PLOS ONE: [sortOrder=DATE_NEWEST_FIRST, sort=Date, newest first, q=subject:"Open science"]PLOShttps://journals.plos.org/plosone/webmaster@plos.orgaccelerating the publication of peer-reviewed sciencehttps://journals.plos.org/plosone/search/feed/atom?sortOrder=DATE_NEWEST_FIRST&sort=Date,+newest+first&unformattedQuery=subject:%22Open+science%22All PLOS articles are Open Access.https://journals.plos.org/plosone/resource/img/favicon.icohttps://journals.plos.org/plosone/resource/img/favicon.ico2024-03-28T09:31:45ZAn open-source FACS automation system for high-throughput cell biologyDiane M. WienerEmily HuynhIlakkiyan JeyakumarSophie BaxSamia SamaJoana P. CabreraVerina TodorovaMadhuri VangipuramShivanshi VaidFumitaka OtsukaYoshitsugu SakaiManuel D. LeonettiRafael Gómez-Sjöberg10.1371/journal.pone.02994022024-03-21T14:00:00Z2024-03-21T14:00:00Z<p>by Diane M. Wiener, Emily Huynh, Ilakkiyan Jeyakumar, Sophie Bax, Samia Sama, Joana P. Cabrera, Verina Todorova, Madhuri Vangipuram, Shivanshi Vaid, Fumitaka Otsuka, Yoshitsugu Sakai, Manuel D. Leonetti, Rafael Gómez-Sjöberg</p>
Recent advances in gene editing are enabling the engineering of cells with an unprecedented level of scale. To capitalize on this opportunity, new methods are needed to accelerate the different steps required to manufacture and handle engineered cells. Here, we describe the development of an integrated software and hardware platform to automate Fluorescence-Activated Cell Sorting (FACS), a central step for the selection of cells displaying desired molecular attributes. Sorting large numbers of samples is laborious, and, to date, no automated system exists to sequentially manage FACS samples, likely owing to the need to tailor sorting conditions (“gating”) to each individual sample. Our platform is built around a commercial instrument and integrates the handling and transfer of samples to and from the instrument, autonomous control of the instrument’s software, and the algorithmic generation of sorting gates, resulting in walkaway functionality. Automation eliminates operator errors, standardizes gating conditions by eliminating operator-to-operator variations, and reduces hands-on labor by 93%. Moreover, our strategy for automating the operation of a commercial instrument control software in the absence of an Application Program Interface (API) exemplifies a universal solution for other instruments that lack an API. Our software and hardware designs are fully open-source and include step-by-step build documentation to contribute to a growing open ecosystem of tools for high-throughput cell biology.Multifunction fluorescence open source <i>in vivo/in vitro</i> imaging system (openIVIS)John M. Branning Jr.Kealy A. FaughnanAustin A. TomsonGrant J. BellSydney M. IsbellAllen DeGrootLydia JamesonKramer KilroyMichael SmithRobert SmithLandon MottelElizabeth G. BranningZoe WorrallFrances AndersonAshrit PanditaradyulaWilliam YangJoseph AbdelmalekJoshua BrakeKevin J. Cash10.1371/journal.pone.02998752024-03-18T14:00:00Z2024-03-18T14:00:00Z<p>by John M. Branning Jr., Kealy A. Faughnan, Austin A. Tomson, Grant J. Bell, Sydney M. Isbell, Allen DeGroot, Lydia Jameson, Kramer Kilroy, Michael Smith, Robert Smith, Landon Mottel, Elizabeth G. Branning, Zoe Worrall, Frances Anderson, Ashrit Panditaradyula, William Yang, Joseph Abdelmalek, Joshua Brake, Kevin J. Cash</p>
The widespread availability and diversity of open-source microcontrollers paired with off-the-shelf electronics and 3D printed technology has led to the creation of a wide range of low-cost scientific instruments, including microscopes, spectrometers, sensors, data loggers, and other tools that can be used for research, education, and experimentation. These devices can be used to explore a wide range of scientific topics, from biology and chemistry to physics and engineering. In this study, we designed and built a multifunction fluorescent open source <i>in vivo/in vitro</i> imaging system (openIVIS) system that integrates a Raspberry Pi with commercial cameras and LEDs with 3D printed structures combined with an acrylic housing. Our openIVIS provides three excitation wavelengths of 460 nm, 520 nm, and 630 nm integrated with Python control software to enable fluorescent measurements across the full visible light spectrum. To demonstrate the potential applications of our system, we tested its performance against a diverse set of experiments including laboratory assays (measuring fluorescent dyes, using optical nanosensors, and DNA gel electrophoresis) to potentially fieldable applications (plant and mineral imaging). We also tested the potential use for a high school biology environment by imaging small animals and tracking their development over the course of ten