Search Results (10)

Advanced driving assistance systems (ADASs) provide rich data on vehicles and their surroundings, enabling early detection and warning of driving risks. This study proposes a short-term risk prediction method based on in-vehicle perception data, aiming to support real-time risk identification in ADAS environments. A variable sliding window approach is employed to determine the optimal prediction window lead length and duration. The method incorporates Monte Carlo simulation for threshold calibration, Boruta-based feature selection, and multiple machine learning models, including the light gradient-boosting machine (LGBM), with performance interpretation via SHAP analysis. Validation is conducted using data from 90 real-world driving sessions. Results show that the optimal prediction lead time and window length are 1.6 s and 1.2 s, respectively, with LGBM achieving the best predictive performance. Risk prediction effectiveness is enhanced when integrating information across the human–vehicle–road environment system. Key features influencing prediction include vehicle speed, accelerator operation, braking deceleration, and the reciprocal of time to collision (TTCi). The proposed approach provides an effective solution for short-term risk prediction and offers algorithmic support for future ADAS applications. Full article

The global expansion of the tourism industry has intensified competition between destinations, necessitating a deeper understanding of their competitive positioning. The aim of this study is to develop a research model that analyzes the competitive environment of a specific tourism destination and its relative position within the market, using Georgia as a case study. The competitive environment is analyzed based on the preferred travel destinations of the leading tourism-generating countries (or segments) of the destination under study. This approach is grounded in the expectation that a destination’s competitiveness in the global tourism market may differ from its position within a market composed of destinations favored by its primary visitor segments. To achieve this, the study applies the segment-centric geo-competitive environment of a tourism destination (SGE-TD) framework, which consists of three sequential analytical steps: (1) identifying competing destinations that define the study destination’s competitive environment, (2) outlining the key characteristics of this environment, and (3) identifying leading destinations and close competitors. This research has both methodological and practical implications. Methodologically, the paper introduces a structured and target-oriented framework incorporating an innovative SGE-TD approach, which defines a competitive environment based on top popular travel destinations among the top tourism generators of the study destination, along with corresponding analytical tools, which can be applied to similar studies. Full article

Eastern Africa is home to strikingly beautiful landscapes, unique wildlife and exotic cultural heritage that create outstanding tourism appeal. Unfortunately, these attractive features do not always translate to high tourism revenues. This paper focuses on analyzing the relationships between tourism performance indicators—arrivals, revenues and the revenue-based revealed comparative advantage (RCA)—and compare them to the components of destination facilities and endowments measured by the Tourism and Travel Competitiveness Index (TTCI). The analysis concentrates on Ethiopia, Kenya, Uganda and Tanzania, using secondary data from 2005 to 2017. The methodology applies correlation analysis and panel regression. As the results show, the TTCI and RCA are negatively correlated, but the components of the TTCI have different relationships to the RCA. Natural heritage positively influences the RCA, while cultural resources do not. The higher RCA values are also enhanced by better tourism services and better ground travel infrastructure. Similar analyses have been performed for Europe and some Asian countries, but not for Eastern Africa. The novelty of the present research is the fact that natural heritage resources can contribute considerably to tourism revenues, while cultural resources are not utilized to their full potential in terms of tourism success. Full article

This study explores an important issue in tourism, namely, the competitiveness of tourism. In the present paper, we aim at analyzing the relationship between tourism and national prosperity. The term competitiveness is a research topic intensively addressed in various fields, and it can answer current research questions related to a constantly changing tourism industry. Thus, the possibility of knowing how competitive this particularly important sector is for the five emerging countries considered in the study, namely, the Czech Republic, Hungary, Poland, Romania, and Slovakia, allows public authorities and entrepreneurs to estimate the revenues that can generate the field of hospitality. Also, based on these results, a series of national strategies specific to the tourism industry can be founded to lead to the increase of its competitiveness. We used cross-country multiple regression analysis to determine variables that are particularly important for the competitiveness of the hospitality industry, a fact for which the study has a theoretical and practical applicability. The study offers the possibility to anticipate the values of this index (TTCI), thus enabling government and industry bodies to take the necessary steps to increase specific competitiveness in the international market. Full article

