bluuebunny/crossref_metadata_2025_split huggingface dataset:
Vulnerability and Capacity Assessment for refugee education crises
Authors: Shamieh Jamal M. , Sawalha Ihab Hanna , Madanat Hanan M. 
Published: September 2020

PurposeThe purpose of this study is to aim at: (1) investigating the vulnerabilities/obstacles that hinder refugees in hosting countries from obtaining quality and adequate education and (2) proposing a Framework for Action to transform these vulnerabilities into capacities.Design/methodology/approachVulnerability and Capacity Assessment (VCA) was used for the purpose of this research. A survey strategy was adopted and data were collected using semi-structured interviews with refugee families. One hundred and twenty families were interviewed.FindingsThe study identified a number of vulnerabilities; including mainly unavailability of educational facilities; quality of the available education; social challenges and psychological needs. The findings revealed that there was a lack of comprehensive and strategic frameworks for mitigating refugee educational crises.Practical implicationsThe lack of adequate and quality education for refugees in host countries is likely to increase illiteracy levels and subsequently trigger humanitarian and natural disasters on the long run. This research emphasizes the importance of developing comprehensive frameworks for quality and adequate refugee education.Originality/valueTo the author's knowledge, and after an extensive review of the existing literature, this is the first study to employ VCA to investigate the extent of the current refugee educational crisis in Jordan. VCA is more commonly used in the context of natural and environmental disasters threatening societies. Relevant authorities need to be aware of the significance of refugee education at individual, communal and national levels, as well as the significance of education to refugee well-being.
Research on key technologies of multi-task-oriented live maintenance robots for Ultra High Voltage multi-split transmission lines
Authors: Jiang Wei , Zou Dehua , Zhou Xiao , Zuo Gan , Ye Gao Cheng , Li Hong Jun 
Published: September 2020

Purpose
The purpose of this study is to solve the key technical problems of the practical application of electric robots. The UHV multi-split transmission line power cable operation robot is an important equipment to ensure the reliable operation of high voltage lines and is a useful exploration to realize high-quality power transmission. As the robot system platform equipment mature and operation environment gradually become more complex, the double arm coordination motion control in extreme environment becomes one of the main bottleneck for its practical in power system.

Design/methodology/approach
This paper summarizes the key technologies related to power cable robots, and aims at key technical indicators such as operation reliability, operation efficiency and operation quality in the robot’s practical process. The dynamic evolution mechanism of the robot’s mechanical configuration, the multi-physics information fusion algorithm in extreme environments, the robot’s autonomous positioning and its error compensation control, the robot’s robust motion control in extreme environments and the dual-arm force-position hybrid coordination control and the dynamic distribution and elimination mechanism of internal forces in the closed chain between robots and operating objects, all the research methods and solutions of the key technologies are proposed, respectively.

Findings
Finally, a new control architecture for power cable robots in the background of the Ubiquitous Power Internet of Things is proposed so as to manage the operation and maintenance of electric power systems. The above key technologies are a new exploration of the operation and maintenance management of EHV (Extra High Voltage) multi-split transmission lines which have laid a solid theoretical foundation for the power cable robot.

Originality/value
High voltage transmission line is the main channel of power transmission. It is an important means to improve the integration of operation and maintenance management of power system to use robot instead of manual inspection and maintenance of power line, in the promotion and application of electric robot. The authors pay attention to the practicability, and the breakthrough of key technologies of robot is the premise of the practicability of robot. In this paper, the robot operation and control in multi-task and complex scenes are studied. The research and implementation of the main key technologies, such as the dynamic evolution mechanism of robot configuration, the coupling and fusion law of multi physical fields in the extreme electric power environment, the autonomous positioning control of manipulator, the robust control of robot in the super electromagnetic field environment and the cooperative operation control of multi manipulator, are discussed.
Group interventions for trauma and substance misuse available for women in criminal justice services: a systematic review of the literature
Authors: Henderson Ashley , Stenfert Kroese Biza 
Published: September 2020

Purpose
In recent years, group interventions have been designed to simultaneously treat the symptoms of post-traumatic stress disorder (PTSD) and substance misuse. This study aims to explore the research literature available regarding these interventions, for women who are involved in the criminal justice system.

