Search Results (10,332)

Objectives: Photochemical systems are frequently recommended as an adjuvant treatment option in peri-implantitis therapy. The aim of the present study was to evaluate the efficacy of these treatment options, as well as a novel curcumin-based option, in a biofilm model on implants. Methods: Eighty dental implants were inoculated with an artificial biofilm of periodontal pathogens and placed in peri-implant pocket models. The following groups were analyzed: I, photodynamic therapy (PDT); II, PDT dye; III, curcumin/DMSO + laser; IV, curcumin/DMSO only; V, dimethyl sulfoxide (DMSO) only; VI, photothermal therapy (PTT); VII, PTT dye; VIII, control. After treatment, remaining bacterial loads were assessed microbiologically using quantitative real-time polymerase chain reaction analysis. Results: The PDT, PTT, and DMSO treatment methods were associated with statistically significant (p < 0.05) improvements in germ reduction in comparison with the other methods and the untreated control group. The mean percentage reductions were as follows: I (PDT) 93.9%, II (PDT dye) 62.9%, III (curcumin/DMSO + laser) 74.8%, IV (curcumin/DMSO only) 67.9%, V (DMSO) 89.4%, VI (PTT) 86.8%, and VII (PTT dye) 66.3%. Conclusions: The commercially available PDT and PTT adjuvant treatment systems were associated with the largest statistically significant reduction in periopathogenic bacteria on implant surfaces. However, activation with laser light at a suitable wavelength is necessary to achieve the bactericidal effects. The use of curcumin as a photosensitizer for 445 nm laser irradiation did not lead to any improvement in antibacterial efficacy in comparison with rinsing with DMSO solution alone. Full article

This was a retrospective study of the profile and initial treatments of adults diagnosed with early-stage (ES) non-small cell lung cancer (NSCLC) during January 2018–December 2021 at 16 leading hospital institutions in Austria, excluding patients enrolled in clinical trials. In total, 319 patients were enrolled at a planned ~1:1:1 ratio across StI:II:III. Most tested biomarkers were programmed death ligand 1 (PD-L1; 58% expressing), Kirsten rat sarcoma virus (KRAS; 22% positive), and epidermal growth factor receptor (EGFR; 18% positive). Of 115/98/106 StI/II/III patients, 82%/85%/36% underwent surgery, followed by systemic therapy in 9%/45%/47% of those [mostly chemotherapy (ChT)]. Unresected treated StIII patients received ChT + radiotherapy [43%; followed by immune checkpoint inhibitors (ICIs) in 39% of those], ICI ± ChT (35%), and ChT-alone/radiotherapy-alone (22%). Treatment was initiated a median (interquartile range) of 24 (7–39) days after histological confirmation, and 55 (38–81) days after first medical visit. Based on exploratory analyses of all patients newly diagnosed with any stage NSCLC during 2018–2021 at 14 of the sites (N = 7846), 22%/10%/25%/43% had StI/II/III/IV. The total number was not significantly different between pre-COVID-19 (2018–2019) and study-specific COVID-19 (2020–2021) periods, while StI proportion increased (21% vs. 23%; p = 0.012). Small differences were noted in treatments. In conclusion, treatments were aligned with guideline recommendations at a time which preceded the era of ICIs and targeted therapies in the (neo)adjuvant setting. Full article

Despite the considerable advances that industrial manufacturing has undergone as a result of digitalization, the real-time monitoring of assembly processes continues to present a significant technical challenge. This article presents a solution to this problem by integrating digital twin technology with radio frequency identification (RFID) in order to improve the monitoring and optimization of assembly processes. The objective of this research is to develop a methodology that ensures synchronized data exchange between physical components and their digital counterparts using RFID for improved visibility and accuracy. The methodology entails the configuration of radio frequency identification systems to track the positions of products on conveyor belts, thereby facilitating real-time monitoring and the prompt detection of any deviations. This integration enhances remote monitoring capabilities and markedly optimizes assembly processes in comparison to traditional methods. The research findings suggest that this approach offers real-time data and monitoring capabilities, which can contribute to improved operational efficiency. This study presents an introduction to digital twins and RFID technology, a review of related research, a detailed methodology, an implementation plan, results and analysis, a discussion of the findings, and conclusions with future recommendations. This article presents a comprehensive discussion of the configuration of an RFID-based digital twin for an assembly line, highlighting the benefits and challenges of integrating these technologies into industrial processes. Full article

