Ultraviolet-B radiation (285-320 nm) elicits a number of cellular signaling elements. We investigated the preventive effect of linalool, a natural monoterpene, against UVB-induced oxidative ...imbalance, activation of mitogen-activated protein kinase (MAPK) and nuclear factor kappa-B (NF-κB) signaling in HDFa cells. We observed that linalool treatment (30 μM) prevented acute UVB-irradiation (20 mJ/cm2) mediated loss of activities of antioxidant enzymes in HDFa cells. The comet assay results illustrate that linalool significantly prevents UVB-mediated 8-deoxy guanosine formation (oxidative DNA damage) rather than UVB-induced cyclobutane pyrimidine (CPD) formation. This might be due to its ability to prevent UVB-induced ROS formation and to restore the oxidative imbalance of cells. This has been reflected in UVB-induced overexpression of MAPK and NF-κB signaling. We observed that linalool inhibited UVB-induced phosphorylation of ERK1, JNK and p38 proteins of MAPK family. Linalool inhibited UVB-induced activation of NF-κB/p65 by activating IκBa. We further observed that UVB-induced expression of TNF-α, IL6, IL-10, MMP-2 and MMP-9 was modulated by linalool treatment in HDFa cells. Thus, linalool protects the human skin cells from the oxidative damages of UVB radiation and modulates MAPK and NF-κB signaling in HDFa cells. The present findings substantiate that linalool may act as a photoprotective agent against UVB-induced skin damages.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
This study aims to project and characterize the climate extremes in Ravi River Basin (RRB) which is considered as a data poor transboundary basin located in India and Pakistan. Performance of the ...three GCDs against observation data was evaluated at three stations. A quantile mapping technique was used to correct the biases of four regional climate models (RCMs) and climate extremes were analysed for future period (2020–2095). Seven temperature and rainfall based indices that represent warm and wet characteristics of climate were chosen. Four statistical parameters and spatial maps were evaluated for the base period 1982–2005. The CPC‐NOAA and PU had the best performance for temperature and rainfall data regarding the time series analysis. The quantile mapping improved three important aspects of the climate cycle; the transitions from dry to wet and wet to dry seasons and peaks as well. At spatial scale, quantile mapping well captured the spatial distribution of the eleven indices other than RX1Day, CWD and FD0. The results show that warm and wet extremes will increase in future at 5% significance level across the entire basin with large changes in north east. The changes will be large for RCP8.5 scenario compare to RCP4.5 scenario and choice of the scenarios has dominant contribution in uncertainty than choice of the models.
We projected the future climate extremes in Ravi River Basin, a transboundary river basin of India and Pakistan. We found the increase in temperature and precipitation extremes under the both RCP4.5 and RCP8.5 scenarios in the Ravi River Basin. Spatial distribution of extreme temperature and precipitation indices for far future (2072–2095) relative to historical period (1982–2005) under RCP4.5 and RCP8.5.
Vulnerability assessment in industrial IoT networks is critical due to the evolving nature of the domain and the increasing complexity of security threats. This study aims to address the existing ...gaps in the literature by conducting a comprehensive survey on the use of attack graphs for vulnerability assessment in IoT networks. Attack graphs serve as a valuable cybersecurity tool for modeling and analyzing potential attack scenarios on systems, networks, or applications. The survey covers the research conducted between 2016 and 2021(34 peer-reviewed journal articles and 28 conference papers), identifying and categorizing the main methodologies and technologies employed in generating and analyzing attack graphs. In this review, core modeling techniques for IoT vulnerability assessment are highlighted, such as Markov Decision Processes (MDP), Feature Pyramid Networks (FPN), K-means clustering, and logistic regression models, along with other techniques involving genetic algorithms like fast-forward (FF), contingent fast-forwards (CFF), advanced reinforcement-learning algorithms, and HARMs models. The evaluation of the performance of these attack graph models using IoT networks or devices as case studies is also emphasized. This survey provides valuable insights into the state-of-the-art in attack graph techniques for IoT network vulnerability assessment, identifying various applications, performances, research opportunities, and challenges. As a reference source, it serves to inform academicians and practitioners interested in leveraging attack graphs for IoT network vulnerability assessment and guides future research directions in this area.
