Desirable Characteristics Research Articles

Assessment of physio-morphological traits, genetic variability, and growth performance among amaranth (Amaranthus species) genotypes from Ethiopia

Amaranths are a type of plant that belongs to the NAD-malic enzyme-type C4 metabolism category. They have a unique C4 anatomy, which is present in their bracts, cotyledons, and leaves. This allows them to produce food through the C4 photosynthetic pathway and rapidly adapt to unfavorable environmental conditions. In this study, 120 amaranth genotypes were evaluated for physio-morphological traits, genetic variability, and growth performance assessment from Ethiopia. The results of the analysis of variance showed that all examined physio-morphological parameters, except the rate of photosynthesis and stomata conductance, had mean squares that varied considerably (P < 0.001) owing to genotypes. The estimates of genetic variability, heritability, and expected genetic advance indicated an incredible extent of genetic diversity among amaranth genotypes, with a significant selection pressure for these traits in the population to produce better genotypes for improved amaranth. Selection based on desirable features such as leaf-to-air vapor pressure deficit, transpiration rate, chlorophyll a, chlorophyll b, total chlorophyll, carotenoid, leaf area, plant height, leaf number, and root weight can be useful in achieving the intended genetic gains for improvement since these traits appear to be more controlled by additive gene activity. Thus, selection in amaranth genotypes may consider these desired yield-related features. Moreover, the study showed that certain genotypes (ALE-073) exhibited better intercellular CO2 concentration (Ci), leaf-to-air vapor pressure deficit (VPD), transpiration rate (E), and leaf number (LN), resulting in better grain yield. Understanding the relationship between LA and E can help in selecting crops for high E and may provide an avenue to improve leaf yield. Furthermore, some of the selected genotypes in this study could be used as potential parents for improving the genetic gain in amaranth breeding programs. The study concluded that there was additive gene action present since the Ch a, Ch b, TCh, and Tca markers exhibited 100 % heritability. This showed that the use of these characteristics for selection, which indicated a potentially exploitable variation, would be more effective and successful in the long run in breeding programs than the use of other traits for splitting generations.

Business View Specification of Enterprise Information Systems Based on Core Ontologies

Enterprise Information Systems (EIS) supporting Business Processes (BPs), particularly Sensitive Business Processes (SBPs), should be characterized by integrity, flexibility, and interoperability. However, the urbanization approach, which we rely on to implement these systems, must address the “three fit” problems that hinder the realization of these desired features at both the business and technical infrastructures: “vertical fit” problems – concerning the business infrastructure; “horizontal fit” problems and “transversal fit” problems – concerning the technical infrastructure. We argue that for overcoming those problems, it is necessary to define an explicit framework for specifying BPs/SBPs. We present in this paper our conceptual specification for the BPs/SBPs modeling domain in the form of a core domain ontology, in order to overcome “horizontal fit” and “transversal fit” problems. Specifically, we introduce (i) our reference ontological framework and (ii) provide an overview of the Core Ontology of Sensitive Business Processes (COSBP). Our focus lies in the representation of SBPs in order to overcome “vertical fit” problems.

Advanced channel coding schemes for B5G/6G networks: State‐of‐the‐art analysis, research challenges and future directions

SummaryAs a consequence of continuing demand for additional capacity and higher quality data transmission, channel coding as a key component of a digital communication network has progressed from a classical single pair, point‐to‐point information theoretic application to a class of coding techniques with diverse parameters. The heterogeneous requirements of B5G/6G networks technology have made flexibility of code parameters the main desired feature while designing channel codes. Owing to this, channel coding techniques have evolved to support enabling applications that depend on different factors such as latency, reliability, energy efficiency and throughput. We review and discuss the application of new techniques, modifications in the design and construction of modern channel coding schemes, including block, convolutional, rateless and space‐time codes. Further, the error correction performance of mainstream channel decoders for LDPC, polar and turbo codes is compared and analysed for their attainable error rate. The aim of this study is to highlight the adaptability of the discussed coding schemes for the forthcoming cellular network landscape. This article also addresses the implementational challenges of high throughput, low latency and machine type communication scenarios. Moreover, some recent studies exploring the role of machine learning for optimisation of B5G/6G networks are classified and discussed. Concluding, research areas pertaining to the scalability of error control coding for next generation networking are addressed.

