bluuebunny/crossref_metadata_2025 huggingface dataset:
Protocol for scoping review on well-being among theatre nurses in large public hospitals in low-income and middle-income countries
Authors: Ramafikeng Matumo , Eboh Winifred Oluchukwu
Published: April 2022

Introduction

Theatre nurses report higher levels of stress and burn-out due to the nature of their work environment. Workplace stress among nurses is associated with decreased well-being resulting is poor health outcomes for patients. However, evidence on well-being among nurses varies considerably, due to the multiple perspectives, definitions and focus on different aspects of well-being. Existing literature has not been consolidated to map out well-being concepts and instruments. In addition, due to limited research in low-income and middle-income countries, the most contextually relevant instruments for this context has not been identified. The aim of this scoping review is to map out existing literature on well-being, key concepts and instruments used to measure well-being among theatre nurses working in public hospitals in low-income and middle-income countries.

Methods and analysis

A scoping review guided by the Joanna Briggs Institute’s methodological approach will be used. PubMed, Scopus, Ebscohost, Web of Science, Emerald Insight, Informa World, Oxford Journals, ScienceDirect and Google scholar will be searched for literature published from 2000 to date. Reference lists of selected articles will also be reviewed. Two reviewers will conduct the screening of articles and data extraction independently and differences will be resolved through a discussion. Data analysis will be guided by both qualitative and quantitative methods.

The scoping review will take place from 1 May 2022 to 1 November 2022, completing the screening, data extraction and analysis phases.

Ethics and dissemination

The study does not require ethical approval. Findings will be published and shared at events to raise awareness on the importance of monitoring well-being among theatre nurses as a strategy to improve surgical outcomes. The review could shed light on an instrument most suitable for low-income and middle-income contexts.
How do Europeans quit using tobacco, e-cigarettes and heated tobacco products? A cross-sectional analysis in 28 European countries
Authors: El Asmar Marie Line , Laverty Anthony A , Vardavas Constantine I , Filippidis Filippos T
Published: April 2022

Objectives

While smoking tobacco remains a substantial cause of harm in Europe, novel products such as electronic cigarettes or e-cigarettes (ECs) and heated tobacco products (HTPs) have entered the market recently. While debate still persists over the role of these novel products, they are now in widespread use. This study aimed to explore the prevalence and methods of attempts to quit EC and HTP.

Setting

We analysed the 2020 Eurobarometer survey, which collected data in 28 European countries.

Participants

A representative sample of individuals residing in these countries aged ≥15 years.

Primary and secondary outcome measures

Multilevel regression analyses were performed to assess differences in quit attempts and cessation methods among tobacco smokers and exclusive EC/HTP users separately.

Results

51.1% of current tobacco smokers and 27.1% of exclusive EC or HTP users reported having ever made a quit attempt. The majority of former and current smokers (75.8%) who made a quit attempt did so unassisted, with 28.8% reporting at least one attempt using a cessation aid. The most popular cessation aids were nicotine replacement therapy or other medication (13.4%) and ECs (11.3%). 58.8% of exclusive EC or HTP users who had made a quit attempt did so unassisted, with 39.5% reporting the use of a cessation aid.

Conclusion

Most EC and HTP users in Europe try to quit unassisted, although more of them report the use of a cessation aid compared with tobacco smokers. Cessation support services should take into consideration the increasing numbers of users of EC and HTP who may be trying to quit.
Tissue P Systems with Vesicles of Multisets
Authors: Alhazov Artiom , Freund Rudolf , Ivanov Sergiu , Verlan Sergey
Published: April 2022

We consider tissue P systems working on vesicles of multisets with the very simple operations of insertion, deletion, and substitution of single objects. With the whole multiset being enclosed in a vesicle, sending it to a target cell can be indicated in those simple rules working on the multiset. As derivation modes we consider the sequential derivation mode, where, if possible, one rule is applied in a derivation step, and the set maximally parallel derivation mode, where in each derivation step a non-extendable set of rules indicating the same target cell is applied. With the set maximally parallel derivation mode, computational completeness can already be obtained with tissue P systems having a tree structure, whereas tissue P systems even with an arbitrary communication structure are not computationally complete when working in the sequential mode. Adding polarizations — only the three polarizations [Formula: see text], [Formula: see text], [Formula: see text] are sufficient — allows for obtaining computational completeness even for tissue P systems working in the sequential mode.
One-Way Restarting Automata and Their Sensitivitys
Authors: Plátek Martin , Otto Friedrich , Mráz František
Published: April 2022

Here we establish and study some rigorous tools suitable for the lexicalized syntactic analysis (LSA) of natural and formal languages. Motivated by the linguistic method of analysis by reduction, we are interested in correctness preserving LSA. We introduce a suitable model of automata, the h-lexicalized one-way restarting automata (h-RRWW), and compare the properties of their input languages, which are the languages considered traditionally in automata theory, to the properties of the so-called basic and h-proper languages. These languages form the basic components for LSA.

