bluuebunny/crossref_metadata_2025 huggingface dataset:
The Immunomodulatory Role of Hypoxic Tumor-Derived Extracellular Vesicles
Authors: Beaumont Joel E. J. , Beelen Nicky A. , Wieten Lotte , Rouschop Kasper M. A.
Published: August 2022

Tumor-associated immune cells frequently display tumor-supportive phenotypes. These phenotypes, induced by the tumor microenvironment (TME), are described for both the adaptive and the innate arms of the immune system. Furthermore, they occur at all stages of immune cell development, up to effector function. One major factor that contributes to the immunosuppressive nature of the TME is hypoxia. In addition to directly inhibiting immune cell function, hypoxia affects intercellular crosstalk between tumor cells and immune cells. Extracellular vesicles (EVs) play an important role in this intercellular crosstalk, and changes in both the number and content of hypoxic cancer-cell-derived EVs are linked to the transfer of hypoxia tolerance. Here, we review the current knowledge about the role of these hypoxic cancer-cell-derived EVs in immunosuppression. In addition, we provide an overview of hypoxia-induced factors (i.e., miRNA and proteins) in tumor-derived EVs, and their role in immunomodulation.
Comparative Efficacy of Tapentadol versus Tapentadol Plus Duloxetine in Patients with Chemotherapy-Induced Peripheral Neuropathy (CIPN): A Randomized Non-Inferiority Clinical Trial
Authors: Sansone Pasquale , Giaccari Luca Gregorio , Aurilio Caterina , Coppolino Francesco , Passavanti Maria Beatrice , Pota Vincenzo , Pace Maria Caterina
Published: August 2022

Introduction: Chemotherapy-induced peripheral neuropathy (CIPN) is a common complication due to treatment with many commonly used anti-cancer agents. CIPN is a mainly sensory neuropathy that can be characterized by the appearance of motor and autonomic alterations. Clinicians may offer duloxetine (DLX) for patients with cancer experiencing CIPN. Our aim was to assess the non-inferiority of the analgesic effect and safety of tapentadol (TP) alone compared to duloxetine plus tapentadol administered to patients with CIPN. Methods: A total of 114 patients were enrolled in the study and randomized to receive tapentadol in a dosage of 50 to 500 mg/day (n = 56) or tapentadol plus duloxetine in a dosage of 60 to 120 mg/day (n = 58) for a period of 4 weeks. We evaluated the analgesia efficacy, defined as a decrease in pain on the NRS between the first administration and 28 days later. Secondary endpoints included analgesia efficacy at 28 and 42 days, defined by a decrease in DN4 and LEPs, decrease in quality of life, and the incidence of any serious or non-serious adverse events after the first administration. Results: In this randomized, double-blind trial comparing TP and TP plus DLX for CIPN management, TP was feasible and non-inferior to the association with DLX as far as the reduction of pain after chemotherapy at 28 days is concerned. Scores on other rating scales evaluating the quality of life, anxiety and depression, and the characteristics of pain revealed similar improvements associated with tapentadol versus duloxetine at these time points. Conclusion: The use of TP is a safe and effective analgesic therapy in patients with CIPN. Positive effects of TP were noted on the patients’ quality-of-life assessments.
5-ALA Is a Potent Lactate Dehydrogenase Inhibitor but Not a Substrate: Implications for Cell Glycolysis and New Avenues in 5-ALA-Mediated Anticancer Action
Authors: Grigalavicius Mantas , Ezzatpanah Somayeh , Papakyriakou Athanasios , Raabe Tine Therese Henriksen , Yannakopoulou Konstantina , Theodossiou Theodossis A.
Published: August 2022

In a course of metabolic experiments, we determined that the addition of δ-aminolevulinic acid (5-ALA) to a panel of glioblastoma multiforme (GBM) cells caused a steep reduction in their glycolytic activity. This reduction was accompanied by a decrease in adenosine triphosphate (ATP) production from glycolysis. These results suggested that 5-ALA is an inhibitor of glycolysis; due to the structural similarity of 5-ALA to the established lactate dehydrogenase (LDH) inhibitors oxamate (OXM) and tartronate (TART), we initially investigated LDH inhibition by 5-ALA in silico. The modelling revealed that 5-ALA could indeed be a competitive inhibitor of LDH but not a substrate. These theoretical findings were corroborated by enzymatic and cell lysate assays in which 5-ALA was found to confer a potent LDH inhibition comparable to that of OXM and TART. We subsequently evaluated the effect of 5-ALA-induced glycolysis inhibition on the viability of GBM cells with diverse metabolic phenotypes. In the Warburg-type cell lines Ln18 and U87, incubation with 5-ALA elicited profound and irreversible cell death (90–98%) at 10 mM after merely 24 h. In T98G, however, which exhibited both high respiratory and glycolytic rates, LD95 was achieved after 72 h of incubation with 20 mM 5-ALA. We additionally examined the production of the 5-ALA photosensitive metadrug protoporphyrin IX (PpIX), with and without prior LDH inhibition by TART. These studies revealed that ~20% of the 5-ALA taken up by the cells was engaged in LDH inhibition. We subsequently performed 5-ALA photodynamic therapy (PDT) on Ln18 GBM cells, again with and without prior LDH inhibition with TART, and found a PDT outcome enhancement of ~15% upon LDH pre-inhibition. We expect our findings to have a profound impact on contemporary oncology, particularly for the treatment of otherwise incurable brain cancers such as GBM, where the specific accumulation of 5-ALA is very high compared to the surrounding normal tissue.
Patterns and Predictors of Cervical Lymph Node Metastasis in Parathyroid Carcinoma
Authors: Hu Ya , Cui Ming , Chang Xiaoyan , Wang Ou , Chen Tianqi , Xiao Jinheng , Wang Mengyi , Hua Surong , Liao Quan
Published: August 2022

