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| 1 | Magnetically treated water irrigation effect on turnip seed germination,seedling growth and enzymatic activities显示文摘Pre-sowing magnetic field seed treatment effects on biological characteristics of vegetables and crops have been studied well.However,studies reporting irrigation with magnetically treated water are scanty.Therefore,the effect of irrigation with magnetically treated water on turnip seed germination,seedling growth and enzymatic activities was evaluated.The tap water was treated at 211 mT for 30,45 and 60 min and used for irrigation of turnip seed and seedlings.Uniform and healthy turnip seed was sown under randomized complete block design(RCBD).The germination,emergence rate index,vigor index I and vigor index II increased up to 28.33%,11.54%,57.59%and 32.26%,respectively.The growth parameters such as seedling lengths,fresh&dry weights,chlorophyll content were also enhanced in response of irrigation with magnetically treated water.The seedlings irrigated with magnetically treated water showed 28.92%,11.36%and 14.76%higher protein content,alpha amylase and protease activities,respectively vs control.Results revealed that irrigation with magnetically treated water has potential to improve turnip germination,seedling growth and enzymatic activities and this study is also extendable to other vegetables and crops for the improvement of germination and growth. | Zia ul Haq Munawar Iqbal Yasir Jamil Hafeez Anwar Ayesha Younis Muhammad Arif M.Zeshan Fareed Fida Hussain | 2016 | Information Processing in Agriculture2016，3，2： | 5 |
| 2 | Water extractable plant nutrients in soils amended with cow manure co-composted with maple tree residues显示文摘Studies on the availability of plant nutrients in soils treated with manure co-composted feed-stocks are very rare.The present investigation aimed at studying the nutrient release pattern from three soils amended with maple tree leaves co-composted with cow manure.Soils were mixed with the compost at the rate of 20 t/hm^(2) and incubated at room temperature.Prior to incubation,plants residue samples were analyzed for total elemental concentrations(NO_(3),NH_(4),P,K,Ca,Mg,Na,Zn,Mn,Fe,Cu,Ni and Cd).Water extractability of nutrients from soils was affected by the type of soil and ratio of composted manure applied.Extractable NH_(4),P,K,Ca and Mg concentrations varied in the descending order of sandy clay,sandy loam and silt loam except NO_(3).The concentrations of P,K,Ca and Mg in the amended soils increased with the ratio of manure co-composted with leaf litter while those of NO_(3),NH_(4) and trace elements decreased.The residual nutrients in soil varied directly with their contents in the compost amendments.Co-composting improved the availability of nutrients in soils and this should be an ideal approach to managing the enormous waste generated from the livestock sector for restoring soil fertility. | Zobia Anwar Muhammad Irshad An Ping Farhan Hafeez Shao Yang | 2018 | International Journal of Agricultural and Biological Engineering2018，11，5： | 1 |
| 3 | Efficacy of steroids, cyclosporin and cyclophos-phamide in steroid resistant idiopathic nephrotic syndrome 显示文摘 | Hafeez F Ahmad T M Anwar S | 2005 | Journal of College of Physicians and Surgeons Pakistan2005，15，6： | 1 |
| 4 | Field evaluation of Eimeria tenella (local isolates) gametocytes vaccine and its comparative efficacy with imported live vaccine, LivaCox?显示文摘 | M. Irfan Anwar Masood Akhtar Iftikhar Hussain A. U. Haq Faqir Muhammad M. Abdul Hafeez M. Shahid Mahmood Saira Bashir | 2008 | Parasitology Research2008，，1： | 1 |
| 5 | Functioning uterus with absent cervix, short vagina and transverse septum 显示文摘 | Hafeez M Haleem S Anwar S | 2009 | J Coil Physicians Surg Pak2009，19，6： | 1 |
| 6 | Image-Based Automatic Energy Meter Reading Using Deep Learning显示文摘We propose to perform an image-based framework for electrical energy meter reading.Our aim is to extract the image region that depicts the digits and then recognize them to record the consumed units.Combining the readings of serial numbers and energy meter units,an automatic billing system using the Internet of Things and a graphical user interface is deployable in a real-time setup.However,such region extraction and character recognition become challenging due to image variations caused by several factors such as partial occlusion due to dust on the meter display,orientation and scale variations caused by camera positioning,and non-uniform illumination caused by shades.To this end,our work evaluates and compares the stateof-the art deep learning algorithm You Only Look Once(YOLO)along with traditional handcrafted features for text extraction and recognition.Our image dataset contains 10,000 images of electrical energymeters and is further expanded by data augmentation such as in-plane rotation and scaling tomake the deep learning algorithms robust to these image variations.For training and evaluation,the image dataset is annotated to produce the ground truth of all the images.Consequently,YOLO achieves superior performance over the traditional handcrafted features with an average recognition rate of 98%for all the digits.It proves to be robust against the mentioned image variations compared with the traditional handcrafted features.Our proposed method can be highly instrumental in reducing the time and effort involved in the currentmeter reading,where workers visit door to door,take images ofmeters and manually extract readings from these images. | Muhammad Imran Hafeez Anwar Muhammad Tufail Abdullah Khan Murad Khan Dzati Athiar Ramli | 2023 | Computers, Materials & Continua2023，，1： | 0 |
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