bluuebunny/crossref_metadata_2025 huggingface dataset:
Who Was Wrong? An Object Detection Based Responsibility Assessment System for Crossroad Vehicle Collisions
Authors: Yawovi Helton Agbewonou , Kikuchi Masato , Ozono Tadachika
Published: October 2022

Car crashes, known also as vehicle collisions, are recurrent events that occur every day. As long as vehicles exist, vehicle collisions will, unfortunately, continue to occur. When a car crash occurs, it is important to investigate and determine the actors’ responsibilities. The police in charge of that task, as well as claims adjusters, usually process manually by going to the crash spot, collecting data on the field, drafting the crash, and assessing responsibilities based on road rules. This later task of assessing responsibilities usually takes time and requires enough knowledge of road rules. With the aim to support the police and claims adjusters and simplify the process of responsibility determination, we built a system that can automatically assess actors’ responsibilities within a crossroad crash. The system is mainly based on image detection and uses a rule-based knowledge system to assess responsibilities within driving recorders’ videos. It uses the crash video recorded by one of the involved vehicles’ driving recorders as the input data source and outputs the evaluation of each actor’s responsibility within the crash. The rule-based knowledge system was implemented to make the reasoning about responsibility assessment clear and allow users to easily understand the reasons for the results. The system consists of three modules: (a) a crash time detection module, (b) a traffic sign detection module, and (c) a responsibility assessment module. To detect a crash within a video, we discovered that the simple application of existing vehicle detection models would result in wrong detections with many false positives. To solve the issue, we made our proposed model take into account only the collided vehicle, its shape, and its position within the video. Moreover, with the biggest challenge being finding data to train the system’s detection models, we built our own dataset from scratch with more than 1500 images of head-on car crashes within the context of crossroad accidents taken by the driving recorder of one of the vehicles involved in the crash. The experiment’s results show how the system performs in (1) detecting the crash time, (2) detecting traffic signs, and (3) assessing each party’s responsibility. The system performs well when light conditions and the visibility of collided objects are good and traffic lights’ view distances are close.
Fitness Costs of Tigecycline Resistance in Acinetobacter baumannii and the Resistance Mechanism Revealed by a Transposon Mutation Library
Authors: Wang Ping , Wang Hongou , Liu Cunwei , Feng Chengjie , Lu Qinghui , Zou Qinghua
Published: October 2022

Acinetobacter baumannii is one of the main pathogens causing nosocomial and community-acquired infections. Tigecycline is an important antibiotic for the treatment of multidrug-resistant A. baumannii infections, but strains resistant to tigecycline have also emerged. There are still many unclear questions concerning the mechanism of tigecycline resistance in A. baumannii. In this study, tigecycline-susceptible and tigecycline-intermediate strains were gradually cultured with sub-minimum inhibitory concentrations of tigecycline to select for tigecycline-resistant mutants, and a tigecycline-resistant strain was cultured under 42 °C to select for tigecycline-susceptible mutants. We found that the acquisition of tigecycline resistance affected the susceptibility of the strains to other antibiotics. Resistance to ampicillin–sulbactam is negatively correlated with tigecycline resistance. The strains will experience fitness costs along with the acquisition of tigecycline resistance. Tigecycline resistance in the strains was not related to 16S rRNA target variation or outer membrane integrity alteration. By constructing a transposon mutation library, we found that transposon insertion of the adeL gene reduced the sensitivity of A. baumannii to tigecycline. This study provides important clues for understanding the mechanism of tigecycline resistance in A. baumannii.
Emergence of Fosfomycin Resistance by Plasmid-Mediated fos Genes in Uropathogenic ESBL-Producing E. coli Isolates in Mexico
Authors: Galindo-Méndez Mario , Navarrete-Salazar Humberto , Baltazar-Jiménez Francisco , Muñoz-de la Paz Eduardo , Sánchez-Mawcinitt María Fernanda , Gómez-Pardo Alexis , Garza-González Elvira , Ponce-de-León-Garduño Luis Alfredo , Franco-Cendejas Rafael , Morfín-Otero Rayo , Rojas-Larios Fabián , Mena-Ramírez Juan Pablo , Morales-de-la-Peña Cecilia Teresita , García-Mendoza Lourdes , Choy-Chang Elena Victoria , Avilés-Benítez Laura Karina , López-Gutiérrez Eduardo , Canizales-Oviedo Jorge Luis , Barlandas-Rendón Nicolás Eric , Maldonado-Anicacio Joyarib Yanelli , Rosales-García Alina Aracely , Ostos-Cantú Heidy Leticia
Published: October 2022

