bluuebunny/crossref_metadata_2025_split huggingface dataset:
Self-organized multi-target trapping of swarm robots with density-based interaction
Authors: Lei Xiaokang , Zhang Shuai , Xiang Yalun , Duan Mengyuan 
Published: April 2023

AbstractThe task of multi-target trapping in swarm robots can often be solved by global shape planning and target assignment, but it still remains a challenge to achieve fully self-organized multi-target trapping behavior based on local information. In this paper, inspired by the concept of spatial density in physics and biology, we proposed a novel density-based method to enable the swarm robots to entrap multiple targets with either single-ring, multi-ring or multi-subgroup formation in a distributed and self-organized way while neither communication among robots nor encirclement function is required. Each robot’s local spatial density is considered as the main clue for the individual’s motion decision-making and the enclosed configurations emerge from such individual-level interactions rather than being explicitly designed. Numerical simulations and real robotic experiments are conducted to validate the effectiveness of the proposed method. The results show that the proposed self-organized trapping method allows a swarm of robots to entrap multiple moving targets in a stable, flexible, noise-tolerate and size-scalable fashion.
Hellenic Headache Society Recommendations for the Use of Monoclonal Antibodies Targeting the Calcitonin Gene-Related Peptide Pathway for the Prevention of Migraine and Cluster Headache—2023 Update
Authors: Mitsikostas D. D. , Alexoudi A. , Arvaniti C. , Giannouli E. , Kouremenos Ε. , Constantinidis T. S. , Fakas Ν. , Deligianni C. , Karapanayiotides T. , Dardiotis Ε. , Gatzonis S. , Konitsiotis S. , Tsivgoulis G. ,   Hellenic Headache Society
Published: April 2023

AbstractThe confirmed involvement of the neuropeptide calcitonin gene-related peptide (CGRP) in the pathophysiology of migraine has led to the development of treatments, which for the first time are specific to migraine and mechanism based, in contrast to repurposed traditional prophylactic anti-migraine medications. Thus, in the last 5 years, the European Medicines Agency (EMA) approved four monoclonal antibodies that target either the CGRP ligand (eptinezumab, fremanezumab, and galcanezumab) or the CGRP receptor (erenumab). These anti-CGRP therapies are indicated for use in people with migraine who have more than 4 migraine days per month. In this consensus article, the Hellenic Headache Society highlights the indications and treatment protocols of these novel anti-migraine therapies, aiming to assist Greek neurologists in the optimal management of people with migraine. The recommendations are based on data from phase 3 randomized-controlled clinical trials, the recent European Headache Federation (EHF) recommendations, a consensus article under the auspices of both the EHF and the European Academy of Neurology (EAN), recent real-world evidence studies, and the authors’ acquired clinical experience.
Aerodynamic performance improvement of a blended wing-body re-entry vehicle using ANSYS CFX
Authors: Hossan Shakil , Srinivas G. 
Published: April 2023

AbstractThe main objective of this paper is to evaluate the aerodynamic performance of a modified blended wing-bodied re-entry vehicle by computational fluid dynamics. This analysis examines the airflow properties like pressure, density, and temperature under hypersonic flow. The study of a blended wing model at different Mach speeds and angles of attack is also included in the research paper. All the simulations in this paper are performed using the computational fluid dynamics tool of ANSYS CFX. Shear stress transport (SST) turbulence computational fluid dynamics model has been used for numerical analysis. Various inlet conditions are applied to get the aerodynamic parameters. The results revealed that the best Re-entry condition is from 10 to 20 degrees angle of attack at Mach 22, and the vehicle is very stable at a high angle of attack and Mach number. The obtained results have been validated with the public domain literature. The blended wing body has been thoroughly examined in various important locations, particularly the spacecraft nose and flap sections.
Basic Geo-Spatial Data Literacy Education for Economic Applications
Authors: Juergens Carsten , Redecker Andreas P. 
Published: April 2023