With respect to their input languages, h-RRWW-automata are not sensitive to the size of the read/write window and they allow computations that are far from being correctness preserving. On the other hand, for their basic and h-proper languages, h-RRWW-automata ensure that the resulting computations are completely correctness preserving, and they yield infinite ascending hierarchies of language classes within the regular, the context-free, and the context-sensitive languages that are based on the size of the read/write window.
Quantum geometric confinement and dynamical transmission in Grushin cylinder
Authors: Gallone Matteo , Michelangeli Alessandro , Pozzoli Eugenio
Published: April 2022

We classify the self-adjoint realizations of the Laplace–Beltrami operator minimally defined on an infinite cylinder equipped with an incomplete Riemannian metric of Grushin type, in the class of metrics yielding an infinite deficiency index. Such realizations are naturally interpreted as Hamiltonians governing the geometric confinement of a Schrödinger quantum particle away from the singularity, or the dynamical transmission across the singularity. In particular, we characterize all physically meaningful extensions qualified by explicit local boundary conditions at the singularity. Within our general classification we retrieve those distinguished extensions previously identified in the recent literature, namely the most confining and the most transmitting one.
Information pattern stability in memristive Izhikevich neural networks
Authors: Takembo Clovis Ntahkie
Published: April 2022

In this paper, modulational instability (MI) of information via membrane potential is studied analytically and numerically in an improved Izhikevich neural network under electromagnetic induction. By applying the powerful discrete multiple scale expansion method, a spatiotemporal nonlinear amplitude differential-difference equation governing the information dynamics is derived from the generic model. Linear stability of plane impulse wave solution is then performed on the latter and the impact of electromagnetic induction feedback through the memristor couplings is portrayed on the growth rate diagram. From the diagram, it is found that negative memristor coupling parameter decreases the critical amplitude while positive parameter increases the critical amplitude. To support our analytical predictions, numerical simulations are performed and data selected from the unstable zone of MI lead to the formation of localized solitonic energy patterns, related to the energy coding patterns in the nervous system. Furthermore, the sampled time series for membrane potential under the influence of memristor coupling revealed the breakdown of action potential into multiple impulse-wave trains for high parameter values thus confirming an analytical prediction. Our results provide a potential way to manipulate information coding in the brain.
Novel interaction phenomena of the new (2 + 1)-dimensional extended shallow water wave equation
Authors: Zhang Yuqing , Hu Hengchun
Published: April 2022

Based on the Hirota bilinear method, we study some kinds of novel interaction solutions of the new integrable [Formula: see text]-dimensional extended shallow water wave equation. Using the symbolic computations, we obtain a rich variety of exact solutions such as the lump solutions, lump-kink solutions, breather solutions and two-kink solutions and these exact solutions are shown analytically and graphically by selecting the proper parameters. These new exact solutions contribute us to our understanding of the physical phenomena of the integrable nonlinear shallow water wave model.
Response of Commercial P-Channel Power VDMOS Transistors to Ionizing Irradiation and Bias Temperature Stress
Authors: Veljković Sandra , Mitrović Nikola , Davidović Vojkan , Golubović Snežana , Djorić-Veljković Snežana , Paskaleva Albena , Spassov Dencho , Stanković Srboljub , Andjelković Marko , Prijić Zoran , Manić Ivica , Prijić Aneta , Ristić Goran , Danković Danijel
Published: April 2022

In this paper, the effects of successively applied static/pulsed negative bias temperature (NBT) stress and irradiation on commercial p-channel power vertical double-diffused metal-oxide semiconductor (VDMOS) transistors are investigated. To further illustrate the impacts of these stresses on the power devices, the relative contributions of gate oxide charge ([Formula: see text]) and interface traps ([Formula: see text]) to threshold voltage shifts are shown and studied. It was shown that when irradiation without gate voltage is used, the duration of the pre-irradiation static NBT stress has a slightly larger effect on the radiation response of power VDMOS transistors. Regarding the fact that the investigated components are more likely to function in the dynamic mode than the static mode in practice, additional analysis was focused on the results obtained during the pulsed NBT stress after irradiation. For the components subjected to the pulsed NBT stress after the irradiation, the effects of [Formula: see text] neutralization and [Formula: see text] passivation (usually related to annealing) are more enhanced than the components subjected to the static NBT stress, because only a high temperature is applied during the pulse-off state. It was observed that in devices previously irradiated with gate voltage applied, the decrease of threshold voltage shift is significantly greater during the pulsed NBT stress than during the static NBT stress.
A Time and Reliability Optimization Algorithm for Workflow Scheduling in Heterogeneous Distributed Computing System
Authors: Jiang Junqiang , Cai Hailin , Xie Lunxin , Sun Zhifang , Pan Li , Yang Zhihe , Lu Ruiqi
Published: April 2022

