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Preprint ARTICLE | doi:10.20944/preprints202303.0252.v1

Do Computerized False Belief Tasks Impact Mentalizing Ability in People with Williams Syndrome?

Ching-fen Hsu, Shi-yu Rao

Subject: Social Sciences, Education Keywords: false belief; Williams syndrome; theory of mind; social cognition

Online: 14 March 2023 (09:02:41 CET)

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Preprint ARTICLE | doi:10.20944/preprints202006.0279.v2

COVID-19 Testing – Impact of Prevalence, Sensitivity, and Specificity on Patient Risk and Cost

Zoe C. Brooks, Saswati Das

Subject: Medicine And Pharmacology, Pathology And Pathobiology Keywords: COVID19; risk; clinical; metrics; cost; false-positive; false-negative; prevalence; sensitivity; specificity

Online: 9 July 2020 (15:57:30 CEST)

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Preprint REVIEW | doi:10.20944/preprints202104.0481.v1

Minimizing Errors in RT-PCR Detection and Quantification of SARS-CoV-2 RNA for Wastewater Surveillance

Warish Ahmed, Stuart Simpson, Paul Bertsch, Kyle Bibby, Aaron Bivins, Linda Blackall, Silvia Bofill-Mas, Albert Bosch, Joao Brandao, Phil Choi, Mark Ciesielski, Erica Donner, Nishita D'Souza, Andreas Farnleitner, Daniel Gerrity, Raul Gonzalez, John Griffith, Pradip Gyawali, Charles Haas, Kerry Hamilton, Chanditha Hapuarachchi, Valerie Harwood, Rehnuma Haque, Greg Jackson, Stuart Khan, Wesaal Khan, Masaaki Kitajima, Asja Korajkic, Giuseppina La Rosa, Blythe Layton, Erin Lipp, Sandra McLellan, Brian McMinn, Gertjan Medema, Suzanne Metcalfe, Wim Meijer, Jochen Mueller, Heather Murphy, Colleen Naughton, Rachel Noble, Sudhi Payyappat, Susan Petterson, Tarja Pitkanen, Veronica Rajal, Brandon Reyneke, Fernando Roman, Joan Rose, Marta Rusinol, Michael Sadowsky, Laura Sala-Comorera, Yin Xiang Setoh, Samendra Sherchan, Kwanrawee Sirikanchana, Wendy Smith, Joshua Steele, Rosalie Sabburg, Erin Symonds, Phong Thai, Kevin Thomas, Josh Tynan, Simon Toze, Janelle Thompson, Andy Whiteley, Judith Wong, Daisuke Sano, Stefan Wuertz, Irene Xagoraraki, Qian Zhang, Amity Zimmer-Faust, Orin Shanks

Subject: Environmental And Earth Sciences, Waste Management And Disposal Keywords: COVID-19; SARS-CoV-2; Wastewater; Surveillance; False-positive; False-negative; RT-PCR

Online: 19 April 2021 (13:08:13 CEST)

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Wastewater surveillance for pathogens using the reverse transcription-polymerase chain reaction (RT-PCR) is an effective, resource-efficient tool for gathering additional community-level public health information, including the incidence and/or prevalence and trends of coronavirus disease-19 (COVID-19). Surveillance of SARS-CoV-2 in wastewater may provide an early-warning signal of COVID-19 infections in a community. The capacity of the world’s environmental microbiology and virology laboratories for SARS-CoV-2 RNA characterization in wastewater is rapidly increasing. However, there are no standardized protocols nor harmonized quality assurance and quality control (QA/QC) procedures for SARS-CoV-2 wastewater surveillance. This paper is a technical review of factors that can lead to false-positive and -negative errors in the surveillance of SARS-CoV-2, culminating in recommendations and strategies that can be implemented to identify and mitigate these errors. Recommendations include, stringent QA/QC measures, representative sampling approaches, effective virus concentration and efficient RNA extraction, amplification inhibition assessment, inclusion of sample processing controls, and considerations for RT-PCR assay selection and data interpretation. Clear data interpretation guidelines (e.g., determination of positive and negative samples) are critical, particularly during a low incidence of SARS-CoV-2 in wastewater. Corrective and confirmatory actions must be in place for inconclusive and/or potentially significant results (e.g., initial onset or reemergence of COVID-19 in a community). It will also be prudent to perform inter-laboratory comparisons to ensure results are reliable and interpretable for ongoing and retrospective analyses. The strategies that are recommended in this review aim to improve SARS-CoV-2 characterization for wastewater surveillance applications. A silver lining of the COVID-19 pandemic is that the efficacy of wastewater surveillance was demonstrated during this global crisis. In the future, wastewater will play an important role in the surveillance of a range of other communicable diseases.

