bluuebunny/crossref_metadata_2025 huggingface dataset:
Screening for TORCH Antibodies in Croatian Childbearing-Aged Women, 2014–2023
Authors: Vilibic-Cavlek Tatjana , Kolaric Branko , Belamaric Marko , Sviben Mario , Ferenc Thomas , Navolan Dan , Bekic Viktor , Milasincic Ljiljana , Antolasic Ljiljana , Vilibic Maja , Vujica Ferenc Mateja , Reicher Ema , Jezek Tadej , Ciohat Ioana , Parvanescu Raluca Catalina , Kos Matea , Bogdanic Maja
Published: June 2024

TORCH infections usually result in mild maternal morbidity, but may cause severe congenital abnormalities. Therefore, it is important to detect maternal infections, monitor the fetus after the disease has been recognized, and define the seronegative women who are at risk of primary infection during pregnancy. From 2014 to 2023, serum samples from 1032 childbearing-aged and pregnant women (16–45 years) were tested for IgM/IgG antibodies to the most common TORCH pathogens: Toxoplasma gondii, rubella virus (RUBV), cytomegalovirus (CMV), and herpes simplex viruses (HSV-1 and HSV-2). The overall IgG seroprevalence rates were 20.1% for T. gondii, 91.3% for RUBV, 70.5% for CMV, 66.8% for HSV-1, and 3.5% for HSV-2. Only HSV-2 seroprevalence was age-related, with a significant progressive increase in seropositivity from 0% in those aged less than 26 years to 9.3% in those older than 40 years. The seroprevalence of T. gondii was higher in residents of suburban/rural areas than in residents of urban areas (27.4% vs. 17.1%). In addition, participants from continental regions were more often toxoplasma-seropositive than those from coastal regions (22.2% vs. 15.3%). HSV-1 seroprevalence was also higher in suburban/rural areas (71.7% vs. 64.7%). Obstetric history was not associated with TORCH seropositivity. Univariate and multivariate risk analysis showed that suburban/rural areas of residence and continental geographic regions were significant risk factors for T. gondii seroprevalence. Furthermore, suburban/rural area of residence was a significant risk factor for HSV-1 seroprevalence, while older age was a significant risk factor for HSV-2 seroprevalence. A declining trend in the seroprevalence of all TORCH pathogens was observed compared to previous Croatian studies (2005–2011). Similarly, the proportion of women simultaneously IgG-seropositive to two or three pathogens decreased over time. The maternal serology before pregnancy could potentially reduce the burden of congenital TORCH infections.
Gear Fault Detection Method Based on Convex Hull Clustering of Autoencoder’s Latent Space
Authors: Batsch Michał , Kiczek Bartłomiej
Published: June 2024

This paper presents a method of pitting failure detection in toothed gears based on the reconstruction of the gear case vibrational signal. The effectiveness of the proposed method was tested in an experiment on a power circulation test stand. The autoencoder deep neural network architecture, semi-supervised training, and validation, along with the latent data convex hull-based clustering, are presented. The proposed method offers high efficiency (0.99 F1-measure) in gear state prediction (100% in failure detection, 98.9% in normal state prediction) and provides more capabilities in terms of generalization in comparison with linear machine learning techniques such as principal component analysis and nonlinear like the generative adversarial network. Moreover, it is distinguished by high sensitivity while also being able to detect even slight surface damage (initial pitting). These findings will be of particular relevance to a range of scientists and practitioners working with gear drives who are willing to implement machine learning in signal processing and diagnosis.
Evaluation of Single-Photon Emission Computed Tomography Myocardial Perfusion Detection Capability through Physical Descriptors
Authors: Dundara Debeljuh Dea , Matheoud Roberta , Pribanić Ivan , Brambilla Marco , Jurković Slaven
Published: June 2024

A comprehensive validation of data acquired by different myocardial perfusion imaging (MPI) systems was performed to evaluate contrast, self-attenuation properties, and perfusion detection capability. An anthropomorphic phantom with a myocardial insert and perfusion defect was used to simulate 99mTc-tetrofosmin distribution. Different MPI systems were evaluated: a SPECT system with iterative reconstruction algorithms and resolution recovery (IRR) with/without scatter correction (SPECT-IRR-SC and SPECT-IRR), and a cardio-centric IQ SPECT/CT system with IRR, with/without scatter and attenuation corrections (IQ-IRR-SC-AC and IQ-IRR). The image quality was assessed through physical descriptors: the contrast between the left ventricular (LV) wall and LV inner chamber (CLV/LVIC), intrinsic contrast (IC), and net contrast (NC). CLV/LVIC was found to be superior for IQ-IRR-SC-AC. The IC results showed non-uniformity of the signal intensity in the LV wall for the SPECT systems. The lowest IC values were obtained for IQ-IRR-SC-AC, except for septal position, where an underestimation of the signal intensity was revealed. The NC was found to be the highest for IQ-IRR-SC-AC and SPECT-IRR-SC. Additionally, for IQ-IRR-SC-AC, the NC increased in posterior and septal positions compared to IQ-IRR, enabling better perfusion detection capability over short-axis images. IQ-IRR showed performances comparable to SPECT-IRR. The characterization and evaluation perfusion detection capability of the MPI systems enabled the investigation of the systems’ performance and limitations.
Multi-Agent Simulation Approach for Modular Integrated Construction Supply Chain
Authors: Attajer Ali , Mecheri Boubakeur
Published: June 2024

