. (d) Effect of chip materials on absorption of nicotine. A solution of 10 mM nicotine in phosphate-buffered saline (PBS) was kept in the wells of the chips made from PEEK or PDMS for 8 hours before it was collected. The concentrations of nicotine were then measured using liquid chromatography coupled to high-resolution accurate mass spectrometry. Nicotine concentrations remaining in solution are expressed as % relative to the stock solution. Data are presented as mean ± SEM. N = 3. PEEK: Polyetheretherketone; PDMS: Polydimethylsiloxane [126].*

resultant increased ocular pressure lead to a plethora of ocular disorders including diabetic retinopathy, macular degeneration etc. Nanoparticle mediated implants or delivery systems attempt to target pro-angiogenic markers in the eye. However, this needs to be carefully implemented with increased attention on not to induce any inflammation and reduction in angiogenesis.

**Figure 6.**

*Patient tumor sample transplanted on the CAM membrane. (A) Tumor formed by transplanting minced sample of ovarian cancer patient tumor. (B) Tumor is eliminated after intravenous injection of PMO-1 containing doxorubicin. (C) Chick embryo major organs look normal 3 days after injection [130].*

Briefly fertilized eggs will be candled to spot the air sac and blood vessels. A small hole of 1×1cm will be made into the egg shell at air sac region. Similarly, a cut is made near the vascular region without disturbing the CAM. Sucking out air from the air sac will distant the CAM from the egg membrane at the vascular region. Once this is achieved, a small incision is made at the CAM of vascular region where implants are introduced through sterilized filters. These filters containing the particle are then incubated over desired time frame. At the end of experiment duration, CAM is fixed and imaged to count the no of blood vessels compared to untreated controls (**Figure 7** represents multiple ways of performing CAM assay for angiogenesis studies).

For a simplistic and cost-effective model like CAM assay, most often the only disadvantages lies in the frequent contamination of samples. This can be eliminated with limited exposure of the opened CAM to outside air and by following stringent sterilization practices [132].

### **4. In vivo models**

Nanocarrier formulations are tested in in vivo models as pre-clinical studies to evaluate its feasibility to escalate to clinical trials and into commercial market at the end of pipeline. The maximum dosage of NPs which could be safely tolerated, the pharmacokinetics and elimination window of NPs from the tested organisms, the accumulation and effect of long-term exposure is analyzed during these experiments. Vertebrates and invertebrate groups of animals are used for these studies to scale up from simplistic biological networks to understanding the effects on complex In Vitro*,* In Vivo *and* Ex Vivo *Models for Toxicity Evaluation of Nanoparticles: Advantages… DOI: http://dx.doi.org/10.5772/intechopen.111806*

#### **Figure 7.**

*Representative images of chorioallantoic membrane (CAM) variants. (A) in-ovo setup by windowing method on day of incubation; (B) ex-ovo setup in a petri plate; (C) ex-ovo setup in a glass-vertical view; (D) ex-ovo setup in a glass-horizontal view; (E) ex-ovo setup on plastic cups, image taken by a camera and; (F) ex-ovo setup in plastic cups, image taken by a Chemidoc (charge-coupled device (CCD) camera) [131].*

organisms genetically closer to human beings. Good lab practices are stringently adhered to while conducting these studies with appropriate ethical standards.

#### **4.1 Invertebrates**

Invertebrate models often have a shorter lifespan which aids researchers in testing nanoparticle toxicities. Due to their shorter life cycle, it's feasible to understand and compare the effects of exposure of NPs in their developmental stages. It also benefits to conduct multiple rounds of testing within a shorter duration of time. The most established invertebrate model systems for nanoparticle toxicity include *Caenorhabditis elegans* and *D. melanogaster.*

#### *4.1.1 C. elegans*

*C. elegans* are nematodes which can grow up to 1 mm in size in its fully developed adult stage. They are often used for understanding nanotoxicity through oral uptake which is also the major form of nanotoxicity in human beings [133–138]. They pose around 70–80% of gene homology with humans and have around 70% of major signal transduction pathways conserved as compared to human beings. They are also transparent in nature allowing to visualize and track the accumulation of fluorescent labeled NPs. (**Figure 8**).

Major studies conducted on testing nanoparticle formulation and its effect on *C. elegans* has found that there have been significant changes in oxidative response, reproduction and lysosomal signaling after oral uptake of particles. For example, treatment with TiO2 NPs have reported to alter the expression levels of glutathione-stransferase gene. Exposure to NPs in *C. elegans* could also be through their vulval slit or opening. The nematodes being hermaphrodite, interaction of NPs at vulval site and spermathecae, where sperms are stored and oocyte fertilization happens, could provide preliminary results on how NPs affect reproduction in organisms. Interestingly, a recent study has reported that exposure of TiO2 NPs in *C. elegans* leads to decreased expression levels of pod-2 a gene known to have role in reproduction in the nematodes [133, 136]. Another study has reported the exposure of silver NPs leading to altered expression levels of proteases involved in lysosomal pathway related genes.

Generation of mutant strains of *C. elegans* has helped in understanding the effects of common particles like graphene oxide (GO), Silver, cadmium quantum dots and TiO2. Tracing of these NPs is often reliable and easy in *C. elegans* due to the transparency of its body. However, *C. elegans* lacks organs like a well-developed lung, kidney, heart etc. which makes it difficult to draw comparisons with higher order species. Also, it only has a 70% homology with human genome with some critical signaling pathways completely absent.

#### *4.1.2 D. melanogaster*

*D. melanogaster* or fruit fly is another model well used for oral toxicity of NPs. Like *C. elegans*, fruit fly poses different life development stages which makes it suitable to study the effect of NPs on different life stages. Effects of NPs in the gut cells, eye and wing development are often studied for testing the toxicity of NPs (**Figure 9**). Along with this, behavioral studies are also conducted where crawling speed and path is monitored [140, 141]. Immune pathway in fruit flies is well studied and they also display a similarity of autophagy related genes with human beings. This makes *D. melanogaster* an ideal model for studying immune response and rate of autophagy with respect to NPs like GO [142]. The effect of nanoparticle exposure to the organisms is also analyzed by studying the effects on reproduction. Offspring number, morphology, development life stages are analyzed to understand the same [140, 143–145].

The studies of nanotoxicity using fruit flies are limited to survival, developmental stages, eclosion rate, fertility and geotaxis performance analysis. Though it provides a significant addition in terms of understanding the toxicity as compared to *in vitro* studies, parallels cannot be drawn between human beings. One of the major challenges in using *D. melanogaster* as a model organism is the absence of an adaptive immunity in the organism. Other limitations include insufficient evidence of the cognitive capabilities of the organism especially affecting behavioral studies. Also,

In Vitro*,* In Vivo *and* Ex Vivo *Models for Toxicity Evaluation of Nanoparticles: Advantages… DOI: http://dx.doi.org/10.5772/intechopen.111806*

#### **Figure 8.**

*Induction of C. elegans major stress or host defense responses by SiNP treatment. Fluorescent images of worms treated with H2O* (*a*), *SiNPs* (*b*)*, and tunicamycin* (*c*) *with a GFP reporter for ER stress. Fluorescent images of worms treated with H2O (d), SiNPs (e), and ethidium bromide (f) with a GFP reporter for mitochondrial stress. Fluorescent images of transgenic worms carrying the GFP reporter for oxidative stress subjected to H2O* (*g*)*, SiNPs (h), and H2O2 (i) treatment. Fluorescent images of transgenic worms carrying the GFP reporter for innate defense subjected to H2O (j), SiNP treatment (k), and physical injury (l). The same magnification was used in all of the images (m). Quantitative analysis of fluorescent intensity fold change of worms treated with H2O and SiNPs and a positive control group corresponding to (a–l). N ≥ 20. Error bars represent mean ± SEM; \*\* p < 0.01 [139].*

#### **Figure 9.**

*Possible mechanism of nanoparticle-induced mortality in adult Drosophila. (A) Location of spiracles in drosophila: sp1, mesothoracic spiracle; sp2, metathoracic spiracle; sp3 to sp9, abdominal spiracles, image from Lehnmann et al. (B) SEM image shows mesothoracic and metathoracic spiracle of an adult drosophila (blue square) Center row (C − E): SEM images of spiracles in unexposed drosophila; sp1 (C), sp2 (D), both 20–50 μm, and an abdominal spiracle (E) at 5 μm. Bottom row (F − H): Spiracles are covered/decorated with nanomaterials (see arrows) after dry exposure of adults to CB (F); MWNTs (G); CB (H) differential toxicity of carbon nanomaterials in drosophila: Larval dietary uptake is benign, but adult exposure causes locomotor impairment and mortality [140].*

vertebrate specific genetic disorder models cannot be developed in *D. melanogaster*. Other than this, unlike other models, amount of ingestion of NPs per flies cannot be accurately standardized as they are not gavage fed. Even after the above-mentioned limitations they remain one of the simplest models along with *C. elegans* to develop transgenic lines by breeding.

