bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep learning informed diffusion equation model for image denoising
Authors: Li Yao , Cheng Li , Guo Zhichang , Xing Yuming 
Published: October 2024

AbstractImage denoising is one of the fundamental problems in image processing. Convolutional neural network (CNN) based denoising approaches have achieved better performance than traditional methods, such as STROLLR and BM3D. However, CNNs can easily bring unexplainable artifacts to denoised images. In this article, a Deep Learning‐Informed Diffusion Equation (DLI‐DE) framework utilizing the image prior or the image gradient prior for image denoising is proposed. The image priors and gradient priors are learned from CNN models and used as coefficients in diffusion equations. The solution of DLI‐DE is infinitely smooth from the uniqueness of existence theorem, which guarantees that the denoised image is free of artifacts. Good properties of DLI‐DE also ensure high‐quality of denoising. The experimental analysis confirms that the denoising performance of DLI‐DE is comparable to that of contemporary CNN‐based denoising methods such as TNRD and DnCNN, while effectively preventing artifacts.
Contraband detection algorithm for X‐ray security inspection images based on global semantic enhancement
Authors: Pei Xiaofang , Ma Changsong , Zhou Jin , Yang Jihai , Xu Yongheng 
Published: October 2024

AbstractAiming at the problem of low detection accuracy caused by overlapping occlusion and noise disturbance, a contraband detection algorithm for X‐ray security inspection images based on global semantic enhancement is proposed to achieve accurate contraband target detection by enhancing global semantic information. First, the disturbance suppression module is used to weaken the noise disturbance at different positions by local suppression and aggregate finer detail information. Then, the parallel cascade search module is used to capture long‐range dependencies and strengthen the representation of global semantic information, which helps the model identify contraband under overlapping occlusion. Finally, the contribution of different features is adaptively adjusted through the feature‐weighted fusion module, which promotes the effective fusion of multi‐scale features and improves the accuracy of model detection. The method in this article has been extensively evaluated and experimented on three mainstream benchmark datasets: SIXray, OPIXray, and PIDray. The mAPs of three datasets reach 93.5%, 91.9%, and 85.9%, respectively. The experimental results fully demonstrate that the method in this article has better performance compared with the latest method, which can meet the practical application requirements of real‐time target detection.
An unsupervised approach for the detection of zero‐day distributed denial of service attacks in Internet of Things networks
Authors: Roopak Monika , Parkinson Simon , Tian Gui Yun , Ran Yachao , Khan Saad , Chandrasekaran Balasubramaniyan 
Published: October 2024

AbstractThe authors introduce an unsupervised Intrusion Detection System designed to detect zero‐day distributed denial of service (DDoS) attacks in Internet of Things (IoT) networks. This system can identify anomalies without needing prior knowledge or training on attack information. Zero‐day attacks exploit previously unknown vulnerabilities, making them hard to detect with traditional deep learning and machine learning systems that require pre‐labelled data. Labelling data is also a time‐consuming task for security experts. Therefore, unsupervised methods are necessary to detect these new threats. The authors focus on DDoS attacks, which have recently caused significant financial and service disruptions for many organisations. As IoT networks grow, these attacks become more sophisticated and harmful. The proposed approach detects zero‐day DDoS attacks by using random projection to reduce data dimensionality and an ensemble model combining K‐means, Gaussian mixture model, and one‐class SVM with a hard voting technique for classification. The method was evaluated using the CIC‐DDoS2019 dataset and achieved an accuracy of 94.55%, outperforming other state‐of‐the‐art unsupervised learning methods.
A novel satisfactory model predictive control based on current variance for high power three‐level‐NPC rectifiers
Authors: Yang Bo , Guo Zhikang , Ye Zongbin , Kong Jiayi , Tan Guojun 
Published: October 2024

AbstractHere, a novel satisfactory model predictive control based on current variance (CV‐SMPC) is proposed for three level neutral point clamped (NPC) rectifiers. CV‐SMPC achieves global optimization of multiple control objectives rather than optimal control of a single control objective with the satisfaction interval. The current satisfaction interval is adjusted online based on the current variance in the CV‐SMPC. The relationship between the current total harmonic distortion (THD), switching frequency, and current variance is established through experimental investigation, enhancing the comprehensibility of control effects. In addition, three simplified sets of candidate vectors are proposed based on the voltage satisfaction interval, thereby reducing the computational burden. Furthermore, the control objectives are categorized into three levels and sequentially combined, eliminating the laborious process of adjusting the weighting factors. Finally, the experimental results conclusively demonstrate the exceptional control performance of CV‐SMPC in both steady‐state and dynamic processes.
Comprehensive design method of controller parameters for three‐phase LCL‐type grid‐connected inverter based on D‐partition
Authors: Ma Zun , Xiao Wenxun , Wang Danyang , Meng Xian , Zhu Lin 
Published: October 2024

