Multiple Aspects Research Articles

Creativity and artificial intelligence: A multilevel perspective

Artificial intelligence is likely to revolutionize multiple aspects of organizational creativity. Through a multilevel theoretical lens, the present paper reviews the extant body of knowledge on creativity at individual, team and organizational levels, and draws a series of propositions on how the implementation of artificial intelligence may affect each level. Spanning cognitive, behavioural and psychological domains, our propositions aim at directing future research efforts on important creativity‐related areas likely to be affected by artificial intelligence, including the trade‐off between convergent and divergent thinking, the distribution of skills within groups, and the absorptive capacity of organizations.

QI$$^2$$: an interactive tool for data quality assurance

AbstractThe importance of high data quality is increasing with the growing impact and distribution of ML systems and big data. Also, the planned AI Act from the European commission defines challenging legal requirements for data quality especially for the market introduction of safety relevant ML systems. In this paper, we introduce a novel approach that supports the data quality assurance process of multiple data quality aspects. This approach enables the verification of quantitative data quality requirements. The concept and benefits are introduced and explained on small example data sets. How the method is applied is demonstrated on the well-known MNIST data set based an handwritten digits.

Madagascar's burned area from Sentinel-2 imagery (2016–2022): Four times higher than from lower resolution sensors

Madagascar is one of the most burned regions in the world, to the point that it has been called the ‘Isle of fire’ or the ‘Burning Island’. An accurate characterization of the burned area (BA) is crucial for understanding the true situation and impacts of fires on this island, where there is an active scientific debate on how fire affects multiple environmental and socioeconomic aspects, and how fire regimes should be in a complex context with differing interests. Despite this, recent advances have revealed that BA in Madagascar is poorly characterised by the currently available global BA products. In this work, we present, validate, and explore a BA database at 20 m spatial resolution for Madagascar covering the period 2016–2022. The database was built based on 75,010 Sentinel-2 images using a two-phase BA detection algorithm. The validation with independent long-term reference units showed Dice coefficients ≥79 %, omission errors ≤24 %, commission errors ≤18 %, and a relative bias ≥ − 8 %. An intercomparison with other available global BA products (GABAM, FireCCI51, C3SBA11, or MCD64) demonstrated that our product (i) exhibits temporal consistency, (ii) represents a significant accuracy improvement, as it reduces BA underestimations by about eightfold, (iii) yields BA estimates four times higher, and (iv) shows enhanced capability in detecting fires of all sizes. The observed BA spatial patterns were heterogeneous across the island, with 32 % of the grasslands burning annually, in contrast to other land cover types such as the dense tropical forest where <2 % burned every year. We conclude that the BA characterization in Madagascar must be addressed using imagery at spatial resolution higher than MODIS or Sentinel-3 (≥250 m), and temporal resolution higher than Landsat (16 days) to deal with cloudiness, the rapid attenuation of burn scars signals, and small fire patches.

Assessing the Impact of Metrics on the Choice of Prognostic Methodologies

Over the past years, advanced prognostic models and approaches have been developed. Most existing approaches are tailored to one specific system and cannot adaptively be used on different systems. This can lead to years of research and expertise being put into implementing prognostic models without the capacity to predict system failures, either because of a lack of data or data quality or because failure behavior cannot be captured by data-driven models. In addition, prognostic models are often evaluated using metrics only related to the correctness of predictions, preventing meaningful evaluation of operational performance. This paper makes use of a framework that can automatically choose prognostic settings based on specific system data. It simultaneously optimizes the choice of methodologies using metrics that capture multiple aspects of prediction quality. We apply this framework to both a simulated data set and a real aircraft data set to characterize the impact of metrics on the choice of prognostic methodologies. The results show that the choice of optimization metric greatly impacts the output of the generic prognostic framework and the overall performance. In addition, a definition for data suitability is provided and assessed on the aircraft system data sets.

