The present review focuses on recent clinical trials that analyze the efficacy of intravitreal therapeutic agents for the treatment of dry age-related macular degeneration (AMD), such as neuroprotective drugs, and complement inhibitors, also called immunomodulatory or anti-inflammatory. A systematic literature search was performed to identify randomized controlled trials published prior to January 2019. Patients affected by dry AMD treated with intravitreal therapeutic agents were included. The changes in the correct visual acuity and the reduction in geographic atrophy progression were evaluated. Several new drugs have shown some promising results, including those targeting the complement cascade and agents called neuroprotective. The action potential of the two groups of drugs is to block the complement cascade model for immunomodulating agents, and prevent the degeneration and apoptosis of ganglion cells for the neuroprotectors, respectively. To the best of knowledge, and after extensive studies on the matter, there are still many investigations to be carried out on dry AMD in collaboration between researchers. They will have to identify truly effective molecules, understand the practical potential of pluripotent stem cells, and refine gene therapies. Only in-depth clinical trials will be able to allow the most appropriate and personalized treatments for each dry AMD patient.

The nature of contemporary Spatial Data Infrastructures lies in the provision of geospatial information in an on-demand fashion. Though recent applications identified the need to react to real-time information in a time-critical way. In particular, research efforts in the field of geospatial Internet of Things have identified substantial gaps in this context, ranging from a lack of standardization for event-based architectures to the meaningful handling of real-time information as ''events''. This manuscript presents work in the field of Event-driven Spatial Data Infrastructures with a particular focus on sensor networks and the devices capturing in-situ measurements. The current landscape of Spatial Data Infrastructures is outlined and used as the basis for identifying existing gaps that retain certain geospatial applications from using real-time information. We present a selection of approaches - developed in different research projects - to overcome these gaps. Being designed for specific application domains, these approaches share commonalities as well as orthogonal solutions and can build the foundation of an overall Event-driven Spatial Data Infrastructure.

With the rapid surge in technological advancements, an equal amount of investment in technology-embedded teaching has become vital to pace up with the ongoing educational needs. Distance education has evolved from the era of postal services to the use of ICT tools in current times. With the aid of globally updated content across the board, technology usage ensures all students receive equal attention without any discrimination. Importantly, web-based teaching allows all kind of students to learn at their own pace, without the fear of being judged, including professionals who can learn remotely without disturbing their job schedules. Having web-based content allows low-cost and robust implementation of the content upgradation. An improved, yet effective, version of the education using such tools is Hybrid Learning (HL). This learning mode aims to provide luxurious reinforcement to its legitimate candidates while maintaining the quality standards of various elements. Incorporated with both traditional and distance learning methods, along with exploiting social media tools for increased comfort level and peer-to-peer collaboration, HL ultimately facilitates the end user and educational setup. The structure of such a hybrid model is realized by delivering the study material via a learning management system (LMS) designed in compliance with quality standards, which is one of the fundamental tackling techniques for controlling quality constraints. In this paper, we present the recently piloted project by COMSATS University Islamabad (previously known as COMSATS Institute of Information Technology) which is driven by technology-embedded teaching model. This model is an amalgam of the traditional class room model with the aid of state-of-the-art online learning technologies. The students are enrolled as full-time students, with all the courses in traditional classroom mode, except one course offered as hybrid course. This globally adapted model helps the students to benefit from both face-to-face learning as well as gaining hands-on experience on technology-enriched education model providing flexibility of timings, learning pace, and boundaries. Our HL model is equipped with two major synchronous and asynchronous blocks. The synchronous block delivers real-time live interaction scenarios using discussion boards, thereby providing a face-to-face environment. Interactions via social network has witnessed equally surging improvement in the output performance. The asynchronous block refers to the lecture videos, slides and handouts, prepared by imminent professors, available 24/7 for students. To ensure quality output, our HL model follows the course learning outcomes (CLOs), and program learning outcomes (PLOs) as per international standards. As a proof of concept, we have deployed a mechanism at the end of each semester to verify the effectiveness of our model. This mechanism fundamentally surveys the satisfaction levels of all the students enrolled in the HL courses. With the surveys already conducted, a significant level of satisfaction has been noted. Extensive results from these surveys are presented in the paper to further validate the efficiency and robustness of our proposed HL model.

This research presents a novel approach for estimating soil organic carbon (SOC) content in agricultural soils using a photocatalytic Chemical Oxygen Demand (PeCOD) analyzer integrated with Geographic Information System (GIS) technology for spatial analysis. The PeCOD method, which relies on photochemical oxidation of organic carbon, demonstrated an uncanny correlation between its values and SOC content, making it a quick and accurate way to estimate SOC levels. Finer materials, such as clayey soils, demonstrated higher SOC content compared to coarser ones and decreased with increasing soil depth. GIS georeferencing enabled precise mapping of SOC distribution and identification of hotspot areas with high SOC content. This study highlights the significance of soil texture and depth on SOC distribution and emphasizes its significance within geological context when studying soil properties. Research results have practical ramifications for sustainable agriculture, climate change mitigation and soil health management - providing farmers and land managers with strategies that increase carbon sequestration while simultaneously improving soil health. Integrating PeCOD analyzer technology with GIS technology offers promising avenues for advanced soil carbon monitoring practices that promote climate-smart agricultural practices.

