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Preprint ARTICLE | doi:10.20944/preprints202308.0937.v1

Challenges and Opportunities in One Health: Google Trends Search Data

Lauren Wisnieski, Karen Gruszynski, Vina Faulkner, Barbara Shock

Subject: Public Health And Healthcare, Public, Environmental And Occupational Health Keywords: Google Trends; disease prediction; Lyme disease; Lyme; Big Data; One Health; negative binomial; mixed models; zoonotic disease; tick-borne disease

Online: 11 August 2023 (11:01:40 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202403.0321.v1

Quality and Readability of Google Search Information on HoLEP for Benign Prostate Hyperplasia

Yam Ting Ho, Jeremy Saad, Femi E Ayeni, Mohan Arianayagam, Bertram Canagasingham, Ahmed Goolam, Nicola Jeffrey, Mohamed Khadra, Raymond Ko, Nicholas Mehan, Sachinka Ranasinghe, Celi Varol, Jonathan Kam, Isaac A Thangasamy

Subject: Medicine And Pharmacology, Urology And Nephrology Keywords: Urological surgical procedures; Prostatectomy; Transurethral resection of prostate; Prostatic hyperplasia; Consumer health information, Health literacy; Health education

Online: 6 March 2024 (04:50:41 CET)

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Preprint ARTICLE | doi:10.20944/preprints202406.0578.v1

Intelligent Network Optimization in Cloud Environments with Generative AI and LLMs

Kapil Patil, Bhavin Desai

Subject: Engineering, Telecommunications Keywords: Artificial intelligence; Neural networks; Machine learning LLM; Cloud computing; Cloud Infra-structure; Next generation networking; Network architecture; Deep Learning

Online: 10 June 2024 (13:46:59 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202404.0476.v1

Metabolomics on Apple (Malus domestica) Cuticle—Search for Authenticity Markers

Kamila Bechynska, Jiri Sedlak, Leos Uttl, Vit Kosek, Petra Vackova, Vladimir Kocourek, Jana Hajslova

Subject: Chemistry And Materials Science, Food Chemistry Keywords: Malus domestica; apple cuticle; UHPLC-HRMS/MS; metabolomic fingerprints; classification models; markers; wax esters

Online: 8 April 2024 (03:04:51 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202309.1375.v1

Detection of Large-Scale Floods Using Google Earth Engine and Google Colab

Rosa Johary, Christophe Révillion, Thibault Catry, Cyprien Alexandre, Pascal Mouquet, Solofoarisoa Rakotoniaina, Gwenaëlle Pennober, Solofo Rakondraompiana

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: flood; radar imagery; Sentinel-1; Google Earth Engine; Python

Online: 20 September 2023 (09:47:41 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202406.0678.v1

Optimization Of The Search For Neuroprotectors Among Bioflavonoids

Igor Belenichev, Victor Ryzhenko, Olena Popazova, Nina Bukhtiyarova, Nadia Gorchakova, Valentyn Oksenych, Oleksandr Kamyshnyi

Subject: Medicine And Pharmacology, Medicine And Pharmacology Keywords: informational technologies; multiple sclerosis; virtual screening; bioflavonoids; neuroprotection

Online: 11 June 2024 (11:07:27 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202407.1467.v1

Localized Crop Classification by NDVI Time Series Analysis of Remote Sensing Satellite Data; Applications for Mechanization Strategy and Integrated Resources Management

Hafiz Md-Tahir, Hafiz Sultan Mahmood, Muzammil Husain, Ayesha Khalil, Muhammad Shoaib, Mahmood Ali, Muhammad Mohsin Ali, Muhammad Tasawar, Yasir Ali Khan, Usman Khalid Awan, Muhammad Jehanzeb Masud Cheema

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: Remote sensing; Geographical information system; Vegetation index; LULC classification; Agricultural mechanization; Strategic planning; Resources management; Artificial intelligence algorithms; Crop phenology, Satellite data; Precision agriculture

Online: 18 July 2024 (11:28:24 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201901.0302.v1

Google Earth, Google SketchUp and GIS software; An Interoperable Work Flow for Generating Elevation Data

José Gomes dos Santos, Kevin Bento, Joaquim Lourenço Txifunga

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: interoperability; digital elevation model; Google Sketchup; geographical information systems-science; free and open source software

Online: 30 January 2019 (05:28:53 CET)

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Preprint ARTICLE | doi:10.20944/preprints202403.0522.v1

Replies to Queries in Gynecologic Oncology by Bard, Bing and the Google Assistant

Edward J. Pavlik, Dharani Ramaiah, Taylor Rives, Allison Swiecki-Sikora, Jamie Land

Subject: Medicine And Pharmacology, Oncology And Oncogenics Keywords: accuracy; virtual assistants; Google; Google Bard/Gemini; Microsoft Bing-Copilot; gynecologic; oncology

Online: 8 March 2024 (14:42:50 CET)

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Preprint ARTICLE | doi:10.20944/preprints202407.0657.v1

Impact of Alcalase Hydrolysis and Simulated Gastrointestinal Digestion on the Release of Bioactive Peptides From Erythrina edulis (Chachafruto) Proteins

Jessica L. Correa, Jose Edgar Zapata, Blanca Hernández-Ledesma

Subject: Biology And Life Sciences, Food Science And Technology Keywords: Erythrina edulis; enzymatic hydrolysis; in vitro gastrointestinal digestion; peptides; antioxidant; macrophages.

Online: 9 July 2024 (14:03:19 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202405.0619.v1

Evaluating Public Library Services Through User-Generated Content: Social Network Analysis of Google Maps Reviews

Chao-Chen Chen, Chen-Chi Chang

Subject: Social Sciences, Library And Information Sciences Keywords: user-generated content; public library evaluation; experiential feedback; service quality; Google Maps review

Online: 10 May 2024 (13:20:23 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201706.0062.v1

Relationship of Google Scholar Versions and Paper Citations

Marjan Mohammadjafari, Hadi Salehi, Kaveh Bakhtiyari, Nader Ale Ebrahim, Mahmoud Danaee, Masoud Shakiba, Masoomeh Shahbazi-Moghadam, Azam Zavvari

Subject: Social Sciences, Library And Information Sciences Keywords: h-index; citations; published version; Scopus database; highly cited paper; bibliometrics

Online: 14 June 2017 (06:07:12 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202404.1552.v1

Flood Extent Delineation and Exposure Assessment in Senegal Using Google Earth Engine: The 2022 Event

Bocar SY, Fatoumata Bintou BAH, Hy Dao

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: flood extent mapping; flood exposition assessment; remote sensing; Google Earth Engine; Sentinel-1; hydrological and hydraulic modelling

Online: 25 April 2024 (15:18:35 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202404.0182.v1

Hybrid Genetic Algorithm and Tabu Search for Solving Preventive Maintenance Scheduling Problem for Cogeneration Plants

Khaled Alhamad, Yousif Alkhezi

Subject: Computer Science And Mathematics, Discrete Mathematics And Combinatorics Keywords: preventive maintenance; scheduling; optimization; genetic algorithm; tabu search; metaheuristic

Online: 2 April 2024 (12:56:52 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202010.0366.v1

Operational Optimization at Signalized Metering Roundabouts Using Cuckoo Search/Local Search Algorithm

Hong Ki An, Yao Liu, Dong Sun Kim

Subject: Engineering, Automotive Engineering Keywords: Metering roundabout; Detector location; AIMSUN; Cucksoo search/Local search algorithm

Online: 19 October 2020 (10:41:42 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202402.1751.v1

Testing the Conjecture That Quantum Processes Create Conscious Experience

Hartmut Neven, Peter Read, Kenneth S. Kosik, Tjitse Van der Molen, Dirk Bouwmeester, Eve Bodnia, Luca Turin, Christof Koch

Subject: Physical Sciences, Quantum Science And Technology Keywords: physical substrate of consciousness; quantum biology; brain-computer interface; brain organoids; anesthesia; xenon

Online: 29 February 2024 (20:24:17 CET)

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Preprint ARTICLE | doi:10.20944/preprints202205.0222.v1

Google Earth Geoscience Video Library (GEGVL): Organizing Geoscience Videos in a Google Earth Environment to Support Place-Based Geoscience Education

Ning Wang, Robert J. Stern, Mary L. Urquhart, Katherine M. Seals

Subject: Environmental And Earth Sciences, Other Keywords: multimedia; geoscience videos; geoscience education; GEGVL; earth systems science education; educational technology; place-based education; active learning

Online: 17 May 2022 (04:37:00 CEST)

