The soundscape studied has gained increasingly frequent attention across multiple disciplines, especially in tourism and leisure domain. While it has already indicated a unique soundscape provides dynamic and memorable tourism experiences, a clearly mapped perspective across different segmentations of soundscapes, both natural and acoustically created, remains missing. Therefore, a comprehensive mapping and review of soundscape studies is imperative to understand its implications for potential inbound tourism research in future. This article aimed to explore potential soundscape studies by assessing trends and developments in recent decades (2013–2023). We applied a bibliometric approach, using a PRISMA framework and under NVivo 12 Plus, VOSViewer, and Biblioshiny-R-Studio software as analytical tools. Significant yield discoveries showed that tourism soundscape research is undergoing steady growth, as evidenced by quantity of publications and citation trends. Single and multi-country international collaborations characterized by soundscape outreach research playing an influential role were highlighted. We identified multiple research themes, such as anthropogenic noise and music heritage, and pointed out how we approached this research from two perspectives: environmental/natural and manufacturing/acoustics. In our review, several keywords and predominant themes were identified, which suggested soundscape studies have recently become an increasingly popular topic in tourism research. The broad spectrum of key themes, such a tourism, tourists, sustainability, areas, and development perspectives, are evidence points of significant diversity in these topics. Most importantly, our research offers significant theoretical and conceptual implications for future direction of soundscape studies. We identified three originality main focus domains in soundscape tourism research: urban and natural environments, technological advancements, and tourists’ perceptions and behaviors.

Tomato (Solanum lycopersicon L.) is a highly valued crop in the world, particularly in Nigeria with high nutritional and economic benefits. However, its production in Iwollo, Southeast Nigeria, is constrained by unfavorable weather conditions. To address this, a study was conducted at the Teaching and Research Farm, Department of Horticultural Technology, Enugu State Polytechnic, Iwollo, Southeast Nigeria to evaluate and select the best cultivar for high tunnel production using the Rank Summation Index. Completely Randomized Design with three replications was used, and six high-yielding cultivars, namely Roma VF, BHN-1021, Supremo, Pomodro, Money maker, and Iwollo local, were evaluated. Data were collected on key agronomic characters and analyzed with Analysis of Variance (ANOVA) at a 0.05 level of probability. There were significant differences in the number of leaves per plant, plant height, number of branches per plant, days to fruit maturity, fresh fruit weight, number of harvested fresh fruits per plant, and fresh fruit yield per plant among the cultivars. These characters that showed significant differences were ranked and summed up to obtain the Rank Summation Index (RSI) score. The results revealed that the Supremo cultivar had the lowest and best score (18). This suggests Supremo as the best cultivar for high tunnel tomato production in the study area, based on its superior performance across key agronomic traits.

This paper provides a comprehensive review of SURF (speeded up robust features) feature descriptor, commonly used technique for image feature extraction. The SURF algorithm has obtained significant popularity because to its robustness, efficiency, and invariance to various image transformations. In this paper, an in-depth analysis of the underlying principles of SURF, its key components, and its use in computer vision tasks such as object recognition, image matching, and 3D reconstruction are proposed. Furthermore, we discuss recent advancements and variations of the SURF algorithm and compare it with other popular feature descriptors. Through this review, the aim is to provide a clear understanding of the SURF feature descriptor and its significance in the area of computer vision.

Objective: This study investigates the efficacy and safety of epidural infiltration with drugs and an oxygen-ozone mixture for treating cervicobrachialgia due to disc-radicular conflict or on a degenerative basis, utilizing both retrospective analysis and direct visualization techniques. Methods: A retrospective study involving 10 patients treated with epidural infiltrations of an oxygen-ozone mixture and cortisone was conducted. The procedures were performed under CT guidance to ensure precise delivery and to monitor the diffusion of the injected substances. Pain levels were assessed using the Numerical Rating Scale (NRS) and treatment efficacy was evaluated based on symptom relief and reduction in NSAID intake. Results: Significant pain reduction was observed post-treatment, with median NRS scores decreasing from 9 (baseline) to 2 (follow-up), and a significant decrease in on-demand NSAID intake. Only one minor complication of a headache was reported. The study also demonstrated the ability of ozone to diffuse through the epidural adipose tissue, potentially enhancing treatment efficacy. Conclusion: The combined use of an oxygen-ozone mixture and cortisone for epidural infiltration is an effective and safe treatment for cervicobrachialgia, offering significant pain relief and minimizing the risk associated with traditional epidural injections. This technique presents a viable non-surgical option for patients suffering from disc-radicular conflict or degenerative conditions.

This study investigates the performance assessment of methanol and water as working fluid in a solar-powered vapour absorption refrigeration system. This research clarifies the system’s performance across a spectrum of operating conditions. Furthermore, the HAP software was utilized to determine and scrutinize the cooling load, facilitating a comparative analysis between software-based results and theoretical calculations. To empirically substantiate the findings, this research investigates methanol-water as a superior refrigerant compared to traditional ammonia- water and LiBr-water systems. Through experimental analysis and its comparison with previous research, the methanol-water refrigeration system demonstrated higher cooling efficiency and better environmental compatibility. The system’s performance was evaluated under varying conditions, showing that methanol-water has a 1% higher coefficient of performance (COP) compared to ammonia-water systems, proving its superior effectiveness in solar-powered applications. This empirical model acts as a pivotal tool for understanding the dynamic relationship between methanol concentration (40%, 50%, 60%) and system performance. The results show that temperature of the evaporator (5–15 ℃), condenser (30 ℃–50 ℃), and absorber (25 ℃–50 ℃) are constant, the coefficient of performance (COP) increases with increase in generator temperature. Furthermore, increasing the evaporator temperature while keeping constant temperatures for the generator (70 ℃–100 ℃), condenser, and absorber improves the COP. The resulting data provides profound insights into optimizing refrigerant concentrations for improved efficiency.

The study focused on investigating the effects of varying levels of HA (HA₁ = 0, HA₂ = 25, HA₃ = 50, HA₄ = 75, and HA₅ = 100) on Red Dragon, Red Prince, and Red Meat varieties of red radish. This analysis aimed to unravel the relationship between different levels of HA and their impact on the growth and productivity of red radish genotypes. The findings revealed that the Red Prince genotype attained the utmost plant height of 24.00 cm, an average of 7.50 leaves per plant, a leaf area of 23.11 cm², a canopy cover of 26.76%, a leaf chlorophyll content of 54.60%, a leaf fresh weight of 41.16 g, a leaf dry weight of 8.20 g, a root length measuring 9.73 cm, a root diameter of 3.19 mm, a root fresh weight of 27.60 g, a root dry weight of 6.75 g, and a remarkable total yield of 17.93 tons per hectare. The implications of this study are poised to benefit farmers within the Dera Ismail Khan Region, specifically in the plain areas of Pakistan, by promoting the cultivation of the Red Prince variety.