bluuebunny/crossref_metadata_2025 huggingface dataset:
Adsorption of As and Pb by Stone Powder/Chitosan/Maghemite Composite Beads (SCM Beads): Kinetics and Column Study
Authors: Song Gunho , Oh Sanghwa
Published: February 2023

Adsorption kinetics of As and Pb onto composite beads synthesized with stone powder, chitosan, and maghemite (SCM beads) with weight ratio of 1:1:0.5 were investigated in batch mode. Several kinetic models such as pseudo-first order kinetic model (PFOKM), pseudo-second order kinetic model (PSOKM), two compartment first order kinetic model (TCFOKM), and modified two compartment first order kinetic model (MTCFOKM) were utilized to analyze the kinetics. Although the beads had low specific surface area and pore volume, MTCFOKM, one of two compartment models, could predict the most accurately because the As and Pb were adsorbed onto at least two kinds of adsorption sites such as functional groups in chitosan and Fe in maghemite. In MTCFOKM, both the fast adsorption fraction (f1’) and the fast adsorption constant (k1’) for Pb were higher than those for As. Therefore, the equilibrium time (teq) for Pb adsorption was shorter than that for As adsorption, indicating that Pb adsorption was more affinitive than As adsorption onto SCM beads (especially maghemite). Column study with a bed column reactor packed with the SCM beads was also conducted. For column study, the effect of flow rate and pore volume on removal efficiency of As and Pb was also investigated. Three models such as the Thomas, Adams-Bohart (A-B), and Yoon-Nelson (Y-N) models were used to fit the column experimental data to analyze the breakthrough curves and the saturation time. Both Thomas and Y-N models were most appropriate. Conclusively, the SCM beads are suitable for adsorption treatment of As and Pb from contaminated groundwater and are particularly effective in Pb removal.
A Review on Antimicrobial Packaging for Extending the Shelf Life of Food
Authors: Fadiji Tobi , Rashvand Mahdi , Daramola Michael O. , Iwarere Samuel A.
Published: February 2023

Food packaging systems are continually impacted by the growing demand for minimally processed foods, changing eating habits, and food safety risks. Minimally processed foods are prone to the growth of harmful microbes, compromising quality and safety. As a result, the need for improved food shelf life and protection against foodborne diseases alongside consumer preference for minimally processed foods with no or lesser synthetic additives foster the development of innovative technologies such as antimicrobial packaging. It is a form of active packaging that can release antimicrobial substances to suppress the activities of specific microorganisms, thereby improving food quality and safety during long-term storage. However, antimicrobial packaging continues to be a very challenging technology. This study highlights antimicrobial packaging concepts, providing different antimicrobial substances used in food packaging. We review various types of antimicrobial systems. Emphasis is given to the effectiveness of antimicrobial packaging in various food applications, including fresh and minimally processed fruit and vegetables and meat and dairy products. For the development of antimicrobial packaging, several approaches have been used, including the use of antimicrobial sachets inside packaging, packaging films, and coatings incorporating active antimicrobial agents. Due to their antimicrobial activity and capacity to extend food shelf life, regulate or inhibit the growth of microorganisms and ultimately reduce the potential risk of health hazards, natural antimicrobial agents are gaining significant importance and attention in developing antimicrobial packaging systems. Selecting the best antimicrobial packaging system for a particular product depends on its nature, desired shelf life, storage requirements, and legal considerations. The current review is expected to contribute to research on the potential of antimicrobial packaging to extend the shelf life of food and also serves as a good reference for food innovation information.
A Semi-Analytical Model for Gas–Water Two-Phase Productivity Prediction of Carbonate Gas Reservoirs
Authors: Chen Dayong , Sun Zheng
Published: February 2023

The productivity prediction of gas wells in carbonate gas reservoirs is greatly affected by the characteristics of gas–water two-phase flow and fracture seepage parameters. Compared with numerical simulation, the productivity prediction based on the analytical model is fast and widely used, but the traditional analytical model is fairly simplified while dealing with the nonlinear problem of the two-phase seepage equation, leading to a large discrepancy in the results of dynamic analysis. To solve this problem, this paper considers the characteristics of gas–water two-phase flow in the reservoir and fracture, uses the dual-medium model to characterize the stress sensitivity of the fracture and reservoir, and establishes a gas–water two-phase productivity prediction model for carbonate gas reservoirs. Combining the flowing material balance equation with the Newton iteration method, the nonlinear parameters of the percolation model are updated step by step with the use of average formation pressure, and the gas–water two-phase model is linearized through successive iterations to obtain the semi-analytical solution of the model. The accuracy of the model was verified using a comparison with the results of commercial numerical simulation software and field application, the gas–water two-phase productivity prediction curve was obtained, and the influence of sensitive parameters on productivity was analyzed. The results show that: (1) the semi-analytical solution method can efficiently deal with the gas–water two-phase nonlinear seepage problem and obtain the productivity prediction curve of carbonate gas wells rapidly and (2) the water production of the carbonate gas reservoir seriously affects the productivity of gas wells. During the development process, the production pressure difference should be reasonably controlled to reduce the negative impact of stress sensitivity on productivity performance.
What Is the Philosophy of Religion?: A Thomistic Account
Authors: Torre Michael D.
Published: February 2023