Educational institutions in Poland often struggle with various problems, such as the lack of an adequate number of rooms or the poor technical condition of buildings. This is due to many factors, such as the age of the buildings, demographic trends, migration, political, social, historical, and cultural conditions and, above all, financial conditions. In order to address these problems, the Krakow University of Technology undertook the implementation of the “Green Classroom” scientific project as part of the “Science for Society” programme of the Ministry of Education and Science. The Green Classroom is a mobile, free-standing educational facility consisting of a geometric arrangement of four basic modules. Integrating this type of facility into existing infrastructure, especially in urban areas, requires the availability of suitable land, taking into account hydro-meteorological and wastewater conditions. This study presents a method using geographic information system (GIS) tools to select school areas where it is possible to locate “Green Classrooms”, taking into account sustainable land retention. Based on typical rainfall for the city of Krakow, stormwater runoff was calculated taking into account the adopted “Green Classroom” module. An additional sealed surface (a “Green Classroom” system) increases the rainwater runoff by approximately 1 m³. In order to balance the rainwater runoff, it is recommended to install a rainwater collection tank with a capacity of 1 m³ next to the “Green Classroom” module. In order to relieve the storm sewer system, especially in highly sealed urban areas, it is recommended to use aboveground or underground stormwater tanks. The size of the tanks should depend on the impervious surfaces and their number on the site conditions. Nomograms for the city of Krakow have been developed to estimate the size of tanks. Full article

Antibiotic, analgesic sedative, and antiseizure medications are among the most commonly used medications in preterm/sick neonates, who are at high risk of nosocomial infections, central nervous system complications, and are exposed to numerous painful/stressful procedures. These severe and potentially life-threatening complications may have serious short- and long-term consequences and should be prevented and/or promptly treated. The reported variability in the medications used in neonates indicates the lack of adequate neonatal studies regarding their effectiveness and safety. Important obstacles contributing to inadequate studies in preterm/sick infants include difficulties in obtaining parental consent, physicians’ unwillingness to recruit preterm infants, the off-label use of many medications in neonates, and other scientific and ethical concerns. This review is an update on the use of antimicrobials (antifungals), analgesics (sedatives), and antiseizure medications in neonates, focusing on current evidence or knowledge gaps regarding their pharmacokinetics, indications, safety, dosage, and evidence-based guidelines for their optimal use in neonates. We also address the effects of early antibiotic use on the intestinal microbiome and its association with long-term immune-related diseases, obesity, and neurodevelopment (ND). Recommendations for empirical treatment and the emergence of pathogen resistance to antimicrobials and antifungals are also presented. Finally, future perspectives on the prevention, modification, or reversal of antibiotic resistance are discussed. Full article

The most recent (eighth) edition of the American Joint Committee on Cancer (AJCC) staging system divides invasive cutaneous melanoma into two broad groups: “low-risk” (stage IA–IIA) and “high-risk” (stage IIB–IV). While surveillance imaging for high-risk melanoma patients makes intuitive sense, supporting data are limited in that they are mostly respective and used varying methods, schedules, and endpoints. As a result, there is a lack of uniformity across different dermatologic and oncologic organizations regarding recommendations for follow-up, especially regarding imaging. That said, the bulk of retrospective and prospective data support imaging follow-up for high-risk patients. Currently, it seems that either positron emission tomography (PET) or whole-body computerized tomography (CT) are reasonable options for follow-up, with brain magnetic resonance imaging (MRI) preferred for the detection of brain metastases in patients who can undergo it. The current era of effective systemic therapies (ESTs), which can improve disease-free survival (DFS) and overall survival (OS) beyond lead-time bias, has emphasized the role of imaging in detecting various patterns of EST response and treatment relapse, as well as the importance of radiologic tumor burden. Full article

A complex AI system must be worked offline because the training and execution phases are processed separately. This process often requires different computer resources due to the high model requirements. A limitation of this approach is the convoluted training process that needs to be repeated to obtain models with new data continuously incorporated into the knowledge base. Although the environment may be not static, it is crucial to dynamically train models by integrating new information during execution. In this article, artificial neural networks (ANNs) are developed to predict risk levels in traffic accidents with relatively simpler configurations than a deep learning (DL) model, which is more computationally intensive. The objective is to demonstrate that efficient, fast, and comparable results can be obtained using simple architectures such as that offered by the Radial Basis Function neural network (RBFNN). This work led to the generation of a driving dataset, which was subsequently validated for testing ANN models. The driving dataset simulated the dynamic approach by adding new data to the training on-the-fly, given the constant changes in the drivers’ data, vehicle information, environmental conditions, and traffic accidents. This study compares the processing time and performance of a Convolutional Neural Network (CNN), Random Forest (RF), Radial Basis Function (RBF), and Multilayer Perceptron (MLP), using evaluation metrics of accuracy, Specificity, and Sensitivity-recall to recommend an appropriate, simple, and fast ANN architecture that can be implemented in a secure alert traffic system that uses encrypted data. Full article