This paper uses the numerical results of surveys sent to Huelva’s (Andalusia, Spain) households to determine the degree of knowledge they have about the urban water cycle, needs, values, and attitudes regarding water in an intermediary city with low water stress. In previous research, we achieved three different households’ clusters. The first one grouped households with high knowledge of the integral water cycle and a positive attitude to smart devices at home. The second cluster described households with low knowledge of the integral water cycle and high sensitivity to price. The third one showed average knowledge and predisposition to have a closer relationship with the water company. This paper continues with this research line, applying Classification and Regression Trees (CART) to determine which hierarchy of variables/factors/ independent components obtained from the surveys are the decisive ones to predict the range of household water consumption in Huelva. Positive attitudes towards improved cleaning habits for personal or household purposes are the highest hierarchy component to predict the water consumption range. Second in the hierarchy, the variable Knowledge Global Score about the integral urban water cycle, associated with water literacy, also contributes to predicting the water consumption range. Together with the three clusters obtained previously, these results will allow us to design water demand management strategies (WDM) fit for purpose that enable Huelva’s households to use water more efficiently.

Our primary objectives were a) to determine the need for, and the availability of point-of-care testing (POCT) for infectious diseases and b) to recommend point-of-care testing strategies and spatial care paths (SCPs) that enhance public health preparedness in regional districts of Thua Thien Hue Province (TTHP), Central Vietnam, where we conducted field surveys. Medical professionals in 7 community health centers (CHCs), 7 district hospitals (DHs) and 1 provincial hospital (PH) participated. Survey questions (English and Vietnamese) determined the status of diagnostic testing capabilities for infectious diseases and other acute medical challenges in TTHP. Infectious disease testing was limited: 6 of 7 CHCs (86%) lacked infectious disease tests. One CHC (14%, 1/7) had two forms of diagnostic tests available for the detection of Malaria. All CHCs lacked adequate microbiology laboratories. District hospitals had few diagnostic tests for infectious diseases (Tuberculosis, Syphilis), blood culture (29%, 2/7), and pathogen culture (57%, 4/7) available. The PH had broader diagnostic testing capabilities but lacked preparedness for highly infectious disease threats (e.g., Ebola, MERS-CoV, SARS, Zika, and Monkeypox). All sites reported having COVID-19 rapid antigen tests; COVID-19 RT-PCR tests were limited to higher tier hospitals. We conclude that infectious disease diagnostic testing should be improved and POC tests must be supplied near patients’ homes and in primary care settings for the early detection of infected individuals and mitigation of the spread of new COVID-19 variants and other highly infectious diseases.

Cultural Tourism (CT), which enhances the economic development of a region, aids a country in reinforcing its identities, enhancing cross-cultural understanding, and preserving the heritage culture of an area. Designing a proper tourism model assists the tourists in understanding the point of interest without the help of a local guide. However, owing to the need for the analysis of different factors, designing such a model is a complex process. Therefore, this article proposes a CT model for Riyadh for peak visitor time. Primarily, the map data and cultural event dataset are processed for location, such as grouping with Kriging Interpolation-based Chameleon (KIC), tree forming, and feature extraction. After that, the event dataset’s attributes are processed with word embedding. Meanwhile, the Social Network Sites (SNS) data like reviews and news are extracted with an external Application Programming Interface (API). The review data is processed with keyword extraction and word embedding, whereas the news data is processed with score value estimation. Lastly, the data are fused corresponding to a historical site and given to the Multi-Quadratic-Long Short Term Memory (MQ-LSTM) Recommendation System (RS); also, the recommended result with the map is stored in a database. Lastly, the database security is maintained with Locality Sensitive Hashing (LSH); moreover, by attaining higher performance values, the proposed model is experimentally verified.

The Model-View-Controller (MVC) architecture, a cornerstone of modern software engineering, offers a robust framework for developing dynamic user interfaces. This paper conducts a broad analysis of MVC’s deployment across various sectors, emphasizing its critical role in technological advancement and market integration. By examining implementation strategies in web development, mobile applications, and enterprise solutions, the study illustrates how MVC enhances application manageability, promotes efficient code reuse, and facilitates parallel development. The paper explores the adoption of MVC principles within major technologies such as Java, .NET, and JavaScript frameworks, underlining its widespread acceptance. Additionally, the analysis covers the preferential use of MVC frameworks within diverse market sectors including technology enterprises, educational institutions, e-commerce, and financial services, which leverage MVC for superior data management and user experience. Emerging trends such as the shift towards the Model-View-ViewModel (MVVM) architecture and the integration of MVC with artificial intelligence and machine learning technologies are also discussed. This comprehensive review not only reaffirms MVC’s enduring relevance but also its adaptive evolution in response to emerging technological demands and market needs.