In the heterogeneous distributed computing systems, efficient task scheduling is necessary for high performance. System reliability and completion time are generally the two important metrics. In this paper, we proposed an algorithm named Merging and Duplication for Makespan and Reliability (MDMR) which combines task merging and task duplication to achieve single-objective constrained optimization of workflow reliability and completion time. The MDMR algorithm is divided into three phases: task merging, entry task duplication and reliability detection with nonentry task duplication. In the task merging phase, two tasks with a sole parent–child relationship are merged into a single task, then this process is iterated until no tasks satisfy the merging condition, thus simplifying the directed acyclic graph. In the entry task duplication phase, the entry task with the lowest reliability is duplicated on the processors, which are available at that moment to increase the reliability while reducing the workflow completion time. In the reliability detection and nonentry task duplication phase, the current workflow scheduling reliability is first calculated, then the result is directly output if the reliability is higher than the target value, otherwise the nonentry task duplication is executed with the aim of increasing the reliability until the value surpasses the target. According to the experimental results, MDMR dominates the compared algorithms and ensures that the entire workflow achieves the target reliability and shortens the workflow makespan as much as possible.
Safety Risk Assessment of Electric Power Operation Site Based On Variable Precision Rough Set
Authors: Chang Zhengwei , Deng Yuanshi , Wu Jie , Xiong Xingzhong , Chen Mingju , Wang Hong , Xie Xiaona
Published: April 2022

In order to improve the intelligent informatization level of electric power production safety and reduce the accidents, the paper constructs a dynamic perception scheme of electric power production site that utilizes multi-dimensional information such as personnel location, equipment status, and image information. This method uses a multi-sensor network to realize the real-time perception of the image and position information of dynamic power work objects, then uses object identification and intelligent analysis to acquire the dynamic factors. Static factors are selected through questionnaire and historical data, and variable precision fuzzy theory is used to calculate the weight of static factors at dynamic power operation sites. A comprehensive evaluation is established to perceive risk and estimate security probability based on static factors and dynamic scene information. The application system can present the situation of the operation scene, and then realize safety assessment and early warning of the dangerous situation in the case of dynamic power monitoring. This method can prevent safety accidents and enhance the overall safety of power operations.
Approximate Multipliers Design Using Approximate Adders for Image Processing Applications
Authors: Joy Vasantha Rani S. P. , Lourdu Jennifer J. R. , Sudhanya P.
Published: April 2022

Addition and multiplication are some of the most broadly adopted arithmetic operations in a wide range of applications. This paper proposes new structures of approximate multipliers to optimize the area, delay, and power without affecting the accuracy metrics. Multipliers and adders play a significant role in the functioning of any digital circuit or system. The overall performance of a processor highly depends on the speed of adders and the energy consumption. In this paper, two types of compact error-tolerant approximate adders are designed and used along with approximate 4:2 compressors to improvise the efficiency of the approximate multipliers. The proposed approximate multipliers show good results when compared to the existing structures in terms of area, delay, power, and accuracy. The approximate multipliers are applied to image sharpening and image multiplication applications. The error-tolerant adder’s performance is evaluated in the practical domain using the image blending application. Peak signal-to-noise ratio (PSNR) performance and the structural similarity index metric (SSIM) are used to assess the modeled designs. The proposed approximate multipliers and adders exhibit better performance in terms of PSNR and SSIM and are found to be an optimized design to apply effectively in various error-tolerant image processing applications.
Vertical Negative Effect Suppression of In-Wheel Electric Vehicle Based on Hybrid Variable-Universe Fuzzy Control
Authors: Zhu Zhengtong , Ge Xinfeng
Published: April 2022

To suppress a negative effect brought by introducing hub motor in vertical vibration of the body and that of a hub motor, a suppressing vertical negative effect algorithm of in-wheel electric vehicle is proposed based on hybrid variable universe fuzzy control (VUFC). Vertical accelerations of the body and that of the hub motor are taken as optimization objects, and to control the main suspension damper and in-wheel damper simultaneously, the semi-actively VUFC algorithm is adopted to improve vertical vibration characteristics effectively. The simulated results show that the peak and root mean square (RMS) of body vertical acceleration (VA) are optimized by 21.0% and 19.6%, respectively, after optimization compared to the original in-wheel electric model, the peak and RMS of hub motor VA are optimized by 30.1% and 32.5%, respectively, and the vertical negative effect is suppressed significantly.
Identifying Possible Improvements of Software Development Life Cycle (SDLC) Process of a Bank by Using Process Mining
Authors: Taskesenlioglu Sedat , Ozkan Necmettin , Erdogan Tugba Gurgen
Published: April 2022