Background: Parathyroid carcinoma (PC) is a rare endocrine malignancy with poor outcomes. Over 60% of PC patients experience repeated disease recurrence or metastasis. The significance of cervical lymph node dissection (LND) for PC remains inconclusive. Methods: PC patients diagnosed at Peking Union Medical College Hospital between 1992 and 2021 were reviewed retrospectively. Clinical data, initial tumor histological staging, parafibromin histochemical staining results, Ki67 index, CDC73 gene mutation status and outcome information were collected systemically. The risk factors for recurrence and lymph node or distant metastasis were explored. Results: Sixty-eight PC patients receiving LND were enrolled. Cervical lymph node metastasis was identified in 19.4% of patients at initial surgery and 25.0% of patients including reoperations for recurrences. The independent risk factor for PC recurrence was a Ki67 index ≥ 5% (HR4.41, 95% confidence interval (CI)1.30–14.95, p = 0.017). Distant metastasis was an independent prognostic factor for PC patient overall survival (HR 5.44, 95% CI 1.66–17.82, p = 0.005). High-risk Schulte staging (p = 0.021) and CDC73 abnormalities (p = 0.012) were risk factors for cervical lymph node metastasis. Conclusion: Most PCs were slow-growing, but lymph node metastasis was not rare. For patients planning to undergo remedial surgery after previous local resection of PC, central LND is suggested for tumors with high-risk Schulte staging or CDC73 abnormalities.
Copper-Catalyzed Reactions of Aryl Halides with N-Nucleophiles and Their Possible Application for Degradation of Halogenated Aromatic Contaminants
Authors: Weidlich Tomáš , Špryncová Martina , Čegan Alexander
Published: August 2022

This review summarizes recent applications of copper or copper-based compounds as a nonprecious metal catalyst in N-nucleophiles-based dehalogenation (DH) reactions of halogenated aromatic compounds (Ar-Xs). Cu-catalyzed DH enables the production of corresponding nonhalogenated aromatic products (Ar-Nu), which are much more biodegradable and can be mineralized during aerobic wastewater treatment or which are principally further applicable. Based on available knowledge, the developed Cu-based DH methods enable the utilization of amines for effective cleavage of aryl-halogen bonds in organic solvents or even in an aqueous solution.
Monolayer CoMoS Catalysts on Hierarchically Porous Alumina Spheres as Bifunctional Nanomaterials for Hydrodesulfurization and Energy Storage Applications
Authors: Delgado Anabel D. , Álvarez-Contreras Lorena , Beltrán Karen A. , Arjona Noé , Guerra-Balcázar Minerva , Béjar José , Aguilar-Elguezabal Alfredo
Published: August 2022

In this work, CoMoS catalysts were synthesized onto porous alumina spheres obtained using Pluronic P-123 (PS) or urea (US) and used as bifunctional nanomaterials for two energy applications: hydrodesulfurization and energy storage. For the first application, the catalysts were assessed in a hydrodesulfurization reactor using two model sulfur molecules, dibenzothiophene and 4,6-dimethyl dibenzothiophene, as well as feeding a heavy oil fraction. The results indicated that the spheres obtained by Pluronic P-123 allowed a greater dispersion degree of MoS2 slabs than US, indicating that the size and hierarchically porous structure of alumina spheres played a principal role as a booster of the HDS catalytic efficiency of DBT, 4,6 DMDBT and diesel fuel. Then, these catalysts were used for the electrocatalysis of the oxygen reduction and oxygen evolution reactions (ORR/OER), which take place in rechargeable Zn-air batteries. For the ORR, the CoMoS catalyst on PS in the presence of a conductive support (N-doped carbon nanotubes + graphene) displayed an overpotential of only 90 mV in comparison with Pt/C. Importantly, the chalcogenide enabled an increase in the stability, maintaining almost two times higher current retention than Pt/C for the ORR and IrO2/C for the OER. These results suggest that expended chalcogenides from the hydrodesulfurization industry can have a second life as co-catalysts for renewable energy storage systems, enabling a circular economy.
Harmful Impact of Tobacco Smoking and Alcohol Consumption on the Atrial Myocardium
Authors: Ohlrogge Amelie H. , Frost Lars , Schnabel Renate B.
Published: August 2022

Tobacco smoking and alcohol consumption are widespread exposures that are legal and socially accepted in many societies. Both have been widely recognized as important risk factors for diseases in all vital organ systems including cardiovascular diseases, and with clinical manifestations that are associated with atrial dysfunction, so-called atrial cardiomyopathy, especially atrial fibrillation and stroke. The pathogenesis of atrial cardiomyopathy, atrial fibrillation, and stroke in context with smoking and alcohol consumption is complex and multifactorial, involving pathophysiological mechanisms, environmental, and societal aspects. This narrative review summarizes the current literature regarding alterations in the atrial myocardium that is associated with smoking and alcohol.
The Landscape of Tumor-Infiltrating Immune Cells in Feline Mammary Carcinoma: Pathological and Clinical Implications
Authors: Nascimento Catarina , Gameiro Andreia , Correia Jorge , Ferreira João , Ferreira Fernando
Published: August 2022

