bluuebunny/crossref_metadata_2025 huggingface dataset:
Use of Biomass Ash in Reinforced Clayey Soil: A Multiscale Analysis of Solid-State Reactions
Authors: Fastelli Maximiliano , Cambi Costanza , Zucchini Azzurra , Sassi Paola , Pandolfi Balbi Elia , Pioppi Leonardo , Cotana Franco , Cavalaglio Gianluca , Comodi Paola
Published: December 2022

Clayey soils are treated with binding agents to improve their mechanical properties, as these soils are widely used in construction. The production of binding agents is an energy-intensive process and emits significant amounts of CO2. In addition, the interest in recycling industry waste materials has increased, and the management of significant waste from biomass power plants remains an issue. We used three biomass ashes derived from pellet, olive, and grapevine combustion as stabilizing agents of a clayey soil. The mechanical effects of the treatment on clay-ash mixtures were evaluated using confined compressive tests. The mixtures’ chemo-mineralogical evolution was evaluated through X-ray powder diffraction and quantitative Rietveld analysis, Fourier transform infrared spectroscopy (FT-IR), and energy-dispersive X-ray spectroscopy coupled with scanning electron microscopy (EDS-SEM). The FT-IR spectra showed an evolution of the Si-O-Si/Al features, with shifting band positions due to polymerization of the tetrahedral units. The EDS-SEM analysis showed an evolution of the Ca/Si distribution and the growth of pozzolanic reaction products, such as C-S-H nanocrystals and gels. This evidence confirms that the pozzolanic reaction occurs by dissolution of clay minerals and/or the amorphous phase of the ash, which affects the macroscopic behavior of clayey soils in terms of stiffening and strengthening, as confirmed by mechanical tests, albeit these effects are non-homogenous and continuous.
Materialized Wishes: Long Banner Paintings from the Mogao Caves of Dunhuang
Authors: Hwang Yoonah
Published: December 2022

This paper explores the religious function and meaning of long banner paintings from Cave 17 of the Mogao Caves in Dunhuang, in conjunction with material culture in Northwestern China in the ninth and tenth centuries CE. The so-called forty-nine-chi banners have peculiar traits such as extremely long lengths, an optional triangular headpiece, and a paired or single strip of textile on which a series of standing bodhisattvas are painted. The author focuses on the large number of textiles used for such banners and questions how the extraordinary length and material used contributed to fulfilling the donor’s wishes. By examining both the banners’ physical characteristics, such as the type of textiles, pigments, and configurations, and the theological background based on the Buddhist and Daoist scriptures about longevity, repentance, and healing, the author suggests that the long banners are a materialized form of longevity and prosperity by physically lengthening the banner with multiple bolts of silk. This paper further argues that depicting multiple bodhisattvas in a pictorial form on a long strip of textile was regarded equally as a powerful means for obtaining good health, prolonging life, eliminating sins, and thus being reborn in the Pure Land.
Plasmapheresis in Neonatal Lupus
Authors: Sharobim Mark , Scribner Angelica S. J. , Rose William N.
Published: December 2022

About 2% of mothers with Sjögren’s syndrome and about 1% of mothers with systemic lupus erythematosus deliver a baby with a congenital heart block (CHB). This is thought to be as a result of the maternal autoantibodies that cross the placenta and cause congenital lupus in the fetus/neonate. Among patients with a 2nd or 3rd degree atrioventricular block, the mortality rate in the neonatal period is about 10%, and most neonates who survive require a pacemaker into adulthood. Despite the compelling mortality and morbidity, the data on the optimal preventive treatments are meager and not well-established. In addition to pharmaceutical therapy, one potentially effective therapy is plasmapheresis. Plasmapheresis is safe in pregnancy, well tolerated, and is effective in removing the offending substances in the serum which may cause disease. We review this literature, in order to educate the reader and to motivate interest in studying this condition in the future.
A Study on Structural Health Monitoring of a Large Space Antenna via Distributed Sensors and Deep Learning
Authors: Angeletti Federica , Iannelli Paolo , Gasbarri Paolo , Panella Massimo , Rosato Antonello
Published: December 2022

Most modern Earth and Universe observation spacecraft are now equipped with large lightweight and flexible structures, such as antennas, telescopes, and extendable elements. The trend of hosting more complex and bigger appendages, essential for high-precision scientific applications, made orbiting satellites more susceptible to performance loss or degradation due to structural damages. In this scenario, Structural Health Monitoring strategies can be used to evaluate the health status of satellite substructures. However, in particular when analysing large appendages, traditional approaches may not be sufficient to identify local damages, as they will generally induce less observable changes in the system dynamics yet cause a relevant loss of payload data and information. This paper proposes a deep neural network to detect failures and investigate sensor sensitivity to damage classification for an orbiting satellite hosting a distributed network of accelerometers on a large mesh reflector antenna. The sensors-acquired time series are generated by using a fully coupled 3D simulator of the in-orbit attitude behaviour of a flexible satellite, whose appendages are modelled by using finite element techniques. The machine learning architecture is then trained and tested by using the sensors’ responses gathered in a composite scenario, including not only the complete failure of a structural element (structural break) but also an intermediate level of structural damage. The proposed deep learning framework and sensors configuration proved to accurately detect failures in the most critical area or the structure while opening new investigation possibilities regarding geometrical properties and sensor distribution.
Low-Altitude Windshear Estimation Method Based on Four-Dimensional Frequency Domain Compensation for Fuselage Frustum Conformal Array
Authors: Li Hai , Zheng Lei , Meng Fanwang
Published: December 2022

