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This chapter begins with a brief history of the ways in which alcohol has been ingrained in American culture since the arrival of European settlers and their enslavement of African people. The chapter then addresses important aspects of alcohol and other drug use among college students. Because of the popularity of alcohol and cannabis among college students, they occupy the primary focus of the chapter, although other psychoactive drugs are briefly discussed as well. The chapter draws from data collected by the Healthy Minds Study, the Center for Collegiate Mental Health (CCMH) and the American College Health Association (ACHA) in describing the prevalence of alcohol and cannabis use among college students, as well as trends in the use of both substances. The reasons college students drink and use cannabis are explored, as are the many consequences, including academic, legal, physical and interpersonal. The chapter examines a number of prevention strategies that colleges have used to minimize the negative consequences of substance use, including large-scale scare tactics, educational efforts and norming campaigns, as well as individually tailored programs; the effectiveness of each is reviewed.

Green labeling and green scapes are generally associated with environmental practices known as eco-labeling. In the hospitality industry, the concept of green scapes and green labeling has been associated through the attraction of customers toward hospitality organization's brand mark. Green practices make a customer conscious and more tangible for a brand or product. Somewhere, green practices have the instinct to throw as an open-up strategy for futurism growth and to build the brand mark at the next market step of the industry. The determination of green practices of a hospitality organization is performed by the environment working employees (Villemereuil & Gaggiotti, 2015). The organization is advantageous only when the in-house environment is attractive. Green scapes are performed only on the criteria of key certification. The viewpoint of this chapter is to fulfill the criteria of green practices (Warren et al., 2008), attracting brand marks in the hospitality organizations of UT regions. This chapter will investigate the perceptions of industrial employees attracting the brand mark of any hospitality organization in UT states. This chapter will highlight the impact of B2B and B2C businesses connecting to the working environment toward attracting the brand mark of hospitality organizations in the UT states region. This chapter will be paying heed to discuss the enhancing effect of B2B businesses in the UT states market of the tourism and hospitality sector. The sample collected for this chapter using closed ended questionnaire from hospitality organization or hotels in UT destination.

The term sustainable tourism has been in existence for many years, yet the concept is still lacking universal agreement in terms of definition, a situation reflected in the difficulties encountered in producing, particularly implementing and related policies. The broad range of issues involved with sustainable development makes integrated policy and governance difficult even in the more specific fields such as sustainable tourism. This chapter begins by reviewing the basic elements of sustainable tourism, its links with the parent subject of sustainable development, and the issues involved in applying the ‘triple bottom line’ concept to tourism. It then examines the relationship between policy formulation and application in the context of governance, and the links between governance and power at different levels. While one of the achievements of sustainable tourism has been its widespread acceptance and official adoption of the concept in many countries, regions and communities, this acceptance has not been translated very often into effective action, owing partly to the lack of integration between stakeholders and partly to the multiple viewpoints making up the tourism landscape which rarely achieve unanimity of policy issues. The chapter includes a discussion of case studies at different scales to illustrate the positive and negative results of the implementation of such policies and concludes with a general summation.

This paper aims to improve the delimitation of plant growth stages in the context of weather index insurance design. We propose a data-driven phase division that minimizes estimation errors in the weather-yield relationship and investigate whether it can substitute an expert-based determination of plant growth phases. We combine this procedure with various statistical and machine learning estimation methods and compare their performance.

Using the example of winter barley, we divide the complete growth cycle into four sub-phases based on phenology reports and expert instructions and evaluate all combinations of start and end points of the various growth stages by their estimation errors of the respective yield models. Some of the most commonly used statistical and machine learning methods are employed to model the weather-yield relationship with each selected method we applied.

Our results confirm that the fit of crop-yield models can be improved by disaggregation of the vegetation period. Moreover, we find that the data-driven approach leads to similar division points as the expert-based approach. Regarding the statistical model, in terms of yield model prediction accuracy, Support Vector Machine ranks first and Polynomial Regression last; however, the performance across different methods exhibits only minor differences.