Preprint ARTICLE | doi:10.20944/preprints202012.0094.v3

“Clinician’s Probability Calculator” to Convert Pre-Test to Post-Test Probability of COVID-19, Based on Method Validation from Each Laboratory

Zoe Brooks, Saswati Das, Tom Pliura

Subject: Medicine And Pharmacology, Pathology And Pathobiology Keywords: COVID-19; SARS-COV-2; False-Positive; False-Negative; Likelihood Ratio; Probability; Calculator; Interpretation

Online: 3 March 2021 (10:08:27 CET)

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Preprint REVIEW | doi:10.20944/preprints202004.0201.v2

Detecting the Coronavirus (COVID-19)

Pravin Pokhrel, Changpeng Hu, Hanbin Mao

Subject: Biology And Life Sciences, Biochemistry And Molecular Biology Keywords: SARS-CoV-2 Detection, SARS-CoV-2 Antibody Test, SARS-CoV-2 Antigen Test, False Negative, False Positive, Sensitivity, Specificity, Point-of-care testing (POCT), SARS-CoV-2 Mutants

Online: 25 March 2021 (15:33:14 CET)

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The COVID-19 pandemic has created huge damage to society and brought panics around the world. Such panics can be ascribed to the seemingly deceptive features of the COVID-19: compared to other deadly viral outspreads, it has medium transmission and mortality rates. As a result, the severity of the causative coronavirus, SARS-CoV-2, was deeply underestimated by the society at the beginning of the COVID-19 outbreak. Based on this, in this review, we define the viruses with features similar to those of SARS-CoV-2 as the Panic Zone viruses. To contain those viruses, accurate and fast diagnosis followed by effective isolation and treatment of patients are pivotal at the early stage of virus breakouts. This is especially true when there is no cure or vaccine available for a transmissible disease, which is the case for current COVID-19 pandemic. As of January 2021, more than two hundred kits for the COVID-19 diagnosis on the market are surveyed in this review, while emerging sensing techniques for SARS-CoV-2 are also discussed. It is of critical importance to rationally use these kits for the efficient management and control of the Panic Zone viruses. Therefore, we discuss guidelines to select diagnostic kits at different outbreak stages of the Panic Zone viruses, SARS-CoV-2 in particular. While it is of utmost importance to use nucleic acid-based detection kits with low false negativity (high sensitivity) at the early stage of an outbreak, the low false positivity (high specificity) gains its importance at later stages of the outbreak. When a society is set to reopen from the lock-down stage of the COVID-19 pandemic, it becomes critical to have antibody based immunoassay kits with high specificity to identify people who can safely return to the society after their recovery of SARS-CoV-2 infections. Given that the emergence of mutant viruses at the beginning of 2021 has complicated current battle against the COVID-19, we also discussed approaches and guidelines to detect viral mutants in the middle of the second wave of the pandemic that started at the end of 2020. Finally, since a massive attack from a viral pandemic requires a massive defense from the whole society, we urge both government and private sectors to research and develop more affordable and reliable point-of-care testing (POCT) kits, which can be used massively by the general public (and therefore called as massive POCT) to contain Panic Zone viruses in future.

Preprint ARTICLE | doi:10.20944/preprints201902.0069.v1

The Effect of Humidity on the Electrical Resistance of Smart Sensor Based on Carbon Fibers

Marcin Górski, Rafał Krzywoń, Sofija Kekez

Subject: Engineering, Civil Engineering Keywords: textile sensor; carbon fiber; false strain compensation

Online: 7 February 2019 (11:28:03 CET)

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Preprint ARTICLE | doi:10.20944/preprints202307.0083.v1

Graph Convolutional-Based Deep Residual Modeling for Rumor Detection on Social Media

Na Ye, Dingguo Yu, Yijie Zhou, Ke-ke Shang, Suiyu Zhang

Subject: Social Sciences, Behavior Sciences Keywords: False information detection; Residual structure; Graph neural network

Online: 5 July 2023 (09:52:20 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202206.0148.v1

Erroneous AI-classification Systems Produce Creative Design Ideas, Predicting Level of Innovation Value

Johan F. Hoorn

Subject: Arts And Humanities, Architecture Keywords: false-class inclusions; serendipity; machine vision; creativity; innovativeness

Online: 10 June 2022 (04:35:14 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0212.v1

Pseudoscorpions of Israel: Annotated Checklist and Key, With New Records of Two Families (Arachnida: Pseudoscorpiones)

