bluuebunny/crossref_metadata_2025 huggingface dataset:
Detection of Experimental Colorectal Peritoneal Metastases by a Novel PDGFRβ-Targeting Nanobody
Authors: Strating Esther , Elias Sjoerd , van Scharrenburg Guus , Luoto Kaisa , Verheem André , Borel Rinkes Inne , Steen Herman , Kranenburg Onno
Published: September 2022

Peritoneal metastases in colorectal cancer (CRC) belong to Consensus Molecular Subtype 4 (CMS4) and are associated with poor prognosis. Conventional imaging modalities, such as Computed Tomography (CT) and Fluorodeoxyglucose-Positron Emission Tomography (FDG-PET), perform very poorly in the detection of peritoneal metastases. However, the stroma-rich nature of these lesions provides a basis for developing molecular imaging strategies. In this study, conducted from 2019 to 2021, we aimed to generate a Platelet-Derived Growth Factor Receptor beta (PDGFRB)-binding molecular imaging tracer for the detection of CMS4 CRC, including peritoneal metastases. The expression of PDGFRB mRNA discriminated CMS4 from CMS1-3 (AUROC = 0.86 (95% CI 0.85–0.88)) and was associated with poor relapse-free survival. PDGFRB mRNA and protein levels were very high in all human peritoneal metastases examined (n = 66). Therefore, we generated a PDGFRB-targeting llama nanobody (VHH1E12). Biotin-labelled VHH1E12 bound to immobilized human and mouse PDGFRB with high affinity (EC50 human PDGFRB = 7 nM; EC50 murine PDGFRB = 0.8 nM), and to PDGFRB-expressing HEK293 cells grown in vitro. A pharmacokinetic analysis of IRDye-800CW-conjugated VHH1E12 in mice showed that the plasma half-life was 6 min. IRDye-800CW-conjugated VHH1E12 specifically accumulated in experimentally induced colorectal cancer peritoneal metastases in mice. A tissue analysis subsequently demonstrated co-localization of the nanobody with PDGFRB expression in the tumour stroma. Our results demonstrate the potential value of PDGFRB-targeted molecular imaging as a novel strategy for the non-invasive detection of CMS4 CRC, in particular, peritoneal metastases.
Osteoporosis in Childhood Cancer Survivors: Physiopathology, Prevention, Therapy and Future Perspectives
Authors: Rossi Francesca , Tortora Chiara , Paoletta Marco , Marrapodi Maria Maddalena , Argenziano Maura , Di Paola Alessandra , Pota Elvira , Di Pinto Daniela , Di Martino Martina , Iolascon Giovanni
Published: September 2022

The improvement of chemotherapy, radiotherapy, and surgical interventions, together with hematopoietic stem cell transplantation, increased childhood cancer survival rate in the last decades, reaching 80% in Europe. Nevertheless, anti-cancer treatments are mainly responsible for the onset of long-term side effects in childhood cancer survivors (CCS), including alterations of the endocrine system function and activity. In particular, the most frequent dysfunction in CCS is a metabolic bone disorder characterized by low bone mineral density (BMD) with increased skeletal fragility. BMD loss is also a consequence of a sedentary lifestyle, malnutrition, and cancer itself could affect BMD, thus inducing osteopenia and osteoporosis. In this paper, we provide an overview of possible causes of bone impairment in CCS in order to propose management strategies for early identification and treatment of skeletal fragility in this population.
A Matched-Pair Analysis after Robotic and Retropubic Radical Prostatectomy: A New Definition of Continence and the Impact of Different Surgical Techniques
Authors: d’Altilia Nicola , Mancini Vito , Falagario Ugo Giovanni , Martino Leonardo , Di Nauta Michele , Calò Beppe , Del Giudice Francesco , Basran Satvir , Chung Benjamin I. , Porreca Angelo , Bianchi Lorenzo , Schiavina Riccardo , Brunocilla Eugenio , Busetto Gian Maria , Bettocchi Carlo , Annese Pasquale , Cormio Luigi , Carrieri Giuseppe
Published: September 2022

Background: Radical prostatectomy is considered the gold-standard treatment for patients with localized prostate cancer. The literature suggests there is no difference in oncological and functional outcomes between robotic-assisted radical prostatectomy (RARP) and open (RRP). (2) Methods: The aim of this study was to compare continence recovery rates after RARP and RRP measured with 24 h pad weights and the International Consultation on Incontinence Questionnaire—Short Form (ICIQ-SF). After matching the population (1:1), 482 met the inclusion criteria, 241 patients per group. Continent patients with a 24 h pad test showing <20 g of urinary leakage were considered, despite severe incontinence, and categorized as having >200 g of urinary leakage. (3) Results: There was no difference between preoperative data. As for urinary continence (UC) and incontinence (UI) rates, RARP performed significantly better than RRP based on objective and subjective results at all evaluations. Univariable and multivariable Cox Regression Analysis pointed out that the only significant predictors of continence rates were the bilateral nerve sparing technique (1.25 (CI 1.02,1.54), p = 0.03) and the robotic surgical approach (1.42 (CI 1.18,1.69) p ≤ 0.001). (4) Conclusions: The literature reports different incidences of UC depending on assessment and definition of continence “without pads” or “social continence” based on number of used pads per day. In this, our first evaluation, the advantage of objective measurement through the weight of the 24 h and subjective measurement with the ICIQ-SF questionnaire best demonstrates the difference between the two surgical techniques by enhancing the use of robotic surgery over traditional surgery.
Nickel-Catalyzed Ethylene Dimerization Based on PNP(NR2)2 Ligands
Authors: Cao Chengang , Fan Haonan , Zhang Jingyi , Ma Jing , Jiang Tao
Published: September 2022