The shift from traditional on-site to off-site construction marks a significant evolution in the construction industry, characterized by increasing levels of prefabrication. These advancements enhance construction efficiency, reduce lead times, and mitigate environmental impacts, leading to modular integrated construction (MiC). However, MiC presents complex supply chain challenges, particularly in the transportation of prefabricated components and fully integrated modules. This study addresses these challenges by employing a multi-agent simulation using AnyLogic to optimize MiC transport logistics. The simulation models the interactions of various agents involved in the MiC process to improve operational efficiency and reduce costs. Results demonstrate that using three vehicles per supplier minimizes total transport costs, effectively balancing fixed and variable expenses while eliminating penalties for project delays. The findings highlight the cost efficiency of MiC, showing potential savings due to centralized assembly and optimized logistics. These significantly reduce material transportation and related costs, contributing to the overall efficiency and sustainability of construction projects. These insights underscore the value of multi-agent simulation in addressing the complexities of MiC supply chains.
Event-Based Modeling of Input Signal Behaviors for Discrete-Event Controllers
Authors: Gomes Luis , Natário Diogo , Costa Anikó , Barros João-Paulo , Campos-Rebelo Rogério
Published: June 2024

Controllers for discrete-event systems are commonly designed using state-based formalisms, like state diagrams and Petri nets. These formalisms are strongly supported by the concept of events, which, from an automation system perspective, can be associated with a simple change in the value of a signal or more complex behavioral evolutions of the signals. In this paper, the characterization of several types of events is proposed, associated with different types of signals, such as Boolean and multivalued signals. The major goal of this characterization is to improve the compactness of the model, benefiting the editing and visual interpretation of the graphical model but keeping precise execution semantics, which in turn allows for the use of computational tools covering the different stages of system development. The behavioral model of the controller is produced using a non-autonomous class of Petri nets, the IOPT nets, and the associated IOPT-Tools, which supports the specification, simulation, property verification, and automatic code generation ready to be deployed into implementation platforms. All the types of proposed events have a behavioral sub-model executed concurrently with the main model of the controller. An application example is provided to illustrate some of the advantages of the adoption of the proposed approach, encapsulating the behavioral dependencies on the evolution of input signals into events.
The Efficiency of Calcium Oxide on Microbial Self-Healing Activity in Alkali-Activated Slag (AAS)
Authors: Hammad Nancy , El-Nemr Amr , Shaaban Ibrahim G.
Published: June 2024

Alkali-activated slag (AAS) materials are one of the most promising sustainable construction composites. These novel materials are highly characterized by their improved mechanical and durability properties. Nevertheless, the high shrinkage rate hinders their full-scale applications. The low Ca/Si ratio, complex hydration process, and fine pore microstructure are the main causes of the reported shrinkage behavior. This study introduces Bacillus subtilis culture for healing the cracking behavior. The enzymatic action leads to precipitating calcium carbonate crystals that fill AAS cracks and pores. Incorporating calcium oxide has been recommended in multiple studies. The main purpose of adding calcium oxide is to enhance the engineering properties of AAS and provide more calcium ions for the biochemical reactions induced by the added bacteria. However, inconsistent findings about the influence of calcium oxide have been reported. This research provides further insights into the effect of calcium oxide (CaO) on the performance of microbial self-healing efficiency in AAS composite. The results highlight that incorporating calcium oxide as 7% of the binder partial replacement has an impact on the engineering properties of bio-AAS materials. The study recommends correlating the percentage of free calcium ions within the AAS mixture with the microbial activity.
STOD: Towards Scalable Task-Oriented Dialogue System on MultiWOZ-API
Authors: Lu Hengtong , Yuan Caixia , Wang Xiaojie
Published: June 2024

Task-oriented dialogue systems (TODs) enable users to complete specific goals and are widely used in practice. Although existing models have achieved delightful performance for single-domain dialogues, scalability to new domains is far from well explored. Traditional dialogue systems rely on domain-specific information like dialogue state and database (DB), which limits the scalability of such systems. In this paper, we propose a Scalable Task-Oriented Dialogue modeling framework (STOD). Instead of labeling multiple dialogue components, which have been adopted by previous work, we only predict structured API queries to interact with DB and generate responses based on the complete DB results. Further, we construct a new API-schema-based TOD dataset MultiWOZ-API with API query and DB result annotation based on MultiWOZ 2.1. We then propose MSTOD and CSTOD for multi-domain and cross-domain TOD systems, respectively. We perform extensive qualitative experiments to verify the effectiveness of our proposed framework. We find the following. (1) Scalability across multiple domains: MSTOD achieves 2% improvements than the previous state-of-the-art in the multi-domain TOD. (2) Scalability to new domains: our framework enables satisfying generalization capability to new domains, a significant margin of 10% to existing baselines.
Application of Improved Sliding Mode and Artificial Neural Networks in Robot Control
Authors: Pham Duc-Anh , Ahn Jong-Kap , Han Seung-Hun
Published: June 2024

