bluuebunny/crossref_metadata_2025 huggingface dataset:
Bioherbicidal Properties of Parthenium hysterophorus, Cleome rutidosperma and Borreria alata Extracts on Selected Crop and Weed Species
Authors: Motmainna Mst. , Juraimi Abdul Shukor , Uddin Md. Kamal , Asib Norhayu Binti , Islam A. K. M. Mominul , Hasan Mahmudul
Published: March 2021

Natural product-based herbicides could be the effective alternatives to synthetic chemical herbicides for eco-friendly weed management. This research, therefore, was conducted to identify the phytotoxic properties of Parthenium hysterophorus L., Cleome rutidosperma DC. and Borreria alata (Aubl.) DC. with a view to introducing them as a tool for natural herbicide development. The methanol extracts of these plants were examined on the germination and growth of Zea mays L., Oryza sativa L., Abelmoschus esculentus (L.) Moench and Amaranthus gangeticus L., Oryza sativa f. Spontanea Roshev. (Weedy rice), Echinochloa colona (L.) Link., Euphorbia hirta L., and Ageratum conyzoides L. under laboratory and glasshouse conditions. A complete randomized design (CRD) with five replications and randomized complete block design (RCBD) with four replications were laid out for laboratory and glasshouse experiments, respectively. In the laboratory experiment, three plant extracts of 0, 6.25, 12.5, 50, and 100 g L−1 were tested on survival rate, hypocotyl, and radicle length of eight test plant species. No seed germination of A. conzyoides, E. hirta, and A. gangeticus were recorded when P. hysterophorus extract was applied at 50 g L−1. C. rutidosperma had the same effect on those plants at 100 g L−1. In the glasshouse, similar extracts and concentrations used in the laboratory experiments were sprayed on at the 2–3 leaf stage for grasses and 4–6 for the broadleaf species. Tested plants were less sensitive to C. rutidosperma and B. alata compared to P. hysterophorus extract. Among the weeds and crops, A. conyzoides, E. hirta, A. esculentus and A. gangeticus were mostly inhibited by P. hysterophorus extract at 100 g L−1. Based on these results, P. hysterophorus was the most phytotoxic among the tested plant extracts and could be used for developing a new natural herbicide for green agriculture.
Wheat Yield Forecasting for the Tisza River Catchment Using Landsat 8 NDVI and SAVI Time Series and Reported Crop Statistics
Authors: Nagy Attila , Szabó Andrea , Adeniyi Odunayo David , Tamás János
Published: March 2021

Due to the increasing global demand of food grain, early and reliable information on crop production is important in decision making in agricultural production. Remote sensing (RS)-based forecast models developed from vegetation indices have the potential to give quantitative and timely information on crops for larger regions or even at farm scale. Different vegetation indices are being used for this purpose, however, their efficiency in estimating crop yield certainly needs to be tested. In this study, wheat yield was derived by linear regressing reported yield values against a time series of six different peak-seasons (2013–2018) using the Landsat 8-derived Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI). NDVI- and SAVI-based forecasting models were validated based on 2018–2019 datasets and compared to evaluate the most appropriate index that performs better in forecasting wheat production in the Tisza river basin. Nash-Sutcliffe efficiency index was positive with E1 = 0.716 for the model from NDVI and for SAVI E1 = 0.909, which means that the forecasting method developed and performed good forecast efficiency. The best time for wheat yield prediction with Landsat 8-SAVI and NDVI was found to be the beginning of full biomass period from the 138th to 167th day of the year (18 May to 16 June; BBCH scale: 41–71) with high regression coefficients between the vegetation indices and the wheat yield. The RMSE of the NDVI-based prediction model was 0.357 t/ha (NRMSE: 7.33%). The RMSE of the SAVI-based prediction model was 0.191 t/ha (NRMSE 3.86%). The validation of the results revealed that the SAVI-based model provided more accurate forecasts compared to NDVI. Overall, probable yield amount is possible to predict far before harvest (six weeks earlier) based on Landsat 8 NDVI and SAVI and generating simple thresholds for yield forecasting, and a potential loss of wheat yield can be mapped.
Genetic Heterogeneity among Chicken Infectious Anemia Viruses Detected in Italian Fowl
Authors: Quaglia Giulia , Mescolini Giulia , Catelli Elena , Berto Giacomo , Muccioli Filippo , Lupini Caterina
Published: March 2021

Chicken infectious anemia virus (CIAV) is a pathogen of chickens associated with immunosuppression and with a disease named chicken infectious anemia. The present survey reports an epidemiological study on CIAV distribution in Italian broiler, broiler breeder and backyard chicken flocks. Twenty-five strains were detected by a specifically developed nested PCR protocol, and molecularly characterized by partial VP1 gene or complete genome sequencing. Viral DNA amplification was successfully obtained from non-invasive samples such as feathers and environmental dust. Sequence and phylogenetic analysis showed the circulation of field or potentially vaccine-derived strains with heterogeneous sequences clustered into genogroups II, IIIa, and IIIb. Marker genome positions, reported to be correlated with CIAV virulence, were evaluated in field strains. In conclusion, this is the first survey focused on the molecular characteristics of Italian CIAVs, which have proved to be highly heterogeneous, implementing at the same time a distribution map of field viruses worldwide.
Clinical Cytogenetics of the Dog: A Review
Authors: Szczerbal Izabela , Switonski Marek
Published: March 2021

