bluuebunny/crossref_metadata_2025 huggingface dataset:
Antimicrobial Susceptibility Profiles and Molecular Characterisation of Staphylococcus aureus from Pigs and Workers at Farms and Abattoirs in Zambia
Authors: Samutela Mulemba Tillika , Phiri Bruno Stephen July , Simulundu Edgar , Kwenda Geoffrey , Moonga Ladslav , Bwalya Eugene C. , Muleya Walter , Nyirahabimana Therese , Yamba Kaunda , Kainga Henson , Kallu Simegnew Adugna , Mwape Innocent , Frey Andrew , Bates Matthew , Higashi Hideaki , Hang'ombe Bernard Mudenda
Published: June 2022

Pigs have been shown to be a reservoir for recently emerging livestock-associated Staphylococcus aureus (LA-SA), including methicillin resistant strains in many countries worldwide. However, there is sparse information about LA-SA strains circulating in Zambia. This study investigated the prevalence, phenotypic and genotypic characteristics of S. aureus from pigs and workers at farms and abattoirs handling pigs in Lusaka Province of Zambia. A total of 492 nasal pig swabs, 53 hand and 53 nasal human swabs were collected from farms and abattoirs in selected districts. Standard microbiological methods were used to isolate and determine antimicrobial susceptibility patterns of S. aureus. Polymerase Chain Reaction was used to confirm the species identity and detect antimicrobial resistance and virulence genes of isolates, whereas genetic diversity was evaluated using spa typing. Overall prevalence of S. aureus was 33.1%, 37.8% for pigs and 11.8% for humans. The isolates were resistant to several antibiotics with resistance ranging from 18% to 98% but were all susceptible to vancomycin. Typical LA-SA spa types were detected. The presence of plasmid mediated resistance genes such as tetM (12.8%), other resistance determinants and immune evasion cluster genes among the isolates is of great public health concern. Thus, continuous surveillance of S. aureus using a “One health” approach is warranted to monitor S.aureus infections and spread of antimicrobial resistance.
Review of Antimicrobial Resistance in Wastewater in Japan: Current Challenges and Future Perspectives
Authors: Baba Hiroaki , Nishiyama Masateru , Watanabe Toru , Kanamori Hajime
Published: June 2022

Antimicrobial resistance (AMR) circulates through humans, animals, and the environments, requiring a One Health approach. Recently, urban sewage has increasingly been suggested as a hotspot for AMR even in high-income countries (HICs), where the water sanitation and hygiene infrastructure are well-developed. To understand the current status of AMR in wastewater in a HIC, we reviewed the epidemiological studies on AMR in the sewage environment in Japan from the published literature. Our review showed that a wide variety of clinically important antibiotic-resistant bacteria (ARB), antibiotic resistance genes (ARGs), and antimicrobial residues are present in human wastewater in Japan. Their concentrations are lower than in low- and middle-income countries (LMICs) and are further reduced by sewage treatment plants (STPs) before discharge. Nevertheless, the remaining ARB and ARGs could be an important source of AMR contamination in river water. Furthermore, hospital effluence may be an important reservoir of clinically important ARB. The high concentration of antimicrobial agents commonly prescribed in Japan may contribute to the selection and dissemination of AMR within wastewater. Our review shows the importance of both monitoring for AMR and antimicrobials in human wastewater and efforts to reduce their contamination load in wastewater.
Antimicrobial-Resistant Enterococcus spp. in Wild Avifauna from Central Italy
Authors: Cagnoli Giulia , Bertelloni Fabrizio , Interrante Paolo , Ceccherelli Renato , Marzoni Margherita , Ebani Valentina Virginia
Published: June 2022

Bacteria of the genus Enterococcus are opportunistic pathogens, part of the normal intestinal microflora of animals, able to acquire and transfer antimicrobial resistance genes. The aim of this study was to evaluate the possible role of wild avifauna as a source of antimicrobial-resistant enterococci. To assess this purpose, 103 Enterococcus spp. strains were isolated from the feces of wild birds of different species; they were tested for antimicrobial resistance against 21 molecules, vancomycin resistance, and high-level aminoglycosides resistance (HLAR). Furthermore, genes responsible for vancomycin, tetracycline, and HLAR were searched. E. faecium was the most frequently detected species (60.20% of isolates), followed by E. faecalis (34.95% of isolates). Overall, 99.02% of the isolated enterococci were classified as multidrug-resistant, with 19.41% extensively drug-resistant, and 2.91% possible pan drug-resistant strains. Most of the isolates were susceptible to amoxicillin/clavulanic acid (77.67%) and ampicillin (75.73%), with only 5.83% of isolates showing an ampicillin MIC ≥ 64 mg/L. HLAR was detected in 35.92% of isolates, mainly associated with the genes ant(6)-Ia and aac(6′)-Ie-aph(2″)-Ia. Few strains (4.85%) were resistant to vancomycin, and the genes vanA and vanB were not detected. A percentage of 54.37% of isolates showed resistance to tetracycline; tet(M) was the most frequently detected gene in these strains. Wild birds may contribute to the spreading of antimicrobial-resistant enterococci, which can affect other animals and humans. Constant monitoring is essential to face up to the evolving antimicrobial resistance issue, and monitoring programs should include wild avifauna, too.
Campylobacter jejuni Biofilm Control with Lavandin Essential Oils and By-Products
Authors: Ramić Dina , Ogrizek Janja , Bucar Franz , Jeršek Barbka , Jeršek Miha , Možina Sonja Smole
Published: June 2022