Software development with its unique characteristics having knowledge-intensive and human-oriented aspects and complex domains, challenges organizations. The timely outcomes with high quality and desired cost that directly affect customer satisfaction have an important place in many organizations, including banks. In the last decade, as an emerging technique for business processes management, process mining has been applied in many domains, including manufacturing, supply chain, government, healthcare, and software engineering. There are limited number of studies on process mining techniques carried out for the software process, especially in the banking sector. A lack of tool infrastructure enabling to run the entire software development process and the challenges in integrating processed data from separated varying tools and assets complicate the use of process mining for software processes. This paper aims to identify the improvement points in the software development process of the Kuveyt Turk Participation Bank in Turkey through the surfacing actions. The findings and results are gathered by the application of process mining techniques of bupaR, and evaluation is provided by experts in the bank. After that, the relevant process improvements are identified. The results of this paper show that using process mining provides the organization with beneficial results, in particular, and a comprehensive view of the end-to-end Software Development Life Cycle (SDLC) processes.
PIECEWISE FRACTIONAL-ORDER MODELING OF THE BREAST CANCER EPIDEMIOLOGY AFTER THE ATEZOLIZUMAB TREATMENT
Authors: SOHAIL AYESHA , ARIF ROBIA , AZIM QURAT UL AIN , NUTINI ALESSANDRO , GEPREEL KHALED A.
Published: April 2022

In this paper, the therapeutic interactions are discussed with the aid of a mathematical model and piecewise differentiation technique. The model is based on the interaction between cell populations in therapeutic stress and cell populations in neoplastic transformation, referring specifically to triple-negative breast cancer (TNBC). The proposed computational approach provides an opportunity for the qualitative and parametric analysis of the clinical trials in question. The proposed mathematical model is based on the analysis of cell–cell interactions according to a logic that examines pathological stress and its influence on the dynamics of the cell population involved in tumor pathology. Detailed literature review and dynamical analysis of the proposed hypothesis are provided in this paper. The existence and non-negativity of the solutions are exploited, the hypothesis is stabilized; it is then further demonstrated with the aid of the piecewise derivative and the relevant application of the formula of Newton interpolation.
MACHINABILITY INVESTIGATION OF HIGH-STRENGTH 7068 ALUMINUM ALLOY: A POTENTIAL STUDY THROUGH EXPERIMENTATION, SPOTTED HYENA OPTIMIZATION AND ADVANCED MODELING APPROACHES
Authors: SOREN TUSHAR RANJAN , KUMAR RAMANUJ , PANDEY ANISH , SAHOO ASHOK KUMAR , PANIGRAHI ISHAM , PANDA AMLANA
Published: April 2022

This research emphasizes the machinability investigation on CNC turning of 7068 aluminum alloys. CVD-coated carbide tool was implemented for the [Formula: see text] full-factorial-based turning experiments in dry conditions. Machinability study includes the assessment of flank wear, cutting tool vibration, surface roughness, cutting temperature, chip reduction coefficient, and chip morphology. The selected tool performed well as very low wear (0.030–0.045[Formula: see text]mm) and low surface roughness (0.28–1.14[Formula: see text][Formula: see text]m) were found. All the input variables have significant impact on the flank wear, cutting tool vibration, cutting temperature, and chip reduction coefficient while for surface roughness, the effects of cutting speed and feed were significant at the 95% confidence level. Further, a novel optimization tool namely the spotted hyena optimizer (SHO) algorithm was utilized to get the optimal levels of input variables. Additionally, two different modeling tools namely multiple adaptive neuro-fuzzy inference system (MANFIS) and radial basis function neural network (RBFNN) were utilized for formulating the cutting response models. Further, the average of the absolute error was estimated for each model and compared. The MANFIS modeling tool exhibited a more close prediction of outputs as compared to RBFNN, as the obtained average absolute error for each response was lower with MANFIS.
L-Functions of Carlitz modules, resultantal varieties and rooted binary trees, II
Authors: Grishkov A. , Logachev D. , Zobnin A.
Published: April 2022

We continue study of some algebraic varieties (called resultantal varieties) started in a paper of authors “L-functions of Carlitz modules, resultantal varieties and rooted binary trees, I”, cited as [4]. These varieties are related with the Sylvester matrix for the resultant of two polynomials, from one side, and with the L-functions of twisted Carlitz modules, from another side. They are described in terms of weighted rooted binary trees. We give some proofs that lack in [4], some examples and tables that confirm conjectures from [4], and some ideas of development of this theory.
Minimal orbit sizes in nilpotent group actions
Authors: Keller Thomas Michael , Lv Heng , Qian Guohua , Yang Dongfang
Published: April 2022

Let [Formula: see text] be a finite nilpotent group. We prove the following results. (1) If [Formula: see text] is of class 2 and acts faithfully and irreducibly on an elementary abelian group [Formula: see text], then all nontrivial orbits of [Formula: see text] on [Formula: see text] have sizes larger than [Formula: see text]. (2) If [Formula: see text] is cyclic, then every subgroup of [Formula: see text] intersecting trivially with the center of [Formula: see text] has order less than [Formula: see text]. We also show that a result like (2) cannot be obtained when the hypothesis that [Formula: see text] is cyclic is replaced by the hypothesis that the center of [Formula: see text] is cyclic.
Power series over integral domains of Krull type
Authors: Giau Le Thi Ngoc , Toan Phan Thanh
Published: April 2022