The dog is an important companion animal and has been recognized as a model in biomedical research. Its karyotype is characterized by a high chromosome number (2n = 78) and by the presence of one-arm autosomes, which are mostly small in size. This makes the dog a difficult subject for cytogenetic studies. However, there are some chromosome abnormalities that can be easily identified, such as sex chromosome aneuploidies, XX/XY leukocyte chimerism, and centric fusions (Robertsonian translocations). Fluorescence in situ hybridization (FISH) with the use of whole-chromosome painting or locus-specific probes has improved our ability to identify and characterize chromosomal abnormalities, including reciprocal translocations. The evaluation of sex chromosome complement is an important diagnostic step in dogs with disorders of sex development (DSD). In such cases, FISH can detect the copy number variants (CNVs) associated with the DSD phenotype. Since cancers are frequently diagnosed in dogs, cytogenetic evaluation of tumors has also been undertaken and specific chromosome mutations for some cancers have been reported. However, the study of meiotic, gamete, and embryo chromosomes is not very advanced. Knowledge of canine genome organization and new molecular tools, such as aCGH (array comparative genome hybridization), SNP (single nucleotide polymorphism) microarray, and ddPCR (droplet digital PCR) allow the identification of chromosomal rearrangements. It is anticipated that the comprehensive use of chromosome banding, FISH, and molecular techniques will substantially improve the diagnosis of chromosome abnormalities in dogs.
Human–Animal Interactions: Expressions of Wellbeing through a “Nature Language”
Authors: Yerbury Rachel M. , Lukey Samantha J.
Published: March 2021

Human–animal interactions (HAIs) can be beneficial for humans in a number of ways, and interactions with wild animals may contribute to human mental wellbeing, partly through nature connectedness. This study applies the “Nature Interaction Pattern” approach (proposed by Kahn and colleagues) to characterize the structure of meaningful human engagement with nature and animals, and to consider the wellbeing outcomes. This qualitative, retrospective study uses open responses from 359 participants who describe how their wild animal encounters affected their nature connectedness. Thematic analysis explores five nature Interaction Patterns and four resulting Psychological Descriptions that occur in the portrayals of the marine animal encounters and these are described using representative quotes. Feelings of love, belonging, positive feelings, fulfillment and the gaining of perspective, were linked with the human–animal experience and the Interaction Patterns. These findings suggest that when people encounter and interact with animals in their natural environment, their mental health and wellbeing may be enhanced. Further, through connecting with nature and animals, reciprocity may occur, that is, when people connect with nature and animals, they can also give back. Within this interaction there becomes an entanglement of experiences thereby encouraging caring for nature and animals.
Chronic Pain in Dogs and Cats: Is There Place for Dietary Intervention with Micro-Palmitoylethanolamide?
Authors: della Rocca Giorgia , Gamba Davide
Published: March 2021

The management of chronic pain is an integral challenge of small animal veterinary practitioners. Multiple pharmacological agents are usually employed to treat maladaptive pain including opiates, non-steroidal anti-inflammatory drugs, anticonvulsants, antidepressants, and others. In order to limit adverse effects and tolerance development, they are often combined with non-pharmacologic measures such as acupuncture and dietary interventions. Accumulating evidence suggests that non-neuronal cells such as mast cells and microglia play active roles in the pathogenesis of maladaptive pain. Accordingly, these cells are currently viewed as potential new targets for managing chronic pain. Palmitoylethanolamide is an endocannabinoid-like compound found in several food sources and considered a body’s own analgesic. The receptor-dependent control of non-neuronal cells mediates the pain-relieving effect of palmitoylethanolamide. Accumulating evidence shows the anti-hyperalgesic effect of supplemented palmitoylethanolamide, especially in the micronized and co-micronized formulations (i.e., micro-palmitoylethanolamide), which allow for higher bioavailability. In the present paper, the role of non-neuronal cells in pain signaling is discussed and a large number of studies on the effect of palmitoylethanolamide in inflammatory and neuropathic chronic pain are reviewed. Overall, available evidence suggests that there is place for micro-palmitoylethanolamide in the dietary management of chronic pain in dogs and cats.
Effects of Desiccation on Metamorphic Climax in Bombina variegata: Changes in Levels and Patterns of Oxidative Stress Parameters
Authors: Petrović Tamara G. , Kijanović Ana , Kolarov Tomašević Nataša , Gavrić Jelena P. , Despotović Svetlana G. , Gavrilović Branka R. , Radovanović Tijana B. , Vukov Tanja , Faggio Caterina , Prokić Marko D.
Published: March 2021

