bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of Climate Change on Cassava Yield in Nigeria: An Autoregressive Distributed Lag Bound Approach
Authors: Anyaegbu Casmir Ndukaku , Okpara Kingsley Ezechukwu , Taweepreda Wirach , Akeju David , Techato Kuaanan , Onyeneke Robert Ugochukwu , Poshyachinda Saran , Pongpiachan Siwatt
Published: December 2022

Across the globe, climate change is threatening the environment, crop yield and food security. The key to ensuring a sustainable environment, crop yield increase and food security is to identify the long-term significant impact of climate change and the means of reducing the effect. This study examined the impacts of climate change on cassava yield in Nigeria. Data were sourced from the Climate Change Knowledge Portal and the Food and Agricultural Organization of the United Nations spanning from 1990 to 2019. The impact of climate change was analyzed using Autoregressive Distributed Lag Bound approach, Error Correction Model and Augmented Dickey–Fuller and Phillips–Perron tests for stationarity test. The model was subjected to diagnostic tests such as stability tests, normality tests, serial correlation tests and heteroscedasticity tests. With the exception of temperature, the study revealed that arable land, rainfall and greenhouse gases such as C2O, nitrous oxide and methane had a long-term significant impact on cassava yield in Nigeria. The study also noted that methane causes long-term significant damage to cassava yield more than any other greenhouse gas and climatic variables in the study. We recommended policies and programs that facilitate the uptake of climate-smart agriculture that centers on greenhouse gas emission reduction and on crop improvement research by breeding crop varieties that will be resilient to climate shocks.
Effect of Silicon on Oat Salinity Tolerance: Analysis of the Epigenetic and Physiological Response of Plants
Authors: Stadnik Barbara , Tobiasz-Salach Renata , Mazurek Marzena
Published: December 2022

Environmental conditions are the primary factor determining the growth and yield of plants. As a result of climate change, the negative impact of abiotic factors is intensifying. One of them is salt stress. Soil salinity is one of the major problems in agriculture in the world and affects many cultivar species. The aim of this study was to evaluate the effect of silicon foliar application on the physiological and epigenetic reaction of oats (Avena sativa L.) under salt stress. The pot experiment was carried out in controlled conditions. Oat plants were subject to sodium chloride (NaCl) at a concentration of 200 mM and applied to the soil. Three concentrations of Optysil (200 g∙L−1 SiO2) were used for foliar fertilization. Measurements were made of the relative chlorophyll content in the leaves, the selected chlorophyll fluorescence parameters, and the gas exchange parameters. In this study, methylation-sensitive amplification polymorphisms (MSAP) analysis was used to investigate the effect of Si application during salinity stress on the DNA methylation level in oat plants. The results of this study indicated that the exogenous application of silicon improved the tolerance of the oat plants to salinity. The doses of 0.1% and 0.2% Optysil had the greatest effect on alleviating the impact of salt stress on the oat plants. In this research, the epigenetic as well as the physiological response of plants to the applied experimental factors were analyzed, which is a broad coverage of the research topic on the effects of salinity and silicon on plants.
Drones in the Sky: Towards a More Sustainable Agriculture
Authors: Arza-García Marcos , Burgess Alexandra Jacquelyn
Published: December 2022

Nowadays, with an increasing world population, the production of bio-resources becomes a strategic sector for supporting any sustainable society [...]
Pest Rodents’ Responses to Rice Farming in Northern Peninsular Malaysia
Authors: Noor Hafidzi Mohd , Burhanuddin Maisarah , Salim Hasber , Asrif Nur Athirah , Jamian Syari , Azhar Badrul
Published: December 2022

Pest rodents significantly reduce crop yields globally each year, necessitating an efficient rodent management program. In small rice-producing nations like Malaysia, these rodents might lead to food insecurity, thus a science-based pest rodent management strategy is crucial. We attempted to identify the key habitat structure that affects rodent pest populations by investigating the relationships of rodent pest populations with farming practices, site-level habitat, and landscape characteristics. We found that rodent abundance in the rice fields was positively correlated with bund height and width. In addition, rice growing stages and planting seasons affected rodent abundance. However, rodent abundance was negatively related to the distance from active burrows to residential areas. As an alternative to chemical control, we suggest that trapping exercises with a covered trap should be conducted around active burrows located nearby residential areas, with high and wide bunds during early rice planting stages in the dry rice planting season.
Two Better Than One? Potential Effects of Intraguild Predation on the Biological Control of Ceratitis capitata (Diptera: Tephritidae) by the Parasitoid Aganaspis daci (Hymenoptera: Figitidae) and the Predator Pseudoophonus rufipes (Coleoptera: Carabidae)
Authors: de Pedro Luis , Beitia Francisco , Tormos José
Published: December 2022