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Preprint REVIEW | doi:10.20944/preprints202403.1401.v1

Plasma Metabolite Profiling in the Search for Early-Stage Biomarkers for Lung Cancer: Some Important Breakthroughs

Jill Meynen, Peter Adriaensens, Maarten Criel, Evelyne Louis, Karolien Vanhove, Michiel Thomeer, Liesbet Mesotten, Elien Derveaux

Subject: Medicine And Pharmacology, Oncology And Oncogenics Keywords: biomarkers; lung cancer; metabolomics; NMR (nuclear magnetic resonance)

Online: 25 March 2024 (07:06:46 CET)

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Preprint ARTICLE | doi:10.20944/preprints202404.0027.v1

Framework to Create Dataset for Disaster Behavior Analysis using Google Earth Engine: A Case Study in Peninsular Malaysia for Historical Forest Fire Behavior Analysis

Yee Jian Chew, Shih Yin Ooi, Ying Han Pang, Zheng You Lim

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: Disaster behavior; forest fire behavior; forest fire dataset; data extraction framework; Google Earth Engine; remote sensing; Malaysia; ChatGPT; Noteable; Large Language Model

Online: 1 April 2024 (10:35:32 CEST)

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Preprint REVIEW | doi:10.20944/preprints202405.1212.v1

Important Repercussions of the COVID-19 Pandemic Lifestyle Avoided by Researchers? Face Masks and Temporomandibular Disorders: A Systematic Search and Review

Szymon Jozef Pietrzyk, Emilia Kielczynska, Martyna Kowalczyk, Mateusz Mazurek, Zygmunt Antoni Domagala

Subject: Public Health And Healthcare, Public Health And Health Services Keywords: temporomandibular joint disorder; TMD; SARS-CoV-2 outbreak; COVID-19; COVID-19 pandemic; face masks; prolonged face mask use; TMJ; complications

Online: 20 May 2024 (12:37:23 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201812.0345.v1

Cloud Drives Forensic Artifacts A Google Drive Case

Tariq Khairallah

Subject: Computer Science And Mathematics, Software Keywords: Cloud Storage Forensics, Cloud Application Artifacts, Data Remnants, Data Carving, Digital Forensic Investigations

Online: 3 January 2019 (12:17:11 CET)

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Preprint ARTICLE | doi:10.20944/preprints201807.0076.v1

Flood Prevention and Emergency Response System Powered by Google Earth Engine

Cheng-Chien Liu, Ming-Chang Shieh, Ming-Hsun Ko, Kung-Hwa Wang

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: flood; disaster prevention; emergency response; decision making, Google earth engine

Online: 4 July 2018 (15:33:44 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202408.1280.v1

Effects of Three Yeast Strains on In Vitro Rumen Fermentation of Corn Stover and a Total Mixed Ration

Bexy Gonzalez-Mora, Francisco Castillo-Rangel, Joel Dominguez-Viveros, Perla Lucia Ordoñez-Baquera, Michael E. Hume, Robin C. Anderson, Monserrath Félix-Portillo, Agustin Corral-Luna, Jaime Salinas-Chavira, Yamicela Castillo-Castillo, Oscar Ruiz-Barrera

Subject: Biology And Life Sciences, Animal Science, Veterinary Science And Zoology Keywords: microbial feed additives; probiotic; Candida norvegensis; Pichia guilliermondii; Saccharomyces cerevisiae

Online: 19 August 2024 (05:49:25 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202409.0663.v1

Adaptive Hyperactivity and Clinical and Laboratory Biomarker Search: The Case of Old Elders in the Blue Zone of Sardinia

Alessandra Scano, Germano Orrù, Goce Kalcev, Giulia Cossu, Massimo Tusconi, Maura Spada, Laura Atzori, Caterina Ferreli, Flavio Cabitza, Diego Primavera, Federica Sancassiani

Subject: Public Health And Healthcare, Public Health And Health Services Keywords: Bipolar Disorders; BD; Laboratory Medicine; Applied Biomedical Technologies; Bipolar Spectrum; Prevention; New Technologies; Hyperactive; Blue Zone; Biomarker

Online: 9 September 2024 (11:25:52 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202004.0316.v1

Multi-temporal Crop Type and Field Boundary Classification with Google Earth Engine

Michael Marszalek, Maximilian Lösch, Marco Körner, Urs Schmidhalter

Subject: Environmental And Earth Sciences, Environmental Science Keywords: Precision farming; Crop type mapping; Digital agriculture; Sentinel-2; Random Forest; SVM; Field boundaries; Canny; Simple non-iterative clustering

Online: 19 April 2020 (03:14:37 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202209.0358.v1

Iterative Qubits Management for Quantum Search

Wenrui Mu

Subject: Computer Science And Mathematics, Information Systems Keywords: Quantum Search; Qubit Management; Iterative Search

Online: 23 September 2022 (05:25:28 CEST)

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Preprint TECHNICAL NOTE | doi:10.20944/preprints202003.0038.v1

Automated Inundation History Mapping over Large Areas using Landsat and Google Earth Engine

Victoria L Inman, Mitchell B Lyons

Subject: Environmental And Earth Sciences, Environmental Science Keywords: Okavango Delta; inundation maps; inundation extent; Landsat; Google Earth Engine; automated time series

Online: 3 March 2020 (11:25:49 CET)

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Preprint ARTICLE | doi:10.20944/preprints202403.0987.v1

Does Athletes' Respiratory Muscle Strength Affect Max VO2 Kinetics?

Gökhan Deliceoğlu, Veli O. Çakır, Banu Kabak, Halil Ibrahim Ceylan, Raul Ioan Muntean, Valentina Ștefănică

Subject: Public Health And Healthcare, Public Health And Health Services Keywords: Respiratory; maximal inspiratory pressure; expiratory pressure; MaxVO2; athletes

Online: 18 March 2024 (09:39:18 CET)

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Preprint ARTICLE | doi:10.20944/preprints202202.0023.v1

Assessing Public Interest Towards Renewable Wind Energy Using Google Trends

Alexandra Perju-Mitran, Daniela Zirra, Raul Augustin Mitran

Subject: Business, Economics And Management, Economics Keywords: consumer behavior; Google Trends; wind energy; public interest; environmental marketing.

Online: 1 February 2022 (21:39:15 CET)

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Preprint ARTICLE | doi:10.20944/preprints202007.0646.v1

Classification of Google Play Store Application Reviews Using Machine Learning

Abdul Karim, Azhari Azhari, Meshrif Alruily, Hamza Aldabbas, Samir Brahim Belhaouri, Ali Adil Qureshi

Subject: Computer Science And Mathematics, Computer Science Keywords: Machine Learning; Natural Language Processing; Text Mining; Semantic Analysis; Scraping; Google Play Store; Rating

Online: 26 July 2020 (17:11:09 CEST)

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Preprint ESSAY | doi:10.20944/preprints202012.0156.v1

Evidence-Based Management of Gout - A Systematic Search and Review

Md Abu Bakar Siddiq

Subject: Medicine And Pharmacology, Immunology And Allergy Keywords: gout; hyperuricemia; lesinurad; life style; prednisolone; uric acid; urate oxidase

Online: 7 December 2020 (13:10:24 CET)

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Gout is the most common form of inflammatory arthritis. Hyperuricaemia is the pre-requisite for gout and is influenced by variable modifiable and non-modifiable risk factors. Clinical features unique for gout are due to deposition of monosodium urate (MSU) crystal in articular and extra articular tissues. Among various treating agents, anti-inflammatory drugs and urate lowering therapies (ULT) are used widely and successfully, however, non-medicinal means are also effective in the disorder. In their updated guidelines, ACR (2012) and EULAR (2016) recommended both medicinal and non-medicinal approaches that could be used in treating gout, though some of the recommendations are based on lower level of evidence. Moreover, researchers’ continued effort in finding new gout managing agents appear promising, for example, role of Lesinurad in gout management (CLEAR1, CLEAR2). In this new synthesis the author is aimed to provide updated information on gout management based on a systematic review including published work within last ten years between 2008 and 2018 and for this purpose, using ‘clinical trials in gout management’ string, published worked searched in PubMed database from 1st September 2018 to 30 October 2018. Besides the recent ACR and EULAR evidence based management guidelines, the author reviewed another 91 (total 93) articles to make this new draft – 39 articles describe role of pharmacological agents and 54 describe different gout risks, pharmacokinetics/pharmacodynamics of ULT, association between raised sUA level and renal impairment, efficacy of non-pharmacological agents in reducing sUA. According to published work, anti-inflammatory agent is the most appropriate drug group in mitigating inflammatory symptoms of gout, though they often adversely affect over other vital 2 organs with impaired function. Besides ULT, uricase analogues are also found useful in non refractory gout. Since anti-inflammatory agents and ULT contraindicate in some clinical conditions, intra-articular steroid and or adrenocorticotropic hormone (ACTH) are appropriate alternatives instead. However, head-to-head comparison between different NSAIDs, NSAID and prednisolone, NSAID and colchicine are yet to perform. Use of combined anti-inflammatory preparations in gout is also based on lower level of evidence. Regarding effective maximum dose and long-standing impact of ULT on vital organs we are yet to reach a conclusion. Likewise, non-medicinal approaches are widely using in achieving target sUA level, though some of them are based on biased study outcomes and or study with inadequate power, requiring further analysis. Among non-pharmacological approaches, life-style modification, restriction of purine rich diets, avoidance of gout inciting agents are important, but inconclusive. Educating patients’ about diseases, risk factors, available treatment options and side effects from them are also important in terms of achieving sUA level, nevertheless too much counseling sometimes could be worthless.

