bluuebunny/crossref_metadata_2025 huggingface dataset:
COVID-19 vaccination and psychological status of Iranian dental students
Authors: Ghadirian Hannaneh , Khami Mohammad Reza , Tabatabaei Seyyedeh Niloufar , mirhashemi Amir Hossein , Bahrami Rashin
Published: September 2022

Objective

The purpose of the present study was to investigate the association of COVID-19 vaccination with the quality and quantity of sleep, the level of stress, and temporomandibular joint (TMJ) disorders (TMDs) in Iranian dental students.

Materials and methods

In this cross-sectional research, we applied a questionnaire including 30 questions on the Perceived Stress Scale (PSS), sleep quality and quantity, Diagnostic Criteria for Temporomandibular Disorders (DC/TMD), and vaccination status. All vaccinated students of the dental schools located in the city of Tehran were invited to participate in the study. Participants were divided into three groups: those vaccinated for less than a month, those vaccinated for 1–3 months, and those vaccinated for more than 3 months. A paired t-test served for statistical analysis.

Results

Overall, 171 out of 235 students (72.77%) completed the questionnaire, among which 90 individuals were fully vaccinated, and were included in the data analysis. Stress levels decreased (mean difference = −1.23, p-value = 0.002) and sleep quality and quantity improved mostly 1–3 months after the vaccination (mean difference = −0.5, p-value = 0.016). However, TMD symptoms were mostly alleviated in people vaccinated for more than 3 months (mean difference = −2.86, p-value <0.05). In this respect, no significant difference was observed between the two genders.

Conclusion

According to the results of the study, vaccination was associated with the improvement of psychological consequences of the COVID-19 pandemic. It is recommended that further longitudinal studies be conducted on larger sample sizes and different age groups by using various data collection methods (especially regarding the assessment of TMD).
Does sleep disturbance predicts posttraumatic stress disorder and depression among college students during COVID-19 lockdown? A longitudinal survey
Authors: Wang Dongfang , Zhao Jingbo , Zhai Shuyi , Ye Haoxian , Bu Luowei , Fan Fang
Published: September 2022

Aim

To examine the cross-sectional and longitudinal associations between self-reported sleep disturbances, posttraumatic stress disorder (PTSD) and depression in a large cohort of Chinese adolescents experiencing the COVID-19 pandemic.

Methods

Participants were 67905 Chinese college students in the two-wave longitudinal web-based survey during early COVID-19 outbreak (Time1, T1: Feb 3rd to 10th, 2020) and initial remission period (Time2, T2: March 24th to April 3rd, 2020). The Youth Self Rating Insomnia Scale (YSIS), 6-Item Impact of Event Scale (IES-6), and 9-Item Patient Heath Questionnaire (PHQ-9) were used to assess adolescents' sleep, PTSD, and depressive symptoms, respectively, at T1 and T2.

Results

Self-reported PTSD and depression prevalence at T1 were 34.6% and 21.6% respectively. While depressive symptoms worsened as the lockdown time increased, while PTSD symptoms decreased. After adjusting for confounding factors, sleep disturbance and sleep deprivation at T1 were significantly associated with increased PTSD and depressive symptoms at T2. Furthermore, sleep disturbance and sleep deprivation also predicted the new onset and persistence of PTSD and depression.

Conclusion

Sleep disturbance predicts the development and persistence of PTSD and depression. Early assessment and treatment of sleep disturbance may be an important strategy for prevention and intervention of PTSD and depression in adolescents after experiencing the special public health emergency.
Adapted digital health literacy and health information seeking behavior among lower income groups in Malaysia during the COVID-19 pandemic
Authors: Marzo Roy Rillera , Chen Hana W. Jun , Abid Khadijah , Chauhan Shekhar , Kaggwa Mark Mohan , Essar Mohammad Yasir , Jayaram Jacynta , Changmai Manah Chandra , Wahab Mohamad Khairuddin bin Adbul , Ariffin Indang Ariati Binti , Alwi Muhammad Najib Bin Mohamad , Head Michael G. , Lin Yulan
Published: September 2022

Background

Misinformation has had a negative impact upon the global COVID-19 vaccination program. High-income and middle-income earners typically have better access to technology and health facilities than those in lower-income groups. This creates a rich-poor divide in Digital Health Literacy (DHL), where low-income earners have low DHL resulting in higher COVID-19 vaccine hesitancy. Therefore, this cross-sectional study was undertaken to assess the impact of health information seeking behavior on digital health literacy related to COVID-19 among low-income earners in Selangor, Malaysia.

Methods

A quantitative cross-sectional study was conducted conveniently among 381 individuals from the low-income group in Selangor, Malaysia. The remote data collection (RDC) method was used to gather data. Validated interviewer-rated questionnaires were used to collect data via phone call. Respondents included in the study were 18 years and older. A normality of numerical variables were assessed using Shapiro-Wilk test. Univariate analysis of all variables was performed, and results were presented as means, mean ranks, frequencies, and percentages. Mann-Whitney U test or Kruskal Wallis H test was applied for the comparison of DHL and health information seeking behavior with characteristics of the participants. Multivariate linear regression models were applied using DHL as dependent variable and health information seeking behavior as independent factors, adjusting for age, gender, marital status, educational status, employment status, and household income.

