bluuebunny/crossref_metadata_2025 huggingface dataset:
Co-Infections, Secondary Infections, and Antimicrobial Use in Patients Hospitalized with COVID-19 during the First Five Waves of the Pandemic in Pakistan; Findings and Implications
Authors: Ramzan Kiran , Shafiq Sameen , Raees Iqra , Mustafa Zia Ul , Salman Muhammad , Khan Amer Hayat , Meyer Johanna C. , Godman Brian
Published: June 2022

Background: COVID-19 patients are typically prescribed antibiotics empirically despite concerns. There is a need to evaluate antibiotic use among hospitalized COVID-19 patients during successive pandemic waves in Pakistan alongside co-infection rates. Methods: A retrospective review of patient records among five tertiary care hospitals during successive waves was conducted. Data were collected from confirmed COVID-19 patients during the first five waves. Results: 3221 patients were included. The majority were male (51.53%), residents from urban areas (56.35%) and aged >50 years (52.06%). Cough, fever and a sore throat were the clinical symptoms in 20.39%, 12.97% and 9.50% of patients, respectively. A total of 23.62% of COVID-19 patients presented with typically mild disease and 45.48% presented with moderate disease. A high prevalence of antibiotic prescribing (89.69%), averaging 1.66 antibiotics per patient despite there only being 1.14% bacterial co-infections and 3.14% secondary infections, was found. Antibiotic use significantly increased with increasing severity, elevated WBCs and CRP levels, a need for oxygen and admittance to the ICU; however, this decreased significantly after the second wave (p < 0.001). Commonly prescribed antibiotics were piperacillin plus an enzyme inhibitor (20.66%), azithromycin (17.37%) and meropenem (15.45%). Common pathogens were Staphylococcus aureus (24.19%) and Streptococcus pneumoniae (20.96%). The majority of the prescribed antibiotics (93.35%) were from the WHO’s “Watch” category. Conclusions: Excessive prescribing of antibiotics is still occurring among COVID-19 patients in Pakistan; however, rates are reducing. Urgent measures are needed for further reductions.
Anthocyanins and Carotenoids Characterization in Flowers and Leaves of Cyclamen Genotypes Linked with Bioactivities Using Multivariate Analysis Techniques
Authors: Cornea-Cipcigan Mihaiela , Bunea Andrea , Bouari Cosmina Maria , Pamfil Doru , Páll Emőke , Urcan Adriana Cristina , Mărgăoan Rodica
Published: June 2022

The present study was carried out to evaluate and compare in vitro antioxidant (2,2-diphenyl-1-picrylhydrazyl (DPPH), Trolox equivalent antioxidant capacity (TEAC), and ferric reducing antioxidant power (FRAP)), antimicrobial, anticancer activities, and the individual carotenoids and anthocyanins content of methanol extracts of the Cyclamen genotypes: Persian cyclamen accessions (Cyclamen persicum Mill.), sowbread (C. mirabile Hildebr.), and ivy-leaved cyclamen (C. hederifolium Mill.) aerial parts. The HPLC-PDA analysis revealed the presence of five individual carotenoids (i.e., neoxanthin, violaxanthin, lutein, β-carotene, and cis-β-carotene) as the main compounds in Cyclamen leaves, and the presence of seven individual anthocycanins (i.e., cyanidin 3,5-di-O-glucoside, peonidin-rutinoside, peonidin 3,5-di-O-glucoside, peonidin 3-O-glucoside, malvidin 3-O-glucoside, malvidin 3,5-di-O-glucoside, and malvidin-rutinoside) in Cyclamen flowers reported, hereby, for the first time. The highest phenolic content was found in the leaves of LC6, C. mirabile (46.32 ± 0.14 mg/g gallic acid equivalents [GAE]), and in the flowers of C. persicum Merengue Magenta (FC15) (58.63 ± 0.17 mg/g GAE), whereas the highest flavonoid content was reported in C. persicum Halios Falbala leaves, namely LC9 (54.90 ± 0.27 mg/g quercetin equivalents [QE]) and in flowers of C. persicum Victora (FC2) (77.87 ± 0.25 mg/g QE). The highest antioxidant activity in DPPH and FRAP assays was reported in C. persicum Dark Violet (LC1) and Victoria (LC2), whereas C. mirabile (LC6) had the highest activity in the TEAC assay. In flowers, high antioxidant activities in DPPH and TEAC were noticed in C. persicum Superserie Red (FC7) and Dark Violet (FC1), respectively, and Halios Falbala (FC9) exhibited the highest activity in the TEAC assay. Additionally, FC9 exhibited the highest antibacterial activity in almost all tested bacteria compared with the leaves extracts. Furthermore, the highest in vitro citotoxicity in MDA-MB-231 cells was noticed in C. hederifolium LC18 (56.71–69.35%) and FC18 (40.07–41.43%), with a lower effect against BJ cells demonstrating selective toxicity. The above findings, highlight the potential use of the Cyclamen flower and leaf extracts as significant anticancer agents along with their antioxidant and antimicrobial properties.
Lung’s Segmentation Using Context-Aware Regressive Conditional GAN
Authors: Khan Zakir , Umar Arif Iqbal , Shirazi Syed Hamad , Rasheed Assad , Yousaf Waqas , Assam Muhammad , Hassan Izaz , Mohamed Abdullah
Published: June 2022

