bluuebunny/crossref_metadata_2025 huggingface dataset:
Simultaneous Localization and Mapping (SLAM) for Autonomous Driving: Concept and Analysis
Authors: Zheng Shuran , Wang Jinling , Rizos Chris , Ding Weidong , El-Mowafy Ahmed
Published: February 2023

The Simultaneous Localization and Mapping (SLAM) technique has achieved astonishing progress over the last few decades and has generated considerable interest in the autonomous driving community. With its conceptual roots in navigation and mapping, SLAM outperforms some traditional positioning and localization techniques since it can support more reliable and robust localization, planning, and controlling to meet some key criteria for autonomous driving. In this study the authors first give an overview of the different SLAM implementation approaches and then discuss the applications of SLAM for autonomous driving with respect to different driving scenarios, vehicle system components and the characteristics of the SLAM approaches. The authors then discuss some challenging issues and current solutions when applying SLAM for autonomous driving. Some quantitative quality analysis means to evaluate the characteristics and performance of SLAM systems and to monitor the risk in SLAM estimation are reviewed. In addition, this study describes a real-world road test to demonstrate a multi-sensor-based modernized SLAM procedure for autonomous driving. The numerical results show that a high-precision 3D point cloud map can be generated by the SLAM procedure with the integration of Lidar and GNSS/INS. Online four–five cm accuracy localization solution can be achieved based on this pre-generated map and online Lidar scan matching with a tightly fused inertial system.
Multi-Instrumental Observations of Midlatitude Plasma Irregularities over Eastern Asia during a Moderate Magnetic Storm on 16 July 2003
Authors: Ye Hailun , Yi Wen , Zhou Baozhu , Wu Jianfei , Yu Bingkun , Tian Penghao , Wang Jianyuan , Long Chi , Lu Maolin , Xue Xianghui , Chen Tingdi , Dou Xiangkang
Published: February 2023

This study presents the observations of midlatitude plasma irregularities over Eastern Asia during a moderate magnetic storm on 16 July 2003. Multi-instrumental observations, including the ground-based ionosondes, the GNSS networks, and the CHAMP and ROCSAT-1 satellites, were utilized to investigate the occurrence and characteristics of midlatitude plasma irregularities. The midlatitude strong spread F (SSF) mainly occurred in the midnight–morning sector as observed by ionosondes over Japan during this storm. SSF was related to plasma depletions, which is also recorded by GNSS network in the form of the enhancement of the rate of total electron content (TEC) change index (ROTI). The possible mechanism for the generation of SSF is that the enhanced eastward electric fields, associated with the prompt penetration electric fields and disturbance dynamo electric fields, cause the uplift and latitudinal extension of equatorial plasma bubbles (EPBs) to generate the observed midlatitude SSF further. Meanwhile, plasma density increased significantly under the influence of this storm. In addition, other common type of spread F, frequency spread F (FSF), was observed over Japan on the non-storm day and/or at high latitude station WK545, which seems to be closely related to the coupling of medium-scale traveling ionospheric disturbances (MSTIDs) and sporadic E (Es) layer. The above results indicate that various types of midlatitude spread F can be produced by different physical mechanisms. It is found that SSF can significantly affect the performance of radio wave propagation compared with FSF. Our results show that space weather events have a significant influence on the day-to-day variability of the occurrence and characteristics of ionospheric F-region irregularities at midlatitudes.
Future Scenarios of Land Use/Land Cover (LULC) Based on a CA-Markov Simulation Model: Case of a Mediterranean Watershed in Morocco
Authors: Beroho Mohamed , Briak Hamza , Cherif El Khalil , Boulahfa Imane , Ouallali Abdessalam , Mrabet Rachid , Kebede Fassil , Bernardino Alexandre , Aboumaria Khadija
Published: February 2023

Modeling of land use and land cover (LULC) is a very important tool, particularly in the agricultural field: it allows us to know the potential changes in land area in the future and to consider developments in order to prevent probable risks. The idea is to give a representation of probable future situations based on certain assumptions. The objective of this study is to make future predictions in land use and land cover in the watershed “9 April 1947”, and in the years 2028, 2038 and 2050. Then, the maps obtained with the climate predictions will be integrated into an agro-hydrological model to know the water yield, the sediment yield and the water balance of the studied area by 2050.The future land use and land cover (LULC) scenarios were created using a CA-Markov forecasting model. The results of the simulation of the LULC changes were considered satisfactory, as shown by the values obtained from the kappa indices for agreement (κstandard) = 0.73, kappa for lack of information (κno) = 0.76, and kappa for location at grid cell level (κlocation) = 0.80. Future scenarios modeled in LULC indicate a decrease in agricultural areas and wetlands, both of which can be seen as a warning of crop loss. There is, on the other hand, an increase in forest areas that could be an advantage for the biodiversity of the fauna and flora in the “9 April 1947” watershed.
Post-Hurricane Damage Severity Classification at the Individual Tree Level Using Terrestrial Laser Scanning and Deep Learning
Authors: Klauberg Carine , Vogel Jason , Dalagnol Ricardo , Ferreira Matheus Pinheiro , Hamamura Caio , Broadbent Eben , Silva Carlos Alberto
Published: February 2023