Results

The mean age of the study participants was 38.16 ± 14.40 years ranging from 18 to 84 years. The vast majority (94.6%) of participants stated that information seeking regarding COVID-19 was easy or very easy. Around 7 percent of the respondents cited reading information about COVID-19 on the internet as very difficult. The higher mean rank of DHL search, content, reliability, relevance, and privacy was found among participants who were widowed, had primary education, or unemployed. An inverse relationship was found between overall DHL and confidence in the accuracy of the information on the internet regarding COVID-19 (β = −2.01, 95% CI = −2.22 to −1.79).

Conclusion

It is important to provide support to lower-income demographics to assist access to high-quality health information, including less educated, unemployed, and widowed populations. This can improve overall DHL.
Thermal pain and detection threshold modulation in augmented reality
Authors: Eckhoff Daniel , Sandor Christian , Cheing Gladys L. Y. , Schnupp Jan , Cassinelli Alvaro
Published: September 2022

Augmented Reality (AR) overlays computer-generated visual, auditory or other sensory information onto the real world. Due to recent technological advancement in the field, it can become increasingly difficult for the user to differentiate between sensory information coming from real and virtual objects, leading to interesting perceptual phenomena. For example, an AR experience in which users can experience their own hands in flames has been shown to elicit heat illusions on the affected hands. In this study, we investigate the potential that AR has for top-down modulation of pain and thermal perception. We assessed thermal pain and detection thresholds on the participant’s right hand while covering it with realistic virtual flames. We compared this experience to a baseline condition with no additional stimuli. We also report on a condition in which the hand is covered by a blue fluid not instantly associated with fire. We found that experiencing a virtual burning hand induces analgesic as well hyperalgesic effects as participants begin to feel heat related pain at lower temperatures and cold related pain at higher temperatures. The experience also impacts significantly on the lowest temperature at which participants starts perceiving warmth. The blue fluid do not affect the thresholds corresponding to the baseline condition. Our research thus confirms previous experiments showing that pain and thermal perception can be manipulated by by AR, while providing quantitative results on the magnitude of this effect.
Identifying hotspots of hydro-hazards under global change: A worldwide review
Authors: Beevers Lindsay , Popescu Ioana , Pregnolato Maria , Liu Yuexiao , Wright Nigel
Published: September 2022

Hydrological hazards (“hydro-hazards”) are defined as extreme events associated with the occurrence, movement and distribution of water, specifically resulting in floods and droughts. As a result of global climate change these hazards are expected to change in the future, with areas of the globe becoming “hotspots” for the intensification of these extremes. This paper is the first global review of the state- of-the-art research on hotspots for floods and drought. The work follows a systematic literature review of published research, and analyses and categorizes the results of 122 published papers after a methodical screening process. The analysis highlighted the geographical areas where increasing hazards are anticipated (e.g., Europe for both floods and droughts), and those areas of the globe where no significant research has been published (e.g., Russia). The methods used to undertake the research are analyzed and new trends identified. Potential avenues for future research are highlighted, including the incorporation of uncertainty analyses into hydro-hazard assessments, the consideration of multi-hazards and their interconnections, and finally the consideration of dynamic vulnerability and exposure in conjunction with changing hydro-hazards to understanding future risk.
Lou Gehrig’s Disease: Amyotrophic Lateral Sclerosis
Authors: Joyce Emily E. , González-Hijón Juan , Chourpiliadis Charilaos , Lovik Anikó , Seitz Christina , Cui Can , Sun Jiangwei , Hu Yihan , Pan Lu , Andersson John
Published: September 2022

Have you ever heard about amyotrophic lateral sclerosis (ALS)? ALS, also called Lou Gehrig’s disease, is a disease that results in muscle weakness and paralysis caused by the death of nerve cells. ALS is a rare disease—approximately 60,000–380,000 people are diagnosed with ALS each year all over the world. ALS is considered an age-associated disease, as symptoms usually appear after age 50. Despite being studied for the last 100 years, the causes of ALS remain unknown, and there is still no effective treatment or cure. ALS symptoms worsen quickly, and affected individuals become entirely dependent on caretakers. People with ALS typically die within 1–3 years following diagnosis. Awareness campaigns like the Ice Bucket Challenge can raise interest in ALS and money for studying—and hopefully one day curing—this rare and terrible disease.
A Fluorescent Alcohol Biosensor Using a Simple microPAD Based Detection Scheme
Authors: Thungon Phurpa Dema , Wang Hui , Vagin Sergei I. , Dyck Colin Van , Goswami Pranab , Rieger B. , Meldrum Alkiviathes
Published: September 2022

A paper-based microfluidic detection device for the detection of ethanol is demonstrated in this work. The method is based on a fluorophore consisting of short-chain conjugated molecular unit susceptible to the protonation of its terminal pyridine groups, along with a carboxyl-functionalized sidechain that acts as a binder and renders it water-soluble. The resulting fluorescent paper device yields large fluorescence changes when exposed to reactions that yield H2O2 in aqueous solutions. Using an enzyme-catalyzed rection that produces H2O2 from ethanol, we developed a two-zone, cut-out paper device containing a reaction zone in which the ethanol-containing analyte is placed, and an adjacent sensor zone where we observe a fluorescence color shift proportional to the ethanol concentration. The limit of detection of the fluidic ethanol biosensor was 0.05 v/v% and the dynamic range was 0.05–2 v/v%. This method was employed to detect the alcohol concentration of consumer vodkas using only a paper sensor and a smartphone camera.
The high resistance loop (H-loop) technique used for all-inside arthroscopic knotless suprapectoral biceps tenodesis: A case series
Authors: Zhou Min , Zhou Chuanhai , Cui Dedong , Long Yi , Guo Jiang , Zheng Zhenze , Meng Ke , Zhang Jinming , Hou Jingyi , Yang Rui
Published: September 2022

Introduction

Suprapectoral tenodesis is a common technique for the treatment of long head biceps tendon lesions. However, so far, there is no gold standard treatment in all-inside arthroscopy. The purpose of the present study was to introduce and evaluate the functional outcomes of an innovative, all-inside arthroscopic high resistance loop (H-loop, high resistance to tissue cutout and 360° grasping of the tendon) technique for long head of biceps (LHB) tenodesis.

