4.6.1. Cell Cultures

The L929 mouse fibroblast cell line and the National Collection of Type Cultures (NCTC) human keratinocyte cell line were obtained from the American Type Culture Collection (LGC Standards srl, Milan, Italy). Cells were cultured at 37 ◦C in a humidified, 5% CO2 atmosphere, in high glucose Dulbecco's modified Eagle's medium (D-MEM) with glutamax (Euroclone, Milan, Italy), which was supplemented with 10% FBS (Euroclone) with penicillin/streptomycin as antibiotics.

#### 4.6.2. Cell Growth and Cell Adhesion

To evaluate cell growth on SCM-coated plates, experiments were performed in quadruplicate on 96-well plates. Both L929 and NCTC cell lines were plated at a density of 5000 cells/well on 96-well plates pre-coated with F1, F2, F3, and F4. *C. reniformis* FSs extracts, prepared, as described in Section 4.4. Conversely, controls were grown onto rat tail standard collagen coated plates, prepared, as already described in the same paragraph. Cells were incubated for 3 days, 6 days, and 15 days at 37 ◦C in complete medium. At the end of the experiments cell viability was assayed by the MTT test (0.5 mg/mL final concentration), as already reported [81]. For the evaluation of cell adhesion on FS-coated wells, experiments were performed in duplicate on 24-well plates. Both L929 and NCTC cell lines were plated at a density of 50,000 cells/well on 24-well plates that were pre-coated with F1, F2, F3, F4 extracts, or rat tail standard collagen as control. Cells were allowed to adhere for 16 h at 37 ◦C in complete medium and then the MTT test was performed as well to estimate the attached cells when compared to control cells on uncoated wells. Data are means ± S.D. of four independent experiments.


**César Quijada**

Departamento de Ingeniería Textil y Papelera, Universitat Politècnica de València. Pza Ferrándiz y Carbonell, E-03801 Alcoy (Alicante), Spain<EMAIL_ADDRESS>Tel.: +34-966-528-419

Received: 12 May 2020; Accepted: 18 May 2020; Published: 20 May 2020

**Abstract:** Intrinsically conductive polymers (CPs) combine the inherent mechanical properties of organic polymers with charge transport, opto-electronic and redox properties that can be easily tuned up to those typical of semiconductors and metals. The control of the morphology at the nanoscale and the design of CP-based composite materials have expanded their multifunctional character even further. These virtues have been exploited to advantage in opto-electronic devices, energy-conversion and storage systems, sensors and actuators, and more recently in applications related to biomedical and separation science or adsorbents for pollutant removal. The special issue "Conductive Polymers: Materials and Applications" was compiled by gathering contributions that cover the latest advances in the field, with special emphasis upon emerging applications.

**Keywords:** polyacetylene; polyaniline; polypyrrole; PEDOT-PSS; copolymers; charge transport models; silica gel composite; carbon composite; antimicrobial; drug release; sensors; adsorption

Intrinsically conductive polymers (CPs) are a fascinating family of organic materials that can be easily synthesized with a large diversity of chemical structures and a wide variety of micro- and nano-morphologies in order to obtain tailored macroscopic physical and chemical properties [1]. The breakthrough discovery of polyacetylene, the first conducting polymer, by Heeger, MacDiarmid and Shirakawa in 1977 (jointly awarded the Nobel Prize in Chemistry for 2000), opened up a completely new field of research, tracking the boundaries between chemistry and solid-state physics. Since then, interest in this intriguing class of polymers has expanded incessantly to become a well-established area of highly dynamic, multidisciplinary research.

From a chemical viewpoint, CPs are π-conjugated organic polymers, that is to say, compounds with their skeletal carbon atoms linked by both σ-bonds and the extended overlap of π-electron orbitals. As a result, neutral CPs show a semiconductor electronic structure with a completely filled π-band (valence band) and an empty π\*-band (conduction band), separated by an energy gap of the order of 1 eV. The intrinsic conductivity arises from *doping*, i.e., when electrons are withdrawn or injected onto the conjugated polymeric chain, while the overall electroneutrality is retained by the incorporation of counter ions, the so-called *dopants*. The doped state is achieved by simple oxidation (p-doping) or reduction (n-doping) reactions, leading to the formation of delocalized charged structural defects (polarons, bipolarons, solitons) that are energetically located within the energy gap and work as charge carriers. Thus, the electrical conductivity of these polymers can be tuned over the full range from insulation to metallic by facile and reversible chemical or electrochemical doping/de-doping.

Jointly with simple control of the doping level, the electronic structure of CPs can be "engineered" by designing novel chemical structures at the molecular level through judicious synthetic chemical or electrochemical strategies, thus enabling a set of desired and tunable optical, electronic and redox/electrochemical properties. This concept has evolved to produce a vast repertory of chemically diverse, lightweight and flexible tailor-made polymer structures, showing attractive properties for a broad spectrum of applications with high technological impact, many of them reaching the marketplace.

Some examples are their use as key materials in thin-film transistors, light-emitting diodes and solar cells, electrochromic displays, (bio)sensors and actuators, secondary batteries and supercapacitors or artificial muscles, just to cite a few [1]. Over the past few decades, some other new applications in biomedical science and tissue engineering, enhanced solid-phase extraction or as adsorbent/ion-exchange materials for environmental issues have emerged as promising growth areas.

In spite of the obvious advantages of CPs over their inorganic semiconducting and metallic counterparts in terms of chemical diversity, tunable conductivity, low density and cost and flexibility, much work is still to be done in order to overcome their inherent limitations regarding solubility/processability, conductivity and long-term stability. For this, the development of CP-based hybrid composites with enhanced properties and controlled shape and morphology has become a flourishing area of discovery within the field. Typical examples are CP nanocomposites with a variety of carbon nanomaterials, metal oxide nanoparticles, or hydrogel inorganic matrices.

The Special Issue "Conductive Polymers: Materials and Applications" was launched to cover the latest advances and developments in the synthesis, characterization, structure–properties relationship and applications of intrinsically conductive polymers, with particular attention given to novel functionalized polymer/copolymer structures or novel CP–inorganic composite materials and their use in emergent applications. The nine articles included in the issue touch di fferent aspects of the goals pursued. A brief summary of their main achievements and conclusions is given below.

In undoped trans-polyacetylene, bond alternation has been widely recognized as the obvious consequence of the existence of two-equivalent degenerate ground states arising from the Peierls instability. Hudson [2] critically reviewed the available experimental studies (X-ray di ffraction (XRD), nuclear magnetic resonance (NMR), Raman or infrared (IR) data) that support the existence of bond alternation and concluded that their results are compromised by the presence of finite chains or finite conjugation segments or other ambiguities. The author proposed a novel synthetic route with the aid of urea inclusion complexes to produce fully extended all s-trans polyacetylene, free of finite-chain polyene impurities.

In recent years, the application of conducting polymer-based materials to biomedical science and healthcare has been the subject of intense research activity. The papers by Robertson et al. [3] and Shah et al. [4] fall within this category. In the former, the authors investigated the activity of polyaniline (PANI) and poly(3-aminobenzoic acid) (P3ABA) as potential antimicrobial agents against *Escherichia coli* and *Staphylococcus aureus*. Both CPs showed high bactericidal action in suspension, but their e fficacy was depressed when applied to agar (an adsorbent surface) and especially to styrene-ethylene-butyrene-styrene films (a non-adsorbent surface). This behavior was attributed to the decreasing contact occurring between bacterial cells and CPs on going from solution to adsorbent surfaces to non-adsorbent films. The remaining activity of P3ABA-containing surfaces was reported to be superior to that published for triclosan, a popular antimicrobial agent, which encouraged the use of this polymer in cost-e ffective antimicrobial surfaces to break pathogen transmission pathways in hospitals. On the other hand, Shah et al. [4] reported the use of polypyrrole (PPY)-based coatings loaded with clinically relevant drugs as systems for switchable drug delivery. The anti-inflammatory dexamethasone phosphate (DMP) and the antibiotic meropenem (MER) were loaded as the anionic dopants. Analysis by energy-dispersive X-ray (EDX) spectroscopy, Fourier transform infrared (FTIR) spectroscopy, ultraviolet–visible (UV–vis) spectroscopy, XRD and electrochemical techniques (cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS)) confirmed the presence of the drugs in the films. The authors showed that the electrochemically-triggered release of drugs in vitro was enhanced relative to the passive delivery from non-stimulated samples. The higher improvement observed for MER was attributed to its higher hydrophilicity and polar character, which makes it more responsive to electrically stimuli within the PPY matrix.

The application of CPs and their composites to the detection of biologically active molecules of interest in medical diagnosis, food or plant analysis is the subject of another three articles. A feature paper by Dkhili et al. [5] reported the electrosynthesis of novel, chemically stable

aniline-piperazine copolymer films that exhibited reversible hydroxyl-ketopiperazine redox transitions between the well-known redox processes of polyaniline. The new copolymer material showed reproducible linear response and high sensitivity for the analysis of dopamine and ascorbic acid, thus being potentially applicable to amperometric sensors. Hybrid materials consisting of silica gel matrices modified with CPs have found interesting applications in analytical science. Djelad et al. [6] described the synthesis of SWCNT-modified silica films by electro-assisted deposition from sol-gel precursors, and their further modification by reactive electrochemical insertion of PEDOT-PSS from the monomer and dopant constituents. The resulting SWCNT@SiO2–PEDOT-PSS composite doubled the electroactive surface area and exhibited a threefold increase in the heterogeneous rate constant of ferrocene, a common electron shuttle in electrochemical biosensors. Sowa et al. [7] modified commercial silica gel particles with PANI by chemical polymerization. Confocal Raman microscopy revealed that PANI preferentially deposited inside the inner pores of the silica particles. The authors optimized an experimental procedure for the extraction and quantification of triterpenic acids from plant samples by using PANI-modified silica gel as the sorbent in dispersive and matrix solid-phase extraction (d-SPE and MSPD) coupled to diode array detection high-performance liquid chromatography (DAD-HPLC).