#### **4.2 Vertebrate models**

Vertebrate models for studying nanotoxicity include zebrafish, rabbit rodent models like mice, rat, hamsters etc. They share higher similarities with human beings in terms of the respiratory, circulatory, and nervous system. However, studying long term exposure of NPs in these organisms, especially rodents, becomes challenging due to their longer lifespan and gestation periods. The following section will briefly discuss the recent reports of using these vertebrate models for nanotoxicology studies and their limitations.

In Vitro*,* In Vivo *and* Ex Vivo *Models for Toxicity Evaluation of Nanoparticles: Advantages… DOI: http://dx.doi.org/10.5772/intechopen.111806*

#### *4.2.1 D. rerio*

Zebrafish or *D. rerio* is one of the few vertebrate models with shorter breeding and offspring rearing period. This allows it to be a vertebrate model with ease to study developmental stages and the effect of NPs on life cycle. Also, oral and circulatory introduction of NPs is possible through zebrafish. The oral toxicity studies are conducted by introducing NPs in embryonic medium or fish water. The NPs are introduced in the blood stream directly using micro injections or intravitreal, intraperitoneal, intraventricular injections. Zebrafish models have been used to develop blood brain barrier models, tumor models and studied to see the effect and penetration properties of these nano formulations [146–150].

Toxicity of nanoparticle formulation is often assessed by survival analysis, cardiac rhythm studies, morphological changes in eye, spine and fin development, edema in cardiac sac etc. Behavioral changes like swimming pattern, response to tapping and light are also investigated. Like fruit flies, conservation of autophagy related genes to human beings allows using zebrafish models for studying the autophagy related gene expression with respect to nanoparticle treatment. Recently, treatment of ZnO nanoparticle in zebrafish model has displayed an increase in inflammation related gene over expression [151]. There are also reports of siler NPs affecting the gut microbiota of zebrafish [152]. Embryonic zebrafish studies have also reported the effect of silica based NPs in reducing the blood pressure in zebrafish and vascular endothelial cells (**Figure 10**) [153].

One of the major limitations of using zebrafish is the inability to use them for studying respiratory effects of aerosol based nano formulations. Other than this limitation they are also not ideal for breast cancer and prostrate cancer models as they lack the appropriate tissue of origin in their body architecture.

#### *4.2.2 Rabbit and rodent models*

Rabbits were classified as rodents till the early 20th century. They along with models with mice, rat and limitedly hamsters have been used for studying pharmacokinetics and pharmacodynamics of nanoparticle formulations. Their organs are also harvested and used for tissue distribution studies as they have striking similarity in tissue characteristics with human beings. Ocular and dermal toxicity of NPs are mostly studied in rabbits. Recently, silver NPs were tested on shaved skin regions on albino rabbits and the toxicity was analyzed using prefixed criteria. Dry skin, scaling in doses lower than 100 ppm and erythema in higher doses up to 4000 ppm was observed as part of this study [154]. Nano-hydroxyapatite was intravenously introduced to New Zealand white rabbits and it was noted that they does not affect liver function, and renal function in the animals [155]. In another study conducted to understand the toxicity of aflatoxin B1, treatment with curcumin and ZnO NPs prevented lipid and protein degradation via oxidation and showed better liver health as compared to aflatoxin B1 treated groups [156]. In corneal fibrosis (haze) model in rabbit using excimer laser performing -9D photorefractive keratectomy (PRK), nanoparticle formulation containing BMP7 topical application 5 minutes after PRK reduced the corneal haze by 50 percent with no toxicity [157]. Nephroprotective effects of NPs have also been studied using rabbit models. Studies using CaO NPs however have reported significant toxicity in liver and kidney after exposure [158].

Rodent models of nanotoxicity mainly includes rats and mice. Immune compromised, genetically altered rodents are very commonly used in nanotoxicology studies

#### **Figure 10.**

*Inflammatory response and vascular endothelial cell dysfunction induced by SiNPs. (a,B) SiNPs increased the recruitment and chemotaxis of neutrophils in caudal vein of Tg(mpo:GFP) zebrafish. (C,D) SiNPs inhibited the expression of vascular endothelial cells in Tg(fli-1:EGFP) zebrafish. n = 30, data are expressed as mean ± standard deviation from three independent experiments (\*p < 0.05). Scale bar: 100μm [153].*

and have been reviewed better in various book chapters and reviews elaborately [159–162]. Briefly they are used for central nervous system disorder models, cancer models, hepatotoxicity models, aerosol treatment models. They provide relatively more homology with human beings; however, the laboratory maintenance of rodents and rabbits are often challenging. Also, historical trait analysis with respect to nanoparticle formulation is often limited by the number of offspring produced and longer gestational periods. Besides this, there is no accepted duration of days or guidelines recommending the number of days nanoparticle exposure in rodents to be monitored. This largely leads to inaccuracies and inconstancies in reporting toxicity of the same or similar nano formulation by different research groups.

### *4.2.3 Primate models*

Primate models for nanotoxicity analysis rose to prominence after a study conducted on *Rhesus macaque* by intravenously injecting 25 mg/kg of phospholipidmicelle-encapsulated CdSe-Cds-ZnS QDs [163]. The study term was 90 days and the authors observed significant changes in behavioral patterns including loss of sleep, appetite, body weight, physical activity etc. By the end of study term, most of these effects were reversed to original state, however the particle displayed accumulation on liver and kidneys. Further studies on this were not carried out to understand the long term implications of hepatic accumulation. Quantum dots are generally considered to be safe to administer after conducting studies on *in vitro* and other *in vivo* models. However, this study indicated the need of behaviorally closer primate models to draw significant conclusion on nanoparticle toxicity before human trials.

Following this study, there were multiple reports of nanoparticle toxicity analysis using primates. Polylyisne conjugated DNA NPs for targeting retinal pigment

In Vitro*,* In Vivo *and* Ex Vivo *Models for Toxicity Evaluation of Nanoparticles: Advantages… DOI: http://dx.doi.org/10.5772/intechopen.111806*

epithelium was studied using baboons showing no inflammatory response in the eye [164]. Also in cynomolgus monkeys, the safety of gadolinium based NPs for imaging purpose was evaluated [165]. In another studies, PEG-bl-PPS polymerosomes were found to be nontoxic in non-human primates [166]. Also, cargo of siRNA in cyclodextrin with transferrin ligands as targeting moieties were also found to be relatively safe in cynomolgus monkeys [167]. However, there were elevated levels of creatinine and nitrogen along with certain inflammatory cytokines at higher dosage. In another study, mice and *Rhesus macaque* were compared on its effect of CdSe/CdS/ZnS semiconductor NPs in placental crossing and miscarriage rates. Interestingly, in the rodent models there was not toxicity recorded even though the particles were shown to cross the placenta. There was no miscarriage in rodents and fetus displayed no abnormalities. However, in primate models there was a 60 percentage rate of miscarriage establishing the fact that primate models are far superior in compared to rodent models for toxicity analysis [168].

Even though they are ideally the closest to understanding human body's response to nano formulations, testing these formulations on them require more human resources and expertise along with stricter ethical guidelines in handling them. Also, these magnificent creatures are often sacrificed at the end of the study to harvest organs and understand tissue damage. Most of them being social organisms, this would have larger implications on their family group and could even lead closer ones to depression. Infant carrying is one such response displayed by mothers losing infants in primates. Secondary responses of curiosity and stress to death of infants or members is often displayed by these primates [169–172]. A closer evaluation of the morality and scientific rationale should be evaluated before conducting such studies.

### **5. Conclusions**

The past few decades witnessed the advent of nanoparticles and their potential use in multiple fields of biomedical sciences. From drug delivery to semiconductor devices, nanoparticles find applications around us. Informed use of nanomaterials, especially on its toxicity is highly relevant as more and more studies report the hazardous effects of these particles. The current chapter discussed *in vitro*, *in vivo*, *ex vivo* models for evaluating nanoparticle toxicity. As we analyze the plethora of assays conducted to study, in some cases, same particles in multiple model systems, we understand the varying toxicity reports. Such studies challenge the dangerous assumption of deeming a NP to be nontoxic by simply analyzing *in vitro* and in some cases rodent models. The need of non-human primate models closer to the genetic and physiological profile of human beings vs. the morale of sacrificing animal life for our benefit need to be carefully questioned. Alternate strategies like organ-on -chip models require further refinement and balance in incorporating parameters to better mimic study conditions.