The use of more than one species to manage a single insect pest is a common practice among biological control programs. However, the beneficial effects of natural enemies are not always additive, which in many cases may be attributed to interspecific interactions such as intraguild predation (IGP). Herein, we investigated the potential IGP between two relevant natural enemies of the Medfly (Ceratitis capitata), the predator Pseudoophonus rufipes and the parasitoid Aganaspis daci, as well as the possible implications of this phenomenon in their efficiency as biocontrol agents. To this end, we assessed their functional responses and different demographic parameters when acting alone and together against C. capitata under laboratory conditions. Coexistence led to a switch in the functional response of both species, from type III to type II in A. daci and the opposite in P. rufipes. Regarding demographic parameters, coexistence resulted in higher parasitoidism and population reduction by A. daci only at low host densities, probably due to competition pressure. In the same circumstances, P. rufipes reduced its predatory activity, rejecting those larvae that were presumably parasitized and causing negligible IGP. At high Medfly densities, A. daci efficiency decreased, and the reduced encounter probability enhanced the predatory activity by P. rufipes. As a result of these trends, Medfly population reduction reached almost 100% at all densities, which suggests an additive effect of both natural enemies and recommends combined releases of these agents as a strategy for the control of the Medfly.
Genome-Wide Identification and Analysis of the MAPK and MAPKK Gene Families in Potato (Solanum tuberosum L.)
Authors: Shang Yutong , Luo Xiaobo , Zhang Heng , Chen Mingjun , Yin Wang , Cao Zhenju , Deng Renju , Li Yan , Li Fei
Published: December 2022

Mitogen-activated protein kinase (MAPK) is an important component of the signal transduction pathway, which plays important roles in regulating plant growth and development, and abiotic stress. Potato (Solanum tuberosum L.) is one of the most popular tuber crops in the world. Genome-wide identification and analysis of the MAPK and MAPKK gene family in potato is not clear. A total of 20 MAPK genes and 8 MAPKK genes were identified in the potato genome. A conservative motif analysis showed that the MAPK protein contained a typical TxY phosphorylation site, and the MAPKK protein contained a conservative characteristic motif S/T-x5-S/T. Phylogenetic analysis showed that potato MAPK (mitogen-activated protein kinase) and MAPKK (mitogen-activated protein kinase kinase) were similar to Arabidopsis, including four groups of members A, B, C and D. Gene structure and promoter sequence analysis showed that all 28 gene family members of potato Solanum tuberosum MAPK (StMAPK) and StMAPKK have coding regions (CDS), and family members in the same group have similar intron and exon compositions, and that most cis-acting elements upstream of gene promoters elements have related to stress response. Chromosome location analysis found that MAPKs were unevenly distributed on 11 chromosomes, while MAPKKs were only distributed on chromosomes Chr. 03 and Chr. 12. Collinearity analysis showed that StMAPKK3 and StMAPKK6 have the same common ancestors among potato, pepper, and tomato. qRT-PCR results showed that the relative expressions of StMAPK14 and StMAPKK2 were significantly upregulated under low-temperature stress. These results could provide new insights into the characteristics and evolution of the StMAPK and StMAPKK gene family and facilitate further exploration of the molecular mechanism responsible for potato abiotic stress responses.
Estimation of Genetic Parameters for Conformation Traits and Milk Production Traits in Chinese Holsteins
Authors: Xue Xiaoshu , Hu Honghong , Zhang Junxing , Ma Yanfen , Han Liyun , Hao Feng , Jiang Yu , Ma Yun
Published: December 2022

The objective of this study was to explore the genetic parameters of conformation traits and milk production traits in Chinese Holstein cattle and to provide a reference for dairy cattle breeding. We collected the phenotypic data of 23 conformation traits and five milk production traits of Chinese Holsteins and used animal models to estimate the genetic parameters of conformation traits and milk production traits. The estimated heritability of conformation traits ranged from 0.11 (angularity) to 0.37 (heel depth) and the genetic correlation between conformation traits ranged from −0.73 (bone quality and rear leg-rear view) to 0.76 (chest width and loin strength). The heritability of milk production traits ranged from 0.23 (somatic cell score) to 0.50 (305-d milk yield). The estimated values of genetic correlation between conformation traits and milk production traits ranged from −0.56 (heel depth and 305-d milk yield) to 0.57 (udder texture and milk fat percentage). There was a positive genetic correlation between most conformation traits and milk fat percentage, but a weak negative genetic correlation with milk yield. Strengthening the moderately and highly heritable milk production and conformation traits, especially the selection of rear udder traits and body shape total score, will be beneficial in improving the performance of dairy cows.
Effects of the Dietary Inclusion of Allium mongolicum Regel Extract on Serum Index and Meat Quality in Small-Tailed Han Sheep
Authors: Zhao Yabo , Zhang Yanmei , Bai Chen , Ao Changjin , Qi Saruli , Cao Qina , Erdene Khas
Published: December 2022