The food industry is constantly struggling with one of the most prevalent biofilm-forming and food-borne pathogenic bacteria, Campylobacter jejuni. Different approaches are used to control biofilms in the food production chain, but none is fully effective. In this study, we aim to produce and determine the chemical profile of essential oils (EOs), ethanolic extracts of flowers prior to distillation (EFs), and ethanolic extracts of post-distillation waste material (EWMs) from Lavandula × intermedia ‘Bila’, ‘Budrovka’ St Nicholas and ‘Budrovka’, which were further used to reduce C. jejuni intercellular signaling, adhesion, and biofilm formation, as well as to test their antioxidant activity. Glycosides of hydroxycinnamic acids were the major constituents of both types of lavandin ethanolic extract, while linalool, linalyl acetate, 1,8-cineol, and camphor were the major compounds found in lavandin EOs. Tested EOs showed the best antibacterial activity with a minimal inhibitory concentration of 0.25 mg/mL. Lavandin EFs proved more effective in reducing C. jejuni intercellular signaling and adhesion compared to lavandin EOs and EWMs, while lavandin EOs showed a slightly better effect against biofilm formation. Interestingly, the best antioxidant activity was determined for lavandin EWMs. A positive and moderate correlation was found between the reduction of C. jejuni intercellular signaling and adhesion, as well as between adhesion and biofilm formation. These findings mean novel bacterial targets are of interest for biofilm control with alternative natural agents throughout the whole food production chain.
Sex-Related Differences in Oxidative, Platelet, and Vascular Function in Chronic Users of Heat-not-Burn vs. Traditional Combustion Cigarettes
Authors: Schirone Leonardo , Loffredo Lorenzo , Carnevale Roberto , Battaglia Simona , Marti Roberta , Pizzolo Stefano , Bartimoccia Simona , Nocella Cristina , Cammisotto Vittoria , Saade Wael , Tanzilli Alessandra , Sciarretta Sebastiano , Chimenti Isotta , De Falco Elena , Cavarretta Elena , Picchio Vittorio , Peruzzi Mariangela , Marullo Antonino , Miraldi Fabio , Violi Francesco , Morelli Andrea , Biondi-Zoccai Giuseppe , Frati Giacomo
Published: June 2022

Smoking is still a major cardiovascular risk factor, despite many public awareness campaigns and dedicated interventions. Recently, modified risk products (MRP), e.g., heat-not-burn cigarettes (HNBCs), have been introduced as surrogates of traditional combustion cigarettes (TCCs). Although these products are promoted as healthier than TCCs, few studies have been conducted to assess it. This work is a sex-focused sub-study of a prospective observational study in which apparently healthy chronic TCC smokers were age-matched with regular HNBC users. Blood samples were collected for biochemical assays and blood pressure and flow-mediated dilation (FMD) were measured. Out of 60 subjects, 33 (55%) were women, and 27 (45%) men, with 11 (33%) vs. 9 (33%) non-smokers, respectively, 10 (30%) vs. 10 (37%) TCC smokers, and 12 (36%) vs. 8 (30%) HNBC smokers (p = 0.946). Bivariate and multivariable analyses showed no statistically significant between-sex differences in NO, H2O2, sCD40L, sNox2-dp, sP-selectin, platelet aggregation, cotinine or FMD, overall, in non-smokers, in TCC smokers, or in HNBC smokers (all p > 0.05). HNBCs appeared safer than TCCs when focusing on Nox2-dp (p = 0.026) and sP-selectin (p = 0.050) but had similar levels of the other measured markers. In conclusion, HNBCs have similar detrimental effects on women and men’s oxidative stress (H2O2: p = 0.49; sNox2-dp: p = 0.31) and platelet activation (sP-selectin: p = 0.33; platelet aggregation p = 0.87).
Antioxidant Activity Evaluation and Assessment of the Binding Affinity to HSA of a New Catechol Hydrazinyl-Thiazole Derivative
Authors: Mic Mihaela , Pîrnău Adrian , Floare Călin G. , Borlan Raluca , Focsan Monica , Oniga Ovidiu , Bogdan Mircea , Vlase Laurian , Oniga Ilioara , Marc Gabriel
Published: June 2022

Polyphenols have attained pronounced attention due to their ability to provide numerous health benefits and prevent several chronic diseases. In this study, we designed, synthesized and analyzed a water-soluble molecule presenting a good antioxidant activity, namely catechol hydrazinyl-thiazole (CHT). This molecule contains 3′,4′-dihydroxyphenyl and 2-hydrazinyl-4-methyl-thiazole moieties linked through a hydrazone group with very good antioxidant activity in the in vitro evaluations performed. A preliminary validation of the CHT developing hypothesis was performed evaluating in silico the bond dissociation enthalpy (BDE) of the phenol O-H bonds, compared to our previous findings in the compounds previously reported by our group. In this paper, we report the binding mechanism of CHT to human serum albumin (HSA) using biophysical methods in combination with computational studies. ITC experiments reveal that the dominant forces in the binding mechanism are involved in the hydrogen bond or van der Waals interactions and that the binding was an enthalpy-driven process. NMR relaxation measurements were applied to study the CHT–protein interaction by changing the drug concentration in the solution. A molecular docking study added an additional insight to the experimental ITC and NMR analysis regarding the binding conformation of CHT to HSA.
Methodological Optimization of Supercritical Fluid Extraction of Valuable Bioactive Compounds from the Acidophilic Microalga Coccomyxa onubensis
Authors: Ruiz-Domínguez Mari Carmen , Medina Elena , Salinas Francisca , Bugueño Waldo , Fuentes Juan-Luis , Vílchez Carlos , Garbayo Inés , Cerezal-Mezquita Pedro
Published: June 2022

