bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of parent and youth experiences in advisory groups as part of a mental healthcare clinical trial: protocol for a mixed-method study
Authors: Rasiah Jananee , Freedman Stephen , Macdonald Lee , Prisnie Kassi , Eltorki Mohamed , Finkelstein Yaron , Hopkin Gareth , Santana Maria-Jose , Thull-Freedman Jennifer , Stang Antonia , Prebeg Matthew , Gagnon Isabelle J , Steele Margaret , Mater Ahmed , Katz Laurence , Greenfield Brian , Plotnick Laurie , Monga Suneeta , Lipman Ellen Louise , Wright Bruce , Dimitropoulos Gina , Porter Robert , Hurley Katrina , Al Hamarneh Yazid N , Newton Amanda
Published: June 2022

Introduction

Patient engagement in healthcare research is a necessity to ensure that research objectives align with priorities, outcomes and needs of the population under study, and to facilitate ease of implementation and adoption of findings. In clinical trials, there is an increasing focus on patient engagement during the planning and conduct of clinical trials due to the potential for ethical and methodological benefits. As patient engagement in clinical trials increases, there is a need to evaluate the approaches of these activities to contribute evidence on what is most appropriate and successful. The purpose of this study is to evaluate patient engagement processes and the activities of patient partners during and after a paediatric mental healthcare trial.

Methods and analysis

Using a mixed-methods study design, we will evaluate patient partners’ engagement activities across set time-points during the trial and after trial completion. In this study, the term ‘patient partner’ is inclusive of two groups of people with lived experience: (1) caregivers (parents, formal/informal caregivers and family), and (2) youth (aged 15–24 years). Engagement will be evaluated using the participant and project questionnaires of the Public and Patient Engagement Evaluation Tool (PPEET), followed sequentially by semi-structured interviews. Quantitative data from the PPEET questionnaire will be analysed and reported using descriptive statistics. Data from open-ended questions from the PPEET questionnaires and semi-structured interviews will be analysed using thematic analysis.

Ethics and dissemination

Approval from Athabasca University Research Ethics Board will be obtained for this project. Findings will be disseminated at both academic and public venues whether in-person or online, and using platforms that are caregiver and youth friendly.

Trial registration number

NCT04902391.
Exploring social capital for family caregivers of patients with chronic organ failure: study protocol for a concept mapping study
Authors: Ng Marques Shek Nam , So Winnie Kwok Wei , Choi Kai Chow , Chan Wallace Chi Ho , Chan Helen Yue Lai , Chan Carmen Wing Han
Published: June 2022

Introduction

Many family caregivers experience significant burdens, especially those who take care of patients with chronic organ failure. Although the social welfare system offers some material assistance, a more sustainable approach to supporting caregivers is warranted. This study aims to explore the social capital (ie, the internal strengths of a community that facilitate different social roles) available for these family caregivers.

Methods and analysis

A participatory design based on Trochim’s concept mapping framework will be used in this study. A total of 119 participants, including patients, family caregivers, professionals and other community members, will be recruited from the community. The study will be divided into three phases. In Phase I, qualitative methods will be used to prepare and generate statements. Participants will be asked to share their views on social capital for family caregivers through interviews. In Phase II, quantitative methods will be used to arrange these statements into a concept map, and participants will be asked to complete a questionnaire to prioritise the statements. Statistical methods will be used to create a map based on the responses. In Phase III, the concept map will be used to formulate action plans. The findings will be presented to the public to produce recommendations for social policy.

Ethics and dissemination

This study was approved by The Chinese University of Hong Kong Survey and Behavioural Research Ethics Committee (Reference No.: SBRE-20-714). Informed consent will be obtained from all participants. This study will reveal which forms of social capital can be mobilised to support family caregivers of patients with chronic organ failure. Recommendations on policies to improve the caregiving experience, strengthen social capital and enhance social care will be produced. Findings will be disseminated through academic conferences and journals, as well as local media to create a greater social impact.

Trial registration number

ChiCTR2100044171.
Automating scattering amplitudes with chirality flow
Authors: Lifson Andrew , Sjödahl Malin , Wettersten Zenny
Published: June 2022

Recently we introduced the chirality-flow formalism, a method which builds on the spinor-helicity formalism and is inspired by the color-flow idea in QCD. With this formalism, Feynman rules and diagrams are simplified to the extent that it is often possible to immediately, by hand, write down a helicity amplitude given a Feynman diagram. In this paper we show that the method can also speed up numerical evaluation of scattering amplitudes by considering $$e^+ e^-$$

e
+

e
-

going to n photons in a MadGraph-based tree-level implementation. We find that the computation time is reduced by roughly a factor ten for six photons, and that it scales better with the number of external particles than the default MadGraph5_aMC@NLO implementation. This performance gain is in part attributed to the more compact Lorentz structures involved, and in part due to a transparent choice of gauge reference vectors which reduces the number of Feynman diagrams considered.
Time evolution of the inside of the black hole’s horizon
Authors: Hadi H. , Darabi F.
Published: June 2022