Design of hyperbolic quasi-zero stiffness metastructures coupled with nonlinear stiffness for low-frequency vibration isolation

Quasi-zero stiffness (QZS) metastructures with simple structures exhibit a high low-frequency vibration isolation performance, but the bearing capacity and working regions are limited due to the linear positive stiffness elements. In this study, a novel hyperbolic QZS metastructure coupled with nonlinear stiffness is designed by combining a pair of cosine-shaped beams and arc-shaped beams for low-frequency vibration isolation. Finite element models (FEM) and experimental analysis are utilized to examine the static characteristics of the metastructure, revealing a wide QZS region and significant load-bearing capacity. The metastructure can achieve effective vibration isolation properties through reasonably designing the unit cells. The influence of geometrical parameters on the QZS region is investigated to optimize and realize desirable QZS features. The dynamic equation and response of the vibration isolation system are determined using the harmonic balance method. Moreover, the corresponding displacement transmissibility is confirmed by numerical simulation. The results of the dynamic sweep frequency experiment further verify the validity of the theoretical analysis model. The hyperbolic QZS metastructure system possesses good vibration isolation performance due to the introduction and compensation of a nonlinear positive stiffness arc beam element. The proposed hyperbolic QZS metastructure provides a significant route for the stiffness compensation of metastructures.

Review Article] How to Improve the Human Mindset

Modern societies are challenged by a range of problems; most, if not all, are aggravated by the way people behave. Our minds are shaped by the combined effect of genes and environment. Of these two, the only practical option for modifying behavior is to adjust the impact of the environment. All communities try to mold their members; thus, the question is not _whether_ we should attempt to form the brains of future generations, but _how_ to optimize the outcome. In this review, I discuss desirable features, brain plasticity, and strategies for enhancing society by tweaking the mindset, and thus the behavioral propensities, of the population.

Sensory-Motor Loop Adaptation in Boolean Network Robots.

Recent technological advances have made it possible to produce tiny robots equipped with simple sensors and effectors. Micro-robots are particularly suitable for scenarios such as exploration of hostile environments, and emergency intervention, e.g., in areas subject to earthquakes or fires. A crucial desirable feature of such a robot is the capability of adapting to the specific environment in which it has to operate. Given the limited computational capabilities of a micro-robot, this property cannot be achieved by complicated software but it rather should come from the flexibility of simple control mechanisms, such as the sensory-motor loop. In this work, we explore the possibility of equipping simple robots controlled by Boolean networks with the capability of modulating their sensory-motor loop such that their behavior adapts to the incumbent environmental conditions. This study builds upon the cybernetic concept of homeostasis, which is the property of maintaining essential parameters inside vital ranges, and analyzes the performance of adaptive mechanisms intervening in the sensory-motor loop. In particular, we focus on the possibility of maneuvering the robot's effectors such that both their connections to network nodes and environmental features can be adapted. As the actions the robot takes have a feedback effect to its sensors mediated by the environment, this mechanism makes it possible to tune the sensory-motor loop, which, in turn, determines the robot's behavior. We study this general setting in simulation and assess to what extent this mechanism can sustain the homeostasis of the robot. Our results show that controllers made of random Boolean networks in critical and chaotic regimes can be tuned such that their homeostasis in different environments is kept. This outcome is a step towards the design and deployment of controllers for micro-robots able to adapt to different environments.

A Five-Step Framework for Creating Forests for the Future

Changing environmental conditions, disturbances, and escalating demands for forest ecosystem services require foresters to restore present forestlands with new forest generations that will exhibit ecological integrity, diversity, high adaptive capacity, and the ability to provide essential ecosystem services. Establishing such forests requires careful consideration of the forest landscape and site dynamics. In pursuit of these requirements, we developed a novel framework that enables the restoration of forest sites and promotes the desired features of the forest complex at the same time. This framework was designed with the methods of system engineering and was organized in the same way as the forest planning process. It was tested in the habitat type of Illyrian Fagus sylvatica forests belonging to the Natura 2000 network. The environmental, vegetation, and site conditions were investigated via field inspections, available forest management plans, and simple GIS analyses. Additionally, we established a seminatural stand composed of European beech, sessile oak, sycamore maple, silver fir, and some wild fruit tree species. The survival of planted species was assessed using census and simple random sampling, the performance of provenances by the Student’s test, while microhabitat factors were explored by a one-way ANOVA. The survival rate of key species was estimated to be 55.6%, while that of fruit species was estimated to be 94.5%. Our framework demonstrated satisfactory performance and contained sufficient benchmarks to facilitate consistent decision-making. In the discussion, we elucidate the framework’s primary features and attributes of the mixed stand, where we also expose some open issues to be addressed in the future.