Finally, the special issue also illustrates the use of CP-based composites as adsorbent materials for the removal of environmentally hazardous chemicals. In a series of two papers, Muhammad et al. [8,9] examined the adsorption behavior of PANI-Fe3O4 composites for the removal of cationic Basic Blue 3 (BB3) [8] and anionic Acid Blue 40 (AB40) [9] dyes from aqueous solution. The composite materials were fully characterized by scanning electron microscopy (SEM), FTIR, EDX, UV and XRD [8]. The adsorption of BB3 and AB40 obeyed Langmuir and Freundlich isotherm models, respectively, while kinetics was of the pseudo-second order. PANI-Fe3O4 composites showed enhanced adsorption capability for BB3 when compared to the individual components and other typical low-cost adsorbents. This e ffect was associated with an increase in surface area and pore volume of the hybrid material. Instead, the composite material was a less e fficient adsorbent for AB40 than pure PANI, probably because repulsive forces from Fe3O4 oxygen lone pairs o ffset the electrostatic attraction between oppositely charged sites of PANI and the dye. Quijada et al. [10] electro-synthesized PANI-activated carbon cloth (ACC) composites in a filter-press cell. Based on SEM, X-ray photoelectron spectroscopy (XPS), N2 adsorption, thermal analysis, CV and direct current (DC) conductivity data, the authors suggested that thin polymer films containing a small amount of phenazine/phenoxazine segments formed within the micro- and mesopores of the carbon fibers, thus showing enhanced conductivity and pseudocapacitance. In heavily loaded PANI-ACC, a nanofibrous thick coating developed which caused strong pore blocking, diminished surface area, and loss of conductivity. Composites with moderate PANI loadings showed promoted pseudo-second order adsorption rate of Acid Red 27 from aqueous solution, which was related to the electrostatic interaction between dye-negative sites and positive N sites in acid-doped PANI.

**Conflicts of Interest:** The author declares no conflict of interest.


**Author details**

*Prebiotics and Probiotics - Potential Benefits in Nutrition and Health*

eters were observed when the groups were compared [101].

**of aflatoxin B1 (AFB1) in poultry**

of AFB1.

growth [99, 102] (**Table 9**).

**4. Conclusions**

the mechanism.

**Acknowledgements**

**3.3 The use of** *Bacillus***-DFM candidate to prevent the toxic effects**

Aflatoxin B1 (AFB1) is the predominant mycotoxin produced by several species of *Aspergillus* [97]. This mycotoxin has hepatotoxic and hepatocarcinogenic effects [98]. It has been reported that AFB1 has detrimental effects on performance parameters, which can cause serious economic problems in the poultry industry [99]. Therefore, the control of AFB1 is critical for producers. In this sense, the use of probiotics has proven effective in preventing and controlling the toxic effects

An *in vitro* study performed in our laboratory showed that 3 of 69 *Bacillus* spp. candidates were capable of biodegrading AFB1 since they reduced the fluorescence and area of clearance around each colony [100]. However, when these *Bacillus* spp. were tested in broiler chickens, no significant differences in performance param-

Despite the previous results, the *Bacillus*-DFM candidate spores formed by the isolate of *Bacillus subtilis* and the two of *Bacillus amyloliquefaciens* were included in the diets containing AFB1 to determine their effect on performance in broiler chickens fed with 2-ppm AFB1-contaminated diet [unpublished work from our laboratory]. The results are promising since the *Bacillus*-DFM improved performance of broilers, and even, there were no significant differences between the negative control (NC) and DFM group. It was due to the capacity of DFM to produce certain essential nutrients, extracellular enzymes, and growth factors to promote host

As it can be seen, probiotics could be considered a potential alternative to the use of antibiotics in poultry since it has been reported that they can improve the performance, as well as prevent and control enteric pathogens in poultry. However, their applications depend on the type of microorganism. In this regard, since lactic acid bacteria (LAB) are very sensitive to pelletizing processes for feed production (heating), environmental factors, and the low pH of the stomach, as well as the presence of bile salts in the small intestine, their administration in a single dose could be the most viable application especially to prevent bacterial diseases in both *in ovo* and broiler chickens. In contrast, *Bacillus* spp. direct-fed microbials (DFM) can be a better alternative since they are more stable because they can form spores. Therefore, DFM can be included in the feed, and, in addition, the production costs are lower than the microencapsulation and freezing or lyophilization processes that are used to maintain the viability of LAB. Finally, probiotics as *Bacillus*-DFM have also shown beneficial effects in preventing and controlling toxic effects of AFB1. Although the mechanisms by which the DFM reduce the effect of AFB1 are still known, our laboratory is working to elucidate

This research was supported by the Arkansas Biosciences Institute under the project: Development of an avian model for evaluation early enteric microbial colonization on the gastrointestinal tract and immune function. The authors thank

the CONACyT for the doctoral scholarship number 270728.

**228**

Daniel Hernandez-Patlan1 , Bruno Solis-Cruz1 , Billy M. Hargis2 and Guillermo Tellez2 \*

1 Laboratorio 5: LEDEFAR, Unidad de Investigacion Multidisciplinaria, Facultad de Estudios Superiores (FES) Cuautitlan, Universidad Nacional Autonoma de Mexico (UNAM), Cuautitlan Izcalli, Estado de Mexico, Mexico

2 Department of Poultry Science, University of Arkansas, Fayetteville, AR, USA

\*Address all correspondence to<EMAIL_ADDRESS>
© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


**5. Conclusions**

The multilayered AlCrN hard coating with the Cr adhesion and the gradient CrN interlayer was deposited on the SS substrate AISI 316L in a dominating cubic CrN structure by LARC PVD. The protective efficiency of the gradient AlCrN PVD coating increases up to 99.8% indicating a passivation layer developed through Al-based reaction products due to the reduced penetration rate of the corrosive media. The presence of surface defects (pinholes, inclusions, etc.) does not significantly affect the failure of coating in static corrosive conditions.

Tribo-corrosion tests performed in 3.5 wt % NaCl solution allows evaluation of the coating reactivity due to the AlN passivation effect combined with the presence of Al-based corrosion products. Change in OCP from −0.18 down to −0.3 V vs. Ag/AgCl after about 2 h-long sliding test under 1 kg load is related to the unprotected layer of Cr rich gradient CrN interlayer due to the partially lost layer of the AlCrN. An appearance and evolution of severe damages in the coating causes OCP shifting down to −0.42 V vs. Ag/AgCl at the beginning of sliding test under 3 kg load, indicating a mechanically initiated reaction with free Al from the AlN and free Cr from the AlCrN and CrN interlayer. The CoF of the coated samples remains about 25% lower (about 0.6) even after partial degradation as compared to the pristine SS under threefold lower load, indicating a reliability of the coating in tribo-contact even after a loss of chemical protection.

**Author Contributions:** Conceptualization, M.A. and I.H.; Methodology, J.B.; Software, T.R.; Validation, M.A., S.B. and I.H.; Formal Analysis, J.B.; Investigation, J.B.; Resources, M.A., S.B. and T.R.; Data Curation, J.B.; Writing-Original Draft Preparation, J.B.; Writing-Review & Editing, M.A. and I.H.; Visualization, J.B.; Supervision, M.A., I.H.; Project Administration, M.A.; Funding Acquisition, M.A. and I.H.

**Funding:** This research was supported by the Estonian Research Council under the personal grant (PUT1063) (I. Hussainova), Estonian Ministry of Higher Education and Research under Projects (IUT19-29 and IUT19-28), the European Union through the European Regional Development Fund, (Project TK141) and TTÜ base finance projects (B54, B56 and SS427) (M. Antonov).

**Acknowledgments:** The authors would like to thank Heinar Vagiström for the help with preparation of AlCrN PVD coatings. The authors would also like to thank Rainer Traksmaa and Arvo Mere for the help with XRD measurements.

**Conflicts of Interest:** The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.


**1. Introduction**

The pure sciences, such as mathematics and physics, have been fundamental in evolution and human survival; the great researchers in these areas were the first Nobel Prize winners in the history of world discoveries. Discoveries that have undoubtedly marked a line in time, in the postulations of the different theories of physics have led to technological advances in different areas of science, whose origin has been observational and experimental from the beginning [1].

At this point in history, the different questions, predictions, and estimates related to the behavior of a certain event or circumstance began to take shape, which was references to other research areas, especially in the medical sciences, for the study of diseases, from the causative agents to the damage caused to health [1].

These pure sciences gave rise to computational sciences, which were the gateway to research focused on artificial intelligence. Shortly after the Second World War, around 1950, when the first article on artificial intelligence was published in the

philosophical journal MIND Computing Machinery and Intelligence, Alan Turing was the first mathematician and researcher who applied his knowledge in developing a computational machine that could perform mathematical analysis. And at the same time, he wondered if this same computational machine could have the ability to think like a human being [2, 3].

The first works developed with artificial intelligence were focused on mathematical sciences, statistical analysis, and on an event that marked history during the Second World War: algorithms to decode the Nazis' attack plan towards the allied countries against the government of Adolf Hitler, and whose intervention saved thousands of soldiers and civilians from each of these countries. On this occasion, artificial intelligence was used for the common good, to stop the machiavellian attacks from a sick and ambitious mind that took more than 20 million people [2, 3].

However, parallel to these feats uncertainty also grows to arise from the historical background of advances in the pure sciences. Such as the discovery of uranium and nuclear weapons, for human survival purposes, the discovery of dynamite to accelerate construction and firearms, for human defense. All of these have been questioned for their use in world wars, where human annihilation has prevailed, the most famous of all, the atomic bomb [2, 3].

Today we are thinking of artificial intelligence for the benefit of health, just health, which allows the approach from genetic and environmental risk factors and social and institutional determinants of the population. However, arises the concern as to whether the use of artificial intelligence is only of interest to ensure the survival of human beings from many diseases of the XXI century and its evolution, or whether we are approaching our annihilation [2–4].

The survival of the human race has been constantly threatened since ancient times by different outbreaks, epidemics, and pandemics of different infectious agents such as bacteria and viruses, an example of this, is the bubonic plague or black plague that wiped out 50% of the European population, and currently, the Covid-19, that had a demographic, social, economic and social impact. This has brought the world population to its knees and has made us understand that we are not indestructible, in fact, we are very vulnerable, and we must take into account nature's limits, the environment that surrounds us, and that exceeding them has led us to commit recklessness that has led to the annihilation of the human race [5].

The question we ask ourselves now is if we have learned the lesson from previous experiences, which have put human survival at risk. Or whether in this case, artificial intelligence will focus only on preserving human life and the environment around us improving our quality of life, or otherwise, we will be conquered again by the ambition for power, expansion, and wanting to be superior to others when we should be working together for our well-being.

The big bang of artificial intelligence focused on medicine and surgical procedures has already begun, the latest industrial revolution, a technological avalanche focused on the solution of more timely health interventions, reflecting real-time decision making, and influencing the health of different specific populations.

Likewise, it is urgent to regulate the uses and applications of artificial intelligence with laws and norms, imposing limits that guarantee the use of this technology only to preserve the human race, not replace it, much less annihilate it.

All countries, whether developed or developing, without exception, must sign international agreements and treaties in which they commit to use it only for the common good.

Being prudent in the development of these technologies and sharing this knowledge among sister countries that we are, without a doubt, would allow an unprecedented advance in science in general.

We must be very alert, and be able to impose limits on ourselves so that we do not engage in unethical behavior that puts the human race at risk.

