Search Results (7,632)

In recent decades, the integration of nanotechnology into dentistry has led to groundbreaking advancements in dental materials and applications. This article explores the role of nanoparticles (NPs) in modern dentistry, highlighting their definitions, unique properties, and various applications. The introduction establishes the significance of nanotechnology in dental health care, emphasizing the potential of NPs to transform traditional practices. The overview includes a discussion of the fundamental properties of NPs, which contribute to their effectiveness in dental applications. The article categorizes NPs into three main groups: antimicrobial, therapeutic, and material property-improving NPs, detailing their clinical uses and mechanisms of action. Furthermore, it addresses current innovations in dental products incorporating NPs and examines emerging trends in the field. The research for this review was conducted using high-quality, peer-reviewed scientific databases, including PubMed, Scopus, Web of Science, and Google Scholar, with no time restriction as an inclusion criterion. These databases were selected for their credibility and comprehensive collections of relevant studies. In conclusion, NPs represent a promising avenue for innovation in dental materials and therapeutics. Their unique properties enable the development of enhanced antimicrobial agents, effective drug delivery systems, and improved material performance. However, the risks associated with cytotoxicity and stability must be carefully managed to ensure safe and effective use. Ongoing research is essential to fully understand and optimize the applications of NPs in dentistry, balancing their benefits against potential health risks. As the field advances, the integration of NPs into clinical practice will likely revolutionize approaches to dental care and treatment. Full article

Body image concerns are key prognostic and pathogenic factors of anorexia nervosa (AN) and bulimia nervosa (BN). This study aimed to investigate the neural mechanisms underlying body image perception across its two domains of estimation and satisfaction in anorexia and bulimia patients and healthy controls (HC). Systematic searches were conducted across eight databases, including PubMed; Cochrane Library; Ovid; Google Scholar; Sage Journals; Scopus; PsycInfo; and ScienceDirect, from database inception until the 23rd of April 2023. The sample pertained to 14 functional magnetic resonance imaging (fMRI) studies and 556 participants, with tasks primarily including image and silhouette-based body estimation and satisfaction paradigms. ALE meta-analysis was conducted to investigate significant clusters of activation foci across the different studies. Shared activations were observed between HC, AN, and BN patients in cortical regions related to object manipulation and recognition, visuospatial awareness, and memory and negative affect regulation. Differential activation in interoceptive and higher-order cognitive or affective control regions likely hold the key to pathological body distortion. This study outlined commonalities and differences in the correlates driving healthy body mapping and eating disorder pathology. Our findings provide pertinent implications for future research, current clinical interventions, and therapeutic outcomes. Full article

The widespread adoption of web services has heightened exposure to cybersecurity threats, particularly SQL injection (SQLi) attacks that target the database layers of web applications. Traditional Web Application Firewalls (WAFs) often fail to keep pace with evolving attack techniques, necessitating adaptive defense mechanisms. This paper introduces a novel generative AI framework designed to enhance SQLi mitigation by leveraging Large Language Models (LLMs). The framework achieves two primary objectives: (1) generating diverse and validated SQLi payloads using in-context learning, thereby minimizing hallucinations, and (2) automating defense mechanisms by testing these payloads against a vulnerable web application secured by a WAF, classifying bypassing attacks, and constructing effective WAF security rules through generative AI techniques. Experimental results using the GPT-4o LLM demonstrate the framework’s efficacy: 514 new SQLi payloads were generated, 92.5% of which were validated against a MySQL database and 89% of which successfully bypassed the ModSecurity WAF equipped with the latest OWASP Core Rule Set. By applying our automated rule-generation methodology, 99% of previously successful attacks were effectively blocked with only 23 new security rules. In contrast, Google Gemini-Pro achieved a lower bypass rate of 56.6%, underscoring performance variability across LLMs. Future work could extend the proposed framework to autonomously defend against other web attacks, including Cross-Site Scripting (XSS), session hijacking, and specific Distributed Denial-of-Service (DDoS) attacks. Full article