AbstractGeospatial data literacy is of paramount importance in an increasingly digital business world. Especially in economic decision-making processes, the ability to judge the trustworthiness of pertinent data sets is inevitable for reliable decisions. Thus, geospatial competencies need to supplement the university’s teaching syllabus of economic degree programmes. Even if these programmes already have a lot of content, it is worth adding geospatial topics to educate students as skilled young experts, being geospatially literate. This contribution shows an approach on how to sensitise students and teachers with an economics background to understand the origin of geospatial data sets, their specific nature, their quality and how to gain geospatial data sets with a particular focus on sustainable economics applications. It proposes a teaching approach for educating students on geospatial characteristics of data, making them aware of spatial reasoning and spatial thinking. Especially it is vital to give them an impression of the manipulating nature of maps and geospatial visualisations. The aim is to show them the power of geospatial data and map products for research in their specific thematic field. The presented teaching concept originates from an interdisciplinary data literacy course geared to students other than geospatial sciences. It incorporates elements of a flipped classroom and a self-learning tutorial. This paper shows and discusses the results of the implementation of the course. Positive exam results imply that the teaching concept provides a suitable way to impart geospatial competencies to students belonging other than geo-related subjects.
A comparative study on the implementation of deep learning algorithms for detection of hepatic necrosis in toxicity studies
Authors: Hwang Ji-Hee , Lim Minyoung , Han Gyeongjin , Park Heejin , Kim Yong-Bum , Park Jinseok , Jun Sang-Yeop , Lee Jaeku , Cho Jae-Woo 
Published: April 2023

AbstractDeep learning has recently become one of the most popular methods of image analysis. In non-clinical studies, several tissue slides are generated to investigate the toxicity of a test compound. These are converted into digital image data using a slide scanner, which is then studied by researchers to investigate abnormalities, and the deep learning method has been started to adopt in this study. However, comparative studies evaluating different deep learning algorithms for analyzing abnormal lesions are scarce. In this study, we applied three algorithms, SSD, Mask R-CNN, and DeepLabV3+, to detect hepatic necrosis in slide images and determine the best deep learning algorithm for analyzing abnormal lesions. We trained each algorithm on 5750 images and 5835 annotations of hepatic necrosis including validation and test, augmented with 500 image tiles of 448 × 448 pixels. Precision, recall, and accuracy were calculated for each algorithm based on the prediction results of 60 test images of 2688 × 2688 pixels. The two segmentation algorithms, DeepLabV3+ and Mask R-CNN, showed over 90% of accuracy (0.94 and 0.92, respectively), whereas SSD, an object detection algorithm, showed lower accuracy. The trained DeepLabV3+ outperformed all others in recall while also successfully separating hepatic necrosis from other features in the test images. It is important to localize and separate the abnormal lesion of interest from other features to investigate it on a slide level. Therefore, we suggest that segmentation algorithms are more appropriate than object detection algorithms for use in the pathological analysis of images in non-clinical studies.
Deep learning based on connected vehicles for icing pavement detection
Authors: Hu Jiajie , Huang Ming-Chun , Yu Xiong Bill 
Published: April 2023

AbstractSlippery road conditions, such as snowy, icy or slushy pavements, are one of the major threats to road safety in winter. The U.S. Department of Transportation (USDOT) spends over 20% of its maintenance budget on pavement maintenance in winter. However, despite extensive research, it remains a challenging task to monitor pavement conditions and detect slippery roadways in real time. Most existing studies have mainly explored indirect estimates based on pavement images and weather forecasts. The emerging connected vehicle (CV) technology offers the opportunity to map slippery road conditions in real time. This study proposes a CV-based slippery detection system that uses vehicles to acquire data and implements deep learning algorithms to predict pavements' slippery conditions. The system classifies pavement conditions into three major categories: dry, snowy and icy. Different pavement conditions reflect different levels of slipperiness: dry surface corresponds to the least slippery condition, and icy surface to the most slippery condition. In practice, more attention should be paid to the detected icy and snowy pavements when driving or implementing pavement maintenance and road operation in winter. The classification algorithm adopted in this study is Long Short-Term Memory (LSTM), which is an artificial Recurrent Neural Network (RNN). The LSTM model is trained with simulated CV data in VISSIM and optimized with a Bayesian algorithm. The system can achieve 100%, 99.06% and 98.02% prediction accuracy for dry pavement, snowy pavement and icy pavement, respectively. In addition, it is observed that potential accidents can be reduced by more than 90% if CVs can adjust their driving speed and maintain a greater distance from the leading vehicle after receiving a warning signal. Simulation results indicate that the proposed slippery detection system and the information sharing function based on the CV technology and deep learning algorithm (i.e., the LSTM network implemented in this study) are expected to deliver real-time detection of slippery pavement conditions, thus significantly eliminating the potential risk of accidents.
Plasticity of wheat seedling responses to K+ deficiency highlighted by integrated phenotyping of roots and root hairs over the whole root system
Authors: Madani Ikram , Peltier Jean-Benoît , Boeglin Martin , Sentenac Hervé , Véry Anne-Aliénor 
Published: April 2023