Design/methodology/approach
Five electronic databases were searched. The review included primary research papers which reported quantitative outcomes for group interventions for female offenders. The quality of each paper was assessed using the framework developed by Kmet et al. (2004).

Findings
A total of 13 research papers met the inclusion criteria and were selected for this review. The papers indicated promising results for the treatment of PTSD and substance misuse in this population group.

Practical implications
This area of research is in early development. Studies adopted different research designs and used different outcome measures to assess effectiveness. The quality assessment indicated that future research should adopt standardised assessment measures, blind researchers to reduce bias and implement randomised controlled trials to produce more robust findings.

Originality/value
To the best of the authors’ knowledge, this systematic review is the first to explore the effectiveness of these interventions, specifically for women in the criminal justice system. The authors consider the existing evidence base for this population group and propose measures for future research.
Using AI to predict service agent stress from emotion patterns in service interactions
Authors: Bromuri Stefano , Henkel Alexander P. , Iren Deniz , Urovi Visara 
Published: September 2020

PurposeA vast body of literature has documented the negative consequences of stress on employee performance and well-being. These deleterious effects are particularly pronounced for service agents who need to constantly endure and manage customer emotions. The purpose of this paper is to introduce and describe a deep learning model to predict in real-time service agent stress from emotion patterns in voice-to-voice service interactions.Design/methodology/approachA deep learning model was developed to identify emotion patterns in call center interactions based on 363 recorded service interactions, subdivided in 27,889 manually expert-labeled three-second audio snippets. In a second step, the deep learning model was deployed in a call center for a period of one month to be further trained by the data collected from 40 service agents in another 4,672 service interactions.FindingsThe deep learning emotion classifier reached a balanced accuracy of 68% in predicting discrete emotions in service interactions. Integrating this model in a binary classification model, it was able to predict service agent stress with a balanced accuracy of 80%.Practical implicationsService managers can benefit from employing the deep learning model to continuously and unobtrusively monitor the stress level of their service agents with numerous practical applications, including real-time early warning systems for service agents, customized training and automatically linking stress to customer-related outcomes.Originality/valueThe present study is the first to document an artificial intelligence (AI)-based model that is able to identify emotions in natural (i.e. nonstaged) interactions. It is further a pioneer in developing a smart emotion-based stress measure for service agents. Finally, the study contributes to the literature on the role of emotions in service interactions and employee stress.
The role of service firms in societal health: the case for symbiotic value
Authors: Aksoy Lerzan , Alkire (née Nasr) Linda , Kandampully Jay , Kemppainen Laura , Kong Lu , McClelland Laura E. 
Published: September 2020

PurposeThe purpose of this study is to highlight the role that service firms can play to improve societal health and create symbiotic value, defined as value created as a result of collaborative relationships between the firm, its employees, customers and the communities in which it operates.Design/methodology/approachThis manuscript examines the case of Millennials as they make up a dominant portion of the current workforce in society and proposes a conceptual framework for symbiotic value creation.FindingsThis study identifies the need to develop supporting mechanisms for the growing role of Millennials as employees and members of society that ultimately, in turn, create symbiotic value.Originality/valueThe paper proposes an integrative framework beyond the traditional and siloed examination of linkages between employee, customer, firm and society, creating new opportunities for extending a service theory and practice.
Coworking space as a practised place between welfare working and managerial challenges
Authors: Ivaldi Silvia , Galuppo Laura , Calvanese Eduardo , Scaratti Giuseppe 
Published: September 2020

Purpose
The paper aims to analyse a specific configuration of coworking space that emphasises the production of social value in the territory (resilient/welfare-oriented coworking). This kind of space represents the current evolution of coworking that recovers the original meaning of coworking space to promote social changes, questions the role of the physical space and brings to the fore its connections between the internal (space) and the external (territory).