Nickel (II) complexes stabilized by PNP(NR2)2 (L1: R = Methyl, L2: R = ethyl, L3: R = isopropyl) ligands were synthesized and characterized. A narrow range of products was observed for catalytic systems containing nickel complexes and ethyl aluminum dichloride (EADC). All exhibit considerable activity in the ethylene dimerization to produce 1-butene. Precatalyst 1 is the most conducive for ethylene dimerization, producing 83.4% C4 (1-C4 36.8%) and 103.0 × 105 g/(molNi·h) in terms of its activity under the appropriate conditions. By adjusting the conditions of the catalytic system for precatalyst 2, high C4 selectivity (88.1%) with reasonable activity (76.9 × 105 g/(molNi·h)) can be obtained. The X-ray single-crystal analysis of complexes presents mononuclear bidentate coordination at the Ni center, and the relationship between certain bite angles may also imply catalytic performance.
Exporting Proteins Associated with Senescence Repair via Extracellular Vesicles May Be Associated with Early Pregnancy Loss
Authors: Zhang Yi , Tang Yunhui , Sun Xinyi , Kang Matt , Zhao Min , Wan Jiayi , Chen Qi
Published: September 2022

Introduction: Dysfunction of placental development is involved in early pregnancy loss. Senescent changes have been seen in missed miscarriage, one type of pregnancy loss. Extracellular vesicles (EVs) have been widely implicated in the pathogenesis of diseases. In this study, we investigated the protein profiles in placental EVs derived from missed miscarriage in comparison with healthy pregnancy. We also investigated whether cargos packed into EVs are involved in the dysfunctional development of the placenta seen in missed miscarriage. Methods: Proteomic analysis of placental EVs derived from healthy and missed-miscarriage placentae was performed. Three senescence-repair-associated proteins, replication protein A-70 (RPA-70), proteasome activator subunit-4 (PMSE-4), and protein activated kinase-2, (PAK-2) were examined in placental EVs and placentae, and in placental explants that had been treated with or without GW4869, by western blotting and immunohistochemistry. Results: The total number of proteins associated with placental EVs was not different between the two groups. However, there were 106 and 151 abundantly expressed proteins associated with placental micro- or nano-EVs from missed miscarriage in comparison with EVs from controls. Of these abundant proteins, 59 and 81 proteins in placental micro- or nano-EVs, respectively, are associated with DNA damage/repair and cell death/survival. We further found higher levels of three senescence-repair-associated proteins (RPA-70, PMSE-4, and PAK-2) associated with placental EVs, but lower levels of these proteins in missed-miscarriage placentae. Regarding inhibition of EV formation or release by GW4869, we found that the expression of these three proteins was higher in GW4869-treated placental explants from missed miscarriage. Discussion: Our data may suggest that “inadvertently” sorting of cargos and exporting proteins associated with senescence-repair by placental EVs may be associated with the dysfunction of placental development seen in missed miscarriage.
Proteome and Glycoproteome Analyses Reveal the Protein N-Linked Glycosylation Specificity of STT3A and STT3B
Authors: Wen Piaopiao , Chen Jingru , Zuo Chenyang , Gao Xiaodong , Fujita Morihisa , Yang Ganglong
Published: September 2022

STT3A and STT3B are the main catalytic subunits of the oligosaccharyltransferase complex (OST-A and OST-B in mammalian cells), which primarily mediate cotranslational and post-translocational N-linked glycosylation, respectively. To determine the specificity of STT3A and STT3B, we performed proteomic and glycoproteomic analyses in the gene knock-out (KO) and wild-type HEK293 cells. In total, 3961 proteins, 4265 unique N-linked intact glycopeptides and 629 glycosites representing 349 glycoproteins were identified from all these cells. Deletion of the STT3A gene had a greater impact on the protein expression than deletion of STT3B, especially on glycoproteins. In addition, total mannosylated N-glycans were reduced and fucosylated N-glycans were increased in STT3A-KO cells, which were caused by the differential expression of glycan-related enzymes. Interestingly, hyperglycosylated proteins were identified in KO cells, and the hyperglycosylation of ENPL was caused by the endoplasmic reticulum (ER) stress due to the STT3A deletion. Furthermore, the increased expression of the ATF6 and PERK indicated that the unfolded protein response also happened in STT3A-KO cells. Overall, the specificity of STT3A and STT3B revealed that defects in the OST subunit not only broadly affect N-linked glycosylation of the protein but also affect protein expression.
Genome Editing Approaches with CRISPR/Cas9 for Cancer Treatment: Critical Appraisal of Preclinical and Clinical Utility, Challenges, and Future Research
Authors: Chira Sergiu , Nutu Andreea , Isacescu Ecaterina , Bica Cecilia , Pop Laura , Ciocan Cristina , Berindan-Neagoe Ioana
Published: September 2022