We are in a historical moment, where technological advances have allowed the survival of the human race, it is important to mention that all the technology used for the creation in record time of vaccines against the covid-19 disease, which has taken so many lives worldwide.

In this way, we must unite our knowledge and efforts from all research fields, and educational institutions, such as universities worldwide, are the guarantors of imposing the limits of the different research approaches, thus favoring the good use of artificial intelligence applications.

If the academy is the one that produces the generation of knowledge for research purposes, and to solve problems, which in this case is focused on the solution of health problems, then it should impose the limits of uses on human beings and their environment.

Each research group, in their different areas, from different universities, should be able to build their methods focus on this discipline, to generate high-level knowledge, which can be translated into different computational languages, with the only purpose of making decisions in real-time.

Currently, the areas of development of artificial intelligence are focused on: Machine learning (machine learning, deep learning, unsupervised, supervised), driven by Massive Data (massive exploitation of data, identifying relationships between them, detecting patterns, making inferences, and learning through probabilistic mathematical models), natural language processing (content extraction, classification, translation, text generators), expert systems (knowledge and rule-based systems, diagnostics), computer vision (exploring the recognition and understanding of images and videos), robotics (advanced laparoscopic surgery such as Da Vinci, the Sojourner, Spirit, Opportunity, and Curiosity robots for space research) and speech recognition [6–8].

The applications, however, are focused on language analysis and understanding, information retrieval, information extraction, answer searches, automatic summaries, automatic translation, automatic document classification, speech recognition, chatbot, child content control, document and opinion detection, and anti-spam filters. Spam, voice assistants, Siri as Apple assistant, Cortana, Alexa, and Bixby all these applications use natural language techniques [6–8].

Search engines and entertainment and communications platforms such as Google Search, Google Maps, Netflix, and social networks such as Facebook, Pinterest, Twitter, Instagram, and Google Photos [6–8].

The challenge in the health areas is not only to create information systems with artificial intelligence, big data, and data mining with sophisticated algorithms for information management; making decisions in real-time is the key to intervening quickly in health problems [6–8].


**6. Future of machine vision measurement technology**

The goal of machine vision research is to provide computers with humanlike perception capabilities so that they can sense the environment, understand the sensed data, take appropriate actions, and learn from this experience in order to enhance future performance. The field has evolved from the application of classical pattern recognition and image processing methods to advanced techniques in image understanding like model-based and knowledge-based vision.

In recent years, there has been an increased demand for machine vision systems to address "real-world" problems. The current state-of-the-art in machine vision needs significant advancements to deal with real-world applications, such as agricultural navigation systems, target recognition, manufacturing, photo interpretation, remote sensing, etc. It is widely understood that many of these applications require vision algorithms and systems to work under partial occlusion, possibly under high clutter, low contrast, and changing environmental conditions. This requires that the vision techniques should be robust and flexible to optimize performance in a given scenario (Sebe et al., 2005 ).


**3. Tools for ncRNA identification**

#### **3.1. Tools for miRNA identification**

*2.2.4. Alignment*

After trimming and filtering, reads are ready for alignment or *de novo* construction. Alignment consists of mapping reads to a reference genome. Various alignment tools have been developed [42, 43] (https://omictools.com/read-alignment-category) including frequently used tools like TopHat [44], STAR [45], Bowtie [46], StringTie [47], etc. (**Table 2**). These softwares have their own specifications highlighting the importance of understanding the utility of each tool and the options they offer. The alignment tool used can have great impact on the end results. It has been observed that the choice of aligner and specific options can affect results of differential gene expression analysis [48]. Aligners can be grouped in two types, gapped (also known as split, e.g. STAR, BWA, etc.) and ungapped (e.g. Bowtie, etc.). Bowtie (ungapped group) can easily map reads to a genome, but is less effective at finding spliced junctions. Aligners in the gapped group are able to align reads and detect spliced variants. In the absence of a reference genome, *de novo* assembly aligners (e.g. Trinity [49]) can be used. In the context of lncRNA read alignment, gapped softwares are preferred since the transcripts are not all annotated and portions of the reads of the same transcript may align to one position of the genome and the remaining to another position. Alignment is one of the longest steps in RNA-Seq sequence analysis therefore selection of the right tool might have significant impact on the outcome of the analysis. It is also important to perform mapping quality control following alignment. Quality check includes the percentages of mapped and unmapped reads,

RNA-Seq transcript construction and the alignment steps can demand considerable computing time. Transcript construction tools are many (https://omictools.com/transcript-quantification-category) including commonly used tools like Cufflinks [63], iReckon [64], StringTie [47], etc. This step requires paired-end data and high sequence coverage to reconstruct lowly expressed transcripts. With the assumption that transcripts are species specific, raw data or alignment files from all samples from the same population can be merged to increase coverage [65]. This modification will help clarify transcript boundaries in case of *de novo* transcript assembly. Particular considerations for lncRNA transcript construction include sample pooling according to species and tissue type. LncRNA expression is known to demonstrate tissue

Overall, the procedures for miRNA identification and discovery are less time consuming and do not include as many steps as for mRNA and lncRNA identification. The global process includes quality and adaptors trimming with quality checkpoints before and after each step. A size selection to keep sequences between 17 and 30 nt (sometimes up to 35 nt) is often performed right after the quality and adaptors trimming step. This is followed by read mapping and filtering of other RNA sequences (rRNA, tRNA, snRNA, mRNA, lncRNA, etc.). The reads thought to represent miRNA are analyzed with miRNA prediction tools like miRDeep2 [69],

the location of the reads (intronic and exonic) and the 5′–3′ coverage.

114 Applications of RNA-Seq and Omics Strategies - From Microorganisms to Human Health

*2.2.5. Transcript construction and quantification*

specificity [66–68].

*2.2.6. miRNA processing steps*

The identification of miRNAs can be either annotation of known miRNAs or discovery of novel miRNAs. A variety of algorithms and bioinformatics tools are applied to annotate known miRNAs as well as to discover new miRNAs from sequence data. These tools can use several features such as sequence conservation among species, structural features like hairpin and minimal folding free energy [72]. Many tools are available for miRNA annotation (https://tools4mirs.org/software/known\_mirna\_identification/) [73] including frequently used tools like miRdeep [74], miRanalyzer [75], mirTools 2.0[71], UEA sRNA Workbench [76], sRNAtoolbox [77], and SeqBuster [78] (**Table 3**). Many more tools have been developed for novel miRNA discovery and miRNA precursor prediction (https://tools4mirs.org/software/ precursor\_prediction/)[73] including frequently used tools like MiPred [79], miRanalyzer [75], miR-Abela [80], MiReNA [81], UEA sRNA Workbench [76] and mirDeep [74] (**Table 3**). Major features of miRNA discovery tools have been reviewed [82–84]. Regarding livestock species, the choice of methods for miRNA discovery and novel miRNA annotation vary among studies and species. For example, De Vliegher et al. [85] used miRbase [86] and UNAFold [87] for miRNA annotation and discovery in bovine mammary gland tissues while Peng et al [88] used miRbase [86] and RNAfold [89] for these purposes in porcine mammary glands. In our own studies, miRbase [86] and mirDeep2 [74] were used to identify miRNAs in various tissues including bovine mammary gland tissues [90], milk fat [90–92], milk whey and cells [90].

#### **3.2. Tools for lncRNA identification**

To date, a large number of lncRNA genes have been identified in the genomes of human (141,353), cow (23,896) and chicken (13,085) (http://www.bioinfo.org/noncode/analysis.php, accessed on 24-03-2017). Several methodologies have been described to identify/distinguish lncRNAs from mRNAs and successfully applied to livestock species such as coding potential calculator (CPC) [122], PhyLoCSF [123], coding-non-coding index (CNCI) [124], coding potential assessment tool (CPAT) [125], Predictor of Long non-coding RNAs and mRNAs based on an improved k-mer scheme (PLEK) [126] and Flexible Extraction of LncRNAs (FEELnc) [127], etc. The FEELnc program developed by the functional annotation of animal genome project consortium (FAANG) [128] is recommended as a standardized protocol for lncRNA analyses in animal species. In order to distinguish lncRNAs from mRNAs, FEELnc program uses a machine-learning method for estimation of a protein-coding score according to the RNA size, open reading frame coverage and multi k-mer usage [127]. The FEELnc program can derive an automatically computed cut-off so it maximizes the lncRNA prediction sensitivity and specificity. An overview of tools for lncRNA identification/characterization is listed in **Table 4**.

**Tools Type Major Function/web link References**

ncrdeathdb

resource to ncRNA-associated cell death interactions. www.rna-society.org/

Transcriptome Analysis of Non‐Coding RNAs in Livestock Species: Elucidating the Ambiguity

long noncoding genes. bioinfo.ibp.ac.cn/

RNA, and lncRNA information with immunologically relevant target genes. http://

annotating newly identified human

Present a computational method and program to predict lncRNA DNA-binding motifs and binding sites. lncrna.smu.edu.cn

Facilitates search for the functions of a specific lncRNA or the lncRNAs associated with a given functional term, or annotate functionally a set of human lncRNAs of interest. http://mlg.hit.edu.cn/

Presents a web-based computational tool that allows users to identify GO annotations and KEGG pathways that may be affected by co-expressed protein-coding genes of single or multiple lncRNAs. www.bio-bigdata.com/

Provides regulatory information about lncRNAs, such as targets, regulatory mechanisms, and experimental evidence for regulation and key molecules participating in regulation. bioinformatics.ustc.edu.cn/lncreg/

Provides comprehensive functional annotations for human lincRNA. http:// www.bioinfo.tsinghua.edu.cn/~liuke/

Integrates ncRNA information related to expression, pathways and diseases in a large number of human tissues and primary cells.

a resource for efficient browsing and visualization of virus-host ncRNAassociated interactions and interaction networks in viral infection. http://www.

www.cbrc.kaust.edu.sa/farna/

rna-society.org/virbase

[138]

http://dx.doi.org/10.5772/intechopen.69872

117

[139]

[140]

[141]

[142]

[143]

[144]

[145]

[146]

[147]

[148]

ncRDeathDB Database Present a comprehensive bioinformatics

LncVar Database Presents genetic variation associated with

IRNdb Database Combines microRNA, PIWI-interacting

AnnoLnc Annotation Presents online portal for systematically

LongTarget Target

LncRNA2Function Functional

Co-LncRNA Function

LncReg Function

Linc2GO Function

FARNA Function

prediction

inferences

inference

inference

inference

annotation

LncVar

irndb.org

lncRNAs.

lncrna2function

Co-LncRNA/

Linc2GO

ViRBase Database Provides the scientific community with

RNA size, open reading frame coverage and multi k-mer usage [127]. The FEELnc program can derive an automatically computed cut-off so it maximizes the lncRNA prediction sensitivity and specificity. An overview of tools for lncRNA identification/characterization is listed in

> binding sites. Predicts transcriptional regulatory relationships between transcription factors and genes. http://rna.