### **Acknowledgements**

Authors acknowledge the financial support provided by Blazer foundation and Medical Biotechnology Program at Department of Biomedical Sciences, UIC College of Medicine Rockford.


Peri-Implant Soft Tissue Augmentation

*Marko Blašković and Dorotea Blašković*

## **Abstract**

The peri-implant soft tissue (PIS) augmentation procedure has become an integral part of implant-prosthetic rehabilitation. Minimal width of keratinized mucosa (KM) of 2 mm is deemed necessary to facilitate oral hygiene maintenance around the implant and provide hard and soft peri-implant tissue stability. PIS thickness of at least 2 mm is recommended to achieve the esthetic appearance and prevent recessions around implant prosthetic rehabilitation. The autogenous soft tissue grafts can be divided into two groups based on their histological composition—free gingival graft (FGG) and connective tissue graft (CTG). FGG graft is used mainly to increase the width of keratinized mucosa while CTG augment the thickness of PIS. Both grafts are harvested from the same anatomical region—the palate. Alternatively, they can be harvested from the maxillary tuberosity. Soft tissue grafts can be also harvested as pedicle grafts, in case when the soft tissue graft remains attached to the donor site by one side preserving the blood supply from the donor region. Clinically this will result in less shrinkage of the graft postoperatively, improving the outcome of the augmentation procedure. To bypass the drawback connected with FGG or CTG harvesting, substitutional soft tissue grafts have been developed.

**Keywords:** connective tissue graft, CTG, free gingival graft, FGG, apically positioned flap, APF, peri-implant soft tissue augmentation, subepithelial connective tissue graft, de-epithelized free gingival graft, keratinized mucosa


**1. Introduction**

One method utilized by the global navigation satellite system (GNSS) to accomplish high-precision positioning is known as precise point positioning (PPP) [1], which has many advantages, including the need for only one receiver configuration as well as its flexible operation and wide-area application. To achieve centimeter-level positioning, PPP requires a convergence time of around 30 min, which makes it challenging to meet user demands in real time and severely restricts the marketing of PPP technology applications. Therefore, PPP ambiguity resolution (AR) technology has been suggested as a solution to the PPP

**Citation:** Du, S.; Shu, B.; Xie, W.; Huang, G.; Ge, Y.; Li, P. Evaluation of Real-time Precise Point Positioning with Ambiguity Resolution Based on Multi-GNSS OSB Products from CNES. *Remote Sens.* **2022**, *14*, 4970. https://doi.org/10.3390/ rs14194970

Academic Editors: Chuang Shi, Xiaopeng Gong, Yidong Lou and Shengfeng Gu

Received: 2 September 2022 Accepted: 4 October 2022 Published: 6 October 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/).

convergence problem. The single-difference (SD) between satellites approach was first suggested by Ge et al. in 2008. The main idea was to estimate uncalibrated phase delay (UPD) products using the fractional portions of the float wide-lane (WL) and narrow-lane (NL) ambiguities. According to their experimental findings, more than 80% of the SD ambiguities from 450 stations over 14 days were fixed under the data test, and the positioning accuracy was increased by 30% in comparison to the float solution [2]. Meanwhile, the integer recovery clocks method and the decoupled clock model were proposed by Laurichese et al. [3,4] and Collins et al. [5,6], respectively, from the perspective of satellite clocks. Using the products provided by these methods, PPP-AR can also be implemented at the user end. Through theoretical derivation and a large amount of data analysis, Geng et al. and Shi et al. verified the equivalence of the three ambiguity resolution processes and the positioning performance [7,8]. The above and related studies enabled the implementation of PPP-AR, effectively shortening the convergence time and enhancing the positioning accuracy [9,10]. As a result, different forms of post-ambiguity resolution products have been released to users by several analysis centers. Chen et al. conducted an analysis of the performance of PPP-AR based on various ambiguity resolution products and demonstrated that these products could significantly increase positioning accuracy and reduce convergence times; however, the positioning performance varied, which suggests that the usefulness of ambiguity resolution products plays a role in PPP-AR performance [11].

The abovementioned research results indicate that PPP-AR technology can, to a certain extent, address the shortcomings of traditional PPP; however, these analyses were based on the post-processing mode. Various academics have conducted extensive studies on real-time PPP, including studies on the accuracy of real-time satellite orbit and clock offset products, the positioning performance of real-time PPP, real-time PPP for time transfer or tropospheric delay retrieval, and more [12–19]. Their findings have shown that realtime satellite orbit and clock offset products can be accurate enough to satisfy user needs, and real-time PPP positioning performance can achieve centimeter-level accuracy after convergence [13,16–19]. However, for the kinematic mode, the four-system positioning still requires longer than 15 min to converge to 0.1, 0.1, and 0.2 m for the east (E), north (N), and up (U) components, respectively [19]. Moreover, El-Mowafy presented a method that can guarantee real-time PPP with a 3D accuracy of less than a decimeter while real-time satellite orbit and clock offset products are unavailable [20]. With the demand for real-time AR products from users, CNES currently broadcasts real-time observable-specific signal bias (OSB) products to the world with open access, which allows for the user implementation of PPP-AR. However, there are a number of issues with real-time PPP-AR technology, including the inferior precision of real-time products compared to post-products, missing or outage real-time OSB corrections, etc. Thus, it is important to evaluate the quality of real-time OSB products and their performance in PPP-AR positioning in order to promote the application of real-time PPP.

In this contribution, the data quality of real-time multi-GNSS OSB products from CNES and the performance of the real-time PPP-AR were evaluated. In Section 2 of this paper, a dual-frequency mathematical model for PPP-AR based on OSB products is introduced. Then, in Section 3, the quality of the OSB products are analyzed using three metrics, the positioning accuracy and convergence time of the real-time PPP-AR are evaluated using various system combinations and positioning modes, and a method that can effectively avoid the interruption of short-term OSB products is validated. Finally, the conclusions are summarized.

#### **2. Methodology**

The dual-frequency ionosphere-free PPP model is first introduced in this section. Then, a method for recovering the integer features of ambiguities using OSB products is described. Finally, an AR method for an ionosphere-free combination is given.

#### *2.1. Dual-frequency Ionosphere-Free PPP Model*

The effects of first-order ionospheric delay can be removed using the dual-frequency ionosphere-free (IF) observation. The following are expressions for the code and carrier phase IF observations (*Ps r*,*IF* and *Ls r*,*IF*, respectively) at a specific epoch:

$$\begin{cases} P\_{r,IF}^s = \rho\_r^s + t\_r - t^s + T\_r + (a\_{12}b\_{r,1} + \beta\_{12}b\_{r,2}) - \left(a\_{12}b\_1^s + \beta\_{12}b\_2^s\right) + e\_{r,IF}^s\\ L\_{r,IF}^s = \rho\_r^s + t\_r - t^s + T\_r + \left(a\_{12}B\_{r,1} + \beta\_{12}B\_{r,2}\right) - \left(a\_{12}B\_1^s + \beta\_{12}B\_2^s\right) + \lambda\_{IF}N\_{r,IF}^s + \varepsilon\_{r,IF}^s \end{cases} \tag{1}$$

$$\begin{cases} \lambda\_{IF} \mathcal{N}\_{r,IF}^s = \alpha\_{12} \lambda\_1 \mathcal{N}\_{r,1}^s + \beta\_{12} \lambda\_2 \mathcal{N}\_{r,2}^s\\ \mathcal{a}\_{12} = \frac{f\_1^2}{f\_1^2 - f\_2^2}, \mathcal{B}\_{12} = -\frac{f\_2^2}{f\_1^2 - f\_2^2} \end{cases} \tag{2}$$

where *s* and *r* denote the satellite and receiver, respectively; *ρs r* is the geometric distance between the satellite and the receiver (m); *tr* and *t s* are the receiver and satellite clock (m), respectively; *Tr* is the slant tropospheric delay (m); *br*,*i* and *bs i* are the code hardware delay of the receiver and the satellite (m), respectively; *Br*,*i* and *Bs i* are the phase hardware delay of the receiver and the satellite (m), respectively; *fi* is the frequency; *λIF* is the IF wavelength; *Ns r*,*IF* is the IF ambiguity (cycle); *es r*,12 and *εs r*,12 represent the sum of the measurement noises and the multipath effects for the code and carrier phase IF observations (m), respectively.