Natural disturbances like hurricanes can cause extensive disorder in forest structure, composition, and succession. Consequently, ecological, social, and economic alterations may occur. Terrestrial laser scanning (TLS) and deep learning have been used for estimating forest attributes with high accuracy, but to date, no study has combined both TLS and deep learning for assessing the impact of hurricane disturbance at the individual tree level. Here, we aim to assess the capability of TLS and convolutional neural networks (CNNs) combined for classifying post-Hurricane Michael damage severity at the individual tree level in a pine-dominated forest ecosystem in the Florida Panhandle, Southern U.S. We assessed the combined impact of using either binary-color or multicolored-by-height TLS-derived 2D images along with six CNN architectures (Densenet201, EfficientNet_b7, Inception_v3, Res-net152v2, VGG16, and a simple CNN). The confusion matrices used for assessing the overall accuracy were symmetric in all six CNNs and 2D image variants tested with overall accuracy ranging from 73% to 92%. We found higher F-1 scores when classifying trees with damage severity varying from extremely leaning, trunk snapped, stem breakage, and uprooted compared to trees that were undamaged or slightly leaning (<45°). Moreover, we found higher accuracies when using VGG16 combined with multicolored-by-height TLS-derived 2D images compared with other methods. Our findings demonstrate the high capability of combining TLS with CNNs for classifying post-hurricane damage severity at the individual tree level in pine forest ecosystems. As part of this work, we developed a new open-source R package (rTLsDeep) and implemented all methods tested herein. We hope that the promising results and the rTLsDeep R package developed in this study for classifying post-hurricane damage severity at the individual tree level will stimulate further research and applications not just in pine forests but in other forest types in hurricane-prone regions.
Spatiotemporal Patterns and Regional Differences in Soil Thermal Conductivity on the Qinghai–Tibet Plateau
Authors: Liu Wenhao , Li Ren , Wu Tonghua , Shi Xiaoqian , Zhao Lin , Wu Xiaodong , Hu Guojie , Yao Jimin , Wang Dong , Xiao Yao , Ma Junjie , Jiao Yongliang , Wang Shenning , Zou Defu , Zhu Xiaofan , Chen Jie , Shi Jianzong , Qiao Yongping
Published: February 2023

The Qinghai–Tibet Plateau is an area known to be sensitive to global climate change, and the problems caused by permafrost degradation in the context of climate warming potentially have far-reaching effects on regional hydrogeological processes, ecosystem functions, and engineering safety. Soil thermal conductivity (STC) is a key input parameter for temperature and surface energy simulations of the permafrost active layer. Therefore, understanding the spatial distribution patterns and variation characteristics of STC is important for accurate simulation and future predictions of permafrost on the Qinghai–Tibet Plateau. However, no systematic research has been conducted on this topic. In this study, based on a dataset of 2972 STC measurements, we simulated the spatial distribution patterns and spatiotemporal variation of STC in the shallow layer (5 cm) of the Qinghai–Tibet Plateau and the permafrost area using a machine learning model. The monthly analysis results showed that the STC was high from May to August and low from January to April and from September to December. In addition, the mean STC in the permafrost region of the Qinghai–Tibet Plateau was higher during the thawing period than during the freezing period, while the STC in the eastern and southeastern regions is generally higher than that in the western and northwestern regions. From 2005 to 2018, the difference between the STC in the permafrost region during the thawing and freezing periods gradually decreased, with a slight difference in the western hinterland region and a large difference in the eastern region. In areas with specific landforms such as basins and mountainous areas, the changes in the STC during the thawing and freezing periods were different or even opposite. The STC of alpine meadow was found to be most sensitive to the changes during the thawing and freezing periods within the permafrost zone, while the STC for bare land, alpine desert, and alpine swamp meadow decreased overall between 2005 and 2018. The results of this study provide important baseline data for the subsequent analysis and simulation of the permafrost on the Qinghai–Tibet Plateau.
Point Cloud Instance Segmentation with Inaccurate Bounding-Box Annotations
Authors: Peng Yinyin , Feng Hui , Chen Tao , Hu Bo
Published: February 2023

Most existing point cloud instance segmentation methods require accurate and dense point-level annotations, which are extremely laborious to collect. While incomplete and inexact supervision has been exploited to reduce labeling efforts, inaccurate supervision remains under-explored. This kind of supervision is almost inevitable in practice, especially in complex 3D point clouds, and it severely degrades the generalization performance of deep networks. To this end, we propose the first weakly supervised point cloud instance segmentation framework with inaccurate box-level labels. A novel self-distillation architecture is presented to boost the generalization ability while leveraging the cheap but noisy bounding-box annotations. Specifically, we employ consistency regularization to distill self-knowledge from data perturbation and historical predictions, which prevents the deep network from overfitting the noisy labels. Moreover, we progressively select reliable samples and correct their labels based on the historical consistency. Extensive experiments on the ScanNet-v2 dataset were used to validate the effectiveness and robustness of our method in dealing with inexact and inaccurate annotations.
Proposal of Mapping Digital Twins Definition Language to Open Platform Communications Unified Architecture
Authors: Cavalieri Salvatore , Gambadoro Salvatore
Published: February 2023