Preprint ARTICLE | doi:10.20944/preprints202406.1948.v1

Machine Learning Meets Meta-heuristics: Bald Eagle Search Optimization and Red Deer Optimization for Feature Selection in Type II Diabetes Diagnosis

Harikumar Rajaguru, Dinesh Chellappan

Subject: Engineering, Bioengineering Keywords: Classifiers; Bald Eagle Search Optimization; Red Deer Optimization; Diabetic Detection; Performance Analysis; Feature extraction.

Online: 27 June 2024 (13:53:21 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202401.0056.v1

Optimization of Greedy Randomized Adaptive Search Procedure

Ahmed Tlili, Salim Chikhi

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Mental representation; GRASP metaheuristic; optimization

Online: 2 January 2024 (09:34:17 CET)

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Preprint ARTICLE | doi:10.20944/preprints202108.0018.v1

Proximal Policy Optimization for Radiation Source Search

Philippe Proctor, Christof Teuscher, Adam Hecht, Marek Osiński

Subject: Physical Sciences, Radiation And Radiography Keywords: deep reinforcement learning; source search and localization; active search; gamma radiation; source parameter estimation; sequential decision making; non-convex environment}

Online: 2 August 2021 (11:14:24 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201608.0184.v1

Search for dynamical origin of social networks

Michail Zak

Subject: Computer Science And Mathematics, Computer Science Keywords: instability; attractors; randomness; quantum-classical hybrid

Online: 20 August 2016 (05:39:37 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201607.0051.v1

Search for QPOs in the Light Curve of the Blazar OJ287: Preliminary Results from 2015/16 Observing Campaign

S. Zola, M. Valtonen, G. Bhatta, A. Goyal, B. Debski, A. Baran, J. Krzesinski, M. Siwak, S. Ciprini, A. Gopakumar, H. Jermak, K. Nilsson, D. Reichart, K. Matsumoto, K. Sadakane, K. Gazeas, M. Kidger, V. Piirola, F. Alicavus, K.S. Baliyan, A. Berdyugin, D. Boyd, M. Campas Torrent, F. Campos, J. Carrillo Gomez, D.B. Caton, V. Chavushyan, J. Dalessio, D. Dimitrov, M. Drozdz, A. Erdem, A. Escartin Perez, V. Fallah Ramazani, A.V. Filippenko, F. Garcia, F. Gomez Pinilla, M. Gopinathan, J.B. Haislip, J. Harmanen, G. Hurst, K.M. Ivarsen, M. Jelinek, A. Joshi, M. Kagitani, N. Kaur, N. Karaman, W.C. Keel, A.P. LaCluyze, B.C. Lee, E. Lindfors, J. Lozano De Haro, J.P. Moore, R. Naves Nogues, A.W. Neely, R.H. Nelson, W. Ogloza, S. Okano, J.C. Pandey, M. Perri, P. Pihajoki, G. Poyner, J. Provencal, T. Pursimo, A. Raj, R. Reinthal, S. Sadegi, T. Sakanoi, J.-L. Salto Gonzales, T. Schweyer, F.C. Soldan Alfaro, E. Sonbas, I. Steele, J.T. Stocke, J. Strobl, L.O. Takalo, T. Tomov, L. Tremosa Espasa, J.R. Valdes, J. Valero Perez, F. Verrecchia, J.R. Webb, M. Yoneda, M. Zejmo, W. Zheng, J. Telting, J. Saario, T. Reynolds, A. Kvammen, E. Gafton, R. Karjalainen, P. Blay

Subject: Physical Sciences, Astronomy And Astrophysics Keywords: galaxies: active; BL Lacertae objects: individual (OJ 287); super massive black holes

Online: 18 July 2016 (10:46:26 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202003.0249.v1

Machine Learning Algorithm’s Measurement and Analytical Visualization of User’s Reviews for Google Play Store

Abdul Karim, Azhari Azhari, Samir Brahim Belhaouri, Ali Adil Qureshi

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: machine learning; preprocessing; semantic analysis; text mining; TF/IDF; scraping; Google Play Store

Online: 11 August 2020 (08:14:10 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202402.1698.v2

Efficient Solutions for Large-Scale Max-Cut Problems: A Hybrid Local Search Heuristic Approach and Comparative Analysis with Quantum Annealing

Haibo Wang, Bahram Alidaee, Lutfu Sagbansua

Subject: Business, Economics And Management, Other Keywords: hybrid heuristics; quantum annealing solver; max-cut

Online: 25 June 2024 (00:23:47 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202005.0328.v1

Comparison of Classification Models for Breast Cancer Identification using Google Colab

SUNDARAMBAL BALARAMAN

Subject: Computer Science And Mathematics, Information Systems Keywords: classification; machine learning; breast cancer

Online: 20 May 2020 (10:53:42 CEST)

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Preprint CONCEPT PAPER | doi:10.20944/preprints201909.0016.v1

Long Term Monitoring of Ghana’s Forest Reserves Using Google Earth Engine

Jeff Dacosta Osei, S. A. Andam-Akorful, Edward Matthew Osei jnr

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: land cover; classification Spatial and temporal Analysis; forest cover; Google Earth Engine (GEE); MODIS; Landsat; NOAA AVHRR

Online: 2 September 2019 (04:51:15 CEST)

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Farm activities continued sand winning operations and the allocation of plots of land to prospective developers in Ghana pose a serious threat to the forest covers and lifespan of the Forest and game reserves. With all the positive add ups to the country from forests, Ghana has lost more than 33.7%(equivalent to 2,500,000 hectares) of its forest, since the early 1990s between 2005 and 2010, the rate of deforestation in Ghana was estimated at 2.19% per annum; the sixth highest deforestation rate globally for that period. This shows how important forest monitoring can be to the forestry commission in Ghana. Despite the frameworks which have been developed to help Ghana to protect and restore its forest resources, inadequate monitoring systems remain a barrier to effective implementation. In this study, Google earth engine was used to map and analyze the structural changes of forest cover using JavaScript to query and compute Landsat, MODIS and NOAA AVHRR satellite imageries of the study area (Ghana) with spatial resolutions 30m, 250m and 7km respectively. A supervised classification was performed on three multi-temporal satellite imageries and a total of six major land use and land cover classes were identified and mapped. By using random Forest-classification technique, from 1985 to 2018 recorded by NOAA AVHRR, forest cover has decreased by 66% and 2000 to 2018 recorded by Landsat and MODIS 61% and 47% respectively. A decrease in the forest has been as a result of anthropogenic activities in Ghana. A change detection analysis was performed on these images and it was noted that Ghana is losing forest reserves in every 5years. Overlay of the reserved forest of the 2000 and the classified map of 2018 shows vegetation changed during 2000-2018 remarkably. Therefore, forest-related institutions like the Forestry Commission can employ and use this monitoring system on Google Earth Engine for processing satellite images particularly Landsat, MODIS and NOAA AVHRR for forest cover monitoring and analysis for fast, efficient and reliable results.