Urban water bodies play a critical role in regulating urban climate, mitigating the urban heat island effect, and enhancing ecological environments. This study focuses on five typical heat island cities in Zhejiang Province, systematically analyzing the cooling effects of urban water bodies. Specifically, the study divides urban buffer zones into basic analytical units based on the urban road network and performs land surface temperature inversion and land use classification using the Google Earth Engine platform. Six representative morphology indicators of water bodies are selected, and the contributions of these indicators to the cooling effects of urban water bodies are evaluated using a Gradient Boosting Decision Tree regression model. Additionally, optimization strategies for water bodies in different cities are proposed. The results show the following: (1) Water bodies in central urban areas generally exhibit significant cooling effects, with the average land surface temperature reduction in water bodies exceeding 5.13 °C compared to built-up areas in all cities. (2) The average land surface temperature in urban buffer zones is generally higher than that in central urban areas, with a temperature difference of at least 0.63 °C. (3) In Huzhou and Jiaxing, the high-temperature and low-temperature zones are relatively concentrated, while in Jinhua, Quzhou, and Shaoxing, a more interspersed distribution of high-temperature and low-temperature zones is observed, reflecting a higher spatial heterogeneity. (4) Among the water body morphology indicators, the water edge density, the proportion of landscape area occupied by water patches, the largest patch index of water, and the water landscape shape index exert a relatively larger impact on cooling effects. These findings provide scientific guidance for optimizing the spatial layout of water bodies in urban buffer zones and improving urban thermal environments. Full article

Urban commercial streets are a crucial component of urban life, serving as the central hubs of commercial activity and providing vital spaces for both residents and visitors to engage in various activities. Walkability is commonly used as a key indicator of environmental quality, playing a significant role in improving residents’ health, community interaction, and environmental quality of life. Therefore, promoting the development of a high-quality walking environment in commercial districts is crucial for fostering urban economic growth and the creation of livable cities. However, existing studies predominantly focus on the impact of the built environment on walkability at the urban scale, with limited attention given to commercial streets, particularly the influence of their physical features on walking-need perceptions. In this study, we utilized Google Street-View Panorama (GSVP) images of the Tenjin commercial district and applied the Semantic Differential (SD) method to assess four walking-need perceptions of visual walkability perception, including usefulness, comfort, safety, and attractiveness. Additionally, deep-learning-based semantic segmentation was employed to extract and calculate the physical features of the Tenjin commercial district. Correlation and regression analysis were used to investigate the impact of these physical features on the four walking-need perceptions. The results showed that the different walking-need perceptions in the Tenjin commercial district are attractiveness > safety > comfort > usefulness. Furthermore, the results show that there are significant spatial distribution differences in walking-need perceptions in the Tenjin commercial district. Safety perception is more prominent on primary roads, all four walking-need perceptions in the secondary roads at a high level, and the tertiary roads have generally lower scores for all walking-need perceptions. The regression analysis indicates that walkable space and the landmark visibility index have a significant impact on usefulness, street cleanliness emerges as the most influential factor affecting safety, greenness is identified as the primary determinant of comfort, while the landmark visibility index exerts the greatest influence on attractiveness. This study expands the existing perspectives on urban street walkability by focusing on street-level analysis and proposes strategies to enhance the visual walkability perception of commercial streets. These findings aim to better meet pedestrian needs and provide valuable insights for future urban planning efforts. Full article

Education is an activity that involves great cognitive load for learning, understanding, concentrating, and other high-level cognitive tasks. The use of the electroencephalogram (EEG) and other brain imaging techniques in education has opened the scientific field of neuroeducation. Insights about the brain mechanisms involved in learning and assistance in the evaluation and optimization of education methodologies according to student brain responses is the main target of this field. Being a multidisciplinary field, neuroeducation requires expertise in various fields such as education, neuroinformatics, psychology, cognitive science, and neuroscience. The need for a comprehensive guide where various important issues are presented and examples of their application in neuroeducation research projects are given is apparent. This paper presents an overview of the current hardware and software options, discusses methodological issues, and gives examples of best practices as found in the recent literature. These were selected by applying the PRISMA statement to results returned by searching PubMed, Scopus, and Google Scholar with the keywords “EEG and neuroeducation” for projects published in the last six years (2018–2024). Apart from the basic background knowledge, two research questions regarding methodological aspects (experimental settings and hardware and software used) and the subject of the research and type of information used from the EEG signals are addressed and discussed. Full article

