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Background: The widespread adoption of Hospital Information Systems (HIS) has brought significant benefits in healthcare quality and workflow efficiency. However, downtimes for system maintenance are inevitable and pose a considerable challenge to continuous patient care. Existing strategies, including manual prescription methods, are no longer effective due to increasing reliance on digital systems. Method: This study implemented two main strategies to mitigate the impact of scheduled downtimes. First, we created an "Emergency query program" that switches to a read-only backup server during downtimes, allowing clinicians to view essential patient data. Second, an "Emergency prescription system" was developed based on the Microsoft Power Platform and integrated into Microsoft Teams. This allows clinicians to perform digital prescriptions even during downtimes. Results: During a planned 90-minute downtime, 282 users accessed the Emergency Prescription System, resulting in 22 prescriptions from various departments. Average times for prescription confirmation and completion were 8 min and 3 s, and 18 min and 40 s, respectively. A post-downtime evaluation revealed high user satisfaction. Conclusion: Essential maintenance-induced HIS downtimes are inherently disruptive to patient care process. Our deployment of an emergency query program and a Microsoft Teams-integrated emergency prescription system demonstrated robust care continuity during HIS downtime. [ABSTRACT FROM AUTHOR]

Purpose: Despite evidence that cashless payment modes influence spending behavior, researchers have yet to explain the underlying mechanism. Cash serves as a store of value, and transactions involve the transference of ownership in circulation. This study aims to unpack why the physical and visceral nature of cash embodies psychological ownership and how the physicality of cash attenuates the awareness of spending, curtailing instinctive and unnecessary spending. Design/methodology/approach: Drawing on data collected in 2013 in New Zealand, the authors conducted another study in the quite different context of China in September 2023, using identical semistructured discussion protocols. The data from 2013 involved five focus group sessions containing at least six participants, involving 31 adults who also completed an open-ended questionnaire immediately before the group discussion commenced. The data collection in 2023 used the same open-ended and semistructured discussion protocol used in 2013, resulting in 180 adult open-ended responses – a nonprobability criterion-based purposive sampling guided participant selection in the 2013 and 2023 studies. Findings: Findings reveal that psychological ownership does manifest in the app more than in the ownership of money itself. People felt happy, confident, safe and secure while using apps that stored their money. Physical attributes of cash result from sensory perceptions of handling, counting and touching cash and coins. A sense of psychological ownership heightens spending awareness and ramifies spending behavior. The research found sadness and guilt as negative emotions when parting with money. Originality/value: This study offers empirical support to explain why psychological ownership of cash regulates spending and why the psychological processes that underlie "owned" money interrupt the spending with cash. [ABSTRACT FROM AUTHOR]

The nation's education-related information reform is making slow progress in light of the recent significant advancements in information technology. Early childhood education informatization has become a crucial part of the national education informatization building, serving as the first link in the chain of lifelong learning. This paper analyzes the significance of using children's games in the classroom and the significance of incorporating new media resources into children's course games by fusing the benefits of new media resources for teaching in a real-world educational setting. The goal is to realize the gamification of early childhood education courses and strengthen the management and deepening of course resources. The study also shows that customer involvement serves as a mediator between a better brand experience and a consumer's desire to make another purchase from the business. Subsequent interviews demonstrated that the following factors accounted for users' motivations for using the app: rewards, competition, feeling of accomplishment, and knowledge acquisition; engagement and identity clarified how using the gamified application affected users' attitude and loyalty towards the main service. In summary, our contribution advances the understanding of how gamified affordances can enhance consumer experiences by adding value to the focus brand that is facilitated by a third-party app as well as the gamified consuming experiences themselves. [ABSTRACT FROM AUTHOR]

