bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of the Effectiveness of the Application of Corrosion Inhibitors to Steel Re-Bars Embedded in Concrete
Authors: Matilla Alberto Leal , Barrio Maria Isabel Prieto , Escamilla Alfonso Cobo , Ferrer Jennifer Pérez , Prieto Tomás Gómez
Published: April 2024

Reinforced concrete is the most widely used material in the construction of building structures, being noted for its versatility and low cost. However, the durability of reinforced concrete structures can be compromised by the corrosion of steel re-bars, especially in the presence of chlorides. To address this challenge and promote sustainability, the use of corrosion inhibitors has been researched as a way to extend the lifespan of structures. This study assessed the effectiveness of using a commercial corrosion inhibitor on steel re-bars embedded in types of concrete with different chloride percentages, using electrochemical methods to measure the corrosion rate and potential. The results indicate that, in the absence of corrosion inhibitors, corrosion rates become unacceptable with chloride percentages equal to or higher than 0.8% by weight of cement. The application of inhibitors significantly reduced the corrosion rate, particularly at chloride percentages of 0.8% and 1.2%, maintaining the re-bars in a passive state or at moderate levels of corrosion. However, for chloride percentages higher than 1.6%, high levels of corrosion were observed, even in the presence of inhibitors. The findings suggest that the use of inhibitors can be an effective strategy in preventing corrosion in reinforced concrete structures, contributing to their structural integrity and long-term sustainability.
Inelastic X-ray Scattering as a Probe of Terahertz Phonon Propagation in Nanoparticle Suspensions
Authors: Cunsolo Alessandro
Published: April 2024

This paper reviews recent inelastic X-ray scattering investigations of simple inhomogeneous materials, such as nanoparticle suspensions in liquids. All studies reported emphasize the ability of immersed nanoparticles to dampen or attenuate acoustic waves through the hosting medium, the effect becoming even more pronounced upon freezing. Additionally, the results show that suspended nanoparticles can cause the onset of non-acoustic modes in the system. Also, the crucial role of Bayesian analysis in guiding spectral line shape modeling and interpretation is discussed. In summary, the presented results demonstrate that the simple inclusion of a sparse amount of nanoparticles profoundly influences sound propagation through a medium. This finding can inspire new avenues in the emerging field of terahertz acoustic steering and manipulation.
Greenhouse Ventilation Equipment Monitoring for Edge Computing
Authors: Feng Guofu , Zhang Hao , Chen Ming
Published: April 2024

Digital twins based on real-world scenarios are heavily reliant on extensive on-site data, representing a significant investment in information technology. This study aims to maximize the capabilities of visual sensors, like cameras in controlled-environment agriculture, by acquiring more target-specific information at minimal additional cost. This approach not only reduces investment but also increases the utilization rate of existing equipment. Utilizing YOLOv7, this paper introduces a system with rotatable pan-tilt cameras for the comprehensive monitoring of large-scale greenhouse ventilation systems. To mitigate the computational load on edge servers at greenhouse sites caused by an abundance of video-processing tasks, a Region of Interest (ROI) extraction method based on tracking is adopted. This method avoids unnecessary calculations in non-essential areas. Additionally, we integrate a self-encoding approach into the training phase, combining object detection and embedding to eliminate redundant feature extraction processes. Experimental results indicate that ROI extraction significantly reduces the overall inference time by more than 50%, and by employing LSTM to classify the state of the fan embedding sequences, a 100% accuracy rate was achieved.
Research on Dynamic Searchable Encryption Method Based on Bloom Filter
Authors: Jin Ziqi , Li Dongmei , Zhang Xiaomei , Cai Zhi
Published: April 2024

Data outsourcing has become more and more popular due to its low cost and flexibility. However, there is a problem that the cloud server used to store data is partially trusted. Searchable encryption is an efficient technology that is devoted to helping people conduct accurate searches without leaking information. Nonetheless, most existing schemes cannot support dynamic updates or meet the privacy requirements of all users. There have been some experiments to solve these issues by implementing a dynamically searchable asymmetric encryption scheme. This paper proposes an efficient searchable encryption scheme based on the Authenticator Bloom Filter (ABF). The solution can support dynamic updates and multiple users and meet forward and backward security. This paper uses an ABF to improve the efficiency of searches and updates while playing a significant role in dynamic updates. This paper designs a new token encryption scheme and file set encryption scheme, which not only helps users reduce time in searches and updates but also supports multi-user modes. Experiments show that the proposed scheme takes less time in searching and updating algorithms, especially when the keyword does not exist. The solution also takes into account the problem of history storage when updating, which reduces the unnecessary consumption of memory and avoids multiple storage states for the same file.
Optimizing sEMG Gesture Recognition: Leveraging Channel Selection and Feature Compression for Improved Accuracy and Computational Efficiency
Authors: Niu Yinxi , Chen Wensheng , Zeng Hui , Gan Zhenhua , Xiong Baoping
Published: April 2024