Microalgae grow in diverse environments and possess a great biotechnological potential as they contain useful bioactive compounds. These bioactive compounds can be obtained by selective and energy-efficient extraction methods. Various industries are using the supercritical fluid extraction (SFE) method to extract these valuable bioactive compounds. Hence, for the first time, we evaluated the effects of SFE on the recovery of bioactive and antioxidant compounds using Coccomyxa onubensis, a eukaryotic acidophilic microalga of potential relevance which can be used in the field of nutraceutical and functional foods. It was isolated from the Tinto River (Pyritic Belt, Huelva, Spain), a mining region in Spain. Variables such as extraction yield, lutein purity (LP) and recovery (LR), total phenols, and antioxidant capacity (Trolox equivalents antioxidant capacity method) were studied using a Box–Behnken design based on a response surface methodology along with the overall extraction curve fitted to a spline linear model. The effects of temperature (30, 50, and 70 °C), pressure (25, 40, and 55 MPa), and the percentage of co-solvent (0, 25%, and 50% v/v ethanol) on SFE were analyzed, resulting in the co-solvent and temperature as the most significant factors followed by the pressure. Under 70 °C, 40 MPa, and 50% v/v ethanol, C. onubensis reached a maximum of 66.98% of LR. The extracts were richest in total phenols and showed the maximum antioxidant activity (36.08 mg GAEs/g extracts and 2.237 mmol TE/g extracts, respectively) under similar pressure and co-solvent percentage values and different temperatures (30 and 70 °C, respectively). The extracts obtained in this study may have potential applications in the food, nutraceutical, and cosmetic industries. SFE is a highly efficient method to valorize microorganisms living in extreme environments, which are so far unexplored using green extraction methods.
Comparative Assessment of the Antioxidant and Anticancer Activities of Plicosepalus acacia and Plicosepalus curviflorus: Metabolomic Profiling and In Silico Studies
Authors: Eltamany Enas E. , Goda Marwa S. , Nafie Mohamed S. , Abu-Elsaoud Abdelghafar M. , Hareeri Rawan H. , Aldurdunji Mohammed M. , Elhady Sameh S. , Badr Jihan M. , Eltahawy Nermeen A.
Published: June 2022

This study presents a comparison between two mistletoe plants—P. acacia and P. curviflorus—regarding their total phenolic contents and antioxidant and anticancer activities. P. curviflorus exhibited a higher total phenolics content (340.62 ± 19.46 mg GAE/g extract), and demonstrated higher DPPH free radical scavenging activity (IC50 = 48.28 ± 3.41µg/mL), stronger reducing power (1.43 ± 0.54 mMol Fe+2/g) for ferric ions, and a greater total antioxidant capacity (41.89 ± 3.15 mg GAE/g) compared to P. acacia. The cytotoxic effects of P. acacia and P. curviflorus methanol extracts were examined on lung (A549), prostate (PC-3), ovarian (A2780) and breast (MDA-MB-231) cancer cells. The highest anticancer potential for the two extracts was observed on PC-3 prostate cancer cells, where P. curviflorus exhibited more pronounced antiproliferative activity (IC50 = 25.83 μg/mL) than P. acacia (IC50 = 34.12 μg/mL). In addition, both of the tested extracts arrested the cell cycle at the Pre-G1 and G1 phases, and induced apoptosis. However, P. curviflorus extract possessed the highest apoptotic effect, mediated by the upregulation of p53, Bax, and caspase-3, 8 and 9, and the downregulation of Bcl-2 expression. In the pursuit to link the chemical diversity of P. curviflorus with the exhibited bioactivities, its metabolomic profiling was achieved by the LC-ESI-TOF-MS/MS technique. This permitted the tentative identification of several phenolics—chiefly flavonoid derivatives, beside some triterpenes and sterols—in the P. curviflorus extract. Furthermore, all of the metabolites in P. curviflorus and P. acacia were inspected for their binding modes towards both CDK-2 and EGFR proteins using molecular docking studies in an attempt to understand the superiority of P. curviflorus over P. acacia regarding their antiproliferative effect on PC-3 cancer cells. Docking studies supported our experimental results; with all of this taken together, P. curviflorus could be regarded as a potential prospect for the development of chemotherapeutics for prostate cancer.
The Use of Thiocyanate Formulations to Create Manganese Porphyrin Antioxidants That Supplement Innate Immunity
Authors: Day Brian J. , Min Elysia , Huang Jie , Stanley Chris
Published: June 2022

