bluuebunny/crossref_metadata_2025_split huggingface dataset:
Speeding up macro‐Raman mapping by reducing the number of sampling points
Authors: Vandenabeele Peter 
Published: July 2024

AbstractMacro‐Raman mapping is an approach that allows to obtain high‐resolution molecular maps of artefacts, over an area of several square centimetres. The method is based on recording thousands of spectra in a grid. The main drawback of this method is that it is very time consuming. A straightforward approach to reduce the measurement time is achieved by reducing the number of points that are measured. Not all points of the map are equally informative: Pixels that are surrounded by similar points might be less interesting to measure. Therefore, an algorithm is proposed to select where to measure and which points to omit. The missing pixels can be filled in a posteriori, by using a suitable interpolation algorithm. The selection of the omitted pixels can be performed based on information that is available from other analytical techniques. In this case, a selection was made based on the local variances in a colour picture. The approach is evaluated by recording macro‐Raman maps of details of a Neptune watercolour painting on paper. In a first stage, the Raman intensities of the scaled and baseline corrected spectra at specific band positions were colour coded and plotted as Raman maps. The interpolation of the Raman maps yielded satisfying results. The image outline could clearly be identified in the maps, and the differently coloured zones were distinguished. Next to this univariate approach, it was demonstrated that also a multivariate data extraction method (principal component analysis) is compatible with the proposed algorithm to measure 25% less datapoints.
Use of a low transformation temperature effect for the targeted reduction of welding distortion in stainless chromium‐nickel steel for an application in rail vehicle construction
Authors: Gamerdinger M. , Akyel F. , Olschok S. , Kahve C. , Fritsche D. C. , Elliesen U. , Hopmann C. , Reisgen U. 
Published: July 2024

AbstractDue to their low thermal conductivity and high thermal expansion, austenitic chromium‐nickel steels have an increased tendency to distortion during welding. In industrial sectors such as rail vehicle construction, there is a high demand for geometrical precision that is not met by distorted components. Introducing a low transformation temperature (LTT) effect in the weld seam influences the stress distribution, which effects the formation of welding distortion. The low transformation temperature effect is achieved by in situ alloying using commercially available materials. The demonstrators made of stainless steel (X2CrNiN18‐7/1.4318) were welded with a low‐alloy filler metal G4Si1. The low transformation temperature effect is assessed by energy dispersive x‐ray spectroscopy and hardness measurements. The effect on distortion was investigated by measuring the demonstrators with a coordinate measuring system and the results were compared with the reference stainless steel demonstrators with stainless filler metal. The alloying process resulted in a reduction of the alloy content to 14.4 m% chromium and 5 m% nickel and a medium‐high hardness of 361 HV 0.2 to 383 HV 0.2. The low transformation temperature effect achieved leads to a significant reduction in welding distortion of up to 78 % compared to the similar reference demonstrators.
A novel sensor placement strategy based on an enhanced damage assessment method in beam‐like structures: Saddle point criteria
Authors: Tufan T. 
Published: July 2024

AbstractSensor placement is one of the vital concerns in civil structure monitoring. A sensor placement strategy based on a damage assessment method has been introduced for beam‐like structures. An existing damage detection method adapted to multi‐modes and different types of beam‐like structures. Then, it is numerically verified to be suitable for detecting any damage location in a 100 degrees of freedom mass‐spring system. Depending on the noise in the response and the limited measurements, the results demonstrate the validity of using the multi‐mode damage indicator. However, there are limitations to this method due to mode shape saddle points. Sensor deployment schemes have been proposed to address the restriction. In contrast to the corresponding procedure, this method does not rely on the optimization algorithm. Sensor placement strategies involve the simultaneous use of accelerometers and large‐area electronics.
Decisive reversal of lethal coronavirus disease 2019 in senescent hamster by synchronic antiviral and immunoregulatory intervention
Authors: Liu Xuan , Zhou Ming , Fang Mujing , Xie Ying , Chen Peiwen , Chen Rirong , Wu Kun , Ye Jianghui , Liu Che , Zhu Huachen , Cheng Tong , Yuan Lunzhi , Zhao Hui , Guan Yi , Xia Ningshao 
Published: July 2024