Quality of YouTube Videos Regarding Anterior Cruciate Ligament Reconstruction Using Quadriceps Tendon Autograft Is Unsatisfactory

PurposeThis study aimed to assess the validity and informational value of teaching material regarding anterior cruciate ligament reconstruction (ACL-R) using quadriceps tendon (QT) autograft provided on the YouTubeTM video platform. MethodsAn extensive systematic search of the YouTubeTM video platform was performed, and all videos that met the criteria were included in the analysis. The analysis of the video content was performed using the DISCERN instrument, Journal of American Medical Association (JAMA) benchmark criteria and Global Quality Score (GQS). The duration of the videos, the date of publication, and the number of likes and views were recorded. Furthermore, videos were categorized based on the source (physicians, companies, patients), the subject (surgical technique, patient experience and overview [overview videos were videos in which multiple aspects were analyzed]) and the type of content (educational or subjective patient experience). ResultsA total of 88 videos were included in the analysis. Seventy-one (80.7%) videos were published by physicians, 15 (17.0%) by patients and 2 (2.3%) by companies. The majority of the videos described various surgical techniques (59 – 67.0%), 80.7% of the videos (72 – 81.8%) had an educational nature, and the remaining 18.2% described patient experiences. The mean length of the videos was 8.21 ±7.88 minutes. The mean number of views was 3988.51 ±9792.98 (range: 9-56047), while the mean numbers of comments and likes were 30.07±70.07 (range: 0-493) and 4.48 ±14.22 (range: 0-82), respectively. The mean DISCERN score, JAMA score, and GQS were 27.43 ±11.56 (95% CI: 25.01–29.85; range: 17-68), 1.22 ±0.85 (95% CI: 1.04–1.40; range: 0-3), and 1.82 ±0.93 (95% CI: 1.63–2.01; range: 1-4), respectively. For all scores, videos published by physicians had higher quality (DISCERN score, JAMA score, and GQS) (p<0.05). Among all of the analyzed videos, overview videos were of the highest quality (p<0.05). ConclusionsYouTube™ is a fast and open-access source of mass information. The overall quality of the videos on ACL reconstruction performed using QT autograft was unsatisfactory, demonstrating low educational quality and reliability. Currently, YouTube™ cannot be recommended as a reliable source of information on ACL reconstruction with the quadriceps tendon.

Understanding Academic Procrastination: Causes, Correlates, and Gender Nuances for Enhanced Self-regulated Learning

The study investigates academic procrastination, analyzing 50 participants using the Procrastination Assessment Scale (PASS). It identifies significant correlations (p &lt; 0.05) between procrastination domains, causes, and self-efficacy, highlighting gender-related nuances. Procrastination affects multiple academic aspects concurrently, with intertwined causes like task aversion and distractions. Strong self-efficacy mitigates procrastination's impact, empowering students in their academic pursuits. The research emphasizes holistic approaches targeting procrastination's core triggers and underscores the importance of bolstering self-efficacy to foster self-regulated learning. Gender-specific differences in procrastination patterns suggest tailored interventions in educational settings. Beyond academia, findings have implications for workplace productivity. The study prompts further exploration of procrastination's long-term effects on careers. It urges proactive measures to combat procrastination's pervasive influence, enabling individuals to seize educational opportunities and confront challenges resiliently.

Easing the Burden on Caregivers- Applications of Artificial Intelligence for Physicians and Caregivers of Children with Cleft Lip and Palate.

Many caregivers of children with cleft lip and palate experience a high level of anxiety throughout their child's medical and surgical care. We aim to evaluate artificial intelligence (AI) as a tool to mitigate these feelings and can aid clinicians in the development of robust pediatric educational materials for caregivers and families. Thirteen of the most common postoperative questions following cleft lip and/or palate repair were developed by an expert panel of senior Pediatric Plastic Surgeons and were posed to ChatGPT. Professional answers from the expert panel were provided and compared to responses from ChatGPT. A literature review was also conducted to generate a new support model for caregivers with children undergoing a surgical procedure. Department of Pediatric Plastic Surgery at a metropolitan Children's Hospital. Senior Pediatric Plastic Surgeons at a metropolitan Children's Hospital. None. The primary outcome was to determine the ability of ChatGPT to respond to common postoperative questions and to develop a model for AI assistance in family-centered perioperative care. ChatGPT had a postoperative question response accuracy rate of 69% when compared with subject matter expert responses, with its greatest errors being information errors. An extensive literature search revealed that AI can assist in multiple traditional perioperative strategies to reduce caregivers and patient anxiety. Artificial Intelligence can help to reduce the burden of generating patient education materials as well as support caregivers in multiple aspects and perioperative care.

