bluuebunny/crossref_metadata_2025_split huggingface dataset:
Near‐field atmospheric inversions for the localization and quantification of controlled methane releases using stationary and mobile measurements
Authors: Kumar Pramod , Broquet Grégoire , Caldow Christopher , Laurent Olivier , Gichuki Susan , Cropley Ford , Yver‐Kwok Camille , Fontanier Bonaventure , Lauvaux Thomas , Ramonet Michel , Shah Adil , Berthe Guillaume , Martin Frédéric , Duclaux Olivier , Juery Catherine , Bouchet Caroline , Pitt Joseph , Ciais Philippe 
Published: April 2022

AbstractThis study evaluates two local‐scale atmospheric inversion approaches for the monitoring of methane (CH4) emissions from industrial sites based on in situ atmospheric CH4 mole fraction measurements from stationary or mobile sensors. We participated in a two‐week campaign of CH4 controlled‐release experiments at TotalEnergies Anomaly Detection Initiatives (TADI) in Lacq, France in October 2019. We analyzed releases from various points within a 40 m × 50 m area with constant rates of 0.16 to 30 g CH4 s−1 over 25 to 75 mins, using fixed‐point and mobile measurements, and testing different inversion configurations with a Gaussian dispersion model. An inlet switching system, combining a limited number (6–7) of high‐precision gas analyzers with a higher number (16) of sampling lines, ensured that a sufficient number of fixed measurement points sampled the plume downwind of the sources and the background mole fractions for any wind direction. The inversions using these fixed‐point measurements provide release rate estimates with approximately 23%–30% average errors and estimates of the location of the releases with approximately 8–10 m average errors. The inversions using the mobile measurements provide estimates with approximately 20%–30% average errors for the release rates and approximately 30 m average errors for the release locations. The precision of the release rate estimates from both inversion frameworks corresponds to the best estimation precision documented on site‐scale CH4 inversions. However, the use of continuous measurements from fixed stations provides much more robust estimates of the source locations than that of the mobile measurements.
Robust stabilization under structured, possibly unstable and impulsive uncertainties
Authors: Stefanovski Jovan D. 
Published: April 2022

AbstractNecessary and sufficient conditions for the robust stabilization under structured dynamical uncertainties, which can be unstable and impulsive, are given. The order of the controller is predefined. It is shown that disturbances in some channels can be completely arbitrary, while the stability is preserved. It is shown that the solution to this problem can be applied to the fault‐tolerant control, where the faults can be unstable and/or impulsive systems. The given conditions are expressed by nonconvex matrix inequalities. However, for two classes of systems, the conditions reduce to LMIs. Examples with random numbers illustrate the design algorithm.
Adaptive ride height controller design for vehicle active suspension systems with uncertain sprung mass and time‐varying disturbance
Authors: Zhao Rongchen , Xie Wei , Yu Gan , Wang Guangwei , Wong Pak Kin , Silvestre Carlos 
Published: April 2022

AbstractIn this article, we address the problem of ride height tracking control of the automotive active air suspension (AAS) system with uncertain sprung mass and external time‐varying disturbances. The proposed adaptive robust control approach guarantees that (i) the ride height converges towards, and stays within, an arbitrarily small neighborhood of the desired height, attaining uniform ultimate boundedness; (ii) the closed‐loop AAS system is (1) adaptive to uncertain sprung mass caused by the change of payload through the design of a projector‐based mass estimator; and, (2) robust to external time‐varying disturbance by developing a nonlinear disturbance observer. At last, co‐simulation (AMESim‐Matlab/Simulink) and experimental tests on a self‐fabricated quarter‐car test rig are conducted to demonstrate the effectiveness and performance of the proposed method.
Applying machine learning to automatically assess scientific models
Authors: Zhai Xiaoming , He Peng , Krajcik Joseph 
Published: April 2022