The satellite clock (*t s* ) in the PPP model is corrected using the clock offset products. Currently, the clock offset products are estimated via the IF combination, which causes the code IF hardware delay to be absorbed by the generated clock offset [21–23]. Therefore, the relationship between the clock offset products (*t s IF*) and the satellite clock (*t s* ) can be expressed as follows:

$$t\_{IF}^{s} = t^{s} + \left(\alpha\_{12}b\_{1}^{s} + \beta\_{12}b\_{2}^{s}\right) \tag{3}$$

By combining Equations (1) and (3), the linearized IF combined function model can be obtained as follows:

$$\begin{cases} \begin{array}{c} p\_{r,IF}^{s} = \mu\_{r}^{s} \cdot \mathbf{x} + t\_{r,IF} - t\_{IF}^{s} + T\_{r} + e\_{r,IF}^{s} \\\ I\_{r,IF}^{s} = \mu\_{r}^{s} \cdot \mathbf{x} + t\_{r,IF} - t\_{IF}^{s} + T\_{r} + \lambda\_{IF} \hat{\mathcal{N}}\_{r,IF}^{s} + \varepsilon\_{r,IF}^{s} \end{array} \tag{4}$$

where *ps r*,*IF* and *l s r*,*IF* denote the observed minus computed (OMC) IF observations of the code and carrier phase, respectively; *μs r* is the unit vector from the receiver to the satellite, and *x* is the coordinate of the estimated parameter. The receiver clock will absorb the code hardware delay of the receiver, which can be represented by the following expression:

$$t\_{r,IF} = t\_r + (a\_{12}b\_{r,1} + \beta\_{12}b\_{r,2})\tag{5}$$

Since the code and carrier phase observations in the PPP model share the same receiver clock parameter, where the parameter is based on the code observation, the code hardware delay will be added to the carrier phase observation [24,25]. Thus, the estimated ambiguity absorbs both the code and phase hardware delays, which can be written as follows:

$$
\hat{N}\_{r,IF}^{s} = N\_{r,IF}^{s} + \left[ a\_{12} (B\_{r,1} - B\_1^s + b\_1^s - b\_{r,1}) + \beta\_{12} (B\_{r,2} - B\_2^s + b\_2^s - b\_{r,2}) \right] / \lambda\_{IF} \tag{6}
$$

where *N*ˆ *s r*,*IF* and *Ns r*,*IF* represent the float and integer ambiguities, respectively. The integer feature of the IF ambiguity (*Ns r*,*IF*) is destroyed, as can be seen from the equation above. Therefore, the integer feature for the IF ambiguity should first be recovered before PPP-AR.

#### *2.2. Method for Recovering the Integer Feature of Ambiguity*

The same function model between the server and the user is required for traditional AR products, which significantly limits the application of the AR products. With the development of AR technology, Laurichesse et al. proposed the use of undifferenced and uncombined OSB products, which comprise both code bias and phase bias [26]. Based on these OSB products, a variety of function models can be used by users to conduct single-frequency or multi-frequency PPP-AR, which helps to meet the current demand for multi-frequency, multi-system, and multi-model PPP-AR. By directly utilizing the OSB products in the code and phase observations, the satellite's code and phase hardware delays can be corrected. The following is an expression for the dual-frequency code bias (*b s* 1 and *b s* 2) and phase bias (*Bs* 1 and *Bs* 2) products [27]:

$$
\begin{pmatrix} \overline{b\_1^s} \\ \overline{b\_2^s} \end{pmatrix} = \begin{pmatrix} \beta\_{12} \begin{pmatrix} b\_1^s - b\_2^s \\ -a\_{12} \left( b\_1^s - b\_2^s \right) \end{pmatrix}, \begin{pmatrix} \overline{B\_1^s} \\ \overline{B\_2^s} \end{pmatrix} = \begin{pmatrix} a\_{12}b\_1^s + \beta\_{12}b\_2^s - B\_1^s \\ a\_{12}b\_1^s + \beta\_{12}b\_2^s - B\_2^s \end{pmatrix} \tag{7}
$$

Since there is one code and phase bias for every code and phase observation, respectively, it is only necessary to add the OSB products directly to the raw observations when they are being employed. Additionally, the IF code and phase biases are formed, which can be expressed as follows:

$$\begin{cases} \overline{\boldsymbol{b}}\_{IF}^{s} = \boldsymbol{a}\_{12} \overline{\boldsymbol{b}}\_{1}^{s} + \beta\_{12} \overline{\boldsymbol{b}}\_{2}^{s} = 0\\ \overline{\boldsymbol{B}}\_{IF}^{s} = \boldsymbol{a}\_{12} \overline{\boldsymbol{B}}\_{1}^{s} + \beta\_{12} \overline{\boldsymbol{B}}\_{2}^{s} = \boldsymbol{a}\_{12} \boldsymbol{b}\_{1}^{s} + \beta\_{12} \boldsymbol{b}\_{2}^{s} - \boldsymbol{a}\_{12} \boldsymbol{B}\_{1}^{s} - \beta\_{12} \boldsymbol{B}\_{2}^{s} \end{cases} \tag{8}$$

When *b s IF* and *Bs IF* are combined with Equation (1), the new IF ambiguity can be stated as follows:

$$
\hat{N}\_{r,IF}^{s} = N\_{r,IF}^{s} + \left[a\_{12}(B\_{r,1} - b\_{r,1}) + \beta\_{12}(B\_{r,2} - b\_{r,2})\right] / \lambda\_{IF} \tag{9}
$$

Because of the negative impact of the code and phase hardware delays on the receiver, the IF ambiguity still does not have the integer feature. Usually, the SD between satellites can be used to eliminate the negative impact of the receiver, and the IF-SD ambiguity will recover the integer feature.

## *2.3. PPP-AR Process*

The integer wide-lane (WL) and float narrow-lane (NL) ambiguities can be used to decompose the IF ambiguity in the IF combination, which translates as follows:

$$
\hat{N}\_{r,IF}^{s} = \left(\frac{f\_2}{f\_1 + f\_2} \lambda\_{WL} N\_{r,WL}^{s} + \lambda\_{NL} \hat{N}\_{r,NL}^{s}\right) / \lambda\_{IF} \tag{10}
$$

where *Ns r*,*WL* is the integer WL ambiguity; *N*ˆ *s r*,*NL* is the float NL ambiguity; and *λWL* and *λNL* are the wavelengths of the WL and NL ambiguities, respectively, which can be formulated as follows:

$$\begin{cases} \lambda\_{WL} = \frac{\mathbb{C}}{f\_1 - f\_2} \\ \lambda\_{NL} = \frac{\mathbb{C}}{f\_1 + f\_2} \end{cases} \tag{11}$$

where *c* denotes the speed of light.

The float NL ambiguity can be derived from Equation (10) when the float WL ambiguity is correctly fixed; the float WL ambiguity can be calculated through the Melbourne– Wübbena (MW) combination and fixed using the rounding method [2]. Then, the float WL and NL ambiguities can be summarized as follows:

$$\begin{cases} \begin{array}{c} \text{\(\hat{N}\_{r,WL}^{s} = \left(\frac{L\_{r,1}^{s}}{\lambda\_{1}} - \frac{L\_{r,2}^{s}}{\lambda\_{2}} - \frac{\lambda\_{2}P\_{r,1}^{s} + \lambda\_{1}P\_{r,2}^{s}}{\lambda\_{\text{WL}}\left(\lambda\_{2} + \lambda\_{1}\right)}\right) \\\ \text{\(\hat{N}\_{r,NL}^{s} = \frac{\lambda\_{1}P\_{r}^{s} \| \text{F}}{\lambda\_{NL}} - \frac{\lambda\_{1}N\_{r,1}^{s} \| \text{F} \|}{\lambda\_{2} - \lambda\_{1}} \end{array}} \tag{12}$$

The WL ambiguity is affected by measurement noise and observation errors to a lesser extent due to its long wavelength, and it can be calculated with high accuracy using multiepoch smoothing [28]. As a result, the rounding method can be used to fix it directly [2]. On the contrary, the float NL ambiguities from different satellites in the PPP model are highly correlated; hence, the LAMBDA method should be used for fixing. After inserting the fixed WL and NL ambiguities into (10), the fixed IF ambiguities are obtained. Then, a virtual observation is employed to constrain the filtering state, and the fixed solution is obtained.

