Graphical Language Research Articles

Analysis and Prediction of Temperature Using an Artificial Neural Network Model for Milling Glass Fiber Reinforced Polymer Composites

Milling parts made from glass fiber-reinforced polymer (GFRP) composite materials are recommended to achieve the geometric shapes and dimensional tolerances required for large parts manufactured using the spray lay-up technique. The quality of the surfaces machined by milling is significantly influenced by the temperature generated in the cutting zone. This study aims to develop an Artificial Neural Network (ANN) model to predict the temperature generated when milling GFRP. The ANN model for temperature prediction was created using a virtual instrument developed in the graphical programming language LabVIEW. Predicting temperature is crucial because excessive heat during milling can lead to several issues, such as tool wear and thermal degradation in the polymer matrix. The temperature in the tool–workpiece contact surface during the milling process was measured using a thermography technique with a ThermaCAM SC 640 camera (provided by FLIR Systems AB, Danderyd, Sweden), and the data were analyzed using the ThermaCAM Researcher Professional 2.8 SR-2 software. Experimental research shows that the cutting speed has a much more significant effect on the temperature in the cutting zone compared to axial depth of cut and feed speed. The maximum temperature of 85.19 °C was measured in the tool–workpiece contact zone during machining at a cutting speed of 75.39 m/min, a feed rate of 250 mm/min, and an axial depth of cut of 12 mm. This temperature rise occurred due to the larger contact area and heightened friction resulting from the abrasive characteristics of the reinforcement material.

GPU Based Virtual Machine for Sleptsov Net Computing

Novel paradigm of Sleptsov Net Computing (SNC) mends imperfections of modern HPC architecture with computing memory implementation and provides a vivid graphical language, fine granulation of concurrent processes, and wide application of formal methods for reliable software design. IDE and VM for SNC have been developed and described in early papers. In the present paper, we considerably reduce GPU memory and thread consumption of the previous prototype implementation, introducing a matrix with condensed columns (MCC), and enhance performance, using the first fireable transition choice on the transition sequence reordered according to the lattice of priorities. MCC takes into consideration procedures of Sleptsov net (SN) arcs processing to enhance performance with rather little overhead compared to traditional sparse matrix formats. We represent a matrix of SN arcs by a pair of considerably smaller matrices, having the same number of columns, with the number of rows equal to the maximal number of nonzero elements over the source matrix columns. The first matrix contains the indexes within the source matrix, the second matrix contains the values within the source matrix. To run an SN, we use the corresponding rectangular matrix of GPU threads, with very few indirect memory accesses via MCC. As a result, we increase VM performance in 2–4 times, and reduce by hundred times GPU memory and thread consumption on programs from the SN software collection.

Ruxolitinib Cream Monotherapy Improved Symptoms and Quality of Life in Adults and Adolescents with Mild-to-Moderate Atopic Dermatitis: Patient-Reported Outcomes from Two Phase III Studies.