Abstract
Understanding the potential impact of anthropogenic climate change on the hydrological regime of the Koshi River Basin (KRB) is very important for sustainable water resources and ecosystem ...management. The hydrological studies are mainly focused on the annual, seasonal, and peak flows of the hydrological regime; however, the ecologically relevant flows of the hydrological regime are less explored. In this study, we analyzed the different flow characteristics based on the magnitude, intensity, and duration using the Indicator of Hydrologic Alterations (IHA) under the influence of shared socio-economic pathway (SSP) scenarios. We found that the KRB will experience a shift in hydro-climatic events, an increase in rise and fall rates of flow, increase in monthly low flows of the hydrological regime, eventually affecting the livelihoods and ecosystem of the basin. This study highlights the importance of environmental flow components (EFCs) in a hydrological regime to better understand the flow characteristics during the future hydro-climatic variability.
Prediction of potential evapotranspiration (PET) using an artificial neural network (ANN) with a different network architecture is not uncommon. Most researchers select the optimal network using ...statistical indicators. However, there is still a gap to be filled in future applications in various drought indices and of assessment of location, duration, average, maximum and minimum. The objective was to compare the performance of PET computed using ANN to the Penman–Monteith technique and compare drought indices standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI), using two different computed PET for the durations of 1, 3, 6, 9, and 12–months. Statistical performance of predicted PET shows an RMSE of 9.34 mm/month, RSR of 0.28, R2 of 1.00, NSE of 0.92, and PBIAS of −0.04. Predicted PET based on ANN is lower than that the Penman–Monteith approach for maximum values and higher for minimum values. SPEI–Penman–Monteith and SPI have a monthly correlation of greater than 0.95 and similar severity categories, but SPEI is lower than SPI. The average monthly index values for SPEI prediction show that SPEI–ANN captures drought conditions with higher values than SPEI–Penman–Monteith. PET–based ANN, performs robustly in prediction, fails by a degree of severity classification to capture drought conditions when utilized.
Abstract
Changes in extreme rainfall tend to be magnified into unpredictable fluctuations in runoff, leading to flooding and drought in the Pasak River Basin of Thailand. Moreover, it also affects ...the operation of the existing infrastructure. Therefore, it is important to monitor changes in the extreme rainfall events and integrate them into planning and operations with the additional challenges posed by climate change. In this study, rainfall data at the ten observed stations across the basin was used to assess the extreme rainfall indices over the baseline period 1985–2014. The five new CMIP6 global climate model datasets and two Shared Socioeconomic Pathways of SSP2-4.5 and SSP5-8.5 were selected to project the future climate scenarios from 2023 to 2100. The extreme rainfall indices trends are analysed using the Mann-Kendall test and Sen's slope, while the IDW technique is adopted to visualise the spatial trends. The results show that most of the rainfall indices in low-altitude areas are higher than in high-altitude areas, except for the duration-based indices CWD and CDD. The observed extreme rainfall shows a larger variation than that predicted by climate models. The very high greenhouse gas emissions exhibited by the SSP5-8.5 scenario contribute to greater uncertainty in future extreme rainfall for plain areas than in high-altitude areas. The Pasak River Basin is expected to experience wet rather than dry climates in the future. The spatial trends from past and future periods highlight the significant increasing trends in the area where the Pasak Jolasid reservoir is located. The results of this study will benefit policymakers in a position to reduce future climate vulnerabilities and can be used for building local adaptation strategies in response to long-term climate change.
