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Internet search is a $120bn business that answers lists of search terms or keywords with relevant links to Internet webpages. Only a few companies have sufficient scale to compete and thus economics of the process are paramount. This study aims to develop a detailed industry-specific modeling of the economics of internet search.

The current research develops a stochastic model of the process of Internet indexing, search and retrieval in order to predict expected costs and revenues of particular configurations and usages.

The models define behavior and economics of parameters that are not directly observable, where it is difficult to empirically determine the distributions and economics.

The model may be used to guide the economics of large search engine operations, including the advertising platforms that depend on them and largely fund them.

Divers were contracted to carry out a detailed baseline survey which will form the Environmental Impact Assessment. This report presents information about the biodiversity of Cawsand Bay and the impact of installing a subsea tidal energy module. Subsequently, this addresses some of the SDG14 targets: 14.5, conserve coastal and marine areas; 14.7, increase the economic benefits from the sustainable use of marine resources to small island developing states and less developed countries; and 14.8, increase scientific knowledge, research and technology for ocean health. Contracted from November to December 2021 over a four-week period, five SCUBA divers conducted baseline transects over regular intervals of five meters at Cawsand Bay in each cardinal direction. Water and sediment samples were analysed to better understand the habitat and benthos at Cawsand Bay. Sediment samples established the biotope by identifying the benthos: sublittoral seagrass beds (SS.SMp.SSgr.Zmar). The data also revealed Zostera marina, commonly known as eelgrass (seagrass), is the most abundant species in the area, resulting in a high oxygen content within the water samples. In turn, this helps establish an environment capable of sustaining high levels of biodiversity for this time of year and is a more efficient support ecosystem.

Those involved in the criminal justice system are very often some of the most marginalised in society and can have some of the most complex needs. Likewise, there is little in the literature on the use of peer support in prison. We begin the chapter by drawing on the literature to examine some of the outcomes associated with peer work in the criminal justice system. The change in identity that marks the desistence process is articulated throughout this chapter. Drawing on his experience of working as a peer in the prison setting, David brings some of these abstract concepts to life.

Mangrove forests are one of the most bio-diverse and productive wetland environments on earth. However, these unique tropical forest environments that occupy coastal areas are among the most threatened habitats globally. These threats include logging, conversion of land for agriculture and mariculture and degradation due to pollution over the past 50 years. The large population of resilient mangroves occupying the Turneffe Atoll area in Belize faces growing anthropogenic threats such as permanent clearing of land for housing, infrastructural development and pollution and natural factors (climate change). Given the few formal studies done to evaluate mangrove resilience at Turneffe Atoll, the purpose of this study was to evaluate mangrove resilience and nursery functions in the Turneffe Atoll Marine Reserve (TAMR).

Mangrove fish abundance and forest structure was assessed by means of a visual census and the point-centred quarter method (PCQM) for 11 sites that span across conservation and general use zones.

This study found that the more resilient mangroves (lower vulnerability ranks, higher standing biomass and higher fish biomass and abundance) exist in general use zones and warrant the need for improved mangrove conservation measures for these areas by Turneffe Atoll Sustainability Association (TASA).

Limitations of the methods for data collection included accessibility within mangrove forests stands when establishing PCQM, observer bias among data collectors, sites without surrounding mangroves were not captured to serve as a true control group and poor visibility underwater affected the estimation of fish species and size. The timeline for this research was only three months based on available funding, and no follow-up study was done to make a true comparison.

The findings of this research have a guiding role in the formulation of conservation measures such as better waste management, a robust framework for mangrove management, a communication strategy to guide public awareness and long-term monitoring surveys.

This study aims to highlight the impact of introducing women directors to board committees, thereby empowering them to contribute to decision-making, and as a result, influence firms’ financial performance in an emerging economy.

This study uses a fixed-effects panel data regression model to test the impact of gender diversity on corporate boards as well as board committees on firms’ financial performance. Two widely used diversity measures, the Blau index and the Shannon index, have been used to enhance the robustness of the results.

The findings suggest that gender diversity on prominent board committees (remuneration committee and nomination committee) positively affects firms’ financial performance when measured by the market-based performance measure, but it is insignificant when measured through accounting-based performance indicator. Furthermore, the benefits of gender diversity accrue to the firms only when women are part of prominent committees and are engaged in governance mechanisms, rather than just being appointed on corporate boards as a means of tokenism.