AbstractThe poor prognosis observed in elderly individuals infected with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) remains a serious clinical burden and the underlying mechanism is unclear, which necessities detailed investigation of disease characteristics and research for efficient countermeasures. To simulate lethal coronavirus disease 2019 (COVID‐19) in senescent human patients, 80‐week‐old male hamsters are intranasally inoculated with different doses of SARS‐CoV‐2 Omicron BA.5 variant. Exposure to a low dose of the Omicron BA.5 variant results in early activation of the innate immune response, followed by rapid viral clearance and minimal lung damage. However, a high dose of BA.5 results in impaired interferon signaling, cytokine storm, uncontrolled viral replication, and severe lung injury. To decrease viral load and reverse the deterioration of COVID‐19, a new bio‐mimic decoy called CoVR‐MV is used as a preventive or therapeutic agent. Administration of CoVR‐MV as a preventive or therapeutic intervention in the early stages of infection can effectively suppress viral load, regulate the immune response, and rescue animals from death and critical illness. These findings underscore the risk associated with SARS‐CoV‐2 Omicron BA.5 exposure in senescent hamsters and highlight the importance of early intervention to prevent disease progression.
Prenatal diagnosis and genetic study of 22q11.2 microduplication in Chinese fetuses: A series of 31 cases and literature review
Authors: Jiang Xiali , Liang Bin , He Shuqiong , Wu Xiaoqing , Zhao Wantong , Xue Huili , Wang Yan , Lin Na , Huang Hailong , Xu Liangpu 
Published: July 2024

AbstractBackgroundPatients with 22q11.2 microduplication syndrome exhibit a high degree of phenotypic heterogeneity and incomplete penetrance, making prenatal diagnosis challenging due to phenotypic variability. This report aims to raise awareness among prenatal diagnostic practitioners regarding the variant's complexity, providing a basis for prenatal genetic counseling.MethodsFamily and clinical data of 31 fetuses with 22q11.2 microduplications confirmed by chromosomal microarray between June 2017 and June 2023 were considered.ResultsPrimary prenatal ultrasound features of affected fetuses include variable cardiac and cardiovascular anomalies, increased nuchal translucency (≥3 mm), renal abnormalities, and polyhydramnios. More than half of fetuses considered showed no intrauterine manifestations; therefore, prenatal diagnostic indicators were primarily advanced maternal age or high‐risk Down syndrome screening. Most fetuses had microduplications in proximal or central 22q11.2 regions, with only three cases with distal microduplications. Among parents of fetuses considered, 87% (27/31) continued the pregnancy. During follow‐up, 19 cases remained clinically asymptomatic.ConclusionNonspecific 22q11.2 microduplication features in fetuses and its mild postnatal disease presentation highlight the need to cautiously approach prenatal diagnosis and pregnancy decision‐making. Increased clinical efforts should be made regarding providing parents with specialized genetic counseling, long‐term follow‐up, and fetal risk information.
Coagulation profiles and percentiles in neonates with hypoxic‐ischemic encephalopathy undergoing therapeutic hypothermia: A step toward more accurate transfusion thresholds
Authors: De Rose Domenico Umberto , Maddaloni Chiara , Ronci Sara , Bersani Iliana , Martini Ludovica , Caoci Stefano , Savarese Immacolata , Di Pede Alessandra , Campi Francesca , Di Felice Giovina , Berti Pierpaolo , Porzio Ottavia , Luciani Matteo , Dotta Andrea 
Published: July 2024