The article seeks to address and answer two questions: “What is Religion?” and “What is the Philosophy of Religion”? It gives a definition of the first and defends it. It places its arguments on the second in relation to a number of current textbooks on the subject, indicating that its views accord with commonly-recognized concerns, but that these deserve to be ordered a certain way. Specifically, it argues that the whole subject should rightly be divided into two parts (each with proper sub-sections): “Natural Theology” (or God as the Fullness and First Cause of Being) and the “Philosophy of Religion” (or God as Final End and Blessedness). This latter part deals with questions such as the relation of morality and religion, the definition of religion, and religious diversity, and ends with the study of the credibility of religion. For, it argues, the end of metaphysics as classically presented itself requires going beyond it to ask whether there is any credible Way to the natural human goal of being entirely happy or perfected. By rights, then, philosophy ends in seeking whether there is a credible true faith (or several), although committing to any one takes one beyond philosophy’s proper limits.
Sensitivity Deterioration of Free-Space Optical Coherent/Non-Coherent OOK Modulation Receiver by Ambient Light Noise
Authors: Ren Weijie , Sun Jianfeng , Cong Haisheng , Jiang Yuxin
Published: February 2023

In free-space optical (FSO) communication systems, on–off keying (OOK) is a widely used modulation format. Coherent and non-coherent OOK receivers with sensitivities of −54.60 dBm and −51.25 dBm, respectively, were built with a communication rate of 1 Gbit/s and a bit error rate of 10−3. In an FSO communication system, the parameters must be designed to ensure a sufficient link margin. In contrast to optical fiber systems, FSO systems have ambient light (AL) noise such as sunlight. The efficiency of sunlight coupling in the single-mode fiber (SMF) of the receivers was calculated in this study. For a signal light with AL, the change in the main components of noise and the sensitivity deterioration were theoretically analyzed and experimentally verified in conditions of coherent reception and non-coherent reception with a preamplifier. For coherent reception, the theoretical sensitivity deterioration results are consistent with the experimental results which indicate that coherent reception exhibits better anti-AL noise performance than non-coherent reception when the power spectral density of the AL is the same. Coherent and non-coherent receivers coupled with SMF can work in direct sunlight. When the receiver lens diameter is greater than 4.88 × 10−4 m, the anti-AL noise performance of the receiver can be improved by increasing the receiver lens diameter.
Hardware Accelerated Design of a Dual-Mode Refocusing Algorithm for SAR Imaging Systems
Authors: Yu Le , Li Yaqi , Wu Nansong
Published: February 2023

The use of satellite synthetic aperture radar (SAR) for moving target imaging has gained popularity recently. Researchers are focused on improving its imaging quality. To achieve high-quality and fast imaging, we have developed a dual-mode refocusing algorithm. We optimized the algorithm’s target speed estimation and carried out data enhancement and quantization design for SAR image refocusing. The design is implemented on a Xilinx XC5VFX130T FPGA. The dual-mode image data are based on a slice size of 512 × 512 for slice mode and 256 × 256 for scan mode in a time-series function simulation. The serial–parallel conversion and pipeline design balances the operating speed and logic resources for optimal performance. Experiment results on slice data of real SAR images show that the system’s processing speed can reach two frames per second, utilizing 69633 LUTs, 255 RAMs, and 296 DSPs.
Machine Learning Models Using SHapley Additive exPlanation for Fire Risk Assessment Mode and Effects Analysis of Stadiums
Authors: Lu Ying , Fan Xiaopeng , Zhang Yi , Wang Yong , Jiang Xuepeng
Published: February 2023

Machine learning methods can establish complex nonlinear relationships between input and response variables for stadium fire risk assessment. However, the output of machine learning models is considered very difficult due to their complex “black box” structure, which hinders their application in stadium fire risk assessment. The SHapley Additive exPlanations (SHAP) method makes a local approximation to the predictions of any regression or classification model so as to be faithful and interpretable, and assigns significant values (SHAP value) to each input variable for a given prediction. In this study, we designed an indicator attribute threshold interval to classify and quantify different fire risk category data, and then used a random forest model combined with SHAP strategy in order to establish a stadium fire risk assessment model. The main objective is to analyze the impact analysis of each risk characteristic on four different risk assessment models, so as to find the complex nonlinear relationship between risk characteristics and stadium fire risk. This helps managers to be able to make appropriate fire safety management and smart decisions before an incident occurs and in a targeted manner to reduce the incidence of fires. The experimental results show that the established interpretable random forest model provides 83% accuracy, 86% precision, and 85% recall for the stadium fire risk test dataset. The study also shows that the low level of data makes it difficult to identify the range of decision boundaries for Critical mode and Hazardous mode.
Skeleton-Based Fall Detection with Multiple Inertial Sensors Using Spatial-Temporal Graph Convolutional Networks
Authors: Yan Jianjun , Wang Xueqiang , Shi Jiangtao , Hu Shuai
Published: February 2023