Unveiling a novel clinical risk assessment model for identifying non-suicidal self-injury risks in depressed Chinese adolescents amidst the COVID-19 pandemic: insights from low self-esteem, internet use, and sleep disturbance.

Non-suicidal self-injury (NSSI) is a highly prevalent behavioral problem among depression adolescent patients that can result in numerous adverse outcomes. This study endeavors to bridge this knowledge gap by creating a comprehensive model that incorporates multiple aspects of NSSI to accurately evaluate its risk in adolescents with depression, thereby enhancing our ability to prevent and address this challenging issue. Using a cross-sectional design, we recruited 302 adolescents with depressive disorders who visited or were hospitalized at Shandong Mental Health Center from December 2021 to June 2022. The participants completed several self-report questionnaires, including the Chinese version of the Internet Addiction Test, the Pittsburgh Sleep Quality Index questionnaire, the Defeat Scale, the Social Avoidance and Distress Scale and the Children's Depression Inventory. Logistic regression analysis was performed to identify the diagnostic factors, which were further used to establish clinical risk assessment models. A receiver operating characteristic curve (ROC) to identify the best model. An external validating team was introduced to verify the assessing efficiency. Based on a logistic regression analysis, three variables have been identified as significant risk factors. Specifically, adolescents with depression who experience low self-esteem, internet use, or suffer from sleep disturbance face an increased risk of NSSI. An integrated risk index for NSSI exhibits excellent accuracy in identifying depressed adolescents at risk of NSSI (area under the curve = 0.86, sensitivity = 0.88, specificity = 0.69). In the validation cohort, the identification performance remains strong (area under the curve = 0.84, sensitivity = 0.72, specificity = 0.81). This study highlighted the role of self-esteem, internet use and sleep disturbance in the development of NSSI. The risk index diagnosing NSSI onset may help to guide the design and application of novel interventions to minimize this risky behavior in future depressed adolescents.

Transcriptional determinants of lipid mobilization in human adipocytes.

Defects in adipocyte lipolysis drive multiple aspects of cardiometabolic disease, but the transcriptional framework controlling this process has not been established. To address this, we performed a targeted perturbation screen in primary human adipocytes. Our analyses identified 37 transcriptional regulators of lipid mobilization, which we classified as (i) transcription factors, (ii) histone chaperones, and (iii) mRNA processing proteins. On the basis of its strong relationship with multiple readouts of lipolysis in patient samples, we performed mechanistic studies on one hit, ZNF189, which encodes the zinc finger protein 189. Using mass spectrometry and chromatin profiling techniques, we show that ZNF189 interacts with the tripartite motif family member TRIM28 and represses the transcription of an adipocyte-specific isoform of phosphodiesterase 1B (PDE1B2). The regulation of lipid mobilization by ZNF189 requires PDE1B2, and the overexpression of PDE1B2 is sufficient to attenuate hormone-stimulated lipolysis. Thus, our work identifies the ZNF189-PDE1B2 axis as a determinant of human adipocyte lipolysis and highlights a link between chromatin architecture and lipid mobilization.

Nesting biology and nest structure of the exotic bee Megachile sculpturalis.

From the 1990s, the Southeast Asia native giant resin bee Megachile sculpturalis (Smith, 1853) was introduced first to North America, and then to many countries in Europe. Despite increasing studies on its invasive potential and geographical expansion, information on nesting behaviour of this species is still extremely scarce. To increase knowledge on the nesting biology of M. sculpturalis, we studied multiple aspects of nesting and pollen provisioning in three consecutive years in artificial nests in Bologna, Italy. We observed 166 bees visiting nests, and followed individual nesting behaviour and success of 41 adult females. We measured cavity diameter in 552 nests and characterised the structure in 100 of them. More than 95% of nest diameters ranged between 0.6 and 1.2 cm, overlapping with several sympatric species of cavity-nesting hymenopterans in the study area. Most nests had a first chamber from the entrance of variable length without brood, followed by an average of about two brood cells with a mean length of 2.85 ± 0.13 cm each. The pollen stored in brood cells was almost monofloral, belonging to the ornamental plant Styphnolobium japonicum (L.) Schott. We estimated that a single female should visit ≈180 flowers to collect enough pollen for a single brood cell. These results fill knowledge gaps on the nesting biology and nest structure of the exotic M. sculpturalis, and they are discussed in relation to possible competition with native bees for nesting sites and foraging resources.