The aim of this study was to evaluate the effects of Allium mongolicum Regel ethanol extract (AME) on the serum index and meat quality of lambs. A total of 30 male Small-tailed Han sheep (3 months old) with an average weight of 33.60 ± 1.23 kg were divided randomly into one of two groups: the control group (CON) was offered a basal diet, and the AME group was offered a basal diet with supplementation 2.8 g·lamb−1·day−1 AME. The trial lasted for 75 days. AME supplementation significantly decreased the concentration of triglyceride and total cholesterol (p < 0.05), and tended to lower the concentration of non-esterified fatty acids (0.05 < p < 0.1), but significantly increased the concentration of high-density lipoprotein, leptin, and insulin (p < 0.05) in the serum of lambs. AME also decreased cooking losses and shear force and increased the content of intramuscular fat in the longissimus dorsi (LD) muscle of lambs (p < 0.05). In addition, there was no difference in the composition of hydrolyzed protein amino acids in the LD muscle among treatments (p > 0.05). However, AME changed the composition of free amino acids and promoted MUFA and PUFA deposition in the LD muscle of the lambs. These findings indicate that a diet supplemented with AME may improve the lipid metabolic capacity and meat quality of lambs.
Administration of a Multi-Genus Synbiotic to Broilers: Effects on Gut Health, Microbial Composition and Performance
Authors: Prentza Zoi , Castellone Francesco , Legnardi Matteo , Antlinger Birgit , Segura-Wang Maia , Kefalas Giorgos , Papaioannou Nikolaos , Stylianaki Ioanna , Papatsiros Vasileios G. , Franzo Giovanni , Cecchinato Mattia , Koutoulis Konstantinos
Published: December 2022

In recent years, the applicability of prebiotics, probiotics and their mixtures, defined as synbiotics, in poultry production has received considerable attention. Following the increasing regulation of antibiotic use, these nutraceuticals are seen as an alternative way to sustain production efficiency and resistance to pathogens and stressors by modulating birds’ gut health. The aim of this study was to evaluate the benefits provided under field conditions by administering the multi-species synbiotic PoultryStar® sol to broilers in drinking water. To this purpose, three Ross 308 broiler flocks, representing separate progenies of a breeder flock which was treated with the same synbiotic, were housed in separate farms, divided into treatment and control groups, and followed throughout the productive cycle. Synbiotic administration was shown to improve gut health even in absence of a challenge, with limited changes in terms of macroscopic intestinal lesions and more overt differences related to histopathological scores and villi length. Synbiotic-fed chickens performed consistently better in terms of body weight gain, feed conversion ratio and survivability. Lastly, the evaluation of the caecal microbiome through next-generation sequencing highlighted the effects of synbiotic supplementation on the composition of the bacterial population, the implications of which will, however, require further studies to be better comprehended.
Size-Mediated Sea Turtle Behavioral Responses at Artificial Habitats in the Northern Gulf of Mexico
Authors: Siegfried Tabitha Renee , Reimer Jackson , Roberto Emma , Noren Christopher , Vidal Alex , Dixon Kristi , DuBois Morgan , Piacenza Susan E.
Published: December 2022

Our understanding of size-specific sea turtle behavior has lagged due to methodological limitations. However, stereo-video cameras (SVC) are an in-water approach that can link body-size and allow for relatively undisturbed behavioral observations. In this study, we conducted SVC dive surveys at local artificial reefs, piers, and jetties in the northern Gulf of Mexico (nGOM) from May 2019 to August 2021. Using SVCs, we measured sea turtle straight carapace length, documented behaviors, and quantified wariness by assessing minimum approach distance (MAD). In green sea turtles (Chelonia mydas), the observed MAD ranged from 0.72 to 5.99 m (mean 2.10 m ± 1.10 standard deviation (SD), n = 73). For loggerhead sea turtles (Caretta caretta), the MAD ranged between 0.93 and 3.80 m (mean 2.12 m ± 0.99 SD, n = 16). Kemp’s ridley sea turtles (Lepidochelys kempii) were similar to loggerheads, and MAD ranged from 0.78 to 3.63 m (mean 2.35 m ± 0.99 SD, n = 8). We then evaluated what biological factors could impact the MAD observed by species, but we excluded Kemp’s ridleys as the sample size was small. Using a linear mixed model and model selection based on AICc, the top ranked model for both green and loggerhead sea turtles included SCL as the most important factor influencing MAD. MAD did not vary with habitat type for either species. Our results showed that larger individuals, regardless of species, have a greater wariness response, becoming startled at greater distances than smaller individuals. The findings of our study support the use of SVC as an accessible, non-invasive tool to conduct ecologically relevant in-water surveys of sea turtles to link behavioral observations to body size.
A Cautionary Tale of Sexing by Methylation: Hybrid Bisulfite-Conversion Sequencing of Immunoprecipitated Methylated DNA in Chrysemys picta Turtles with Temperature-Dependent Sex Determination Reveals Contrasting Patterns of Somatic and Gonadal Methylation, but No Unobtrusive Sex Diagnostic
Authors: Mizoguchi Beatriz A. , Valenzuela Nicole
Published: December 2022

Background: The gonads of Chrysemys picta, a turtle with temperature-dependent sex determination (TSD), exhibit differential DNA methylation between males and females, but whether the same is true in somatic tissues remains unknown. Such differential DNA methylation in the soma would provide a non-lethal sex diagnostic for TSD turtle hatchings who lack visually detectable sexual dimorphism when young. Methods: Here, we tested multiple approaches to study DNA methylation in tail clips of Chrysemys picta hatchlings, to identify differentially methylated candidate regions/sites that could serve as molecular sex markers To detect global differential methylation in the tails we used methylation-sensitive ELISA, and to test for differential local methylation we developed a novel hybrid method by sequencing immunoprecipitated and bisulfite converted DNA (MeDIP-BS-seq) followed by PCR validation of candidate regions/sites after digestion with a methylation-sensitive restriction enzyme. Results: We detected no global differences in methylation between males and females via ELISA. While we detected inter-individual variation in DNA methylation in the tails, this variation was not sexually dimorphic, in contrast with hatchling gonads. Conclusions: Results highlight that differential DNA methylation is tissue-specific and plays a key role in gonadal formation (primary sexual development) and maintenance post-hatching, but not in the somatic tail tissue.
Isolation, Identification and Genetic Characterization of Antibiotic Resistant Escherichia coli from Frozen Chicken Meat Obtained from Supermarkets at Dhaka City in Bangladesh
Authors: Hossain Mridha. Md. Kamal , Islam Md. Sharifull , Uddin Md. Salah , Rahman A. T. M. Mijanur , Ud-Daula Asad , Islam Md. Ariful , Rubaya Rubaya , Bhuiya Anjuman Ara , Alim Md. Abdul , Jahan Nusrat , Li Jinquan , Alam Jahangir
Published: December 2022