The association between high-density lipoprotein cholesterol (HDL-C) and cardiovascular disease (CVD) is controversial. HDL-C is one content type of high-density lipoprotein (HDL). HDL consists of diverse proteins and lipids and can be classified into different subclasses based on size, shape, charge, and density, and can change dynamically in disease states. Therefore, HDL-C levels alone cannot represent HDLs’ cardioprotective role. In this review, we summarized the methods for separating HDL subclasses, the studies on the association between HDL subclasses and cardiovascular risk (CVR), and the impact of lipid-modifying medications and nonpharmacological approaches (exercise training, dietary omega fatty acids, and low-density lipoprotein apheresis) on HDL subclasses. As HDL is a natural nanoplatform, recombinant HDLs (rHDLs) have been used as a delivery system in vivo by loading small interfering RNA, drugs, contrast agents, etc. Therefore, we further reviewed the HDL subclasses used in rHDLs and their advantages and disadvantages. This review would provide recommendations and guidance for future studies on HDL subclasses’ cardioprotective roles. Full article

This study presents a production and development process of an IoT-based weather monitoring and emergency notification system for confined-space environments. The system comprises four working hardware stations cooperating through a data transfer command, an open-source data management system, and a cloud database. The system was preliminarily tested in a relevant confined-space area known as the Muang-On Cave, located in Chiang Mai, Thailand. The system was used to monitor weather conditions and detect emergency signals at all stations for seventeen days during the wet to dry transitional season. The data, including temperature, relative humidity, carbon dioxide, total volatile organic compounds, and emergency codes, were displayed on the web server every 80 to 110 s. However, the extremely humid conditions in the cave actively affected the erroneous readings of gas-detecting sensors that should be accounted for further improvement. Since the system was devised from low-cost electrical and non-electrical materials and open-source software, the total capital cost of the system production indicates a relatively low cost estimated at nearly USD 200. Testing the studied system in other natural caves elsewhere is highly recommended for system stability assessment. Full article

This study explored smallholder dairy production and cattle welfare in Eastern Uganda using mixed methods evaluation approaches. A focus group of 17 members performed a SWOT analysis of local farms, identifying strengths like available land, forage, and community support but weaknesses including disease, parasites, and lack of technologies. Field assessments of 12 farms using a modified Welfare Quality^® protocol revealed 25% had inadequate body condition; 33% lacked adequate water access; 50% provided comfortable housing; and 42% had animals with health issues. Six recommendations were formulated to address needs via training, veterinary services access, data systems, finance, milk market development, and pasture improvements. Though struggling with resource constraints and animal health, eastern Uganda’s favorable climate and community present opportunities to enhance productivity and welfare with targeted actions like skills development and access to technologies. However, external inputs require alignment with smallholder realities. Findings detail current conditions while highlighting local perspectives to guide appropriate innovations sensitive to economic limitations and values-based motives. Collaborating with producers to incrementally elevate management can improve livelihoods and animal well-being. Full article

The productivity of forests in sub-Saharan Africa is often summarized into large compartments or site classes. However, the classification of forest productivity levels based on the original site index model in Tanzania and the techniques applied to generate the model did not include the micro-toposequence variations within compartments. This may create false expectations of wood supply and hinder the estimation of sustainable harvesting processes. This study analyzed variations in forest productivity and the site index in P. patula stands in two forest plantations of Tanzania to assess the applicability and generality of the present site classification system. We used dominant height as a proxy for forest productivity in 48 plots at the Sao Hill forest plantation (SHFP) and 24 plots at the Shume forest plantation (SFP). We stratified the sampling plots in each site class along the soil catena and recorded the elevation, slope, and slope positions (summit, mid, and lower). Our results showed that the site classes did not generally match the previously assigned site classes and the productivity of a given site class varied between the two plantations. We found a consistently higher productivity than that implied by the original site index in SFP, while in SHFP, the productivity was both higher and lower than estimated in different compartments. Both elevations and slope significantly contributed to predicting the productivity variations within site classes. Overall, the results indicate that physiographic factors affect variations in forest productivity within the assigned site classes. We recommend a more comprehensive site productivity assessment that takes into account physiographic variations and hence provides more accurate information for sustainable forest plantation management in Tanzania and in the region at large. Full article