AbstractInvolving students in scientific modeling practice is one of the most effective approaches to achieving the next generation science education learning goals. Given the complexity and multirepresentational features of scientific models, scoring student‐developed models is time‐ and cost‐intensive, remaining one of the most challenging assessment practices for science education. More importantly, teachers who rely on timely feedback to plan and adjust instruction are reluctant to use modeling tasks because they could not provide timely feedback to learners. This study utilized machine learning (ML), the most advanced artificial intelligence (AI), to develop an approach to automatically score student‐drawn models and their written descriptions of those models. We developed six modeling assessment tasks for middle school students that integrate disciplinary core ideas and crosscutting concepts with the modeling practice. For each task, we asked students to draw a model and write a description of that model, which gave students with diverse backgrounds an opportunity to represent their understanding in multiple ways. We then collected student responses to the six tasks and had human experts score a subset of those responses. We used the human‐scored student responses to develop ML algorithmic models (AMs) and to train the computer. Validation using new data suggests that the machine‐assigned scores achieved robust agreements with human consent scores. Qualitative analysis of student‐drawn models further revealed five characteristics that might impact machine scoring accuracy: Alternative expression, confusing label, inconsistent size, inconsistent position, and redundant information. We argue that these five characteristics should be considered when developing machine‐scorable modeling tasks.
Panax notoginseng saponins improves healing of high glucose‐induced wound through the GSK‐3β/β‐catenin pathway
Authors: Lei Ting , Gao Ya , Duan Yuhong , Cui Chunli , Zhang Li , Si Mingming 
Published: April 2022

AbstractChronic non‐healing wounds are one of the most common complications of diabetes mellitus and results in a huge physical and mental burden for patients. Panax notoginseng saponins (PNS) have a wide range of applications in anti‐apoptosis, anti‐oxidation, and promoting blood circulation. Our study aimed to explore whether PNS could improve diabetic wound healing. High‐glucose (HG, 30 Mm) were used to incubated human umbilical vein endothelial cells (HUVECs) to simulate the hyperglycemia environment in vivo, and 200 μg/ml (optimum harmless concentration screened) PNS was added into HG‐incubated HUVECs to investigate the protective effect of PNS on the cells. Compared with control, high glucose treatment significantly suppressed HUVEC proliferation, invasion, migration, angiogenesis, malondialdehyde (MDA) production and nitric oxide (NO) release, promoted cell apoptosis, and deactivated the GSK‐3β/β‐catenin/VEGF pathway. PNS treatment could largely rescue the effects of HG on cell dysfunction and improve the deactivation of GSK‐3β/β‐catenin/VEGF pathway. ICG‐001, a small molecular β‐catenin inhibitor that can selectively antagonize β‐catenin mediated transcriptional activity, could eliminate the protective effects of PNS on cell dysfunction and activation of GSK‐3β/β‐catenin/VEGF pathway. Moreover, Furthermore, a diabetic model (50 mg/kg streptozotocin induced) with back skin wound was established in rats, and the wounds were administrated with petrolatum, gelatin/Bletilla striata gelatin (GT/BSGT), or GT/BSGT plus PNS. We found that PNS signally facilitated wound healing and matrix remodeling in vivo. In conclusion, our study verified that PNS improved wound healing in hyperglycemic rats via promoting endothelial cell proliferation, invasion, migration, angiogenesis, suppressing cell apoptosis and oxidative damage, and activating the GSK‐3β/β‐catenin pathway.
A novel process driving Alzheimer's disease validated in a mouse model: Therapeutic potential
Authors: Greenfield Susan A. , Cole Gregory M. , Coen Clive W. , Frautschy Sally , Singh Ram P. , Mekkittikul Marisa , Garcia‐Ratés Sara , Morrill Paul , Hollings Owen , Passmore Matt , Hasan Sibah , Carty Nikisha , Bison Silvia , Piccoli Laura , Carletti Renzo , Tacconi Stephano , Chalidou Anna , Pedercini Matthew , Kroecher Tim , Astner Hubert , Gerrard Philip A. 
Published: April 2022

