Impact of environmental and geographical position on the chemometric classification of ethanol extracts from Isotoma longiflora leaves by E. Imelda, K. Khairan, R.R. Lubis, T. Karma, R. Idroes

“…Based on the cross-validation using linear discriminant analysis showed that the prediction model had a 100 percent accuracy. The present study thus revealed the effect of geographical location on the composition of bioactive compounds in Isotoma longiflora, suggesting the potential of chemometric techniques for quality control and assurance in traditional medicine.…”
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On the lidar-turbulence paradox and possible countermeasures by A. Peña, G. G. Yankova, V. Mallini

“…At 175 and 241 m, the prediction accuracy reduces, and better agreement is achieved within the highest mean wind speed ranges only. …”
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Network pharmacology and in silico investigation into the therapeutic potential of phytoconstituents of Peucedanum ostruthium as anti-tubercular agents by Neeru Bhanwala, Raunak Katiyar, Sumit Kumar, Ashok K. Datusalia, Gopal L. Khatik

“…The phytoconstituents of P. ostruthium were studied using Swiss Target Prediction to determine the target genes. The DisGeNET datasets were used to extract genes and variations associated with TB. …”
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Rapid Detection of Astaxanthin in Antarctic Krill Meal by Computer Vision Combined with Convolutional Neural Network by Quantong ZHANG, Yao ZHENG, Liu YANG, Shuaishuai ZHANG, Quanyou GUO

“…For model validation, the relative errors ranged from 0.10% to 6.46%, indicating small deviations between the predictions and the observations. The astaxanthin content prediction model demonstrated high accuracy, enabling quick and nondestructive detection of astaxanthin content in krill meal samples.…”
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Cytokine and Chemokine Profile in Patients with Multiple Myeloma Treated with Bortezomib by Paweł Robak, Edyta Węgłowska, Izabela Dróżdż, Damian Mikulski, Dariusz Jarych, Magdalena Ferlińska, Ewa Wawrzyniak, Małgorzata Misiewicz, Piotr Smolewski, Wojciech Fendler, Janusz Szemraj, Tadeusz Robak

“…In conclusion, distinct cytokines are involved in the pathogenesis of MM and may play a prominent role in the prediction of treatment response. However, a single measurement of serum cytokines should be interpreted with caution and further studies are needed.…”
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Association between bone mineral density and scoliosis: a two-sample mendelian randomization study in european populations by Fangjun Yang, Jiantao Wen

“…Conclusion In conclusion, the present study demonstrates that the causal role of genetic prediction of scoliosis increases with decreasing lumbar BMD. …”
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Innovative epitopes in Staphylococcal Protein-A an immuno-informatics approach to combat MDR-MRSA infections by Pengjun Zhou, Pengjun Zhou, Xing Shi, Jinquan Xia, Yifei Wang, Shaowei Dong

“…B-cell epitopes were predicted using the BepiPred tool. Predicted epitopes underwent docking studies with HLA molecules to evaluate binding properties. …”
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Analysis and Identification of Factors Influencing the Survival of Burn Injury Patients with an Artificial Intelligence Approach by Sara Hashemi, Shahla Faramarzi, Laya Rahmani Pirouz, Azita Yazdani

“…Early detection and recognition of these risk factors are essential, and the provision of predictive models can be beneficial. This research was conducted with the aim of reviewing the effectiveness of artificial intelligence in predicting survival in burn patients. …”
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Investigation of the influence of the heterogeneous structure of concrete on its strength by V.M. Volchuk, M.A. Kotov, Ye G. Plakhtii, O.A. Tymoshenko, O.H. Zinkevych

“…The proposed approach can be interpreted as an express method of predicting the strength of concrete mixture, which is implemented without the use of special equipment. …”
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Crop water productivity assessment and planting structure optimization in typical arid irrigation district using dynamic Bayesian network by Yantao Ma, Jie Xue, Xinlong Feng, Jianping Zhao, Junhu Tang, Huaiwei Sun, Jingjing Chang, Longke Yan

“…The results demonstrate that the combination of TimeGAN and DBN better improves the accuracy of the model for the dynamic prediction, particularly for short-term predictions with 4 years as the optimal timescale (R2 > 0.8). …”
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Traffic flow modelling of vehicles on a six lane freeway: Comparative analysis of improved group method of data handling and artificial neural network model by Isaac Oyeyemi Olayode, Alessandro Severino, Frimpong Justice Alex, Elmira Jamei

