Search Results (38,663)

This research examines the information management processes implemented in student dormitories and evaluates the enhancement of institutional efficiency based on student satisfaction. The study involved 150 students residing in dormitories across two universities, and data were collected through participant interviews. The findings indicate that while dormitory management is perceived as effective in some areas, there are significant opportunities for improvement in information management, communication, and service quality. Based on the student feedback, this article proposes several strategies to enhance dormitory management, including the adoption of digital platforms for better communication, regular maintenance schedules, and improved transparency in financial management. The challenges of implementing these measures, such as resource constraints and institutional resistance to change, are also discussed. These recommendations aim to improve student satisfaction and, consequently, institutional efficiency. Full article

To reduce errors in sub-synchronous oscillation (SSO) modal identification and improve the accuracy and noise resistance of the traditional Prony algorithm, this paper focuses on SSOs caused by the integration of doubly fed induction generators (DFIGs) with series compensation into the grid. A novel SSO modal identification method based on the hippopotamus optimization–variational mode decomposition (HO-VMD) and singular value decomposition–regularized total least squares–Prony (SVD-RTLS-Prony) algorithms is proposed. First, the energy ratio function is used for real-time monitoring of the system to identify oscillation signals. Then, to address the limitations of the VMD algorithm, the HO algorithm’s excellent optimization capabilities were utilized to improve the VMD algorithm, leading to preliminary denoising. Finally, the SVD-RTLS-improved Prony algorithm was employed to further suppress noise interference and extract oscillation characteristics, allowing for the accurate identification of SSO modes. The performance of the proposed method was evaluated using theoretical and practical models on the Matlab and PSCAD simulation platforms. The results indicate that the algorithms effectively perform denoising and accurately identify the characteristics of SSO signals, confirming its effectiveness, accuracy, superiority, and robustness against interference. Full article

Background: Compared with the da Vinci platform, there is limited experience with the Hugo RAS^® platform for colorectal surgery in Europe. This difference is especially notable when considering complex procedures such as total colectomy. Aim: To demonstrate the feasibility and safety of using the Hugo RAS^® (Medtronic, Minneapolis, MN, USA) platform for total colectomy. Clinical case: An 18-year-old female patient with Familial Adenomatous Polyposis (FAP) and a BMI of 19 underwent a total colectomy with ileorectal anastomosis using the Hugo RAS^® platform. The procedure lasted 253 min without complications. The postoperative period was uneventful, and she was discharged from the hospital on the third postoperative day. Conclusion: The Hugo RAS^® platform is an emerging minimally invasive robotic that can be used even for total colectomy with proper patient selection. The placement and choice of arms and trocars were crucial to obtaining a similar operative time to the standard laparoscopic approach. The certification of Hugo’s new instruments, such as energy devices and staplers, will make this platform even more competitive. Full article

In the domain of healthcare, wearable health monitoring devices have emerged as essential tools for the advancement of patient health tracking. These devices facilitate the provision of real-time medical data to clinicians, enabling early diagnosis, timely intervention, and enhanced management of individual health. This study introduces an innovative trimodal wearable health monitoring device in the form of a wristwatch. The device integrates a breath analyzer for the assessment of gaseous phase biomarkers, a sweat analyzer for the evaluation of aqueous-phase biomarkers, and an infrared sensor for the measurement of body temperature in the optical phase. Engineered on a compact 3 cm × 3 cm printed circuit board, the device has been optimized for wearability, power efficiency, and seamless integration with both wired and wireless charging and communication systems. Furthermore, custom software applications, designed for both Windows and Android platforms, have been developed to facilitate intuitive data visualization and storage on personal computers and smartphones. Empirical results from real-time chemical testing substantiate the device’s efficacy and potential as an advanced solution for wearable health monitoring. Full article

Public participation is a requirement for contemporary urban governance in China, especially in the protection planning of historic districts. In the rapid development stage, many historic districts have lost their functional positioning in cities and are gradually disappearing due to outdated facilities and services. Previous studies have pointed out that protecting historic and cultural districts requires the joint efforts of multiple stakeholders. Integrating multiple stakeholders’ interests and needs is a complex problem in related research fields and planning practices. The traditional forms of public participation, such as questionnaire surveys, interviews, and symposiums, have the problem of high time costs for collection and analysis. At the same time, the information has been translated multiple times, making it challenging to avoid misunderstandings and errors. Therefore, there is an urgent need for an alternative platform for public participation in the renewal of China’s historic districts. Taking Houzaimen Street in Jinan City as an example, this paper uses the Bayesian network to establish a spatial evaluation model of historic districts. Our aims are to translate natural semantics into the design semantics of the architectural field, accurately locate the spatial problems of the historic district, and provide targeted improvement measures. In this paper, a public feedback channel for Houzaimen Street is established to provide a reference for the renewal of the historic district and the advancement of public participation. Full article

