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The existence of optical-ultraviolet Tidal Disruption Events (TDEs) could be considered surprising because their electromagnetic output was originally predicted to be dominated by X-ray emission from an accretion disk. Yet over the last decade, the growth of optical transient surveys has led to the identification of a new class of optical transients occurring exclusively in galaxy centers, many of which are considered to be TDEs. Here we review the observed properties of these events, identified based on a shared set of both photometric and spectroscopic properties. We present a homogeneous analysis of 33 sources that we classify as robust TDEs, and which we divide into classes. The criteria used here to classify TDEs will possibly get updated as new samples are collected and potential additional diversity of TDEs is revealed. We also summarize current measurements of the optical-ultraviolet TDE rate, as well as the mass function and luminosity function. Many open questions exist regarding the current sample of events. We anticipate that the search for answers will unlock new insights in a variety of fields, from accretion physics to galaxy evolution.

Recent studies of Tidal Disruption Events (TDEs) have revealed unexpected correlations between the TDE rate and the large-scale properties of the host galaxies. In this review, we present the host galaxy properties of all TDE candidates known to date and quantify their distributions. We consider throughout the differences between observationally-identified types of TDEs and differences from spectroscopic control samples of galaxies. We focus here on the black hole and stellar masses of TDE host galaxies, their star formation histories and stellar populations, the concentration and morphology of the optical light, the presence of AGN activity, and the extra-galactic environment of the TDE hosts. We summarize the state of several possible explanations for the links between the TDE rate and host galaxy type. We present estimates of the TDE rate for different host galaxy types and quantify the degree to which rate enhancement in some types results in rate suppression in others. We discuss the possibilities for using TDE host galaxies to assist in identifying TDEs in upcoming large transient surveys and possibilities for TDE observations to be used to study their host galaxies.

PurposeThe current study sought to investigate the moderating effect of supply chain disruptions (SCD) (supply chain – supply disruption, catastrophic disruption and infrastructure disruption) on the relationship between supply chain resilience (SCR) and supply chain performance (SCP) of manufacturing firms in Ghana.Design/methodology/approachThe quantitative research approach and explanatory research designs were utilised. A sample of 345 manufacturing firms were drawn from a population of 2,495 manufacturing firms in the Accra metropolis. The Partial Least Squares Structural Equation Modelling (PLS-SEM) was employed to accomplish the research objectives.FindingsFirst, the study revealed that SCR has a significant positive effect on SCP. Second, the authors found reasonable evidence to support that SCD have a significant positive moderating effect on the relationship between SCR and SCP, except for supply chain catastrophic disruption which had a negative impact. It can be concluded that the components of SCD have heterogeneous impact in the SCR and SCP nexus.Research limitations/implicationsThe study is limited to manufacturing firms in Ghana and does not make a distinction among resilience strategies.Practical implicationsIncreased SCR boost manufacturing companies' supply chains' performance and aid to lessen the adverse effects of SCD relating to infrastructure and supply. It implies that supply chain managers are able to reduce the effects of infrastructure and supply disruptions. Also, techniques that reduce the adverse impact of SCD relating to catastrophe would be beneficial for supply chain managers in Ghana and other countries with comparable economic environments.Originality/valueThe study provides a unique contribution on the moderating role of the dimensions of SCD (supply, infrastructure and catastrophic) on the nexus between SCR and SCP in a developing economy context in a dynamic changing environment. Policymakers would get better insights into instituting the required policies needed to revamp firms with weak supply chains as a result of supply chain disruption.

The purpose of this paper is to provide a review of the literature on the original disruption index (DI 1 ) and its variants in scientometrics. The DI 1 has received much media attention and prompted a public debate about science policy implications, since a study published in Nature found that papers in all disciplines and patents are becoming less disruptive over time. This review explains in the first part the DI 1 and its variants in detail by examining their technical and theoretical properties. The remaining parts of the review are devoted to studies that examine the validity and the limitations of the indices. Particular focus is placed on (1) possible biases that affect disruption indices (2) the convergent and predictive validity of disruption scores, and (3) the comparative performance of the DI 1 and its variants. The review shows that, while the literature on convergent validity is not entirely conclusive, it is clear that some modified index variants, in particular DI 5 , show higher degrees of convergent validity than DI 1 . The literature draws attention to the fact that (some) disruption indices suffer from inconsistency, time-sensitive biases, and several data-induced biases. The limitations of disruption indices are highlighted and best practice guidelines are provided. The review encourages users of the index to inform about the variety of DI 1 variants and to apply the most appropriate variant. More research on the validity of disruption scores as well as a more precise understanding of disruption as a theoretical construct is needed before the indices can be used in the research evaluation practice.

Recent claimed detections of tidal disruption events (TDEs) in multi-wavelength data have opened potential new windows into the evolution and properties of otherwise dormant supermassive black holes (SMBHs) in the centres of galaxies. At present, there are several dozen TDE candidates, which share some properties and differ in others. The range in properties is broad enough to overlap other transient types, such as active galactic nuclei (AGN) and supernovae (SNe), which can make TDE classification ambiguous. A further complication is that “TDE signatures” have not been uniformly observed to similar sensitivities or even targeted across all candidates. This chapter both reviews those events that are unusual relative to other TDEs, including the possibility of TDEs in pre-existing AGN, and summarises those characteristics thought to best distinguish TDEs from continuously accreting AGN, strongly flaring AGN, SNe, and Gamma-Ray Bursts (GRBs), as well as other potential impostors like stellar collisions, “micro-TDEs,” and circumbinary accretion flows. We conclude that multiple observables should be used to classify any one event as a TDE. We also consider the TDE candidate population as a whole, which, for certain host galaxy or SMBH characteristics, is distinguishable statistically from non-TDEs, suggesting that at least some TDE candidates do in fact arise from SMBH-disrupted stars.