In this paper, we examined how the oxidative status (antioxidant system and oxidative damage) of Bombina variegata larvae changed during the metamorphic climax (Gosner stages: 42—beginning, 44—middle and 46—end) and compared the patterns and levels of oxidative stress parameters between individuals developing under constant water availability (control) and those developing under decreasing water availability (desiccation group). Our results revealed that larvae developing under decreasing water availability exhibited increased oxidative damage in the middle and end stages. This was followed by lower levels of glutathione in stages 44 and 46, as well as lower values of catalase, glutathione peroxidase, glutathione S-transferase and sulfhydryl groups in stage 46 (all in relation to control animals). Comparison between stages 42, 44 and 46 within treatments showed that individuals in the last stage demonstrated the highest intensities of lipid oxidative damage in both the control and desiccation groups. As for the parameters of the antioxidant system, control individuals displayed greater variety in response to changes induced by metamorphic climax than individuals exposed to desiccation treatment. The overall decrease in water availability during development led to increased oxidative stress and modifications in the pattern of AOS response to changes induced by metamorphic climax in larvae of B. variegata.
Effects of Lippia citriodora Leaf Extract on Lipid and Oxidative Blood Profile of Volunteers with Hypercholesterolemia: A Preliminary Study
Authors: Angiolillo Antonella , Leccese Deborah , Palazzo Marisa , Vizzarri Francesco , Casamassima Donato , Corino Carlo , Di Costanzo Alfonso
Published: March 2021

Lippia citriodora is a plant traditionally used for its anti-inflammatory, antioxidant and antispasmodic effects, as well as for additional biological activities proven in cell culture, animal studies and a small number of human clinical trials. The plant has also shown a marked improvement in blood lipid profile in some animal species. In the present preliminary study, we investigated the effect of a leaf extract on lipid and oxidative blood profile of hypercholesterolemic volunteers. Twelve adults received Lippia citriodora extract caps, containing 23% phenylpropanoids, (100 mg, once a day) for 16 weeks. Selected blood lipids and plasma oxidative markers were measured at baseline and after 4, 8 and 16 weeks of treatment. Compared with baseline, total cholesterol levels significantly decreased and high-density lipoprotein cholesterol increased, while low-density lipoprotein cholesterol and triglycerides showed only a downward trend. Oxidative status was improved due to a decrease in the concentration of total oxidant status, reactive oxygen metabolites and malondialdehyde, and a significant increase in ferric reducing ability of plasma, vitamin A and vitamin E. These preliminary results suggest that dietary supplementation with Lippia citriodora extract can improve the lipid profile, enhance blood antioxidant power, and could be a valuable natural compound for the management of human hypercholesterolemia.
The Impact of Melatonin and NLRP3 Inflammasome on the Expression of microRNAs in Aged Muscle
Authors: Sayed Ramy KA , Fernández-Ortiz Marisol , Fernández-Martínez José , Aranda Martínez Paula , Guerra-Librero Ana , Rodríguez-Santana César , de Haro Tomás , Escames Germaine , Acuña-Castroviejo Darío , Rusanova Iryna
Published: March 2021

Muscular aging is a complex process and underlying physiological mechanisms are not fully clear. In recent years, the participation of the NF-kB pathway and the NLRP3 inflammasome in the chronic inflammation process that accompanies the skeletal muscle’s aging has been confirmed. microRNAs (miRs) form part of a gene regulatory machinery, and they control numerous biological processes including inflammatory pathways. In this work, we studied the expression of four miRs; three of them are considered as inflammatory-related miRs (miR-21, miR-146a, and miR-223), and miR-483, which is related to the regulation of melatonin synthesis, among other targets. To investigate the changes of miRs expression in muscle along aging, the impact of inflammation, and the role of melatonin in aged skeletal muscle, we used the gastrocnemius muscle of wild type (WT) and NLRP3-knockout (NLRP3−) mice of 3, 12, and 24 months-old, with and without melatonin supplementation. The expression of miRs and pro-caspase-1, caspase-3, pro-IL-1β, bax, bcl-2, and p53, was investigated by qRT-PCR analysis. Histological examination of the gastrocnemius muscle was also done. The results showed that age increased the expression of miR-21 (p < 0.01), miR-146a, and miR-223 (p < 0.05, for both miRs) in WT mice, whereas the 24-months-old mutant mice revealed decline of miR-21 and miR-223 (p < 0.05), compared to WT age. The lack of NLRP3 inflammasome also improved the skeletal muscle fibers arrangement and reduced the collagen deposits compared with WT muscle during aging. For the first time, we showed that melatonin significantly reduced the expression of miR-21, miR-146a, and miR-223 (p < 0.05 for all ones, and p < 0.01 for miR-21 at 24 months old) in aged WT mice, increased miR-223 in NLRP3− mice (p < 0.05), and induced miR-483 expression in both mice strains, this increase being significant at 24 months of age.
Recent Advances in Anti-Metastatic Approaches of Herbal Medicines in 5 Major Cancers: From Traditional Medicine to Modern Drug Discovery
Authors: Park Jinkyung , Jeong Dahee , Song Meeryoung , Kim Bonglee
Published: March 2021

Metastasis is the main cause of cancer-related death. Despite its high fatality, a comprehensive study that covers anti-metastasis of herbal medicines has not yet been conducted. The aim of this study is to investigate and assess the anti-metastatic efficacies of herbal medicines in the five major cancers, including lung, colorectal, gastric, liver, and breast cancers. We collected articles published within five years using PubMed, Google Scholar, and Web of Science with “cancer metastasis” and “herbal medicine” as keywords. Correspondingly, 16 lung cancer, 23 colorectal cancer, 10 gastric cancer, 10 liver cancer, and 18 breast cancer studies were systematically reviewed. The herbal medicines attenuated metastatic potential targeting various mechanisms such as epithelial mesenchymal transition (EMT), reactive oxygen species (ROS), and angiogenesis. Specifically, the drugs regulated metastasis related factors such as matrix metalloproteinase (MMP), serine-threonine protein kinase/extracellular regulated protein kinase (AKT/ERK), angiogenic factors, and chemokines. Overall, the present study is the first review, comprehensively investigating the anti-metastasis effect of herbal medicines on five major cancers, providing the experimental models, doses and durations, and mechanisms. Herbal medicines could be a potent candidate for anti-metastatic drugs.
Multidimensional Comparative Analysis of Bioactive Phenolic Compounds of Honeys of Various Origin
Authors: Gośliński Michał , Nowak Dariusz , Szwengiel Artur
Published: March 2021

