dataesr/scientific-paragraphs-categorization huggingface dataset:
Although the influence of the power plant PP5 on HOA-2 is expected, contribution of this source can not be exclude for HOA-1 as well. On the other hand, quantification of the Middle Eastern contribution to the HOA-2 factor remains to be assessed, since the current dataset cannot provide sufficient information on separating the contribution of power plants on the island versus more regional Middle East emissions (Fig. S165b ). Although this hypothesis needs further investigation, the presence of HOA-2 in the Middle East would be consistent with recent findings highlighting the importance of OC emissions from diesel generators used in Lebanon as a mean of complementary power generation  (Fadel et al. , 2022). In conclusion, based on the relative contribution of OA factors (Fig. 9 ) and the NWR analysis (Fig.
Conclusions Near-real-time chemical composition of submicron aerosols and source apportionment of carbonaceous aerosols was performed for the first time in Nicosia, a medium-size European capital city (circa 250,000 inhabitants) in Cyprus located in the Eastern Mediterranean and surrounded by Middle East countries with fast growing population and increasing emissions of air pollutants. Continuous observations were performed at an urban background site, for approximately 6 months (between 7 December 2018 and 31 May 2019), in order to obtain a large and representative dataset capturing specific features related to cold and warm periods, such as domestic heating and regional transport. Measurements of the major fractions of PM1 were carried out with a Q-ACSM and an Aethalometer complemented by a comprehensive suite of collocated instruments (e.
As mentioned in the previous paragraph, this review focused on evidence from the literature for air taxis, mainly on the architectures, algorithms, and techniques that deal with safety and security. The systematic review process presented in this section was carried out with the collaboration of the online tool Parsifal. Parsifal provides all necessary support to execute the systematic review protocol in a formalized, stepped way, including review objectives, research questions, keywords, synonyms, inclusion and exclusion criteria, data extraction, and others  [22, 23]. This review was divided into four stages. During Step 1, the plan consisted of the definition of objectives, search sources, criteria for inclusion or exclusion of studies, the language of the studies, search key, etc. In Step 2, the execution was carried out, where the studies were taken from the predefined sources during Step 1 and placed in Parsifal.
Step 1: Planning The main objective of this review was to identify techniques, architectures, and algorithms used to diagnose and mitigate attacks on air taxis. Research questions, search sources, search strings, and inclusion and exclusion criteria were defined during the planning phase. Among the research questions, the following were defined: 1. What are the main techniques that have been investigated to provide security and safety support for air taxis? 2. What types of tests (e. g. , simulation, databases, etc. ) are used to test security and safety techniques in air taxis? 3. What is missing for air taxis to be implemented in everyday life? 4. What gaps exist in safety and computer security in air taxis?.
Study Selection After performing the search in repositories with the search strings, defining a period from January 2015 to January 2022, a total of 213 studies were identified. Their information was exported from the databases in Bibtex format and imported on the Parsifal platform. The database with the most significant number of articles related to the topic was IEEEXplore Digital Library, followed by the SCOPUS, Web of Science, and ACM Digital Library, as its possible to see in Figure  1. One hundred and fifteen articles were identified in IEEEXplore Digital Library (53. 3%), seventy-two in SCOPUS (34. 2%), twenty in Web of Science (9. 3%), and only six in Scopus (2. 8%). The first selection was made by reading the titles and abstracts, identifying the inclusion and exclusion criteria. The articles accepted were those that met at least one of the inclusion criteria, and the rejected articles were those that met at least one exclusion criterion.
In the end, 178 articles were accepted, and 35 were rejected. The distribution of the selected articles in each of the bases can be observed in the graph of Figure  2. The highest number of articles were found in the IEEExplorer Digital Library database, followed by SCOPUS. After primary study selection, each accepted article was read in its totality and rematched to an inclusion or exclusion criteria. During the full reading, summaries were generated as results. The number of articles accepted in the final selection stage can be seen in Figure  3. The highest number of articles found and consequently accepted were on IEEE, with a total of 41 studies selected, followed by SCOPUS, with 13 accepted articles, Web of Science, with 7, and only 2 from ACM. Among the accepted articles, the criterion that received the highest level of acceptance was that of studies that use techniques and/or algorithms of safety or security in flying cars.
