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Water scarcity is increasingly a global cause of concern mainly due to widespread changes in climate conditions and increased consumptive water use driven by the exponential increase in population growth. In addition, increased pollution of fresh water sources due to rising production and consumption of pharmaceuticals and organic chemicals will further exacerbate this concern. Although surface water contamination by individual chemicals is often at very low concentration, pharmaceuticals for instance are designed to be efficacious at low concentrations, creating genuine concern for their presence in freshwater sources. Furthermore, the additive impact of multiple compounds may result in toxic or other biological effects that otherwise will not be induced by individual chemicals. Globally, different legislative frameworks have led to pre-emptive efforts which aim to ensure good water ecological status. Reports detailing the use and types of effect-based measures covering specific bioassay batteries that can identify specific mode of actions of chemical pollutants in the aquatic ecosystem to evaluate the real threat of pollutants to aquatic lives and ultimately human lives have recently emerged from monitoring networks such as the NORMAN network. In this review, we critically evaluate some studies within the last decade that have implemented effect-based monitoring of pharmaceuticals and organic chemicals in aquatic fauna, evaluating the occurrence of different chemical pollutants and the impact of these pollutants on aquatic fauna with special focus on pollutants that are contaminants of emerging concern (CEC) in urban wastewater. A critical discussion on studies that have used effect-based measures to assess biological impact of pharmaceutical/organic compound in the aquatic ecosystem and the endpoints measurements employed is presented. The application of effect-based monitoring of chemicals other than assessment of water quality status is also discussed.

Poly- and perfluoroalkyl substances (PFASs) are a group of synthetic organic surfactants that have become a global concern because of their toxicity and widespread presence in the aquatic environment and organisms globally. In this study, a new analytical method has been developed and validated for the analysis of 15 perfluorinated compounds in different water matrices: river water, drinking water and seawater. Water extraction was performed in anion exchange solid phase extraction cartridges, and extracts were analysed by liquid chromatography in tandem with mass spectrometry. Recoveries for target analytes were between 35 and 120%, depending on the water matrix. Method detection limits were in the range of 0.5–17 ng L−1. The validated method was applied to the determination of perfluorinated compounds in water samples around Ireland. Eight compounds out of fifteen were detected at least in one sample. Measured concentrations were higher in river water than seawater, and drinking water had the lowest levels, although still detectable for a considerable amount of compounds. The most prevalent compounds were PFPeA, PFOA and PFHxA, present in all types of water, and they had the highest concentrations.

Reintroduction programs are important tools for wildlife conservation. However, captive rearing environments may lead to maladaptive behavior and physiological alterations that reduce survival probability after release. For captive rearing programs that raise individuals captured from the wild during early ontogeny for later release, there is a lack of information about when during ontogeny the detrimental effects of captive rearing may become evident. In this study we compared cortisol levels, predation rates and swimming behavior between hatchery-produced and wild-caught larval lake sturgeon (Acipenser fulvescens), a threatened fish species, at three times over 9 days. Cortisol levels did not indicate that hatchery-produced individuals were more stressed, but cortisol reactivity to an acute stressor disappeared for both hatchery-produced and wild-caught larvae after 9 days in the hatchery. Swimming activity levels decreased over time for hatchery-produced larvae but increased over time for wild-caught larvae, suggesting that behavioral trajectories may be programmed prior to the larval stage. Neither increasing nor decreasing activity levels was advantageous for survival, as predation rates increased over time in captivity for larvae from both treatments. Results suggest that physiological and behavioral phenotypes may not accurately predict survival for individuals released from reintroduction programs and that the captive environment may inhibit transition to the wild even if cortisol levels do not indicate high stress. Findings emphasize that even a short amount of time in captivity during early ontogeny can affect phenotypes of individuals captured from wild populations, which may impact the success of reintroduction programs.

Biological monitoring constitutes an integrated approach for the assessment of environment risk of pollutants discharged in wastewater effluents. Among the techniques associated with biological monitoring, the use of biomarkers—molecular, biochemical responses—and bioindicators—individual to community responses—are the most prevalent applied methods. Biomonitoring has been applied in acute and chronic studies, although it is generally accepted that the long-term tests are more sensitive to measure effluent toxicity. A good bioindicator should integrate a long-term interaction of the environmental conditions, and simultaneously react in a quantifiable manner to relevant changes. Biomonitoring integrates the effects of total pollution on many individuals and processes; however, biological variability and the complexity of correlating observed effects with specific pollutants accounts for the need of complementing biomonitoring with chemical analysis. Nonetheless, application of biomonitoring covers essential aspects, such as formulation and validation of ecological water quality objectives, determining the effectiveness of pollution control measures, and as an alarm notification for process failure, among others.

Organoboron chemistry began more than 150 years ago when the synthesis and reactivity of triethylborane was described. Organoboron chemistry research has rapidly increased within the past few decades due to the increased usage of organoboron compounds in organic synthesis and biomedical applications. This chapter gives an overview of the general physical and chemical characteristics of select organoboron compounds. Only compounds incorporating a boron–carbon bond are discussed in detail.