Antimicrobials have been used to improve animal welfare, food security, and food safety that promote the emergence, selection, and dissemination of antimicrobial-resistant (AMR) bacteria. In this study, 50 E. coli were isolated from frozen chicken meat samples in Dhaka city. Antibiotic sensitivity patterns were assessed through the disk diffusion method and finally screened for the presence of antimicrobial resistance genes (ARG) using the polymerase chain reaction (PCR). Among the 160 samples, the prevalence of E. coli was observed in fifty samples (31.25%). All of these isolates were found resistant to at least one antimicrobial agent, and 52.0% of the isolates were resistant against 4–7 different antimicrobials. High resistance was shown to tetracycline (66.0%), followed by resistance to erythromycin (42.0%), ampicillin and streptomycin (38.0%), and sulfonamide (28.0%). In addition, the most prevalent ARGs were tet(A) (66.0%), ereA (64.0%), tet(B) (60.0%), aadA1 and sulI (56.0%), blaCITM (48.0%) and blaSHV (40.0%). About 90.0% of isolates were multidrug resistant. This study reveals for the first time the current situation of E. coli AMR in broilers, which is helpful for the clinical control of disease as well as for the development of policies and guidelines to reduce AMR in broilers production in Bangladesh.
Increasing Consumption of Antibiotics during the COVID-19 Pandemic: Implications for Patient Health and Emerging Anti-Microbial Resistance
Authors: Malik Shahana Seher , Mundra Sunil
Published: December 2022

The emergence of COVID-19 infection led to the indiscriminate use of antimicrobials without knowing their efficacy in treating the disease. The gratuitous use of antibiotics for COVID-19 treatment raises concerns about the emergence of antimicrobial resistance (AMR). In this systematic review, we performed a thorough systematic search using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines of scientific databases (Scopus, Web of Science, and PubMed) to identify studies where antibiotics were prescribed to treat COVID-19 (December 2019 to December 2021). Of 970 identified studies, 130 were included in our analyses. Almost 78% of COVID-19 patients have been prescribed an antibiotic. Cephalosporins were the most prescribed (30.1% of patients) antibiotics, followed by azithromycin (26% of patients). Antibiotics were prescribed for COVID-19 patients regardless of reported severity; the overall rate of antibiotic use was similar when comparing patients with a severe or critical illness (77.4%) and patients with mild or moderate illness (76.8%). Secondary infections were mentioned in only 11 studies. We conclude that concerns related to COVID-19 and the lack of treatment strategy led to the overuse of antibiotics without proper clinical rationale. Based on our findings, we propose that antimicrobial stewardship should be retained as a priority while treating viral pandemics.
Functional Characterization of Sugar Beet M14 Antioxidant Enzymes in Plant Salt Stress Tolerance
Authors: Li Jinna , Yu Bing , Ma Chunquan , Li Hongli , Jiang Desheng , Nan Jingdong , Xu Meng , Liu He , Chen Sixue , Duanmu Huizi , Li Haiying
Published: December 2022

Salt stress can cause cellular dehydration, which induces oxidative stress by increasing the production of reactive oxygen species (ROS) in plants. They may play signaling roles and cause structural damages to the cells. To overcome the negative impacts, the plant ROS scavenging system plays a vital role in maintaining the cellular redox homeostasis. The special sugar beet apomictic monosomic additional M14 line (BvM14) showed strong salt stress tolerance. Comparative proteomics revealed that six antioxidant enzymes (glycolate oxidase (GOX), peroxiredoxin (PrxR), thioredoxin (Trx), ascorbate peroxidase (APX), monodehydroascorbate reductase (MDHAR), and dehydroascorbate reductase3 (DHAR3)) in BvM14 were responsive to salt stress. In this work, the full-length cDNAs of genes encoding these enzymes in the redox system were cloned from the BvM14. Ectopic expression of the six genes reduced the oxidative damage of transgenic plants by regulating the contents of hydrogen peroxide (H2O2), malondialdehyde (MDA), ascorbic acid (AsA), and glutathione (GSH), and thus enhanced the tolerance of transgenic plants to salt stress. This work has charecterized the roles that the antioxidant enzymes play in the BvM14 response to salt stress and provided useful genetic resources for engineering and marker-based breeding of crops that are sensitive to salt stress.
Caffeic Acid Phenethyl Ester Loaded PEG–PLGA Nanoparticles Enhance Wound Healing in Diabetic Rats
Authors: Nasrullah Mohammed Z.
Published: December 2022