Fosfomycin is currently a viable option against urinary tract infections, particularly against extended-spectrum β-lactamases (ESBL)-producing E. coli, due to its unique mechanism of action and its low resistance among bacteria. The objective of this study was to investigate two of the three most common mechanisms of resistance against this antibiotic among 350 ESBL-producing E. coli strains isolated from the urine of Mexican patients. The prevalence of fosfomycin resistance in our study was 10.9% (38/350). Of all resistant isolates analyzed, 23 (60.5%) were identified as fos-producing organisms, with 14 strains carrying fosA3 and 9, fosA1. Additionally, 11 (28.9%) fosfomycin-resistant isolates presented resistance due to impaired antibiotic transport and 8 (21.0%) both mechanisms. No resistance mechanism investigated in the study was found on 12 strains. All 38 confirmed ESBL-producing isolates carried a blaCTX-M subtype, 36 (94.5%) belonged to the O25b-ST131 clone, and all of them were able to transfer the fosfomycin resistance trait to recipient strains horizontally. This is the first study in Mexico demonstrating a plasmid-mediated fosfomycin resistance mechanism among clinical E. coli strains. Since our results suggest a strong association among fos and blaCTX-M genes and ST131 clones in uropathogenic E. coli, plasmid-mediated fosfomycin resistance should be closely monitored.
Ultrasound-Assisted Extraction, LC–MS/MS Analysis, Anticholinesterase, and Antioxidant Activities of Valuable Natural Metabolites from Astragalus armatus Willd.: In Silico Molecular Docking and In Vitro Enzymatic Studies
Authors: Lekmine Sabrina , Bendjedid Samira , Benslama Ouided , Martín-García Antonio Ignacio , Boussekine Samira , Kadi Kenza , Akkal Salah , Nieto Gema , Sami Rokayya , Al-Mushhin Amina A. M. , Baakdah Morooj M. , Aljaadi Abeer M. , Alharthy Saif A.
Published: October 2022

The Astragalus armatus Willd. plant’s phenolic constituent extraction and identification were optimized using the ultrasound-assisted extraction (UAE) method and the LC–MS/MS analysis, respectively. Additionally, cupric reducing antioxidant capacity (CUPRAC), beta carotene, reducing power, DMSO alcalin, silver nanoparticle (SNP)-based method, phenanthroline, and hydroxyl radical tests were utilized to assess the extract’s antioxidant capacity, while the neuroprotective effect was examined in vitro against acetylcholinesterase enzyme. This study accurately estimated the chemical bonding between the identified phenolic molecules derived from LC–MS/MS and the AChE. The extract was found to contain sixteen phenolic substances, and rosmarinic, protocatechuic, and chlorogenic acids, as well as 4-hydroxybenzoic, hyperoside, and hesperidin, were the most abundant substances in the extract. In all antioxidant experiments, the plant extract demonstrated strong antioxidant activity and a significant inhibitory impact against AChE (40.25 ± 1.41 μg/mL). According to molecular docking affinity to the enzyme AChE, the top-five molecules were found to be luteolin, quercetin, naringenin, rosmarinic acid, and kaempferol. Furthermore, these tested polyphenols satisfy the essential requirements for drug-like characteristics and Lipinski’s rule of five. These results highlight the significance of the A. armatus plant in cosmetics, as food additives, and in the pharmaceutical industry due to its rosmarinic and chlorogenic acid content.
Improving Deep Learning-Based Recommendation Attack Detection Using Harris Hawks Optimization
Authors: Zhou Quanqiang , Huang Cheng , Duan Liangliang
Published: October 2022

Recommendation attack attempts to bias the recommendation results of collaborative recommender systems by injecting malicious ratings into the rating database. A lot of methods have been proposed for detecting such attacks. Among these works, the deep learning-based detection methods get rid of the dependence on hand-designed features of recommendation attack besides having excellent detection performance. However, most of them optimize the key hyperparameters by manual analysis which relies too much on domain experts and their experience. To address this issue, in this paper we propose an approach based on the Harris Hawks Optimization (HHO) algorithm to improve the deep learning-based detection methods. Being different from the original detection methods which optimize the key hyperparameters manually, the improved deep learning-based detection methods can optimize the key hyperparameters automatically. We first convert the key hyperparameters of discrete type to continuous type according to the uniform distribution theory to expand the application scope of HHO algorithm. Then, we use the detection stability as an early stop condition to reduce the optimization iterations to improve the HHO algorithm. After that, we use the improved HHO algorithm to automatically optimize the key hyperparameters for the deep learning-based detection methods. Finally, we use the optimized key hyperparameters to train the deep learning-based detection methods to generate classifiers for detecting the recommendation attack. The experiments conducted on two benchmark datasets illustrate that the improved deep learning-based detection methods have effective performance.
Study on Evolution of the Thermophysical and Mechanical Properties of Inner Shaft Lining Concrete during Construction Period
Authors: Zhang Chi , Zhang Yu , Yang Weihao , Yin Jiying , Zhang Tao
Published: October 2022

The asymmetric temperature field is one of the main factors inducing the cracking of the inner shaft lining during freezing-shaft sinking. The evolution equation for the thermophysical and mechanical properties of shaft lining concrete during construction period is the basis for revealing the cracking mechanism. In this study, several experiments were conducted to reveal the evolution of the temperature field, thermal conductivity, specific heat capacity, compressive strength, tensile strength, and elastic modulus of shaft lining concrete with age and lining thickness within the first 7 d after pouring. Results show that the shaft lining concrete temperature curve after pouring can be divided into five stages: induction, slow heating, rapid heating, rapid cooling, and slow cooling. Thermal conductivity and specific heat capacity reached the maximum on Day 1 and gradually decreased with an increase in age. The compressive strength, tensile strength and elastic modulus significantly increased with age. With an increase in thickness, the shaft lining concrete at the same age improved its three mechanical parameters. Finally, the evolution equation for these thermophysical and mechanical parameters with age within the first 7 d after pouring was fitted based on experimental data. This study is expected to provide a thermophysical and mechanical basis for studying the cracking mechanism of the inner shaft lining.
Agrochemical Contamination and Ageing Effects on Greenhouse Plastic Film for Recycling
Authors: Picuno Pietro , Godosi Zoe , Picuno Caterina
Published: October 2022