We consider the Wheeler–DeWitt equation near the horizon of the black hole where the entangled vacuum state is chosen as the static universe state. Then, using the entangled property of the vacuum state, we investigate the dynamical evolution of the subsystems, namely inside and outside of the horizon
Cybersecurity for Battlefield of Things — A Comprehensive Review
Authors: Singh Anuraj , Sharma Gaurav , Krishnamurthi Rajalakshmi , Kumar Adarsh , Bhatia Surbhi , Mashat Arwa
Published: June 2022

Battlefield of Things (BoT) is a modern defense network that connects smart military devices to strategic networks. Cybersecurity plays a vital role in maintaining the security of BoT networks and provides encrypted communication networks with combat devices on an end-to-end or peer-to-peer basis. This paper proposes approaches to BoT networks that operate on a three-tier architecture, starting with an application and service layer, a network and cybersecurity layer, and finally, a battlefield layer; implements CNN-YOLO-based target detection; and also formulates information security policies, privacy, and IT laws to maintain algorithmic data access and authorization. It connects a battlefield combat equipment network to a command data center’s ground base station wireless, Bluetooth, sensor, radio, and ethernet cable. This paper analyzes prior Internet of Things (IoT) device attack strategies by collecting data sets of IoT security breaches from external sources. How the system security works, what breach techniques an attacker can use, how to avoid these, and how our systems can be strengthened to protect us from future attacks are discussed in detail.
A Deep Convolutional Neural Network Stacked Ensemble for Malware Threat Classification in Internet of Things
Authors: Naeem Hamad , Cheng Xiaochun , Ullah Farhan , Jabbar Sohail , Dong Shi
Published: June 2022

Malicious attacks to software applications are on the rise as more people use Internet of things (IoT) devices and high-speed internet. When a software system crash happens caused by malicious action, a malware imaging method can examine the application. In this study, we present a novel malware classification method that captures suspected operations in a variety of discrete size image features, allowing us to identify such IoT device malware families. To decrease deep neural network training time, essential local and global image features are selected using a combined local and global feature descriptor (LBP-GLCM). The classification performance of the proposed deep learning model is improved by combining the predictions of weak learners (CNNs) and using them as knowledge input to a multi-layer perceptron meta learner. This is a neural network ensemble with stacked generalization that is used to improve network generalization ability. The public dataset used for performance evaluation contains 5472 samples from 11 different malware families. In order to compare the proposed methodology to current malware detection systems, we developed a baseline experiment. The proposed approach improved malware classification results to 98.5% accuracy and 98.4% accuracy when using [Formula: see text] and [Formula: see text] image sizes, respectively. Overall, the results showed that the stacked generalization ensemble with multi-step extracting features is a more effective method for classification performance and response time.
Alternating odd pretzel knots and chirally cosmetic surgeries
Authors: Varvarezos Konstantinos
Published: June 2022

A pair of surgeries on a knot is chirally cosmetic if they result in homeomorphic manifolds with opposite orientations. Using recent methods of Ichihara, Ito, and Saito, we show that, except for the (2, 5) and (2, 7)-torus knots, the genus 2 and 3 alternating odd pretzel knots do not admit any chirally cosmetic surgeries. Further, we show that for a fixed genus, at most finitely many alternating odd pretzel knots admit chirally cosmetic surgeries.
Traversable wormhole solutions in f(R,T) gravity with noncommutative geometry
Authors: Godani Nisha
Published: June 2022

In this paper, the wormholes have been constructed in the framework of the linear [Formula: see text] gravity model with noncommutative geometry. The wormhole solutions are obtained in the context of Gaussian and Lorentzian distributions of matter using [Formula: see text] gravity. The energy conditions such as null, weak, strong, and dominant energy conditions are explored and the regions satisfying these conditions are examined for both forms of matter distributions. Further, the stability of wormhole solutions is studied with the help of TOV (Tolman–Oppenheimer–Volkoff) equations. It is found that the wormhole solutions are stable and free from exotic matter for the suitable choice of parameters.
Complexity of distances: Theory of generalized analytic equivalence relations
Authors: Cúth Marek , Doucha Michal , Kurka Ondřej
Published: June 2022

We generalize the notion of analytic/Borel equivalence relations, orbit equivalence relations, and Borel reductions between them to their continuous and quantitative counterparts: analytic/Borel pseudometrics, orbit pseudometrics, and Borel reductions between them. We motivate these concepts on examples and we set some basic general theory. We illustrate the new notion of reduction by showing that the Gromov–Hausdorff distance maintains the same complexity if it is defined on the class of all Polish metric spaces, spaces bounded from below, from above, and from both below and above. Then we show that [Formula: see text] is not reducible to equivalences induced by orbit pseudometrics, generalizing the seminal result of Kechris and Louveau. We answer in negative a question of Ben Yaacov, Doucha, Nies, and Tsankov on whether balls in the Gromov–Hausdorff and Kadets distances are Borel. In appendix, we provide new methods using games showing that the distance-zero classes in certain pseudometrics are Borel, extending the results of Ben Yaacov, Doucha, Nies, and Tsankov. There is a complementary paper of the authors where reductions between the most common pseudometrics from functional analysis and metric geometry are provided.
Every Δ20 degree is a strong degree of categoricity
Authors: Csima Barbara F. , Ng Keng Meng
Published: June 2022