Method

From September 2020 to March 2022, a series of cases of 32 consecutive patients (28 rotator cuff tear with LHBT pathology and 4 superior labrum anterior-posterior (SLAP) tears which including 2 type II and 2 type IV) who received LHB tenodesis using all-inside arthroscopic high resistance loop technique were included in this study. The American Shoulder and Elbow Surgeon Score (ASES), Visual Analog Scale (VAS), Simple Shoulder Test Score (SST), Constant–Murley scores, and University of California at Los Angeles Scoring System (UCLA) were used to evaluate the clinical outcomes of patients in preoperative and final follow-up. Meanwhile, postoperative complications were also observed.

Result

32 patients (14 women and 18 men, average age was 55.7 years) underwent all-inside arthroscopic knotless suprapectoral biceps tenodesis using the H-Loop stitch technique. The mean time of follow-up was 16.2 ± 2.6 months. The ASES, VAS, Constant–Murley, SST, and UCLA scores improved from 51.5 ± 15.8, 5.5 ± 1.6, 57.8 ± 14.7, 5.0 ± 2.8, and 16.1 ± 3.8 preoperatively, to 89.1 ± 7.5, 1.0 ± 0.8, 87.3 ± 5.5, 10.4 ± 1.5, and 31.3 ± 2.6 in the last follow-up, respectively (p < 0.001). During the follow-up, no patients in this study experienced postoperative complications such as infection of the wound, injury of nerves, and hardware failure; no patients required revision after their operation. In addition, none of the patients had cramping or a “Popeye” deformity during follow-up.

Conclusion

This article presents an innovative, all-arthroscopic H-loop technique for LHB tenodesis. This technique for LHB tenodesis showed favorable functional and cosmetic outcomes, as well as high satisfaction rates. Due to its simplicity of operation and satisfactory preliminary clinical outcomes, H-loop technique is perhaps another option to choose in all-inside arthroscopic LHB tenodesis.
Microbial and metabolomic insights into the bovine lipometabolic responses of rumen and mammary gland to zymolytic small peptide supplementation
Authors: Liu En , Xiao Weiwei , Pu Qijian , Xu Lanjiao , Wang Long , Mao Kang , Hong Wei , Qu Mingren , Xue Fuguang
Published: September 2022

Small peptides provide the easily utilized nitrogen for rumen microbial and promote acetate generation for milk fat synthesis. However, the impacts of peptide supplements on lipometabolic processes were still unclear. Therefore, a total of 800 multiparous dairy herds (with an average live weight of 667.6 ± 39.4 kg, an average lactation of 89.3 ± 18.8 days, and an average calving parity of 2.76 ± 0.47) were randomly allocated to the control (CON) and the small peptide (SP) supplement (100 g/day for each cow) treatments, respectively. A 35-day-long feeding procedure that includes a 7-day-long pretreatment test and a 28-day-long treatment test was followed for all cows. Dry matter intake (DMI) was recorded every day and calculated by the deviation between the supply and residue, while the daily milk production was automatically recorded through the rotary milking facilities. Milk samples were collected from each replicate on the last day, followed by the milk quality and milk lipid composition measurement. Rumen fluid samples were collected on the last day through esophageal tubing 3 h after morning feeding for the determination of the underlying mechanism of the small peptide on lipid metabolism through the measurement of rumen lipometabolic-related metabolites and rumen bacterial communities. Results indicated that dry matter intake showed an increasing trend, while milk production and the milk fat content remarkably increased after SP supplement (P < 0.05). Further detailed detection showed the mainly increased milk composition focused on monounsaturated fatty acid (MUFA) and polyunsaturated fatty acid (PUFA). Acetate-producing microbes, such as Acetitomaculum, Bifidobacterium, Succiniclasticum, and Succinivibrio, and butyrate-producing microbes, such as Shuttleworthia and Saccharofermentans, significantly proliferated, which causatively brought the increased ruminal content of acetate, isobutyrate, and butyrate after SP supplement (P < 0.05) compared with CON. Lipometabolic metabolites such as phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylinositol (PI), phosphatidylserine (PS), triacylglycerol (TG), and Acetyl-CoA also significantly increased after SP supplement. In summary, SP supplements help to increase milk fat content through the proliferation of rumen bacterial communities, which provided more acetate and butyrate for milk fat synthesis combined with the promotion of ruminal lipometabolism.
A Backstepping Controller Based on a Model-Assisted Extended State Observer for a Slice Rotor Supported by Active Magnetic Bearings
Authors: Xu Boyuan , Zhou Jin , Xu Longxiang
Published: September 2022

