bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessing inclusivity in online platforms through usability evaluation with Google Analytics
Authors: van den Berg Annelieke C. , Giest Sarah , Kraaij Wessel 
Published: October 2022

AbstractAs online platforms are swiftly becoming a dominant interface of government–citizen interactions, it is crucial that these platforms are inclusive. This article considers the potential of using digital trace data for assessing inclusivity in online platforms. Given that Google Analytics (GA) is a popular tool for collecting and analyzing digital trace data, this article asks to what extent GA is useful in usability evaluation for assessing inclusivity. This article reports on a case study in which GA was used for the usability evaluation of an online participation platform of a local government in The Netherlands. The usability evaluation via GA highlights that the platform was less inclusive toward two categories of users, namely, mobile users and users who access the platform via social media or referral. We conclude that GA is helpful for assessing inclusivity in online government platforms, particularly to the extent that it can be used to monitor whether there are differences in usability for different categories of users. Shortcomings of GA are that it gives limited insights into underlying reasons for identified behavioral patterns, that data quality can be compromised, and that functionalities of GA are restricted based on privacy or legal considerations.
Hypernudging in the changing European regulatory landscape for digital markets
Authors: Morozovaite Viktorija 
Published: October 2022

AbstractThe European regulatory landscape for digital markets is undergoing a transformative change. There is an observed shift toward the protection of public values and fundamental rights, as the market mechanism and market values that traditionally led regulatory processes in digital markets seem to have fallen short. In the context of the user‐centric digital economy, a clear commitment to safeguarding citizens' interests is ever‐more salient. This article provides a comprehensive account of hypernudging—dynamically personalized user steering, which represents the next generation user influencing techniques online, with the potential to lead to multifaceted individual and collective harms. However, problematizing the phenomenon for digital policy purposes is not a straightforward task. Due to the complexity and opaqueness of its underlying mechanisms and effects, policymakers are operating under conditions of uncertainty, necessitating a shared understanding of what impact hypernudging has on users as well as crafting a shared vision of values that ought to be embedded and safeguarded in digital choice architectures. To highlight the developing European approach in relation to hypernudging, the assessment of the recent legislative initiatives—the Artificial Intelligence Act, the Digital Markets Act, and the Digital Services Act—showcases underlying learning opportunities for addressing emergent challenges.
Effects of mindfulness‐based interventions on fatigue and psychological wellbeing in women with cancer: A systematic review and meta‐analysis of randomised control trials
Authors: McCloy Kairen , Hughes Ciara , Dunwoody Lynn , Marley Joanne , Gracey Jackie 
Published: October 2022

AbstractBackgroundCancer diagnosis and treatment can cause fatigue, stress and anxiety which can have a detrimental effect on patients, families and the wider community. Mindfulness‐based interventions appear to have positive effects on managing these cancer‐related symptoms.ObjectiveTo investigate the efficacy of mindfulness on cancer related fatigue (CRF) and psychological well‐being in female cancer patients.MethodsFive databases (CINHAL, Ovid Medline, Ovid Psych Info, Scopus, and Cochrane), and two trial registers (WHO and Clinicaltrials.gov) were searched for randomised control trials from inception to April 2021 and updated in August 2022. Meta‐analysis was performed using Review Manager 5.4. The standardised mean difference (SMD) and 95% confidence intervals (CI) were used to determine the intervention effect. Subgroup analysis was performed for adaptation to types of mindfulness, length of intervention and types of comparator used.ResultsTwenty‐one studies with a total of 2326 participants were identified. Mindfulness significantly improved CRF (SMD −0.81, 95% CI −1.17 to −0.44), depression (SMD−0.74, 95% CI −1.08 to −0.39) and anxiety (SMD −0.92, 95% CI −1.50 to −0.33). No effect was observed for quality of life (SMD 0.32, 95% CI −0.13–0.87) and sleep (SMD −0.65, 95% CI −1.34–0.04). Subgroup analysis revealed that there was little difference in SMD for adapted type of mindfulness (p = 0.42), wait list control compared to active comparator (p = 0.05) or length of intervention (p = 0.29).ConclusionMindfulness appears to be effective in reducing CRF and other cancer related symptoms in women. Adaptations to mindfulness delivery did not have negative impact on results which may aid delivery in the clinical settings.
Expectations versus reality: Understanding the accuracy of impressions made during virtual interviews of pediatric pulmonary fellowship programs
Authors: Atwood Daniel T. , Chiel Laura E. , Nelson Benjamin A. , Casey Alicia M. 
Published: October 2022