AbstractBackgroundIn the literature, there are no studies about the transfusion threshold for neonates with hypoxic‐ischemic encephalopathy (HIE) undergoing therapeutic hypothermia (TH). In order to facilitate accurate interpretation of coagulation results in these neonates, we aimed to generate specific reference intervals in this specific population.MethodsThis retrospective study included all HIE neonates admitted from 2014 to 2022 to undergo TH. All infants during TH underwent blood exams, including the coagulation profile. Our primary outcome was to assess the estimates of the 3rd, 10th, 25th, 50th, 75th, 90th, and 97th percentiles for each parameter on admission (before transfusion). By the receiver operating characteristic (ROC) analysis, the area under the ROC curve (AUC) and the best cut‐off point were used to evaluate the ability of the prothrombin time expressed as international normalized ratio (PT‐INR) to predict the risk of any bleeding.ResultsA total of 143 infants were included in this study. On admission, the median fibrinogen value was 205 mg/dL, prothrombin time 18.6 seconds, PT‐INR 1.50, activated partial thromboplastin time 38.3 seconds, thrombin time 18.6 seconds, antithrombin 57.0%. The optimal cut‐off of PT‐INR in predicting the risk of any bleeding was greater than 1.84 (AUC .623, p = .024).ConclusionFor the first time, we proposed the percentiles of coagulation parameters in our cohort of neonates with HIE. Furthermore, we found that a PT‐INR greater than 1.84 can significantly predict the risk of any bleeding. Further studies are needed to determine if a restrictive versus a liberal transfusion approach can be equally safer for these high‐risk infants.
Current surgical practice for central venous access to deliver chemotherapy and enteral access for nutritional support in pediatric patients with an oncological diagnosis
Authors: van den Bosch Ceder H. , Grant Christa N. , Brown Erin G. , Morrison Zachary D. , Luques Lisandro M. , Christison‐Lagay Emily R. , Baertschiger Reto M. 
Published: July 2024

AbstractCentral venous access through tunneled central venous catheters (CVCs) are one of the cornerstones of modern oncologic practice in pediatric patients since CVCs provide a reliable access route for the administration of chemotherapy. Establishing best practices for CVC management in children with cancer is essential to optimize care. This article reviews current best practices, including types of devices, their placement, complications, and long‐term outcomes. Additionally, nutrition status and nutritional support are also very important determinants of outcomes and care in pediatric surgical oncology patients. We review current nutritional assessment, support, access for enteral and parenteral nutrition delivery, and their complications, mainly from a surgical perspective. Overall, access surgery, whether for CVCs, or for enteral access can be challenging, and best practice guidelines supported by current though limited evidence are necessary to minimize complications and optimize outcomes.
Phytoconstituents with cardioprotective properties: A pharmacological overview on their efficacy against myocardial infarction
Authors: Ullah Aman , Mostafa Nada M. , Halim Sobia Ahsan , Elhawary Esraa A. , Ali Ain , Bhatti Rohail , Shareef Usman , Al Naeem Waiel , Khalid Asaad , Kashtoh Hamdy , Khan Ajmal , Al‐Harrasi Ahmed 
Published: July 2024

AbstractMyocardial infarction (MI) is considered one of the most common cardiac diseases and major cause of death worldwide. The prevalence of MI and MI‐associated mortality have been increasing in recent years due to poor lifestyle habits viz. residency, obesity, stress, and pollution. Synthetic drugs for the treatment of MI provide good chance of survival; however, the demand to search more safe, effective, and natural drugs is increasing. Plants provide fruitful sources for powerful antioxidant and anti‐inflammatory agents for prevention and/or treatment of MI. However, many plant extracts lack exact information about their possible dosage, toxicity and drug interactions which may hinder their usefulness as potential treatment options. Phytoconstituents play cardioprotective role by either acting as a prophylactic or adjuvant therapy to the concurrently used synthetic drugs to decrease the dosage or relief the side effects of such drugs. This review highlights the role of different herbal formulations, examples of plant extracts and types of several isolated phytoconstituents (phenolic acids, flavonoids, stilbenes, alkaloids, phenyl propanoids) in the prevention of MI with reported activities. Moreover, their possible mechanisms of action are also discussed to guide future research for the development of safer substitutes to manage MI.
Event‐triggered resilient joint mobile robot localization and sensor fault estimation
Authors: Lu Yanyang , Karimi Hamid Reza , Li Bin , Chen Chih‐Chiang 
Published: July 2024