Learning about labor markets

We study a general equilibrium model of the labor market in which agents slowly learn about their suitability for jobs. Our model reproduces desirable features of the data, many of which standard models fail to replicate. We explore how, in such an environment, asymmetric information can lead to substantial misallocation. We calibrate our model to US data and quantify the welfare loss arising from misallocation due to informational frictions. The tractability of the model allows us to explore the responsiveness of wages and employment to an aggregate shock. We find that wage rigidity arises endogenously because of protracted learning, and in line with the data, the model is able to generate a larger and more persistent employment response.

Multispectral metal-based electro-optical metadevices with infrared reversible tunability and microwave scattering reduction

Abstract The demand for advanced camouflage technology is increasing in modern military warfare. Multispectral compatibility and adaptive capabilities are increasingly desired features in camouflage materials. However, due to the strong wavelength dependence and limited tunability of electromagnetic wave responses, achieving simultaneous multispectral compatibility and adaptive capability in a single structure or device remains a challenge. By integrating coding metamaterials with infrared (IR) electrochromic devices, we demonstrate a highly integrated multispectral metal-based electro-optical metadevice. The fabricated metadevices enable the reversible tunability of IR emissivity (0.58 at 3–5 µm, 0.50 at 7.5–13 µm) and wideband microwave scattering reduction (&gt;10 dB at 10–20 GHz). The excellent integration performance is attributed to the remarkable electromagnetic control capabilities of the coding metamaterials in a chessboard-like configuration and the IR electrochromic devices based on metal reversible electrodeposition. Furthermore, the monolithic integrated design with shared barium fluoride substrate and electrodes allows the metadevices to have a simple architecture, and the careful design avoids coupling between functions. Our approach is general enough for the design of various electrochromic devices and metamaterials for multispectral camouflage, offering valuable insights for the development of advanced adaptive multispectral camouflage systems.

Evaluation of usability and user feedback to guide telepharmacy application development in Indonesia: a mixed-methods study

BackgroundIn Indonesia, the adoption of telepharmacy was propelled by the COVID-19 pandemic, prompting the need for a user-friendly application to support both the general population and pharmacists in accessing healthcare services. Therefore, this study aimed to evaluate usability and user feedback of a pioneering telepharmacy application known as Tanya Obat (translating to “Ask about Medications”) in Indonesia, from the perspectives of the general population and pharmacists.MethodsA mixed-methods sequential study was conducted with the early-stage Tanya Obat application in Bandung City. Participants, including the general population and pharmacists, were instructed to use the application for a week. Questionnaires for the general population and pharmacists were distributed from March to May and February to June 2023, respectively. The System Usability Scale questionnaire was adopted to describe usability of the developed application. Further exploration of the quantitative results required collecting open-ended feedback to assess the impressions of the participants, difficulties encountered, and desired features for enhanced user-friendliness. The collected statements were summarized and clustered using thematic analysis. Subsequently, the association between the characteristics of participants and perceived usability was determined with the Chi-square test.ResultA total of 176 participants, comprising 100 individuals from the general population and 76 pharmacists, engaged in this study. In terms of usability, the questionnaire showed that Tanya Obat application was on the borderline of acceptability, with mean scores of 63.4 and 64.1 from the general population and pharmacists, respectively. Additionally, open-ended feedback targeted at achieving a more compelling user experience was categorized into two themes, including concerns regarding the functionality of certain features and recommendations for improved visual aesthetics and bug fixes. No significant associations were observed between the characteristics of participants and perceived usability (p-value > 0.05).ConclusionThe results showed that the perceived usability of Tanya Obat developed for telepharmacy was below average. Therefore, feature optimizations should be performed to facilitate usability of this application in Indonesia.