A lightweight multi-material combination of steel and aluminium alloy is becoming a novel approach towards environmentally sustainable transport systems. However, the joining of steel/Al is difficult due to the formation of brittle and hard intermetallic compounds (IMC) at the interface. Hence, there is an immense need to critically review the metallurgical challenges of IMC formation for steel/Al dissimilar RSW and summarise its significance and current scenario for controlling IMC formation and growth. This article presents the review of past research works that focus on controlling the formation and growth of IMC for steel/Al dissimilar resistance spot welding during the last decade. It also includes IMC formation mechanism, advanced characterisation techniques, significance of IMC thickness and effect of process parameters on IMC formation. Fe2Al5 is the most brittle and dominant IMC formed at the interface, which affects the soundness of the welded joint. Application of third-party interlayer at the interface, directly or by an auxiliary process, is observed as an effective approach for controlling the growth of IMC. Though this interlayer does not prevent the formation of IMC, it will reduce the growth or brittleness of IMC by changing its chemical configuration. [ABSTRACT FROM AUTHOR]

Online platforms aggregating brands, such as Amazon and Alibaba's Tmall, have emerged as powerful intermediaries for brands. Although these platforms offer unprecedented access to consumers, the platform controls this access. Thus, concerns are raised about how these platforms interfere with the brand experience and, ultimately, performance. The question of how brands can govern their platform operations more effectively thus arises. There are essentially two types of governance models: a one-party (1P) marketplace (wholesaling to the platform) and a third-party (3P) marketplace (selling directly to the consumer on the platform). However, it is unclear how 1P or 3P operations affect brand performance. To that extent, the authors study the market share implications of operations on JD.com, a 1P platform, and Tmall, a 3P platform, for almost 2,000 brands. On average, 1P operations decrease shares, whereas 3P operations lift shares. These changes depend on different brand-specific moderators. For 1P operations, share drops are more substantial for brands that are unable to elicit a trustworthy consumer relationship, when alternative brands abound and rogue-seller activities are severe in the product category. The 3P share lifts, in contrast, are more substantial for premium-priced, nonleading brands with prior direct-to-consumer experience. [ABSTRACT FROM AUTHOR]

Today, Smart Assistants (SAs) are supported by significantly improved Natural Language Processing (NLP) and Natural Language Understanding (NLU) engines as well as AI-enabled decision support, enabling efficient information communication, easy appliance/device control, and seamless access to entertainment services, among others. In fact, an increasing number of modern households are being equipped with SAs, which promise to enhance user experience in the context of smart environments through verbal interaction. Currently, the market in SAs is dominated by products manufactured by technology giants that provide well designed off-the-shelf solutions. However, their simple setup and ease of use come with trade-offs, as these SAs abide by proprietary and/or closed-source architectures and offer limited functionality. Their enforced vendor lock-in does not provide (power) users with the ability to build custom conversational applications through their SAs. On the other hand, employing an open-source approach for building and deploying an SA (which comes with a significant overhead) necessitates expertise in multiple domains and fluency in the multimodal technologies used to build the envisioned applications. In this context, this paper proposes a methodology for developing and deploying conversational applications on the edge on top of an open-source software and hardware infrastructure via a multilayer architecture that simplifies low-level complexity and reduces learning overhead. The proposed approach facilitates the rapid development of applications by third-party developers, thereby enabling the establishment of a marketplace of customized applications aimed at the smart assisted living domain, among others. The supporting framework supports application developers, device owners, and ecosystem administrators in building, testing, uploading, and deploying applications, remotely controlling devices, and monitoring device performance. A demonstration of this methodology is presented and discussed focusing on health and assisted living applications for the elderly. [ABSTRACT FROM AUTHOR]

Mobile devices (MDs) are used by mobile cloud computing (MCC) customers and by other users because of their portability, robust connectivity, and ability to house and operate third-party applications (apps). However, the apps installed on an MD may pose data security risks to the MD owner and to other MCC users, especially when the requested permissions include access to sensitive data (e.g., user's location and contacts). Calculating the risk score of an app or quantifying its potential harmfulness based on user input or on data gathered while the app is actually running may not provide reliable and sufficiently accurate results to avoid harmful consequences. This study develops and evaluates a risk assessment framework for Android-based MDs that does not depend on user input or on actual app behavior. Rather, an app risk evaluator assigns a risk category to each resident app based on the app's classification (benign or malicious) and the app's risk score. The app classifier (a trained machine learning model) evaluates the permissions and intents requested by the app. The app risk score is calculated by applying a probabilistic function based on the app's use of a set of selected dangerous permissions. The results from testing of the framework on an MD with real-life resident apps indicated that the proposed security solution was effective and feasible. [ABSTRACT FROM AUTHOR]