days. Our system demonstrated its ability to measure a wide dynamic range fluorescent response from millimolar to picomolar concentrations in the same sample while measuring responses across visible wavelengths. These results demonstrate the power and flexibility of open-source hardware and software and how it can be integrated with customizable manufacturing to create low-cost scientific instruments with a wide range of applications. Our study provides a promising model for the development of low-cost instruments that can be used in both research and education.For long-term sustainable software in bioinformaticsLuis Pedro Coelho10.1371/journal.pcbi.10119202024-03-15T14:00:00Z2024-03-15T14:00:00Z<p>by Luis Pedro Coelho</p>teemi: An open-source literate programming approach for iterative design-build-test-learn cycles in bioengineeringSøren D. PetersenLucas LevassorChristine M. PedersenJan MadsenLea G. HansenJie ZhangAhmad K. HaidarRasmus J. N. FrandsenJay D. KeaslingTilmann WeberNikolaus SonnenscheinMichael K. Jensen10.1371/journal.pcbi.10119292024-03-08T14:00:00Z2024-03-08T14:00:00Z<p>by Søren D. Petersen, Lucas Levassor, Christine M. Pedersen, Jan Madsen, Lea G. Hansen, Jie Zhang, Ahmad K. Haidar, Rasmus J. N. Frandsen, Jay D. Keasling, Tilmann Weber, Nikolaus Sonnenschein, Michael K. Jensen</p>
Synthetic biology dictates the data-driven engineering of biocatalysis, cellular functions, and organism behavior. Integral to synthetic biology is the aspiration to efficiently find, access, interoperate, and reuse high-quality data on genotype-phenotype relationships of native and engineered biosystems under FAIR principles, and from this facilitate forward-engineering strategies. However, biology is complex at the regulatory level, and noisy at the operational level, thus necessitating systematic and diligent data handling at all levels of the design, build, and test phases in order to maximize learning in the iterative design-build-test-learn engineering cycle. To enable user-friendly simulation, organization, and guidance for the engineering of biosystems, we have developed an open-source python-based computer-aided design and analysis platform operating under a literate programming user-interface hosted on Github. The platform is called teemi and is fully compliant with FAIR principles. In this study we apply teemi for i) designing and simulating bioengineering, ii) integrating and analyzing multivariate datasets, and iii) machine-learning for predictive engineering of metabolic pathway designs for production of a key precursor to medicinal alkaloids in yeast. The teemi platform is publicly available at PyPi and GitHub.Open government data use: The Brazilian states and federal district casesIlka KawashitaAna Alice BaptistaDelfina SoaresMorgana Andrade10.1371/journal.pone.02981572024-03-05T14:00:00Z2024-03-05T14:00:00Z<p>by Ilka Kawashita, Ana Alice Baptista, Delfina Soares, Morgana Andrade</p>
Purpose <p>This paper presents the results of an online survey and subsequent interviews investigating whether, how, and why public administrations of Brazilian states and the federal district (Federation Units) use open government data. According to the literature reviewed, the questions were categorized into four big groups: benefits, barriers, enablers, and drivers.</p> Design/Methodology/Approach <p>The Survey method, based on a questionnaire followed by interviews, was used to collect and analyze data from the open data officers of 26 Brazilian Federation Units.</p> Findings <p>The use of open government data is controversial as responses from the questionnaires and interviews do not match and raise questions about how well-represented each Federation Unit was. Evidence of open government data use was found. Among others, findings showed that political leadership committed to using open data facilitates and motivates public agents to use these data. Additionally, interviews indicated that the lack of human resources with the knowledge, skills, and capabilities to use open data is a relevant barrier to data use. Findings also revealed that open government data mainly support policy and decision-making processes.</p> Practical implications <p>This research contributed to the open data and public administration fields. It portrays diverse realities of open government data use and institutionalization in Brazilian state and district public administrations. In addition, it provides lists of open government data use benefits, barriers, drivers, and enablers from the perspective of these administrations so that they can benchmark against each other and improve their OGD use.