AbstractThe availability in the soil of potassium (K+), a poorly mobile macronutrient required in large quantities for plant growth, is generally suboptimal for crop production in the absence of fertilization, making improvement of the ability of crops to adapt to K+ deficiency stress a major issue. Increasing the uptake capacity of the root system is among the main strategies to achieve this goal. Here, we report an integrative approach to examine the effect of K+ deficiency on the development of young plant entire root system, including root hairs which are known to provide a significant contribution to the uptake of poorly mobile nutrients such as K+, in two genetically distant wheat varieties. A rhizobox-type methodology was developed to obtain highly-resolved images of root and root hairs, allowing to describe global root and root hair traits over the whole root system via image analysis procedures. The two wheat varieties responded differently to the K+ shortage: Escandia, a wheat ancestor, reduced shoot biomass in condition of K+ shortage and substantially increased the surface area of its root system, specifically by increasing the total root hair area. Oued Zenati, a landrace, conversely appeared unresponsive to the K+ shortage but was shown to constitutively express, independently of the external K+ availability, favorable traits to cope with reduced K+ availability, among which a high total root hair area. Thus, valuable information on root system adaptation to K+ deficiency was provided by global analyses including root hairs, which should also be relevant for other nutrient stresses.
Improving the bias of a pseudo-maximum likelihood estimate of the extreme value index by k-records
Authors: Louzaoui Abderrahim , El Arrouchi Mohamed 
Published: April 2023

AbstractThe paper focusses on the estimation of the extreme value index in terms ofk-records based on a maximum likelihood approach, which is suggested recently by Louzaoui and El Arrouchi (J Probab Stat, 2020). Its asymptotic normality is well investigated in order to propose a bias correction while ensuring that the new estimator becomes asymptotically unbiased and still normal. Some numerical studies are also provided in order to show how the proposed estimators behave in practice.
Size and composition of colloidal phosphorus across agricultural soils amended with biochar, manure and biogas slurry
Authors: Eltohamy Kamel Mohamed , Milham Paul J. , Gouda Mostafa , Menezes-Blackburn Daniel , Khan Sangar , Liu Boyi , Jin Junwei , Ye Ye , Liang Xinqiang 
Published: April 2023

AbstractThe long-term application of organic amendments like manure, biochar and biogas slurry can increase phosphorus (P) levels in agricultural soils; however, at present, it's not clear how this affects the P association with different mobile water-dispersible colloidal particles (Pcoll). Thus, this study aimed to assess the effects of the long-term application of different organic amendments on the abundance, size and compositional characteristics of Pcoll. For this purpose, a total of 12 soils amended with the above three organic amendments were sampled from the Zhejiang Province, China, and Pcoll were fractionated into nano-sized (NC; 1–20 nm), fine-sized (FC; 20–220 nm), and medium-sized (MC; 220–450 nm) by a combination of differential centrifugation and ultrafiltration steps. These three Pcoll forms together accounted for 74 ± 14% of the total soil solution dissolved P content, indicating that Pcoll release was a key process in the overland P transport from these soils. Soils treated with biochar showed lower Pcoll contents than those treated with manure or slurry alone; this effect should be further explored in a controlled inductive research approach. Compositional analysis showed that inorganic P was the predominant Pcoll form in the NC (54 ± 20%) and FC (63 ± 28%) fractions, but not in the MC (42 ± 26%) fraction. Among the three fractions, the organic carbon (OC)–calcium (Ca) complex was the major carrier of NC-bound Pcoll, MC-bound Pcoll was better correlated with OC–manganese/iron/aluminium colloids than with OC–Ca colloids, and both of these phenomena co-occurred in the FC fraction. The current study provides novel insights into the impact of various carbon amendments on the propensity for P loss associated with different soil mobile colloidal fractions, and will therefore, inform future agronomic and environmental-related policies and studies.
Abdominal cocoon syndrome; a rare etiology of intestinal obstruction; a case report
Authors: Saleem Athary , Alenezi Ali , Alenezi Saqer , Hassan Maher , Alshammari Khaled , Alkandari Mohammed 
Published: April 2023

