Utilization of refuse-derived fuel in industrial applications: Insights from Uttar Pradesh, India by Utsav Sharma, Dayanand Sharma, Amit Kumar, Tushar Bansal, Ankit Agarwal, Shudhanshu Kumar, Abid Hussian, Hesam Kamyab, Moinul Haq

“…The RDF samples were collected from five strategic locations in Uttar Pradesh: Morta Site, Pipeline Site, and Sector 146 Noida, covering various waste compositions found at these landfill sites. …”
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Toward enhancement of antibody thermostability and affinity by computational design in the absence of antigen by Mark Hutchinson, Jeffrey A. Ruffolo, Nantaporn Haskins, Michael Iannotti, Giuliana Vozza, Tony Pham, Nurjahan Mehzabeen, Harini Shandilya, Keith Rickert, Rebecca Croasdale-Wood, Melissa Damschroder, Ying Fu, Andrew Dippel, Jeffrey J. Gray, Gilad Kaplan

“…In silico tools that can streamline the process of antibody discovery and optimization are critical to support a pipeline that is growing more numerous and complex every year. …”
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Detecting gene copy number alterations by Oncomine Comprehensive genomic profiling in a comparative study on FFPE tumor samples by Fabio Bozzi, Elena Conca, Marco Silvestri, Gianpaolo Dagrada, Alice Ardore, Donata Penso, Daniele Lorenzini, Chiara Costanza Volpi, Desirè Viola Trupia, Adele Busico, Iolanda Capone, Federica Perrone, Elena Tamborini, Andrea Vingiani, Luca Agnelli, Giancarlo Pruneri

“…According to proprietary software pipeline, OCA+ accurately identified gains characterized by CN ≥ 5,2. …”
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BeatProfiler: Multimodal In Vitro Analysis of Cardiac Function Enables Machine Learning Classification of Diseases and Drugs by Youngbin Kim, Kunlun Wang, Roberta I. Lock, Trevor R. Nash, Sharon Fleischer, Bryan Z. Wang, Barry M. Fine, Gordana Vunjak-Novakovic

“…We then demonstrate that the data acquired by our automatic acquisition pipeline can be further harnessed for machine learning (ML) analysis to phenotype a disease model of restrictive cardiomyopathy and profile cardioactive drug functional response. …”
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Improving H2RG Performance in SPHEREx Brassboard Model by Chi H. Nguyen, Phillip Korngut, C. Darren Dowell, James Bock, Jill Burnham, Samuel Condon, Walter Cook, Grigory Heaton, Howard Hui, Branislav Kecman, Hiromasa Miyasaka, Kenneth Manatt, Hien T. Nguyen, Stephen Padin, Marco Viero

“…Additionally, we observe that the gain of optical pixels is consistently ∼90% that of the reference pixels, prompting additional correction steps in the data reduction pipeline.…”
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Nicotine dependence is associated with an increased risk of developing chronic, non-communicable inflammatory disease: a large-scale retrospective cohort study by Khalaf Kridin, Khalaf Kridin, Khalaf Kridin, Cristian Papara, Katja Bieber, David A. De Luca, Jan Philipp Klein, Marlene A. Ludwig, Philip Curman, Philip Curman, Philip Curman, Philip Curman, Artem Vorobyev, Astrid Dempfle, Ralf J. Ludwig

“…Using propensity score matching (PSM) to control for age, sex, ethnicity, and other CID risk factors, we contrasted the risk of developing any or any of the 38 CIDs in 881,192 EHRs from individuals with nicotine dependence to PSM-matched unexposed counterparts.ResultsThe analytical pipeline was validated by demonstrating an increased risk of individuals exposed to nicotine dependence for subsequent diagnosis of myocardial infarction, malignant neoplasm of the lung, and chronic obstructive pulmonary disease. …”
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Hierarchizing multi-scale environmental effects on agricultural pest population dynamics: a case study on the annual onset of Bactrocera dorsalis population growth in Senegalese or... by Caumette, Cécile, Diatta, Paterne, Piry, Sylvain, Chapuis, Marie-Pierre, Faye, Emile, Sigrist, Fabio, Martin, Olivier, Papaïx, Julien, Brévault, Thierry, Berthier, Karine