Honey is a natural product which owes its health benefits to its numerous bioactive compounds. The composition of honey is highly diverse and depends on the type of honey and its origin. Antioxidant capacity arises mainly from the total content of polyphenols and their composition. The aim of this study was to perform a multidimensional comparative analysis of phenolic compounds of honeys of various origins. Honeydew, buckwheat, manuka, Malaysian and goldenrod honeys had the highest antioxidant capacity (above 400 mg Trolox equivalents kg−1). These honeys were also characterized by the highest total polyphenol content (about 2500 mg gallic acid equivalents (GAE) kg−1) and the highest total flavonoid content (1400–1800 mg catechin equivalents (CAE) kg−1). Other honeys had much lower antioxidant properties. A multidimensional analysis of the profiles of phenolic compounds showed that honeys constitute a non-homogeneous data set and manuka honey was in contrast to other samples. Principal component analysis (PCA) (based on 18 phenolic compounds) distinguished honeys into five groups. Manuka, Malaysian and honeydew honeys created their own separate groups and the location of other honeys was variable. Ultra-high-performance liquid chromatography (UHPLC) analysis demonstrated that profiles of polyphenols in honeys were highly varied. Caffeic acid, datiscetin and rhamnetin were characteristic compounds for manuka honey. Quercetin, kaempferol and apigenin were present in all honeys except Malaysian honey. The antioxidant properties and the profiles of bioactive phenolic compounds of honeys were miscellaneous. The richest sources of polyphenols were local buckwheat and honeydew honeys, alongside exotic manuka and Malaysian honeys. These honeys could provide valuable ingredients to the human diet, helping to prevent diseases.
Accurate Simulation of Light Propagation in Complex Skin Tissues Using an Improved Tetrahedron-Based Monte Carlo Method
Authors: Jia Hao , Chen Bin , Li Dong
Published: March 2021

Understanding light transportation in skin tissues can help improve clinical efficacy in the laser treatment of dermatosis, such as port-wine stains (PWS). Patient-specific cross-bridge PWS vessels are structurally complicated and considerably influence laser energy deposition due to shading effects. The shading effect of PWS vessels is investigated using a tetrahedron-based Monte Carlo (MC) method with extended boundary condition (TMCE). In TMCE, body-fitted tetrahedra are generated in different tissues, and the precision of photon–surface interaction can be considerably improved via mesh refinement. Such improvement is difficult to achieve with the widely used voxel-based MC method. To fit the real physical boundary, the extended boundary condition is adapted by extending photon propagation to the semi-infinite tissue layers while restricting the statistics of photon propagation in the computational domain. Results indicate that the shading parameters, such as the cross angle, vessel distance, and geometric shadow (GS), of cross-bridge blood vessel pairs determine the peak characteristics of photon deposition in deep vessels by affecting the relative deposition of collimated and diffused light. Collimated light is shaded, attenuated, and partially transformed into diffused light due to the increase in vessel distance and GS of vessel pairs, resulting in difficulty in treating deep and shallow vessels with one laser pulse. The TMCE method can be used for the individualized and precise forecasting of laser energy deposition based on the morphology and embedding characteristics of vascular lesions.
Application of Fatigue Damage Evaluation Considering Linear Hydroelastic Effects of Very Large Container Ships Using 1D and 3D Structural Models
Authors: Lee Sang-Ick , Boo Seung-Hwan , Kim Beom-Il
Published: March 2021

Owing to the increasing size and speed of ships to ensure economic efficiency, the hydroelastic phenomena of the hull have emerged as an important factor to be considered in the evaluation of strength during the design stage of current ship building procedures. In this study, we established a method to evaluate fatigue strength with linear spring effects using a 1D (one-dimensional) beam model and a 3D (three-dimensional) global Finite Element (FE) model. Firstly, FSI (fluid–structure interaction) analysis was carried out using the 1D beam model of a 15,000 twenty equivalent unit (TEU) container ship. In this step, the method proposed was to calculate the stress RAO (Response Amplitude Operator) of the hot spot points using only the hull girder load from the beam model. Next, a modal superposition analysis was carried out using the 3D global FE model that was directly calibrated to the fatigue damage of the hot spot points. Based on these stress transfer functions with hydroelastic effects, spectral fatigue analysis was carried out, and the portion of linear springing effects in the fatigue damage was analyzed, respectively. These results were compared with the rigid-body-based results in the final design stage. Finally, the applicability of the proposed method at the actual design stage is discussed.
Design and Optimization of Piezoelectric-Powered Portable UV-LED Water Disinfection System
Authors: Şala Derda E. , Dalveren Yaser , Kara Ali , Derawi Mohammad
Published: March 2021