Atopic dermatitis (AD) is associated with itch, skin pain, sleep disturbances, and diminished quality of life (QoL). Ruxolitinib (Janus kinase [JAK] 1/JAK2 inhibitor) cream demonstrated efficacy and safety in adults and adolescents with mild-to-moderate AD in two phase III studies (TRuE-AD1/TRuE-AD2). In TRuE-AD1/TRuE-AD2, significant improvements in itch were observed as early as 12 h following application of ruxolitinib cream. The aim of this paper was to assess additional patient-reported outcomes (PROs) in the vehicle-controlled (VC) and long-term safety (LTS) periods of TRuE-AD1/TRuE-AD2. In the TRuE-AD studies, patients aged ≥12 years with AD were randomized 2:2:1 to apply twice-daily 1.5% ruxolitinib cream, 0.75% ruxolitinib cream, or vehicle cream continuously for 8weeks (VC period). During the LTS period, patients applied the same ruxolitinib cream strength, but on an as-needed basis; patients who initially applied vehicle were re-randomized to apply 0.75% or 1.5% ruxolitinib cream. Pooled data from both study periods were analyzed. PRO assessments included symptoms (itch [Patient-Oriented Eczema Measure, POEM], skin pain [numerical rating scale], and sleep [POEM and Patient-Reported Outcomes Measurement Information System]) and assessments of disease-specific QoL (Dermatology Life Quality Index [DLQI] and the children's version [CDLQI]). A total of 1208 and 1031 patients from the VC and LTS periods, respectively, were included in the analysis. Significant improvements in skin pain were observed within 12h among patients who applied ruxolitinib cream versus vehicle; improvements continued throughout the VC period. Improvements in patient-reported symptoms (including sleep) were observed within 2 weeks (first assessment) of ruxolitinib cream application. At Week 2, significant improvements in symptom burden and overall QoL were observed with ruxolitinib cream (0.75%/1.5%) versus vehicle in POEM (-8.9/-9.8 vs -2.2; both p<0.0001), DLQI (mean changes from baseline, -5.8/-6.1 vs -1.2; both p<0.0001), and CDLQI (-4.3/-5.3 vs -1.3; both p<0.0001). Further symptom burden and QoL improvements were reported during the VC period and were maintained through the end of the LTS period (Week 52). Consistent with the previously reported itch response data, ruxolitinib cream improved skin pain within 12 h of application. Ruxolitinib cream improved patient-reported AD symptom burden and overall QoL by Week 2. Improvements continued or were maintained for 52 weeks. (Graphical abstract and plain language summary available). ClinicalTrials.gov identifiers, NCT03745638 and NCT03745651 (both studies were registered on November 19, 2018).

Visual Communication Bridging Intercultural Barriers: Collaborative Methods Supporting the Social Inclusion of Young Refugees

This paper explores the possibilities of graphic languages in an intercultural context while analysing the potential of creative methods when working with refugee youth. The practice-based aspect of this research is undertaken with Open Doors Hungary, a community-based design project that creates a programme for unaccompanied refugee minors. The aim of Open Doors is to help young refugees integrate into Hungarian society and develop means of communication and quality relations with the host society. Refugee youth arriving in Hungary face serious problems: the loss of home and community, the traumas suffered during the journey, the cultural differences, and the lack of a common language make their social integration extremely challenging. These challenges are exacerbated by xenophobia and stereotypical opinions about foreigners. Social inclusion requires frequent contact with the local society, and refugee youth need new tools (cultural knowledge, language skills, intercultural skills) to overcome their disadvantages. Since 2013, the author has been working with refugee youth using participatory design tools such as regular creative sessions, workshops, and eight camps based on the integrating role of creativity and art. During these sessions, young refugees and their Hungarian and European peers learned about different visual communication tools and created common messages in the form of videos, animations, photos, posters, booklets, and murals. Through these activities, refugee youth become part of the design process, and the final result is based on their choices. In the theoretical research and field experiences, this paper states that design thinking and the creative process allow interactive cultural exchange, value sharing, safe and open discussions, and community building. As a global language, visual communication can be a tool for intercultural communication, storytelling, and self-expression. The opportunity for refugee youth and their Hungarian peers to work in intercultural teams develops new competencies and creates shared ownership and community.

Developing a Graphical Domain-Specific Modeling Language for Efficient Lightweight Block Cipher Schemas Configuration: LWBCLang

The lightweight block cipher is an encryption technique with negligible computational overhead. Despite its advantages, it faces a substantial challenge. Correct handwriting of the script code for the cipher scheme is a challenge for programmers. In this research, we suggest a new graphical domain-specific modeling language to make it easier for both non-technical users and domain specialists to implement lightweight block cipher schemes. The proposed language, called LWBCLang, is a modular and extensible language that offers graphical components for constructing three essential types of inner block cipher structures. Seven different methods of keystream generation and all the tests of the NIST suite with performance analysis are provided. In the context of its meta-model, LWBCLang's abstract and concrete syntaxes are specified. LWBCLang has been implemented as an internal DSML with Python as the host language. The evaluation of LWBCLang is based on qualitative analysis to demonstrate the language's effectiveness and efficiency. Further benefits of this proposed language are evaluated and discussed in depth in this research.

