bluuebunny/crossref_metadata_2025 huggingface dataset:
A Review of Deep Learning-Based Visual Multi-Object Tracking Algorithms for Autonomous Driving
Authors: Guo Shuman , Wang Shichang , Yang Zhenzhong , Wang Lijun , Zhang Huawei , Guo Pengyan , Gao Yuguo , Guo Junkai
Published: October 2022

Multi-target tracking, a high-level vision job in computer vision, is crucial to understanding autonomous driving surroundings. Numerous top-notch multi-object tracking algorithms have evolved in recent years as a result of deep learning’s outstanding performance in the field of visual object tracking. There have been a number of evaluations on individual sub-problems, but none that cover the challenges, datasets, and algorithms associated with visual multi-object tracking in autonomous driving scenarios. In this research, we present an exhaustive study of algorithms in the field of visual multi-object tracking over the last ten years, based on a systematic review approach. The algorithm is broken down into three groups based on its structure: methods for tracking by detection (TBD), joint detection and tracking (JDT), and Transformer-based tracking. The research reveals that the TBD algorithm has a straightforward structure, however the correlation between its individual sub-modules is not very strong. To track multiple objects, the JDT technique combines multi-module joint learning with a deep network framework. Transformer-based algorithms have been explored over the past two years, and they have benefits in numerous assessment indicators, as well as tremendous research potential in the area of multi-object tracking. Theoretical support for algorithmic research in adjacent disciplines is provided by this paper. Additionally, the approach we discuss, which uses merely monocular cameras rather than sophisticated sensor fusion, is anticipated to pave the way for the quick creation of safe and affordable autonomous driving systems.
Human Activity Recognition for Assisted Living Based on Scene Understanding
Authors: Achirei Stefan-Daniel , Heghea Mihail-Cristian , Lupu Robert-Gabriel , Manta Vasile-Ion
Published: October 2022

The growing share of the population over the age of 65 is putting pressure on the social health insurance system, especially on institutions that provide long-term care services for the elderly or to people who suffer from chronic diseases or mental disabilities. This pressure can be reduced through the assisted living of the patients, based on an intelligent system for monitoring vital signs and home automation. In this regard, since 2008, the European Commission has financed the development of medical products and services through the ambient assisted living (AAL) program—Ageing Well in the Digital World. The SmartCare Project, which integrates the proposed Computer Vision solution, follows the European strategy on AAL. This paper presents an indoor human activity recognition (HAR) system based on scene understanding. The system consists of a ZED 2 stereo camera and a NVIDIA Jetson AGX processing unit. The recognition of human activity is carried out in two stages: all humans and objects in the frame are detected using a neural network, then the results are fed to a second network for the detection of interactions between humans and objects. The activity score is determined based on the human–object interaction (HOI) detections.
Analyzing the Data Completeness of Patients’ Records Using a Random Variable Approach to Predict the Incompleteness of Electronic Health Records
Authors: Gurupur Varadraj P. , Abedin Paniz , Hooshmand Sahar , Shelleh Muhammed
Published: October 2022

The purpose of this article is to illustrate an investigation of methods that can be effectively used to predict the data incompleteness of a dataset. Here, the investigators have conceptualized data incompleteness as a random variable, with the overall goal behind experimentation providing a 360-degree view of this concept conceptualizing incompleteness of a dataset both as a continuous, discrete random variable depending on the aspect of the required analysis. During the course of the experiments, the investigators have identified Kolomogorov–Smirnov goodness of fit, Mielke distribution, and beta distributions as key methods to analyze the incompleteness of a dataset for the datasets used for experimentation. A comparison of these methods with a mixture density network was also performed. Overall, the investigators have provided key insights into the use of methods and algorithms that can be used to predict data incompleteness and have provided a pathway for further explorations and prediction of data incompleteness.
Information Relaying Methods in VANET: Algorithms, Standards and Tests
Authors: Cui Tao , Sun Chen , Li Lantao
Published: October 2022

This paper considers information transmission issue observed in a large scale test of cellular-based vehicular to everything (C-V2X) technology in China, which is the information blockage for the vehicle-to-vehicle (V2V) wireless communication. With such findings, we propose utilizing relaying-based information routing solutions by the support of K-means-type algorithm and an on-request relay selection method in a vehicular adhoc network (VANET). From the algorithm perspective, we refine the K-means-based VANET seeding principle with considerations on the global vehicle layout. On the other hand, base station and/or core network aided relay selection associated with vehicle maneuver is introduced for waking up relays when necessary in order to address the typical non-line-of-sight (NLOS) signal attenuation by taking the power consumption into consideration. To evaluate the system performance, we conduct Matlab and network simulator (NS)-3 simualtions to justify the algorithms, and adopt Veins-based simulations to show the data packets loss gain over non-relaying scenarios of realistic V2V scenario with NLOS signal dissemination.
Review of Machine-Learning Techniques Applied to Structural Health Monitoring Systems for Building and Bridge Structures
Authors: Gomez-Cabrera Alain , Escamilla-Ambrosio Ponciano Jorge
Published: October 2022