A strong degree of categoricity is a Turing degree [Formula: see text] such that there is a computable structure [Formula: see text] that is [Formula: see text]-computably categorical (there is a [Formula: see text]-computable isomorphism between any two computable copies of [Formula: see text]), and such that there exist two computable copies of [Formula: see text] between which every isomorphism computes [Formula: see text]. The question of whether every [Formula: see text] degree is a strong degree of categoricity has been of interest since the first paper on this subject. We answer the question in the affirmative, by constructing an example.
Space-time fractional Anderson model driven by Gaussian noise rough in space
Authors: Liu Junfeng , Wang Zhi , Wang Zengwu
Published: June 2022

In this paper, we study a class of space-time fractional Anderson model driven by multiplicative Gaussian noise which is white/colored in time and has the covariance of a fractional Brownian motion with Hurst index [Formula: see text] in space. We prove the existence of the solution in the Skorohod sense and obtain the upper and lower bounds for the [Formula: see text]th moments for all [Formula: see text]. Then we can prove that solution of this equation in the Skorohod sense is weakly intermittent. We also deduce the Hölder continuity of the solution with respect to the time and space variables.
COMPLEX NETWORK ANALYSIS OF A GRAPHIC NOVEL: THE CASE OF THE BANDE DESSINÉE THORGAL
Authors: LABATUT VINCENT
Published: June 2022

The task of extracting and analyzing character networks from works of fiction, such as novels and movies, has been the object of a number of recent publications. However, only a very few of them focus on graphic novels, and even fewer on European graphic novels. In this paper, we focus on Thorgal, a bande dessinée, i.e. a comic of the French-Belgian tradition. We manually annotate all the volumes of this series, in order to constitute a corpus allowing us to extract its character network. We perform a descriptive analysis of the network structure and compare it to real-world and fictional social networks. We also study the effect of character filtering over the network structure. Finally, we leverage complex network analysis tools to answer two research questions from the literature, related to the similarity between Thorgal and the Saga of Icelanders; and to the position of women in the series. Our data and source code are both publicly available online.
Free Vibration Analysis of Rectangular Thin Plates Resting on Nonhomogeneous Elastic Foundations by Using Matched Interface and Boundary Algorithms and their Multi-Domain Formulations
Authors: Song Zhiwei , He Xiaoqiao , Li Wei
Published: June 2022

Matched interface and boundary (MIB) algorithms and their multi-domain formulations are developed to solve free vibration problems of thin plates resting on unidirectionally and bidirectionally nonhomogeneous elastic foundations. Winkler and Pasternak types of elastic foundations are considered. Three types of MIB algorithms are introduced to handle unidirectional interfaces caused by nonhomogeneous foundations. On the basis of in-depth understanding of MIB method and Kirchhoff plate theory, new multi-domain MIB (MD-MIB) algorithms are proposed to handle bidirectional interfaces caused by nonhomogeneous foundations that cannot be handled by using the existing MIB method. Three types of MD-MIB algorithms are developed by using three domain decomposition strategies. A number of examples are chosen to validate the applicabilities of different MIB and MD-MIB algorithms to the title problems. Numerical results obtained by using MIB and MD-MIB algorithms are compared with the existing solutions or finite element solutions. Numerical studies show that MIB and MD-MIB algorithms are efficient approaches to deal with nonhomogeneous elastic foundations.
EXAMINING THE IMPACTS OF TRUST AND CREATIVITY ON INNOVATION FOCUSED PROMOTIVE VOICE
Authors: SABOL MISTY A. , WINTON BRADLEY G.
Published: June 2022

Drawing upon the literature on individual creativity, trust, and promotive voice, this study proposes that the intra-individual characteristics of creativity and innovation trust affect an individual’s innovation-focused promotive voice. This study argues that creativity is an antecedent to innovation-focused promotive voice and that innovation trust mediates this relationship. Using data from 288 participant responses, we apply PLS structural equation modelling to explain innovation-focused promotive voice. Results show that trust has meaningful relationships with creativity and innovation-focused promotive voice. These results suggest that intra-individual factors impact interpersonal relations and interactions among innovators in regard to proposing innovative ideas. These insights contribute to the conversation on how scholars and practitioners can better organise and lead people to facilitate the development and management of innovation.
Construction of Fuzzy Hyper BCI-Algebras Using Fuzzy Hypergroupoid
Authors: Muhiuddin G. , Mohammadzadeh E. , Mohammadzadeh F. , Borzooei R. A.
Published: June 2022

In this paper, by considering the notion of fuzzy hyperoperation, we define the concept of fuzzy hyper [Formula: see text]-algebras as a generalization of [Formula: see text]-algebras and study related properties. Moreover, we introduce the notions of fuzzy hyper [Formula: see text]-ideal and weak (strong) fuzzy hyper [Formula: see text]-ideal, and then examine the relations among them. Finally, we investigate the relation between fuzzy hyper [Formula: see text]-algebras with fuzzy hypersemigroup, fuzzy hypergroup and hyper [Formula: see text]-algebras.
Impact of time delay and cooperation strategy on the stability of a predator–prey model with Holling type III functional response
Authors: Benamara I. , El Abdllaoui A. , Mikram J.
Published: June 2022