A comparison of reserved graph grammar and edge-based graph grammar

Abstract Context-sensitive graph grammars are natural formalisms for the generation and parsing of visual programming languages. Being intuitive, rigorous, and expressive tools, they have been frequently employed in a wide range of research fields. Nevertheless, the expressive powers of the existing context-sensitive formalisms have not been investigated yet. To this end, this paper is dedicated to the comparison of expressive powers of the two prevalent graph grammar formalisms, Reserved Graph Grammar (RGG) and Edge-based Graph Grammar (EGG). By introducing a special variant of RGG as an intermediary, the relation between them concerning the expressive power is revealed that the set of graph languages of EGG is a proper subset of that of RGG. Moreover, bidirectional transformations between EGG and the variant of RGG are accordingly established, allowing them to take the advantages of each other in applications.

Gothic Locks: Pioneering Drawings for Hydraulic Works in 16th-Century Holland

Just as Gothic cathedrals have long dominated the perception of medieval architecture, the spectacular drawings of the German lodges have shaped our view of the medieval design process. However, their towering importance has diverted scholarly attention from alternative drafting practices and reinforced the view of a homogeneous Gothic design practice based on quadrature. Historians generally accept that in the 16th century a new Renaissance graphic language challenged and ultimately replaced the Gothic tradition north of the Alps. However, this antagonistic narrative of one dominant practice superseding the other needs to be re-examined because hitherto neglected drawings for other types of buildings reveal that medieval drafting practice was more varied and open to new developments than is often believed. This paper will examine three rare sets of architectural drawings, together consisting of over thirty sheets, made for three stone sluices in the provinces of Utrecht and Holland between 1556 and 1563. They show that for technically demanding hydraulic works, drawings directed every step of the process, from enabling discussion of the most suitable design to guiding the stonemasons in the execution of the work. Moreover, they demonstrate that for such projects, Gothic masters did not adhere to tradition but engaged with new design methods, using scale, colour, and multiple views to convey all aspects of the project, thus indicating that changes in style and method were not always interrelated.

Test Stand for Microjet Engine Prototypes

To investigate the functionality and performance of a prototype microjet engine, we constructed a versatile test stand tailored to the specifications of a 400 N prototype. This test stand facilitated a comprehensive study by enabling real-time recording of 45 essential parameters for analysis, encompassing temperatures, pressures, speed, fuel flow, thrust, vibration, and various other monitored metrics. All parameters and control elements were seamlessly integrated via a data acquisition and control system, utilizing a compactDAQ (Data Acquisition) system from National Instruments and a custom Virtual Instrument programmed with graphical language. The test stand offers both manual and automated operation modes, with the flexibility for hybrid operation. For instance, following the idle regime, manual control using a potentiometer can seamlessly transition from automated control via a proportional control (P control) mechanism. Before the experimental campaign, rigorous verification and validation tests were conducted to ensure the reliability and accuracy of the setup. The experimental campaign comprised a series of manual tests focusing on the fuel system and automated tests covering starting, idle, working, and stopping regimes. This structured approach allowed for a comprehensive evaluation across different operational scenarios, providing insights into the engine’s behavior and performance under varying conditions.

PIONEER REAL UK: A Multi-Centre, Prospective, Real-World Study of Once-Daily Oral Semaglutide Use in Adults with Type 2 Diabetes.

