A Risk-Optimized Framework for Data-Driven IPO Underperformance Prediction in Complex Financial Systems by Mazin Alahmadi

“…This paper attempts to predict IPO short-term underperformance during a month post-listing. The current research landscape lacks modern models that address the needs of small and imbalanced datasets relevant to emerging markets, as well as the risk preferences of investors. …”
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Comparative analysis of fit, mechanical properties, and surface characteristics in subtractive- and additive-manufactured zirconia crowns by Su-Min Cho, Ji-Man Park, Alexis Ioannidis, Ryan Jin Young Kim, Hye-Min Chung

“…The replica technique measured marginal and internal gaps (axial, line angle, and occlusal) between the crowns and abutments. …”
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Characterization of Historical Aerosol Optical Depth Dynamics Using LSTM and Peak Enhancement Techniques by Horia-Alexandru Cămărășan, Alexandru Mereuță, Lucia-Timea Deaconu, Horațiu-Ioan Ștefănie, Andrei-Titus Radovici, Camelia Botezan, Zoltán Török, Nicolae Ajtai

“…While the LSTM effectively captured general seasonal trends, it tended to smooth extreme AOD events. To mitigate this, a post-processing algorithm was developed to enhance the representation of AOD peaks and valleys. …”
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Diagnosis, evaluation and management of osteoporosis in chronic kidney disease: navigating treatment approaches – Indian consensus statement by Vijay Kher, Rajkumar Sharma, Georgi Abraham, Bharat Shah, Sishir Gang, Sanjeev Gulati, Manisha Sahay, Jatin Kothari, Anil Kumar BT, Raja Ramachandran, Sanjay Kalra, Rakesh Kumar Sahay, Om Lakhani, Jay Kumar Sharma, Deepak Bunger, Thomas L. Nickolas

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A field methodology to advance social equity and transformative adaptation to climate change in smallholder communities by Patti Petesch, Eleanor Fisher, Olivia Ebenstål Almeida, Jon Hellin, Renee Bullock

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Navigating the Development of Dry Powder for Inhalation: A CDMO Perspective by Beatriz Noriega-Fernandes, Mariam Ibrahim, Rui Cruz, Philip J. Kuehl, Kimberly B. Shepard

“…Contract development and manufacturing organizations (CDMOs) play a key role in supporting the development of drug products for inhalation, from early feasibility to post marketing. However, a critical gap exists for these newcomers: a clear, integrated, and a CDMO-centric roadmap for navigating the complexities of pulmonary/nasal drug product development. …”
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The Impact of Polychlorinated Biphenyls on the Development of Zebrafish (<i>Danio rerio</i>) by Megan Moma, Abi Lee, M. Brady Olson, Karin L. Lemkau, W. James Cooper

“…Zebrafish were exposed to a standard PCB mixture (Aroclor 1254) for the first 5 days post fertilization, as there is a gap in knowledge during this important developmental period for fish (i.e., organization of the body). …”
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High Mobility Group Box 1 (HMGB1): Molecular Signaling and Potential Therapeutic Strategies by Sayantap Datta, Mohammad Atiqur Rahman, Saisudha Koka, Krishna M. Boini

“…High Mobility Group Box 1 (HMGB1) is a highly conserved non-histone chromatin-associated protein across species, primarily recognized for its regulatory impact on vital cellular processes, like autophagy, cell survival, and apoptosis. …”
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Segmentation and finite element analysis in orthopaedic trauma by Kevin Y. Wang, Alexander R. Farid, Simon Comtesse, Arvind G. von Keudell

“…FEA provides valuable outcome measures such as stress distribution, strain quantification, fracture gap motion, failure prediction, and implant stability. …”
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Simulation of oak early life history and interactions with disturbance via an individual-based model, SOEL. by Kenneth F Kellner, Robert K Swihart

“…Following midstory removal, lower weevil infestation probability and lower post-dispersal acorn survival resulted in a modest decline in seedling density, but the decline did not persist to the sapling life stage class. …”
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RUSSIAN-BELARUSIAN BORDER REGION AS AN INTERCAPITAL REGION by A. P. Katrovskiy, A. K. Nizhnikova

“…The gap between successful metropolitan areas and inter-capital periphery is widening. …”
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Development and Implementation of Informational Toolkits to Address Inequities in COVID-19 Testing by Sunasia Mims, Jessica Rhinehart, Melissa Ryan, Susan Driggers, Travaé Hardaway Griffith, Grace Okoro, Tiffany Osborne, Lori Brand Bateman, Janet M. Turan, Raegan H. Durant, Barbara Hansen, Gabriela R. Oates