On the use of elliptic PDEs for the parameterisation of planar multipatch domains

AbstractThis paper presents a parameterisation framework based on (inverted) elliptic PDEs for addressing the planar parameterisation problem of finding a valid description of the domain’s interior given no more than a spline-based description of its boundary contours. The framework is geared towards isogeometric analysis (IGA) applications wherein the physical domain is comprised of more than four sides, hence requiring more than one patch. We adopt the concept of harmonic maps and propose several PDE-based problem formulations capable of finding a valid map between a convex parametric multipatch domain and the piecewise-smooth physical domain with an equal number of sides. In line with the isoparametric paradigm of IGA, we treat the parameterisation problem using techniques that are characteristic for the analysis step. As such, this study proposes several IGA-based numerical algorithms for the problem’s governing equations that can be effortlessly integrated into a well-developed IGA software suite. We augment the framework with mechanisms that enable controlling the parametric properties of the outcome. Parametric control is accomplished by, among other techniques, the introduction of a curvilinear coordinate system in the convex parametric domain, for which more general elliptic PDEs are adopted. Depending on the application, parametric control allows for building desired features into the computed map, such as homogeneous cell sizes or boundary layers.

"An app is just available at all times"-the process and outcomes of converting the Georgia Tuberculosis Reference Guide into a mobile application.

The physical, paper-based Georgia TB Reference Guide has served as the clinical reference handbook on tuberculosis (TB) diagnostic and treatment guidelines for the state of Georgia in the United States. Supported by the Georgia Department of Public Health, the production of the 112-page palm-sized booklet was previously led by a team of Georgia-based TB experts at Emory University and printed every three-five years with updates to clinical management guidelines and TB consult contact information. However, the costs associated with editorial printing combined with delays in updating a static printed booklet with revised guidance hampered the utility of the tool. Considering the barriers with paper-based production and based on the beneficial use of apps to support the dissemination of clinical management guidance in other settings, the booklet was converted into a mobile application. This paper describes the process of developing a mobile app version of the Georgia TB Reference Guide in an easy-to-update and readily available format. We employed a user-centered design approach to develop the app, including a series of qualitative interviews and quantitative surveys. Participants included a mix of state officials and local TB experts. First, initial foundational interviews were conducted to conceptualize current utilization practices of both the paper and PDF versions of the tool. Second, the findings from the initial interviews were organized thematically and informed the design of the app, which was then beta tested by a round of previously unsampled TB experts as well as a re-sample from the initial interviews. Third, the designs were coded into developmental phases and beta tested among users of the current Georgia TB Reference Guide. Fourth, the app was published and downloaded by a pre-selected group of local users who provided answers to a follow-up survey after using the app for one month. Fifth, user growth, self-reported demographics, and app usage between February and July 2022 were recorded through automatic data metrics built into the app. The paper copy Georgia TB Reference Guide usage themes included commonly referenced content, navigation paths, and desired features and content. The themes were converted into features and designs such as prioritizing commonly reviewed topics and guide customization with bookmarks and notes. Iterations of the designs were driven by feedback from TB experts and included home page featured content, improving content readability, and improving the search feature. The follow-up survey revealed a 90% preference for the app over the paper version of the guide. In the six months following the app's release, the app was downloaded by 281 individuals in the United States. The majority of downloads were in Georgia and the app also expanded organically to 19 other states. The experience of converting the Georgia TB Reference Guide offers specific and effective steps to converting a medical reference guide into a mobile application tool that is readily available, easy to use, and easy to update. The organic dissemination of the app beyond the state of Georgia's borders within the first six months of app launch underscores desire among TB healthcare professionals for high-quality digital reference content outside the state. This experience offers clear outlines for replication in other contexts and demonstrates the utility of similar mobile medical reference tools.

Integrating regular expressions into neural networks for relation extraction

Relation extraction aims to identify semantic relationships between entities from the given sentences. The development of deep learning prompts a variety of neural-based relation extraction models. These models can learn features from sentences automatically, but controlling their learned patterns is equally difficult. Therefore, it is hard to take steps to improve their performance further. A possible way to modify the models is by utilizing human-defined rules to introduce rule-based knowledge and guiding the models to capture the desired features based on human intent. As an efficient human knowledge, regular expression (RE) is helpful in extracting particular targets from text, which is also logical and interpretable. A novel embedding method is proposed to transform REs into learnable representations available to neural networks (NNs). Then, the rule-based representations are investigated to be integrated into different levels of NNs. Three representative relation extraction models based on recurrent neural network (RNN), convolutional neural network (CNN), and Transformer encoder, respectively, are selected as baselines to incorporate our rule-based representations. The experimental results show that the models with rule-based information outperform their original ones on the F1-score by 3.75%, 4.06%, and 2.57%, and the identification accuracy of complex samples is also significantly improved, verifying the effectiveness of our approaches. Our work is easy to reproduce and can be generally applied to various neural networks, proving that data-driven relation extraction methods can take advantage of the rule-based knowledge provided by REs.

