*3.1. Porosity*

Porosity is one of the most important defects, which is linked to mechanical properties of DED processed parts. There are two major types of porosities: Interlayer porosity and intralayer porosity. Interlayer porosity occurs due to a lack of sufficient energy input to melt the filler material (powder or wire), leading to un-melted regions. This happens near the substrate or between un-melted tracks, when the linear heat input (heat source energy/scanning speed) is decreased or the mass flow rate is increased or a combination of the two. Interlayer pores are usually large and irregular in shape and occur due to higher solidification cooling rates. Low dilution values also cause the occurrence of interlayer porosities. Intralayer porosity is linked to the use of inert shielding gas during the DED process, promoting gas entrapment. Intralayer pores are usually spherical in shape and occur at random locations, owing to vaporization leading to gas trapped porosities, and observed within regions having lower solidification cooling rates [82,85,86]. High dilution refers to the occurrence of intralayer porosities. Interlayer and intralayer porosities are schematically shown in Figure 6a,b, respectively. Porosity is also dependent on the initial powder characteristics and uniformity [87]. If the starting powders do not have a uniform size distribution, it will give rise to more porosity in the final build. Inherent porosity inside the powder particle also leads to defects in the final part [88]. Taking all these modes of porosities into account, it is important to control the shape and size range of powders, and also maintain optimal process parameters during deposition. Porosity can be measured both qualitatively and quantitatively. Some commonly used techniques include the Archimedes principle, X-ray computed tomography, and optical microscopy.

Another important parameter in the literature, referred to as the global energy density (GED), establishes a relationship between interlayer (lack of fusion) and intralayer (keyholing) porosity:

$$\text{GED} = \frac{P}{vd} \tag{8}$$

In Equation (8), GED is defined for laser based DED, where *P* is the laser power, *v* is the scan speed, and *d* is the laser spot size. GED can be easily correlated with dilution. As shown in Figure 6c, lower values of GED lead to less dilution (the negative slope), meaning more propensity to a lack of fusion defect, whereas higher values of GED lead to high dilution (the positive slope), meaning more tendency to form keyhole porosity [85].

**Figure 6.** Schematic of: (**a**) Lack of fusion porosity (interlayer porosity), (**b**) keyholing porosity (intralayer porosity), and (**c**) the intersection of interlayer and intralayer porosity with respect to global energy density (GED).

#### *3.2. Changes in Chemical Compositions due to Solute Segregation and Loss of Alloying Elements*

When several layers are deposited during AM, it gives rise to the redistribution of solute particles, leading to the segregation and formation of heterogeneous microstructural bands, also known as heat a ffected zone (HAZ). This happens due to di fferences in the compositions at the interfaces of the substrate and deposit. The amount of solute segregation also depends upon the solidification cooling rates, with higher solidification cooling rates having a higher probability of a solute trap. These changes give rise to compositional inhomogenity along the printed material [89,90]. Another phenomenon, the loss of alloying elements, occurs due to the preferential vaporization of a few elements in the alloy during DED, due to di fferences in the boiling points of individual elements. For example, in a study of printed 304L stainless steels, compositional gradients developed along the build direction due to a greater loss of volatile elements (e.g., Cr, Mn, and Ni) as more heat built up in the system. The loss of these austenite stabilizers led to an increased hardness in the build direction due to the presence of a more martensitic phase in the upper layers [91]. The Langmuir equation can quantitatively predict the vaporization flux of the alloying elements, given by [65]:

$$J\_{\mathbf{i}} = \frac{\lambda P\_{\mathbf{i}}}{\sqrt{2\pi M\_{\mathbf{i}}T}} \tag{9}$$

where *J*i is the vaporization flux of alloying elements, *M*i is the molecular weight, *P*i is the vapor pressure of the alloying elements, *T* is the temperature, and λ is a positive fraction, which estimates the condensation of some vaporized atoms. Consecutively, the mass of material vaporized can be estimated by:

$$
\Delta m\_{\rm i} = \frac{LA\_{\rm s}I\_{\rm i}}{v} \tag{10}
$$

where Δ *m*i is the mass vaporized, *L* is the track length, *A*s is the melt pool area, *v* is the scan speed, and *J*i is the vaporization flux of alloying elements. An example where the above equations were applied to estimate the amount of material lost during AM inferred that Al in Ti-6Al-4V is most susceptible to composition changes during DED, followed by Mn in stainless steel 316, with the least susceptible being Cr in Inconel 625 [92].