AbstractRationaleAs a result of the SARS‐CoV‐2 pandemic, all pediatric pulmonary fellowship programs conducted virtual interviews for the first time in the Fall of 2020. This study aimed to understand the accuracy of virtual‐interview derived‐impressions of fellowship programs, as well as applicant preference for future fellowship interview cycles.MethodsA group of pediatric pulmonary fellows and Program Directors designed a REDCap survey. The survey was distributed to all first‐year pediatric pulmonary fellows who participated in the 2020–2021 virtual interview season.Results23/52 (44%) of first‐year pediatric pulmonary fellows completed the survey. 96% were able to form general impressions about fellowship programs during their virtual interviews. 96% reported that generally their fellowship experience matched their virtual‐interview derived‐impressions. 17 of the 19 factors applicants use to rank programs had no statistically significant change (p > 0.05) in impression from virtual interview to fellowship experience. The two factors with a statistically significant (p < 0.05) change in impression were patient care related—volume of “bread and butter” pediatric pulmonary patients and volume of tertiary care pediatric pulmonary patients. 87% prefer some form of in‐person interview option in future application cycles. A tiered interview format in which applicants are first invited to a virtual interview day followed by an optional in‐person second look day was the most popular preference for future interview cycles (48%).ConclusionsVirtual interviews may provide accurate representations of pediatric pulmonary fellowship programs and applicants prefer some type of in‐person interview option in future application cycles.
Identification and characterization of UDP‐glycosyltransferase genes and the potential role in response to insecticides exposure in Bactrocera dorsalis
Authors: Chen Meng‐Ling , Zhang Shu‐Xia , Guo Peng‐Yu , Qin Qing‐Shi , Meng Li‐Wei , Yuan Guo‐Rui , Wang Jin‐Jun 
Published: October 2022

AbstractBACKGROUNDThe oriental fruit fly, Bactrocera dorsalis (Hendel) is a worldwide pest damaging a wide range of hosts. Due to the long‐term indiscriminate use of insecticides, B. dorsalis has developed serious resistance to several insecticides. UDP‐glycosyltransferases (UGTs) are secondary metabolic enzymes involved in biotransformation and play an important role in the metabolism of plant secondary metabolites and synthetic insecticides in insects. Thus, we suspect that UGTs in B. dorsalis play an important role in insecticide tolerance.RESULTSIn this study, 31 UGT genes were identified in the genome of B. dorsalis, belonging to 13 subfamilies. Real‐time quantitative polymerase chain reaction (RT‐qPCR) results revealed that 12 UGT genes were highly expressed in the antennae, midgut, Malpighian tubule and fat body. The mRNA expressions of 17 UGT genes were up‐regulated upon exposure to λ‐cyhalothrin, imidacloprid, abamectin and chlorpyrifos. Knockdown of the selected five UGT genes (BdUGT301D2, BdUGT35F2, BdUGT36K2, BdUGT49D2, BdUGT50B5) by RNA interference increased the mortality of B. dorsalis from 9.29% to 27.22% upon exposure to four insecticides.CONCLUSIONThe abundance of UGTs in B. dorsalis is similar to other insect species, and 12 out of 31 UGTs were specifically expressed in metabolic tissues, suggesting a key role in detoxification. Down‐regulation of five selected UGT genes increased the susceptibility of B. dorsalis to various insecticides, indicating that UGTs may play an important role in tolerance of B. dorsalis to multiple insecticides. © 2022 Society of Chemical Industry.
Legislators do not harness voter support for disaster preparedness
Authors: Anderson Sarah E. , DeLeo Rob , Taylor Kristin 
Published: October 2022