In this paper, a low-altitude wind speed estimation method based on the fuselage frustum conformal array system is proposed. Firstly, based on the signal model of the fuselage conformal array radar, the four-dimensional joint phase compensation of the echo data in the Doppler domain and three-dimensional space-frequency domain is performed by using the four-dimensional frequency domain compensation method. Secondly, the clutter covariance matrix is estimated by the compensated echo data, and a space-time Adaptive Processing (STAP) processor suitable for low-altitude windshear target is constructed to suppress clutter. Finally, the maximum Doppler value of each distance cell is extracted, and the wind velocity is estimated. Simulation results show that the proposed method can effectively suppress clutter and accurately estimate wind speed.
High-Sensitivity Liquid Dielectric Characterization Differential Sensor by 1-Bit Coding DGS
Authors: Xie Bingfang , Gao Zhiqiang , Wang Cong , Ali Luqman , Muhammad Azeem , Meng Fanyi , Qian Cheng , Ding Xumin , Adhikari Kishor Kumar , Wu Qun
Published: December 2022

This paper presents two devices to detect the liquid dielectric characterization. The differential method was used to enhance the robustness and reduce tolerance. A basic sensor based on defected ground structure (DGS) was designed and the optimization for the squares of the DGS via adaptive genetic algorithm was applied to enhance the performance of the microwave sensor, which was shown by the difference of the two resonant frequencies. Furthermore, the electric field distribution was enhanced. Glass microcapillary tubes were used to hold samples to provide an environment of non-invasive. The optimized device exhibited the sensitivity of 0.076, which is more than 1.52 times than the basic structure. It could be considered a sensitive and robust sensor with quick response time for liquid dielectric characterization.
Majorization-Minimization Method for Elliptic Localization in the Absence of Transmitter Position
Authors: Wu Liehu , Zou Yanbin
Published: December 2022

This paper investigates the problem of elliptic localization in the absence of transmitter position. An efficient iterative method is developed to jointly evaluate the target and transmitter positions. Using the measurement information from the indirect paths reflected from the target and the direct paths between the transmitter and receivers, a non-convex maximum likelihood estimation (MLE) problem is formulated. Owing to the non-convex nature of the issue, we apply the majorization–minimization (MM) principle to address the MLE problem, which iteratively minimizes a convex surrogate function instead of the original objective function. Moreover, the proposed MM method is further extended to tackle a general scenario where both multiple unknown transmitters and receiver position errors are considered. Finally, numerical simulations demonstrate that the proposed MM method outperforms the state-of-the-art methods.
Collaborative 3D Scene Reconstruction in Large Outdoor Environments Using a Fleet of Mobile Ground Robots
Authors: Lewis John , Lima Pedro U. , Basiri Meysam
Published: December 2022

Teams of mobile robots can be employed in many outdoor applications, such as precision agriculture, search and rescue, and industrial inspection, allowing an efficient and robust exploration of large areas and enhancing the operators’ situational awareness. In this context, this paper describes an active and decentralized framework for the collaborative 3D mapping of large outdoor areas using a team of mobile ground robots under limited communication range and bandwidth. A real-time method is proposed that allows the sharing and registration of individual local maps, obtained from 3D LiDAR measurements, to build a global representation of the environment. A conditional peer-to-peer communication strategy is used to share information over long-range and short-range distances while considering the bandwidth constraints. Results from both real-world and simulated experiments, executed in an actual solar power plant and in its digital twin representation, demonstrate the reliability and efficiency of the proposed decentralized framework for such large outdoor operations.
Towards Haptic-Based Dual-Arm Manipulation
Authors: Turlapati Sri Harsha , Campolo Domenico
Published: December 2022

Vision is the main component of current robotics systems that is used for manipulating objects. However, solely relying on vision for hand−object pose tracking faces challenges such as occlusions and objects moving out of view during robotic manipulation. In this work, we show that object kinematics can be inferred from local haptic feedback at the robot−object contact points, combined with robot kinematics information given an initial vision estimate of the object pose. A planar, dual-arm, teleoperated robotic setup was built to manipulate an object with hands shaped like circular discs. The robot hands were built with rubber cladding to allow for rolling contact without slipping. During stable grasping by the dual arm robot, under quasi-static conditions, the surface of the robot hand and object at the contact interface is defined by local geometric constraints. This allows one to define a relation between object orientation and robot hand orientation. With rolling contact, the displacement of the contact point on the object surface and the hand surface must be equal and opposite. This information, coupled with robot kinematics, allows one to compute the displacement of the object from its initial location. The mathematical formulation of the geometric constraints between robot hand and object is detailed. This is followed by the methodology in acquiring data from experiments to compute object kinematics. The sensors used in the experiments, along with calibration procedures, are presented before computing the object kinematics from recorded haptic feedback. Results comparing object kinematics obtained purely from vision and from haptics are presented to validate our method, along with the future ideas for perception via haptic manipulation.
Repeatability of Inertial Measurement Units for Measuring Pelvic Mobility in Patients Undergoing Total Hip Arthroplasty
Authors: Vayalapra Sushanth , Wang Xueyang , Qureshi Arham , Vepa Abhinav , Rahman Usama , Palit Arnab , Williams Mark A. , King Richard , Elliott Mark T.
Published: December 2022