#### *3.3. Printability of Alloys*

Not all alloys are suitable to be processed by AM. Quantitatively, the printability of alloys could be defined using a dimensionless parameter known as thermal strain (Equation (11)). Lower values of thermal strain cause lesser residual stress in the material, thereby increasing the printability of the alloy by AM:

$$
\varepsilon^\* = \frac{\beta \Delta T}{EI} \frac{t}{F} \frac{t}{\sqrt{\rho}} H \tag{11}
$$

where β is the bulk thermal expansion coe fficient, Δ *T* is the change in temperature, *t* is the deposition time, *H* is the heat input, *EI* is the flexural rigidity, *F* is the Fourier number, and ρ is the density of material (the derivation of this particular equation has been performed in literature [92]). So, with an increase in βΔ *T*, *t*, and *H*, there is an increase in the thermal strain, whereas an increase in *EI* and *F* can decrease thermal strain.

#### **4. Mechanical Properties**

## *4.1. Tensile Strength*

The tensile strength and ductility of printed parts is dependent on the DED process parameters and the microstructure. There are several instances from the literature, which record varying trends of tensile behavior and ductility for the same material printed by DED. For instance, in one study, the tensile strength of DED fabricated Ti-6Al-4V was found to be similar to wrought manufactured Ti-6Al-4V, but with reduced ductility [93]. Another study showed that DED processed Ti-6Al-4V has a higher tensile strength due to a finer microstructure as compared with wrought alloy, but still exhibits lower ductility, due to a combination of the fine microstructure and the presence of internal defects [94]. Yet another study on DED processed parts showed an anisotropic porosity and tensile behavior in three di fferent orientations, due to microstructural anisotropy [95]. The same study also demonstrated that with a 0.0124% increase in oxygen and decrease in the alpha lath width of DED processed Ti-6Al-4V, the yield strength and ultimate tensile strength (UTS) increased without any change in ductility. Post-processing, like heat treatments or hot isostatic pressing, tends to improve the ductility with a slight decrease in the tensile strength [94].


**1. Introduction**

Organic fertilizers are derived from municipal sewage sludge (SS), or chicken manure (CM), horse manure (HM), blood and bone meal, and all manures are examples of organic fertiliz‐ ers. Organic fertilizers also include vegetable matter (i.e., cottonseed meal, vegetable remains, and yard waste compost). There is often low available concentrations of nutrients in organic fertilizersusedinagriculturalproduction.However,organicfertilizershaveimportantfunctions that cannot be gained from synthetic inorganic fertilizers, they increase soil organic matter, improve soil physical structure, enhance soil fungal and bacterial activity, and reduce eutro‐ phication (excess N and P in natural water resources), provide low‐cost adsorbents that binds with agricultural contaminants and prevent natural water contamination by pesticides and inorganic fertilizers [1], and hence, reducing the impact of xenobiotics on surface and ground‐ water quality. In addition, over the last 50 years, the amount of N and P pollution entering our nation's waters has escalated dramatically. Thirty percent of US streams have high levels of N and P contamination and drinking water violations due to nitrates and phosphates that have been doubled in the last 8 years [2] due to over application of inorganic fertilizers. According‐ ly, environmentallyandeconomicallyviableagriculture requires theuseof cultivationpractices and innovative technologies that maximize agrochemical efficacy while minimizing their side‐ effects.

Organic farming "farming without chemicals" requires organic fertilizers. While such a definition is concise and clear, it is unfortunately untrue and misses out on several character‐ istics which are of fundamental importance. All materials, living or dead, contain chemical compounds; therefore, organic farming utilizes chemicals. The United States Department of Agriculture (USDA) has framed a handy definition of organic farming: "Organic farming is a production system, which avoids or largely excludes the use of synthetically compounded fertilizers, pesticides, growth regulators, and livestock feed additives." The potential health hazards of pesticide residues, nitrates, and phosphates resulting from conventional agriculture are now receiving attention. There is growing scientific evidence about the positive quality aspects of organically produced food like higher dry matter and vitamin content and improved storage quality. Unlike conventional agriculture, organic farming has not been blessed with extensive research and development, nor have organic farmers had the back‐up of advisory services. Organic farming needs a continued research efforts, and it is agriculture for our future.