Plastic films used for crop protection have reached notable consumption all over Europe, as well as in the rest of the world. This phenomenon however poses a serious environmental problem connected with the impact on the sustainability of agricultural production and relevant plastic footprint. Mechanical recycling of agricultural plastics is a common technique, but limited by many factors, as the loss of mechanical properties of plastic film. This phenomenon, due to its ageing after being exposed to natural weather conditions, plays a crucial role, especially when aggravated by contamination with agrochemicals ordinarily used for crop health and pest management. This article reports the result of some laboratory tests on agricultural plastic film, artificially aged for different periods and contaminated with two different agrochemicals (anti-aphid or fungicide). These results show that the impact of agrochemicals on plastic film is considerable, since it worsens the ageing process of the plastic film, conducting a more rapid reduction in its mechanical properties—mostly, a faster reduction in the elongation at break below 50% of the corresponding value of the virgin plastic film. This phenomenon, other than reducing the working life of the plastic film, gives it a low potential for being transformed into a closed-loop recycled material when entering the recycling stage. The increase in the value of the detected Carbonyl Index (CI) confirms the tendency of the material to degrade rapidly when in contact with agrochemicals, hence indicating that it may be impossible to mechanically recycle it.
Predefined-Time Nonsingular Attitude Control for Vertical-Takeoff Horizontal-Landing Reusable Launch Vehicle
Authors: Wang Mingze , Wei Changzhu , Pu Jialun , Cui Naigang
Published: October 2022

This paper presents a novel predefined-time nonsingular tracking control system for a vertical-takeoff horizontal-landing (VTHL) reusable launch vehicle (RLV) in the face of parameter uncertainties, model couplings and external disturbances. Firstly, this paper proposes a novel predefined-time prescribed performance function (PTPPF) with desired steady-state and transient performance. The convergence time of PTPPF from the transient state to the steady state can be flexibly adjusted by changing one parameter. Moreover, the decreasing rate of PTPPF in the transient phase can also be adjusted by changing one parameter on the premise of not changing the convergence time of PPF to reach steady state. A novel predefined-time terminal sliding mode surface (SMS) is designed to avoid the singularity, and the attitude tracking errors on SMS are predefined-time stable. By utilizing PTPPF and error transformation, this paper designs a novel nonsingular sliding mode controller to guarantee the attitudes of RLV with desired tracking performance. Without using piecewise functions, the phenomenon of singularity can be avoided. The Lyapunov method is used to verify the stability of the controller. Lastly, a numerical simulation is presented to validate the efficiency of the proposed controller.
Intelligent Arabic Handwriting Recognition Using Different Standalone and Hybrid CNN Architectures
Authors: Albattah Waleed , Albahli Saleh
Published: October 2022

Handwritten character recognition is a computer-vision-system problem that is still critical and challenging in many computer-vision tasks. With the increased interest in handwriting recognition as well as the developments in machine-learning and deep-learning algorithms, researchers have made significant improvements and advances in developing English-handwriting-recognition methodologies; however, Arabic handwriting recognition has not yet received enough interest. In this work, several deep-learning and hybrid models were created. The methodology of the current study took advantage of machine learning in classification and deep learning in feature extraction to create hybrid models. Among the standalone deep-learning models trained on the two datasets used in the experiments performed, the best results were obtained with the transfer-learning model on the MNIST dataset, with 0.9967 accuracy achieved. The results for the hybrid models using the MNIST dataset were good, with accuracy measures exceeding 0.9 for all the hybrid models; however, the results for the hybrid models using the Arabic character dataset were inferior.
Core Ontology for Describing Production Equipment According to Intelligent Production
Authors: Vlasenko Lidiia , Lutska Nataliia , Zaiets Nataliia , Korobiichuk Igor , Hrybkov Serhii
Published: October 2022

This article presents the development of a core ontology for describing knowledge about the technological and technical parts of a production plant, in particular, theoretical knowledge for monitoring, diagnosing and forecasting of production equipment, taking into account the concept of Industry 4.0. This study is related to the definition of terms and their relationships for the processing industry in the core ontology. The core ontology is the basis for the development of domain and application ontologies, which create conditions for the system solution for the complex problems of operating industrial equipment. It consists of an ontological classification of core concepts according to the fundamental basic formal ontology. The essences of BFO were specified and revealed by methods of decomposition and generalization according to generally accepted structures of industrial enterprises. The proposed ontology contains 33 classes, 7 object properties and 34 individuals. The ontology is conceptually transparent and semantically clear, so it is suitable for theoretical knowledge transfer, sharing and retrieval. The ontology is implemented in the OWL language and validated. This article provides examples of requests for work with ontology, which prove the effectiveness of its use in industrial enterprises.
Smart Battery Technology for Lifetime Improvement
Authors: Teodorescu Remus , Sui Xin , Vilsen Søren B. , Bharadwaj Pallavi , Kulkarni Abhijit , Stroe Daniel-Ioan
Published: October 2022

