In Vivo RNA Delivery to Hematopoietic Stem and Progenitor Cells via Targeted Lipid Nanoparticles by Shi, Dennis, Toyonaga, Sho, Anderson, Daniel G

“…However, these therapies have several limitations owing to the manufacturing complexities and toxicity resulting from required conditioning regimens. Here, we developed a c-kit (CD117) antibody-targeted lipid nanoparticle (LNP) that, following a single intravenous injection, can deliver RNA (both siRNA and mRNA) to HSCs in vivo in rodents. …”
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Disposition kinetics of tylosin administered intravenously and intramuscularly in Desert Sheep and Nubian Goats by Taha, A.A., Elsheikh, H.A., Khalafalla, A.E., Osman, I. A. M., Abdullah, A. Salam

“…The present study has shown that, despite the significant differences in some of the drug pharmacokinetic parameters between sheep and goats for the i.v. route, identical intravenous and intramuscular dosage regimens of tylosin may be recommended for the two species.…”
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Targeted hematopoietic stem cell depletion through SCF-blockade by Chan, Yan Y., Ho, Pui Y., Dib, Carla, Swartzrock, Leah, Rayburn, Maire, Willner, Hana, Ko, Ethan, Ho, Katie, Down, Julian D., Wilkinson, Adam C., Nakauchi, Hiro, Denis, Morgane, Cool, Taylor, Czechowicz, Agnieszka

“…Further, to augment efficacy, combination regimens were also explored. Results We confirm that only ACK2 inhibits SCF binding fully and prevents HSC proliferation in vitro. …”
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Precious metal price prediction using deep neural networks by Peng, Zhiling

“…Then, four traditional regression methods in machine learning are used to train and evaluate the same dataset of the gold price, including the linear regression, support vector regression (SVR), decision tree regression and the random forest algorithm. …”
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Evaluating machine learning for predicting youth suicidal behavior up to 1 year after contact with mental-health specialty care by O’Reilly, LM, Fazel, S, Rickert, ME, Kuja-Halkola, R, Cederlöf, M, Hellner, C, Larsson, H, Lichtenstein, P, D’Onofrio, BM

“…Logistic regression is not clearly worse than machine-learning approaches. …”

一首 "长恨" "长" 又 "恨" ：《长恨歌》作为 "新乐府" 的解读 = The eternalised hatred of ‘The Song of Everlasting Hatred’ : from the perspective of the ‘YueFu’ movement... by 曾思慧 Chew, Si Hui

“…The Song of Everlasting Regret is an artistic portrayal of true love. Although the language used was purposed to be easily understood and entertaining, the last four sentences still puzzled many till this day. …”
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Using a machine learning approach for property market analysis by Xu, Mengxing

“…In the end, the predictions with regression models were conducted. Linear regression fit the Hong Kong property market best, while the K-Nearest Neighbors with k equals 3 performs best in Singapore property market. …”
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Common risk factors in the returns on stocks : empirical evidence from Singapore. by Kurniawan, Morina., Ng, Chin Thin.

“…Regression of excess stock returns on the term and default factors, captures very little variation in the returns of stocks. …”
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Genomic profiling of mycobacterium tuberculosis strains, Myanmar by Aung, Htin Lin, Nyunt, Wint Wint, Fong, Yang, Biggs, Patrick J., Winkworth, Richard C., Lockhart, Peter J., Yeo, Tsin Wen, Hill, Philip C., Cook, Gregory M., Aung, Si Thu

“…Introducing new oral drugs to replace those currently used in treatment regimens for multidrug-resistant TB will also be useful for treating TB in Myanmar.…”
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Estimation of diaphragm wall deflections for deep braced excavation in anisotropic clays using ensemble learning by Zhang, Runhong, Wu, Chongzhi, Goh, Anthony Teck Chee, Böhlke, Thomas, Zhang, Wengang