#### *4.4. Implications for Policy and Practice*

The current study offers several important implications for policy and practice. Our results highlight the significance of positive father involvement in healthy child development. At the policy level, increased funding and resources should be allocated to support programs and initiatives (e.g., responsible fatherhood programs) that encourage and facilitate positive father involvement in the lives of children among families with low income. At the practice level, more effort is needed to actively engage fathers in parenting interventions, services, and programs. Our finding that fathers' cognitive stimulation is a key promotive factor for children's healthy social, behavioral, and cognitive development points to the need for fatherhood programming to include components that focus on enhancing fathers' involvement in activities that are cognitively stimulating for their children. For example, practitioners working with fathers with low income could help fathers create a languagerich and cognitively stimulating home environment and build skills to interact with their children in ways that promote language and cognitive development (e.g., reading books the child, using educational materials, telling stories, singing songs, etc.) [69]. Further, considering that paternal harsh discipline was a salient risk factor for behavior problems in children, efforts to engage fathers in programs that focus on positive parenting and maltreatment prevention are needed.

#### **5. Conclusions**

The findings of the study contribute to a body of emerging research examining patterns of father involvement among families with low income. The identification of four father involvement patterns (i.e., *high positive involvement*; *engaged but harsh discipline*; *low cognitive stimulation*; *lower involvement*) and their unique associations with child development provide meaningful information that can be incorporated into interventions for young children in socioeconomically disadvantaged families. Given that our findings highlight the pivotal role of positive father involvement, such as paternal cognitive stimulation, on healthy child development, researchers and clinicians developing interventions for positive child development should consider actively engaging fathers in intervention programs and services. Finally, future research should explore potential differences and diversity in patterns of father involvement across different racial/ethnic groups and different developmental stages of children.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/article/ 10.3390/children8121164/s1, Table S1: Descriptive statistics for the indicators, covariates, and distal outcomes, Table S2: Effects of the covariates on the distal outcomes, Syntax S1: Mplus syntax.

**Author Contributions:** Conceptualization, S.Y. and S.S.-S.; methodology, M.K. and J.Y.; formal analysis, M.K. and J.Y.; writing—original draft preparation, S.Y., M.K., J.Y., J.W., A.L. and J.Y.L.; writing review and editing, Y.Z., S.S.-S. and J.Y.L.; project administration, S.Y. and S.S.-S.; funding acquisition, S.Y. and S.S.-S. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Department of Health and Human Services Administration for Children and Families, Office of Planning Research and Evaluation (grant #90PR0015). The content is solely the responsibility of the authors and does not necessarily represent the official views of the study sponsors.

**Institutional Review Board Statement:** The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of The Ohio State University (protocol ID: 2018B0532), approval date is 19 December 2018.

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.

**Data Availability Statement:** Restrictions apply to the availability of these data. Data were obtained from the Inter-university Consortium for Political and Social Research.

**Acknowledgments:** S.Y. was supported by the National Institute of Drug Abuse through K01DA050778 (Yoon, PI).

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

#### **References**

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*3.1.2 AEKF SOC estimator for ANFIS 3RC ECM SAFT Li-ion battery model: accuracy performance*

For simplification purpose and SOC and battery terminal voltage accuracy, as alternative Li-ion 3RC ECM structure required to implement the AEKF SOC estimator on a MATLAB R2021b platform is considered the ANFIS 3RC ECM SAFT Li-ion battery model consisting of Rint-3RC ECM dynamic part block, and second ANFIS model attached to OCV(SOC) nonlinear block. The overall simplified ANFIS 3RC ECM battery model structure is described by the following equations:

$$\text{soc}(k+1) = \text{soc}(k) - \frac{\eta T\_\iota u(k)}{C\_{\text{nom}}},\\\text{soc}(\mathbf{0}) = \text{SOCmi} \tag{19}$$

$$y(k) = V\_{OCV}(k) - V\_d(k) = \left(\frac{anf\text{fs}(soc(k))}{soc(k)}\right)soc(k) - anf\text{fs}(u(k))\tag{20}$$

In all the MATLAB simulations for implementing the AEKF SOC estimator are considered the following parameters values:

• SOC initial value = 0.4,

Covariance of estimated value of SOC, Phat = 1e-10,

The MATLAB simulations results are presented in **Figure 18a–c**. Similar to ARX model developed in previous chapter 2, in **Figure 18** the robustness of AEKF