The increasing burden on human malignant diseases became a major concern for healthcare practitioners, that must deal with tumor relapse and the inability to efficiently treat metastasis, in addition to side effects. Throughout the decades, many therapeutic strategies have been employed to improve the clinical outcomes of cancer patients and great efforts have been made to develop more efficient and targeted medicines. The malignant cell is characterized by genetic and epigenetic modifications, therefore targeting those specific drivers of carcinogenesis is highly desirable. Among the genome editing technologies, CRISPR/Cas9 stood as a promising candidate for cancer treatment alternatives, due to its low complexity design. First described as a defense mechanism of bacteria against invading foreign DNA, later it was shown that CRISPR components can be engineered to target specific DNA sequences in a test tube, a discovery that was awarded later with the Nobel Prize in chemistry for its rapid expansion as a reliable genome editing tool in many fields of research, including medicine. The present paper aims of describing CRISPR/Cas9 potential targets for malignant disorders, and the approaches used for achieving this goal. Aside from preclinical studies, we also present the clinical trials that use CRISPR-based technology for therapeutic purposes of cancer. Finally, a summary of the presented studies adds a more focused view of the therapeutic value CRISPR/Cas9 holds and the associated shortcomings.
Establishment and Characterization of hTERT Immortalized Hutchinson–Gilford Progeria Fibroblast Cell Lines
Authors: Lin Haihuan , Mensch Juliane , Haschke Maria , Jäger Kathrin , Köttgen Brigitte , Dernedde Jens , Orsó Evelyn , Walter Michael
Published: September 2022

Hutchinson–Gilford progeria syndrome (HGPS) is a rare premature aging syndrome caused by a dominant mutation in the LMNA gene. Previous research has shown that the ectopic expression of the catalytic subunit of telomerase (hTERT) can elongate the telomeres of the patients’ fibroblasts. Here, we established five immortalized HGP fibroblast cell lines using retroviral infection with the catalytic subunit of hTERT. Immortalization enhanced the proliferative life span by at least 50 population doublings (PDs). The number of cells with typical senescence signs was reduced by 63 + 17%. Furthermore, the growth increase and phenotype improvement occurred with a lag phase of 50–100 days and was not dependent on the degree of telomere elongation. The initial telomeric stabilization after hTERT infection and relatively low amounts of hTERT mRNA were sufficient for the phenotype improvement but the retroviral infection procedure was associated with transient cell stress. Our data have implications for therapeutic strategies in HGP and other premature aging syndromes.
Extended Overview of Ocular Phenotype with Recent Advances in Hypohidrotic Ectodermal Dysplasia
Authors: Callea Michele , Bignotti Stefano , Semeraro Francesco , Cammarata-Scalisi Francisco , El-Feghaly Jinia , Morabito Antonino , Romano Vito , Willoughby Colin E.
Published: September 2022

The term ectodermal dysplasias (EDs) describes a heterogeneous group of inherited developmental disorders that affect several tissues of ectodermal origin. The most common form of EDs is hypohidrotic ectodermal dysplasia (HED), which is characterized by hypodontia, hypotrichosis, and partial or total eccrine sweat gland deficiency. HED is estimated to affect at least 1 in 17,000 people worldwide. Patients with HED have characteristic facies with periorbital hyperpigmentation, depressed nasal bridge, malar hypoplasia, and absent or sparse eyebrows and eyelashes. The common ocular features of HED include madarosis, trichiasis, and ocular chronic surface disease due to dry eye syndrome, which manifests clinically with discomfort, photophobia, and redness. Dry eye is common in HED and results from a combination of ocular surface defects: mucus abnormalities (abnormal conjunctival mucinous glands), aqueous tear deficiency (abnormalities in the lacrimal gland) and lipid deficiency (due to the partial or total absence of the meibomian glands; modified sebaceous glands with the tarsal plate). Sight-threatening complications result from ocular surface disease, including corneal ulceration and perforation with subsequent corneal scarring and neovascularization. Rare ocular features have been reported and include bilateral or unilateral congenital cataracts, bilateral glaucoma, chorioretinal atrophy and atresia of the nasolacrimal duct. Recognition of the ocular manifestations of HED is required to perform clinical surveillance, instigate supportive and preventative treatment, and manage ocular complications.
Drama Therapy for Children and Adolescents with Psychosocial Problems: A Systemic Review on Effects, Means, Therapeutic Attitude, and Supposed Mechanisms of Change
Authors: Berghs Marij , Prick Anna-Eva J. C. , Vissers Constance , van Hooren Susan
Published: September 2022