Another fact mentioned in the literature is the absence of systems that can identify the weather, such as winds, on sunny days. In other words, it is not enough to provide general data, but complete access to real-time climate data is required. Meeting all current climate needs will require engineers and scientists to not only implement observational systems, but also databases that gather meteorological data from aircraft sensors to initialize numerical prediction models. All studies found in the literature that relate to accidents due to attacks are focused on GPS, for example, GPS spoofing and jamming  [35, 40, 42, 46, 48, 49]. One of the reasons that may justify this is the fact that GPS is the most recurrent target of attacks on civilian air vehicles  [40] , since these vehicles do not have encryption, unlike military vehicles.
Technique Study Machine learning  [14, 34, 36, 54, 63, 64]  Bayesian belief network  [35]  Object-oriented BBN  [35]  Gas models  [35]  Reliability diagram  [36]  Artificial intelligence  [54]  Encryption  [54]  Trajectory-based operations overview  [65]  A technique for deriving classification models to predict conditions that increase the probability of air crashes involving fatalities and serious injuries is presented in  [34]. The study comprises machine learning classification techniques, including decision trees, Knearest neighbors, support vector machines (SVMs), and artificial neural networks (ANNs) that are applied to datasets derived from original data obtained from Federal Aviation Administration (FAA) aviation accident and incident records from 1975-2002. Accident data are filtered to focus on FAA Part 91 (General Aviation) accidents involving manufactured, fixed-wing, and powered aircraft.
Type of Test Study Accident data  [34]  GPS fault emulation  [35]  Multi-agent system  [16]  Airborg SITL simulation  [9]  Non-specific simulation  [40, 41, 46]  Safety-driven behavior management  [63]  Systolic FLS architecture  [13]  In  [34] , we used a dataset of FAA aviation accident and incident records from 1975-2016 to test the application of different machine learning techniques to derive classification models to predict conditions that increase the probability of aircraft accidents involving fatalities and serious injuries. According to the authors, FAA data are divided into accident and incident records and cover FAR Parts 91 (GA), 121 (commercial aviation), 135 (air taxis), ultralights (103), parachute operations (105), helicopters (133), agricultural operations (137), and flight schools (141).
In  [16] , a multi-agent system was used, which, according to the authors, has the advantage of the possibility of creating and simulating multiple vehicles (or agents) that act independently, as would happen in real situations. This tool uses the Netlogo language and allows the modeling of multiple UAVs with stochastic trajectories created in a decentralized way, verifying how the model deals with conflicts and obstacles  [16]. Safety-driven behavior management, on the other hand, has as its main focus the modeling of situations and problems of knowledge representation in the context of situational risks, and can be customized depending on the research objective  [63]. Finally, the systolic FLS architecture proposed in  [13]  was designed and tested using MATLAB and VHDL to interface with five Lidar sensors and five ultrasonic sensors using an Intel Altera OpenVINO FPGA board.
HAMSTER integrates four platforms: (1) Nimble, (2) NCI, (3) NP, and (4) SPHERE, where the SPHERE platform is focused on architectural security and safety issues. Security and safety Platform for HEt-eRogeneous systEms (SPHERE) is HAMSTER's safety and security platform. Unmanned vehicles have different peripherals and modules, so they require different levels of safety, thus leading to the need to classify modules according to their importance and criticality. According to  [41] , modules are categorized as primary or secondary. Primary modules have the crucial components for the aircraft to fly, be aware of its location, and be able to make an emergency landing safely. These modules are the GPS receiver, autopilot, flight plan, radar, etc. The authors carry out architecture validations through concrete implementations of HAMSTER modules.
Therefore, it is necessary to investigate and treat safety and security together in a UAV architecture. In this sense, STUART is the only architecture concerned with both insecurities. However, the architecture is still in the simulation testing phase and has not been tested on a real avionics architecture. Likewise,  [68]  presents a container framework that proposes resilient control against DoS attacks for real-time UAV systems using containers. Container technology is open source and offers software isolation  [69, 70]  and abstraction of many features in the Linux kernel. System isolation using containers leads to less execution overhead, less memory usage, and a smaller footprint. Compared to virtual machines (VMs), containers have advantages in lightness  [68]  because they share the host kernel, while a virtual machine needs a hypervisor to communicate with the kernel.