An integral domain [Formula: see text] is said to be of Krull type if [Formula: see text] is a locally finite intersection of essential valuation overrings [Formula: see text] of [Formula: see text]. If each [Formula: see text] is required to be one-dimensional and discrete, then [Formula: see text] is called a Krull domain. In this paper, we show that if [Formula: see text] is an integral domain of Krull type such that some [Formula: see text] is not an SFT ring, then the power series ring [Formula: see text] is not a locally finite intersection of valuation domains. This is a generalization of our previous work, where [Formula: see text] is assumed to be a valuation domain. It follows that [Formula: see text] is a Krull domain if and only if both [Formula: see text] and [Formula: see text] are integral domains of Krull type, which is an improvement of a result by Paran and Temkin. We also prove that if [Formula: see text] is a Prüfer domain, then [Formula: see text] is a Krull domain if and only if [Formula: see text] is an integral domain of Krull type.
Irreducible modules for the loop of derivations of rational quantum torus
Authors: Tantubay Santanu
Published: April 2022

Let [Formula: see text] be a rational quantum torus associated with the matrix [Formula: see text]. Let [Formula: see text] be the Lie algebra of derivations of [Formula: see text]. In this paper, we consider the Lie algebra [Formula: see text], where [Formula: see text] is a commutative associative unital algebra over [Formula: see text] and classify its irreducible modules with finite-dimensional weight spaces.
Decomposable groups with exactly two nonlinear non-faithful irreducible characters
Authors: Li Yali , Meng Qingyun
Published: April 2022

In [Finite solvable groups with exactly two nonlinear non-faithful irreducible characters, J. Algebra Appl. 18(5) (2019) 1950091], the first author studied directly indecomposable, solvable groups with exactly two nonlinear non-faithful irreducible characters. In this paper, we study the decomposable case and give a classification of decomposable groups possessing exactly two nonlinear non-faithful irreducible characters. In particular, nilpotent groups with this property are also classified.
Finite and nilpotent strongly verbally closed groups
Authors: Klyachko Anton A. , Miroshnichenko Veronika Yu. , Olshanskii Alexander Yu.
Published: April 2022

We show, in particular, that, if a finite group [Formula: see text] is a retract of any finite group containing [Formula: see text] as a verbally closed subgroup, then the centre of [Formula: see text] is a direct factor of [Formula: see text].
Investigating Interdependencies Between Key Features of Lessons Learned: An Integral Approach for Knowledge Sharing
Authors: Abbas Yawar , Martinetti Alberto , Frunt Lex , Klinkers Jeroen , Rajabalinejad Mohammad , van Dongen Leo A. M.
Published: April 2022

While there is a clear consensus in the literature on the need to share lessons learned, it remains unclear how to properly do so. This paper addresses this point and offers insight into how best to incorporate tacitly held social preferences for developing knowledge-sharing strategies. A descriptive survey was conducted to analyse the knowledge sharing practices for lessons learned within the railway sector. Eight variables are investigated that are derived from the four LEAF features: learnability, embraceability, applicability, and findability. This study revealed that for learnability, storytelling and discussion with colleagues are preferred ways to share personal experiences. Trust and the creation of a learning culture emerged as key aspects of embraceability. With regard to applicability, a process-related knowledge-sharing focus for intraorganisational and a content-related focus for interorganisational knowledge domains are preferred. Better technological findability is identified as a key area of improvement. Finally, novel dependencies are established using the chi-square test between key LEAF features.
A Novel Multilayer Model for Link Prediction in Online Social Networks Based on Reliable Paths
Authors: Sarhangnia Fariba , Ali Asgharzadeholiaee Nona , Boshkani Zadeh Milad
Published: April 2022

Link Prediction (LP) is one of the critical problems in Online Social Networks (OSNs) analysis. LP is a technique for predicting forthcoming or missing links based on current information in the OSN. Typically, modelling an OSN platform is done in a single-layer scheme. However, this is a limitation which might lead to incorrect descriptions of some real-world details. To overcome this limitation, this paper presents a multilayer model of OSN for the LP problem by analysing Twitter and Foursquare networks. LP in multilayer networks involves performing LP on a target layer benefitting from the structural information of the other layers. Here, a novel criterion is proposed, which calculates the similarity between users by forming intralayer and interlayer links in a two-layer network (i.e. Twitter and Foursquare). Particularly, LP in the Foursquare layer is done by considering the two-layer structural information. In this paper, according to the available information from the Twitter and Foursquare OSNs, a weighted graph is created and then various topological features are extracted from it. Based on the extracted features, a database with two classes of link existence and no link has been created, and therefore the problem of LP has become a two-class classification problem that can be solved by supervised learning methods. To prove the better performance of the proposed method, Katz and FriendLink indices as well as SEM-Path algorithm have been used for comparison. Evaluations results show that the proposed method can predict new links with better precision.
(D4)-Objects in Abelian Categories
Authors: Kalebogaz Berke , Keskin Tütüncü Derya
Published: April 2022