The application of wearable devices for fall detection has been the focus of much research over the past few years. One of the most common problems in established fall detection systems is the large number of false positives in the recognition schemes. In this paper, to make full use of the dependence between human joints and improve the accuracy and reliability of fall detection, a fall-recognition method based on the skeleton and spatial-temporal graph convolutional networks (ST-GCN) was proposed, using the human motion data of body joints acquired by inertial measurement units (IMUs). Firstly, the motion data of five inertial sensors were extracted from the UP-Fall dataset and a human skeleton model for fall detection was established through the natural connection relationship of body joints; after that, the ST-GCN-based fall-detection model was established to extract the motion features of human falls and the activities of daily living (ADLs) at the spatial and temporal scales for fall detection; then, the influence of two hyperparameters and window size on the algorithm performance was discussed; finally, the recognition results of ST-GCN were also compared with those of MLP, CNN, RNN, LSTM, TCN, TST, and MiniRocket. The experimental results showed that the ST-GCN fall-detection model outperformed the other seven algorithms in terms of accuracy, precision, recall, and F1-score. This study provides a new method for IMU-based fall detection, which has the reference significance for improving the accuracy and robustness of fall detection.
Analytical Applicability of Graphene-Modified Electrode in Sunset Yellow Electrochemical Assay
Authors: Măgeruşan Lidia , Pogăcean Florina , Cozar Bogdan Ionuţ , Pruneanu Stela
Published: February 2023

Due to the recent increase in average living standards, food safety has caught public attention. It is necessary to conduct a qualitative and quantitative rapid test of prohibited food additives since the inclusion of food additives or the improper usage of synthetic dyes can negatively impact on the human health. Herein, a highly sensitive method for Sunset Yellow detection based on a glassy carbon electrode modified with few-layer graphenes was proposed. The electrochemical behavior of SY at the GR-exf/GCE modified surface was investigated by Cyclic Voltammetry, Square Wave Voltammetry, Electrochemical Impedance Spectroscopy and Amperometry. The influences of pH, scan rate, and interfering species were studied. Under optimized conditions, the developed sensor shows good linearity over a broad SY concentration range, e.g., 0.028–30 µM, with a low limit of detection (LOD = 0.0085 µM) and quantification (LOQ = 0.028 µM) (data obtained by amperometric technique). Furthermore, the modified electrode shows good selectivity, precision and sensitivity and has been successfully applied for SY quantification from commercially available pharmaceutical formulation as well as from candy bars and orange juice.
Determination of Anthracene Derivatives in Baltic Amber Using SERS
Authors: Kundalevich Anna , Zyubin Andrey , Matveeva Karina , Samusev Ilia , Lyatun Ivan
Published: February 2023

The article describes the results of Raman spectroscopy and SERS for the study of fluorescent components of Baltic amber via the extraction method. Using SERS, it was possible to confirm the presence of anthracene derivatives in amber: tetracene and benzanthracene. It has been shown that SERS methods are effective for the detection of aromatic compounds; they increase the registered Raman signal and make it possible to identify peaks characteristic of the compounds under study. By combining experimental methods with DFT simulations, anthracene derivatives were modeled and confirmed to be present in the structure of Baltic amber. A combination of the proposed methods can be used to distinguish between different types of amber and isolate the necessary amber components. The obtained results are promising for compiling spectral maps of ambers for their possible classification by their place of origin.
Residual Creep Life Assessment of High-Temperature Components in Power Industry
Authors: Pivdiablyk Ivanna , Di Goh Zhu , Chye Liam Kok , Shandro Robert , Lefebvre Fabien
Published: February 2023

A large percentage of power, petroleum, and chemical plants over the world were in operation for a long duration with the corresponding critical components being used beyond the design life of 30 to 40 years. It is generally more cost-effective to refurbish or modernize the degraded equipment or components, rather than to construct a new plant. Therefore, a reliable plant life extension assessment that can evaluate the critical components is needed. The key element in plant life extension is the residual life assessment technology. However, at present, there is still no general consensus among the industry players on the approach to adopt when performing residual life assessment for such a critical damage mechanism as creep. In this article, a three-level residual life assessment methodology is proposed as a general approach for high-temperature components prone to creep. A detailed validation of the selected guidelines and calculation models is also described. Eventually, an application of the three-level methodology to a real industrial case study is presented.
Using Mobile Edge AI to Detect and Map Diseases in Citrus Orchards
Authors: da Silva Jonathan C. F. , Silva Mateus Coelho , Luz Eduardo J. S. , Delabrida Saul , Oliveira Ricardo A. R.
Published: February 2023