Design/methodology/approach
The paper presents an action research on a rising network of coworking spaces. The action research was based on qualitative interviews of the founders and main stakeholders of the network and monthly meetings discussions with the steering committee of the coworking spaces.

Findings
The paper provides some key elements that highlight different meanings related to the value produced by the coworking spaces and related interpretations of the material and immaterial characteristics of the spaces. The results also highlight different managerial challenges connected with these interpretations.

Originality/value
The main results of the study shed light on the fact that it is not enough to focus on material aspects of the coworking space, such as the design and the dispositions of furniture and the curatorship of the relationships among coworkers, if the desired outcome is a reinterpretation of work against the consolidated individualistic paradigm. Rather, the boundary work is the condition that permits to sustain and maintain the evolutionary trajectory of coworking in the most innovative direction. Inside a network of different stakeholders, aimed at integrating individual and collective needs, the constant crossing of boundaries between people, relationships and contexts is the process that permits to generate new meanings and possibilities of action (affordance), holding a transformative potential.
Earlier and slower or later and faster: Spring migration pace linked to departure time in a Neotropical migrant songbird
Authors: González Ana M. , Bayly Nicholas J. , Hobson Keith A. 
Published: September 2020

Abstract

Migratory birds travel vast distances and the timing of migratory flights can affect survival and the ability to reproduce. For Neotropical migrant songbirds, early spring departure from wintering sites, early arrival to the breeding grounds and higher reproductive success have been related to the use of suitable habitats and environmental conditions during the non‐breeding season. However, how migratory strategies are shaped by winter habitat choice is largely unknown due to the general inability to track birds from specific wintering habitats to stopovers or breeding destinations.

We assessed how winter habitat (native forest vs. shade‐grown coffee plantations) relates to spring departure date and migration pace in Swainson's Thrush Catharus ustulatus. We also determined the effect of departure date and total migration duration on the arrival date of birds detected near or within their breeding range.

We used a novel application of Motus radiotelemetry arrays to track individuals from their wintering grounds in the Andes of South America along their migratory journey to North America.

We found variation in migratory strategies between habitats, with birds wintering in native forest departing later than birds in coffee. We present isotopic evidence for native forest being of higher quality than shade‐coffee for Swainson's Thrush and hypothesize that moister conditions in forest, as shown by stable isotope (δ13C) analysis of thrush whole blood, provides favourable pre‐migratory conditions allowing birds to delay departure from wintering grounds. Habitat, between‐site and ‐year variation in departure date, suggests that birds made facultative adjustments to winter habitat quality and environmental conditions. Independent of habitat, birds that departed later migrated faster and this pattern was maintained along the migration route (n = 44). Migrating earlier and slower or later and faster was unlikely to result in significant differences in arrival time to breeding destinations.

Our findings reveal underappreciated complexity in migratory decisions by long‐distance migrants that contrast with the current paradigm of earlier departures and arrival from optimal habitats. The next step is to understand the relative fitness benefits of early versus late schedules or whether each strategy is an equally good response to experienced conditions.
Determining the prevalence, identity and possible origin of bacterial pathogens in soil
Authors: Ferraresso Jacopo , Lawton Benedict , Bayliss Sion , Sheppard Samuel , Cardazzo Barbara , Gaze Will , Buckling Angus , Vos Michiel 
Published: September 2020