The competitiveness of tourist destinations presents, from the perspective of sustainability, certain benefits in terms of local and regional development: the involvement of local authorities (city, local and county councils, population) in the conservation of tourist resources, the involvement of tourism agencies in the promotion of rural areas, the creation of brands for each tourist destination/region and the protection of cultural-historical heritage from degradation. Competitiveness, as a segment of sustainability, integrated in Romanian local communities, is necessary in order to offer tourists an unmistakable experience of the natural and anthropogenic tourism potential of destinations, to raise the population’s awareness, to preserve traditions, customs and habits and to practice tourism based on sustainability, awareness and without any pollution of terrestrial and aquatic ecosystems. This study aims to highlight the image of Romania’s tourism competitiveness, which could support the tourism economy in the long term, by analysing the Global Tourism and Travel Competitiveness Index (TTCI) in Romania, compared to two other neighbouring countries, Bulgaria and Hungary. The Global Competitiveness Index provides an integrative picture of the main sub-indices that interfere in the formation of a country’s competitiveness, with insights on the 12 pillars that intervene in the sustainable development of tourist destinations worldwide. Full article

Eastern Africa is a relatively dry area, with a considerable pastoralist population, which is among the poorest segments of society. Pastoralism is a form of subsistence lifestyle, and while pastoralists produce a large proportion of the region’s livestock products, they are not covered well by statistical recording. Pastoralists are experts in keeping livestock in arid rangelands, but they often suffer from land alienation, environmental degradation, and conflict with other land use intentions. The semiarid rangelands in Eastern Africa are home to spectacular savanna wildlife populations, attracting substantial conservation and tourism revenues. Estimations indicate that pastoralism generates significant economic values in the national income due to livestock production and maintenance of tourism attractions. To assess this contribution, the concept of total economic valuation (TEV) is applied. The main aim of the paper is to analyze the contribution of pastoralism to the tourism-related GDP of Ethiopia, Kenya, Uganda, and Tanzania, where considerable numbers of pastoralists live. Because of the lack of statistical data on pastoralism, the second objective is to construct a database of indicators that measure the extent of pastoralism for these countries for 2004, 2014, and 2018. The methodology includes the construction of the above database using secondary sources, and then to apply correlation and regression analysis on this database and the economic and tourism performance data series of the studied four countries. The results of the analysis showed that the extent of pastoralism is positively related to GDP and to value added by tourism and agriculture, and international tourism receipts are positively related to pastoralism’s contribution to GDP. The tourism competitiveness index (TTCI) was found to be negatively related to the size of the pastoralism sector. The policy implications of our findings are that pastoralist societies are increasingly important not only for their marketed economic output, but for their services provided to tourism and to the environment; therefore, instead of neglecting them, they should be more in the focus of development. Full article

Humanized Virus Suppressing Factor-variant 13 (hzVSF-v13), a monoclonal IgG4 antibody against vimentin, was investigated in moderate to severe COVID-19 pneumonia through a Phase II study. Patients were randomized to two different IV doses of the test drug or saline with standard of care. Overall, 64 patients were recruited, and 62 entered the efficacy assessment in the full analysis set. Primary endpoint: The clinical failure rate at day 28 was 15.8% for placebo, 9.1% for low-dose hzVSF-v13 and 9.5% for high-dose hzVSF-v13 (not significant). A trend toward better efficacy was shown in several secondary endpoints, with statistical significance between low-dose hzVSF-v13 and placebo in terms of the rate of improved patients on the ordinal scale for clinical improvement (OSCI): 90.0% vs. 52.63% (p = 0.0116). In the severe stratum, the results of low-dose hzVSF-v13 vs. placebo were 90.0% and 22.2% for OSCI (p = 0.0092), 9 days and 14 days for time to discontinuation of oxygen therapy (p = 0.0308), 10 days and 15 days for both time to clinical improvement (TTCI) and time to recovery (TTR) and p = 0.0446 for both TTCI and TTR. Change from baseline of NEWS2 score at day 28 was −3.4 vs. + 0.4 (p = 0.0441). The results propose hzVSF-v13 as a candidate in the treatment of severe COVID-19. Full article