</p> Originality and research implications <p>For academia, this research provides empirical evidence of the factors influencing public administrations’ use of open government data at the subnational level in Brazil. Even though Brazil ranks high on OGD global assessments, few studies on its use and reuse in the public sector were identified. This is one of the first academic studies focusing on open government data use in the country. It also contributes by offering to the academic community two instruments, a questionnaire and an interview protocol, which can be applied to other public settings to expand this study’s results or open new research paths by applying them to other contexts.</p>Endorsements of five reporting guidelines for biomedical research by journals of prominent publishersPeiling WangDietmar WolframEmrie Gilbert10.1371/journal.pone.02998062024-02-29T14:00:00Z2024-02-29T14:00:00Z<p>by Peiling Wang, Dietmar Wolfram, Emrie Gilbert</p>
Biomedical research reporting guidelines provide a framework by which journal editors and the researchers who conduct studies can ensure that the reported research is both complete and transparent. With more than 16 different guidelines for the 11 major study types of medical and health research, authors need to be familiar with journal reporting standards. To assess the current endorsements of reporting guidelines for biomedical and health research, this study examined the instructions for authors (IFAs) of 559 biomedical journals by 11 prominent publishers that publish original research or systematic reviews/meta-analyses. Data from the above original sources were cleaned and restructured, and analyzed in a database and text miner. Each journal’s instructions or information for authors were examined to code if any of five prominent reporting guidelines were mentioned and what form the guideline adherence demonstration took. Seventeen journals published the reporting guidelines. Four of the five reporting guidelines listed journals as endorsers. For journals with open peer review reports, a sample of journals and peer reviews was analyzed for mention of adherence to reporting guidelines. The endorsement of research guidelines by publishers and their associated journals is inconsistent for some publishers, with only a small number of journals endorsing relevant guidelines. Based on the analysis of open peer reviews, there is evidence that some reviewers check the adherence to the endorsed reporting guidelines. Currently, there is no universal endorsement of reporting guidelines by publishers nor ways of demonstrating adherence to guidelines. Journals may not directly inform authors of their guideline endorsements, making it more difficult for authors to adhere to endorsed guidelines. Suggestions derived from the findings are provided for authors, journals, and reporting guidelines to ensure increased adequate use of endorsed reporting guidelines.Multi-channel magnetic resonance spectroscopy graphical user interface (McMRSGUI)Travis CarrellMary P. McDougall10.1371/journal.pone.02991422024-02-28T14:00:00Z2024-02-28T14:00:00Z<p>by Travis Carrell, Mary P. McDougall</p>
This work introduces an open-sourced graphical user interface (GUI) software enabling the combination of multi-channel magnetic resonance spectroscopy data with different literature-based methods for the improvement of the quality and reliability of combined spectra. The multi-channel magnetic resonance spectroscopy graphical user interface (McMRSGUI) is a MATLAB-based spectroscopy processing GUI equipped to load multi-channel MRS data, pre-process, combine, and export combined data for evaluation with open-source quantification software (jMRUI). A literature-based, decision-tree process was incorporated into the combination type selection to serve as a guide to minimize spectral distortion in selecting between weighting methods. Multi-channel, simulated spectra were combined with the different combination techniques and evaluated for spectral distortion to validate the code. The incorporation of the combination methods into a single processing software enables multi-channel magnetic resonance spectroscopy (MRS) data to be combined and compared for improved spectral quality with little user knowledge of combination techniques. Through the spectral peak distortion simulation of the combination methods, combined signal-to-noise ratio (SNR) values from the literature were verified. The spectral peak distortion simulation provides a secondary tool for researchers to estimate the spectral SNR levels when spectral distortion could occur and use this knowledge to further guide the selection of their combination technique. The McMRSGUI provides a software toolkit for evaluating multi-channel MRS data and their combination. Simulations evaluating spectral distortion at different noise levels were performed for each combination method to validate the GUI and demonstrate a method for researchers to assess the combined SNR levels at which they could be introducing spectral distortion.Multimodal spatial availability: A singly-constrained measure of accessibility considering multiple modesAnastasia SoukhovJavier Tarriño-OrtizJulio A. Soria-LaraAntonio Páez10.1371/journal.pone.02990772024-02-23T14:00:00Z2024-02-23T14:00:00Z<p>by Anastasia Soukhov, Javier Tarriño-Ortiz, Julio A. Soria-Lara, Antonio Páez</p>