Oral semaglutide provides an alternative to injectable glucagon-like peptide-1 receptor agonists (GLP-1RAs) for treatment of type 2 diabetes (T2D). The PIONEER REAL studies evaluate clinical outcomes of oral semaglutide treatment of T2D in a real-world setting. PIONEER REAL UK focused on adults living with T2D in the UK. The multi-centre, prospective and non-interventional single-arm study enrolled 333 participants and followed them for 34-44 weeks. Participants were treated as part of routine clinical practice and had not been previously treated with injectable glucose-lowering medication. The primary endpoint was change in glycated haemoglobin (HbA1C) from baseline to end of study (EOS). Secondary endpoints included change in body weight, proportion of participants with HbA1C < 7% (53 mmol/mol) at EOS and proportion of participants with ≥ 1%-point HbA1C reduction and body weight reduction of ≥ 3% or ≥ 5% at EOS. Treatment satisfaction was assessed by Diabetes Treatment Satisfaction Questionnaire (DTSQ) status and change. Of 333 participants, 299 completed the study and 227 were on treatment at EOS. People treated with oral semaglutide experienced significantly reduced HbA1C by an estimated change of - 1.1%-points (95% CI - 1.27 to - 0.96; P < 0.0001) or - 12.2 mmol/mol (CI - 13.87 to - 10.47; P < 0.0001). Estimated change in body weight was - 4.8 kg (CI - 5.47 to - 4.12; P < 0.0001). At EOS, an HbA1C level < 7% (53 mmol/mol) was recorded in 46.3% of participants. A ≥ 1%-point reduction in HbA1C combined with a ≥ 3% reduction in body weight was observed in 36.4% of participants, and 27.1% had a ≥ 1%-point reduction in HbA1C and a ≥ 5% body weight reduction. Treatment satisfaction improved significantly during the study. No new safety concerns or cases of severe hypoglycaemia were reported. People living with T2D in the UK experienced a meaningful decrease in HbA1C and body weight after initiation of oral semaglutide treatment. No new safety issues were observed. ClinicalTrials.gov: NCT04862923. Graphical plain language summary available for this article.

Optimizing ZX-diagrams with deep reinforcement learning

Abstract ZX-diagrams are a powerful graphical language for the description of quantum processes with applications in fundamental quantum mechanics, quantum circuit optimization, tensor network simulation, and many more. The utility of ZX-diagrams relies on a set of local transformation rules that can be applied to them without changing the underlying quantum process they describe. These rules can be exploited to optimize the structure of ZX-diagrams for a range of applications. However, finding an optimal sequence of transformation rules is generally an open problem. In this work, we bring together ZX-diagrams with reinforcement learning, a machine learning technique designed to discover an optimal sequence of actions in a decision-making problem and show that a trained reinforcement learning agent can significantly outperform other optimization techniques like a greedy strategy, simulated annealing, and state-of-the-art hand-crafted algorithms. The use of graph neural networks to encode the policy of the agent enables generalization to diagrams much bigger than seen during the training phase.

Building a Graphical Modelling Language for Efficient Homomorphic Encryption Schema Configuration: HomoLang

Homomorphic encryption (HE) is an emerging technology that enables computing on data while the data is encrypted. It has advantages, but it also has a significant difficulty. Programmers that use General-Purpose Programming Languages (GPPLs) may find it difficult to handwrite the script code for the HE correctly. This paper presents the front-end compiler design for the first graphical modelling language (DSML) to implement HE schemas, called HomoLang. It is providing a graphical environment with graphical building nodes that represent the HE concepts to enable the building of HE schemas. A high degree of abstraction and a decrease in grammatical and runtime errors improved the expressiveness and efficiency of implementation. Six security tests for security analysis were provided. The efficiency of the submitted language was evaluated using four subjective metrics. This paper provides a detailed explanation of the attributes, evaluation details, and design of the submitted HomoLang.

On the power of local graph expansion grammars with and without additional restrictions

We study graph expansion grammars, a type of graph grammar that has recently been introduced with motivations in natural language processing. Graph expansion generalizes the well-known hyperedge replacement. In contrast to the latter, the former is able to generate graph languages of unbounded treewidth, like the set of all graphs. In an earlier paper, the complexity of the membership problem of the generated languages was studied, the main result being a polynomial parsing algorithm for local DAG expansion grammars (there called local DAG expansion grammars), a subclass of graph expansion grammars that generates directed acyclic graphs. Here, we study the generative power of local graph expansion grammars. While they, unrestricted, are able to simulate Turing machines, we identify natural restrictions that give rise to a pumping lemma and ensure that the generated languages have regular path languages as well as a semi-linear Parikh image.