Consideration of pelvic mobility when positioning implants for total hip arthroplasty (THA) has been shown to reduce the risk of complications such as dislocation, squeaking and excessive wear. We aim to test the repeatability of pelvic tilt measurements taken between three positions (standing, flexed-seated and step-up) by an inertial measurement unit (IMU) and hence, evaluate their reliability in screening for high pelvic mobility in patients undergoing THA. The repeated IMU measurements of pelvic tilt were analysed for consistency and compared with measures taken by x-ray analysis. Our study showed greater variation in measures taken by the IMU particularly in the flexed-seated position. The patient’s pelvic tilt in this position negatively correlated with their mid-back angle, suggesting the posture of the patient is a source of variation in the flexed-seated position if not kept consistent during assessments. IMUs were overall able to produce accurate and reliable measurements of pelvic tilt; however, protocols will need to be adjusted to factor in a patient’s mid-back angle when taking future readings.
3D Gaze Estimation Using RGB-IR Cameras
Authors: Mokatren Moayad , Kuflik Tsvi , Shimshoni Ilan
Published: December 2022

In this paper, we present a framework for 3D gaze estimation intended to identify the user’s focus of attention in a corneal imaging system. The framework uses a headset that consists of three cameras, a scene camera and two eye cameras: an IR camera and an RGB camera. The IR camera is used to continuously and reliably track the pupil and the RGB camera is used to acquire corneal images of the same eye. Deep learning algorithms are trained to detect the pupil in IR and RGB images and to compute a per user 3D model of the eye in real time. Once the 3D model is built, the 3D gaze direction is computed starting from the eyeball center and passing through the pupil center to the outside world. This model can also be used to transform the pupil position detected in the IR image into its corresponding position in the RGB image and to detect the gaze direction in the corneal image. This technique circumvents the problem of pupil detection in RGB images, which is especially difficult and unreliable when the scene is reflected in the corneal images. In our approach, the auto-calibration process is transparent and unobtrusive. Users do not have to be instructed to look at specific objects to calibrate the eye tracker. They need only to act and gaze normally. The framework was evaluated in a user study in realistic settings and the results are promising. It achieved a very low 3D gaze error (2.12°) and very high accuracy in acquiring corneal images (intersection over union—IoU = 0.71). The framework may be used in a variety of real-world mobile scenarios (indoors, indoors near windows and outdoors) with high accuracy.
Physics-Guided Real-Time Full-Field Vibration Response Estimation from Sparse Measurements Using Compressive Sensing
Authors: Jana Debasish , Nagarajaiah Satish
Published: December 2022

In civil, mechanical, and aerospace structures, full-field measurement has become necessary to estimate the precise location of precise damage and controlling purposes. Conventional full-field sensing requires dense installation of contact-based sensors, which is uneconomical and mostly impractical in a real-life scenario. Recent developments in computer vision-based measurement instruments have the ability to measure full-field responses, but implementation for long-term sensing could be impractical and sometimes uneconomical. To circumvent this issue, in this paper, we propose a technique to accurately estimate the full-field responses of the structural system from a few contact/non-contact sensors randomly placed on the system. We adopt the Compressive Sensing technique in the spatial domain to estimate the full-field spatial vibration profile from the few actual sensors placed on the structure for a particular time instant, and executing this procedure repeatedly for all the temporal instances will result in real-time estimation of full-field response. The basis function in the Compressive Sensing framework is obtained from the closed-form solution of the generalized partial differential equation of the system; hence, partial knowledge of the system/model dynamics is needed, which makes this framework physics-guided. The accuracy of reconstruction in the proposed full-field sensing method demonstrates significant potential in the domain of health monitoring and control of civil, mechanical, and aerospace engineering systems.
QCL Active Area Modeling with a View to Being Applied to Chemical Substance Detection Systems
Authors: Mączka Mariusz , Hałdaś Grzegorz , Pawłowski Stanisław
Published: December 2022

Numerical research into the QCL tunability aspects in respect to being applied in chemical substance detection systems is covered in this paper. The QCL tuning opportunities by varying power supply conditions and geometric dimensions of the active area have been considered. Two models for superlattice finite (FSML) and infinite (RSM) size were assumed for simulations. The results obtained have been correlated with the absorption map for selected chemical substances in order to identify the potential detection possibilities.
Validation of a Lumped Parameter Model of the Battery Thermal Management System of a Hybrid Train by Means of Ultrasonic Clamp-On Flow Sensor Measurements and Hydronic Optimization
Authors: De Rosa Raffaele , Romagnuolo Luca , Frosina Emma , Belli Luigi , Senatore Adolfo
Published: December 2022