SummaryThe event‐triggered joint sensor fault estimation and mobile robot (MR) localization (MRL) problem (MRLP) subject to the potential fluctuations of the estimator gain are investigated. From the external sensor to the estimator, to decrease the consumption of sensor energy and cut down network bandwidth resources, an event‐triggered scheme is considered. For the sake of characterizing the phenomenon induced by the inaccurate calculation of estimator gain, an uncertainty with the bounded second moment is employed. The purpose of this study is theoretically to find a feasible and effective approach to the addressed joint estimation problem such that the estimation error (EE) covariance (EEC) meets the given performance index. First, a minimum upper bound (UB) of the EEC is derived. Subsequently, in terms of the proposed joint estimation approach and the corresponding results obtained, an algorithm to address the resilient joint sensor fault estimation and MRLP is summarized. At the end, the effectiveness of the proposed algorithm is validated through conducting a set of comparisive experiments.
A vision transformer‐based robotic perception for early tea chrysanthemum flower counting in field environments
Authors: Qi Chao , Chen Kunjie , Gao Junfeng 
Published: July 2024

AbstractThe current mainstream approaches for plant organ counting are based on convolutional neural networks (CNNs), which have a solid local feature extraction capability. However, CNNs inherently have difficulties for robust global feature extraction due to limited receptive fields. Visual transformer (ViT) provides a new opportunity to complement CNNs' capability, and it can easily model global context. In this context, we propose a deep learning network based on a convolution‐free ViT backbone (tea chrysanthemum‐visual transformer [TC‐ViT]) to achieve the accurate and real‐time counting of TCs at their early flowering stage under unstructured environments. First, all cropped fixed‐size original image patches are linearly projected into a one‐dimensional vector sequence and fed into a progressive multiscale ViT backbone to capture multiple scaled feature sequences. Subsequently, the obtained feature sequences are reshaped into two‐dimensional image features and using a multiscale perceptual field module as a regression head to detect the overall scale and density variance. The resulting model was tested on 400 field images in the collected TC test data set, showing that the proposed TC‐ViT achieved the mean absolute error and mean square error of 12.32 and 15.06, with the inference speed of 27.36 FPS (512 × 512 image size) under the NVIDIA Tesla V100 GPU environment. It is also shown that light variation had the greatest effect on TC counting, whereas blurring had the least effect. This proposed method enables accurate counting for high‐density and occlusion objects in field environments and this perception system could be deployed in a robotic platform for selective harvesting and flower phenotyping.
IoT malware detection using static and dynamic analysis techniques: A systematic literature review
Authors: Kumar Sumit , Ahlawat Prachi , Sahni Jyoti 
Published: July 2024

AbstractThe Internet of Things (IoT) is reshaping the world with its potential to support new and evolving applications in areas, such as healthcare, automation, remote monitoring, and so on. This rapid popularity and growth of IoT‐based applications coincides with a significant surge in threats and malware attacks on IoT devices. Furthermore, the widespread usage of Linux‐based systems in IoT devices makes malware detection a challenging task. Researchers and practitioners have proposed a variety of techniques to address these threats in the IoT ecosystem. Both researchers and practitioners have proposed a range of techniques to counter these threats within the IoT ecosystem. However, despite the multitude of proposed techniques, there remains a notable absence of a comprehensive and systematic review assessing the efficacy of static and dynamic analysis methods in detecting IoT malware. This research work is a systematic literature review (SLR) that aims to offer a concise summary of the latest advancements in the field of IoT malware detection, specifically focusing on the utilization of static and dynamic analytic techniques. The SLR focuses on examining the present status of research, methodology, and trends in the area of IoT malware detection. It accomplishes this by synthesizing the findings from a wide range of scholarly works that have been published in well‐regarded academic journals and conferences. Additionally, the SLR highlights the significance of the empirical process that includes the role of selecting datasets, accurate feature selection and the utilization of machine learning algorithms in enhancing the detection accuracy. The study also evaluates the capability of different analysis techniques to detect malware and compares the performance of various models for IoT malware detection. Furthermore, the review concluded by addressing several open issues and challenges that the research community as a whole must address.
Advanced carbon nitride‐based single‐atom photocatalysts
Authors: Zhang Zifan , Xiang Kun , Wang Haitao , Li Xin , Zou Jing , Liang Guijie , Jiang Jizhou 
Published: July 2024