Internal symmetries in Kaluza-Klein models

The usual approach to Kaluza-Klein considers a spacetime of the form M4 × K and identifies the isometry group of gK0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {g}_K^0 $$\\end{document}, the internal vacuum metric, with the gauge group in four dimensions. In these notes we discuss a variant approach where part of the gauge group does not come from full isometries of gK0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {g}_K^0 $$\\end{document}, but instead comes from weaker internal symmetries that only preserve the Einstein-Hilbert action on K. Then the weaker symmetries are spontaneously broken by the choice of vacuum metric and generate massive gauge bosons within the Kaluza-Klein framework, with no need to introduce ad hoc Higgs fields. Using the language of Riemannian submersions, the classical mass of a gauge boson is calculated in terms of the Lie derivatives of gK0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {g}_K^0 $$\\end{document}. These massive bosons can be arbitrarily light and seem able to evade the standard no-go arguments against chiral fermionic interactions in Kaluza-Klein. As a second main theme, we also question the traditional assumption of a Kaluza-Klein vacuum represented by a product Einstein metric. This should not be true when that metric is unstable. In fact, we argue that the unravelling of the Einstein metric along certain instabilities is a desirable feature of the model, since it generates inflation and allows some metric components to change length scale. In the case of the Lie group K = SU(3), the unravelling of the bi-invariant metric along an unstable perturbation also breaks the isometry group from (SU(3) × SU(3))/ℤ3 down to (SU(3) × SU(2) × U(1))/ℤ6, the gauge group of the Standard Model. We briefly discuss possible ways to stabilize the internal metric after that first symmetry breaking and produce an electroweak symmetry breaking at a different mass scale.

Metal-organic framework/MXene nanohybrid composites as an emerging electrochemical sensing platform for food safety and biomedical monitoring: From synthesis to application

Metal-organic frameworks (MOFs) are created through the self-assembly process of metal ions or clusters with organic linkers. These materials have attracted important interest owing to their advantageous features, comprising abundant pore structures, ultrahigh porosity, and well-exposed active sites. However, some traditional MOFs have limitations in terms of low stability and conductivity. Despite significant endeavors to enhance the stability of MOF materials, limited advancement has prompted researchers to concentrate on the development of hybrid materials. MXenes, a group of 2D transition-metal compounds comprising nitrides, carbides, and carbonitrides, are recognized for their diverse composition and their ability to form various buildings with rich surface chemistry. The hybridization of MOFs with functional MXene layered could be advantageous if the host structure offers suitable interactions to enhance and stabilize the desired features. Current research has concentrated on incorporating MXenes and MOFs to generate nanohybrid materials with boosted electrochemical features, thus broadening the scope for new applications. This review explores potential design approaches for MXene@MOF nanohybrids, the tunable characteristics of the resulting hybrids, and their use in electrochemical sensing platforms for food safety and biomedical monitoring. Finally, the authors discuss the challenges and future opportunities of MOF@MXene-derived nanocomposites.

N-to-S Acyl Transfer as an Enabling Strategy in Asymmetric and Chemoenzymatic Synthesis.

The observation of thioester-mediated acyl transfer processes in nature has inspired the development of novel protein synthesis and functionalization methodologies. The chemoselective transfer of an acyl group from S-to-N is the basis of several powerful ligation strategies. In this work, we sought to apply the reverse process, the transfer of an acyl group from N-to-S, as a method to convert stable chiral amides into more reactive thioesters. To this end, we developed a novel cysteine-derived oxazolidinone that serves as both a chiral imide auxiliary and an acyl transfer agent. This auxiliary combines the desirable features of rigid chiral imides as templates for asymmetric transformations with the synthetic applicability of thioesters. We demonstrate that the auxiliary can be applied in a range of highly selective asymmetric transformations. Subsequent intramolecular N-to-S acyl transfer of the chiral product and in situ trapping of the resulting thioester provides access to diverse carboxylic acid derivatives under mild conditions. The oxazolidinone thioester products can also be isolated and used in Pd-mediated transformations to furnish highly valuable chiral scaffolds, such as noncanonical amino acids, cyclic ketones, tetrahydropyrones, and dihydroquinolinones. Finally, we demonstrate that the oxazolidinone thioesters can also serve as a surrogate for SNAC-thioesters, enabling their seamless use as non-native substrates in biocatalytic transformations.