Preprint ARTICLE | doi:10.20944/preprints202408.0157.v1

In Search of Easily Accessible and Reliable Malignancy Biomarkers in Liquid Biopsies: The Case of miRNAs in Extracellular Vesicles in the Plasma of Patients with Papillary Thyroid Cancer

Giuseppa D'Amico, Radha Santonocito, Godfrey Grech, Giuseppa Graceffa, Calogero Cipolla, Federics Scalia, Samuele Raccosta, Mauro Manno, Everly Conway de Macario, Alberto J. L. Macario, Francesco Cappello, Francesca Rappa, Celeste Caruso Bavisotto, Claudia Campanella

Subject: Biology And Life Sciences, Life Sciences Keywords: thyroid cancer; extracellular vesicles; microRNAs; cancer biomarkers; chaperone system; Hsp60; CCT; liquid biopsy

Online: 2 August 2024 (12:21:28 CEST)

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Preprint REVIEW | doi:10.20944/preprints202103.0523.v1

'Copper and Bronze in Art' and the Search for Rare Corrosion Products

Gerhard Eggert

Subject: Chemistry And Materials Science, Metals, Alloys And Metallurgy Keywords: basic copper(II) formate; ‘Black Spots’; chalconatronite; copper(II) hydroxide; copper sulfide; curly malachite; namuwite; sodium copper(II) formate; verdigris

Online: 22 March 2021 (11:50:06 CET)

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Preprint ARTICLE | doi:10.20944/preprints202406.2016.v1

Reducing Racial and Ethnic Bias in AI Models: A Comparative Analysis of ChatGPT and Google Bard

Tavishi Choudhary

Subject: Social Sciences, Ethnic And Cultural Studies Keywords: Diversity; Ethical Artificial Intelligence,; Ethnic Bias; Inequality; Racial Bias; Digital Law; Data Bias,; Sentiment Analysis

Online: 28 June 2024 (06:51:06 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202405.1538.v1

A Possibilistic Formulation of Autonomous Search for Targets

Zhijin Chen, Branko Ristic, Du Yong Kim

Subject: Computer Science And Mathematics, Signal Processing Keywords: Possibility theory; autonomous systems; robust estimation

Online: 23 May 2024 (11:16:07 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202404.0896.v1

Interpolation Once Binary Search over a Sorted List

Jun-Lin Lin

Subject: Computer Science And Mathematics, Computer Science Keywords: binary search; interpolation search; interpolated binary search

Online: 15 April 2024 (08:44:02 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202208.0253.v1

Theoretical Search for Gravitational Bound States of Tachyons

Charles Schwartz

Subject: Physical Sciences, Space Science Keywords: General Relativity; Schwarzschild metric; circular flows; tachyons; neutrinos; Dark Matter; black holes

Online: 15 August 2022 (08:26:33 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202111.0107.v1

Dealing with the Ambiguity of Glycan Substructure Search

Vincenzo Daponte, Catherine Hayes, Julien Mariethoz, Frederique Lisacek

Subject: Biology And Life Sciences, Biochemistry And Molecular Biology Keywords: Glycan structure; Knowledge representation; Pattern recognition; Ontology; Semantic web

Online: 5 November 2021 (08:34:05 CET)

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Preprint ARTICLE | doi:10.20944/preprints202107.0241.v1

Consumer Behaviour in Search of a Circular Economy

Antoni Seguí-Alcaraz

Subject: Business, Economics And Management, Accounting And Taxation Keywords: circular economy; environment; consumer

Online: 12 July 2021 (11:14:35 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201807.0040.v1

Comparison of the Automatically Calibrated Google Evapotranspiration Application—EEFlux and the Manually Calibrated METRIC Application

Foad Foolad, Philip Blankenau, Ayse Kilic, Richard G. Allen, Justin L. Huntington, Tyler A. Erickson, Doruk Ozturk, Charles G. Morton, Samuel Ortega, Ian Ratcliffe, Trenton E. Franz, David Thau, Rebecca Moore, Noel Gorelick, Baburao Kamble, Peter Revelle, Ricardo Trezza, Wenguang Zhao, Clarence W. Robison

Subject: Engineering, Civil Engineering Keywords: Google Earth Engine; EEFlux; METRIC; evapotranspiration; Landsat; water resources management

Online: 3 July 2018 (11:51:31 CEST)

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Reliable evapotranspiration (ET) estimation is a key factor for water resources planning, attaining sustainable water resources use, irrigation water management, and water regulation. During the past few decades, researchers have developed a variety of remote sensing techniques to estimate ET. The Earth Engine Evapotranspiration Flux (EEFlux) application uses Landsat imagery archives on the Google Earth Engine platform to calculate the daily evapotranspiration at the local field scale (30 m). Automatically calibrated for each Landsat image, the EEFlux application design is based on the widely vetted Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC) model and produces ET estimation maps for any Landsat 5, 7 or 8 scene in a matter of seconds. In this research we evaluate the consistency and accuracy of EEFlux products that are produced when standard US and global assets are used. Processed METRIC products for 58 scenes distributed around the western and central United States were used as the baseline for comparison. The goal of this paper is to compare the results from EEFlux with the standard METRIC applications to illustrate the utility of the EEFlux products as they currently stand. Given that EEFlux is derived from METRIC, differences are expected to occur due to differing calibration methods (automatic versus manual) and differing input datasets. The products compared include the fraction of reference ET (ETrF), actual ET (ETa), and surface energy balance components net radiation (Rn), ground heat flux (G), and sensible heat flux (H), as well as Ts, albedo and NDVI. The product comparisons show that the intermediate products of Ts, Albedo, and NDVI, and also Rn have similar values and behavior for both EEFlux and METRIC. Larger differences were found for H and G. Despite the more significant differences in H and G, results show that EEFlux is able to calculate ETrF and ETa values comparable to the values from trained expert METRIC users for agricultural areas. For non-agricultural areas such as semi-arid rangeland and forests, the automated EEFlux calibration algorithm needs to be improved in order to be able to reproduce ETrF and ETa that is similar to the manually calibrated METRIC products.

Preprint ARTICLE | doi:10.20944/preprints202311.1793.v1

Estimating the CSLE Biological Conservation Measures B Factor Using Google Earth Engine

Youfu Wu, Haijing Shi, Xihua Yang, Junfeng Shui, Minghang Guo, Li Li

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: B-factor; CSLE; google earth engine; soil erosion; data patching

Online: 28 November 2023 (10:11:26 CET)

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Preprint COMMUNICATION | doi:10.20944/preprints202209.0041.v1

G-Net Light: A Lightweight Modified Google Net for Retinal Vessel Segmentation

Shahzaib Iqbal, Saud Naqvi, Haroon Ahmed, Ahsan Saadat, Tariq M. Khan

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Deep Learning; Convolutional Neural Networks; Medical Image Segmentation

Online: 5 September 2022 (03:12:55 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202402.1125.v1

Water Quality of Eastern Mediterranean Catchments Subject to Different Environmental Pressures Employing Autonomous Unmanned Surface Vehicles (USVs)

Georgios Katsouras, Elias Dimitriou, Sotirios Karavoltsos, Stylianos Samios, Aikaterini Sakellari, Angeliki Mentzafou, Nikolaos Tsalas, Michael Scoullos

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: remote sensing; water quality; autonomous USV; inland and coastal waters; telemetric stations

Online: 20 February 2024 (11:49:48 CET)

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Preprint ARTICLE | doi:10.20944/preprints202311.0077.v1

Network Reconfiguration for Loss Reduction using Tabu Search and a Voltage Drop

Dionicio Zocimo Ñaupari Huatuco, Luiz Filho, Franklin Simeon Pucuhuayla, Yuri Percy M. Rodriguez

Subject: Engineering, Electrical And Electronic Engineering Keywords: network reconfiguration; distribution system; optimization; Tabu Search; minimization; distribution system loss; OpenDSS; Python

Online: 2 November 2023 (07:01:03 CET)

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Preprint ARTICLE | doi:10.20944/preprints202402.1216.v1

Mapping Garlic Crops and Change Analysis in the Erhai Lake Basin Based on Google Earth Engine

Wenfeng Li, Jiao Pan, Wenyi Peng, Yngzhi Li, Chao Li

Subject: Biology And Life Sciences, Agricultural Science And Agronomy Keywords: GEE; Erhai Lake Basin; Garlic Extract; Feature Selection; Random Forest

Online: 21 February 2024 (10:23:03 CET)

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Preprint ARTICLE | doi:10.20944/preprints202307.0800.v1

Forest Monitoring Based on Sentinel-2 Satellite Imagery, Google Earth Engine Cloud Computing, and Machine Learning

Tamás Molnár, Géza Király

Subject: Biology And Life Sciences, Forestry Keywords: forest monitoring; remote-sensing; satellite image; bark beetle damage; Sentinel-2; vegetation index; water index

Online: 12 July 2023 (11:13:47 CEST)

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Preprint TECHNICAL NOTE | doi:10.20944/preprints202208.0484.v1

A Simple Procedure to Preprocess and Ingest High-Resolution Ocean Color Data into Google Earth Engine