In this paper, we propose and analyze a delayed predator–prey model with Holling type III functional response taking into account cooperation behavior in predators. The time delay is introduced in the attack rate to represent the time necessary to trigger the attack. Each analytical result is followed by an ecological interpretation. We investigate the effect of hunting cooperation on both the number and the level of positive steady states. We observe that the level of the positive equilibrium decreases when increasing the hunting cooperation parameter. Then, we study the impact of the delay as well as the cooperation in hunting on the dynamics of the system. We prove that the presence of delay in the attack rate induces stability switches around the coexisting equilibrium when predators cooperate. In addition, we consider the discrete delay as a bifurcation parameter and prove that the model undergoes a Hopf-bifurcation at the coexisting equilibrium when the delay crosses some critical values. Numerical simulations are presented to confirm our analytical findings.
Quasi-statistical convergence in neutrosophic normed spaces for triple sequence spaces
Authors: Granados Carlos , Choudhury Chiranjib
Published: June 2022

In this paper, we present the notion of quasi-statistical convergence of triple sequences in the neutrosophic normed spaces mainly as a generalization of statistical convergence of triple sequences. We investigate a few principal properties of the newly presented notion and investigate the relationship with statistical convergence of triple sequences in the neutrosophic normed spaces. In the end, we introduce the concept of quasi-statistical Cauchy sequence of triple sequences and show that quasi-statistical Cauchy sequences for triple sequences are equivalent to quasi-statistical convergent triple sequences in the neutrosophic normed spaces.
Radiation Hardening Design of Nonvolatile Hybrid Flip-Flop Based on Spin Orbit Torque MTJ and SRAM
Authors: Zhao Dongyan , Wang Yubo , Chen Yanning , Shao Jin , Fu Zhen , Wang Guangyao , Pan Biao , Zhang Peng , Pan Cheng
Published: June 2022

Spin orbit torque magnetic tunnel junction (SOT-MTJ) has been widely used for designing nonvolatile flip-flop (NVFF), thanks to its ultrafast switching speed, zero static power consumption, nearly unlimited endurance, etc. However, in the space environment, the write pulse width of the SOT-MTJ is comparable to radiation-induced current duration. Thus, the SOT-MTJ-based NVFF may suffer from soft error induced by the nonvolatile single event upset (NVSEU) in the backup mode. In this paper, we analyze the sensitive nodes in different work modes and propose the radiation hardening circuits for master–slave NVFF (MS-NVFF) to solve the NVSEUs. Based on a physics-based SOT-MTJ compact model and a 40[Formula: see text]nm CMOS design kit, the reliability of MS-NVFF is verified by simulation with 2[Formula: see text]pC charge, which could be reliably integrated into aerospace and avionics electronics in hostile environments.
Research on Job Preference in China’s Internet Industry Through the Conjoint Analysis
Authors: Lei Nuo
Published: June 2022

Internet startups in China are currently facing a severe labor force shortage. The White Paper on Employment Insights in China’s Internet Industry (Enterprise Chapter) has highlighted that labor force distribution in China’s Internet Industry is imbalanced, with 60% of resumes going to 3% of big firms, leaving startups unable to hire enough employees, instead big firms unable to find the suitable staff. This study aims to determine how Internet startups improve their appeal to fill their labor force shortage. We have undertaken a conjoint analysis experiment online with Internet firms in China. Our results indicate that the annual salary is the most essential criteria for respondents when choosing a job, followed by firm size, weekly working hours, location, and team-building activities. There are also distinct preferences among employees. For example, female Internet employees and those with master’s degrees are more sensitive to income fluctuations. On this basis, Chinese Internet startups can attract Internet employees with a cost-effective strategy that combines improved pecuniary conditions and non-pecuniary conditions based on characteristics of different types of employees.
Fracture analysis of functionally graded material reinforced with MWCNT
Authors: Yadav Aanchal , Bhardwaj Gagandeep , Patil R. U. , Godara R. K.
Published: June 2022

Computational model based on extended isogeometric analysis is implemented for the fracture analysis of functionally graded material (FGM) reinforced with multi-walled carbon nanotube (MWCNT), i.e., FGM-MWCNT structure under mechanical and thermo-mechanical loading conditions. The FGM body taken for the study is composed of metal (Ti–6Al–4V) on the left side and ceramic (ZiO2) on right side. For the gradation of FGM properties that change throughout the domain length, exponential law is assumed. Moreover, the FGM is reinforced with 0–5% of MWCNT to obtain FGM-MWCNT composite. In order to perform this fracture analysis, first the equivalent mechanical and thermal properties of the FGM-MWCNT composite are evaluated using some of the micromechanics models cited in the literature. Using the interaction integral approach, SIFs are extracted. The results of the test show that when the volume percentage of MWCNTs increases, it enhances the failure resistance of the composite.
BrainEx: Interactive Visual Exploration and Discovery of Sequence Similarity in Brain Signals
Authors: Howell-Munson Alicia , Micek Christopher , Li Ziheng , Clements Michael , Nolan Andrew C. , Powell Jackson , Solovey Erin T. , Neamtu Rodica
Published: June 2022