Place-based accessibility measures communicate the potential interaction with opportunities at a zone that populations can access. Recent research has explored the implications of how opportunities are counted by different accessibility methods. In conventional measures, opportunities are multiply counted if more than one zone offers access to the same opportunity. This multi-count of opportunities leads to values of accessibility that are difficult to interpret. A possible solution to enhance the meaning-making of accessibility results is by constraining the calculations to match a known quantity. This ensures all zonal values sum up to a predetermined quantity (i.e., the total number of opportunities). In this way, each value can be meaningfully related to this total. A recent effort that implements this solution is spatial availability, a singly-constrained accessibility measure. In this paper, we extend spatial availability for use in the case of multiple modes or more generally, heterogeneous population segments with distinct travel behaviors. After deriving a multimodal version of spatial availability, we proceed to illustrate its features using a synthetic example. We then apply it to an empirical example of low emission zones in Madrid, Spain. We conclude with suggestions for future research and its use in evaluating policy interventions.Research on joint model relation extraction method based on entity mappingHongmei TangDixiongxiao ZhuWenzhong TangShuai WangYanyang WangLihong Wang10.1371/journal.pone.02989742024-02-23T14:00:00Z2024-02-23T14:00:00Z<p>by Hongmei Tang, Dixiongxiao Zhu, Wenzhong Tang, Shuai Wang, Yanyang Wang, Lihong Wang</p>
Relationship Extraction (RE) is a central task in information extraction. The use of entity mapping to address complex scenarios with overlapping triples, such as CasRel, is gaining traction, yet faces challenges such as inadequate consideration of sentence continuity, sample imbalance and data noise. This research introduces an entity mapping-based method CasRelBLCF building on CasRel. The main contributions include: A joint decoder for the head entity, utilizing Bi-LSTM and CRF, integration of the Focal Loss function to tackle sample imbalance and a reinforcement learning-based noise reduction method for handling dataset noise. Experiments on relation extraction datasets indicate the superiority of the CasRelBLCF model and the enhancement on model’s performance of the noise reduction method.Potential of APSIS-InSAR for measuring surface oscillations of tropical peatlandsMartha J. LedgerAndrew SowterKeith MorrisonChris D. EvansDavid J. LargeAhmed AthabDavid GeeChloe BrownSofie Sjögersten10.1371/journal.pone.02989392024-02-23T14:00:00Z2024-02-23T14:00:00Z<p>by Martha J. Ledger, Andrew Sowter, Keith Morrison, Chris D. Evans, David J. Large, Ahmed Athab, David Gee, Chloe Brown, Sofie Sjögersten</p>
Tropical peatland across Southeast Asia is drained extensively for production of pulpwood, palm oil and other food crops. Associated increases in peat decomposition have led to widespread subsidence, deterioration of peat condition and CO<sub>2</sub> emissions. However, quantification of subsidence and peat condition from these processes is challenging due to the scale and inaccessibility of dense tropical peat swamp forests. The development of satellite interferometric synthetic aperture radar (InSAR) has the potential to solve this problem. The Advanced Pixel System using Intermittent Baseline Subset (APSIS, formerly ISBAS) modelling technique provides improved coverage across almost all land surfaces irrespective of ground cover, enabling derivation of a time series of tropical peatland surface oscillations across whole catchments. This study aimed to establish the extent to which APSIS-InSAR can monitor seasonal patterns of tropical peat surface oscillations at North Selangor Peat Swamp Forest, Peninsular Malaysia. Results showed that C-band SAR could penetrate the forest canopy over tropical peat swamp forests intermittently and was applicable to a range of land covers. Therefore the APSIS technique has the potential for monitoring peat surface oscillations under tropical forest canopy using regularly acquired C-band Sentinel-1 InSAR data, enabling continuous monitoring of tropical peatland surface motion at a spatial resolution of 20 m.Synthetic images aid the recognition of human-made art forgeriesJohann OstmeyerLudovica SchaerfPavel BuividovichTessa CharlesEric PostmaCarina Popovici10.1371/journal.pone.02959672024-02-14T14:00:00Z2024-02-14T14:00:00Z<p>by Johann Ostmeyer, Ludovica Schaerf, Pavel Buividovich, Tessa Charles, Eric Postma, Carina Popovici</p>