Due to the environmental pollution threatening human life, clean water accessibility is one of the major global issues. In this context, in literature, there are many portable water disinfection systems utilizing ultraviolet (UV) radiation. UV water disinfection systems employ piezoelectric-based electric power along with UV light-emitting diode (LED) sources. This paper elaborates on the detailed design and parametric optimization of a portable UV disinfection system. The proposed system aims to generate piezoelectric harvesting-based electrical power simply by shaking, and the generated power is then used to supply UV-LEDs for water disinfection. To this end, overall system parameters along with a physical-mathematical model of mechanical, electrical and biochemical aspects of the system are fully developed. Moreover, the main design parameters of the developed model are derived for optimal operation of the system by employing Genetic Algorithm (GA). Finally, optimal design parameters were identified for three different cost scenarios. The model can further be improved for practical implementation and mass production of the system.
Depth-Extrapolation-Based True-Amplitude Full-Wave-Equation Migration from Topography
Authors: Liu Hao , Liu Xuewei
Published: March 2021

The lack of an initial condition is one of the major challenges in full-wave-equation depth extrapolation. This initial condition is the vertical partial derivative of the surface wavefield and cannot be provided by the conventional seismic acquisition system. The traditional solution is to use the wavefield value of the surface to calculate the vertical partial derivative by assuming that the surface velocity is constant. However, for seismic exploration on land, the surface velocity is often not uniform. To solve this problem, we propose a new method for calculating the vertical partial derivative from the surface wavefield without making any assumptions about the surface conditions. Based on the calculated derivative, we implemented a depth-extrapolation-based full-wave-equation migration from topography using the direct downward continuation. We tested the imaging performance of our proposed method with several experiments. The results of the Marmousi model experiment show that our proposed method is superior to the conventional reverse time migration (RTM) algorithm in terms of imaging accuracy and amplitude-preserving performance at medium and deep depths. In the Canadian Foothills model experiment, we proved that our method can still accurately image complex structures and maintain amplitude under topographic scenario.
Application of Kalman Filter to Improve 3D LiDAR Signals of Autonomous Vehicles in Adverse Weather
Authors: Lin Shih-Lin , Wu Bing-Han
Published: March 2021

A worldwide increase in the number of vehicles on the road has led to an increase in the frequency of serious traffic accidents, causing loss of life and property. Autonomous vehicles could be part of the solution, but their safe operation is dependent on the onboard LiDAR (light detection and ranging) systems used for the detection of the environment outside the vehicle. Unfortunately, problems with the application of LiDAR in autonomous vehicles remain, for example, the weakening of the echo detection capability in adverse weather conditions. The signal is also affected, even drowned out, by sensory noise outside the vehicles, and the problem can become so severe that the autonomous vehicle cannot move. Clearly, the accuracy of the stereo images sensed by the LiDAR must be improved. In this study, we developed a method to improve the acquisition of LiDAR data in adverse weather by using a combination of a Kalman filter and nearby point cloud denoising. The overall LiDAR framework was tested in experiments in a space 2 m in length and width and 0.6 m high. Normal weather and three kinds of adverse weather conditions (rain, thick smoke, and rain and thick smoke) were simulated. The results show that this system can be used to recover normal weather data from data measured by LiDAR even in adverse weather conditions. The results showed an effective improvement of 10% to 30% in the LiDAR stereo images. This method can be developed and widely applied in the future.
Bending Fatigue Behavior of 17-4 PH Gears Produced by Additive Manufacturing
Authors: Concli Franco , Bonaiti Luca , Gerosa Riccardo , Cortese Luca , Nalli Filippo , Rosa Francesco , Gorla Carlo
Published: March 2021

The introduction of Additive Manufacturing (AM) is changing the way in which components and machines can be designed and manufactured. Within this context, designers are taking advantage of the possibilities of producing parts via the addition of material, defining strategies, and exploring alternative design or optimization solutions (i.e., nonviable using subtractive technologies) of critical parts (e.g., gears and shafts). However, a safe and effective design requires specific resistance data that, due to the intrinsic modernity of additive technologies, are not always present in the literature. This paper presents the results of an experimental campaign performed on gear-samples made by 17-4 PH and produced via Laser Powder Bed Fusion (PBF-LB/M). The tests were executed using the Single Tooth Bending Fatigue (STBF) approach on a mechanical pulsator. The fatigue limit was determined using two different statistical approaches according to Dixon and Little. The obtained data were compared to those reported in the ISO standard for steels of similar performance. Additional analyses, i.e., Scanning Electron Microscopy SEM, were carried out to provide a further insight of the behavior 17-4PH AM material and in order to investigate the presence of possible defects in the tested gears, responsible for the final failure.
Immobilised Humic Substances as Low-Cost Sorbents for Emerging Contaminants
Authors: Ansone-Bertina Linda , Upska Karina , Dobkevica Linda , Kviesis Jorens , Meija Raimonds , Klavins Maris
Published: March 2021