AbstractSingle‐atom catalysts (SACs) have rapidly become a hot topic in photocatalytic research due to their unique physical and chemical properties, high activity, and high selectivity. Among many semiconductor carriers, the special structure of carbon nitride (C3N4) perfectly meets the substrate requirements for stabilizing SACs; they can also compensate for the photocatalytic defects of C3N4 materials by modifying energy bands and electronic structures. Therefore, developing advanced C3N4‐based SACs is of great significance. In this review, we focus on elucidating efficient preparation strategies and the burgeoning photocatalytic applications of C3N4‐based SACs. We also outline prospective strategies for enhancing the performance of SACs and C3N4‐based SACs in the future. A comprehensive array of methodologies is presented for identifying and characterizing C3N4‐based SACs. This includes an exploration of potential atomic catalytic mechanisms through the simulation and regulation of atomic catalytic behaviors and the synergistic effects of single or multiple sites. Subsequently, a forward‐looking perspective is adopted to contemplate the future prospects and challenges associated with C3N4‐based SACs. This encompasses considerations, such as atomic loading, regulatory design, and the integration of machine learning techniques. It is anticipated that this review will stimulate novel insights into the synthesis of high‐load and durable SACs, thereby providing theoretical groundwork for scalable and controllable applications in the field.
Making minimally invasive procedures more sustainable: A systematic review comparing the environmental footprint of single‐use versus multi‐use instruments
Authors: Martins Russell Seth , Salar Hashim , Salar Musa , Luo Jeffrey , Poulikidis Kostantinos , Razi Syed Shahzad , Latif M. Jawad , Tafuri Kyle , Bhora Faiz Y. 
Published: July 2024

AbstractBackgroundHealthcare systems contribute 5%–10% of the global carbon footprint. Given the detrimental impact of climate change on population health, health systems must seek to address this environmental responsibility. This is especially relevant in the modern era of minimally invasive procedures (MIP) where single‐use instruments are increasingly popular. We compared the environmental footprint of single‐use versus multi‐use instruments in MIP.MethodsWe conducted a systematic review across five databases to identify relevant original studies, following the PRISMA guidelines. We extracted environmental impact data and performed a quality assessment of included studies.ResultsWe included 13 studies published between 2005 and 2024. Eight employed Life Cycle Analysis (LCAs), which is the gold standard methodology for studies evaluating environmental impact. The instruments studied included laparoscopy systems, endoscopes, cystoscopes, bronchoscopes, duodenoscopes, and ureteroscopes. Six studies, including three high quality LCAs and one fair quality LCA, showed that single‐use instruments have a significantly higher environmental footprint than their multi‐use counterparts. Six studies suggested a lower environmental footprint for single‐use instruments, and one study presented comparable results. However, these studies were of poor/fair quality.ConclusionAlthough our systematic review yielded mixed results, all high quality LCAs suggested multi‐use instruments may be more environmentally friendly than their single‐use counterparts. Our findings are limited by inter‐study heterogeneity and methodological quality. There is an urgent need for additional research employing gold standard methodologies to explore the interplay between environmental impact and operational factors such as workflow efficiency and cost‐benefit ratio to allow health systems to make more informed decisions.
The Irradiated
Authors: Höglund Johan 
Published: July 2024

AbstractThis chapter discusses American fiction produced during the period after WW2 to the present and reveals how it registers and rationalizes the enormous, but also notably inexpensive, violence and death that nuclear weapons made possible. The release of this violence during and after the war produced stories set in futures where the climate of the planet has clearly broken down as an effect of militarized capitalism and where the capitalist world-system is crumbling. In some of these stories, a planet damaged by nuclear violence and lingering radiation takes the form of a gigantic, monstrous, and uncontrollable security threat that demands the attention of the military. By telling such stories, the chapter argues, these narratives must be considered as the proper beginning of the American Climate Emergency Narrative.