“…We then developed a flexible analysis pipeline centred on a recent machine learning algorithm, which allows the combination of gradient boosting and grouped random effects models or Gaussian processes, to hierarchize the effects of multi-scale environmental variables on the onset of annual BD population growth in orchards. …”
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Development of an artificial intelligence-based application for the diagnosis of sarcopenia: a retrospective cohort study using the health examination dataset by Chang-Won Jeong, Dong-Wook Lim, Si-Hyeong Noh, Sung Hyun Lee, Chul Park

“…Additionally, we developed an algorithm for the calculation of T-Score calculated as (measurement value-Young adult mean)/(Young adult SD) using the Aggregation Pipeline by MongoDB, with the mean and standard deviation for skeletal muscle area (SMA), SMA/height2, SMA/weight, and SMA/body mass index (BMI) for both sexes and different age groups. …”
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Beyond the fever: shotgun metagenomic sequencing of stool unveils pathogenic players in HIV-infected children with non-malarial febrile illness by Patricia Nabisubi, Stephen Kanyerezi, Grace Kebirungi, Ivan Sserwadda, Mike Nsubuga, Grace Kisitu, Patricia Ntege Nahirya, Bonny Mulindwa, George P. Akabwai, Sylvia Nantongo, Adeodata Kekitiinwa, Edgar Kigozi, Nsubuga Moses Luutu, Fred Ashaba Katabazi, Leymon Kalema, Andrew Katabalwa, Daudi Jjingo, Gerald Mboowa

“…Bioinformatics analysis was conducted to identify and characterise the microbial composition and potential pathogenic taxa associated with NMFI using the CZID pipeline. Results Our findings reveal a diverse array of microbial taxa in the stool samples of HIV-infected children with NMFI. …”
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Computational pathology assessments of cardiac stromal remodeling: Clinical correlates and prognostic implications in heart transplantation by Eliot G. Peyster, MD, MSc, Cai Yuan, PhD, Sara Arabyarmohammadi, PhD, Priti Lal, MD, Michael D. Feldman, MD, PhD, Pingfu Fu, PhD, Kenneth B. Margulies, MD, MS, Anant Madabhushi, PhD, FAIMBE, FIEEE, FNAI

“…Source code for the stromal feature analysis pipeline is hosted on GitHub and freely available: https://github.service.emory.edu/CYUAN31/Pathomics_StromalBioMarker_in_Myocardium.git.…”
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High-throughput untargeted metabolomics reveals metabolites and metabolic pathways that differentiate two divergent pig breeds by S. Bovo, M. Bolner, G. Schiavo, G. Galimberti, F. Bertolini, S. Dall’Olio, A. Ribani, P. Zambonelli, M. Gallo, L. Fontanesi

“…The molecular data were analysed using a bioinformatics pipeline specifically designed for identifying differentially abundant metabolites between the two breeds in a robust and statistically significant manner, including the Boruta algorithm, which is a Random Forest wrapper, and sparse Partial Least Squares Discriminant Analysis (sPLS-DA) for feature selection. …”
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The James Webb Space Telescope Absolute Flux Calibration. III. Mid-infrared Instrument Medium Resolution Integral Field Unit Spectrometer by David R. Law, Ioannis Argyriou, Karl D. Gordon, G. C. Sloan, Danny Gasman, Alistair Glasse, Kirsten Larson, Leigh N. Fletcher, Alvaro Labiano, Alberto Noriega-Crespo