To improve the robustness of a slice rotor system supported by active magnetic bearings (AMBs), here, we propose a backstepping controller based on a model-assisted extended state observer (MESO-BC). Based on a generalized extended state observer (GESO), a model-assisted extended state observer is studied with consideration of the linear model of AMBs. The model-assisted extended state observer can estimate the unknown disturbances of the active magnetic bearing system, such as model inaccuracy and external disturbance, and is superior to the generalized extended state observer with respect to observation errors and the speed of convergence errors. In addition, it is compared with the backstepping controller based on a generalized extended state observer (GESO-BC) and conventional adaptive backstepping controller (ABC), and the simulation and experimental results verify the effectiveness of the proposed method. The experimental results demonstrate that the overshoot of the MESO-BC decrease by 5.94% and 13.2% as compared with the GESO-BC and ABC under the effect of pulse disturbance, respectively, and the rotor displacement of the MESO-BC reduce by 40.3% and 54.6% as compared with the GESO-BC and ABC under the effect of the sinusoidal disturbance, respectively.
TPE-RBF-SVM Model for Soybean Categories Recognition in Selected Hyperspectral Bands Based on Extreme Gradient Boosting Feature Importance Values
Authors: Zhao Qinghe , Zhang Zifang , Huang Yuchen , Fang Junlong
Published: September 2022

Soybeans with insignificant differences in appearance have large differences in their internal physical and chemical components; therefore, follow-up storage, transportation and processing require targeted differential treatment. A fast and effective machine learning method based on hyperspectral data of soybeans for pattern recognition of categories is designed as a non-destructive testing method in this paper. A hyperspectral-image dataset with 2299 soybean seeds in four categories is collected. Ten features are selected using an extreme gradient boosting algorithm from 203 hyperspectral bands in a range of 400 to 1000 nm; a Gaussian radial basis kernel function support vector machine with optimization by the tree-structured Parzen estimator algorithm is built as the TPE-RBF-SVM model for pattern recognition of soybean categories. The metrics of TPE-RBF-SVM are significantly improved compared with other machine learning algorithms. The accuracy is 0.9165 in the independent test dataset, which is 9.786% higher for the vanilla RBF-SVM model and 10.02% higher than the extreme gradient boosting model.
Improving Cleaning Performance of Rice Combine Harvesters by DEM–CFD Coupling Technology
Authors: Ding Bochuan , Liang Zhenwei , Qi Yongqi , Ye Zhikang , Zhou Jiahao
Published: September 2022

The cleaning device is an important part of combine harvesters, as its superior or inferior performance directly affects the performance of the combine harvester greatly. With an increasing rice yield, the current single-duct cleaning performance declines greatly, and causes a large grain sieve loss level and a direct grain loss for the farms. To optimize the existing single-duct cleaning device to meet the large feeding rate requirement, firstly, the terminal velocity of rice grain and MOG (material other than grain) for different varieties was experimentally measured by the custom-made device. The effects of the moisture content of rice grains and the length of short straws on terminal velocity were studied in detail. Then, the gas–solid two-phase flow theory was comprehensively applied by utilizing the discrete element method (DEM) and computational fluid dynamics (CFD) to study the working mechanism of the existing single-duct cleaning unit, and the cleaning performance was evaluated from the view of the motion law of the threshing output within the cleaning shoe. At last, a multi-duct cleaning device was put forward, and a field experiment was performed to assess the performance of the newly developed cleaning device. The results showed that the grain sieve losses ratio and grain impurity ratio improved dramatically, proving that structure optimization of the cleaning device was feasible.
Do Metals Increase or Decrease Nitrous Oxide Emissions and Maize Yields from Upland Soils?
Authors: Park Ye Lim , Lee Hyun Ho , Kim Sung Un , Kang Namgoo , Hong Chang Oh
Published: September 2022

Metals, including copper (Cu), iron (Fe), and zinc (Zn), are associated with nitrous oxide (N2O) production processes, such as nitrification and denitrification. This study aimed to elucidate the effects of Cu, Fe, and Zn on N2O emissions and to determine cumulative N2O emission and crop yields from upland soils. Metals were applied at a rate of 20 kg ha−1 in upland soil supporting maize (Zea mays L.) growth in 2018 and 2019. While the mean value of cumulative N2O emissions across both years was 5.19 kg N2O ha−1 yr−1 for the control soil, those of soil treated with Cu, Fe, and Zn were 3.37, 2.48, and 4.82 kg N2O ha−1 yr−1, respectively. Ammonium (NH4+) concentration in soil was highest after Fe application, and nitrate (NO3−) concentration was lowest. The copy number of the amoA gene related to NH4+ oxidation was lowest after Fe enhancement, implying that nitrification was inhibited. Furthermore, N2O emission decreased with Cu addition because the copy number of the nosZ gene associated with N2O reduction to N2 was the highest. Because Cu and Fe decreased yield-scaled N2O emission, the application of either metal could reduce N2O emission per unit area of maize production, suggesting that both metals are beneficial soil amendments for reducing N2O emissions while maintaining maize yield.
Enhanced Metabolism Evolved High-Level Resistance to Fenoxaprop-P-Ethyl in Alopecurus japonicus
Authors: Li Zongfang , Liu Haozhe , Wang Junzhi , Chen Wen , Bai Lianyang , Pan Lang
Published: September 2022