The concept of Digital Twin is of fundamental importance to meet the main requirements of Industry 4.0. Among the standards currently available to realize Digital Twins there is the Digital Twins Definition Language. Digital Twin requires exchange of data with the real system it models and with other applications that use the digital replica of the system. In the context of Industry 4.0, a reference standard for an interoperable exchange of information between applications, is Open Platform Communications Unified Architecture. The authors believe that interoperability between Digital Twins and Open Platform Communications Unified Architectures communication standard should be enabled. For this reason, the main goal of this paper is to allow a Digital Twin based on the Digital Twins Definition Language to exchange data with any applications compliant to the Open Platform Communications Unified Architecture. A proposal about the mapping from Digital Twins Definition Language to the Open Platform Communications Unified Architecture will be presented. In order to verify the feasibility of the proposal, an implementation has been made by the authors, and its description will be introduced in the paper. Furthermore, the main results of the validation process accomplished on the basis of this implementation will be given.
Highly Elastically Deformable Coiled CNT/Polymer Fibers for Wearable Strain Sensors and Stretchable Supercapacitors
Authors: Choi Jin Hyeong , Noh Jun Ho , Choi Changsoon
Published: February 2023

Stretchable yarn/fiber electronics with conductive features are optimal components for different wearable devices. This paper presents the construction of coil structure-based carbon nanotube (CNT)/polymer fibers with adjustable piezoresistivity. The composite unit fiber is prepared by wrapping a conductive carbon CNT sheath onto an elastic spandex core. Owing to the helical coil structure, the resultant CNT/polymer composite fibers are highly stretchable (up to approximately 300%) without a noticeable electrical breakdown. More specifically, based on the difference in the coil index (which is the ratio of the coil diameter to the diameter of the fiber within the coil) according to the polymeric core fiber (spandex or nylon), the composite fiber can be used for two different applications (i.e., as strain sensors or supercapacitors), which are presented in this paper. The coiled CNT/spandex composite fiber sensor responds sensitively to tensile strain. The coiled CNT/nylon composite fiber can be employed as an elastic supercapacitor with excellent capacitance retention at 300% strain.
LP-MAB: Improving the Energy Efficiency of LoRaWAN Using a Reinforcement-Learning-Based Adaptive Configuration Algorithm
Authors: Teymuri Benyamin , Serati Reza , Anagnostopoulos Nikolaos Athanasios , Rasti Mehdi
Published: February 2023

In the Internet of Things (IoT), Low-Power Wide-Area Networks (LPWANs) are designed to provide low energy consumption while maintaining a long communications’ range for End Devices (EDs). LoRa is a communication protocol that can cover a wide range with low energy consumption. To evaluate the efficiency of the LoRa Wide-Area Network (LoRaWAN), three criteria can be considered, namely, the Packet Delivery Rate (PDR), Energy Consumption (EC), and coverage area. A set of transmission parameters have to be configured to establish a communication link. These parameters can affect the data rate, noise resistance, receiver sensitivity, and EC. The Adaptive Data Rate (ADR) algorithm is a mechanism to configure the transmission parameters of EDs aiming to improve the PDR. Therefore, we introduce a new algorithm using the Multi-Armed Bandit (MAB) technique, to configure the EDs’ transmission parameters in a centralized manner on the Network Server (NS) side, while improving the EC, too. The performance of the proposed algorithm, the Low-Power Multi-Armed Bandit (LP-MAB), is evaluated through simulation results and is compared with other approaches in different scenarios. The simulation results indicate that the LP-MAB’s EC outperforms other algorithms while maintaining a relatively high PDR in various circumstances.
SwimmerNET: Underwater 2D Swimmer Pose Estimation Exploiting Fully Convolutional Neural Networks
Authors: Giulietti Nicola , Caputo Alessia , Chiariotti Paolo , Castellini Paolo
Published: February 2023

Professional swimming coaches make use of videos to evaluate their athletes’ performances. Specifically, the videos are manually analyzed in order to observe the movements of all parts of the swimmer’s body during the exercise and to give indications for improving swimming technique. This operation is time-consuming, laborious and error prone. In recent years, alternative technologies have been introduced in the literature, but they still have severe limitations that make their correct and effective use impossible. In fact, the currently available techniques based on image analysis only apply to certain swimming styles; moreover, they are strongly influenced by disturbing elements (i.e., the presence of bubbles, splashes and reflections), resulting in poor measurement accuracy. The use of wearable sensors (accelerometers or photoplethysmographic sensors) or optical markers, although they can guarantee high reliability and accuracy, disturb the performance of the athletes, who tend to dislike these solutions. In this work we introduce swimmerNET, a new marker-less 2D swimmer pose estimation approach based on the combined use of computer vision algorithms and fully convolutional neural networks. By using a single 8 Mpixel wide-angle camera, the proposed system is able to estimate the pose of a swimmer during exercise while guaranteeing adequate measurement accuracy. The method has been successfully tested on several athletes (i.e., different physical characteristics and different swimming technique), obtaining an average error and a standard deviation (worst case scenario for the dataset analyzed) of approximately 1 mm and 10 mm, respectively.
Application of 3D Printing Technology in Sensor Development for Water Quality Monitoring
Authors: Sun Yifan , Li Dunzhu , Shi Yunhong , Wang Zeena , Okeke Saviour I. , Yang Luming , Zhang Wen , Zhang Zihan , Shi Yanqi , Xiao Liwen
Published: February 2023