Artificial intelligence (AI) advances and the rapid adoption of generative AI tools, like ChatGPT, present new opportunities and challenges for higher education. While substantial literature discusses AI in higher education, there is a lack of a systems approach that captures a holistic view of the structure and dynamics of the AI transformation of higher education institutions (HEIs). To fill this gap, this article develops a causal loop diagram (CLD) to map the causal feedback mechanisms of AI transformation in a typical HEI. We identify important variables and their relationships and map multiple reinforcing and balancing feedback loops accounting for the forces that drive the AI transformation and its impact on value creation in a typical HEI. The model shows how, motivated by AI technology advances, the HEI can invest in AI to improve student learning, research, and administration while dealing with academic integrity problems and adapting to job market changes by emphasizing AI-complementary student skills. We explore model insights, scenarios, and policy interventions and recommend that HEI leaders become systems thinkers to manage the complexity of the AI transformation and benefit from the AI feedback loops while avoiding policy traps that may lead to decline. We also discuss the notion of HEIs influencing the direction of AI and directions for future research on AI transformation and the sustainability of HEIs. Full article

The focus on maintenance actions in the early design phases has been a trend in recent years. The main sources of information during the design of the maintainability process include operator reports, maintainer experience, failure history, and manufacturer recommendations. During this process, an important aspect is related to the configuration of maintenance tasks and interventions, such as their main phases, activities, and durations. The allocation or estimation of maintainability involves identifying and/or estimating the mean time to repair (MTTR) for each component or system. The time of the maintenance tasks or the repair time are fundamental for companies, as the availability of equipment directly depends on this parameter. In this study, a new method for evaluating maintainability during the design phases is proposed. The method is based on the integration of the maintenance task analysis (MTA) principles and the UNE 151001 maintainability evaluation standard. A data structure is proposed that serves the application of the UNE151001 procedures, obtaining a data-based maintainability evaluation. As a validation procedure, an application of the proposed approach is presented using two overhead cranes. Comparisons and recommendations are made regarding the maintainability of both pieces of equipment. Finally, some managerial and engineering insights are presented. Full article

To promote efficient construction waste recycling and reuse, a novel waste management approach based on blockchain technology was introduced to the industry. However, adopting blockchain platforms in construction waste recycling and reuse may impact the behavioral strategies of stakeholders and impede the prediction of the specific impacts of stakeholders’ decisions. Accordingly, this study addresses two primary questions: (1) What are the collaborative framework and the behavioral evolution trends of multiple stakeholders within the context of blockchain? (2) How can the behavioral strategies of multiple stakeholders be systematically coordinated to achieve efficient construction waste recycling and reuse driven by blockchain? To answer these questions, a tripartite game model combined with system dynamics was constructed. In this model, we aimed to elucidate the internal organizational framework, analyze the dynamic evolution process, and assess the influence of decisions made by multiple stakeholders at the individual level. It also offers corresponding policy recommendations for efficient construction waste recycling and reuse driven by blockchain at the system level. This study offers three innovations. First, it considers the decision-making of multiple stakeholders as an interdependent and coevolutionary process to overcome the defects of analyzing only one type of participant. Second, in contrast to the static analysis method, it employs a dynamic system approach to deeply analyze the evolving structures of blockchain-based projects. Third, it provides a theoretical framework for the practical implementation of blockchain-driven platforms in managing construction waste recycling and reuse, thus fostering effective policy development and management practices. This framework aims to promote sustainable development in construction waste recycling and reuse projects in China as well as globally. Full article

Background: Recommendations state all people with ovarian cancers (OCs) receive genetic counseling, but testing uptake is only between 15 and 31%. Those with a prior diagnosis of OC who have not received genetic testing represent a missed opportunity for life-saving genetic risk information. The Genetic Risk Analysis in ovarian CancEr (GRACE) study aimed to evaluate the feasibility of the retrospective identification (“Traceback”) of individuals diagnosed with OC. Methods: This nonrandomized intervention study within two integrated health care systems identified participants with a history of OC between 1998 and 2020 who did not have genetic testing or testing limited to BRCA1/2. Participants received clinical genomic sequencing via a custom 60 gene panel. This study measured the feasibility of the Traceback methodology in OC survivors. Results: The initial cohort included 929 individuals, of which 57% had no prior genetic testing. Of the 302 eligible for recruitment, 88 consented to participate. We were able to outreach 97% of the eligible population using contact information from medical records. The stage at diagnosis was the only factor associated with consent. Of the 78 who returned their saliva sample, 21% had pathogenic/likely pathogenic variants, and 79% had negative results. Conclusion: The GRACE study resulted in a 29% uptake of genetic testing in OC survivors. The time since diagnosis did not have an impact on consent or ability to contact. GRACE can inform the implementation of future Traceback programs, providing guidance on how to prevent and mitigate the burden of OC and other hereditary cancers. Full article