Electrification of the field of transport is one of the key elements needed to reach the targets of greenhouse gas emissions reduction and carbon neutrality planned by the European Green Deal. In the railway sector, the hybrid powertrain solution (diesel–electric) is emerging, especially for non-electrified lines. Electric components, especially battery power systems, need an efficient thermal management system that guarantees the batteries will work within specific temperature ranges and a thermal uniformity between the modules. Therefore, a hydronic balancing needs to be realized between the parallel branches that supply the battery modules, which is often realized by introducing pressure losses in the system. In this paper, a thermal management system for battery modules (BTMS) of a hybrid train has been studied experimentally, to analyze the flow rates in each branch and the pressure losses. Since many branches of this system are built inside the battery box of the hybrid train, flow rate measurements have been conducted by means of an ultrasonic clamp-on flow sensor because of its minimal invasiveness and its ability to be quickly installed without modifying the system layout. Experimental data of flow rate and pressure drop have then been used to validate a lumped parameter model of the system, realized in the Simcenter AMESim® environment. This tool has then been used to find the hydronic balancing condition among all the battery modules; two solutions have been proposed, and a comparison in terms of overall power saved due to the reduction in pressure losses has been performed.
Track Geometry Prediction Using Three-Dimensional Recurrent Neural Network-Based Models Cross-Functionally Co-Simulated with BIM
Authors: Sresakoolchai Jessada , Kaewunruen Sakdirat
Published: December 2022

Railway track maintenance plays an important role in enabling safe, reliable, and seamless train operations and passenger comfort. Due to the increasing rail transportation, rolling stocks tend to run faster and the load tends to increase continuously. As a result, the track deteriorates quicker, and maintenance needs to be performed more frequently. However, more frequent maintenance activities do not guarantee a better overall performance of the railway system. It is crucial for rail infrastructure managers to optimize predictive and preventative maintenance. This study is the world’s first to develop deep machine learning models using three-dimensional recurrent neural network-based co-simulation models to predict track geometry parameters in the next year. Different recurrent neural network-based techniques are used to develop predictive models. In addition, a building information modeling (BIM) model is developed to integrate and cross-functionally co-simulate the track geometry measurement with the prediction for predictive and preventative maintenance purposes. From the study, the developed BIM models can be used to exchange information for predictive maintenance. Machine learning models provide the average R2 of 0.95 and the average mean absolute error of 0.56 mm. The insightful breakthrough demonstrates the potential of machine learning and BIM for predictive maintenance, which can promote the safety and cost effectiveness of railway maintenance.
Robust Wheel Detection for Vehicle Re-Identification
Authors: Ghanem Sally , Kerekes Ryan A.
Published: December 2022

Vehicle re-identification is a demanding and challenging task in automated surveillance systems. The goal of vehicle re-identification is to associate images of the same vehicle to identify re-occurrences of the same vehicle. Robust re-identification of individual vehicles requires reliable and discriminative features extracted from specific parts of the vehicle. In this work, we construct an efficient and robust wheel detector that precisely locates and selects vehicular wheels from vehicle images. The associated hubcap geometry can hence be utilized to extract fundamental signatures from vehicle images and exploit them for vehicle re-identification. Wheels pattern information can yield additional information about vehicles in questions. To that end, we utilized a vehicle imagery dataset that has thousands of side-view vehicle collected under different illumination conditions and elevation angles. The collected dataset was used for training and testing the wheel detector. Experiments show that our approach could detect vehicular wheels accurately for 99.41% of the vehicles in the dataset.
Bolt Positioning Detection Based on Improved YOLOv5 for Bridge Structural Health Monitoring
Authors: Wang Diyong , Zhang Meixia , Sheng Danjie , Chen Weiming
Published: December 2022

To improve the stability of the bridge structure, we detect bolts in the bridge which cause the symmetry failure of the bridge center. For data acquisition, bolts are small-scale objects under complex background in images, and their feature expression ability is limited. Due to those questions, we propose a new bolt positioning detection based on improved YOLOv5 for bridge structural health monitoring. This paper makes three major contributions. Firstly, according to the calibration anchor boxes of bolts, the size and proportion parameters of the initial anchor boxes are optimized by K-means++ clustering algorithm to solve the initial clustering problem of anchor boxes in object detection. Second, the hypercolumn (HC) technique fuses the low-level global features of the trunk and the high-level local features of three different scales to solve the problem of the inefficient distribution of anchors and insufficient extraction of classification features. In this way, we improve the detection accuracy and speed of bolt detection. Finally, we establish a dataset of bridge bolts through network collection and public datasets, including 1494 images. We compare and verify the new method in the collected bolt dataset. The experimental results show that the precision (P) of the improved YOLOv5x is up to 87.3%, and the average precision (AP) is up to 86.3%, which are 6.5% and 5.9% higher than the original YOLOv5x, respectively.
Micro-Image Strain Sensing Method for Displacement and Strain Measurement in One United Sensor
Authors: Zhang Lixiao , Chen Xixian , Li Weijie , Xie Botao , Zhou Guangyi , Zhao Xuefeng
Published: December 2022