Computer Network Virus Defense with Data Mining-based Active Protection

A novel approach is presented in this paper to address the limitations of virtual machine technology, active kernel technology, heuristic killing technology, and behaviour killing technology in computer network virus defence. The proposed method provides data mining technology, specifically Object-Oriented Analysis (OOA) mining, to detect deformed and unknown viruses by analyzing the sequence of Win API calls in PE files. Experimental results showcase the Data Mining-based Antivirus (DMAV) system's superiority over existing virus scanning software in multiple aspects: higher accuracy in deformed virus detection, enhanced active defence capabilities against unknown viruses (with a recognition rate of 92%), improved efficiency, and a reduced false alarm rate for non-virus file detection. Furthermore, the paper introduces an OOA rule generator to optimize feature extraction, enhancing the system's intelligence and robustness. This research provides a promising solution to support virus detection accuracy, active defence mechanisms, and overall efficiency while minimizing false positives in virus scanning, thus contributing significantly to the advancement of computer network security.

Framework for metamodel-based design optimization considering product performance and assembly process complexity

This paper proposes a method for simultaneous evaluation of the assembly process complexity together with the performance of the future product. It allows for product design optimization, considering different aspects of the future design at the early stage of the development process. The proposed method, embodied in a fully automated framework, substitutes the traditional sequential development process with a more efficient and rapid combined procedure, which addresses multiple design aspects simultaneously. Design for assembly (DFA) rules, used as quantitative metrics of the ease-of-assembly of the whole product and individual assembly operations, are automatically evaluated together with performance metrics, estimated based on finite element (FE) simulations. The direct solution to this optimization problem might be inefficient or impossible since it requires the recurrent evaluation of computationally expensive discrete and continuous functions with unknown behavior that represent the optimization objectives and constraints. For that reason, the proposed framework employs regression models based on the Gaussian process and artificial neural networks, thus achieving the optimal design of a product as a result of metamodel-based design optimization (MBDO). The suggested approach is demonstrated in the optimization of a gearbox assembly, considering its mechanical performance and assembly process. Comparing the results of the metamodel-based and direct design optimization shows that MBDO allows finding a better solution using a three times smaller computational budget. In addition, analysis of the results obtained using stationary sampling data sets of different sizes highlighted the limitations of the employed sampling procedure.

Exploring the Rural Revitalization Effect under the Interaction of Agro-Tourism Integration and Tourism-Driven Poverty Reduction: Empirical Evidence for China

Under the robust impetus of China’s rural revitalization strategy, agro-tourism integration and tourism-driven poverty reduction have profoundly impacted various aspects of China’s economy, society, and ecology. This has propelled coordinated urban–rural development and the sustainable development of the tourism industry. This study introduces an analytical framework encompassing tourism-driven poverty reduction, agro-tourism integration, and rural revitalization. Through PVAR and threshold models, it empirically examines the interactive effects, dynamic relationships, and threshold effects between agro-tourism integration, tourism-driven poverty reduction, and rural revitalization. The conclusions are as follows: Firstly, the indices of rural revitalization and the level of agro-tourism integration show an increasing trend across Chinese provinces, with varying trends in tourism-driven poverty reduction efficiency. Secondly, there is a significant dynamic relationship among these factors, with the explanatory power of tourism-driven poverty reduction and agro-tourism integration gradually strengthening. Agro-tourism integration is identified as the most effective means of driving rural revitalization, while tourism-driven poverty reduction has a relatively weaker direct impact. Thirdly, tourism-driven poverty reduction exhibits a positive impulse response to agro-tourism integration. The improvement in tourism-driven poverty reduction efficiency propels further development in agro-tourism integration, thereby fostering rural revitalization. The efficiency of tourism-driven poverty reduction presents a single threshold effect in the process of agro-tourism integration promoting rural revitalization. Fourthly, the development of China’s tourism industry has become an indispensable means of promoting rural revitalization and poverty reduction. However, rural revitalization is a comprehensive project influenced by various factors, requiring improvements and development across multiple aspects.