Abstract

Introduction
and importance: The abdominal cocoon is a rare entity of intestinal obstruction. The exact etiopathogenesis of this condition is unknown. Most patients presented with signs and symptoms of intestinal obstruction. Radiological investigations such as abdominal ultrasonography and computed tomography are crucial to evaluate and diagnose abdominal cocoon syndrome, while most cases are usually identified intraoperatively.

Case presentation
A 32-year-old male patient presented to our hospital with three days of left iliac fossa pain that was associated with multiple vomiting episodes and bowel habits alterations. Physical examination showed a distended abdomen with generalized tenderness. Laboratory investigations showed abnormal values. A plain abdominal X-ray revealed multiple air-fluid levels. Then abdominal CT was performed, and the clinical picture was consistent with small bowel obstruction. So, diagnostic laparoscopy was decided after the conservative management plan failed, during which a cocoon sac was detected intraoperatively. The resected specimen was sent for histopathological studies. The postoperative period was uneventful.

Clinical discussion
Abdominal cocoon syndrome is an unusual cause of abdominal obstruction that can be categorized surgically into four types. It is considered a life-threatening surgical emergency. The clinical features of abdominal cocoon syndrome include those of intestinal obstruction. Radiological tools aid in the diagnosis demonstration but the definitive diagnosis is achieved by laparotomy and histopathology.

Conclusion
Due to the rare etiologic origin of abdominal cocoon syndrome, we report the case of a 32-year-old male patient with left iliac fossa pain, found to be caused by detected abdominal cocoon syndrome.

Highlights
Global Distribution and Morphology of Small Seamounts
Authors: Gevorgian Julie , Sandwell David T. , Yu Yao , Kim Seung‐Sep , Wessel Paul 
Published: April 2023

AbstractSeamounts are isolated elevations in the seafloor with circular or elliptical plans, comparatively steep slopes, and relatively small summit area (Menard, 1964). The vertical gravity gradient (VGG), which is the curvature of the ocean surface topography derived from satellite altimeter measurements, has been used to map the global distribution of seamounts (Kim & Wessel, 2011, https://doi.org/10.1111/j.1365-246x.2011.05076.x). We used the latest grid of VGG to update and refine the global seamount catalog; we identified 19,325 new seamounts, expanding a previously published catalog having 24,643 seamounts. Seven hundred thirty‐nine well‐surveyed seamounts, having heights ranging from 421 to 2,500 m, were used to estimate the typical radially symmetric seamount morphology. First, an Empirical Orthogonal Function (EOF) analysis was used to demonstrate that these small seamounts have a basal radius that is linearly related to their height—their shapes are scale invariant. Two methods were then used to compute this characteristic base to height ratio: an average Gaussian fit to the stack of all profiles and an individual Gaussian fit for each seamount in the sample. The first method combined the radial normalized height data from all 739 seamounts to form median and median‐absolute deviation. These data were fit by a 2‐parameter Gaussian model that explained 99.82% of the variance. The second method used the Gaussian function to individually model each seamount in the sample and further establish the Gaussian model. Using this characteristic Gaussian shape we show that VGG can be used to estimate the height of small seamounts to an accuracy of ∼270 m.
Unraveling the Magnetic Signal of Individual Grains in a Hawaiian Lava Using Micromagnetic Tomography
Authors: Kosters Martha E. , de Boer Rosa A. , Out Frenk , Cortés‐Ortuño David I. , de Groot Lennart V. 
Published: April 2023