The innate immune response to infection results in inflammation and oxidative damage, creating a paradox where most anti-inflammatory and antioxidant therapies can further suppress an already inadequate immune response. We have previously reported the beneficial effects of the exogenous supplementation of innate immunity with small pseudohalide thiocyanate (−SCN) in a mouse model of a cystic fibrosis (CF) lung infection and inflammation. The object of this study was to evaluate the use of −SCN as a counter anion for cationic manganese porphyrin (MnP) catalytic antioxidants, which could increase the parent compound’s antioxidant spectrum against hypohalous acids while supplementing innate immunity. The antioxidant activities of the parent compound were examined, as its chloride salt was compared with the −SCN-anion exchanged compound, (MnP(SCN) versus MnP(Cl)). We measured the superoxide dismutase activity spectrophotometrically and performed hydrogen peroxide scavenging using oxygen and hydrogen peroxide electrodes. Peroxidase activity was measured using an amplex red assay. The inhibition of lipid peroxidation was assessed using a thiobarbituric acid reactive species (TBARS) assay. The effects of the MnP compounds on macrophage phagocytosis were assessed by flow cytometry. The abilities of the MnP(Cl) formulations to protect human bronchiolar epithelial cells against hypochlorite (HOCl) and glycine chloramine versus their MnP(SCN) formulations were assessed using a cell viability assay. We found that anions exchanging out the chloride for −SCN improved the cellular bioavailability but did not adversely affect the cell viability or phagocytosis and that they switched hydrogen-peroxide scavenging from a dismutation reaction to a peroxidase reaction. In addition, the −SCN formulations improved the ability of MnPs to protect human bronchiolar epithelial cells against hypochlorous acid (HOCl) and glycine chloramine toxicity. These novel types of antioxidants may be more beneficial in treating lung disease that is associated with chronic infections or acute infectious exacerbations.
In Patients with Chronic Kidney Disease Advanced Glycation End-Products Receptors Isoforms (sRAGE and esRAGE) Are Associated with Malnutrition
Authors: Caldiroli Lara , Molinari Paolo , Dozio Elena , Rigolini Roberta , Giubbilini Paola , Romanelli Massimiliano M. Corsi , Castellano Giuseppe , Vettoretti Simone
Published: June 2022

Background: in patients with chronic kidney disease (CKD), the inflammatory and pro-oxidant milieu may contribute to malnutrition development. In this study, we investigated the relationship between inflammation, advanced glycation end-products (AGEs), and their receptors (RAGEs) with malnutrition in CKD patients. Methods: we evaluated 117 patients. AGEs were quantified by fluorescence intensity using a fluorescence spectrophotometer, soluble RAGEs isoforms, and inflammatory interleukins by ELISA. Malnutrition was assessed by a malnutrition inflammation score. Results: mean age was 80 ± +11 years, eGFR was 25 ± +11 mL/min/1.73 m2 and BMI was 28 ± 5 Kg/m2. Malnourished individuals were older, had lower estimated protein intake (nPCR 0.65 ± 0.2 vs. 0.8 ± 0.2 vs. 0.8 ± 0.3, p = 0.01), higher C reactive protein (CRP 0.6 ± 1 vs. 0.6 ± 0.7 vs. 0.17 ± 0.13, p = 0.02) and tumor necrosis factor α (TNF α 14.7 ± 8.7 vs. 15.6 ± 8 vs. 11.8 ± 5.8, p = 0.029). Malnourished patients had higher sRAGE (2813 ± 1477 vs. 2158 ± 1236 vs. 2314 ± 1115, p = 0.035) and esRAGE (648 [408–1049] vs. 476 [355–680] vs. 545 [380–730] p = 0.033). In the multivariate analysis, only sRAGE maintained its association with malnutrition (p = 0.02) independently of aging and inflammation. Conclusions: in CKD patients, RAGEs isoforms, but not AGEs, are associated with malnutrition, irrespective of systemic inflammation, aging, and renal function.
Rapid-Response Magnetic Enrichment Strategy for Significantly Improving Sensitivity of Multiplex PCR Analysis of Pathogenic Listeria Species
Authors: Xiao Fangbin , Bai Xuekun , Wang Keyu , Sun Yifan , Xu Hengyi
Published: June 2022

Listeria monocytogenes and Listeria ivanovii are important pathogenic Listeria spp. that cause infections in humans and animals. Establishing a rapid and sensitive method for the simultaneous screening of pathogenic Listeria spp. is of great significance for ensuring food safety. Multiplex polymerase chain reaction (mPCR) has been extensively reported to simultaneously detect several pathogens in food with high sensitivity, but a time-consuming pre-enrichment process is necessary. In this study, we report the usage of surface-modified polyethyleneimine-coated positively charged magnetic nanoparticles (PEI-MNPs) for rapid enrichment of pathogenic Listeria spp. through electrostatic interactions. The enrichment process takes only 10 min with high capture efficiency (more than 70%) at a wide pH range and ionic strength. Combined with mPCR analysis, the PEI-MNPs-mPCR strategy can simultaneously, rapidly, and sensitively detect pathogenic Listeria spp. without a time-consuming pre-concentration process. Under the optimal conditions, the detection limits of L. monocytogenes and L. ivanovii in lettuce were both as low as 101 CFU/mL, which was a hundred times lower than that without magnetic enrichment. In conclusion, the magnetic enrichment strategy based on charge interaction combined with mPCR analysis has great application potential in shortening the pre-concentration time of foodborne pathogens and improving the detection sensitivity.
A Latency-Aware Offloading Strategy over Fiber-Wireless (FiWi) Infrastructures for Tactile Internet Services
Authors: Dai Qinglong , Qian Jin , Qin Guangjun , Li Jianwu , Zhao Jun
Published: June 2022