As its periastron passage occurred during the third quarter of 2020, system 24 Aqr is of particular significance. New visual solutions for the latest speckle interferometry observations collected by the Lowell Discovery Telescope (LTD) with its new QWSSI speckle camera are presented here. A variety of techniques were used to analyze the system, including ORBITX code for orbital solution, Al-Wardat’s method for analyzing multiple stellar systems, and Edwards’ method for analyzing visual and spectroscopic binaries. We derive precise masses and the complete set of its fundamental parameters for the three components, and we introduce a new orbital solution, and a new dynamical parallax, which is very close to the measured value given by Hipparcos 2007 and from that of Gaia DR2. In the next section, we discuss the possibility of a coplanar orbit. In conclusion, we demonstrate that we need a 65-m telescope to resolve the inner binary visually, although an array of telescopes could be used instead.

Fear of COVID-19 has been understandably widespread, given continual exposure to dire information from pandemic media coverage and interpersonal communications. The present study addresses a limitation of the extended parallel process model in predicting fear of COVID-19 by inclusion of the concept of emotional contagion. The main gap in the literature is filled by the study’s distinctive contribution that broadens and upgrades the extended parallel process model. The model is extended by its integration with the theory of emotional processing. The study is based on a national panel of adults (N = 206). The methods include path modeling by SmartPLS. In addition, multigroup analyses examine overall model differences between gender classifications. Findings and conclusions can be used to minimize excessive fear, and at the same time to promote confidence in following official public guidance and protective regulations to cope with the pandemic. © The Author(s) 2023.

As companies continue to put data and business analytics as their top priority, universities will need to supply students with the appropriate skill sets that meet this demand and offer future opportunities to their graduates. Although business analytics is a new field, many of the required competencies stem from already established areas such as Information/Computer Technology or Information Systems. Using a sample of 225 randomly selected AACSB accredited business schools this study examined the new developments in Business Analytics undergraduate academic programs, and determined the amount of overlap between the Business Analytics and the Information/Computer Technology degree programs. Our findings reveal that approximately 36 percent of the Business Analytics programs overlap with the Information/Computer Technology programs. In addition, the top three required courses in most Business Analytics programs include a Database course, predictive analytics course, and Introduction to Business Analytics. This research provides valuable insight for schools that haven't adopted a Business Analytics degree yet or are looking to improve their existing curriculum. In addition, colleges and universities can now utilize the appropriate Information Systems courses and include them as important foundation and part of their Business Analytics programs.

This study investigates reasons behind high employee turnover of IT professionals through the value placed on intrinsic, extrinsic, leisure, and social rewards. It addresses two questions; what are the most preferred work values by IT professionals, and how do they differ from other professions. Data was collected via a survey using subjects from Amazon Mechanical Turk. A sample of 380 respondents was used. Key findings reveal that intrinsic rewards were the most important work values for IT professionals followed by leisure, extrinsic, and social rewards. Furthermore, when compared to the preferences of non-IT professionals, the levels of preferences for intrinsic rewards were statistically significantly higher for IT professionals than all other professions. This study provides valuable insight regarding key motivating factors of IT professionals and offers practical implications for practitioners relating to job characteristics that are most likely to reduce IT turnover and rethink their rewards systems.

Faculty teaching data analytics at undergraduate level are often faced with the tension created by student under-preparedness, the demands of the course, and time constraints. How do faculty close this gap? In this paper, we propose the use of flow diagramming as an accessible method for interpreting regression analyses, in ways that are time efficient and not alienating to the student. Our study shows that the use of such flow diagrams has a positive effect on student understanding without additional remedial instruction. Time saved can be directed at core learning objectives of the analytics.

Logistic regression (LoR) is a foundational supervised machine learning algorithm and yet, unlike linear regression, appears rarely taught early on, where analogy and proximity to linear regression would be an advantage. A random sample of 50 syllabi from undergraduate business statistics courses shows only two percent of the courses included LoR. Conceivable reasons for this dearth of LoR content is likely related to topic complexity, time constraints, and varying degrees of tool ease of use and support. We propose that these constraints can be countered by: [1] introducing logistic regression early, [2] informed tool selection prioritizing ease of use with comprehensive output, and [3] using/developing innovative, accessible, and easy to understand concept learning aids. This approach would leverage the proximity to linear regression and probability readily embed distributed practice for student understanding of a foundational technique.

Blockchain is being promoted as the platform to disrupt business as usual in many transaction-heavy sectors. Questions remain about the future standards of blockchain, their feature set, functionality, and the willingness of organisations to disrupt their existing revenue streams via blockchain.  The most significant near-term promise that affords industry is the cost and complexity savings via the standardization of their technology infrastructure stacks.  This paper explores the benefits available of reduced costs and complexity via the adoption of blockchain.

Successful property management, which can be done by individual owners or by professional property managers, has numerous interrelated complex business processes: tenant attraction, screening, leasing, tenant move-in, property maintenance, retention/lease renewals, tenant move-out, and reputation management. Property managers must be highly skilled communicators and thoroughly understand the legal implications of housing and contract law in their operating environments. The lack of affordable solutions available to small and mid-sized property managers drives their use of fragmented technology solutions provided by numerous technology vendors that employ redundant data-gathering methods, putting them at a competitive disadvantage. This research paper explores the information systems needs of property managers in contrast to the solutions available to them in the marketplace.