AbstractThe LCL‐type inverter is a core component in grid‐connected renewable energy systems, with its performance heavily influenced by the controller. Conventional design methods of controller parameters generally rely on approximation or trial and error, making it difficult to optimize parameters for multiple performance indices. This paper proposes a comprehensive design method of controller parameters for a three‐phase LCL‐type grid‐connected inverter based on the D‐partition method, obtaining a multi‐objective parameter stability domain of controller parameters that simultaneously satisfies multiple performance indices, such as gain margin, phase margin, and current loop bandwidth. The stability domain can be visually presented, which can avoid repetitive adjustments. Additionally, the variation trend of the stability domain when there are deviations in the LCL filter parameters is analyzed. Finally, the accuracy and effectiveness of the proposed design method are validated through simulations and experiments, achieving precise parameter design for the controller of LCL grid‐connected inverters even in the presence of deviations in filter parameters.
Secure and efficient trust enabled routing in mobile ad hoc network using game theory and grey wolf optimisation techniques
Authors: Ravale Ujwala , Borkar Gautam M. 
Published: October 2024

AbstractMobile Ad hoc Networks (MANETs) are crucial wireless networks for military, corporate, and emergency use, yet they are vulnerable to disruptions from malicious nodes. The presence of malicious nodes can lead to message transmission and routing disorganisation, and network performance is effectively compromised. Game theory‐based fuzzy secure clustering (GTFSC) improves performance metrics in low‐scale and high‐scale networks. This protocol's novel ability to dynamically scale performance measures as nodes expand improves efficiency and adaptability. While improving performance metrics, the proposed algorithm also efficiently identifies malicious nodes and re‐routes the transmission, excluding the found malicious nodes. For any MANET system, secure and successful data transmission is paramount. The proposed protocol integrates various algorithms to fulfil its aim of customised EGT, GWO, and fuzzy clustering. Black hole attacks, grey hole attacks, Sybil attacks, and data tampering attacks are all considered to provide comprehensive attacks on MANET. Every node is assigned trust values, which get updated on data transmission. Fuzzy Clustering is employed to identify malicious nodes. Evolutionary Game Theory (EGT) optimises network organisation by designating cluster heads and clusters as nodes. Additionally, the proposed protocol leverages the Grey Wolf Optimisation Routing Algorithm (GWO), which establishes efficient routes from the source to the sink node. The analysis result shows maximum performance with a packet delivery ratio of around 98%, throughput of 90% end‐to‐end delay reduced by 15%, and energy consumption reduced by 18%, respectively, compared to an existing protocol.
Active vibration isolation by emulating the inerter through relative acceleration feedback
Authors: Arandia-Krešić Srećko , Turalija Stipe , Alujević Neven , Vladimir Nikola 
Published: October 2024

This study focuses on the realisation of a small-scale inerter by relative acceleration feedback and its use to isolate vibration. Two accelerometers attached to the two mechanical terminals of an electrodynamic force actuator are used to obtain the relative acceleration signal. This signal is then amplified by a constant gain and fed back to the two electrical terminals of the electrodynamic actuator as a voltage command. This sensor-actuator system is coupled to a two Degree-Of-Freedom (DOF) mechanical oscillator to study the feedback loop’s stability and the maximum achievable inertance effect. A fully coupled simulation model including the dynamics of the two inertial accelerometers and the electrodynamic actuator is developed. It is shown that, because of the active control system emulating an inerter, an antiresonance appears in the transfer admittance function of the two DOF mechanical system. Therefore, significant vibration isolation effect can be achieved in the narrow frequency band around the antiresonance. The antiresonance frequency is easily tuned by adjusting the feedback gain. The synthetized inertance is a complex frequency dependent function, which is predominantly real-valued in the frequency range between 5 and 1600 Hz. It is shown that it does not depend on the mechanical system properties, but only on the properties of the transducers used and the signal conditioning in the feedback loop. As a result, this frequency range can be adjusted according to a particular application.
Kutane Sarkoidose
Authors: Schauer Franziska , Diehl Rebecca 
Published: October 2024