This study is among the first to investigate the relationship between gender diversity and financial performance through the lens of committee assignments. Moreover, the unique cultural and institutional setting offered by India, which is an emerging economy, provides a fertile ground for understanding the role of women leaders in the workforce.

Maintaining the safety of the human is a major concern in factories where humans co-exist with robots and other physical tools. Typically, the area around the robots is monitored using lasers. However, lasers cannot distinguish between human and non-human objects in the robot’s path. Stopping or slowing down the robot when non-human objects approach is unproductive. This research contribution addresses that inefficiency by showing how computer-vision techniques can be used instead of lasers which improve up-time of the robot.

A computer-vision safety system is presented. Image segmentation, 3D point clouds, face recognition, hand gesture recognition, speed and trajectory tracking and a digital twin are used. Using speed and separation, the robot’s speed is controlled based on the nearest location of humans accurate to their body shape. The computer-vision safety system is compared to a traditional laser measure. The system is evaluated in a controlled test, and in the field.

Computer-vision and lasers are shown to be equivalent by a measure of relationship and measure of agreement. R² is given as 0.999983. The two methods are systematically producing similar results, as the bias is close to zero, at 0.060 mm. Using Bland–Altman analysis, 95% of the differences lie within the limits of maximum acceptable differences.

In this paper an original model for future computer-vision safety systems is described which is equivalent to existing laser systems, identifies and adapts to particular humans and reduces the need to slow and stop systems thereby improving efficiency. The implication is that computer-vision can be used to substitute lasers and permit adaptive robotic control in human–robot collaboration systems.

This paper aims to analyse the influence of workforce diversity on the firm’s likelihood to develop organisational innovations. Operationalising human resources diversity is not straightforward, and its effect has been rather overlooked in the context of non-technological innovations. This study analyses the impact of task-related diversity among research and development (R&D) unit workers and women R&D workers, in particular.

To estimate the impact of task-related diversity on firm propensity to undertake organisational innovation, this study uses a generalised linear model (GLM) – with a binomial family and log–log extension. GLMs are used to control problems of over-dispersion, which, in models with binary response variables, could generate inaccurate standard error estimates and provide inconsistent results.

This paper provides three important results. Firstly, employee diversity increases the firm’s propensity to engage in organisational innovations. Secondly, the influence of each facet of task-related diversity varies depending on the type of organisational innovation considered. Thirdly, gender has an effect on the innovation process; this study shows that women play a different role in the production of non-technological innovations.

This paper makes several contributions to the literature. Firstly, it makes a theoretical contribution to research on innovation management by considering the influence of human resources diversity on the development of non-technological innovations. Secondly, this study analyses the role of workforce diversity in an R&D department context to clarify the contribution made by women R&D workers.

In times of crisis, such as the Covid-19 global pandemic, journalists who write about biomedical information must have the strategic aim to be clearly and easily understood by everyone. In this study, we assume that journalistic discourse could benefit from language redundancy to improve clarity and simplicity aimed at science popularization. The concept of language redundancy is theoretically discussed with the support of discourse analysis and information theory. The methodology adopted is a corpus-based qualitative approach. Two corpora samples with Brazilian Portuguese (BP) texts on Covid-19 were collected. One with texts from a monthly science digital magazine called Pesquisa FAPESP aimed at students and researchers for scientific information dissemination and the other with popular language texts from a news Portal G1 (Rede Globo) aimed at unspecified and/or non-specialized readers. The materials were filtered with two descriptors: “vaccine” and “test.” Preliminary analysis of examples from these materials revealed two categories of redundancy: paraphrastic and polysemic. Paraphrastic redundancy is based on concomitant language reformulation of words, sentences, text excerpts, or even larger units. Polysemic redundancy does not easily show material evidence, but is based on cognitively predictable semantic association in socio-cultural domains. Both kinds of redundancy contribute, each in their own way, to improving text readability for science popularization in Brazil.

This chapter explores the role of artificial intelligence (AI), particularly its subfield of machine learning (ML) methods, as a core technology of the fintech revolution in the financial services industry. It simplifies some of the complex concepts related to AI by introducing the main ML paradigms and related techno-methodic aspects. This chapter uses real-world examples to illustrate how next-generation AI powered by ML is transforming the financial services industry. Next, in illustrating the risks associated with AI adoption, this chapter discusses the need for regulation to address the essential facets of AI governance, including transparency, accountability, ethics, and responsible use. Lastly, it looks at emerging regulatory approaches across leading global jurisdictions. The primary goal is to give readers an initial understanding of AI's profound impact on the financial sector.