PLOS ONE: [sortOrder=DATE_NEWEST_FIRST, sort=Date, newest first, q=subject:"Research facilities"]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:%22Research+facilities%22All PLOS articles are Open Access.https://journals.plos.org/plosone/resource/img/favicon.icohttps://journals.plos.org/plosone/resource/img/favicon.ico2024-03-28T14:54:44ZComparative evaluation of four rapid diagnostic tests that detect human <i>Trypanosoma cruzi-</i>specific antibodies to support diagnosis of Chagas Disease in urban population of ArgentinaRocío RiveroM. Soledad SantiniConstanza Lopez-AlbizuMarcelo RodriguezAdriana CalbosaDaniela OlivetoMónica EstevaMargarita BisioLaura C. Bohorquez10.1371/journal.pntd.00119972024-03-15T14:00:00Z2024-03-15T14:00:00Z<p>by Rocío Rivero, M. Soledad Santini, Constanza Lopez-Albizu, Marcelo Rodriguez, Adriana Calbosa, Daniela Oliveto, Mónica Esteva, Margarita Bisio, Laura C. Bohorquez</p>
Background <p>Chagas disease (CD), caused by the parasite <i>Trypanosoma cruzi</i>, is the most important endemic anthropozoonosis in Argentina. Since 2010, the World Health Organization has highlighted the urgent need to validate diagnostic systems that allow rapid detection of <i>T</i>. <i>cruzi</i>, infection in primary healthcare centers. Serological rapid diagnostic tests (RDTs) for <i>T</i>. <i>cruzi</i>, infection could be used to improve case management, as RDTs do not require specialized laboratories or highly trained staff to use them. We aimed to generate unbiased performance data of RDTs in Argentina, to evaluate their usefulness for improving <i>T</i>. <i>cruzi</i>, diagnosis rates.</p> Methods and principal findings <p>This is a retrospective, laboratory-based, diagnostic evaluation study to estimate the clinical sensitivity/specificity of four commercially available RDTs for <i>T</i>. <i>cruzi</i>, using the Chagas disease diagnostic algorithm currently used in Argentina as the reference standard. In total, 400 serum samples were tested, 200 from individuals with chronic <i>T</i>. <i>cruzi</i> infection and 200 from individuals not infected with <i>T</i>. <i>cruzi</i>. All results were registered as the agreement of at least two operators who were blinded to the reference standard results. The sensitivity estimates ranged from 92.5–100% (95% confidence interval (CI) lower bound 87.9–98.2%); for specificity, the range was 76–96% (95% CI lower bound 69.5–92.3%). Most RDTs evaluated showed performances comparable with the reference standard method, showing almost perfect concordance (<i>Kappa</i> 0.76–0.92).</p> Conclusions <p>Our study demonstrates that, under controlled laboratory conditions, commercially available RDTs for CD have a performance comparable to the Argentinian diagnostic algorithm, which is based on laboratory-based serological tests. For the next stage of our work, the RDTs will be evaluated in real-world settings.</p>Field-based molecular detection of <i>Batrachochytrium dendrobatidis</i> in critically endangered <i>Atelopus</i> toads and aquatic habitats in EcuadorLenin R. Riascos-FloresJulio BonillaLeopoldo Naranjo-BriceñoKatherine Apunte-RamosGrace C. Reyes-OrtegaMarcela CabreraJosé F. Cáceres-AndradeAndrea Carrera-GonzalezJomira K. Yánez-GalarzaFausto Siavichay PesántezLuis A. Oyagata-CachimuelPeter GoethalsJorge CeliChristine Van der HeydenH. Mauricio Ortega-Andrade10.1371/journal.pone.02992462024-03-14T14:00:00Z2024-03-14T14:00:00Z<p>by Lenin R. Riascos-Flores, Julio Bonilla, Leopoldo Naranjo-Briceño, Katherine Apunte-Ramos, Grace C. Reyes-Ortega, Marcela Cabrera, José F. Cáceres-Andrade, Andrea Carrera-Gonzalez, Jomira K. Yánez-Galarza, Fausto Siavichay Pesántez, Luis A. Oyagata-Cachimuel, Peter Goethals, Jorge Celi, Christine Van der Heyden, H. Mauricio Ortega-Andrade</p>
<i>Batrachochytrium dendrobatidis</i> (Bd) is a lethal fungal species that parasitizes vertebrates and is associated with the worldwide decline of amphibian populations. The development of sensitive, rapid detection methods, particularly DNA-based techniques, is critical for effective management strategies. This study evaluates the efficacy of DNA extraction and a portable PCR device in a mountable field laboratory setup for detecting Bd near the habitats of three critically endangered <i>Atelopus</i> toad species in Ecuador. We collected skin swabs from <i>Atelopus balios</i>, <i>A</i>. <i>nanay</i>, <i>and A</i>. <i>bomolochos</i>, and environmental DNA (eDNA) samples from streams in Andean and coastal regions of