The development of sensors for water quality monitoring is crucial to protect water quality, aquatic biota and human health. Traditional sensor manufacturing methods have significant drawbacks, such as low fabrication freedom, limited material choice and expensive manufacturing cost. As a possible alternative method, 3D printing technologies are increasingly popular in sensor development due to their high versatility, fast fabrication/modification, powerful processing of different materials and ease of incorporation with other sensor systems. Surprisingly, a systematic review examining the application of 3D printing technology in water monitoring sensors has not yet been conducted. Here, we summarized the development history, market share and advantages/disadvantages of typical 3D printing techniques. Specifically focused on the 3D-printed sensor for water quality monitoring, we then reviewed the applications of 3D printing in the development of sensors’ supporting platform, cell, sensing electrode as well as all-3D-printed sensors. The fabrication materials and processing, and the sensor’s performances regarding detected parameters, response time and detection limit/sensitivity, were also compared and analyzed. Finally, the current drawbacks of 3D-printed water sensors and potential directions for future study were discussed. This review will substantially promote the understanding of 3D printing technology used in water sensor development and benefit the protection of water resources.
Open Data Insights from a Smart Bridge Datathon: A Multi-Stakeholder Observation of Smart City Open Data in Practice
Authors: Cammers-Goodwin Sage
Published: February 2023

“Open Data” efforts are growing, especially in Europe, where open data are seen as a possible ethical driver of innovation. As smart cities continue to develop, it is important to explore how open data will affect the stakeholders of smart public spaces. Making data open and accessible not only has a managerial and technical component but also creates opportunities to shift power dynamics by granting individuals (and entities) access to data they might not otherwise be able to obtain. The scope of those who could access these data is wide, including data-illiterate citizens, burgeoning startups, and foreign militaries. This paper details the process of making data “open” from the MX3D smart bridge in Amsterdam through a “datathon”. The development and outcomes of opening the data and the event itself bring us closer to understanding the complexity of open data access and the extent to which it is useful or empowering for members of the public. While open data research continues to expand, there is still a dearth of studies that qualitatively detail the process and stakeholder concerns for a modern smart city project. This article serves to fill this gap.
Studying at a New Remote University Campus: Challenges and Strategies in Students’ Sustainable Self-Development
Authors: Zeng Wenyu , Wu Shiyong , Chen Wei
Published: February 2023

In the context of higher education expansion, student enrolment in remote branch campuses within China has increased dramatically, but the challenges and strategies for the sustainability of these students are not adequately reflected in the literature. This study investigated students’ learning experiences at a newly remote university campus, concentrating on the challenges students encounter and the strategies they adopt. We recruited 30 university students studying at a remote branch campus in China as the research subjects and employed interpretative phenomenological analysis to explore participants’ experiences. The findings indicated that students are challenged by the learning atmosphere, the number and quality of teachers, learning spaces, the campus and urban environment, and university and community culture. In response to various challenges, students tend to adopt self-adjustment strategies rather than seeking support from the institution. It can be concluded that students’ sustainability at the new remote branch campus is influenced by learning, environmental and culture-related factors, and students develop an attitude of helplessness. Strategic interventions should be adopted to enhance their learning experience and promote sustainable development.
Analyzing Interdependencies among Influencing Factors in Smart Manufacturing
Authors: Abdullah Fawaz , Al-Ahmari Abdulrahman , Anwar Saqib
Published: February 2023

The manufacturing industry has grown increasingly computerized and complex. Such changes are brought about mainly by adopting Industry 4.0 (I4) technologies. I4.0 promises a future of mass-producing highly individualized goods via responsive, autonomous, and cost-effective manufacturing operations. Adopting I4.0 technologies significantly improves a company’s productivity, efficiency, effectiveness, innovation, sustainable management, and sustainability. As is well known, implementing I4.0 technologies results in smart and sustainable manufacturing outputs. Despite their significance, I4.0 technologies have received less attention in the literature, and their influence on MSOs is unknown. This study analyzes the factors influencing manufacturing strategy outputs (MSOs), adopting I4.0 technologies using the fuzzy DEMATEL method. This research utilizes the fuzzy DEMATEL method to address the vagueness and uncertainties inherent in human judgments. Furthermore, this method is utilized to determine the cause-and-effect relationship and analyze the interdependence of factors. It explores the interrelationships among MSO factors from the perspectives of academic and industry experts. Identifying cause-and-effect aspects boosts the market’s competitiveness and prioritizes them. The results demonstrated that cost, quality, and performance are the most influential factors on MSOs.
The Sustainability of Emerging Social Vulnerabilities: The Hikikomori Phenomenon in Southern Italy
Authors: Esposito Vincenzo , Addeo Felice , D’Auria Valentina , Lenzi Francesca Romana
Published: February 2023