After declaring COVID-19 pneumonia as a pandemic, researchers promptly advanced to seek solutions for patients fighting this fatal disease. Computed tomography (CT) scans offer valuable insight into how COVID-19 infection affects the lungs. Analysis of CT scans is very significant, especially when physicians are striving for quick solutions. This study successfully segmented lung infection due to COVID-19 and provided a physician with a quantitative analysis of the condition. COVID-19 lesions often occur near and over parenchyma walls, which are denser and exhibit lower contrast than the tissues outside the parenchyma. We applied Adoptive Wallis and Gaussian filter alternatively to regulate the outlining of the lungs and lesions near the parenchyma. We proposed a context-aware conditional generative adversarial network (CGAN) with gradient penalty and spectral normalization for automatic segmentation of lungs and lesion segmentation. The proposed CGAN implements higher-order statistics when compared to traditional deep-learning models. The proposed CGAN produced promising results for lung segmentation. Similarly, CGAN has shown outstanding results for COVID-19 lesions segmentation with an accuracy of 99.91%, DSC of 92.91%, and AJC of 92.91%. Moreover, we achieved an accuracy of 99.87%, DSC of 96.77%, and AJC of 95.59% for lung segmentation. Additionally, the suggested network attained a sensitivity of 100%, 81.02%, 76.45%, and 99.01%, respectively, for critical, severe, moderate, and mild infection severity levels. The proposed model outperformed state-of-the-art techniques for the COVID-19 segmentation and detection cases.
Heavy Metals in Sediments and Greater Flamingo Tissues from a Protected Saline Wetland in Central Spain
Authors: Valiente Nicolas , Pangerl Alexander , Gómez-Alday Juan José , Jirsa Franz
Published: June 2022

Aquatic ecosystems often act as sinks for agricultural, industrial, and urban wastes. Among potential pollutants, heavy metals can modify major biogeochemical cycles by affecting microorganisms and other biota. This study assessed the distribution and concentration of heavy metals (Cd, Hg, Cu, Pb, and Zn) in Pétrola Lake, a heavily impacted area in central Spain where the greater flamingo Phoenicopterus roseus breeds. This study was designed to determine the concentration and identify the potential sources of heavy metals in Pétrola Lake protected area, including sediments, agricultural soils, and tissues of the greater flamingo. A six-step sequential extraction was performed to fractionate Cu, Pb, and Zn from lake sediments and agricultural soil samples to gain insight into different levels of their bioavailability. Our results showed that Pb and Cd accumulated in lake sediments and agricultural soils, respectively, most likely derived from anthropogenic sources. Multivariate analysis revealed differences between these (Pb and Cd) and the remaining studied elements (Cu, Hg, and Zn), whose concentrations were all below the pollution threshold. Lead pollution in sediments was apparently dominated by organic matter binding, with fractions up to 34.6% in lake sediments. Cadmium slightly accumulated in agricultural soils, possibly associated with the use of fertilizers, but still below the pollution thresholds. In the flamingo samples, low bioaccumulation was observed for all the studied elements. Our study suggests that human activities have an impact on heavy metal accumulation in sediments and soils, despite being below the pollution levels.
Pulsed Electric Fields for Valorization of Platelets with No Therapeutic Value towards a High Biomedical Potential Product—A Proof of Concept
Authors: Salvador Daniela , Almeida Henrique , Rego Duarte , Mendonça Pedro , Sousa Ana Paula , Serra Margarida , Redondo Luis
Published: June 2022

Nowadays, the standard media used in clinical-scale mesenchymal stem cell (MSC) production to supply hundreds of clinical trials uses animal-derived components as supplements, which raises several health concerns. Consequently, the development of xeno-free media supplements has emerged. In the current study, the effect of pulse electric field (PEF) application to platelet concentrates (PC) with no therapeutic value for producing platelet releasates (PR) able to sustain the ability of bone marrow-MSCs (BM-MSCs) to self-renew and differentiate was tested. It was demonstrated that PEF application to PC induces platelet activation and growth factor (GF) release, namely PDGF, FGF, IGF, and TGF-β. The highest GF release was observed for TGF-β, achieving similar levels to those attained in platelet lysates (PL). BM-MSCs expanded in the presence of PR obtained by the application of PEF (7 pulses of 10 and 12.5 kV/cm) to PC (PR PEF) retained the characteristic MSC cell-surface markers, and the ability to proliferate and differentiate into osteogenic, adipogenic, and chondrogenic lineages. In this study, evidence is provided that PR PEF represents a suitable alternative to fetal bovine serum (FBS) for use in MSC production.
Experimental Research on In Situ Uniaxial Tensile Response of Silica-Based PLC Optical Splitters
Authors: Zheng Yu , Jiang Lianqiong , Cheng Jie , Liu Jianzhe , Duan Ji’an
Published: June 2022