Analysis on the Influence and Approaches of Children's Self-Identity Construction

Children's self-identity plays a very important role in children's character formation, the establishment of three views and life development. Therefore, it is crucial to focus on the factors that form children's self-identity. This paper analyzes the important role of self-identity in children's development and reveals the key factors affecting the construction of self-identity. This paper argues that factors such as social and cultural environment, parental concepts, cultural background, and social development will affect the formation of children's self-identity. Therefore, this paper suggests that in order to pay attention to the formation of children's self-identity, it is necessary to work together from multiple subjects and aspects. First of all, in a multicultural society, it is necessary to understand different cultures with an open and inclusive attitude, so that children can be exposed to more perspectives and enrich their cognition. Second, parents should give children support and correct guidance. Schools and other educational departments should strengthen the education and guidance of children.

Financial dissatisfaction in people with psychotic disorders - A short report on its prevalence and correlates in a large naturalistic psychosis cohort

Psychotic disorders have a strong negative impact on multiple aspects of daily life, including people's financial situation. This exploratory study examines the level of financial dissatisfaction and its correlates in a large cohort of people with psychotic disorders. Data from the first assessments of people with psychotic disorders (n = 5271) who were included in the Pharmacotherapy Monitoring and Outcome Survey (PHAMOUS; 2006–2020), which is conducted in the northern Netherlands, were used. The Manchester Short Assessment of Quality of Life (MANSA) was used to measure financial dissatisfaction. In addition, sociodemographic and psychiatric characteristics, substance use and global and social functioning were assessed. One-fifth to one-third of people with psychotic disorders report financial dissatisfaction, fluctuating over the year in which they were assessed. These proportions are considerably higher than in the general population. Cannabis and other substance use were associated with higher levels of financial dissatisfaction (small to medium effect). The other significant associations showed (very) small effect sizes. Therefore, we conclude that financial dissatisfaction in people with psychotic disorders appears to be relatively independent of other demographic and psychiatric characteristics, and global and social functioning. These findings are an important first step for increasing knowledge on financial dissatisfaction among people with psychotic disorders. The findings can also contribute to raising awareness about the topic for healthcare professionals working in this field.

Sex, Power, and Violence: What Do the Rape Incidents in Susan Brownmiller's Against Our Will Actually Show?

Susan Brownmiller's groundbreaking book, Against Our Will: Men, Women, and Rape, brought much-needed attention to a tremendously understudied crime and exposed many dangerous misconceptions. However, it also inspired a massive debate about whether sexual violence is primarily driven by desires for sex or power, and that argument persists today. For this study, we treated the book's incidents ( N = 245) as data, instead of as a narrative, and systematically analyzed them. Overall, our findings suggest many perpetrators identified by Brownmiller may have been sexually frustrated, and multiple aspects of their behavior indicate they were seeking sexual relief. At the same time, many also seemed to be seeking increased sexual power to fulfill their desires, and a small subset may have specifically sought revenge against women. Together, these results suggest a potential middle ground exists amidst a polarized debate between scholars with adversarial perspectives.

Integrating innovation in teaching of special care dentistry: Exploration of students’ perceptions