Elígio de Raús Maúre, Simon Ilyushchenko, Genki Terauchi

Subject: Environmental And Earth Sciences, Oceanography Keywords: remote sensing; ocean color; Google Earth Engine; MODIS/Aqua, SGLI/GCOM-C, swath reprojection, Earth Engine data ingestion

Online: 29 August 2022 (10:09:58 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202102.0513.v1

Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun Rule

Lucas Terres de Lima, Sandra Fernández-Fernández, João Francisco Gonçalves, Luiz Magalhães Filho, Cristina Bernardes

Subject: Environmental And Earth Sciences, Atmospheric Science And Meteorology Keywords: Sea-Level Rise; GIS; Open-Source Software; Modeling

Online: 23 February 2021 (12:39:09 CET)

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Preprint ARTICLE | doi:10.20944/preprints202102.0421.v1

Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun Rule

Lucas Terres de Lima, Sandra Fernández-Fernández, João Francisco Gonçalves, Luiz Magalhães Filho, Cristina Bernardes

Subject: Environmental And Earth Sciences, Atmospheric Science And Meteorology Keywords: Sea-Level Rise; GIS; Open-Source Software; Modeling

Online: 18 February 2021 (13:52:49 CET)

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Preprint ARTICLE | doi:10.20944/preprints202012.0701.v1

Impacts of COVID-19 Pandemic and Its Lockdown on Global Eating Behavior: A Google Trends Analysis

Hung Nguyen Ngoc, Wantanee Kriengsinyos

Subject: Biology And Life Sciences, Food Science And Technology Keywords: COVID-19; eating behavior; diet; food concern; Google Trends; health behavior.

Online: 28 December 2020 (12:55:42 CET)

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COVID-19 pandemic and its restrictive measures have present serious unprecedented challenges to human eating behavior. Given that Google Search has become a valuable information resource to examine, predict, and estimate human online interests and behavior, that somehow linked to real people concerns. This study aimed to investigate the features and evaluate the impacts of the COVID-19 pandemic and its lockdown on consumer worldwide interest in eating behavior and its related factors. Google Trends-Relative Search Volumes (RSV) of distinct keywords related to eating behavior, were obtained from a timeframe before and during the COVID-19 pandemic, from January 1, 2018, to December 13, 2020. During the global lockdown from March 11, 2020, to June 30, 2020, RSV curves exhibited a short-term fluctuation of interest in multiple keywords related to eating behavior and its related factors such as food purchasing, food security, food poisoning, panic buying, stocking up, health awareness and mental illness. Spearman’s correlation analysis showed a strong correlation between daily confirmed cases and examined keywords. Univariate repeated measures ANOVA following with Bonferroni Post-hoc test revealed that during the year with the presence of COVID-19 pandemic, people worldwide pay more concerns in each keyword (1) environmental and economic factors (unemployment: +269%, food shortage: +180%, food bank: +50%); (2) health- and food-safety concerns (immunity: +138%, vitamin C: +90%, vitamin D: +55%, zinc: +47%, food storage containers: +40%, food packaging: +31%); (3) food choices and interest (local meat: +84%, frozen food: +67%, CSA: +65%, flour: +66%, bread: +53%, soybean oil: +45%, local fruit: +43%, canned tomato: +42%, refrigerated food: +41%, canned meat: +39%, pancake: +37%, cookie: +29%, butter: +29%, canned fish: +29%, liquior: +20%); (4) social and individual factors (take-out: +128%, deliver: +53%), (6) lifestyle factors (stationary bicycle: +110%, dumbbell: +89%, yoga mat: +84%, treadmill: +65%, grocery store: +51%); (6) psychological factors (isolation: +113%). COVID-19 pandemic and its lockdown have had far-reaching effects on global concerns in many factors related to human eating behavior. Swift action is necessarily performed to strengthen the resilience of the food supply chain system, support and adapt to the new normal behavior, and mitigation the profound negative changes, especially targeting those in high-risks and vulnerable groups and food-insecure regions.

Preprint ARTICLE | doi:10.20944/preprints202405.0284.v1

Lead Detection with Sentinel-1 in the Beaufort Gyre using Google Earth Engine

Jullian C.B. Williams, Stephen F. Ackley, Alberto M. Mestas-Nuñez, Grant J. Macdonald

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: sea ice; cryosphere; Arctic Ocean; Beaufort Sea; Leads; Google Earth Engine

Online: 6 May 2024 (10:12:06 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202408.0152.v1

Effects of Icon Grouping based on Familiartity on Search Times and Eye Movements

Yujeong Ha, Seung-Kweon Hong

Subject: Engineering, Industrial And Manufacturing Engineering Keywords: visual search; icon grouping; familiarity of icon; color contrast ratio

Online: 2 August 2024 (10:45:02 CEST)

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Preprint REVIEW | doi:10.20944/preprints202401.2087.v1

Understanding and Modeling the Pathophysiology of Hydrocephalus: In Search of Better Treatment Options

Verayna Newland, Bonnie L. Blazer-Yost

Subject: Biology And Life Sciences, Neuroscience And Neurology Keywords: choroid plexus; cerebrospinal fluid; electrolyte transport; ventriculomegaly; preclinical hydrocephalic models

Online: 31 January 2024 (01:51:21 CET)

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Preprint ARTICLE | doi:10.20944/preprints202305.1456.v1

Distraction and Visual Search Characteristics of Young Drivers When Using Navigation System Displays

Tamer Yared, Patrick Patterson, Ahmad Mumani

Subject: Engineering, Safety, Risk, Reliability And Quality Keywords: Navigation System display; Distraction; Visual Search Behavior; Fixation; Dwell; Eye-tracking; Young Drivers; Night Driving; Driving Safety

Online: 22 May 2023 (03:38:37 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202206.0397.v1

Improve Ubiquitination-site Prediction Using Physicochemical Properties and Machine Learning with Grid Search

Xiaoye Mo, Samuel Cho, Xia Jiang

Subject: Computer Science And Mathematics, Computer Science Keywords: ubiquitination; ubiquitination-site; PCP; protein physicochemical properties; prediction; machine learning; grid search

Online: 29 June 2022 (07:48:46 CEST)

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ABSTRACT Background Ubiquitination plays an important role in protein post-translational processes and has been found to be involved in a number of regulatory functions including proteasome degradation, DNA repair, transcription, signal transduction, endocytosis, and sorting. As the identification of ubiquitination site is critical to furthering our understanding of the mechanism of ubiquitination, various experimental and machine learning methods have been used to conduct this task. It has been an important but challenging task to improve the accuracy of ubiquitination site prediction. In this research, we explore the possibility of improving the prediction performance of machine learning by incorporating grid search in the training process. Method We developed grid search procedures for each of six widely used machine learning methods including NB, LR, DT, SVM, LASSO, and KNN, and applied them to ubiquitination site prediction using the six PCP datasets that were previously developed. For each of the ML methods, we developed a set of values for each of the tunable hyperparameters available to the method. These sets of values then can be combined to form a large grid of hyperparameter settings, and each of these settings is used in the grid search. We integrated 5-fold cross-validation in grid search to train and test ML models and applied an additional independent validation procedure by conducting a pre-training 80-20 sample split. We evaluated the performance of the six methods by comparing them side by side for each of the six datasets. We also compared the grid search results with the results that were previously published without doing grid search. To optimize the prediction performance, we trained 1.1 million ML models in total through grid search. Results We compared the overall prediction performance of these six methods, as well as their prediction performance when working with balanced vs. imbalanced data, and large-scale vs. small-scale data. From the perspective of dataset, we find that the overall performance of every PCP dataset has been significantly improved in this study compared to the previous study, with the percentage increase of the average AUC of all six datasets ranging from 7.9% (PCP-4) up to 17.0% (PCP-1). From the perspective of method, we find that three out of four methods significantly benefit from grid search comparing to their previously published non-grid search results, with the maximum AUC improvement as high as 47% (LASSO on PCP-5), 43.3% (NB on PCP-1), and 33.7% (SVM on PCP-6). SVM overall ranks number one, followed by KNN as the number two performer based on their average AUCs on all datasets. But these two also ranked the top two (KNN 76 days and SVM 15 days) in terms of the total running time that they need to do grid search. We also find that SVM, KNN, and DT tend to handle small-scale and imbalanced datasets better, while LR, and LASSO are doing well with large-scale and balanced datasets. NB is more sensitive to data imbalance while less sensitive to the size of a dataset. Conclusions Our results show that using grid search has improved the performance of ubiquitination prediction significantly. We find that the performance of a method is closely related to its hyperparameter setting and the type of data it handles. Even though SVM is on average an outperformer, none of the methods can provide the best performance for all datasets. When sufficient computing resources are well accessible, grid search is an effective way to identify both a top performing model for a machine learning method and a suitable machine learning method for a particular dataset.