Technology advances and lower equipment costs are enabling non-invasive, convenient recording of brain data outside of clinical settings in more real-world environments, and by non-experts. Despite the growing interest in and availability of brain signal datasets, most analytical tools are made for experts in the specific device technology, and have rigid constraints on the type of analysis available. We developed BrainEx to support interactive exploration and discovery within brain signals datasets. BrainEx takes advantage of algorithms that enable fast exploration of complex, large collections of time series data, while being easy to use and learn. This system enables researchers to perform similarity search, explore feature data and natural clustering, and select sequences of interest for future searches and exploration, while also maintaining the usability of a visual tool. In addition to describing the distributed architecture and visual design for BrainEx, this paper reports on a benchmark experiment showing that it outperforms other existing systems for similarity search. Additionally, we report on a preliminary user study in which domain experts used the visual exploration interface and affirmed that it meets the requirements. Finally, it presents a case study using BrainEx to explore real-world, domain-relevant data.
Defining Configurable Virtual Reality Templates for End Users
Authors: Artizzu Valentino , Cherchi Gianmarco , Fara Davide , Frau Vittoria , Macis Riccardo , Pitzalis Luca , Tola Alessandro , Blecic Ivan , Spano Lucio Davide
Published: June 2022

This paper proposes a solution for supporting end users in configuring Virtual Reality environments by exploiting reusable templates created by experts. We identify the roles participating in the environment development and the means for delegating part of the behaviour definition to the end users. We focus in particular on enabling end users to define the environment behaviour. The solution exploits a taxonomy defining common virtual objects having high-level actions for specifying event-condition-action rules readable as natural language sentences. End users exploit such actions to define the environment behaviour. We report on a proof-of-concept implementation of the proposed approach, on its validation through two different case studies (virtual shop and museum), and on evaluating the approach with expert users.
Essential Expectations of Users of Web Configurators: An Empirical Survey
Authors: Leclercq Tony , Abbasi Ebrahim Khalil , Dumas Bruno , Remiche Marie-Ange , Heymans Patrick
Published: June 2022

Web configurators are increasingly used to support mass customisation of all sorts of products and services. As these business-critical applications become more and more widespread, users with different profiles and expectations, as well as increasingly complex products and services, have to be addressed during the configurator's design process.

While past research on product configuration has focused on knowledge representation and automated reasoning, researchers have paid less attention to the design and evaluation of user experience. This paper is the first to perform an in-depth study of the user's perspective on configurators. It identifies the users' favourite perceived values and qualities as well as the undesired defects of configurators. It also ranks these items by order of importance and investigates which characteristics of configurators influence, positively or negatively, the perceived values.

To achieve this, a questionnaire-based survey was performed. Users were asked to answer detailed questions about their perceptions of configurators and influencing characteristics. The responses shows that the validity of the customised product and its adequacy in matching user's needs and preferences are the most desired perceived values. The study also identifies usability and product visualisation as the favourite qualities. Consequently, their absence, in addition to the absence of configuration progress and state indicator, are the worst defects. These and other observations detailed in the paper are a first step towards the systematic definition of guidelines for optimizing user experience in Web configurators.
GesFabri: Exploring Affordances and Experience of Textile Interfaces for Gesture-based Interaction
Authors: Jiang Mengqi , Nanjappan Vijayakumar , Liang Hai-Ning , ten Bhömer Martijn
Published: June 2022

Textile interfaces are of interest to ubiquitous computing as they are easy to carry and manipulate. However, interesting questions remain about what type of natural gestures people make when interacting with textile interfaces and their emotional response to this interaction. We introduce GesFabri, a set of five interactive textile interfaces with distinct textures, created to investigate the intuitive interaction gestures and accompanied the emotional experience. This research sought to (1) design textile interfaces with intuitive gesture affordance, (2) explore the emotional effects of the developed gesture-based interfaces under four feedback modes (touch-only, visual feedback, audio feedback, multisensory feedback). The experimental results verify our hypotheses that (1) textile texture could provide natural gesture affordances; (2) the GesFabri interfaces' feedback mode was the main factor in the differences of emotional valence, arousal, GSR; and (3) both gesture-based interaction on textiles and the feedback mode had an impact on user emotions. These results highlight the gesture affordances of the e-textile interfaces and contribute to a better understanding of the user experience when interacting with gesture-based textile interfaces.
Iterative Mixed Method Approach to B2B SaaS User Personas
Authors: Boyle Rachael E. , Pledger Ruslana , Brown Hans-Frederick
Published: June 2022