Ecuador. For eDNA, a comparison was made with duplicates of the samples that were processed in the field and in a standard university laboratory. Our findings revealed Bd detection in eDNA and swabs from 6 of 12 water samples and 10 of 12 amphibian swab samples. The eDNA results obtained in the field laboratory were concordant with those obtained under campus laboratory conditions. These findings highlight the potential of field DNA-based monitoring techniques for detecting Bd in amphibian populations and their aquatic habitats, particularly in remote areas. Furthermore, this research aligns with the National Action Plan for the Conservation of Ecuadorian Amphibians and contributes to the global effort to control this invasive and deadly fungus.Weather or not—Global climate databases: Reliable on tropical mountains?Andreas HempJudith Hemp10.1371/journal.pone.02993632024-03-13T14:00:00Z2024-03-13T14:00:00Z<p>by Andreas Hemp, Judith Hemp</p>
Global, spatially interpolated climate datasets such as WorldClim and CHELSA, widely used in research, are based on station data, which are rare in tropical mountains. However, such biodiversity hotspots are of high ecological interest and require accurate data. Therefore, the quality of such gridded datasets needs to be assessed. This poses a kind of dilemma, as proving the reliability of these potentially weakly modelled data is usually not possible due to the lack of stations. Using a unique climate dataset with 170 stations, mainly from the montane and alpine zones of sixteen mountains in Tanzania including Kilimanjaro, we show that the accuracy of such datasets is very poor. Not only is the maximum amount of mean annual precipitation drastically underestimated (partly more than 50%), but also the elevation of the precipitation maximum deviates up to 850m. Our results show that, at least in tropical regions, they should be used with greater caution than before.Manual versus machine: How accurately does the Medical Text Indexer (MTI) classify different document types into disease areas?Duncan A. Q. MooreOhid YaqubBhaven N. Sampat10.1371/journal.pone.02975262024-03-13T14:00:00Z2024-03-13T14:00:00Z<p>by Duncan A. Q. Moore, Ohid Yaqub, Bhaven N. Sampat</p>
The Medical Subject Headings (MeSH) thesaurus is a controlled vocabulary developed by the U.S. National Library of Medicine (NLM) for classifying journal articles. It is increasingly used by researchers studying medical innovation to classify text into disease areas and other categories. Although this process was once manual, human indexers are now assisted by algorithms that automate some of the indexing process. NLM has made one of their algorithms, the Medical Text Indexer (MTI), available to researchers. MTI can be used to easily assign MeSH descriptors to arbitrary text, including from document types other than publications. However, the reliability of extending MTI to other document types has not been studied directly. To assess this, we collected text from grants, patents, and drug indications, and compared MTI’s classification to expert manual classification of the same documents. We examined MTI’s recall (how often correct terms were identified) and found that MTI identified 78% of expert-classified MeSH descriptors for grants, 78% for patents, and 86% for drug indications. This high recall could be driven merely by excess suggestions (at an extreme, all diseases being assigned to a piece of text); therefore, we also examined precision (how often identified terms were correct) and found that most MTI outputs were also identified by expert manual classification: precision was 53% for grant text, 73% for patent text, and 64% for drug indications. Additionally, we found that recall and precision could be improved by (i) utilizing ranking scores provided by MTI, (ii) excluding long documents, and (iii) aggregating to higher MeSH categories. For simply detecting the presence of any disease, MTI showed > 94% recall and > 87% precision. Our overall assessment is that MTI is a potentially useful tool for researchers wishing to classify texts from a variety of sources into disease areas.Establishing age and gender-specific serum creatinine reference ranges for Thai pediatric populationSakon SuwanrungrojParichart PattarapanitchaiSirinart ChomeanChollanot Kaset10.1371/journal.pone.03003692024-03-12T14:00:00Z2024-03-12T14:00:00Z<p>by Sakon Suwanrungroj, Parichart Pattarapanitchai, Sirinart Chomean, Chollanot Kaset</p>