Background: Single-step transepithelial photorefractive keratectomy (TPRK) is a modern refractive surgery technique that offers a no-touch approach for correcting myopia and astigmatism. This study aims to evaluate the short-term visual and refractive outcomes of TPRK in patients with myopia and astigmatism over a 6-month follow-up period. Methods: This retrospective cohort study included patients who underwent single-step TPRK using the Amaris 750S laser platform with SmartSurf^ACE and SmartPulse^® technologies, targeting a plano refraction. Procedures were performed with aspheric, non-wavefront-guided profiles, and outcomes were assessed postoperatively. Results: 96% of eyes achieved 20/20 or better uncorrected distance visual acuity (UDVA), with 98% reaching 20/25 or better, and 100% achieving 20/32 or better. UDVA was the same or better than preoperative corrected distance visual acuity (CDVA) in 96% of eyes, and no eyes lost two or more Snellen lines. Refractive outcomes showed strong precision, with 93% of eyes within ±1.00 D of the target. Astigmatism correction was accurate, with 100% of eyes having ≤1.00 D of astigmatism, and 80% achieving a precise astigmatism angle of error between −5° and 5°. Conclusion: Single-step TPRK with SmartSurf^ACE and SmartPulse^® technologies provides highly effective and predictable visual and refractive outcomes for myopia and astigmatism. The procedure consistently delivers precise corrections with minimal complications, making it a reliable option for refractive surgery. Full article

An online social media platform such as Instagram has become a popular communication channel that millions of people are using today. However, this media also becomes an avenue where fake accounts are used to inflate the number of followers on a targeted account. Fake accounts tend to alter the concepts of popularity and influence on the Instagram media platform and significantly impact the economy, politics, and society, which is considered cybercrime. This paper proposes a framework to classify fake and real accounts on Instagram based on a deep learning approach called the Long Short-Term Memory (LSTM) network. Experiments and comparisons with existing machine and deep learning frameworks demonstrate considerable improvement in the proposed framework. It achieved a detection accuracy of 97.42% and 94.21% on two publicly available Instagram datasets, with F-measure scores of 92.17% and 89.55%, respectively. Further experiments on the Twitter dataset reveal the effectiveness of the proposed framework by achieving an impressive accuracy rate of 99.42%. Full article

In this study, we designed three promising platforms based on metal–organic frameworks (MOFs) to develop paper-based analytical devices (PADs) for biosensing applications. PADs have become increasingly popular in field sensing in recent years due to their portability, low cost, simplicity, efficiency, fast detection capability, excellent sensitivity, and selectivity. In addition, MOFs are excellent choices for developing highly sensitive and selective sensors due their versatility for functionalizing, structural stability, and capability to adsorb and desorb specific molecules by reversible interactions. These materials also offer the possibility to modify their structure and properties, making them highly versatile and adaptable to different environments and sensing needs. In this research, we synthesized and characterized three different amino-functionalized MOFs: UiO-66-NH₂ (Zr), MIL-125-NH₂ (Ti), and MIL-101-NH₂ (Fe). These MOFs were used to fabricate PADs capable of sensitive and portable monitoring of alkaline phosphatase (ALP) enzyme activity by laser-induced fluorescence (LIF). Overall, amino-derivated MOF platforms demonstrate significant potential for integration into biosensor PADs, offering key properties that enhance their performance and applicability in analytical chemistry and diagnostics. Full article

