Međunarodno tržište jabuke - stanje i tendencije

This paper deals with international apple market analysis. Average export rate was 10,4 million tons (2006-2012) with moderate growth tendency of 2,36%. The most significant and largest exporter is China, which is the largest producer as well, with 1,5 million tons and 14% share of the world's total export. Then comes Italy, USA, Chile and France which amount to half of the world's total export, combined. Import is at 10,1 million tons, at an average rate of 2,5% growth, which represents a trend of slightly intensive growth comparing to export. The largest importer is Russia, with 1,5 million tons and 14% share of the world market. Large importers are also Germany, Great Britain, the Netherlands and France, which absorb one third (1/3) of the world's total import, combined. For the next period, we can expect further expansion of the international trade. It will depend mostly on the level of production and financial power of the consumers - predominantly on economic factors. Trade of organic apples (integral and organic system of production) shall increase.U radu se analizira međunarodno tržište jabuke. Determinisane su promene u međunarodnom prometu, apostrofirani su najveći izvoznici i uvoznici. Prosečan izvoz iznosio je 10,4 miliona tona (2006-2012) sa tendencijom umerenog rasta po stopi od 2,4%. Najznačajniji izvoznik jeste Kina, koja je i najveći svetski proizvođač, sa 1,5 miliona tona i učešćem od 14% u ukupnom svetskom izvozu. Slede Italija, SAD, Čile i Francuska koje zajedno daju polovinu svetskog izvoza jabuke. Uvoz iznosi 10,1 miliona tona i beleži trend nešto intenzivnijeg rasta u odnosu na izvoz, po prosečnoj stopi od 2,5% godišnje. Najveći uvoznik je Rusija sa 1,5 miliona tona i učešćem u svetu od 14%. Veliki uvoznici su i Nemačka, Velika Britanija, Holandija i Francuska, koje zajedno apsorbuju trećinu svetskog uvoza. U narednom periodu može se očekivati dalja ekspanzija međunarodne trgovine. Ona će, pre svega, zavisiti od nivoa proizvodnje i kupovne moći potrošača, dominantno od ekonomskih faktora. Intenziviraće se trgovina jabuke proizvedene u integralnom i organskom sistemu proizvodnje

Comparative screening of the anti-oxidant and antimicrobial activities of Sempervivum marmoreum L. extracts obtained by various extraction techniques

This paper presents a comparative study of the anti-oxidant and anti-microbial activities, total phenolic compounds and total flavonoids in extracts obtained from houseleek (Sempervivum marmoreum L.) leaves by the classical (maceration), ultrasonic and Soxhlet extraction (CE, UE and SE, respectively). The extract obtained by the CE contained higher amounts of phenolic and flavonoid compounds and showed a better antioxidant activity than those obtained using other two techniques. All the extracts, independent of the extraction technique applied, showed antimicrobial activities against Aspergillus niger and Candida albicans only but not against the tested bacteria

Content of Trace Metals in Medicinal Plants and their Extracts

The heavy metals (Fe, Cu, Zn and Mn) contents of selected plant species, grown in Southeast region of Serbia, that are traditionally used in alternative medicine were determined. Among the considered metals, iron content was the highest one and varied from 137.53 up to 423.32 mg/kg, while the contents of Cu, Zn and Mn were remarkably lower, and ranged from 8.91 to 62.20 mg/kg. In addition, an analysis of plants extracts showed a significant transfer of heavy metals during extraction procedure; therefore, the corresponding extraction coefficients reached values up to 88.8%. Those were especially high in the ethanol based extracts. Moreover, it is was established that such coefficients mostly depend on the solvent nature and also on the treated plant species. The obtained results impose that medicinal plants from Southeast region of Serbia due to rather low content of heavy metals are appropriate for preparation of teas and medicinal extracts

A convergence on Boolean algebras generalizing the convergence on the Aleksandrov cube