Accurate assessment of kidney function in children requires age and gender-specific reference ranges for serum creatinine. Traditional reference values, often derived from adult populations and different ethnic backgrounds, may not be suitable for children. This study aims to establish specific reference ranges for serum creatinine in the Thai pediatric population, addressing the gap in localized and age-appropriate diagnostic criteria. This retrospective study analyzed serum creatinine levels from Thai children aged newborn to 18 years, collected from the Laboratory Information System of the Queen Sirikit National Institute of Child Health from January 2017 to December 2021. The Bhattacharya method was employed to establish reference ranges, considering different age groups and genders. The study compared these newly established reference values with international studies, including those of Schlebusch H., Pottel H., and Chuang GT., to validate their relevance and accuracy. A total of 27,642 data entries (15,396 males and 12,246 females) were analyzed. The study established distinct reference ranges for serum creatinine, which varied significantly across different age groups and between genders. These ranges were found to gradually increase with age from 2 months to 18 years. The study also highlighted notable differences in reference values when compared with other ethnic populations. The study successfully establishes tailored reference ranges for serum creatinine in Thai children, providing a valuable tool for more accurate diagnosis and monitoring of kidney health in this demographic. This initiative marks a significant advancement in pediatric nephrology in Thailand and suggests a need for continuous refinement of these ranges and further research in this area.Recommendations for increasing yield of the edible <i>Pinus pinea</i> L. pine nutsVerónica Loewe-MuñozClaudia DelardRodrigo del RíoMónica Balzarini10.1371/journal.pone.03000082024-03-05T14:00:00Z2024-03-05T14:00:00Z<p>by Verónica Loewe-Muñoz, Claudia Delard, Rodrigo del Río, Mónica Balzarini</p>
In <i>Pinus pinea</i>, cone to pine nut yield (total pine nut weight expressed as percentage of cone weight), an important crop trait, is decreasing worldwide. This phenomenon is of great concern, since the nuts of this species are highly demanded. Cone weight, seed and pine nut morphometry, and pine nut yield were monitored in a non-native area in Chile for 10 years. For this purpose, 560 cones, and the seeds and pine nuts contained in them, were counted, measured and weighed in a multi-environment study involving seven plantations. Seed and pine nut damage was evaluated. Two contrasting categories of cone weight (heavy/light) were defined. Cone to pine nut yield (PY) and other traits were calculated and compared between categories using a mixed linear model. Regression trees were used to explain PY variability. Cone weight was higher than in the species’ native range (474 g vs 300 g on average). Pine nut number per cone and PY were significantly higher in the heavy cone category than in the light cone category (125 vs 89 units, and 4.05 vs 3.62%, respectively), The percentage of damaged seeds was lower in heavy than in light cones (9.0% vs 15.9%). Thus, PY depended on seed and pine nut morphometry as well as on seed health. Management practices, such as fertilization and irrigation, could be used to boost production of heavy cones and consequently increase PY.Validation of global precipitation time series products against tree ring records and remotely sensed vegetation greennessVinicius ManvailerAndreas Hamann10.1371/journal.pone.02991112024-02-29T14:00:00Z2024-02-29T14:00:00Z<p>by Vinicius Manvailer, Andreas Hamann</p>
Global interpolated climate products are widely used in ecological research to investigate biosphere-climate interactions and to track ecological response to climate variability and climate change. In turn, biological data could also be used for an independent validation of one aspect of climate data quality. All else being equal, more variance explained in biological data identifies the better climate data product. Here, we compare seven global precipitation time series products, including gauge-based datasets (CRU-TS, UDEL-TS, GPCC), re-analysis products (ERA5, CHELSA), a satellite-based dataset (PERSIANN) and a multi-source product that draws on gauge, re-analysis, and satellite data (MSWEP). We focus on precipitation variables, because they are more difficult to