This review identifies current machine-learning algorithms implemented in building structural health monitoring systems and their success in determining the level of damage in a hierarchical classification. The integration of physical models, feature extraction techniques, uncertainty management, parameter estimation, and finite element model analysis are used to implement data-driven model detection systems for SHM system design. A total of 68 articles using ANN, CNN and SVM, in combination with preprocessing techniques, were analyzed corresponding to the period 2011–2022. The application of these techniques in structural condition monitoring improves the reliability and performance of these systems.
Weakly Supervised Learning with Positive and Unlabeled Data for Automatic Brain Tumor Segmentation
Authors: Wolf Daniel , Regnery Sebastian , Tarnawski Rafal , Bobek-Billewicz Barbara , Polańska Joanna , Götz Michael
Published: October 2022

A major obstacle to the learning-based segmentation of healthy and tumorous brain tissue is the requirement of having to create a fully labeled training dataset. Obtaining these data requires tedious and error-prone manual labeling with respect to both tumor and non-tumor areas. To mitigate this problem, we propose a new method to obtain high-quality classifiers from a dataset with only small parts of labeled tumor areas. This is achieved by using positive and unlabeled learning in conjunction with a domain adaptation technique. The proposed approach leverages the tumor volume, and we show that it can be either derived with simple measures or completely automatic with a proposed estimation method. While learning from sparse samples allows reducing the necessary annotation time from 4 h to 5 min, we show that the proposed approach further reduces the necessary annotation by roughly 50% while maintaining comparative accuracies compared to traditionally trained classifiers with this approach.
A Review of the Optimal Design of Neural Networks Based on FPGA
Authors: Wang Chenghao , Luo Zhongqiang
Published: October 2022

Deep learning based on neural networks has been widely used in image recognition, speech recognition, natural language processing, automatic driving, and other fields and has made breakthrough progress. FPGA stands out in the field of accelerated deep learning with its advantages such as flexible architecture and logic units, high energy efficiency ratio, strong compatibility, and low delay. In order to track the latest research results of neural network optimization technology based on FPGA in time and to keep abreast of current research hotspots and application fields, the related technologies and research contents are reviewed. This paper introduces the development history and application fields of some representative neural networks and points out the importance of studying deep learning technology, as well as the reasons and advantages of using FPGA to accelerate deep learning. Several common neural network models are introduced. Moreover, this paper reviews the current mainstream FPGA-based neural network acceleration technology, method, accelerator, and acceleration framework design and the latest research status, pointing out the current FPGA-based neural network application facing difficulties and the corresponding solutions, as well as prospecting the future research directions. We hope that this work can provide insightful research ideas for the researchers engaged in the field of neural network acceleration based on FPGA.
A Sustainable Opportunity to Re-Inhabit Traditional Buildings in Italy: Energy Efficiency Actions End Fiscal Incentives
Authors: Cinieri Valentina , Garzulino Andrea
Published: October 2022

In recent decades, the Italian building trade has recorded an increasing interest in the renovation and improvement of both listed and unlisted existing buildings by the Ministry of Culture, growing the debate on adapting historical buildings to current sustainability needs. The Italian National Institute of Statistics (ISTAT) observed the increase in family commuting and the attractiveness of marginal territories. Despite the scarcity of services, one-fifth of Italian small municipalities are attractive according to some indicators, primarily the demographic growth in the last three years. The COVID-19 pandemic has contributed to the re-evaluation of inland areas. Remote working and the new need for open spaces could increase the return to small villages and be further boosted by the fiscal incentives. This paper considers the evolution of last year’s real estate market, evaluating whether the regulatory tools for energy retrofit and tax relief meet the trade crisis with a possible benefit of preserving historical buildings. This research cannot ignore the European background; therefore, this paper offers an overview of EU regulatory strategies for energy efficiency recently issued to increase sustainability, focusing on tax credits for improving existing buildings. In conclusion, some considerations are proposed for future in-depth research.
From Folk Art to Abstraction: Ukrainian Embroidery as a Medium of Avant-Garde Experimentation
Authors: Denysova Katia
Published: October 2022

The article examines the correlation between the stylistic iconography of traditional Ukrainian embroideries and the experiments in modernist painting that led to the emergence of abstraction, Suprematism in particular. The focus is made on the artistic output of the embroidery workshops in the villages of Verbivka and Skoptsi, both located on the territory of present-day Ukraine, in the early 1910s. These studios, led by Natalia Davydova and Alexandra Exter, and Yevheniia Prybylska, respectively, engaged ‘leftist’ artists and local artisans to produce a new type of embroidery, relinquishing the mere stylization characteristic of other kustar studios in the Russian Empire. While scholars in Ukraine have undertaken extensive research to highlight the centrality of the Ukrainian context in progressive artists’ engagement with folk embroidery on the territory of the Russian Empire, internationally this phenomenon is still largely viewed under the generalized imperialist term of the ‘Russian avant-garde’. Using existing scholarship as the foundation, the present article seeks to redress this misconception. It also recognizes the long overdue need to situate the handicrafts revival movement in Ukraine within the broader framework of the engagement with vernacular culture by the nationally minded intelligentsia in East-Central Europe, while contrasting it with similar undertakings in Russia proper.
Improvement of the Sensor Capability of the NAO Robot by the Integration of a Laser Rangefinder
Authors: Bonaiuto Vincenzo , Zanela Andrea
Published: October 2022