Feline mammary carcinoma (FMC) shares key molecular and clinicopathological features with human breast cancer. We have herein studied the inflammatory infiltrate of FMC in order to uncover potential therapeutic targets and prognostic markers. To this end, the expression of different markers (CD3, CD4, CD8, CD20, CD56, FoxP3, CD68 and CD163) was analyzed in total, stromal (s) and intratumoral (i) tumor-infiltrating lymphocytes (TILs) and tumor-associated macrophages (TAMs), in 73 feline mammary carcinomas. The results revealed that higher percentages of sCD8+ TILs were associated with longer disease-free survival (p = 0.05) and overall survival (p = 0.021). Additionally, higher percentages of iCD4+ TILs correlated with positive lymph node status (p = 0.003), whereas CD163+ TAMs were associated with undifferentiated tumors (p = 0.013). In addition, sCD3+ (p = 0.033), sCD8+ (p = 0.044) and sCD68+ (p = 0.023) immune cells were enriched in triple negative normal-like carcinomas compared to other subtypes. Altogether, our results suggest that specific subsets of immune cells may play a major role in clinical outcome of cats with mammary carcinoma, resembling what has been reported in human breast cancer. These data further support the relevance of the feline model in breast cancer studies.
Preparation of Ca2Al1–mFem(OH)6Cl·2H2O-Doped Hydrocalumites and Application of Their Derived Mixed Oxides in the Photodegradation of Ibuprofen
Authors: Jiménez Alejandro , Valverde Marta , Misol Alexander , Trujillano Raquel , Gil Antonio , Vicente Miguel Angel
Published: August 2022

Aluminum from saline slags generated during the recycling of this metal, extracted under reflux conditions with aqueous NaOH, was used in the synthesis of hydrocalumite-type solids with the formula Ca2Al1–mFem(OH)6Cl·2H2O. The characterization of the obtained solids was carried out by powder X-ray diffraction, infrared spectroscopy, thermal analysis, element chemical analysis, N2 adsorption-desorption at −196 °C and electron microscopy. The results showed the formation of Layered Double Hydroxide-type compounds whose characteristics varied as the amount of incorporated Fe3+ increased. These solids were calcined at 400 °C and evaluated for the catalytic photodegradation of ibuprofen, showing promising results in the elimination of this drug by advanced oxidation processes. The CaAl photocatalyst (without Fe) showed the best performance under UV light for the photodegradation of ibuprofen.
The Association between Obesity and Depression among Children and the Role of Family: A Systematic Review
Authors: Kanellopoulou Aikaterini , Antonogeorgos George , Douros Konstantinos , Panagiotakos Demosthenes B.
Published: August 2022

One of the most critical factors that affects or leads to obesity is depression. However, another point of view is that obesity leads to depression. This systematic review estimates evidence arising from observational and systematic studies concerning the association between obesity and depression in children and adolescents. Moreover, the role of the family environment is investigated in this review. A systematic literature search was performed for research conducted between 2014 and 2021 on PubMed. The basic inclusion criteria were the language, study issue and type, and age of the participants. Studies that examined non-healthy populations, or were not related, or with no access were excluded. Titles and abstracts were screened independently, and full-text manuscripts meeting inclusion criteria were extracted. Finally, twenty-seven studies were retained. Most of them highlighted a positive association between obesity and depression. However, it is not clear whether obesity leads to depression or vice versa. Our review also revealed that the role of the family in this association has not been well studied and understood, since only one study addressed the issue. The evidence from our review emphasizes major public health issues; therefore, appropriate health policies should be developed. Moreover, additional research is required to fully understand the role of the family environment in the association between depression and obesity in childhood.
Characteristics of Thin High Entropy Alloy Films Grown by Pulsed Laser Deposition
Authors: Laszlo Edwin Alexandru , Crăciun Doina , Dorcioman Gabriela , Crăciun Gabriel , Geantă Victor , Voiculescu Ionelia , Cristea Daniel , Crăciun Valentin
Published: August 2022