In the task of upper-limb pattern recognition, effective feature extraction, channel selection, and classification methods are crucial for the construction of an efficient surface electromyography (sEMG) signal classification framework. However, existing deep learning models often face limitations due to improper channel selection methods and overly specific designs, leading to high computational complexity and limited scalability. To address this challenge, this study introduces a deep learning network based on channel feature compression—partial channel selection sEMG net (PCS-EMGNet). This network combines channel feature compression (channel selection) and feature extraction (partial block), aiming to reduce the model’s parameter count while maintaining recognition accuracy. PCS-EMGNet extracts high-dimensional feature vectors from sEMG signals through the partial block, decoding spatial and temporal feature information. Subsequently, channel selection compresses and filters these high-dimensional feature vectors, accurately selecting channel features to reduce the model’s parameter count, thereby decreasing computational complexity and enhancing the model’s processing speed. Moreover, the proposed method ensures the stability of classification, further improving the model’s capability of recognizing features in sEMG signal data. Experimental validation was conducted on five benchmark databases, namely the NinaPro DB4, NinaPro DB5, BioPatRec DB1, BioPatRec DB2, and BioPatRec DB3 datasets. Compared to traditional gesture recognition methods, PCS-EMGNet significantly enhanced recognition accuracy and computational efficiency, broadening its application prospects in real-world settings. The experimental results showed that our model achieved the highest average accuracy of 88.34% across these databases, marking a 9.96% increase in average accuracy compared to models with similar parameter counts. Simultaneously, our model’s parameter size was reduced by an average of 80% compared to previous gesture recognition models, demonstrating the effectiveness of channel feature compression in maintaining recognition accuracy while significantly reducing the parameter count.
A Material Stress–Strain–Time–Temperature Creep Model for the Analysis of Asphalt Cores in Embankment Dams
Authors: Wang Weibiao
Published: April 2024

Asphalt cores in embankment dams are subject to loading and temperature changes during construction and reservoir impounding. Asphalt samples were drilled out from the Quxue Dam and Laojiaoxi Dam cores during construction. The diameter of the samples was 100 mm, and the length was about 450 mm. The samples were cut into specimens measuring 200 mm in length. Long-term triaxial creep tests were conducted on the specimens. The tests were run systematically at different radial confining stresses in the range of 0.5–1.5 MPa and at different temperatures in the range of 5–30 °C. More than 3.5 years were required to complete the tests. Based on the systematic test results and the application of the viscoelastic theory, a material stress–strain–time–temperature creep model (SSTTC) is proposed. The performance of asphalt cores in dams is discussed. The proposed SSTTC model may be applied in the numerical analysis of asphalt cores in dams during dam construction and reservoir impounding.
Minimal Terracini Loci in a Plane and Their Generalizations
Authors: Ballico Edoardo
Published: April 2024

We study properties of the minimal Terracini loci, i.e., families of certain zero-dimensional schemes, in a projective plane. Among the new results here are: a maximality theorem and the existence of arbitrarily large gaps or non-gaps for the integers x for which the minimal Terracini locus in degree d is non-empty. We study similar theorems for the critical schemes of the minimal Terracini sets. This part is framed in a more general framework.
Underemployment, Work Needs, and Job Satisfaction: Does Social Support Matter?
Authors: Kirazci Furkan , Buyukgoze-Kavas Aysenur
Published: April 2024

Global problems that have emerged in recent years have caused an increase in underemployment rates, especially in developing countries. Researchers emphasize that underemployment has as many negative consequences as unemployment on well-being. In order to examine the variables that may buffer these consequences, we draw on the Psychology of Working Theory to propose a model in which a mediating role of psychological needs and a moderating role of social support are assumed in the relationship between underemployment and job satisfaction. We collected and analyzed data from 459 Turkish employees (181 women and 278 men) and found that underemployment was negatively related to job satisfaction and that work needs satisfaction mediated the relationship between underemployment and job satisfaction. Further, social support moderated the relationship between subjective underemployment and job satisfaction, so it was insignificant when social support was higher. These findings provide researchers and practitioners with a different perspective on underemployment.
Dynamic Bayesian Network-Enabled Approach for Organizational Leadership Measurement of Complex Construction Projects
Authors: Shen Hao , Luo Lan , Niu Xiaoxuan , Fu Chengqian , Han Yujie
Published: April 2024

Complex construction projects are characterized by a large scale, high dynamics, many unknown risks, high complexity, etc., which often result in serious consequences, such as schedule delays, cost overruns, and uncontrolled objectives. Organizational leadership, which can be dynamically adjusted to the changes in the external environment, is the most important management ability of project managers. Therefore, it is of great significance to systematically analyze organizational leadership for the management of complex construction projects. In this paper, through the dynamic Bayesian method, the influencing factors of organizational leadership of complex construction projects and its dynamic development law are studied in depth. First, 17 organizational leadership factors are identified. Second, a dynamic Bayesian measurement model of organizational leadership was developed using 128 training samples. Third, the developed measurement model was applied for model analysis. The results of the study are as follows. (1) This study models changes in organizational leadership influences over time. (2) The organizational leadership measurement model proposed in this study can be applied in practice to predict leadership trends in specific projects. (3) Leaders should pay more attention to management competence in the personal leadership dimension, culture building in the relational leadership dimension, and institutional support in the strategic leadership dimension. This study proposes a quantifiable model for project leaders that breaks through the traditional model of studying organizational leadership from a static perspective, provides a quantifiable model for project leaders, and can cope with the dynamics of actual projects so that project leaders can control the whole leadership process macroscopically, thus providing an important reference to improve the organizational leadership capacity of complex construction projects.
Contrast Agent Dynamics Determine Radiomics Profiles in Oncologic Imaging
Authors: Watzenboeck Martin L. , Beer Lucian , Kifjak Daria , Röhrich Sebastian , Heidinger Benedikt H. , Prayer Florian , Milos Ruxandra-Iulia , Apfaltrer Paul , Langs Georg , Baltzer Pascal A. T. , Prosch Helmut
Published: April 2024