Drama therapy is applied to children and adolescents with psychosocial problems. Drama therapy is an experimental form of treatment which methodologically uses drama and theatre processes to achieve psychological growth. Although in clinical practice, drama therapy has been applied successfully, little is known about how and why drama therapy contributes to a decrease in psychosocial problems. A systematic narrative review was performed to obtain more insight into this issue. Eight databases were systematically searched. Ten out of 3742 studies were included, of which there were four random controlled trails, three non-controlled trials, and three pre-and post-test design studies. We identified the results, drama therapeutic means, attitude, and mechanism of change. Positive effects were found on overall psychosocial problems, internalizing and externalizing problems, social functioning, coping and regulation processes, social identity, and cognitive development. An adaptive approach was mentioned as the therapeutic attitude. The means established contribute to a dramatic reality, which triggers the mechanisms of change. These are processes that arise during treatment and which facilitate therapeutic change. We found ten supposed mechanisms of change to be frequently used in all studies. No direct relations were found between the results, drama therapeutic attitude, means, and mechanisms of change.
Effect of Ultrasonic Vibration Frequency on Ni-Based Alloy Cladding Layer
Authors: Yao Fangping , Li Jinhua , Fang Lijin , Ming Zhi
Published: September 2022

In order to maximize the performance of the nickel-based cladding layer without adding a reinforcing phase, ultrasonic vibrations of different frequencies are assisted in the laser cladding process. The morphology of the cladding layer was analyzed by a metallographic microscope, the microstructure of the cladding layer was analyzed by SEM, the element segregation of the cladding layer was analyzed by EDS energy spectrum, and the microhardness of the cladding layer was tested by a microhardness tester. Hardness and friction-wear performance of the cladding layer were tested using a friction and wear tester. The test results show that the appropriate ultrasonic frequency can obviously refine the microstructure of the cladding layer, the hardness and wear resistance of the cladding layer have been significantly improved due to the refinement of the structure, and it has a good fine grain for the cladding layer. The strengthening effect maximizes the performance of the cladding layer.
Peak Cutting Force Estimation of Improved Projection Profile Method for Rock Fracturing Capacity Prediction with High Lithological Tolerance
Authors: Duan Mingyu , Shao Lefei , Huang Qibai , Wang Chenlin , Li Xuefeng , Huang Yizhe
Published: September 2022

Prediction of rock fracturing capacity demands particular requirements for the exploitation of mineral resources, especially for the parameter design of conical pick performance for hard rock fragmentation, which must take into account differences in rock mechanical properties. Among these parameters, the peak cutting force (PCF) is important in designing, selecting, and optimizing the cutting head of mining equipment and a cutability index of rocks. Taking high lithological tolerance as demand traction, this study proposes a theoretical model for estimating the peak cutting force of conical picks based on the improved projection profile method for which the influence of alloy head, pick body structure, and installation parameters are taken into consideration. Besides, experimental results corresponding to different numbers of rock samples are used to verify the accuracy and stability of the theoretical model. Meanwhile, the comparison of performance in cutting force estimation between this model and four other existing theoretical models is conducted. The results found that the new method has the highest correlation coefficient with the experimental results and the lowest root mean square error comparing with other models, i.e., the estimation performance of this method has high lithological tolerance when the rock type increases and the lithology changes. Consequently, the proposed peak cutting force estimation of improved projection profile method will provide a more valid and accurate prediction for rock fracturing capacity with large differences in rock mechanical properties.
Neural Network Solver for Small Quantum Clusters
Authors: Walker Nicholas , Kellar Samuel , Zhang Yi , Tam Ka-Ming , Moreno Juana
Published: September 2022

Machine learning approaches have recently been applied to the study of various problems in physics. Most of these studies are focused on interpreting the data generated by conventional numerical methods or the data on an existing experimental database. An interesting question is whether it is possible to use a machine learning approach, in particular a neural network, for solving the many-body problem. In this paper, we present a neural network solver for the single impurity Anderson model, the paradigm of an interacting quantum problem in small clusters. We demonstrate that the neural-network-based solver provides quantitative accurate results for the spectral function as compared to the exact diagonalization method. This opens the possibility of utilizing the neural network approach as an impurity solver for other many-body numerical approaches, such as the dynamical mean field theory.
Genetic Diversity and Relatedness of Group-Living Small Mammals on the Mongolian Plateau
Authors: Wang Guiming , Wan Xinrong , Liu Wei , Shan Xueyan
Published: September 2022

Genetic diversity plays an important role in the evolution and adaptation of organisms. Losses of genetic diversity make organisms more vulnerable to climate changes and diseases, reducing the viability of small populations. In addition to natural selection, genetic drift, dispersal, inbreeding, and population bottleneck, the social systems of animals may also affect the genetic diversity of populations. We aimed to test the hypothesis that the delayed dispersal of group-living small mammals would reduce genetic diversity through attenuated gene flow but enhance genetic relatedness. We used microsatellite analysis to estimate genetic diversity and the Queller and Goodnight relatedness coefficients of Daurian pikas (Ochotona dauurica) and Mongolian gerbils (Meriones unguiculatus), two socially monogamous small mammals living in social groups in Inner Mongolia, China. The average genetic relatedness of social groups was inversely related to the average genetic diversity of social groups in Daurian pikas but not in Mongolian gerbils, partially supporting our hypothesis. Dispersal following frequent local extinctions resulted in the recolonization of burrow systems by individuals with different genetic makeups, increasing genetic diversity and reducing the genetic relatedness of the social groups of Daurian pikas. On the other hand, delayed short-distance dispersal was sufficient to maintain the high genetic diversity and high genetic relatedness of gerbil social groups independently.
Browsing Damage on Scots Pine: Direct and Indirect Effects of Landscape Characteristics, Moose and Deer Populations
Authors: Pfeffer Sabine E. , Dressel Sabrina , Wallgren Märtha , Bergquist Jonas , Kalén Christer
Published: September 2022