Starting from solid-solutions (SS) of AlCoCrFeNix high-entropy alloys (HEAs) that have been produced with high purity constituent elements by vacuum arc remelting (VAR) method varying the nickel molar ratio x from 0.2 to 2.0, we investigated the synthesis of protective thin films of HEAs and high-entropy nitrides (HENs) with the aid of the pulsed laser deposition (PLD) system. The structure of all ten available bulk targets have been examined by means of X-Ray Diffraction (XRD), as well as their elemental composition by means of energy dispersion X-ray spectroscopy (EDS). Three targets with nickel molar composition x = 0.4, 1.2 and 2.0 corresponding to BCC, mixed BCC and FCC, and finally FCC structures were used for thin film depositions using a KrF excimer laser. The depositions were performed in residual low vacuum (10−7 mbar) and under N2 (10−4 mbar) at room temperature (RT~25 °C) on Si and glass substrates. The deposited films’ structure was investigated using grazing incidence XRD, their surface morphology, thickness and elemental composition by scanning electron microscopy (SEM), EDS and X-ray photoelectron spectroscopy (XPS), respectively. A homemade four-point probe (4PP) set-up was applied to determine layers electrical resistance. Besides, a Nanoindentation (NI) was employed to test films’ mechanical properties. XRD results showed that all deposited films, regardless of the initial structure of targets, were a mixture of FCC and BCC structures. Additionally, the quantitative and qualitative EDS and XPS results showed that the elemental composition of films was rather close to that of the targets. The depositions under an N2 atmosphere resulted in the inclusion of several percentage nitrogen atoms in a metallic nitride type compound into films, which may explain their higher electrical resistivity. The Young’s modulus, nanohardness and friction coefficient values showed that the deposited films present good mechanical properties and could be used as protective coatings to prevent damage in harsh environments.
COVID-19 Vaccines Related User’s Response Categorization Using Machine Learning Techniques
Authors: Shahzad Ahmed , Zafar Bushra , Ali Nouman , Jamil Uzma , Alghadhban Abdulaziz Jarallah , Assam Muhammad , Ghamry Nivin A. , Eldin Elsayed Tag
Published: August 2022

Respiratory viruses known as coronaviruses infect people and cause death. The multiple crown-like spikes on the virus’s surface give them the name “corona”. The pandemic has resulted in a global health crisis and it is expected that every year we will have to fight against different COVID-19 variants. In this critical situation, the existence of COVID-19 vaccinations provides hope for mankind. Despite severe vaccination campaigns and recommendations from health experts and the government, people have perceptions regarding vaccination risks and share their views and experiences on social media platforms. Social attitudes to these types of vaccinations are influenced by their positive and negative effects. The analysis of such opinions can help to determine social trends and formulate policies to increase vaccination acceptance. This study presents a methodology for sentiment analysis of the global perceptions and perspectives related to COVID-19 vaccinations. The research is performed on five vaccinations that include Sinopharm, Pfizer, Moderna, AstraZeneca, and Sinovac on the Twitter platform extracted using Twitter crawling. To effectively perform this research, tweets datasets are categorized into three groups, i.e., positive, negative and natural. For sentiment classification, different machine learning classifiers are used such as Random Forest (RF), Naive Bayes (NB), Decision Tree (DT), Logistic Regression (LR), and Support Vector Machine (SVM). It should be noted that the Decision tree classifier achieves the highest classification performance in all datasets as compared to the other machine learning algorithms. For COVID-19 Vaccine Tweets with Sentiment Annotation (CVSA), the highest accuracy obtained is 93.0%, for the AstraZeneca vaccine dataset 90.94%, for the Pfizer vaccine dataset 91.07%, 88.01% accuracy for the Moderna vaccine dataset, for the Sinovac vaccine dataset 92.8% accuracy, and 93.87% accuracy for the Sinopharm vaccine dataset, respectively. The quantitative comparisons demonstrate that the proposed research achieves better accuracy as compared to state-of-the-art research.
Skin Sensory Assessors Highly Agree on the Appraisal of Skin Smoothness and Elasticity but Fairly on Softness and Moisturization
Authors: Saito Naoki , Matsumori Kohei , Kazama Taiki , Arakawa Naomi , Okamoto Shogo
Published: August 2022

We tested the reliability of sensory evaluations of tactile sensation on bare skin and investigated the reliability among evaluation attributes by trained and untrained assessors. Two trained professional panelists and two untrained researchers evaluated skin in terms of several attributes: smooth–rough, elastic–not elastic, soft–hard (surface), soft–hard (base), moisturized–dry. Twenty-two women aged 25–57 years were evaluated, and the sensory evaluation was repeated twice. Correlation coefficients and intraclass correlation coefficients (ICCs) were used to examine intra- and inter-assessor reliability. The sensory evaluation and physical quantities acquired by commercial and non-commercial instruments were moderately correlated. Smooth–rough and elastic–not elastic showed high or moderate inter-assessor reliabilities with mean correlation coefficients between panelists of 0.81 and 0.58, respectively. Further, the ICC (2,1) values were 0.64 and 0.51, respectively, and the ICC (2,2) values were 0.77 and 0.67, respectively. Conversely, the reliabilities of soft–hard (surface), soft–hard (base), and moisturized–dry were low; the mean correlation coefficients between the panelists were 0.36, 0.23, and 0.22; the ICC (2,1) values were 0.27, 0.23, and 0.17; and the ICC (2,2) values were 0.42, 0.29, and 0.26, respectively. Reliability differed between attributes. We found no meaningful differences between the trained and untrained panelists regarding intra- or inter-assessor reliability.
Spatial Variations of Aquatic Bacterial Community Structure and Co-Occurrence Patterns in a Coal Mining Subsidence Lake
Authors: Fan Tingyu , Fang Wangkai , Zhao Yifan , Lu Akang , Wang Shun , Wang Xingming , Xu Liangji , Wei Xiangping , Zhang Lei
Published: August 2022