AbstractNatural disasters are worsening, but elected officials have not adequately invested in programs that would improve disaster preparedness. Federal spending and election outcomes have been taken to suggest policymakers' failure to support long‐term preparedness results from a lack of interest in disaster preparedness among voters and a pervasive preference among voters for more spending on disaster relief than preparedness. However, our national survey experiment on state legislators and public preferences shows that the public is equally interested in disaster preparedness and relief and that both the public and legislators are open to increases in spending on preparedness. The support for preparedness can be motivated by information about past disaster losses rather than having to make difficult predictions about future losses. This study suggests the lack of preparedness spending stems not from voter disinterest, but from a failure of legislators to harness voter support for preparedness. Specifically, the legislators included in our study report being less responsive to attentive voters' preferences on preparedness than relief.
Eliciting and working with student thinking: Preservice science teachers' enactment of core practices when orchestrating collaborative group work
Authors: Chan Kennedy Kam Ho 
Published: October 2022

AbstractAs more and more science teacher educators are subscribing to a practice‐based teacher education curriculum, it is becoming increasingly necessary to identify and articulate smaller grain‐sized teaching practices nested within a core practice in important instructional contexts in order to facilitate preservice science teachers' (PSTs') learning of core practices. This paper illustrates how to achieve this goal using data from a qualitative study that aimed to characterize how PSTs enact the core practice of eliciting and working with student thinking in the three key stages of collaborative group work in rehearsals: whole‐class warm‐up, small group work, and whole‐class share‐out. Based on existing teaching practices synthesized from prior studies, as well as empirical data from the study, we identify the intermediate‐level practices (teaching moves) and technique‐level practices (talk moves) enacted by PSTs when orchestrating group work as well as the PSTs' strengths and missed opportunities in enacting these different grain‐sized practices. Findings reveal that, although the PSTs were able to enact a variety of talk moves when orchestrating group work, they missed opportunities to engage in intermediate‐level practices. For example, there were only a few instances in which the PSTs could explicitly work with the student thinking they noticed while circulating among the groups during whole‐class share‐out. We also identify three ways in which the PSTs used this intermediate‐level practice, reflective of their differing orientations toward using student thinking. We propose an integrative framework that decomposes the focal core practice into a nested set of practices of varying grain sizes, including medium grain‐sized teaching moves and small grain‐sized talk moves, during and across the key stages of group work. We discuss the implications of our findings for science teacher preparation and methodological approaches for capturing PSTs' enactment of the focal core practice, as well as the possible contributions of the framework.
Interventionist Research
Authors: Bjørn Pernille , Menendez-Blanco Maria , Borsotti Valeria 
Published: October 2022

AbstractFemTech.dk is fundamentally about combining research and interventions with a focus on making long-term change. Inspired by sociotechnical design (Mumford 2006) and action research (Bjørn and Boulus 2011; Bjørn and Boulus-Rødje 2015), FemTech.dk follows two main interlinked paths: (1) unpacking and understanding the challenges related to unbalanced gender representation in computer science, and (2) intervening and extending the field of computer science to allow for multiple, diverse agendas. In this way, the overall methodological approach is characterized as action research.
GRACE: Designing Sociomaterial Assemblages Unpacking Gender Equity in Computing
Authors: Bjørn Pernille , Menendez-Blanco Maria , Borsotti Valeria 
Published: October 2022