This paper focuses on integrating a laser rangefinder system with an anthropomorphic robot (NAO6—Aldebaran, United Robotics Group) to improve its sensory and operational capabilities, as part of a larger project concerning the use of these systems in “assisted living” activities. This additional sensor enables the robot to reconstruct its surroundings by integrating new information with that identified by the on-board sensors. Thus, it can identify more objects in a scene and detect any obstacles along its navigation path. This feature will improve the efficiency of navigation algorithms, increasing movement competence in environments where people live and work. Indeed, these environments are characterized by details and specificities within a range of distances that best suit the new robot design. The paper presents a laser finder integration project that consists of two different parts, which are as follows: the former, the mechanical part, provided the NAO robot’s head; the latter, the software, provided the robot with proper software drivers to enable integration of the new sensor with its acquisition system. Some experimental results in an actual environment are presented.
The Effect of Model Resolution on the Vertical and Temporal Variation in the Simulated Martian Climate
Authors: Zhou Yu-Wei , Chow Kim-Chiu , Xiao Jing
Published: October 2022

To study the impact of model horizontal resolution on the simulated climate of Mars, we increased the model resolution of the Mars general circulation model MarsWRF from the commonly used 5° × 5° (standard resolution, SR) to 3° × 3° (high resolution, HR). We applied an interactive dust scheme to parameterize the dust-lifting process and investigated the effect of model resolution from three aspects: (1) temporal variation; (2) horizontal distribution; and (3) vertical distribution. From the results of the simulations, we obtained the following conclusions: (1) The seasonal variation in some zonal-mean fields such as the column optical depth and T15 temperature could be reasonably simulated in both the SR and HR simulations, and the results were similar. (2) The effect of resolution on the horizontal distribution of the climate fields was significant at some regions with complicated terrain. (3) The HR simulation could be different from the SR simulation in the vertical dynamic field and thermal field. To obtain more accurate simulation results, it is recommended to use a higher resolution simulation when the vertical distribution is a major concern in the study.
Multi-Hazard Assessment of a Flood Protection Levee
Authors: Selmi Mbarka , Hamdi Yasser , Moiriat Denis
Published: October 2022

Earthquake-induced liquefaction is one of the main causes of levee breaches that can threaten human life and property. Conventionally, liquefaction hazard has been assessed in terms of the factor of safety FoS against liquefaction which ignores the potential variability of groundwater table (GWT) due to precipitation events. A probabilistic methodology, taking into account these GWT variations over time, is therefore presented in this study to assess the liquefaction hazard of an earthen flood protection levee. A frequency analysis based on the Annual Maxima/Generalised Extreme Value (AM/GEV) approach is first used to characterize the distribution of GWT extreme values. The CPT-based method is then applied with the provided GWT scenarios to predict liquefaction and display the hazard curves. Assuming a single constant GWT estimate during an earthquake revealed a certain liquefaction hazard within a sandy layer. Considering GWT variations during earthquakes showed, however, that liquefaction is unlikely to occur with an FoS threshold set at 1.0. These findings highlight: (1) the conservatism of the conventional approach that overestimates the liquefaction hazard, (2) the importance of the proposed probabilistic approach as a complementary tool for more reliable decision-making, and (3) the dependency of liquefaction hazard predictions on the degree of uncertainty in GWT estimates and FoS threshold.
Evaluation of MODIS Dark Target AOD Product with 3 and 10 km Resolution in Amazonia
Authors: Palácios Rafael , Nassarden Danielle C. S. , Franco Marco A. , Morais Fernando G. , Machado Luiz A. T. , Rizzo Luciana V. , Cirino Glauber , Pereira Augusto G. C. , Ribeiro Priscila dos S. , Barros Lucas R. C. , Biudes Marcelo S. , Curado Leone F. A. , Rodrigues Thiago R. , Menezes Jorge , Landulfo Eduardo , Artaxo Paulo
Published: October 2022