Applications of lithium-ion batteries are widespread, ranging from electric vehicles to energy storage systems. In spite of nearly meeting the target in terms of energy density and cost, enhanced safety, lifetime, and second-life applications, there remain challenges. As a result of the difference between the electric characteristics of the cells, the degradation process is accelerated for battery packs containing many cells. The development of new generation battery solutions for transportation and grid storage with improved performance is the goal of this paper, which introduces the novel concept of Smart Battery that brings together batteries with advanced power electronics and artificial intelligence (AI). The key feature is a bypass device attached to each cell that can insert relaxation time to individual cell operation with minimal effect on the load. An advanced AI-based performance optimizer is trained to recognize early signs of accelerated degradation modes and to decide upon the optimal insertion of relaxation time. The resulting pulsed current operation has been proven to extend lifetime by up to 80% in laboratory aging conditions. The Smart Battery unique architecture uses a digital twin to accelerate the training of performance optimizers and predict failures. The Smart Battery technology is a new technology currently at the proof-of-concept stage.
Li-Ion Battery Short-Circuit Protection by Voltage-Driven Switchable Resistance Polymer Layer
Authors: Beletskii Evgenii V. , Alekseeva Elena V. , Anishchenko Dmitrii V. , Levin Oleg V.
Published: October 2022

Safety issues with lithium-ion batteries prevent their widespread use in critical areas of technology. Various types of protective systems have been proposed to prevent thermal runaway and subsequent battery combustion. Among them, thermoresistive systems, representing polymer composites that sharply increase their resistance when the temperature rises, have been actively investigated. However, they are triggered only when the heating of the battery has already occurred, i.e., the system undergoes irreversible changes. This paper describes a new type of protective polymer layer based on the intrinsically conducting polymer poly[Ni(CH3OSalen)]. The response mechanism of this layer is based on an increase in resistance both when heated and when the cell voltage exceeds the permissible range. This makes it possible to stop undesirable processes at an earlier stage. The properties of the polymer itself and of the lithium-ion batteries modified by the protective layer have been studied. It is shown that the introduction of the polymer protective layer into the battery design leads to a rapid increase of the internal resistance at short circuit, which reduces the discharge current and sharply reduces the heat release. The effectiveness of the protection is confirmed by analysis of the battery components before the short circuit and after it.
Microstructure Modulation of Zn Doped VO2(B) Nanorods with Improved Electrochemical Properties towards High Performance Aqueous Batteries
Authors: Liu Dewei , Zhang Qijie , Chen Xiaohong , Dai Haiyang , Zhai Xuezhen , Chen Jing , Gong Gaoshang , Shang Cui , Wang Xuzhe
Published: October 2022

Vanadium dioxide with monoclinic structure is theoretically a promising layered cathode material for aqueous metal-ion batteries due to its excellent specific capacity. However, its poor cycling stability limits its application as an electrode material. In this study, a series of Zn-doped VO2 (V1−xZnxO2) nanorods were successfully fabricated by the technology of one-step hydrothermal synthesis. The XRD result indicated that there was a slight lattice distortion caused by doped Zn2+ with a larger ion radius. The positron lifetime spectrum showed that there were vacancy cluster defects in all the samples. The electrochemical measurement demonstrated the enhancement of the specific capacitance of V1−xZnxO2 electrodes compared with the undoped sample. In addition, the discharge capacitance of the sample remained around 86% after 1000 charge/discharge cycles. This work proves that Zn2+ doping is a valid tactic for the application of nano-VO2(B) in energy storage electrode materials.
Therapeutic Effect of Biomimetic Scaffold Loaded with Human Amniotic Epithelial Cell-Derived Neural-like Cells for Spinal Cord Injury
Authors: Qiu Chen , Sun Yuan , Li Jinying , Xu Yuchen , Zhou Jiayi , Qiu Cong , Zhang Shaomin , He Yong , Yu Luyang
Published: October 2022

Spinal cord injury (SCI) results in devastating consequences for the motor and sensory function of patients due to neuronal loss and disrupted neural circuits, confronting poor prognosis and lack of effective therapies. A new therapeutic strategy is urgently required. Here, human amniotic epithelial cells (hAEC), featured with immunocompatibility, non-tumorgenicity and no ethical issues, were induced into neural-like cells by a compound cocktail, as evidenced with morphological change and the expression of neural cell markers. Interestingly, the hAEC-neural-like cells maintain the characteristic of low immunogenicity as hAEC. Aiming at SCI treatment in vivo, we constructed a 3D-printed GelMA hydrogel biomimetic spinal cord scaffold with micro-channels, in which hAEC-neural-like cells were well-induced and grown. In a rat full transection SCI model, hAEC-neural-like cell scaffolds that were implanted in the lesion demonstrated significant therapeutic effects; the neural circuit and hindlimb locomotion were partly recovered compared to little affection in the SCI rats receiving an empty scaffold or a sham implantation operation. Thus, the establishment of hAEC-neural-like cell biomimetic scaffolds may provide a safe and effective treatment strategy for SCI.
Development of a CT-Compatible, Anthropomorphic Skull and Brain Phantom for Neurosurgical Planning, Training, and Simulation
Authors: Lai Marco , Skyrman Simon , Kor Flip , Homan Robert , El-Hajj Victor Gabriel , Babic Drazenko , Edström Erik , Elmi-Terander Adrian , Hendriks Benno H. W. , de With Peter H. N.
Published: October 2022