User persona research has primarily been done on Business-to-Consumer (B2C) products, generated hybridly with interviews or surveys or purely quantitatively through clickstream data, often to serve sales / marketing teams. However, the application of these approaches in different circumstances to this is still relatively novel. How can we segment users in a way that is both helpful and accurate for a Business-to-Business (B2B) Software-as-a-Service (SaaS) product and its product development stakeholders, for a product with "imperfect" / obfuscated product analytics data and disjointed user journeys? We performed an iterative, qualitative and mixed quantitative approach to user personas that utilized survey data, user interviews, and preprocessed / manipulated web analytics data to provide a complete picture of the user. Survey data provided user background and insight into who to recruit while interviews provided insight into user journeys, personalities, and pain points. Using dimensionality reduction and an iterative clustering approach informed by survey and interview insights, we generated clusters based on users' time per page and clicks per feature data from our web analytics. Diving into the data behind each cluster and triangulating with interview and survey data enabled us to identify six distinct user personas. We recommend our approach to user segmentation, an as yet unexplored combination of qualitative and mixed quantitative methods, for the research teams of other mid-sized B2B SaaS companies as a way to address domain-specific challenges and bridge the data and user journeys gaps to paint a full, accurate picture of the user.
Engineering Annotations: A Generic Framework for Gluing Design Artefacts of Interactive Systems
Authors: Winckler Marco , Palanque Philippe , Hak Jean Luc , Barboni Eric , Nicolas Olivier , Goncalves Laurent
Published: June 2022

Along the design process of interactive system multiple intermediate artefacts (such as user interface prototypes, task models, dialog models?) are created, tested, revised, and improved until the development team produces a full-fledged system. However, relevant information for describing the design solution and/or supporting design decisions (such as rational about the design, decisions made, recommendations, etc.) are not explicitly captured in the models/artefacts, hence the need for annotations. Many approaches argue against information duplication to increase maintainability of the artefacts. Nonetheless, annotations created on one artefact are usually relevant to other artefacts/models. So that, there is a need for tools and techniques to coordinate annotations across artefacts/models which is the contribution of the present work. In this paper, we propose a model-based approach that was conceived to handle annotations in a systematic way along the development process of interactive systems. As part of the solution, we propose an annotation model built upon the W3C's Web Annotation Data Model. The feasibility of the approach is demonstrated by means of a tool suite featuring a plugin, which has been deployed and tested over the multi-artefacts. The overall approach is illustrated on the design of an interactive cockpit application performing two design iterations. The contribution brings two main benefits for interactive systems engineering: i) it presents a generic pattern for integrating information in multiple usually heterogenous artefacts throughout the design process of interactive systems; and ii) it highlights the need for tools helping to rationalize and to document the various artefacts and the related decisions made during interactive systems design.
Shifting Capsule Networks from the Cloud to the Deep Edge
Authors: Costa Miguel , Costa Diogo , Gomes Tiago , Pinto Sandro
Published: June 2022

Capsule networks (CapsNets) are an emerging trend in image processing. In contrast to a convolutional neural network, CapsNets are not vulnerable to object deformation, as the relative spatial information of the objects is preserved across the network. However, their complexity is mainly related to the capsule structure and the dynamic routing mechanism, which makes it almost unreasonable to deploy a CapsNet, in its original form, in a resource-constrained device powered by a small microcontroller (MCU). In an era where intelligence is rapidly shifting from the cloud to the edge, this high complexity imposes serious challenges to the adoption of CapsNets at the very edge. To tackle this issue, we present an API for the execution of quantized CapsNets in Arm Cortex-M and RISC-V MCUs. Our software kernels extend the Arm CMSIS-NN and RISC-V PULP-NN to support capsule operations with 8-bit integers as operands. Along with it, we propose a framework to perform post-training quantization of a CapsNet. Results show a reduction in memory footprint of almost 75%, with accuracy loss ranging from 0.07% to 0.18%. In terms of throughput, our Arm Cortex-M API enables the execution of primary capsule and capsule layers with medium-sized kernels in just 119.94 and 90.60 ms, respectively (STM32H755ZIT6U, Cortex-M7 @ 480 MHz). For the GAP-8 SoC (RISC-V RV32IMCXpulp @ 170 MHz), the latency drops to 7.02 and 38.03 ms, respectively.
How Stimulating Is a Green Stimulus? The Economic Attributes of Green Fiscal Spending
Authors: O'Callaghan Brian , Yau Nigel , Hepburn Cameron
Published: June 2022

When deep recessions hit, some governments spend to rescue and recover their economies. Key economic objectives of such countercyclical spending include protecting and creating jobs while reinvigorating economic growth—but governments can also use this spending to achieve long-term social and environmental goals. During the coronavirus disease 2019 (COVID-19) pandemic, claims have been made that green recovery investments can meet both economic and environmental objectives. Here, we investigate the evidence behind these claims. We create a bespoke supervised machine learning algorithm to identify a comprehensive literature set. We analyze this literature using both structured qualitative assessment and machine learning models. We find evidence that green investments can indeed create more jobs and deliver higher fiscal multipliers than non-green investments. For policymakers, we suggest strong prioritization of green spending in recovery. For researchers, we highlight many research gaps and unalignment of research patterns with spending patterns.
Electrochemical Properties and Electrochemical Milling of (TiB + TiC)/TC4 Composites
Authors: Zhang Shuoshan , Hu Xiaoyun , Li Hansong , Yang Yitian
Published: June 2022