ZUSAMMENFASSUNGDie Sarkoidose ist eine Multisystemerkrankung, deren Ursache bislang ungeklärt ist. Pathognomonisch sind nicht verkäsende Granulome, die alle Gewebe oder Organsysteme betreffen können. Aufgrund der guten klinischen Sichtbarkeit der kutanen Sarkoidose ist diese oft der erste Hinweis für das Vorliegen einer systemischen Sarkoidose. Die Dermatologie spielt somit eine wichtige Rolle bei der Früherkennung dieser multisystemischen Erkrankung. Eine reine Hautmanifestation ohne systemische Beteiligung ist möglich. Die häufigsten Vertreter hierfür sind die makulopapulöse und die noduläre Sarkoidose. Zum anderen gibt es unspezifische Hautmanifestationen, wie zum Beispiel das Erythema nodosum, welches im Rahmen einer systemischen Sarkoidose auftreten kann. Die Diagnose wird mittels Gewebebiopsie gestellt. Die Biomarker CRP, sIl-2R und Neopterin können bei Hautmanifestation Hinweis für eine systemische Beteiligung sein. Die Therapie richtet sich nach Schwere der Hautmanifestation und systemischer Beteiligung. Zur Behandlung der kutanen Sarkoidose zugelassen sind topische, intraläsionale oder systemische Glukokortikosteroide. Bei therapierefraktären Verläufen können off-label immunmodulierende oder immunsuppressive Medikamente eingesetzt werden.
Zaungast in der Kniekehle
Authors: Zhang Zheng 
Published: October 2024

SummaryBei der Baker-Zyste handelt es sich um eine flüssigkeitsgefüllte Ausstülpung der Gelenkkapsel hinter dem Knie, meist infolge von Überlastung, Verletzung oder Knieerkrankungen wie Arthritis oder Arthrose. In der Traditionellen Chinesischen Medizin (TCM) gelten als ursächliche pathologische Faktoren unter anderem Nässe und Kälte, Blutstagnation im Blasenmeridian sowie Leber- und Nierenschwäche. Zu den wichtigen Akupunkturpunkten – auch im besprochenen Fall – zählen insbesondere die Ashi-Punkte „Drachen umzingeln“, Lokal- und Regionalpunkte auf dem Blasenmeridian und bewährte Fernpunkte, die nach pathologischem Muster und Schmerzausstrahlung ausgewählt werden.
Gute Lösungen
Authors: Stern Cornelia 
Published: October 2024

SummaryFür die Wahl des richtigen Auszugsmediums einer Heilpflanzenzubereitung ist das Löslichkeitsverhalten der wirksamkeitsbestimmenden Inhaltsstoffe entscheidend. Am Beispiel der wichtigsten Pflanzenwirkstoffe wird die Löslichkeit in Wasser (Infus und Dekokt), Ethanol (Tinktur) und Öl (Ölauszug) dargestellt. Im Fokus stehen Gerbstoffe, Bitterstoffe, ätherische Öle, Saponine und Flavonoide und ihre jeweiligen Untergruppen.
Novel Approach to Identify Severe Maternal Morbidity Clusters: A Latent Class Analysis
Authors: Ibarra Andrea J. , Lopa Samia H. , Phan BaDoi N. , Himes Katherine , Butters Meryl A. , Beck Stacy , Catov Janet M. 
Published: October 2024