Reducing browsing damages from cervids (Cervidae) on economically valuable tree species is a challenging task in many countries. Apart from cervid abundance, landscape characteristics, such as forest composition, land use, forage availability and climatic conditions, may affect the degree of browsing through both direct and indirect effects. A better understanding of basic mechanisms in this complex system is needed to design efficient and convincing management strategies. Focusing on Sweden as a case, which has been widely studied using regression analyses only, we applied path analysis to test the validity of a model on the indirect and direct links between landscape characteristics, cervid populations, and browsing damages on Scots pine (Pinus sylvestris). Our results validated the tested model in which moose (Alces alces) density and pine availability directly influence browsing damages. Increasing amounts of pine forests, preferred deciduous trees, and young forest had positive direct effects on moose densities and thereby indirectly contributed to increased browsing damages. The density of smaller deer species showed no direct effect on browsing damages on pine. Path analysis corroborated our attempt to disentangle direct and indirect potential causal drivers of browsing damages and shows that the choice of statistical method may alter the understanding of mechanistic driving forces.
The Influence of Social Network Content on the Perception of Smiles—A Randomized Controlled Trial
Authors: Čalušić Šarac Martina , Jakovac Marko
Published: September 2022

Background: This randomized trial’s objective was to investigate the impact of social network content on the perception of smiles among specialists, doctors, students of dental medicine, and laypeople. Method: A sample of 360 respondents was shown 7 digitally altered photographs of smiles (85.63% female, 14.37% male). Dental specialists, dentists, dental students (first to third year and fourth to sixth year), and laypeople made up the sample. Respondents were asked to rank the images on a scale of 1 to 10, starting with the least appealing and moving up to the most attractive, using a Google Form. Respondents were divided into experimental and control groups at the end of the following month by random selection. The experimental group followed an Instagram profile posting two images of beautiful smiles for seven days, while the control group received no intervention at all. Both groups then completed the same questionnaire again. The comparison of esthetic scores between the experimental and control group was performed using the Mann–Whitney U-test and the difference in test responses between the starting point of the measurement and after exposure to perfect content on social media within individual groups was tested with the Wilcoxon paired-samples test. When comparing the absolute difference of scores, the Mann–Whitney U-test and the Kruskal–Wallis test were used. Results: Respondents in the experimental group rated the rounded embrasures of the incisors with lower esthetic scores compared to the control group that was not exposed to images on the Instagram social network. In those exposed to Instagram (experimental group), laypeople showed significantly greater satisfaction with their own smile after the exposure to Instagram, whereas no such difference was present in the control group. Conclusions: The content of social networks potentially has an influence on smile perception, most visible in the perception of incisal embrasures and self-perception of smile.
Pre-Archaeological Investigation by Integrating Unmanned Aerial Vehicle Aeromagnetic Surveys and Soil Analyses
Authors: Cao Wei , Qing Hao , Xu Xing , Liu Chang , Chen Silin , Zhong Yi , Liu Jiabo , Li Yuanjie , Jiang Xiaodong , Gao Dalun , Jiang Zhaoxia , Liu Qingsong
Published: September 2022

Magnetic surveys have been widely used in archaeological field investigations. However, conventional survey methods are often restricted by complicated field conditions and ambiguities in data interpretation. In this study, a novel magnetic survey system was designed for pre-archaeological investigation (preliminary survey prior to the archaeological excavation) based on a modified quadrotor unmanned aerial vehicle (UAV) and was successfully applied to an archaeological area with a complex landform in Huizhou, China. Results show that the target anomaly identified by UAV aeromagnetic survey corresponds well to the location of a potential archaeological site. Subsequent soil analyses further confirm the archaeological value of UAV aeromagnetic results and provide strong constraints on the interpretation of target anomalies. This study demonstrates that the newly proposed UAV aeromagnetic system can adapt to the various field conditions with the advantages of flexibility and efficiency, which has great potential for future archaeological investigations.
A Data Normalization Technique for Detecting Cyber Attacks on UAVs
Authors: Basan Elena , Basan Alexandr , Nekrasov Alexey , Fidge Colin , Abramov Evgeny , Basyuk Anatoly
Published: September 2022