Let 𝒜 be an abelian category and [Formula: see text]. Then M is called a [Formula: see text]-object if, whenever A and B are subobjects of M with [Formula: see text] and [Formula: see text] is an epimorphism, [Formula: see text] is a direct summand of A. In this paper we give several equivalent conditions of [Formula: see text]-objects in an abelian category. Among other results, we prove that any object M in an abelian category 𝒜 is [Formula: see text] if and only if for every subobject K of M such that K is the intersection [Formula: see text] of perspective direct summands [Formula: see text] and [Formula: see text] of M with [Formula: see text], every morphismr [Formula: see text] can be lifted to an endomorphism [Formula: see text] in [Formula: see text].
The Least Eigenvalue of Unicyclic Graphs with Application to Spectral Spread
Authors: Guo Jiming , Zhang Gege , Wang Zhiwen , Tong Panpan
Published: April 2022

Let [Formula: see text] be the set of connected unicyclic graphs of order [Formula: see text] and girth [Formula: see text]. Let [Formula: see text] be obtained from a cycle [Formula: see text] (in an anticlockwise direction) by identifying [Formula: see text] with the root of a rooted tree [Formula: see text] of order [Formula: see text] for each [Formula: see text], where [Formula: see text] and [Formula: see text]. In this note, the graph with the minimal least eigenvalue (and the graph with maximal spread) in [Formula: see text] is determined.
On Orientably Regular Non-abelian Covering Maps of the Platonic Maps
Authors: Ma Jicheng
Published: April 2022

We investigate the orientably regular non-abelian coverings of regular maps. A complete classification of dihedral coverings of the Platonic maps for branching over faces (or, dually, vertices) is given. As a result, we generalise the results of Jones and Surowski on regular cyclic coverings of the Platonic maps.
DRIVERS OF INNOVATION PERFORMANCE AND FIRM PERFORMANCE: EXAMINING THE INTER-RELATIONSHIP OF RISK-TAKING, RISK MANAGEMENT AND OPEN INNOVATION
Authors: LENDOWSKI EVA , OLDEWEME ANDREAS , SCHEWE GERHARD
Published: April 2022

This study empirically examines how risk-taking and risk management affect open innovation (OI) and innovation performance in terms of new product or service success (NPS) and new product or service innovativeness (NPI) and analyses how OI is related to innovation performance and firm performance, utilising a combination of survey and secondary data. To test the proposed hypotheses, we perform structural equation modelling (SEM) based on a sample of 309 German firms. Our findings show that a higher level of risk-taking, as well as more extensive risk management, is associated with an increased OI intensity. Additionally, we find that supporting a positive attitude towards risk-taking, implementing risk management and engaging in OI increases the innovation performance of a firm. However, we can only detect an indirect relationship between OI and firm performance. Overall, our findings contribute to research on drivers and outcomes of OI and drivers of innovation and firm performance.
ASSESSING THE IMPACT OF PATENT ATTRIBUTES ON THE VALUE OF DISCRETE AND COMPLEX INNOVATIONS
Authors: DANISH MOHD SHADAB , RANJAN PRITAM , SHARMA RUCHI
Published: April 2022

This study assesses the degree to which the social value of patents can be connected to the private value of patents across discrete and complex innovation. The underlying theory suggests that the social value of cumulative patents is less related to the private value of patents. We use the patents applied between 1995 and 2002 and granted on or before December 2018 from the Indian Patent Office (IPO). Here, the patent renewal information is utilised as a proxy for the private value of the patent. We have used a variety of logit regression model for the impact assessment analysis. The results reveal that the technology classification (i.e., discrete vs. complex innovations) plays an important role in patent value assessment, and some technologies are significantly different than the others even within the two broader classifications. Moreover, the non-resident patents in India are more likely to have a higher value than the resident patents. According to the conclusions of this study, only a few technologies from the discrete and complex innovation categories have some private value. There is no evidence that patent social value indicators are less useful in complicated technical classes than in discrete ones.
Strategic Environmental Assessment (SEA) Practice of Urban Planning in Australia and New Zealand: A Comparison
Authors: Kabir Zobaidul , Morgan Richard K.
Published: April 2022