Background: Neurosurgical procedures are complex and require years of training and experience. Traditional training on human cadavers is expensive, requires facilities and planning, and raises ethical concerns. Therefore, the use of anthropomorphic phantoms could be an excellent substitute. The aim of the study was to design and develop a patient-specific 3D-skull and brain model with realistic CT-attenuation suitable for conventional and augmented reality (AR)-navigated neurosurgical simulations. Methods: The radiodensity of materials considered for the skull and brain phantoms were investigated using cone beam CT (CBCT) and compared to the radiodensities of the human skull and brain. The mechanical properties of the materials considered were tested in the laboratory and subsequently evaluated by clinically active neurosurgeons. Optimization of the phantom for the intended purposes was performed in a feedback cycle of tests and improvements. Results: The skull, including a complete representation of the nasal cavity and skull base, was 3D printed using polylactic acid with calcium carbonate. The brain was cast using a mixture of water and coolant, with 4 wt% polyvinyl alcohol and 0.1 wt% barium sulfate, in a mold obtained from segmentation of CBCT and T1 weighted MR images from a cadaver. The experiments revealed that the radiodensities of the skull and brain phantoms were 547 and 38 Hounsfield units (HU), as compared to real skull bone and brain tissues with values of around 1300 and 30 HU, respectively. As for the mechanical properties testing, the brain phantom exhibited a similar elasticity to real brain tissue. The phantom was subsequently evaluated by neurosurgeons in simulations of endonasal skull-base surgery, brain biopsies, and external ventricular drain (EVD) placement and found to fulfill the requirements of a surgical phantom. Conclusions: A realistic and CT-compatible anthropomorphic head phantom was designed and successfully used for simulated augmented reality-led neurosurgical procedures. The anatomic details of the skull base and brain were realistically reproduced. This phantom can easily be manufactured and used for surgical training at a low cost.
The Scores and Manner of Performing the Stand and Reach Test in Girls and Boys of Different Body Weight
Authors: Jankowicz-Szymańska Agnieszka , Kawa Justyna , Wódka Katarzyna , Smoła Eliza , Bibro Marta A. , Bac Aneta
Published: October 2022

Introduction: Flexibility is one of the components of Health-Related Fitness. The range of flexion has been the participant of numerous publications, but research into the quality of flexibility is lacking. The aim of the study has been to compare the scores and the quality of the stand and reach test in both overweight girls and boys and girls and boys with normal body weight. We have checked whether the forward bend movement is symmetrically distributed over the hip joints and the lumbar and thoracic spine and how it influences the position of the knee and ankle joints. Material and methods: 100 girls and 100 boys aged 10–14 years were examined. Flexibility was measured using the stand and reach test. The quality of the bend was assessed by examining the range of movement in individual body segments: the range of flexion of the thoracic and lumbar spine (linear measurements), the range of flexion of the hip joint, and the position of the knee and ankle joints at maximum flexion (angular measurements). The results were subjected to statistical analysis. Results: The participants, especially boys, had poor flexibility. A poor stand and reach test result correlated with a lower range of flexion of the thoracic and lumbar spine, greater flexion of the hip and knee joints, and greater plantar flexion at maximum torso bend position. Although the mean stand and reach score was slightly greater for the girls, gender did not significantly differentiate the way in which the stand and reach test was performed. Being overweight also did not affect the quantity or quality of the stand and reach test. Conclusions: Limitation of flexibility is common in 10–14-year-old children and results mainly from limited mobility of the spine. The compensation for this is excessive movement in the joints of the lower extremities.
Sustainable Feedstocks and Challenges in Biodiesel Production: An Advanced Bibliometric Analysis
Authors: Sales Misael B. , Borges Pedro T. , Ribeiro Filho Manoel Nazareno , Miranda da Silva Lizandra Régia , Castro Alyne P. , Sanders Lopes Ada Amelia , Chaves de Lima Rita Karolinny , de Sousa Rios Maria Alexsandra , Santos José C. S. dos
Published: October 2022

Biodiesel can be produced from vegetable oils, animal fats, frying oils, and from microorganism-synthesized oils. These sources render biodiesel an easily biodegradable fuel. The aim of this work was to perform an advanced bibliometric analysis of primary studies relating to biodiesel production worldwide by identifying the key countries and regions that have shown a strong engagement in this area, and by understanding the dynamics of their collaboration and research outputs. Additionally, an assessment of the main primary feedstocks employed in this research was carried out, along with an analysis of the current and future trends that are expected to define new paths and methodologies to be used in the manufacture of biodegradable and renewable fuels. A total of 4586 academic outputs were selected, including peer-reviewed research articles, conference papers, and literature reviews related to biodiesel production, in the time period spanning from 2010 to 2021. Articles that focused on feedstocks for the production of biodiesel were also included, with a search that returned 330 papers. Lastly, 60 articles relating to biodiesel production via sewage were specifically included to allow for an analysis of this source as a promising feedstock in the future of the biofuel market. Via the geocoding and the document analyses performed, we concluded that China, Malaysia, and India are the largest writers of articles in this area, revealing a great interest in biofuels in Asia. Additionally, it was noted that environmental concerns have caused authors to conduct research on feedstocks that can address the sustainability challenges in the production of biodiesel.
Tumor Necrosis Factor-α (TNFα) Stimulates Triple-Negative Breast Cancer Stem Cells to Promote Intratumoral Invasion and Neovasculogenesis in the Liver of a Xenograft Model
Authors: Narasimhan Harini , Ferraro Francesca , Bleilevens Andreas , Weiskirchen Ralf , Stickeler Elmar , Maurer Jochen
Published: October 2022