The data analysis subsystem of an Unmanned Aerial Vehicle (UAV) includes two main modules: a data acquisition module for data processing and a normalization module. One of the main features of an adaptive UAV protection system is the analysis of its cyber-physical parameters. An attack on a general-purpose computer system mainly affects the integrity, confidentiality and availability of important information. By contrast, an attack on a Cyber-Physical System (CPS), such as a UAV, affects the functionality of the system and may disrupt its operation, ultimately preventing it from fulfilling its tasks correctly. Cyber-physical parameters are the internal parameters of a system node, including the states of its computing resources, data storage, actuators and sensor system. Here, we develop a data normalization technique that additionally allows us to identify the signs of a cyber-attack. In addition, we define sets of parameters that can highlight an attack and define a new database format to support intrusion detection for UAVs. To achieve these goals, we performed an experimental study of the impact of attacks on UAV parameters and developed a software module for collecting data from UAVs, as well as a technique for normalizing and presenting data for detecting attacks on UAVs. Data analysis and the evaluation of the quality of a parameter (whether the parameter changes normally, or abrupt anomalous changes are observed) are facilitated by converting different types of data to the same format. The resulting formalized CPS model allows us to identify the nature of an attack and its potential impact on UAV subsystems. In the future, such a model could be the basis of a CPS digital twin in terms of security. The presented normalization technique supports processing raw data, as well as classifying data sets for their use in machine learning (ML) analyses in the future. The data normalization technique can also help to immediately determine the presence and signs of an attack, which allows classifying raw data automatically by dividing it into different categories. Such a technique could form the basis of an intrusion detection system for CPSs. Thus, the obtained results can be used to classify attacks, including attack detection systems based on machine learning methods, and the data normalization technique can be used as an independent method for detecting attacks.
Systemic Risk Analysis of Multi-Layer Financial Network System Based on Multiple Interconnections between Banks, Firms, and Assets
Authors: Gao Qianqian
Published: September 2022

Global financial systems are increasingly interconnected, and risks can spread more easily, potentially causing systemic risks. Research on systemic risk based on multi-layer financial networks is relatively scarce, and studies usually focus on only one type of risk. This paper develops a model of the multi-layer financial network system based on three types of links: firm-bank credit, asset-bank portfolio, and interbank lending, which simulates systemic risk under three risk sources: firm credit default, asset depreciation, and bank bankruptcy. The impact of the multi-layer financial network structure, default risk threshold, and bank asset allocation strategy is further explored. It has been shown that the larger the risk shock, the greater the systemic risk under different risk sources, and the risk propagation cycle tends to rise and then decline. As centralized nodes in the multi-layer financial network system, bank nodes may play both blocking and propagation roles under different risk sources. Furthermore, the multi-layer financial network system is most susceptible to bank bankruptcy risk, followed by firm credit default risk. Further research indicates that increasing the average degree of firms in the bank–firm credit network, the density of the bank-asset portfolio network, and the bank capital adequacy ratio all contribute to reducing systemic risk under the three risk sources. Additionally, the more assets a bank holds in a single market, the more vulnerable it is to the risks associated with that market.
Highs, Lows and Turning Points in Marginalised Transitions and Experiences of Noncompletion amongst Pushed Dropouts in South African Higher Education
Authors: Masutha Mukovhe
Published: September 2022

Against a backdrop of dominant deficit, victim-blaming and class/colourblind theories of unequal educational transitions and higher education outcomes, this article analyses thematically in-depth narrative interviews with Black working class “dropouts” in South African higher education to explore how this group of former students narrate and make sense of their educational journeys and how their accounts could strengthen efforts to achieve just and equitable experiences and outcomes for students from all walks of life. Their narrative accounts reveal that, (a) in their marginalised educational transitions, despite disrupted and sometimes traumatic formative years (lows), their transformative habitus and community cultural wealth enables them to find highs in nadir moments; (b) their educational pathways are paved with unlikely steppingstones and improvising agents of transformation who overcome the odds of under-resourced schooling experiences; (c) despite policymakers’ best intentions, student financial aid moderates but does not ameliorate the perils of being Black and working class in higher education; (d) as pushed dropouts, they are victims of a class and colourblind criminalisation of failure that naturalises injustice in already unjust educational contexts. This study illuminates the transformative and social justice potential in analysing narrative accounts of those who often disappear from higher education without a trace.
Implementation of a Clustering-Based LDDoS Detection Method
Authors: Hussain Tariq , Saeed Muhammad Irfan , Khan Irfan Ullah , Aslam Nida , Aljameel Sumayh S.
Published: September 2022