#### **Figure 18.**

*(a) Robustness of ANFIS AEKF SOC estimator to changes in SOC initial values from SOCini = 0.7 to SOCini = 0.4; (b) the ANFIS 3RC ECM Li-ion battery OCV voltage accuracy.*

#### **Figure 19.**

*(a) The ANFIS 3RC ECM Li-ion battery SOC residual error; (b) the ANFIS 3RC ECM Li-ion battery terminal voltage residual error with respect with the battery terminal voltage estimated by AEKF.*

SOC estimator to changes in the battery SOC initial values from SOCini = 0.7 to SOCini = 0.4 is shown. In **Figure 18b** the predicted values of battery terminal and OCV voltages cell by AEKF and ANFIS are compared with 3RC ECM true values.

The battery SOC and terminal voltage accuracy are revealed in **Figure 19a** and **b**, respectively, based on SOC and battery terminal voltage residuals.

#### **3.2 Discussion: ANFIS models and AEKF SOC estimator performance analysis**

Based on the information accessible from the battery SOC and terminal voltage residual errors presented in the first two subsections of Section 3, more precisely the MATLAB simulation results and the statistics criteria values RMSE, RSE, MAE, MAPE, collected in **Table 2**, can be made a rigorous performance analysis of both ANFIS models and AEKF SOC estimator.

*Investigations of Using an Intelligent ANFIS Modeling Approach for a Li-Ion Battery… DOI: http://dx.doi.org/10.5772/intechopen.105529*


**2.1 Link analysis**

Link analysis is a quantitative study of hyperlinks among websites [15]. Similar to a mechanism of counting of quoted works in journals and articles, the importance of websites can be evaluated with links and their analysis. As previously mentioned, the importance or influence of a website on the Internet is defined as Web Impact Factor [5], which, obviously, is similar to the concept of an impact factor of a journal (*Journal Impact Factor, JIF*).

The idea behind the link analysis is that one can practically assume that a number of links pointing to (guiding toward another location) the academic space of a web content can be proportional to productivity of a research of an organization at the level of a university [9], departments [16], research groups [17], or individual researches [18].

Calculation of WIF [19] can be obtained as a logic amount of a number of links, i.e., external or incoming links (*inlinks*) toward a website divided by a number of sites of a certain web host in a certain moment of time. Further information regarding the calculation of WIF is to be looked for in the work [6, 19].


**3. Conclusion**

Dormancy is a state of lack of germination in seeds/tubers even though the required conditions (temperature, humidity, oxygen, and light) have been provided and is based on hard seed coat impermeability or a lack of supply and activity of the enzymes necessary for germination. Dormancy is an important factor limiting production in many field crops. Several physical and chemical pretreatments are applied to organic material (seeds/tubers) for overcoming dormancy. Physical and internal dormancy can be found together in some plant species and this makes it difficult to provide high-frequency healthy seedling growth, whereas the sprouting of seeds/tubers sown and the formation of healthy seedlings is a prerequisite for plant production. This chapter focuses on four different methods that have not been reported elsewhere for overcoming dormancy. We think that these newly described methods will help growers and researchers to overcome dormancy problem in plant production.


Preface

This book provides a comprehensive overview of current ocular diagnostic methods, including their theoretical basis, practical approach, and usage in clinical practice, as well as recent advances in keratitis treatment methods.

The authors of the 2019 World Health Organization Report on Vision reported that at least 2.2 billion people globally have vision impairment; of these, at least one billion have an issue that could have been treated or prevented. Keratitis is still one of the leading causes of blindness in the world. In most cases, corneal diseases represent preventable or treatable ophthalmic diseases, therefore a comprehensive knowledge of epidemiology, causes, accurate diagnosis, and treatment of the multiple forms of keratitis is crucial in clinical practice.

The book underlines the role of ocular surface system homeostasis. The ocular surface system is composed of the surface and glandular epithelia of the cornea, conjunctiva, lacrimal gland, accessory lacrimal glands, and meibomian gland, and their apical (tears) and basal (connective tissue) matrices, the eyelashes with their associated glands of Moll and Zeis, those components of the eyelids responsible for the blink, and the nasolacrimal duct. All components of this vital system are linked functionally by continuity of the epithelia, by innervation, and by the endocrine, vascular, and immune systems. Ocular surface system homeostasis encompasses the causes, clinical forms, and methods of treatment of multiple diseases including non-infectious and infectious keratitis. Keratitis is a disease of many etiological factors, multiple forms, and different severity; therefore management and therapeutic options should be implemented according to disease form and severity.