Mobile robots are autonomous devices capable of self-motion, and are utilized in applications ranging from surveillance and logistics to healthcare services and planetary exploration. Precise trajectory tracking is a crucial component in robotic applications. This study introduces the use of improved sliding surfaces and artificial neural networks in controlling mobile robots. An enhanced sliding surface, combined with exponential and hyperbolic tangent approach laws, is employed to mitigate chattering phenomena in sliding mode control. Nonlinear components of the sliding control law are estimated using artificial neural networks. The weights of the neural networks are updated online using a gradient descent algorithm. The stability of the system is demonstrated using Lyapunov theory. Simulation results in MATLAB/Simulink R2024a validate the effectiveness of the proposed method, with rise times of 0.071 s, an overshoot of 0.004%, and steady-state errors approaching zero meters. Settling times were 0.0978 s for the x-axis and 0.0902 s for the y-axis, and chattering exhibited low amplitude and frequency.
Identification, Elucidation and Deployment of a Cytoplasmic Male Sterility System for Hybrid Potato
Authors: Eggers Ernst-Jan , Su Ying , van der Poel Esmee , Flipsen Martijn , de Vries Michiel E. , Bachem Christian W. B. , Visser Richard G. F. , Lindhout Pim
Published: June 2024

Recent advances in diploid F1 hybrid potato breeding rely on the production of inbred lines using the S-locus inhibitor (Sli) gene. As a result of this method, female parent lines are self-fertile and require emasculation before hybrid seed production. The resulting F1 hybrids are self-fertile as well and produce many undesirable berries in the field. Utilization of cytoplasmic male sterility would eliminate the need for emasculation, resulting in more efficient hybrid seed production and male sterile F1 hybrids. We observed plants that completely lacked anthers in an F2 population derived from an interspecific cross between diploid S. tuberosum and S. microdontum. We studied the antherless trait to determine its suitability for use in hybrid potato breeding. We mapped the causal locus to the short arm of Chromosome 6, developed KASP markers for the antherless (al) locus and introduced it into lines with T and A cytoplasm. We found that antherless type male sterility is not expressed in T and A cytoplasm, proving that it is a form of CMS. We hybridized male sterile al/al plants with P cytoplasm with pollen from al/al plants with T and A cytoplasm and we show that the resulting hybrids set significantly fewer berries in the field. Here, we show that the antherless CMS system can be readily deployed in diploid F1 hybrid potato breeding to improve hybridization efficiency and reduce berry set in the field.
The Impact of Glycosylation on the Functional Activity of CD133 and the Accuracy of Its Immunodetection
Authors: Gisina Alisa , Yarygin Konstantin , Lupatov Alexey
Published: June 2024

The membrane glycoprotein CD133 (prominin-1) is widely regarded as the main molecular marker of cancer stem cells, which are the most malignant cell subpopulation within the tumor, responsible for tumor growth and metastasis. For this reason, CD133 is considered a promising prognostic biomarker and molecular target for antitumor therapy. Under normal conditions, CD133 is present on the cell membrane in glycosylated form. However, in malignancies, altered glycosylation apparently leads to changes in the functional activity of CD133 and the availability of some of its epitopes for antibodies. This review focuses on CD133’s glycosylation in human cells and its impact on the function of this glycoprotein. The association of CD133 with proliferation, differentiation, apoptosis, autophagy, epithelial–mesenchymal transition, the organization of plasma membrane protrusions and extracellular trafficking is discussed. In this review, particular attention is paid to the influence of CD133’s glycosylation on its immunodetection. A list of commercially available and custom antibodies with their characteristics is provided. The available data indicate that the development of CD133-based biomedical technologies should include an assessment of CD133’s glycosylation in each tumor type.
Reverse Logistics in the Construction Industry: Status Quo, Challenges and Opportunities
Authors: Chen Xiaomin , Qiu Dong , Chen Yunxin
Published: June 2024

Implementing reverse logistics in the construction industry is considered a crucial method to achieve a circular economy. Despite a wealth of research focusing on improving reverse logistics systems, businesses still encounter challenges during the implementation process. Therefore, this study conducted a systematic literature review utilizing bibliometric methods to analyze 623 articles on reverse logistics in the construction industry published on Web of Science from 1995 to 2023. Additionally, a comprehensive review of 56 high-quality literature on obstacles to implementing reverse logistics in the construction industry and optimizing reverse supply chains was conducted. This review uncovered the current status and challenges of implementing reverse logistics in the construction industry and proposed potential solutions to address these issues. The main findings of this study include: (1) increasing academic interest in construction waste reverse logistics, with Chinese scholars leading the way and publications predominantly in environmental and construction journals, with limited coverage in logistics journals; (2) the primary obstacles to implementing reverse logistics in the construction industry lie in supply chain management, such as lacking deconstruction designs, incomplete recycling markets, difficulties in evaluating the quality of secondary materials, and insufficient supply chain integration; (3) proposing a framework for a construction industry reverse logistics supply chain ecosystem, aiming to establish a platform to facilitate online collection of construction waste, online transactions of secondary materials, end-to-end monitoring, and data analytics for consultation.
Modular Housing Using Fibre-Reinforced Plastic Polymers (FRPs)
Authors: Cairoli Maria , Iannace Gino
Published: June 2024