Micro-image strain sensing (MISS) is an innovative technology to measure strain within a measurement range of ±8300 microstrains. It has been proved to be effective and satisfy all requirements in the field of structural health monitoring. However, there is still room for improvement and extend the range of measurement. In this paper, an improved method is proposed to increase the measurement range of strain and displacement. Moreover, various tests were conducted to verify the efficiency of the improved method. The results showed that the modified method is efficient and accurate and can be readily used to extend the measurement range of both strain and displacement. This research will likely help stimulate the development of multifunctional sensors to obtain abundant useful information about structures in the field of structural health monitoring. It will allow measuring strain and displacement, which require different levels of accuracy, using one unified sensor.
Wireless Link Selection Methods for Maritime Communication Access Networks—A Deep Learning Approach
Authors: Hoeft Michal , Gierlowski Krzysztof , Wozniak Jozef
Published: December 2022

In recent years, we have been witnessing a growing interest in the subject of communication at sea. One of the promising solutions to enable widespread access to data transmission capabilities in coastal waters is the possibility of employing an on-shore wireless access infrastructure. However, such an infrastructure is a heterogeneous one, managed by many independent operators and utilizing a number of different communication technologies. If a moving sea vessel is to maintain a reliable communication within such a system, it needs to employ a set of network mechanisms dedicated for this purpose. In this paper, we provide a short overview of such requirements and overall characteristics of maritime communication, but our main focus is on the link selection procedure—an element of critical importance for the process of changing the device/system which the mobile vessel uses to retain communication with on-shore networks. The paper presents the concept of employing deep neural networks for the purpose of link selection. The proposed methods have been verified using propagation models dedicated to realistically represent the environment of maritime communications and compared to a number of currently popular solutions. The results of evaluation indicate a significant gain in both accuracy of predictions and reduction of the amount of test traffic which needs to be generated for measurements.
Phenomena of Bacillus sphaericus LMG 22257 Activity and Its Influence on Properties of Portland Cement Mortar Exposed to Different Curing Media
Authors: Mahat Siti Baizura , Johari Megat Azmi Megat , Mokhtar Norfaniza , Kok Keong Choong , Idris Mohd Nazri , Wan Zakaria Wan Zafira Ezza , Chun Charles Ng Wai , Tajarudin Husnul Azan
Published: December 2022

This study determined the influences of Bacillus sphaericus Laboratorium voor Microbiologie Gent (LMG) 22257 bacteria activity on mortar samples cured in various media regarding compressive strength, porosity, water absorption, and water permeability. Three types of curing media were utilized, namely distilled water (D.W.), deposition water (D.M.), and run-off water (R.W.). The compressive strength was measured using 100 mm mortar cubes. The water porosity, water absorption, and water permeability were analyzed using the Leeds permeability cell with dimensions of the mortar cylindrical specimens of 55 mm diameter and 40 mm thickness. Scanning electron microscopy (SEM) and energy-dispersive X-ray spectrometry (EDX) were utilized, respectively, for microstructure analysis and quantifying the elements with atomic numbers. The results indicated the presence of calcium carbonate and more calcium silicate hydrate (CSH) depositions on bacterial mortars. The inclusion of Bacillus sphaericus LMG 22257 bacteria activity and curing media type affected mortar properties through compressive strength and durability improvements, as well as the reduction in water porosity, water absorption, and water permeability of mortar. The comparison of CaCO3 precipitation, such as a sufficient growth nutrient requirement and hostile bacteria environment, was observed. Curing in R.W. produced the most significant bio-based cement (BBC) mortar improvement, followed by D.M. BBC curing in runoff water had a 40% improvement in strength compared to normal curing. As a conclusion, runoff water is a highly promising sufficient nutrient to bacteria for the biomineralization process to produce CaCO3. This work also aims to apply this approach in the field, especially in sewerage and drainage systems.
SEDIS—A Rumor Propagation Model for Social Networks by Incorporating the Human Nature of Selection
Authors: Govindankutty Sreeraag , Gopalan Shynu Padinjappurathu
Published: December 2022

The explosive evolution of the internet has paved the path for the rise of social networks, which can help people connect remotely. Currently, social networks are commonly used for sharing thoughts, feelings, information, and personal life, which vary from individual to individual. The world has witnessed a tremendous increase in social media usage in the last decade, and more people are expected to spend their time online after the COVID-19 pandemic. This increases the rapid propagation of rumors and fake news within societies and communities. On one end, social networks act as an excellent platform for digital marketing and sharing information. However, on the other end, social network rumors and fake news create a significant impact on society, including riots. To study and analyze social network rumors, several mathematical rumor propagation epidemic models have been proposed. The majority are related to disease-spreading epidemic models and reject the human aspect of social selection. This paper introduces a new mathematical rumor propagation model for social networks by incorporating the human psychological aspect of selection as a separate state. Our mathematical analysis and computational simulation proved that the model exists within the system. It was also proven that the system is always non-negative and there always exists a solution in the system. Our implementation of an intervention mechanism within the discrete compartmental model simulation proved the necessity of an effective interference that can help to prevent the implications of uncontrolled rumor dissemination within social networks.
Measurement of Charge and Refractive Indices in Optically Trapped and Ionized Living Cells
Authors: Muhammed Endris , Erenso Daniel B. , Gao Ying , Chen Li , Kelley Michele , Vazquez Carina , Gale Mitchell , Nichols Cody , Crogman Horace T.
Published: December 2022