It is important to note that when using the MW combination to obtain the float WL ambiguity, the antenna phase center correction of the receiver and satellite must be taken into account [29,30]. The formula is as follows:

$$\mathcal{N}\_{r,WL}^{s} = \left(\frac{L\_{r,1}^{s} + z\_{r,1}^{s}}{\lambda\_{1}} - \frac{L\_{r,2}^{s} + z\_{r,2}^{s}}{\lambda\_{2}} - \frac{\lambda\_{2} \cdot (P\_{r,1}^{s} + z\_{r,1}^{s}) + \lambda\_{1} \cdot (P\_{r,2}^{s} + z\_{r,2}^{s})}{(\lambda\_{2} + \lambda\_{1}) \cdot \lambda\_{WL}}\right) \tag{13}$$

$$\begin{cases} z\_{r,1}^s = z\_{r,1} \cdot \sin \theta\_r^s - z\_1^s \\ z\_{r,2}^s = z\_{r,2} \cdot \sin \theta\_r^s - z\_2^s \end{cases} \tag{14}$$

where *zr*,1 and *zr*,2 are the vertical phase center offsets of the receiver antenna for the two frequencies, and similarly, *zs* 1 and *zs* 2 are those of the satellite antenna. *θs r* denotes the elevation angle of the satellite *s* with respect to the receiver *r*.

#### **3. Real-Time PPP-AR Performance**

In this section, we will first introduce the experimental data and processing strategies. Then, the quality of the real-time OSB products is analyzed. In addition, the performance of various PPP-AR combinations and modes based on the OSB products is assessed. Finally, a prediction method is proposed to effectively avoid the influence of short-term missing OSB products.

#### *3.1. Data and Strategy*

The post-store OSB products from day of year (DOY) 121 to 151 in 2021 were downloaded from http://www.ppp-wizard.net/products/REALTIME/ (accessed on 2 August 2022) to make it easier to analyze the real-time OSB products and PPP-AR.

The details of the dual-frequency and multi-GNSS real-time OSB products from CNES as of DOY 151 in 2021 are displayed in Table 1. It should be noted that the code bias was stable during the day [31]; therefore, the code bias was not analyzed.

**Table 1.** OSB product information provided by CNES.

**Note:** The sampling interval of post-store OSB products was 30 s. The "Frequency Number" only represents the index of the frequency for each system, which is convenient for the description below.

Figure 1 depicts the distribution of the 90 Multi-GNSS Experiment (MGEX) stations used to perform the PPP float solution and PPP-AR around the globe. These stations can receive GPS, Galileo, and BDS dual-frequency signals. The experiment time was from DOY 121 to 151 in 2021, which is a total of 31 days. To fully evaluate the real-time PPP-AR performance with different satellite systems, several combinations of static and kinematic positioning experiments were carried out. The combinations were as follows: 1) GPS-only; 2) GPS+Galileo; 3) GPS+Galileo+BDS. In the experimental analysis, incomplete observational data or data that did not pass quality checks (including detection, identification, and adaption (DIA) [32,33] and the Inter Quartile Range (IQR) method [34]) were excluded, where the excluded data were about 4% of the total data.

**Figure 1.** The 90 globally distributed MEGX stations used for the PPP-AR experiment.

All the PPP and PPP-AR experiments were performed with in-house software based on the secondary development of GAMP [35]. The phase windup was applied by the phase polarization effects. For the GPS L1/L2, Galileo E1/E5a, and BDS B1I/B3I frequencies, the igs14.atx file was utilized to correct the satellite phase center offset (PCO) and phase center variation (PCV); the receiver PCO and PCV of GPS were used for Galileo and BDS because those of Galileo and BDS were unavailable. It should be noted that the satellite orbit, clock offset, and OSB products from CNES were used in PPP-AR. The elevation and observable arc were used to define which ambiguity subsets should be employed, and the ratio test and bootstrapping success rate were used to validate whether the fixed subsets could be trusted. The detailed strategy for positioning is summarized in Table 2.

#### *3.2. Quality Analysis of Phase Bias*

The two key metrics for analyzing the quality of real-time OSB products are data availability (DA) and stability, where DA can be defined as the ratio of available epochs to all epochs in a day. Figure 2 displays the DA results for the GPS, Galileo, and BDS satellites based on the mean DA of each satellite at two frequencies during a period of 31 days. As can be observed, all GPS and Galileo satellites had a DA of more than 90%, whereas the majority of BDS satellites had DAs of less than 60%. The major reason for the inferior DAs of BDS satellites can be inferred as the subpar quality of the real-time satellite orbit and the offset products for BDS [37,38], which hinder the generation of the phase bias products in real time.

**Figure 2.** Mean DA of GPS (**left**), Galileo (**middle**), and BDS (**right**) satellites.

The mean DA of each satellite for each system is displayed in Table 3, which numerically reflects the DA of each system. Since frequency 1 and frequency 2 are two frequencies that are utilized to estimate the clock offset products of each system [39], the DAs of frequency 1 and frequency 2 are almostsame for each system. The overall DAs of the GPS and Galileo satellites were greater than 97%, while that of the BDS satellites was smaller than 50%. In conclusion, although real-time PPP-AR can be implemented using the OSB products, a consistent and reliable real-time PPP-AR service cannot be guaranteed due to its unstable DA, particularly in the case of BDS satellites. Therefore, a critical issue for real-time PPP-AR is how to avoid or weaken the influence of the absent phase bias products.

**Table 3.** Overall DA of GPS, Galileo, and BDS satellites.

The maximum fluctuation value (MAX) and standard deviation (STD), where MAX is the absolute value of the difference between the maximum and minimum phase biases within one day, can be applied to evaluate the stability of real-time OSB products. Given that the results for the two frequencies were nearly identical, the 31-day data were counted to obtain the mean MAX and STD of frequency 1 for each satellite; the results are shown in Figure 3. With the exception of G01 and G21, all other GPS satellites had MAX and STD values that were better than 0.08 and 0.025 cycles, respectively. The MAX and STD of Galileo were only marginally inferior to those of GPS, with values at around 0.12 and 0.05 cycles, respectively. Apart from C07, C13, and C24, the MAX and STD of the remaining BSD MEO and IGSO satellites were approximately 0.15 and 0.05 cycles, respectively, whereas the MAX and STD of the GEO satellites were noticeably greater than those of the other satellites, exceeding 0.5 and 0.2 cycles, respectively. This was due to the fact that the quality of the satellite orbit and clock offset products for GEO satellites is poorer than that for MEO and IGSO satellites, leading to more satellite orbit and clock offset errors being absorbed by the phase bias. It is worth mentioning that the MAX and STD trends for each satellite were consistent, indicating that fewer outliers were included in the phase bias, which is beneficial to achieving a more robust PPP-AR performance.

**Figure 3.** Mean MAX and STD of GPS (**top**), Galileo (**middle**), and BDS (**bottom**) satellites for frequency 1.

Similarly, the mean MAX and STD values of each system were calculated in order to depict the overall stability of each system numerically; the results are displayed in Table 4. The MAX and STD of the GPS, Galileo, and BDS systems were 0.045 and 0.012; 0.081 and 0.028; and 0.292 and 0.085 cycles, respectively, among which the BDS system was obviously inferior to the GPS and Galileo systems.

**Table 4.** Overall MAX and STD of GPS, Galileo, and BDS satellites.


**5. Conclusions**

Ultimately, Bactrian camels were infected with diverse *Cryptosporidium* species in Xinjiang, northwestern China. Most of these microorganisms have been reported in humans, showing their potential public health relevance and requiring the attention of public health authorities. More molecular studies may be helpful to assess the importance and genetic diversity of *Cryptosporidium* in this region.

**Acknowledgments:** We are grateful to Md Robiul Karim from Bangabandhu Sheikh Mujibur Rahman Agricultural University for his cordial help in editing the English text of a draft of this manuscript.

**Conflicts of Interest:** The authors declare no conflict of interest.

**Author Contributions:** Conceptualization, M.Q. and L.Z.; methodology, M.Q. and L.Z.; validation, M.Q. and L.Z.; formal analysis, Y.C. and Z.C.; investigation, Q.Z., B.J., C.X., and T.W.; software, C.X.; resources, M.Q.; data curation, Z.C.; writing—original draft preparation, Y.C. and Z.C.; writing—review and editing, Y.C. and Z.C.; visualization, M.Q. and L.Z.; supervision, M.Q. and L.Z.; project administration, M.Q. and L.Z.; funding acquisition, M.Q. and L.Z. All authors have read and agreed to the published version of the manuscript.