TNBC represents the most aggressive breast cancer subtype. Although cancer stem cells (CSCs) are a minor fraction of all cancer cells, they are highly cancerous when compared to their non-stem counterparts, playing a major role in tumor recurrence and metastasis. Angiogenic stimuli and the tumor environment response are vital factors in cancer metastasis. However, the causes and effects of tumor angiogenesis are still poorly understood. In this study, we demonstrate TNFα effects on primary triple-negative breast cancer stem cells (BCSCs). TNFα stimulation increased the mesenchymality of BCSCs in an intermediate epithelial-to-mesenchymal transition (EMT) state, enhanced proliferation, self-renewal, and invasive capacity. TNFα-treatment elicited BCSC signaling on endothelial networks in vitro and increased the network forming capacity of the endothelial cells. Our findings further demonstrate that TNFα stimulation in BCSCs has the ability to instigate distinct cellular communication within the tumor microenvironment, inducing intra-tumoral stromal invasion. Further, TNFα-treatment in BCSCs induced a pre-metastatic niche through breast-liver organ crosstalk by inducing vascular cell adhesion molecule-1 (VCAM-1) enriched neovasculogenesis in the liver of tumor-bearing mice. Overall, TNFα is an important angiogenic target to be considered in breast cancer progression to attenuate any angiogenic response in the tumor environment that could lead to secondary organ metastasis.
Exploring Computational Data Amplification and Imputation for the Discovery of Type 1 Diabetes (T1D) Biomarkers from Limited Human Datasets
Authors: Alcazar Oscar , Ogihara Mitsunori , Ren Gang , Buchwald Peter , Abdulreda Midhat H.
Published: October 2022

Background: Type 1 diabetes (T1D) is a devastating disease with serious health complications. Early T1D biomarkers that could enable timely detection and prevention before the onset of clinical symptoms are paramount but currently unavailable. Despite their promise, omics approaches have so far failed to deliver such biomarkers, likely due to the fragmented nature of information obtained through the single omics approach. We recently demonstrated the utility of parallel multi-omics for the identification of T1D biomarker signatures. Our studies also identified challenges. Methods: Here, we evaluated a novel computational approach of data imputation and amplification as one way to overcome challenges associated with the relatively small number of subjects in these studies. Results: Using proprietary algorithms, we amplified our quadra-omics (proteomics, metabolomics, lipidomics, and transcriptomics) dataset from nine subjects a thousand-fold and analyzed the data using Ingenuity Pathway Analysis (IPA) software to assess the change in its analytical capabilities and biomarker prediction power in the amplified datasets compared to the original. These studies showed the ability to identify an increased number of T1D-relevant pathways and biomarkers in such computationally amplified datasets, especially, at imputation ratios close to the “golden ratio” of 38.2%:61.8%. Specifically, the Canonical Pathway and Diseases and Functions modules identified higher numbers of inflammatory pathways and functions relevant to autoimmune T1D, including novel ones not identified in the original data. The Biomarker Prediction module also predicted in the amplified data several unique biomarker candidates with direct links to T1D pathogenesis. Conclusions: These preliminary findings indicate that such large-scale data imputation and amplification approaches are useful in facilitating the discovery of candidate integrated biomarker signatures of T1D or other diseases by increasing the predictive range of existing data mining tools, especially when the size of the input data is inherently limited.
Postpartum Blood Loss in COVID-19 Patients—Propensity Score Matched Analysis
Authors: Januszewski Marcin , Santor-Zaczyńska Małgorzata , Ziuzia-Januszewska Laura , Kudan Michał , Jakimiuk Alicja A. , Wierzba Waldemar , Jakimiuk Artur J.
Published: October 2022

The aim of this study was to compare the estimated blood loss and the frequency of obstetric hemorrhage among pregnant women with and without COVID-19 infection. The study was carried out in the Department of Obstetrics and Gynecology, at the Central Clinical Hospital of the Ministry of the Interior and Administration in Warsaw, Poland. From 15 May 2020 to 26 April 2021, a total of 224 parturients with COVID-19 infection were admitted for labor. The control group consisted of 300 randomly recruited pre-pandemic deliveries that took place between 15 May 2019 and 26 April 2020 at the Department. The primary outcome was the presence of postpartum hemorrhage, defined as an estimated blood loss of ≥500 mL within 24 h after birth or the need to transfuse 2 or more units of packed red blood cells (pRBCs). Secondary outcomes were the difference between hemoglobin and hematocrit levels at 24 h postpartum, the number of pRBCs units transfused, and the need for transperitoneal drainage. After applying the propensity-score-matching procedure for postpartum bleeding risk factors, 325 eligible patients were included in the final analysis, divided into 203 COVID-19 positive and 122 COVID-19 negative prepandemic deliveries. SARS-CoV-2 infected patients were characterized by a longer activated partial thromboplastin time (APTT), a reduced prothrombin time (PT), and lower platelet count at initial presentation. COVID-19 deliveries were found to be associated with a higher frequency of postpartum hemorrhage, an increased estimated blood loss, the more frequent use of peritoneal drainage, and more pRBCs units transfused. During the pandemic, an increased risk of postpartum hemorrhage posed another threat to SARS-CoV-2 infected pregnant women. It is essential to be aware of this when approaching COVID-19 delivery and to implement efficient preventative methods.
Vascular Function in Chronic Non-Communicable Diseases
Authors: Tesauro Manfredi , Noce Annalisa
Published: October 2022