The book's first section, discusses the practical approach to treating keratitis. Chapter 1 "Bacterial Keratitis" discusses bacterial keratitis. Chapter 2 "Infectious Keratitis after Surgery" examines potential infectious complications after refractive surgeries. Chapter 3 "Alternative Treatment Approaches in Bacterial Keratitis" reviews novel drug delivery systems, such as contact lenses for constant drug delivery, microemulsions, plasma and phage therapy, cross-linking, thymosin beta 4, novel implantable sustained-release antibacterial disc, and intrastromal injections with antibiotic agents.

The second section covers non-infectious keratitis. Chapter 4 "Peripheral Ulcerative Keratitis Associated with Autoimmune Diseases" presents a stepwise approach to diagnosing and treating peripheral ulcerative keratitis. Chapter 5 "Dry Eye Disease: Chronic Ocular Surface Inflammation" examines the role of ocular surface inflammation in dry eye disease pathogenesis.

The last book section discusses two essential issues related to keratitis: intraocular pressure measurements in Chapter 6 "Challenges of the Intraocular Pressure Measurements in the Keratitis" and prevention of corneal injury in sedated and

mechanically ventilated patients in Chapter 7 "Prevention of Corneal Injury in Critically Ill Sedated and Mechanically Ventilated Patients: Theoretical and Evidence-Based Practice".


**1.4. The routes for synthesis of carbon nanomaterials**

There are several methods employed to obtain carbon nanomaterials. They are described very well by Tomanek in [14].

The nanotubes synthesis involve high energetic or temperature processes such as: arc evaporation (AE), chemical vapor deposition (CVD), conversion of carbon monoxide at high pressure in HiPCO process, ball milling (BM), as well as, the pulsed laser vaporization (PLV).

Arc discharge or arc evaporation (AE) can be used successfully for fullerenes, multi-wall carbon nanotubes and single-wall carbon nanotubes synthesis. Direct current of 10-20V is supplied to electrodes in a cooling inert gas environment. Nanotubes are formed on cathode during electrode evaporation in the direction of electric field lines. On the other hand fullerenes are founded in the soot on chamber walls. For syntheses of single-wall nanotubes the presence of catalyst into electrodes is required [2, 15].

The chemical vapor deposition (CVD) is a very common process for covert hydrocarbons gases into a diamond-like carbon (DLC) coating or carbon nanotubes. Conversion takes place at high temperature in thermal CVD, or can be assisted by plasma in plasma-enhanced CVD (PE-CVD). In the presence of water and by using a substrate (usually silicon) vertically aligned nanotube arrays (VANTAs) can be obtained by CVD. This process is called "Supergrowth".

A low-cost synthesis technique for nanotubes and related nanostructures from layered substances, such as graphite is the ball milling (BM). The BM is performed at room temperature, but the impact of a macroscopic ball on a powdered substance leads locally to a temperature increase that enables rearrangement of chemical bonds. Changes are induced in chemical bonding and structure by pressure, often introduced by hitting the material with a foreign object.

Pulsed laser vaporization (PLV) or laser ablation is a technique to produce high-quality carbon nanostructures. A laser beam is focused on a heated carbon target. The resulting plume and vapors are carried by an inert gas to a cooled cooper collector called cold finger (CF), where the raw material condenses. A sea urchin, also known as a dahlia structure, is a colloquial designation for the compact agglomeration of carbon nano-horns formed during the laser ablation process.

PLV or PLD (pulsed laser deposition) is the technique that will be in great detail described below along the results of the synthesis obtained using this method.