Deep Learning models have presented promising results when applied to Agriculture 4.0. Among other applications, these models can be used in disease detection and fruit counting. Deep Learning models usually have many layers in the architecture and millions of parameters. This aspect hinders the use of Deep Learning on mobile devices as they require a large amount of processing power for inference. In addition, the lack of high-quality Internet connectivity in the field impedes the usage of cloud computing, pushing the processing towards edge devices. This work describes the proposal of an edge AI application to detect and map diseases in citrus orchards. The proposed system has low computational demand, enabling the use of low-footprint models for both detection and classification tasks. We initially compared AI algorithms to detect fruits on trees. Specifically, we analyzed and compared YOLO and Faster R-CNN. Then, we studied lean AI models to perform the classification task. In this context, we tested and compared the performance of MobileNetV2, EfficientNetV2-B0, and NASNet-Mobile. In the detection task, YOLO and Faster R-CNN had similar AI performance metrics, but YOLO was significantly faster. In the image classification task, MobileNetMobileV2 and EfficientNetV2-B0 obtained an accuracy of 100%, while NASNet-Mobile had a 98% performance. As for the timing performance, MobileNetV2 and EfficientNetV2-B0 were the best candidates, while NASNet-Mobile was significantly worse. Furthermore, MobileNetV2 had a 10% better performance than EfficientNetV2-B0. Finally, we provide a method to evaluate the results from these algorithms towards describing the disease spread using statistical parametric models and a genetic algorithm to perform the parameters’ regression. With these results, we validated the proposed pipeline, enabling the usage of adequate AI models to develop a mobile edge AI solution.
Failure Identification Using Model-Implemented Fault Injection with Domain Knowledge-Guided Reinforcement Learning
Authors: Moradi Mehrdad , Van Acker Bert , Denil Joachim
Published: February 2023

The safety assessment of cyber-physical systems (CPSs) requires tremendous effort, as the complexity of cyber-physical systems is increasing. A well-known approach for the safety assessment of CPSs is fault injection (FI). The goal of fault injection is to find a catastrophic fault that can cause the system to fail by injecting faults into it. These catastrophic faults are less likely to occur, and finding them requires tremendous labor and cost. In this study, we propose a reinforcement learning (RL)-based method to automatically configure faults in the system under test and to find catastrophic faults in the early stage of system development at the model level. The proposed method provides a guideline to utilize high-level domain knowledge about a system model for constructing the reinforcement learning agent and fault injection setup. In this study, we used the system (safety) specification to shape the reward function in the reinforcement learning agent. The reinforcement learning agent dynamically interacted with the model under test to identify catastrophic faults. We compared the proposed method with random-based fault injection in two case studies using MATLAB/Simulink. Our proposed method outperformed random-based fault injection in terms of the severity and number of faults found.
The Great Wall Vibration Monitoring of Traffic and Natural Hazards Using MEMS Accelerometers
Authors: Wang Jian , Liu Xu , Liu Fei , Chen Cai , Tang Yuyang
Published: February 2023

The stability of the Great Wall is mainly affected by traffic vibrations and natural hazards, such as strong winds, heavy rainfall, and thunderstorms, which are extremely harmful to the safety of the Great Wall. To determine the impact of the above factors on the Great Wall, a comparative analysis based on MEMS (micro-electro-mechanical system) accelerometer data was conducted between the non-impacts and the impacts of the above factors. An analysis of the relationship between vibration acceleration and each potential hazard based on a visual time series chart was presented using the data of accelerometers, traffic video, meteorology, rainfall, and wind. According to the results, traffic vibration is one of the primary dangerous factors affecting the stability of the Great Wall, Moreover, the intensity of the vibrations increases with the traffic flow. Thunderstorms also influence the stability of the Great Wall, with enhanced thunderstorm excitation resulting in increased vibration displacement. Furthermore, wind load is an influencing factor, with average wind speeds greater than 9 m/s significantly affecting the stability of the Great Wall. Rainfall has no impact on the stability of the Great Wall in the short term. This research can provide important guidance for risk assessment and protection of the Great Wall.
Constant Force-Tracking Control Based on Deep Reinforcement Learning in Dynamic Auscultation Environment
Authors: Zhang Tieyi , Chen Chao , Shu Minglei , Wang Ruotong , Di Chong , Li Gang
Published: February 2023

Intelligent medical robots can effectively help doctors carry out a series of medical diagnoses and auxiliary treatments and alleviate the current shortage of social personnel. Therefore, this paper investigates how to use deep reinforcement learning to solve dynamic medical auscultation tasks. We propose a constant force-tracking control method for dynamic environments and a modeling method that satisfies physical characteristics to simulate the dynamic breathing process and design an optimal reward function for the task of achieving efficient learning of the control strategy. We have carried out a large number of simulation experiments, and the error between the tracking of normal force and expected force is basically within ±0.5 N. The control strategy is tested in a real environment. The preliminary results show that the control strategy performs well in the constant force-tracking of medical auscultation tasks. The contact force is always within a safe and stable range, and the average contact force is about 5.2 N.
Estimation of the Acoustic Transducer Beam Aperture by Using the Geometric Backscattering Model for Side-Scan Sonar Systems
Authors: Nguyen Van Duc , Luu Ngoc Minh , Nguyen Quoc Khuong , Nguyen Tien-Dung
Published: February 2023

In this paper, we propose an algorithm for estimating the beam aperture of the acoustic transducers by using the geometric backscattering model for side-scan sonar systems. The geometric backscattering model is developed to describe the propagation paths of the signal transmitted from the transducers towards the seabed and backscatters to the hydrophones. To evaluate our proposed algorithm, we have developed a side-scan sonar system. The side-scan sonar system uses two transducers, operating on two different frequencies and focusing on two different wave beams, to scan the images of the seabed. The proposed algorithm provides the estimated beam apertures of each transducer. Our obtained results agree quite well with the parameters provided by the manufacturers. Moreover, these results are used to calibrate the scanned images. We provide the scanned sonar 3D images of the Dong Do lakebed, Vietnam, to justify our proposal.
Industry 4.0: Options for Human-Oriented Work Design
Authors: Hirsch-Kreinsen Hartmut
Published: February 2023