“…The photometric repeatability is stable to better than 1% in the wavelength range 5–18 μ m, and the S/N ratio of the delivered spectra is consistent between bootstrapped measurements, pipeline estimates, and theoretical predictions. The MRS point-source calibration agrees with that of the MIRI imager to within 1% from 7 to 21 μ m and is approximately 1% fainter than prior Spitzer observations, while the extended source calibration agrees well with prior Cassini Composite Infrared Spectrometer and Voyager Infrared Interferometer Spectrometer and Radiometer observations.…”
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An efficient method for predicting the morphology of proppant packs based on a surrogate model by Tao ZHANG, Hangyu ZHOU, Yifan ZHANG, Jianchun GUO, Haoran GOU, Tang TANG

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Toward accurate prediction of carbon dioxide (CO2) compressibility factor using tree-based intelligent schemes (XGBoost and LightGBM) and equations of state by Behnam Amiri-Ramsheh, Aydin Larestani, Saeid Atashrouz, Elnaz Nasirzadeh, Meriem Essakhraoui, Ali Abedi, Mehdi Ostadhassan, Ahmad Mohaddespour, Abdolhossein Hemmati-Sarapardeh

“…To design a successful CO2 injection process, it is very important to have precise knowledge about the compressibility factor (Z-factor) of CO2 as it directly affects material balance calculations, pipeline design, design of surface facilities, and CO2 compression. …”
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Mental health phenotypes of well-controlled HIV in Uganda by Leah H. Rubin, Leah H. Rubin, Leah H. Rubin, Leah H. Rubin, Kyu Cho, Jacob Bolzenius, Julie Mannarino, Rebecca E. Easter, Raha M. Dastgheyb, Aggrey Anok, Stephen Tomusange, Deanna Saylor, Maria J. Wawer, Noeline Nakasujja, Gertrude Nakigozi, Robert Paul

“…Participants completed the Patient Health Questionnaire (PHQ-9), Beck Anxiety Inventory (BAI), and the PTSD Checklist-Civilian (PCL-C). A clustering pipeline consisting of dimension reduction with UMAP followed by HBDScan was used to identify MH subtypes using total symptom scores. …”
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Consensus for Operating Room Multimodal Data Management: Identifying Research Priorities for Data-Driven Surgery by Alain Garcia Vazquez, MD, Juan Verde, MD, Ariosto Hernandez Lara, MD, Didier Mutter, MD, Lee Swanstrom, MD, 5G-OR Research Committee, 5G-OR Consensus Panel, Ariosto Hernandez Lara, Barbara Seeliger, Daniel Hashimoto, Deepak Alapatt, Joel Lavanchy, Juan Verde, Lise Lecointre, Pietro Mascagni, Pr.Danail Stoyanov, Didier Mutter, MD, Dirk Willhelm, MD, Pr.Gerald Fried, MD, Gretchen Jackson, MD, PhD, Jean-Paul Mazellier, PhD, Lee Swanstrom, MD, Pr.Lena Maier-Hein, Pr.Nicolas Padoy, PhD, Pr.Sascha Treskatsch, MD, Pr.Silvana Perretta, MD, PhD, Pr.Stefanie Speidel, Pr.Teodor Grantcharov, Annika Mareike Engel, BSc, MEng, Axel Boese, DrIng, Carla M. Pugh, MD, PhD, Cesare Hassan, Fabian Dietrich, PhD, Felix Nickel, MD, MME, Franziska Jurosch, MSc, Guido Beldi, MD, Henriette Hegermann, Dr, Johannes Horsch, Dipl-Ing, Julian Rosenkranz, Ing, MSc, Keno Sponheuer, DrMed, Luca Milone, MD, PhD, FACS, Nariaki Okamoto, MD, PhD, Patrick Seeling, PhD, Pedro Filipe Pereira Gouveia, MD, PhD, Roland Croner, Prof.Dr, Sandra Keller, PhD, Sharona B Ross, Taiga Wakabayashi, MD, Ph.D, Takeaki Ishizawa, MD, PhD, Takeshi Urade, MD, PhD, Thomas Schnelldorfer, MD, PhD, Thorge Lackner, MSc, and MEng

