• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.851-860
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• 2021

The Knowledge Transfer (KT) for higher education institutions (HEIs) is boundless. Still and all, the members of the staff affiliated with these institutions do recognize an array of hitches in relation to KT practices. The study in question underscores social interactions, training, and Information and Communication Technology (ICT) as the primary barriers and treats them as the independent variables of the study. The study posits that inadequate management of the above-mentioned barriers would impact effective KT unfavorably. Besides, putting forth some striking solutions needed to fix the obstructions that hamper the adequate management of the KT exercises is another aim of the study. For data collection purposes, the study picks out higher education institutions (public) of the Quetta district. The reckoned sample size is 317 subjects. The research type that has been used is cross-sectional research and, in this context, the cross-sectional explanatory sequential design has been used. Concerning the findings of the paper, the results of PLS-SEM show positive and significant relationships of social interaction and training with knowledge transfer, while ICT shows an insignificant positive relationship with the knowledge transfer. The most influencing factor for the knowledge transfer is social interaction as suggested by social interaction theory.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.294-302
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• 2022

Detection of fake news is a complex and a challenging task. Generation of fake news is very hard to stop, only steps to control its circulation may help in minimizing its impacts. Humans tend to believe in misleading false information. Researcher started with social media sites to categorize in terms of real or fake news. False information misleads any individual or an organization that may cause of big failure and any financial loss. Automatic system for detection of false information circulating on social media is an emerging area of research. It is gaining attention of both industry and academia since US presidential elections 2016. Fake news has negative and severe effects on individuals and organizations elongating its hostile effects on the society. Prediction of fake news in timely manner is important. This research focuses on detection of fake news spreaders. In this context, overall, 6 models are developed during this research, trained and tested with dataset of PAN 2020. Four approaches N-gram based; user statistics-based models are trained with different values of hyper parameters. Extensive grid search with cross validation is applied in each machine learning model. In N-gram based models, out of numerous machine learning models this research focused on better results yielding algorithms, assessed by deep reading of state-of-the-art related work in the field. For better accuracy, author aimed at developing models using Random Forest, Logistic Regression, SVM, and XGBoost. All four machine learning algorithms were trained with cross validated grid search hyper parameters. Advantages of this research over previous work is user statistics-based model and then ensemble learning model. Which were designed in a way to help classifying Twitter users as fake news spreader or not with highest reliability. User statistical model used 17 features, on the basis of which it categorized a Twitter user as malicious. New dataset based on predictions of machine learning models was constructed. And then Three techniques of simple mean, logistic regression and random forest in combination with ensemble model is applied. Logistic regression combined in ensemble model gave best training and testing results, achieving an accuracy of 72%.

• Natural Product Sciences
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• v.28 no.3
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• pp.121-129
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• 2022

Despite considerable efforts, cancer remains an aggressive killer worldwide. Chemotherapeutic drugs that are currently in use lead to destructive side effects and have not succeeded in fulfilling expectations. For centuries, medicinal plants are used for treating various diseases and are also known to have anticancer activity. The main aim of this research was to evaluate antiproliferative activity of saffron, clove, fenugreek, and green tea on Vero and MDA-MB-231 cell lines and to subsequently analyze the effect of these extracts on IRAK-4, TAK1, IKK-alpha, IKK-beta, NF-Kappa B, IRF3, IRF7 genes in Toll Like Receptors (TLRs) pathway. Antiproliferative assay was done by Neutral Red Dye uptake assay. Methanolic extract of green tea was found to be most effective against both cell lines as IC₅₀ was achieved at least concentration of the extract. For molecular studies, MDAMB-231 cells were sensitized with methanolic extract of green tea at same IC₅₀, and RT-PCR was performed to determine the relative expression of genes. Expression of IRAK-4, TAK1, IKK-beta, NF-Kappa B, IRF3 genes was down regulated and IRF7 and IKKalpha was upregulated. Green tea has a potential cytotoxic effect on both cell lines which was demonstrated by its effect on the expression of (TLRs) pathway genes.

• The korean journal of orthodontics
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• v.53 no.5
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• pp.298-306
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• 2023

Objective: Pain following the insertion of separators and archwires varies with age, sex, race, ethnicity, threshold, and health status. This study aimed to evaluate the characteristics of pain in orthodontic patients after the insertion of elastomeric separators, its effects on daily life, and its association with age and sex in a population not previously studied in this regard. Methods: A cross-sectional study of 130 patients undergoing orthodontic treatment included collecting data on demographics, pain experienced following the placement of separators, time of onset, duration, characteristics, change in dietary pattern or chewing side, intake of analgesics, and severity of pain on the Wong Baker's scale. The results are reported as counts and percentages. Associations between sex and age were evaluated using Pearson's chi-square test. Results: Among the 130 patients, 56.2% were 9-20 years old, 63.8% experienced pain following the insertion of separators, 22.9% had their first episode of pain at 4 hours, 56.6% experienced intermittent pain, and 37.3% experienced discomfort; 18.1% males and 81.9% females experienced pain following the insertion of separators. Pearson's chi-square test showed a significant association between pain and sex (P = 0.04). Most patients (37.3%) reported "hurts little more" for pain intensity on Wong Baker's scale and 21.7% reported all four quadrants as sites of pain. Conclusions: The pain experienced after separator insertion was associated with sex and age. Females experienced more pain than males and patients between the age range of 21 and 36 years suffered more pain during mastication than between 9 and 20 years old.

• Environmental Engineering Research
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• v.25 no.1
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• pp.88-95
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• 2020

An investigation of rare metals recovery from LiNi_xCo_yMn_zO₂ cathode material of the end-of-life lithium-ion batteries is presented. To determine the influence of reductant on the leach process, the cathode material (containing Li 7.6%, Co 20.4%, Mn 19.4%, and Ni 19.3%) was leached in H₂SO₄ solutions either with or without H₂O₂. The optimal process parameters with respect to acid concentration, addition dosage of H₂O₂, temperature, and the leaching time were found to be 2.0 M H₂SO₄, 4 vol.% H₂O₂, 70℃, and 150 min, respectively. The yield of metal values in the leach liquor was > 99%. The leach liquor was subsequently treated by precipitation techniques to recover nickel as Ni(C₄H₇N₂O₂)₂ and lithium as Li₂CO₃ with stoichiometric ratios of 2:1 and 1.2:1 of dimethylglyoxime:Ni and Na₂CO₃:Li, respectively. Cobalt was recovered by solvent extraction following a 3-stage process using Na-Cyanex 272 at pH_eq ~5.0 with an organic-to-aqueous phase ratio (O/A) of 2/3. The loaded organic phase was stripped with 2.0 M H₂SO₄ at an O/A ratio of 8/1 to yield a solution of 114 g/L CoSO₄; finally recovered CoSO₄.xH₂O by crystallization. The process economics were analyzed and found to be viable with a margin of $476 per ton of the cathode material.