Sharon Warburg, Shlomi Aharon, Igor Armiach Steinpress, Prashant P. Sharma, Danilo Harms, Efrat Gavish-Regev

Subject: Biology And Life Sciences, Ecology, Evolution, Behavior And Systematics Keywords: Cheiridiidae; False scorpions; Levant; Species List; Syarinidae; Taxonomy; Zoogeography

Online: 2 June 2023 (14:16:19 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202301.0479.v1

Wear Development in Oscillating Rolling Element Bearings

Sebastian Wandel, Arne Bartschat, Jakob Glodowski, Norbert Bader, Gerhard Poll

Subject: Engineering, Mechanical Engineering Keywords: grease lubrication; false brinelling; oscillating bearing; pitch bearing; wear

Online: 26 January 2023 (10:44:02 CET)

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Preprint ARTICLE | doi:10.20944/preprints202307.1436.v1

Target Tracking Limits in a Dense Clutter Environments

Zvonko Radosavljevic, Dejan Ivkovic, Branko Kovacevic

Subject: Computer Science And Mathematics, Signal Processing Keywords: multi target tracking; false track discrimination; radar; probability of detection

Online: 21 July 2023 (02:34:08 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202205.0357.v1

Differentiating False Positive Lesions from Clinically Significant Cancer and Normal Prostate Tissue using VERDICT MRI and Other Diffusion Models

Snigdha Sen, Vanya Valindria, Paddy J. Slator, Hayley Pye, Alistair Grey, Alex Freeman, Caroline Moore, Hayley Whitaker, Shonit Punwani, Saurabh Singh, Eleftheria Panagiotaki

Subject: Medicine And Pharmacology, Other Keywords: prostate cancer; diffusion MRI; false positives; biophysical modelling; deep learning

Online: 26 May 2022 (08:30:28 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202112.0476.v1

Comparison of social inequality in HPV vaccination among teenagers with parental reports and healthcare providers’ records in the 2019 National Immunization Survey-Teen.

Sol Seo Choi, Bongkyoo Choi

Subject: Social Sciences, Sociology Keywords: Human Papillomavirus, vaccine, social inequality, NIS-Teen, false negative, SES.

Online: 30 December 2021 (00:14:38 CET)

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Preprint ARTICLE | doi:10.20944/preprints202012.0683.v1

Effectiveness of tDCS to Improve Recognition and Reduce False Memories in Older Adults

Juan C Melendez, Encarnación Satorres, Alfonso Pitarque, Iraida Delhom, Elena Real, Joaquin Escudero

Subject: Social Sciences, Psychology Keywords: transcranial direct current stimulation; true recognition; false recognition; aging; experiment.

Online: 28 December 2020 (11:15:38 CET)

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Preprint ARTICLE | doi:10.20944/preprints201711.0160.v1

Assessing the Performances of Protein Function Prediction Algorithms from the Perspectives of Identification Accuracy and False Discovery Rate

Chunyan Yu, Xiaoxu Li, Hong Yang, Yinghong Li, Weiwei Xue, Yuzong Chen, Lin Tao, Feng Zhu

Subject: Biology And Life Sciences, Biochemistry And Molecular Biology Keywords: false discovery rate; machine learning; protein function prediction; support vector machine; BLAST

Online: 24 November 2017 (11:14:05 CET)

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The knowledge of protein function is essential for the study of biological processes, the understanding of disease mechanism and the exploration of novel therapeutic target. Apart from experimental methods, a number of in-silico approaches have been developed and extensively used for protein function prediction. Among these approaches, BLAST predicts functions based on protein sequence similarity, and machine learning predicts functional families from protein sequences irrespective of their similarity, which complements BLAST and other methods in predicting diverse classes of proteins including distantly related proteins and homologous proteins of different functions. However, their identification accuracies and the false discovery rate have not yet been assessed so far, which greatly limits the usage of these prediction algorithms. Herein, a comprehensive comparison of the performances among four popular functional prediction algorithms (BLAST, SVM, PNN and KNN) was conducted. In particular, the performance of these algorithms were systematically assessed by four metrics (sensitivity, specificity, accuracy and Matthews correlation coefficient) based on the independent test datasets generated from 93 protein families defined by UniProtKB Keywords. Moreover, the false discovery rates of these algorithms were evaluated by scanning the genomes of four representative model species (homo sapiens, arabidopsis thaliana, saccharomyces cerevisiae and mycobacterium tuberculosis). As a result, the substantially higher sensitivity and stability of BLAST and SVM were observed compared with that of PNN and KNN. But the machine learning algorithms (PNN, KNN and SVM) were found capable of significantly reducing the false discovery rate (SVM < PNN ≈ KNN). In summary, this study comprehensively assessed the performance of four popular algorithms applied to protein function prediction, which could facilitate the selection of the most appropriate method in the related biomedical research.