Comparing Graph Sample and Aggregation (SAGE) and Graph Attention Networks in the Prediction of Drug-Gene Associations of Extended-Spectrum Beta-Lactamases in Periodontal Infections and Resistance.

Gram-negative bacteria exhibit more antibiotic resistance than gram-positive bacteria due to their cell wall structure and composition differences. Porins, or protein channels in these bacteria, can allow small, hydrophilic antibiotics to diffuse, affecting their susceptibility. Mutations in porin protein genes can also impair antibiotic entry. Predicting drug-gene associations of extended-spectrum beta-lactamases (ESBLs) is crucial as they confer resistance to beta-lactam antibiotics, challenging the treatment of infections. This aids clinicians in selecting suitable treatments, optimizing drug usage, enhancing patient outcomes, and controlling antibiotic resistance in healthcare settings. Graph-based neural networks can predict drug-gene associations in periodontal infections and resistance. The aim of the study was to predict drug-gene associations of ESBLs in periodontal infections and resistance. The study focuses on analyzing drug-gene associations using probes and drugs. The data was converted into graph language, assigning nodes and edges for drugs and genes. Graph neural networks (GNNs) and similar algorithms were implemented using Google Colab and Python. Cytoscape and CytoHubba are open-source software platforms used for network analysis and visualization. GNNswere used for tasks like node classification, link prediction, and graph-level prediction. Three graph-based models were used: graph convolutional network (GCN), Graph SAGE, and graph attention network (GAT). Each model was trained for 200 epochs using the Adam optimizer with a learning rate of 0.01 and a weight decay of 5e-4. The drug-gene association network has 57 nodes, 79 edges, and a 2.730 characteristic path length. Its structure, organization, and connectivity are analyzed using the GCN and Graph SAGE, which show high accuracy, precision, recall, and an F1-score of 0.94. GAT's performance metrics are lower, with an accuracy of 0.68, precision of 0.47, recall of 0.68, and F1-score of 0.56, suggesting that it may not be as effective in capturing drug-gene relationships. Compared to ESBLs, both GCN and Graph SAGE demonstrate excellent performance with accuracy, precision, recall, and an F1-score of 0.94. These results indicate that GCN and Graph SAGE are highly effective in predicting drug-gene associations related to ESBLs. GCN and Graph SAGE outperform GAT in predicting drug-gene associations for ESBLs. Improvements include data augmentation, regularization, and cross-validation. Ethical considerations, fairness, and open-source implementations are crucial for future research in precision periodontal treatment.

Helen Keller’s ‘Sense of light’: life-writing, light-writing and the photosynthetic subject

ABSTRACT Contributors to Mere Light ask how ‘light’ falls in and through the non-visual medium of the literary text, illuminating that medium’s potential to initiate an experience of immediacy. While we might look to the luminous inscriptions of medieval mystics for its template, a fascinating post-Enlightenment exemplar of this paradox is the literary ‘self-recording’ of the deafblind modern ‘miracle’ Helen Keller. ‘Illustrated’ with often surreal photographs that both marked their modernity and complemented their thematic preoccupation with the dynamics of light, Keller’s nine autobiographies strove to replicate her primarily ‘tactual’ sense experience in graphic language while tendering apparently eyewitness images of light. Where these literary dissimulations bring the body of Keller’s disabled I into view, they develop a complex ‘sense of light’ as vibrant, self-actualising literary metaphor, capable of moving between sight and touch, and thus beyond the limits of both. Projecting its speaking I as light’s writing alongside illustrative photographs that projected that I as light-written, Keller’s life-writing synthesises sight and touch. Epitomised in her experimental The World I Live In (1908), this was to ‘photo’ synthesise the mimetic pretenses of post-Enlightenment visualising technologies with a transhistorical disability aesthetics oriented around peripheral – hence invisible – embodiment.