The importance of the application of Strategic Environmental Assessment (SEA) for policies and plans is rapidly growing and will one day make the policies and plans environmentally and socially sustainable. While there have been legal requirements for SEA process and practice available in Australia and New Zealand for more than two decades, there is a dearth of information on how SEA is working in two separate jurisdictions. This comparative study on SEA practice is an attempt to fill this gap. The SEAs of two major urban plans of two major cities of two countries were reviewed and analysed to understand the practice of the SEA process. The SEA process of two urban plans of two countries was assessed against a set of good practice criteria. In addition, interviews were conducted with key informants, who were involved in the planning process, which provided valuable information. The study identified the key characteristics of two separate models of SEA practice alongside their advantages and disadvantages. The findings indicate that there are similarities and dissimilarities in SEA practices in both jurisdictions. The key similarities include the legal requirements for SEA, including community participation, in both jurisdictions. The key dissimilarities of SEA applications include the application of two separate models where the extent of flexibility, rigidity, integrative and separate issues related to the application of SEA varies. Also, there are common shortcomings identified in practice including relatively less attention is paid to socioeconomic issues and cumulative impacts. It is expected that the comparative study will help both Australia and New Zealand to learn lessons from each other, and thereby improve the practice of SEA in their own jurisdictions. The study also provides valuable insights by revealing some key characteristics of the SEA system of both countries. The findings of this study can be useful for the improvement of SEA practice for urban policy and plan by addressing the shortcomings identified in this study in both countries, and in other jurisdictions with a similar context.
A diffusive tuberculosis model with early and late latent infections: New Lyapunov function approach to global stability
Authors: Wang Xingyu , Liu Zhijun , Wang Lianwen , Guo Caihong
Published: April 2022

This paper formulates a diffusive tuberculosis (TB) model with early and late latent infections, vaccination and treatment that may more properly describe the slow and fast dynamics of TB transmission. We develop a new concise approach to determine the combination coefficients in the Lyapunov function candidate for the model and its time derivative in the case that both are the linear combinations of several Volterra-type functions, which highly simplifies the computations in global dynamical analysis for the nonlinear high-dimensional model. Based on the TB case data reported in China, the parameter values of the model are estimated. We further predict the TB prevalence trend in China. Sensitivity analysis for the control reproduction number and endemic equilibrium is conducted to seek some effective interventions that can significantly reduce initial TB transmission and lower TB prevalence levels in China. In the end, numerical simulations show that the bigger diffusive rates pick up the speeds of convergence to the equilibria of the model.
Augmented Convolutional Neural Network Models with Relative Multi-Head Attention for Target Recognition in Infrared Images
Authors: Nebili Billel , Khellal Atmane , Nemra Abdelkrim , Mascarilla Laurent
Published: April 2022

Deep convolutional neural network (CNN) models are typically trained on high-resolution images. When we apply them directly to low-resolution infrared images, for example, the performances will not always be satisfactory. This is due to CNN layers that operate in a local neighborhood, which is already poor in information for infrared images. To overcome these weaknesses and increase information of global nature, a hybrid architecture based on CNN with self-attention mechanism is proposed. This later provides information about the global context by capturing the long-range interactions between the different parts of an image. In this paper, we have incorporated a convolutional–attentional form in the top layers of two pre-trained networks VGGNet and ResNet. The convolutional–attentional form is a concatenation of two paths; the original convolutional feature maps of the pre-trained network, and the output of a relative multi-head attentional block. Extensive experiments are conducted in the FLIR starter thermal dataset, where we achieve a [Formula: see text] overall accuracy in the four-class FLIR starter thermal dataset. Moreover, the proposed architectures exceed the state of the art in target recognition on two-class FLIR starter thermal dataset with a [Formula: see text] improvement in overall classification accuracy. In addition, a study on the effect of different hyper-parameters and error analysis is carried out to give some research forward directions.
Extensive Study of DFT-Quantum Calculations Based QSAR Modeling of Fused 1,2,4-Triazine Derivatives Revealed Potent CYP1A1 Inhibitors
Authors: Ahmed Hany E. A. , Amer Adel , Senior Samir A. , Ihmaid Saleh , Almalghrabi Mohammad , El Massry Abdel-Moneim , Ahmed Sahar , Musa Arafa , Almikhlafi Mohannad A. , Salama Samir A. , Elhenawy Ahmed A.
Published: April 2022

In a continuing effort for our research group, we identify new active 1,2,4-triazine derivatives as novel cancer preventive agents that target CYP1A1 activity, through the application of quantitative structure–activity relationship (QSAR) theory. For this purpose, novel fused 1,2,4-triazine derivatives, namely, 4-Amino-6-substituted benzyl-3-(2-substituted benzylidenehydrazinyl)-1,2,4-triazin-5(4H)-ones and acetylated 6-substituted benzyl-7-oxo-3-substituted phenyl-2,3-dihydro-7[Formula: see text]-[1,2,4]triazolo[4,3-[Formula: see text]][1,2,4]triazine analogs were utilized for the prediction of the QSAR model. Furthermore, the application of this QSAR equation served successfully as a rational guide for predicting the activities of newly synthesized analogs. The DFT calculation was applied to recognize the physicochemical parameters at B3LYP/6- 311G* level to gain a clear view of global and local molecular reactivity. Besides, the molecular features of the investigated compounds were identified through HOMO, LUMO and molecular electrostatic potential (MEP) which were plotted to determine the charge transfer within the molecules. Promising two novel 1,2,4-triazine compounds were identified with observed significant inhibitions (83% and 67%) and CYP1A1 activity was predicted. The chemical configuration of the two actives showed good alignment of [Formula: see text]-methoxy benzyl aminotriazinone fragments, hydrazino and carbonyl linker in structure–activity relationship and interaction. Molecular modeling analysis supported with MD simulations was undertaken to investigate different binding interactions with the target binding site. These projects offered a good application of a promising QSAR model for prediction of highly active compounds for further lead optimization.
Automatic Assessment of Depression and Anxiety through Encoding Pupil-wave from HCI in VR Scenes
Authors: Li Mi , Zhang Wei , Hu Bin , Kang Jiaming , Wang Yuqi , Lu Shengfu
Published: April 2022