**Funding:** This study was supported in part by the National Natural Science Foundation of China (31660712, 31702227), the Program for Young and Middle-aged Leading Science, Technology, and Innovation of Xinjiang Production & Construction Corps (2018CB034), and the Key Technologies R&D Programme of Xinjiang Production & Construction Corps (2020AB025).


Department of Applied Physics and Astronomy, College of Sciences, University of Sharjah, PO BOX, 27272 Sharjah, United Arab Emirates e-mail<EMAIL_ADDRESS>
Department of Mechanical and Industrial Engineering, University of Gharyan, Gharyan, Libya e-mail<EMAIL_ADDRESS>
**Keywords** Academic advising · Targeted · Academic performance · Probation · Education quality

# **1 Introduction**

Academic Advising has received considerable attention in recent years by postsecondary educational institutions. Furthermore, academic advising has been identified as one of the factors that can significantly improve the quality of education by positively impacting students' academic performance and increasing retention rates in colleges and universities [1]. For decades, there has been significant research interest in the topic of how academic advising contributes to the academic success of students. Over the years, it has been shown by many researchers that the old theories that attributed students' success to individual characteristics, skills, work ethics and motivational factors are not entirely valid [2]. Recent research findings have highlighted the role of institutions to provide focused academic advising programs, whose primary goal is to provide guidance to students and assist them throughout their selected academic program [3].

The initial focus of academic advising programs focuses on developmental academic advising programs, where the focus is to work on assisting students overcome the overwhelming experience of the college lifestyle [4]. In recent years, several definitions of academic advising have emerged in the literature, the most popular of which is that of Campbell and Nutt (2008) [5], which states "*academic advising acknowledges and supports individual student characteristics, values and motivation*". They further add "*academic advising connects students to campus and helps them feel cared for, both of which have been shown as essential to student engagement*" [5]. Initially, the focus of academic advising programs was on freshmen students, however, it was soon realized that junior and senior students also needed advising as well.

The main objective of academic advising was articulated in several articles to include several key roles:

As mentioned above, initial research on academic advising has focused on freshmen students to help them cope with or overcome the culture shock some of them faced when they started their college years [6]. This was due to several reported cases where students' failure was attributed to their inability to properly adjust to the free-style of college life in the absence of the watchful eyes of their parents. In addition, other factors such as course selection, load and instructor preference were identified as factors contributing to students' performance in their early college years. It was later identified by several researchers such as Light [7] who described "good academic advising" as follows: "*the single most underestimated characteristic of a successful college experience*". Other researchers have echoed the same view adding that effective academic advising plays a crucial part in referring college students to resources and opportunities that "*support their engagement, success, and the attainment of key learning outcomes*" [5]. They further add: "*Academic advising is one of the few campus services that promote student interaction with caring and concerned university employees*". The result of these findings led to the common understanding that academic advising should be the responsibility of the institution that must be added to the services provided by the academic institutions to support students in achieving their academic goals. As stated previously, academic advising contributes to students' success in many ways starting with motivation and support to simply help students feel they are cared for.

Over the past few decades, institutions have taken several approaches to provide their students with effective academic advising programs. These approaches are divided into the following three main categories:

According to Light (2001), developmental academic advising is considered a type of counseling that aims to assist students by addressing their social and intellectual obstacles [8]. The focus of this form of advising is to offer support to students in areas such as environmental and interpersonal interactions, behavioral awareness and problem-solving, as well as decision-making and evaluation skills. Furthermore, academic advising is student-centered academic advising that focuses on the personal needs and growth of students [9]. The goals set for the academic advisor include.

In prescriptive academic advising, the advisor's role is limited to highlighting to the student what classes she/he ought to take in accordance with her/his study plans [10]. The advisor is also asked to provide her/his advisees with an overview of the regulations and bylaws of the institution. Harrison et al. (2009) reported that prescriptive academic advising is a hierarchical process in which the academic advisor assumes control of the information, and the students take on a passive role as recipients of this information [11]. The example often drawn is the advisor takes the role of the doctor, while the student takes the role of the patient accepting the prescription from the "doctor", hence the name prescriptive [12]. Advising is conducted over several optional pre-scheduled meetings between the advisor and the student during which the advisor goes over what the student needs to do next. It should be emphasized here that all approaches include meetings between advisors and students; however, in prescriptive academic advising the discussion is limited to policies, regulations, study plans and degree requirements.

The third approach is intrusive academic advising. It owes its name to the intervention strategy taken to conduct academic advising. It is a proactive approach that focuses on providing (or in some cases limiting) academic advising to students who are "at risk" [13]. It involves well-organized and structured steps that start with identifying the targeted group of advisees to be asked to attend a set of special advising sessions. Besides aiding and guidance to selected advisees, additional goals of intrusive academic advising include [14]

In addition to academic performance, advisors are also asked to monitor student attendance, their behavior in class and study habits. The advantage of intrusive academic advising is manifested in the fact that it utilizes a systematic approach that solves problems such as the reluctance of some students to participate in or take advantage of academic advising. In addition, it takes advantage of the fact that many college students navigate through college depending on other means of academic advising, especially peer advising, which is considered by many as the most popular form of advising among college students.

At the University of Sharjah (UOS) (Sharjah, United Arab Emirates), academic Advising has been conducted in a prescriptive approach, where every student is assigned to an academic advisor upon enrollment in her/his academic program. Advisors are asked to meet with the students periodically to explain to them the rules and regulations and provide them guidance/assistance with registering for the right courses to ensure they follow their study plan and graduate on time or at the least possible time. Academic advisors are selected among instructors who are very familiar with study plans and well-versed in the field. As a result of the rapid increase in the number of students, academic advisors may find themselves overwhelmed and, at times, unable to meet the expectations established by university academic advising programs. In addition, it has been reported that students do not show up for academic advising sessions due to various reasons, including their reluctance to admit that they need help. To deal with this, the university has experimented with the "pin-code approach", where students are not allowed to register until they visit their academic advisor and get her/his approval on the set of courses they need to sign up for. This approach did not work very well because of the added logistics and administrative layers, which hindered efforts to improve the online registration process. In addition, students who were progressing well in their academic programs and did not feel they need to meet with their academic advisor were not happy with the additional delays they were experiencing. In the end, the University of Sharjah decided to limit the pin-code approach to students under academic probation.

To deal with this, the Registration Department took the lead in offering a special proactive academic advising program, which is a mix of the three previously mentioned approaches. The approach focuses on students who are under academic probation. The approach utilizes the online tools available at Learning Management Systems (LMS) available at the university. The objective of this endeavor is to develop a creative academic advising approach that provides students who are under academic probation with adequate advising, counseling, guidance and much more. Rather than rely on academic staff who are already overwhelmed with teaching load and administrative assignments as well as research responsibilities, the Registration Department took on the responsibility to establish a "mixed approach for academic advising" that relies heavily on the utilization of technological tools in conducting academic advising. As will be detailed in the next section, this creative approach has many advantages, the most important of which is direct communication with the students through LMS tools, which ensures confidentiality as well as personalized emails.

# **2 Targeted Approach for Academic Advising**

As briefly mentioned in the introduction, the approach targets academically challenged students, i.e., students under academic probation, with the following goals:

Targeting students under probation was taken to be a testing phase of the approach with plans to expand the approach to include *students at risk*, i.e., those with a CGPA less than 2.3.

The targeted students were selected three weeks into the semester after all registration processes are completed. The delay was necessary to account for incomplete grades and any changes in the CGPA of the students due to various reasons. A report is extracted from the SIS database containing all students who are under academic probation in all departments. Figure 1 shows a typical example of one of the batches in the Fall of the 2014–2015 academic year.

**Fig. 1** Distribution of students under probation in every college, the overall percentage of students under probation is about 10%. The data was taken from the Student Information System (SIS) at the University of Sharjah

It should be noted here that the percentage of students who are under academic probation at the University of Sharjah hovers around 10%, which is similar to that reported in the literature. After compiling the lists of the students, a course page is created on the Learning Management System (Blackboard). Students were automatically enrolled into the program, and notification emails were sent to everyone outlining the objectives of the program, the dates of each activity and the deadlines associated with the assignments and activities.

