Customers' need for uniqueness theory versus brand congruence theory: the impact on satisfaction with social network sites

Social media brands may experience a lack of competitiveness and attraction due to the silent negative increase of customers' need for uniqueness (NFU). This is the result of a tension between the theory of brand congruence, that most brands endeavor to establish with their customers, and the theory of consumers' NFU, that many consumers aim to fulfill, that has not been previously examined. Whilst the theory of brand congruence states that consumers have a favorable attitude towards brands that greatly match their self-concept (brand similarity), the theory of uniqueness, when brand similarity is shared with others, generates avoidance of similarities with others, leading to a reduction in engagement and satisfaction. Social media platforms including Facebook are at risk from customers' NFU which significantly reduces users' satisfaction, hence reducing the attractiveness and usage of Facebook. To examine this, the paper identifies the paradox of similarity in relation to both theories and examines the relationship between consumers' socialization within Social Network Sites (SNSs), brand similarity, consumers' need for uniqueness, and consumers' satisfaction with the SNS. The conceptual model was tested using data from 341 consumers in the US. The findings show that whilst satisfaction with the SNS is enhanced by brand similarity and friend liking, it is undermined by customers' need for uniqueness. Implications for online brand communities and SNSs (Facebook) are discussed and guidance for future research is provided

The effect of foliar application of methanol on productivity and fruit quality of grapevine cv. Flame Seedless

Field experiments were conducted in 2002 and 2003 on 6-year-old grapevine cv. Flame Seedless. The content of chlorophyll a and b, carotenoids and total carbohydrates increased after methanol application. Foliar application of aqueous methanol was very effective increasing the number of leaves per shoot and leaf area. Furthermore, 30 % methanol increased significantly the number of stomata of developing leaves at the first application time (shoot length: 20-30 cm) while 10, 30, 40 and 50 % methanol solutions were more effective at the second application date (prebloom). Increasing the chlorophyll content, the leaf area and the number of stomata per unit leaf area by methanol application increased net productivity of vines. There was a highly significant positive correlation between total yield, chlorophyll and carbohydrates content. Generally, all methanol treatments significantly increased length and diameter of shoots and internode length at both application dates. Application of methanol increased total soluble solids (TSS), the TSS/acid ratio and total anthocyanins in berry skins but decreased total acidity. Most significant effects were obtained by spraying 30 % methanol at the two application dates.

Security Enhancement of IoT and Fog Computing Via Blockchain Applications

Blockchain technology is now becoming highly appealing to the next generation because it is better tailored to the information age. Blockchain technologies can also be used in the Internet of Things (IoT) and fog computing. The development of IoT and Fog Computing technologies in different fields has resulted in a major improvement in distributed networks. Blockchain technology is now becoming highly appealing to the next generation because it is better tailored to the information age. Blockchain technologies can also be used in IoT and fog computing.  The blockchain principle necessitates a transparent data storage mechanism for storing and exchanging data and transactions throughout the network. In this paper, first, we explained Blockchain, its architecture, and its security. Then we view Blockchain application in IoT security. Then we explained Fog computing, Generic Security Requirements for Fog Computing, and we also discuss Blockchain applications that enhance Fog Computing Security. Finally, we conduct a review of some recent literature on using Blockchain applications to improve the security of IoT and fog computing and a comparison of the methods proposed in the literature

Domestic thermoelectric cogeneration system optimization analysis, energy consumption and CO 2 emissions reduction

In this paper, a domestic thermoelectric cogeneration system (DCS) is suggested. This system permits to use the lost heat of exhaust gases to simultaneously heat water and produce electricity via thermoelectric generators (TEG). To proceed, the concept of the system is drawn and the corresponding thermal modeling is developed. An optimization analysis, based on the position of the thermoelectric generators within the system, is carried out using the thermal modeling. The TEGs are places on the inner or outer walls of the tank or the pipe (cases 2–5), or on all of them (case 6). Results show that water can be heated to up to 97 °C, when TEGs are located on the inner wall of the tank. More the TEGs are nearer to the exhaust gases, higher is the total power produced by the TEGs and lower is the water temperature. The power produced by one TEG in direct contact with the exhaust gases is 0.35 W and the water temperature is 76 °C. Also, a DCS with TEG located at all layers can generate up to 52 W and 81 °C hot water, however this configuration has high initial cost. An economic and environmental concerns are considered. Results show that DCS with TEGs located on the inner wall of the pipe has a payback period of 1 year and 8 months when water is heated 60 times per month. In addition to that, it was shown that the location of TEGs do not affect the amount of CO2 gas reduced which is about 6 tons yearly. Finally, this study shows that the configuration where TEGs are placed at the inner wall of the pipe is the most cost-effective energy recovery configuration

Optimasi Parameter Permesinan Terhadap Waktu Proses Pada Pemrograman Cnc Milling Dengan Berbasis Cad/cam