SummarySoil biomes are vast, exceptionally diverse and crucial to the health of ecosystems and societies. Soils also contain an appreciable, but understudied, diversity of opportunistic human pathogens. With climate change and other forms of environmental degradation potentially increasing exposure risks to soilborne pathogens, it is necessary to gain a better understanding of their ecological drivers. Here we use the Galleria mellonella insect virulence model to selectively isolate pathogenic bacteria from soils in Cornwall (UK). We find a high prevalence of pathogenic soil bacteria with two genera, Providencia and Serratia, being especially common. Providencia alcalifaciens, P. rustigianii, Serratia liquefaciens and S. plymuthica strains were studied in more detail using phenotypic virulence and antibiotic resistance assays and whole‐genome sequencing. Both genera displayed low levels of antibiotic resistance and antibiotic resistance gene carriage. However, Serratia isolates were found to carry the recently characterized metallo‐β‐lactamase blaSPR‐1 that, although not conferring high levels of resistance in these strains, poses a potential risk of horizontal transfer to other pathogens where it could be fully functional. The Galleria assay can be a useful approach to uncover the distribution and identity of pathogenic bacteria in the environment, as well as uncover resistance genes with an environmental origin.
An AI framework and a metamodel for collaborative situations: Application to crisis management contexts
Authors: Benaben Frederick , Fertier Audrey , Montarnal Aurélie , Mu Wenxin , Jiang Zheng , Truptil Sebastien , Barthe‐Delanoë Anne‐Marie , Lauras Matthieu , Mace‐Ramete Guillaume , Wang Tiexin , Bidoux Loïc , Lamothe Jacques 
Published: September 2020

AbstractIdentifying, designing, deploying and maintaining accurate collaborative networks of organizations (e.g. responders in a crisis situation) are key activities in nowadays ecosystems. However, there is a lack regarding formal approaches dedicated to characterize collaborative networks of organizations. Formal descriptions of collaborative situations, that could be used, transformed, computed and exploited would be of great benefit for the quality of such collaborative networks. This article presents a model‐based AI framework for describing collaborative situations and the associated formal metamodel dedicated to be instantiated to characterize collaborative situations in a very wide range of application domains. This metamodel (describing collaborative situation between organizations) is structured according to four complementary dimensions: the context (social, physical and geographical environment), the partners (the involved organizations, their capabilities resources and relations), the objectives (the aims of the network, the goals to be the achieved and the risks to avoid, etc.) and the behaviour (the collaborative processes to be implemented by the partners to achieve the objectives in the considered context). Besides, this metamodel can be extended for some precise application domains. This article focuses on this mechanism in the specific context of crisis management.
A mathematical model for the diffusion of emergency warning messages during CBRNe emergencies
Authors: D’Arienzo Marco , Di Paolo Ferruccio , Chiacchiararelli Laura , Malizia Andrea , Indovina Luca 
Published: September 2020

AbstractUnderstanding the diffusion of warning messages is essential to adequately respond to emergency events and situations. This is especially true in urgent scenarios, that is situations where external events are happening at the same rate or faster than the diffusion process itself. In this paper, an information diffusion model (Bass model) is proposed to study the spread of warning messages during emergencies involving urgent diffusion dynamics, for example a CBRNe event. In the present study, the Bass model is applied to two hazardous materials transportation accidents reported in the literature: the Pittsburgh phosphorus oxychloride release and the precautionary evacuation occurred in Confluence due to toxic chemicals released after a train derailment. Warning data collected from the two accidents and reported in published literature studies were used in this work and fitted with the Bass model. The diffusion of emergency warning messages is modelled as a two‐component system, where the spread of information is characterized by (a) a “broadcast process” that disseminates the emergency warning vertically (in the sense that many people are alerted simultaneously) and (b) a horizontal “contagion process” whereby people first hear of the event and then sequentially tell others (social media, word‐of‐mouth and peer‐to‐peer communication). The Bass model provided an excellent fit of the warning diffusion times related to both accidents suggesting that the very first phase of the warning process is sustained by a “broadcast” information diffusion process. However, after less than 1 hr from the beginning of the warning process the efficacy of its diffusion is dominated by the “contagion” component, that is the effectiveness of a robust social network between individuals. In conclusion, the Bass model proved to be a handy tool to assess epidemics spreading of information from the people who adopted the information. Our results suggest that the general Bass model applied to diffusion of emergency warning has the potential to provide key information in the management of emergencies. This approach can be applied right away by professional communicators, advisors and decision‐makers in case of a CBRNe event.
Fingerprint error rate on close non‐matches
Authors: Koehler Jonathan J. , Liu Shiquan 
Published: September 2020