Preprint ARTICLE | doi:10.20944/preprints202204.0314.v1

The Coronavirus Disease 2019 Spatial Care Path: Home, Community, and Emergency Diagnostic Portals

Gerald J. Kost

Subject: Medicine And Pharmacology, Pathology And Pathobiology Keywords: Emergency Use Authorization; endemic; false omission; false omission rate; home testing; point-of-care testing (POCT); positive predictive value geometric mean-squared; prevalence boundary; recursive protocol; tier; visual logistics

Online: 30 April 2022 (08:42:08 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201711.0027.v1

Classification-Based Singing Melody Extraction Using Deep Convolutional Neural Networks

Sangeun Kum, Juhan Nam

Subject: Engineering, Control And Systems Engineering Keywords: convolution neural networks; melody extraction; singing voice activity detection; voice false alarm detection

Online: 3 November 2017 (14:51:47 CET)

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Preprint ARTICLE | doi:10.20944/preprints202304.1259.v1

Quantitative Loop-mediated Isothermal Amplification Detection of Ustilaginoidea virens Causing Rice False Smut

Yu Zhang, Xinyue Li, Shuya Zhang, Tianling Ma, Chengxin Mao, Chuanqing Zhang

Subject: Biology And Life Sciences, Biochemistry And Molecular Biology Keywords: rice false smut; quantitative loop-mediated isothermal amplification (q-LAMP); detection; ustiloxins biosynthetic gene

Online: 30 April 2023 (04:40:34 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202307.2084.v1

Non-Cooperative Spectrum Sensing Strategy based on Recurrence Quantification Analysis in the Context of the Cognitive Radio

Jean-Marie KADJO, Koffi YAO, Ali MANSOUR, Denis JEUNE

Subject: Computer Science And Mathematics, Signal Processing Keywords: cognitive radio; dynamic spectrum access; spectrum sensing; embedding parameters; false nearest neighbours; recurrence quantification analysis

Online: 31 July 2023 (10:08:43 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202104.0688.v1

Direct Quantitation of SARS-CoV-2 Using Droplet Digital PCR in Suspected Samples With Very Low Viral Load

Michela Deiana, Chiara Piubelli, Antonio Mori, Gian Paolo Chiecchi, Giulia La Marca, Martina Leonardi, Davide Treggiari, Anna Beltrame, Lucia Moro, Zeno Bisoffi, Elena Pomari

Subject: Biology And Life Sciences, Biochemistry And Molecular Biology Keywords: droplet digital PCR; real time RT-PCR; SARS-CoV-2; false negative; viral load; diagnosis

Online: 26 April 2021 (20:09:26 CEST)

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Working Paper ARTICLE

Detecting Malicious False Frame Injection Attacks on Video Surveillance at the Edge Using Electrical Network Frequency Signals

Deeraj Nagothu, Yu Chen, Erik Blasch, Alexander Aved, Sencun Zhu

Subject: Computer Science And Mathematics, Information Systems Keywords: video surveillance; visual layer attack; electrical network frequency (ENF) signal; false frame injection (FFI) attack

Online: 1 April 2019 (09:50:05 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202308.1497.v1

The Impact of Repeating COVID-19 Rapid Antigen Tests on on Prevalence Boundary Performance and Missed Diagnoses

Gerald J Kost

Subject: Medicine And Pharmacology, Epidemiology And Infectious Diseases Keywords: Coronavirus disease-2019 (COVID-19); Emergency Use Authorization (EUA); false negative (FN); false omission rate (RFO); point-of-care testing (POCT); prevalence boundary (PB); rapid antigen test (RAgT); repeated testing; sensitivity and specificity; tier

Online: 22 August 2023 (07:25:00 CEST)

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Preprint REVIEW | doi:10.20944/preprints202004.0155.v1

COVID-19 Testing: Challenges, Limitations and Suggestions for Improvement

Emily Hu

Subject: Medicine And Pharmacology, Epidemiology And Infectious Diseases Keywords: COVID-19; Coronavirus; False-negative; Nucleic Acid Test; Screening; Diagnostic Accuracy; Missed Diagnosis; Epidemic; Infectious Disease

Online: 9 April 2020 (14:37:56 CEST)

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Preprint BRIEF REPORT | doi:10.20944/preprints202002.0424.v1

Insufficient Sensitivity of RNA Dependent RNA Polymerase Gene of SARS-CoV-2 Viral Genome as Confirmatory Test using Korean COVID-19 Cases