Background: The reproducibility of radiomics features extracted from CT and MRI examinations depends on several physiological and technical factors. The aim was to evaluate the impact of contrast agent timing on the stability of radiomics features using dynamic contrast-enhanced perfusion CT (dceCT) or MRI (dceMRI) in prostate and lung cancers. Methods: Radiomics features were extracted from dceCT or dceMRI images in patients with biopsy-proven peripheral prostate cancer (pzPC) or biopsy-proven non-small cell lung cancer (NSCLC), respectively. Features that showed significant differences between contrast phases were identified using linear mixed models. An L2-penalized logistic regression classifier was used to predict class labels for pzPC and unaffected prostate regions-of-interest (ROIs). Results: Nine pzPC and 28 NSCLC patients, who were imaged with dceCT and/or dceMRI, were included in this study. After normalizing for individual enhancement patterns by defining seven individual phases based on a reference vessel, 19, 467 and 128 out of 1204 CT features showed significant temporal dynamics in healthy prostate parenchyma, prostate tumors and lung tumors, respectively. CT radiomics-based classification accuracy of healthy and tumor ROIs was highly dependent on contrast agent phase. For dceMRI, 899 and 1027 out of 1118 features were significantly dependent on time after contrast agent injection for prostate and lung tumors. Conclusions: CT and MRI radiomics features in both prostate and lung tumors are significantly affected by interindividual differences in contrast agent dynamics.
Hepatitis-C-Related Hepatocellular Carcinoma, Still a Relevant Etiology beyond a Hepatitis C Infection Cure
Authors: Vargas-Accarino Elena , Higuera Mónica , Buti María , Mínguez Beatriz
Published: April 2024

Background: In the past decades, global changes, including hepatitis B vaccination, hepatitis B and C antiviral therapies, and the increasing prevalence of steatotic liver disease, have influenced the landscape of liver cancer etiologies. Methods: We performed a retrospective study focused on the etiological factors of de novo hepatocellular carcinoma (HCC) diagnoses in an academic center between 2019 and 2022. Results: Among 352 consecutive patients with HCC, alcohol-related liver disease was the predominant etiology (33.3%), followed by hepatitis C (HCV) infection (30.7%). Significant associations were found between HCC etiology and patient demographics, BCLC stage at diagnosis, and cirrhosis prevalence. Conclusions: Whereas accessibility to antiviral therapy is granted, HCV infection remains as one of the main HCC etiologies. MASLD-related HCC, although growing globally, is not as relevant in our area. Strong public policies need to be implemented to prevent alcohol consumption, the main etiology of liver disease and liver cancer.
A Novel ceRNET Relying on the lncRNA JPX, miR-378a-3p, and Its mRNA Targets in Lung Cancer
Authors: Mosca Nicola , Pezzullo Mariaceleste , De Leo Ilenia , Truda Anna , Marchese Giovanna , Russo Aniello , Potenza Nicoletta
Published: April 2024

Lung cancer is the leading cause of cancer-related death worldwide. Non-coding RNAs are emerging as critical players for the onset and progression of cancer. Analyses of three different datasets revealed that the lncRNA JPX was overexpressed in adenocarcinoma tissues in comparison to normal lungs, as expected for an oncogene. Intriguingly, the predicted binding miR-378a-3p showed a significant inverse correlation with JPX expression. The lncRNA/miRNA physical interaction was validated by reporter vectors. Then, the oncogenic activity of JPX, the tumor-suppressive role of miR-378a-3p, and the contribution of their functional interaction to cancer hallmarks were demonstrated using assays for cell proliferation, migration, invasion, and 3D-spheroid formation. Finally, molecular circuits were investigated by boosting the expression of both JPX and miR-378a-3p, singularly and in combination, demonstrating that JPX counteracted miR-378a-3p silencing activity toward its oncogenic targets GLUT1, NRP1, YY1, and Wnt5a. Overall, the data unveil a novel ceRNET (competing endogenous RNA network), wherein JPX acts as a ceRNA by binding to miR-378a-3p, thus reducing the miRNA silencing activity toward its downstream targets, and eliciting oncogenic pathways driving lung cancer. The knowledge of the network may pave the way to develop new diagnostic panels, and innovative RNA-targeted and RNA-based therapeutic strategies.
Colorectal Cancer: Epidemiology, Risk Factors, and Prevention
Authors: Roshandel Gholamreza , Ghasemi-Kebria Fatemeh , Malekzadeh Reza
Published: April 2024