With the rapid advancement and transformation of technology, information and communication technologies (ICT), in particular, have attracted everyone’s attention. The attackers took advantage of this and can caused serious problems, such as malware attack, ransomware, SQL injection attack, etc. One of the dominant attacks, known as distributed denial-of-service (DDoS), has been observed as the main reason for information hacking. In this paper, we have proposed a secure technique, called the low-rate distributed denial-of-service (LDDoS) technique, to measure attack penetration and secure communication flow. A two-step clustering method was adopted, where the network traffic was controlled by using the characteristics of TCP traffic with discrete sense; then, the suspicious cluster with the abnormal analysis was detected. This method has proven to be reliable and efficient for LDDoS attacks detection, based on the NS-2 simulator, compared to the exponentially weighted moving average (EWMA) technique, which has comparatively very high false-positive rates. Analyzing abnormal test pieces helps us reduce the false positives. The proposed methodology was implemented using Python for scripting and NS-2 simulator for topology, two public trademark datasets, i.e., Web of Information for Development (WIDE) and Lawrence Berkley National Laboratory (LBNL), were selected for experiments. The experiments were analyzed, and the results evaluated using Wireshark. The proposed LDDoS approach achieved good results, compared to the previous techniques.
Transformer-Based Distillation Hash Learning for Image Retrieval
Authors: Lv Yuanhai , Wang Chongyan , Yuan Wanteng , Qian Xiaohao , Yang Wujun , Zhao Wanqing
Published: September 2022

In recent years, Transformer has become a very popular architecture in deep learning and has also achieved the same state-of-the-art performance as convolutional neural networks on multiple image recognition baselines. Transformer can obtain global perceptual fields through a self-attention mechanism and can enhance the weights of unique discriminable features for image retrieval tasks to improve the retrieval quality. However, Transformer is computationally intensive and finds it difficult to satisfy real-time requirements when used for retrieval tasks. In this paper, we propose a Transformer-based image hash learning framework and compress the constructed framework to perform efficient image retrieval using knowledge distillation. By combining the self-attention mechanism of the Transformer model, the image hash code is enabled to be global and unique. At the same time, this advantage is instilled into the efficient lightweight model by knowledge distillation, thus reducing the computational complexity and having the advantage of an attention mechanism in the Transformer. The experimental results on the MIRFlickr-25K dataset and NUS-WIDE dataset show that our approach can effectively improve the accuracy and efficiency of image retrieval.
A Novel Anomaly Detection System on the Internet of Railways Using Extended Neural Networks
Authors: Islam Umar , Malik Rami , Al-Johani Amnah , Khan Muhammad. , Daradkeh Yousef , Ahmad Ijaz , Alissa Khalid , Abdul-Samad Zulkiflee , Tag-Eldin Elsayed
Published: September 2022

The Internet of Railways (IoR) network is made up of a variety of sensors, actuators, network layers, and communication systems that work together to build a railway system. The IoR’s success depends on effective communication. A network of railways uses a variety of protocols to share and transmit information amongst each other. Because of the widespread usage of wireless technology on trains, the entire system is susceptible to hacks. These hacks could lead to harmful behavior on the Internet of Railways if they spread sensitive data to an infected network or a fake user. For the previous few years, spotting IoR attacks has been incredibly challenging. To detect malicious intrusions, models based on machine learning and deep learning must still contend with the problem of selecting features. k-means clustering has been used for feature scoring and ranking because of this. To categorize attacks in two datasets, the Internet of Railways and the University of New South Wales, we employed a new neural network model, the extended neural network (ENN). Accuracy and precision were among the model’s strengths. According to our proposed ENN model, the feature-scoring technique performed well. The most accurate models in dataset 1 (UNSW-NB15) were based on deep neural networks (DNNs) (92.2%), long short-term memory LSTM (90.9%), and ENN (99.7%). To categorize attacks, the second dataset (IOR dataset) yielded the highest accuracy (99.3%) for ENN, followed by CNN (87%), LSTM (89%), and DNN (82.3%).
Numerical Analysis and Experimental Investigation of Cavitating Flows Considering Thermal and Compressibility Effects
Authors: Sedlář Milan , Krátký Tomáš , Komárek Martin , Vyroubal Michal
Published: September 2022

This article deals with the numerical simulation of unsteady cavitating flow around hydrofoils, supported by experimental research realized in a cavitation tunnel situated in the Centre of Hydraulic Research. Two straight NACA hydrofoils (NACA0020 and NACA2412) were employed. The comprehensive unsteady CFD analysis was based on scale-resolving simulations (hereinafter SRS) with the aim of capturing correctly the interactions between the cavitation structures and re-entrant flow as well as the compressibility and thermal effects of cavitation. The static pressure fluctuations during the cavity oscillation cycles and the evaporation and condensation processes are discussed in detail. To predict correctly the high-pressure peaks during the bubble cloud collapses and the pressure pulse propagation speed, the real properties of water and the mixture total energy conservation equation were considered. In addition, the estimated content of undissolved air was taken into account. The numerical simulations were validated by means of already published experiments or compared with experiments conducted by the authors, and with good agreement.
Overview of the Policy Instruments for Renewable Energy Development in China
Authors: Song Dongdong , Liu Yuewen , Qin Tianbao , Gu Hongsong , Cao Yang , Shi Hongjun
Published: September 2022