The techniques and analyses employed by remote sensing provide key information about atmospheric particle properties at regional and global scales. However, limitations in optical spectral models used to represent the different types of aerosols in the atmosphere and their effects (direct and indirect) are still one of the major causes of sources of uncertainties and substantial impacts in climate prediction. There are no studies yet in South America, especially in the Amazon Basin, that have evaluated the advantages, disadvantages, inconsistencies, applicability, and suitability of the MODIS sensor (Moderate Resolution Imaging Spectroradiometer) destined for monitoring the ambient aerosol optical thickness over rivers and continents. In this study, the results of the DT (Dark Target) algorithm for products with 3 km and 10 km resolutions were systematically evaluated for six sites in the Amazon rainforest. The comparisons between the products were carried out with the AERONET (Aerosol Robotic Network) measurements, which were used as reference. Statistical parameters between AERONET vs. MODIS were also evaluated based on biomass burning records in the site regions. Here, the DT 10 km product showed satisfactory performance for the Amazon region, with observations between the expected error (EE) limits above 66%, in addition to R > 0.8 and RMSE < 0.3. However, the regional analysis for the two sites in the central and southern regions of the Amazon basin did not have the same performance, where the results showed an EE of 24 and 47%, respectively. The DT 3 km product did not perform well in any site, with an EE below 50%. Both products overestimated the AOD, but the 3 km product overestimated it approximately four times more due to its algorithm setup. Thus, we recommend the 10 km product for general analysis in Amazonia. Regional biomass burning records showed a direct relationship with the AERONET vs. MODIS DT with overestimation of both products. All variations between products and sites were justified based on the difficulty of retrieving surface reflectance and the model selected for local aerosols. Improvements in the optical spectral model currently implemented in the algorithms, with more realistic representations of the main types of the aerosol present in the Amazon Basin, may contribute to better performance among the evaluated products.
Comparison of Future Changes in Frequency of Climate Extremes between Coastal and Inland Locations of Bengal Delta Based on CMIP6 Climate Models
Authors: Das Samiran , Kamruzzaman Mohammad , Islam Abu Reza Md. Towfiqul , Zhu Dehua , Kumar Amit
Published: October 2022

Climate change is perceived to be the primary reason for the amplification of extreme climatic phenomena. Estimation of changes in extreme values under climate change thus plays an important role in disaster risk assessment and management. However, the different changes in extremes in two distinct regions: inland and coast under climate change are yet to be investigated meticulously. This study is intended to assess the changes in frequency of rainfall and temperature extremes under the impact of climate change in two distinct locations: coast and inland of Bengal delta, a region highly vulnerable to climate change. The multi-model ensemble (projections from CMIP6 framework) technique with the application of frequency analysis was employed to appraise the impact in two future time horizons. Results suggest that the inland estimate of extreme rainfall by the end of this century is barely able to exceed the coastal estimate of extreme rainfall in present conditions. The rate of increase of warm extremes is almost similar; however, with the cold extreme, the increase rate is a little higher inland than on the coast. In both regions, a greater rise in climate extremes is expected in the far future than in the near future. Overall, the coastal area is expected to be more vulnerable to flooding while the inland to drought under climate change in the Bengal delta region.
Interference Effects in Fully Differential Ionization Cross Sections near the Velocity Matching in P + He Collisions
Authors: Bastola Sujan , Dhital Madhav , Majumdar Shruti , Hasan Ahmad , Lomsadze Ramaz , Davis Jacob , Lamichhane Basu , Borbély Sandor , Nagy Ladislau , Schulz Michael
Published: October 2022

We performed a fully differential experimental and theoretical study on ionization of He in intermediate-energy collisions with protons for a small projectile coherence length. Data were taken for an ejected electron energy corresponding to a speed close to the projectile speed (velocity matching). In the fully differential angular electron distributions, a pronounced double-peak structure, observed previously for a coherence length much larger than the atomic size, is much less pronounced in the current data. This observation is interpreted in terms of interference between first-and higher-order transition amplitudes. Although there is large quantitative disagreement between experiment and theory, the qualitative agreement supports this interpretation.
Extended Gevrey Regularity via Weight Matrices
Authors: Teofanov Nenad , Tomić Filip
Published: October 2022

The main aim of this paper is to compare two recent approaches for investigating the interspace between the union of Gevrey spaces Gt(U) and the space of smooth functions C∞(U). The first approach in the style of Komatsu is based on the properties of two parameter sequences Mp=pτpσ, τ>0, σ>1. The other one uses weight matrices defined by certain weight functions. We prove the equivalence of the corresponding spaces in the Beurling case by taking projective limits with respect to matrix parameters, while in the Roumieu case we need to consider a larger space than the one obtained as the inductive limit of extended Gevrey classes.
Dynamical Analysis and Finite-Time Synchronization for a Chaotic System with Hidden Attractor and Surface Equilibrium
Authors: Zhang Runhao , Xi Xiaojian , Tian Huaigu , Wang Zhen
Published: October 2022

In this paper, a chaotic system with surface equilibrium and a hidden attractor was studied, and the dynamical behavior, synchronization scheme and circuit application of the system were analyzed. Firstly, the stability analysis and dynamic behavior of the system were carried out (the type of attractor, bifurcation, Poincaré section, Lyapunov exponents spectrum and complexity). Secondly, the finite-time synchronization observer was designed according to the finite-time stability theorem to achieve the synchronization of the finite-time master–slave systems, and the error system asymptotically approached zero. Finally, the existence and practicability of the original system were proven through the implementation of the circuit system, and through using an appropriate control circuit to realize the synchronization of chaotic master–slave systems.
First Passage Analysis in a Queue with State Dependent Vacations
Authors: Dshalalow Jewgeni , White Ryan
Published: October 2022