PurposeSocial media is still influencing consumers and is extending social commerce (S-Commerce) use. Different social media activities can influence the users' trust and e-satisfaction at different ...levels, which in turn influence the purchase intentions. This is evident for the food and beverage industry as S-Commerce mediated by social media can help realise a shorter time to market and meet buyer demands. In addition, credibility factors may influence trust and purchase intentions. Understanding the various factors of influence such as social constructs, namely ratings, reviews and referrals; design constructs such as credibility and features and behavioural constructs such as trust, satisfaction and motivation; and analysing the relationship between these factors and how they influence purchase intentions can provide deeper insights into S-Commerce research, decision-making process and purchase intentions particularly from a food and beverage context.Design/methodology/approachDrawing on trust through social media activities and surface credibility as well as e-commerce satisfaction, the authors have proposed a research model to investigate the purchase intention of consumers in S-Commerce platforms. Survey data were collected from six countries in Asia and analysed using SEM-PLS.FindingsResults indicated that both trust and surface credibility significantly influence e-commerce satisfaction leading to purchase intention. Furthermore, surface credibility, which is a novel predictor for purchase intention in S-Commerce context, is highly significant on e-commerce satisfaction. Besides, encouraged by surface credibility, it was identified that trust significantly affects e-commerce satisfaction and results in purchase intention. This research adds contribution to theory and practice in S-Commerce stream as discussed at the end of the paper.Originality/valueThe results of this research contribute to the S-Commerce literature and have practical implications for practitioners in the food and beverage industry. As such, focussing on these constructs, this paper analyses the relationship between the social media activities, trust, e-commerce satisfaction, surface credibility and intention to buy.
This article looks at the co-creation of value in the branding process with members of online communities. Three online communities in Iran are analyzed through 45 interviews with members along with ...three interviews with top managers of the three brands of these communities. A content analysis shows a clear process in that the social interactions of customers in online brand communities with their favorite brands help develop relationship quality and increase customer brand loyalty. The findings suggest that firms may develop their branding strategies using social media and online brand communities through relationship marketing by using an online co-creation strategy. The findings also serve to inform practitioners of the impact of social media on branding and how they can best facilitate these brand relationships.
This study investigates the constructs and related theories that drive social capital in energy sector from the intention perspectives. This research uses theories of ‘social support’ and ‘planned ...behaviour’ alongside satisfaction and perceived value to propose a research model that drives social capital for energy sectors in Malaysia. The model reveals that the Theories of Planned Behaviour (TPB) and Social Support Theory (SST) alongside satisfaction and perceived value factors promote social capital development in energy sectors. Using PLS–SEM to analyse data gathered from energy sector employees in Malaysia, this research demonstrates that social capital is present when there is trust and loyalty among the users and positively effects energy sectors in terms of the productivity, effectiveness, efficiency and profitability. The study also contributes to the understanding of individuals' use of social capital in energy sector. A survey is adapted and distributed to 100 respondents as a mean to study on the validity and reliability of the research factors. Results indicate that all seven hypotheses proposed significantly influence social capital.
The applications of social commerce constructs Shanmugam, Mohana; Sun, Shiwei; Amidi, Asra ...
International journal of information management,
June 2016, 2016-06-00, 20160601, Letnik:
36, Številka:
3
Journal Article
Recenzirano
Odprti dostop
•This study investigates the social support constructs during trust-building from both emotional and informational perspectives separately.•The findings that social commerce constructs has more ...significant effect on emotional support than that on informational support.•Results indicate that social commerce constructs can lead to greater emotional and informational support•This study extends social support theory and trust literature.
Social commerce has evolved quickly in practice and gained attention in the IS discipline. However, trust has remained a vital component and is dominantly worth investigating. The purpose of this study, therefore, is to examine the roles of social commerce constructs and social support constructs (i.e., emotional support and informational support) in establishing trust on online community platforms. The study will apply the theoretical foundation of social commerce constructs proposed by Hajli. In order to provide a detailed understanding of the proposed model, a quantitative study involving a survey data gathered from online communities in Malaysia, including Facebook, Trip Advisor and LinkedIn was conducted. The data was analyzed and hypotheses were tested with structural equation modeling (SEM). Our results shed some lights on social commerce literature. The findings show that there are significant effect of social commerce constructs on social support, namely the emotional and informational support, and in turn, on trust- building.
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