bluuebunny/crossref_metadata_2025 huggingface dataset:
Grain-Filling Rate Improves Physical Grain Quality in Barley Under Heat Stress Conditions During the Grain-Filling Period
Authors: Shirdelmoghanloo Hamid , Chen Kefei , Paynter Blakely H. , Angessa Tefera Tolera , Westcott Sharon , Khan Hammad Aziz , Hill Camilla Beate , Li Chengdao
Published: May 2022

Heat stress is a primary constraint to Australia's barley production. In addition to impacting grain yield, it adversely affects physical grain quality (weight and plumpness) and market value. The incidence of heat stress during grain filling is rising with global warming. However, breeding for new superior heat-tolerant genotypes has been challenging due to the narrow window of sensitivity, the unpredictable nature of heat stress, and its frequent co-occurrence with drought stress. Greater scientific knowledge regarding traits and mechanisms associated with heat tolerance would help develop more efficient selection methods. Our objective was to assess 157 barley varieties of contrasting genetic backgrounds for various developmental, agro-morphological, and physiological traits to examine the effects of heat stress on physical grain quality. Delayed sowing (i.e., July and August) increased the likelihood of daytime temperatures above 30°C during grain-filling. Supplementary irrigation of field trials ensured a reduced impact of drought stress. Heat tolerance appeared to be the primary factor determining grain plumpness. A wide variation was observed for heat tolerance, particularly among the Australian varieties. Genotypic variation was also observed for grain weight, plumpness, grain growth components, stay-green and stem water-soluble carbohydrates (WSC) content, and mobilisation under normal and delayed sown conditions. Compared to normal sowing, delayed sowing reduced duration of developmental phases, plant height, leaf size, head length, head weight, grain number, plumpness, grain width and thickness, stem WSC content, green leaf area retention, and harvest index (HI), and increased screenings, grain length, grain-filling rate (GFR), WSC mobilisation efficiency (WSCME), and grain protein content. Overall, genotypes with heavier and plumper grains under high temperatures had higher GFR, longer grain-filling duration, longer green leaf area retention, higher WSCME, taller stature, smaller leaf size, greater HI, higher grain weight/plumpness potentials, and earlier flowering. GFR played a significant role in determining barley grain weight and plumpness under heat-stress conditions. Enhancing GFR may provide a new avenue for improving heat tolerance in barley.
The Impact of Cognitive Behavioral Therapy on Peripheral Interleukin-6 Levels in Depression: A Systematic Review and Meta-Analysis
Authors: Ma Haijing , Xu Jiatong , Li Ruonan , McIntyre Roger S. , Teopiz Kayla M. , Cao Bing , Yang Fahui
Published: May 2022

There is interest in the role of peripheral interleukin-6 (IL-6) in depression and the effect of treatment (e. g., pharmacologic, psychosocial, neurostimulation). However, the relationship between cognitive behavioral therapy (CBT), IL-6 and depression has not yet been established. We conducted a meta-analysis to explore the association between CBT and change of peripheral IL-6 levels in depressive symptoms or major depressive disorder (MDD). A systematic search of online databases (i.e., PubMed, Web of Science, Google Scholar, PsycINFO, and Cochrane Library) was completed from inception to May 2021. In total, 10 eligible papers with 940 participants reporting peripheral IL-6 levels before and after CBT were included in the analysis. The main result indicates that peripheral levels of IL-6 were significantly lower after CBT intervention in individuals with depression, with a small effect (SMD = 0.38, 95% CI: 0.07, 0.69, p = 0.02). The results of subgroup analyses demonstrate that (1) there was a significant decrease in IL-6 for studies that were equal to or <8 weeks in duration vs. more than 8 weeks in duration, and (2) IL-6 was significantly reduced in the Diagnostic and Statistical Manual of Mental Disorders (DSM) diagnosis (i.e., DSM-IV, DSM-IV-TR, or DSM-V) of MDD, but not for the subgroup without DSM diagnosis. Publication year was identified as a potential contributor to heterogeneity of the results from our analysis. Taken together, our findings support the notion that CBT influences peripheral IL-6 in individuals with depression and represents a point of commonality with other antidepressant treatment modalities (e.g., antidepressants).

Systematic Review Registration

https://doi.org/10.17605/osf.io/tr9yh, identifier: 10.17605/osf.io/tr9yh.
COVID-19 Information Overload, Negative Emotions and Posttraumatic Stress Disorder: A Cross-Sectional Study
Authors: Wang Jingjun , Huang Xia , Wang Ya , WANG Mengmeng , XU Jiajun , LI Xiaolin
Published: May 2022

Background

Under the context of the COVID-19 pandemic, a large amount of COVID-19-related information can cause an individual's perceived information overload, further halting the individual's psychological health. As a minor psychological discomfort could develop severe mental disorders such as posttraumatic stress disorder, it is necessary to understand the chain linkage of COVID-19 information overload turn to posttraumatic stress disorder to ensure timely intervention can be offered at each point of mental state transformation. Hence, we examined the negative outcomes of COVID-19 information overload and investigated the direct and indirect effects of COVID-19 on posttraumatic stress disorder.