Colorectal cancer (CRC) is the third most common cancer and the second most common cause of cancer mortality worldwide. There are disparities in the epidemiology of CRC across different populations, most probably due to differences in exposure to lifestyle and environmental factors related to CRC. Prevention is the most effective method for controlling CRC. Primary prevention includes determining and avoiding modifiable risk factors (e.g., alcohol consumption, smoking, and dietary factors) as well as increasing protective factors (e.g., physical activity, aspirin). Further studies, especially randomized, controlled trials, are needed to clarify the association between CRC incidence and exposure to different risk factors or protective factors. Detection and removal of precancerous colorectal lesions is also an effective strategy for controlling CRC. Multiple factors, both at the individual and community levels (e.g., patient preferences, availability of screening modalities, costs, benefits, and adverse events), should be taken into account in designing and implementing CRC screening programs. Health policymakers should consider the best decision in identifying the starting age and selection of the most effective screening strategies for the target population. This review aims to present updated evidence on the epidemiology, risk factors, and prevention of CRC.
Enhanced Methane Dry Reforming with Ni/SiO2 Catalysts Featuring Hierarchical External Nanostructures
Authors: Kim Yong Jun , Kim Min-Jae , Kim Dong Hyun , Mnoyan Anush , Lee Kyubock
Published: April 2024

Global energy demand escalates the interest in effective and durable catalytic systems for the dry reforming of methane (DRM), a process that converts CO2/CH4 into H2/CO syngas. Porous silica-supported nickel (Ni) catalysts are recognized as a promising candidate due to robust DRM activity associated with the confinement of Ni particles in the mesopores that reduces the catalyst deactivation by carbon byproduct deposits and sintering of active Ni sites. However, the small-sized pore configurations in the mesoporous catalysts hinders the fast mass transfer of reactants and products. A unique combination of the hierarchical nanostructure with macro–mesoporous features of the support is adopted to enhance the catalytic performance via the dual effect of the efficient mass transfer and minimized sintering issue. This study delves into the influence of SiO2 geometry and pore structure on the catalytic performance of Ni-based catalysts. Three types of porous silica supports were synthesized through various methods: (a) hydrothermal-assisted sol–gel for dendritic mesoporous silica (DMS), (b) spray-pyrolysis-assisted sol–gel for spray evaporation-induced self-assembly (EISA) silica, and (c) oven-assisted sol–gel for oven EISA silica. Among the prepared catalysts the hierarchical external nanostructured Ni/DMS showed the superior CH4 and CO2 conversion rates (76.6% and 82.1%), even at high space velocities (GHSV = 360 L∙g−1·h−1). The distinctive macro–mesoporous geometry effectively prevents the sintering of Ni particles and promotes the smooth diffusion of the reactants and products, thus improving catalytic stability over extended reaction periods (24 h). This research highlights the significant impact of macro–mesoporosity revealed in DMS support catalysts on the physicochemical properties of Ni/DMS and their crucial role in enhancing DRM reaction efficiency.
Biodiesel Production over Banana Peel Biochar as a Sustainable Catalyst
Authors: Soares Dias Ana Paula , Pedra Igor , Salvador Érica , Rijo Bruna , Costa Pereira Manuel Francisco , Serralha Fátima , Nogueira Isabel
Published: April 2024

Biodiesel from waste frying oil was produced via methanolysis using biochar-based catalysts prepared by carbonizing banana peels (350 °C and 400 °C) mixed with 20% (wt.) of alkali carbonates (Na, Li, or K). The catalysts exhibited a bi-functional character: acidic and basic. Raman spectroscopy confirmed the alkali’s role in char graphitization, influencing morphology and oxygen content. Oxygenated surface sites acted as acidic sites for free fatty acid esterification, while alkali sites facilitated triglyceride transesterification. The best catalyst obtained by carbonization at 350 °C, without alkali modifier, led to 97.5% FAME by processing a waste frying oil with 1.2 mg KOH/g oil acidity. Most of the studied catalysts yielded high-quality glycerin, allowing the significance of homogenous catalyzed processes to be discarded.
Ethylene Oligomerization Catalyzed by Different Homogeneous or Heterogeneous Catalysts
Authors: Peng Anfeng , Huang Zheng , Li Gang
Published: April 2024

Linear α-olefins (LAOs) are linear alkenes with double bonds at the ends of the molecular chains. LAOs with different chain lengths can be widely applied in various fields. Ethylene oligomerization has become the main process for producing LAOs. In this review, different homogeneous or heterogeneous catalysts recently reported in ethylene oligomerization with Ni, Fe, Co, Cr, etc., as active centers will be discussed. In the homogeneous catalytic system, we mainly discuss the effects of the molecular structure and the electronic and coordination states of complexes on their catalytic activity and selectivity. The Ni, Fe, and Co homogeneous catalysts are discussed separately based on different ligand types, while the Cr-based homogeneous catalysts are discussed separately for ethylene trimerization, tetramerization, and non-selective oligomerization. In heterogeneous catalytic systems, we mainly concentrate on the influence of various supports (metal–organic frameworks, covalent organic frameworks, molecular sieves, etc.) and different ways to introduce active centers to affect the performance in ethylene oligomerization. Finally, a summary and outlook on ethylene oligomerization catalysts are provided based on the current research. The development of highly selective α-olefin formation processes remains a major challenge for academia and industry.
Single-Cell RNA-Sequencing Reveals Heterogeneity and Transcriptional Dynamics in Porcine Circulating CD8+ T Cells
Authors: Han Pingping , Guo Yaping , Zhang Wei , Wang Daoyuan , Wu Yalan , Li Xinyun , Zhu Mengjin
Published: April 2024