“We shall be faithful from generation to generation”: analysing the mechanisms of perpetuating dictatorship as canvased in Guy Delisle’s Pyongyang

ABSTRACT Graphic travel memoirs have increasingly delved into functioning as a socio-political commentary on the locale being travelled, and Guy Delisle’s Pyongyang: A Journey in North Korea (2005) is no exception. Through a critical analysis of the image–word interactions in Delisle’s Pyongyang, the research paper attempts to canvas the mechanisms by way of which totalitarianism is perpetuated in North Korea. To elaborate, the paper primarily explores the representation of three strategies of perpetuating dictatorship in Pyongyang – through propaganda politics, censorship or impositions and fearmongering or terrorisation. Firstly, the article outlines how propaganda techniques like assertion, glittering generalities, testimonials, and pinpointing the enemy, among others, are used to create a charade of strength and prosperity by the regime; secondly, it showcases how bans, restrictions and censorship help in subjugating the citizens; and thirdly, the paper outlines how fear and terror reduce the population into being mere puppets of the regime, thwarting all possibilities of an uprising against the despotic rule. By decoding the graphic language embedded in this visual-verbal narrative, the article argues that Delisle’s text captures the mechanisms of perpetuating dictatorship in North Korea, thereby also serving as an alternative political document.

Enhancing Visual Comfort in Commercial Spaces the Application of Graphic Language on Walls

Abstract: Graphic presentation is very important in modern Interior spaces and becoming one of the main means of building spatial experiences. Visual comfort plays a critical role in creating a positive atmosphere for customers, manipulating their overall experience and the engagement with space. While various elements contribute to visual comfort, the use of graphic language on the walls gained attention as a powerful tool for creating visually appealing and engaging environments. Through an extensive review of literature, this research examines the impact of graphic language, including patterns, texture, and imagery, on visual comfort in Commercial spaces. This research analyzes the use of graphic language on the walls of various types of fast-food restaurants in the Sultanate of Oman to understand the efficiency of different graphic elements in enhancing visual comfort. Furthermore, the research investigates the psychological and perceptual factors underlying the positive effects of graphic language, including the influence on mood, attention, and cognitive processing. The findings suggest that well designed graphic language on walls can considerably contribute to the visual comfort of customers, advancing a sense of relaxation, stimulation, and emotional connection. The paper concludes by highlighting the practical implication for designers, architects, and business owners, stressing the significance of thoughtfully integrating graphic language on the walls to craft visually pleasing and comfortable commercial environments. Employing the power of graphic language facilitates businesses to enhance their customers’ visual journey, resulting in enhanced satisfaction, stronger brand commitment, and overall success in the competitive market.

Hidden Semi-Markov Models for Semantic-Graph Language Modeling

Semantic communication is expected to play a critical role in reducing traffic load in future intelligent large-scale sensor networks. With advances in Machine Learning (ML) and Deep Learning (DL) techniques, design of semantically-aware systems has become feasible in recent years. This work focuses on improving the reliability of the semantic information represented in a graph-based language that has been recently proposed. Inaccuracies in the representation of the semantic information can arise due to multiple factors, such as algorithmic shortcomings or sensory errors, decreasing the performance of the semantic extractor. This study aims to model the temporal evolution of semantic information, represented using the graph language, to enhance its reliability. Each unique graph configuration is treated as a distinct state, leading to a Hidden Semi-Markov Model (HSMM) defined over the state space of the graph configurations. The HSMM formulation enables the integration of prior knowledge on the semantic signal into the graph sequences, enhancing the accuracy in identifying semantic innovations. Within the HSMM framework, algorithms designed for graph smoothing, semantic information fusion, and model learning are introduced. The efficacy of these algorithms in improving the reliability of the extracted semantic-graphs is demonstrated through simulations and video streams generated in the CARLA simulation environment.