In the era of the climate emergency and different pandemics, systems that can provide an immediate response to housing needs are required. This paper aims to evaluate the use of fibre-reinforced plastic polymers (FRPs) to satisfy this need. In particular, a modular emergency housing system that utilises FRPs for structures and cladding is proposed, which proves adaptable to both different uses and different kinds of temporary or permanent buildings. By adapting modular emergency housing to different contexts, developing an integrated design process (IDP) and building information modelling (BIM) methodology, this research aims to provide innovations for the the architecture, engineering, and construction (AEC) sector, including FRPs, through a digitised approach, applied also to an experimental case study. A pilot unit of the modular emergency housing system, a nearly zero-energy building (nZEB), is described in detail, while laboratory tests are reported. Construction considerations confirm the sustainability and highlight the adaptability of the modular system to different housing needs conditions, justifying the possible future development of supply chain industrialisation supported by the presented methodology.
Striatal GDNF Neurons Chemoattract RET-Positive Dopamine Axons at Seven Times Farther Distance Than Medium Spiny Neurons
Authors: Montaño-Rodriguez Ana Rosa , Schorling Tabea , Andressoo Jaan-Olle
Published: June 2024

Glial cell line-derived neurotrophic factor (GDNF) is among the strongest dopamine neuron function- and survival-promoting factors known. Due to this reason, it has clinical relevance in dopamine disorders such as Parkinson’s disease and schizophrenia. In the striatum, GDNF is exclusively expressed in interneurons, which make up only about 0.6% of striatal cells. Despite clinical significance, histological analysis of striatal GDNF system arborization and relevance to incoming dopamine axons, which bear its receptor RET, has remained enigmatic. This is mainly due to the lack of antibodies able to visualize GDNF- and RET-positive cellular processes; here, we overcome this problem by using knock-in marker alleles. We find that GDNF neurons chemoattract RET+ axons at least seven times farther in distance than medium spiny neurons (MSNs), which make up 95% of striatal neurons. Furthermore, we provide evidence that tyrosine hydroxylase, the rate-limiting enzyme in dopamine synthesis, is enriched towards GDNF neurons in the dopamine axons. Finally, we find that GDNF neuron arborizations occupy approximately only twelve times less striatal volume than 135 times more abundant MSNs. Collectively, our results improve our understanding of how endogenous GDNF affects striatal dopamine system function.
Empowering Communication: A Deep Learning Framework for Arabic Sign Language Recognition with an Attention Mechanism
Authors: Abdul Ameer R. S. , Ahmed M. A. , Al-Qaysi Z. T. , Salih M. M. , Shuwandy Moceheb Lazam
Published: June 2024

This article emphasises the urgent need for appropriate communication tools for communities of people who are deaf or hard-of-hearing, with a specific emphasis on Arabic Sign Language (ArSL). In this study, we use long short-term memory (LSTM) models in conjunction with MediaPipe to reduce the barriers to effective communication and social integration for deaf communities. The model design incorporates LSTM units and an attention mechanism to handle the input sequences of extracted keypoints from recorded gestures. The attention layer selectively directs its focus toward relevant segments of the input sequence, whereas the LSTM layer handles temporal relationships and encodes the sequential data. A comprehensive dataset comprised of fifty frequently used words and numbers in ArSL was collected for developing the recognition model. This dataset comprises many instances of gestures recorded by five volunteers. The results of the experiment support the effectiveness of the proposed approach, as the model achieved accuracies of more than 85% (individual volunteers) and 83% (combined data). The high level of precision emphasises the potential of artificial intelligence-powered translation software to improve effective communication for people with hearing impairments and to enable them to interact with the larger community more easily.
Role of Clinical and Multimodality Neuroimaging in the Evaluation of Brain Death/Death by Neurologic Criteria and Recent Highlights from 2023 Updated Guidelines
Authors: Suthar Pokhraj Prakashchandra , Jhaveri Miral D. , Kounsal Avin , Pierce Lillian D. , Singh Jagadeesh S.
Published: June 2024

Purpose of Review: This review aims to provide a comprehensive overview of the diagnosis of brain death/death by neurologic criteria (BD/DNC) by emphasizing the clinical criteria established by the American Academy of Neurology (AAN) in light of their updated guidelines released in 2023. In this review, we will focus on the current implementation of ancillary tests including the catheter cerebral angiogram, nuclear scintigraphy, and transcranial Doppler, which provide support in diagnoses when clinical examination and apnea tests are inconclusive. Finally, we will also provide examples to discuss the implementation of certain imaging studies in the context of diagnosing BD/DNC. Recent Findings: Recent developments in the field of neurology have emphasized the importance of clinical criteria for diagnosing BD/DNC, with the AAN providing clear updated guidelines that include coma, apnea, and the absence of brainstem reflexes. Current ancillary tests, including the catheter cerebral angiogram, nuclear scintigraphy, and transcranial Doppler play a crucial role in confirming BD/DNC when the clinical assessment is limited. The role of commonly used imaging studies including computed tomography and magnetic resonance angiographies of the brain as well as CT/MR perfusion studies will also be discussed in the context of these new guidelines. Summary: BD/DNC represents the permanent cessation of brain functions, including the brainstem. This review article provides the historical context, clinical criteria, and pathophysiology that goes into making this diagnosis. Additionally, it explores the various ancillary tests and selected imaging studies that are currently used to diagnose BD/DNC under the newly updated AAN guidelines. Understanding the evolution of how to effectively use these diagnostic tools is crucial for healthcare professionals who encounter these BD/DNC cases in their practice.
Application of a Machine Learning-Based Classification Approach for Developing Host Protein Diagnostic Models for Infectious Disease
Authors: Scherr Thomas F. , Douglas Christina E. , Schaecher Kurt E. , Schoepp Randal J. , Ricks Keersten M. , Shoemaker Charles J.
Published: June 2024