Pigs are the most important source of meat and valuable biomedical models. However, the porcine immune system, especially the heterogeneity of CD8 T cell subtypes, has not been fully characterized. Here, using single-cell RNA sequencing, we identified 14 major cell types from peripheral blood circulating cells of pigs and observed remarkable heterogeneity among CD8 T cell types. Upon re-clustering of CD8+ T cells, we defined four CD8 T cell subtypes and revealed their potential differentiation trajectories and transcriptomic differences among them. Additionally, we identified transcription factors with potential regulatory roles in maintaining CD8 T cell differentiation. The cell-cell communication analysis inferred an extensive interaction between CD8 T cells and other immune cells. Finally, cross-species analysis further identified species-specific and conserved cell types across different species. Overall, our study provides the first insight into the extensive functional heterogeneity and state transitions among porcine CD8 T cell subtypes in pig peripheral blood, complements the knowledge of porcine immunity, and enhances its potential as a biomedical model.
Frequency of Gene Polymorphisms in Admixed Venezuelan Women with Recurrent Pregnancy Loss: Microsomal Epoxy Hydroxylase (rs1051740) and Enos (rs1799983)
Authors: Peña María Johanna , De Sanctis Claudia Valentina , De Sanctis Juan Bautista , Garmendia Jenny Valentina
Published: April 2024

Recurrent pregnancy loss (RPL) affects around 2% of women of reproductive age. Primary RPL is defined by ≥2 pregnancy losses and no normal birth delivery. In secondary RPL, the losses are after a normal pregnancy and delivery. Most cases have no clear aetiology, although primary cases are the most complex. Several gene single nucleotide polymorphisms (SNPs) have been associated with RPL. The frequency of some SNPs is increased in women suffering from RLP from Asian or Caucasian races; however, in admixed populations, the information on possible genetic links is scarce and contradictory. This study aimed to assess the frequency of two SNPs present in two different enzymes involved in medical conditions observed during pregnancy. It is a case–control study. Microsomal epoxy hydrolase (mEPH) is involved in detoxifying xenobiotics, is present in the ovaries, and is hormonally regulated. The endothelial nitric oxide synthase (NOS3) that forms nitric is involved in vascular tone. Two SNPs, rs1051740 (mEPH) and rs1799983 (NOS3), were assessed. The study included 50 controls and 63 primary RPL patients. The frequency of mutated alleles in both SNPs was significantly higher in patients (p < 0.05). Double-mutated homozygotes were encountered only in RPL patients (p < 0.05). Genetic polymorphisms rs1051740 and rs1799983 may be involved in primary RPL in the Venezuelan admix population. Genetic studies could provide crucial information on the aetiology of primary RPL.
Quality of Zinc Coating Formed on Structural Steel by Hot-Dip Galvanizing after Surface Contamination
Authors: Vontorová Jiřina , Mohyla Petr , Kreislová Kateřina
Published: April 2024

This paper deals with the evaluation of the surface of structural steel whose samples were deliberately contaminated with transparent spray primer, adhesive label glue, and welding sprays prior to hot-dip galvanizing. The galvanized samples were studied by optical microscopy, GDOES, adhesion tests, and condensation humidity tests. The effect of surface contamination on the quality of the zinc coating was found to be significant. In some cases, the zinc coating is damaged (after contamination with welding sprays), in others, it is completely absent (after contamination with spray primer or adhesive label glue).
Corrosion Behavior of Hybrid Zinc Coatings Based on Chitosan and Corrosion Inhibitor BTA: Effect of the Molecular Weight and ζ-Potential
Authors: Milkova Viktoria , Boshkova Nelly , Grancharov Georgy , Stoilova Olya , Boshkov Nikolai
Published: April 2024

The creation of anticorrosion hybrid zinc-based coatings containing chitosan particles with low (LMC) or high (HMC) molecular weight is an effective method for safe and durable exploitation of different steel infrastructures. In this work, hybrid coatings consisting of zinc and two types of chitosan particles (LMC or HMC) were obtained to protect low-carbon steel from corrosion attack in a chloride environment. Chitosans with different molecular weights (CS50 Mw 50–190 kDa and CS190 Mw 190–310 kDa) have been applied. Furthermore, both particle types were prepared with or without additional content of incorporated corrosion inhibitor benzotriazole (BTA). The chitosan particles were obtained and thereafter electrodeposited in the form of hybrid coatings on mild steel substrates. The electrokinetic charge and hydrodynamic size of the particles and the stability of their aqueous suspensions were evaluated using dynamic light scattering. The concentration of BTA loaded into the particles was determined by the difference between the initial concentration of the compound added during the particle preparation and the concentration in the supernatant after centrifugation of the dispersion. The hybrid coatings were compared concerning their surface morphology, topography, and hydrophilicity (SEM and AFM analysis, water contact angle measurement) as well as corrosion and electrochemical behavior (potentiodynamic polarization curves—PD, polarization resistance—Rp, cyclic voltammetry—CVA). The protective characteristics of the coatings were studied in 5% NaCl solution. The results obtained from the PD studies demonstrated lower corrosion current densities of all hybrid coatings compared to the ordinary zinc one. In addition, the Rp tests showed enhanced protective ability and corrosion resistance of LMC and LMCB compared to the ordinary zinc, HMC, and HMCB, respectively. The obtained scientific information presented the effect of the molecular weight and ζ-potential of the particles on the anticorrosion ability of the hybrid coatings compared to the ordinary zinc one.
A Holistic Approach to Use Educational Robots for Supporting Computer Science Courses
Authors: Mamatnabiyev Zhumaniyaz , Chronis Christos , Varlamis Iraklis , Himeur Yassine , Zhaparov Meirambek
Published: April 2024

