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6-Gingerol, a pungent ingredient of ginger, has been reported to possess anti-inflammatory and antioxidant activities, but the effect of 6-gingerol on pressure overload-induced cardiac remodeling remains inconclusive. In this study, we investigated the effect of 6-gingerol on cardiac remodeling in in vivo and in vitro models, and to clarify the underlying mechanisms. C57BL/6 mice were subjected to transverse aortic constriction (TAC), and treated with 6-gingerol (20 mg/kg, ig) three times a week (1 week in advance and continued until the end of the experiment). Four weeks after TAC surgery, the mice were subjected to echocardiography, and then sacrificed to harvest the hearts for analysis. For in vitro study, neonatal rat cardiomyocytes and cardiac fibroblasts were used to validate the protective effects of 6-gingerol in response to phenylephrine (PE) and transforming growth factor-β (TGF-β) challenge. We showed that 6-gingerol administration protected against pressure overload-induced cardiac hypertrophy, fibrosis, inflammation, and dysfunction in TAC mice. In the in vitro study, we showed that treatment with 6-gingerol (20 μM) blocked PE-induced-cardiomyocyte hypertrophy and TGF-β-induced cardiac fibroblast activation. Furthermore, 6-gingerol treatment significantly decreased mitogen-activated protein kinase p38 (p38) phosphorylation in response to pressure overload in vivo and extracellular stimuli in vitro, which was upregulated in the absence of 6-gingerol treatment. Moreover, transfection with mitogen-activated protein kinase kinase 6 expressing adenoviruses (Ad-MKK6), which specifically activated p38, abolished the protective effects of 6-gingerol in both in vitro and in vivo models. In conclusion, 6-gingerol improves cardiac function and alleviates cardiac remodeling induced by pressure overload in a p38-dependent manner. The present study demonstrates that 6-gingerol is a promising agent for the intervention of pathological cardiac remodeling.

Purpose This study aims to estimate the determinants of international tourist flows between destinations by using the panel gravity model. Design/methodology/approach The multi-dimensional panel gravity model was used to analyse tourism originating from 30 different countries to the 14 most-visited countries in the world between 2008 and 2016. Income (i.e. per capita gross domestic product for both the origin and destination countries), distance between countries, various economic indicators and six dummy variables were added to the gravity model as control variables. Findings The results indicated that tourist arrivals depended mainly on economic factors, i.e. income and trade variables were significant determinants of tourist arrivals. The results also suggested that estimated international tourist flows are a negative function of distance, as is postulated in economic theory. Originality/value In recent years, gravity models have been used frequently to analyse international tourism demand and have demonstrated their ability to evaluate the effects of various determinants of international tourism for many countries. The literature includes studies that used a two-dimensional panel gravity model to analyse the determinants of tourism demand to a single country from many different countries. This study differs in terms of specificity; in that, it relied on a three-dimensional panel gravity model that allowed for modelling of multiple destination countries. As a result, more comprehensive and general results relative to the determinants of tourism demand were obtained. In addition, the application of a non-nested three-dimensional panel data model, which has limited use, contributes a new perspective to the econometric literature. 基于多维面板重力模型的旅游需求分析 摘要 Purpose目的 本研究旨在通过采用面板引力模型来估计目的地之间国际旅游流量的决定因素。 Design/methodology/approach设计/方法/方法 多维面板引力模型用于分析2008年至2016年间来自30个不同国家的游客赴世界上前14位旅游目的地国家的旅游情况。收入（即客源国和目的地国家的人均国内生产总值）, 国家之间的距离, 各种经济指标和六个虚拟变量作为控制变量加入到引力模型中。 Findings调查结果 结果表明, 游客到访主要取决于经济因素, 即收入和贸易变量是游客到访的重要决定因素。结果还表明, 估计的国际旅游流量是距离的负函数。 Originality/value创意/价值 近年来, 引力模型经常被用来分析国际旅游需求, 并证明了它们能够评估许多国家的各种国际旅游决定因素的影响。文献包括使用二维面板引力模型来分析来自许多不同国家的单个国家的旅游需求的决定因素的研究。该研究的不同之处在于, 它依赖于非嵌套集合模型三维面板引力模型, 允许对多个目的地国家进行建模。因此, 此研究获得了与旅游需求决定因素相关的更全面和广泛的结果。此外, 使用不常运用的非嵌套三维面板数据模型的应用为计量经济学文献提供了新的视角。 关键词 国际旅游需求, 重力模型, 多维面板数据模型 Análisis de la demanda turística utilizando un modelo de gravedad de paneles multidimensionales Propósito Este estudio tiene como objetivo estimar los determinantes de los flujos turísticos internacionales entre destinos mediante el uso del modelo de panel de gravedad. Diseño/metodología/enfoque El modelo de gravedad de panel multidimensional se utilizó para analizar el turismo que se originó en 30 países diferentes a los 14 países más visitados del mundo entre 2008 y 2016. Resultados Los resultados indicaron que las llegadas de turistas dependían principalmente de factores económicos, es decir, las variables de ingresos y comercio fueron determinantes significativos de las llegadas de turistas. Los resultados también sugirieron que los flujos turísticos internacionales estimados son una función negativa de la distancia. Originalidad/valor En los últimos años, los modelos de gravedad se han utilizado con frecuencia para analizar la demanda turística internacional y han demostrado su capacidad para evaluar los efectos de varios determinantes del turismo internacional para muchos países. La literatura incluye estudios que utilizaron un modelo de gravedad de panel bidimensional para analizar los determinantes de la demanda turística a un solo país desde muchos países diferentes. Este estudio difiere en términos de especificidad en que se basó en un modelo tridimensional de panel de gravedad que permitió el modelado de múltiples países de destino. Palabras clave Demanda turística internacional, Modelo de gravedad, Modelo de datos de panel multidimensional