This contribution deals with the diffusion of Industry 4.0 technologies and their consequences for work. Additionally, design options for work in Industry 4.0 are discussed. The following are outlined: First, since there are as yet no concrete future prospects for digital work, different development perspectives can be envisioned. Second, the development of Industry 4.0, therefore, has to be regarded as a design project. One theoretical basis for this is the “sociotechnical systems” approach. Third, this approach enables criteria for the design and implementation of human-oriented forms of digitized work to be systematically developed. The empirical basis of this contribution derives from research findings on the implementation of Industry 4.0 technologies and the development of digitized work in German industry. The research results are based on qualitative research methods such as company case studies and expert interviews.
The Vulnerability of Young Refugees Living in Reception Centres in Luxembourg: An Overview of Conditions and Experiences across Subjective Temporal Imaginaries
Authors: Gilodi Amalia , Richard Catherine , Albert Isabelle , Nienaber Birte
Published: February 2023

Vulnerability has become a key concept in discourses and policies on international protection and reception of refugees. In this context, the notion has been described as a tool to provide special provisions to groups at higher risk or one to perpetuate political agendas within increasingly hostile reception systems. However, vulnerability as an analytical concept has received less attention, with both policymakers and scholars often employing different conceptualisations of vulnerability or treating it as a self-explanatory condition. Building on a previous conceptual elaboration, this paper sets out to apply an understanding of vulnerability as multi-layered, dynamic and embedded in a study of the lived experiences of a group of potentially ‘vulnerable’ migrants, based on ‘fixed’ contextual criteria. Drawing from in-depth interviews with young adults who obtained refugee status in Luxembourg but still live in ‘temporary’ reception centres, this paper provides a wide analytical overview of the conditions of vulnerability encountered by this specific group of migrants, in the process of building their lives in a new country. Following the participants’ subjective temporal imaginaries of past, present and future, the analysis highlights and problematises conditions of structural, situational and experiential vulnerability emerging from their accounts and experiences, and discusses their possible implications.
Zat12 Gene Ameliorates Temperature Stress in Wheat Transgenics by Modulating the Antioxidant Defense System
Authors: Kaur Manpreet , Asthir Bavita , Kaur Ramandeep , Chaudhary Ankur
Published: February 2023

The present study was undertaken with the objective to reconnoiter the role of Zat12-related biochemical activities in temperature stress tolerance in wheat transgenic lines Z-8-12 1A, Z-8-12 1B, Z-8-19, and Z-15-10, which were produced by transforming wheat-cultivar PBW 621. Zat12 transgenics (ZT) along with non-transgenic (NT) wheat cultivars (PBW 621, PBW, 550, and HD 3086) were assessed at the three-weeks seedling stage under chilling (−2 °C and −4 °C) and heat (30 °C and 32 °C) stress. Specific activities of superoxide dismutase (SOD), peroxidase (POD), ascorbate peroxidase (APX), glutathione-S-transferase (GST), glutathione reductase (GR), and antioxidants (proline and ascorbate) were profoundly increased under temperature stress in ZT related to NT. However, under −4 °C and 32 °C, a significantly higher increase was reported. In contrast, H2O2 and MDA were found to be much lower in ZT than in NT. Similarly, lesser decreases in length, fresh weight, and dry weight of seedlings were reported in ZT at 30 °C and 32 °C. RT-PCR studies revealed the enhanced expression of Zat12 in the roots of seedlings at the 5, 10, and 14 days after germination (DAG) stages in ZT under the stress conditions. Upregulation of the antioxidant defense system in ZT and their better tolerance depict an alternative for wheat cultivation under temperature stress-prone areas.
Effect of Social Presence toward Livestream E-Commerce on Consumers’ Purchase Intention
Authors: Chen Li-Ru , Chen Farn-Shing , Chen Der-Fa
Published: February 2023

The booming development of livestream e-commerce has attracted considerable academic attention, but research on how social presence affects consumers’ purchase decisions is limited. To this end, this article proposed a theoretical framework for the influence of social presence on consumers’ purchasing decisions based on social presence theory. In this study, structural equation modeling was carried out on 390 data collected from a questionnaire to verify the mechanisms by which social presence influences purchase intention. The study found that social presence enhances consumer identification, which in turn enhances consumers’ purchase intention. Meanwhile, this study not only verified the mediating role of consumer identification but also tested the positive moderating role of self-improvement by livestream e-commerce. This study found that a live streaming host’s social presence influences the consumers’ purchase behavior, and it provides decision support for companies to sell products through livestreaming platforms, which has important theoretical significance and practical application value.
The Ascending Ramsey Index of a Graph
Authors: Chartrand Gary , Zhang Ping
Published: February 2023