Methods

A convenient sample of Chinese adults (n= 1150) was investigated by an online survey from July 2020 to March 2021. The extent of COVID-19 information overload was measured by the information overload severity scale on the text of the COVID-19 pandemic. Psychological distress symptoms were measured using a 7-item anxiety scale (GAD-7), the 9-item Patient Health Questionnaire depression module (PHQ-9), and the psychometric properties of the PTSD Checklist (PCL-C). Structural equation modeling and bootstrap methods were utilized to analyze the relationships between variables.

Results

COVID-19 information overload is positively related to an individual's anxiety, depression, and posttraumatic stress disorder. Furthermore, COVID-19 information overload can indirectly affect an individual's PTSD symptoms by increasing the feeling of depression. R2values of anxiety, depression, and PTSD were 0.471, 0.324, and 0.795, respectively.

Conclusion

COVID-19 information overload, anxiety, depression, and PTSD are negative psychological states, and each variable is closely linked with the others, suggesting the need for potential psychological interventions at specific times. Practical public training, such as crisis coping and information filtering, is essential. Regulation of technology companies is also essential.
Exploring Association Between Social Media Addiction, Fear of Missing Out, and Self-Presentation Online Among University Students: A Cross-Sectional Study
Authors: Zhu Xinhong , Xiong Zhenfang
Published: May 2022

Background

Social media addiction (SMA) is known to be associated with excess use of social media. However, few studies have focused on the links of self-presentation on social media, fear of missing out (FoMO) and SMA. The present study investigated the relationships of self-presentation, FoMO and SMA among university students.

Methods

Online survey was conducted with 2,744 respondents, who completed online survey including social media use, FoMO and SMA. Self-presentation on social media and privacy information protection were assessed via researcher-designed questionnaires. Self-presentation on social media was composed of basic information shown on social media and expression willingness. Privacy information protection contained information viewed by others and privacy settings in social media platforms.

Results

The most common information posted on social media were gender, hobby, age, personal photos, videos, and birthday. The most common social platforms with privacy setting were QQ zone (62.2%), WeChat (60.1%), and QQ (40.3%). FoMO (OR = 2.852, P = 0.000), information viewed by others (OR = 4.261, P = 0.000), managing a personal homepage (OR = 1.339, P = 0.002), accept a stranger's “friend request” (OR = 1.251, P = 0.028) and undergraduate students and above (OR = 1.439, P = 0.001) predicted expression willingness. FoMO (OR = 5.278, P = 0.000), information viewed by others (OR = 9.673, P = 0.000), privacy setting in QQ (OR = 0.817, P = 0.002) and in Tik Tok (OR = 0.536, P = 0.019) and female (OR = 0.588, P = 0.004) significantly influenced basic information shown on social media. Furthermore, FoMO (OR = 4.165, P = 0.000), expression willingness (OR = 1.645, P = 0.000), and information viewed by others (OR = 1.406, P = 0.000) positively affected the level of SMA. Risk of SMA increased as time spent on social media per day. However, basic information shown on social media did not significantly influence SMA.

Conclusion

In general, students with higher level of FoMO and expression willingness are more likely to experience SMA. These results highlight individual behaviors on social media should be considered as essential elements for assessing problematic engaging to social media.
A Study on the Effectiveness of Rumor Control via Social Media Networks to Alleviate Public Panic About COVID-19
Authors: Lu Ben , Sun Jinlu , Chen Bo , Wang Qi , Tan Qi
Published: May 2022

The COVID-19 outbreak triggered a massive spread of unverified news on social media and has become a source of rumors. This paper studies the impact of a virtual rumor control center (RCC) on Weibo user behavior. The collected COVID-19 breaking news stories were divided into positive, negative, and neutral categories, while the moderating effect model was used to analyze the influence of anti-rumor on user behavior (forwarding, liking, and commenting). Our research found that rumor refuting does not directly affect user behavior but does have an indirect moderating effect. Rumor refuting has a profound impact on user forwarding behavior in cases of positive and negative news. Specifically, when the epidemic becomes more serious, the role of rumor refuting becomes critical, and vice versa. Refuting rumors reduces user willingness to forward positive or negative news, with more impact on negative news. Time lag analysis shows a significant moderation of unverified news within 72 h of refuting rumors but indicated an apparent weakening trend over time. Furthermore, we discovered non-linear feature and counter-cyclical phenomena in the moderating effect of rumor refutation.
COVID-19 Impact on Household Food Security in Urban and Peri-Urban Areas of Hyderabad, India
Authors: Padmaja Ravula , Nedumaran Swamikannu , Jyosthnaa Padmanabhan , Kavitha Kasala , Abu Hatab Assem , Lagerkvist Carl-Johan
Published: May 2022