The (TiB + TiC)/TC4 composite is a new material with superior high-temperature resistance properties and structural strength. However, it cannot be easily machined by conventional methods. Electrochemical machining is an ideal method for the processing of titanium-matrix composites. In this study, the electrochemical properties of (TiB + TiC)/TC4 composites were investigated. The polarization curve of (TiB + TiC)/TC4 in a NaCl solution with a volume fraction of 20% was measured. The decomposition voltage was approximately 7.2 V. Basic electrochemical dissolution experiments were carried out on TC4 and (TiB + TiC)/TC4. The surface morphology was measured to investigate the dissolution mechanism. It was demonstrated that the reinforcing phase will fall off with the dissolution of TC4 and will not participate in the electrochemical dissolution reaction. Finally, electrochemical milling experiments on (TiB + TiC)/TC4 with different voltages and cathode feed rates were carried out to study the removal rate and surface roughness of the material. The material removal rate (MRR) increased, while the surface roughness decreased with the increases in the voltage and feed rate. A maximum MRR of 171.11 mm3/min and minimum surface roughness of 4.281 μm were obtained at a voltage of 50 V with a feed rate of 20 mm min−1.
Effects of Minor Mechanical Deformation on the Lifetime and Performance of Commercial 21700 lithium-Ion Battery
Authors: Li Ling , Chen Xiaoping , Yuan Quan , Wang Tao , Ji Hongbo , Papović Snežana , Raleva Katerina , Pan Fuzhong , Yang Tonghuan , Li Jia
Published: June 2022

Vehicular lithium-ion batteries (LIBs) may suffer from minor damage or defects owing to external mechanical abuse, such as deformation and scratches, during cycling. This study uses non-destructive testing methods to analyze the effects of minor mechanical deformation on the lifetime and performance of commercial 21700 lIBs. Firstly, incremental capacity analysis (ICA) is performed to quantify the charge/discharge performance and cycle aging behavior of LIBs under different deformations. Secondly, X-ray computed tomography (XCT) technology is utilized to qualitatively analyze the internal structure variations of LIBs caused by minor mechanical deformation. Results show that with an increase in mechanical deformation, the internal resistances of LIBs increase, charging curves move to high voltage areas, and peak points of the incremental capacity (IC) curves decrease and move to high voltage areas. Cyclic charge/discharge of LIBs with different deformations show that with an increase in cycles, the capacity and state-of-health (SOH) of mechanically deformed LIBs decrease significantly due to the changes in the internal structure of batteries. Furthermore, the tomographic images of LIBs demonstrate that the increased internal gaps within the electrodes result in the increase of internal resistance, and the mechanism for capacity loss of batteries in the cyclic is revealed.
Core-Shell Structured Gel Polymer Electrolyte with Single-Ion Conducting and Thermal Stability Bifunction for Lithium-Ion Batteries
Authors: Shen Xiu , Hu Texiong , Zeng Yuejing , Huang Xiao , Zhang Peng , Zhao Jinbao
Published: June 2022

The commercial electrolyte of lithium-ion batteries (LIBs) is usually liquid state supplemented by a porous polyolefin separator to prevent short circuit. Recent years, polymer electrolyte shows great potential for its flexibility and enhanced safety. And novel single-ion conductor gel polymer electrolyte (SIGPE) could effectively suppress the anion polarization by immobilizing anions on the polymer bone. Further enhancing the thermal stability of SIGPE plays a significant role for the safety of the LIBs. Herein, a novel bifunctional core–shell structured composite was prepared, consisting of thermal stable polyimide as core and a composite single-ion conductor polymer. The relations of fiber morphology with spinning parameters and heat-treatment temperature were studied carefully. As a result, the composite core–shell structured membrane shows excellent high dimensional thermal stability up to 190 °C. Moreover, when the charged half battery was stored at 150 °C, the core–shell structured SIGPE cell shows excellent potential stability while ordinary cell quickly short out, greatly enhancing the safety of the LIBs. The ionic conductivity of the plasticized gel electrolyte could reach 1.7*10−5 S cm−1 with a Li-ion transference number of 0.76. The assembled LiFePO4 battery shows stable cycle performance and remained 85% capacity after 100 cycles.
The Response of Phonon Frequencies, Sound Velocity, Electronic, Optical, and Mechanical Properties of Indium (Phosphide, Arsenide, and Antimonide) to Hydrostatic Pressure
Authors: Degheidy A. R. , Abuali A. M. , Elkenany Elkenany B.
Published: June 2022

The pressure dependence of phonon vibrations, the velocity of sound, and some other related physical quantities of