Preprint ARTICLE | doi:10.20944/preprints202407.1274.v1

Political Bias in AI-Language Models: A Comparative Analysis of ChatGPT-4, Perplexity, Google Gemini, and Claude

Tavishi Choudhary

Subject: Social Sciences, Political Science Keywords: Artificial Intelligence (AI); Bias in Algorithms; Ethical Artificial Intelligence; Language Models; Political Bias

Online: 16 July 2024 (05:25:50 CEST)

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Artificial intelligence (AI) driven language models have seen a rapid rise in development, deployment, and adoption over the last few years. This surge has sparked many discussions about their societal and political impact, including political bias. Bias is a crucial topic in the context of large models due to its far-reaching consequences on technology, politics, and society. It significantly influences public perception, decision-making, political discourse, and AI policy governance and ethics. This study investigates political bias through a comparative analysis of four prominent AI models: ChatGPT-4, Perplexity, Google Gemini, and Claude.Through a comprehensive analysis by systematically and categorically evaluating their responses to politically and ideologically charged tests and prompts, utilizing the Pew Research Center’s Political Typology Quiz, the Political Compass assessment, and ISideWith political party quiz, this study identifies significant ideological leanings and the nature of political bias within these models. The findings revealed that ChatGPT-4 and Claude exhibit a liberal bias, Perplexity is more conservative, while Google Gemini adopts more centrist stances. The presence of such biases underscores the critical need for transparency in AI development and the incorporation of diverse training datasets, regular audits, and user education to mitigate these biases. This analysis also advocates for more robust practices and comprehensive frameworks to assess and reduce political bias in AI, ensuring these technologies contribute positively to society and support informed, balanced, and inclusive public discourse, which will point towards neutrality.The results of this study add to the ongoing discourse about the ethical implications and development of AI models, highlighting the critical need to build trust and integrity in AI models. Additionally, future research directions have been outlined to explore and address the complex issue of bias in AI.

Preprint ARTICLE | doi:10.20944/preprints202305.0393.v1

Evaluation of Replies to Voice Queries in Gynecologic Oncology by Virtual Assistants Siri, Alexa, Google, and Cortana

Jamie M Land, Edward J. Pavlik, Elizabeth Ueland, Sara Ueland, Nicholas Per, Kristen Quick, Justin W. Gorski, McKayla J. Riggs, Megan L. Hutchcraft, Josie D. Llanora, Do Hyun Yun

Subject: Public Health And Healthcare, Other Keywords: Virtual assistants; Gynecologic; Oncology; Siri; Alexa; Google; Cortana; Validity

Online: 6 May 2023 (08:42:27 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202106.0473.v1

Application of Earth Observation Data and Google Earth Engine for Monitoring Coral Reef Exposure to Environmental Stressors

Michael J. Williamson, Emma J. Tebbs, Henry J. Thompson, Terrence P. Dawson, Catherine E. I. Head, David M. P. Jacoby

Subject: Biology And Life Sciences, Anatomy And Physiology Keywords: bleaching; coral reef; environmental stress; Google Earth Engine; monitoring; remote sensing; satellite

Online: 18 June 2021 (10:43:50 CEST)

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Coral reefs are critical ecosystems globally for marine fauna, biodiversity and through the services they provide to humanity. However, they are significantly threatened by anthropogenic stressors, such as climate change. By combining 9 environmental variables and ecological and health-based thresholds obtained from the available literature, we develop, using fuzzy logic (discontinuous functions), a Coral Reef Stress Exposure Index (CRSEI) for remotely monitoring coral reef exposure to environmental stressors. Our approach capitalises on the abundance of readily available satellite Earth Observation (EO) data available in the Google Earth Engine (GEE) cloud-based geospatial processing platform. CRSEI values from 3157 distinct reefs were generated and mapped across 12 important coral reef ecosystem regions. Quantitative analyses indicated that the index detected significant temporal differences in stress and was, therefore, able to capture historic change at a global scale. We also applied the CRSEI to three case-study reef ecosystems, previously well-monitored for stress and disturbance using other methods. PCA analysis indicated that depth, current, sea surface temperature (SST) and SST anomaly accounted for the greatest contribution to the variance in stress in these three regions. The CRSEI corroborated temporal and spatial differences in stress exposure from known disturbances within these reference regions, in addition to identifying the potential drivers of inter- and intra-region differences in stress, namely depth, degree heating weeks and SST anomaly. We discuss how the index can be further improved in future with site-specific thresholds for each stress variable, and the incorporation of additional variables not currently available in GEE. This index provides an open access tool, built around a free and powerful processing platform, that has broad potential to assist in the regular monitoring of our increasingly imperilled coral reef ecosystems, and, in particular, those that are remote or inaccessible.

Preprint ARTICLE | doi:10.20944/preprints202312.1168.v1

Search for Novel Phases in Y-Ba-Cu-O Family

Danijel Djurek

Subject: Physical Sciences, Condensed Matter Physics Keywords: thermo-acoustic resonator; delafossites; spin-charge separation; spinons; holons

Online: 19 December 2023 (04:46:17 CET)

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Preprint ARTICLE | doi:10.20944/preprints202309.1273.v1

Facial Emotions Detection using an Efficient Neural Architecture Search Network

Usman Islam, Rabbia Mahum, AdulMalik AlSalman, Mohamed Sharaf, Haseeb Hassan, Bingding Huang

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Facial Emotion Detection; Deep Learning; Classification; Neural Architecture Search Network

Online: 20 September 2023 (03:36:23 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202308.1279.v1

A Purely Entity-Based Semantic Search Approach for Document Retrieval

Mohamed Lemine SIDI, Serkan GUNAL

Subject: Computer Science And Mathematics, Information Systems Keywords: Keywords: Information Retrieval; Document Retrieval; Knowledge graphs; Entity-based Search; Entity Linking.

Online: 17 August 2023 (09:47:09 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202308.0955.v1

Dual Neighborhoods Search for Solving The Minimum Dominating Tree Problem

Ze Pan, Xinyun Wu, Caiquan Xiong

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Meta-heuristic; Dominating tree; Dual neighborhoods; Fast neighborhood evaluation; Optimization

Online: 14 August 2023 (09:13:05 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0309.v1

A Machine Learning Python-based Search Engine Optimization Audit Software

Konstantinos I. Roumeliotis, Nikolaos D. Tselikas

Subject: Computer Science And Mathematics, Software Keywords: search engine optimization; seo techniques; python seo tool; machine learning seo

Online: 5 June 2023 (10:38:37 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202207.0385.v1

Stochastic Thermal Load Dispatch Employing Opposition-based Greedy Heuristic Search

Manmohan Singh, JS Dhillon

Subject: Engineering, Electrical And Electronic Engineering Keywords: fuzzy theory; heuristic search; stochastic economic load dispatch; risk analysis

Online: 26 July 2022 (05:21:14 CEST)

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Preprint CONCEPT PAPER | doi:10.20944/preprints202107.0533.v1

In Search of a Social Master Frame for Energy Transition

Giorgio Osti

Subject: Business, Economics And Management, Accounting And Taxation Keywords: energy; transition; socialisation; meta frame; master frame

Online: 23 July 2021 (10:03:02 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202104.0660.v1

The Search for the Universality Class of Metric Quantum Gravity

Riccardo Martini, Alessandro Ugolotti, Omar Zanusso

Subject: Physical Sciences, Acoustics Keywords: quantum gravity; universality; asymptotic safety

Online: 26 April 2021 (12:08:28 CEST)

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Preprint REVIEW | doi:10.20944/preprints201807.0606.v1

Mechanisms of Protein Search for Targets on DNA: Theoretical Insights

Alexey A. Shvets, Maria P. Kochugaeva, Anatoly B. Kolomeisky

Subject: Chemistry And Materials Science, Theoretical Chemistry Keywords: protein-DNA interactions; facilitated diffusion; protein target search; discrete-state stochastic models

Online: 31 July 2018 (05:39:04 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202107.0622.v1

An Extensible and Modular Design and Implementation of Monte Carlo Tree Search for the JVM

Larkin Liu, Jun Tao Luo

Subject: Computer Science And Mathematics, Information Systems Keywords: Monte Carlo Tree Search, Software Design, Markov Decision Process

Online: 28 July 2021 (10:29:08 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202008.0487.v1