In this study, the mechanical and optical properties of silica-based planar lightwave circuit (PLC) optical splitters under uniaxial tensile loading are studied by building an in situ experimental test platform. The tensile test results revealed that the adhesively-bonded fiber array-PLC chip joints are weak areas of the PLC optical splitter. Combined with the real-time monitoring of the optical performance index insertion loss (IL) during the tensile test, it was found that the changing trend of ΔIL-time curves is related to the deformation, damage, and debonding process of the weak area. Based on the experimental results and phenomena, the correspondence between ΔIL at 1.55 μm wavelength and the damage degree of PLC optical splitters is established, that is, ΔIL in (−5 dB; 0 dB], (−15 dB; −5 dB], and (−∞, −15 dB] belong to light damage, moderate damage, and severe damage, respectively. This research can provide a useful reference for damage characteristics analysis and reliability design of PLC optical splitters.
Natural Sources, Pharmacological Properties, and Health Benefits of Daucosterol: Versatility of Actions
Authors: El Omari Nasreddine , Jaouadi Imane , Lahyaoui Manal , Benali Taoufiq , Taha Douae , Bakrim Saad , El Menyiy Naoual , El Kamari Fatima , Zengin Gökhan , Bangar Sneh Punia , Lorenzo José M. , Gallo Monica , Montesano Domenico , Bouyahya Abdelhakim
Published: June 2022

Daucosterol is a saponin present in various natural sources, including medicinal plant families. This secondary metabolite is produced at different contents depending on species, extraction techniques, and plant parts used. Currently, daucosterol has been tested and explored for its various biological activities. The results reveal potential pharmacological properties such as antioxidant, antidiabetic, hypolipidemic, anti-inflammatory, immunomodulatory, neuroprotective, and anticancer. Indeed, daucosterol possesses important anticancer effects in many signaling pathways, such as an increase in pro-apoptotic proteins Bax and Bcl2, a decrease in the Bcl-2/Bax ratio, upregulation of the phosphatase and tensin homolog (PTEN) gene, inhibition of the PI3K/Akt pathway, and distortion of cell-cycle progression and tumor cell evolution. Its neuroprotective effect is via decreased caspase-3 activation in neurons and during simulated reperfusion (OGD/R), increased IGF1 protein expression (decreasing the downregulation of p-AKT3 and p-GSK-3b4), and activation of the AKT5 signaling pathway. At the same time, daucosterol inhibits key glucose metabolism enzymes to keep blood sugar levels within normal ranges. Therefore, this review describes the principal research on the pharmacological activities of daucosterol and the mechanisms of action underlying some of these effects. Moreover, further investigation of pharmacodynamics, pharmacokinetics, and toxicology are suggested.
The Effect of Pre-Treatment of Arabica Coffee Beans with Cold Atmospheric Plasma, Microwave Radiation, Slow and Fast Freezing on Antioxidant Activity of Aqueous Coffee Extract
Authors: Tarasov Aleksey , Bochkova Anastasia , Muzyukin Ilya , Chugunova Olga , Stozhko Natalia
Published: June 2022

Thermal and non-thermal technologies used in food processing should be not only effective in terms of decontamination and preservation but also minimize undesirable losses of natural bioactive compounds. Arabica (Coffea arabica) is the most cultivated variety of coffee, making it a valuable source of phytonutrients, including antioxidants. In the present study, green and roasted Arabica coffee beans were treated with slow freezing (SF), fast freezing (FF), microwave radiation (MWR) and cold atmospheric plasma (CAP). Moisture content (MC) of coffee beans and antioxidant activity (AOA) of aqueous extracts were measured. Green coffee showed a decrease in MC after MWR treatment, and roasted coffee showed an increase in MC after freezing. After SF and FF at −19 °C for 24 h, all extract samples showed an increase in AOA by 4.1–17.2%. MWR treatment at 800 W for 60 s was accompanied by an increase in the AOA of green coffee extracts by 5.7%, while the changes in the AOA of roasted coffee extracts were insignificant. Sequential combined treatments of SF + MWR and FF + MWR resulted in an additive/synergistic increase in the AOA of green/roasted coffee extracts, up to +23.0%. After CAP treatment with dielectric barrier discharge (DBD) parameters of 1 μs, 15 kV and 200 Hz for 5 and 15 min, green coffee showed a decrease in the extract AOA by 3.8% and 9.7%, respectively, while the changes in the AOA of roasted coffee extracts were insignificant. A high positive correlation (r = 0.89, p < 0.001) between AOA and MC was revealed. The results obtained indicate that SF, FF, MWR and combined treatments may be applied at the pre-extraction stage of coffee bean preparation in order to increase the yield of antioxidant extractives.
Multimodal Classification of Safety-Report Observations
Authors: Paraskevopoulos Georgios , Pistofidis Petros , Banoutsos Georgios , Georgiou Efthymios , Katsouros Vassilis
Published: June 2022

Modern businesses are obligated to conform to regulations to prevent physical injuries and ill health for anyone present on a site under their responsibility, such as customers, employees and visitors. Safety officers (SOs) are engineers, who perform site audits to businesses, record observations regarding possible safety issues and make appropriate recommendations. In this work, we develop a multimodal machine-learning architecture for the analysis and categorization of safety observations, given textual descriptions and images taken from the location sites. For this, we utilize a new multimodal dataset, Safety4All, which contains 5344 safety-related observations created by 86 SOs in 486 sites. An observation consists of a short issue description, written by the SOs, accompanied with images where the issue is shown, relevant metadata and a priority score. Our proposed architecture is based on the joint fine tuning of large pretrained language and image neural network models. Specifically, we propose the use of a joint task and contrastive loss, which aligns the text and vision representations in a joint multimodal space. The contrastive loss ensures that inter-modality representation distances are maintained, so that vision and language representations for similar samples are close in the shared multimodal space. We evaluate the proposed model on three tasks, namely, priority classification of input observations, observation assessment and observation categorization. Our experiments show that inspection scene images and textual descriptions provide complementary information, signifying the importance of both modalities. Furthermore, the use of the joint contrastive loss produces strong multimodal representations and outperforms a baseline simple model in tasks fusion. In addition, we train and release a large transformer-based language model for the Greek language based on the Electra architecture.
Flexural Strength and Stiffness of Donut-Type Voided Slab
Authors: Chung Joo-Hong , Jung Hyung-Suk , Choi Hyun-Ki
Published: June 2022