This paper deals with a single-server queue where the server goes on maintenance when the queue is exhausted. Initially, the maintenance time is fixed by deterministic or random number T. However, during server’s absence, customers are screened by a dispatcher who estimates his service times based on his needs. According to these estimates, the dispatcher shortens server’s maintenance time and as the result the server returns earlier than planned. Upon server’s return, if there are not enough customers waiting (under the N-Policy), the server rests and then resumes his service. At first, the input and service are general. We then prove a necessary and sufficient condition for a simple linear dependence between server’s absence time (including his rest) and the number of waiting customers. It turns out that the input must be (marked) Poisson. We use fluctuation and semi-regenerative analyses (previously established and embellished in our past work) to obtain explicit formulas for server’s return time and the queue length, both with discrete and continuous time parameter. We then dedicate an entire section to related control problems including the determination of the optimal T-value. We also support our tractable formulas with many numerical examples and validate our results by simulation.
Testing Multivariate Normality Based on t-Representative Points
Authors: Liang Jiajuan , He Ping , Yang Jun
Published: October 2022

Testing multivariate normality is an ever-lasting interest in the goodness-of-fit area since the classical Pearson’s chi-squared test. Among the numerous approaches in the construction of tests for multivariate normality, normal characterization is one of the common approaches, which can be divided into the necessary and sufficient characterization and necessary-only characterization. We construct a test for multivariate normality by combining the necessary-only characterization and the idea of statistical representative points in this paper. The main idea is to transform a high-dimensional sample into a one-dimensional one through the necessary normal characterization and then employ the representative-point-based Pearson’s chi-squared test. A limited Monte Carlo study shows a considerable power improvement of the representative-point-based chi-square test over the traditional one. An illustrative example is given to show the supplemental function of the new test when used together with existing ones in the literature.
Development and Environmental Assessment of a Phase Change Material Based Thermal Management System for Na/NiCl2 Batteries
Authors: Richter Maria , Dittrich Robert , Zindel Annika , Nousch Laura , Lehmann Michael , Franke Michael , Eißmann Nadine , Hutsch Thomas , Cerdas Felipe , Zellmer Sabrina , Herold Daniela
Published: October 2022

The sodium/nickel chloride battery (Na/NiCl2) is considered an eco-friendly, long-term stable and safe alternative to other secondary battery technologies. The overall system efficiency of this high-temperature battery can be increased by optimizing the thermal management system. This paper addresses the integration of a phase change material (PCM) into the battery modules and evaluates the thermal performance and environmental impact of such a design. The module layout with PCM and heat transfer elements (HTEs) was selected based on 2D FEM simulation results and verified in a prototype Na/NiCl2 module. It was shown that the module temperatures could be kept within the operating limits during operation by the HTEs and the PCM even at high current rates. Since no critical temperature limits were reached, the usable battery capacity was higher compared to results of a reference module without PCM or HTEs. In addition, the PCM prolonged the cooling down process after discharge. In parallel with the experimental studies, the environmental performance of the battery was evaluated using a life cycle assessment (LCA). Amongst other things, it was found that the application of PCM is also beneficial from an ecological point of view.
White Blood Cell Classification Using Multi-Attention Data Augmentation and Regularization
Authors: Bayat Nasrin , Davey Diane D. , Coathup Melanie , Park Joon-Hyuk
Published: October 2022

Accurate and robust human immune system assessment through white blood cell evaluation require computer-aided tools with pathologist-level accuracy. This work presents a multi-attention leukocytes subtype classification method by leveraging fine-grained and spatial locality attributes of white blood cell. The proposed framework comprises three main components: texture-aware/attention map generation blocks, attention regularization, and attention-based data augmentation. The developed framework is applicable to general CNN-based architectures and enhances decision making by paying specific attention to the discriminative regions of a white blood cell. The performance of the proposed method/model was evaluated through an extensive set of experiments and validation. The obtained results demonstrate the superior performance of the model achieving 99.69 % accuracy compared to other state-of-the-art approaches. The proposed model is a good alternative and complementary to existing computer diagnosis tools to assist pathologists in evaluating white blood cells from blood smear images.
Design of Inter-BAN Authentication Protocols for WBAN in a Cloud-Assisted Environment
Authors: Almuhaideb Abdullah M. , Alghamdi Huda A.
Published: October 2022