With the emergence of the tactile internet, low-latency, even, real-time data transmission is indispensable for human-agent–robot teamwork. Offloading is considered a feasible approach. Determining the offloading solution according to the dynamic network circumstance is attractive. In this paper, we investigate the resource management issue in a three-tier, heterogeneous, fiber-wireless (FiWi) network with offloading. Based on the model of the wireless link, the fiber link, the data rate, and the offloading, a mixed-integer, non-linear problem is formulated to obtain the minimum total latency for tactile internet services. Through constraint relaxation, MINLP is converted to a linear problem (LP). A Lagrange multiplier method with Karush–Kuhn–Tucker (KKT) conditions is used to solve LP. Using the numerical simulation, the superiority of our work is evaluated and compared with the previous work.
Diagnostic Evaluation of Rheumatoid Arthritis (RA) in Finger Joints Based on the Third-Order Simplified Spherical Harmonics (SP3) Light Propagation Model
Authors: Kim Stephen Hyunkeol , Montejo Ludguier , Hielscher Andreas
Published: June 2022

This work focuses on the evaluation of third-order simplified spherical harmonics (SP3) model-based image reconstruction with respect to its clinical utility to diagnose rheumatoid arthritis (RA). The existing clinical data of 219 fingers was reconstructed for both absorption and scattering maps in fingers by using the reduced-Hessian sequential quadratic programming (rSQP) algorithm that employs the SP3 model of light propagation. The k-fold cross validation method was used for feature extraction and classification of SP3-based tomographic images. The performance of the SP3 model was compared to the DE and ERT models with respect to diagnostic accuracy and computational efficiency. The results presented here show that the SP3 model achieves clinically relevant sensitivity (88%) and specificity (93%) that compare favorably to the ERT while maintaining significant computational advantage over the ERT (i.e., the SP3 model is 100 times faster than the ERT). Furthermore, it is also shown that the SP3 is similar in speed but superior in diagnostic accuracy to the DE. Therefore, it is expected that the method presented here can greatly aid in the early diagnosis of RA with clinically relevant accuracy in near real-time at a clinical setting.
Predictive Distillation Method of Anchor-Free Object Detection Model for Continual Learning
Authors: Gang Sumyung , Chung Daewon , Lee Joonjae
Published: June 2022

Continual learning (CL) is becoming increasingly important, not only for storage space because of the ever-increasing amount of data being generated, but also for associated copyright problems. In this study, we propose ground truth’ (GT’), which is a combination of ground truth (GT) and a prediction of the teacher model that distills the prediction results of the previously trained model, called the teacher model, by applying the knowledge distillation (KD) technique to an anchor-free object detection model. Among all the objects predicted by the teacher model, an object for which the prediction score is higher than the threshold value is distilled into the current trained model, called the student model. To avoid interference with new class learning, the IoU is obtained between every object of the GT and the predicted objects. Through the continual learning scenario, even if the reuse of past data is limited, if new data are sufficient, the proposed model minimizes catastrophic forgetting problems and enables learning for newly added classes. The proposed model was learned in PascalVOC 2007 + 2012 and tested in PascalVOC2007, with better results of 9.6% p mAP and 13.7% p F1i shown in the scenario 19 + 1. The result in scenario 15 + 5 showed better results than the compared algorithm, with 1.6% p mAP and 0.9% p F1i. The scenario 10 + 10 also outperformed the other alternatives, with 0.9% p mAP and 0.6% p F1i.
Reuse or Disposal of Waste Foundry Sand: An Insight into Environmental Aspects
Authors: Cioli Flavio , Abbà Alessandro , Alias Carlotta , Sorlini Sabrina
Published: June 2022

From a circular economy perspective, the recovery and reuse of waste plays a fundamental role. Foundries purchase hundreds of millions of siliceous sands every year to create molds and cores that give shape to the casting. These sands, after several uses, become waste that must be properly recovered or disposed of; they are called waste foundry sands (WFS). The reuse of WFS leads to a reduction in: (i) the consumption of raw materials; (ii) the emissions into the atmosphere; and (iii) the amount of waste sent to landfill—on the other hand, the impact that their use generates on the environment and human health must be carefully assessed. Leaching tests are a fundamental tool for establishing the hazardousness of a waste and its release of contaminants into the environment. This paper presents an analysis of the scientific literature regarding the chemical characteristics of WFS and their release following leaching tests carried out in the laboratory; the environmental standards adopted by the countries that have issued guidelines regarding the reuse of WFS will also be presented.
Centrifugal Model Test Study on the Mechanical Characteristics of Shield Tunnels Influenced by Different Types of Openings for Cross Passages
Authors: Lu Ping , Yuan Dajun , Luo Weiping , Jin Dalong , Liu Minggao
Published: June 2022

To investigate the mechanical characteristics of shield tunnels when openings are made for the construction of cross passages, a series of centrifugal model tests were conducted. The segmental features of the shield tunnel were simulated in the tests, and the influence of different types of openings, namely, rectangular opening, small circular opening, and big circular opening was compared. External earth pressures, structural deformations, dislocations, and structural stresses were monitored during the tests, while the influence of different buried depths was also investigated. The results show that (1) soil arching effect occurred in the overlying soil due to the deformation of the tunnel, and the earth pressure reduction coefficients can guide the tunnel structural design; (2) vertical deformations of the main tunnel and the dislocations between adjacent rings increased with the opening sizes significantly; (3) significant stress concentration occurred close to the openings, and the compressive stress at the inner surface may even exceed the limit strength of the concrete. In summary, the adverse responses of the tunnel increased with the increase of the buried depth and the opening size. Targeted measures should be taken, such as temporary support, longitudinal connections, and high-strength materials near the openings.
Properties on Yttrium-Doped/Undoped Barium Cerate and Barium Zirconate Thin Films Formed by E-Beam Vapor Deposition
Authors: Campos Covarrubias Monica Susana , Sriubas Mantas , Bockute Kristina , Poskaite Aurelija , Vazgys Rokas , Gazda Maria , Laukaitis Giedrius
Published: June 2022