AbstractMicromagnetic Tomography (MMT) is a new technique that allows the determination of magnetic moments of individual grains in volcanic rocks. Current MMT studies either showed that it is possible to obtain magnetic moments of relatively small numbers of grains in ideal sample material or provided important theoretical advances in MMT inversion theory and/or its statistical framework. Here, we present a large‐scale application of MMT on a sample from the 1907‐flow from Hawaii's Kilauea volcano producing magnetic moments of 1,646 grains. We produced 261,305 magnetic moments in total for these 1,646 grains, an increase of three orders of magnitude compared to earlier studies to assess the robustness of the MMT results, and a major step toward the number of grains that is necessary for paleomagnetic applications of MMT. Furthermore, we show that the recently proposed signal strength ratio is a powerful tool to scrutinize and select MMT results. Despite this progress, still only relatively large iron‐oxide grains with diameters >1.5–2 μm can be reliably resolved, impeding a reliable paleomagnetic interpretation. To determine the magnetic moments of smaller (<1 μm) grains that may exhibit pseudo‐single domain behavior and are therefore better paleomagnetic recorders, the resolution of the microcomputed tomography and magnetic scans necessary for MMT must be improved. Therefore, it is necessary to reduce the sample size in future MMT studies. Nevertheless, our study is an important step toward making MMT a useful paleomagnetic and rock‐magnetic technique.
The Global Seismic Moment Rate of Mars After Event S1222a
Authors: Knapmeyer M. , Stähler S. , Plesa A.‐C. , Ceylan S. , Charalambous C. , Clinton J. , Dahmen N. , Durán C. , Horleston A. , Kawamura T. , Kim D. , Li J. , Plasman M. , Zenhäusern G. , Weber R. C. , Giardini D. , Panning M. P. , Lognonné P. , Banerdt W. B. 
Published: April 2023

AbstractThe seismic activity of a planet can be described by the corner magnitude, events larger than which are extremely unlikely, and the seismic moment rate, the long‐term average of annual seismic moment release. Marsquake S1222a proves large enough to be representative of the global activity of Mars and places observational constraints on the moment rate. The magnitude‐frequency distribution of relevant Marsquakes indicates a ‐value of 1.06. The moment rate is likely between and , with a marginal distribution peaking at . Comparing this with pre‐InSight estimations shows that these tended to overestimate the moment rate, and that 30% or more of the tectonic deformation may occur silently, whereas the seismicity is probably restricted to localized centers rather than spread over the entire planet.
Direct Observations of Electron Firehose Fluctuations in the Magnetic Reconnection Outflow
Authors: Cozzani G. , Khotyaintsev Yu. V. , Graham D. B. , André M. 
Published: April 2023

AbstractElectron temperature anisotropy‐driven instabilities such as the electron firehose instability (EFI) are especially significant in space collisionless plasmas, where collisions are so scarce that wave–particle interactions are the leading mechanisms in the isotropization of the distribution function and energy transfer. Observational statistical studies provided convincing evidence in favor of the EFI constraining the electron distribution function and limiting the electron temperature anisotropy. Magnetic reconnection is characterized by regions of enhanced temperature anisotropy that could drive instabilities—including the electron firehose instability—affecting the particle dynamics and the energy conversion. However, in situ observations of the fluctuations generated by the EFI are still lacking and the interplay between magnetic reconnection and EFI is still largely unknown. In this study, we use high‐resolution in situ measurements by the Magnetospheric Multiscale spacecraft to identify and investigate EFI fluctuations in the magnetic reconnection exhaust in the Earth's magnetotail. We find that the wave properties of the observed fluctuations largely agree with theoretical predictions of the non‐propagating EF mode. These findings are further supported by comparison with the linear kinetic dispersion relation. Our results demonstrate that the magnetic reconnection outflow can be the seedbed of EFI and provide the first direct in situ observations of EFI‐generated fluctuations.