Lipid nanoparticles (LNPs), widely used in disease diagnosis and drug delivery, face the challenge of being surrounded by biological macromolecules such as proteins upon entering the human body. These molecules compete for binding sites on the nanoparticle surfaces, forming a protein corona. The impact of different types of protein coronas on LNP delivery remains unclear. In this study, we employed a newly developed, highly sensitive LNP labeling platform and analyzed the endocytosis of HeLa cells under different nutritional conditions using proteomics to address this critical issue. Our research found that under conditions of complete medium and amino acid starvation, most DNA-FITC vesicles in HeLa cells were located in the perinuclear region 4 h after transfection. In contrast, under serum starvation conditions, only a small portion of DNA-FITC vesicles were in the perinuclear region. On the other hand, through proteomics, we discovered that cells that were enriched in amino acids and complete medium contained more proteins, whereas those under serum starvation had relatively fewer enriched proteins. Through KEGG pathway enrichment analysis, we identified the phagosome and endocytosis pathways as particularly important. Lastly, differential analysis of proteins in these pathways revealed that proteins such as F-actin, Coronin, vATPase, TUBA, TUBB, MHCII, and TSP may have significant impacts on cellular endocytosis. Our research findings indicate that it is necessary to regulate cellular endocytosis based on different protein coronas to achieve optimal cytoplasmic release. Full article

As a major coal-producing area, the Shanxi section of the Yellow River Basin has been significantly affected by coal mining activities in the local ecological environment. Therefore, an in-depth study of the ecological evolution in this region holds great scientific significance and practical value. In this study, the Shanxi section of the Yellow River Basin, including its planned coal mining area, was selected as the research subject. An improved remotely sensed ecological index model (NRSEI) integrating the remotely sensed ecological index (RSEI) and net primary productivity (NPP) of vegetation was constructed utilizing the Google Earth Engine platform. The NRSEI time series data from 2003 to 2022 were calculated, and the Sen + Mann–Kendall analysis method was employed to comprehensively assess the ecological environment quality and its evolutionary trends in the study area. The findings in this paper indicate the following data: (1) The contribution of the first principal component of the NRSEI model is more than 70%, and the average correlation coefficient is higher than 0.79. The model effectively integrates the information of multiple ecological indicators and enhances the applicability of regional ecological environment evaluation. (2) Between 2003 and 2022, the ecological environment quality in the Shanxi section of the Yellow River Basin showed an overall upward trend, with the average NRSEI value experiencing phases of fluctuation, increase, decline, and stabilization. The NRSEI values in non-coal mining areas consistently remained higher than those in coal mining areas. (3) Over 60% of the areas have improved ecological conditions, especially in coal mining areas. (4) The impact of coal mining on the ecological environment is significant within a 6 km radius, while the effects gradually diminish in the 6 to 10 km range. This study not only offers a reliable methodology for evaluating ecological environment quality on a large scale and over a long time series but also holds significant guiding value for the ecological restoration and sustainable development of the Shanxi section of the Yellow River Basin and its coal mining area. Full article

The COVID-19 pandemic disrupted economic processes and various facets of daily life, including education, necessitating adjustments to help society adapt to the temporary status quo, with Romanian educational institutions being profoundly affected, and a full transition to online learning was mandated by central authorities in March 2020. The paper’s scope is to assess the sustainability of e-learning in Romanian higher education in the aftermath of the COVID-19 outbreak. The study was conducted on bachelor students from three Romanian universities through an online questionnaire with a sample size of 505 valid responses. This study aims to investigate the relationships between information quality (IQ), system quality (SQ), service quality (SEQ), and quality of life (QL) within an integrated model, based on the variables of the technology acceptance model (TAM) and performance models of information systems (IS). Specifically, the research explores how these factors, along with the mediating roles of perceived usefulness (PU) and perceived ease of use (PEOU), influence students’ behavioral intention to adopt e-learning systems (BISE) and actual use of them (EUOES) as a sustainable solution for post-pandemic COVID-19 education. Partial least squares structural equation modeling (PLS–SEM) was the selected method for data analysis performed with SmartPLS 4.0 software. The research results demonstrated that PU and PEOU showed a positive correlation relationship and were significantly influenced by IQ, SQ, and QL in the educational setting. The study also revealed that PEOU and PU exerted a positive influence on students’ behavioral intention to adopt e-learning systems (BISE) sustainably and on their actual use (EUOES). This study benefits universities and higher education institutions by providing insights into enhancing e-learning platforms and integrating technology effectively, as well as by supporting the formulation of sustainable online learning strategies beyond the COVID-19 pandemic. Full article