> structure, human lncRNA transcripts and genes. http://www.lncipedia.org/.

eukaryotic lncRNAs. Offers an improved user interface enabling greater accessibility to sequence information, expression data and the literature. http://www.lncrnadb.org/.

annotation resources. Allows achieving refined annotation of lncRNAs within the interested region. http://biocc.hrbmu.edu.cn/

nucleotide polymorphisms (SNPs) in human/ mouse lncRNAs. bioinfo.life.hust.edu.cn/

curation and collection of information on human lncRNAs. http://lncrna.big.ac.cn/

annotation of non-coding RNAs (excluding tRNAs and rRNAs) for 18 species including human, mouse, cow, rat, chicken, pig, fruitfly, zebrafish, *Caenorhabditis elegans* and yeast.

analysis of lncRNAs in domestic animals. Offers information on genome-wide expression profiles and animal quantitative trait loci (QTLs) of domestic animals. http://

Contains annotation of lncRNA loci publicly available with the predominant transcript form consisting of two exons. https://www.

res.xaut.edu.cn/aldb/index.jsp

[129]

[130]

[131]

[132]

[133]

[134]

[135]

[136]

[137]

**Tools Type Major Function/web link References**

sysu.edu.cn/chipbase/.

ChIPBase Database Identifies binding motif matrices and their

116 Applications of RNA-Seq and Omics Strategies - From Microorganisms to Human Health

LNCipedia Database Provides basic transcript information and

lncRNAdb Database Provides comprehensive annotation of

LNCat Database Stores the information of 24 lncRNA

LNCat/

lncRNASNP/

index.php/Main\_Page

www.noncode.org/

gencodegenes.org

LncRNASNP Database Provide comprehensive resources of single

lncRNAWiki Database Provide open-content and publicly editable

NONCODE Database Presents the most complete collection and

ALDB Database Enables the exploration and comparative

GENCODE Database Presents all gene features in the human genome.

**Table 4**.

highly versatile and user-friendly interaction with data in order to easily classify small RNA sequences with putative functional importance [155]. For other small RNAs, ncPRO-seq [156] allows the discovery of unknown ncRNA or siRNA-coding regions from small RNA sequence data. DARIO [94] is a web-tool that allows annotation and detection of ncRNAs from various species but not livestock species. CoRAL [157] is a machine learning method that classifies ncRNAs by relying on biologically interpretable features. Several tools also have been developed for predicting circRNAs such as PredicircRNATool [158] and PredcircRNA [159] which apply a machine learning approach to distinguish circRNAs from other ncRNAs (**Table 5**).

Transcriptome Analysis of Non‐Coding RNAs in Livestock Species: Elucidating the Ambiguity

based on quantifiable deviations from a hypothetical uniform distribution regarding the decisive piRNA cluster characteristics. https://sourceforge.net/

from small RNA-seq data using a density based clustering approach. http://epigenomics.snu.ac.kr/piclustweb

on their genomic location in gene, intron, intergenic, CDS, UTR, repeat elements, pseudogenes and syntenic regions. bicresources.jcbose.ac.in/

and classification of the non-miRNA small RNA transcriptome. http:// seqcluster.readthedocs.io/#

ncRNA- or siRNA-coding regions from sRNA sequence data. http://ncpro.

ncRNAs from various species but not livestock species. http://dario.bioinf.

piRNAs, snRNAs, snoRNAs, scRNAs (small cytoplasmic RNAs), tRNAs, and rRNAs information. lisanwanglab.org/

RNAs (snoRNAs) and small cajal bodyspecific RNAs (scaRNAs). gene.fudan.

uni-leipzig.de/index.py

edu.cn/snoRNAbase.nsf

classifies ncRNA by relying on biologically interpretable features. http://wanglab.pcbi.upenn.edu/coral [152]

http://dx.doi.org/10.5772/intechopen.69872

119

[153]

[154]

[155]

[156]

[94]

[157]

[160]

[161]

**Tools Types Main Features/web link References**

projects/protrac/

zhumur/pirnaquest

curie.fr/.

DASHR

ProTRAC piRNA prediction Detects and analyses piRNA clusters

piClust piRNA prediction Finds piRNA clusters and transcripts

piRNAQuest piRNA database Provides annotation of piRNAs based

SeqCluster ncRNA classification A framework python for the annotation

ncPRO-seq ncRNA discovery Allows the discovery of unknown

DARIO ncRNA discovery Allows annotation and detection of

CoRAL ncRNA classification A machine learning method that

DASHR Database Stores human small ncRNAs: miRNAs,

Sno/scaRNAbase Database A curated database for small nucleolar

**Table 4.** Overview of tools for the analysis of lncRNA sequence data.

#### **3.3. Tools for identification of other non-coding RNA**

Currently, few tools have been developed for the identification of groups of ncRNAs other than miRNAs and lncRNAs. The popular tools for piRNA identification include ProTRAC [152], piClust [153], piRNAQuest [154], etc. (**Table 5**). proTRAC detects piRNA clusters based on a probabilistic analysis with assumption of a uniform distribution while piClust uses a density based clustering approach for the detection of piRNAs. piRNAQuest allows a search of the piRNome for silencers [154]. Another notable framework is SeqCluster [155], a python pipeline for the annotation and classification of non-miRNA small ncRNAs. The pipeline permits a highly versatile and user-friendly interaction with data in order to easily classify small RNA sequences with putative functional importance [155]. For other small RNAs, ncPRO-seq [156] allows the discovery of unknown ncRNA or siRNA-coding regions from small RNA sequence data. DARIO [94] is a web-tool that allows annotation and detection of ncRNAs from various species but not livestock species. CoRAL [157] is a machine learning method that classifies ncRNAs by relying on biologically interpretable features. Several tools also have been developed for predicting circRNAs such as PredicircRNATool [158] and PredcircRNA [159] which apply a machine learning approach to distinguish circRNAs from other ncRNAs (**Table 5**).

**3.3. Tools for identification of other non-coding RNA**

**Table 4.** Overview of tools for the analysis of lncRNA sequence data.

Currently, few tools have been developed for the identification of groups of ncRNAs other than miRNAs and lncRNAs. The popular tools for piRNA identification include ProTRAC [152], piClust [153], piRNAQuest [154], etc. (**Table 5**). proTRAC detects piRNA clusters based on a probabilistic analysis with assumption of a uniform distribution while piClust uses a density based clustering approach for the detection of piRNAs. piRNAQuest allows a search of the piRNome for silencers [154]. Another notable framework is SeqCluster [155], a python pipeline for the annotation and classification of non-miRNA small ncRNAs. The pipeline permits a

**Tools Type Major Function/web link References**

lncrna2target.org/

cbi.pku.edu.cn/

sourceforge.net/

com/tderrien/FEELnc

ibiomedical.net/plek/

a web interface for searching targets of a particular lncRNA or for the lncRNAs that target a particular gene. https://www.

Identifies lncRNAs-associated modules from protein interaction networks and predicts the function of lncRNAs based on the protein functions in the modules. lncin.ym.edu.tw

Integrates experimentally verified functional interactions between noncoding RNAs (excluding tRNAs and rRNAs) and other biomolecules (proteins, RNA and genomic DNA). www.bioinfo.org.cn/NPInter

Distinguishes between coding and noncoding RNA. Uses a Support Vector Machine-based classifier to assess the protein-coding potential of a transcript. cpc.

com/www-bioinfo-org/CNCI

Distinguishes between protein-coding and non-coding sequences independent of known annotations. Applies to a variety of species without whole-genome sequence or with poorly annotated information. https://github.

Distinguishes between coding and noncoding RNA. Uses a logistic regression model to assess the protein coding potential. rna-cpat.

Derives an automatically computed cut-off so it maximizes the lncRNA prediction sensitivity and specificity. https://github.

Uses k-mer scheme and a support vector machine (SVM) algorithm to distinguish lncRNAs from mRNAs. http://www.

[149]

[150]

[151]

[122]

[124]

[125]

[127]

[126]

LncRNA2Target Database Stores lncRNA-to-target genes. Provides

118 Applications of RNA-Seq and Omics Strategies - From Microorganisms to Human Health

Lncin Function

NPInter Function

CPC Coding

CNCI Coding

CPAT Coding

FEELnc LncRNA

PLEK lncRNA

annotation

annotation

potential assessment

potential assessment

potential assessment

prediction

prediction

**4. Tools for differential expression analysis of non-coding RNA**

controlling FDR while NOISeq is efficient in avoiding false positives [29].

*5.1.1. Bioinformatics tools for target prediction and functional inference of miRNAs*

for inferring the functions of miRNAs is shown in **Figure 4**.

**5.1. Functional inference of miRNAs**

**non‐coding RNA**

**5. Bioinformatics tools for target prediction and functional inference of**

Following discovery and detection of important ncRNAs from RNA sequence data, the important next steps are to understand their regulatory roles. Since ncRNAs commonly act by interacting with target genes (mostly inhibit expression), various tools have been developed to predict their target genes and to infer their functions (**Tables 3** and **4**). A simple work flow

Inferring individual targets for a given miRNA can be done either by computational or experimental methods. Computational target prediction is coordinated in a sequence-specific manner and the target genes are normally predicted based on information derived from the

Various tools allow for the detection of genes (mRNA or ncRNA) differentially expressed (DE) between two or more conditions or states from sequence data. The major differences among tools are their implemented statistical methods, input and output file formats as well as filtering steps for DE analyses. Many tools such as DESeq [169], edgeR [170], NBPSeq [171], TSPM [172], baySeq [173], EBSeq [174], NOISeq [175], SAMseq [176] and ShrinkSeq [177] use count data as input file, while others like limma [178] and Cufflinks use transformed data or BAM files (the binary version of sequence alignment data) as input, respectively. Tools that use count data can be divided in to two groups; parametric (DESeq [169], edgeR [170], NBPSeq [171], TSPM [172], baySeq [173], EBSeq [174]) and non-parametric methods (NOISeq [175], SAMseq [176]). For parametric methods, most softwares (baySeq [173], DESeq [169], NBPSeq [171], edgeR [170], EBSeq [174] and NBPSeq) use a negative binomial model to account for over dispersion except ShrinkSeq which has two options for distribution, either negative binomial or a zero-inflated negative binomial distribution. These methods also implement different statistical test approaches; DESeq, edgeR and NBPSeq perform a classical hypothesis testing approach while baySeq, EBSeq and ShrinkSeq apply Bayesian methods. The comparison of methods and performances have been done and reviewed by many authors [29, 179– 183]. In general, no single method performs well for all datasets. In a survey of performance of DE analyses methods, Conesa et al. [29] observed that limma package [178] performed well under many conditions. Many studies observed similar performances by DESeq and edgeR in ranking genes [29, 179–183]. However, DESeq is more conservative while edgeR is more liberal in controlling false discovery rate (FDR) [29]. Other tools such as SAMseq is better in

