The research was conducted at Faculty of Agriculture, Damascus University/
Syria, with the help of Scientific Agricultural Research Center in Latakia during
2013 and 2014 seasons. Three rootstocks were used i.e. Sour orange, citrumelo
and troyer c
itrange, to study some factors affecting the success of micrografting
technique (concentrations and periods of sterilization, rootstock, shoot tip size, type
of nutritive medium and the grafting method). The nutritive medium was prepared,
and the shoot tips was isolated from Navel orange source, then the micrografting
was done for the three rootstocks.
This research has concentrated on the economical properties and the
profits resulting from Carnation plantation in Latakia Governorate
studying the productivity cost and the indicatives of economical
feasibility based on data and statements gather
ed from site of
research(Arab Almelik),and relying, in determining wages and
materials costs, on the current market prices in 2015.
we havesought to achieve the following targetsStudying the reality
the production of Ornamental Plants in the Syria, in general,
andLatakia Governorate, inparticular,and Calculating
The Ornamental Plants (Altlfona) of important economic cultivations were introduced to the recently Syrian agriculture "as one of the most important alternative cultivations, especially" in the coastal strip, as a prospective areas for the spread of
these agriculture This research has concentrated on the economical properties and the profits resulting from Carnation plantation in Latakia Governorate studying the productivity cost and the indicatives of economical feasibility based on data and statements gathered from site of research (Arab Almelik),and relying, in determining wages and materials costs, on the current market prices in 2015.
In this research, we have sought to achieve the following targets:
- Studying the reality the production of Ornamental Plants in the Syria, in general, and Latakia Governorate, in particular, during the period from 2005 to 2013.
- Calculating the productivity cost of Altlfona plants in Latakia Governorate.
- Making an economical evaluation of Altlfona plants in Latakia Governorate.
In conclusion, we have reached the following result:
• Totally achieved net profit per annum from one greenhouse of Altlfona plantation amounted to 668212.7Syrian Pounds.
• Profitability Coefficient in proportion to invested capital has amounted to 27.19% and to 49.67% in proportion to the productivity cost.
• Time indicator of Capital recovery for Altlfona has amounted to 3.67 years.
نفذت تجارب مخبرية بهدف معرفة تأثير مستخلص من ريزومات، سنابل مع بذور، أوراق من
في إنبات بذور سبعة أنواع من النباتات المزروعة في أطباق Sorghum halepense L. نباتات الرزين
الإنبات (الفليفلة، الخيار، الكوسا، البندورة، الفاصولياء، القمح، الذرة الصفراء).
تبين من النتائج أن
إضافة ١٠ أو ١٥ أو ٢٠ ملليترًا من رشاحة هذه المستخلصات إلى الأطباق عند الزراعة يمنع إنبات
بذور الأنواع التالية: الفاصولياء، الفليفلة وفقط عند استخدام ٢٠ ملليترًا لأنواع الخيار والكوسا
والبندورة. كما يخفض نسبة الإنبات في الأطباق التي زرعت ببذور القمح، الذرة الصفراء.
Since their inception, transformer-based language models have led to impressive performance gains across multiple natural language processing tasks. For Arabic, the current state-of-the-art results on most datasets are achieved by the AraBERT languag
e model. Notwithstanding these recent advancements, sarcasm and sentiment detection persist to be challenging tasks in Arabic, given the language's rich morphology, linguistic disparity and dialectal variations. This paper proffers team SPPU-AASM's submission for the WANLP ArSarcasm shared-task 2021, which centers around the sarcasm and sentiment polarity detection of Arabic tweets. The study proposes a hybrid model, combining sentence representations from AraBERT with static word vectors trained on Arabic social media corpora. The proposed system achieves a F1-sarcastic score of 0.62 and a F-PN score of 0.715 for the sarcasm and sentiment detection tasks, respectively. Simulation results show that the proposed system outperforms multiple existing approaches for both the tasks, suggesting that the amalgamation of context-free and context-dependent text representations can help capture complementary facets of word meaning in Arabic. The system ranked second and tenth in the respective sub-tasks of sarcasm detection and sentiment identification.