At present, there have been many studies on the methods of using the deep learning regression model to assess depression level based on behavioral signals (facial expression, speech, and language); however, the research on the assessment method of anxiety level using deep learning is absent. In this article, pupil-wave, a physiological signal collected by Human Computer Interaction (HCI) that can directly represent the emotional state, is developed to assess the level of depression and anxiety for the first time. In order to distinguish between different depression and anxiety levels, we use the HCI method to induce the participants’ emotional experience through three virtual reality (VR) emotional scenes of joyful, sad, and calm, and construct two differential pupil-waves of joyful and sad with the calm pupil-wave as the baseline. Correspondingly, a dual-channel fusion depression and anxiety level assessment model is constructed using the improved multi-scale convolution module and our proposed width-channel attention module for one-dimensional signal processing. The test results show that the MAE/RMSE of the depression and anxiety level assessment method proposed in this article is 3.05/4.11 and 2.49/1.85, respectively, which has better assessment performance than other related research methods. This study provides an automatic assessment technique based on human computer interaction and virtual reality for mental health physical examination.
Defining a Knowledge Graph Development Process Through a Systematic Review
Authors: Tamašauskaitė Gytė , Groth Paul
Published: April 2022

Knowledge graphs are widely used in industry and studied within the academic community. However, the models applied in the development of knowledge graphs vary. Analysing and providing a synthesis of the commonly used approaches to knowledge graph development would provide researchers and practitioners a better understanding of the overall process and methods involved. Hence, this article aims at defining the overall process of knowledge graph development and its key constituent steps. For this purpose, a systematic review and a conceptual analysis of the literature was conducted. The resulting process was compared to case studies to evaluate its applicability. The proposed process suggests a unified approach and provides guidance for both researchers and practitioners when constructing and managing knowledge graphs.
Combatting Energy Issues for Mobile Applications
Authors: Li Xueliang , Chen Junyang , Liu Yepang , Wu Kaishun , Gallagher John P.
Published: April 2022

Energy efficiency is an important criterion to judge the quality of mobile apps, but one third of our arbitrarily sampled apps suffer from energy issues that can quickly drain battery power. To understand these issues, we conduct an empirical study on 36 well-maintained apps such as Chrome and Firefox, whose issue tracking systems are publicly accessible. Our study involves issue causes, manifestation, fixing efforts, detection techniques, reasons of no-fixes, and debugging techniques. Inspired by the empirical study, we propose a novel testing framework for detecting energy issues in real-world mobile apps. Our framework examines apps with well-designed input sequences and runtime context. We develop leading edge technologies, e.g., pre-designing input sequences with potential energy overuse and tuning tests on-the-fly, to achieve high efficacy in detecting energy issues. A large-scale evaluation shows that 90.4% of the detected issues in our experiments were previously unknown to developers. On average, these issues can double the energy consumption of the test cases where the issues were detected. And our test achieves a low number of false positives. Finally, we show how our test reports can help developers fix the issues.
HINNPerf: Hierarchical Interaction Neural Network for Performance Prediction of Configurable Systems
Authors: Cheng Jiezhu , Gao Cuiyun , Zheng Zibin
Published: April 2022

Modern software systems are usually highly configurable, providing users with customized functionality through various configuration options. Understanding how system performance varies with different option combinations is important to determine optimal configurations that meet specific requirements. Due to the complex interactions among multiple options and the high cost of performance measurement under a huge configuration space, it is challenging to study how different configurations influence the system performance. To address these challenges, we propose
HINNPerf
, a novel hierarchical interaction neural network for performance prediction of configurable systems.
HINNPerf
employs the embedding method and hierarchic network blocks to model the complicated interplay between configuration options, which improves the prediction accuracy of the method. In addition, we devise a hierarchical regularization strategy to enhance the model robustness. Empirical results on 10 real-world configurable systems show that our method statistically significantly outperforms state-of-the-art approaches by achieving average 22.67% improvement in prediction accuracy. In addition, combined with the Integrated Gradients method, the designed hierarchical architecture provides some insights about the interaction complexity and the significance of configuration options, which might help users and developers better understand how the configurable system works and efficiently identify significant options affecting the performance.