The work proposed here is an automated pre and post-processor integrated to PanAir that is is a high-order aerodynamic panel method-based software for flow analysis developed in 70s but still in active use especially for preliminary aircraft design. With the integrated environment proposed in this work, manipulation of input and output data to and from PanAir is bypassed successfully that is otherwise requires manual manipulations and use of third party software. The integrated environment is validated over a Cessna 210 aircraft with a modified NLF (1)-0414 airfoil. The flow around the aircraft is analyzed using PanAir together with the integrated environment and results show that pre and post processing times reduced and ease in PanAir use is increased significantly. [ABSTRACT FROM AUTHOR]

Summary: Software‐defined network (SDN) technology is widely used for computer networks, especially in enterprise data centers and virtualized networking. However, SDN networks encounter severe challenges to security. One such challenge comes from third‐party applications that contain malicious logic and security vulnerabilities, resulting in controller integrity attacks. In this paper, we propose a defensive mechanism of object integrity for SDN (DMoiSDN) to mitigate the issue known as Cross‐App Poisoning (CAP). Our results contribute to increasing the integrity level of the controller's resources by conducting a potential risk analysis, which showed a decrease of 57% in the risk factor for potential attacks. We further examined the results of comparing DMoiSDN's performance with related work that uses information flow control (IFC) policies. The best results among the three conducted scenarios were as follows: we found that decreased latency in our system ranged from 12% to 90%, with an average of 59%, when encountering an increase in requests. It ranged from 78% to 49%, with an average of 63%, when receiving a variable number of total permissions for each application. DMoiSDN is expected to show a perceptible but reasonable latency and, to some extent, be able to avoid a critical impact on performance. [ABSTRACT FROM AUTHOR]

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Motivation The BigWig and BigBed file formats were originally designed for the visualization of next-generation sequencing data through a genome browser. Due to their versatility, these formats have long since become ubiquitous for the storage of processed sequencing data and regularly serve as the basis for downstream data analysis. As the number and size of sequencing experiments continues to accelerate, there is an increasing demand to efficiently generate and query BigWig and BigBed files in a scalable and robust manner, and to efficiently integrate these functionalities into data analysis environments and third-party applications. Results Here, we present Bigtools , a feature-complete, high-performance, and integrable software library for generating and querying both BigWig and BigBed files. Bigtools is written in the Rust programming language and includes a flexible suite of command line tools as well as bindings to Python. Availability and implementation Bigtools is cross-platform and released under the MIT license. It is distributed on Crates.io, Bioconda, and the Python Package Index, and the source code is available at https://github.com/jackh726/bigtools. [ABSTRACT FROM AUTHOR]

Our institutional approach to performing periodic constancy checks on dose calculations for the Varian Eclipse treatment planning system is described, including details of how the Radformation ClearCheck software is leveraged for highly efficient results analysis. Photon- and electron-specific synthetic phantoms are created which allow all modality-specific fields to be spatially separated and calculated in a single plan, with field-specific structures encompassing individual irradiated volumes facilitating field-specific dose distribution evaluations. Plan comparison templates in ClearCheck allow for the near-instantaneous evaluation of 116 and 165 individual calculation metrics for photon and electron fields, respectively. The methodology is further applied to the Radformation ClearCalc finite-size pencil beam and electron algorithms for secondary algorithm validation. The total time required for constancy evaluations of 6 primary algorithms and 4 secondary algorithms is less than one hour, with much of that time used for passive dose calculation. [ABSTRACT FROM AUTHOR]