Transcriptome Analysis of Non‐Coding RNAs in Livestock Species: Elucidating the Ambiguity

http://dx.doi.org/10.5772/intechopen.69872

121

**Table 5.** Overview of tools and databases for sequence analysis of other small ncRNAs.


**2.2 Cardiovascular disease**

According to the guidelines of the American College of Cardiology (ACA)/ American Heart Association (AHA) Task Force, surgical interventions can be classified into three categories according to the risk associated with the procedure itself [11]:

Similarly, patients can be stratified in three categories based on the presence of risk factors for perioperative complications:

The recommendations provided by the AHA/ACC and the ESAIC can be schematically summarized for patients undergoing elective hip replacement as follows: patients with major risk factors require immediate cardiological evaluation, which, in most cases, will lead to myocardial revascularization, valve surgery, or modification of current medical therapy. In this case, the surgery can only be postponed unless it is considered an emergency and, therefore, undelayable. Patients with intermediate risk factors can undergo elective surgery without additional investigations if their functional reserve is at least moderate, and the proposed intervention is at (low or) intermediate risk such as hip replacement. The use of the risk calculator of the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) is a recommended tool for cardiac perioperative risk stratification. In addition, the assessment of high-sensitivity cardiac troponins in high-risk patients 48 hours before

and 72 hours after major surgery is recommended to detect preexisting or postoperative cardiac failure [12]. Therapy with beta blockers should be continued throughout the perioperative period, mostly in patients who have known ischemic heart disease or myocardial ischemia. In patients treated with acetylsalicylic acid, the discontinuation of the therapy should be considered in the perioperative period and should be balanced among the risk of bleeding and the risk of thrombotic complications. For patients undergoing hip replacement, the execution of a baseline electrocardiogram (ECG) in the preoperative period should be mandatory. In the case of patients belonging to the minor-risk class of cardiovascular risk (i.e., elderly patients and patients with a traumatic femur or pelvis fracture) with indication for hip replacement, prolonged monitoring outside the operating room (recovery room/ICU) is strongly recommended, as a good clinical practice to reduce the overall postoperative risk.

## **2.3 Respiratory disorders**

Since chest radiograph rarely alters the perioperative management, it should not be included among the routine investigations. Similarly, spirometry is not recommended as a preoperative routine examination in all patients affected by respiratory problems. On the contrary, patients with obstructive sleep apnea syndrome (OSAS) should be evaluated carefully for potentially difficult airway in the need of ventilatory support or endotracheal intubation. History of previous surgical procedures and referred difficult airway should be investigated especially in patients with diagnosed or suspected OSAS. The use of specific questionnaires to screen for patients with OSAS is recommended when polysomnography (gold standard) is not available. In particularly, among others, the STOP-BANG questionnaire is the most sensitive, specific, and best validated score [13]. Perioperative continuous positive airway pressure (CPAP) must be continued in patients with OSAS to reduce hypoxic events. Moreover, patients with suspected or diagnosed OSAS receiving sedative or general anesthesia during or before surgery should be monitored in the immediate postoperative phase. Of note, stop smoking at least 4 weeks prior to surgery reduces postoperative complications [14].

### **2.4 Management of antiplatelets/anticoagulant drugs**

The perioperative management of anticoagulant therapy is cumbersome due to the complexity of the issue, as well as the simultaneous need to balance the risk of bleeding and the risk of thromboembolic events. On the one hand, surgery should be performed when coagulation is almost normalized to limit the risk of bleeding complications from excessive anticoagulation both during surgery and in the postoperative period. On the other hand, it is necessary to limit as much as possible the interval between the suspension and the restoration of the anticoagulant therapy in order to avoid thromboembolic complications.

A rational approach to the management of anticoagulant therapy should be multidisciplinary and involves the other specialists aiming to carefully evaluate the rationale of the ongoing therapy, the risk of bleeding related to the specific surgical procedure, and the risk of the patient to develop thromboembolic or hemorrhagic events during the complete or suboptimal anticoagulation therapy in the perioperative phase. Taken all together, the final decision should also consider all the therapeutic tools available that are able to modify the coagulation cascade in relation to the specific clinical context [15–18]. Many patients undergoing total hip replacement are on antiplatelet therapy, generally, with low-dose acetylsalicylic acid, ticlopidine, or

### *Anesthesia for Hip Replacement DOI: http://dx.doi.org/10.5772/intechopen.104666*

clopidogrel, more rarely with dipyridamole, indobuphene, or picotamide monohydrate. As for beta blockers, acetylsalicylic acid should be continued in the perioperative period, and its use is associated with a lower incidence of myocardial ischemia in the absence of a substantial increase in surgical bleeding [15]. In general, for mediumand high-risk procedures, clopidogrel should be routinely stopped 7 days before surgery with an exception for patients at high risk of thromboembolic events in whom an interval of 5 days before surgery is recommended and, if available, a platelet function test should be performed to evaluate an adequate platelet function. However, the ACC/AHA Task Force suggests that hip replacement surgery can be safely performed without stopping clopidogrel perioperatively [19]. Ticlopidine is the antiaggregant of choice in patients that are intolerant and/or allergic to acetylsalicylic acid. The antiplatelet effect persists for over 8 days after stopping the drug. The management of ticlopidine therapy in the perioperative period is not codified. For elective hip surgery, it is recommended to discontinue ticlopidine therapy, whereas for emergency procedures, in the case of significant bleeding risk, it would be preferable to perform a platelet transfusion of platelet concentrates [20, 21]. In view of the limited number of relevant publications, it is difficult to release recommendation regarding the perioperative management of antiplatelet therapy with dipyridamole, indobufen, and picotamide. Although some cases of epidural hematoma after locoregional anesthesia have been described in patients receiving acetylsalicylic acid or nonsteroidal anti-inflammatory drugs, the incidence of this complication does not appear to be significantly increased in patients treated with antiplatelet drugs [22, 23]. According to the existing knowledge, locoregional anesthesia is considered suitable for patients on antiplatelet therapy [15, 24]. Similar conclusions may not be drawn for ticlopidine because there is not yet sufficient evidence in the literature. Regarding patients treated with low-molecular-weight heparin (LMWH), heparin should be suspended based on the dosage administered depending on its use as prophylaxis or therapeutic of thromboembolic events. For hip replacement surgery, a 12-hour interval before surgery is recommended when LMWH is used at prophylactic dose. Noteworthy, when a therapeutic dose of enoxaparin (1 mg/kg) is used, a 24-hour interval is recommended. The LMWH can be generally resumed at least 12 hours after hip replacement surgery. The new oral anticoagulants (NAO or DOAC) are a recent class of drugs that act by selectively inhibiting a single coagulation factor, either II or X (**Table 1**), unlike the antivitamin K antagonists (AVK) Warfarin and Acenocoumarol, which act on several factors at the same time (VII, II, IX, and X). DOACs have been introduced

*Abbreviation: Tmax, time to peak drug concentration after dose.*

*\*Half-life varies with renal function, with increasing half-life, with increased renal impairment.*

#### **Table 1.**

*Mechanisms of action and characteristics of new oral anticoagulants.*

#### **Table 2.**

*Summary of withdrawal time of new oral anticoagulant stratified by renal clearance and type low versus high risk surgery.*

into clinical practice for the prevention of stroke and systemic thromboembolism in patients with atrial fibrillation and for the prevention and treatment of venous thromboembolism. Currently, the DOACs approved by the European Medicines Agency (EMA) on the market are the following:

**Table 1** summarizes the mechanisms of action of DOACs. **Table 2** reports the withdrawal times in relation to surgery and renal function.


**5. Acknowledgment**

A portion of this study was supported by a Grant-in-Aid for Scientific Research (B) 21404002, Japan and the AA Science Platform Program of the Japan Society for the Promotion of Science.


**5. Conclusion**

33.9% compared to the one predicted for E0. In **Figure 11**, the impact of increasing the ethanol/ gasoline fraction from E0 to E100 is seen to be significant. The deviation in the predicted droplet surface temperature for E100 is 24.3% compared to the one predicted for E0. The impacts of dif-

Diff % = |(*tim eEN* –*tim eE*0)| \_\_\_\_\_\_\_\_\_\_\_\_\_\_ *tim eE*0

The droplet lifetimes of ethanol-gasoline fuel mixtures (**Figures 10**–**11**) have been estimated under standard engine conditions. The impact of different ambient conditions on these pre-

As can be seen from **Figures 12** and **13**, increasing the ambient temperature (500 to 650 K), or pressure (3 to 20 bar), leads to a proportional reduction in estimated droplet lifetimes with

**Figure 12.** The impact of ambient temperatures on droplet lifetimes for E0, E50, E85 and E100 fuel blends, estimated at

ferent ethanol/gasoline fuel mixtures on droplet lifetimes are presented in **Table 6**.

dictions is presented in **Figures 12** and **13**.

**Blends Time (ms) Diff%** E0 1.988 —

74 Advances in Biofuels and Bioenergy

E50 2.093 5.282 E85 2.356 18.511

E100 2.662 33.903

E5 1.989 0.050 *Note:*

E20 1.994 0.302 × 100%

**Table 6.** The impact of ethanol/gasoline fuel blends on the estimated droplet lifetimes.

ambient pressures 3 and 20 bar.

almost the same effect for all ethanol-gasoline blends.

In this chapter, the maximum entropy method was applied for the droplet distribution of diesel and biodiesel fuel sprays in conditions relevant to diesel internal combustion engines. The droplet distribution for biodiesel was more skewed to the right compared to the predicted diesel spray. The theoretical distribution indicated that biodiesel fuel droplets are larger than those of diesel fuel. The model was validated against available experimental data to show a reasonable agreement between both results.

The discrete component model was used to analyze the heating and evaporation of blended diesel-biodiesel fuel sprays and droplets using 22 types of biodiesel, European standard diesel, gasoline FACE C, and ethanol-gasoline fuels. The full compositions of diesel, biodiesel and gasoline fuels were considered. The diesel and gasoline fuels consisted of 98 and 20 hydrocarbons respectively, while the 22 biodiesel fuels consisted of 4 to 18 components of methyl esters.

The effect of increasing biodiesel fuel concentration on the evolutions of droplet surface temperatures and evaporation times was clearly illustrated. The predicted B5 fuel droplet lifetimes for the 22 types of biodiesel fuel were only 1% less than that of pure diesel (PD) fuel. The RME biodiesel fuel droplets were observed to have lifetimes close to that of PD fuel, where their predicted lifetimes for B5 and B100 droplets were up to 0.4 and 0.6%, respectively, less than the one estimated for PD fuel droplet. However, for ethanol, the predicted E5 fuel droplet lifetimes were only 0.05% greater than that of pure gasoline (E0) and only 0.3% greater for E20.