This paper investigates the impact of the COVID-19 pandemic on food security and on coping-strategies in urban and peri-urban areas of the Hyderabad, India. Household survey data were collected before (October 2018) and during (January 2021) the onset of the pandemic. Results from logistic regression with the standarized Food Insecurity Expecience Scale (FIES) as dependent variable reveal that close to 40% of the households surveyed experienced a deterioration in food security status during the pandemic. In particular, we find that food security is closely related to the sector of employment in which the primary income- earning member of a household is engaged. To mitigate the impact of the pandemic on their food security, our sampled households adopted a variety of consumption-smoothing strategies including availing credit from both formal and informal sources, and liquidating their savings. Compared to households with severe or moderate level of food insecurity, households facing a mild level of food insecurity relied on stored food as a strategy to smoothen consumption in response to the income shock imparted by the pandemic. In addition, the results indicate that urban households, who adopted similar coping strategies as those adopted by peri-urban households, tended to be more food-insecure. Finally, the duration of unemployment experienced during the pandemic significantly influenced the status of household food security. These findings can inform the formulation of immediate and medium-term policy responses, including social protection policies conductive to mitigating the impacts of the COVID-19 pandemic and ameliorating the governance of urban food security during unexpected events and shocks.
Mindfulness and Understanding of Self-Care for Leaders of Extension: Promoting Well-Being for Health Educators and Their Clients
Authors: Dysart Anna , Harden Samantha M.
Published: May 2022

Background

Mindfulness and self-care, practiced through a variety of methods like meditation and exercise, can improve overall sense of holistic well-being (i.e., flourishing). Increasing mindfulness and self-care may lead to increased flourishing and job satisfaction among the nation-wide Cooperative Extension system delivery personnel (agents) through a theory-based online program and an extended experiential program.

Methods

Cooperative Extension agents from two states were invited to participate in MUSCLE via statewide listservs. Participants were invited to attend sessions and complete competency checks and between-session assignments each week. The study was conducted using Zoom. Pre- and post- program surveys included validated scales for flourishing and physical activity status. Due to high demand for mindfulness programing during the onset of the COVID-19 pandemic, experiential “Mindful Meet-up” 30-minute sessions were held on Zoom. Dissemination and implementation of the two differing interventions (i.e., MUSCLE and Mindful Meet-ups) were examined.

Results

MUSCLE (more intensive program with assignments and competency checks) had lower reach, and did not show statistically increased flourishing or physical activity. Mindful Meet-ups had higher attendance and proportional reach during the beginning of the pandemic, but no practical measure of flourishing or physical activity behaviors. Unsolicited qualitative feedback was encouraging because the interventions were well-received and participants felt as though they were more mindful.

Conclusions

While agents anecdotally reported personal improvements, capturing data on outcomes was challenging. Complementing outcome data with implementation and dissemination outcomes allowed for a richer picture to inform intervention decision-making (i.e., offering the same or new programming depending on participant needs).
The Effect of Nursing Internships on the Effectiveness of Implementing Information Technology Teaching
Authors: Tseng Li-Ping , Hou Tung-Hsu , Huang Li-Ping , Ou Yang-Kun
Published: May 2022

In nursing education, the diversity of clinical scenarios is complex and dynamic, and it is a challenge for nursing students to learn this clinical knowledge in conventional teaching mechanisms. However, integrating information technology into teaching can promote diversity of learning environment. This study aimed to investigate the effectiveness of teaching mechanisms which combined clinical simulation scenario and Information Technology Integrated Instruction. This study applied innovative experimental teaching in medical–surgical and critical care nursing courses for nursing students in their fourth or fifth year at a five-year junior college. Instructional systems design was combined with clinical simulation scenarios and technology to develop multidimensional teaching strategies. Fifth-year students' overall OSCE mean score was considerably higher than that of fourth-year students; specifically, their scores on basic life support and care for subdural hemorrhage varied substantially. Compared with fourth-year students, fifth-year students performed considerably greater on situational awareness. The results of the present study can be used to develop nursing core competencies and improve the clinical care competency of nursing personnel.
Soleus H and Lower Limb Posterior Root Muscle Reflexes During Stepping After Incomplete SCI
Authors: Tansey Keith E. , Farrell Bradley J. , Bruce Joy A. , McKay William B.
Published: May 2022

The goal of this study was to examine and compare the step cycle related modulation of the soleus H and posterior root muscle (PRM) reflexes in subjects with and without spinal cord injury. Ten subjects without neurological injury and fifteen subjects with spinal cord injury (SCI) underwent soleus H reflex and lower limb PRM reflex testing while standing and stepping in a robotic gait orthosis. Reflex amplitudes were evaluated during standing, mid stance and mid swing to determine if speed and/or injury altered step cycle related neuromodulation. H and PRM reflexes in the soleus underwent step cycle related modulation in injured and uninjured subjects though the degree of modulation differed between the two reflexes with the H reflex showing more step cycle related modulation. We found in the SCI group that both the soleus H and soleus PRM reflex amplitudes were higher relative to the non-injured group and modulated less during the step cycle. We also found that modulation of the soleus H reflex, but not soleus PRM reflex, correlated to the lower extremity motor scores in individuals with SCI. Our evidence suggests that the inability to provide appropriate step cycle related reflex modulation may be due to decreased supra-spinal regulation of motoneuron and spinal excitability and could be an indicator of the severity of injury as it relates to clinically measured lower extremity motor scores.
Metabolomics Analysis Across Multiple Biofluids Reveals the Metabolic Responses of Lactating Holstein Dairy Cows to Fermented Soybean Meal Replacement
Authors: Wang Zuo , Yu Yuannian , Shen Weijun , Tan Zhiliang , Tang Shaoxun , Yao Hui , He Jianhua , Wan Fachun
Published: May 2022