AbstractThis chapter introduces GRACE, a FemTech sociomaterial assemblage that performs concerns related to equity in computing. GRACE is an interactive installation combining IoT, origami paper, and the history of computing performed at three events in Denmark, the USA, and France. Each event was designed to unpack equity in computing through different types of sociomaterial performances, while allowing us to collect data about the lived experiences of equity in computing. GRACE is both reconfigurable and relational. It is reconfigurable because GRACE is malleable and can take different forms (reaching out to people who are committed to the agenda as well as to people who are within the domain but not necessarily committed to the agenda) – even though its core remains the same. GRACE is relational because the nature of the installation emerges in use and thus is shaped by the relational connections created through specific use and people enacting the artefact. Through sociomaterial manifestations, GRACE seamlessly integrates the performance of equity in computing with data collection on equity in computing. We argue that designing GRACE as a sociomaterial assemblage allowed for long-term engagement with a gender-equity agenda across multiple diverse encounters and over several years.
Classification and Detection of Malicious Attacks in Industrial IoT Devices via Machine Learning
Authors: Shahin Mohammad , Chen F , Bouzary Hamed , Hosseinzadeh Ali , Rashidifar Rasoul 
Published: October 2022

AbstractThe term “the Industrial Internet of Things” has become increasingly more pervasive in the context of manufacturing as digitization has become a business priority for many manufacturers. IIoT refers to a network of interconnected industrial devices, resulting in systems that can monitor, collect, exchange, analyze, and deliver valuable data and new insights. These insights can then help drive smarter, and faster business decisions for manufacturers. However, these benefits have come at the cost of creating a new attack vector for the malicious agents that aim at stealing manufacturing trade secrets, blueprints, or designs. As a result, cybersecurity concerns have become more relevant across the field of manufacturing. One of the main tracks of research in this field deals with developing effective cyber-security mechanisms and frameworks that can identify, classify, and detect malicious attacks in industrial IoT devices. In this paper, we have developed and implemented a classification and detection framework for addressing cyber-security concerns in industrial IoT which takes advantage of various machine learning algorithms. The results prove the satisfactory performance and robustness of the approach in classifying and detecting the attacks.
Assessment of High Porosity Lattice Structures for Lightweight Applications
Authors: Ambu Rita , Calì Michele 
Published: October 2022

AbstractAdditive manufacturing (AM) methods have a growing application in different fields such as aeronautical, automotive, biomedical, and there is a huge interest towards the extension of their use. In this paper, lattice structures for AM are analysed with regards to stiffness and printability in order to verify the suitability for applications where the main requirement of efficiency in terms of stiffness has to be balanced with other needs such as weight saving, ease of manufacturing and recycling of the material. At this aim, lattice structures with high porosity unit cells and large cell size made of a recyclable material were considered with a geometrical configuration allowing 3D printing without any supports. The lattice structures considered were based on body-centred cubic (BCC) and face centred cubic (FCC) unit cell combined with cubic cell. Finally, a multi-morphology lattice structure obtained by mixing different unit cells is also proposed. The lattice structures were modelled and structurally analysed by means of finite element method (FEM), manufactured with a Fusion deposition modelling (FDM) printer and evaluated in relation to printability and dimensional accuracy. The results show that the proposed structure with mixed cells is potentially advantageous in terms of weight saving in relation to the mechanical properties.
Assessment of Ergonomics Risk Experienced by Welding Workers in a Rail Component Manufacturing Organization
Authors: Nedohe Khumbuzile , Mpofu Khumbulani , Makinde Olasumbo 
Published: October 2022