To conclude, the B5 fuel droplet lifetimes for all 22 types of biodiesel fuels used in this study are almost identical to the one predicted for PD fuel; i.e. diesel fuel can be possibly blended with up to 5% biodiesel fuel without any noticeable effect on the evolutions of their droplet radii or surface temperatures. Similarly, the E5 and E20 fuel droplet lifetimes are almost identical to the one predicted for E0 fuel; i.e. gasoline fuel can be possibly blended with up to 20% ethanol fuel without/minimal modifications to the gasoline engine. Also, increasing the ambient pressure, or temperature, will lead to a faster evaporation of E0-E100 droplets regardless of their blending ratios.

LP length parameter PD pure diesel fuel E0 pure gasoline fuel PME palm methyl ester

PMK palm kernel methyl ester

Atomization of Bio-Fossil Fuel Blends http://dx.doi.org/10.5772/intechopen.73180 77

PTE peanut methyl ester RME rapeseed methyl ester SFE safflower methyl ester SMD Sauter mean diameter SME soybean methyl ester SNE sunflower methyl ester

TGE tung methyl ester TME tallow methyl ester WCO waste cooking oil

Symbols

YGR yellow grease methyl ester

*A* spray penetration coefficient

*D* diffusion coefficient [m2 s−1]

*k* thermal conductivity [W m−1 K−1]

*d* nozzle diameter [m]

*p* pressure [Pa]

*R* radius [μm]

*U* velocity [ms−1] *Y* mass fraction

*κ* thermal diffusivity

*ρ* density [kg m−3]

*μ* dynamic viscosity [Pa s]

*t* time [ms]

*T* temperature [K]


*Edited by Yik-Hong Ho*

In recent years, significant progress in colorectal surgery has been made which includes laparoscopic techniques, pre-operative management, emergency colorectal surgery, fast track multimodal recovery, management of complex wound problems and colorectal cancer follow-up. "Contemporary Issues in Colorectal Surgical Practice" aims to bridge the gap between the journal article and the traditional textbook in these areas.

Contemporary Issues in Colorectal Surgical Practice

ISBN 978-953-51-0257-1

Photo by zizulhalmi / iStock

## Contemporary Issues in Colorectal Surgical Practice

*Edited by Yik-Hong Ho*


*Jatropha Curcas* **L. Biomass Waste and Its Utilization**

*Jatropha Curcas* **L. Biomass Waste and Its Utilization**

DOI: 10.5772/intechopen.72803

Sri Rizki Putri Primandari, A.K.M. Aminul Islam, Zahira Yaakob and Swapan Chakrabarty Zahira Yaakob and Swapan Chakrabarty Additional information is available at the end of the chapter

Sri Rizki Putri Primandari, A.K.M. Aminul Islam,

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.72803

#### **Abstract**

*Jatropha curcas* L. is cultivated for its oil utilization as fuel feedstock. This main purpose is achieved with the biomass waste after oil extraction. The biomass wastes are leaf and stem from pruning, fruit hull, seed husk, and oily-cake. This paper discusses the utilization of the waste in order to achieve zero waste of jatropha and develop the jatropha utilizations. Jatropha waste is also utilized as fertilizer, briquettes, adsorbent, resin, and bioactive compost. It can also be utilized as feedstock for production of polymer composite, combustion for gasifier, biogas, liquid oil, and dye. These wide utilizations make jatropha very suitable for biofuel proposes.

**Keywords:** biomass, Jatropha cake, utilization, environment, waste management


**Author details**

Gabriela Prelipcean1 and Mircea Boscoianu2

1 Stefan cel Mare University of Suceava, Romania

2 Henri Coanda Air Force Academy of Brasov, Romania

### **References**

[5] Baldo, f., Rabelo, R.J., Vallejos, R.V., 2008, Modeling Performance Indicators' Selec‐ tion Process for VO Prtners' Suggestions, in Proceedings BASYS'2008 – 8th IFIP Int. Conf. on Information Technology for Balance Automation Systems, pp.67-76, Spring‐ er, Heilderberg.

port on analyzing and solving the conflicts on processing demands by taking reactive decisions; the partners' configuration; the support on re-planning share by means of the ba‐ sic programming actions within VE; integration with the cooperation platform (data integra‐ tion; security communications; inter-functionality or interaction). Taking into account the complexity of DSS-VE/VO systems, innovative issues should be investigated, especially to‐

The future developments of the concepts linked to VE (new assessment models based on ability to add real value, changes in the competition nature between firms, new possibilities for integration/ mixing with DSS) should consider the following future directions of re‐ search: the development of VE platforms dedicated for SMEs and startups; the specification of operational characteristics and the analysis of the distributed architectures; the develop‐ ment of the new methods of management, coordination, cooperation and negotiations be‐ tween VEs; special focus on social aspects regarding the development of VEs. Other aspects to cover in future work should take into account: the coordination functionalities such as distributed resource management and scheduling and the new role of negotiation in a VE as a central task in the formation of a VE/ VO but also in the operation and success of these

[1] Afsarmanesh, H., Camarinha-Matos, L.M., 2000, A virtual tourism enterprise, Pro‐ ceedings of WISE 2000 – 1st ACM/IEEE International Conference on Web Informa‐

[2] Afsarmanesh, H., Camarinha-Matos, LM, 2005. A Framework for Management of Virtual Organization Breeding Environments. 6TH ifip working conference on virtu‐

[3] Alexakis, S., Kolmel, B., Heep, T., 2004, VO in Industry: State of the Art, in Collabora‐ tive Networked Organizations: A Research Agenda for Emerging Business Models",

[4] Ambroszkiewicz, S., Cetnarowicz, K., Radko, B., 1998, Enterprise Formation Mecha‐ nisms based on Mobile Agents, In Holsten, A. et al. (eds.), Proc. of the Workshop on Intelligent Agents in Information and Process Management, KI'98, TZI-Bericht, No.9.

tion Systems Engineering, Vol. 1, IEEE Computer Society Press, Hong Kong.

wards the line of intelligent coordination.

and Mircea Boscoianu2

1 Stefan cel Mare University of Suceava, Romania

2 Henri Coanda Air Force Academy of Brasov, Romania

al enterprises, PROVE-05, Valencia, Spain.

innovative vehicles.

110 Decision Support Systems

**Author details**

Gabriela Prelipcean1

**References**

Kluwer.

[19] Clements, P. E., Papaioannou, T., Edwards. J., 1997, Aglets: Enabling the Virtual En‐ terprise, In Wright, D et al. (Eds.), Proc. of Mesela '97 - 1st Int'l Conf. on Managing Enterprises - Stakeholders, Engineering, Logistics and Achievement. Mechanical En‐ gineering Publications Ltd.

[31] Fu, K.S., 1970, Learning Control Systems--Review and Outlook, IEEE Transactions on

Emerging Applications of the New Paradigm of Intelligent Decision Making Process: Hybrid Decision Support Systems

for Virtual Enterprise (DSS-VE) http://dx.doi.org/10.5772/3371 113

[32] Gadomski, A. M., Bologna, S., Di Constanzo, G., Perini, A., Schaerf, M., 2001, To‐ wards intelligent decision support systems for emergency managers: the IDA ap‐ proach, International Journal Risk Assessment and Management, vol.2, no. 3-4.

[33] Holland, J.H., 1975, Adaptation in Natural and Artificial Systems, University of

[34] Holsaplle, C. W., Whinston, A. B., 1996, Decision Support Systems: A Knowledge-

[35] Ivanov, D., Arkhipov, A. and Sokolov, B., 2003, Intelligent planning and control of manufacturing supply chains in virtual enterprises, in Proceeding of PRO-VE'03 – Processes and Foundations for Virtual Organizations, Kluwer Academic Publishers,

[36] Jain, A. K., Aparicio IV, M., Singh, M. P., 1999, Agents for Process Coherence in Vir‐

[37] Jansson, K., Eschenbacher, J., 2005, Challenges in Virtual Organisations Management – Report on methods for distributed business process management. Tech. Report D32.1. European Collaborative networked Organizations LEADership initiative. FP6

[38] Janssen, T. L., 1989, Network expert diagnostic system for real-time control, Proceed‐ ings of the second international conference on industrial and engineering applica‐

[39] Katzy, B. R., Schuh, G., 1997, The Virtual Enterprise, in: Molina, A., Sanchez, J. M., Kusiak, A. (eds.), Handbook of Life Cycle Engineering: Concepts, Methods and

[40] Kazi, A.S., Hannus, M., 2002, Virtual enterprise reference architecture and methodol‐

[41] Kerschberg, L., 1997, Knowledge rovers: Cooperative intelligent agent support for enterprise information architectures, in P. Kandzia and M. Klusch, Eds., Cooperative Information Agents, First International Workshop, CIA'97, Kiel, Germany, Proceed‐

[42] Kim, C., Son, Y., Kim, T., Kim, K., 2004, A modeling approach for designing a value chain of VE. Virtual Enterprises and collaborative Environments, IFIP 5th working conference on virtual enterprises, Kluwer Academic Publishers, Toulouse, France.

[43] Little, J. D.C., 1970, Models and Managers: The Concept of a Decision Calculus, Man‐

tual Enterprises, In Communications of the ACM, March, Vol. 42, No. 3.

tions of artificial intelligence and expert systems, Vol. 1 (IEA/AUIE '89).

ogy, eWork and eBusiness in AEC, ECPPM 2002, Slovenia.

based Approach, West Publishing Company, Minneapolis/St Paul.

Automatic Control, No. 15.

Michigan Press, Ann Harbor, MI.

Tools, New York, Chapman & Hall.

ing, Springer-Verlag.

agement Science, 6, No. 8.

Switzerland.

IP 506958.

[31] Fu, K.S., 1970, Learning Control Systems--Review and Outlook, IEEE Transactions on Automatic Control, No. 15.