This study searches the impact of tourism growth on emission pollutants in Cyprus (north), which is a small island in the Mediterranean and has shown significant development in hotel and casino sectors in the last two decades. Results from time-series analyses reveal that an inverted U-shaped EKC hypothesis is confirmed for Cyprus with and without tourism development. Tourism also exerts positively significant and long-term effects on the levels of carbon emissions, revealing that growth in the tourism sector causes degradation in the environment.

Countries prioritize secure and cheap energy over clean energy in their energy policies, and Türkiye is no different. The Strategy Plan 2015–2019 of the Ministry of Energy and Natural Resources emphasizes the exploitation of domestic coal for energy security, while Türkiye intends to curb its emissions by 41% by 2030. These two targets contradict in terms of climate change mitigation. In retrospect, this study aims to determine the role of coal, wind, and solar power in energy policy-making through scenario analyses. The results indicate that if Türkiye continued its pre-2020 energy policy, its use of domestic coal would be important for energy security. On the other hand, both wind and solar have the capacity to contribute to the country’s efforts towards energy security and climate change mitigation.

Food is not only a basic need but also a vital component of the tourist experience and a strategic element in enhancing destination attractiveness. The literature suggests that about one-third of tourist expenditures are on food. The issue of tourism-induced food inflation is timely and important, especially considering the post-pandemic inflationary environment and the recovery in global tourism. Turkey is an appropriate case study due to its high dependence on tourism and significant food inflation. This paper aims to empirically examine tourism-driven food inflation in Turkey over a lengthy period, 2005 (1) – 2024 (12). In this study, the Gregory and Hansen cointegration test, which investigates the cointegration relationship under a structural break, is used, and the long-run relationship between the series is estimated using FMOLS and CCR methods. The results confirm a long-run relationship between tourism arrivals and food price inflation. Moreover, oil prices, water, electricity, and natural gas prices increase, and income is found to have significant effects on tourism-food prices. Although tourism arrivals caused an increase in food prices, this effect is not as high as expected because food prices exhibit higher volatility due to more inelasticity in their supply and demand relative to other consumer goods.