The voided slab system has been known as an effective technique to replace a heavy reinforced concrete slab system without the decrease in flexural strength. However, according to the previous studies, the flexural capacities such as flexural strength, stiffness and ductility of the voided slabs were practically lower than that of the solid slabs depending on the void shapes and details. Therefore, in this study, an analytical and experimental study were conducted to derive the optimal void shape and details focused on the flexural capacities of voided slabs. Based on a finite element (FE) analysis, a donut-type void shaper, which was a hexahedron with rounded edges and a hole penetrating the center, was suggested as the optimal shape in voided slabs, and an experimental study was conducted to verify flexural capacities of the donut-type voided slab. The flexural strength, stiffness and deflection of the donut-type voided slab were investigated by void shape and fixing method of void shaper as variables. The ductility of voided slab was also evaluated, because ductility is as important as strength for the safe design of slab member. The test results showed that the flexural strength of the donut-type voided slabs was equivalent to 98% and 105% that of the solid RC specimen, and the donut-type voided slab specimens had enough ductility for the flexural member. The stiffness of the donut-type voided slab was decreased about 8~9% compared with the solid slab, but it was improved up to 7% compared to the non-donut-type voided slab. Based on test results, the flexural design method of the donut-type voided slab associated with the void shape and fixing device of void shaper was suggested, and it was confirmed that the donut-type voided slab is one of the efficient alternatives to replace heavy flat plate slabs.
Exploration of the Relationship between Planning Research Investment and National Macro Development—An Empirical Study Based on Papers since 1950
Authors: Wu Zhiqiang , Li Xiang
Published: June 2022

The world is accelerating globalization and urbanization; thus, planning plays an irreplaceable role in the macro development, especially in sustainable development. Planning research is important in turning theories of planning into urban practices. This research based on the theory that planning research is crucial, as it represents that planning-related activities improve processes in urbanization. However, the current understanding of the importance of planning research is limited. There is no research on the interaction between planning research and macro national development to support the importance of planning or its research. This study uses 750,000 articles on urban planning fields from WoS from 1950 to the present. Firstly, the study concludes the investment pattern changes of the global planning research. Over the past 70 years, the total number and diversity of countries engaged in planning research have grown rapidly, and developing countries have gradually integrated into the mainstream research community and become the main contributors. Secondly, the investment intensity and characteristics of planning research are consistent with the speed and characteristics of urbanization, which proves that to some extent, the demand of urbanization development drives the investment of planning research. Then, according to the different characteristics of planning research investment in different countries, this paper summarizes the main investment characteristics of major countries, analyzes the development rule behind the investment characteristics, and predicts the interaction with the international political and economic pattern. By analyzing the relationship between planning research intensity and urbanization, it is found that the investment intensity of planning research has a time rule with urbanization and has different interactions in different stages of urbanization development. It was found that the intensity of planning research was strongly correlated with HDI, and the amount of research was crucial.
Impact of Physiotherapy on Patients Suffering from COVID-19: An Observational Study
Authors: Onu Ilie , Iordan Daniel-Andrei , Matei Daniela , Hrisca-Eva Oana-Diana , Buculei Ioana , Galaction Anca-Irina , Serban Ionela Lăcrămioara , Dobrin Mona-Elisabeta , Popa-Velea Ovidiu , Costin Dan Eugen , Mocanu George Dănuț , Dobre Andreea-Georgiana , Gherghel Robert
Published: June 2022

Introduction: COVID-19 was the turning point of 2020, endangering the health of the entire population around the world. Among other therapeutic methods and supportive measures, physiotherapy represents a useful intervention applied on COVID-19 patients suffering from respiratory symptoms, this being supported by recent literature data. Materials and Methods: The study was performed on 45 patients diagnosed with COVID-19 (28 men, 17 women, mean age = 65.03, standard deviation = 14.83). They participated for 2 weeks (the required period of hospitalization) to a series of 14 physiotherapy sessions, which included: position changing, respiratory control, passive joint movements, bed workout, and walking exercises. Depending on the status of the patient, two distinct types of physiotherapy were performed (mild and active). The status of the patients was assessed through a basic assessment of the vital signs, range of motion, degree of dyspnea, and also through the UZ Leuven Start To Move protocol (STMP). The statistical analysis of the data was performed using the Statistica 10 program and included the Spearman correlations (for measuring the strength and direction of association between the ranked variables), the Mann-Whitney test (for measuring the significance of the differences between the groups of patients who undergone light vs. active physiotherapy) and factor analysis (for assessing the changes of the clinical parameters investigated in the study, depending on the type of applied therapy). All differences were considered significant at p < 0.05. Results: The majority of patients (n = 38) benefited from physiotherapy, with the complete disappearance of symptoms met only in the group of patients who followed active physiotherapy. These effects depended on the applied type of physiotherapy (mild vs. active, p = 0.47). In contrast, all patients who were unable to perform physiotherapy (n = 7) remained symptomatic at discharge. Conclusion: The results of this study point out the significant additional role of physiotherapy for a better management of COVID-19 patients. More studies are needed to investigate not only the impact that physiotherapy has on the symptoms of this disease, but also its effects on effort capacity, muscle strength and lung capacity.
RegioRail—GNSS Train-Positioning System for Automatic Indications of Crisis Traffic Situations on Regional Rail Lines
Authors: Fikejz Jan , Kavička Antonín
Published: June 2022