interpolate than temperature, and show larger divergence among gridded data products. Our validation is based on 20 years of remotely sensed vegetation greenness (MODIS-EVI) and 120 years of tree ring records from the International Tree Ring Data Bank (ITRDB). The results for the 20-year EVI based validation shows that all gauge and re-analysis data products performed similarly, but were outperformed by the multi-source MSWEP product, especially in regions with low weather station coverage, such as Africa. For analyzing long 120-year time-series, UDEL-TS showed superior performance prior to the 1940s, with especially large margins for northern Asia and the Himalayas region. For other regions, CRU-TS and GPCC could be recommended. We provide maps that can guide the best regional choice of climate product for research involving time series of biological response to historic climate variability and climate change.Evaluation of the environmental polio surveillance system—Northern Region, Ghana, 2021Benjamin BaguuneEunice Baiden LaryeaJoseph Asamoah FrimpongSamuel DapaaKwame Kodom AchempemErnest KenuDennis Odai Laryea10.1371/journal.pone.02943052024-02-29T14:00:00Z2024-02-29T14:00:00Z<p>by Benjamin Baguune, Eunice Baiden Laryea, Joseph Asamoah Frimpong, Samuel Dapaa, Kwame Kodom Achempem, Ernest Kenu, Dennis Odai Laryea</p>
Background <p>Acute Flaccid Paralysis (AFP) surveillance is the gold standard in the polio eradication initiative. The environmental component of polio surveillance can detect circulating Polioviruses from sewage without relying on clinical presentation. The effectiveness of the Environmental Surveillance (ES) is crucial to global polio eradication. We assessed the usefulness and attributes of the ES system in the Northern region and determined if the system is meeting its objectives.</p> Methods <p>We conducted a descriptive cross-sectional evaluation in the Northern region from 2019 to 2020 using the updated US Centers for Disease Control and Prevention guideline. We interviewed stakeholders, reviewed records, and observed surveillance activities from 29<sup>th</sup> March to 7<sup>th</sup> May, 2021. Quantitative data were analyzed manually as frequencies and proportions whiles thematic analysis was used for the qualitative data.</p> Results <p>One of 48 (2.1%) samples collected tested positive for circulating vaccine-derived Poliovirus (cVDPV). The cVDPV detection triggered enhanced AFP surveillance that resulted in the identification of a case of AFP. Three rounds of polio vaccination campaigns were organized. All surveillance officers interviewed were willing to continue providing their services for the ES. Reporting form has few variables and is easy to complete. The completeness of forms was 97.9% (47/48). Samples collected were dispatched on the same day to the testing laboratory. The system’s data was managed manually.</p> Conclusion <p>The system was useful in detecting polio outbreaks. Data quality was good, the system was simple, flexible, acceptable, representative, and fairly stable. Sensitivity was high but predictive value positive was low. Timeliness in reporting was good but feedback from the national level could not be assessed. There is a need to improve on the feedback system and ensure that, the surveillance data is managed electronically.</p>Strengthening laboratories in response to outbreaks in humanitarian emergencies and conflict settings: Results, challenges and lessons from expanding PCR diagnostic capacities for COVID-19 testing in YemenIsmail Mahat BashirAli Ahmed Al-WaleediSaeed Mohamed Al-ShaibaniMohammed RajamanarShougi Al-AkbariAbdulelah Al-HaraziLayla Salim AliwahNahed Ahmed SalemDina Al-AdemiAmal BarakatNicole SarkisAbdinasir AbubakarMikiko SengaAltaf MusaniAdham Rashad Ismail Abdel MoneimNuha Mahmoud10.1371/journal.pone.02986032024-02-23T14:00:00Z2024-02-23T14:00:00Z<p>by Ismail Mahat Bashir, Ali Ahmed Al-Waleedi, Saeed Mohamed Al-Shaibani, Mohammed Rajamanar, Shougi Al-Akbari, Abdulelah Al-Harazi, Layla Salim Aliwah, Nahed Ahmed Salem, Dina Al-Ademi, Amal Barakat, Nicole Sarkis, Abdinasir Abubakar, Mikiko Senga, Altaf Musani, Adham Rashad Ismail Abdel Moneim, Nuha Mahmoud</p>