AbstractThe accuracy of fingerprint identifications is critically important to the administration of criminal justice. Accuracy is challenging when two prints from different sources have many common features and few dissimilar features. Such print pairs, known as close non‐matches (CNMs), are increasingly likely to arise as ever‐growing databases are searched with greater frequency. In this study, 125 fingerprint agencies completed a mandatory proficiency test that included two pairs of CNMs. The false‐positive error rates on the two CNMs were 15.9% (17 out of 107, 95% C.I.: 9.5%, 24.2%) and 28.1% (27 out of 96, 95% C.I.: 19.4%, 38.2%), respectively. These CNM error rates are (a) inconsistent with the popular notion that fingerprint evidence is nearly infallible, and (b) larger than error rates reported in leading fingerprint studies. We conclude that, when the risk of CNMs is high, the probative value of a reported fingerprint identification may be severely diminished due to an elevated false‐positive error risk. We call for additional CNM research, including a replication and expansion of the present study using a representative selection of CNMs from database searches.
A Replication Crisis in Methodological Research?
Authors: Boulesteix Anne-Laure , Hoffmann Sabine , Charlton Alethea , Seibold Heidi 
Published: September 2020

AbstractStatisticians have been keen to critique statistical aspects of the “replication crisis” in other scientific disciplines. But new statistical tools are often published and promoted without any thought to replicability. This needs to change, argue Anne-Laure Boulesteix, Sabine Hoffmann, Alethea Charlton and Heidi Seibold
Acetic acid buffer as extraction medium for free and bound phenolics from dried blackcurrant (Ribes nigrum L.) skins
Authors: Azman Ezzat Mohamad , Charalampopoulos Dimitris , Chatzifragkou Afroditi 
Published: September 2020

AbstractThe aim of this study was to investigate the effects of different solvent and extraction temperatures on the free and bound phenolic compounds and antioxidant activity of dried blackcurrant skins (DBS). Apart from acetic acid buffer solution, different solvent systems, including water, methanol, and mixtures of methanol/water, were also employed and the effects of solvent and temperature (30 and 50 °C) on the free and bound forms of anthocyanins, hydroxycinnamic acids, and flavonols yield were assessed. The results showed that among all solvents, acetic acid buffer resulted in the highest free anthocyanin content (1,712.3 ± 56.1 mg/100 g) (P < 0.05) after 2 hr extraction at 50 °C from DBS, while lower amounts of bound anthocyanins and anthocyanidins were detected after acid hydrolysis. Acetic acid buffer extracts exhibited the highest free hydroxycinnamic acid content (268.0 ± 4.5 mg/100 g), total phenolic content (3702.2 ± 259.3 mg GAE/100 g), and DPPH activity (60.7 ± 2.0% of inhibition). However, their free flavonol content was slightly lower (60.2 ± 0.8 mg/100 g) compared to 100% methanol at 30 and 50 °C (71.4 ± 1.5 mg/100 g and 71.5 ± 6.2 mg/100 g, respectively). Two‐way ANOVA indicated interactions between solvent and temperature (P < 0.05), which suggested that the relationship between solvent and phenolic compounds depends on the extraction temperature.Practical ApplicationOverall, acetic acid buffer is more environmental friendly, efficient, and cost effective than other solvents, thus, offering an improved extraction method for phytochemicals as valuable ingredients for nutraceutical applications, from underutilized dried blackcurrant skins (DBS).