The failure of firms in the face of technological change has been a topic of intense research and debate, spawning the theory (among others) of disruptive technologies. However, the theory suffers from circular definitions, inadequate empirical evidence, and lack of a predictive model. We develop a new schema to address these limitations. The schema generates seven hypotheses and a testable model relating to platform technologies. We test this model and hypotheses with data on 36 technologies from seven markets. Contrary to extant theory, technologies that adopt a lower attack (\"potentially disruptive technologies\") (1) are introduced as frequently by incumbents as by entrants, (2) are not cheaper than older technologies, and (3) rarely disrupt firms; and (4) both entrants and lower attacks significantly reduce the hazard of disruption. Moreover, technology disruption is not permanent because of multiple crossings in technology performance and numerous rival technologies coexisting without one disrupting the other. The proposed predictive model of disruption shows good out-of-sample predictive accuracy. We discuss the implications of these findings.

Before the invention of electric lighting, humans were primarily exposed to intense (>300 lux) or dim (<30 lux) environmental light—stimuli at extreme ends of the circadian system’s dose–response curve to light. Today, humans spend hours per day exposed to intermediate light intensities (30–300 lux), particularly in the evening. Interindividual differences in sensitivity to evening light in this intensity range could therefore represent a source of vulnerability to circadian disruption by modern lighting. We characterized individual-level dose–response curves to light-induced melatonin suppression using a within-subjects protocol. Fifty-five participants (aged 18–30) were exposed to a dim control (<1 lux) and a range of experimental light levels (10–2,000 lux for 5 h) in the evening. Melatonin suppression was determined for each light level, and the effective dose for 50% suppression (ED50) was computed at individual and group levels. The group-level fitted ED50 was 24.60 lux, indicating that the circadian system is highly sensitive to evening light at typical indoor levels. Light intensities of 10, 30, and 50 lux resulted in later apparent melatonin onsets by 22, 77, and 109 min, respectively. Individual-level ED50 values ranged by over an order of magnitude (6 lux in the most sensitive individual, 350 lux in the least sensitive individual), with a 26% coefficient of variation. These findings demonstrate that the same evening-light environment is registered by the circadian system very differently between individuals. This interindividual variability may be an important factor for determining the circadian clock’s role in human health and disease.

Purpose This paper aims to identify, analyse and organise the literature about blockchains in supply chain management (SCM) context (blockchain–SCM integration) and proposes an agenda for future research. This study aims to shed light on what the main current blockchain applications in SCM are, what the main disruptions and challenges are in SCM because of blockchain adoption and what the future of blockchains holds in SCM. Design/methodology/approach This study followed the systematic review approach to analyse and synthesise the extant literature on blockchain–SCM integration. The review analysed 27 papers between 2008 and 2018 in peer-reviewed journals. Findings Blockchain–SCM integration is still in its infancy. Scholars and practitioners are not fully aware of the potential of blockchain technology to disrupt traditional business models. However, the electric power industry seems to have a relatively mature understanding of blockchain–SCM integration, demonstrated by the use of smart contracts. Additionally, the disintermediation provided by blockchain applications has the potential to disrupt traditional industries (e.g. health care, transportation and retail). Research limitations/implications The limitations of this study are represented mainly by the scarcity of studies on blockchain–SCM integration in leading journals and databases. Practical implications This study highlights examples of blockchain–SCM integration, emphasising the need to rethink business models to incorporate blockchain technology. Originality/value This study is the first attempt to synthesise existing publications about the blockchain–SCM integration, shedding light on the disruption caused by, and the necessity of, the SCM reconfigurations.

Entering the COVID-19 pandemic wreaked havoc on supply chains. Reacting to the pandemic and adaptation in the “new normal” have been challenging tasks. Exiting the pandemic can lead to some after-shock effects such as “disruption tails.” While the research community has undertaken considerable efforts to predict the pandemic’s impacts and examine supply chain adaptive behaviors during the pandemic, little is known about supply chain management in the course of pandemic elimination and post-disruption recovery. If capacity and inventory management are unaware of the after-shock risks, this can result in highly destabilized production–inventory dynamics and decreased performance in the post-disruption period causing product deficits in the markets and high inventory costs in the supply chains. In this paper, we use a discrete-event simulation model to investigate some exit strategies for a supply chain in the context of the COVID-19 pandemic. Our model can inform managers about the existence and risk of disruption tails in their supply chains and guide the selection of post-pandemic recovery strategies. Our results show that supply chains with postponed demand and shutdown capacity during the COVID-19 pandemic are particularly prone to disruption tails. We then developed and examined two strategies to avoid these disruption tails. First, we observed a conjunction of recovery and supply chain coordination which mitigates the impact of disruption tails by demand smoothing over time in the post-disruption period. Second, we found a gradual capacity ramp-up prior to expected peaks of postponed demand to be an effective strategy for disruption tail control.

Female pet dogs are sterilized by surgically removing their ovaries as a means to eliminate the source of germ cells and sex steroids. Surgical sterilization is inevitably invasive to the animals and costly to their owners, and an alternative method that is non-invasive and affordable has been long sought without success. In this study, a proof-of-concept of sterilizing female dogs by a non-surgical alternative was developed and successfully tested. Presentation: Monday, June 13, 2022 12:30 p.m. - 2:30 p.m.