Robots are intelligent machines that are capable of autonomously performing intricate sequences of actions, with their functionality being primarily driven by computer programs and machine learning models. Educational robots are specifically designed and used for teaching and learning purposes and attain the interest of learners in gaining knowledge about science, technology, engineering, arts, and mathematics. Educational robots are widely applied in different fields of primary and secondary education, but their usage in teaching higher education subjects is limited. Even when educational robots are used in tertiary education, the use is sporadic, targets specific courses or subjects, and employs robots with narrow applicability. In this work, we propose a holistic approach to the use of educational robots in tertiary education. We demonstrate how an open source educational robot can be used by colleges, and universities in teaching multiple courses of a computer science curriculum, fostering computational and creative thinking in practice. We rely on an open-source and open design educational robot, called FOSSBot, which contains various IoT technologies for measuring data, processing it, and interacting with the physical world. Grace to its open nature, FOSSBot can be used in preparing the content and supporting learning activities for different subjects such as electronics, computer networks, artificial intelligence, computer vision, etc. To support our claim, we describe a computer science curriculum containing a wide range of computer science courses and explain how each course can be supported by providing indicative activities. The proposed one-year curriculum can be delivered at the postgraduate level, allowing computer science graduates to delve deep into Computer Science subjects. After examining related works that propose the use of robots in academic curricula we detect the gap that still exists for a curriculum that is linked to an educational robot and we present in detail each proposed course, the software libraries that can be employed for each course and the possible extensions to the open robot that will allow to further extend the curriculum with more topics or enhance it with activities. With our work, we show that by incorporating educational robots in higher education we can address this gap and provide a new ledger for boosting tertiary education.
Improved Joint Formation and Ductility during Electron-Beam Welding of Ti6Al4V and Al6082-T6 Dissimilar Alloys
Authors: Kotlarski Georgi , Kaisheva Darina , Ormanova Maria , Stoyanov Borislav , Dunchev Vladimir , Anchev Angel , Valkov Stefan
Published: April 2024

The current work is based on investigating the influence of different technological conditions of electron-beam welding on the microstructure and mechanical properties of joints between Ti6Al4V and Al6082-T6 dissimilar alloys. The plates were in all cases preheated to 300 °C. Different strategies of welding were investigated such as varying the electron-beam current/welding speed ratio (Ib/vw) and applying a beam offset towards the aluminum side. The heat input during the experiments was varied in order to guarantee full penetration of the electron beam. The macrostructure of the samples was studied, and the results indicated that using a high beam power and a high welding speed leads to an increased formation of defects within the structure of the weld seam. Utilizing a lower beam current along with a lower welding speed leads to the stabilization of the electron-beam welding process and thus to the formation of an even weld seam with next to no defects and high ductility. Using this approach gave the highest ultimate tensile strength (UTS) of 165 MPa along with a yield strength (YS) of 80 MPa and an elongation (ε) figure of 18.4%. During the investigation, improved technological conditions of electron-beam welding of Ti6Al4V and Al6082-T6 dissimilar alloys were obtained, and the results were discussed regarding possible practical applications of the suggested approach along with its scientific contribution to developing further strategies for electron-beam welding of other dissimilar alloys. The downsides and the economic effect of the presented method for welding Ti6Al4V and Al6082-T6 were also discussed.
Visceral Leishmaniasis Masquerading as Drug-Induced Pancytopenia in Lung Cancer Patients
Authors: Laroumagne Sophie , Tronchetti Julie , Dutau Hervé , Astoul Philippe
Published: April 2024

Maintenance chemotherapy is a standard treatment in patients with non-progressive advance staged IV non-squamous non-small cell lung cancer after induction therapy. Here, we report the case of a 53-year-old man undergoing a maintenance monotherapy with pemetrexed who presented prolonged pancytopenia despite filgrastim injections. A bone marrow aspiration revealed a macrophage activation syndrome with Leishmania amastigotes. A Polymerase Chest Reaction testing confirmed the diagnosis of visceral leishmaniasis. Treatment with liposomal amphotericin B was started. Oncologists should bear in mind that visceral leishmaniasis in endemic areas can potentially induce severe and prolonged pancytopenia in immunosuppressed patients, during chemotherapy in particular.
Terrestrial Tardigrada (Water Bears) of the Słowiński National Park (Northern Poland)
Authors: Bartylak Tomasz , Kayastha Pushpalata , Polishchuk Anastasiia , Roszkowska Milena , Bartylak Magdalena Maria , Rutkowski Tomasz , Zacharyasiewicz Michał , Kaczmarek Łukasz
Published: April 2024