In recent years, infectious disease diagnosis has increasingly turned to host-centered approaches as a complement to pathogen-directed ones. The former, however, typically requires the interpretation of complex multiple biomarker datasets to arrive at an informative diagnostic outcome. This report describes a machine learning (ML)-based classification workflow that is intended as a template for researchers seeking to apply ML approaches for developing host-based infectious disease biomarker classifiers. As an example, we built a classification model that could accurately distinguish between three disease etiology classes: bacterial, viral, and normal in human sera using host protein biomarkers of known diagnostic utility. After collecting protein data from known disease samples, we trained a series of increasingly complex Auto-ML models until arriving at an optimized classifier that could differentiate viral, bacterial, and non-disease samples. Even when limited to a relatively small training set size, the model had robust diagnostic characteristics and performed well when faced with a blinded sample set. We present here a flexible approach for applying an Auto-ML-based workflow for the identification of host biomarker classifiers with diagnostic utility for infectious disease, and which can readily be adapted for multiple biomarker classes and disease states.
The Liver and Lysosomal Storage Diseases: From Pathophysiology to Clinical Presentation, Diagnostics, and Treatment
Authors: Lipiński Patryk , Tylki-Szymańska Anna
Published: June 2024

The liver, given its role as the central metabolic organ, is involved in many inherited metabolic disorders, including lysosomal storage diseases (LSDs). The aim of this manuscript was to provide a comprehensive overview on liver involvement in LSDs, focusing on clinical manifestation and its pathomechanisms. Gaucher disease, acid sphingomyelinase deficiency, and lysosomal acid lipase deficiency were thoroughly reviewed, with hepatic manifestation being a dominant clinical phenotype. The natural history of liver disease in the above-mentioned lysosomal disorders was delineated. The importance of Niemann–Pick type C disease as a cause of cholestatic jaundice, preceding neurological manifestation, was also highlighted. Diagnostic methods and current therapeutic management of LSDs were also discussed in the context of liver involvement.
Beyond Diagnosis and Comorbidities—A Scoping Review of the Best Tools to Measure Complexity for Populations with Mental Illness
Authors: Kapustianyk Grace , Durbin Anna , Shukor Ali , Law Samuel
Published: June 2024

Beyond the challenges of diagnosis, complexity measurement in clients with mental illness is an important but under-recognized area. Accurate and appropriate psychiatric diagnoses are essential, and further complexity measurements could contribute to improving patient understanding, referral, and service matching and coordination, outcome evaluation, and system-level care planning. Myriad conceptualizations, frameworks, and definitions of patient complexity exist, which are operationalized by a variety of complexity measuring tools. A limited number of these tools are developed for people with mental illness, and they differ in the extent to which they capture clinical, psychosocial, economic, and environmental domains. Guided by the PRISMA Extension for Scoping Reviews, this review evaluates the tools best suited for different mental health settings. The search found 5345 articles published until November 2023 and screened 14 qualified papers and corresponding tools. For each of these, detailed data on their use of psychiatric diagnostic categories, definition of complexity, primary aim and purpose, context of use and settings for their validation, best target populations, historical references, extent of biopsychosocial information inclusion, database and input technology required, and performance assessments were extracted, analyzed, and presented for comparisons. Two tools—the INTERMED, a clinician-scored and multiple healthcare data-sourced tool, and the VCAT, a computer-based instrument that utilizes healthcare databases to generate a comprehensive picture of complexity—are exemplary among the tools reviewed. Information on these limited but suitable tools related to their unique characteristics and utilities, and specialized recommendations for their use in mental health settings could contribute to improved patient care.
Molar Incisor Hypomineralization: Optimizing Treatment Protocols for Hypersensitivity: A Randomized Clinical Trial
Authors: Bardellini Elena , Amadori Francesca , Rosselli Laura , Garo Maria Luisa , Majorana Alessandra , Conti Giulio
Published: June 2024

Dentin hypersensitivity (DH) is a common challenge in pediatric patients with molar incisor hypomineralization (MIH), stemming from enamel porosity or exposed dentin after enamel breakdown. This three-arm randomized controlled clinical trial aims to evaluate the effectiveness of three different desensitizing treatment protocols. The study was conducted on 39 children, aged 6–14 years old, with MIH and DH. Group A received casein phosphopeptide plus amorphous calcium phosphate fluoride (CPP-ACPF) mousse and sham light therapy, Group B received placebo mousse and photo-bio-modulation therapy (PMBT), and Group C received both CPP-ACPF mousse and PMBT. DH evaluation using a visual analogue scale was performed at multiple time points. Both CPP-ACPF mousse and PMBT individually demonstrated desensitizing effects on dental elements affected by MIH. While PMBT had a greater immediate effect, the combination of the two therapies proved most effective in reducing DH. The VAS scores were statistically lower in group C compared to groups A and B, both after the first session (p = 0.0001) and after 28 days (p = 0.0005). This study suggests promising avenues for managing DH in MIH patients, highlighting the potential of combined therapies, specifically CPP-ACPF mousse and PMBT, for enhanced clinical outcomes.
Correction: Wu et al. Accumulatively Increasing Sensitivity of Ultrawide Instantaneous Bandwidth Digital Receiver with Fine Time and Frequency Resolution for Weak Signal Detection. Electronics 2022, 11, 1018
Authors: Wu Chen , Tang Taiwen , Elangage Janaka , Krishnasamy Denesh
Published: June 2024