The post-ionization dynamics of chemo-treated and untreated 4T1 breast cancer cells ionized by laser trapping techniques are studied. We have determined each cell’s charge and refractive index by developing a theoretical model for the forces determining the post-ionization dynamics. The shift in a cell’s refractive index due to an intense oscillating electric field was studied, and the results are reported here. We observed that a trapped cell, as it becomes charged, will eventually exit the trap perpendicular to the beam’s direction; this means that the electric force of the cell overcomes the trapping force. As a result, the cell’s conductivity changes due to the oscillating field, causing a decrease in the cell’s refractive index.
Enhanced Photocatalytic Degradation of Methylene Blue Using Ti-Doped ZnO Nanoparticles Synthesized by Rapid Combustion
Authors: Wongrerkdee Sutthipoj , Wongrerkdee Sawitree , Boonruang Chatdanai , Sujinnapram Supphadate
Published: December 2022

ZnO and Ti-doped ZnO (Ti-ZnO) nanoparticles were synthesized using rapid combustion. The morphology of ZnO and Ti-ZnO featured nanoparticles within cluster-like structures. The ZnO and Ti-ZnO structures exhibited similar hexagonal wurtzite structures and crystal sizes. This behavior occurred because Zn2+ sites of the ZnO lattice were substituted by Ti4+ ions. The chemical structure characterization implied the major vibration of the ZnO structure. The physisorption analysis showed similar mesoporous and non-rigid aggregation structures for ZnO and Ti-ZnO using N2 adsorption–desorption. However, Ti-ZnO demonstrated a specific surface area two times higher than that of ZnO. This was a major factor in improving the photocatalytic degradation of methylene blue (MB). The photocatalytic degradation analysis showed a kinetic degradation rate constant of 2.54 × 10−3 min−1 for Ti-ZnO, which was almost 80% higher than that of ZnO (1.40 × 10−3 min−1). The transformation mechanism of MB molecules into other products, including carbon dioxide, aldehyde, and sulfate ions, was also examined.
Genotypic and Phenotypic Characterization of Erythromycin-Resistant Staphylococcus aureus Isolated from Bovine Mastitis and Humans in Close Contact
Authors: Rasool Zainab , Noreen Hadiqua , Anjum Asfa , Rizvi Azka , Rabaan Ali A. , Halwani Muhammad A. , Sabour Amal A. , Aljeldah Mohammed , Shammari Basim R. Al , Alhajri Salah M. , Alshubaith Ibrahim H. , Garout Mohammed , Firyal Sehrish , Ahmed Naveed
Published: December 2022

Staphylococcus aureus (S. aureus) is a major causative agent of mastitis and is resistant to many antibiotics. Thus, there is a need to characterize the genetic determinants of S. aureus erythromycin resistance, such as ermA, ermB and ermC. The current study aimed to determine the phenotypic and genotypic erythromycin resistance profile and relatedness of S. aureus recovered from bovine mastitis and humans in close contact. A total of 14 mastitis-infected buffalo milk samples and 16 samples from their respective milkers were collected from different farms of Lahore, Pakistan. The antibiotic resistance profile was determined through the disk diffusion test. The overall prevalence of S. aureus in mastitis-affected buffaloes was found to be 75%, of which 52.1% were resistant to erythromycin and 42.8% to clindamycin. S. aureus isolates recovered from milker nasal samples showed 56.25% resistance to erythromycin and 44% resistance to clindamycin. Genotypic antibiotic resistance profiles were determined from 14 milk samples through PCR. Overall, eight (52.1%), three (21.4%) and five (35.7%) S. aureus isolates were positive for the ermA, ermB and ermC genes, respectively. Moreover, 16 milker nasal S. aureus isolates were also tested for the presence of ermA, ermB and ermC genes. The ermA, ermB and ermC genes were observed in nine(56.7%), five (31.3%) and seven (43.7%) isolates, respectively. A significant association was shown between phenotypic and genotypic erythromycin resistance. The results indicate both that there are sufficient genetic similarities, and the actual transmission of erythromycin resistance genes between these two hosts of S. aureus.
SafeHANDS: A Multimodal Hand Hygiene Intervention in a Resource-Limited Neonatal Unit
Authors: Dramowski Angela , Erasmus Louisa M. , Aucamp Marina , Fataar Aaqilah , Cotton Mark F. , Coffin Susan E. , Bekker Adrie , Whitelaw Andrew C.
Published: December 2022