Delayed wound healing is a serious complication of diabetes and a main reason for foot amputation. Caffeic acid phenethyl ester (CAPE) is a main active constituent of honeybee propolis with reported appealing pharmacological activities. In the current study, CAPE was loaded onto PEG–PLGA nanoparticles and showed a particle size of 198 ± 7.3 nm and polydispersity index of 0.43 ± 0.04. An in vivo study was performed to appraise the wound-healing activity of CAPE-loaded PEG–PLGA nanoparticles (CAPE-NPs) in diabetic rats. Wound closure was significantly accelerated in rats treated with CAPE-NPs. This was confirmed via histological examinations of skin tissues that indicated expedited healing and enhanced collagen deposition. This was accompanied by observed antioxidant activity as evidenced by the prevention of lipid peroxidation and the exhaustion of superoxide dismutase (SOD) and catalase (CAT) activities. In addition, CAPE-NPs showed superior anti-inflammatory activity as compared with the regular formula of CAPE, as they prevented the expression of interleukin-6 (IL-6) as well as tumor necrosis-alpha (TNF-α). The pro-collagen actions of CAPE-NPs were highlighted by the enhanced hyroxyproline content and up-regulation of Col 1A1 mRNA expression. Furthermore, the immunohistochemial assessment of skin tissues indicated that CAPE-NPs enhance proliferation and angiogenesis, as shown by the increased expression of transforming growth factor β1 (TGF-β1) and platelet-derived growth factor subunit B (PDGF-B). In conclusion, CAPE-loaded PEG–PLGA nanoparticles possess potent healing effects in diabetic wounds. This is mediated, at least partially, by its antioxidant, anti-inflammatory, and pro-collagen as well as angiogenic activities.
Anomaly Detection of Consumption in Hotel Units: A Case Study Comparing Isolation Forest and Variational Autoencoder Algorithms
Authors: Mendes Tomás , Cardoso Pedro J. S. , Monteiro Jânio , Raposo João
Published: December 2022

Buildings are responsible for a high percentage of global energy consumption, and thus, the improvement of their efficiency can positively impact not only the costs to the companies they house, but also at a global level. One way to reduce that impact is to constantly monitor the consumption levels of these buildings and to quickly act when unjustified levels are detected. Currently, a variety of sensor networks can be deployed to constantly monitor many variables associated with these buildings, including distinct types of meters, air temperature, solar radiation, etc. However, as consumption is highly dependent on occupancy and environmental variables, the identification of anomalous consumption levels is a challenging task. This study focuses on the implementation of an intelligent system, capable of performing the early detection of anomalous sequences of values in consumption time series applied to distinct hotel unit meters. The development of the system was performed in several steps, which resulted in the implementation of several modules. An initial (i) Exploratory Data Analysis (EDA) phase was made to analyze the data, including the consumption datasets of electricity, water, and gas, obtained over several years. The results of the EDA were used to implement a (ii) data correction module, capable of dealing with the transmission losses and erroneous values identified during the EDA’s phase. Then, a (iii) comparative study was performed between a machine learning (ML) algorithm and a deep learning (DL) one, respectively, the isolation forest (IF) and a variational autoencoder (VAE). The study was made, taking into consideration a (iv) proposed performance metric for anomaly detection algorithms in unsupervised time series, also considering computational requirements and adaptability to different types of data. (v) The results show that the IF algorithm is a better solution for the presented problem, since it is easily adaptable to different sources of data, to different combinations of features, and has lower computational complexity. This allows its deployment without major computational requirements, high knowledge, and data history, whilst also being less prone to problems with missing data. As a global outcome, an architecture of a platform is proposed that encompasses the mentioned modules. The platform represents a running system, performing continuous detection and quickly alerting hotel managers about possible anomalous consumption levels, allowing them to take more timely measures to investigate and solve the associated causes.
The Effect of Ethanol Propolis Extracts on Inhibition of Growth of Fusarium solani on Hen Eggs
Authors: Gniewosz Małgorzata , Pobiega Katarzyna , Olbryś Natalia , Kraśniewska Karolina , Synowiec Alicja
Published: December 2022

The inhibition of growth of Fusarium solani mold on the shells of coated table hen eggs of a ethanol extract of propolis was investigated. Hen eggs were inoculated with F. solani spores and then coated with propolis extract at a concentration of 1, 2, 3, 5 or 10% using the spray method. Hen eggs were stored at room temperature for 28 days. Weight loss and the color of coated hen eggs were checked during storage. The color of hen eggs was tested using the CIELab method. Propolis extract was found to inhibit the growth of F. solani on hen eggshells. A reduction of three log cycles in the number of molds was observed on hen eggs coated with 10% propolis extract. Coating hen eggs with propolis extract slowed down and limited weight loss. No statistically significant changes in color parameters or sensory characteristics were observed during storage of hen eggs. There was a slight smell of propolis on the shells of hen eggs. Spraying table hen eggs with propolis extract at a concentration of 10% can help to improve the microbiological safety of hen eggs in terms of anti-mold protection.
Photomechanical Solid Polymers: Model for Pressure and Strain Induced by Photoisomerization and Photo-Orientation
Authors: Sekkat Zouheir
Published: December 2022