Chronic non-communicable diseases (CNCDs) are one of the major causes of mortality and morbidity worldwide [...]
Sarcoidosis and COVID-19: At the Cross-Road between Immunopathology and Clinical Manifestation
Authors: Tana Claudio , Cinetto Francesco , Mantini Cesare , Bernardinello Nicol , Tana Marco , Ricci Fabrizio , Ticinesi Andrea , Meschi Tiziana , Scarpa Riccardo , Cipollone Francesco , Giamberardino Maria Adele , Spagnolo Paolo
Published: October 2022

Coronavirus disease 2019 (COVID-19) has been associated with dysregulation of the immune system featuring inappropriate immune responses, exacerbation of inflammatory responses, and multiple organ dysfunction syndrome in patients with severe disease. Sarcoidosis, also known as Besnier–Boeck–Schaumann disease, is an idiopathic granulomatous multisystem disease characterized by dense epithelioid non-necrotizing lesions with varying degrees of lymphocytic inflammation. These two diseases have similar clinical manifestations and may influence each other at multiple levels, eventually affecting their clinical courses and prognosis. Notably, sarcoidosis patients are at high risk of severe COVID-19 pneumonia because of the underlying lung disease and chronic immunosuppressive treatment. In this narrative review, we will discuss interactions between sarcoidosis and COVID-19 in terms of clinical manifestations, treatment, and pathogenesis, including the role of the dysregulated renin–angiotensin system, altered immune responses involving increased cytokine levels and immune system hyperactivation, and cellular death pathways.
Viscosity-Sensitive Solvatochromic Fluorescent Probes for Lipid Droplets Staining
Authors: Wang Mao-Hua , Cui Wei-Long , Yang Yun-Hao , Wang Jian-Yong
Published: October 2022

Lipid droplets (LDs) are simple intracellular storage sites for neutral lipids and exhibit important impact on many physiological processes. For example, the changes in the polar microenvironment inside LDs could affect physiological processes, such as lipid metabolism and storage, protein degradation, signal transduction, and enzyme catalysis. Herein, a new fluorescent chemo-sensor (Couoxo-LD) was formulated by our molecular design strategy. The probe could be applied to effectively label intracellular lipid droplets. Intriguingly, Couoxo-LD demonstrated positive sensitivity to both polarity and viscosity, which might be attributed to its D-π-A structure and the twisted rotational behavior of the carbon–carbon double bond (TICT). Additionally, Couoxo-LD was successfully implemented in cellular imaging due to its excellent selectivity, pH stability, and low biotoxicity. In HeLa cells, the co-localization curve between Couoxo-LD and commercial lipid droplet dyes overlapped at 0.93. The results indicated that the probe could selectively sense LDs in HeLa cells. Meanwhile, Couoxo-LD can be applied for in vivo imaging of zebrafish.
All-Polymeric Electrode Based on PEDOT:PSS for In Vivo Neural Recording
Authors: Filho Gilberto , Júnior Cláudio , Spinelli Bruno , Damasceno Igor , Fiuza Felipe , Morya Edgard
Published: October 2022

One of the significant challenges today in the brain–machine interfaces that use invasive methods is the stability of the chronic record. In recent years, polymer-based electrodes have gained notoriety for achieving mechanical strength values close to that of brain tissue, promoting a lower immune response to the implant. In this work, we fabricated fully polymeric electrodes based on PEDOT:PSS for neural recording in Wistar rats. We characterized the electrical properties and both in vitro and in vivo functionality of the electrodes. Additionally, we employed histological processing and microscopical visualization to evaluate the tecidual immune response at 7, 14, and 21 days post-implant. Electrodes with 400-micrometer channels showed a 12 dB signal-to-noise ratio. Local field potentials were characterized under two conditions: anesthetized and free-moving. There was a proliferation of microglia at the tissue–electrode interface in the early days, though there was a decrease after 14 days. Astrocytes also migrated to the interface, but there was not continuous recruitment of these cells in the tissue; there was inflammatory stability by day 21. The signal was not affected by this inflammatory action, demonstrating that fully polymeric electrodes can be an alternative means to prolong the valuable time of neural recordings.
A Design Method for Semi-Rigid Steel Frame via Pre-Established Performance-Based Connection Database
Authors: Yin Tulong , Wang Zhan , Pan Jianrong , Zheng Kaixiang , Liu Deming , Lu Shengcan
Published: October 2022