The Telecare Medical Information System (TMIS) is a technology used in Wireless Body Area Networks (WBAN) that is used efficiently for remote healthcare services. TMIS services can be provided as cloud computing services for storage and processing purposes. TMIS uses wearable sensors to collect patient data and transmit it to the controller node over a public channel. The data is then obtained from the controller node by the medical server and stored in the database for analysis. However, an attacker can attempt to launch attacks on data transferred across an unsecured channel. Several schemes have therefore been proposed to provide mutual authentication however, there are security and performance problems. Therefore, the research aims to design two secure and efficient inter-BAN authentication protocols for WBAN: protocol-I (P-I) for emergency authentication and protocol-II (P-II) for periodic authentication. To analyze the proposed protocols, we conduct an informal security analysis, implement Burrows-Abadi-Needham (BAN) logic analysis, validate the proposed protocols using the Automated Validation of Internet Security Protocols and Applications (AVISPA) simulation tool, and conduct a performance analysis. Consequently, we show that the proposed protocols meet all the security requirements in this research, achieve mutual authentication, prevent passive and active attacks, and have suitable performance for WBAN.
Latest Findings of the Regenerative Materials Application in Periodontal and Peri-Implant Surgery: A Scoping Review
Authors: Gallo Simone , Pascadopoli Maurizio , Pellegrini Matteo , Pulicari Federica , Manfredini Mattia , Zampetti Paolo , Spadari Francesco , Maiorana Carlo , Scribante Andrea
Published: October 2022

Regenerative dentistry represents a therapeutic modern approach involving biomaterials and biologics such as mesenchymal stem cells. The role of regenerative dentistry is promising in all branches of dentistry, especially in periodontology and implantology for the treatment of bony defects around teeth and implants, respectively. Due to the number of different materials that can be used for this purpose, the aim of the present review is to evidence the regenerative properties of different materials both in periodontitis and peri-implantitis as well as to compare their efficacy. Clinical trials, case-control studies, cross-sectional studies, and cohort studies have been considered in this review. The outcome assessed is represented by the regenerative properties of bone grafts, barrier membranes, and biological materials in the treatment of intrabony and furcation defects, peri-implantitis sites, alveolar ridge preservation, and implant site development. Based on the studies included, it can be stated that in the last years regenerative materials in periodontal and peri-implant defects treatments have shown excellent results, thus providing valuable support to surgical therapy. To achieve optimal and predictable results, clinicians should always consider factors like occlusal load control, prevention of microbial contamination, and wound dehiscence. Further evidence is required about the use of enamel matrix derivative in alveolar ridge preservation, as well as of stem cells and bone morphogenetic proteins-2 in furcation defects and peri-implantitis sites. Considering the high amount of research being conducted in this field, further evidence is expected to be obtained soon.
A Novel Method to Achieve Precision and Reproducibility in Exposure Parameters for Low-Frequency Pulsed Magnetic Fields in Human Cell Cultures
Authors: Ronniger Michael , Aguida Blanche , Stacke Christina , Chen Yangmengfan , Ehnert Sabrina , Erdmann Niklas , Eschenburg Georg , Falldorf Karsten , Pooam Marootpong , Wing Anthony , Ahmad Margaret
Published: October 2022

The effects of extremely low-frequency electromagnetic field (ELF-MF) exposure on living systems have been widely studied at the fundamental level and also claimed as beneficial for the treatment of diseases for over 50 years. However, the underlying mechanisms and cellular targets of ELF-MF exposure remain poorly understood and the field has been plagued with controversy stemming from an endemic lack of reproducibility of published findings. To address this problem, we here demonstrate a technically simple and reproducible EMF exposure protocol to achieve a standardized experimental approach which can be readily adopted in any lab. As an assay system, we chose a commercially available inflammatory model human cell line; its response to magnetic fields involves changes in gene expression which can be monitored by a simple colorimetric reporter gene assay. The cells were seeded and cultured in microplates and inserted into a custom-built, semi-automated incubation and exposure system which accurately controls the incubation (temperature, humidity, CO2) and magnetic-field exposure conditions. A specific alternating magnetic field (<1.0% spatial variance) including far-field reduction provided defined exposure conditions at the position of each well of the microplate. To avoid artifacts, all environmental and magnetic-field exposure parameters were logged in real time throughout the duration of the experiment. Under these extensively controlled conditions, the effect of the magnetic field on the cell cultures as assayed by the standardized operating procedure was highly reproducible between experiments. As we could fully define the characteristics (frequency, intensity, duration) of the pulsed magnetic field signals at the position of the sample well, we were, for the first time, able to accurately determine the effect of changing single ELF-MF parameters such as signal shape, frequency, intensity and duty cycle on the biological response. One signal in particular (10 Hz, 50% duty cycle, rectangular, bipolar, 39.6μT) provided a significant reduction in cytokine reporter gene expression by 37% in our model cell culture line. In sum, the accuracy, environmental control and data-logging capacity of the semi-automated exposure system should greatly facilitate research into fundamental cellular response mechanisms and achieve the consistency necessary to bring ELF-MF/PEMF research results into the scientific mainstream.
Hydrogen Dynamics in Hydrated Chitosan by Quasi-Elastic Neutron Scattering
Authors: Hirota Yuki , Tominaga Taiki , Kawabata Takashi , Kawakita Yukinobu , Matsuo Yasumitsu
Published: October 2022