As electrolyte materials for proton conductive fuel cells, perovskite-type materials such as barium cerates and barium zirconates have received a lot of attention due to their high protonic conduction at intermediate temperatures. Yet, the crystalline structure and the microstructure of the electrolyte layers are of the utmost importance that define the resulting protonic conductivity. The aim of this research was to investigate the formation of doped/undoped BCO and BZO thin films using e-beam vapor deposition and to analyze the influence of the formation parameters on the microstructural and crystallographic properties. Crystalline structure and microstructure were investigated by X-ray diffractometer and scanning electron microscope, while the elemental composition of the resulting thin films was analyzed by an energy-dispersive X-ray spectroscope. It was found that the formed thin films were highly dense and consisted of the oriented columnar grains. The crystallinity of the thin films was strongly expressed with the predominant crystallographic orientations for undoped/doped barium cerates. Yttrium dopant had an influence on the lattice parameters and crystallite sizes. With the chosen technological parameters allowed to both, barium cerates and barium zirconates did not form carbonates and did not experience the degradation process.
Predicting Employee Attrition Using Machine Learning Approaches
Authors: Raza Ali , Munir Kashif , Almutairi Mubarak , Younas Faizan , Fareed Mian Muhammad Sadiq
Published: June 2022

Employee attrition refers to the natural reduction in the employees in an organization due to many unavoidable factors. Employee attrition results in a massive loss for an organization. The Society for Human Resource Management (SHRM) determines that USD 4129 is the average cost-per-hire for a new employee. According to recent stats, 57.3% is the attrition rate in the year 2021. A research study needs to be implemented to find the causes of employee attrition and a learning framework to predict employee attrition. This research study aimed to analyze the organizational factors that caused employee attrition and the prediction of employee attrition using machine learning techniques. The four machine learning techniques were applied in comparison. The proposed optimized Extra Trees Classifier (ETC) approach achieved an accuracy score of 93% for employee attrition prediction. The proposed approach outperformed recent state-of-the-art studies. The Employee Exploratory Data Analysis (EEDA) was applied to determine the factors that caused employee attrition. Our study revealed that the monthly income, hourly rate, job level, and age are the key factors that cause employee attrition. Our proposed approach and research findings help organizations overcome employee attrition by improving the factors that cause attrition.
Scene Text Detection Using Attention with Depthwise Separable Convolutions
Authors: Hassan Ehtesham , L. Lekshmi V.
Published: June 2022

In spite of significant research efforts, the existing scene text detection methods fall short of the challenges and requirements posed in real-life applications. In natural scenes, text segments exhibit a wide range of shape complexities, scale, and font property variations, and they appear mostly incidental. Furthermore, the computational requirement of the detector is an important factor for real-time operation. To address the aforementioned issues, the paper presents a novel scene text detector using a deep convolutional network which efficiently detects arbitrary oriented and complex-shaped text segments from natural scenes and predicts quadrilateral bounding boxes around text segments. The proposed network is designed in a U-shape architecture with the careful incorporation of skip connections to capture complex text attributes at multiple scales. For addressing the computational requirement of the input processing, the proposed scene text detector uses the MobileNet model as the backbone that is designed on depthwise separable convolutions. The network design is integrated with text attention blocks to enhance the learning ability of our detector, where the attention blocks are based on efficient channel attention. The network is trained in a multi-objective formulation supported by a novel text-aware non-maximal procedure to generate final text bounding box predictions. On extensive evaluations on ICDAR2013, ICDAR2015, MSRA-TD500, and COCOText datasets, the paper reports detection F-scores of 0.910, 0.879, 0.830, and 0.617, respectively.
Application and Theory of Multimedia Signal Processing Using Machine Learning or Advanced Methods
Authors: Kim Cheonshik
Published: June 2022

Machine learning (ML) uses algorithms to identify and predict useful patterns from data [...]
A Novel Method for Survival Prediction of Hepatocellular Carcinoma Using Feature-Selection Techniques
Authors: Ali Mona A. S. , Orban Rasha , Rajammal Ramasamy Rajalaxmi , Muthusamy Suresh , Subramani Saanthoshkumar , Sekar Kavithra , Rajeena P. P. Fathimathul , Gomaa Ibrahim Abd Elatif , Abulaigh Laith , Elminaam Diaa Salam Abd
Published: June 2022

The World Health Organization (WHO) predicted that 10 million people would have died of cancer by 2020. According to recent studies, liver cancer is the most prevalent cancer worldwide. Hepatocellular carcinoma (HCC) is the leading cause of early-stage liver cancer. However, HCC occurs most frequently in patients with chronic liver conditions (such as cirrhosis). Therefore, it is important to predict liver cancer more explicitly by using machine learning. This study examines the survival prediction of a dataset of HCC based on three strategies. Originally, missing values are estimated using mean, mode, and k-Nearest Neighbor (k-NN). We then compare the different select features using the wrapper and embedded methods. The embedded method employs Least Absolute Shrinkage and Selection Operator (LASSO) and ridge regression in conjunction with Logistic Regression (LR). In the wrapper method, gradient boosting and random forests eliminate features recursively. Classification algorithms for predicting results include k-NN, Random Forest (RF), and Logistic Regression. The experimental results indicate that Recursive Feature Elimination with Gradient Boosting (RFE-GB) produces better results, with a 96.66% accuracy rate and a 95.66% F1-score.
Study on the Determination Method of Cast Blasting Stockpile Forms in an Open-Pit Mine
Authors: Zhang Zhao , Zhang Ruixin , Sun Jiandong , Xu Xiaofeng , Tao Yabin , Lv Shuaikang , Feng Dukang
Published: June 2022