AbstractThe various types of welding workstation designs used in a rail component manufacturing system environment have drawn the attention of industrial engineers to the safety and efficiency of the workers during welding operations. Welding operations are carried out using several posture configurations, which have a negative physical ergonomic impact on the workers, especially in manual welding processes. This empirical research investigates the ergonomics conditions of welding workplaces with the aim of ascertaining the disorders that may be associated with working posture during welding operations among the South African population. Twenty-seven (27) welders were randomly selected, and data was collected using a structured questionnaire. The majority (67 percent of the welders) stated that they experience discomfort and pain whilst they carry out their task, which contradicts ergonomic guidelines for working posture. Forty-eight percent of the welding workers were frequently physically tired. Sixty-three (63) percent agree that they perform repetitive tasks, and a majority of 78% of welding workers reported neck discomfort as a result of tilting their neck posture for a longer period during welding operations. It was deduced that the correlation among risk factors associated with workstation design, repetitive tasks, contribute to the awkward posture adopted whilst welding, that, if retained for a long duration, could lead to musculoskeletal injuries, poor quality of work, and reduced productivity. Based on these results, in order to increase productivity, it was proposed to redesign the welding workstations and to prioritize interventional ergonomic programme to minimize the MSDs problems.
Development of a Sensor Integrated Machining Vice Towards a Non-invasive Milling Monitoring System
Authors: Stavropoulos Panagiotis , Manitaras Dimitris , Papaioannou Christos , Souflas Thanassis , Bikas Harry 
Published: October 2022

AbstractThe future of manufacturing processes is the fully autonomous operation of machine tools. The reliable autonomous operation of machine tools calls for the integration of inline quality control systems that will be able to assess in real time the process status and ensure that the machine tool, process and workpiece are complying with the manufacturing tolerances and requirements. Sensor integrated tooling for machining processes can significantly contribute towards this goal as they can facilitate monitoring close to the actual process. However, most of the solutions proposed so far are highly expensive or very complex to integrate and operate in an industrial environment. To this end, this paper proposes an approach for a sensor integrated vise using low-cost industrial sensors that can easily be integrated in existing machine tools in a non-invasive fashion. The development and dynamic analysis of the system is presented, along with an experimental verification against a lab-scale, high accuracy sensing setup
Development Process for Information Security Concepts in IIoT-Based Manufacturing
Authors: Koch Julian , Eggers Kolja , Rath Jan-Erik , Schüppstuhl Thorsten 
Published: October 2022

AbstractDigital technologies are increasingly utilized by manufacturers to make processes more transparent, efficient and networked. Novel utilization elicits the challenge of preventing deployed information technology from compromising processual security. The digital enabling of formerly analog operation technology, the extensive use of information technology connectivity like MQTT, TCP/IP, Wi-Fi, and the deployment of IoT edge computing platforms create an application scenario for the Industrial Internet of Things (IIoT), which also introduces the associated vulnerabilities, which have been extensively exploited in the past. This paper introduces a development process for information security concepts designed for production scenarios based on the IIoT. This concept is then applied using an illustrative use case from aircraft production. The main contents of the development process include: Formulation of reasonable assumptions, system modelling, threat analysis including risk assessment, recommendation of countermeasures, reassessment after incorporating countermeasures. Specifically, a Data Flow Diagram as the model is developed, and a “risk first” variation of the STRIDE methodology is applied to identify threats and prioritize them. The aforementioned state-of-the-art methodologies are adjusted to our cyber-physical use case in the IIoT. The resulting concept aims to enable manufacturing processes to be digitized as sought. The adjustments to the methodologies are independent from our use case and may be suitable to a broad field of scenarios in the IIoT.
AI-Based Engineering and Production Drawing Information Extraction
Authors: Haar Christoph , Kim Hangbeom , Koberg Lukas 
Published: October 2022

AbstractThe production of small batches to single parts has been increasing for many years and it burdens manufacturers with higher cost pressure. A significant proportion of the costs and processing time arise from indirect efforts such as understanding the manufacturing features of engineering drawings and the process planning based on the features. For this reason, the goal is to automate these indirect efforts. The basis for the process planning is information defined in the design department. The state of the art for information transfer between design and work preparation is the use of digital models enriched with additional information (e.g. STEP AP242). Until today, however, the use of 2D manufacturing drawings is widespread. In addition, a lot of knowledge is stored in old, already manufactured components that are only documented in 2D drawings. This paper provides an AI(Artificial Intelligence)-based methodology for extracting information from the 2D engineering and manufacturing drawings. Hereby, it combines and compiles object detection and text recognition methods to interpret the document systematically. Recognition rates for 2D drawings up to 70% are realized.