Mitochondria, as the powerhouse of most cells, are not only responsible for the generation of adenosine triphosphate (ATP) but also play a decisive role in the regulation of apoptotic cell death, especially of cancer cells. Safe potential delivery systems which can achieve organelle-targeted therapy are urgently required. In this study, for effective pancreatic cancer therapy, a novel mitochondria-targeted and ROS-triggered drug delivery nanoplatform was developed from the TPP-TK-CPI-613 (TTCI) prodrug, in which the ROS-cleave thioketal functions as a linker connecting mitochondrial targeting ligand TPP and anti-mitochondrial metabolism agent CPI-613. DSPE-PEG2000 was added as an assistant component to increase accumulation in the tumor via the EPR effect. This new nanoplatform showed effective mitochondrial targeting, ROS-cleaving capability, and robust therapeutic performances. With active mitochondrial targeting, the formulated nanoparticles (TTCI NPs) demonstrate much higher accumulation in mitochondria, facilitating the targeted delivery of CPI-613 to its acting site. The results of in vitro antitumor activity and cell apoptosis revealed that the IC₅₀ values of TTCI NPs in three types of pancreatic cancer cells were around 20~30 µM, which was far lower than those of CPI-613 (200 µM); 50 µM TTCI NPs showed an increase in apoptosis of up to 97.3% in BxPC3 cells. Therefore, this mitochondria-targeted prodrug nanoparticle platform provides a potential strategy for developing safe, targeting and efficient drug delivery systems for pancreatic cancer therapy. Full article

The aim of this study is to analyze the relationship between sustainability and tourism competitiveness and potential differences in these parameters between geographical regions. The Travel and Tourism Competitiveness Index (TTCI) of the World Economic Forum is most commonly used to measure tourism competitiveness, however, this index has been criticized by some academics. We propose a synthetic indicator (I^mα) using the multicriteria double reference point method, which can measure tourism competitiveness more accurately by applying different degrees of substitutability among pillars. The Sustainable Development Index (SDG Index) frames the implementation of Sustainable Development Goals and was used to analyze sustainability data. The new tourism competitiveness index (I^mα) was obtained at both the global and regional level. It is important to note that some countries have a different ranking in the regional and global tourism competitiveness indexes, which shows a different behaviors among regions. The relationship between sustainability and tourism competitiveness is positive in all the analyses performed, though it is stronger when calculated without allowing substitutability, especially when considering the regional index. These trends show the value of this regional study of tourism competitiveness, because in addition to helping managers develop strategies to improve tourism competitiveness, it allows them to know the effect that these strategies will have on sustainability. Full article

Conventional autonomous emergency braking (AEB) systems derive the relative distance of a curve using a curvature calculated through an in-vehicle sensor. However, as the AEB system cannot reflect geometric factors of a curve with variable curvature, it does not accurately estimate relative distances, based on which the AEB performance is evaluated. Accordingly, an AEB system reflecting the geometric information of curves needs to be considered and developed to improve the AEB performance for curves. This study proposes a method to improve the performance of AEB systems for curves through curvilinear coordinate conversion, which is used to reflect the geometric information of roads for the navigation of an autonomous vehicle. Both the host and target vehicles are located by means of curvilinear coordinate conversion. The positions thus identified are used to calculate the relative distance and lanes. Finally, the hazard risk criterion—that is, time-to-collision (TTC)—is derived using the proposed AEB system. To demonstrate the effectiveness of the proposed AEB system, this study compares it with the conventional AEB system by analyzing the collision avoidance performance on curves through relative distances and TTC. Full article