Environmental pollution with contaminants of emerging concern (CECs) is a worldwide problem that is receiving increasing attention. Although these substances have been released in the aquatic environment for a long time, wastewater treatment plants are still incapable of removing emerging contaminants completely. Consequently, trace metals, metalloids and pharmaceuticals, as well as surfactant leftovers, are often found in environmental samples. Environmentally friendly and cost-effective sorbents such as humic substances can be used for purification if their sorption properties are increased by immobilization. To our knowledge, immobilized humic substances have not been widely studied as sorbents up to now. In this study, humic substances were immobilized to obtain low-cost sorbents. The chosen methods for characterization of the obtained sorbents showed successful immobilization. Traditional pollutants, such as Cr(III) (a metal), As(V) (a metalloid) and chlorpromazine (a pharmaceutical), were used as representative contaminants. Sorption experiments were conducted using the batch system, and sorption was also studied based on the sorbent dosage, initial concentration of the studied element or substance, solution pH and sorption time. The results show that all the obtained immobilized humic substances in this study can be used as sorbents to remove contaminants from water. At the same time, from these humic substances, only those immobilized using iron compounds are suitable for the removal of arsenic.
Infrared Imaging and NDT
Authors: Usamentiaga Rubén , Venegas Pablo
Published: March 2021

Infrared thermography has become a mature and widely accepted technology with applications in many different fields, from medical to industrial [...]
A Probabilistic-Based Deep Learning Model for Skin Lesion Segmentation
Authors: Adegun Adekanmi Adeyinka , Viriri Serestina , Yousaf Muhammad Haroon
Published: March 2021

The analysis and detection of skin cancer diseases from skin lesion have always been tedious when done manually. The complex nature of skin lesion images is one of the key reasons for this. The skin lesion images contain noise and artifacts such as hairs, oil and bubbles, blood vessels, and skin lines. They also have variegated colors, low contrast, and irregular borders. Various computational approaches have been designed in the past for aiding in the detection and diagnosis of skin cancer diseases using skin lesion images. The existing techniques have been limited due to the interference of the aforementioned features of skin lesion. Recently, machine learning techniques, in particular the deep learning techniques have been used for the detection of skin cancer. However, they are still limited to the fuzzy and irregular borders of skin lesion images coupled with the low contrast that exists between the diseased lesion and healthy tissues. In this paper, we utilized a probabilistic model for the enhancement of a fully convolutional network-based deep learning system to analyze and segment skin lesion images. The probabilistic model employs an efficient mean-field approximate probabilistic inference approach with a fully connected conditional random field that utilizes a Gaussian kernel. The probabilistic model further performs a refinement of skin lesion borders. The whole framework is tested and evaluated on publicly available skin lesion image datasets of ISBI 2017 and PH2. The system achieved a better performance, having an accuracy of 98%.
Evaluation of the Trueness of Digital Implant Impressions According to the Implant Scan Body Orientation and Scanning Method
Authors: Lee Bora , Nam Na-Eun , Shin Seung-Ho , Lim Jung-Hwa , Shim June-Sung , Kim Jong-Eun
Published: March 2021

This study investigated the trueness of a digital implant impression according to the orientation of the implant scan body (ISB) and the scanning method. With the flat surface of the ISB facing either the buccal or proximal direction, the ISB was scanned using one tabletop scanner (T500) and three types of intraoral scanner (TRIOS 3, CS3600, and i500). The effects of differences in the scanning method and ISB orientation were assessed. Postalignment data were subsequently obtained with the abutments generated using a digital library, and superimposed with reference data using a best-fit algorithm, followed by root-mean-square error (RMSE) analysis. The RMSE was lower in the buccal groups (28.15 ± 8.87 μm, mean ± SD) than in the proximal groups (31.94 ± 8.95 μm, p = 0.031), and lower in the full-scan groups (27.92 ± 10.80 μm) than in the partial-scan groups (32.16 ± 6.35 μm, p = 0.016). When using the tabletop scanner, the trueness was higher when the ISB was connected buccally (14.34 ± 0.89 μm) than when it was connected proximally (29.35 ± 1.15 μm, p < 0.001). From the findings of this study it can be concluded that the operator should connect the ISB so that its flat surface faces the buccal direction, and attempt to scan all areas. Additionally, it is advantageous to connect an ISB buccally when using a tabletop scanner.
A Systematical Characterization of TeO2–V2O5 Glass System Using Boron (III) Oxide and Neodymium (III) Oxide Substitution: Resistance Behaviors against Ionizing Radiation
Authors: Tekin H. O. , Issa Shams A. M. , Kilic G. , Zakaly Hesham M. H. , Tarhan N. , Sidek H. A. A. , Matori K. A. , Zaid M. H. M.
Published: March 2021

This study aimed to perform an extensive characterization of a 74.75TeO2–0.25V2O5–(25 − x)B2O3-xNd2O3 glass system with (x = 0, 0.5, 1.0, and 1.5 mol%) for radiation shielding properties. Linear and mass attenuation coefficients were determined using Phy-X PSD software and compared with the simulation using Monte Carlo software MCNPX (version 2.7.0). Half value layer, mean free path, tenth value layer, effective atomic number, exposure buildup factor, and energy absorption buildup factors of VTBNd0.0, VTBNd0.5, VTBNd1.0, and VTBNd1.5 glasses were determined, respectively. The results showed that boron (III) oxide and neodymium (III) oxide substitution has an obvious impact on the gamma ray attenuation properties of the studied glasses. It can be concluded that the VTBNd1.5 sample with the highest content of neodymium (III) oxide (1.5 mol%) is the superior sample for shielding of gamma radiation in the investigated energy range.
Rheology, Hydration, and Microstructure of Portland Cement Pastes Produced with Ground Açaí Fibers
Authors: Azevedo Afonso , de Matos Paulo , Marvila Markssuel , Sakata Rafael , Silvestro Laura , Gleize Philippe , Brito Jorge de
Published: March 2021