The identification of the position of rail vehicles plays a crucial role in the control of rail traffic. Available, up-to-date information on the position of vehicles allows us to efficiently deal with selected traffic situations where the position of vehicles is very important. The main objective of this article is to introduce (i) a concept of a solution for identification of the current position of rail vehicles based on the worldwide-recognized system of the GNSS with the use of an original railway network data model, and (ii) the use of this concept as supplementary support for the dispatcher control of rail traffic on regional lines. The solution was based on an original, multilayer rail network data model supporting (i) the identification of rail vehicle position and (ii) novel algorithms evaluating the mutual positions of several trains while detecting the selected crisis situation. In addition, original algorithms that enable automatic network model-building (on the database server level) directly from the official railway infrastructure database were developed. The verification of the proposed solutions (using rail traffic simulations) was focused on the evaluation of (i) the changing mutual positions (distances) of trains on the railway network, (ii) the detection of nonstandard or crisis traffic situations, and (iii) the results of the calculations of necessary braking distances of trains for stopping and collision avoidance. The above verification demonstrated the good applicability of the proposed solutions for the potential deployment within supplementary software support for real traffic control. The described concept of the supplementary support determined for railway traffic control (using the localization of trains by means of the GNSS) is intended mainly for regional, single-rail lines. This type of line is very often not sufficiently equipped with standard signaling and interlocking equipment to ensure the necessary traffic safety. Therefore, when deploying this support, the new algorithms for the automatic detection of critical traffic situations represent a significant potential contribution to increasing operational safety.
Wheel Arrangement of Four Omni Wheel Mobile Robot for Compactness
Authors: Hijikata Masaaki , Miyagusuku Renato , Ozaki Koichi
Published: June 2022

Compact omnidirectional mobile robots are required to automate transportation of raw materials, products, etc. within an industrial plant. This paper focuses on omni wheel robots with low vibration and wheel arrangements that contribute to compactness. Due to its wheels’ configuration, our proposed compact robot may have different sensitivity to noise (controller) and different performance (errors) when following a predetermined path, compared to conventional ones. Using a simple DC motor, a robot with the proposed arrangement and a conventional robot run along a predetermined path. A linear–quadratic regulator that is processed lightly is used to control the robots for practicality. As a result, the robot’s trajectory in the proposed arrangement showed a distortion different from that of the conventional type. The distortion of the trajectory was attributed to the inability of the DC motor to rotate stably at low speed. The different distortions exhibited suggest that the wheel arrangement changes the effect of imperfect control on the robot’s motion. In addition, the proposed arrangement showed the possibility of being suitable for a transport robot because the wheels are placed in the four corners of the robot, facing forward, backward, left, and right.
Optimization of Microalgae–Bacteria Consortium in the Treatment of Paper Pulp Wastewater
Authors: Sátiro Josivaldo , Cunha André , Gomes Ana P. , Simões Rogério , Albuquerque Antonio
Published: June 2022

The microalgae–bacteria consortium is a promising and sustainable alternative for industrial wastewater treatment, since it may allow good removal of organic matter and nutrients, as well as the possibility of producing products with added value from the algae biomass. This research investigated the best bacterial and microalgae inoculation ratio for system start-up and evaluation of removing organic matter (as chemical oxygen demand (COD)), ammoniacal nitrogen (NH4+–N), nitrite nitrogen (NO2−–N), nitrate nitrogen (NO3−–N), phosphate phosphorus (PO43−–P) and biomass formation parameters in six photobioreactors with a total volume of 1000 mL. Reactors were operated for 14 days with the following ratios of pulp mill biomass aerobic (BA) and Scenedesmus sp. microalgae (MA): 0:1 (PBR1), 1:0 (PBR2), 1:1 (PBR3), 3:1 (PBR4), 5:1 (PBR5), and 1:3 (PBR6). Results show that COD removal was observed in just two days of operation in PBR4, PBR5, and PBR6, whereas for the other reactors (with a lower rate of initial inoculation) it took five days. The PBR5 and PBR6 performed better in terms of NH4+–N removal, with 86.81% and 77.11%, respectively, which can be attributed to assimilation by microalgae and nitrification by bacteria. PBR6, with the highest concentration of microalgae, had the higher PO43−–P removal (86%), showing the advantage of algae in consortium with bacteria for phosphorus uptake. PBR4 and PBR5, with the highest BA, led to a better biomass production and sedimentability on the second day of operation, with flocculation efficiencies values over 90%. Regarding the formation of extracellular polymeric substances (EPS), protein production was substantially higher in PBR4 and PBR5, with more BA, with average concentrations of 49.90 mg/L and 49.05 mg/L, respectively. The presence of cyanobacteria and Chlorophyceae was identified in all reactors except PBR1 (only MA), which may indicate a good formation and structuring of the microalgae–bacteria consortium. Scanning electron microscopy (SEM) analysis revealed that filamentous microalgae were employed as a foundation for the fixation of bacteria and other algae colonies.
Surface Modification of Materials by Atmospheric-Pressure Plasma to Improve Impregnation with Essential Oils for the Control of Tropilaelaps Mites in Honeybees (Apis mellifera)
Authors: Boonmee Thummanoon , Wongthaveethong Laedlugkana , Sinpoo Chainarong , Disayathanoowat Terd , Pettis Jeffery S. , Chaimanee Veeranan
Published: June 2022