“…Onboarding and technical training facilitated implementation in health care settings. Pre/post implementation surveys showed high perceived usefulness and feasibility of the health care toolkits. …”
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Expecting the expected – learning from the past to provide forward scenarios through geomorphic change detection, monitoring and modeling by G. Bossi, M. Cavalli, M. Mantovani, F. T. Catelan, A. Ballaera, F. Ceccotto, G. Marcato, A Pasuto

“…In 2020, a new LiDAR survey of the area allowed assessment of the sediment dynamics within the catchment through the comparison with the post-2010 event LiDAR DTM. Based on DEM of difference maps, new insight into the behaviour of the catchment emerged, which appears to be influenced both by natural processes and anthropic activities. …”
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Propagating observation errors to enable scalable and rigorous enumeration of plant population abundance with aerial imagery by Andrii Zaiats, T. Trevor Caughlin, Jennyffer Cruz, David S. Pilliod, Megan E. Cattau, Rongsong Liu, Richard Rachman, Maisha Maliha, Donna Delparte, John D. J. Clare

“…We apply it to estimate the abundance of a foundational shrub species in post‐wildfire landscapes in the western United States. …”
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A Robotic Prosthetic Hand for Computer Mouse Operations by Ziming Chen, Yiming He, Boao Li, Huasong Min, Fuchun Sun, Shuguang Li, Bin Fang

“…It enables an enveloping grasp of the computer mouse and facilitates diverse finger‐based clicking and scrolling operations. In addition, a mapping between the hand movements (myoelectric signals) and the computer mouse operations is created by combining a neural network classifier and a post‐processing algorithm. …”
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YOLO-LPSS: A Lightweight and Precise Detection Model for Small Sea Ships by Liran Shen, Tianchun Gao, Qingbo Yin

“…The characteristics of YOLO-LPSS are as follows: (1) Strengthening the backbone’s ability to extract and emphasize features relevant to small ship objects, particularly in semantic-rich layers. (2) A sophisticated, learnable method for up-sampling processes is employed, taking into account both deep image information and semantic information. (3) Introducing a post-processing mechanism in the final output of the resampling process to restore the missing local region features in the high-resolution feature map and capture the global-dependence features. …”
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Evaluation of seasonal variation of groundwater quality by using the correlation matrices method in Koppal Taluk, Karnataka, India by Ramesh Basanagouda, Avinash Pandurang, Maradi Nayaka

“…Factor analysis suggested the first three principal components (PCs) in this analysis were 96% (Monsoon), 93.50% (Pre-Monsoon), and 87% (Post-Monsoon) of the cumulative variance correspondingly, and TDS was the most representative variable across all seasons.  …”
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Transformer-Based Multi-Target Object Detection and Tracking Framework for Robust Spatio-Temporal Memory in Dynamic Environments by Tareq Mahmod AlZubi, Umar Raza Mukhtar

“…The Target Proposal Module generates object candidates using a transformer encoder-decoder structure, and the memory decoder integrates both proposal and track vectors to predict object locations and identities in real-time, minimizing post-processing. The framework incorporates a multi-scale attention pyramid to handle variations in object scale and utilizes a deformable transformer for generating accurate object proposals. …”
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R-Sparse R-CNN: SAR Ship Detection Based on Background-Aware Sparse Learnable Proposals by Kamirul Kamirul, Odysseas A. Pappas, Alin M. Achim

“…The adoption of sparse proposals streamlines the pipeline by eliminating the need for proposal generators and post-processing for overlapping predictions. The proposed BAPs enrich object representation by integrating ship and background features, allowing the model to learn their contextual relationships for more accurate distinction of ships in complex environments. …”
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Multi-layer obstacle-avoiding rectilinear steiner minimal tree algorithm based on deep reinforcement learning by Xing Huang, Yuhan Zhu, Yanbo Xu, Yajun Xie, Genggeng Liu

“…Then, an agent is designed to learn edge selection for constructing the Multi-Layer Obstacle-Avoiding Steiner Tree (ML-OAST) using Double Deep Q-Network (DDQN). Finally, a post-processing stage is applied to further shorten the total wirelength through fast pruning and local optimization. …”
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