Background: Hand hygiene (HH) is a cornerstone of programmes to prevent healthcare associated infections (HAI) globally, but HH interventions are seldom reported from African neonatal units. Methods: We conducted a quasi-experimental study evaluating the impact of a multi-modal intervention (SafeHANDS) on HH compliance rates, alcohol-based handrub (ABHR) usage, the Hand Hygiene Self-Assessment Framework (HHSAF) score, and healthcare-associated bloodstream infection (HA-BSI) rates at a 132-bed South African neonatal unit (4 wards and 1 neonatal intensive care unit [NICU]). The intervention included a campaign logo, HH training, maternal education leaflets, ABHR bottles for staff, and the setting of HH performance targets with feedback. Three 5-month study phases were completed in July 2020 (baseline), December 2020 (early) and May 2021 (intensive). Results: A total of 2430 HH opportunities were observed: 1002 (41.3%) at baseline, 630 (25.9%) at early and 798 (32.8%) at intensive study phases. At baseline, the overall neonatal unit HH compliance rate was 61.6%, ABHR use was 70 mL/patient day, and the baseline HHSAF score was ‘basic’ (165). The overall neonatal unit HH compliance rate was unchanged from baseline to intensive phases (617/1002 [61.6%] vs. 497/798 [62.3%]; p = 0.797). The ABHR use remained similar between phases (70 versus 73 mL/patient day). The HHSAF score improved to ‘intermediate’ level (262). There was no change in the neonatal unit HA-BSI rate. Conclusion: Despite improvement in the HHSAF score, no improvement in overall HH compliance rates, ABHR usage, or HA-BSI rates was observed. Future HH interventions in resource-limited neonatal units should incorporate implementation science and behaviour modification strategies to better understand the barriers and facilitators of HH best practice.
Impact of Coronavirus Pandemic on Tuberculosis and Other Imported Diseases Screening among Migrant Minors in Spain
Authors: Mellado-Sola Isabel , Rodríguez-Molino Paula , Armas Elisa-Andrea , Nogueira López Javier , Falces-Romero Iker , Rey Cristina Calvo , Grasa Lozano Carlos , Mellado María José , López-Hortelano Milagros García , Sainz Talía
Published: December 2022

Background: In recent decades, the increase in population movements has turned the focus to imported diseases. The COVID-19 pandemic has negatively impacted the access to health care systems, especially in highly vulnerable populations. We address the effects of the pandemic on the health screening of migrant unaccompanied minors (UM) in Spain. Method: Retrospective cross-sectional study including UM screened for imported diseases with a unified protocol at a pediatric reference unit for tropical and infectious diseases in Madrid, Spain. We compared the pre-pandemic (2018–2019) and post-pandemic periods (2020–2021). Results: A total of 192 minors were screened during the study period, with a drop in UM’s referral to our center in the post-pandemic years (140 in 2018–2019 vs. 52 in 2020–2021). Out of 192, 161 (83.9%) were diagnosed with at least one medical condition. The mean age was 16.8 years (SD 0.8) and 96.9% were males. Most cases were referred for a health exam; only 38% of children were symptomatic. Eosinophilia was present in 20.8%. The most common diagnosis were latent tuberculosis infection (LTBI) (72.9%), schistosomiasis (15.1%), toxocariasis (4.9%) and strongyloidiasis (4.9%). The prevalence of LTBI did not vary significantly (69.3% vs. 82.7%, p = 0.087). A total of 38% of the patients diagnosed with LTBI never started treatment or were lost to follow-up, as were two out of three patients with active pulmonary tuberculosis. Conclusions: In this series, the number of UM referred for health screening has dropped dramatically after the COVID pandemic, and two years after the beginning of the pandemic, access to care is still limited. Lost to follow-up rates are extremely high despite institutionalization. Specific resources, including multidisciplinary teams and accessible units are needed to improve diagnoses and linkage to care in this vulnerable population.
Programmatic Implementation of Contact Investigation in Eight African Countries
Authors: Koura Kobto G. , Mbitikon Olivia B. , Fiogbé Attannon A. , Ouédraogo Abdoul R. , Kuate Kuate Albert , Magassouba Aboubacar S. , Soumana Alphazazi , Hermana Georges , Gning Barnabé , Dogo Mohammed F. , Andefa Monicah , Badoum Gisèle
Published: December 2022

The objective was to implement CI under national tuberculosis programmatic conditions and to advocate for its scaling up. Contact investigation was implemented in 150 Basic Management Units identified across eight countries. The target populations (children <5 years and persons living with HIV (PLHIV)) were evaluated during home and clinic visits using standardized tools, clinical examinations and, according to each country, additional tests. Contacts with active TB received TB treatment and those eligible received TB preventive therapy (TPT). Data were collected each quarter using standardized forms. Meetings were organized with partners to share preliminary results and advocate for scaling up. From October 2020 to December 2021, 9049 home visits were performed. The proportions of children <5 years and PLHIV who were screened and diagnosed with active TB were, respectively, 2.6% and 10.1%. Ninety-three percent of children <5 years and 98% of PLHIV living at home received TPT or TB treatment, respectively. The scale-up for contact investigation partially or at national level in 2022 was effective in six of the eight countries included in the project. These results indicate that CI is feasible under programmatic conditions within the National TB Programs of African countries.
Vaccinating Children against SARS-CoV-2: A Literature Review and Survey of International Experts to Assess Safety, Efficacy and Perceptions of Vaccine Use in Children
Authors: Hookham Lauren , Lee Hillary C. , Patel Divya A. , Coelho Mariana , Giglio Norberto , Le Doare Kirsty , Pannaraj Pia S.
Published: December 2022