The translation of moral panic into misogynist e-bile: the case of Turkish singer Gülşen

ABSTRACT In this paper, we examine a recent incident involving Gülşen, a Turkish singer who was brutally attacked on Twitter (now X), and demonstrate how moral panics translate into misogynist e-bile and violent cyber-attacks, both of which reinforce a polarized political environment. We analysed tweets posted 24–August 30 2022 and show that e-bile was used distinctly more often by opponents of Gülşen who are characterized by religiously conservative norms and values. We suggest that Gülşen’s subsequent criminalization by state institutions (she was detained and arrested in the aftermath of #arrestgülşen) effectively validated the violent attacks of Gülşen’s opponents while leaving her supporters intimidated and paralysed. Our study contributes to the understanding of e-bile by suggesting that cultural intelligibility and political hegemony make space for and legitimize the graphic language of online communities. By the same token, misogynistic and homophobic invective turns into an instrument of symbolic violence that is exercised by culturally and politically privileged segments of society.

Gender Differences in Perceptions of Psoriatic Arthritis Disease Impact, Management, and Physician Interactions: Results from a Global Patient Survey.

We evaluated the impact of gender on disease severity, health-related quality of life (HRQoL), treatment management, and patient-healthcare professional (HCP) interactions from the perspectives of patients with psoriatic arthritis (PsA). Data were collected from a global online patient survey conducted by The Harris Poll (November 2, 2017 to March 12, 2018). Eligible patients were aged ≥ 18years, with a self-reported diagnosis of PsA for > 1year, had visited a rheumatologist/dermatologist in the past 12months, and had reported previously using ≥ 1 conventional synthetic or biologic disease-modifying antirheumatic drug. Data were stratified by gender and analyzed descriptively, inferentially by binomial (chi-square) tests, and by multivariate logistic regression models. Data from 1286 patients who participated were included: 52% were female, 48% were male. Varying perceptions of disease severity between males and females were indicated by differences in symptoms leading to a diagnosis of PsA, and in symptoms reported despite treatment; more females than males reported joint tenderness, skin patches/plaques, and enthesitis. More females than males reported a major/moderate impact of PsA on their physical activity and emotional/mental well-being. Reasons for switching medication differed between genders, with more females switching because they perceived their medication to not be effective enough related to their joint symptoms. More females than males were very satisfied with their communication with their rheumatologist and were more likely to discuss the impact of PsA on their daily lives, their treatment satisfaction, and treatment goals with their rheumatologist. Patients' perceptions of the impact of PsA on HRQoL, treatment management, and interactions with HCPs varied between males and females. More females than males reported major/moderate physical and emotional impacts of PsA. When treating patients, it is important for HCPs to consider the potential impact of gender on patients' experience of PsA and its symptoms. Graphical plain language summary available for this article.

Design and Usability Testing of a Web-Based Intervention Module for Obesity: CoPT Nutri Trail

INTRODUCTION: Online interventions have emerged as innovative solutions to address health issues, notably obesity, while minimizing the necessity for in-person interactions during the recent COVID-19 pandemic. There is urgency in designing and developing an appropriate online intervention module within a web-based application. This study aims to describe the design process and usability of the online Canteen Operators, Parents, and Teachers (CoPT Nutri Trail) module for an upcoming school-based obesity intervention. MATERIALS AND METHODS: The design methodology consists of four phases: content development, design, web app development, and usability testing. The web application was designed to personalize usage for teachers, parents, and canteen operators to foster healthy environments for children. Thirteen experts, including teachers, nutritionists, and IT professionals, participated in the usability testing. RESULTS: All experts agreed that the design of the web application met the requirements of target users, requiring slight improvements in graphic design, language, and information elements. The web application tool was found acceptable, as the usability of alpha scores for all interface elements ranged from 68.2% to 86.6%, falling between good and very good scores. The content validation indices indicate good levels of validity (ranging from 0.83 to 1.00). CONCLUSION: The CoPT Nutri Trail web application is ready to be launched as a school-based intervention for obesity.