Integration Difficulties Research Articles

Advancing the Commercialization of Perovskite‐Based Radiation Detectors for High‐Resolution Imaging

AbstractRadiation detectors play an indispensable role in medical diagnostics, industrial non‐destructive inspection and national security. Recently, halide perovskites are considered as the new generation of radiation active materials due to excellent optoelectronic properties such as adjustable bandgap, high absorption coefficient, high carrier mobility and low cost. The radiation detectors based on perovskite show high sensitivity and low detection limit, contributing to excellent spatial resolution for imaging. However, the commercialization of perovskite radiation detectors for high quality imaging still faces many challenges, including ion migration in perovskite, fermi level pinning and electrochemical reaction at the interface of perovskite/electrode, and difficulties of integration with readout circuit. All the issues hinder the further improvement of device performance. This review summarizes the material forms and the optimized growth methods of perovskite for radiation imaging detectors. Further, this work focuses on challenges and improvements of the interface between perovskites and electrodes. Meanwhile, this work outlines the technical routes used to realize array detectors for radiation imaging. The comprehensive review would guide the commercialization of perovskite radiation detectors for high‐quality imaging.

Underreporting, Prevalence, and Epidemiological Trends of Orofacial Clefts in the Brazilian Amazon Region.

Cleft lip and palate are the most common congenital anomalies of the cranial segment worldwide. Particularly in low-income and middle-income countries, these conditions are associated with increased morbidity and mortality, socioeconomic challenges, and considerable psychological and social integration difficulties for affected individuals. This study aims to evaluate the epidemiological profile of patients with these conditions treated at a newly established specialized center in the Brazilian Amazonian Region. Data were extracted from medical records at a Reference Service for Clefts and Craniofacial Anomalies in the north of Brazil, covering the period from 2016 to 2020. These were compared with data from the official epidemiological health portal of the Brazilian Ministry of Health. The study recorded a total of 852 patients, with males comprising 54.4%. The predominant type of cleft was the transforaminal cleft, which accounted for 69.4% of cases, followed by postforamen clefts at 17.3%. The left side was more frequently affected in 63% of the cases. The primary surgical intervention performed was cheiloplasty, representing 39.5% of all procedures. Notably, 52% of the patients were from the interior regions of the state. The 2019 DataSUS data indicated a prevalence of cleft lip and palate in the State of Pará of 4.26 per 10,000 live births. However, data from this single specialized hospital showed a higher prevalence of 7.58 per 10,000 live births. These results may reflect underreporting of the number of cases reported in national official data sets.

Analyzing financial analysts' role in business optimization and advanced data analytics

This paper explores the evolving role of financial analysts in business optimization, focusing on their increasing reliance on advanced data analytics to drive strategic decision-making. It examines the historical shift from traditional financial analysis to more data-centric responsibilities, highlighting how modern financial analysts contribute to operational efficiency, cost reduction, and revenue growth through data-driven insights. Integrating advanced tools such as artificial intelligence, machine learning, and predictive analytics has enabled financial analysts to interpret complex datasets, optimize business processes, and improve market positioning. However, adopting these technologies comes with challenges, including a steep learning curve, data integration difficulties, and ethical concerns related to data privacy and bias in AI algorithms. This paper also discusses future trends in financial analysis, emphasizing the growing importance of real-time data analysis and automation in business optimization. The paper concludes by stressing the need for financial analysts to continually adapt to the rapidly evolving technological landscape to effectively shape corporate strategy.

Streamlining budgeting and forecasting across multi-cloud environments with dynamic financial models

This review paper explores the complexities of financial management in multi-cloud environments, emphasizing the need for streamlined budgeting and forecasting processes. It begins by addressing the challenges inherent in managing finances across multiple cloud platforms, such as integration difficulties, data silos, and cost management issues. The paper then provides an overview of dynamic financial models, detailing their components and benefits in overcoming these challenges. It highlights the role of automation, real-time data utilization, and predictive analytics in enhancing financial accuracy and efficiency. Furthermore, the paper discusses the importance of collaborative platforms in fostering stakeholder communication and coordination. Finally, strategic planning, best practices for multi-cloud financial management, and emerging trends and prospects are outlined. The review underscores the significance of aligning financial models with organizational goals and leveraging advanced technologies to achieve optimal financial outcomes in multi-cloud settings. Keywords: Multi-Cloud Financial Management, Budgeting and Forecasting, Dynamic Financial Models, Automation in Finance, Predictive Analytics.

