No abstract

Heritage buildings are considered a source of pride for countries, and their preservation is an important pursuit. Different techniques have been adopted in this regard, and many review papers have addressed them either qualitatively or quantitatively through bibliometric analysis. Nevertheless, none of these review studies conducted a general dynamic quantitative analysis of the vast amount of scientific literature about heritage buildings preservation (HBP) research domain over time. Therefore, the current study performs a bibliometric analysis of the relevant literature considering a time of two decades (2002–2022). A total of 863 peer-reviewed journal articles were extracted from the Web of Science Core Collection database. A five-step methodology was followed employing VOSviewer, CiteSpace, and Biblioshiny as the bibliometric software tools. The main findings revealed the annual publication trends and the most prominent articles. It was also found that 60% of the literature publications were published in journals, and only 2.4% corresponded to review studies. The scientific collaboration networks showed the most prolific researchers and countries. Further, the citation analysis of journals identified the most reliable information sources for academic researchers. Finally, the conceptual and intellectual knowledge structures were visualised and studied via science mapping analysis to map the research domain evolution and determine its trending patterns and promising areas for future exploration. The conducted review provides fellow researchers with a systematic summarised database to be familiarized with the HBP literature and identify potential research opportunities to conduct state-of-the-art research with the top contributors in the field (researchers, journals, and countries). In addition, policymakers can utilize the results from this research to find expert authors and academic support to facilitate forming partnerships to plan and fund relevant research and address the practical implications of preserving valuable heritage buildings.

State Highway Agencies (SHAs) and Departments of Transportation (DOTs) allocate their limited resources to thousands of competing projects in multi-year transportation programs using expert judgement for the expected construction costs and durations. Such estimates overlook influencing parameters known in the planning phase and the importance of building reliable databases to support decision making. Meanwhile, it is possible to generate meaningful predictions in early stages of project development based on historical data gathering and analysis. The present research introduces a newly developed method for conceptual cost and duration estimation for public highway projects utilizing an ensemble of machine learning (ML) models and data collected for projects completed between 2004 and 2015 (roads, bridges, and drainage projects). Unlike previous studies, the proposed method includes project parameters that affect construction durations and costs and were not studied simultaneously before. The parameters considered are facility type, project scope, highway type, length, width, location, level of technical complexity, and new parameters pertinent to payment and procurement methods. The developed method was tested using 29 and 56 randomly selected projects, and the results yielded a Mean Absolute Percentage Error (MAPE) of 7.4% and 4.5% for the duration and cost, respectively, which are lower than the estimation errors of methods reported in recent literature. Additionally, the generalization abilities were assessed by the Mann-Whitney test, and the developed method is found to successfully handle diverse projects. Thus, machine learning models can assist agencies in the review process of competing projects from a high-level management perspective to ultimately develop better management execution programs.

With the new age of technology and the release of the Internet of Things (IoT) revolution, there is a need to connect a wide range of devices with varying throughput and performance requirements. In this paper, a digital transmitter of NarrowBand Internet of Things (NB-IoT) is proposed targeting very low power and delay-insensitive IoT applications with low throughput requirements. NB-IoT is a new cellular technology introduced by 3GPP in release 13 to provide wide-area coverage for the IoT. The low-cost receivers for such devices should have very low complexity, consume low power and hence run for several years. In this paper, the implementation of the data path chain of digital uplink transmitter is presented. The standard specifications are studied carefully to determine the required design parameters for each block. And the design is synthesized in UMC 130-nm technology.

Purpose to compare between recurrence incidence after primary pterygium excision when using preoperative subconjunctival injection of Bevacizumab (Avastin) and using it as a postoperative eye drops. Methods thirty two eyes of thirty patients (two patients had bilateral pterygium) with primary pterygia were clinically examined, classified into 3 groups and operated by simple excision with bare sclera technique. Group 1 included 10 patients received Bevacizumab (Avastin) in the form of eye drops (10 mg/ml) 3 times daily for 6 days postoperative. Group 2 included 10 patients received preoperative Bevacizumab in the form of subconjunctival injection (1.25 mg/0.05ml) single dose 1 week preoperative. Group 3 included 10 patients (12 eyes) 2 patients with bilateral Pterygium didn’t receive any form of Bevacizumab. Postoperative follow up was done clinically and by serial photography at 1 week, 1 month, 3 months and 6 months searching for signs of recurrence and/or complications. Results The results showed different grades of recurrence in 18 eyes of 32.True recurrence was seen in 7 patients of 18 (1 patient in group 1, 2 in group 2 and 4 in group3).Recurrence grades in group 1and 2 who used the Bevacizumab (20%grade II, 50% grade III, and 30% grade IV). Recurrence could be predicted by 100% depending on fibrovascular tissue appearing in the surgical bed at 3 months postoperative (P value 0.038).Preoperative fleshy pterygium has high statistical significance in realation to recurrence(P value = 0.006).Patient’s sex, residence and occupation had no statistically significant value in the process of recurrence (P value > 0.05). Patients with recurrent Pterygia (in group 1&2) had statistically significant changes in the corneal K- readings at 3 months and 6 months.No significant difference in the limbal or central corneal thickness in the operated eye and the other eye (Pvalue > 0.05). Conclusion Bevacizumab (Avastin) is a well tolerated drug with multiple drug delivery methods.The eye drops give better results than the subconjunctival injection.Appearance of fibrovascular tissue in the surgical bed at 3 months predict the recurrence by 100%. Preoperative fleshy pterygia will mostly recur again whatever Bevacizumab form was used .The corneal thickness by anterior segment OCT has no role in prediction or detection of early pterygium recurrence.