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Making love differences in programmed orienting as well as the role involving estradiol in addiction-related actions.
DR reduced with oil fraction. It was concluded that XG performs better in the presence of oil than GG.This study assessed the perceived causes, indicators and impacts of climate change by disaggregating farmers in to adaptor and non-adaptor groups in Goat based agro-pastoral livelihood zone of Ethiopia. The collected quantitative and qualitative data were analysed in descriptive statistics, linear regression, anomaly index, Likert rating scale and conceptual narrations. The findings demonstrated that an increasing temperature and a decreasing rainfall trends were perceived by farmers across the study decades. Higher deforestation rate, rash natural resource exploitation, poor soil and water management rehearses and alarming population growth in descending order were identified as climate change causes. Livestock and crop yield decline, livestock/human diseases epidemics and death, as well as recurrent conflicts due to grazing land were its associated impacts. The status and nature of climate change causes, indicators and impacts were however significantly diverse within similar awareness groups. Linsitinib To mitigate its adverse impacts, the farmers were thus applied livestock, crop and non-agriculture related adaptation strategies. Shortage of finance and eligible household labor combined with the absence of climate related information, training and extension services were hindered farmers to take any measure to the climate change. Therefore, to encourage the farmers' responsiveness, the finding underlines the importance of supplying applicable as well as legitimate natural resource exploitation system, followed by access to climate related information, awareness rising trainings, credit and input delivery services at local and community level.Internet of Things (IoT) presents opportunities for designing new technologies for organizations. Many organizations are beginning to accept these technologies for their daily work, where employees can be connected, both on the organization's premises and the "outside", for business continuity. However, organizations continue to experience data breach incidents. Even though there is a plethora of researches in Information Security, there "seems" to be little or lack of interest from the research community, when it comes to human factors and its relationship to data breach incidents. The focus is usually on the technological component of Information Technology systems. Regardless of any technological solutions introduced, human factors continue to be an area that lacks the required attention. Making the assumption that people will follow expected secure behavioral patterns and therefore system security expectations will be satisfied, may not necessarily be true. Security is not something that can simply be purchased; human factors will always prove to be an important space to explore. Hence, human factors are without a doubt a critical point in Information Security. In this study, we propose an Organizational Information Security Framework For Human Factors applicable to the Internet of Things, which includes countermeasures that can help prevent or reduce data breach incidents as a result of human factors. Using linear regression on data breach incidents reported in the United States of America from 2009 to 2017, the study validates human factors as a weak-point in information security that can be extended to Internet of Things by predicting the relationship between human factors and data breach incidents, and the strength of these relationships. Our results show that five breach incidents out of the seven typified human factors to statistically and significantly predict data breach incidents. Furthermore, the results also show a positive correlation between human factors and these data breach incidents.Thermodynamic and surface properties of the ternary system were studied at different higher temperatures (1973 K, 2073 K, 2173 K and 2273 K). The thermodynamic properties were studied using the Chou, Kohler and Toop models. Meanwhile, the surface properties were investigated using the same models plus the Butler model. The thermodynamic and surface properties of the ternary alloys computed from different models were compared with one another. The surface concentration of the components of the ternary Ti-Al-Si alloy was computed using Butler's equation.The present study explores English as a foreign language (EFL) learning strategies used in Hungarian, Chinese, and Mongolian university students with different cultural and linguistic backgrounds. A total of 519 university students participated in the survey from the three different countries. The Strategy Inventory for Language Learning (SILL), developed by Rebecca Oxford (2003), was administered to explore cross-cultural differences in strategy use in the study. To explain cultural divergences, we employed Hofstede's 6-D model of cultural values. The study identified a number of cross-cultural similarities and differences in strategy use among these three groups. All the subsamples similarly preferred the use of metacognitive learning strategies; however, there were some significant differences among the countries. A significant difference was observed in cognitive language learning strategy usage for the Hungarian subsample compared to the Mongolian subsample. With regard to the affective field, we noticed that the Mongolian and Chinese students employed affective strategies significantly more frequently. The Hungarian students rated the use of affective strategies the lowest by comparison. These differences may be partly linked to the cultural traditions of the participating countries. Our findings also suggest that although students' cultural background is a significant factor, linguistic and educational background and teaching traditions are also crucial.Earlier studies on foreign direct investment (FDI) and firm productivity have mainly focused on the general impacts of FDI on local firms' productivity. This current research extends the existing literature by examining the heterogeneity issue in firm productivity by clustering Indonesian manufacturing firms into nine industrial groups. Two estimation methods are applied stochastic frontier analysis and panel data analysis, which emerge three key findings. Firstly, the impacts of FDI vary among firm clusters, with six out of nine clusters are able to grasp the positive benefits of FDI, whereas three out of nine clusters experience negative productivity effects. Secondly, the labor-intensive clusters tend to receive negative productivity effects, whereas the capital-intensives clusters receive positive productivity impacts. Thirdly, the sources of FDI-productivity vary across clusters, with scale-efficiency as the most dominant source and technology advancement as the second dominant source. These findings justify the importance of estimating firms in homogenous industrial groups to gain precision findings of productivity benefits.
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