Land subsidence caused by underground coal mining critically influences the structure and function of ecosystems in mining areas. However, knowledge on the aquatic bacterial community structure and interspecies interactions in subsidence lakes are still limited. To address this issue, we collected water samples from a coal mining subsidence lake and its connected river and investigated the spatial distribution and co-occurrence patterns of the bacterial community using 16S rRNA amplicon sequencing. The results revealed that the bacterial α-diversity in the subsidence lake was higher than that in the river. The bacterial community composition was also significantly different between the subsidence lake and its connected river. Total nitrogen explained 21.4% of the bacterial community composition variation, while sulfate explained 38.4% of the bacterial functional composition variation. Co-occurrence network analysis indicated that the modularity indices and stability of the microbial network in the subsidence lake were significantly higher than those in rivers, which presented more resistance to environmental disturbance. Keystone bacterial taxa in the subsidence lake and river included the Clostridiaceae 1 family, and the Shewanella, Flavobacterium, and Limnohabitans genera, which play vital roles in the carbon, sulfur, and nitrogen cycles. Moreover, functional analysis showed that assimilatory sulfate reduction processes had a major role in the sulfur cycle of the subsidence lake and its connected river ecosystem. Overall, our findings provide new insights into the microbial community structure and assembly in subsidence lakes and its connected river ecosystems, with significant implications for the responsible utilization of water resources and the promotion of sustainable development in mining areas.
Impacts of Parthenium hysterophorus L. on Plant Species Diversity in Ginir District, Southeastern Ethiopia
Authors: Boja Mesfin , Girma Zerihun , Dalle Gemedo
Published: August 2022

Invasive alien species are considered the second greatest global threat to biodiversity. This study is aimed at determining the impacts of Parthenium hysterophorus on herbaceous and woody plant species diversity in the Ginir district, southeast Ethiopia. Data on vegetation were collected from the three study sites’ four land use types, with each land use type having invaded and non-invaded land units. A systematic random sampling method was used for establishing sampling plots. To examine the impacts of the invasive on native plant diversity, a total of 160 plots (120 plots of 1 m2 on grazing lands, roadsides, and abandoned agricultural lands and 40 plots of 20 m2 for sampling herbaceous and tree (shrub) species, respectively) were established. The number of plots was equally distributed in both invaded and adjacent non-invaded areas. Plant species from each plot were recorded and identified. In each plot, all the individuals of P. hysterophorus were counted, the heights of the five tallest individuals were measured, and the mean height was calculated. The percentage cover of P. hysterophorus was visually estimated. The data were analyzed using both descriptive and inferential statistics. A total of 105 plant species (45 trees/shrubs and 60 herbaceous) belonging to 84 genera and 42 families were documented in the study area. The result showed a strong negative relationship between the density of P. hysterophorus and other plant species richness (r = −0.82, p = 0.013) and species abundance (r = −0.917, p = 0.001) per study site of the invaded community. Species richness in the non-invaded site was higher (105 species) than in the invaded area (63 species), demonstrating the negative impact of P. hysterophorus on local biodiversity. Furthermore, the number of plant families was 42 in the non-invaded area, in contrast to only 32 in the invaded areas, a 23.8% decline. Of the plant communities, similarity indices between non-invaded and invaded sites among different land use types were >50%. It was concluded that P. hysterophorus was one of the most dominant invasive alien species in the study area that reduced the species diversity of various plant species. Putting in place a strategy and effective planning for the control and management of this invasive alien species is strongly recommended.
Analytical Performance of Different Laboratory Methods for Measuring Susoctocog-Alfa
Authors: Novembrino Cristina , Quaglia Ilaria , Molinari Angelo , Borchiellini Alessandra , Coppola Antonio , Santoro Rita , Boscolo-Anzoletti Massimo , Galbiati Eleonora , Zanon Ezio , Valpreda Alessandra
Published: August 2022

Recombinant porcine factor VIII (rpFVIII) is indicated for treating bleeding episodes in acquired haemophilia A, but there are few data regarding laboratory methods to adequately monitor treatment. This study involving three Italian laboratories aimed to evaluate the analytical performance of different assays for measuring rpFVIII. Five spiked rpFVIII samples (0.5–1.5 IU/mL) were analysed on three days, in triplicate, with eleven combinations of reagents (Werfen, Boston, MA, USA: SynthasIL and SynthaFax for one-stage assay, Chromogenix Coamatic FVIII for chromogenic assay), FVIII depleted plasmas (with or without von Willebrand factor—VWF) and calibrators (HemosIL human calibrator plasma, porcine calibrator diluted in FVIII deficient plasma with or without VWF). The assays were performed on ACL TOP analysers (Werfen, Boston, MA, USA). Intra- and inter-assay and inter-laboratory Coefficient of Variation (CV%) were calculated together with percentage of recovery (% recovery) on the expected value. The results showed that the reagent combinations reaching satisfactory analytical performance are: SynthasIL/human calibrator/deficient plasma+VWF (total recovery 99.4%, inter-laboratory CV 4.04%), SynthasIL/porcine calibrator/deficient plasma+VWF (total recovery 111%, inter-laboratory CV 2.75%) and Chromogenic/ porcine calibrator/deficient plasma+VWF (total recovery 96.6%, inter-laboratory CV 8.32%). This study highlights that the use of porcine standard (when available) and FVIII deficient plasma with VWF should be recommended.
Efficient Privacy-Preserving K-Means Clustering from Secret-Sharing-Based Secure Three-Party Computation
Authors: Wei Weiming , Tang Chunming , Chen Yucheng
Published: August 2022