Açaí (Euterpe oleracea) is a Brazilian typical fruit that is enveloped by natural fibers. This work investigated the effect of incorporating ground açaí fibers (in natura and chemically treated with NaOH and HCl) in 5–10 wt.% replacement of Portland cement on the rheology, hydration, and microstructure of pastes. Rotational rheometry, isothermal calorimetry, X-Ray Diffraction (XRD), and Scanning Electron Microscopy (SEM) were performed to evaluate the cement pastes, in addition to SEM-EDS, FTIR, zeta potential, and XRD for fiber characterization. The results showed that the chemical treatment reduced the cellulose and lignin contents in açaí fibers while increasing its surface roughness. The addition of 5% of either fiber slightly increased the yield stress and viscosity of paste, while 10% addition drastically increased these properties, reaching yield stress and viscosity values respectively 40 and 8 times higher than those of plain paste. The incorporation of 5% in natura fibers delayed the cement hydration by about 2.5 days while 10% in natura fibers delayed it by over 160 h. The chemical treatment significantly reduced this retarding effect, leading to a 3 h delay when 5% treated fibers were incorporated. Overall, the combined NaOH/HCl treatment was effective for açaí fibers functionalization and these fibers can be used in cementitious composites.
Artificial Macropores with Sandy Fillings Enhance Desalinization and Increase Plant Biomass in Two Contrasting Salt-Affected Soils
Authors: Zhang Yifu , Zhang Ruihong , Zhang Baofeng , Xi Xiaobo
Published: March 2021

Salt accumulation in topsoil is a widespread restricting factor that limits agricultural production and threatens food security in arid and semi-arid regions. However, whether this upward enrichment was suppressed by macropores was less documented. Therefore, artificial macropores with sandy fillings (AMSF) method was proposed in this study. Soil column experiments showed a significant improvement of saturated hydraulic conductivity (Ks) by more than 260% under artificial macropore treatment. Freshwater irrigation was conducted to monitor the short-term water and salt movement. This research aimed at evaluating the potential benefit of AMSF method on soil desalinization in coastal farmland of northern China. The results demonstrated that downward movement of soil water was stimulated in AMSF method, accordingly, washing more salt ions out of top rooting zone. Particularly, 10 cm or more macropore depth treatments of AMSF method enhanced total desalinization by 52.1% to 176.6% in 0–30 cm soil layer, in comparison to the control group without macropore. Subsequent observations for alfalfa showed higher biomass by 20.8% under 15 cm macropore depth. The results here provided an exploration demonstration to pursue these studies with the ultimate goal of optimizing application strategies for amendment in coastal salt-affected lands of northern China.
Optimizing Design of Smart Workplace through Multi-Objective Programming
Authors: Aly Shady , Tyrychtr Jan , Vrana Ivan
Published: March 2021

Smart environments have proven very supportive to the improvement of the performance of people in different workplaces. Plenty of applications have been introduced spanning different settings including healthcare, ambient assisted living, homes, offices, and manufacturing environment, etc. However, subjectivity and ambiguity prevail in the majority of research, and still, up to date, rare approaches found quantitatively and objectively constructing or assessing the impact of smart enabling technologies on the performance of the subject environment. Further, no approaches have considered optimizing the adoption of those smart technologies with respect to objectives achievement. This article presents a novel optimization methodology for designing a smart workplace environment in conditions of ambiguity or fuzziness. The methodology begins with defining and weighing the overall goals and objectives of the workplace. The Prometthe multi-criterion decision-making technique is used to weigh the operational objectives with respect to the overall workplace goals. Next, the relation among basic building blocks of the model; namely: the operational objectives, smartness features, and smart enabling technologies are quantified, utilizing fuzzy relations. Then, the fuzzy goal programming techniques will be utilized to optimize the impact relation values while considering the budget constraint. The proposed optimization methodology is implemented on the development and optimization of the smart clinic, as a typical instance of the workplace.
Self-Supervised Transfer Learning from Natural Images for Sound Classification
Authors: Shin Sungho , Kim Jongwon , Yu Yeonguk , Lee Seongju , Lee Kyoobin
Published: March 2021

We propose the implementation of transfer learning from natural images to audio-based images using self-supervised learning schemes. Through self-supervised learning, convolutional neural networks (CNNs) can learn the general representation of natural images without labels. In this study, a convolutional neural network was pre-trained with natural images (ImageNet) via self-supervised learning; subsequently, it was fine-tuned on the target audio samples. Pre-training with the self-supervised learning scheme significantly improved the sound classification performance when validated on the following benchmarks: ESC-50, UrbanSound8k, and GTZAN. The network pre-trained via self-supervised learning achieved a similar level of accuracy as those pre-trained using a supervised method that require labels. Therefore, we demonstrated that transfer learning from natural images contributes to improvements in audio-related tasks, and self-supervised learning with natural images is adequate for pre-training scheme in terms of simplicity and effectiveness.
Effect of Selenium Nanoparticles on Carbon Tetrachloride-Induced Hepatotoxicity in the Swiss Albino Rats
Authors: Ebaid Hossam , Al-Tamimi Jameel , Hassan Iftekhar , Habila Mohamed A. , Rady Ahmed M. , Alhazza Ibrahim M. , Ahmed Ashraf M.
Published: March 2021