Diabetes is a complex global healthcare burden involving multiple organ systems with its prevalence on the rise. SGLT2 inhibitors enhance glucose excretion. The objective of our literature review was to determine the association between cutaneous adverse drug reactions (CADRs) and the use of SGLT2 inhibitors. We collected data on CADRs related to the use of SGLT2 inhibitors from all available published articles and studied their details to understand the patterns of their association. PubMed, Cochrane, Google, and Embase were searched for relevant articles. A total of 37 papers were included and studied. Most articles were case reports followed by pharmacovigilance studies, case series, and reviews. The cutaneous findings ranged from benign eruptions to severe reactions. The available literature suggests a strong link between the use of SGLT2 inhibitors and Fournier’s gangrene/necrotizing fasciitis. T2DM patients using SGLT2 inhibitors have also developed fixed drug eruptions, drug-induced pruritus, and Sweet syndrome/acute febrile neutrophilic dermatosis, among other skin lesions. We found that SGLT2 inhibitors present a risk of developing CADRs. Raising awareness among healthcare providers regarding CADRs to SGLT2 inhibitors can reduce complications, minimize hospitalizations, and improve patient care in the vulnerable population of diabetes patients. Full article

Background/Objectives: Peri-intubation hypotension is a known complication of endotracheal intubation. In the hospital setting, peri-intubation hypotension has been shown to increase hospital mortality and length of stay. The use of prophylactic vasopressors at the time of sedation induction to prevent peri-intubation hypotension has been raised. This systematic review and meta-analysis aims to review the safety and efficacy of this practice. Methods: The study was fully registered with PROSPERO on 13 October 2022, and screening for eligibility was initiated on 20 September 2024. Randomized controlled trials, along with retrospective or prospective cohort studies, were included in the search. The terms “peri-intubation hypotension”, “vasopressors”, “intubation”, and “anesthesia induced hypotension” were used to search the title/summary in PubMed, Cochrane Library, and Google Scholar databases. An assessment of bias for each study was conducted using the Newcastle-Ottawa Quality Assessment Scale. The primary outcome was the rate of hypotension peri-intubation. Any complications secondary to hypotension or vasopressors were the secondary outcome. Results: We identified 13 studies, which were all randomized controlled studies, to include in the final analysis. The risk ratio for preventing peri-intubation hypotension was 1.6 (95% CI, 1.2–2.14) with the use of prophylactic phenylephrine while giving propofol versus no prophylactic vasopressors and 1.28 (95% CI 1.03–1.60) with the use of ephedrine. Conclusions: These findings suggest that in patients undergoing intubation in the operating room with propofol, prophylactic vasopressors given with induction for intubation decrease the odds of hypotension. Full article

Introduction: Pregnant women’s experiences and concerns regarding childbirth are complex, necessitating a multidimensional and personalized approach in maternal care. This study explores the psychological and emotional factors influencing pregnant women’s decisions regarding their mode of delivery. The results will provide valuable insights for the development of educational and counseling strategies designed to support pregnant women in making informed and conscious decisions about their childbirth. Material and method: This cross-sectional study aimed to develop and validate a questionnaire exploring the psychological dimensions of childbirth. Factor analysis was employed to assess emotional perceptions, perceived medical risks, and the impact of cesarean section on pregnant women. The questionnaire was distributed online via Google Forms, using social networks like Facebook and Instagram to ensure rapid and broad accessibility. The questionnaire was available for seven months, from January to July 2023. Results: McDonald’s ω, Cronbach’s α, average inter-item correlation, and total item correlations were calculated to assess the consistency of the questionnaire items in measuring the same construct. The three-factor model emerged as the primary structure based on exploratory and confirmatory factor analyses (EFA and CFA). The first profile, centered on the psychological and emotional benefits of vaginal birth, highlights the importance of the natural birth experience for the mother’s psychological well-being. The second profile addresses concerns about medical risks and the need for interventions. The third profile focuses on perceptions and concerns related to the intelligence and adaptability of children born by cesarean section and the effects of anesthesia. Conclusions: Each profile reflects different strategies for seeking control and security amid childbirth uncertainties. These include emphasizing the psychological benefits of vaginal birth, addressing medical risks, and focusing on the impact of interventions on child development. Understanding these variables is essential for providing appropriate counseling and psychosocial support, thereby optimizing the birth experience and promoting the health of both mother and child. The integration of multi-factor and single-factor models in the questionnaire analysis serves complementary purposes, providing distinct yet interrelated insights into the instrument’s structure and validity. Full article