“…The primary objective of this study was to evaluate the predictive accuracy and efficacy of both models in replicating complex traffic patterns and to provide insights into their suitability for real-time traffic flow applications. …”
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Intra-abdominal pressure and residual renal function decline in peritoneal dialysis: a threshold-based investigation by Jingjing Zhang, Lei Song, Zhongwei Ma, Lina Sun, Xiaoqing Wang, Duanyan Liu, Feng Huang, Yulin Man

“…Furthermore, an IAP ≥15.65 cmH2O was a robust discriminator for the prediction of the rate of RRF decline.Conclusion Patients in the high IAP group experienced a more rapid decline in RRF. …”
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Towards compressive and tensile strengths of hybrid steel and PVA fibre-reinforced cementitious composites: Experimental and analytical by Gang Chen, Mingyan Lv, Haitang Zhu, Jianwen Zhang, Le Zhang

“…In addition, currently available analytical/statistical models for predicting the strength of HFRCCs are far from satisfactory and, therefore, need to be improved. …”
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Validation of mortality risk scores after esophagectomy by Sabine Schiefer, Nerma Crnovrsanin, Ingmar F. Rompen, Nicolas Jorek, Mohammed Al-Saeedi, Thomas Schmidt, Henrik Nienhüser, Leila Sisic

“…However, due to their limited predictive ability, improvements are needed to apply these strategies effectively in clinical practice.…”
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Digital mapping of soil organic carbon in a plain area based on time-series features by Kun Yan, Decai Wang, Yongkang Feng, Siyu Hou, Yamei Zhang, Huimin Yang

“…This study focused on the DSM of SOC in Fengqiu County, China, using terrain, climate, single-time ecological factors, and time-series features of time-series ecological factors as environmental covariates to investigate whether time-series environmental covariates could improve the accuracy in a plain area. SOC prediction models were established using random forests (RF), backpropagation neural networks (BP), and support vector machines (SVM). …”
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Formation Mechanism and the Height of the Water-Conducting Fractured Zone Induced by Middle Deep Coal Seam Mining in a Sandy Region: A Case Study from the Xiaobaodang Coal Mine by Xiaoshen Xie, Enke Hou, Shuangming Wang, Xueyang Sun, Pengfei Hou, Shibin Wang, Yongli Xie, Yongan Huang

“…This research can provide significant theoretical insights for the prediction of the WCFZ, enabling the prevention of water hazards on mine roofs and assisting with water resources protection.…”
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Fluidization of fine coal particles in an ultrasound enhanced gas-solid fluidized bed by Sayuri Naicker, Neeraj Kuarsingh, Milan Carsky, David Lokhat

“…The addition of the ultrasound correction factor was able to improve the prediction capability of the model that was developed for the minimum fluidization velocity. …”
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Study on Overburden Rock Movement and Stress Distribution Characteristics under the Influence of a Normal Fault by Quansen Wu, Peng Kong, Quanlin Wu, Xinggang Xu, Xingyu Wu, Tao Guo

“…The research results in this paper provide a scientific basis for the classification, prediction, and prevention of rock bursts under similar geological conditions.…”
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In-depth characterization of miRNome in papillary thyroid cancer with BRAF V600E mutation by Azliana Mohamad Yusof, Francis Yew Fu Tieng, Rohaizak Muhammad, Shahrun Niza Abdullah Suhaimi, Isa Mohamed Rose, Sazuita Saidin, Rahman Jamal, Imilia Ismail, Nurul-Syakima Ab Mutalib

“…MiRNAs differentially expressed between BRAF V600E-positive and BRAF V600E-negative PTC tissues were validated in silico using The Cancer Genome Atlas (TCGA) THCA datasets containing 420 samples. MiRNA target prediction and pathway enrichment analysis were performed to identify biological pathways altered in this cancer. …”
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Temporal Forecasting of Distributed Temperature Sensing in a Thermal Hydraulic System With Machine Learning and Statistical Models by Stella Pantopoulou, Matthew Weathered, Darius Lisowski, Lefteri H. Tsoukalas, Alexander Heifetz

“…We treat each gauge of a FOS as an independent temperature sensor. We first study prediction of DTS time series using Vanilla LSTM and ARIMA models trained on prior history of the same FOS that is used for testing. …”
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