This research addresses the challenge of separating plant growth stages when phenology information is unavailable. Moreover, it evaluates the performance of statistical and machine learning methods in the context of crop yield prediction. The suggested phase-division in conjunction with advanced statistical methods offers promising avenues for improving weather index insurance design.

The UN Sustainable Development Goals (SDGs) use indicators in an attempt to foster policy integration and coherence in order to achieve transformative societal change. But the SDGs, like their predecessor Millennium Goals, have not been entirely successful in this effort. Many studies have identified continuing challenges to integrating multiple goals in this way, linked to the complex patterns of interaction between the goals and the nature of the policy systems and subsystems in which they operate. This chapter builds on the policy design literature to argue that the main aim of the SDGs is to reconcile what are otherwise incoherent policy goals and inconsistent policy instruments in a process of policy integration. This process is made more complex in the case of this kind of “super-wicked” problem in which multiple actors face time constraints across multiple policy levels, sectors and venues. It identifies four different techniques for policy integration in such policy nexuses – policy harmonization, mainstreaming, coordination, and institutionalization – and assesses their possibilities for success in the SDG case against what is possible given the nature of the nexus and the capacity of governments to deal with it. The paper contributes to the current literature on policy integration, wicked problems, and the SDGs by further conceptualizing how integrative strategies can be better designed and implemented through capacity-building efforts aimed at developing coordinative relationships within conflict-ridden, multi-actor and multilevel cross-sectoral policy domains.

Informal conversational encounters are explored using free indirect discourse (FID) as a novel storytelling method to gain a multi-generational understanding of the experiences of women working in public relations (PR) in 1960s/1970s Britain.

Echoing a literary tradition, anonymised transcripts of recordings provide impressionist accounts that immerse the reader in the thoughts and feelings of novelistic characters. An informal network of women narrate their stories with a much younger listener enabling exploration of intergenerational relationships and the intersection of gender and age.

This unstructured approach develops a complex yet natural flow to create unique withness-understandings. The author/narrator introduces a conception of informal conversational encounters, supporting an organic approach of interweaving storying, everyday performance, situated accountings, narrative unfoldings and inside/outside points of view.

An interplay of multiple female voices reveals a degree of symmetry in fractal patterns of women's early career experiences over the duration of a generation. Facilitation of sense-making through intergenerational conversations connects with Mannheim's theory of generational unity.

Women's beginnings of PR careers in 1960s/1970s Britain demonstrate a liberal feminist perspective in taking responsibility for their careers and enjoyment beyond the workplace in a man's world.

This paper aims to present the design development and measurement of two aerodynamic slotted X-bands back-to-back planer substrate-integrated rectangular waveguide (SIRWG/SIW) to Microstrip (MS) line transition for satellite and RADAR applications. It facilitates the realization of nonplanar (waveguide-based) circuits into planar form for easy integration with other planar (microstrip) devices, circuits and systems. This paper describes the design of a SIW to microstrip transition. The transition is broadband covering the frequency range of 8–12 GHz. The design and interconnection of microwave components like filters, power dividers, resonators, satellite dishes, sensors, transmitters and transponders are further aided by these transitions. A common planar interconnect is designed with better reflection coefficient/return loss (RL) (S₁₁/S₂₂ ≤ 10 dB), transmission coefficient/insertion loss (IL) (S₁₂/S₂₁: 0–3.0 dB) and ultra-wideband bandwidth on low profile FR-4 substrate for X-band and Ku-band functioning to interconnect modern era MIC/MMIC circuits, components and devices.

Two series of metal via (6 via/row) have been used so that all surface current and electric field vectors are confined within the metallic via-wall in SIW length. Introduced aerodynamic slots in tapered portions achieve excellent impedance matching and tapered junctions with SIW are mitered for fine tuning to achieve minimum reflections and improved transmissions at X-band center frequency.

Using this method, the measured IL and RLs are found in concord with simulated results in full X-band (8.22–12.4 GHz). RLC T-equivalent and p-equivalent electrical circuits of the proposed design are presented at the end.

The measurement of the prototype has been carried out by an available low-cost X-band microwave bench and with a Keysight E4416A power meter in the microwave laboratory.