Accurate prediction of soybean yield is important for safeguarding food security and improving agricultural management. Recent advances have highlighted the effectiveness and ability of Machine Learning (ML) models in analyzing Remote Sensing (RS) data for this purpose. However, most of these models do not fully consider multi-source RS data for prediction, as processing these increases complexity and limits their accuracy and generalizability. In this study, we propose the Multi-Residual Attention-Based Multi-Stream 3D-ResNet-BiLSTM (MHRA-MS-3D-ResNet-BiLSTM) model, designed to integrate various RS data types, including Sentinel-1/2 imagery, Daymet climate data, and soil grid information, for improved county-level U.S. soybean yield prediction. Our model employs a multi-stream architecture to process diverse data types concurrently, capturing complex spatio-temporal features effectively. The 3D-ResNet component utilizes 3D convolutions and residual connections for pattern recognition, complemented by Bidirectional Long Short-Term Memory (BiLSTM) for enhanced long-term dependency learning by processing data arrangements in forward and backward directions. An attention mechanism further refines the model’s focus by dynamically weighting the significance of different input features for efficient yield prediction. We trained the MHRA-MS-3D-ResNet-BiLSTM model using multi-source RS datasets from 2019 and 2020 and evaluated its performance with U.S. soybean yield data for 2021 and 2022. The results demonstrated the model’s robustness and adaptability to unseen data, achieving an R² of 0.82 and a Mean Absolute Percentage Error (MAPE) of 9% in 2021, and an R² of 0.72 and MAPE of 12% in 2022. This performance surpassed some of the state-of-the-art models like 3D-ResNet-BiLSTM and MS-3D-ResNet-BiLSTM, and other traditional ML methods like Random Forest (RF), XGBoost, and LightGBM. These findings highlight the methodology’s capability to handle multiple RS data types and its role in improving yield predictions, which can be helpful for sustainable agriculture. Full article

Houttuynia cordata (H. cordata) is widely used in respiratory disease control as an important heat-clearing and detoxifying traditional Chinese medicine. It effectively clears away heat and toxins, eliminates carbuncles, and drains pus, and it is diuretic and detoxicating. The aim of this study is to review the botany, chemical composition, pharmacological effects, and quality control of H. cordata to establish a better-quality evaluation system. Google Scholar, Baidu Scholar, PubMed, ScienceDirect, Web of Science, and multiple databases, including China National Knowledge Infrastructure (CNKI) and Wanfang Data, were searched. A structural diagram of the compound was drawn using ChemDraw software. H. cordata contains volatile oils, flavonoids, and alkaloids. It has antibacterial, anti-inflammatory, antiviral, antioxidant, antitumor, and immunity-enhancing pharmacological effects. By analyzing the literature, it was predicted that Houttuynia sodium, methyl nonyl ketone, quercetin, and quercitrin could be used as the quality markers (Q-marker) of H. cordata. This provides a basis for further research into the applications of H. cordata. Full article

Effective communication between students and instructors is vital for student success. Traditionally, this communication has taken place in person within classroom settings. However, with technological advancements, online classes have become more common. The COVID-19 pandemic accelerated this shift, significantly disrupting traditional communication methods between students and instructors and transforming the educational landscape, particularly in higher education. We conducted a qualitative narrative literature review of the technological tools that emerged during the pandemic and explored how today’s instructors can effectively use them to enhance student engagement and motivation in online classrooms. The review utilized the SANRA (scale for the assessment of narrative reviews) guidelines to ensure the quality of the studies used. Twenty-two articles published within the last ten years were chosen based on their relevance to higher education and student–instructor communication. The articles were analyzed for effective and ineffective educational communication tools (e.g., Zoom or Google Classroom) utilized during the pandemic, focusing on what worked and what could be improved. The findings revealed that live video sessions were more effective than pre-recorded videos, voice-only sessions, or email/text communications in fostering student engagement and motivation. Full article