Background <p>When the COVID-19 pandemic was declared, Yemen, a country facing years of conflict had only one laboratory with PCR testing capacity. In this article, we describe the outcome of the implementation of molecular based diagnostics platform in Yemen and highlight the key milestones the country went through to increase access to testing for its populations residing in a geographically vast and politically divided country.</p> Methods <p>A retrospective assessment of COVID-19 laboratory response activities was done detailing the needs assessment process, timelines, geographical coverage, and outcomes of the activities. Laboratory data was analyzed to construct the geographical locations of COVID-19 testing laboratories and the numbers of tests performed in each facility to highlight the demands of testing for travelers. Finally, we discuss the impact these activities had in enabling the movement of people across international borders for economic gains and in delivery of critical humanitarian aid.</p> Outcome <p>PCR testing capacities in Yemen significantly improved, from one laboratory in Sanaa in April 2020 to 18 facilities across the country by June 2022. In addition, the number of functional Real-Time PCR thermocyclers increased from one to 32, the PCR tests output per day improved from 192 to 6144 tests per day. Results from analysis of laboratory data showed there were four peaks of COVID-19 in Yemen as October 2022. The majority of laboratory tests were performed for travelers than for medical or public health reasons. Demand for laboratory testing in Yemen was generally low and waned over time as the perceived risk of COVID-19 declined, in parallel with rollout of the COVID-19 vaccines.</p> Discussion/Conclusion <p>The successful expansion of laboratory testing capacity was instrumental in the control and management of COVID-19 cases and critical in the implementation of public response strategies, including restrictions on gathering. Laboratory testing also facilitated the movement of humanitarian agencies and delivery of aid and enabled hundreds of thousands of Yemeni nationals to travel internationally. By virtue of these outcomes, the impact of laboratory strengthening activities was thus felt in the health sector and beyond.</p>Study protocol for factors influencing the adoption of ChatGPT technology by startups: Perceptions and attitudes of entrepreneursVarun GuptaHongji Yang10.1371/journal.pone.02984272024-02-15T14:00:00Z2024-02-15T14:00:00Z<p>by Varun Gupta, Hongji Yang</p>
Background <p>Generative Artificial Intelligence (AI) technology, for instance Chat Generative Pre-trained Transformer (ChatGPT), is continuously evolving, and its userbase is growing. These technologies are now being experimented by the businesses to leverage their potential and minimise their risks in business operations. The continuous adoption of the emerging Generative AI technologies will help startups gain more and more experience with adoptions, helping them to leverage continuously evolving technological innovation landscape. However, there is a dearth of prior research on ChatGPT adoption in the startup context, especially from Entrepreneur perspective, highlights the urgent need for a thorough investigation to identify the variables influencing this technological adoption. The primary objective of this study is to ascertain the factors that impact the uptake of ChatGPT technology by startups, anticipate their influence on the triumph of companies, and offer pragmatic suggestions for various stakeholders, including entrepreneurs, and policymakers.</p> Method and analysis <p>This study attempts to explore the variables impacting startups’ adoption of ChatGPT technology, with an emphasis on comprehending entrepreneurs’ attitudes and perspectives. To identify and then empirically validate the Generative AI technology adoption framework, the study uses a two-stage methodology that includes experience-based research, and survey research. The research method design is descriptive and Correlational design. Stage one of the research study is descriptive and involves adding practical insights, and real-world context to the model by drawing from the professional consulting experiences of the researchers with the SMEs. The outcome of this stage is the adoption model (<i>also called as research framework</i>), building Upon Technology Adoption Model (TAM), that highlight the technology adoption factors (<i>also called as latent variables</i>) connected with subset of each other and finally to the technology adoption factor (or otherwise). Further, the latent variables and their relationships with other latent variables as graphically highlighted by the adoption model will be translated into the structured questionnaire. Stage two involves survey based research. In this stage, structured questionnaire is tested with small group of entrepreneurs (<i>who has provided informed</i> consent) and finally to be distributed among startup founders to further validate the relationships between these factors and the level of influence individual factors have on overall technology adoption. Partial Least Squares Structural Equation Modeling (PLS-SEM) will be used to analyze the gathered data. This multifaceted approach allows for a comprehensive analysis of the adoption process, with an emphasis on understanding, describing, and correlating the key elements at play.