We compare the forcing related properties of a complete Boolean algebra B with the properties of the convergences $\lambda_s$ (the algebraic convergence) and $\lambda_{ls}$ on B generalizing the convergence on the Cantor and Aleksandrov cube respectively. In particular we show that $\lambda_{ls}$ is a topological convergence iff forcing by B does not produce new reals and that $\lambda_{ls}$ is weakly topological if B satisfies condition $(\hbar)$ (implied by the ${\mathfrak t}$-cc). On the other hand, if $\lambda_{ls}$ is a weakly topological convergence, then B is a $2^{\mathfrak h}$-cc algebra or in some generic extension the distributivity number of the ground model is greater than or equal to the tower number of the extension. So, the statement "The convergence $\lambda_{ls}$ on the collapsing algebra B=\ro ((\omega_2)^{<\omega}) is weakly topological" is independent of ZFC

New models of adipogenic differentiation highlight a cell-autonomous response to temperature

Temperature is a key regulator of brown adipose tissue (BAT) function, acting through central sensory inputs to influence metabolism and energy storage. Although animal models have produced a wealth of information on the pathways, effectors and responses mediating the physiological response of adipose tissue to temperature in vivo, the use of cell culture models now offers evidence of an additional cell-autonomous response to temperature changes, in the absence of neural input. In particular, stem cell models provide new insight into the regulation of adipogenic differentiation and the induction of browning features in vitro. Here the basis for adipogenic responsiveness to low temperature is discussed, together with different human cell models available to outline the benefits of cell-based approaches for future BAT research

Antioksidativna aktivnost etanolnih ekstrakata Solanum Retroflexum

In this paper the antioxidant activity of ethanolic extracts from Solanum retroflexum Dun fruits were investigated. The extracts were obtained by classical technique and by Soxhlet extraction. In order to investigate the possibilities of future utilization of Solanum retroflexum fruits, the antioxidant activity, by FRAP and DPPH method was determined. Results showed the extract obtained by 75% ethanol and classic extraction during 45 minutes at 60°C, had the highest antioxidant activity, both for DPPH and FRAP method (EC50 was 60,67 μg/mL and 1,55 μmol Fe2+/mg, respectively). There was good correlation of results for antioxidant activity obtained by both methods and for all analyzed extracts.Rad se bavi ispitivanjem antioksidativne aktivnosti etanolnih ekstrakata ploda biljke Solanum retroflexum Dun. Ekstrakti su dobijeni tehnikama klasične i Soxhlet extrakcije. Potencijalna antioksidativna aktivnost je ispitana FRAP i DPPH metodama. Rezultati su pokazali da ekstrakt dobijen klasičnom ekstrakcijom sa 75% rastvorom etanola na 60°C i za vreme 45 minuta, ima najveću antioksidativnu aktivnost (EC50 = 60,67 μg/ml, 1,55 μmol Fe2+/mg), kao i da postoji dobra korelacija rezultata dobijenih obema metodama u slučaju svih analiziranih ekstrakata

Multivariate Relations Aggregation Learning in Social Networks

Multivariate relations are general in various types of networks, such as biological networks, social networks, transportation networks, and academic networks. Due to the principle of ternary closures and the trend of group formation, the multivariate relationships in social networks are complex and rich. Therefore, in graph learning tasks of social networks, the identification and utilization of multivariate relationship information are more important. Existing graph learning methods are based on the neighborhood information diffusion mechanism, which often leads to partial omission or even lack of multivariate relationship information, and ultimately affects the accuracy and execution efficiency of the task. To address these challenges, this paper proposes the multivariate relationship aggregation learning (MORE) method, which can effectively capture the multivariate relationship information in the network environment. By aggregating node attribute features and structural features, MORE achieves higher accuracy and faster convergence speed. We conducted experiments on one citation network and five social networks. The experimental results show that the MORE model has higher accuracy than the GCN (Graph Convolutional Network) model in node classification tasks, and can significantly reduce time cost.Comment: 11 pages, 6 figure