Introduction: The balance of risks and benefits of COVID-19 vaccination in children is more complex than in adults with limited paediatric data resulting in no global consensus on whether all healthy children should be vaccinated. We sought to assess the safety, efficacy, and effectiveness of childhood vaccination against SARS-CoV-2, as well as better understanding perceptions of vaccination in parents and vaccine experts. Methods: We performed a literature review for COVID-19 vaccine safety, efficacy, effectiveness, and perceptions. We searched international safety databases for safety data and developed an electronic survey to elicit country-specific COVID-19 immunisation data, including vaccine regulations, policies, rates, and public attitudes solicited from vaccine experts. Results: Nine studies were included in the final safety analysis. Local reactions were frequently reported across all studies and vaccine types. Adverse events reported to surveillance systems tended to be non-serious, and commonly included injection site reactions and dizziness. Twenty-three studies reported immunogenicity, efficacy, and effectiveness data. There were nine randomised control trials of six different vaccine types, which showed seroconversion of neutralising antibodies in vaccinated children ranging from 88% to 100%. The vaccine efficacy for Pfizer and Moderna vaccines ranged from 88% to 100%. There were 118 survey responses representing 55 different countries. Reported vaccination rates ranged from <1% to 98%. Most respondents described “mixed opinions” regarding paediatric vaccination policies in their country. By region, a more positive public attitude towards vaccination correlated with higher vaccination rates. Discussion: In this mixed-methods review, we have found evidence that vaccination against COVID-19 in children is safe, efficacious, and effective. Overall, the combined evidence from both the literature review and survey highlights the need for further data on both the safety and effectiveness of COVID-19 vaccinations in children.
Humoral Response after Two Doses of BNT162b2 mRNA Vaccine Has a Role in Predicting Response after Three Doses That Is Related to Plasma HIV Viremia and Nadir CD4+ Cell Count in HIV-Positive Patients
Authors: Basso Monica , Pirola Nicole , Pascoli Susanna , Bragato Beatrice , Vinci Antonio , Iannetta Marco , Colombo Francesco , Geremia Nicholas , Martignago Luca , Rossi Maria Cristina , Cipriani Ludovica , Giobbia Mario , Scotton Pier Giorgio , Parisi Saverio Giuseppe
Published: December 2022

We investigated the spike IgG levels of HIV+ patients on antiretroviral therapy six months after they received their second dose (T2) and six months after the third dose (T3) of the BNT162b2 mRNA vaccine, as well as the influence of different levels of plasma HIV viremia of overall CD4+ cell count and nadir value on the humoral time course. One hundred eighty-four patients were enrolled. The median age was 55 years, the median CD4+ cell count was 639 cells/mm3 and the median nadir value was 258 cells/mm3. On the basis of all tests performed during the study period, persistently undetectable plasma HIV RNA (PUD) was found in 66 patients, low-level viremia (LLV) in 57 and ongoing viremia (OV) in 61. Serum levels of IgG antibodies against a trimeric S-protein antigen were tested with DiaSorin Liaison SARS-CoV-2 TrimericS IgG and the response was classified as optimal (>75th percentile), intermediate (50th–25th percentile) and low (<25th percentile). The frequencies of the three different patterns of plasma HIV viremia (PUD, LLV and OV) were comparable in patients with low, intermediate and optimal IgG response evaluated at T2, with no difference in overall CD4+ cell count or nadir count. At T3, 92.9% of patients achieved an optimal response: T2 response proved to be the most important factor in predicting T3 optimal response in patients with LLV and OV.A nadir value ≤ 330 cells/mm3 had 100% sensitivity in predicting a non-optimal response. In conclusion, we demonstrated the persistence of anti-spike IgG, with high serum levels occurring in most patients six months after the third dose of the BNT162b2 mRNA vaccine and a predictive role of humoral response at T2 in subjects with detectable plasma HIV viremia. Immunological alterations related to past immunodeficiency may persist despite immune reconstitution, and the nadir value could be a useful tool for elaborating personalized vaccine schedules.
A Case of Congenital Pulmonary Vein Stenosis with Secondary Post-Capillary Pulmonary Hypertension and Left Sided Congestive Heart Failure in a Cat
Authors: Kriström Karin , Karlstam Erika , Nielsen Tove , Lagerqvist Anne , Dirven Mark
Published: December 2022

A five-month-old, 3.8 kg intact male Maine coon cat presented for dyspnea characterized by increased respiratory effort in addition to open-mouth breathing. Thoracic radiographs showed pectus excavatum, enlarged cardiac silhouette, and generalized interstitial patterns. Echocardiography revealed normal left atrial (LA) and left ventricular dimensions. A large tubular structure, suspected to be a distended pulmonary vein (PV), was identified as draining into the LA. Severe eccentric and concentric right ventricular hypertrophy and paradoxical septal motion were noted. Based on Doppler echocardiography, both pulmonary venous and pulmonary artery pressure was severely elevated. Clinical, radiographic, and echocardiographic abnormalities were hypothesized to result from pulmonary vein stenosis (PVS), causing severely elevated pulmonary venous pressures and resulting in clinical signs of left-sided congestive heart failure (L-CHF) and severe post-capillary pulmonary hypertension (Pc-PH). The prognosis for good quality of life was assessed as poor, and the owner elected euthanasia. Necropsy confirmed the presence of PVS with severe dilation of the PVs draining all but the left cranial lung lobe. All lung lobes except the left cranial lobe had increased tissue density and a mottled cut surface. This case report shows that, in rare cases, both L-CHF and Pc-PH may be present without LA enlargement. To the authors’ knowledge, this is the first report on PVS in veterinary medicine.