In this research, the absorption and release rate of the essential oil, Amomum krervanh, by seven different materials were evaluated. Cardboard showed the highest EO absorption capacity (0.93 ± 0.0052 μL of oil/mg of dry cardboard) followed by balsa wood and drawing board with the EO absorption of 0.77 ± 0.043 and 0.62 ± 0.010 μL of oil/mg of dry material, respectively. The results also demonstrated that cardboard had the highest EO retention (52.84 ± 0.687% after 20 min of analysis). Additionally, the essential oil was released from the drawing board and cardboard at the same rate during the observation period. Surface modification of drawing board and cardboard was performed using atmospheric-pressure plasma for enhancing the material properties for Tropilaelaps control. The absorption capacity of cardboard was decreased after plasma treatment at an argon flow rate of 0.25 and 0.5 Lpm for 60 s/cm2. However, the atmospheric-pressure plasma did not change the EO release property of these materials. Scanning electron microscopy analyses indicated a fractured and scaly surface after plasma treatment of gas flow rate at 0.5 Lpm and 1.0 Lpm for 30 s/cm2. The surface chemical composition of materials was not altered following plasma treatment. Although the number of mite-infested brood cells did not differ significantly between treatment groups at the end of the field experiment, Tropilaelaps spp. populations in the plasma-treated cardboard impregnated with EO 5% (v/v) treatment were lower on days 7–14 of the experiment. Thus, parameters related to the atmospheric-pressure plasma should be further optimized to improve the material surfaces for use with essential oils to control honeybee mites.
Assessment of Termination Criteria at Each Drought Response Stage on Climate Change in a Multi-Purpose Dam
Authors: Kim Jungmin , Park Jinhyeog , Kwon Heongak
Published: June 2022

In this study, the termination criteria at each drought response stage were shown to increase storage volume while maintaining the stability of the water supply service during drought in multi-purpose dams. For 52 of the Representative Concentration Pathway (RCP) 4.5/8.5 scenarios of the IPCC (Intergovernmental Panel on Climate Change) fifth assessment report (AR5), dam inflows were calculated through the precipitation-runoff modeling system (PRMS), and time reliability and supply reliability were estimated. Moreover, given the application of termination criteria at each drought response stage, the volume of additional water supply was calculated, while the number of days for additional supply availability of water for residential and industrial use and water for residential, industrial, and agricultural use and river maintenance was quantified as well. The CMCC-CMS(RCP4.5) GCM exhibited the largest volume of additional water supply at 74.15 million m3, which corresponds to 52.0 days of water for residential and industrial use and to 47.7 days of water for residential, industrial, and agricultural use and river maintenance. The analysis revealed that the volume and the number of days of additional water supply also increased for other GCMs due to the application of termination criteria at each drought response stage.
Modular Spiral Heat Exchanger Thermal Modelling
Authors: Červenka Bystrík , Holubčík Michal , Drga Juraj , Malcho Milan
Published: June 2022

Spiral plate heat exchangers (SPHEs) are used in industrial applications due to their enhanced thermal performance and tolerance to a soiled stream. The coupling of several SPHEs in series might further improve performance in terms of the effectiveness parameter. In the present study, a compact connection of several SPHE modules is proposed and investigated. For this purpose, a numerical model for the prediction of the effectiveness parameter of a modular SPHE was developed. The model predicted a 2.9% increase in the maximal effectiveness for a two-module SPHE in comparison to a conventional single module SPHE. The temperature profiles of particular streams within the two-module SPHE were predicted. The improved thermal performance and compactness of the modular SPHE configuration observed is advantageous for space-constrained applications.
Multi-Classification of Motor Imagery EEG Signals Using Bayesian Optimization-Based Average Ensemble Approach
Authors: Kamhi Souha , Zhang Shuai , Ait Amou Mohamed , Mouhafid Mohamed , Javaid Imran , Ahmad Isah Salim , Abd El Kader Isselmou , Kulsum Ummay
Published: June 2022