We can classify the Hikikomori phenomenon with the classification of “social pathology”: the Hikikomori phenomenon, and its spread in society, appear to be a real danger to the sustainability and resilience of the very society in which it occurs. This is because the social isolation of an individual, especially if young and non-independent, impacts the community of reference in human, economic and psychological terms. Therefore, an analysis that investigates the social aspects of the Hikikomori phenomenon cannot disregard the fact that it can be said to be sustainable in the community of reference within which it occurs. This, without wishing to produce a judgment on the merits of the social pathology, is relevant to assessing the capacity of that community to sustain its presence and spread and the human and social costs required to contain it. The research aims to explore the Hikikomori phenomenon in the context of Southern Italy, considering it as an emerging social vulnerability that impacts very deeply onto the sustainability of a social, economic and community systems such as the Campania region one. The following paper therefore presents empirical work conducted in southern Italy, in the Campania region. The methodology used is Mixed Methods, and the research design is Sequential Exploratory. The respondents were reached through the help of the association Hikikomori Italia.
Brewer’s Spent Grain Used in Fiber-Enriched Burgers—Influence of Sustainability Information on Consumer Responses
Authors: Curutchet Ana , Arcia Patricia , Prisco Fátima , Tarrega Amparo
Published: February 2023

Brewer’s spent grain (BSG) is the main brewery by-product, whose main use is animal feed but its incorporation into food can improve nutritional quality and sustainability. However, consumers base food preferences on packaging cues that assign meaning to food products. Furthermore, sustainability communication in food is poorly studied. Therefore, the objective of this work was to study the effect of communicating BSG enrichment in beef burgers on consumer responses. Three burger brands were considered and three labels were designed that included information about the addition of fiber. A total of 276 Uruguayans completed an online survey to measure their purchase intention. The way participants were informed about fiber addition did not influence their responses and the brand was the only factor that affected the results. Cluster analysis was applied, identifying four clusters. The brand was always the only significant variable and two of the clusters were highly interested in purchasing the fiber-enriched burgers. The results suggest consumers are interested in the inclusion of BSG in their products and expect information on the origin of the ingredient but not deep communication about the concept of ‘by-products.’
Investigating Extreme Snowfall Changes in China Based on an Ensemble of High-Resolution Regional Climate Models
Authors: Zhu Jinxin , Weng Xuerou , Guo Bing , Zeng Xueting , Dong Cong
Published: February 2023

Anthropogenically induced global warming intensifies the water cycle around the world. As a critical sector of the water cycle, snow depth and its related extremes greatly impact agriculture, animal husbandry, and food security, yet lack investigation. In this study, five high-resolution climate models are selected to simulate and project snow depth and its extremes over China. The simulation capabilities of models in reproducing the basic climate variables in winter are gauged in terms of spatial and temporal patterns over nine subregions. It is found that the driving global climate model (GCM) can contribute to similar patterns, while the different regional climate model (RCM) schemes lead to large variations in the snowfall accumulating on the land surface. The warming magnitude is larger under a higher representative concentration pathway (RCP) scenario (2.5 °C greater under RCP8.5 than RCP4.5). The distribution of ensemble mean winter precipitation changes is more fragmented because of the relatively low skill in reproducing water-related content in the climate system. The projected precipitation change is larger under RCP8.5 than under RCP4.5 due to the amplification of the hydrological cycle by temperature warming. The projected changes in the ensemble mean snow depth mainly occur over the Tibetan Plateau with a decreasing trend. Only several grids over the Himalayas Mountains and the upper stream of the Yarlung Zangbo River are projected with a slight increase in snow depth. Both the intensity and frequency of extreme snow events are projected to increase in Northeast China and Inner Mongolia, which are important agricultural and animal husbandry production areas in China. The reason behind this projection can be explained by the fact that the hydrological cycle intensified by temperature warming leads to excessive snowfall stacking up during winter. The changes in extreme snowfall events in the future will have a significant impact on China’s agricultural and animal husbandry production and threaten food security.
Sustainable Business Model Design: A Multi-Case Approach Exploring Generic Strategies and Dynamic Capabilities on the Example of German Wine Estates
Authors: Dressler Marc
Published: February 2023

Business model design needs to encounter increasing and highly dynamic challenges due to counter-caesural environmental changes. Empirical research on strategic sustainability is expected to provide guidance for needed dynamic transformation and sustainability. The reported research builds on a multi-case research of four German wine estates. The cases each represent a specific generic strategic grouping and distinct business models and are thereby suited to analyse sustainability by leaning on the concept of dynamic capabilities. Sustainability was examined as a strategic vehicle for innovation in the wine industry and a nuanced view of dynamic capabilities. Premium strategist turned out to strongly engage and profile in sustainability with aligned dynamic capabilities as a building block to generate premium products. Quality leadership also leverages product quality with comprehensive dynamic capabilities aiming for sustainability by building on size and a professional structure but less on environmental profiling. The price–value strategy approaches sustainability primarily from a market-based and circular economy view. Niche strategist’s dynamic capabilities in the analysed population illustrated an entrepreneurial and effectuation-based approach with specific dynamic capabilities fine-tuned to exploit market opportunities. The multi-case analyses thereby allowed us to identify strategy-specific and business-model-suiting capabilities.
Kinematics Modeling and Singularity Analysis of a 6-DOF All-Metal Vibration Isolator Based on Dual Quaternions
Authors: Zheng Chao , Zou Luming , Zheng Zhi , Xue Xin
Published: February 2023