To attract the students, the program was given the name "Academic Success Program", which gave it a positive spin. Students are invited to take part in the following parts:

The first activity of the Academic Success Program is the online "Entrance Survey", which is made up of a combination of MC questions, short answer questions and open-ended responses. In addition to demographic questions, the survey was constructed to gain an insight into the main challenges the students face, and the reasons that led to their sub-bar academic performance. The questions also focus on students' study habits, utilization of LMS (Blackboard), interactions with instructors outside classes, test-taking strategies, time management and participation in extracurricular activities, such as sports, social and cultural activities. Students are also given the opportunity to list additional challenges, including domestic and financial difficulties. The survey was conducted online using the tools available on the Blackboard. It should be noted that students were asked to write their student number at the beginning of the survey for analysis purposes acknowledging full anonymity. Students were asked to fill out the online survey before they attend the workshops.

In the second part of the program, students were asked to attend a workshop on policies and procedure pertaining to academic probation. In addition, students were trained on how to avoid academic warnings and how to overcome their academic probation status. Students are also taught how to calculate their GPA and to predict how much they need to score in their current courses to raise their TGPA and CGPA. In addition, the workshop highlights policies on repeating courses and advantages of department/program changes.

In the third part of the academic success program, students are given an interactive motivational seminar conducted by one of the senior instructors. The seminar is entitled "You are not alone". The focus of the presentation is engaging the students in a discussion type of seminar during which students are encouraged to talk about their challenges and difficulties. The instructor steers the discussion using factual stories and figures and success stories. Upon the completion of the workshops, students are asked to fill out a survey containing quiz-like questions on the material covered. In addition to understanding the policies and regulations, the purpose of the exit survey is to gauge the students' understanding of the real challenges they face and how to deal with such challenges.

# **3 Results and Discussion**

A total of 320 students participated in the program. The demographics of the students showed that the number of male and female students participating in the program was 58% (M) to 42% (F). Students from all colleges took part in the program with the highest number of students from the College of Engineering, which is mainly due to the fact that the College of Engineering has the largest number of students in the University of Sharjah. Data on high school curriculum and ethnic background is currently being examined in another research project and will be reported in due time.

Careful examination of the entrance survey showed that most students (about 76%) go on probation by the end of the second semester. While this is typical and attributed to many factors, which include nonacademic issues such as students' inability to cope with the free-style and responsibility-free college environment [4, 8, 12]. This is evident from the above than average absence and irregular study habits the students have reported. For example, over 67% of the students have reported that they never visited their instructors during office hours, while over 73% reported limited use of the material available on the Blackboard. Over 68% of the students reported they never felt prepared for the exams and experienced high levels of anxiety. Students' involvement in extracurricular activities is very limited, with less than 20% participating in sports, cultural and social activities. When students were asked to list the reasons behind their poor academic performance, the answers varied with the following common issues:

Surprisingly, when students were asked if they knew what to do to get out of their low academic standing, 78% of them answered yes, they know. One interesting finding is highlighted when students were asked about their level of participation in discussions during lectures, especially answering questions 68% said they did not participate nor did they answer questions in class. These numbers support research evidence and findings that showed a higher percentage of students under probation tend to be among shy and reluctant students [6]. In conclusion, entrance survey responses have revealed that students are facing a number of challenges, some of which are academic while the remaining can be considered as social distractions, personal and family issues, poor time management, poor study habits and healthrelated issues.

During the interactive workshop and motivational seminar, the focus was to highlight the UOS policies on probation, calculating and forecasting GPA and CGPA and providing students with tips on how to improve academic standing by repeating courses. The workshop was interactive where students were encouraged to participate and ask questions.

In the second part of the workshop, students were asked to attend a motivational interactive seminar entitled "You are not alone". The seminar was given by senior instructors who have an outstanding academic advising track record and are wellacquainted with the issues UOS students face, especially those related to cultural challenges and peer pressure. The objective of the workshop is to list some facts and statistics about academic probation within UOS (Fig. 2), available support and motivate the students to overcome their poor academic performance. Some of the key takeaways from the workshop include.

In addition, the instructor also highlights the fact that institutions' approach to academic probation warnings, especially the first two warnings as a signal for immediate action accompanied by immediate actions aimed at overcoming academic

**Fig. 2** A slide from the motivational seminar highlighting the distribution of the students under probation among colleges. The figure was taken from the motivational PowerPoint presentation, which was prepared by the authors

**Fig. 3** Announcement for ASP, workshop and motivational seminar. The figure was taken from the promotional posters, which were prepared by the authors

probation status. It was highlighted during the seminar that upon receiving academic warnings, students are expected to "hit the panic button" to.

After that, instructors listed the five main contributors to academic probation, which are commonly reported in the literature. These include.

Students are then invited to discuss or share their own experiences with any of the above factors. During the open discussions, students reported additional factors, the most important of which were those linked to the conservative Arabic culture. The first factor was "getting parents involved"! It was evident from the discussion, and, due to various reasons, students tend to hide their academic difficulties from their parents hoping that they can overcome them on their own. Oftentimes, they fail to do so, and the problem is compounded. The second factor is linked to students' reluctance to talk about their problems to their peers or academic advisors simply because of fear of the consequences. This is more pronounced among female students. At the end of the session, students were given enough time to ask questions and raise concerns in the presence of the registration and admission directors and the dean of academic support service.

The last part of the "Academic Success Program" is the exit assessment survey, where students were asked to answer several questions aimed at.

# **4 Impact of ASP on the Academic Performance of the Students**

To measure the impact of the proactive *mixed approach for academic advising*  approach on the academic performance of the students, we conducted the following two exercises:

For the comparison to be valid, we selected students with almost the same background, i.e., the same academic CGPA, the same college or program and the same level of study. Figure 4 shows the gain of the selected group of students who attended all activities of the Academic Success Program.

**Fig. 4** The students' CGPA gain after taking part in all activities of the Academic Success Program

It is evident from Fig. 4 that our *mixed approach for academic advising* approach had a great positive impact on the students. More than 75% of the students were able to raise their CGPA above 2 and overcome their academic probation status. This result is even more pleasing when the results were compared to the second group of students who did not attend the program, where only 34% of these students were able to improve their academic standing beyond 2.

# **5 Conclusions**

The mixed approach for the academic advising program at the University of Sharjah was conducted twice in the academic years 2014–2015 and 2015–2016 with overwhelming success. The program catered to students who are currently under academic probation regardless of the number of academic warnings they have. Except for the workshop and motivational seminar, all surveys and supporting material were communicated to the students via the Learning Management System (Blackboard).

The factors contributing to students' academic struggles were identified. These will be communicated to higher authorities at the university to design special advising/counseling programs for those who need such services. Students experiencing financial difficulties were directed to proper financial aid offices and special funding agencies.

Students learnt "tricks of the trade" where they were not only exposed to the details of the UOS bylaws and policies, but they were taught how to maneuver within the study plan to avoid academic probation. Examples include repeating courses, mixing up courses in accordance with the level of difficulty, student issues and petitions, grievance requests and change program requests. In addition, students learnt how to calculate and forecast their GPA, CGPA and much more.

The impact of the special academic advising program was very pleasing and exceeded the expectations of the authors. Over 75% of the students who took part in the program had a significant increase in their CGPA and were able to overcome their academic probation status. The results were very pleasing not only to the authors but also to the university administration.

Organizers faced several challenges, the most important of which is the lowerthan-expected attendance rates. The reasons behind this may be attributed to the fact that students were reluctant to participate in the program so their peers do not find out about their academic status. In addition, those who missed the activities reported logistical issues, such as the time and location of the workshop. This will be resolved in the future by offering the program at different times during the semester. In addition, we are planning to expand the program to include more categories of students above the current cutoff, i.e., students with a CGPA above 2.3.

**Acknowledgements** The authors would like to acknowledge and appreciate the support provided by colleagues at the Registration Department, the Academic Computing Section at the Information Technology Centre and the Admissions Department. Special thanks go to the chancellor of the University of Sharjah, Prof. Hamid Al Naimiy, for his support and funding for the project.

# **References**

**Open Access** This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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**2.5 Various microbial catalysts**

*Current Topics in Biochemical Engineering*

to be controlled.