Previous research has shown that Artificial Intelligence is capable of distinguishing between authentic paintings by a given artist and human-made forgeries with remarkable accuracy, provided sufficient training. However, with the limited amount of existing known forgeries, augmentation methods for forgery detection are highly desirable. In this work, we examine the potential of incorporating synthetic artworks into training datasets to enhance the performance of forgery detection. Our investigation focuses on paintings by Vincent van Gogh, for which we release the first dataset specialized for forgery detection. To reinforce our results, we conduct the same analyses on the artists Amedeo Modigliani and Raphael. We train a classifier to distinguish original artworks from forgeries. For this, we use human-made forgeries and imitations in the style of well-known artists and augment our training sets with images in a similar style generated by Stable Diffusion and StyleGAN. We find that the additional synthetic forgeries consistently improve the detection of human-made forgeries. In addition, we find that, in line with previous research, the inclusion of synthetic forgeries in the training also enables the detection of AI-generated forgeries, especially if created using a similar generator.Spurious prospective effects between general and domain-specific self-esteem: A reanalysis of a meta-analysis of longitudinal studiesKimmo SorjonenBo Melin10.1371/journal.pone.02981582024-02-13T14:00:00Z2024-02-13T14:00:00Z<p>by Kimmo Sorjonen, Bo Melin</p>
A recent meta-analysis, of 38 studies with data from 43 independent samples (total <i>N</i> = 24,668), claimed evidence for positive reciprocal prospective effects, and hence for both top-down and bottom-up processes, between general and domain-specific self-esteem. However, the meta-analytic cross-lagged effects were estimated while adjusting for a prior measurement of the outcome variable and it is known that such adjusted cross-lagged effects may be spurious due to correlations with residuals and regression to the mean. In the present reanalyses, we found all of the prospective effects to be spurious. Consequently, claims about increasing prospective effects and top-down and bottom-up processes between general and domain-specific self-esteem can be questioned. It is important for researchers to be aware of the limitations of cross-lagged panel analyses, and of analyses of correlational data in general, in order not to overinterpret findings.Identifying the most important facilitators of open research data sharing and reuse in Epidemiology: A mixed-methods studyAnneke ZuiderwijkBerkay Onur TürkFrances Brazier10.1371/journal.pone.02979692024-02-08T14:00:00Z2024-02-08T14:00:00Z<p>by Anneke Zuiderwijk, Berkay Onur Türk, Frances Brazier</p>
To understand how open research data sharing and reuse can be further improved in the field of Epidemiology, this study explores the facilitating role that infrastructural and institutional arrangements play in this research discipline. It addresses two research questions: 1) What influence do infrastructural and institutional arrangements have on open research data sharing and reuse practices in the field of Epidemiology? And 2) how could infrastructural and institutional instruments used in Epidemiology potentially be useful to other research disciplines? First, based on a systematic literature review, a conceptual framework of infrastructural and institutional instruments for open research data facilitation is developed. Second, the conceptual framework is applied in interviews with Epidemiology researchers. The interviews show that two infrastructural and institutional instruments have a very high influence on open research data sharing and reuse practices in the field of Epidemiology, namely (a) access to a powerful search engine that meets open data search needs and (b) support by data stewards and data managers. Third, infrastructural and institutional instruments with a medium, high, or very high influence were discussed in a research workshop involving data stewards and research data officers from different research fields. This workshop suggests that none of the influential instruments identified in the interviews are specific to Epidemiology. Some