Chitosan, an environmentally friendly and highly bio-producible material, is a potential proton-conducting electrolyte for use in fuel cells. Thus, to microscopically elucidate proton transport in hydrated chitosan, we employed the quasi-elastic neutron scattering (QENS) technique. QENS analysis showed that the hydration water, which was mobile even at 238 K, moved significantly more slowly than the bulk water, in addition to exhibiting jump diffusion. Furthermore, upon increasing the temperature from 238 to 283 K, the diffusion constant of water increased from 1.33 × 10−6 to 1.34 × 10−5 cm2/s. It was also found that a portion of the hydrogen atoms in chitosan undergo a jump-diffusion motion similar to that of the hydrogen present in water. Moreover, QENS analysis revealed that the activation energy for the jump-diffusion of hydrogen in chitosan and in the hydration water was 0.30 eV, which is close to the value of 0.38 eV obtained from the temperature-dependent proton conductivity results. Overall, it was deduced that a portion of the hydrogen atoms in chitosan dissociate and protonate the interacting hydration water, resulting in the chitosan exhibiting proton conductivity.
An Objective and Repeatable Sac Isolation Technique for Comparing Biomechanical Metrics in Abdominal Aortic Aneurysms
Authors: Chung Timothy K. , Gueldner Pete H. , Kickliter Trevor M. , Liang Nathan L. , Vorp David A.
Published: October 2022

(1) Abdominal aortic aneurysm (AAA) biomechanics-based metrics often reported may be over/under-estimated by including non-aneurysmal regions in the analyses, which is typical, rather than isolating the dilated sac region. We demonstrate the utility of a novel sac-isolation algorithm by comparing peak/mean wall stress (PWS, MWS), with/without sac isolation, for AAA that were categorized as stable or unstable in 245 patient CT image sets. (2) 245 patient computed tomography images were collected, segmented, meshed, and had subsequent finite element analysis performed in preparation of our novel sac isolation technique. Sac isolation was initiated by rotating 3D surfaces incrementally, extracting 2D projections, curve fitting a Fourier series, and taking the local extrema as superior/inferior boundaries for the aneurysmal sac. The PWS/MWS were compared pairwise using the entire aneurysm and the isolated sac alone. (3) MWS, not PWS, was significantly different between the sac alone and the entire aneurysm. We found no statistically significant difference in wall stress measures between stable (n = 222) and unstable (n = 23) groups using the entire aneurysm. However, using sac-isolation, PWS (24.6 ± 7.06 vs. 20.5 ± 8.04 N/cm2; p = 0.003) and MWS (12.0 ± 3.63 vs. 10.5 ± 4.11 N/cm2; p = 0.022) were both significantly higher in unstable vs. stable groups. (4) Our results suggest that evaluating only the AAA sac can influence wall stress metrics and may reveal differences in stable and unstable groups of aneurysms that may not otherwise be detected when the entire aneurysm is used.
Formation of Three-Dimensional Spheres Enhances the Neurogenic Potential of Stem Cells from Apical Papilla
Authors: Basabrain Mohammed S. , Zhong Jialin , Luo Haiyun , Liu Junqing , Yi Baicheng , Zaeneldin Ahmed , Koh Junhao , Zou Ting , Zhang Chengfei
Published: October 2022

Cell-based neural regeneration is challenging due to the difficulty in obtaining sufficient neural stem cells with clinical applicability. Stem cells from apical papilla (SCAPs) originating from embryonic neural crests with high neurogenic potential could be a promising cell source for neural regeneration. This study aimed to investigate whether the formation of 3D spheres can promote SCAPs’ neurogenic potential. Material and methods: Three-dimensional SCAP spheres were first generated in a 256-well agarose microtissue mold. The spheres and single cells were individually cultured on collagen I-coated μ-slides. Cell morphological changes, neural marker expression, and neurite outgrowth were evaluated by confocal microscope, ELISA, and RT-qPCR. Results: Pronounced morphological changes were noticed in a time-dependent manner. The migrating cells’ morphology changed from fibroblast-like cells to neuron-like cells. Compared to the 2D culture, neurite length, number, and the expression of multiple progenitors, immature and mature neural markers were significantly higher in the 3D spheres. BDNF and NGF-β may play a significant role in the neural differentiation of SCAP spheres. Conclusion: The formation of 3D spheres enhanced the neurogenic potential of SCAPs, suggesting the advantage of using the 3D spheres of SCAPs for treating neural diseases.
Plant Use Adaptation in Pamir: Sarikoli Foraging in the Wakhan Area, Northern Pakistan
Authors: Aziz Muhammad Abdul , Ullah Zahid , Adnan Muhammad , Sõukand Renata , Pieroni Andrea
Published: October 2022