Introduction: This study was undertaken to investigate students’ perceptions of innovation-integrated learning, adopted as an alternative approach for special care dentistry (SCD) training. Methods: Ninety final-year dental students from the 2021 cohort were divided into eight groups to complete an innovation project dedicated to eight categories of patients with special health care needs. Discussion and final presentations, involving related experts were conducted remotely via an online platform. Then, students were invited to answer a validated online feedback survey on their perceptions of the learning approach. Results: The response rate for the feedback survey was 91.1% (n=82). Most students agreed that the activity was interesting, improved their knowledge and understanding of SCD, allowed engagement between peers, supported sharing of ideas and experiences, encouraged student–lecturer interactions, and enhanced knowledge integration and application. Students also expressed that the activity enhanced creativity and innovation, instilled an interest and positive attitude toward learning SCD, and encouraged teamwork. However, a few students noted facing some limitations in completing their projects (i.e., technological challenges and reduced physical access to purchase materials). Around half felt neutral about having an increased workload from this activity. Moreover, perceptions differed regarding time and financial commitments, as well as supervisors’ and patients’ involvement during the project development process. Conclusion: Students perceived that the innovation-oriented learning activity, was beneficial in multiple aspects of SCD training. Keywords: Innovation, Learning, Dental Students, Perception

Game Theory Based Dynamic Event-Driven Service Scheduling in Cloud Manufacturing

Due to the individualized consumer needs, cloud manufacturing (CMfg) has been widely used in the optimization of available manufacturing resource allocation to enhance resource utilization and reduce energy consumption. However, efficient scheduling of tasks and subtasks under dynamic CMfg environments to these re-sources are challenging problems. This paper proposes a game theory based on task scheduling and model selection for effectively exploiting distributed manufacturing resources in CMfg, and the Nash equilibrium (NE) in this game theory is implemented by a double ant colony optimization (DACO) algorithm. Through this model, services provided by different providers can handle a batch of tasks in real-time. Besides, to satisfy different service providers and demanders, the proposed approach considers multiple task attributes simultaneously, including completion time, cost, service quality, service composition capability, service availability, energy consumption, service sustainability, service maintainability, and service trust. Simulation results demonstrate that the proposed method is not only effective for the relevant optimization objective but also can achieve great performance under real-time CMfg environments. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —To provide the best production guides, the efficiency of configuration optimization of manufacturing resources is critical to the control and management of smart manufacturing systems. This paper investigates the dynamic scheduling problem for manufacturing services in CMfg. Previous task scheduling approaches fail to evaluate multiple factors together, like completion time, cost, and energy consumption. Also, the traditional scheduling method cannot respond to requests caused by service state changes in an efficient way. Therefore, in this paper, a game theory model that consists of a static scheduling sub-game and a dynamic selection sub-game is presented. This model is achieved by adopting a proposed double ant colony optimization algorithm that solves constrained non-linear programming. Simulation experiments shown in this paper prove that the proposed method outperforms existing scheduling methods in multiple aspects, including completion time and energy consumption. Also, this method can be readily implemented and incorporated into real production environments. Future work can improve the proposed method by analyzing the uncertainty during scheduling tasks and sharing the logistics resources on the same routes.

Pharmaceutical changes and countermeasures for transformation of traditional Chinese medicine preparations in medical institutions into new drugs based on human use experience

Traditional Chinese medicine(TCM) preparations in medical institutions, as a unique and important form of preparations in China, have a long history of human use and serve as a bridge between clinical experience prescriptions and new Chinese medicine preparations. The state encourages medical institutions to transform their preparations into new traditional Chinese medicines, emphasizing their role as &quot;incubators&quot;. Since the proposal of the traditional Chinese medicine registration and evaluation evidence system with the integration of TCM theory, human use experience(HUE), and clinical experience, the idea of transforming preparations used in medical institutions into new drugs based on HUE has been increasingly valued by drug research and development organizations. In the transformation process, pharmaceutical changes should be concerned from multiple aspects. This paper discusses the pharmaceutical changes and countermeasures based on the transformation of traditional Chinese medicine preparations in medical institutions into new drugs based on HUE from the aspects of excipients, dosage forms, production technology, production scale, packaging materials and containers, production sites, and registration standards. It is emphasized that scientific decisions should be made according to the characteristics and clinical needs of drugs to ensure the stability of drug quality. The impacts of pharmaceutical changes on drug quality should be objectively assessed based on appropriate evaluation indexes and detection methods. The layout should be carried out in advance, and the key pharmaceutical information of the preparations should be kept stable, so as to underpin the transformation of traditional Chinese medicine preparations in medical institutions into new drugs based on HUE.

How can health science popularization KOL better produce professional voices?

How can health science popularization KOL better produce professional voices?