The single multiplicative neuron model has been frequently used by researchers in recent years, as it does not have a complex structure and does not include the hidden layer unit number problem, unlike many feed-forward artificial neural network models. The model of single multiplicative neuron model artificial neural networks does not have statistical assumptions just like in many artificial neural network models. The random error term is not used in the mathematical model of single multiplicative neuron model artificial neural networks. This situation is not acceptable considering that artificial neural networks work with random samples. Based on this idea, for the first time, by including a random error term in the single multiplicative neuron model artificial neural network model, mathematical equations of likelihood functions are given for normal, cauchy, logistic, gumbel, and laplace distributions. A new statistical training algorithm is proposed to obtain optimal weights and bias values of the network. In the new training algorithm, particle swarm optimization proposed by Kennedy and Eberhart (in: Proceedings of IEEE international conference on neural networks (ICNN '95). IEEE, pp 1942–1948, 1995) is used in maximizing likelihood functions. In the performance evaluation of the proposed method, Nasdaq and S&P500 time series in different years are analyzed and the analysis results are compared with many artificial neural network models in the literature. Finally, it is concluded that the proposed method produces very successful forecasting results.

In the wake of escalating climate change impacts, Pakistan’s flood defense infrastructure, which is mainly comprised of dike systems, is now facing unprecedented problems. This article explores the many intricate aspects of dike resilience in the context of heightened flood risk intensified by global warming. The study provides a comprehensive insight into the current state of dike structures in Pakistan by carefully integrating the real-time data from site visits that includes comprehensive field and laboratory testing, detailed case studies, and substantial literature evaluation. This study does a thorough analysis of how unusual weather patterns impact the occurrence of floods, classifies floods based on return periods, and illuminates the role of dikes in territorial safeguarding. The geotechnical assessment of specific dikes offers valuable information about their condition and performance, while the contemporary cross-sections give a glimpse into their design effectiveness. Examining instances of dike collapses via case studies reveals the underlying weaknesses and thresholds in the light of the limit state as defined by the Euro Code, hence shaping the discourse on possible corrective measures. Further, this study highlights the potential applications of secondary materials and promotes the implementation of sustainable flood protection structures as additional aspects of dike management and flood mitigation. The synthesis of research results provides a bench mark and establishes a foundation for a proactive approach to flood prevention, emphasizing the need for durable, flexible, and robust flood control systems to defend against the imminent danger of climate-driven hydrological extremes.

This paper undertakes the investigation of ordered vector spaces by applying nonstandard analysis. We introduce and study two types of nonstandard hulls of ordered vector spaces. Norm-nonstandard hulls of ordered Banach spaces are also investigated.

An experimental study was conducted to investigate turbulent flow through from rectangular cross-sectional area to rectangular transition duct. Three kinds of channels with different length, side angle and geometrical dimensions were designed and then flow characteristic of them were all tested. The transition duct have different inlet and outlet cross-sectional areas, outlet section is double than inlet sectional area. Measurements were made at several station along the channel and at various flow-rates, Reynolds numbers ranging from 2.105 to 6.105, in which the two-dimensional mean, local velocity and pressure were measured at the x/l = 0.20, 0.40, 0.60, 0.80, 1.00 ratio, inlet by using hot wire anemometer. Based on experimental results, different flow characteristics were obtained. According to mean and local velocity and pressure drop values, each section point of the transition duct showed various values. Friction coefficient was lowered with increasing pipe length and increasing Reynolds number. Cross flows was shown in the short pipe along length at the low Reynolds.

Since terrorism is a matter of both national and international threats, working on terrorism and terrorist organization with different aspects, could be considered as beneficial one. In order to combat against this threat considering the sources of terrorism financing, whether there is a PKK and narco-terror relationship and examine the causes and consequences of this connection is deemed necessary. Accordingly, it may also be useful to explore, the benefits of the PKK terrorist organization thanks to drug trafficking and examine its presence at different stages of drug trafficking. Therefore, first of all, the concept of narco-terrorism will be emphasized and drug trafficking activities of the PKK terrorist organization will be evaluated in this context. In addition to this, drug trafficking activities the PKK has done to meet the financial need, will be discussed in more detail, from its establishment until today.