This experiment was performed to reveal the metabolic responses of dairy cows to the replacement of soybean meal (SBM) with fermented soybean meal (FSBM). Twenty-four lactating Chinese Holstein dairy cattle were assigned to either the SBM group [the basal total mixed ration (TMR) diet containing 5.77% SBM] or the FSBM group (the experimental TMR diet containing 5.55% FSBM), in a completely randomized design. The entire period of this trial consisted of 14 days for the adjustment and 40 days for data and sample collection, and sampling for rumen liquid, blood, milk, and urine was conducted on the 34th and 54th day, respectively. When SBM was completely replaced by FSBM, the levels of several medium-chain FA in milk (i.e., C13:0, C14:1, and C16:0) rose significantly (p < 0.05), while the concentrations of a few milk long-chain FA (i.e., C17:0, C18:0, C18:1n9c, and C20:0) declined significantly (p < 0.05). Besides, the densities of urea nitrogen and lactic acid were significantly (p < 0.05) higher, while the glucose concentration was significantly (p < 0.05) lower in the blood of the FSBM-fed cows than in the SBM-fed cows. Based on the metabolomics analysis simultaneously targeting the rumen liquid, plasma, milk, and urine, it was noticed that substituting FSBM for SBM altered the metabolic profiles of all the four biofluids. According to the identified significantly different metabolites, 3 and 2 amino acid-relevant metabolic pathways were identified as the significantly different pathways between the two treatments in the rumen fluid and urine, respectively. Furthermore, glycine, serine, and threonine metabolism, valine, leucine, and isoleucine biosynthesis, and cysteine and methionine metabolism were the three key integrated different pathways identified in this study. Results mainly implied that the FSBM replacement could enhance nitrogen utilization and possibly influence the inflammatory reactions and antioxidative functions of dairy cattle. The differential metabolites and relevant pathways discovered in this experiment could serve as biomarkers for the alterations in protein feed and nitrogen utilization efficiency of dairy cows, and further investigations are needed to elucidate the definite roles and correlations of the differential metabolites and pathways.
Establishing an MRI-Based Protocol and Atlas of the Bearded Dragon (Pogona vitticeps) Brain
Authors: Foss Kari D. , Keller Krista A. , Kehoe Spencer P. , Sutton Bradley P.
Published: May 2022

The bearded dragon (Pogona vitticeps) has become a popular companion lizard, and as such, clients have increasingly come to expect the application of advanced diagnostic and therapeutic options in their care. The purpose of this study was to establish an MRI-based protocol and brain atlas to improve diagnostic capabilities in bearded dragons presenting with neurologic dysfunction. Using a high-field 3T magnet, in vivo MRI of the brain was successfully performed in seven healthy bearded dragons utilizing an injectable anesthetic protocol utilizing intravenous alfaxalone. From this, we created an atlas of the brain in three planes, identifying nine regions of interest. A total scan time of 35 min allowed for the collection of a quality diagnostic scan and all lizards recovered without complication. This study provides practitioners a neuroanatomic reference when performing brain MRI on the bearded dragon along with a concise and rapid MRI protocol.
Design, Analysis, and Testing of a Scaled Propeller for an Innovative Regional Turboprop Aircraft
Authors: Ciliberti Danilo , Nicolosi Fabrizio
Published: May 2022

This paper describes the design, numerical analyses, and wind tunnel tests of the scaled model of a propeller serving as a propulsive element for the experimental tests of an advanced regional turboprop aircraft with engines installed on the horizontal tailplane tips. The design has been performed by complying with the thrust similarity from the full-scale aircraft propulsive requirements. Numerical analyses with a high-fidelity aerodynamic solver confirmed that the initial design made with XROTOR would achieve the expected performance. Finally, a strengthened version of the propeller has been manufactured via 3D printing and tested in the wind tunnel. Test data include measurements of thrust as well as propeller normal force at different angles of attack. Good agreement between numerical and experimental results has been observed, enabling the propeller to be used confidently in the aircraft wind tunnel powered test campaign.
Non-Structural Carbohydrates, Foliar Nutrients, Yield Components and Oxidative Metabolism in Pecan Trees in Response to Foliar Applications of Growth Regulators
Authors: Ojeda-Barrios Damaris Leopoldina , Orozco-Meléndez Laura Raquel , Cano-Medrano Raquel , Sánchez-Chávez Esteban , Parra-Quezada Rafael Ángel , Calderón-Jurado Marisela , Jacobo-Cuellar Juan Luis , Hernández-Ordoñez Elizabeth , Cruz-Álvarez Oscar
Published: May 2022