With decades of research, semi-rigid beam-to-column connections have been widely accepted. However, most studies have been restricted to the local connection level, leaving system-oriented analysis and design methods with a meager investigation, which leads to the fact that the active use of semi-rigid connections in practice is rare. This study aims to provide a system-level design method to bridge the gap between element and connection design, and the two main contributions are to propose a method for designing semi-rigid steel frames by pre-establishing a performance-based connection database and to formulate refined classification criteria for connection performance levels. In this method, the frame design is transformed into finding an appropriate matching of performance requirements between elements and connections. The classification criteria for connection performance levels are based on the assumption that the structural responses (stability, resistance, and deformation) are only slightly affected by the properties of connections within the same level. The emphasis is on the rotational stiffness and moment resistance of the connection. Finally, the results of examples indicate that the connection database is portable and can be applied to various frames, avoiding the repetitive design for connections in different projects. In addition, tuning the performance requirements of the connection can greatly reduce the number of design variables compared to tuning its geometry, and more importantly, it provides designers with a clearer update path, which can significantly shorten the process of trial-and-error and quickly arrive at the final design.
A Multiscale Modelling Approach to Support Knowledge Representation of Building Codes
Authors: Jiang Liu , Shi Jianyong , Pan Zeyu , Wang Chaoyu , Mulatibieke Nazhaer
Published: October 2022

Knowledge representations of building codes are essential and critical resources for the organization, retrieval, sharing, and reuse of implicit knowledge in the AEC industry. Against this background, traditional code compliance checking is time-consuming and error-prone. This research aimed to utilize various knowledge representation techniques to establish a knowledge model of building codes to facilitate the automated code compliance checking. The proposed knowledge model consists of three levels to achieve conceptual, logical, and correlational representations of building codes. The concept-level model provides the basic knowledge elements. The clause-level model was developed based on a unified top schema and provides the conceptual graph, mapping logics, and checking logics of each clause. The code-level model is constructed based on the explicit cross-references and semantic connections between clauses. The investigations on the model applications indicate two aspects. On the one hand, the proposed knowledge model shows high potential for semantic searching and knowledge recommendation. On the other hand, the automated code-compliance-checking processes based on the proposed multiscale knowledge model can achieve three main advantages: guiding designers to create a building model with completely necessary information, mitigating the differences between building information and regulatory information, and making the checking procedures more friendly and relatively transparent to users.
Could the BGN Gene Be Pathogenic with Spontaneous Coronary Artery Dissection (SCAD) and Fibromuscular Dysplasia (FMD)?
Authors: Kolton Lexie , Robin Charlie , Xu Jianfeng , Wei Jun , Patil Rupa , Robin Jason
Published: October 2022

BACKGROUND. Spontaneous coronary artery dissection (SCAD) is a cause of myocardial infarction, especially in younger women without cardiovascular risk factors. Patient management and diagnostics are still largely based on retrospective and observational studies. Most patients with SCAD report chest pain and have elevated biomarkers with ECG findings. SCAD can lead to cardiogenic shock, ventricular arrhythmias and cardiac arrest, and is commonly associated with fibromuscular dysplasia (FMD). Genetic associations are still in their infancy with this disease process. METHODS. An Invitae 29 gene aortopathy panel was performed on a mother with a thoracic aortic aneurysm and her daughter who presented with SCAD and was noted to have FMD. RESULTS. The patient and her mother were both noted to have a heterozygous mutation of the Biglycan (BGN) gene (Variant c.1030T > G (p.Tyr344His)) of undetermined significance. An extensive literature review was performed, including a review of the UK Biobank. This is the first case to our knowledge showing a possible link between the BGN mutation and SCAD/FMD. CONCLUSIONS. The BGN mutation has been recognized to be correlated with aortic aneurysm and aortic dissection. It has not yet been explored to be associated with SCAD/FMD. This paper highlights the potential link between the BGN gene and SCAD/FMD. Further research looking at this association is warranted.
Evaluation of Ni-Doped Tricobalt Tetroxide with Reduced Graphene Oxide: Structural, Photocatalysis, and Antibacterial Response
Authors: Malafatti João Otávio Donizette , Moreira Ailton José , Paris Elaine Cristina , Cardenas Flechas Leydi Julieta , Pereira Otávio Augusto Poli , Rincón Joya Miryam
Published: October 2022

Cobalt oxide (Co3O4) nanoparticles were successfully prepared by sol–gel and hydrothermal methods for antibacterial and photocatalytic applications with the addition of 1%, 4% nickel (Ni), and reduced graphene oxide (rGO). The structural and morphological properties of the nanoparticles were obtained by XRD, TEM and FESEM techniques. Cobalt oxide showed typical crystallographic planes to cubic phase and particles with inferior diameter to 30 nm. The Ni-Co3O4 + rGO nanocrystals exhibit a band gap value of 2.0 eV. The bactericidal tests for S. aureus and E. coli revealed that the insertion rGO synthesized by the sol–gel method promoted the antimicrobial activity for both microorganisms. Afterward, the photocatalytic assay for the atrazine contaminant showed significant responses to pesticide removal attributed to the simultaneous adsorption and degradation process. In addition, the sol–gel process found a better response to Ni-Co3O4 in the presence of rGO, indicating a nanocomposite superior synergism.