Objective Whether clusters exist within severe maternal morbidity (SMM), a set of life-threatening heterogeneous conditions, is not known. Our primary objective was to identify SMM clusters using a data-driven clustering technique, their associated predictors and outcomes.
Study Design From 2008 to 2017, we used a delivery database supplemented by state data and medical record abstraction from a single institution in Pennsylvania. To identify SMM clusters, we applied latent class modeling that included 23 conditions defined by 21 Centers for Disease Control SMM indicators, intensive care unit (ICU) admission, or prolonged postpartum length of stay. Logistic regression models estimated risk for SMM clusters and associations between clusters and maternal and neonatal outcomes.
Results Among 97,492 deliveries, 2.7% (N = 2,666) experienced SMM by any of the 23 conditions. Four clusters were identified as archetypes of SMM. Deliveries labeled as Hemorrhage (37.7%, N = 1,004) were characterized by blood transfusions and sickle cell anemia; Critical Care (28.1%, N = 748) by ICU admission and amniotic embolism; Vascular (24.5%, N = 654) by cerebrovascular conditions; and Shock (9.8%, N = 260) by ventilatory support and shock. Hypertensive disorders of pregnancy, depression, and Medicaid insurance were associated with Shock cluster. People in all clusters had a high risk of maternal death within 1 year (odds ratio: 12.0, 95% confidence interval: 6.2–23). Infants born to those in the shock cluster had the highest odds of neonatal death, low Apgar scores, and neonatal ICU admission.
Conclusion We identified four novel SMM clusters that may help understand the collection of conditions defining SMM, underlying pathways and the importance of comorbidities such as depression and social determinants of health markers that amplify the well-established risk factors for SMM such as hypertensive disorders of pregnancy.
Key Points
Clinical Analysis of Inhaled Nitric Oxide Therapy in Preterm Infants at Different Gestational Ages: A National Retrospective Multicenter Study
Authors: Liang Guo-bao , Wang Lian , Huang Sheng-qian , Feng Bao-ying , Yao Mu-lin , Fan Xu-fang , Wang Meng-jiao , Zhu Lu , Zhang Jing , Zheng Zhi , Zhu Yao , Shen Wei , Duan Wen-li , Mao Jian , Wu Fan , Li Zhan-kui , Xu Fa-lin , Ma Li , Wei Qiu-fen , Liu Ling , Lin Xin-zhu 
Published: October 2024

Objective This study aimed to investigate clinical features of inhaled nitric oxide (iNO) in preterm infants with a gestational age (GA) < 34 weeks in China.
Study Design The clinical data of 434 preterm infants with GA < 34 weeks, treated with iNO in the neonatology departments of eight Class A tertiary hospitals in China over a 10-year period from January 2013 to December 2022, were included in this retrospective multicenter investigation. The infants were divided into three groups based on GA: 24 to 27 weeks (extremely preterm infants), 28 to 31 weeks (very preterm infants), and 32 to 33 weeks (moderate preterm infants). The use of iNO, perinatal data, incidence and mortality of indication for iNO treatment, therapeutic effects of iNO, incidence of short-term complications for iNO treatment, and mortality were compared among these three groups.
Results Over the past 10 years, the proportion of iNO use was highest in extremely preterm infants each year. The lower the GA, the higher the iNO use rate: 4.20% for GA 24 to 27 weeks, 1.54% for GA 28 to 31 weeks, and 0.85% for GA 32 to 33 weeks. There was no significant difference in the therapeutic effect of iNO among the three groups. The incidence of neonatal pulmonary hemorrhage, neonatal shock, late-onset diseases, retinopathy of prematurity requiring intervention, intracranial hemorrhage (grade 3 or 4), periventricular leukomalacia, neonatal necrotizing enterocolitis (≥stage II), and moderate to severe bronchopulmonary dysplasia was highest in extremely preterm infants and increased with decreasing GA. Mortality was negatively correlated with GA and birth weight. The highest rate of iNO treatment in 24 to 27 weeks' preterm infants was due to hypoxic respiratory failure (HRF), whereas the highest rate of iNO treatment in 32 to 33 weeks' preterm infants was due to documented persistent pulmonary hypertension of the newborn (PPHN). The rates of iNO treatment due to HRF and documented PPHN were 54.3 and 60.6%, respectively, in extremely preterm infants, significantly higher than in very preterm and moderate preterm infants (all p < 0.05). Within the same GA group, the proportion of preterm infants treated with iNO for HRF was lower than that for documented PPHN (all p < 0.05), but there was no statistically significant difference in mortality between HRF and documented PPHN treated with iNO (all p > 0.05).
Conclusion Among preterm infants with GA < 34 weeks, the rate of iNO usage was highest in extremely preterm infants. However, iNO failed to improve the clinical outcome of extremely preterm infants with refractory hypoxemia, and there was no significant difference in the therapeutic effect of iNO among preterm infants with different GAs.
Modulating Immune Responses: The Double-Edged Sword of Platelet CD40L
Authors: Bendas Gerd , Gobec Martina , Schlesinger Martin 
Published: October 2024