Let G be a graph with a given red-blue coloring c of the edges of G. An ascending Ramsey sequence in G with respect to c is a sequence G1, G2, …, Gk of pairwise edge-disjoint subgraphs of G such that each subgraph Gi (1≤i≤k) is monochromatic and Gi is isomorphic to a proper subgraph of Gi+1 (1≤i≤k−1). The ascending Ramsey index ARc(G) of G with respect to c is the maximum length of an ascending Ramsey sequence in G with respect to c. The ascending Ramsey index AR(G) of G is the minimum value of ARc(G) among all red-blue colorings c of G. It is shown that there is a connection between this concept and set partitions. The ascending Ramsey index is investigated for some classes of highly symmetric graphs such as complete graphs, matchings, stars, graphs consisting of a matching and a star, and certain double stars.
Diagnostic Performance of Dengue NS1 and Antibodies by Serum Concentration Technique
Authors: Luvira Viravarn , Thawornkuno Charin , Lawpoolsri Saranath , Thippornchai Narin , Duangdee Chatnapa , Ngamprasertchai Thundon , Leaungwutiwong Pornsawan
Published: February 2023

Dengue infection has been a public health problem worldwide, especially in tropical areas. A lack of sensitive diagnostic methods in the early phase of the illness is one of the challenging problems in clinical practices. We, herein, analyzed 86 sera of acute febrile patients, from both dengue and non-dengue febrile illness, to study the diagnostic performance of dengue diagnostics. When compared with detection by Polymerase Chain Reaction (PCR), dengue NS1 detection by enzyme-linked immunosorbent assay (ELISA) had the highest sensitivity of 82.4% (with 94.3% specificity), while NS1 by rapid diagnostic test (RDT) had 76.5% sensitivity. IgM detection by ELISA and RDT showed only 27.5% and 17.9% sensitivity, respectively. The combination of NS1 and IgM in RDT yielded a sensitivity of 78.4%, with 97.1% specificity. One of the essential steps in making a diagnosis from patient samples is the preparation process. At present, a variety of techniques have been used to increase the number of analytes in clinical samples. In this study, we focused on the sample concentration method. The sera were concentrated three times with the ultrafiltration method using a 10 kDa molecular weight cut-off membrane. The results showed an increase in the sensitivity of RDT-NS1 detection at 80.4%, with 100% specificity. When combining NS1 and IgM detection, the concentration method granted RDT an 82.4% sensitivity, with 100% specificity. In conclusion, serum concentration by the ultrafiltration method is a simple and applicable technique. It could increase the diagnostic performance of point-of-care dengue diagnostics.
Impact of COVID-19 Pandemic on Seroprevalence of HIV, HBV, HCV and HTLV I-II in a Blood Bank in Medellín, Colombia, 2019–2022
Authors: Cardona-Arias Jaiberth Antonio , Higuita-Gutiérrez Luis Felipe
Published: February 2023

The objective of this research was to analyze the impact of the COVID-19 pandemic on seroprevalence of HIV, HBV, HCV and HTLV I-II in donors from a blood bank in Medellin, Colombia, 2019–2022. A cross-sectional analytical study was carried out with three groups: pre-pandemic with 14,879 donors; preventive isolation with 9035; and selective isolation + new normality with 26,647 subjects. Comparisons were made with Chi2 and Bonferroni adjustment, Kruskal–Wallis’ H with Dunnett’s post-hoc, prevalence ratios, and multivariate logistic regression. COVID-19 decreased donations of men, altruistic and repetitive donors, and increased the age of donors. HIV increased with the COVID-19 pandemic, while HBV, HCV, and HTLV I-II decreased. The pandemic had an independent effect on these viral infections. These findings constitute an alert about what may be happening in the general population and show the importance of improving epidemiological surveillance and the investigation of these infections.
Diagnostic Accuracy of a Thick Blood Smear Compared to qPCR for Malaria Associated with Pregnancy in Colombia
Authors: Cardona-Arias Jaiberth Antonio , Higuita Gutiérrez Luis Felipe , Carmona-Fonseca Jaime
Published: February 2023

This study aimed to evaluate the accuracy of the thick blood smear (TBS) versus quantitative polymerase chain reaction (qPCR) for the diagnosis of malaria associated with pregnancy (MAP) caused by P. falciparum or P. vivax in Colombia in its gestational malaria (GM), placental malaria (PM), and congenital malaria (CM) forms as well as to compare its accuracy in different subgroups of pregnant women according to the presence of fever, anemia and a history of malaria. This was a diagnostic evaluation of 829 pregnant women, 579 placentas, 381 umbilical cord samples, and 221 neonatal peripheral blood samples. Accuracy was evaluated based on the parameters of sensitivity, specificity, predictive values, likelihood ratios, and validity index, with their 95% confidence intervals. The frequency of GM was 36% (n = 297/829), PM 27% (n = 159/579), and CM 16.5% (n = 63/381) in umbilical cord samples and 2% (n = 5/221) in neonatal peripheral blood samples. For GM, the sensitivity was 55%, with higher rates in those infected with P. vivax (68%), with a history of malaria (69%), and with fever (96%). These three subgroups presented the best results in terms of the negative likelihood ratio and validity index. For PM, sensitivity was 8%; in subgroup analyses in terms of species, symptomatology (anemia and fever), and history of malaria, it was 1–18%, and the negative likelihood ratio was >0.80 in all subgroups. No false positives were recorded in any of the subgroups. The TBS did not detect any cases of CM. This study found the TBS yielded satisfactory results in terms of diagnosing GM for P. vivax, pregnant women with previous malaria and febrile. It also showed that the TBS is not useful for diagnosing PM and CM. It is necessary to conduct surveillance of MAP with molecular methods in in groups where TBS is deficient (asymptomatic GM, P. falciparum, and pregnant women without history of malaria) to optimize the timely treatment of PM and CM, avoid the deleterious effects of MAP and achieve the malaria elimination goals in Colombia.
The Current Distribution of Oncomelania hupensis Snails in the People’s Republic of China Based on a Nationwide Survey
Authors: Lv Chao , Li Yin-Long , Deng Wang-Ping , Bao Zi-Ping , Xu Jing , Lv Shan , Li Shi-Zhu , Zhou Xiao-Nong
Published: February 2023

