Effect of Species Composition on Growth and Yield in Mixed Beech–Coniferous Stands by Avram Cicșa, Gheorghe-Marian Tudoran, Maria Cicșa (Boroeanu), Alexandru-Claudiu Dobre, Gheorghe Spârchez

“…Under the same site conditions, we generated models to determine, for each species (spruce, fir, and beech), the main parameters of the site index, including mean height, dominant height, standing volume yield, and mean annual volume increment for different compositional species proportions (p_sp) and categories of proportions (i.e., low p_sp, between 10 and 50%, and high p_sp, ranging between 60 and 90%). …”
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Elliptical vibration chiseling: a novel process for texturing ultra-high-aspect-ratio microstructures on the metallic surface by Zhiwei Li, Jianfu Zhang, Zhongpeng Zheng, Pingfa Feng, Dingwen Yu, Jianjian Wang

“…The experimental results also verify the accuracy of the developed surface generation model of microstructures. Finally,the effects of elliptical trajectory, depth of cut, tool shape, and tool edge radius on the surface generation of micro ribs have been discussed.…”
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Assessing the impact of drum drying on the nutritional properties of pineapple pomace-fortified crispy mushroom sheets by Phunsiri Suthiluk, Phunsiri Suthiluk, Matchima Naradisorn, Matchima Naradisorn, Sutthiwal Setha, Sutthiwal Setha

“…Moreover, the experimental values of the dependent variables closely matched the predicted values, indicating the reliability of the generated models. It was evident that both steaming temperature and rotation speed significantly influenced DPPH, FRAP, and SDF contents and the optimized conditions could be employed for the production of functional crispy mushroom sheets. …”
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Performance metrics for models designed to predict treatment effect by C. C. H. M. Maas, D. M. Kent, M. C. Hughes, R. Dekker, H. F. Lingsma, D. van Klaveren

“…In a simulation study, the metric values of deliberately “perturbed models” were compared to those of the data-generating model, i.e., “optimal model”. To illustrate these performance metrics, different modeling approaches for predicting treatment effect are applied to the data of the Diabetes Prevention Program: 1) a risk modelling approach with restricted cubic splines; 2) an effect modelling approach including penalized treatment interactions; and 3) the causal forest. …”
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On the Difference between the Information Bottleneck and the Deep Information Bottleneck by Aleksander Wieczorek, Volker Roth

“…Combining the information bottleneck model with deep learning by replacing mutual information terms with deep neural nets has proven successful in areas ranging from generative modelling to interpreting deep neural networks. …”
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Aspectos ecológicos da aroeira (Myracrodruon urundeuva Allemão- Anacardiaceae): fenologia e germinação de sementes Ecological aspects of aroeira (Myracrodruon urundeuva Allemão - A... by Yule Roberta Ferreira Nunes, Marcílio Fagundes, Hisaias de Souza Almeida, Maria das Dores Magalhães Veloso

“…Therefore, basic studies on the ecology of threatened forest species are essential to generate models and mechanisms for the management and restoration of their natural populations.…”
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Development and validation of prediction models for poor sleep quality among older adults in the post-COVID-19 pandemic era by Min Du, Manchang Li, Xuejun Yu, Shiping Wang, Yaping Wang, Wenxin Yan, Qiao Liu, Min Liu, Jue Liu

“…Five prediction models with 10-fold cross validation including the Least Absolute Shrinkage and Selection Operator (LASSO), Stochastic Volatility Model (SVM), Random Forest (RF), Artificial Neural Network (ANN), and XGBoost model based on the area under curve (AUC) were used to develop and validate predictors.Results The prevalence of poor sleep quality (PSQI >7) was 30.69% (3117/10,156). Among the generated models, the LASSO model outperformed SVM (AUC 0.579), RF (AUC 0.626), ANN (AUC 0.615) and XGBoost (AUC 0.606), with an AUC of 0.7. …”
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Learning From Few Cyber-Attacks: Addressing the Class Imbalance Problem in Machine Learning-Based Intrusion Detection in Software-Defined Networking by Seyed Mohammad Hadi Mirsadeghi, Hayretdin Bahsi, Risto Vaarandi, Wissem Inoubli

“…We propose custom deep learning architectures based on GANs and Siamese Neural Networks for generative modeling and similarity-based intrusion detection. …”
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Modeling homophily in dynamic networks with application to HIV molecular surveillance by Victor DeGruttola, Masato Nakazawa, Tuo Lin, Jinyuan Liu, Ravi Goyal, Susan Little, Xin Tu, Sanjay Mehta

“…Our simulation studies demonstrated the validity of our approach for modeling homophily, by showing that the estimates it produced matched the specified values of the statistical network generating model. Conclusions Our novel methods provide a simple and flexible statistical network-based approach for modeling the growth of viral (or other microbial) genetic clusters from linkage to new infections based on genetic distance.…”
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PENGEMBANGAN INFRASTRUKTUR JALAN SEBAGAI IMPLEMENTASI RENCANA TATA RUANG WILAYAH KABUPATEN KETAPANG by Ferry Juniardi, Heri Azwansyah