Foliar sprays of growth regulators have commercial potential for improving the performance of some of the parameters associated with alternate bearing in pecan trees. The objective was to evaluate the behaviour of alternate bearing through analysis of seasonal variations in buds and leaflets of non-structural carbohydrates (glucose, fructose, sucrose, and starch), mineral nutrients (N-total, P, K+, Ca2+, Mg2+, Fe2+, Cu2+, Mn2+ and Zn2+), yield components (nut weight per kilogram and kernel percentage) and oxidative metabolism (superoxide dismutase, hydrogen peroxide, catalase, guaiacol peroxidase and antioxidant capacity) in cv. Wichita pecan trees in response to foliar applications of gibberellic acid (50 mg L−1), calcium prohexadione (500 mg L−1) or thidiazuron (10 mg L−1). The experiment was of a completely randomized experimental design with five replicates. Foliar growth regulator (GRs) sprays help maintain the concentration of non-structural carbohydrates in the leaflets and buds between the evaluation years. With the exception of K+ (12.9 and 10.9 g kg−1) and Zn2+ (45.1 and 30.5 mg kg−1), the GRs did not show any effects on the concentrations of the foliar mineral nutrients. The results suggest foliar sprays of gibberellic acid improve the performance of parameters associated with alternate bearing, including oxidative metabolism.
Coping Strategies of Smallholder Coffee Farmers under the COVID-19 Impact in Indonesia
Authors: Wulandari Suci , Djufry Fadjry , Villano Renato
Published: May 2022

COVID-19 significantly impacts coffee production, which smallholders dominate. Unaddressed impacts will affect coffee production sustainability. However, smallholders face some constraints. This study aims to determine the impact of COVID-19 from the perspective of Arabica and Robusta farmers in Indonesia, examine technical recommendations as coping strategies, and develop an institutional model to accelerate implementation. We analyzed the divergences in the perceptions of different categories and clusters using farm-level data. Descriptive statistics, Mann–Whitney analysis, cluster analysis, and crosstab analysis were used to explore the facts. Immediate effects of COVID-19 were observed through a decline in household income, impacting the allocation of farming costs, which influences productivity related to the intensity of cultivation, particularly in purchasing and fertilization decisions. It was explored by the study that coffee livestock integration is an important strategy to improve farmers’ livelihood to mitigate the impact. The innovation sharing model complements this technical recommendation as institutional recommendations, including innovation sharing elements and processes. Four farmer clusters have been identified based on the adoption spectrum and farmer conditions. The intervention provides innovation-sharing elements for farmers who have not adopted integration. Where integration was partially completed, reusing waste is recommended by completing innovation elements and improving the sharing process.
(1→3)-α-D-glucooligosaccharides as Elicitors Influencing the Activity of Plant Resistance Pathways in Wheat Tissues
Authors: Nowak Artur , Tyśkiewicz Renata , Wiater Adrian , Jaroszuk-Ściseł Jolanta
Published: May 2022

Laetiporus sulphureus (Bull.: Fr.) Murrill is an arboreal species of the large-fruited Basidiomycota fungus from the Polyporales, family Laetiporaceae. The cell wall of this fungus is the source of many bioactive polymer compounds, including (1→3)-α-D-glucans. (1→3)-α-D-glucans can be hydrolyzed to shorter compounds, (1→3)-α-D-glucooligosaccharides (GOS), with different degrees of polymerization (DP). The use of GOS obtained from L. sulphureus (1→3)-α-D-glucans, as an elicitor of plant resistance, may be important for biological protection used in sustainable agriculture. In the presented study, GOS influenced the activity of antioxidant enzymes (Catalase−CAT, Ascorbate Peroxidase−APX, Guaiacol Peroxidase−GPX, and Superoxide Dismutase−SOD), lignin and flavonoids producing phenylpropanoids pathways (Phenylalanine Ammonia-Lyase−PAL and Tyrosine Ammonia-Lyase−TAL), and pathogen-related proteins (with Glucanase−GLUC and Chitinase−CHIT activity) in wheat (Triticum aestivum L.) seedling tissues. Other than that, the application of GOS increased the fresh weight of wheat stems and roots by 1.5–2-times, compared to the water control. The GOS at a concentration of 0.05% most strongly increased the activity of APX and GPX, where a 2-fold (up to 6000 U) and a 3-fold (up to 180 U) increase in enzymatic activity in wheat stems was observed, compared to the control. Simultaneously, 0.1% GOS significantly increased the activity of PAL (80 U in stems and 50 U in roots) and TAL (60 U in stems and 50 U in roots), where a 4–5-fold increase in enzymatic activity was observed, both in comparison to the water control and commercial elicitors (chitosan−CHI and laminarin−LAM). No effect of GOS on GLUC activity was observed, but a 1.5–2-fold increase in CHIT activity in plant tissues was noted. The complexity of the influence of GOS on the level of marker enzymes indicates the potential of their application in agriculture. This work is the first report of the successful use of (1→3)-α-D-glucooligosaccharides as an elicitor inducing resistance in the cereal plant (wheat).
Fine Mapping and Functional Analysis of Major QTL, CRq for Clubroot Resistance in Chinese Cabbage (Brassica rapa ssp. pekinensis)
Authors: Wei Xiaochun , Li Jundang , Zhang Xiaowei , Zhao Yanyan , Nath Ujjal Kumar , Mao Lixia , Xie Zhengqing , Yang Shuangjuan , Shi Gongyao , Wang Zhiyong , Tian Baoming , Su Henan , Yang Zhiyuan , Wei Fang , Yuan Yuxiang
Published: May 2022