In this paper, samples of mosses, lichens and cryptogams (mosses mixed with lichens) collected from Słowiński National Park (northern Poland) were studied for water bears (Tardigrada). In total, 27 tardigrade taxa were identified: 21 to the species level, one identified as „cf.” and three to the genus level, with six species (Eremobiotus ginevrae, Hypsibius dujardini, Hypsibius scabropygus, Milnesium beasleyi, Minibiotus intermedius and Notahypsibius pallidoides) being new records for Poland. Two possibly new for science species were also found, belonging to genera Diphascon and Mesobiotus. Additionally, a very rare eutardigrade Pseudohexapodibius degenerans has been found in the samples analyzed in the present study for the first time outside of the type locality. The effects of habitat and substrate on species richness were also investigated and showed no significant differences between mosses and lichens, as well as all substrates except for concrete walls.
The Effects of the Pericapsular Nerve Group Block on Postoperative Pain in Patients with Hip Fracture: A Multicenter Study
Authors: Iacovazzo Carmine , Sara Rosario , Buonanno Pasquale , Vargas Maria , Coviello Antonio , Punzo Roberta , Maffei Vincenzo , Marra Annachiara
Published: April 2024

Background: An adequate early mobilization followed by an effective and pain-free rehabilitation are critical for clinical and functional recovery after hip and proximal femur fracture. A multimodal approach is always recommended so as to reduce the administered dose of analgesics, drug interactions, and possible side effects. Peripheral nerve blocks should always be considered in addition to spinal or general anesthesia to prolong postoperative analgesia. The pericapsular nerve group (PENG) block appears to be a less invasive and more effective analgesia technique compared to other methods. Methods: We conducted multicenter retrospective clinical research, including 98 patients with proximal femur fracture undergoing osteosynthesis surgery within 48 h of occurrence of the fracture. Thirty minutes before performing spinal anesthesia, 49 patients underwent a femoral nerve (FN) block plus a lateral femoral cutaneous nerve (LCFN) block, and the other 49 patients received a PENG block. A non-parametric Wilcoxon–Mann–Whitney (α = 0.05) test was performed to evaluate the difference in resting and dynamic numerical rating scale (NRS) at 30 min, 6 h, 12 h, and 24 h. Results: the PENG block administration was more effective in reducing pain intensity compared to the FN block in association with the LFCN block, as seen in the resting and dynamic NRS at thirty minutes and 12 h follow-up. Conclusion: the PENG block was more effective in reducing pain intensity than the femoral nerve block associated with the lateral femoral cutaneous nerve block in patients with proximal femur fracture undergoing to osteosynthesis.
Referable Diabetic Retinopathy Prediction Algorithm Applied to a Population of 120,389 Type 2 Diabetics over 11 Years Follow-Up
Authors: Romero-Aroca Pedro , Verges Raquel , Pascual-Fontanilles Jordi , Valls Aida , Franch-Nadal Josep , Mundet Xavier , Moreno Antonio , Basora Josep , Garcia-Curto Eugeni , Baget-Bernaldiz Marc
Published: April 2024

(1) Background: Although DR screening is effective, one of its most significant problems is a lack of attendance. The aim of the present study was to demonstrate the effectiveness of our algorithm in predicting the development of any type of DR and referable DR. (2) Methods: A retrospective study with an 11-year follow-up of a population of 120,389 T2DM patients was undertaken. (3) Results: Applying the results of the algorithm showed an AUC of 0.93 (95% CI, 0.92–0.94) for any DR and 0.90 (95% CI, 0.89–0.91) for referable DR. Therefore, we achieved a promising level of agreement when applying our algorithm. (4) Conclusions: The algorithm is useful for predicting which patients may develop referable forms of DR and also any type of DR. This would allow a personalized screening plan to be drawn up for each patient.
The Gini and Mean Log Deviation Indices of Multivariate Inequality of Opportunity
Authors: Kapera Marek , Kobus Martyna
Published: April 2024

The most common approach to measuring inequality of opportunity in income is to apply the Gini inequality index or the Mean Log Deviation (MLD) index to a smoothed distribution (i.e., a distribution of type mean incomes). We show how this approach can be naturally extended to include life outcomes other than income (e.g., health, education). We propose two measures: the Gini and MLD indices of multivariate inequality of opportunity. We show that they can be decomposed into the contribution of each outcome and the dependence of the outcomes. Using these measures, we calculate inequality of opportunity in health and income across European countries.
Research on Tracking Technique Based on BPSK-CSK Signals
Authors: Chen Yuxin , Cheng Jie , Li Xiaodong , Bai Xue , Nie Zhixi
Published: April 2024