Background: Brain biopsy is required for the accurate specification and further diagnosis of intracranial findings. The conventional stereotactic frames are used clinically for biopsies and offer the highest possible precision. Unfortunately, they come with some insurmountable technical and logistical limitations. The aim of the present work is to determine the clinical precision in the needle biopsy of the human brain using a new patient-specific stereotactic navigation device based on 3D printing. Methods: MRI data sets of human cadaver heads were used to plan 32 intracranial virtual biopsy targets located in different brain regions. Based on these data, 16 individualized stereotactic frames were 3D-printed. After the intraoperative application of the stereotactic device to the cadaver’s head, the actual needle position was verified by postoperative CT. Results: Thirty-two brain areas were successfully biopsied. The target point accuracy was 1.05 ± 0.63 mm, which represents the difference between the planned and real target points. The largest target point deviation was in the coronal plane at 0.60 mm; the smallest was in the transverse plane (0.45 mm). Conclusions: Three-dimensional-printed, personalized stereotactic frames or platforms are an alternative to the commonly used frame-based and frameless stereotactic systems. They are particularly advantageous in terms of accuracy, reduced medical imaging, and significantly simplified intraoperative handling. Full article

This study aimed to evaluate the influence of the guidance level on the accuracy of immediately placed implants. Methods: Eighteen identical maxillary models (randomly split into three groups (n = 6): fully guided (FG), pilot-guided (PG), and freehand (FH)) were used to place 72 implants (n = 24). After placement, the mean global, angular, mesial–distal, buccal–palatal, and vertical deviation at the platform and apex of the placed implants, relative to the preoperatively planned positions, was calculated. Results: Significant differences in global and mesial–distal deviation were found between implants in the FG group and implants in the PG and FH groups. Significant differences were also found between the implants in the FG and FH groups as well as the implants in the PG and FH groups in terms of angular and mesial–distal apex deviation. Finally, significant differences were found between the implants in the FG and PG groups in terms of buccal–palatal platform deviation. Conclusions: The results of this in vitro study show that immediate implants placed using fully guided surgical guides have significantly less deviation, and are therefore more accurate, than implants placed freehand or using pilot guides, but this should be further validated in a clinical trial. Full article

This study explores the critical challenges the livestock sector faces, particularly those related to biosecurity, animal welfare, and antibiotic use restrictions. It highlights the need to implement advanced information and communication technologies to enhance operational sustainability and decision-making. We introduce the Biorisk^® External platform, a cloud-based visit control system designed to optimize biosecurity management by accurately tracking visitor activity through QR codes and GPS geolocation. During a 6-month study period from July to December 2023, we analyzed visits to 142 different swine production sites and 30 vehicle movement patterns. The analysis revealed trends in visitation patterns and compliance with biosecurity SOPs. The software categorized visits as authorized (A), not authorized with access (NAWA), and not authorized without access (NAWOA), providing a framework to assess biosecurity risks. Additionally, network analysis identified interconnected farms, which were classified as ‘superspreaders’, highlighting their considerable risk of disease transmission. This study advocates for the integration of digital systems in livestock operations to improve biosecurity measures, facilitate real-time data input, and support informed decision-making. By enhancing biosecurity protocols through technology, the livestock industry can better safeguard animal health, increase operational efficiency, and reduce potential economic losses associated with disease outbreaks. Full article

While the wind turbine industry has been primarily dominated by horizontal-axis wind turbines, the forefront of knowledge of these turbines has revealed significant challenges in various aspects, including manufacturing, structural design, cost, and maintenance. On the other hand, the advantages associated with Darrieus vertical-axis wind turbines (VAWTs) demonstrate significant potential that can address the existing challenges of the wind turbine industry. Current work aims to investigate the practicality of this potential for the wind energy sector. To this end, the benefits of employing Darrieus turbines for domestic and industrial applications, isolated operation, and on/offshore windfarm applications have been explored. It is apparent that Darrieus VAWTs are better suited to a wide range of environments, whether they are deployed in isolation or integrated systems, and whether they are utilized on a small or large scale. Darrieus VAWTs are adaptable to urban unsteady variable wind, are less expensive on large scales, provide higher power density at the windfarm level, and provide stability for offshore platforms. Nevertheless, challenges remain in fully harnessing VAWT potential rooted in their complex aerodynamics. This serves as a primary challenge for VAWTs to address the challenges of the wind turbine industry in line with the 2050 roadmap. Full article