The Role of Digital Technologies in Climate Change Management: Strategies for Minimizing the Environmental Impact of USA Companies

The article examines the role of digital technologies in climate change management and reducing the environmental impact of U.S. companies. Innovations such as artificial intelligence, the Internet of Things, and big data are analyzed for their ability to help companies minimize CO2 emissions, optimize resource use, and improve energy efficiency. Challenges companies face when implementing digital solutions: high initial costs, integration difficulties, and regulatory complexities, are discussed. Strategies for overcoming these barriers to achieve sustainable development are proposed.

Training of HOTS integration in elementary school level mathematics teaching as an effort to strengthen state defense awareness

Strengthening state defense awareness could be supported by the existence of educators from remote and border areas who have adequate performance of high-order thinking skills (HOTS). Currently, HOTS has not been consistently introduced in mathematics learning for teachers in remote areas. This study is a part of the teachers’ development program concerned with delivering effective methods in teaching mathematics at the elementary school level and gaining teachers’ State Defense Awareness to provide educators’ perspectives regarding HOTS implementation in mathematics learning in remote areas of Indonesia. Data was collected by giving questionnaires to the teachers as pre-tests and post-tests. The results showed that the teachers of some remote areas recognized the advantages as well as the difficulties of HOTS integration in learning activities. Teachers' understanding of applying HOTS in mathematics teaching could be slightly increased through comprehensive training regarding HOTS. It was also found that teachers from remote and border areas are still required to be more encouraged to implement and develop HOTS in mathematics learning through training in education research activities.

Getting to the situation: the N400 can indicate meaning integration beyond word priming

ABSTRACT Can integration processes during reading be detected in the N400 time window? Although many results have supported this possibility, recent research controlling for semantic priming concluded that only word-meaning retrieval is detected in the N400 [Delogu, F., Brouwer, H., & Crocker, M. W. (2019). Event-related potentials index lexical retrieval (N400) and integration (P600) during language comprehension. Brain and Cognition, 135, 103569. https://doi.org/10.1016/j.bandc.2019.05.007]. We report three experiments designed to detect N400 integration effects by encouraging situation-level comprehension, manipulating integration difficulty through event congruence. Experiments 1 and 2 created narrative texts and questions targeting attention to event structures, showing priming but no additional integration effects. In Experiment 3, readers formed mental images, updating their mental model with each sentence. The results show integration effects during the N400 window and later around 600 ms, indicating both priming and message-level integration effects can emerge in the N400 when readers engage in situational comprehension.

A systematic review of flipped classroom approaches in language learning

This systematic literature review aims to offer an in-depth analysis of the existing research landscape regarding the application of the flipped classroom approach within the domain of language learning. The investigators methodically selected and analyzed 57 papers from 656 documents using a systematic and rigorous approach to literature selection. Our findings demonstrate the significant international impact of this field, with contributions from many countries and districts as well as globally excellent academic institutions. This review examines multiple areas of research, including improving students’ perceptions and attitudes in flipped classrooms, language proficiency, motivational factors, etc. In addition, the research methods employed were evaluated, with a particular emphasis on mixed methods which combined the quantitative method with the qualitative method. Even though the application of flipped classrooms in language learning has achieved some achievements, some limitations are obvious. The most notable are the problem of sample size, the difficulty of technology integration, the lack of teacher training, the singularity of language research, etc. The research gaps revealed in this literature review, indicate interesting possibilities for future research. The diversity of research languages, the multiplicity of research methods, the integration of advanced technologies, and intensive teacher training will be significant of the area focus. This systematic literature review not only enriches the existing knowledge system but also has the potential to the direction of the development of flipped classrooms in language learning.

Nonreciprocal Acoustic Devices with Asymmetric Peierls Phases.