In terms of efficiency, a container is generally tens of MBs, while a VM easily exceeds a GB. ContainerDrone provides support mechanisms for three system resources, namely the central processing unit (CPU), communication channel, and memory, and also offers resilient control against DoS attacks for real-time UAVs. The ContainerDrone framework has proven to be reliable in protecting against DoS attacks launched within the container by limiting attacker access to three critical system resources: the CPU, memory, and communication channel. Experiments have shown that the proposed structure can be effective against various types of container control environment (CCE) DoS attacks. In this study, the authors did not consider physical component failures, software failures caused by bugs and/or logic failures, or any attack other than DoS.
A scarecrow architecture utilizes geo-enclosed areas with manning restrictions as well as aircraft volume restrictions from which these geo-enclosed areas are dynamically computed. According to the authors in  [7] , the safety margin of the dynamic structure is continuously calculated to provide guidance to the control algorithms that regulate airspace loading. Scarecrow Architecture, BRECCIA, HAMSTER, and STUART are four examples of concise, drill-down architectures for air taxis, each with its own goals and objectives as described. The most widespread architecture in the literature, not only in terms of references but also in terms of technical software and hardware evolutions, is NASA's vehicle  [11, 32, 54, 66, 67]. NASA has contributed efforts in the development of air taxi aircraft designs.
Conclusions This section discusses current approaches in progress in the literature and open gaps in general. The first point to be discussed is about recent accidents, because, as far as we know, there are no studies that use up-to-date databases considering the evolution of aviation in recent years. Aviation has progressed, and with that, the causes of accidents have also changed, so using recent databases will bring an accurate view with respect to air taxis through new sets and prediction models. As discussed throughout the results, one of the main concerns of current pilots is detailed information about the weather during flights. Examples of this information are wind gusts, thunderstorms, unexpected air events, bad weather alerts, etc. Although systems with this information already exist, state-of-the-art systems with high accuracy of real-time information are still lacking.
Acknowledgements The  World Health Organization Global Maternal Sepsis Study (GLOSS)  is a research project implemented by the WHO in a global network of health facilities between 2017 and 2018. This project is part of the WHO response to the Sepsis resolution adopted by the 70th World Health Assembly (2017). We sincerely thank the women who participated in this study. WHO is grateful to the extensive network of institutions and individuals who contributed to the project design and implementation, including researchers, study coordinators, data collectors, data clerks, and other partners including the staff from the  Ministries of Health  and WHO offices. We would like to thank  Allisyn Moran  (Scientist at the  World Health Organization (WHO)  in the Department of Maternal, newborn, Child, and  Adolescent Health (MCA) ) and  Marian Knight  for their comments on this manuscript.
The main aim of the present study is to evaluate the influence of multi-walled carbon nanotubes (MWCNTs) and TiO 2 nanoparticles (NPs) on lubricant and fluid flow within natural gas turbine meters. In light of this purpose, disparate concentration of TiO 2 NPs (0. 1, 0. 2, and 0. 3 wt%), various volume flow rates 0. 14, 0. 35, and 0. 12 cm 3 S were employed for experimental analyses. In the facet of simulation, Gambit software version 2. 4. 6 to mesh oil pathway and Fluent software version for solving the equations were utilized. It was revealed that the pressure drop in the presence of nanoparticles was increased. Moreover, there was an increase in pressure drop value with raising the NPs concentration; for instance, the pressure drop value of MWCNTs-containing nanofluids at the volume flow rate of 0.
Numerical analysis The oil pathway is meshed by Gambit software version 2. 4. 6 and the equations have been solved by Fluent software version 19. 1. ANSYS-FLUENT software has been used to solve the governing equations discretized with a double-precision solver using the SIMPLEC algorithm. The convergence criteria for continuity, momentum, and energy equations were all set to 10 -6. For the mesh independence check, Fig. 6  is plotted, and given the optimal number of cells, 368,462 is selected. The absolute convergence criteria for the continuum equation and the velocity equation with residuals below have been considered.