Soyoun Kim, Dong-Min Kim, Baeckseung Lee

Subject: Medicine And Pharmacology, Pathology And Pathobiology Keywords: SARS-CoV-2; Korean COVID-19; Wuhan Corona virus; real time PCR Ct Value; Sensitivity; False Negative

Online: 28 February 2020 (12:03:13 CET)

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Preprint REVIEW | doi:10.20944/preprints202308.2016.v1

Anomaly Detection in Power System State Estimation: Review and New Directions

Austin Cooper, Arturo Bretas, Sean Meyn

Subject: Engineering, Electrical And Electronic Engineering Keywords: Anomaly Detection; Cyber-Security; False Data Injection; Hypothesis Testing; Machine Learning; Power System Monitoring; Quickest Change Detection; State Estimation

Online: 30 August 2023 (07:23:42 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202307.1051.v4

Net Energy Gain from a Berry Geometrical Phase: Low-Energy Perturbations of the Strong Interaction and the QCD Mass Gap

Mark Gibbons

Subject: Physical Sciences, Particle And Field Physics Keywords: Berry geometrical phase; symmetry groups; self-organized criticality; dual superconductivity; scale- and gauge-invariance; hyperbolic curvature; false vacuum; QCD mass gap

Online: 25 August 2023 (08:49:43 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202207.0039.v1

Symmetrical Simulation Scheme for Anomaly Detection in Autonomous Vehicles Based on LSTM Model

Abdulaziz A. Alsulami, Qasem Abu Al-Haija, Ali Alqahtani, Raed Alsini

Subject: Engineering, Electrical And Electronic Engineering Keywords: Autonomous vehicles (A.V.); Anomaly Detection (A.D.); Deep Learning (DL), Symmetry; Long Short-Term Memory (LSTM); False Data Injection (FDI) Attacks

Online: 4 July 2022 (08:14:45 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202106.0482.v3

Fighting the COVID-19 Infodemic in News articles and False Publications: The NeoNet Text Classifier, a Supervised Machine Learning Algorithm

Mohammad AR Abdeen, Ahmed Abdeen Hamed, Xindong Wu

Subject: Computer Science And Mathematics, Algebra And Number Theory Keywords: COVID-19 Infodemic; Text Classification; TFIDF Features; Network Training modes; Supervised Learning; Misinformation; News Classification; False Publications; PubMed; Anomaly Detection

Online: 26 July 2021 (12:06:04 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201703.0191.v1

A Non-Parametric Maximum for Reasonable Number of Rejected Hypotheses: Objective Optima for False Discovery Rate and Significance Threshold in Exploratory Research with Application to Ordinal Survey Analysis

Amir hassan Ghaseminejad tafreshi

Subject: Computer Science And Mathematics, Information Systems Keywords: High-dimensional data analysis, Multiple hypothesis testing, False discovery rate, Optimum significance threshold, Maximum for reasonable number of rejected hypotheses, Big data analysis

Online: 24 March 2017 (18:29:35 CET)

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Preprint ARTICLE | doi:10.20944/preprints202105.0272.v1

Deep Learning and Conventional Machine Learning for Image-Based in-Situ Fault Detection During Laser Welding: A Comparative Study

Christian Knaak, Moritz Kröger, Frederic Schulze, Peter Abels, Arnold Gillner

Subject: Engineering, Automotive Engineering Keywords: real-time quality prediction; spatio-temporal features; feature importance; recurrent neural network; high-speed infrared imaging; convolutional neural network; lack of fusion (false friends)

Online: 12 May 2021 (13:55:12 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202204.0091.v1

Evidence-Based Evaluation of PCR Diagnostics for SARS-Cov-2 and The Omicron Variants by Sanger Sequencing

Sin Hang Lee

Subject: Medicine And Pharmacology, Epidemiology And Infectious Diseases Keywords: SARS-CoV-2; SARS-CoV; RT-PCR; Sanger sequencing; RT-qPCR; receptor-binding domain (RBD); N-terminal domain (NTD); Omicron; multi-allelic SNPs; false-positive

Online: 12 April 2022 (03:57:29 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201911.0023.v1

Antibody Screening by Microarray Technology – Direct Identification of Selective High-Affinity Clones

Martin Paul, Michael G. Weller

Subject: Biology And Life Sciences, Biology And Biotechnology Keywords: monoclonal antibodies; Mabs; fusion; false positives; hapten immunoassays; competitive immunoassays; ELISA; antibody validation; antibody quality; microarray; hybridoma technology; linker recognition; high-throughput screening; HTS; heterology concept

Online: 3 November 2019 (17:00:59 CET)

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