InAs
,

InP
,

and

InSb

semiconductors have been determined. This investigation is done using the empirical pseudopotential method. We proposed a pressure dependence of the pseudopotential form factors; hence we were able to calculate the pressure dependence of the fundamental energy gaps. Using the values of the fundamental band gaps, we were able to calculate the refractive index, static dielectric constant, high-frequency dielectric constant, longitudinal and transverse phonon frequencies, elastic constants, mechanical moduli, and velocity of sound. Our findings may serve as a reference for experimental work at high pressures.
β-Blockers are associated with increased B-type natriuretic peptide levels differently in men and women in heart failure with preserved ejection fraction
Authors: Harada Eisaku , Mizuno Yuji , Ishii Masanobu , Ishida Toshifumi , Yamada Toshihiro , Kugimiya Fumihito , Yasue Hirofumi
Published: June 2022

Pathogenesis and treatment for heart failure with preserved ejection fraction (HFpEF) may differ in men and women in sinus rhythm (SR).
Nonplatelet thromboxane generation is associated with impaired cardiovascular performance and mortality in heart failure
Authors: Hariri Essa , Kakouros Nikolaos , Bunsick David A. , Russell Stuart D. , Mudd James O. , Laws Katherine , Lake Mikhailia W. , Rade Jeffrey J.
Published: June 2022

Nonplatelet thromboxane generation in heart failure is independently associated with risk of death, transplant, or need for mechanical support. Measurement of urine thromboxane metabolites using a clinically available assay may be a useful surrogate for invasive measurement of cardiovascular hemodynamics and performance that could provide prognostic information and facilitate tailoring of therapy in patients with heart failure. Inhibiting nonplatelet thromboxane generation or its biological effects is a potential strategy for improving cardiovascular performance and outcomes in heart failure.
Genetic Relationship and Evolution Analysis among Malus Mill Plant Populations Based on SCoT Molecular Markers
Authors: Yao Yuan
Published: June 2022

Malus Mill genotype is highly heterozygous, and many theoretical problems such as genetic relationship and evolution process among germplasm are difficult to be solved by traditional analysis methods. The development of SCoT(start codon targeted polymorphism) molecular markers suitable for apples is of great significance for studying the origin, evolution, genetic relationship and genetic diversity of Malus Mill germplasm resources. In this paper, the genetic relationship and evolution of 15 materials were analyzed by SCoT molecular marker. The results showed that the gene differentiation coefficient values of four Malus Mill plants at the species level were 0.423, 0.439, 0.428 and 0.460, respectively, which indicated that there was obvious genetic differentiation among the populations of these four Malus Mill plants, but there were some differences among the populations of different Malus Mill plants. The gene differentiation coefficient of coextensive populations with different geographical distribution varied from 0.177 to 0.086 (average 0.138), which indicated that the genetic similarity of species in coextensive composite populations was high and there was a close genetic relationship among species. This indicates that SCoT molecular markers can be effectively used in the analysis of intraspecific genetic relationship and identification of intraspecific strains of Malus Mill plants.
Intelligent Detection of Vehicle Driving Safety Based on Deep Learning
Authors: Wang Deyun
Published: June 2022

With the continuous increase in the number of cars, traffic safety problems are also becoming more and more serious, whether the driver wears a seat belt to protect the driver’s personal safety so that the problem can be solved in the event of a traffic accident. The author puts forward the research status of deep learning and convolutional neural network, as well as its theory and technology, and conducts in-depth analysis and research, a small target detection algorithm Deconv-SSD based on transposed convolution is proposed, driver area localization algorithm Squeeze-YOLO is based on lightweight model, and driver seat belt detection algorithm is based on semantic segmentation. Deconv-SSD achieves fast vehicle detection through depthwise separable convolution and fusion of multiresolution feature maps and then utilizes the salient features of the front windshield; through the method of lightweight feature extraction and the Squeeze-YOLO algorithm, the rapid positioning of the driver area is realized. Fast segmentation of seat belts is based on semantic segmentation algorithm and pruning technology in the positioning area, and by judging the maximum connected domain area after segmentation, the driver’s seat belt detection is realized. Experiments and data analysis are carried out on the proposed algorithm. When the image resolution is consistent with the feature extraction model, the average accuracy of Deconv-SSD is compared with the original SSD algorithm in the PASCALVOC public dataset, from 77.2% to 79.6%. In the self-made seat belt detection dataset, Squeeze-YOLO can reach 73 FPS when the average accuracy is 99.96%, the semantic segmentation algorithm accelerated by pruning achieves an accuracy of 94.87% at a speed of 305 FPS, and the validity of the experiment is verified.
Intelligent Integration Method of AI English Teaching Resource Information under Multi-Agent Collaboration
Authors: Liu Minjuan
Published: June 2022

In order to improve the intelligent effect of English teaching in the era of intelligent education, this article conducts an intelligent integration system of AI English teaching resources and information on the basis of multi-agent collaboration. Moreover, this article analyzes the principles and properties of the three algorithms, ALO, GWO, and MFO, and integrates them into the D2D power allocation problem in the two communication modes. In addition, this article studies the effects of population size, variable dimension, and convergence on the overall energy efficiency and generation of D2D users through simulation and combines improved algorithms to construct an intelligent integration system of AI English teaching resources and information under multi-agent collaboration. The simulation experiment study shows that the intelligent integration system of AI English teaching resources and information under the multi-agent writing proposed in this article can play an important role in the integration of English teaching resources and information.