|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Comparison of rate of surgical wound infection, length of hospital stay and patient eonvenience in complicated appendicitis between pnmary clo- sure and delayed primary closure显示文摘 | Khan KI Mshmoed s Akmal M | 2012 | J Pak Med Assoc2012，62，6： | 1 |
| 2 | Role of prochylactic antibiotics in Milligan Morgan hemorrhoidectomy-a randomized control trial 显示文摘 | Khan KI Akmal M Waqas A | 2014 | Int J Surg2014，12，8： | 1 |
| 3 | A novel variant of GALC in a familial case of Krabbe disease:Insights from structural bioinformatics and molecular dynamics simulation显示文摘Krabbe disease or globoid cell leukodystrophy(GLD;MIM#245200)is a rare and fatal lysosomal storage disease with an autosomal recessive mode of inheritance that results from the deficiency of galactocerebrosidase(GALC;E.C.3.2.1.46),a lysosomal enzyme encoded by the GALC gene.1 GALC breaks down galactosylceramide,a cerebroside located mainly in the myelin sheath.Defects in GALC cause the accumulation of a cytotoxic metabolite,galactosylsphingosine or psychosine,which can be toxic to oligodendrocytes and Schwann cells.2 The failure to digest galactosylceramide triggers the formation of multi-nucleated globoid cells,causing severe demyelination,axonopathy,and neuronal death.3 The reported frequency of Krabbe disease is 1 in 100,000 live births with symptoms including irritability,loss of motor ability,spasticity,ataxia,visual dysfunction,seizures,andcognitive impairment. | Ikram Ullah Muhammad Waqas Muhammad Ilyas Sobia Ahsan Halim Akmal Ahmad Natalia Dominik Wahid Ullah Muhammad Abbas Muhammad Aamir Henry Houlden Stephanie Efthymiou Ajmal Khan Ahmed Al-Harrasi | 2023 | Genes & Diseases2023，10，6： | 0 |
| 4 | Sustainable food industrial waste management through single cell protein production and characterization of protein enriched bread显示文摘Production of single cell protein(SCP)from food waste is one of the promising approaches for excellent waste management.In the present study,SCP was produced through submerged fermentation using selected food wastes(banana peel,citrus peel,carrot pomace and potato peel).During process optimization,combinations of various temperature and nitrogen sources were studied for optimum SCP yield(g/100g).The results indicated that maximum SCP yield was obtained at 30℃ for 7 days on potato peels,whereas citrus and banana peels exhibited the lowest SCP yield at the same process conditions.The SCP compositional analysis indicated that the amount of non-essential amino acids was significantly higher than wheat flour.Furthermore,SCP enriched bread was prepared by adding SCP at different concentrations(0,4,8,and 12%).The organoleptic properties indicated that SCP addition up to 4%was acceptable to prepare protein enriched bread.Thus,SCP may be effectively used for food waste management and food security. | Muhammad Kashif Iqbal Khan Muhammad Asif Zafar Ullah Razzaq Akmal Nazir Abid Aslam Maan | 2022 | Food Bioscience2022，46，2： | 0 |
| 5 | Ensemble Deep Learning Framework for Situational Aspects-Based Annotation and Classification of International Student’s Tweets during COVID-19显示文摘As the COVID-19 pandemic swept the globe,social media plat-forms became an essential source of information and communication for many.International students,particularly,turned to Twitter to express their struggles and hardships during this difficult time.To better understand the sentiments and experiences of these international students,we developed the Situational Aspect-Based Annotation and Classification(SABAC)text mining framework.This framework uses a three-layer approach,combining baseline Deep Learning(DL)models with Machine Learning(ML)models as meta-classifiers to accurately predict the sentiments and aspects expressed in tweets from our collected Student-COVID-19 dataset.Using the pro-posed aspect2class annotation algorithm,we labeled bulk unlabeled tweets according to their contained aspect terms.However,we also recognized the challenges of reducing data’s high dimensionality and sparsity to improve performance and annotation on unlabeled datasets.To address this issue,we proposed the Volatile Stopwords Filtering(VSF)technique to reduce sparsity and enhance classifier performance.The resulting Student-COVID Twitter dataset achieved a sophisticated accuracy of 93.21%when using the random forest as a meta-classifier.Through testing on three benchmark datasets,we found that the SABAC ensemble framework performed exceptionally well.Our findings showed that international students during the pandemic faced various issues,including stress,uncertainty,health concerns,financial stress,and difficulties with online classes and returning to school.By analyzing and summarizing these annotated tweets,decision-makers can better understand and address the real-time problems international students face during the ongoing pandemic. | Shabir Hussain Muhammad Ayoub Yang Yu Junaid Abdul Wahid Akmal Khan Dietmar P.F.Moller Hou Weiyan | 2023 | Computers, Materials & Continua2023，，6： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员