Nonreciprocity in acoustics is of paramount importance in many practical applications and has been experimentally realized using nonlinear media, moving fluids, or time modulation, which regrettably suffer from large volumes and high-power consumption, difficulty in integration, and inevitable vibrations or phase noise. In modern Hamiltonian theory, the violation of system's reciprocity can be achieved via asymmetric Peierls phases, which typically involves with non-Hermiticity or time-reversal symmetry breaking. Here, we propose a framework for designing nonreciprocal acoustic devices based on the asymmetric Peierls phases that can be fully controlled via active acoustic components. The fully controlled Peierls phases enable various high-performance acoustic devices, including non-Hermitian extensions of isolators, gyrators, and circulators, which are otherwise impossible in previous approaches that are bound by Hermiticity or passivity. We reveal that the transmission phases in isolators are equivalent to the Peierls phase plus a constant. The nonreciprocal phase delay in gyrators and the unirotational transmission behavior in circulators result from the gauge-invariant Aharonov-Bohm phases determined by Peierls phases. Our work not only uncovers multiple intriguing physics related to Peierls phases but also provides a general approach to compact, integratable, nonreciprocal acoustic devices.

Optimizing the Utilization of Online Public Access Catalog as a Means of Information Retrieval in Libraries

This study aims to explore the optimization of the Online Public Access Catalogue (OPAC) as an information retrieval tool in the Library of SMA Negeri 3 Medan, focusing on identifying the challenges and barriers to its effective use. A qualitative descriptive approach was employed, utilizing interviews, observations, and documentation as data collection methods. Interviews were conducted with a librarian and three students, while observations focused on the practical issues related to OPAC usage. The findings reveal that the use of OPAC in the library is not optimal, with challenges including system integration difficulties, insufficient librarian training, and limited user familiarity. Efforts to enhance OPAC usage involve promoting OPAC awareness, increasing computer access points, and ongoing system maintenance. However, the effectiveness of these measures is hindered by technical and educational constraints, highlighting the need for targeted interventions to fully leverage OPAC's potential in improving library services.

Introduction to In Session special issue: Psychotherapy for complex PTSD.

Complex Posttraumatic Stress Disorder (CPTSD) is a condition resulting from exposure to chronic, interpersonal traumatic events, in which some form of control or power dynamics existed. Its clinical picture includes the main symptom clusters of posttraumatic stress disorder, accompanied by dysregulated emotion, problems in interpersonal relationships, and difficulties in identity integration. In addition, both clinical work and research have shown CPTSD to include highly distressing and complicated psychological phenomena, such as identification with the aggressor, various forms of dissociation, self-harmand self-destructive behaviors, and more. Due to this highly complex and multilayered clinical picture, the treatment of CPTSD poses a significant clinical challenge to therapists. In this special issue of In Session, we present a series of case studies, each representing a different therapeutic approach to CPTSD (e.g., skills training for affective and interpersonal regulation, Eye Movement Desensitization and Reprocessing, psychodynamic, integrative psychotherapy). These cases also represent a wide variety of patient populations, as well as different types of underlying traumatic events. Together, they reveal the breadth of clinical possibilities currently available to trauma therapists encountering cases of CPTSD. They also highlight the challenges and dilemmas that clinicians often face when treating this condition, as well as ways to overcome those.

Research advances in tumor diagnosis and early detection

This review explores recent advances in tumor diagnosis and early detection, focusing on cutting-edge developments in molecular diagnostic technologies, imaging techniques, and the integration of multi-omics data. Current tumor diagnostic methods have limitations in terms of sensitivity and specificity, particularly for early tumor detection. However, with continuous progress in research and emerging technologies, especially the advent of liquid biopsy, which enables the detection of circulating tumor DNA (ctDNA), exosomes, and tumor-educated platelets (TEPs), the sensitivity and accuracy of early cancer detection have significantly improved. Moreover, the combined application of artificial intelligence and high-resolution imaging technology has enhanced the precision of diagnosis. Despite these advances, challenges, such as the high cost of technology and difficulties in data integration, continue to impede widespread clinical adoption. Therefore, I believe that future research should prioritize the innovation of these technologies to improve their applicability for early detection across various cancer types, ultimately contributing to the advancement of personalized therapy.

Qualitative Exploration of the "Guilt Gap" Among Physician-Faculty with Caregiving Responsibilities.