[19] Clements, P. E., Papaioannou, T., Edwards. J., 1997, Aglets: Enabling the Virtual En‐ terprise, In Wright, D et al. (Eds.), Proc. of Mesela '97 - 1st Int'l Conf. on Managing Enterprises - Stakeholders, Engineering, Logistics and Achievement. Mechanical En‐

[20] Cunha, M.M., Putnik, G.D., Carvalho, J.D. and Avila P., A review of environments supporting virtual enterprise integration, Knowledge and technology integration in production and services, Fifth IFIP international Conference on Information technol‐ ogy for Balanced Automation Systems in Manufacturing and Services, Kluwer Aca‐

[21] Cristopher, M.L., 1994, Logistics and supply chain management, Pitman Publishing,

[22] Christopher, M., 1994, New directions in Logistics, Logistics and Distribution Plan‐ ning – strategies for management, ed. by James Cooper, Kogan Page Limited, 2nd

[23] Davidow, W.H., Malone, M.S., 1992, The Virtual Corporation: Structuring and Revi‐

[24] Dorn, J. Hrastnik, P. and A. Rainer, 2004, Conferences as Virtual organization, Virtu‐ al Enterprises and Collaborative Environments, IFIP 5th working conference on vir‐

[25] Drissen-Silva, M.V., Rabelo, R.J., 2009, A Collaborative Decision Support Framework for Managing the Evolution of Virtual Enterprises, International Journal of Produc‐

[26] Ferber, J., Gutknecht, O., 1998, A meta-model for the analysis and design of organiza‐ tions in multi-agent systems. In Proceedings of the 3nd International Conference on

[27] Ferreira, D., Goletz, T. and Ferraz, R., 2000, A workflow-based approach to the inte‐ gration of enterprise networks, Proceedings CARS& FOF 2000, Port of Spain, Trini‐

[28] Fischer, K., Muller, J. P., Heimig, I., Scheer, A., 1996, Intelligent Agents in Virtual En‐ terprises, Proceedings of the First International Conference and Exhibition on The Practical Applications of Intelligent Agents and Multi-Agent Technology, April 1996,

[29] Fox, M.S., Chionglo, J.F. Barbuceanu, M., 1993, The Integrated Supply Chain Man‐ agement System, University of Toronto, Enterprise Integration Laboratory, Toronto.

[30] Franke, U., 2001, The Concept of Virtual Web Organizations and Its Implications on Changing Market Conditions, Electronic Journal of Organizational Virtualness, Vol.

talising the Corporation for the 21st Century, Harper Business.

tual enterprises, Kluwer Academic Publishers, Toulouse, France.

gineering Publications Ltd.

London.

112 Decision Support Systems

edition.

dad.

London, U.K.

3 No.4.

tion Research, 47 (17).

Multi-Agent Systems (ICMAS-98).

demic Publishers, 2002, Cancun, MX.

[44] Lopes Cardoso, L., Malucelli, A., Rocha, A.P., Oliveira, E., 2005, Institutional Services for Dynamic Virtual Organizations, In 6th IFIP working conference on virtual enter‐ prises (PRO-VE'05), Valencia, Spain.

[57] Rabelo, R.J., Camarinha-Matos, L.M., Vallejos, R., 2000, Agent-based brokerage for virtual enterprise creation in the moulds industry, in E-business and Virtual Enter‐

Emerging Applications of the New Paradigm of Intelligent Decision Making Process: Hybrid Decision Support Systems

for Virtual Enterprise (DSS-VE) http://dx.doi.org/10.5772/3371 115

[58] Rabelo, R. J. Camarinha-Matos, L.M., 1996, Towards Agile Scheduling in Extended Enterprise. In Balanced Automation Systems II - Implementation Challenges for An‐ thropocentric Manufacturing. (Luis M. Camarinha-Matos and Hamideh Afsarma‐

[59] Rabelo, R.J., Camarinha-Matos, L.M., 1994, Negotiation in multi-agent based dynam‐

[60] Rocha, A., Oliveira, E., 1999, An electronic market architecture for the formation of virtual enterprises, in Infrastructures for Virtual Enterprises, Kluwer, Boston.

[61] Slats, P. A., 1995, Logistics Chain Modeling, European Journal of Operational Re‐

[62] Shen, W., Norrie, D., 1999, Agent-Based Systems for Intelligent Manufacturing: A State of the Art Survey, International Journal of Knowledge and Information Systems

[63] Szirbik, N. B., Hammer, D. K., Goossenaerts, J. B. M., Aerts, A. T. M., 1999, Mobile Agent Support for Tracking Products in Virtual Enterprises, AGENT'99, Seattle,

[64] Stone, P., Veloso, M., 2000, Multiagent Systems: A Survey from a Machine Learning

[65] Tølle, M., Bernus, P., 2003, Reference models supporting enterprise networks and vir‐ tual enterprises, International Journal of Networking and Virtual Organisations, Vol.

[66] Tsakopoulos, S., Bokma, A., Plekhanova, V., 2003, Partner evaluation and selection in virtual enterprises using a profile theory based approach, in Proceeding of PRO-VE'03 – Processes and Foundations for Virtual Organizations, Kluwer Academic

[67] Venkatraman, N., Henderson, C., 1998, Real Stategies for Virtual Organising, Sloan

[68] Vernadat, F. B., 1996, Enterprise Modeling and Integration Principles and Applica‐

[69] Wigand, R., Picot, A., Reichwald, R., 1998, Information, Organization and Manage‐ ment: Expanding Markets and Corporate Boundaries, Chichester: John Wiley and

[70] Wildeman, L., 1998, Alliances and networks: the next generation, International Jour‐

ic scheduling, International Journal on Robotics and CIM, Vol.11(4).

prises, Kluwer Academic Publishers.

nesh, (Eds.)), Chapman & Hall.

USA, May, Workshop Notes, ACM.

Perspective, Autonomous Robots, Volume 8, No. 3.

search, No. 87.

1(2).

2, No. 1.

Sons.

Publishers, Switzerland.

Management Review, Issue 40.

tions, Chapman and Hall Publishers.

nal Technology Management, Vol. 15.

[57] Rabelo, R.J., Camarinha-Matos, L.M., Vallejos, R., 2000, Agent-based brokerage for virtual enterprise creation in the moulds industry, in E-business and Virtual Enter‐ prises, Kluwer Academic Publishers.

[44] Lopes Cardoso, L., Malucelli, A., Rocha, A.P., Oliveira, E., 2005, Institutional Services for Dynamic Virtual Organizations, In 6th IFIP working conference on virtual enter‐

[45] Lopes Cardoso, L., Oliveira, E., 2004, Virtual Enterprise Normative Framework With‐ in Electronic Institutions, In Proceedings of the Fifth International Workshop Engi‐

[46] Loss, L., Pereira-Klen, A.A., Rabelo, R.J., 2006, Virtual Organization Management: An Approach Based on Inheritance Information. In Global conference on Sustainable Po‐ duct Deelopment and Life Cycle Engineering. Oct.03-06, Sao Carlos, SP, Brazil.

[47] Luczak et. al., 2005, Realization of the Virtual Enterprise Paradigm in the clothing in‐ dustry though e-business technology, Virtual Organizations Systems and Practice.

[48] Malhotra, Y., 2000, Knowledge Management and Virtual Organizations, Idea Group

[49] Meystel, A.M., Albus, J.S., 2002, Intelligent System: architecture, design and control,

[50] Negretto, H., Hodik, J., Mulder, W., Ollus, M., Pondrelli, P., Westphal, I., 2008, VO Management Solutions: VO management e-services, in Methods and Tools for Col‐

[51] Norman, R., Ramirez, R., 1993, From Value Chain to Value Constellation: Designing

[52] Oliveira, E., Rocha, A.P., 2000, Agents advanced features for negotiation in electronic commerce and virtual organisation formation process, European Perspectives on

[53] Petersen, S.A., Gruninger, M., 2000, An agent-based model to support the formation of virtual enterprises', International ICSC Symposium on Mobile Agents and Multiagents in Virtual organisations and E-Commerce (MAMA'2000), Wollongong, Aus‐

[54] Prelipcean G., Boscoianu M., 2008, An innovative decision support system for strate‐ gic investments in power sector, WSEAS TRANSACTIONS on POWER SYSTEMS,

[55] Prelipcean G., Boscoianu M., 2008, Computational framework for assessing decisions in energy investments based on a mix between real options analysis and artificial neural networks, in Proceedings of the 9th WSEAS International Conference on

[56] Rabelo, R., F Baldo, F., Tramontin, R.J., 2004, Smart configuration of dynamic virtual enterprises, Virtual Enterprises and collaborative Environments, IFIP 5th working conference on virtual enterprises, Kluwer Academic Publishers, Toulouse, France.

Mathematics & Computers in Business and Economics (MCBE'80).

laborative.Netwoked Organisations, Springer, Heilderberg.

Interactive Strategy, Harvard Business Review.

Agent-Mediated Commerce, Springer-Verlag.

ISSN 1790-5060, Issue 6, volume 3, June 2008.

neering Societies in the Agents World (ESAW'04), Toulouse, France.

prises (PRO-VE'05), Valencia, Spain.

Publishing, USA.

114 Decision Support Systems

tralia.

John Wiley and Sons.

[71] Wognum, P.M., Faber, C., 2003, Infrastructures for collaboration in virtual organiza‐ tions, Int. Journal of Computer Applications in Technology, Geneva, Vol. 18, Issue 1-4.

**Chapter 6**

**Optimal Control of Integrated Production – Forecasting**

The production planning problem has received much attention, and many sophisticated models and procedures have been developed to deal with this problem. Many other compo‐ nents of production systems have also been taken into account by researchers in so called

In this work, optimal control theory is used to derive the optimal production rate in a manu‐ facturing system presenting the following features: the demand rate during a certain period depends on the demand rate of the previous period (dependent demand), the demand rate depends on the inventory level, items in inventory are subject to deterioration, and the firm can adopt a periodic or a continuous review policy. Also, we are using the fact that the cur‐ rent demand is related to the previous demand in order to integrate the forecasting compo‐ nent into the production planning problem. The forecast of future demand for the products being produced is needed to plan future activities. Forecasting information is an important input in several areas of manufacturing activity. This problem has been considered in the literature. The proposed approach is different from that of other authors which is mainly based on time-series. In [1], the authors deal with the interaction between forecasting and stock control in the case of non-stationary demand. In [2], the authors assume a distribution for the unknown demand, estimate its parameters and replace the unknown demand pa‐ rameters by these estimates in the theoretically correct model. In [3], the authors propose an approach to evaluate the impact of interaction between demand forecasting method and stock control policy on the inventory system performances. In [4], the authors present a sup‐ ply chain management framework based on model predictive control (MPC) and time series forecasting. In [5], the authors consider a data-driven forecasting technique with integrated inventory control for seasonal data and compare it to the traditional Holt-Winters algorithm

> © 2012 Hedjar et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

© 2012 Hedjar et al.; licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

distribution, and reproduction in any medium, provided the original work is properly cited.

integrated systems, in order to achieve a more effective control over the system.

**System**

**1. Introduction**

R. Hedjar, L. Tadj and C. Abid

Additional information is available at the end of the chapter

[72] Zweger, A., Tolle, M., Vesterager, J., 2002, VERAM: Virtual Enterprise Reference Ar‐ chitecture and Methodology, Global Engineering and Manufacturing in Enterprise Networks GLOBEMEN, eds. I. Karvonen et. al., Julkaisija Utgivare Publisher, Fin‐ land.