Cast blasting–dragline stripping technology is the most advanced mining technology used in open-pit mines. For a long time, however, its precision has been hindered. In this paper, we aim to improve the precision of cast blasting–dragline stripping technology and promote its intelligent design. We present a method to determine cast blasting stockpile forms. First, the 3D point cloud data for the Heidaigou open-pit mine from recent years were collected and counted, and a 3D mathematical model of overcasting stripping steps was constructed. Then, data classification and multivariate statistical analysis were used to establish a cast blasting stockpile characteristic parameter database. Next, locally weighted linear regression was used as the fitting method to achieve shape fitting under different cast blasting step heights. Finally, interval estimation was used as the fitting result test method to verify the morphology of the acquired cast blasting stockpile form. The research results show that the cast blasting stockpile form obtained by fitting can truly reflect the cast blasting effect of the Heidaigou open-pit mine and ensure the reliability and accuracy of the subsequent design of cast blasting–dragline stripping technology.
Promise for Personalized Diagnosis? Assessing the Precision of Wireless Consumer-Grade Electroencephalography across Mental States
Authors: D’Angiulli Amedeo , Lockman-Dufour Guillaume , Buchanan Derrick Matthew
Published: June 2022

In the last decade there has been significant growth in the interest and application of using EEG (electroencephalography) outside of laboratory as well as in medical and clinical settings, for more ecological and mobile applications. However, for now such applications have mainly included military, educational, cognitive enhancement, and consumer-based games. Given the monetary and ecological advantages, consumer-grade EEG devices such as the Emotiv EPOC have emerged, however consumer-grade devices make certain compromises of data quality in order to become affordable and easy to use. The goal of this study was to investigate the reliability and accuracy of EPOC as compared to a research-grade device, Brainvision. To this end, we collected data from participants using both devices during three distinct cognitive tasks designed to elicit changes in arousal, valence, and cognitive load: namely, Affective Norms for English Words, International Affective Picture System, and the n-Back task. Our design and analytical strategies followed an ideographic person-level approach (electrode-wise analysis of vincentized repeated measures). We aimed to assess how well the Emotiv could differentiate between mental states using an Event-Related Band Power approach and EEG features such as amplitude and power, as compared to Brainvision. The Emotiv device was able to differentiate mental states during these tasks to some degree, however it was generally poorer than Brainvision, with smaller effect sizes. The Emotiv may be used with reasonable reliability and accuracy in ecological settings and in some clinical contexts (for example, for training professionals), however Brainvision or other, equivalent research-grade devices are still recommended for laboratory or medical based applications.
A Software Digital Lock-In Amplifier Method with Automatic Frequency Estimation for Low SNR Multi-Frequency Signal
Authors: Wang Yifan , Cheng Yuhua , Chen Kai , Wang Li , Wang Hongrong
Published: June 2022

In the fault diagnosis field, the fault feature signal is weak and contaminated by the noise. The lock-in amplifier is a useful tool for weak signal detection. Aiming to the amplitude error of the lock-in amplifier caused by frequency deviation between the measured signal and the reference signal, a DFT-based automatic signal frequency estimation method is studied to improve the frequency accuracy of the reference signal. Based on this frequency estimation method, a software digital lock-in amplifier method is proposed to detect the multiple frequencies signals. This proposed method can automatically measure the frequency value of the measured signal without prior frequency information. Then, the reference signals are generated through this frequency value to make the digital lock-in amplifier estimate the amplitude of the measured signal. Moreover, an iterative structure is used to implement the multiple frequencies signal measurement. The frequencies and amplitudes measurement accuracies are tested. Under different SNR conditions, the frequency relative error is less than 0.1%. In addition, the amplitude relative error with different signal frequencies is less than 1.7% when the SNR is −1 dB. This proposed software digital lock-in amplifier method has a higher signal frequency tracking ability and amplitude measurement accuracy.
Performance Prediction of High-Speed Hydrogen Gas-Lubricated Herringbone Grooved Journal Bearing
Authors: Qiang Mingchen , Zhao Qi , Yan Shaohang , Liu Xue , Hou Yu , Lai Tianwei
Published: June 2022

The liquefaction of hydrogen is considered to be a crucial process in the large-scale utilization of hydrogen energy. In hydrogen liquefaction, hydrogen turbo-expander is a key refrigerating machine for high liquefaction efficiency. Performance of the turbo-expander is directly affected by the hydrogen gas bearings. To obtain a deep understanding of the performance characteristics of hydrogen gas bearings, the static and dynamic characteristics of herringbone grooved journal bearings under hydrogen and other lubricating gases were numerically calculated and compared. The bearing load capacity and critical mass of hydrogen gas bearings were slightly lower than those of helium-, air- and nitrogen-lubricated bearings. To improve the performance of the hydrogen gas bearings used in high-speed turbo-machinery, the influence of working conditions was analyzed. It is found that the load capacity of hydrogen gas bearings can be improved by increasing the ambient pressure, reducing the gas film clearance, and raising the bearing eccentricity ratio. Meanwhile, the critical mass increases, and the bearing dynamic stability is enhanced.
Social Network Analysis: Mathematical Models for Understanding Professional Football in Game Critical Moments—An Exploratory Study
Authors: Assunção Diana , Pedrosa Isabel , Mendes Rui , Martins Fernando , Francisco João , Gomes Ricardo , Dias Gonçalo
Published: June 2022