The current legal and policy system of renewable energy in China has set up a framework of policy instruments, which provides an important foundation for dealing with climate change and promoting the healthy development of the renewable energy industry with the goal of “carbon neutrality” and “emission peak”. However, the current policy instruments cannot meet the needs for rapid development of the renewable energy industry. This paper investigates, analyzes, and concludes the status of renewable energy development along with related policy instruments in different renewable energy sources by literature and points out the problems of current policy instruments, and puts forward corresponding countermeasures. Moreover, from the perspective of energy consumption market transformation, the authors carried out an analysis of China’s challenges of policy instruments, pointing out that China’s renewable energy policy instruments have the potential to take one step further in the areas of the regulatory system, legal system and legal security system.
A Critical Analysis of the Oxy-Combustion Process: From Mathematical Models to Combustion Product Analysis
Authors: Raho Brenda , Colangelo Gianpiero , Milanese Marco , de Risi Arturo
Published: September 2022

Fossil fuels are the most widely used resource for energy production. Carbon dioxide (CO2) emissions are correlated with climate change, and therefore these emissions must be reduced in the future. It is possible by means of many different technologies, and one of the most promising seems to be oxyfuel combustion. This process, with oxygen and recirculating gas, produces a concentrated stream of CO2 and water. In recent years, many scientists carried out research and studies on the oxyfuel process, but a sufficient level of knowledge was not yet reached to exploit the great potential of this new technology. Although such areas of research are still highly active, this work provides an overview and summary of the research undertaken, the state of development of the technology, and a comparison of different plants so far.
Oil-Removal Performance of Rotating-Disk-Type Oil Separator
Authors: Lee Haneol , Lee Yeawan , Kim Yong-Jin , Han Bangwoo , Kim Hak-Joon
Published: September 2022

Oil mist adversely affects the health of workplace workers, and for this reason, regulations on the limitation of the oil-mist exposure of workers are becoming stricter. In order to reduce the amount of the exposure of workers to oil mist, it is important to effectively remove oil mist from machine tools. In this study, the collection efficiency according to the geometry of the oil-mist-collection cyclone consisting of several disks and the output power and rotation speed of the motor were evaluated. Most of the generated oil mists were less than 10 μm, and the mist removal was assessed using an optical particle counter. The cyclone airflow rate increased linearly with the rotational speed, and the rate was affected more by the cyclone geometry than by the power consumption. The mist-removal performance was significantly enhanced when plate- and cone-type disks were added to the rotating blades. The removal efficiencies of PM10 and PM2.5 under the maximum operational conditions of 5000 rpm and a flow rate of 3.73 m3/min were 93.4% and 78.4%, respectively. The removal capacity was more affected by the cyclone geometry than the rotational speed. The experimental results were similar to those predicted by the modified Lapple theory when an appropriate slope parameter (β) was used.
Development of a Weighting Procedure for Geomechanical Risk Assessment
Authors: Mortazavi Ali , Kuzembayev Nursultan
Published: September 2022

Underground mining is one of the riskiest industries. It is well established that the investigation of geomechanical parameters at the design stage of an underground mine provides the approximate rock mass characteristics, which are associated with some risks in the design. From a realistic risk assessment point of view, it is essential to classify risky design parameters as relevant to risk groups and determine a suitable weighting strategy for risk-prone elements aiming at risk assessment. Therefore, a realistic weighting procedure is an essential step in making realistic design decisions to increase the safety of mining operations and economic vitality. This study aimed to develop a realistic weighting procedure to assess and compare various geomechanical parameters that pose a risk to opening stability. In this research, sub-level stoping mining methods, which are commonly used in the Kazakhstan mining industry, were selected to test the developed weighting algorithm. In this study, the risk-prone geomechanical parameters for the chosen mining method were defined, and a weighting procedure was developed using the Fuzzy Analytic Hierarchy Process (FAHP) method. The proposed methodology was verified against available data from the Ridder–Sokolny underground mine, and the analysis results showed good agreement with actual observations in the mine. The obtained preliminary results show that FAHP is a reliable method for weighting geomechanical parameters and can be used as an input in any geomechanical risk assessment practice.
The Potential of Constructed Wetland Systems and Photodegradation Processes for the Removal of Emerging Contaminants—A Review
Authors: Sánchez Marta , Ruiz Isabel , Soto Manuel
Published: September 2022

The presence of emerging organic contaminants (EOCs) in the environment is increasing and requires the development of technologies for their effective removal. Therefore, a literature review on the behavior of EOCs during municipal wastewater treatment, both in major treatment systems and particularly in constructed wetlands (CWs), was carried out. The study also reviewed the behavior of EOCs in anaerobic digesters (ADs) and advanced oxidation processes, particularly in TiO2-based photocatalysis, which are being proposed as promising pre- and post-treatments for combination with CW. The following ten compounds were screened: acetaminophen (ACE), ofloxacin (OFL), caffeine (CAF), carbamazepine (CBZ), ketoprofen (KET), ibuprofen (IBU), diclofenac (DCL), clofibric acid (ACB), bisphenol A (BPA), and sotalol (SOT). The degradation pathways of the selected EOCs are largely influenced by their physicochemical and biochemical properties. Sorption and biodegradation are the main elimination mechanisms found in AD and CW treatment systems, where the combination of anaerobic and aerobic environments improves the elimination efficiency of EOCs. However, various contaminants appear recalcitrant. In this sense, in combination with CWs, TiO2-based photocatalysis emerges as a promising post-treatment for advanced EOC removal from wastewater.