Schistosomiasis is a helminth infection caused by the genus Schistosoma, which is still a threat in tropical and sub-tropical areas. In the China, schistosomiasis caused by Schistosoma japonicum is mainly endemic to the Yangtze River valley. The amphibious snail Oncomelania hupensis (O. hupensis) is the unique intermediate host of S. japonicum; hence, snail control is a crucial approach in the process of schistosomiasis transmission control and elimination. In 2016, a nationwide snail survey was conducted involving all snail habitats recorded since 1950 in all endemic counties of 12 provinces. A total of 53,254 existing snail habitats (ESHs) were identified, presenting three clusters in Sichuan Basin, Dongting Lake, and Poyang Lake. The overall habitat area was 5.24 billion m2, of which 3.58 billion m2 were inhabited by O. hupensis. The area inhabited by snails (AIS) in Dongting and Poyang Lakes accounted for 76.53% of the population in the country. Three typical landscape types (marshland and lakes, mountains and hills, and plain water networks) existed in endemic areas, and marshland and lakes had a predominant share (3.38 billion m2) of the AIS. Among the 12 endemic provinces, Hunan had a share of nearly 50% of AIS, whereas Guangdong had no ESH. Ditches, dryland, paddy fields, marshland, and ponds are common habitat types of the ESH. Although the AIS of the marshland type accounted for 87.22% of the population in the whole country, ditches were the most common type (35,025 or 65.77%) of habitat. Six categories of vegetation for ESHs were identified. A total of 39,139 habitats were covered with weeds, accounting for 55.26% of the coverage of the area. Multiple vegetation types of snail habitats appeared in the 11 provinces, but one or two of these were mainly dominant. Systematic sampling showed that the presence of living snails was 17.88% among the 13.5 million sampling frames. The occurrence varied significantly by landscape, environment, and vegetation type. The median density of living snails in habitats was 0.50 per frame (0.33 m × 0.33 m), and the highest density was 40.01 per frame. Furthermore, two main clusters with high snail densities and spatial correlations indicated by hotspot analysis were identified: one in Hunan and Hubei, the other in Sichuan. This national survey is the first full-scale census on the distribution of O. hupensis, which is significant, as transmission interruption and elimination are truly becoming the immediate goal of schistosomiasis control in China. The study discerns the detailed geographic distribution of O. hupensis with the hotspots of snail density in China. It is beneficial to understand the status of the snail population in order to finally formulate further national control planning.
Possible Scenarios for a Micro-Watershed Based on Level of Urbanization: Using Flood Design to Advance Ecohydrological Principles
Authors: Campos-Delgado David , Ramos-Palacios Carlos , Cisneros-Vidales Alicia , Algara-Siller Marcos
Published: February 2023

Traditional urban schemes that incorporate extended impervious areas can increase surface run-off. Therefore, urban growth that considers eco-hydrological principles can foster sustainability in cities. This work projected three possible urban development patterns for San Luis Potosi’s micro-watershed, characterized by flood design estimations and different urban densities considerations. The selected micro-watershed is located in the western periphery of the city, which is in the process of being urbanized. As the study site is in a semi-arid region where data are scarce, this research used the rational method and the software Rhinoceros for modeling urban scenarios. Models included criteria that allow for comparing a traditional urbanization perspective of what is expected (without green areas) with alternatives that consider green areas as well as different urban densities and that favor eco-hydrological principles. The high urban-density (green area) scenario shows a sustainable alternative for the micro-watershed by which eco-hydrological principles are fostered, as well as an alternative to high urban density without undermining real-estate profitability. Although calculations could be strengthened by using more local data, the results provide insights for urban planners and developers on the sustainable transformation of the micro-watershed.
Surgical Protocols before and after COVID-19—A Narrative Review
Authors: Shivkumar Sahana , Mehta Vini , Vaddamanu Sunil Kumar , Shetty Urvashi A. , Alhamoudi Fahad Hussain , Alwadi Maram Ali M. , Aldosari Lujain Ibrahim N. , Alshadidi Abdulkhaliq Ali F. , Minervini Giuseppe
Published: February 2023