“…These innovations have resulted in operating rooms evolving into data-rich environments, which, in turn, requires a thorough understanding of the data pipeline for improved and more intelligent real-time data usage. …”
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Forest Fire Clustering: A Novel Tool for Identifying Star Members of Clusters by Xingyin Wei, Jing Chen, Su Zhang, Feilong He, Yunbo Zhao, Xuran He, Yongjie Fang, Xinhao Chen, Hao Yang

“…We compare the performance of FFC with that of DBSCAN and HDBSCAN on this data set by configuring them into the same processing pipeline for identifying star members. Our results indicate that FFC outperforms the two others in terms of the quality of clusters, particularly for clusters located at distances greater than 2 kpc. …”
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PHARAOH: A collaborative crowdsourcing platform for phenotyping and regional analysis of histology by Kevin Faust, Min Li Chen, Parsa Babaei Zadeh, Dimitrios G. Oreopoulos, Alberto J. Leon, Ameesha Paliwal, Evelyn Rose Kamski-Hennekam, Marly Mikhail, Xianpi Duan, Xianzhao Duan, Mugeng Liu, Narges Ahangari, Raul Cotau, Vincent Francis Castillo, Nikfar Nikzad, Richard J. Sugden, Patrick Murphy, Safiyh S. Aljohani, Philippe Echelard, Susan J. Done, Kiran Jakate, Zaid Saeed Kamil, Yazeed Alwelaie, Mohammed J. Alyousef, Noor Said Alsafwani, Assem Saleh Alrumeh, Rola M. Saleeb, Maxime Richer, Lidiane Vieira Marins, George M. Yousef, Phedias Diamandis

“…Moreover, by using our PHARAOH pipeline, we showcase how correlation of cohort-level cytoarchitectural features with accompanying biological and outcome data can help systematically devise interpretable morphometric models of disease. …”
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Physiochemical and functional evaluation of the first-in-class anti-cancer IgE antibody drug, MOv18, through process development and good manufacturing practice production by Heather J Bax, Jitesh Chauhan, Alexandra J McCraw, Melanie Grandits, Chara Stavraka, Heike Lentfer, Tim Hillyer, Simon Carroll, Kim Vigor, Chris Selkirk, Mariangela Figini, Jack Cheeseman, Paulina A Urbanowicz, Richard A Gardner, Daniel I R Spencer, Nigel Westwood, Sarah Mellor, James Spicer, Debra H Josephs, Sophia N Karagiannis

“…We confirm the suitability of the pipeline described for generating intact, functionally active, clinical-grade material for this novel therapeutic class as an Investigational Medicinal Product (IMP), with comparable characteristics to the original research-grade antibody. …”
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Predictive value of ENLIGHT-DP in patients with metastatic lung adenocarcinoma treated with immune checkpoint inhibitors and platinum chemotherapy directly from histopathology slid... by Eli Pikarsky, Anna Elia, Gal Dinstag, Omer Tirosh, Tuvik Beker, Ranit Aharonov, Hovav Nechushtan, Leon Gugel, Yaron Kinar, Michael Tabi, Tzivia Gottlieb, Aron Popovtzer, Johnathan Arnon, Yakir Rottenberg, Philip Blumenfeld

“…We present an analysis of ENLIGHT-DP, a novel transcriptome-based biomarker directly from histopathology slides, in patients with lung adenocarcinoma (LUAD) treated with ICI and platinum-based chemotherapy.Methods We retrospectively scanned high-resolution H&E slides from pretreatment tumor-tissue samples of 50 patients with metastatic LUAD treated with first-line ICI with (46) or without (4) platinum-based chemotherapy and applied our ENLIGHT-DP pipeline to generate, in a blinded manner, an individual prediction score. …”
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