Extracting Reliable Twitter Data for Flood Risk Communication using Manual Assessment and Google Vision API from Text and Images

Xiaohui Liu, Bandana Kar, Francisco Alejandro Montiel Ishino, Chaoyang Zhang, Faustine Williams

Subject: Social Sciences, Geography, Planning And Development Keywords: Twitter; data reliability; risk communication; data mining; Google Cloud Vision API

Online: 22 August 2020 (02:32:40 CEST)

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Working Paper ARTICLE

A Rapid Extraction Method for Regional-Scale Agricultural Disasters Based on Google Earth Engine

Zhengrong Liu, Huanjun Liu, Chong Luo, Haoxuan Yang, Xiangtian Meng, Yongchol Ju, Dong Guo

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: Google Earth Engine; MODIS; disaster monitoring; remote sensing index

Online: 21 July 2020 (03:12:22 CEST)

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Remote sensing has been used as an important tool for disaster monitoring and disaster scope extraction, especially for the analysis of spatial and temporal disaster patterns of large-scale and long-duration series. Based on the Google Earth Engine cloud platform, this study used MODIS vegetation index products with 250-m spatial resolution synthesized over 16 days from the period 2005–2019 to develop a rapid and effective method for monitoring disasters across a wide spatiotemporal range. Three types of disaster monitoring and scope extraction models are proposed: the normalized difference vegetation index (NDVI) median time standardization model (R_{NDVI_TM(i)}), the NDVI median phenology standardization model (R_{NDVI_AM(i)(j)}), and the NDVI median spatiotemporal standardization model (R_{NDVI_ZM(i)(j)}). The optimal disaster extraction threshold for each model in different time phases was determined using Otsu’s method, and the extraction results were verified by medium-resolution images and ground-measured data of the same or quasi-same period. Finally, the disaster scope of cultivated land in Heilongjiang Province from 2010–2019 was extracted, and the spatial and temporal patterns of the disasters were analyzed based on meteorological data. This analysis revealed that the three aforementioned models exhibited high disaster monitoring and range extraction capabilities, with verification accuracies of 97.46%, 96.90%, and 96.67% for R_{NDVI_TM(i)}, R_{NDVI_AM(i)}, and _(j)R_{NDVI_ZM(i)(j)}, respectively. The spatial and temporal disaster distributions were found to be consistent with the disasters of the insured plots and the meteorological data across the entire province. Moreover, different monitoring and extraction methods were used for different disasters, among which wind hazard and insect disasters often required a delay of 16 days prior to observation. Each model also displayed various sensitivities and were applicable to different disasters. Compared with other techniques, the proposed method is fast and easy to implement. This new approach can be applied to numerous types of disaster monitoring as well as large-scale agricultural disaster monitoring and can easily be applied to other research areas. This study presents a novel method for large-scale agricultural disaster monitoring.

Preprint ARTICLE | doi:10.20944/preprints202007.0072.v1

A Rapid Extraction Method of Regional Scale Agricultural Disasters Based on Google Earth Engine

Zhengrong Liu, Huanjun Liu, Chong Luo, Haoxuan Yang, Yongchol Ju, Dong Guo

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: Google Earth Engine; MODIS; Disaster monitoring

Online: 5 July 2020 (12:32:00 CEST)

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Remote sensing has been used as an important tool for disaster monitoring and disaster scope extraction, especially for the analysis of temporal and spatial disasters patterns of large-scale long time series. In order to find out a rapid and effective method to monitor disaster in a wide range, based on the Google Earth Engine cloud platform, this study used MODIS vegetation index products of 250 meter spatial resolution synthesized in 16 days during the year 2005-2019 and three kinds of disaster monitoring and scope extraction models are proposed: normalized vegetation index median time standardization (RNDVI_TM(i)) model, the normalized vegetation index median phenology Standardization(RNDVI_AM(i)(j)) model, normalized vegetation index median spatiotemporal Standardization (RNDVI_ZM(i)(j)) model. The optimal threshold of disaster extraction for each model in different time phases was determined by Otsu method, and the extraction results were verified by Medium resolution image and ground measured data of the same or quasi-same period. Finally, the disaster scope of cultivated land in Heilongjiang province from 2010 to 2019 was extracted and the temporal and spatial pattern of disasters was analyzed based on the meteorological data. It shows that the three above-mentioned models have high disaster monitoring and range extraction capabilities with the verification accuracy of RNDVI_TM(i) 97.46%, RNDVI_AM(i)(j) 96.90%, and RNDVI_ZM(i)(j) 96.67% respectively. The spatial and temporal distribution of disasters is consistent with the disaster of the insured plots and meteorological data in the whole province. Meanwhile, it turns out that different monitoring and extraction methods are used in different disasters, among which wind hazard and insect disasters often need to be delayed for 16 days to observe. Each model also has various sensitivity and applicability to different disasters. Compared with other methods, this method is fast, and convenient, which allows it to be used for large-scale agricultural disaster monitoring and is easy to be applied into other research areas. The research provides a new idea for large-scale agricultural disaster monitoring.

Preprint ARTICLE | doi:10.20944/preprints202402.0442.v1

Search for Extreme Mass Ratio Inspirals using Particle Swarm Optimization and Reduced Dimensionality Likelihoods

Xiao-Bo Zou, Soumya D. Mohanty, Hong-Gang Luo, Yu-Xiao Liu

Subject: Physical Sciences, Astronomy And Astrophysics Keywords: LISA; Gravitational Waves; EMRI; PSO; Likelihood Ratio

Online: 7 February 2024 (11:51:12 CET)

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Preprint ARTICLE | doi:10.20944/preprints202005.0002.v1

Grammar Guided Genetic Programming for Network Architecture Search and Road Detection on Aerial Orthophotography

Víctor de la Fuente Castillo, Alberto Díaz-Álvarez, Miguel-Ángel Manso-Callejo, Francisco Serradilla García

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Grammar Evolution; Deep Learning; Network Architecture Search; Grammar Guided Genetic Programming

Online: 2 May 2020 (11:36:18 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201811.0436.v1

Comparing Supervised Machine Learning Strategies and Linguistic Features to Search for Very Negative Opinions

Sattam Almatarneh, Pablo Gamallo

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: sentiment analysis; opinion mining; linguistic features; classification; very negative opinions

Online: 19 November 2018 (09:35:13 CET)

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Preprint ARTICLE | doi:10.20944/preprints202309.0285.v1

Assessment of Land Desertification in the Brazilian East Atlantic Region using the Medalus Model and Google Earth Engine

Theilon Henrique de Jesus Macêdo, Cristiano Tagliaferre, Bismarc Lopes da Silva, Alessandro De Paula, Odair Lacerda Lemos, Felizardo Adenilson Rocha, Rosilene Gomes de Souza Pinheiro, Ana Carolina Santos Lima

Subject: Environmental And Earth Sciences, Environmental Science Keywords: Environmental Sensitivity; Modeling; Environmental Quality; Cloud computing

Online: 6 September 2023 (14:50:48 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202309.0316.v1

Assessment of Land Desertification in the Brazilian East Atlantic Region Using the Medalus Model and Google Earth Engine

Theilon Henrique de Jesus Macêdo, Cristiano Tagliaferre, Bismarc Lopes da Silva, Alessandro De Paula, Odair Lacerda Lemos, Felizardo Adenilson Rocha, Rosilene Gomes de Souza Pinheiro, Ana Carolina Santos Lima

Subject: Environmental And Earth Sciences, Environmental Science Keywords: Environmental Sensitivity; Modeling; Environmental Quality; Cloud computing

Online: 6 September 2023 (13:53:12 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202206.0020.v1

Comparison of Lake Area Extraction Algorithms in Qinghai-Tibet Plateau Leveraging Google Earth Engine and Landsat-9 Data

Xusheng Li, Donghui Zhang, Chenchen Jiang, Yingjun Zhao, Hu Li, Donghua Lu, Kai Qin, Donghua Chen, Yufeng Liu, Yun Sun, Saisai Liu

Subject: Environmental And Earth Sciences, Environmental Science Keywords: Landsat-9 data; Qinghai-Tibet Plateau; Lake Waterbody; GEE; Algorithms comparison

Online: 1 June 2022 (13:14:56 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202402.1671.v1

Bioactive Properties of Venoms Isolated from Whiptail Stingrays and the Search for Molecular Mechanisms and Targets

Craig A. Doupnik, Carl A. Luer, Catherine J. Walsh, Jessica Restivo, Jacqueline Xinlan Brick