*2.3. Self-Concept Clarity*

As part of our biography, our identities form, evolve, and change in concert with our learning through experiences. These experiences are influenced by both internal and external factors: family, friends, geographic location, religious faith, culture, race, ethnicity, socioeconomic status, perceptions of stress and opportunity, and society. Being is the embodiment of our living existence. As such, it changes throughout our lives such that our biography, our being, is formed through learning acquired from the collective sum of our life's experiences [37]. Our biography is an "unfinished product constantly undergoing change and development—either through experiences that we self-initiate or else through experiences which are initiated by others" [37] (p. 25). Self-concept clarity reflects an individual's internal self-beliefs and is characterized by consistency and temporal stability [38]; however, it may also fluctuate contingent upon the influence of environmental factors [39]. Self-concept has been found to be correlated with psychological well-being and resiliency in adapting to stressors [40,41]. Furthermore, the evaluative self-analysis component of self-concept clarity is correlated with self-esteem, or individual discernment of value [42]. For those that experience IPV, there is a clear association with the self-doubt and loss of agency that negatively affects women's identities [43]. The "certainty about one's beliefs regarding his or her personal attributes" is knowledge integrant of self-esteem and can be influenced by individual perceptions of stress, psychological resiliency, and excogitative behaviors [42] (p. 486). Psychological stresses such as those associated with IPV elicit self-discontinuity or individual perceptions of past and present discontinuity, which necessarily compromise the clarity of self-views. Given that self-concept clarity was found to mediate the relationship between stress and perceptions of well-being, it is paramount that the effects of IPV on identity and concept of self be integral to addressing complex mental health issues [43,44]. This is especially critical given the previously discussed increased prevalence of comorbid mental health factors associated with women.

#### **3. Implications**

It has been suggested that women with poor self-esteem may be at greater risk for developing drug use disorders compared with men; however, research has shown mixed results related to self-esteem enhancing measures as they influence effective treatment outcomes. For example, Trucco et al.'s (2007) alcohol dependence research showed no correlation between self-esteem and the occurrence of relapse or successful treatment outcomes [45]. As such they suggested that while self-esteem may have a role in the development of substance use disorder, increased levels of self-esteem do not necessarily lead to treatment success [45]. Future research focused on "aspects of self-perception" rather than self-esteem as a general construct when looking to develop effective prevention and relapse measures may elucidate mitigation measures [45]. Prior research on selfconcept clarity has focused on distinctions within self-analysis, particularly between the two aspects of self-consciousness: private (attention to one's own thoughts and feelings) and public (awareness of oneself as a social object [46,47]. Women have an increased occurrence of self-reflection upon their own personality characteristics, suggesting higher private self-consciousness and validating prior hypotheses regarding gender differentiation of the self-consciousness trait [47]. Furthermore, women tend to be more open to the experiences of self and others through self-reflection, whereas "individuals higher in masculinity (agency) represented their own and others' emotions in less complex ways" [47] (p. 479). Yet, increased private self-consciousness or self-reflection may exacerbate potential negative self-perception in women. Rumination, the act of engaging in repetitive negative thoughts, "enhances the effects of depressed mood on thinking, impairs effective problem solving, interferes with instrumental behavior, and erodes social support", so that "the initial symptoms of depression among people who chronically ruminate are likely to become more severe and evolve into episodes of major depression" [48] (p. 367). Gender differentiation research in rumination found increased rates of rumination and reflection in women compared to men, with greater statistical significance for those in childhood and adolescence [48].

It is imperative that we gain a clearer understanding of women's lived experiences and values as they relate to the complex nature of mental health, including both IPV and SUD associated outcomes. Individualized interventions that recognize the role that gender, and intersecting identities have on women's experiences will help to potentially reduce stigma and treat trauma. Notably, research on mice has shown epigenetic inheritance of perpetuated trauma through the transformation of genomic changes found in subsequent generations [49] (p. 20). While there is a clear gap in the literature regarding human studies focused on the effect of traumatic stress on inheritance, several studies have shown increased inheritance susceptibility for PTSD [49,50]. Additional research on genetic epidemiology and environmental interactivity associated with SUD is also needed [51]. With the potential for inherited trauma and associated negative biological and psychological outcomes for future generations, we must acknowledge and address symptoms at inception.

The pervasive and expensive nature of complex mental health conditions has created a behavioral health crisis with exorbitant costs for organizations due to employee turnover, and reduced productivity and healthcare. However, companies that ensure that mental health resources and services are accessible improve employee outcomes, thereby increasing organizational performance. In a McKinsey study of more than 1000 employers, greater than 90% reported that the COVID-19 crisis has affected employee productivity and behavioral health [52]. Shortly before the pandemic spread across the globe and ensuing quarantine measures were implemented, published research illustrated the profound need for organizations to focus on mental health. At that time, 91% of respondents believed companies should be concerned about mental health, while 85% who were considering a new job were evaluating associated mental health benefits [53]. Estimates of behavioral health impacts of COVID-19 on the healthcare system in the U.S. alone may reach \$200 billion annually; this does not even factor in vulnerable or at-risk populations [52].