Platform ecosystems shift the locus of innovation from internal departments to third-party developers, leading to knowledge boundaries between the platform owner and these external developers. Whereas traditional knowledge management approaches focus on intraorganizational knowledge sharing, platform owners have to adopt an inter-organizational approach to integrate knowledge across firm boundaries. Platform owners thus rely on knowledge boundary resources such as technical documentation, information portals, training materials, sample code, blogs, and online communities to overcome knowledge boundaries in their ecosystems. Existing research has identified different types of knowledge boundaries and knowledge boundary resources, but further research is needed to clarify how they influence third-party application development. Against this background, we study how third-party developers integrate knowledge boundary resources into their development practices. To derive an in-depth understanding of the phenomenon, we used cognitive fit theory and conducted a single case study of SAP’s Business Technology Platform. Based on 23 interviews, we developed a process model and distilled two primary purposes why third-party developers use knowledge boundary resources: learning and problemsolving. Based on these purposes, we explain the emergence of a knowledge boundary resource-purpose fit that shapes the selection, evaluation, and usage of knowledge boundary resources. We then draw upon various knowledge boundary resource characteristics to condense four cases with a particularly favorable knowledge boundary resource-purpose fit. Based on our results, we derive five propositions to help platform owners design effective knowledge boundary resources. [ABSTRACT FROM AUTHOR]

Android stands out as one of the most prevalent mobile operating systems globally, due to its widespread adoption and open-source nature. However, its susceptibility to malware attacks, facilitated by the ability to install third-party applications without centralized control, poses significant security challenges. Despite efforts to integrate security measures, the proliferation of malicious activities and vulnerabilities emphasizes the need for advanced detection techniques. This study implemented and optimized Long Short-Term Memory (LSTM) and Neural Network (NN) models for malware detection on the Android platform. Leveraging meticulous hyperparameter tuning and robust data preprocessing techniques, this study aimed to increase the efficacy of LSTM and NN models in identifying and mitigating various forms of malware. The results demonstrate remarkable performance, with the LSTM model achieving an accuracy of 99.24%, precision of 99.07%, recall of 98.79%, and F1-score of 98.93%, and the NN model attaining an accuracy of 99.18%, precision of 99.02%, recall of 98.84%, and F1-score of 98.93%. By addressing these challenges and achieving such high levels of accuracy and effectiveness, this study contributes significantly to the ongoing endeavor to fortify defenses against cyber threats, thus fostering a safer digital environment for users worldwide. [ABSTRACT FROM AUTHOR]

As the area of robotics achieves promising results, there is an increasing need to scale robotic software architectures towards real-world domains. Traditionally, robotic architectures are integrated using common frameworks, such as ROS. Therefore, systems with a uniform structure are produced, making it difficult to integrate third party contributions. Virtualisation technologies can simplify the problem, but their use is uncommon in robotics and general integration procedures are still missing. This paper proposes and evaluates a containerised approach for designing and integrating multiform robotic architectures. Our approach aims at augmenting preexisting architectures by including third party contributions. The integration complexity and computational performance of our approach is benchmarked on the EU H2020 SecondHands robotic architecture. Results demonstrate that our approach grants simplicity and flexibility of setup when compared to a non-virtualised version. The computational overhead of using our approach is negligible as resources were optimally exploited. [ABSTRACT FROM AUTHOR]