AbstractIntroductionThe neuronal mechanism driving Alzheimer's disease (AD) is incompletely understood.MethodsImmunohistochemistry, pharmacology, biochemistry, and behavioral testing are employed in two pathological contexts—AD and a transgenic mouse model—to investigate T14, a 14mer peptide, as a key signaling molecule in the neuropathology.ResultsT14 increases in AD brains as the disease progresses and is conspicuous in 5XFAD mice, where its immunoreactivity corresponds to that seen in AD: neurons immunoreactive for T14 in proximity to T14‐immunoreactive plaques. NBP14 is a cyclized version of T14, which dose‐dependently displaces binding of its linear counterpart to alpha‐7 nicotinic receptors in AD brains. In 5XFAD mice, intranasal NBP14 for 14 weeks decreases brain amyloid and restores novel object recognition to that in wild‐types.DiscussionThese findings indicate that the T14 system, for which the signaling pathway is described here, contributes to the neuropathological process and that NBP14 warrants consideration for its therapeutic potential.
Close follow‐up is associated with fewer stricture formation and results in earlier detection of histological relapse in the long‐term management of eosinophilic esophagitis
Authors: Bon Lorenz , Safroneeva Ekaterina , Bussmann Christian , Biedermann Luc , Schreiner Philipp , Vavricka Stephan R. , Schoepfer Alain M. , McCright‐Gill Talaya , Simon Hans‐Uwe , Straumann Alex , Chehade Mirna , Greuter Thomas 
Published: April 2022

AbstractBackground and aimsNo recommendations exist regarding optimal follow‐up schedule in patients with eosinophilic esophagitis (EoE) under maintenance treatment.MethodsWe retrospectively evaluated a long‐term surveillance concept at the Swiss EoE clinic, where clinical, endoscopic and histological disease activity is assessed annually regardless of EoE symptoms. Data on 159 adult patients under maintenance steroid treatment with available follow‐up were analyzed. Patients were classified as having close (duration between visits <18 months) or non‐close follow‐up (≥18 months).ResultsWe analyzed a total of 309 follow‐up visits of 159 patients (123 males, age at diagnosis 38.9 ± 15.4 years). 157 (51%) visits were within a close follow‐up schedule (median duration between visits of 1.0 years (interquartile range (IQR) 0.9–1.2)), while 152 visits (49%) were not (median duration between visits 2.9 years (IQR 2.0–4.1)). There was no difference regarding ongoing clinical, endoscopic, and histological disease activity, and adherence to prescribed steroid treatment between the two groups. However, stricture formation was significantly less frequently observed at visits within a close follow‐up schedule (22.9 vs. 33.6%, p = 0.038). Absence of close follow‐up was a significant risk factor for stricture development in a multivariate regression model. Patients who achieved histological remission and were followed within a close‐follow‐up schedule had significantly earlier detection of histological relapse compared to patients not within such close follow‐up.ConclusionClose follow‐up is associated with fewer stricture formation and appears to result in earlier detection of histological relapse in patients with eosinophilic esophagitis. We advocate for regular assessment of disease activity (every 12–18 months) in order to detect relapsing disease as early as possible, and therefore potentially minimize the risk for EoE complications.
Accelerating development of fish and wildlife professionals will take more than training
Authors: Siemer William F. , Baumer Meghan S. , Pomeranz Emily F. , Decker Daniel J. , Forstchen Ann B. , Riley Shawn J. , Schiavone Michael V. , Smith Christian A. , Lederle Patrick E. 
Published: April 2022