Introduction: Differences in time commitments and resources contribute to the difficulties of work-life integration for many physician-scientists, particularly for women with family caregiving responsibilities. Understanding the challenges faced by this population is critical for the retention of these critical members of the workforce. Methods: We conducted semi-structured telephone interviews with recipients of the 2017 Doris Duke Charitable Foundation's Fund to Retain Clinical Scientists (FRCS) and reviewed application narratives from the 2020 award recipients. Award recipients were asked about their caregiving responsibilities and careers, particularly as they related to the impact of the FRCS award and the aftereffects of the COVID-19 pandemic. Analysts then iteratively revised the coding scheme and interpreted the data using qualitative thematic analysis. Results: Of the 14 interviewees and 19 narrative contributors, 25 (76%) were women. The main qualitative themes that emerged were as follows: (1) women experience unrealistically high caregiving burdens, (2) women are overburdened by disadvantageous and undervalued expectations at work, (3) work-life expectations increased during the COVID-19 pandemic, and (4) unrealistic work-life expectations led to guilt and burnout. Conclusions: These findings provide a rich understanding of the factors contributing to guilt and burnout among physician-scientists, particularly women, and how work duties that increase physician obligations exacerbated these challenges. Understanding these experiences is critical to supporting and retaining a diverse workforce in academic medicine.

Research on Innovative Application and Practical Challenges of Generative Artificial Intelligence in English Teaching

With rapid IT advancements, generative AI is gradually transforming education, notably in English language teaching, displaying significant potential. This paper explores the application of generative AI in English teaching and the accompanying challenges. Firstly, through literature review, we summarize the development process of generative artificial intelligence technology, relevant theoretical basis and its application status in the field of education. The paper examines generative AI's application in English teaching, analyzing scenarios like personalized learning, interactive dialogues, automated assessment & feedback, and teacher tools. It also delves into practical impacts via case studies and discusses challenges like technical hurdles, integration difficulties, and ethical considerations. Finally, this paper summarizes the major contributions of generative AI in English teaching and puts forward suggestions for future development trends.

Evaluating the barriers of blockchain adoption in the Australian logistics industry

ABSTRACT Blockchain technology holds the potential to revolutionise the logistics industry by sharing tamper-proof information in a decentralised manner, building trust among parties. However, adoption in the Australian logistics industry lags behind other sectors. This study uses fuzzy DEMATEL to investigate barriers to blockchain adoption, identifying thirteen key barriers within the technology-organisation-environment (TOE) framework. Cost of investment and integration difficulties among partners are the most prominent barriers, particularly within organisational contexts. The findings offer a theoretical foundation and practical insights for overcoming barriers and successfully implementing blockchain in logistics.

Artificial intelligence in psychodermatology: A brief report of applications and impact in clinical practice.

This report evaluates the potential of artificial intelligence (AI) in psychodermatology, emphasizing its ability to enhance diagnostic accuracy, treatment efficacy, and personalized care. Psychodermatology, which explores the connection between mental health and skin disorders, stands to benefit from AI's advanced data analysis and pattern recognition capabilities. A literature search was conducted on PubMed and Google Scholar, spanning from 2004 to 2024, following PRISMA guidelines. Studies included demonstrated AI's effectiveness in predicting treatment outcomes for body dysmorphic disorder, identifying biomarkers in psoriasis and anxiety disorders, and refining therapeutic strategies. The review identified several studies highlighting AI's role in improving treatment outcomes and diagnostic accuracy in psychodermatology. AI was effective in predicting outcomes for body dysmorphic disorder and identifying biomarkers related to psoriasis and anxiety disorders. However, challenges such as limited dermatologist knowledge, integration difficulties, and ethical concerns regarding patient privacy were noted. AI holds significant promise for advancing psychodermatology by improving diagnostic precision, treatment effectiveness, and personalized care. Nonetheless, realizing this potential requires large-scale clinical validation, enhanced dataset diversity, and robust ethical frameworks. Future research should focus on these areas, with interdisciplinary collaboration essential for overcoming current challenges and optimizing patient care in psychodermatology.