Driven by the need for impact resistance and vibration reduction for mechanical devices in extreme environments, an all-metal vibration isolator with 6-degree-of-freedom (6-DOF) motion that is horizontally symmetrical was developed. Its stiffness and damping ability are provided by oblique springs in symmetrical arrangement and a metal–rubber elasto-porous damper. The spring is symmetrically distributed in the center axis of the support load surface. It is necessary to investigate the kinematics and the singularity before conducting multi-body dynamics analysis of the vibration isolator. Based on the theory of dual quaternions, the forward kinematics equations of the isolator were successively derived for theoretical kinematics modeling. In addition, an enhanced Broyden numerical iterative algorithm was developed and applied to the numerical solution of the forward kinematics equations of the vibration isolator. Compared with the traditional rotation-matrix method and Newton–Raphson method, the computational efficiency of the enhanced Broyden numerical iterative algorithm was increased by 680% and 290%, respectively. This was due to the enhanced algorithm without the calculations of any inverse matrix and forward kinematics equations. Finally, according to the forward kinematics Jacobian matrix, the position-singularity trajectory at a given orientation and the orientation-singularity space at a given position are calculated, which provides a basis for the algorithm of the 6-DOF vibration isolator to avoid singular positions and orientations.
Shot Boundary Detection Based on Global Features and the Target Features
Authors: Li Qiuling , Chen Xiao , Wang Bingbing , Liu Jing , Zhang Guofeng , Feng Bin
Published: February 2023

Video processing plays an important role in the intelligent monitoring and management system of agricultural information. Video shot boundary detection is the basic symmetry step underlying video processing techniques. According to the current shot boundary detection algorithm, the feature changes between gradual transition frames are difficult to detect, and the misdetection situation is caused by ignoring the attention of the target feature during the feature extraction. A novel symmetry multi-step comparative scheme of shot boundary detection algorithm based on global features and target features is proposed. First, the RGB color histogram features of the video frame are extracted. Second, foreground object detection for the video frames is performed using the Gaussian Mixture Model (GMM), and the scale-invariant features transformation (SIFT) of the foreground targets is extracted. Finally, global features and target features fusion through weights, calculating the difference between adjacent frames across multiple steps, generate a pattern distance map. The pattern distance map of the gradual transition and the cut detection is different; we can judge the gradual transition and the cut detection according to the pattern distance map. Experiments show that the proposed symmetry method improves by about 2% in recall and accuracy compared to other algorithms.
Heavy Metals Content in Selected Medicinal Plants Produced and Consumed in Serbia and Their Daily Intake in Herbal Infusions
Authors: Kandić Irina , Kragović Milan , Petrović Jelena , Janaćković Peđa , Gavrilović Milan , Momčilović Miloš , Stojmenović Marija
Published: February 2023

The heavy metals content (HMs) was investigated in 14 different medicinal plants collected from the three regions in Central Serbia, Zlatar, Sokobanja, and Kopaonik. The concentrations of Cd, Cr, Ni, Hg and Pb were determined: Cd (<0.03–2.72 mg/kg); Cr (<0.08–12.1 mg/kg); Ni (<0.08–12.2 mg/kg); Pb (0.6–49.0 mg/kg); the Hg concentration was below the detection limit of 0.06 mg/kg in all samples. The daily intake of HMs due to ingestion of 200 mL of herbal infusion was in all cases below the recommended limit prescribed by the World Health Organization. The estimated daily intake values were below the values for the oral reference dose regulated by the U.S. Environmental Protection Agency (USA EPA). The target hazard quotient and hazard index for Cd, Cr Ni, and Pb were below 1. Nevertheless, due to the tendency of heavy metals to accumulate in the organism, attention should be paid to the daily intake of herbal infusion during long-term usage. Specifically, it is recommended to consume not more than one cup (200 mL) of infusion per day made from thyme (Mt. Zlatar) and blueberry (Mt. Kopaonik), and not more than two cups per day for other herbs.
Compliance between Food and Feed Safety: Eight-Year Survey (2013–2021) of Aflatoxin M1 in Raw Milk and Aflatoxin B1 in Feed in Northern Italy
Authors: Ferrari Luca , Rizzi Nicoletta , Grandi Elisa , Clerici Eleonora , Tirloni Erica , Stella Simone , Bernardi Cristian Edoardo Maria , Pinotti Luciano
Published: February 2023