The COVID-19 epidemic has affected not only people’s daily lives but also the working methods of clinicians, surgical procedures, open/minimally invasive procedures, operating room management, patient and healthcare worker safety, education and training. The main objective of this study was to review selected articles and determine the changes in the general surgery protocols/procedures before and after the emergence of the COVID-19 pandemic. The literature was carried out in PubMed-Medline, Cochrane Library, Embase, Scopus and Google Scholar. The terms utilised for the searches were “SARS-CoV-2”, “Surgery”, “COVID-19”, “Surgical protocol”, “Surgical recommendations” and “before and after”. A total of 236 studies were identified, out of which 41 studies were included for data extraction. Significant changes in all the articles were observed with respect to the surgeries done before, during and after the COVID-19 pandemic. Specifically, the number of elective surgeries were considerably fewer in comparison to the pre-pandemic period. Since the COVID-19 pandemic started, hospitals all throughout the world have conducted significantly fewer procedures, particularly elective/non-urgent surgeries.
Analysis of Antibodies Induced after SARS-CoV-2 Vaccination Using Antigen Coded Bead Array Luminex Technology
Authors: Song Zixuan , Luo Qizhi , Wan Ling , Zhu Quan , Liu Rongjiao , Yin Xiangli , Lu Xiaofang , Wei Leiyan , Xiang Zhiqing , Zou Yizhou
Published: February 2023

Objectives. Since the outbreak of SARS-CoV-2 in late 2019, nearly 12.2 billion doses of the COVID-19 vaccine have been administered worldwide; however, the humoral immune responses induced by different types of vaccines are yet to be fully validated. Methods. We analyzed antibody levels in 100 serum samples after vaccination with different types of COVID-19 vaccines and their reactivity against the RBD antigen of Delta and Omicron variants using a bead-based microarray. Results. Elevated levels of anti-wild-type (WT)-RBD IgG and anti-WT-NP IgG were detected in participants who received two doses of the inactivated vaccines (CoronaVac or BBIBP-CorV) and three doses of the recombinant spike protein vaccine (ZF2001), indicating that antibody responses to SARS-CoV-2 were generated regardless of the vaccine administered. We found highly correlated levels of serum anti-RBD IgG and anti-NP IgG (r = 0.432, p < 0.001). We observed that the antibodies produced in vivo after COVID-19 vaccination still reacted with variants of SARS-CoV-2 (p < 0.0001). Conclusions. Our results show that high levels of specific antibodies can be produced after completion of COVID-19 vaccination (two doses of the inactivated vaccines or three doses of ZF2001), with some degree of cross-reactivity to the RBD antigen of Delta and Omicron variants, and provide an accessible and practical experimental method for post-vaccination antibody detection.
A Case Series and Literature Review of Telogen Effluvium and Alopecia Universalis after the Administration of a Heterologous COVID-19 Vaccine Scheme
Authors: Hernández Arroyo Jenny , Izquierdo-Condoy Juan S. , Ortiz-Prado Esteban
Published: February 2023

COVID-19 vaccines have positively changed the course of the pandemic. They entered the market after only one year of the initial trials, which that yielded positive results in terms of safety and efficacy. However, after inoculating billions of people in the most extensive vaccination campaign worldwide, mild but common and some rare but potentially fatal adverse events have been reported. Among several self-reported adverse events, hair loss and alopecia have been linked to COVID-19 mRNA or viral vector vaccines. We tracked and followed a series of five cases with post-vaccine telogen effluvium and alopecia development in Ecuador. Here, we reported the clinical presentation of two women and three men with the diagnosis of post-vaccine hair loss. All patients received a heterologous vaccination scheme (mRNA and attenuated virus vaccine) with an additional viral vector booster associated with the apparition of telogen effluvium and alopecia universalis between 3 and 17 days after the vaccine was administered.
Neutralizing Antibodies as Predictors of Vaccine Breakthrough Infection in Healthcare Workers Vaccinated with or without a Heterologous Booster Dose: A Cohort Study during the Third COVID-19 Wave in Peru
Authors: Hueda-Zavaleta Miguel , Gómez de la Torre Juan C. , Cáceres-DelAguila José Alonso , Muro-Rojo Cecilia , De La Cruz-Escurra Nathalia , Copaja-Corzo Cesar , Aragón-Ayala Carlos J. , Benítes-Zapata Vicente A.
Published: February 2023

We evaluated neutralizing antibody (NAbs) levels as a protective factor against vaccine breakthrough infection (VBI) in healthcare workers (HCWs) during the third COVID-19 wave in Peru. This retrospective cohort study employed the information from a private laboratory in Lima (Peru) of HCW who received only two BBIBP-CorV vaccines or (additionally) a heterologous booster with BNT162b2. We evaluated the association between the VBI and the levels of NAbs at 21, 90, 180, and 210 days after the BBIBP-CorV second dose. NAbs were calculated with the cPass™ SARS-CoV-2 Neutralization Antibody Detection kit (surrogate virus neutralization test (sVNT)) and the Elecsys® anti-SARS-CoV-2 S Test. Of the 435 HCW evaluated, 31.72% had an infection previous to vaccination, 68.28% received a booster dose, and 23.21% had a VBI during the third wave. The variables associated with a lower risk of VBI were male sex (aRR: 0.43) and those who had (180 days after BBIBP-CorV inoculation) NAbs levels ≥ 60% (aRR: 0.58) and ≥90% (aRR: 0.59) on cPass™, and ≥500 with Elecsys® (aRR: 0.58). HCW whose NAbs persisted at higher levels six months after the BBIBP-CorV showed a lower risk of suffering from a VBI during the third COVID-19 wave.