AbstractHastening the development of early and mid‐career fish and wildlife (hereafter wildlife) professionals in state and federal agencies is an acute need. In particular, development and application of exceptional reasoning and judgment skills is critical. It would be shortsighted, however, for wildlife agency administrators to assume professional development is simply a matter of staff training. Decker et al. (2019) completed an expert panel study in 2019 to identify habits and practices of consistently high performing wildlife management professionals. Decker et al. (2019) suggest 5 clusters of competencies are characteristic of consistently high‐performing wildlife professionals: being a critically inquisitive, continuous learner; practicing multi‐level, integrative systems thinking; being self‐disciplined; using a balanced approach; and having the emotional intelligence to interact successfully with others. Based on observations from a series of workshops with wildlife professionals, our collective professional experience, and literature review, we contend that impediments to expression of key habits/practices identified by Decker et al. (2019) exist at the group and organizational, as well as the individual level. We argue that providing individual training is necessary, but not sufficient to create work environments where wildlife professionals in state and federal wildlife agencies can develop and apply reasoning and judgment skills. Structural and cultural change in wildlife agencies would enhance effectiveness of public wildlife management. We hope this empirically‐grounded commentary stimulates reflection within wildlife agencies and a commitment to organizational behavior that catalyzes professional development.
NAD: Machine Learning Based Component for Unknown Attack Detection in Network Traffic
Authors: Krzysztoń Mateusz , Lew Marcin , Marks Michał 
Published: April 2022

AbstractDetection of unknown attacks is challenging due to the lack of exemplary attack vectors. However, previously unknown attacks are a significant danger for systems due to a lack of tools for protecting systems against them, especially in fast-evolving Internet of Things (IoT) technology. The most widely used approach for malicious behaviour of the monitored system is detecting anomalies. The vicious behaviour might result from an attack (both known and unknown) or accidental breakdown. We present a Net Anomaly Detector (NAD) system that uses one-class classification Machine Learning techniques to detect anomalies in the network traffic. The highly modular architecture allows the system to be expanded with adapters for various types of networks. We propose and discuss multiple approaches for increasing detection quality and easing the component deployment in unknown networks by known attacks emulation, exhaustive feature extraction, hyperparameter tuning, detection threshold adaptation and ensemble models strategies. Furthermore, we present both centralized and decentralized deployment schemes and present preliminary results of experiments for the TCP/IP network traffic conducted on the CIC-IDS2017 dataset.
Signature-Based Detection of Botnet DDoS Attacks
Authors: Szynkiewicz Paweł 
Published: April 2022

AbstractThe distributed denial of service (DDoS) attack is an attempt to disrupt the proper availability of a targeted server, service or network. The attack is achieved by corrupting or overwhelming the target’s communications with a flood of malicious network traffic. In the current era of mass connectivity DDoS attacks emerge as one of the biggest threats, staidly causing greater collateral damage and heaving a negate impacting on the integral Internet Infrastructure. DDoS attacks come in a variety of types and schemes, they continue to evolve, steadily becoming more sophisticated and larger at scale. A close investigation of attack vectors and refining current security measures is required to efficiently mitigate new DDoS threats. The solution described in this article concerns a less explored variation of signature-based techniques for DDoS mitigation. The approach exploits one of the traits of modern DDoS attacks, the utilization of Packet generation algorithms (PGA) in the attack execution. Proposed method performs a fast, protocol-level detection of DDoS network packets and can easily be employed to provide an effective, supplementary protection against DDoS attacks.
Chromite compositional variability and associated PGE enrichments in chromitites from the Gomati and Nea Roda ophiolite, Chalkidiki, Northern Greece
Authors: Bussolesi Micol , Grieco Giovanni , Zaccarini Federica , Cavallo Alessandro , Tzamos Evangelos , Storni Niccolò 
Published: April 2022