Alopecurus japonicus has been a serious weed across China and developed resistance to the acetyl-CoA carboxylase (ACCase)-inhibiting herbicide. The A. japonicus ACCase gene mutations accounting for target-site resistance (TSR) have been clarified, while non-target-site resistance (NTSR) is not distinct. Here, dose–response testing indicated that an A. japonicus population (R) was resistant to four ACCase-inhibiting herbicides fenoxaprop-P-ethyl, sethoxydim, clethodim, and pinoxaden. Compared with herbicide-susceptible A. japonicus (S), no known resistant mutations for TSR in ACCase were identified in the R population using sequencing. To investigate the NTSR mechanism, increased metabolism of fenoxaprop-P-ethyl was detected in the R population using high-performance liquid chromatography (HPLC) analysis. Notably, resistance cannot be reversed by P450 and GST inhibitors. RNA-seq was performed to further explore the resistance mechanisms, and eight candidate contigs (four glycosyl transferases (GT) and four ATP-binding cassette (ABC) transporters) were chosen and their expression patterns were validated using RT-qPCR. Three GT and three ABC transporter contigs were constitutively upregulated in the R population. In short, six contigs expressed highly in the R population causing enhanced fenoxaprop-P-ethyl metabolism appear to be involved in fenoxaprop-P-ethyl resistance.
Plasma Protein Binding Rate and Pharmacokinetics of Lekethromycin in Rats
Authors: Sun Pan , Xiao Hongzhi , Qiu Jicheng , Cao Yuying , Kong Jingyuan , Zhang Suxia , Cao Xingyuan
Published: September 2022

Lekethromycin (LKMS), a novel macrolide lactone, is still unclear regarding its absorption. Thus, we conducted this study to investigate the characteristics of LKMS in rats. We chose the ultrafiltration method to measure the plasma protein binding rate of LKMS. As a result, LKMS was characterized by quick absorption, delayed elimination, and extensive distribution in rats following intramuscular (im) and subcutaneous (sc) administration. Moreover, LKMS has a high protein binding rate (78–91%) in rats at a concentration range of 10–800 ng/mL. LKMS bioavailability was found to be approximately 84–139% and 52–77% after im and sc administration, respectively; however, LKMS was found to have extremely poor bioavailability after oral administration (po) in rats. The pharmacokinetic parameters cannot be considered linearly correlated with the administered dose. Additionally, LKMS and its corresponding metabolites were shown to be metabolically stable in the liver microsomes of rats, dogs, pigs, and humans. Notably, only one phase I metabolite was identified during in vitro study, suggesting most of drug was not converted. Collectively, LKMS had quick absorption but poor absorption after oral administration, extensive tissue distribution, metabolic stability, and slow elimination in rats.
Dietary Supplementation with Eucommia ulmoides Leaf Extract Improved the Intestinal Antioxidant Capacity, Immune Response, and Disease Resistance against Streptococcus agalactiae in Genetically Improved Farmed Tilapia (GIFT; Oreochromis niloticus)
Authors: Huang Dongyu , Zhu Jian , Zhang Lu , Ge Xianping , Ren Mingchun , Liang Hualiang
Published: September 2022

A 7-week rearing trial was designed to investigate the effects of Eucommia ulmoides leaf extract (ELE) on growth performance, body composition, antioxidant capacity, immune response, and disease susceptibility of diet-fed GIFT. The results showed that dietary ELE did not affect growth performance or whole-body composition (p > 0.05). Compared with the control group, plasma ALB contents increased in the 0.06% dietary ELE group (p < 0.05), and plasma ALT and AST activities decreased in the 0.08% dietary ELE group (p < 0.05). In terms of antioxidants, compared with GIFT fed the control diet, 0.06% dietary ELE upregulated the mRNA expression levels of Nrf2 pathway-related antioxidant genes, including CAT and SOD (p < 0.05), and 0.06% and 0.08% dietary ELE upregulated the mRNA levels of Hsp70 (p < 0.05). In terms of immunity, 0.06% dietary ELE suppressed intestinal TLR2, MyD88, and NF-κB mRNA levels (p < 0.05). Moreover, the mRNA levels of the anti-inflammatory cytokines TGF-β and IL-10 were upregulated by supplementation with 0.04% and 0.06% dietary ELE (p < 0.05). In terms of apoptosis, 0.06% and 0.08% ELE significantly downregulated the expression levels of FADD mRNA (p < 0.05). Finally, the challenge experiment with S. agalactiae showed that 0.06% dietary ELE could inhibit bacterial infection, and significantly improve the survival rate of GIFT (p < 0.05). This study demonstrated that the supplementation of 0.04–0.06% ELE in diet could promote intestinal antioxidant capacity, enhance the immune response and ultimately improve the disease resistance of GIFT against Streptococcus agalactiae.
The Investigation of the Impact of Toxicity of Metals on Oxygen-Evolving Complex in Spinacia oleracea
Authors: Azmat Rafia , Saleem Ailyan , Ahmed Waseem , Qayyum Abdul , El-Serehy Hamed A. , Ali Sajid
Published: September 2022