AbstractThe CD40–CD40L receptor ligand pair plays a fundamental role in the modulation of the innate as well as the adaptive immune response, regulating monocyte, T and B cell activation, and antibody isotype switching. Although the expression and function of the CD40–CD40L dyad is mainly attributed to the classical immune cells, the majority of CD40L is expressed by activated platelets, either in a membrane-bound form or shed as soluble molecules in the circulation. Platelet-derived CD40L is involved in the communication with different immune cell subpopulations and regulates their functions effectively. Thus, platelet CD40L contributes to the containment and clearance of bacterial and viral infections, and additionally guides leukocytes to sites of infection. However, platelet CD40L promotes inflammatory cellular responses also in a pathophysiological context. For example, in HIV infections, platelet CD40L is supportive of neuronal inflammation, damage, and finally HIV-related dementia. In sepsis, platelet CD40L can induce extensive endothelial and epithelial damage resulting in barrier dysfunction of the gut, whereby the translocation of microbiota into the circulation further aggravates the uncontrolled systemic inflammation. Nevertheless, a distinct platelet subpopulation expressing CD40L under septic conditions can attenuate systemic inflammation and reduce mortality in mice. This review focuses on recent findings in the field of platelet CD40L biology and its physiological and pathophysiological implications, and thereby highlights platelets as vital immune cells that are essential for a proper immune surveillance. In this context, platelet CD40L proves to be an interesting target for various inflammatory diseases. However, either an agonism or a blockade of CD40L needs to be well balanced since both the approaches can cause severe adverse events, ranging from hyperinflammation to immune deficiency. Thus, an interference in CD40L activities should be likely done in a context-dependent and timely restricted manner.
Equilibrium densities of intrinsic defects in transition metal diselenides of molybdenum and tungsten
Authors: Holtzman Luke N. , Vargas Preston Allen , Hennig Richard G. , Barmak Katayun 
Published: October 2024

Point defects are thermodynamically stabilized in all crystalline materials, with increased densities negatively impacting the properties and performance of transition metal dichalcogenides (TMDs). While recent point defect reduction methods have led to considerable improvements in the optoelectronic properties of TMDs, there is a clear need for theoretical work to establish the lower limit of defect densities, as represented by thermal equilibrium. To that end, an ab initio and thermodynamic analysis of the equilibrium densities of intrinsic point defects in MoSe2 and WSe2 is presented. The intrinsic defect formation energies at the limits of the selenium and metal-rich regimes are determined by density functional theory (DFT) and then augmented with elemental chemical potential functions to determine temperature- and pressure-dependent formation energies. Equilibrium defect densities are determined for MSe, SeM, vM, and vSe, where M and v, respectively, represent the metal and the vacancy, as a function of synthesis temperature and pressure. The effects of vibrational free energy contributions and treatment of the DFT exchange–correlation potential are found to be non-negligible. Calculated equilibrium densities are several orders of magnitude below reported defect densities in TMDs made by chemical vapor deposition, chemical vapor transport, and flux methods, thereby establishing that current synthesis methods are either kinetically limited or impurity dominated.
Propensity of hydroxide and hydronium ions for the air–water and graphene–water interfaces from ab initio and force field simulations
Authors: Scalfi Laura , Lehmann Louis , dos Santos Alexandre P. , Becker Maximilian R. , Netz Roland R. 
Published: October 2024

Understanding acids and bases at interfaces is relevant for a range of applications from environmental chemistry to energy storage. We present combined ab initio and force-field molecular dynamics simulations of hydrochloric acid and sodium hydroxide highly concentrated electrolytes at the interface with air and graphene. In agreement with surface tension measurements at the air–water interface, we find that HCl presents an ionic surface excess, while NaOH displays an ionic surface depletion, for both interfaces. We further show that graphene becomes less hydrophilic as the water ions concentration increases, with a transition to being hydrophobic for highly basic solutions. For HCl, we observe that hydronium adsorbs to both interfaces and orients strongly toward the water phase, due to the hydrogen bonding behavior of hydronium ions, which donate three hydrogen bonds to bulk water molecules when adsorbed at the interface. For NaOH, we observe density peaks of strongly oriented hydroxide ions at the interface with air and graphene. To extrapolate our results from concentrated electrolytes to dilute solutions, we perform single ion-pair ab initio simulations, as well as develop force-field parameters for ions and graphene that reproduce the density profiles at high concentrations. We find the behavior of hydronium ions to be rather independent of concentration. For NaOH electrolytes, the force-field simulations of dilute NaOH solutions suggest no hydroxide adsorption but some adsorption at high concentrations. For both interfaces, we predict that the surface potential is positive for HCl and close to neutral for NaOH.