</p> Discussion <p>This is the first study to investigate the factors that impact the adoption of Generative AI, for instance ChatGPT technology by startups from the Entrepreneurs perspectives. The study’s findings will give Entrepreneurs, Policymakers, technology providers, researchers, and Institutions offering support for entrepreneurs like Academia, Incubators and Accelerators, University libraries, public libraries, chambers of commerce, and foreign embassies important new information that will help them better understand the factors that encourage and hinder ChatGPT adoption. This will allow them to make well-informed strategic decisions about how to apply and use this technology in startup settings thereby improving their services for businesses.</p>Earthworms and plants can decrease soil greenhouse gas emissions by modulating soil moisture fluctuations and soil macroporosity in a mesocosm experimentPierre GanaultJohanne NahmaniYvan CapowiezNathalie FrominAmmar ShihanIsabelle BertrandBruno BuatoisAlexandru Milcu10.1371/journal.pone.02898592024-02-15T14:00:00Z2024-02-15T14:00:00Z<p>by Pierre Ganault, Johanne Nahmani, Yvan Capowiez, Nathalie Fromin, Ammar Shihan, Isabelle Bertrand, Bruno Buatois, Alexandru Milcu</p>
Earthworms can stimulate microbial activity and hence greenhouse gas (GHG) emissions from soils. However, the extent of this effect in the presence of plants and soil moisture fluctuations, which are influenced by earthworm burrowing activity, remains uncertain. Here, we report the effects of earthworms (without, anecic, endogeic, both) and plants (with, without) on GHG (CO<sub>2</sub>, N<sub>2</sub>O) emissions in a 3-month greenhouse mesocosm experiment simulating a simplified agricultural context. The mesocosms allowed for water drainage at the bottom to account for the earthworm engineering effect on water flow during two drying-wetting cycles. N<sub>2</sub>O cumulative emissions were 34.6% and 44.8% lower when both earthworm species and only endogeic species were present, respectively, and 19.8% lower in the presence of plants. The presence of the endogeic species alone or in combination with the anecic species slightly reduced CO<sub>2</sub> emissions by 5.9% and 11.4%, respectively, and the presence of plants increased emissions by 6%. Earthworms, plants and soil water content interactively affected weekly N<sub>2</sub>O emissions, an effect controlled by increased soil dryness due to drainage via earthworm burrows and mesocosm evapotranspiration. Soil macroporosity (measured by X-ray tomography) was affected by earthworm species-specific burrowing activity. Both GHG emissions decreased with topsoil macropore volume, presumably due to reduced moisture and microbial activity. N<sub>2</sub>O emissions decreased with macropore volume in the deepest layer, likely due to the presence of fewer anaerobic microsites. Our results indicate that, under experimental conditions allowing for plant and earthworm engineering effects on soil moisture, earthworms do not increase GHG emissions, and endogeic earthworms may even reduce N<sub>2</sub>O emissions.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.Flexing with lines or pipes: Techno-economic comparison of renewable electricity import options for European research facilitiesJohannes Hampp10.1371/journal.pone.02928922024-02-08T14:00:00Z2024-02-08T14:00:00Z<p>by Johannes Hampp</p>