The code-shift keying (CSK) modulation method can achieve higher information transmission rates without changing the spread spectrum signal bandwidth. In order to optimise the spread spectrum modulation and demodulation of GNSS signals, in addition to the signal structure, binary phase-shift keying (BPSK) and CSK signals using time-division multiplexing are proposed. A tracking method based on the BPSK-CSK signals is also proposed, which generates the P-branch local codes by fast Fourier transform to obtain the code-slice spacings for the E-branch and the L-branch local codes. Then, the tracked BPSK signals and tracked CSK signals are compared and analysed. Finally, the bit error rate (BER) and tracking error of each method are compared and analysed by comparing with the tracking of conventional BPSK signals and tracking of CSK signals, in order to verify the convergence process of the I-branch integral value. The BPSK-CSK signal tracking method proposed in this paper combines the high information transmission rate of CSK-modulated signals and the low BER of BPSK signals, and the results provide a solid foundation for high-precision GNSS services.
Two-Phase Industrial Control System Anomaly Detection Using Communication Patterns and Deep Learning
Authors: Kim Sungjin , Jo Wooyeon , Kim Hyunjin , Choi Seokmin , Jung Da-I , Choi Hyeonho , Shon Taeshik
Published: April 2024

Several cases of Industrial Internet of Things (IIoT) attacks with zero-day vulnerabilities have been reported. To prevent these attacks, it is necessary to apply an abnormal behavior detection method; however, there are three main problems that make it hard. First, there are various industrial communication protocols. Instead of IT environments, many unstandardized protocols, which are usually defined by vendors, are used. Second, legacy devices are commonly used, not only EOS (End-of-service), but also EoL (End-of-Life). And last, the analysis of collected data is necessary for defining normal behavior. This behavior should be separately defined in each IIoT. Therefore, it is difficult to apply abnormal behavior detection in environments where economic and human investment is difficult. To solve these problems, we propose a deep learning based abnormal behavior detection technique that utilizes IIoT communication patterns. The proposed method uses a deep learning technique to train periodic data acquisition sequences, which is one of the common characteristics of IIoT. The trained model determined the sequence of packet is normal. The proposed technique can be applied without an additional analysis. The proposed method is expected to prevent security threats by proactively detecting cyberattacks. To verify the proposed method, a dataset was collected from the Korea Electric Power Control System. The model that defines normal behavior based on the application layer exhibits an accuracy of 79.6%. The other model, defining normal behavior based on the transport layer, has an accuracy of 80.9%. In these two models, most false positives and false negatives only occur when the abnormal packet is in a sequence.
Robust Embedded PID Control Software Execution Based on Automatic Malfunction Profile Feedback
Authors: Lee Sanghoon , Park Daejin
Published: April 2024

As the information technology (IT) industry advances, embedded systems are being applied in various industrial sectors. With the expansion of application areas, there is a growing demand for high-precision, high-specification embedded systems, leading to the increased complexity of embedded software. Consequently, software errors can cause system malfunctions, resulting in accidents such as airplane crashes and the sudden acceleration of cars, leading to significant loss of life and property damage. Therefore, measures to ensure the safety and stability of increasing embedded systems malfunctions are necessary. This paper proposes a system that monitors the operation of target embedded systems in real-time and compares the extracted normal operation current/voltage patterns with the current/voltage data of a target embedded system (TES). It compares the operation data of the TES with automatically generated normal operation patterns by forcibly exposing them. It suggests algorithms for immediately detecting and efficiently recovering from the TES malfunctions. The proposed system applies two algorithms. (a) Monitoring TES current: When a malfunction is detected, a monitoring embedded systme (MES) resets the TES to restore normal operation. If malfunctions persist, it controls TES by using an algorithm to shut it down. Additionally, a proportional integral derivation (PID) control is applied to stabilize the current state. (b) Monitoring TES voltage: If a voltage drop occurs, the MES immediately stops the TES operation to minimize damage. The proposed algorithms were validated through experiments. For a normal TES consuming up to 95 mA, an error detection rate of 20% was applied. The TES was reset if it consumed over 114 mA. It was confirmed that the TES was stopped upon detecting the third malfunction. Regarding voltage, when the normal operating voltage of the system was around 5 V, if the TES operating voltage dropped below 4.3 V, it was detected as a malfunction, and the algorithm to stop the TES operation was validated.
A High-Speed V-Band Distributed OOK Modulator in 65 nm CMOS
Authors: Mehmood Zubair , Seo Munkyo
Published: April 2024

This paper presents a high-speed V-band on-off keying (OOK) modulator in 65 nm CMOS based on distributed transmission lines architecture. The high-speed operation of the proposed OOK modulator is attained by distributing a single large switching transistor into smaller units. The effects of parasitic capacitances of each small switch are mitigated by series inductors, forming an artificial transmission line. The switch size and the number of stages are optimized for a reasonable balance between insertion loss and isolation. Small signal measurement of the OOK modulator reveals 3.8 dB insertion loss and 20.5 dB isolation at 60 GHz, with <5 dB insertion loss and >16 dB on-off ratio from 50 GHz to 70 GHz. Testing with a modulation setup shows the modulator is fully functional up to 5 Gbps at a 60 GHz carrier. Limitations of the test setup prevent modulation testing at >5 Gbps. The fabricated modulator does not consume any DC power and has an active footprint of 0.025 mm2.