Considering the Social Network Analysis approach and based on the creation of mathematical models, the aim of this study is to analyze the players’ interactions of professional football teams in critical moments of the game. The sample consists in the analysis of a 2019/2020 season UEFA Champions League match. The mathematical models adopted in the analysis of the players (micro analysis) and the game (macro analysis) were obtained through the uPATO software. The results of the networks indicated a performance pattern trend more robust in terms of the mathematical model: Network Density. As far as it concerned, we found that the Centroid Players had a decisive role in the level of connectivity and interaction of the team. Regarding the main critical moments of the game, the results showed that these were preceded by periods of great instability, obtaining a differentiated performance in the following mathematical models: Centrality, Degree Centrality, Closeness Centrality, and Degree Prestige. We concluded that the networks approach, in concomitance with the dynamic properties of mathematical models, and the critical moments of the game, can help coaches to better evaluate the level of interaction and connectivity of their players toward the actions imposed by opponents.
A VPN-Encrypted Traffic Identification Method Based on Ensemble Learning
Authors: Cao Jie , Yuan Xing-Liang , Cui Ying , Fan Jia-Cheng , Chen Chin-Ling
Published: June 2022

One of the foundational and key means of optimizing network service in the field of network security is traffic identification. Various data transmission encryption technologies have been widely employed in recent years. Wrongdoers usually bypass the defense of network security facilities through VPN to carry out network intrusion and malicious attacks. The existing encrypted traffic identification system faces a severe problem as a result of this phenomenon. Previous encrypted traffic identification methods suffer from feature redundancy, data class imbalance, and low identification rate. To address these three problems, this paper proposes a VPN-encrypted traffic identification method based on ensemble learning. Firstly, aiming at the problem of feature redundancy in VPN-encrypted traffic features, a method of selecting encrypted traffic features based on mRMR is proposed; secondly, aiming at the problem of data class imbalance, improving the Xgboost identification model by using the focal loss function for the data class imbalance problem; Finally, in order to improve the identification rate of VPN-encrypted traffic identification methods, an ensemble learning model parameter optimization method based on optimal Bayesian is proposed. Experiments revealed that our proposed VPN-encrypted traffic identification method produced more desirable VPN-encrypted traffic identification outcomes. Meanwhile, using two encrypted traffic datasets, eight common identification algorithms are compared, and the method appears to be more accurate in identifying encrypted traffic.
Influence of Metro Track Irregularities on Pantograph Vibration and Its Interaction with Catenary
Authors: An Bolun , Wang Pu , Ma Shuai , Ma Zhuoran , Zhong Yanglong , Zhao Wenqiang
Published: June 2022

The problem of excessive wear of pantograph strips frequently occurs on China’s Z City Metro Line 1. After on-site investigation and analysis by the metro operating company, it was speculated that the problem was related to abnormal track irregularities. Therefore, taking Z City Metro Line 1 as the main research object, the measured track irregularity of the whole line was analyzed and compared with other typical track spectra, and a track-vehicle-pantograph-catenary coupling dynamics model was established to analyze the relationship between the pantograph-catenary dynamic characteristics and the track irregularity. The two frequency ranges of the track irregularity that have a significant impact on the pantograph-catenary contact were found. Finally, after numerical calculation and analysis, it is recommended to focus on the irregularities with the two wavelength ranges of 9~16 m and 3~4 m in the maintenance.
Conceptual Design of an Extended Reality Exercise Game for the Elderly
Authors: Fu Yu , Hu Yan , Sundstedt Veronica , Forsell Yvonne
Published: June 2022

Facing the increasingly serious ageing problem, IT technology is being applied more and more to alleviate the increasing health demands of the elderly. Virtual reality (VR) games, in particular, have been shown to benefit the physical and mental health of the elderly. However, almost all consumer-level VR games address the general user, not considering the characteristics of the elderly, such as their particular needs regarding cognitive aspects and safety. In addition, the existing VR rowing games’ research typically focuses on athlete training or is based on a rowing machine. Extending on previous research, this paper proposes a conceptual design of a VR rowing game, VRrowing to provide a home exercise game for the elderly which benefits both physical and mental health. This research first analysed the relevant literature and existing VR exercise games for the elderly to find characteristics and their particular needs. Then, following design principles (in exercise games, human–computer interaction, and user interfaces (UIs)) for the elderly, this study proposed a conceptual design of VRrowing through the MDA framework (standing for mechanics, dynamics, and aesthetics). The results cover the system architecture, activities and tasks, patterns and roles, mechanics and structures, and UI examples. Based on comprehensive consideration of the results from relevant research and fostering strengths and circumventing weaknesses, VRrowing was designed as a sports game, aimed at the elderly according to their characteristics and needs, which fills the void of home VR rowing games for seniors’ exercise. This research has reference value for scientific research or development personnel in VR game applications and evaluations, especially for such games targeting the elderly.