We obtain high-resolution images with an optimal contrast  (38). Briefly, ssDNA-enriched samples were added to a mix of formamide, BAC and glyoxal, to generate a hyperphase film onto the surface of a water bath. The DNA was picked up on positive functionalized carbon-coated grids by a brief contact with the hyperphase film surface. Grids were then washed in a large volume of purified milliQ water followed by 100% ethanol and dried with filter paper. Finally, molecules adsorbed onto the grids were positively stained with 2% aqueous uranyl acetate and dried. Samples were visualized in annular dark field mode, filtered in zero loss, with a Zeiss EM902 transmission electron microscope equipped with Electron Energy Loss Spectrometer (EELS). Electron micrographs were obtained at 50 000 or 85 000 magnifications (140 000 for the inlays) acquired using a Veletta high-resolution CCD camera asso-ciated to a dedicated iTEM software (Olympus, Soft Imaging Solutions).
All fluorescent antibodies were from Molecular Probes and used at 1/100 dilution. Antibodies were diluted in blocking buffer. Samples were washed four times in PBS between each antibody incubation. Samples were mounted in fluorescent mounting medium (DAKO). Images were acquired and analysed on an Axio Imager Z1 microscope using the Axio Vision software (Zeiss). Broken replication tracks were excluded from the analysis.
S1 nuclease DNA fiber assay Detection of ssDNA gaps on nascent DNA was performed as already described  (45)  with minor modifications. Analogue pulses and treatments were performed as described above and in the figure legends. Cells were then extracted in 100 mM NaCl, 300 mM Sucrose, 3 mM MgCl 2 , 10 mM PIPES pH 6. 8, 0. 5% Triton X-100 for 7 min at room temperature and incubated for 20 min at 37 • C in S1 nuclease buffer (50 mM NaCl, 30 mM sodium acetate pH 4. 6, 2 mM zinc acetate and 5% glycerol) supplemented or not with 20 U ml -1 of S1 nuclease (Invitrogen). Nuclei were collected by scrapping in PBS 0. 1% BSA followed by centrifugation at 1500 × g for 5 min at 4 • C. Nuclei were resuspended in PBS 10 mM EDTA. DNA was spread and immune-stained as described above. Images were acquired on an Axio Observer Z1 microscope using Axio Vision software (Zeiss) and analysed on ImageJ software.
Immunofluorescence Cells were pre-extracted in CSK100 buffer for 5 min on ice under gentle agitation. Cells were fixed in 4% paraformaldehyde for 20 min and permeabilized in methanol at -20 • C for 10 s. Cells were incubated for 1 h at room temperature with primary antibodies (rabbit anti-RAD51 Calbiochem PC130 1/200 and mouse anti-PCNA Santa Cruz PC10 1/500) diluted in IF buffer (3% BSA, 0. 5% Tween 20 in PBS). Cells were washed three times in PBS and stained for 30 min with secondary antibodies from Molecular Probes (goat anti-rabbit AF488 1/1000, goat anti-mouse AF594 1/1000). Coverslips were mounted in fluorescent mounting medium (DAKO) supplemented with DAPI (1. 5 g/ml). Images were acquired on an AxioImager Z1 microscope using the Axio Vision software (Zeiss). Intensity was quantified with the ImageJ software.
From the above data, we could infer that the accumulation of RAD51 on post-replicative chromatin correlates with the observation of multi-branched structures in vivo which illustrates post-replicative RAD51-dependent recombination events occurring to fill in the gaps accumulated behind the RFs. Finally, we assessed the impact of RAD51 inhibition on cell survival after UVC irradiation. Whereas B02 treatment had similar effects on cell proliferation in unirradiated XPV and XPV pol cells (data not shown), it increased UVC sensitivity to a higher extent in XPV cells than in XPV pol cells (Figures  7C, D , Supplementary Table  S19 ). In particular, at the sub-lethal dose of 2 J m -2 , XPV cells were sensitized by lower concentrations of B02 than XPV pol cells (Figure  7D ). Importantly, these findings were fully recapitulated in poldepleted MRC5-V1 cells (Supplementary Figures  S8C, D ).
ACKNOWLEDGEMENTS The authors are indebted to  L. Blanco  for the kind gift of anti-PrimPol antibody. The authors thank  L. Blanco ,  A. Doherty , and all members of the P. L. K. lab for helpful discussions and  J. H. Guervilly  for critical reading of the manuscript. The authors thank  Barbara Ben-Yamin  and  Raphaël Corre  for the RT-qPCR experiments.