Photoactive polymers are important for fundamental studies and applications in several area of photonics such as data storage and holography and nonlinear optics and photomechanics. The latter is perhaps one of the most important applications of such materials, since they act as light to mechanical energy transducers and move under light action. For example, azo-polymers irradiated by inhomogeneous resonant ultra-violet or visible light undergo molecular and macroscopic motion, at sub-glass transition temperatures by photoisomerization of the azo dyes. Our recent research in this field highlighted the fundamentals of mobility enhancement by light, including light-induced viscosity change and acceleration of relaxation times, and photomechanics, encompassing motions in gradients of actinic light leading to surface structuring and actuation. In this paper, we present an original model which predicts the creation of mechanical pressure, i.e., motion, by a photo-induced change in the occupied volume and length of anisometric isomers, and we give simple analytical expressions describing the dynamics of volume as well as strain change upon polarized light irradiation of photomechanic samples.
Combustion and Fluid Mechanics, Advance in Fire Safety Science, Volume 1
Authors: Rogaume Thomas , Batiot Benjamin
Published: December 2022

Fires remain a major risk with dramatic impacts on humans, buildings, structures, the environment, the economy, etc [...]
Automatic Speech Recognition for Uyghur, Kazakh, and Kyrgyz: An Overview
Authors: Du Wenqiang , Maimaitiyiming Yikeremu , Nijat Mewlude , Li Lantian , Hamdulla Askar , Wang Dong
Published: December 2022

With the emergence of deep learning, the performance of automatic speech recognition (ASR) systems has remarkably improved. Especially for resource-rich languages such as English and Chinese, commercial usage has been made feasible in a wide range of applications. However, most languages are low-resource languages, presenting three main difficulties for the development of ASR systems: (1) the scarcity of the data; (2) the uncertainty in the writing and pronunciation; (3) the individuality of each language. Uyghur, Kazakh, and Kyrgyz as examples are all low-resource languages, involving clear geographical variation in their pronunciation, and each language possesses its own unique acoustic properties and phonological rules. On the other hand, they all belong to the Altaic language family of the Altaic branch, so they share many commonalities. This paper presents an overview of speech recognition techniques developed for Uyghur, Kazakh, and Kyrgyz, with the purposes of (1) highlighting the techniques that are specifically effective for each language and generally effective for all of them and (2) discovering the important factors in promoting the speech recognition research of low-resource languages, by a comparative study of the development path of these three neighboring languages.
An Assistant System for Translation Flipped Classroom
Authors: Chen Jingxian , Li Feng , Zhang Xuejun , Li Bin
Published: December 2022

To achieve the goal of training translators that meet the current social needs, the innovation of translation teaching methods is necessary. Studies have proven that students in flipped classrooms (FCs) have greater performance than students in traditional classrooms. However, the preparation time for FCs could be three times higher than that of traditional classrooms, which leads to the reluctance of teachers to conduct FCs. Machine translation (MT) is believed to be a useful tool to improve the translation efficiency of human translators. However, in practice, teachers found that many students cannot work with MT effectively. To solve the above problems, this paper designs a Translation Flipped Classroom Assistance System (TFCAS) based on cloud computing and MT. A parameter is proposed to measure students’ ability to translate evaluation. TFCAS has reduced the burden of teachers in the FC mode and helped students become accustomed to working with MT. Application data stored in the MySQL database, such as sentence pairs, will be used to optimize the neural machine translation model we developed for the system. The system makes MT and the training of translators support each other’s sustainable development and conforms to the trend of deepening teaching reform.
Optimization on Linkage System for Vehicle Wipers by the Method of Differential Evolution
Authors: Chen Tsai-Jung , Hong Ying-Ji , Lin Chia-Han , Wang Jing-Yuan
Published: December 2022

We consider an optimization problem on the maximal magnitude of angular acceleration of the output-links of a commercially available center-driven linkage system (CDLS) for vehicle wipers on windshield. The purpose of this optimization is to improve the steadiness of a linkage system without weakening its normal function. Thus this optimization problem is considered under the assumptions that the frame of the fixed links of linkage system is unchanged and that the input-link rotates at the same constant angular speed with its length unchanged. To meet the usual requirements for vehicle wipers on windshield, this optimization problem must be solved subject to 10 specific constraints. We expect that optimizing the maximal magnitude of angular acceleration of the output-links of a linkage system would also be helpful for reducing the amplitudes of sound waves of wiper noise. We establish the motion model of CDLS and then justify this model with ADAMS. We use a “Differential Evolution” type method to search for the minimum of an objective function subject to 10 constraints for this optimization problem. Our optimization computation shows that the maximal magnitude of angular acceleration of both output-links of this linkage system can be reduced by more than 10%.
Experimentally Validated Analytical Solutions to Homogeneous Problems of Electrical Impedance Tomography (EIT) on Rectangular Cement-Based Materials
Authors: Yoon Seyoon , Jeon Dongho , Oh Jae-Eun , Kim Min-Kyoung , Kim Dong-Joo
Published: December 2022