AbstractThe Gomati and Nea Roda ophiolites are located into the Serbo-Macedonian massif of the Chalkidiki peninsula (Northern Greece). The present work focuses on the variability of platinum-group elements (PGEs), geochemistry, spinel mineral chemistry, and platinum-group minerals (PGMs) — base metal minerals (BMMs) assemblage in chromitites of three Gomati localities (St. George, Tripes, and Limonadika) and Nea Roda. The studied chromitites show variable textures and are heavily altered. Primary silicates are almost completely replaced by chlorite, and chromite rims are altered into ferrian chromite. The variability of spinel mineral chemistry in terms of Cr# [Cr/(Cr + Al)] and Mg# [Mg/(Mg + Fe2+)], and the PGE contents, argues for a genesis in a supra-subduction setting (SSZ), at different stratigraphic positions in the ophiolite section. Chromitites from Tripes have the lowest Cr# (0.5–0.6) and the highest PGE contents (3516 ppb), similar to some chromitites formed in small magma chambers in the cumulate sections above the Moho. The high PGE contents of Tripes chromitites are due to an IPGEs-enriched melt derived from critical melting of mantle peridotites. Limonadika and St. George show the highest Cr# (0.77–0.96 and 0.74–0.87, respectively) and variable PGE contents (175 ppb and 383 ppb on average respectively), compatible with a genesis from boninitic magmas in the mantle section. Nea Roda chromitites have intermediate to high Cr# (0.66–0.75) and low PGE contents (135 ppb on average) and show similarities to other intermediate chromitites formed from evolving magma sources at subduction initiation. BMMs detected in both ophiolites are primary (pentlandite) and secondary (mainly millerite and heazlewoodite) sulfides. All the detected PGMs are primary, crystallized from the melt, and entrapped into chromite, and they are mainly laurites. In the studied chromitites, the absence of alloys indicates that the circulating fluids during chloritization were at high fS2and fO2, and did not remobilize the PGEs. The same fluids are probably responsible for the low-T crystallization of an uncommon suite of arsenides and antimonides at St. George.
An Erwinia amylovora inducible promoter for improvement of apple fire blight resistance
Authors: Gaucher Matthieu , Righetti Laura , Aubourg Sébastien , Dugé de Bernonville Thomas , Brisset Marie-Noëlle , Chevreau Elisabeth , Vergne Emilie 
Published: April 2022

Abstract

Key message

pPPO16, the first Ea-inducible promoter cloned from apple, can be a useful component of intragenic strategies to create fire blight resistant apple genotypes.

Abstract
Intragenesis is an important alternative to transgenesis to produce modified plants containing native DNA only. A key point to develop such a strategy is the availability of regulatory sequences controlling the expression of the gene of interest. With the aim of finding apple gene promoters either inducible by the fire blight pathogen Erwinia amylovora (Ea) or moderately constitutive, we focused on polyphenoloxidase genes (PPO). These genes encode oxidative enzymes involved in many physiological processes and have been previously shown to be upregulated during the Ea infection process. We found ten PPO and two PPO-like sequences in the apple genome and characterized the promoters of MdPPO16 (pPPO16) and MdKFDV02 PPO-like (pKFDV02) for their potential as Ea-inducible and low-constitutive regulatory sequences, respectively. Expression levels of reporter genes fused to these promoters and transiently or stably expressed in apple were quantified after various treatments. Unlike pKFDV02 which displayed a variable activity, pPPO16 allowed a fast and strong expression of transgenes in apple following Ea infection in a Type 3 Secretion System dependent manner. Altogether our results does not confirmed pKFDV02 as a constitutive and weak promoter whereas pPPO16, the first Ea-inducible promoter cloned from apple, can be a useful component of intragenic strategies to create fire blight resistant apple genotypes.
Unterstützung der Handlungssicherheit von Pflegefachpersonen im Umgang mit Notfallsituationen in Pflegeheimen
Authors: Rubeis Giovanni , Hasseler Martina , Primc Nadia 
Published: April 2022

ZusammenfassungEine beträchtliche Anzahl an Notfalleinsätzen und Krankenhauszuweisungen bei Pflegeheimbewohner:innen wird als vermeidbar eingestuft und stellt eine unnötige Belastung oder Gefährdung für die Bewohner:innen dar. Ein Grund für diese unnötigen Einsätze liegt häufig in Handlungsunsicherheiten der verantwortlichen Pflegefachpersonen. Im Projekt NOVELLE sollen Handlungsempfehlungen für ausgewählte Notfallsituationen entwickelt werden, die den Pflegefachpersonen eine operationalisierte Entscheidung ermöglichen und so deren Handlungssicherheit stärken. Hierfür wurden Herausforderungen für die Handlungssicherheit von Pflegefachpersonen mittels einer qualitativen Interviewstudie erhoben und ausgewertet. Hier werden die Resultate der Studie vorgestellt.