Clubroot disease caused by Plasmodiophora brassicae is one of the major threats to Brassica crops. New clubroot resistant varieties of Chinese cabbage (B. rapa ssp. pekinensis) have been developed through breeding, but the underlying genetic mechanism of clubroot resistance is still unclear. In this study, two Chinese cabbage DH lines, clubroot-resistant Y635-10 and susceptible Y177-47 were crossed to develop F2 population for fine mapping and cloning resistance gene CRq. After sequence analysis, the expression vector was constructed by gateway technology and transferred into Arabidopsis thaliana for functional characterization. Bulked segregant analysis sequencing (BSA-seq) confirmed that CRq is located in the 80 kb genomic region on chromosome A03 between markers GC30-FW/RV and BGA. In silico tools confirmed that the gene length was 3959 bp with 3675 bp coding sequences (CDs), and it has three exons and two introns. In addition, we found 72bp insertion in the third exon of CRq in the susceptible line. We developed and verified functional marker Br-insert1, by which genotyping results showed that 72bp insertion might lead to the destruction of the LRR region of Y177-47, resulting in a loss of resistance relative to clubroot. The results of genetic transformation showed that the roots for wild-type Arabidopsis thaliana were significantly enlarged compared with T2 generation transgenic Arabidopsis after treatment by P. brassicae spores, and transgenic Arabidopsis had certain resistance. Therefore, CRq is a candidate gene of clubroot disease resistance in Chinese cabbage, which could be used as a reference for elucidating disease resistance mechanisms and the marker-assisted breeding of clubroot resistant varieties.
Analysis of Load-Sharing and Contact Characteristics of the Concentric Face Gear Split-Torque Transmission System with Elastic Supports
Authors: Gong Fei , Zhu Rupeng , Li Pingjun , Jin Guanghu
Published: May 2022

The concentric face gear split-torque transmission system (CFGSTTS) is a new form of drive that is primarily used in helicopter transmission systems. Its load-sharing performance among different branches and tooth contact characteristics have a great impact on the service life of helicopter transmissions. It contains ten meshing pairs, the load distribution is complicated, and the tooth contact areas are difficult to determine. Therefore, based on the multi-point constraint method and nonconforming grid, a quasi-static analysis model of the CFGSTTS coupled with flexible supports was established and the load-sharing performance and contact characteristics were studied. The model considered the support stiffness, backlash, installation error, and web structure of the upper face gear, which could comprehensively reflect the meshing state of the system. The load-sharing coefficient curves, tooth contact area diagram, and meshing force were obtained. The results indicated that (1) a larger idler support stiffness and a smaller input gear support stiffness could achieve better load equalization performance; (2) better load equalization between idler gears could be acquired with a lower face gear support stiffness factor of approximately 0.9; (3) increasing the axial mounting error caused the contact area to shift to the top and inner end of the face gear tooth, which was detrimental to the transmission; and (4) adjusting the backlash of the idler gears, input gears, and tail gear had little influence on the load balance and contact.
Mobile Internet Technology Adoption for Sustainable Agriculture: Evidence from Wheat Farmers
Authors: Khan Nawab , Ray Ram L. , Kassem Hazem S. , Zhang Shemei
Published: May 2022

Mobile internet technology (MIT) is considered a significant advancement in information and communication technology (ICT), due to its crucial impact on the financial system and social life. In addition, it is an essential technology to overcome the digital divide between urban and rural areas. In terms of agricultural advancement, MIT can play a key role in data collection and the implementation of smart agricultural technologies. The main objectives of this study were to (i) investigate MIT adoption and use in sustainable agriculture development among selected wheat farmers of Pakistan and (ii) examine the crucial factors influencing MIT adoption. This study selected 628 wheat farmers from four districts of Khyber Pakhtunkhwa Province (KPK), Pakistan, for sampling. This study used a bivariate probit method for sampling wheat farmers. The analysis of wheat farmer’s data showed farmer’s age, farm size, farm location, and knowledge about Internet technology (IT) are strongly correlated with MIT adoption in sustainable agriculture development. Results showed on average, 65% of wheat farmers have mobile devices supporting these Internet technologies, and 55% use MIT in agricultural environments. Since the extant research on MIT adoption for agriculture production in Pakistan is sparse, this study helps advance MIT adoption-based studies. These outcomes may draw the attention of decision-makers dealing with IT infrastructure and agricultural equipment who can support farmers adopting MIT.
Micro-Computed Tomography Soft Tissue Biological Specimens Image Data Visualization
Authors: Gaspar Branislav , Mrzilkova Jana , Hozman Jiri , Zach Petr , Lahutsina Anastasiya , Morozova Alexandra , Guarnieri Giulia , Riedlova Jitka
Published: May 2022

