Two field experiments were conducted during the spring season 2020 in Karbala governorate to study the effect of irrigation systems, irrigation intervals, biofertilizers and polymers on some characteristics of vegetative growth and potato production. The results showed that there were significant differences in the values of the average plant height due to the effect of the double interference between the irrigation system and the improvers, The height of potato plant under any irrigation system was superior when adding conditioners compared to the control treatment, as it reached 48.56, 58.00 and 64.33cm when adding polymer, biofertilizer, and polymers+ biofertilizers, respectively compared with the control treatment of 44.64cm in the surf

Severe periodontitis is ranked as the sixth most prevalent disease affecting humankind, with an estimated 740 million people affected worldwide. The diagnosis of periodontal diseases mainly relies upon assessment of conventional clinical parameters. However, these parameters reflect past, rather than current, clinical status or future disease progression and, likely, outcome of periodontal treatment. Specific and sensitive biomarkers for periodontal diseases have been examined widely to address these issues and some biomarkers have been translated as point-of-care (PoC) tests. The aim of this review was to provide an update on PoC tests for use in the diagnosis and management of periodontal diseases. Among the PoC tests developed so

The adsorption of hexavalent chromium by preparing activated carbon from date seeds with zinc chloride as chemical activator and granular date seeds was studied in a batch system. The characteristics of date seeds and prepared activated carbon (ZAC) were determined and found to have a surface area 500.01 m²/g and 1050.01  m²/g , respectively and  iodine number of 485.78 mg/g and 1012.91  mg/g, respectively. The effects of PH value (2-12), initial sorbate concentration(50-450mg/L), adsorbent weight (0.004-0.036g) and contact time (30-150 min) on the adsorption process were studied . For Cr(VI) adsorption on ZAC, at 120 min time contact, pH solution 2 and 0.02  adsorbent  weight  will ach

antimicrobial solutions against Coliforms, E. coli O157: H7, yeasts and molds were evaluated by agar well diffusion method. Chitosan (CH) exhibited best antimicrobial activity against the treated microorganisms at concentration of (5%) with contact time for 6hrs at refrigeration temperature (4ÚC), zones of inhibition for (GA) and (CH) for each solution alone ranging from (0 to 10 mm), chitosan solution (CH) exhibited both antibacterial and antifungal activities, Gum Arabic washing solution showed significant antibacterial activity (P < 0.05) against the microorganisms at concentration (15%), without inhibitory effect against E. coli O157:H7 at concentration (10%), in the current study the results confirmed that (15%) (w/v) of GA and 5%

  The purpose of this research shed light on the analysis of the relationship between training needs and organizational commitment and the role of a variable contract psychological, and start search of a dilemma thought provoking fundamental questions revolve around the search was the answer to all those questions of tricks theoretical framework to the variables of research first and test models of the relationship and impact secondly During six hypotheses major, The objective of the research the impact of the factors that affect training needs in organizational commitment center the psychological contract, and applied research on a sample of 100 individuals working in the engineering department and maintenance at the D

Spelling correction is considered a challenging task for resource-scarce languages. The Arabic language is one of these resource-scarce languages, which suffers from the absence of a large spelling correction dataset, thus datasets injected with artificial errors are used to overcome this problem. In this paper, we trained the Text-to-Text Transfer Transformer (T5) model using artificial errors to correct Arabic soft spelling mistakes. Our T5 model can correct 97.8% of the artificial errors that were injected into the test set. Additionally, our T5 model achieves a character error rate (CER) of 0.77% on a set that contains real soft spelling mistakes. We achieved these results using a 4-layer T5 model trained with a 90% error inject