Droplet volume prediction methods in electrohydrodynamic jet printing based on multi-source data fusion

Electrohydrodynamic jet printing technology has garnered significant interest in additive manufacturing due to its advantages in higher resolution printing and greater viscosity material applicability. Nonetheless, the challenges associated with femtoliter-level droplets and the micrometer-scale printing space have rendered traditional optical observation methods for volume calculation impractical for integration into the printing systems. Obtaining the droplet volume accurately has become a formidable challenge in electrohydrodynamic printing. While existing research utilizes machine learning for the end-to-end prediction of process parameters to droplet volume, traditional prediction methods cannot achieve online prediction due to the complex spray states characteristic of electrohydrodynamic jet printing and pose integration difficulties within printing systems. This paper introduces a multi-source data fusion model suitable for electrohydrodynamic printing droplet volume prediction. The model employs the VGG network to extract features from Taylor cone images in the jetting state and synchronously fuse these with process parameter features. The fused features are then correlated with droplet volume labels through the MLP network for comprehensive model training. The performance of the proposed model has improved by 10% in prediction accuracy compared to single modal data. We integrated the prediction method into an electrohydrodynamic jet printing system and experimented with printing pixel-pit substrates. The results indicate that the prediction accuracy of the volume prediction system is over 92%. The printing efficiency has improved approximately 3 times compared to the traditional method, significantly enhancing overall performance.

The effect of social media engagement on social integration of elderly migrants in China: the mechanism of perceived social support and psychological resilience

Surging numbers of older parents have migrated with adult children to developed urban areas under China’s internal family migration, experiencing several difficulties in social integration in local society. Social media has become an essential tool for older adults to gather information, socialize, and entertain. However, few studies have focused on the relationship between social media use and social integration among older migrants and the underlying psychological mechanisms. Drawing on the Media system dependency (MSD) theory and the Stress-buffering hypothesis, this study developed and tested a conceptual research model by conducting a cross-sectional online survey study (N = 1001). The results indicate that understanding and orientation, rather than entertainment, are two primary motivations for trailing parents to use social media. The activeness of social media engagement (exposure condition), rather than the intensity of social media use (selective exposure), can positively influence the social integration of older migrants. Psychological resilience cannot mediate the relationship between social media engagement and social integration, which is proved to be mainly achieved through perceived social support and the partial chain mediation of perceived social support and psychological resilience. These findings shed theoretical and practical light on the design of older migrant-friendly social media apps and the efforts of adult children and communities to enhance the social integration of older internal migrants through social media engagement.

Real-time mapping of photo-sono therapy induced cavitation using Doppler optical coherence tomography.

Photo-sono therapy (PST) is an innovative anti-vascular approach based on cavitation-induced spallation. Currently, passive cavitation detection (PCD) is the prevalent technique for cavitation monitoring during treatment. However, the limitations of PCD are the lack of spatial information of bubbles and the difficulty of integration with the PST system. To address this, we proposed a new, to the best of our knowledge, cavitation mapping method that integrates Doppler optical coherence tomography (OCT) with PST to visualize bubble dynamics in real time. The feasibility of the proposed system has been confirmed through experiments on vascular-mimicking phantoms and in vivo rabbit ear vessels, and the results are compared to high-speed camera observations and PCD data. The findings demonstrate that Doppler OCT effectively maps cavitation in real time and holds promise for guiding PST treatments and other cavitation-related clinical applications.

Optical fiber integrated WGM cylindrical cavity resonator.

Whispering gallery mode (WGM) resonators are usually discrete optical devices, which have integration difficulties with an optical fiber system. Here we present a new, to the best of our knowledge, type of optical fiber whispering gallery mode resonator based on a cylindrical cavity, which is located in the multimode fiber core and fabricated by femtosecond laser micromachining together with fast hydrofluoric acid etching techniques. When light traveling in the fiber core is tangent to the cylindrical cavity wall, it is coupled into the cavity and circulates along the cavity wall to excite WGM resonance before being coupled out to the same tangential path and continuing propagation in the fiber core. The device is fully integrated into the optical fiber, simple in fabrication, convenient in operation, low in cost, and has a good quality factor (Q) of 1.06 × 104. The device enriches the family of WGM resonators and is expected to have promising applications in photonics.