*4.1. Iron*

In several studies, a wide range of variation in Fe concentration has been observed in peas, chickpeas, common beans, mungbeans, and lentils (Table 1). Significant genetic variability in Fe concentration was observed in the core collection of common beans [169,170], common bean populations [171–173], and a large collection of lentil accessions [174,175]. Cultivars of lentils (18), peas (17), common beans (10), and chickpeas (8) grown at several locations in Southern Saskatchewan (2005–2006) had Fe concentration of 75.6–100 mg kg−1, 47.7–58.1 mg kg−1, 57.7–80.7 mg kg−1, and 48.6–55.6 mg kg−1, respectively [11]. A 100 g serving of any of these pulse crops provided over 50% of the RDA for Fe. A substantial variation in concentration of Fe was observed in 94 diverse accessions each of chickpeas [12] and peas [13]. Further, Diapari et al. [12] identified several chickpea accessions with high Fe concentration (52–60 mg kg−1) that could be utilized for the development of cultivars with high Fe concentration. Significant variation was observed in Fe concentration (35–87 mg kg−1) in mungbean lines commonly grown in South Asia [176]. In a recent study, Dissanayaka [29] reported significant variation in a pea genome wide association study (GWAS) panel of 177 accessions evaluated at Saskatoon and Rosthern Saskatchewan, Canada, and Fargo, North Dakota, USA.

The environment significantly a ffected the concentration of minerals in field peas, chickpeas, common beans, and lentils grown at di fferent locations in Saskatchewan, Canada [11]. Diapari et al. [13] and Dissanayaka [29] reported a significant e ffect of genotypes, year, and location with higher Fe concentration at Rosthern compared with Saskatoon in peas.

Effect of genotypes was also significant in lentils [25,28] and chickpea [12,28]. Along with environment, Fe concentration was also a ffected by varieties and locations. For example, Ariza-Nieto et al. [177] in common beans and DellaValle et al. [178] in lentils observed di fferences in Fe concentration at the same location due to varieties, whereas Moraghan et al. [179] reported higher Fe concentration in seeds harvested from acid soil compared to calcareous soil. Diapari et al. [13] reported that the genetic factor was responsible for substantial variation in Fe concentration in pea seeds grown at di fferent locations in Saskatchewan.

**Table 1.** Genetic variation and identified genomic regions and/or markers for the seed concentration of variousmicronutrientsinpulsecrops.

**Table 1.** *Cont.*

Several SNP markers associated with Fe concentration were identified in peas [13,26,27,29], chickpeas [12,23], and lentils [24,25] that can be used in marker-assisted selection (Table 1). In peas, Diapari et al. [13] reported an association of nine SNPs with Fe concentration in 94 diverse accessions, whereas Dissanayaka [29] reported significant association of three SNP markers with Fe concentration in a pea GWAS panel of 177 accessions. Ma et al. [26] identified five QTLs for Fe concentration in a pea population developed from "Aragorn" (PI 648006) and "Kiflica" (PI 357292). Similarly, Gali et al. [27] observed several QTLs for seed iron concentration on four LGs of pea population PR-02 (Orb X CDC Striker) and six LGs of PR-07 (Carerra X CDC Striker).

In chickpeas, Diapari et al. [12] identified two SNPs on Chromosome (chr) 4 and one each on chr1 and chr6 in 94 diverse accessions, whereas Upadhyaya et al. [23] observed associations of six QTLs for Fe concentration on Chromosomes 1, 3, 4, 5, and 7 in a population developed from a cross between ICC 4958 and ICC 8261. In lentils, Aldemir et al. [24] identified 21 QTLs for Fe concentration on several linkage groups (three each on LG1, LGII, and LGVII, six QTLs on LGIV, four QTLs on LGV, and two QTLs on LGVI), whereas Khazaei et al. [25] reported nine QTLs in a panel of 138 accessions, and two of them were tightly linked to Fe concentration in Chromosomes 5 and 6. Similarly, several QTLs were identified for Fe concentration in common bean populations, DOR364 X G19833 [171], G14519 X G4825 [172], and G21242 X G21078 [173].


**Abstract**

Bringing a child into your family is an emotional experience. New parents are excited to begin a new chapter with their new little ones but also apprehensive about what the future may bring. The hopes, joys, and anxieties of parenthood are unparalleled. When a child has any kind of special need, those emotions can be more pronounced and all-encompassing as parents and caregivers struggle to adjust to the unknown. This chapter will outline common milestones of young children, challenges experienced by parents and caregivers of young children with exceptionalities, and strategies and resources designed to support families on their journeys. The information is designed to be presented in a way to help set families and their little ones up for success. The content provided in this chapter is built on the premise that knowledge is power, that all children can learn, and that parent-professional partnerships are central to the growth of all learners.

**Keywords:** resources, partnerships, typically developing, atypically developing, child development, resources, challenges


2.2.3. Socio-Environmental Factors

Perceived parental concern regarding adolescent weight. Youths' perception of their parents' concern regarding their weight and if they are getting su fficient physical activity was assessed with a two-item index on a 5-point scale, where 5 is the highest level of perceived parental concern. The following two items were used: How concerned are your parents about you becoming overweight? and How concerned are your parents about you not getting enough physical activity? (Cronbach's α = 0.75) [34].

Perceived parent body size. Two indices that represent how youth perceive their parents' body size were constructed using images of the PBIA, one for males and the other for females. Participants were asked to select the figure that is closest to the usual adult weight of their mother and father: Which number under the figures in the figure Box A is closest to the usual adult weight of your mother? and Which number under the figures in the figure Box B is closest to the usual adult weight of your father? The PBIA silhouettes were modified from Stunkard et al. [47] to include larger body shapes. The silhouettes range from underweight (BMI <19) to highly severe obesity (BMI >50) [48]. The 13-point response scale for each item depicts a spectrum of silhouettes with 1 representing underweight, and 13 representing extremely obese (Cronbach's α = 0.47) [38].

Mother/father healthy values. Perception of parent healthy values was evaluated using two items that ask how concerned your parents are about (1) staying fit and exercising and (2) losing weight or preventing weight gain: How much does your mother/father feel about staying fit and exercising (for herself/himself)? and How much does your mother feel about losing weight or keeping from gaining weight (for herself/himself)? Separate indices were constructed for mother and father health values, with each consisting of these two items (Cronbach's α = 0.73, 0.83, respectively). The response scale for these indices ranges from 1 to 4, with 4 as the highest level of concern [34].

Home availability of healthy foods. An index of fruit and vegetable availability in the home was created using two items that range from 1 to 4, with 4 indicating the highest frequency of healthy food availability in the home: Fruits and vegetables are available in my home ... (1) Never, (2) Sometimes, (3) Usually, (4) Always, and Vegetables are served at dinner in my home ... (1) Never, (2) Sometimes, (3) Usually, (4) Always. (Cronbach's α =0.69) [34].

### 2.2.4. Body Mass Index (BMI)

Height, weight, and waist circumference were measured by trained study sta ff. Participants were weighed to the nearest 0.1 kg while wearing minimal clothing using a calibrated electronic TANITA scale (model BC533; Tokyo, Japan). Height was determined to the nearest 0.1 cm using a conventional stadiometer, with the youth standing barefoot, with their shoulders in a normal position. BMI was determined to categorize participants as healthy-weight, overweight, or obese, based on the World Health Organization (WHO) age- and sex-specific classifications for youth aged 5 to 19 years [53].


**4. Vaginal natural orifice transluminal endoscopic surgery (vNOTES)**

Natural orifice surgery (NOTES) originated in Gastroenterology/General Surgery circa 2004, utilizing rectal and oral endoscopy to visualize the peritoneum through specific visceral organ sites, such as the fundus of the stomach [11]. NOTES was heralded as a novel method of peritoneal access, subverting the need for skin incisions.

Approximately 10 years later, NOTES has been applied to gynecology by several authors. It was piloted first by Dr. Baekenlandt in the setting of hysterectomy, demonstrating feasibility and safety [12, 13] of the technique. It was developed further for other applications, predominately adnexal surgery via posterior colpotomy while maintaining the uterus. Although there has been limited adoption in the US, this technique has reached faster acceptance internationally, with a high percentage of laparoscopic procedures currently being completed using this method in Taiwan [14–16]. Preliminarily, many early studies have found lower blood loss, shorter hospital stay, and less postoperative pain with vNOTES procedures compared to other accepted modalities [17, 18].

For Gynecologists, it is well known that the vaginal epithelium rapidly heals. Vaginal surgery has been performed safely for generations from vaginal hysterectomies to the historic culdocentesis. In many ways, vaginal surgery has been the conventional "natural orifice" surgery. NOTES, therefore, naturally lent itself to gynecologic surgery. vNOTES is particularly useful for adnexal surgery at the time of vaginal hysterectomy, which offers safe, direct visualization of adjacent anatomy. This is particularly useful in light of the growing evidence suggesting that opportunistic salpingectomy may reduce the risk of epithelial ovarian cancers [17].

While this field is in its infancy in the United States, the technique has great potential to meaningfully impact the field of Gynecology. It combines the techniques of our predecessors with novel technology. In the opinion of some authors, this comes at a critically important time, as the classical vaginal surgical skills in Gynecology are at risk of being lost in many academic settings. Vaginal hysterectomies in general practice and in OB/GYN residencies are decreasing [15, 16] in favor of laparoscopic procedures. This is an unsettling trend, where a procedure that was once the hallmark of gynecologic surgery appears to be phasing out slowly. Many authors suggest that a strong benefit of full acceptance of vNOTES techniques in

gynecology will be the maintenance of the vaginal surgery skills. Many consider these skills and techniques of vaginal surgery to be the original first steps towards a minimally invasive culture in gynecology, and that they were seen as the original "calling card" of our field for much of the specialty's existence.


*2.6. Economic Viability*

Prices were obtained from "Fruga", a company trading on the Polish market in fruit produced in Poland and imported from other EU countries. The calculation was based on the average monthly prices received by the grower. Fruit mass losses measured each month were due to transpiration and differences in respiration of fruit undergoing the treatments. In addition, the losses identified after 6 months of storage included fruit mass loss due to fungal diseases and physiological disorders disqualifying the affected fruit as not meeting the highest commercial quality standard applicable in OECD countries [35].

### *2.7. Statistical Analysis*

The results were analysed by one-way and multiple-way ANOVA according to the experimental design, using Statistica 13.3 (TIBCO Software Inc., Palo Alto, CA, USA). The assumed sources of variation included the used rootstocks, the storage atmosphere (CA, NA) and the application of 1-MCP. The mean values were compared using Duncan's test at *p* ≤ 0.05%. The correlation coefficient analysis was carried out using Microsoft Office 365 Excel tools.

#### **3. Results and Discussion**