“…Then the results of ELMs were compared with conventional soft computing methods such as Decision Tree Regression (DTR), Multilayer Perceptron Regression (MLPR), and Multivariate Adaptive Regression Splines (MARS). …”
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Behind every domain there is a shift: adapting distortion-aware vision transformers for panoramic semantic segmentation by Zhang, J, Yang, K, Shi, H, ReiB, S, Peng, K, Ma, C, Fu, H, Torr, PHS, Wang, K, Stiefelhagen, R

“…Extensive experiments are conducted, which cover indoor and outdoor scenarios, and each of them is investigated with Pin2Pan and Syn2Real regimens. Trans4PASS+ achieves state-of-the-art performances on four domain adaptive panoramic semantic segmentation benchmarks. …”

Knowledge and practice regarding medication use among elderly with chronic diseases in Felda Tembangau 2, Kemayan, Pahang by Farid, Aina Natasha Mohd

“…The elderly population, defined as those aged 60 and above, faces unique challenges in managing chronic diseases due to physiological changes, limited access to healthcare information, and barriers in understanding and adhering to medication regimens. The aim of this study was to determine the levels of knowledge and practice regarding medication use among elderly with chronic diseases in FELDA Tembangau 2, Kemayan, Pahang and to explore the correlation between these two variables. …”
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Dynamic physiological imaging and quantification of tumor microcirculation by Koh, Tong San.

“…These include a generalized mamillary distributed- parameter model for capillary-tissue exchange, a regression approach to regularization using both conventional and generalized Singular Value Decomposition (SVD), and the use of piecewise continuous regression models for the automatic estimation of bolus arrival times. …”
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NBA Sleep Tracking Data Imputation by Licht, Joseph D.

“…Motivated by existing work on time series data imputation, four main techniques are evaluated: K-Nearest Neighbors Regression, Linear Interpolation, Linear Regression, and Quadratic Regression. …”
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Performance evaluation of SAFIS for benchmark problems by Sinara Vijayan.

“…The two regression problems considered here are Auto-mpg and California Housing. …”
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Orthogonal vs. uncorrelated least squares discriminant analysis for feature extraction by Nie, Feiping, Xiang, Shiming, Liu, Yun, Hou, Chenping, Zhang, Changshui

“…In this paper, a new discriminant analysis for feature extraction is derived from the perspective of least squares regression. To obtain great discriminative power between classes, all the data points in each class are expected to be regressed to a single vector, and the basic task is to find a transformation matrix such that the squared regression error is minimized. …”
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Sustainable energy management: Artificial intelligence-based electricity consumption prediction in limited dataset environment for industry applications by Chuan, Zun Liang, Tan, Lit Ken, Wee, Angel Chi Chyin, Yim Hin, Tham, Shao, Jie Ong, Jia, Yi Low, Chong, Yeh Sai

“…This study aimed to develop a modified stacked ensemble multivariable Artificial Intelligence (AI)-based predictive algorithm, specifically Stacked Simple Linear Regression and Multiple Linear Regression (SLR-MLR), and Stacked Simple Linear Regression and Multiple Non-Linear Regression (SLR-MNLR) utilizing the Cross Industry Standard Process for Data Mining (CRISP-DM) data science methodology. …”
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Exchange rate prediction based on machine learning methods by Hong, Yuyue

“…Keywords: Exchange Rate, Time Series Forecasting, Machine Learning, Neural Networks, Random Forest, Support Vector Regression, Random Vector Functional Link Network…”
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Prediction of stock price direction with machine learning models by Kant Kaw Khin

“…The ML models used in this paper are Random Forest (RF) Classification, XGBoost Classification, Long Short-Term Memory (LSTM) Classification and LSTM Regression model. The classification models are used to predict price stock direction, while the regression model is used to predict closing prices. …”
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Threat intelligence using machine learning packet dissection by Sowinski-Mydlarz, Viktor, Li, Jun, Ouazzane, Karim, Vassilev, Vassil

“…Four machine learning models, i.e., Neural Networks, Support Vector Machines, Logistic Regression and Linear Regression, are applied respectively to calculate the probability of suspicious packets. …”
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