Due to the COVID-19 pandemic, the use of software applications has increased by end users, which is an issue regarding user data privacy. Numerous apps are collecting sensitive data like user location and phone number, which are becoming hotspots for cyber-attacks. A cyberattack breaches your data, attacking your information, thereby losing data integrity, confidentiality, and availability. Cyberattack refers to the unauthorized intrusion of external personnel into a user's private digital space. We have proposed a solution to provide secure data storage in third-party applications and leverage the power of Blockchain and Interplanetary File Systems. The proposed approach offers reliable role-based access to control data storage service that maintains data integrity, availability, and confidentiality. The proposed model uses the aforementioned technologies because they provide a distributed and decentralized nature of data storage and add-on support to data immutability. Traditionally the technologies used for such services are centralized and provide a single point of attack for the attacker. It puts confidential user data in jeopardy. The proposed solutions store encrypted data distributed to reduce reliance on big tech giants for data storage support and uproot the fear of collapsing systems due to a single point of failure. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) includes billions of sensors and actuators (which we refer to as IoT devices) that harvest data from the physical world and send it via the Internet to IoT applications to provide smart IoT services and products. Deploying, managing, and maintaining IoT devices for the exclusive use of an individual IoT application is inefficient and involves significant costs and effort that often outweigh the benefits. On the other hand, enabling large numbers of IoT applications to share available third-party IoT devices, which are deployed and maintained independently by a variety of IoT device providers, reduces IoT application development costs, time, and effort. To achieve a positive cost/benefit ratio, there is a need to support the sharing of third-party IoT devices globally by providing effective IoT device discovery, use, and pay between IoT applications and third-party IoT devices. A solution for global IoT device sharing must be the following: (1) scalable to support a vast number of third-party IoT devices, (2) interoperable to deal with the heterogeneity of IoT devices and their data, and (3) IoT-owned, i.e., not owned by a specific individual or organization. This paper surveys existing techniques that support discovering, using, and paying for third-party IoT devices. To ensure that this survey is comprehensive, this paper presents our methodology, which is inspired by Systematic Literature Network Analysis (SLNA), combining the Systematic Literature Review (SLR) methodology with Citation Network Analysis (CNA). Finally, this paper outlines the research gaps and directions for novel research to realize global IoT device sharing. [ABSTRACT FROM AUTHOR]

Purpose: ACR and AAPM task group's guidelines addressing commissioning for dedicated MR simulators were recently published. The goal of the current paper is to present the authors' 2-year experience regarding the commissioning and introduction of a QA program based on these guidelines and an associated automated workflow. Methods: All mandatory commissioning tests suggested by AAPM report 284 were performed and results are reported for two MRI scanners (MAGNETOM Sola and Aera). Visual inspection, vendor clinical or service platform, third-party software, or in-house python-based code were used.Automated QA and data analysis was performed via vendor, in-house or third-party software. QATrack+ was used for QA data logging and storage. 3D geometric distortion, B0 inhomogeneity, EPI, and parallel imaging performance were evaluated. Results: Contrasting with AAPM report 284 recommendations, homogeneity and RF tests were performed monthly. The QA program allowed us to detect major failures over time (shimming, gradient calibration and RF interference). Automated QA, data analysis, and logging allowed fast ACR analysis daily and monthly QA to be performed in 3 h. On the Sola, the average distortion is 1 mm for imaging radii of 250 mm or less. For radii of up to 200 mm, the maximum, average (standard deviation) distortion is 1.2 and 0.4 mm (0.3 mm). Aera values are roughly double the Sola for radii up to 200 mm. EPI geometric distortion,ghosting ratio,and long-termstability were found to be under themaximum recommended values. Parallel imaging SNR ratio was stable and close to the theoretical value (ideal g-factor). No major failures were detected during commissioning. Conclusion: An automated workflow and enhanced QA program allowed to automatically trackmachine and environmental changes over time and to detect periodic failures and errors that might otherwise have gone unnoticed.The Sola is more geometrically accurate, with a more homogenous B0 field than the Aera. [ABSTRACT FROM AUTHOR]

Social media and firm applications are two mobile service marketing mechanisms that rely on push or pull promotions to be effective. Literature, however, has yet to uncover how the promotions may complement each other when purposefully implemented. Our study examines this possibility in the grocery industry over three months. First, we create and manage a supermarket's Instagram profile, posting to the account (push promotion). Next, we compare performance measures with a third-party mobile app (pull promotion), which provides aggregated customer views and access to the supermarket profile. A time-series analysis reveals a sequential chain from push promotion to pull promotion to performance, the temporal effect of a push to pull, and the mediating effect from push to pull to purchase with an elasticity of.23. Results are important to those balancing push and pull promotional efforts and those involved with digital marketing and promotion in retailing. [ABSTRACT FROM AUTHOR]