The current article reported the investigation of metal toxicity on the oxygen-evolving complex (OEC) in Spinacia oleracea related to depletion in chloride ion concentration, an essential part of the photosystem (II). The greenhouse experiment was conducted where S. oleracea was cultivated in three replicates with control plants (plants “a”) treated with tap water. Moreover, 30 ppm of Cu2+ ion solution and Pb2+ ion solution was used to irrigate the rest of the plants, labeled as plants “b” and “c”, respectively, on alternative days. Advanced technologies such as Atomic Absorption Spectrophotometry (AAS), Scanning Electron Microscopy (SEM), Energy Dispersive Spectroscopy (EDS), and UV-visible Spectrophotometry were used to monitor the essential nutrients in leaves to validate the function of the photosystem (I and II). Reduced Cl− ions contents showed that both metals (Cu2+ and Pb2+) altered the essential elements of the oxygen-evolving complex (OEC) of photosystem (II), required to maintain the coordination structure of the Mn4CaO5 cluster. SEM analysis revealed the modified leaf structure of the S. oleracea under Cu2+ and Pb2+ accumulation due to which distorted cellular structure, reduced surface area, and the (shattered) stomatal opening compared to the plants “a” were observed. The EDS analysis of plants “b” and “c” showed high oxygen contents followed by reduced chloride contents over plants “a”, reflecting the infirmity of OEC to push out oxygen, which leads to generating oxidative stress. The lower pigment concentration in leaves of metal-contaminated plants “b” and “c” impacts carbon assimilation, which is linked to the reduced stomatal opening and influences the gaseous exchange rates. Additionally, increased contents of K+ and Ca2+ may be due to self-defense mechanisms under low chloride contents to speed up oxygen evolution to protect plants against oxidative stress. It was concluded that Cu2+ and Pb2+ metal toxicity influences essential Cl− and K+ contents, which modify the photosystem II system; subsequently, a reduced growth rate was observed.
Rice Nudix Hydrolase OsNUDX2 Sanitizes Oxidized Nucleotides
Authors: Kondo Yuki , Rikiishi Kazuhide , Sugimoto Manabu
Published: September 2022

Nudix hydrolase (NUDX) hydrolyzes 8-oxo-(d)GTP to reduce the levels of oxidized nucleotides in the cells. 8-oxo-(d)GTP produced by reactive oxygen species (ROS) is incorporated into DNA/RNA and mispaired with adenine, causing replicational and transcriptional errors. Here, we identified a rice OsNUDX2 gene, whose expression level was increased 15-fold under UV-C irradiation. The open reading frame of the OsNUDX2 gene, which encodes 776 amino acid residues, was cloned into Escherichia coli cells to produce the protein of 100 kDa. The recombinant protein hydrolyzed 8-oxo-dGTP, in addition to dimethylallyl diphosphate (DMAPP) and isopentenyl diphosphate (IPP), as did Arabidopsis AtNUDX1; whereas the amino acid sequence of OsNUDX2 had 18% identity with AtNUDX1. OsNUDX2 had 14% identity with barley HvNUDX12, which hydrolyzes 8-oxo-dGTP and diadenosine tetraphosphates. Suppression of the lacZ amber mutation caused by the incorporation of 8-oxo-GTP into mRNA was prevented to a significant degree when the OsNUDX2 gene was expressed in mutT-deficient E. coli cells. These results suggest that the different substrate specificity and identity among plant 8-oxo-dGTP-hydrolyzing NUDXs and OsNUDX2 reduces UV stress by sanitizing the oxidized nucleotides.
New Types of Distance Padovan Sequences via Decomposition Technique
Authors: Włoch Andrzej , Wołowiec-Musiał Małgorzata , Bednarz Urszula
Published: September 2022

In this paper, we introduce new kinds of generalized Padovan sequences and study their properties using number decomposition techniques. In particular, we consider three types of generalized Padovan sequences defined by the same recurrence equation with distinct initial conditions which follows from special number decomposition. Using the number decomposition method, we give their mutual relations and direct binomial formulas for considered sequences. Moreover, we give some combinatorial properties of these sequences and also define their matrix generators.
A Flexible and Simple Lossless DWT Filter Bank Using a MAXFLAT FIR Half-Band Filter
Authors: Chung Daewon , Cho Woon , Kim Yunsun , Jeon Joonhyeon
Published: September 2022

This paper describes a simple, lossless and computationally efficient two-band single (s-) filter bank that creates an opposite band output by subtracting the primary filtered data from the original data. For computationally efficient and error-free s-filter bank achievement, a maximally flat (MAXFLAT) half-band filter with zero odd-order coefficients is characterized from a unique perfect reconstruction condition, and an explicit impulse–response formula (for non-zero integer coefficients of even order) is derived in a closed form of the filter. The examples are shown to provide a complete and accurate solution for the design of such s-filter banks. In addition, the effectiveness of the proposed s-filter banks is clearly verified by comparing the lossless 5/3 and lossy 9/7 filter banks (in the JPEG2000). The simulation results show that the s-filter banks lead to better performance than the JPEG2000 filter banks using two filters although allowing low computational complexity of less than 50%. This new approach is shown to provide significant advantages over existing lossless discrete wavelet transform (DWT) filter banks in both design flexibility and computational complexity.
Modeling and Predicting Urban Expansion in South Korea Using Explainable Artificial Intelligence (XAI) Model
Authors: Kim Minjun , Kim Geunhan
Published: September 2022

Over the past few decades, most cities worldwide have experienced a rapid expansion with unprecedented population growth and industrialization. Currently, half of the world’s population is living in urban areas, which only account for less than 1% of the Earth. A rapid and unplanned urban expansion, however, has also resulted in serious challenges to sustainable development of the cities, such as traffic congestion and loss of natural environment and open spaces. This study aims at modeling and predicting the expansion of urban areas in South Korea by utilizing an explainable artificial intelligence (XAI) model. To this end, the study utilized the land-cover maps in 2007 and 2019, as well as several socioeconomic, physical, and environmental attributes. The findings of this study suggest that the urban expansion tends to be promoted when a certain area is close to economically developed area with gentle topography. In addition, the existence of mountainous area and legislative regulations on land use were found to significantly reduce the possibility of urban expansion. Compared to previous studies, this study is novel in that it captures the relative importance of various influencing factors in predicting the urban expansion by integrating the XGBoost model and SHAP values.
A High-Efficiency Dual-Band Linear-to-Circular Polarization Converter Based on Rectangular-Slot Reflective Metasurface
Authors: Majeed Abdul , Zhang Jinling , Awan Zeeshan Akbar , Memon Saifullah , Ishfaq Muhammad , Wang Chenchen
Published: September 2022

