Cephalaria syriaca seed oil

Cephalaria syriaca shrad., in Turkish pelemir, grows predominantly in the southeastern district of Turkey as a weed in cereal fields. Pelemir seeds are sometimes used for extraction of their oil, as an improver of baking value of wheat, and as an antistaling agent for bread. The seeds contain 7.8% moisture; their chemical composition on a dry basis is: crude fat, 25.3%, crude protein, 15.9%; N-free extract, 40.4%; crude fiber, 11.9%; crude ash, 6.5%. Characteristics of the seed oil are: specific gravity at 25 C, 0.9229; refractive index at 25 C, 1.4706; saponification value, 192; iodine value, 88.4; thiocyanogen value, 58.8; Reichert-Meissl value, 0.36; Polenske value, 0.25; unsaponifiable matter, 1.24%; hydroxyl value, 20.9. The fatty acid components are: lauric acid, 1.5%; myristic acid, 19.5%; palmitic acid, 9.4%; stearic acid, 2%; oleic acid, 23.0%; linoleic acid, 36.9%. The chemical composition of extracted cakes on a dry basis is: crude protein, 20.4%; crude fat, 0.8%; N-free extract, 50.5%; crude ash, 6.4%; crude fiber; 14.4%%; saponin, 7.5%. The oil contains 7.8% epoxy acid, calculated as epoxy oleic acid, which makes its use as an edible oil rather difficult but renders it usable in industries using epoxidized oils. Due to its high content of myristic acid, the oil is very suitable for soapmaking as well.     

头颈部CT血管造影和ABCD2评分对短暂性脑缺血血管特征及介入疗效评价

【摘要】 目的 探讨头颈部CT血管造影（CTA）及ABCD2评分对短暂性脑缺血发作（TIA）患者血管特征及介入治疗的意义。方法 对2010年1月—2012年1月收治的64例临床诊断TIA患者行ABCD2评分及头颈部CTA检查,分析患者头颈部血管狭窄程度、分布及其与ABCD2评分的相关性。按动脉狭窄程度将患者分为低和中高危组,中高危组中有22例患者行血管支架成形术治疗,分别于术后3、6和12个月进行随访。结果 64例患者中,头颈动脉狭窄52例（81.25％）,累及动脉149段,其中颅内动脉81段（54.36%）,颅外动脉68段（45.64％）。低危组患者动脉狭窄以轻、中度为主,中高危组患者以中、重度为主（χ2 = 10.126,P = 0.018）。与血管支架成形术前的 ABCD2评分（6.41 ± 0.50）分相比,术后患者3、6和12个月评分明显降低,分别为（2.88 ± 0.69）、（2.82 ± 0.63）和（3.00 ± 0.71）分,差异有统计学意义（F = 86.657,P ＜ 0.05）。结论 头颈部CTA联合ABCD2评分能对 TIA患者狭窄血管及介入疗效进行有效评价。     

Synthesis of barium mercaptides and application of antimony/barium mercaptides

1　ＩＮＴＲＯＤＵＣＴＩＯＮＡｎｔｉｍｏｎｙｍｅｒｃａｐｔｉｄｅｓ[1～ 4 ] ｕｓｅｄａｓｈｅａｔｓｔａｂｉｌｉｚ ｅｒｉｓａｔｔｒａｃｔｉｖｅｎｏｔｏｎｌｙｆｏｒｉｔｓｒｅｌａｔｉｖｅｌｙｌｏｗｃｏｓｔ ,ｂｕｔａｌｓｏｆｏｒｉｔｓｓｉｍｉｌａｒｓｔａｂｉｌｉｚｉｎｇｅｆｆｅｃｔｃｏｍｐａｒｅｄｗｉｔｈｔｈａｔｏｆｔｈｅｍｏｓｔｅｘｃｅｌｌｅｎｔｏｎｅ ｏｒｇａｎｏｔｉｎ .Ｂｙｍａｋｉｎｇｆｕｌｌｕｓｅｏｆｔｈｅｐｌｅｎｔｉｆｕｌａｎｔｉｍｏｎｙｒｅｓｏｕｒｃｅ ,ｄｅｖｅｌｏｐｉｎｇａｎｔｉｍｏｎｙｍ…     