Although there are many articles dealing with web map applications, they often focus on just one or a few applications. Several articles deal with the technical solution of the applications, but relatively few are focused on the cartographic aspects of these applications. This article evaluates eight web mapping applications based on six cartographic aspects: map key, map scale, map layout, navigation elements, labels, and analytical tools. The objective is to identify differences in the presentation of geographic information and propose improvements for cartographic quality and user-friendliness. The methodology involved visual analysis at two scales. The comparison included applications such as Mapy.cz, OpenStreetMap, Google Maps, Bing Maps, HERE Maps, MapQuest, ViaMichelin, and Locus Map. The results revealed significant differences among the applications that may impact user orientation and experience. For instance, Google Maps does not display forest symbols on its default map, which can reduce clarity, whereas Mapy.cz offers the most comprehensive range of analytical tools. Advertisements in applications like MapQuest and ViaMichelin disrupt the user experience, and some applications lack essential functions, such as distance measurement. The paper identifies strengths and weaknesses in the cartographic design of these applications. Findings reveal that while each application possesses unique characteristics, they share common features. An interesting feature is the absence of cartographic symbols and labels of some elements in some applications. The study recommends the unification of cartographic principles and further user testing to optimize the layout and functionality of web mapping applications. Full article

Introduction—Aim: Adopting a lifestyle that incorporates regular physical activity confers substantial benefits to both physical and mental health and is recommended for prediabetic individuals. The aim of this study is to investigate the impact of activity tracking apps on increasing physical activity and its effect on glycemic control in people with prediabetes. Materials and Methods: This pilot study included 37 participants, 18 in the prediabetic group and 19 in the normoglycemic group matched for age and gender (mean age 53 years, 40% males). Participants used the Google Fit app for 3 months. The number of daily steps was recorded via the app, and blood and urine tests as well as body fat measurements were conducted before and following 3 months of app use. The co-primary outcome was the change in steps, and the change in HbA1c in both groups. Secondary outcomes were the change in fasting plasma glucose (FPG) (main secondary outcome), as well as lipid parameters, body mass index, visceral fat, and kidney function indices among the two groups. Results: Both groups increased the daily step count following the app intervention, without any statistically significant difference when we compared the steps change between the two groups. We found a statistically significant difference between HbA1c levels in favor of the prediabetic compared to the normoglycemic group [mean difference (MD) 0.16, 95%CI 0.04, 0.28, p-value 0.01)], following the 3-month intervention. Additionally, there was a statistically significant difference between FPG levels in favor of the prediabetic compared to the normoglycemic group (MD 9.06, 95%CI 4.16, 13.96, p-value 0.001). Conclusions: The present study suggests that the use of activity tracking apps, combined with tailored activity goals and monthly supportive phone calls, may contribute to improved glycemic control among individuals with prediabetes. Full article

Floods have catastrophic effects worldwide, particularly in monsoonal Asia. This systematic review investigates the literature from the past two decades, focusing on the use of remote sensing (RS), Geographic Information Systems (GISs), and technologies for flood disaster management in South Asia, and addresses the urgent need for effective strategies in the face of escalating flood disasters. This study emphasizes the importance of tailored GIS- and RS-based flood disaster studies inspired by diverse research, particularly in India, Pakistan, Bangladesh, Sri Lanka, Nepal, Bhutan, Afghanistan, and the Maldives. Our dataset comprises 94 research articles from Google Scholar, Scopus, and ScienceDirect. The analysis revealed an upward trend after 2014, with a peak in 2023 for publications on flood-related topics, primarily within the scope of RS and GIS, flood-risk monitoring, and flood-risk assessment. Keyword analysis using VOSviewer revealed that out of 6402, the most used keyword was “climate change”, with 360 occurrences. Bibliometric analysis shows that 1104 authors from 52 countries meet the five minimum document requirements. Indian and Pakistani researchers published the most number of papers, whereas Elsevier, Springer, and MDPI were the three largest publishers. Thematic analysis has identified several major research areas, including flood risk assessment, flood monitoring, early flood warning, RS and GIS, hydrological modeling, and urban planning. RS and GIS technologies have been shown to have transformative effects on early detection, accurate mapping, vulnerability assessment, decision support, community engagement, and cross-border collaboration. Future research directions include integrating advanced technologies, fine-tuning spatial resolution, multisensor data fusion, social–environmental integration, climate change adaptation strategies, community-centric early warning systems, policy integration, ethics and privacy protocols, and capacity-building initiatives. This systematic review provides extensive knowledge and offers valuable insights to help researchers, policymakers, practitioners, and communities address the intricate problems of flood management in the dynamic landscapes of South Asia. Full article