Diagnostic technologies using X-rays and/or acoustic emissions for concrete infrastructures containing internal pores, defects, and cracks have attracted considerable interest. However, computerized tomography (CT) for concrete is challenging due to its radiation shielding characteristics. Electrical impedance tomography (EIT), initially developed for medical use, has recently shown a potential for developing a macro-CT technique for concrete structures. This study derived EIT analytical solutions for rectangular cement-based samples and validated them with experimental data obtained from cubic mortar samples. The experimental validation of the three mathematical functions (Dirac delta, Heaviside step, and Gaussian) used as current injection models, the Gaussian function produced the lowest relative absolute error (4.02%). This study also explored appropriate experimental setups for cement-based materials, such as Shunt model, current flow paths, and potential distribution.
Special Issue on Application of Image Processing in Medicine
Authors: Koprowski Robert , Wilczyński Sławomir , Lanza Michele
Published: December 2022

The title and theme of this Special Issue “Application of Image Processing in Medicine” is currently very popular, topical, and important [...]
Review of the Research on Soil Disturbance by Tools
Authors: Wang Xinzhong , Fang Weiquan , Han Dianlei , Chen Xuegeng
Published: December 2022

The discrete element method can be used to analyze the interaction between tools and soil. It can be used to guide the optimal design of tools, but the appropriate simulation and test method selected is important to achieve the goal. This paper mainly introduces the disturbance of soil by tillage tools. The disturbance of the soil by tools include soil loosening, soil movement, and soil mixing. The disturbance contour is used to visually display the disturbance results, and the cross-sectional area, lateral soil throwing amount, ditch ridge height, ditch width, and ditch backfill are used to characterize the cross-sectional shape. Tracers are usually used to track soil particles to visually display the particle movement path during disturbance; this can be used to study the soil disturbance trend by the tools. When parameters and models are appropriate, the movement and contact of microscopic soil particles can be accurately simulated. By comparing the particle behavior of simulation and experiment, the contact model and contact parameters can be verified. The method introduced provides a reference for the optimal design of the tools and the research of disturbance by the tools.
Short Text Clustering Algorithms, Application and Challenges: A Survey
Authors: Ahmed Majid Hameed , Tiun Sabrina , Omar Nazlia , Sani Nor Samsiah
Published: December 2022

The number of online documents has rapidly grown, and with the expansion of the Web, document analysis, or text analysis, has become an essential task for preparing, storing, visualizing and mining documents. The texts generated daily on social media platforms such as Twitter, Instagram and Facebook are vast and unstructured. Most of these generated texts come in the form of short text and need special analysis because short text suffers from lack of information and sparsity. Thus, this topic has attracted growing attention from researchers in the data storing and processing community for knowledge discovery. Short text clustering (STC) has become a critical task for automatically grouping various unlabelled texts into meaningful clusters. STC is a necessary step in many applications, including Twitter personalization, sentiment analysis, spam filtering, customer reviews and many other social network-related applications. In the last few years, the natural-language-processing research community has concentrated on STC and attempted to overcome the problems of sparseness, dimensionality, and lack of information. We comprehensively review various STC approaches proposed in the literature. Providing insights into the technological component should assist researchers in identifying the possibilities and challenges facing STC. To gain such insights, we review various literature, journals, and academic papers focusing on STC techniques. The contents of this study are prepared by reviewing, analysing and summarizing diverse types of journals and scholarly articles with a focus on the STC techniques from five authoritative databases: IEEE Xplore, Web of Science, Science Direct, Scopus and Google Scholar. This study focuses on STC techniques: text clustering, challenges to short texts, pre-processing, document representation, dimensionality reduction, similarity measurement of short text and evaluation.
Effects of Imperfect Assembly and Magnetic Properties on the Three-Pole AMB System
Authors: Chen Shyh-Leh , Li Yi-Tsung , Lin Chin-Hsiang , Chen Chao-Yun
Published: December 2022

This study is concerned with a three-pole active magnetic bearing (AMB) system with assembly error and non-uniform flux distribution. The assembly error, which is the result of the misalignment of the back-up bearing and the stator of AMB, induces strong nonlinear uncertainty in the AMB dynamics. The non-uniform flux distribution, which is mainly due to non-uniform material properties, manufacturing errors, etc., makes the magnetic force model more complicated. A stable-levitation controller is designed in consideration of the above factors. The controller is designed using the method of feedback linearization and integral sliding mode control (ISMC). Both simulation and experimental results indicate that the rotor can be levitated to the center of the back-up bearing, verifying the effectiveness of the proposed stable-levitation controller.
Experiments and Fluent–Engineering Discrete Element Method-Based Numerical Analysis of Block Motion in Underwater Rock-Plug Blasting
Authors: Wu Liang , Liang Zhijian , Chen Ming , Zhou Junru
Published: December 2022