UX Design for an E-commerce Application: A Design Thinking Perspective

The development of e-commerce applications has revolutionized the way people conduct business, but challenges still exist in designing applications that align with user needs and expectations. This study aims to document the design-thinking (DT) approach used in the development of a customized e-commerce application based on the user's perspective, with the goal of extracting the user experience of traditional commerce processes to identify its features. In this study, we focused on the first four phases of DT, which include empathize, define, ideate, and prototype, to gather insights and understand the experiences, needs, pain points, and solutions of the local producers. The data gathered from interviews and observations was subjected to content analysis to identify patterns and themes related to desired features. After analysis, the researchers identified key app features, including integrating data analytics for product performance and demand forecasting, introducing a peer-vendor marketplace, a vendor-managed inventory management system, and a product verification system for authenticity. A mockup prototype design was created and presented to users for feedback. The study highlights the importance of user perspectives in e-commerce app design and the value of design thinking in creating a customized user experience that aligns with user needs.

Understanding Media Consumption Habits of Gen Z in Metaverse and Virtual Reality Project

Generation Z, born amidst the digital revolution, navigates a media landscape vastly different from previous generations. Their unique habits, characterized by mobile-first content, community-driven engagement, and a preference for short-form, interactive experiences, present both challenges and opportunities for emerging technologies like the Metaverse and Virtual Reality (VR). This research embarks on an exploratory journey, delving into the nexus between Gen Z's media consumption patterns and their potential adoption of these immersive realities. Through a mixed-methods approach, the research will analyze how Gen Z's digital media preferences, ranging from short-form video platforms to online communities, influence their perception and potential engagement with the Metaverse and VR. In-depth interviews and focus groups will uncover their desired features and functionalities within these virtual environments, ensuring alignment with their existing media consumption habits. Additionally, content analysis of online forums and social media discussions will provide valuable insights into their concerns and expectations surrounding these new frontiers. By understanding the interplay between Gen Z's media consumption and their potential engagement with the Metaverse and VR, this research aims to achieve several key objectives. Firstly, it seeks to identify the potential influence of their media habits on their willingness to adopt these technologies. Secondly, it aims to explore their desired functionalities and the types of content they envision within these virtual spaces. Furthermore, the research strives to investigate the role of online communities and influencers in shaping their attitudes and decisions regarding the Metaverse and VR. Finally, it seeks to address the potential risks and ethical considerations associated with Gen Z's participation in these immersive realities, aiming to pave the way for a more inclusive and responsible digital future.

An Improved Algebraic Structure of Nonlinear Dynamical Systems

A substitution box is regarded as an eminent source of nonlinearity and perplexity in most of the block ciphers. In this work, we propose that the involvement of a local ring has a favorable influence on the highly desirable features of this nonlinear cryptographic system. We deploy the unit group of a local ring by considering its correspondence with the Galois field and design an algorithm that utilizes the algebraic properties of the local ring [Formula: see text], to synthesize a highly efficient S-box.

A Neuroinclusive School Model: Focus on the School, Not on the Child

ABSTRACT Inclusive education involves adapting schools upfront to the needs of students with diverse profiles to enable them to fulfill their potential and develop a sense of belonging to their schools. This study aimed to design a model that clarifies the features of school occupations and environments that support the participation and well-being of autistic students and their peers. A research-design approach was used to develop the model. Through the iterative and collaborative process, it came out as necessary for the model to target a larger diversity of students, especially those who are neurodivergent. The model includes nine desirable features of school environments and occupations that support the meaningful participation and the well-being of neurodivergent students. The importance for people in the social environment to celebrate neurodiversity, and to provide safe and caring spaces, came out as particularly critical. The model also provides indications relating to the physical environment (e.g. being free from excessive stimuli) and to the desired features of activities (e.g. harnessing passions and strengths, offering various options). It invites collaboration between stakeholders to create more welcoming schools for neurodivergent students and their peers.