In this article, a novel and high-efficiency dual-wideband linear-to-circular polarization conversion based on a rectangular-slot reflective metasurface is anticipated, one that can convert linearly polarized (LP) electromagnetic waves into right- and left-hand circularly polarized waves in two non-adjacent frequency bands. The converter is an orthotropic design, with a pair of mutually orthogonal symmetric axes (u and v) along orientations tilted at 45° to the y-axis. The simulated results indicate that the dual-wideband circularly polarized wave is achieved under a y-polarized an electromagnetic (EM) incidence wave over the bands of 16.49–23.54 GHz and 26.44–34.56 GHz with 3 dB axial ratio relative bandwidths of 35.23% and 26.62%, respectively, and a polarization conversion ratio (PCR) in excess of 99%. A detailed mathematical investigation is proposed to determine the fundamental factor causing the dual-wideband linear-to-circular polarization conversion. The phase difference (∆φuv) between ruu and rvv under u- and v- polarized incident waves is ±90°, and it entirely determines the 3 dB reflected wave axial ratio. Any reflective converter can work efficiently as a linear-to-circular polarization conversion if the phase difference (∆φuv) is close to ±90°.
Towards Digitalization of Water Supply Systems for Sustainable Smart City Development—Water 4.0
Authors: Adedeji Kazeem B. , Ponnle Akinlolu A. , Abu-Mahfouz Adnan M. , Kurien Anish M.
Published: September 2022

Urban water supply systems are complex and dynamic in nature, and as a result, can be considered complex to manage owing to enhanced urbanization levels, climate change, growing and varying consumer demands, and limited water resources. The operation of such a system must be managed effectively for sustainable water supply to satisfy the growing consumer demand. This creates a need for intelligent systems for the purposes of operational management. In recent years, computing technologies have been applied to water systems to assist water utilities in addressing some of these problems. Unfortunately, previous ICT solutions have not been able to provide the necessary support for applications to deal with the dynamics of water supply system environments. With the increasing growth in technology, the water sector is moving to the full phase of digitalization to enhance the sustainability of systems. Thus, a new industrial revolution in the water context (Water 4.0) is being researched. This is referred to as Water 4.0, which offers better possibilities to enhance the sustainability of water supply system operations. This paper presents an overview of Water 4.0 and its applications in enhancing water supply system operations. Key features of Water 4.0 are discussed. Furthermore, challenges and future opportunities offered by technology for sustainable operation of municipal water services are discussed.
Therapeutic Potential of Myrrh, a Natural Resin, in Health Management through Modulation of Oxidative Stress, Inflammation, and Advanced Glycation End Products Formation Using In Vitro and In Silico Analysis
Authors: Rahmani Arshad Husain , Anwar Shehwaz , Raut Ravindra , Almatroudi Ahmad , Babiker Ali Yousif , Khan Amjad Ali , Alsahli Mohammed A. , Almatroodi Saleh A.
Published: September 2022

Oxidative stress, hyper-inflammatory responses, and protein glycation are the chief contributing factors in the pathogenesis of several diseases. This study aimed to explore the therapeutic role of myrrh in health management through in vitro and in silico studies. Antioxidant potential, anti-inflammatory potential, antiglycation, and advanced glycation end products (AGEs) formation inhibition activities were determined by various in vitro assays. Molecular docking was performed to predict the non-covalent binding of macromolecules (receptor) and a small molecule (ligand). Myrrh extract contained significant antioxidant activity as reflected by FRAP value (16.12 µg ascorbic acid/100 mg dry weight), the maximum percentage of DPPH scavenging (57.71%), and maximum hydrogen peroxide reducing activity (58.71%) at a concentration of 600 µg/mL. Further, the extract exhibited maximum protection from bovine serum albumin (BSA) denaturation inhibition (53.47%), anti-proteinase action (43.517%), and egg albumin denaturation inhibition (44.95%) at a dose of 600 µg/mL concentration. Myrrh is used in pharmacy as an antiseptic, anti-inflammatory, antimicrobial, antifungal, and anti-venom remedy. This study aimed to explore the antioxidant, anti-inflammatory, antiarthritic, antiglycation, and advanced glycation end products (AGEs) formation inhibition ability of methanolic myrrh extract. It was found that myrrh has good antioxidant potential due to plenty of flavonoids and polyphenolic compounds, as reflected by results of the 2,2′-diphenyl-1-picrylhydrazyl radical (DPPH) assay, FRAP (ferric reducing antioxidant power) test, and hydrogen peroxide reducing test. Furthermore, myrrh methanolic extract was found to be significantly effective against heat-induced albumin denaturation, and percent inhibition of denaturation increases with increased extract concentration. The presence of myrrh extract at a dose of 600 μg/mL decreased browning intensity (59.38%), percent aggregation index (59.88%), and percentage amyloid structure (56.13%). We used molecular docking tools to study the role of myrrh in oxidative stress (Catalase), antioxidant property (Superoxide dismutase), and antiviral property (spike protein S). The molecular docking analysis confirmed four phytoconstituents; 2,3-Furandione, Curzerene, delta-Elemene, and Furanoeudesma-1,3-Diene interact with catalase and superoxide dismutase. Curzerene and Furanoeudesma-1,3-Diene showed remarkable interaction with SARS-CoV-2 spike protein S. Our data suggest that myrrh resin extract can be used to develop a suitable alternative therapy for various diseases linked with oxidative stress, inflammation, glycation, and AGEs.
Superpixel Image Classification with Graph Convolutional Neural Networks Based on Learnable Positional Embedding
Authors: Bae Ji-Hun , Yu Gwang-Hyun , Lee Ju-Hwan , Vu Dang Thanh , Anh Le Hoang , Kim Hyoung-Gook , Kim Jin-Young
Published: September 2022