of our findings thus seem to apply to multiple other disciplines. This study contributes to Science by identifying field-specific facilitators and challenges for open research data in Epidemiology, while at the same time revealing that none of the identified influential infrastructural and institutional instruments were specific to this field. Practically, this implies that open data infrastructure developers, policymakers, and research funding organizations may apply certain infrastructural and institutional arrangements to multiple research disciplines to facilitate and enhance open research data sharing and reuse.HLD-DDoSDN: High and low-rates dataset-based DDoS attacks against SDNAbdullah Ahmed BahashwanMohammed AnbarSelvakumar ManickamGhassan IssaMohammad Adnan AladailehBasim Ahmad AlabsiShaza Dawood Ahmed Rihan10.1371/journal.pone.02975482024-02-08T14:00:00Z2024-02-08T14:00:00Z<p>by Abdullah Ahmed Bahashwan, Mohammed Anbar, Selvakumar Manickam, Ghassan Issa, Mohammad Adnan Aladaileh, Basim Ahmad Alabsi, Shaza Dawood Ahmed Rihan</p>
Software Defined Network (SDN) has alleviated traditional network limitations but faces a significant challenge due to the risk of Distributed Denial of Service (DDoS) attacks against an SDN controller, with current detection methods lacking evaluation on unrealistic SDN datasets and standard DDoS attacks (i.e., high-rate DDoS attack). Therefore, a realistic dataset called HLD-DDoSDN is introduced, encompassing prevalent DDoS attacks specifically aimed at an SDN controller, such as User Internet Control Message Protocol (ICMP), Transmission Control Protocol (TCP), and User Datagram Protocol (UDP). This SDN dataset also incorporates diverse levels of traffic fluctuations, representing different traffic variation rates (i.e., high and low rates) in DDoS attacks. It is qualitatively compared to existing SDN datasets and quantitatively evaluated across all eight scenarios to ensure its superiority. Furthermore, it fulfils the requirements of a benchmark dataset in terms of size, variety of attacks and scenarios, with significant features that highly contribute to detecting realistic SDN attacks. The features of HLD-DDoSDN are evaluated using a Deep Multilayer Perception (D-MLP) based detection approach. Experimental findings indicate that the employed features exhibit high performance in the detection accuracy, recall, and precision of detecting high and low-rate DDoS flooding attacks.German funders’ data sharing policies—A qualitative interview studyMichael AngerChristian WendelbornChristoph Schickhardt10.1371/journal.pone.02969562024-02-08T14:00:00Z2024-02-08T14:00:00Z<p>by Michael Anger, Christian Wendelborn, Christoph Schickhardt</p>
Background <p>Data sharing is commonly seen as beneficial for science but is not yet common practice. Research funding agencies are known to play a key role in promoting data sharing, but German funders’ data sharing policies appear to lag behind in international comparison. This study aims to answer the question of how German data sharing experts inside and outside funding agencies perceive and evaluate German funders’ data sharing policies and overall efforts to promote data sharing.</p> Methods <p>This study is based on sixteen guided expert interviews with representatives of German funders and German research data experts from stakeholder organisations, who shared their perceptions of German’ funders efforts to promote data sharing. By applying the method of qualitative content analysis to our interview data, we categorise and describe noteworthy aspects of the German data sharing policy landscape and illustrate our findings with interview passages.</p> Results <p>We present our findings in five sections to distinguish our interviewees’ perceptions on a) the status quo of German funders’ data sharing policies, b) the role of funders in promoting data sharing, c) current and potential measures by funders to promote data sharing, d) general barriers to those measures, and e) the implementation of more binding data sharing requirements.</p> Discussion and conclusion <p>Although funders are perceived to be important promoters and facilitators of data sharing throughout our interviews, only few German funding agencies have data sharing policies in place. Several interviewees stated that funders could do more, for example by providing incentives for data sharing or by introducing more concrete policies. Our interviews suggest the academic freedom of grantees is widely perceived as an obstacle for German funders in introducing mandatory data sharing requirements. However, some interviewees stated that stricter data sharing requirements could be justified if data sharing is a part of good scientific practice.</p>