A sectoral decomposition analysis of Turkish CO2 emissions over 1990–2007

At a time of increased international concern and negotiations for greenhouse gas emission reduction, country studies on the underlying effects of greenhouse gas emission growth gain importance. The case of Turkey is particularly interesting due to rapidly growing emissions, accompanied by a political will and actions to reduce the quick growth. The refined Laspeyres method is used in this study to identify factors that accelerate or reduce the increase in Turkish CO₂ emissions. A year-by-year decomposition over 1990-2007 is carried out at sectoral level based on disaggregated data that is consistent over time and consistent with international standards. Various interesting results on the underlying effects of sectoral emission growth are found. Valuable insights are gained into CO₂ impacts of sectoral policies including energy and emission intensities, fuel switching and activity changes. The results yield important hints for the planning of energy and climate policy.     

Forecasting based on sectoral energy consumption of GHGs in Turkey and mitigation policies

Recently, global warming and its effects have become one of the most important themes in the world. Under the Kyoto Protocol, the EU has agreed to an 8% reduction in its greenhouse gas (GHG) emissions by 2008–2012. The GHG emissions (total GHG, CO₂, CO, SO₂, NO₂, E (emissions of non-methane volatile organic compounds)) covered by the Protocol are weighted by their global warming potentials (GWPs) and aggregated to give total emissions in CO₂ equivalents. The main subject in this study is to obtain equations by the artificial neural network (ANN) approach to predict the GHGs of Turkey using sectoral energy consumption. The equations obtained are used to determine the future level of the GHG and to take measures to control the share of sectors in total emission. According to ANN results, the maximum mean absolute percentage error (MAPE) was found as 0.147151, 0.066716, 0.181901, 0.105146, 0.124684, and 0.158157 for GHG, SO₂, NO₂, CO, E, and CO₂, respectively, for the training data with Levenberg–Marquardt (LM) algorithm by 8 neurons. R² values are obtained very close to 1. Also, this study proposes mitigation policies for GHGs.     

A new method for estimating solar radiation from bright sunshine data

Daily values of H/H₀, the ratio of total horizontal radiation to that outside the atmosphere has been correlated with s/S, bright sunshine as a fraction of daylength for 3 yr measurements in Adana and Ankara, Turkey. Using a maximum-likelihood quadratic fit, we show that monthly averages s/S and its standard deviation σ_s/S can be used to estimate the monthly average H/H₀ as

H/H₀ = 0.204 + 0.758s/S − 0.250[s/S² + σ²_s/S.

Comparison of the estimations of the above equation with measurements from different regions of Turkey indicate that less than 5 per cent relative error is possible. A further correlation σ²_s/S with s/S makes it possible to estimate H/H₀ with just the knowledge of s/S.     

A new ship energy management algorithm to the smart electricity grid system

In this paper, a new energy management algorithm has been suggested for the ships connected with alternative energies considering the smart electricity grid features. The algorithm focuses on the use of optimum energy source on the shipboard based on the priorities of authorities such as the most economic, environmental, or both criteria at the ports. The algorithm is performed in MATLAB, and several case studies are simulated to validate the results. The 5 maritime nations, which are at different regions: United States, Belgium, Turkey, China, and Australia, are taken into account in the case studies. The actual data of a bulk carrier ship have been used to achieve tangible results in the simulations. The results of the case studies are compared to determine the changes of energy cost and released emission to meet demand of electricity on the ships. Capital cost of the proposed concept is also given to make an economic evaluation. The results show that the ship energy management algorithm provides the significant economic and environmental advantages. This paper aims to contribute to the importance of the ships in the smart electricity grid concept for the maritime and electricity sector representatives.