Motor Imagery (MI) classification using electroencephalography (EEG) has been extensively applied in healthcare scenarios for rehabilitation aims. EEG signal decoding is a difficult process due to its complexity and poor signal-to-noise ratio. Convolutional neural networks (CNN) have demonstrated their ability to extract time–space characteristics from EEG signals for better classification results. However, to discover dynamic correlations in these signals, CNN models must be improved. Hyperparameter choice strongly affects the robustness of CNNs. It is still challenging since the manual tuning performed by domain experts lacks the high performance needed for real-life applications. To overcome these limitations, we presented a fusion of three optimum CNN models using the Average Ensemble strategy, a method that is utilized for the first time for MI movement classification. Moreover, we adopted the Bayesian Optimization (BO) algorithm to reach the optimal hyperparameters’ values. The experimental results demonstrate that without data augmentation, our approach reached 92% accuracy, whereas Linear Discriminate Analysis, Support Vector Machine, Random Forest, Multi-Layer Perceptron, and Gaussian Naive Bayes achieved 68%, 70%, 58%, 64%, and 40% accuracy, respectively. Further, we surpassed state-of-the-art strategies on the BCI competition IV-2a multiclass MI database by a wide margin, proving the benefit of combining the output of CNN models with automated hyperparameter tuning.
Experimental Study of the Usage of Combined Biopolymer and Plants in Reinforcing the Clayey Soil Exposed to Acidic and Alkaline Contaminations
Authors: Ni Jing , Chen Jiaqi , Liu Shuojie , Hao Ganglai , Geng Xueyu
Published: June 2022

In the last decade, biopolymers have been extensively studied, showing a great potential in soil reinforcement and the promotion of vegetation growth with limited environmental impact. In this paper, a soil reinforcing method with combined biopolymer (xanthan gum, XG) and plants (oat) was proposed to strengthen the clayey soil with different pore fluid pH values. A series of laboratory tests were conducted, mainly including the plant cultivation tests and the direct shear tests. It was found that oats grew better in the neutral, weakly acidic, and weakly alkaline soil environments. Both 0.25% XG and 0.50% XG that mostly promoted plant growth, also led to higher soil shear strength. An excessive XG content (e.g., 0.75% and 1.00%) may lead to the formation of a hard XG–soil matrix, preventing oat growth and therefore resulting in a lower shear strength. The XG–oat combination was found to be more effective in treating the soils with acidic pH values. Furthermore, the XG–oat combination is able to reduce the types and contents of heavy metal elements in the soil. Therefore, we suggest using biopolymers in combination with plants to improve the stability and geotechnical performances of the shallow soil slopes that are exposed to acidic and alkaline contamination.
WRNFS: Width Residual Neuro Fuzzy System, a Fast-Learning Algorithm with High Interpretability
Authors: Kong Lingkun , Chen Dewang , Cheng Ruijun
Published: June 2022

Although the deep neural network has a strong fitting ability, it is difficult to be applied to safety-critical fields because of its poor interpretability. Based on the adaptive neuro-fuzzy inference system (ANFIS) and the concept of residual network, a width residual neuro-fuzzy system (WRNFS) is proposed to improve the interpretability performance in this paper. WRNFS is used to transform a regression problem of high-dimensional data into the sum of several low-dimensional neuro-fuzzy systems. The ANFIS model in the next layer is established based on the low dimensional data and the residual of the ANFIS model in the former layer. The performance of WRNFS is compared with traditional ANFIS on three data sets. The results showed that WRNFS has high interpretability (fewer layers, fewer fuzzy rules, and fewer adjustable parameters) on the premise of satisfying the fitting accuracy. The interpretability, complexity, time efficiency, and robustness of WRNFS are greatly improved when the input number of single low-dimensional systems decreases.
Inter-Varietal Variation in Phenolic Profile, Sugar Contents, Antioxidant, Anti-Proliferative and Antibacterial Activities of Selected Brassica Species
Authors: Zafar Irsa , Hussain Abdullah Ijaz , Fatima Tabinda , Abdullah Alnasser Sulaiman Mohammed , Ahmad Ashfaq
Published: June 2022

The main objective of this research work was to evaluate the variation in nutritional profile, antioxidant, anti-proliferative and antibacterial activities of selected species of Brassica. Five locally grown Brassica species (cauliflower, broccoli, red cabbage, white cabbage and Chinese cabbage) were collected from Ayub Agriculture Research Institute (AARI), Faisalabad, Pakistan. Polyphenolic rich extracts of these Brassicaceae species were prepared by Soxhlet extraction technique using ethanol. Phenolic acids, flavonoids and sugar contents of the investigated species were determined and quantified by RP-HPLC. Antioxidant activity was carried out by measurement of total phenolic contents (TPC), total flavonoid contents (TFC), reducing potential and 2, 2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging capacity. Anti-proliferative activity of all the extracts was determined by MTT assay on lung cancer cell line A549. Antibacterial activity was tested against the two bacterial strains, i.e., Bacillus cereus (B. cereus) and Escherichia coli (E. coli). HPLC analysis revealed the presence of gallic acid, p-coumaric acid, chlorogenic acid and benzoic acid as the major phenolic acids, whereas catechine was the major flavonoid in most of the extracts. The TPC ranged from 9.7 to 32.8 mg/g of dry plant material, measured GAE and TFC ranged from 7.7 to 23.7 mg/g of dry plant material, measured as CE. Higher TPC and TFC were found in red cabbage extract followed by cauliflower, broccoli, white cabbage and Chinese cabbage. Red cabbage extract also showed higher DPPH radical scavenging activity (IC50 = 2.3 µg/mL) followed by cauliflower, broccoli, white cabbage and Chinese cabbage. Maltodextrose was the major sugar followed by fructose in all species of Brassica. Promising anti-proliferative and antibacterial activities were also recorded by the selected Brassica extracts.
A Set of Novel Procedures for Carbon Fiber Reinforcement on Complex Curved Surfaces Using Multi Axis Additive Manufacturing
Authors: Kipping Johann , Kállai Zsolt , Schüppstuhl Thorsten
Published: June 2022