Aflatoxins (AFs) are fungal metabolites that are found in feed and food. When ruminants eat feed contaminated with aflatoxin B1 (AFB1), it is metabolised and aflatoxin M1 (AFM1) is excreted in the milk. Aflatoxins can result in hepatotoxic, carcinogenic, and immunosuppressive effects. The European Union thus set a low threshold limit (50 ng/L) for presence of AFM1 in milk. This was in view of its possible presence also in dairy products and that quantification of these toxins is mandatory for milk suppliers. In the present study, a total of 95,882 samples of whole raw milk, collected in northern Italy between 2013 and 2021, were evaluated for presence of AFM1 using an ELISA (enzyme-linked immunosorbent assay) method. The study also evaluated the relationship between feed materials collected from the same farms in the same area during the same period (2013–2021) and milk contamination. Only 667 milk samples out of 95,882 samples analysed (0.7%) showed AFM1 values higher than the EU threshold limit of 50 ng/L. A total of 390 samples (0.4%) showed values between 40 and 50 ng/L, thus requiring corrective action despite not surpassing the regulatory threshold. Combining feed contamination and milk contamination data, some feedingstuffs seem to be more effective in defying potential carryover of AFs from feed to milk. Combining the results, it can be concluded that a robust monitoring system that covers both feed, with a special focus on high risk/sentinel matrices, and milk is essential to guarantee high quality and safety standards of dairy products.
The Theoretical Description of the Transverse Momentum Spectra: A Unified Model
Authors: Gupta Rohit , Menon Anjaly , Jain Shubhangi , Jena Satyajit
Published: February 2023

Analysis of transverse momentum distributions is a useful tool to understand the dynamics of relativistic particles produced in high-energy collisions. Finding a proper distribution function to approximate the spectra is a vastly developing area of research in particle physics. In this work, we have provided a detailed theoretical description of the unified statistical framework in high-energy physics. We have tested the applicability of this framework on experimental data by analyzing the transverse momentum spectra of pion produced in heavy-ion collision at RHIC and LHC. We have also attempted to explain the transverse momentum spectra of charged hadrons formed in pp collision at different energies using the unified statistical framework. This formalism has been proved to nicely explain the spectra of particles produced in soft processes as well as hard scattering processes in a consistent manner.
Phage Therapy in Germany—Update 2023
Authors: Willy Christian , Bugert Joachim J. , Classen Annika Y. , Deng Li , Düchting Anja , Gross Justus , Hammerl Jens A. , Korf Imke H. E. , Kühn Christian , Lieberknecht-Jouy Simone , Rohde Christine , Rupp Markus , Vehreschild Maria J. G. T. , Vogele Kilian , Wienecke Sarah , Witzenrath Martin , Würstle Silvia , Ziehr Holger , Moelling Karin , Broecker Felix
Published: February 2023

Bacteriophage therapy holds promise in addressing the antibiotic-resistance crisis, globally and in Germany. Here, we provide an overview of the current situation (2023) of applied phage therapy and supporting research in Germany. The authors, an interdisciplinary group working on patient-focused bacteriophage research, addressed phage production, phage banks, susceptibility testing, clinical application, ongoing translational research, the regulatory situation, and the network structure in Germany. They identified critical shortcomings including the lack of clinical trials, a paucity of appropriate regulation and a shortage of phages for clinical use. Phage therapy is currently being applied to a limited number of patients as individual treatment trials. There is presently only one site in Germany for large-scale good-manufacturing-practice (GMP) phage production, and one clinic carrying out permission-free production of medicinal products. Several phage banks exist, but due to varying institutional policies, exchange among them is limited. The number of phage research projects has remarkably increased in recent years, some of which are part of structured networks. There is a demand for the expansion of production capacities with defined quality standards, a structured registry of all treated patients and clear therapeutic guidelines. Furthermore, the medical field is still poorly informed about phage therapy. The current status of non-approval, however, may also be regarded as advantageous, as insufficiently restricted use of phage therapy without adequate scientific evidence for effectiveness and safety must be prevented. In close coordination with the regulatory authorities, it seems sensible to first allow some centers to treat patients following the Belgian model. There is an urgent need for targeted networking and funding, particularly of translational research, to help advance the clinical application of phages.
Determinants of Chikungunya and O’nyong-Nyong Virus Specificity for Infection of Aedes and Anopheles Mosquito Vectors
Authors: Cottis Solène , Blisnick Adrien A. , Failloux Anna-Bella , Vernick Kenneth D.
Published: February 2023

Mosquito-borne diseases caused by viruses and parasites are responsible for more than 700 million infections each year. Anopheles and Aedes are the two major vectors for, respectively, malaria and arboviruses. Anopheles mosquitoes are the primary vector of just one known arbovirus, the alphavirus o’nyong-nyong virus (ONNV), which is closely related to the chikungunya virus (CHIKV), vectored by Aedes mosquitoes. However, Anopheles harbor a complex natural virome of RNA viruses, and a number of pathogenic arboviruses have been isolated from Anopheles mosquitoes in nature. CHIKV and ONNV are in the same antigenic group, the Semliki Forest virus complex, are difficult to distinguish via immunodiagnostic assay, and symptomatically cause essentially the same human disease. The major difference between the arboviruses appears to be their differential use of mosquito vectors. The mechanisms governing this vector specificity are poorly understood. Here, we summarize intrinsic and extrinsic factors that could be associated with vector specificity by these viruses. We highlight the complexity and multifactorial aspect of vectorial specificity of the two alphaviruses, and evaluate the level of risk of vector shift by ONNV or CHIKV.
Metastatic Multifocal Malignant Peripheral Nerve Sheath Tumour in the Cervicothoracic Spinal Cord of a Dog Initially Mimicking Meningomyelitis
Authors: Espinosa Javier , Ortega María , Pumarola Martí , Fraga Eduardo , Martín Laura
Published: February 2023