The study recorded the food uses of wild food plants (WFPs) among the Sarikoli diaspora and the dominant Wakhi in Broghil Valley, North Pakistan, to understand their food adaptation, mainly by looking through the lens of food ethnobotanies. A total of 30 participants took part in the study, which included 15 elderly individuals from each ethnic group. Data were gathered through semi-structured interviews. We recorded 29 WFPs, mostly used as cooked vegetables and snacks. The food uses, as well as the local plant nomenclatures, linked to WFPs of the two studied groups were completely homogenized, which could be attributed to the cultural assimilation of the Sarikoli people to Wakhi culture. We found that although traditional knowledge on WFPs has been homogenized, social change in nearby regions is also threatening the traditional knowledge of the two communities, as evidenced by the smaller number of plants reported compared to that of all other field ethnobotanical studies conducted in nearby regions. Moreover, the growth of legal restrictions and sanctions on accessing natural resources are posing serious challenges to cultural resilience in the valley, and the restrictions on cross-border movement in particular are creating challenges for those who have cross-border kinship relationships between the two groups. We suggest specific measures, such as the promotion of food tourism and educational activities, to protect traditional knowledge and bicultural heritage from further erosion in the region.
Obtaining of Recombinant Camel Chymosin and Testing Its Milk-Clotting Activity on Cow’s, Goat’s, Ewes’, Camel’s and Mare’s Milk
Authors: Akishev Zhiger , Aktayeva Saniya , Kiribayeva Assel , Abdullayeva Aliya , Baltin Kairat , Mussakhmetov Arman , Tursunbekova Annelya , Ramankulov Yerlan , Khassenov Bekbolat
Published: October 2022

In the cheese-making industry, commonly chymosin is used as the main milk-clotting enzyme. Bactrian camel (Camelus bactrianus) chymosin (BacChym) has a milk-clotting activity higher than that of calf chymosin for cow’s, goat’s, ewes’, mare’s and camel’s milk. A procedure for obtaining milk-clotting reagent based on recombinant camel chymosin is proposed here. Submerged fermentation by a recombinant yeast (Pichia pastoris GS115/pGAPZαA/ProchymCB) was implemented in a 50 L bioreactor, and the recombinant camel chymosin was prepared successfully. The activity of BacChym in yeast culture was 174.5 U/mL. The chymosin was concentrated 5.6-fold by cross-flow ultrafiltration and was purified by ion exchange chromatography. The activity of the purified BacChym was 4700 U/mL. By sublimation-drying with casein peptone, the BacChym powder was obtained with an activity of 36,000 U/g. By means of this chymosin, cheese was prepared from cow’s, goat’s, ewes’, camel’s and mare’s milk with a yield of 18%, 17.3%, 15.9%, 10.4% and 3%, respectively. Thus, the proposed procedure for obtaining a milk-clotting reagent based on BacChym via submerged fermentation by a recombinant yeast has some prospects for biotechnological applications. BacChym could be a prospective milk-clotting enzyme for different types of milk and their mixtures.
Radiation-Induced Rescue Effect: Insights from Microbeam Experiments
Authors: Yu Kwan Ngok
Published: October 2022

The present paper reviews a non-targeted effect in radiobiology known as the Radiation-Induced Rescue Effect (RIRE) and insights gained from previous microbeam experiments on RIRE. RIRE describes the mitigation of radiobiological effects in targeted irradiated cells after they receive feedback signals from co-cultured non-irradiated bystander cells, or from the medium previously conditioning those co-cultured non-irradiated bystander cells. RIRE has established or has the potential of establishing relationships with other non-traditional new developments in the fields of radiobiology, including Radiation-Induced Bystander Effect (RIBE), Radiation-Induced Field Size Effect (RIFSE) and ultra-high dose rate (FLASH) effect, which are explained. The paper first introduces RIRE, summarizes previous findings, and surveys the mechanisms proposed for observations. Unique opportunities offered by microbeam irradiations for RIRE research and some previous microbeam studies on RIRE are then described. Some thoughts on future priorities and directions of research on RIRE exploiting unique features of microbeam radiations are presented in the last section.
Exposure of Pisum sativum L. Seeds to Methomyl and Imidacloprid Cause Genotoxic Effects in Pollen-Mother Cells
Authors: Siddiqui Sazada , Alrumman Sulaiman A.
Published: October 2022

Pesticides are commonly used in modern agricultural systems to protect the plants from pests. Even though they potentially increase the crop yield, they have undesirable toxic effects on the consumers of plant products and nontarget host plants. However, there are limited studies to demonstrate the cytological changes induced by pesticides on plant cells. In the present study, we assess the cytological changes induced by two most commonly used insecticides, methomyl (ME) and imidacloprid (IM), using Pisum sativum L. as model plant system. P. sativum seeds were exposed to various concentrations of ME and IM (0.1, 0.2, 0.3, 0.4 and 0.5%) for 1, 3, and 6 h, and their effects on seed germination (SG), radicle length (RL), mitotic index (MI), chromosomal aberrations frequency (CAF), and micronucleus frequency (MNF) were studied. The results indicate that these insecticides decrease MI in root-tip cells, and increase in the MNF in pollen-mother cells in a dose-dependent manner. Additionally, insecticide-treated groups showed a dose- and time-dependent increase in the percentage of aberrant meiotic cells. Clumped nuclei (CNU), stickiness (STC), bridges (BRs), laggards (LGs), secondary association (SA), and precocious separation (PS) were among the frequently observed anomalies. The findings of this study indicate that commonly used insecticides ME and IM have substantial genotoxic effects on the root-tip and pollen-mother cells of P. sativum L.