Graph convolutional neural networks (GCNNs) have been successfully applied to a wide range of problems, including low-dimensional Euclidean structural domains representing images, videos, and speech and high-dimensional non-Euclidean domains, such as social networks and chemical molecular structures. However, in computer vision, the existing GCNNs are not provided with positional information to distinguish between graphs of new structures; therefore, the performance of the image classification domain represented by arbitrary graphs is significantly poor. In this work, we introduce how to initialize the positional information through a random walk algorithm and continuously learn the additional position-embedded information of various graph structures represented over the superpixel images we choose for efficiency. We call this method the graph convolutional network with learnable positional embedding applied on images (IMGCN-LPE). We apply IMGCN-LPE to three graph convolutional models (the Chebyshev graph convolutional network, graph convolutional network, and graph attention network) to validate performance on various benchmark image datasets. As a result, although not as impressive as convolutional neural networks, the proposed method outperforms various other conventional convolutional methods and demonstrates its effectiveness among the same tasks in the field of GCNNs.
Microbiological Follow-Up of Bioreactor-Assisted Must Alcoholic Fermentation by Flow Cytometry
Authors: Sizzano Federico , Blackford Marie , Bourdin Gilles
Published: September 2022

The monitoring of must fermentation in a bioreactor, in which the main physico-chemical parameters are tightly controlled, can provide useful analytical information transferable to winemaking on a larger scale. In this experiment, we followed the growth of Saccharomyces cerevisiae during the bioreactor-assisted alcoholic fermentation of a Chasselas must by means of flow cytometry. We used fluorescent dyes and volumetric counting to monitor cell viability and concentration for two weeks. Our study suggests that the use of flow cytometry during bioreactor-assisted alcoholic fermentation provides various types of information—viz., cell viability, number and function—in a timely manner, and that the process can therefore be used effectively to inform experimentation at this scale.
New Anthropology in Works of Vasily Chekrygin
Authors: Bobrinskaya Ekaterina
Published: September 2022

The article considers the concept of new anthropology in the works of Vasily Chekrygin in the context of the scientific and philosophical ideas of his time. Chekrygin’s anthropology drew on the new concepts of life, discoveries made in biology and chemistry and new ideas of matter. A paradoxical fusion of scientific and occult thought, coupled with ideas of Christian anthropology, formed a crucial component of Chekrygin’s works. The artist produced his anthropological project at the intersection of two cultural paradigms: that of Christianity, on the one hand, and science and the occult, on the other. This blend of such heterogeneous concepts was not an accidental fact of the artist’s biography. It makes it possible to see certain problems and antinomies that were fundamental to the Russian culture of the 1910s through the early 1920s.
Convolutional Neural Networks for Automated ULF Wave Classification in Swarm Time Series
Authors: Antonopoulou Alexandra , Balasis Georgios , Papadimitriou Constantinos , Boutsi Adamantia Zoe , Rontogiannis Athanasios , Koutroumbas Konstantinos , Daglis Ioannis A. , Giannakis Omiros
Published: September 2022

Ultra-low frequency (ULF) magnetospheric plasma waves play a key role in the dynamics of the Earth’s magnetosphere and, therefore, their importance in Space Weather phenomena is indisputable. Magnetic field measurements from recent multi-satellite missions (e.g., Cluster, THEMIS, Van Allen Probes and Swarm) are currently advancing our knowledge on the physics of ULF waves. In particular, Swarm satellites, one of the most successful missions for the study of the near-Earth electromagnetic environment, have contributed to the expansion of data availability in the topside ionosphere, stimulating much recent progress in this area. Coupled with the new successful developments in artificial intelligence (AI), we are now able to use more robust approaches devoted to automated ULF wave event identification and classification. The goal of this effort is to use a popular machine learning method, widely used in Earth Observation domain for classification of satellite images, to solve a Space Physics classification problem, namely to identify ULF wave events using magnetic field data from Swarm. We construct a Convolutional Neural Network (ConvNet) that takes as input the wavelet spectrum of the Earth’s magnetic field variations per track, as measured by Swarm, and whose building blocks consist of two alternating convolution and pooling layers, and one fully connected layer, aiming to classify ULF wave events within four different possible signal categories: (1) Pc3 wave events (i.e., frequency range 20–100 MHz), (2) background noise, (3) false positives, and (4) plasma instabilities. Our preliminary experiments show promising results, yielding successful identification of more than 97% accuracy. The same methodology can be easily applied to magnetometer data from other satellite missions and ground-based arrays.