Privacy-preserving machine learning has become an important study at present due to privacy policies. However, the efficiency gap between the plain-text algorithm and its privacy-preserving version still exists. In this paper, we focus on designing a novel secret-sharing-based K-means clustering algorithm. Particularly, we present an efficient privacy-preserving K-means clustering algorithm based on replicated secret sharing with honest-majority in the semi-honest model. More concretely, the clustering task is outsourced to three semi-honest computing servers. Theoretically, the proposed privacy-preserving scheme can be proven with full data privacy. Furthermore, the experimental results demonstrate that our proposed privacy version reaches the same accuracy as the plain-text one. Compared to the existing privacy-preserving scheme, our proposed protocol can achieve about 16.5×–25.2× faster computation and 63.8×–68.0× lower communication. Consequently, the proposed privacy-preserving scheme is suitable for secret-sharing-based secure outsourced computation.
On the Spatial Distribution of Temporal Complexity in Resting State and Task Functional MRI
Authors: Omidvarnia Amir , Liégeois Raphaël , Amico Enrico , Preti Maria Giulia , Zalesky Andrew , Van De Ville Dimitri
Published: August 2022

Measuring the temporal complexity of functional MRI (fMRI) time series is one approach to assess how brain activity changes over time. In fact, hemodynamic response of the brain is known to exhibit critical behaviour at the edge between order and disorder. In this study, we aimed to revisit the spatial distribution of temporal complexity in resting state and task fMRI of 100 unrelated subjects from the Human Connectome Project (HCP). First, we compared two common choices of complexity measures, i.e., Hurst exponent and multiscale entropy, and observed a high spatial similarity between them. Second, we considered four tasks in the HCP dataset (Language, Motor, Social, and Working Memory) and found high task-specific complexity, even when the task design was regressed out. For the significance thresholding of brain complexity maps, we used a statistical framework based on graph signal processing that incorporates the structural connectome to develop the null distributions of fMRI complexity. The results suggest that the frontoparietal, dorsal attention, visual, and default mode networks represent stronger complex behaviour than the rest of the brain, irrespective of the task engagement. In sum, the findings support the hypothesis of fMRI temporal complexity as a marker of cognition.
Design of DNA Storage Coding with Enhanced Constraints
Authors: Li Xiangjun , Zhou Shihua , Zou Lewang
Published: August 2022

Traditional storage media have been gradually unable to meet the needs of data storage around the world, and one solution to this problem is DNA storage. However, it is easy to make errors in the subsequent sequencing reading process of DNA storage coding. To reduces error rates, a method to enhance the robustness of the DNA storage coding set is proposed. Firstly, to reduce the likelihood of secondary structure in DNA coding sets, a repeat tandem sequence constraint is proposed. An improved DTW distance constraint is proposed to address the issue that the traditional distance constraint cannot accurately evaluate non-specific hybridization between DNA sequences. Secondly, an algorithm that combines random opposition-based learning and eddy jump strategy with Aquila Optimizer (AO) is proposed in this paper, which is called ROEAO. Finally, the ROEAO algorithm is used to construct the coding sets with traditional constraints and enhanced constraints, respectively. The quality of the two coding sets is evaluated by the test of the number of issuing card structures and the temperature stability of melting; the data show that the coding set constructed with ROEAO under enhanced constraints can obtain a larger lower bound while improving the coding quality.
Memory Forensics-Based Malware Detection Using Computer Vision and Machine Learning
Authors: Shah Syed Shakir Hameed , Ahmad Abd Rahim , Jamil Norziana , Khan Atta ur Rehman
Published: August 2022

Malware has recently grown exponentially in recent years and poses a serious threat to individual users, corporations, banks, and government agencies. This can be seen from the growth of Advanced Persistent Threats (APTs) that make use of advance and sophisticated malware. With the wide availability of computer-automated tools such as constructors, email flooders, and spoofers. Thus, it is now easy for users who are not technically inclined to create variations in existing malware. Researchers have developed various defense techniques in response to these threats, such as static and dynamic malware analyses. These techniques are ineffective at detecting new malware in the main memory of the computer and otherwise require considerable effort and domain-specific expertise. Moreover, recent techniques of malware detection require a long time for training and occupy a large amount of memory due to their reliance on multiple factors. In this paper, we propose a computer vision-based technique for detecting malware that resides in the main computer memory in which our technique is faster or memory efficient. It works by taking portable executables in a virtual environment to extract memory dump files from the volatile memory and transform them into a particular image format. The computer vision-based contrast-limited adaptive histogram equalization and the wavelet transform are used to improve the contrast of neighboring pixel and to reduce the entropy. We then use the support vector machine, random forest, decision tree, and XGBOOST machine learning classifiers to train the model on the transformed images with dimensions of 112 × 112 and 56 × 56. The proposed technique was able to detect and classify malware with an accuracy rate of 97.01%. Its precision, recall, and F1-score were 97.36%, 95.65%, and 96.36%, respectively. Our finding shows that our technique in preparing dataset with more efficient features to be trained by the Machine Learning classifiers has resulted in significant performance in terms of accuracy, precision, recall, F1-score, speed and memory consumption. The performance has superseded most of the existing techniques in its unique approach.
Time-Dependent Prediction of Microblog Propagation Trends Based on Group Features
Authors: Zhao Qin , Zhou Zheyu , Li Jingjing , Jia Shilin , Pan Jianguo
Published: August 2022