Discussion Up to now, investigations on HIV-1 bNAbs have been exclusively focused on IgG antibodies. Env-specific IgA antibodies are elicited in response to HIV-1 infection  (Lopez et al. , 2018; Nabi et al. , 2017; Ruiz et al. , 2016)  but remain understudied despite their functional relevance  (Black et al. , 1996; Lopez et al. , 2018; β-hairpin (left; 10-1074 [PDB accession no. 5T3Z]   and 3H+109L    (D) Same as in C but for BG505 SOSIP. 664-7-176 complex. (E) Superposition of the reconstructions obtained for the three BG505 SOSIP. 664-bNAb complexes studied (side and top views), showing the overlap between their respective binding sites. For a better comparison, the data from the BG505 SOSIP. 664-7-269-3BNC117 complex was reprocessed with a resolution limit of 7 Å. Mouquet, 2014; Planque et al.
FcγR and FcαR expression on isolated cells was evaluated by flow cytometric staining with APC anti-human CD16 (clone REA423; Miltenyi Biotec), BV421 anti-human CD89 (clone A59; BD Biosciences), FITC antihuman CD64 (clone 10. 1; Invitrogen), and human anti-CD32a antibody MDE8 (van  Royen-Kerkhof et al. , 2005)  coupled to DyLight 594 (Thermo Fisher Scientific). Data on stained cells were acquired using a BD LSR Fortessa cytometer (BD) and analyzed using FlowJo software (v10. 7. 1).
Once merged, sequences were assigned with GL Ig genes using IgBlast (https://www. ncbi. nlm. nih. gov/igblast/), which was also used to remove sequences with low-quality features (stop codon, V-gene E-value >10 -3 , undefined CDR H 3 and FWRs, or subject alignment starts >9) and database building. CD-HIT clustering program (http://weizhongli-lab. org/cd-hit/) allowed exclusion of redundant reads (99% identity), and only representative and isotype-checked sequences were then used to perform divergence/identity analyses using Needle program (http:// embossgui. sourceforge. net/demo/manual/needle. html) to align and compute similarity scores with library sequences trimmed at the end of FWR3 and FWR4 for alignment with V-gene GL and pt7 bNAb reference sequence, respectively (gapopen, 10; gapextent, 0.
Protein microarrays All experiments were performed at 4°C using ProtoArray Human Protein Microarrays (Thermo Fisher Scientific). Microarrays were blocked for 1 h in blocking solution (Thermo Fisher Scientific), washed, and incubated for 1 h 30 min with IgG antibodies at 2. 5 µg/ml as previously described  (Planchais et al. , 2019). After washing, arrays were incubated for 1 h 30 min with AF647-conjugated goat anti-human IgG antibodies (at 1 µg/ml in PBS; Thermo Fisher Scientific) and revealed using GenePix 4000B microarray scanner (Molecular Devices) and GenePix Pro 6. 0 software (Molecular Devices) as previously described  (Planchais et al. , 2019). Fluorescence intensities were quantified using Spotxel software (SICASYS Software), and mean fluorescence intensity (MFI) signals for each antibody (from duplicate protein spots) were plotted against the reference antibody mGO53 (nonpolyreactive isotype control) using Prism software (v8.
1. 2; GraphPad). For each antibody, Z-scores were calculated using ProtoArray Prospector software (v5. 2. 3; Thermo Fisher Scientific), and deviation (σ) to the diagonal and polyreactivity index (PI) values were calculated as previously described  (Planchais et al. , 2019). Antibodies were defined as polyreactive when PI > 0. 21. HEp-2 cell IFA Binding of human anti-HIV-1 Env and control monoclonal IgG antibodies (mGO53  [Wardemann et al. , 2003]  and ED38  [Meffre et al. , 2004] ) to HEp-2 cell-expressing autoantigens was analyzed at 100 µg/ml by indirect IFA (ANA HEp-2 AeskuSlides; Aesku. Diagnostics) following the manufacturer's instructions in two independent experiments. IFA sections were examined using the fluorescence microscope Axio Imager 2 (Zeiss), and pictures were taken at magnification 40× with 5,000 msacquisition using ZEN imaging software (Zen 2.