Background: This study investigated selenium nanoparticles’ protective effects (SE-NPs) against carbon tetrachloride (CCl4)-induced hepatic injury in rats. Methods: Rats were divided into four groups (n = 8). Group 1 rats received the vehicle solution only. Group 2 received a single intraperitoneal injection of 1 mL/kg CCl4 in liquid paraffin (1:1 v/v). Group 3 was treated with SE-NPs (2.5 mg/kg) twice a week for three weeks before receiving CCl4 challenge. Oxidative stress, liver function, liver histopathology and serum lipid levels were evaluated. Results: Plasma concentrations of aspartate transaminase (AST), gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP), urea, creatinine, malondialdehyde (MDA) and the toxicity marker, lactate dehydrogenase (LDH), were significantly elevated in rats treated with CCl4 compared to the controls. CCl4 also caused a significant decline in liver glutathione (GSH) concentration. SE-NP pretreatment significantly improved the level of AST, urea, creatinine, MDA, LDH, and GSH in the CCl4-injected rats towards the control levels. Conclusions: SE-NPs restored both liver function and hepatic structure in CCl4 treated rats. SE-NPs exhibit an ability to counter markers of liver injury induced by CCl4 and restore oxidative stability to lipid profiles and liver structure and function.
Wind Turbine Power Curve Modelling with Logistic Functions Based on Quantile Regression
Authors: Jing Bo , Qian Zheng , Zareipour Hamidreza , Pei Yan , Wang Anqi
Published: March 2021

The wind turbine power curve (WTPC) is of great significance for wind power forecasting, condition monitoring, and energy assessment. This paper proposes a novel WTPC modelling method with logistic functions based on quantile regression (QRLF). Firstly, we combine the asymmetric absolute value function from the quantile regression (QR) cost function with logistic functions (LF), so that the proposed method can describe the uncertainty of wind power by the fitting curves of different quantiles without considering the prior distribution of wind power. Among them, three optimization algorithms are selected to make comparative studies. Secondly, an adaptive outlier filtering method is developed based on QRLF, which can eliminate the outliers by the symmetrical relationship of power distribution. Lastly, supervisory control and data acquisition (SCADA) data collected from wind turbines in three wind farms are used to evaluate the performance of the proposed method. Five evaluation metrics are applied for the comparative analysis. Compared with typical WTPC models, QRLF has better fitting performance in both deterministic and probabilistic power curve modeling.
Use of Ecofriendly Glass Powder Concrete in Construction of Wind Farms
Authors: García del Toro Eva M. , Alcala-Gonzalez Daniel , Más-López María Isabel , García-Salgado Sara , Pindado Santiago
Published: March 2021

Silicon is the main element in the composition of glass and it has been seen that it can be used as a partial replacement for cement in the manufacture of concrete. Different dosages of glass powder and cement were applied to manufacture the concrete mixes. Initially, the characteristics of fresh concrete were studied, such as consistency, air content, apparent density and workability. Secondly, compressive strength tests were performed on the different concrete mixtures produced. The consistency tests allowed us to classify these concretes within the group of fluids. The air content of these concretes increased with the rate of substitution of cement by glass powder, resulting in lighter concretes. Density tests showed that this parameter decreased as the rate of substitution of cement increased. A coefficient k has been calculated for the substitution of glass powder by cement in the binder, using the Bolomey formula. Also, a mathematical model has been proposed to further analyze the experimental data. Major contributions of this work were to study the possible application of this concrete in different dispersions as a surface protection layer against the action of corrosion, in wind turbine foundations as well as the stabilization of the wind farm roads.
The Investigation of Microstructure and Mechanical Behavior and the Fractographic Analysis of the Ti49.1Ni50.9 Alloy in States with Different Activation Deformation Volumes
Authors: Churakova Anna , Gunderov Dmitry , Kayumova Elina
Published: March 2021

In this article, the microstructure and mechanical behavior of the Ti49.1Ni50.9 alloy with a high content of nickel in a coarse-grained state, obtained by quenching, ultrafine-grained (obtained through the equal-channel angular pressing (ECAP) method) and nanocrystalline (high pressure torsion (HPT) + annealing), were investigated using mechanical tensile tests at different temperatures. Mechanical tests at different strain rates for determining the parameter of strain rate sensitivity m were carried out. Analysis of m showed that with an increase in the test temperature, an increase in this parameter was observed for all studied states. In addition, this parameter was higher in the ultrafine-grained state than in the coarse-grained state. The activation deformation volume in the ultrafine-grained state was 2–3 times greater than in the coarse-grained state at similar tensile temperatures. Fractographic analysis of samples after mechanical tests was carried out. An increase in the test temperature led to a change in the nature of fracture from quasi-brittle–brittle (with small pits) at room temperature to ductile (with clear dimples) at elevated temperatures. Microstructural studies were carried out after the tensile tests at different temperatures, showing that at elevated test temperatures, the matrix was depleted in nickel with the formation of martensite twins.