Underwater rock-plug blasting is a special blasting technique for excavating underwater inlets. In the process of rock-plug blasting excavation, the blasting-block movement from the difference in water pressure inside and outside the tunnel is one of the key factors for successful construction. Laboratory underwater rock-plug blasting experiments were conducted using small explosive charges, and a high-speed camera was adopted to observe and study block motion. Then, numerical simulations were conducted for the model experiment based on the Fluent and Engineering Discrete Element Method (EDEM) coupling program developed using the user-defined function (UDF) interface to reveal the mechanism underpinning the penetration of underwater rock-plug blasting. The results showed that the process of block motion in underwater rock-plug blasting can be divided into two stages. In the first stage, broken blocks move to two sides along the axis of the rock plug under the blast load. A blasting crater is formed on the downstream end face of the rock plug under the effects of the free face, while the upstream end face is loosened, or blocks are ejected under the influence of the water pressure. In the second stage, blocks flow to the broken-rock pit under the effects of water scouring and gravity, and, finally, the rock plug is penetrated. The larger the head of water and the opening angle of the rock plug are, the better the penetration effect for the rock plug is. The Fluent–EDEM coupling algorithm was in good agreement with the experimental results in terms of the rock-plug blasting effect and the velocity curve of the blocks, indicating that the coupling method had a favorable effect in simulating the interaction of blocks and water during underwater rock-plug blasting. The findings are expected to promote the application and popularization of the rock-plug blasting technique and can provide a reference for rock-plug blasting in water-intake and water-diversion projects.
A Novel Strategy for Automatic Mode Pairing on the Model Updating of Railway Systems with Nonproportional Damping
Authors: Ribeiro Diogo , Bragança Cássio , Brehm Maik , Zabel Volkmar , Calçada Rui
Published: December 2022

Mode pairing is a crucial step for the stability of any model-updating strategy based on experimental modal parameters. Automatically establishing a stable and assertive correspondence between numerical and experimental modes, in many cases, proves to be a very challenging task, especially in situations where complex mode shapes are present. This article presents a novel formulation for the automatic mode pairing between experimental and numerical complex modes based on an Energy-based Modal Assurance Criterion (EMAC). The efficiency of the proposed criterion was demonstrated on the basis of a case study involving the pairing between numerical and experimental modes of a passenger railway vehicle. A highly complex detailed FE numerical model of the vehicle was developed involving the modeling of the carbody, bogies and axles. A numerical damped modal analysis allowed obtaining the main global rigid-body and flexural modes of the vehicle’s carbody, as well as several local modes associated to the vibration of specific components of the carbody. Due to the localized damping provided by the suspensions, these modes presented complex modal ordinates, especially for the rigid-body modes. The comparison between the results obtained from the application of the EMAC and the classical MAC criteria, on the pairing of five global mode shapes, proved that the EMAC criterion is much more assertive, avoiding mismatches between the experimental global modes and some of the local numerical modes with similar configurations, and, consequently, establishing the correct correspondences between experimental and numerical modes.
GPU-Accelerated Infill Criterion for Multi-Objective Efficient Global Optimization Algorithm and Its Applications
Authors: Xu Shengguan , Zhang Jiale , Chen Hongquan , Gao Yisheng , Gao Yunkun , Gao Huanqin , Jia Xuesong
Published: December 2022

In this work, a novel multi-objective efficient global optimization (EGO) algorithm, namely GMOEGO, is presented by proposing an approach of available threads’ multi-objective infill criterion. The work applies the outstanding hypervolume-based expected improvement criterion to enhance the Pareto solutions in view of the accuracy and their distribution on the Pareto front, and the values of sophisticated hypervolume improvement (HVI) are technically approximated by counting the Monte Carlo sampling points under the modern GPU (graphics processing unit) architecture. As compared with traditional methods, such as slice-based hypervolume integration, the programing complexity of the present approach is greatly reduced due to such counting-like simple operations. That is, the calculation of the sophisticated HVI, which has proven to be the most time-consuming part with many objectives, can be light in programed implementation. Meanwhile, the time consumption of massive computing associated with such Monte Carlo-based HVI approximation (MCHVI) is greatly alleviated by parallelizing in the GPU. A set of mathematical function cases and a real engineering airfoil shape optimization problem that appeared in the literature are taken to validate the proposed approach. All the results show that, less time-consuming, up to around 13.734 times the speedup is achieved when appropriate Pareto solutions are captured.
DPG-LSTM: An Enhanced LSTM Framework for Sentiment Analysis in Social Media Text Based on Dependency Parsing and GCN
Authors: Yin Zeyu , Shao Jinsong , Hussain Muhammad Jawad , Hao Yajie , Chen Yu , Zhang Xuefeng , Wang Li
Published: December 2022

Sentiment analysis based on social media text is found to be essential for multiple applications such as project design, measuring customer satisfaction, and monitoring brand reputation. Deep learning models that automatically learn semantic and syntactic information have recently proved effective in sentiment analysis. Despite earlier studies’ good performance, these methods lack syntactic information to guide feature development for contextual semantic linkages in social media text. In this paper, we introduce an enhanced LSTM-based on dependency parsing and a graph convolutional network (DPG-LSTM) for sentiment analysis. Our research aims to investigate the importance of syntactic information in the task of social media emotional processing. To fully utilize the semantic information of social media, we adopt a hybrid attention mechanism that combines dependency parsing to capture semantic contextual information. The hybrid attention mechanism redistributes higher attention scores to words with higher dependencies generated by dependency parsing. To validate the performance of the DPG-LSTM from different perspectives, experiments have been conducted on three tweet sentiment classification datasets, sentiment140, airline reviews, and self-driving car reviews with 1,604,510 tweets. The experimental results show that the proposed DPG-LSTM model outperforms the state-of-the-art model by 2.1% recall scores, 1.4% precision scores, and 1.8% F1 scores on sentiment140.