In the original publication [...]
A Novel DOA Estimation Algorithm Based on Robust Mixed Fractional Lower-Order Correntropy in Impulsive Noise
Authors: Lan Xiaoyu , Hu Jingyi , Zhang Yudi , Ma Shuang , Tian Ye
Published: June 2024

The estimation of direction of arrival (DOA) is paramount in the realm of practical array signal processing systems. Nevertheless, traditional estimation methods often rely heavily on the Gaussian noise assumption, rendering them ineffective in achieving high-precision estimates in environments plagued by strong impulsive noise. To address this challenge, this paper introduces a novel DOA estimation algorithm that leverages mixed fractional lower-order correntropy (MFLOCR) in the context of Alpha-stable distributed impulsive noise. Correntropy is used as a measure of the similarity of the signals, using a Gaussian function to smooth extreme values and provide greater robustness against impulsive noise. By utilizing diverse kernel lengths to jointly regulate the kernel function, the concept of correntropy is expanded and implemented in the fractional lower-order moment (FLOM) algorithm for received signals. Subsequently, the MFLOCR is derived by adjusting the resulting form of correntropy. Finally, an enhanced DOA estimation algorithm is proposed that combines the MFLOCR operator with the MUSIC algorithm, specifically tailored for impulsive noise environments. Furthermore, a proof of boundedness is provided to validate the effectiveness of the proposed approach in such noisy conditions. Simulation experiments confirmed that the proposed method outperforms existing DOA estimation methods in the context of intense impulsive noise, a low generalized signal-to-noise ratio (GSNR), and a smaller number of snapshots.
Offloading Strategy Based on Graph Neural Reinforcement Learning in Mobile Edge Computing
Authors: Wang Tao , Ouyang Xue , Sun Dingmi , Chen Yimin , Li Hao
Published: June 2024

In the mobile edge computing (MEC) architecture, base stations with computational capabilities are subject to service coverage limitations, and the mobility of devices leads to dynamic changes in their connections, directly impacting the offloading decisions of agents. The connections between base stations and mobile devices, as well as the connections between base stations themselves, are abstracted into an MEC structural diagram due to the difficulty of deep reinforcement learning (DRL) in capturing the complex relationships between nodes and their multi-order neighboring nodes in the graph; decisions solely generated by DRL have limitations. To address this issue, this study proposes a hierarchical mechanism strategy based on Graph Neural Reinforcement Learning (M-GNRL) under multiple constraints. Specifically, the MEC structural graph constructed with the current device as an observation point aggregates to learn node features, thus comprehensively considering the contextual information of nodes, and the learned graph information serves as the environment for deep reinforcement learning, effectively integrating a graph neural network (GNN) with DRL. In the M-GNRL strategy, edge features from GNN are introduced into the architecture of the DRL network to enhance the accuracy of agents’ decision-making. Additionally, this study proposes an updated algorithm to obtain graph data that change with observation points. Comparative experiments demonstrate that the M-GNRL algorithm outperforms other baseline algorithms in terms of system cost and convergence performance.
Effects of Fe Contamination on the Reliability of Gate Oxide Integrity in Advanced CMOS Technology
Authors: Wang Fan , Fang Minghai , Yu Peng , Zhou Wenbin , Cao Kaiwei , Xie Zhen , Liu Xiangze , Yan Feng , Ji Xiaoli
Published: June 2024

Fe contamination has always been one of the most critical issues in the integrated circuit (IC) industry due to its catastrophic effect on device reliability and electrical characteristics. With complementary metal oxide semiconductor (CMOS) technology scaling down, this issue has been attracting more attention. In this paper, the impact of Fe impurity on the reliability of gate oxide integrity (GOI) in advanced CMOS technology is investigated. Intentional contamination of polysilicon gates was conducted in both boron- and phosphorus-doped devices. Failure analysis of the gate oxide was conducted with high-resolution transmission electron microscopy (HRTEM) and the energy dispersive X-ray (EDX) technique. The experimental results disclose that the properties of PMOS are much more sensitive to Fe contamination than those of NMOS. It is suggested that the reason for the above phenomena is that Fe precipitates at the PMOS gate/oxide interface but dissolves uniformly in the NMOS poly gate due to lower formation energy of the FeB pair (0.65 eV) in PMOS than that of the P4-Fe cluster (3.2 eV) in NMOS.
A Hardware Trojan Diagnosis Method for Gate-Level Netlists Based on Graph Theory
Authors: Gao Hongxu , Zhai Guangxi , Li Zeyu , Zhou Jia , Li Xiang , Wang Quan
Published: June 2024