The conventional machine learning-based method for the prediction of microblogs’ reposting number mainly focuses on the extraction and representation of static features of the source microblogs such as user attributes and content attributes, without taking into account the problem that the microblog propagation network is dynamic. Moreover, it neglects dynamic features such as the change of the spatial and temporal background in the process of microblog propagation, leading to the inaccurate description of microblog features, which reduces the performance of prediction. In this paper, we contribute to the study on microblog propagation trends, and propose a new microblog feature presentation and time-dependent prediction method based on group features, using a reposting number which reflects the scale of microblog reposting to quantitatively describe the spreading effect and trends of the microblog. We extract some dynamic features created in the process of microblog propagation and development, and incorporate them with some traditional static features as group features to make a more accurate presentation of microblog features than a traditional machine learning-based research. Subsequently, based on the group features, we construct a time-dependent model with the LSTM network for further learning its hidden features and temporal features, and eventually carry out the prediction of microblog propagation trends. Experimental results show that our approach has better performance than the state-of-the-art methods.
Congestion-Aware Rideshare Dispatch for Shared Autonomous Electric Vehicle Fleets
Authors: Huang Chenn-Jung , Hu Kai-Wen , Hsieh Cheng-Yang
Published: August 2022

The problem of traffic congestion caused by the fast-growing travel demands has been getting serious in urban areas. Meanwhile, the future of urban mobility has been foreseen as being electric, shared, and autonomous. Accordingly, the routing and charging strategies for fleets of shared autonomous electric vehicles (SAEVs) need to be carefully addressed to cope with the characteristics of the rideshare service operation of the SAEV fleets. In the literature, much work has been done to develop various traffic control strategies for alleviating the problem in urban traffic congestion. However, little research has proposed effective solutions that integrate the route of charging strategies for SAEV fleets with the urban traffic congestion problem. In this regard, this work presents an integrated framework that tackles the route and charging of SAEV fleets as well as the urban traffic congestion prevention issues. Notably, our contribution in this work not only proposes a joint solution for the problems of the urban traffic congestion control and rideshare dispatch of SAEV fleets, but also fills the gap of the routing and charging strategies for mixed privately owned EVs (PEV) and SAEV fleets in the literature. A general optimization framework is formulated, and effective heuristics are proposed to tackle the above-mentioned problems in this work. The feasibility and effectiveness of the proposed algorithms were evaluated through four different scenarios in the simulation. After applying the proposed algorithms, the traffic volumes of the oversaturated main arterial road were diverted to other less busy road sections, and the traveling times of EV passengers were decreased by 28% during peak periods. The simulation results reveal that the proposed algorithms not only provide a practical solution to prevent the problem in urban traffic congestion during rush hours, but also shorten the travel times of EV passengers effectively.
A Log-Logistic Predictor for Power Generation in Photovoltaic Systems
Authors: Souza Guilherme , Santos Ricardo , Saraiva Erlandson
Published: August 2022

Photovoltaic (PV) systems are dependent on solar irradiation and environmental temperature to achieve their best performance. One of the challenges in the photovoltaic industry is performing maintenance as soon as a system is not working at its full generation capacity. The lack of a proper maintenance schedule affects power generation performance and can also decrease the lifetime of photovoltaic modules. Regarding the impact of environmental variables on the performance of PV systems, research has shown that soiling is the third most common reason for power loss in photovoltaic power plants, after solar irradiance and environmental temperature. This paper proposes a new statistical predictor for forecasting PV power generation by measuring environmental variables and the estimated mass particles (soiling) on the PV system. Our proposal was based on the fit of a nonlinear mixed-effects model, according to a log-logistic function. Two advantages of this approach are that it assumes a nonlinear relationship between the generated power and the environmental conditions (solar irradiance and the presence of suspended particulates) and that random errors may be correlated since the power generation measurements are recorded longitudinally. We evaluated the model using a dataset comprising environmental variables and power samples that were collected from October 2019 to April 2020 in a PV power plant in mid-west Brazil. The fitted model presented a maximum mean squared error (MSE) of 0.0032 and a linear coefficient correlation between the predicted and observed values of 0.9997. The estimated average daily loss due to soiling was 1.4%.
Application of the Analytical Hierarchy Process to Select the Most Appropriate Mining Equipment for the Exploitation of Secondary Deposits
Authors: Patyk Michał , Bodziony Przemysław
Published: August 2022

A methodology is outlined for equipment selection for the extraction of secondary deposits, supported by the Multiple Criteria Decision Making (MCDM) tool based on the Analytic Hierarchy Process (AHP) method and applied to evaluate its impact on the mining system’s performance and the viability of the rock mining project. The equipment selection analysis affords us the means to explore selected options, taking technological and economic parameters into account, and opening the way for making the decision to begin or discontinue mining operations. The simulation results show how maintaining the mining site in a good condition impacts on the actual duty cycle of mining equipment, the time required to complete the hauling task and the operating costs.
Enrichment of the Usage of Solar Purification of Water by Employing Hybrid Nanofluid Mixtures
Authors: Darabee Sonia , Hamdan Mohammad , Daghari Hadi , Ajib Salman
Published: August 2022