Where local resources for renewable electricity are scarce or insufficient, long-distance electricity imports will be required in the future. Even across long distances, the variable availability of renewable energy sources needs to be managed for which dedicated storage options are usually considered. Other alternatives could be demand-side flexibility and concentrated solar power with integrated thermal energy storage. Here their influence on the cost of imported electricity is explored. Using a techno-economic linear capacity optimization, exports of renewable electricity from Morocco and Tunisia to CERN in Geneva, Switzerland in the context of large research facilities are modeled. Two different energy supply chains are considered, direct imports of electricity by HVDC transmission lines, and indirect imports using H2 pipelines subsequent electricity generation. The results show that direct electricity exports ranging from 58 EUR/MWh to 106 EUR/MWh are the more economical option compared to indirect H2-based exports ranging from 157 EUR/MWh to 201 EUR/MWh. Both demand-side flexibility and CSP with TES offer significant opportunities to reduce the costs of imports, with demand-side flexibility able to reduce costs for imported electricity by up to 45%. Research institutions in Central Europe could initiate and strengthen electricity export-import partnerships with North Africa to take on a leading role in Europe’s energy transition and to secure for themselves a long-term, sustainable electricity supply at plannable costs.Windblown sand hazards risk assessment along the highways based on GIS-game theory combination weightLiangying LiLele LvZhizhong TaoWenhua YinQi LiZhenqiang Wang10.1371/journal.pone.02922632024-02-08T14:00:00Z2024-02-08T14:00:00Z<p>by Liangying Li, Lele Lv, Zhizhong Tao, Wenhua Yin, Qi Li, Zhenqiang Wang</p>
Windblown sand hazards seriously threaten the safe operation of highways in desert areas. Reasonable risk assessment can provide the basis for windblown sand hazards prevention and risk reduction. To facilitate the formulation of better windblown sand hazards prevention and reduction strategies, a new windblown sand hazards risk assessment model along the highways was proposed, in which seven evaluation indicators were selected from danger of the hazard-causing factors, vulnerability of the hazard-forming environment, and the vulnerability of the hazard-bearing body. The model was established based on the combination weighting method of game theory, and the risk map was generated based on the GIS platform. Finally, the model was applied to the windblown sand hazards risk assessment along the Wuhai-Maqin Highway. The result showed that the risk of the windblown sand hazards along the Wuhai-Maqin Highway is mainly medium, low, and very low. High and very high risk windblown sand hazards sections account for only 33% of the total length of the highway. The high and very high risk highway sections of the windblown sand hazards are mainly distributed in the hinterland of shifting dunes area and near the horizontal curve with a small radius in the flat sandy land area. By comparing with the real information of windblown sand hazards along the highway, correlation was up to 85.93%, which verified the accuracy of the model. The model can be applied to windblown sand hazards risk assessment along the highways.Empirical study of college students’ extracurricular reading preference by functional data analysis of the library book borrowing behaviorFan ZhangYuling LiuChao SongChun YangShaoyong Hong10.1371/journal.pone.02973572024-01-26T14:00:00Z2024-01-26T14:00:00Z<p>by Fan Zhang, Yuling Liu, Chao Song, Chun Yang, Shaoyong Hong</p>
Library data contains many students’ reading records that reflect their general knowledge acquisition. The purpose of this study is to deeply mine the library book-borrowing data, with concerns on different book catalogues and properties to predict the students’ extracurricular interests. An intelligent computing framework is proposed by the fusion of a neural network architecture and a partial differential equations (PDE) function module. In model designs, the architecture is constructed as an adaptive learning backpropagation neural network (BPNN), with automatic tuning of its hyperparameters. The PDE module is embedded into the network structure to enhance the loss functions of each neural perceptron. For model evaluation, a novel comprehensive index is designed using the calculus of information entropy. Empirical experiments are conducted on a diverse and multimodal time-series dataset of library book borrowing records to demonstrate the effectiveness of the proposed methodology. Results validate that the proposed framework is capable of revealing the students’ extracurricular reading interests by processing related book borrowing records, and expected to be applied to “big data” analysis for a wide range of various libraries.