Visualization of soft tissues in microCT scanning using X-rays is still a complicated matter. There is no simple tool or methodology on how to set up an optimal look-up-table while respecting the type of soft tissue. A partial solution may be the use of a contrast agent. However, this must be accompanied by an appropriate look-up-table setting that respects the relationship between the soft tissue type and the Hounsfield units. The main aim of the study is to determine experimentally derived look-up-tables and relevant values of the Hounsfield units based on the statistical correlation analysis. These values were obtained from the liver and kidneys of 24 mice in solutions of ethanol as the centroid value of the opacity look-up-table area under this graph. Samples and phantom were scanned by a Bruker SkyScan 1275 micro-CT and Phywe XR 4.0 and processed using CTvox and ORS Dragonfly software. To reconstruct the micro-CT projections, NRecon software was used. The main finding of the study is that there is a statistically significant relationship between the centroid of the area under the look-up-table curve and the number of days for which the animal sample was stored in an ethanol solution. H1 of the first hypothesis, i.e. that suggested the Spearman’s correlation coefficient does not equal zero (r1 ≠ 0) regarding this relationship was confirmed. On the other hand, there is no statistically significant relationship between the centroid of the area under the look-up-table curve and the concentration of the ethanol solution. In this case, H1 of the second hypothesis, i.e. that the Spearman’s correlation coefficient does not equal zero (r2 ≠ 0) regarding this relationship was not confirmed. Spearman’s correlation coefficients were −0.27 for the concentration and −0.87 for the number of days stored in ethanol solution in the case of the livers of 13 mice and 0.06 for the concentration and 0.94 for the number of days stored in ethanol solution in the case of kidneys of 11 mice.
An Accurate Multiple Sclerosis Detection Model Based on Exemplar Multiple Parameters Local Phase Quantization: ExMPLPQ
Authors: Macin Gulay , Tasci Burak , Tasci Irem , Faust Oliver , Barua Prabal Datta , Dogan Sengul , Tuncer Turker , Tan Ru-San , Acharya U. Rajendra
Published: May 2022

Multiple sclerosis (MS) is a chronic demyelinating condition characterized by plaques in the white matter of the central nervous system that can be detected using magnetic resonance imaging (MRI). Many deep learning models for automated MS detection based on MRI have been presented in the literature. We developed a computationally lightweight machine learning model for MS diagnosis using a novel handcrafted feature engineering approach. The study dataset comprised axial and sagittal brain MRI images that were prospectively acquired from 72 MS and 59 healthy subjects who attended the Ozal University Medical Faculty in 2021. The dataset was divided into three study subsets: axial images only (n = 1652), sagittal images only (n = 1775), and combined axial and sagittal images (n = 3427) of both MS and healthy classes. All images were resized to 224 × 224. Subsequently, the features were generated with a fixed-size patch-based (exemplar) feature extraction model based on local phase quantization (LPQ) with three-parameter settings. The resulting exemplar multiple parameters LPQ (ExMPLPQ) features were concatenated to form a large final feature vector. The top discriminative features were selected using iterative neighborhood component analysis (INCA). Finally, a k-nearest neighbor (kNN) algorithm, Fine kNN, was deployed to perform binary classification of the brain images into MS vs. healthy classes. The ExMPLPQ-based model attained 98.37%, 97.75%, and 98.22% binary classification accuracy rates for axial, sagittal, and hybrid datasets, respectively, using Fine kNN with 10-fold cross-validation. Furthermore, our model outperformed 19 established pre-trained deep learning models that were trained and tested with the same data. Unlike deep models, the ExMPLPQ-based model is computationally lightweight yet highly accurate. It has the potential to be implemented as an automated diagnostic tool to screen brain MRIs for white matter lesions in suspected MS patients.
Impacts of Learning Orientation on the Modeling of Programming Using Feature Selection and XGBOOST: A Gender-Focused Analysis
Authors: Woo HoSung , Kim Ja-Mee
Published: May 2022

In programming, modeling is a generalized explanatory system that organizes key characteristics of a specific matter or object of interest using computer science concepts. Modeling is integral for both automation design in programming education and communication in the collaborative process. This study investigates the effect of learning orientation on the modeling stage based on gender. The study includes 756 male and 688 female elementary-school students. We analyzed the results of XGBOOST by extracting the influential characteristics from feature selection along with the basic statistics. As a result of the study, it was confirmed that learners, regardless of gender, had the largest gap in modeling and that this was the stage at which differences occurred in programming education. For male students, the process of collecting data for modeling or devising a solution was found to be an important learning method. This shows that it is necessary to create an environment to focus on activities that derive solutions from the collected data along with strengthening information retrieval education. Although female students showed a similar tendency to male students, the process of cooperating with friends as a differentiating factor was found to be an important learning method. It seems necessary to apply teaching and learning methods that can strengthen team projects that can collaborate with friends. The findings could serve as a reference for teaching and learning design and operation for effective programming education.
Influencing Factors of the Length of Lane-Changing Buffer Zone for Autonomous Driving Dedicated Lanes
Authors: Hou Fujin , Zhang Ying , Wang Shujian , Shen Zhengxi , Mao Peipei , Qu Xu
Published: May 2022

With the development of intelligent transportation, dedicated highway lanes for autonomous vehicles (AVs), necessary for ensuring their right of way, have emerged as critical issues in intelligent transportation research, which makes it necessary to set up specialized lane-changing buffer zones in the lane adjacent to the dedicated one. Restricted by the current situation of intelligent transportation systems, based on NGSIM data, this study filters out typical lane-changing description data featuring lane-changing behaviors and constructs a principal component analysis (PCA) model containing factors affecting the longitudinal driving distance during the whole lane-changing procedure. The validity of the model is evaluated with a significance test. Comparing the PCA model to a general linear regression model, suggestions on setting the length of lane-changing buffer zones are put forward. The length of the buffer zone mainly considers speed, acceleration, and the flow in the dedicated lane. In general, a shorter buffer zone length can be achieved by increasing the design speed of the buffer zone, raising the headway of AVs in the dedicated lane, reducing the acceleration rate of lane-changing vehicles, and reducing the time proportion of the lane change preparation stage, which occurs earlier in the procedure.
Radical Concept Generation Inspired by Cross-Domain Knowledge
Authors: Zhang Junlei , Tan Runhua
Published: May 2022