A nine year old cross-breed dog was presented with a two week history of ambulatory tetraparesis and proprioceptive ataxia affecting all four limbs. Meningomyelitis of Unknown Origin (MUO) was presumptively diagnosed based on the magnetic resonance imaging (MRI) findings and cerebrospinal fluid (CSF) analysis. The dog received a tapering dose of glucocorticoids and cyclosporine, showing significant improvement and the stabilization of the clinical signs for seven months. After this period, the dog showed an acute clinical deterioration and a follow-up MRI revealed new multiple lesions affecting different spinal nerve roots along the cervicothoracic spinal cord. Following euthanasia, a final diagnose of multiple malignant peripheral nerve sheath tumors (MPNSTs) was made based on the histopathological examination. MPNSTs can affect the cranial nerves, spinal nerves or the associated nerve roots at any location and can lead to secondary spinal cord compression. The aim of the present case report is to describe the clinical presentation and atypical MRI findings of a dog with histologically confirmed multiple MPNSTs. According to the reviewed literature, this is the first reported case of simultaneous MPNSTs in the cervicothoracic spinal cord of a dog.
Detection of Endoparasites in Non-Native Raccoons from Central Italy
Authors: Lombardo Andrea , Diano Marco , Brocherel Giuseppina , Palmerini Lucia , Giovannini Serena , Mezher Ziad , Iurescia Manuela , Cerci Tamara , Caprioli Andrea , Eleni Claudia , Raso Caterina , Mariacher Alessia , Del Lesto Irene , Cappai Nadia , Mattioli Luca , De Liberato Claudio , Fichi Gianluca
Published: February 2023

The raccoon (Procyon lotor) is a carnivore native to North and Central America, gradually introduced into Asia and Europe, including Italy. It is an important carrier of multiple endoparasites, both Protozoa and Helminths, some of them being zoonotic. The aim of this study was to investigate the endoparasites of the non-native raccoon population of Central Italy. Sixty-two raccoons were collected by local competent authorities (sixty trapped and euthanized, two found dead) and subjected to necroscopic examination. Carcasses underwent a broad parasitological investigation, including coprological techniques (macroscopic examination of the gastrointestinal tract, lungs, trachea, and heart, Flotac®, Baermann test, and immunofluorescence for Giardia duodenalis and Cryptosporidium spp.), research on respiratory/urinary capillariosis and artificial digestion for Trichinella spp. larvae, and a histopathological examination of the ileum. Ascarid parasites were further identified at the species level using a next-generation sequencing-based amplicon sequencing approach. The results showed the presence of different Protozoa and Nematodes: Baylisascaris procyonis (26/62; 41.9%), Pearsonema sp. (6/62; 9.6%), Capillariidae (6/62; 9.6%), Eimeria sp. (2/62; 3.2%), Cryptosporidium sp. (2/62; 3.2%), and Ancylostomatidae (2/62; 3.2%). B. procyonis is an emerging helminthic zoonotic agent considered a serious concern for public and animal health, given the possibility of its transmission to paratenic hosts, including humans and pets. The demonstrated role of the raccoon as a multi-parasite carrier should be an incentive to continuing the eradication/control of this alien species, and supports the need to implement related disease surveillance programs.
Multifunctional Chitosan/Xylan-Coated Magnetite Nanoparticles for the Simultaneous Adsorption of the Emerging Contaminants Pb(II), Salicylic Acid, and Congo Red Dye
Authors: Farghal Hebatullah H. , Nebsen Marianne , El-Sayed Mayyada M. H.
Published: February 2023

In this work, we develop chitosan/xylan-coated magnetite (CsXM) nanoparticles as eco-friendly efficient adsorbents for the facile removal of contaminants from water. Characterization of CsXM using Fourier Transform Infra-Red (FTIR) Spectroscopy, Scanning Electron Microscopy (SEM), X-Ray Diffraction (XRD), Thermogravimetric Analysis (TGA), Transmission Electron Microscopy (TEM), Zeta potential measurements, and Brunauer-Emmet-Teller (BET) analysis, confirmed the successful preparation of a chitosan/xylan complex coated over magnetite, which is characterized by being mesoporous, thermally stable and of neutral charge. Three contaminants, Pb(II), salicylic acid (SA), and congo red (CR), were chosen as representative pollutants from three major classes of contaminants of emerging concern: heavy metals, pharmaceuticals, and azo dyes. Pb(II), SA, and CR at initial concentrations of 50 ppm were removed by 64.49, 62.90, and 70.35%, respectively, on applying 6 g/L of CsXM. The contaminants were successfully removed in ternary systems, with Pb (II) and SA being more competitive in their adsorption than CR. Adsorption followed the Freundlich isotherm model and the pseudo-second order kinetic model, while the binding was suggested to occur mainly via chemical chelation for Pb(II) and physical interaction for SA and CR, which demonstrates the multifunctional potential of the nanoparticles to capture different contaminants regardless of their charge.