The milling process is one of many machining processes for manufacturing component. The length of time in the process of milling machining is influenced by selection and design of machining parameters including cutting speed, feed rate and depth of cut. The purpose of this study to know the influence of cutting speed, feed rate and depth of cut as independent variables versus operation time at CNC milling process as dependent variables. Each independent variable consists of three level of factors; low, medium and high.Time machining process is measured from operation time simulation program, feed cut length and rapid traverse length. The results of statistically from software simulation MasterCam X Milling, then do the comparison to CNC Milling machine.  The data from experiments was statistically analyzed by ANOVA and Regression methods by software Minitab 16.Results show that the greater feed rate and depth of cut shorten the operation time of machinery, whereas cutting speed is not a significant influence. The depth of cut has the highest contribution to the value of 49.56%, followed by feed rate 43% and cutting speed 0.92%. Optimal time of machining process total is 71.92 minutes, with machining parameter on the condition cutting speed is 75360 mm/minutes, the feed rate is 800 mm/minutes and depth of cut = 1 mm. Results of comparison time machining process in software Mastercam X milling with CNC Milling machine indicates there is the difference not significant with the value of 0,35%

QUANTITATIVE STUDIES ABOUT TSUNAMI GENERATION AND PROPAGATION WAVES BY A STOCHASTIC SUBMARINE SLUMP AND LANDSLIDE SOURCE MODEL

Tsunami generation and propagation due to a vertical time-dependent extent of a stochastic submarine slump and landslide model for different values of Froude number and noise intensity are investigated. The critical parameters controlling the oscillations and the amplitude of the free surface elevation are through the Froude number and the noise intensity induced by the stochastic submarine slump and landslide source model. Quantitative information about the tsunami generation and propagation waves will be provided by estimating the evolution of the displaced water volume, the potential, kinetic and total energy of the resulting waves and the averaged tsunami velocity components at different Froude numbers. The inclusion of the random noise of the submarine slump and landslide deformation provided an additional and a noticeable contribution to the quantitative characteristics of the free surface elevation

Gestational diabetes mellitus: Association with maternal and neonatal complications

Background and objectives: Gestational diabetes mellitus (GDM) is known to be associated with pregnancy complications but there is limited evidence about the strength of these associations in recent clinical practice, especially after the introduction of strict guidelines for the management of pregnancies with GDM in a multidisciplinary team setting. The objectives of our study were to first compare the rates of complications in pregnancies with GDM with those that had pre-existing diabetes mellitus and those without diabetes; and second, to derive measures of effect size expressed as odds ratios after adjustment for confounding factors to assess the independent association of GDM in prediction of these pregnancy complications. Materials and Methods: This was a prospective cohort study undertaken at a large maternity unit in the United Kingdom between January 2010 and June 2022. We included singleton pregnancies that were booked at our unit at 11–13 weeks’ gestation. Multivariate regression analysis was carried out to determine the risks of complications in pregnancies with GDM after adjusting for pregnancy characteristics. Risks were expressed as odds ratio (OR) (95% confidence intervals [CI]) and expressed graphically in forest plots. Results: The study population included 53,649 singleton pregnancies including 509 (1%) with pre-existing DM, 2089 (4%) with GDM and 49,122 (95%) pregnancies without diabetes. Multivariate regression analysis demonstrated that there was a significant independent contribution from GDM in the prediction of adverse outcomes, including maternal complications such as preterm delivery, polyhydramnios, preeclampsia and delivery of large for gestational age neonates and elective caesarean section (CS); and neonatal complications including admission to neonatal intensive care unit, hypoglycaemia, jaundice and respiratory distress syndrome. Conclusions: GDM is associated with an increased rate of pregnancy complications compared to those without diabetes, even after adjustment for maternal and pregnancy characteristics. GDM does not increase the risk of stillbirth, hypoxic ischaemic encephalopathy or neonatal death

GreenSTEM’s microbe technology is an efficient, effective, and affordable way to clean up fuel and chemical spills

Non-Peer ReviewedPetroleum hydrocarbons are used as fuel and for chemical synthesis. If spilled, fuels and chemicals poison our soil and water, causing local environmental disasters. Bioremediation uses organisms to clean up (remediate) pollutants. We have isolated and characterized microbe strains from contaminated sites, and use them to remediate contaminated sites elsewhere. We identify our strains using their DNA sequences and their appearance. Some microbes, called fungal endophytes, form symbioses, in other words metabolic partnerships between a plant and a fungus. These symbioses have been shown to stimulate plant growth and root formation, even on contaminated soil. Surprisingly, some of our other microbes can degrade hydrocarbons underground, without plants. GreenSTEM has powerful technology: we use native microbes to degrade hydrocarbons and chemicals as they grow on the contaminants as food. Based on our progress to date with fuels and other chemicals, we anticipate isolating new strains specific for other intractable toxins

New Hybrid heat recovery concept applied to exhaust gas

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