There has been considerable research in recent years on the additive manufacturing (AM) of carbon fiber reinforced polymer (CFRP) parts based on the process of fused deposition modeling (FDM). The currently-applied steps within the manufacturing pipeline, such as slicing and path planning, consider only the planar case of filament deposition and mostly make no use of the possibility to place single pre-impregnated (prepreg) filaments. Classical methods such as tape-laying and laminating struggle with highly curved and complex geometries and require the costly production of molds, whereas when using AM, these geometries can be realized more easily and molds can be created using the same process. In this paper, a set of algorithms is presented that aims to resolve these problems. Criteria are formulated which enable the goal oriented development and evaluation of the presented methods and represent metrics for future methods. The developed algorithms enable the use of both continuous and discontinuous fiber patches in a much wider range of applications in designing and manufacturing of CFRPs. This opens up new possibilities in this promising field. The developed metrics and infrastructure further constitute progress in the field of multi-axis non-planar path planning for slicing algorithms in general and the conducted evaluation proves the formal applicability of the developed algorithms.
Detecting Atypical Values and Their Influence on Blast-Induced Seismic Measurement Results
Authors: Stanković Siniša , Katalinić Mateja , Kuhinek Dalibor , Bohanek Vječislav
Published: June 2022

Blasting is an essential part of any mining or civil engineering project along with all the benefits that it brings, such as cost and time effectiveness, and safety. Still, there are a few downsides to blasting. Ground oscillation velocity as the most significant impact of blasting has been studied broadly. However, not all measured values should be used for PPV (peak particle velocity) predictor or model development. If a false measured value is included in the model or predictor development, it will provide erroneous results that can lead to the damage of the surrounding structures or an increase in the cost of blasting works. There is no clearly defined procedure for separating atypical values (outliers) within blast-induced seismic-effects measurement data. This paper recommends how to properly validate vibration velocity data by detecting and excluding atypical values and how it influences blast-induced seismic measurement results.
Effect of Adjuvant, Concentration and Water Type on the Droplet Size Characteristics in Agricultural Nozzles
Authors: Milanowski Marek , Subr Alaa , Combrzyński Maciej , Różańska-Boczula Monika , Parafiniuk Stanisław
Published: June 2022

One of the goals of adding adjuvants to agricultural spray solutions is to enhance the droplet size characteristics of this spray. Droplet size, in turn, has an influence in the deposited spray quality, in addition to the drift and losses of spray to off-target places. The aim of this research was to evaluate the effect of adding adjuvants to two types of water from different sources on the droplet size characteristics. Two types of adjuvants were employed in the tests: the active substance content of the first adjuvant was a 50% aqueous solution of sodium salt of alkylbenzenesulfonic acid—10% (HY), whereas the second was from rapeseed oil (natural origin)—85% (OL). Both adjuvants were tested in two concentrations: the first was with the concentration recommended by the manufacturer (100%), whereas the second concentration was 50% of the recommended dose. Two types of water from different sources were used in the tests: the first was from a village in the eastern part of Poland (WS), whereas the second was tap water from the city of Lublin, Poland (WUP). Dv0.1, Dv0.5, or volume median diameter (VMD), Dv0.9, Sauter mean diameter (SMD), relative span (RS), and the droplet size distribution were measured and calculated as characteristics of the droplet size. Results showed that the source of water affected the influence of adding adjuvant to the spray solution. Water from the WS source with adjuvant resulted in a numerical decrease in the Dv0.5 values in the percentage of droplet size range below 150 µm, whereas water from the WUP source resulted in an increase in these values (except when adding the HY adjuvant at 50% concentration). Adjuvant concentration significantly (p < 0.05) influenced the features of Dv0.9, SMD, and RS. Adding the OL adjuvant type numerically decreased the percentage of droplet size below 150 µm, and the Dv0.5 values, but only when the WS water source was used.
Classification and Regression of Muscle Neural Signals on Human Lower Extremities via BP_AdaBoost
Authors: Wang Junyao , Dai Yuehong , Si Xiaxi
Published: June 2022

Electromyography (EMG) signals are widely applied in the classification of human motion and intention recognition as having the characteristic of earlier than actual limb motion. In this article, to improve its accuracy of classification and prediction, we firstly analyze the relationship between muscle length and joint movement and select rectus femoris and biceps femoris as the experimental muscles to collect neural signals by means of musculoskeletal analysis software. EMG sensors are used to measure those muscles’ EMG signals of five kinds of knee movements, including thigh-raising, calf-raising, squatting, knee bending on chair, and walking. We designed a BP_AdaBoost algorithm with the BP neural network as a weak classifier and weak regressor, and a muscle neural activation is used as the input for recognition. It is a negative correlation between the length of the rectus femoris and the biceps femoris during gait. Their muscle neural signals are used as the input of the recognition algorithm. The experiment results show that the proposed algorithm improves the rate of BP neural network from 78.82% to 93.52%. The thigh EMG signal successfully maps the knee joint angle by utilizing BP_AdaBoost; its error in identifying five kinds of motion modes is lowest compared with other regression algorithms.