“…This study requires data of movement of vehicles and the road network, obtained from the relevant agencies/departments and field survey. Vehicles trip generation models influenced by number of health facilities (X3), while pull models of vehicle movement influenced by number of residents (X1) and number of health facilities ( X3). …”
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Analysis of the Technical Accuracy of a Patient-Specific Stereotaxy Platform for Brain Biopsy by Marcel Müller, Dirk Winkler, Robert Möbius, Michael Werner, Welf-Guntram Drossel, Erdem Güresir, Ronny Grunert

“…The frames underwent an autoclave sterilization process prior to rescanning. The scan-generated models were compared with the planned CAD models and the deviation of the planned target points in the XY-plane, Z-direction and in the resulting direction were determined. …”
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Granite magmatism and mantle filiation by M. Pichavant, A. Villaros, J. A.-S. Michaud, B. Scaillet

“…<p>Current granite magma generation models essentially reduce to two groups: (1) intra-crustal melting and (2) basaltic origin. …”
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Use of routine HIV testing data for early detection of emerging HIV epidemics in high-risk subpopulations: A concept demonstration study by Houssein H. Ayoub, Susanne F. Awad, Laith J. Abu-Raddad

“…Using hypothesis-generation modeling, we aimed to investigate and demonstrate the concept of using routine HIV testing data to identify and characterize hidden epidemics in high-risk subpopulations. …”
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Implementing OpenMP 4.0 for the NVIDIA PTX architecture in GCC compiler by A. V. Monakov, V. A. Ivanishin

“…To implement execution of one logical OpenMP thread by a group of PTX threads we developed a new code generation model that allows to keep all PTX threads active, have their local state (register contents) mirrored, and have side effects from atomic instructions and system calls such as malloc happen only once per warp. …”
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Spatiotemporal distribution prediction of gas concentration based on GCN-GRU by QIN Jiaxin, GE Shuwei, LONG Fengqi, ZHANG Yongqian, LI Xue

“…Through sequence-to-sequence based models and autoencoders, GRU generates model prediction results. The experimental results show the following points. ① The GCN-GRU model can accurately predict the overall trend of gas concentration changes. …”
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Support Vector Machine Berbasis Feature Selection Untuk Sentiment Analysis Kepuasan Pelanggan Terhadap Pelayanan Warung dan Restoran Kuliner Kota Tegal by Oman Somantri, Dyah Apriliani

“…The purpose of this research is to optimize the generated model by applying feature selection using Informatioan Gain (IG) and Chi Square algorithm on the best model produced by SVM on the classification of customer satisfaction level based on culinary restaurants at Tegal City so that there is an increasing accuracy from the model. …”
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An Insight into the Structural Requirements and Pharmacophore Identification of Carbonic Anhydrase Inhibitors to Combat Oxidative Stress at High Altitudes: An In-Silico Approach by Amena Ali, Abuzer Ali, Musarrat Husain Warsi, Mohammad Akhlaquer Rahman, Mohamed Jawed Ahsan, Faizul Azam

“…The coefficient of determination for both the training and test sets were statistically significant in the generated model. The best QSAR model was chosen based on the values of R² (0.8757) and Q² (0.7888). …”
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Predicting future depressive episodes from resting-state fMRI with generative embedding by Herman Galioulline, Stefan Frässle, Samuel J. Harrison, Inês Pereira, Jakob Heinzle, Klaas Enno Stephan

“…However, functional magnetic resonance imaging (fMRI) has received very little attention for this purpose so far.Here, we explored the utility of generative models (i.e. different dynamic causal models, DCMs) as well as functional connectivity (FC) for predicting future episodes of depression in never-depressed adults, using a large dataset (N = 906) of task-free (''resting state'') fMRI data from the UK Biobank (UKB). …”
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A Data Science Approach to Predictive Analytic Research and Knowledge Translation by Stacey Fisher, Robert Talarico, Yulric Sequeira, Carol Bennett, Sarah Spruin, Amy Hsu, Peter Tanuseputro, Doug Manuel

“…Results Algorithm development involves variable pre-specification and documentation of model variables, followed by creation of data preprocessing code to generate model variables from the study dataset. Preprocessing uses algorithm specification documentation and a function library, building upon and integrating with existing algorithms when possible to preventing code duplication. …”
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Preeminently Robust Neural PPG Denoiser by Ju Hyeok Kwon, So Eui Kim, Na Hye Kim, Eui Chul Lee, Jee Hang Lee

“…By casting the noise reduction problem into a signal restoration approach, we aim to achieve a solid performance in the reduction of different noise types using a single neural denoiser built upon transformer-based deep generative models. Using this proposed method, we conducted the experiments on the noise reduction of a PPG signal synthetically contaminated with five types of noise. …”
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