Cross-domain knowledge can stimulate radical concept generation (RCG), but there is a lack of guidance to utilize the cross-domain knowledge for RCG. This paper proposes an effective process of RCG in four steps: (1) Identifying radical technology opportunities based on analysis of the dynamic relationship between demand and technical performances; (2) Applying laws and lines of the technological system evolution to determine the search direction of cross-domain knowledge in a qualitative perspective; (3) Taking the minimum complementary distance measure for appropriate cross-domain knowledge in a quantitative perspective; (4) Forming radical concepts using the cross-domain knowledge as inspirations. The method reduces risks and costs caused by uncertainty in RCG and has potential to fertilize research on radical innovation and knowledge-based innovation. A radical concept of gas generator demonstrates the effectiveness of the proposed method.
End-to-End Convolutional Neural Network Framework for Breast Ultrasound Analysis Using Multiple Parametric Images Generated from Radiofrequency Signals
Authors: Kim Soohyun , Park Juyoung , Yi Joonhwan , Kim Hyungsuk
Published: May 2022

Breast ultrasound (BUS) is an effective clinical modality for diagnosing breast abnormalities in women. Deep-learning techniques based on convolutional neural networks (CNN) have been widely used to analyze BUS images. However, the low quality of B-mode images owing to speckle noise and a lack of training datasets makes BUS analysis challenging in clinical applications. In this study, we proposed an end-to-end CNN framework for BUS analysis using multiple parametric images generated from radiofrequency (RF) signals. The entropy and phase images, which represent the microstructural and anatomical information, respectively, and the traditional B-mode images were used as parametric images in the time domain. In addition, the attenuation image, estimated from the frequency domain using RF signals, was used for the spectral features. Because one set of RF signals from one patient produced multiple images as CNN inputs, the proposed framework overcame the limitation of datasets in a broad sense of data augmentation while providing complementary information to compensate for the low quality of the B-mode images. The experimental results showed that the proposed architecture improved the classification accuracy and recall by 5.5% and 11.6%, respectively, compared with the traditional approach using only B-mode images. The proposed framework can be extended to various other parametric images in both the time and frequency domains using deep neural networks to improve its performance.
Neuroplasticity-Based Pruning Method for Deep Convolutional Neural Networks
Authors: Camacho Jose David , Villaseñor Carlos , Lopez-Franco Carlos , Arana-Daniel Nancy
Published: May 2022

In this paper, a new pruning strategy based on the neuroplasticity of biological neural networks is presented. The novel pruning algorithm proposed is inspired by the knowledge remapping ability after injuries in the cerebral cortex. Thus, it is proposed to simulate induced injuries into the network by pruning full convolutional layers or entire blocks, assuming that the knowledge from the removed segments of the network may be remapped and compressed during the recovery (retraining) process. To reconnect the remaining segments of the network, a translator block is introduced. The translator is composed of a pooling layer and a convolutional layer. The pooling layer is optional and placed to ensure that the spatial dimension of the feature maps matches across the pruned segments. After that, a convolutional layer (simulating the intact cortex) is placed to ensure that the depth of the feature maps matches and is used to remap the removed knowledge. As a result, lightweight, efficient and accurate sub-networks are created from the base models. Comparison analysis shows that in our approach is not necessary to define a threshold or metric as the criterion to prune the network in contrast to other pruning methods. Instead, only the origin and destination of the prune and reconnection points must be determined for the translator connection.
Color Recognition of Transparent Plastic Based on Multi-Wavelength Transmission Spectrum
Authors: Shi Chaoyi , Dai Fuliang , Lu Cuiping , Yu Shaohui , Lu Meina , Gao Xianhe , Wang Zhongma , Zhang Sheng
Published: May 2022

Plastic recycling is the most effective way to solve plastic pollution. Color recognition of plastic is a key step in the plastic recycling process, which is very important for improving the utilization rate of waste plastic. At present, the manual recognition method is inefficient and cannot meet the requirements of large-scale production, while the existing color recognition based on machine vision has problems such as low recognition accuracy of similar colors, complicated algorithm and high system cost. According to the above problems, a color recognition method based on multi-wavelength transmission spectrum was proposed in this paper for the color recognition of colorless, light blue, light green and apple green transparent plastic. For each transparent plastic, the transmission spectra at 381 nm, 439 nm, 620 nm and white transmission light source were obtained, and the ratios of R, G and B wavebands of the transmission spectra were used to set up a color feature, which was then used for color recognition. A color recognition model was established based on the color features and naive Bayes model. The 10-fold cross-validation results showed that the recognition accuracy of the four colors of transparent plastic reached 100%.
Some Generalizations of the Jensen-Type Inequalities with Applications
Authors: Rodić Mirna
Published: May 2022

Motivated by some results about reverses of the Jensen inequality for positive measure, in this paper we give generalizations of those results for real Stieltjes measure dλ which is not necessarily positive using several Green functions. Utilizing these results we define some new mean value theorems of Lagrange and Cauchy types, and derive some new Cauchy-type means.