With the increasing complexity of integrated circuit design, the threat of a hardware Trojan (HT) is becoming more and more prominent. At present, the research mainly focuses on the detection of HTs, but the amount of research on the diagnosis of HTs is very small. The number of existing HT diagnosis methods is generally completed by detecting the HT nodes in the netlist. The main reason is the lack of consideration of the integrity of HTs, so the diagnosis accuracy is low. Based on the above reason, this paper proposes two implanted node search algorithms named layer-by-layer difference search (LDS) and layer-by-layer grouping difference search (LGDS). The LDS algorithm can greatly reduce the search time, and the LGDS algorithm can solve the problem of input node disorder. The two methods greatly reduce the number of nodes sorting and comparing, and therefore the time complexity is lower. Moreover, the relevance between implanted nodes is taken into account to improve the diagnosis rate. We completed experiments on an HT diagnosis; the HT implantation example is from Trust-Hub. The experimental results are shown as follows: (1) The average true positive rate (TPR) of the diagnosis using KNN, RF, or SVM with the LDS or LGDS algorithm is more than 93%, and the average true negative rate (TNR) is 100%. (2) The average proportion of implanted nodes obtained by the LDS or LGDS algorithm is more than 97%. The proposed method has a lower time complexity compared with other existing diagnosis methods, and the diagnosis time is shortened by nearly 75%.
Quality Control and Safety Assessment of Online-Purchased Food Supplements Containing Red Yeast Rice (RYR)
Authors: Vanhee Celine , Jacobs Bram , Canfyn Michael , Malysheva Svetlana V. , Willocx Marie , Masquelier Julien , Van Hoorde Koenraad
Published: June 2024

Dietary supplements containing red yeast rice (RYR), a fermentation product of the fungus Monascus purpureus grown on white rice, remain popular in Europe as proclaimed cholesterol-lowering aids. The cholesterol-lowering effects are due to the occurrence of monacolin K, which is often present as a mixture of monacolin K lactone (MK) and as monacolin K hydroxy acid (MKA). MK is structurally similar to the cholesterol-lowering medicine lovastatin. Recently, due to safety concerns linked to the use of statins, the European Commission prohibited RYR supplements with a maximum serving exceeding 3 mg of total monacolins per day. Moreover, the amount of the mycotoxin citrinin, potentially produced by M. purpureus, was also reduced to 100 µg/kg. Evidently, manufacturers that offer their products on the European market, including the online market, must also be compliant with these limits in order to guarantee the safety of their products. Therefore, thirty-five different RYR supplements, purchased from an EU-bound e-commerce platform or from registered online pharmacies, were screened for their compliance to the European legislation for citrinin content and the amount of total monacolin K. This was conducted by means of a newly developed LC-MS/MS methodology that was validated according to ISO 17025. Moreover, these supplements were also screened for possible adulteration and any contamination by micro-organisms and/or mycotoxins. It was found that at least four of the thirty-five RYR supplements (≈11%) might have reason for concern for the safety of the consumer either due to high total monacolin K concentrations exceeding the European predefined limits for total monacolins or severe bacterial contamination. Moreover, three samples (≈9%) were likely adulterated, and the labeling of six of the seventeen samples (≈35%) originating from an EU-based e-commerce platform was not compliant, as either the mandatory warning was missing or incomplete or the total amount of monacolins was not mentioned.
One-Year Monitoring of Prevalence and Diversity of Dairy Propionic Acid Bacteria in Raw Milk by Means of Culture-Dependent and Culture-Independent Methods
Authors: Bücher Carola , Burtscher Johanna , Zitz Ulrike , Domig Konrad J.
Published: June 2024

Even low levels of dairy propionic acid bacteria (dPAB) can cause cheese defects, resulting in severe economic losses for the producers of selected raw milk cheeses. Therefore, routine quality control of raw cheese milk for dPAB contamination is essential if propionic acid fermentation is undesired. Although knowledge of dPAB contamination of raw milk is important to understand cheese spoilage, long-term dPAB screening data are outdated, and studies taking into account different farm management parameters and their potential influence on dPAB levels are scarce. This study aims to provide insight into the dPAB levels of raw milk over time, to identify farm management factors that potentially influence dPAB levels, and to compare a cultural yeast extract lactate agar (YELA) and lithium glycerol agar (LGA) and a culture-independent method (qPCR) for dPAB quantification with respect to their applicability in routine quality control for the dairy industry. For this purpose, bulk tank milk from 25 dairy farms was screened for dPAB contamination over a one-year period. We were able to identify significant differences in the dPAB contamination levels in raw milk depending on selected farm-specific factors and observed relationships between the different types of milking systems and dPAB contamination levels in raw milk. When dPAB were quantified by cultivation on YELA, strong overgrowth of commensal microbiota impeded counting. Therefore, we conclude that quantification on LGA or by qPCR is preferable. Both methods, colony counting on LGA as well as quantification of dPAB using qPCR, have advantages for the application in (routine) quality control of raw milk, one being low-tech and inexpensive, the other being fast and highly specific, but the detection of (low level) dPAB contamination in raw milk remains a challenge.
Distribution of Elements in Durum Wheat Seed and Milling Products: Discrimination between Cultivation Methods through Multivariate Data Analysis
Authors: Fattobene Martina , Liu Fuyong , Conti Paolo , Zamponi Silvia , Governatori Catia , Nardi Sandro , Russo Raffaele Emanuele , Berrettoni Mario
Published: June 2024