Subject: Medicine And Pharmacology, Pharmacology And Toxicology Keywords: apoptosis; cell adhesion; cell growth; fibrosarcoma; galectin-like proteins; stingray; toxin; venom

Online: 29 February 2024 (11:41:25 CET)

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Preprint REVIEW | doi:10.20944/preprints202307.1828.v1

Effects of Dichlorodiphenyltrichloroethane on Female Reproductive Tract Leading to Infertility and Cancer: Systematic Search and Review

Shermeen Syed, Shandana Qasim, Maheen Ejaz, Sammar Malik, Nimra Khan, Haider Ali, Himasadat Zaker, Eleftheria Hatzidaki, Charalampos Mamoulakis, Aristides M. Tsatsakis, Syed Tahir Abbas Shah, Saira Amir

Subject: Biology And Life Sciences, Toxicology Keywords: Dichlorodimethyltrichloroethane; Endocrine Disruptors; Female; Infertility; Neoplasms; Persistent Organic Pollutants; DDTs

Online: 27 July 2023 (09:33:22 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202409.1396.v1

Search for True Ternary Fission in the Reaction ⁴⁰Ar+²⁰⁸Pb

Md Ashaduzzaman, Antonio Di Nitto, Emanuele Vardaci, Giovanni La Rana, Pia Antonella Setaro, Tathagata Banerjee, Antonio Vanzanella, Giuseppe Alifano

Subject: Physical Sciences, Nuclear And High Energy Physics Keywords: Ternary Fission; Fusion-fission reactions; Heavy ions; Spectrometers for nuclear physics

Online: 18 September 2024 (12:37:30 CEST)

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Preprint TECHNICAL NOTE | doi:10.20944/preprints202404.1595.v1

Get Free Copy: A Multi-Repository Search Platform for Biomedical Publications

Nodir Kosimkhujaev, Kuan-lin Huang

Subject: Biology And Life Sciences, Other Keywords: open science; preprint; web platform

Online: 24 April 2024 (10:03:29 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.1210.v1

Inverse Evaluation of Monopile Pile-soil Interaction Parameters Using Random Search

Hou Qiao, Wei Li, Zhenqiang Jiang, Chuanrui Guo

Subject: Engineering, Marine Engineering Keywords: offshore wind; parameter inversion; pile-soil interaction; random search

Online: 16 June 2023 (10:13:49 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202212.0481.v1

EJS: Multi-Strategy Enhanced Jellyfish Search Algorithm for En-Gineering Applications

Gang Hu, Jiao Wang, Min Li, Abdelazim Hussien, Muhammad Abbas

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Meta-heuristic algorithm; Jellyfish search algorithm; Sine and cosine learning factors; Local escape operator; Opposition-based learning

Online: 26 December 2022 (09:06:46 CET)

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Preprint ARTICLE | doi:10.20944/preprints202007.0122.v1

A Tryptophan-based Assay Method to Search Regulatory Compounds for TCTP

Seri Jo, Eun-Wha Jang, Mi-Sun Kim, Suwon Kim, Kyunglim Lee, Dong Hae Shin

Subject: Biology And Life Sciences, Biochemistry And Molecular Biology Keywords: Transcriptionally controlled tumor protein (TCTP); Tryptophan; Florescence; Flavonoid; Native gel electrophoresis

Online: 7 July 2020 (09:49:17 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202001.0318.v1

Efficient Binary Symbiotic Organisms Search Algorithm Approaches for Feature Selection Problems

Hekmat Mohmmadzadeh, Farhad Soleimanian Gharehchopogh

Subject: Computer Science And Mathematics, Computer Science Keywords: efficient binary symbiotic; feature selection; classification; optimization

Online: 26 January 2020 (08:30:17 CET)

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Feature selection is one of the main data preprocessing steps in machine learning. Its goal is to reduce the number of features by removing extra and noisy features. Feature selection methods must consider the accuracy of classification algorithms while performing feature reduction on a dataset. Meta-heuristic algorithms are the most successful and promising methods for solving this issue. The symbiotic organisms search algorithm is one of the successful meta-heuristic algorithms which is inspired by the interaction of organisms in the nature called Parasitism Commensalism Mutualism. In this paper, three engulfing binary methods based on the symbiotic organisms search algorithm are presented for solving the feature selection problem. In the first and second methods, several S-shaped and V-shaped transfer functions are used for binarizing the symbiotic organisms search algorithm, respectively. These methods are called BSOSS and BSOSV. In the third method, two new operators called BMP and BCP are presented for binarizing the symbiotic organisms search algorithm. This method is called EBSOS. The third approach presents an advanced binary version of the coexistence search algorithm with two new operators, BMP and BCP, to solve the feature selection problem, named EBSOS. The proposed methods are run on 18 standard UCI datasets and compared to base and important meta-heuristic algorithms. The test results show that the EBSOS method has the best performance among the three proposed approaches for binarization of the coexistence search algorithm. Finally, the proposed EBSOS approach was compared to other meta-heuristic methods including the genetic algorithm, binary bat algorithm, binary particle swarm algorithm, binary flower pollination algorithm, binary grey wolf algorithm, binary dragonfly algorithm, and binary chaotic crow search algorithm. The results of different experiments showed that the proposed EBSOS approach has better performance compared to other methods in terms of feature count and accuracy criteria. Furthermore, the proposed EBSOS approach was practically evaluated on spam email detection in particular. The results of this experiment also verified the performance of the proposed EBSOS approach. In addition, the proposed EBSOS approach is particularly combined with the classifiers including SVM, KNN, NB and MLP to evaluate this method performance in the detection of spam emails. The obtained results showed that the proposed EBSOS approach has significantly improved the accuracy and speed of all the classifiers in spam email detection.

Preprint ARTICLE | doi:10.20944/preprints201807.0212.v1

Optical Pumping of TeH⁺: Implications for Search for Varying m_p/m_e

Patrick R. Stollenwerk, Mark G. Kokish, Antonio G. S. de Oliveira-Filho, Fernando R. Ornellas, Brian C. Odom

Subject: Physical Sciences, Atomic And Molecular Physics Keywords: time variation of constants; proton-electron mass ratio; molecular ion; laser cooling

Online: 12 July 2018 (08:04:03 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201711.0128.v1

Quantum Inspired General Variable Neighborhood Search (qGVNS) for Dynamic Garbage Collection

Christos Papalitsas, Panayiotis Karakostas, Theodore Andronikos, Spyros Sioutas, Konstantinos Giannakis

Subject: Computer Science And Mathematics, Computer Science Keywords: metaheuristics; VNS; quantum inspired; qGVNS; optimization; TSP; routing algorithms; GPS application; garbage collection

Online: 20 November 2017 (11:37:18 CET)

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Preprint ARTICLE | doi:10.20944/preprints201805.0274.v1

A Prototype of Speech Interface Baed on Google Cloud Platform to Access a Semantic Website

Jimmy Aurelio Rosales-Huamani, José Luis Castillo-Sequera, Juan Carlos Montalvan-Figueroa, Joseps Andrade-Choque

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: artificial intelligence; semantic web; natural language; Google cloud speech; SPARQL

Online: 21 May 2018 (12:38:00 CEST)

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Preprint REVIEW | doi:10.20944/preprints202407.1177.v1

Challenges and Obstacles in the Use of Search and Rescue Dogs During Disaster Operations: A Case Study of the Earthquake in Turkey

Vladimir M. Cvetković, Nemanja Miljković

Subject: Social Sciences, Safety Research Keywords: search and rescue (SAR) dogs; disaster response; earthquake; environmental challenges; equip-ment needs; cultural perceptions; logistical hurdles; rescue operations; Turkey earthquake 2023; rescue dog safety

Online: 16 July 2024 (05:35:27 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202408.2273.v1

Self-adaptive Differential Evolution for Multi-objective Optimization with Local Search and Indicator-based Selection

Datong Xie

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: multi-objective optimization; self-adaptive differential evolution; orthogonal design; indicator-based selection; local search; k-nearest neighbor

Online: 30 August 2024 (15:54:27 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202407.0359.v1

In Search of Phytoremediation Candidates: Eu(III) Bioassociation and Root Exudation in Hydroponically Grown Plants

Max Klotzsche, Viktor Dück, Björn Drobot, Manja Vogel, Johannes Raff, Thorsten Stumpf, Robin Steudtner

Subject: Environmental And Earth Sciences, Pollution Keywords: europium; speciation; phytoremediation; bioassociation; laser spectroscopy; lanthanides; hydroponics; plant uptake; root exudates; thermodynamic modelling

Online: 3 July 2024 (16:13:19 CEST)

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