The transition is fabricated on FR-4 substrate with compact size 14 mm × 21.35 mm × 1.6 mm and hence economical with IL lie within limits 0.6–1 dB and RL is lower than −10 dB in bandwidth 7.05–17.10 GHz. Because of such outstanding fractional bandwidth (FBW: 100.5%), the transition could also be useful for Ku-band with IL close to 1.6 dB.

Although climate change-related risks affect all stakeholders along the supply chain, the potential impact on small and micro-sized suppliers is incredibly excessive. The corresponding toll of these climate risk threats on the mental health and well-being of owners of small and micro-sized suppliers can adversely affect their participation in sustainability efforts, ultimately impacting the firm's performance. This often-overlooked dynamic forms the core of our research. We probe into two pivotal aspects: how industry dynamism and climate risk affect the mental health and well-being of owners of small and micro-sized suppliers and how, in turn, dictate involvement and, consequently, supply chain sustainability performance. This is further nuanced by the moderating role of the abusive behavior of buyers.

Our study is built on resource dependency theory and the supporting empirical evidence is fortified by a mixed-methods sequential explanatory design. This study comprises three phases. In the first phase, our experiment examines the effect of industry dynamism and climate risk exposure on sustainable supply chain management performance. Hypotheses H1a and H1b are tested in the first phase. The second phase involves using a survey and structural equation modeling to test the comprehensiveness of the model. Here, the relationship between industry dynamism, climate risk exposure, mental health and well-being of owners of small and micro-sized supplier firms, supplier involvement and sustainable supply chain management (H2–H7) is tested in the second phase. In the third phase, we adopt a qualitative approach to verify and provide descriptive explanations of phase two findings.

Our findings underscore the significance of small and micro-sized suppliers in sustainability, offering invaluable insights for both theoretical understanding and practical implementation. Our study highlights that buyers must allocate sufficient resources to support small and micro-sized supplier firms and collaborate closely to address climate change and its impacts.

The key takeaway from this study is that buyer firms should consider SDG 3, which focuses on the good health and well-being of their employees and the mental health and well-being of owners of small and micro-sized suppliers in their upstream supply chain. This approach enhances sustainability performance in supply chains.

This is one of the first studies that shows that industry dynamism and climate risk exposure can negatively impact small and micro-sized suppliers in the presence of a contextual element, i.e. abusive behavior of buyers, and ultimately, it negatively impacts sustainable supply chain performance dimensions.

This study aims to use regression Least-Square Support Vector Machine (LS-SVM) as a probabilistic model to determine the factor of safety (FS) and probability of failure (PF) of anisotropic soil slopes.

This research uses machine learning (ML) techniques to predict soil slope failure. Due to the lack of analytical solutions for measuring FS and PF, it is more convenient to use surrogate models like probabilistic modeling, which is suitable for performing repetitive calculations to compute the effect of uncertainty on the anisotropic soil slope stability. The study first uses the Limit Equilibrium Method (LEM) based on a probabilistic evaluation over the Latin Hypercube Sampling (LHS) technique for two anisotropic soil slope profiles to assess FS and PF. Then, using one of the supervised methods of ML named LS-SVM, the outcomes (FS and PF) were compared to evaluate the efficiency of the LS-SVM method in predicting the stability of such complex soil slope profiles.

This method increases the computational performance of low-probability analysis significantly. The compared results by FS-PF plots show that the proposed method is valuable for analyzing complex slopes under different probabilistic distributions. Accordingly, to obtain a precise estimate of slope stability, all layers must be included in the probabilistic modeling in the LS-SVM method.

Combining LS-SVM and LEM offers a unique and innovative approach to address the anisotropic behavior of soil slope stability analysis. The initiative part of this paper is to evaluate the stability of an anisotropic soil slope based on one ML method, the Least-Square Support Vector Machine (LS-SVM). The soil slope is defined as complex because there are uncertainties in the slope profile characteristics transformed to LS-SVM. Consequently, several input parameters are effective in finding FS and PF as output parameters.