Many staple foods originate from durum wheat and its milling products; because of this, it is very important to know their characteristics. This study investigates elemental contents in these products and if differences exist because of organic farming. The concentrations of 28 elements in the whole seed and in milling products, that is, bran, semolina and flour, of durum wheat, were determined through ICP-OES. The wheats were grown under conventional or organic agronomic practices to verify the possibility of discriminating, using the elemental content, between products coming from one or the other practice. The elements were more abundant in the outer layer of the seed, the bran, but most of them were also present in the others. Traces of Sb were present only in 3% of the samples, while traces of Tl were detected in approximately half of the seed and bran samples but not in other samples. The absence of an element was more characteristic of specific products, e.g., most semolina and flour lacked Co, while other elements showed small differences between products from organic and conventional cultivation or between different milling products, which was the case, for example, for traces of Ag, B, and V. The concentrations of these elements were coupled with multivariate discriminant analysis, specifically PLS-DA, to identify the cultivation provenance of the milled products. A few elements, although different for each product, are sufficient to attain precision and accuracy of classification close to 1; small differences exist for different products. The worst is flour, where the predicted precision and accuracy are 0.92, although using only three elements: B, K, and Se. Semolina attains perfect prediction when also adding to the three previous elements, Ag, Cd, and Cu. Further elements are necessary for bran, while Fe and Mg replace K and Ag to classify seeds. In conclusion, five elements, B, Cd, Cu, K, and Se, are the most important in distinguishing between organic and conventional agriculture; these elements also permit some differentiation among products. The method could help in fraud prevention.
Assessing Residual Gastric Fluid Volume after Administering Diluted Oral Contrast until One Hour Prior to Anesthesia in Children: An Observational Cohort Study
Authors: Narayanasamy Suryakumar , Fleck Robert J. , Kandil Ali I. , Afonya Boma , Mahmoud Hana , Lee Jiwon , Ding Lili , Mahmoud Mohamed A.
Published: June 2024

Background: Gastric fluid volume has been used as a surrogate marker for pulmonary aspiration risk in studies evaluating fasting protocol safety. This study measured residual gastric fluid volume in children using a protocol in which diluted oral contrast medium was administered up until one hour before anesthesia. Methods: This was a single-center prospective observational cohort trial of 70 children for elective abdominal/pelvic computed tomography (CT). Imaging was performed after diluted enteral contrast medium administration, beginning two hours before and ending at least one hour before induction. For each patient, gastric fluid volume was calculated using an image region of interest. The primary outcome measure was gastric fluid volume measured using the computed tomography image. Results: The median time from the end of contrast administration to imaging was 1.5 h (range: 1.1 to 2.2 h). Residual gastric volume, measured using CT was <0.4 mL/Kg in 33%; ≥0.4 mL/Kg in 67%; and ≥1.5 mL/Kg in 44% of patients. Residual gastric volumes measured using CT and aspiration were moderately correlated (Spearman’s correlation coefficient = 0.41, p = 0.0003). However, the median residual gastric volume measured using CT (1.17, IQR: 0.22 to 2.38 mL/Kg) was higher than that of aspiration (0.51, IQR: 0 to 1.58 mL/Kg, p = 0.0008 on differences in paired measures). Three cases of vomiting were reported. No evidence of pulmonary aspiration was identified. Conclusions: Children who receive large quantities of clear fluid up to one hour before anesthesia can have a significant gastric residual volume.
Evaluation of the Dimensional Accuracy of Robot-Guided Laser Osteotomy in Reconstruction with Patient-Specific Implants—An Accuracy Study of Digital High-Tech Procedures
Authors: Msallem Bilal , Veronesi Lara , Beyer Michel , Halbeisen Florian S. , Maintz Michaela , Franke Adrian , Korn Paula , Dragu Adrian , Thieringer Florian M.
Published: June 2024

Background/Objective: With the rapid advancement in surgical technologies, new workflows for mandibular reconstruction are constantly being evaluated. Cutting guides are extensively employed for defining osteotomy planes but are prone to errors during fabrication and positioning. A virtually defined osteotomy plane and drilling holes in robotic surgery minimize potential sources of error and yield highly accurate outcomes. Methods: Ten mandibular replicas were evaluated after cutting-guided saw osteotomy and robot-guided laser osteotomy following reconstruction with patient-specific implants. The descriptive data analysis summarizes the mean, standard deviation (SD), median, minimum, maximum, and root mean square (RMS) values of the surface comparison for 3D printed models regarding trueness and precision. Results: The saw group had a median trueness RMS value of 2.0 mm (SD ± 1.7) and a precision of 1.6 mm (SD ± 1.4). The laser group had a median trueness RMS value of 1.2 mm (SD ± 1.1) and an equal precision of 1.6 mm (SD ± 1.4). These results indicate that robot-guided laser osteotomies have a comparable accuracy to cutting-guided saw osteotomies, even though there was a lack of statistical significance. Conclusions: Despite the limited sample size, this digital high-tech procedure has been shown to be potentially equivalent to the conventional osteotomy method. Robotic surgery and laser osteotomy offers enormous advantages, as they enable the seamless integration of precise virtual preoperative planning and exact execution in the human body, eliminating the need for surgical guides in the future.