In terms of human needs, water has traditionally been regarded as the most significant bioresource. However, there are still limitations on the quality and mobility of drinking water. Renewable energy technologies are at the forefront of research to bridge the gap between conventional fuels and renewable energy systems. Currently, the main objective is to speed up the solar water disinfection process of contaminated water when hybrid nanofluid mixtures are added. Five hybrid nanofluid mixtures containing different amounts of aluminum oxide (Al2O3) and Titanium oxide (TiO2) nanoparticles were used in this study, focusing on how they affected the solar disinfection of polluted water. Five hybrid nanofluid mixtures of different volumes and volume concentrations were used for this purpose; each one was introduced into a contaminated water-contained glass container with a volume of 500 mL. Additionally, a sixth container, used exclusively for comparison, was filled with tainted water. All containers were installed next to each other and exposed to solar radiation for simultaneous measures under identical metrological conditions. During the experimental time, and after exposure to sun radiation for one, two, and three hours, samples were taken from each bottle. to gauge the toll of Total coliforms and E. coli by using the IDEXX setup. It was found that adding a hybrid nanofluid mixture of any composition speeds up the disinfection process. Additionally, it was found that the optimal concentration of the hybrid nanofluid mixture to cut down the Total Coliform was with a volume concentration of 250 mL of Al2O3 and 250 mL of TiO2, while that to cut down the E. coli count was 400 mL of Al2O3 and 100 mL of TiO2. Finally, it may be concluded that among all hybrid mixtures used, the hybrid nanofluid with a volume concentration of 250 mL of Al2O3 and 250 mL of TiO2 is the most efficient in the solar water disinfection process.
Assessment of Selected Factors Influencing the Purchase of Electric Vehicles—A Case Study of the Republic of Croatia
Authors: Mutavdžija Maja , Kovačić Matija , Buntak Krešimir
Published: August 2022

The use of electric vehicles and their adoption have become imperative due to the policies and goals to reduce harmful emissions emitted by fossil fuel vehicles. The adoption and acceptance of electric vehicles by the public may be determined by several factors, such as the price of the vehicles, the environmental and political costs of vehicle production, infrastructure availability, etc. However, given the diverse context of each country, different factors may have a different impact on customer attitudes. According to that fact, the purpose of this research is to identify which factors influence attitudes towards the purchase of electric vehicles in the Republic of Croatia. In order to identify those factors, this paper is based on a survey in which 578 randomly selected respondents took part. The research was conducted between 1 October 2021 and 1 May 2022. The obtained research results were analyzed using linear regression, i.e., moderation analysis. The results indicated that the most significant factors influencing attitudes towards the purchase of electric cars are difficulties in servicing, the cost of battery replacement, lack of charging infrastructure, and the reduced impact on environmental pollution. The basic conclusion of this research is that it is necessary to invest more in the development of infrastructure that supports the use of electric vehicles and in the development of electric vehicles themselves and their characteristics.
Short-Term Hydro-Thermal-Solar Scheduling with CCGT Based on Self-Adaptive Genetic Algorithm
Authors: Postolov Borche , Hinov Nikolay , Iliev Atanas , Dimitrov Dimitar
Published: August 2022

This paper presents a new metaheuristic approach based on a self-adaptive genetic algorithm (SAGA) for solving the short-term hydro-thermal-solar scheduling with combined-cycle (CCGT) units. First of all, the proposed approach is applied to a test system with different characteristics, considering the valve-point effect. The simulation results obtained from the new SAGA are compared with the results obtained from some other metaheuristic methods, such as AIS, DE, and EP to reveal the validity and verify the feasibility of the proposed approach. The test results show that the proposed metaheuristic approach proves the effectiveness and superiority of the SAGA algorithm for solving the short-term hydro-thermal-solar scheduling (SHTSS) problem.
Variable Weighting Coefficient of EMF-Based Enhanced Sliding Mode Observer for Sensorless PMSM Drives
Authors: Cao Fuqiang , An Quntao , Zhang Jianqiu , Zhao Mengji , Li Siwen
Published: August 2022

In the field of permanent magnet synchronous motor (PMSM) control, the sliding mode observer (SMO)-based sensorless control is widely used; however, the actual control input of the current observation function is asymmetric. It can lead to different velocities of the estimated currents approaching to the actual currents and will make the current and back EMF fluctuations more severe, and result in more skewed angle and speed estimates, especially at a lower carrier ratio. In response to the above problems, this paper proposes a variable weighting coefficient of an EMF-based sliding mode observer (VWC-SMO). Unlike the traditional sliding mode observers, the weighted sliding mode switching variables and their bandpass-filtered values are used as the input of the current observer in the VWC-SMO. Thereby, the asymmetry of the control input in the current observation function can be well-suppressed, and almost the same approaching velocity on the two sides of the sliding surface can be obtained. Therefore, chattering near the sliding surface can also be suppressed. The method is verified on a motor controller experimental platform, and the comparative results shows that the VWC-SMO can reduce chattering of the observed currents and mitigate back EMFs fluctuations and improve the dynamic and steady-state performance.