**2.4 Other types of MFCs**

efficiency by the mediator, it requires a high concentration, but because of its high toxicity, it has a strong influence on the cells; therefore, the level of use is necessary

Finally, the cathode solution is explained as follows. The electrons generated at the anode are carried to the cathode, where the reduction reaction takes place. When oxygen, the most common electron acceptor, is used as an oxidizing agent, aeration is necessary because oxygen has low solubility (about 8 mg/L DO). There are cases where oxygen generation by the photosynthesis of algae is used for oxygen supply [40, 41]. In the reaction at the cathode, H2O is produced by oxygen, whereby the electrons were carried from the anode via an external circuit and protons were carried from the anode solution via CEM. There is also a report that the addition of hydrogen peroxide leads to an improvement in power generation [42]. Besides oxygen, there are various electron acceptors [43]; for example, an oxidizing agent such as iron ferricyanide is also used for the cathode. In many cases, the ferricyanide has a high mass transfer efficiency and a high cathode potential so that a high output can be obtained. The combination of carbon electrodes and ferricyanides to achieve power 50–80% higher than the combination of Pt/carbon electrodes and oxygen was reported [44]. In the case of using ferricyanide, once the trivalent iron ion receives the electrons, it becomes divalent, and when it delivers the electrons to oxygen, it reverts to the trivalent state. However, the latter reaction is less likely to occur owing to the low solubility of oxygen. Ferricyanide is an excellent electron acceptor, but owing to its toxicity, its use is generally limited to the laboratory. Other than oxygen and ferricyanide, there are also many candidates, for example, nitrate, persulfate, permanganate, and manganese dioxide. It is also possible to use the nitrate contained in the wastewater because its redox potential is close to that of

oxygen, and then, the nitrate is reduced to nitrogen gas at the cathode [43].

MFCs are typically divided into a dual-chambered cell described above and a single-chambered cell (**Figure 5**). In the latter, a membrane-type positive electrode with oxygen permeability called an air cathode is used [45]. The electrode is coated with the platinum catalyst, and H2O is produced from the oxygen permeated from the atmosphere, the proton in solution, and the electron from the anode. However,

**56**

**Figure 5.**

*Other types of MFCs. Med: mediator, CEM: cation exchange membrane.*

Various microorganisms have been studied for a long time since the first experiments on *S. cerevisiae* and *E. coli* [4]. The classification of these catalysts is largely based on the purity and complexity of the cultured microbial systems. Many different microorganisms are used in the pure system [37, 38, 47, 48]. *S. cerevisiae* is a safe microorganism used in foods and can grow even in the presence of a high concentration of sugar, sulfate, and ammonium nitrogen. MFCs show high performance when using *S. cerevisiae* and glucose as a catalyst and a fuel, respectively [43]. *E. coli* can also ferment sugar well and is used for the study of MFCs using glucose as a fuel. Although it can generate electricity without a mediator, in the present situation, the power generated is low, so an artificial mediator is added in order to achieve better performance. Besides the two examples, there are also *Pseudomonas aeruginosa*, *Enterococcus faecalis*, *Rhodoferax ferrireducens*, *Geothrix fermentans*, *Shewanella* species, *Geobacter* species, *Clostridium* species, and sulfatereducing bacteria. The possibility of utilizing extremophilic microorganisms is also being studied [49], and to add a new perspective to power generation by MFCs, the utilization of photosynthetic bacteria at the anode is also examined [40]. One of the advantages of these MFCs is the elimination of carbon dioxide released into the atmosphere. Meanwhile, in complex systems, the use of various wastewater and waste sludge has been reported [25, 37, 46, 50]. Many studies on bacterial communities under the control of MFCs have been conducted using those aforementioned resources. It is thought that the bacteria belonging to the phylum Proteobacteria were involved in power generation [51, 52]. However, owing to the complexity of bacterial interactions, their contribution to power generation within these communities is not well understood yet.

In such a research situation, there are relatively many examples of research on *S. oneidensis* and *G. sulfurreducens*, and the details of their power generation mechanisms are being clarified. *S. oneidensis* can produce self-synthesized mediators, like flavin compounds. The strain has not only such a mediator but also an extracellular electron transport system involved in power generation. This system, present from the inner membrane to the outer membrane, plays a role in carrying the electrons to the extracellular receptors (i.e., the electrodes in this case) by contacting them directly. In particular, cell-surface-localized cytochromes (MtrC and OmcA) are

important components for the electron transfer [53]. On the other hand, *G. sulfurreducens* has electrically conductive pili, called nanowires, which can transfer electrons to extracellular electron acceptors on the cell surface [54]*. S. oneidensis* also has an electrically conductive structure similar to the pili, but its structure is different, whereby the membrane structure containing the cytochrome protein described above was raised [54]. In any case, it has been confirmed that electrons can be delivered via such protrusions. It is expected that new developments will be made in the future, such as introducing the genes related to these mechanisms into other species, especially model organisms, such as *E. coli* and *S. cerevisiae*.


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## Meet the editor

Dr. Muhammad Zubair is an associate professor in the Department of Mechanical and Nuclear Engineering, University of Sharjah, United Arab Emirates. Prior to this role, Dr. Zubair worked as an assistant professor and graduate program coordinator at the University of Engineering and Technology Taxila, Pakistan. Dr. Zubair's interests include nuclear reactor safety, accident analysis, reliability and risk analysis, digital instru-

mentation and control, and radiation detection and measurements. He has a strong research background supported by publications in international journals, conferences, and book chapters. He is engaged in different research projects including one coordinated by the International Atomic Energy Agency (IAEA). He also serves as editor, associate editor, and technical committee member for international journals and conferences.

Contents

**Section 1**

**Section 2**

**Section 3**

**Section 4**

Uncertainty

**Section 5**

Reliability

*and Amadou Ouane*

Water Reactor (PWR)

**Preface XI**

Introduction **1**

**Chapter 1 3**

Reliability for Optimal Systems **9**

**Chapter 2 11**

Reliability and Risk Analysis **35**

**Chapter 3 37**

Maintenance and Uncertainty Analysis **45**

**Chapter 4 47**

Reliability for Digital and Analog Systems **63**

**Chapter 5 65**

Introductory Chapter: An Overview of Reliability and Risk Analysis

The Optimal System for Complex Series-Parallel Systems with Cold Standby Units: A Comparative Analysis Approach

Importance Analysis of Containment Spray System in Pressurized

Optimal Maintenance Policy for Second-Hand Equipments under

Digital On-Chip Calibration of Analog Systems towards Enhanced

*by Michal Sovcik, Lukas Nagy, Viera Stopjakova and Daniel Arbet*

*by Ibrahima dit Bouran Sidibe, Imene Djelloul, Abdou Fane*

*by Muhammad Zubair and Eslam Ahmed*

*by Ibrahim Yusuf and Ismail Muhammad Musa*

*by Muhammad Zubair and Priyonta Rahman*

### Contents

Preface

This book presents the state of the art in reliability and risks analysis engineering from a product lifecycle standpoint. The book provides comprehensive insights into optimization of systems, digital and analog systems, uncertainty quantification, and maintenance as well as risk analysis. The book is intended for senior undergraduate and postgraduate students in related engineering programs such as mechanical engineering, manufacturing engineering, industrial engineering, and engineering management programs, as well as for researchers and engineers in the reliability and

The book is structured in a way that the optimization methods for components and systems are described first. This is because components are the most basic building blocks of engineering systems. The techniques discussed in this chapter provide a comprehensive overview of some reliability features of series-parallel systems under minor and complete failure. Failure and repair time of all units were assumed to be exponentially distributed. Explanatory expressions for system characteristics such as system availability, mean time to failure (MTTF), and profit function and cost benefits for all configurations have been obtained and validated by performing numerical experiments. The next chapter describes reliability analysis in the nuclear industry. It investigates the Containment Spray System (CSS) by using the fault tree analysis (FTA) technique to obtain results of the top event probabilities, minimal cut sets (MCS), risk decrease factor (RDF), fisk increase factor (RIF), and

The chapter on maintenance and uncertainty addresses a maintenance optimization problem for remanufactured equipment that will be reintroduced into the market as secondhand equipment. It discusses and derives an optimal maintenance policy for such equipment to overcome the uncertainty of reparation action. Moreover, the chapter presents experiments and evaluates different life cycles of technologies according to their obsolescence processes (accidental or progressive vanishing) on the optimal operating condition. The last chapter on reliability for digital and analog systems deals with a digital method of calibration for analog-integrated circuits as a means of extending its lifetime and reliability, which consequently affects the reliability of the analog electronic system. The chapter reveals the implementation of an ultra-low voltage on-chip system of the digitally calibrated variable-gain

The editor and the contributors (authors) would like to thank Ms. Dolores Kuzelj

**Muhammad Zubair**

University of Sharjah,

Sharjah, United Arab Emirates

Department of Mechanical and Nuclear Engineering,

amplifier (VGA), fabricated in CMOS 130 nm technology.

risk fields.

sensitivity analysis.

and the staff at IntechOpen.