bluuebunny/crossref_metadata_2025 huggingface dataset:
Current Situation and Strategy Formulation of College Sports Psychology Teaching Following Adaptive Learning and Deep Learning Under Information Education
Authors: Mou Chuan , Tian Yi , Zhang Fengrui , Zhu Chao
Published: January 2022

This study aims to explore the current situation and strategy formulation of sports psychology teaching in colleges and universities following adaptive learning and deep learning under information education. The informatization in physical education, teaching methods, and teaching processes make psychological education more scientific and efficient. First, the relevant theories of adaptive learning and deep learning are introduced, and an adaptive learning analysis model is implemented. Second, based on the deep learning automatic encoder, college students’ sports psychology is investigated and the test results are predicted. Finally, the current situation and development strategy of physical education in colleges and universities are analyzed. The results show that when the learning rate is 1, 0.1, and 0.01, there is no significant change in the analysis factors of recall, ndcg, item_coverage, and sps. When the learning rate is 1, their analysis factors change obviously, and it is calculated that the optimal learning rate of the model is 1. And the difficulty of the recommended test questions by using the sports psychology teaching method based on adaptive learning and deep learning is relatively stable. The test questions include various language points of sports psychology. Compared with others methods, adaptive learning and deep learning can provide comprehensive test questions for sports psychology teaching. This study provides technical support for the reform of sports psychology teaching in colleges and universities and contributes to optimizing the information-based teaching mode.
Tongue Postures and Tongue Centers: A Study of Acoustic-Articulatory Correspondences Across Different Head Angles
Authors: Chiu Chenhao , Weng Yining , Chen Bo-wei
Published: January 2022

Recent research on body and head positions has shown that postural changes may induce varying degrees of changes on acoustic speech signals and articulatory gestures. While the preservation of formant profiles across different postures is suitably accounted for by the two-tube model and perturbation theory, it remains unclear whether it is resulted from the accommodation of tongue postures. Specifically, whether the tongue accommodates the changes in head angle to maintain the target acoustics is yet to be determined. The present study examines vowel acoustics and their correspondence with the articulatory maneuvers of the tongue, including both tongue postures and movements of the tongue center, across different head angles. The results show that vowel acoustics, including pitch and formants, are largely unaffected by upward or downward tilting of the head. These preserved acoustics may be attributed to the lingual gestures that compensate for the effects of gravity. Our results also reveal that the tongue postures in response to head movements appear to be vowel-dependent, and the tongue center may serve as an underlying drive that covariates with the head angle changes. These results imply a close relationship between vowel acoustics and tongue postures as well as a target-oriented strategy for different head angles.
A Comparison of Caregiver Burden for Different Types of Dementia: An 18-Month Retrospective Cohort Study
Authors: Huang Wen-Chien , Chang Ming-Che , Wang Wen-Fu , Jhang Kai-Ming
Published: January 2022

Background

This study aimed to elucidate the influence of dementia etiologies on the degree of caregiver burden and determine which factors predict a high caregiving burden.

Methods

This 18-month retrospective cohort study enrolled 630 patients and their caregivers from the Dementia Center of Changhua Christian Hospital. The care team performed face-to-face interviews every 6 months, for 18 months from when a diagnosis of dementia was made. The primary outcome was the change in Zarit Burden Interview (ZBI) scores. Generalized estimating equations were used for the longitudinal data analysis.

Results

Participants with Lewy body disease (LBD) had a significantly higher caregiving burden compared with those with Alzheimer's disease (AD) (β = 3.83 ± 1.47, Wald = 6.79, p = 0.009) after adjusting for patient and caregiver features. Caregivers of mixed-type dementia and frontotemporal dementia (FTD) experienced a greater burden than caregivers of AD, at 6- and 18-month follow-up. Patients with more severe dementia, neuropsychiatric symptoms, being cared for by more than two caregivers, or utilizing social resources were associated with higher ZBI scores; the depressive mood of caregiver also predicted higher ZBI scores.

Conclusion

This longitudinal study demonstrated that caregiver burden was influenced by the underlying dementia etiology of patients. The dementia care team should provide personalized education and transfer patients and caregivers to appropriate resources, especially for high-risk populations.
Applying Relatedness to Explain Learning Outcomes of STEM Maker Activities
Authors: Weng Xiaojing , Chiu Thomas K. F. , Jong Morris S. Y.
Published: January 2022

A growing interest has been observed among K-12 school educators to incorporate maker pedagogy into science, technology, engineering, and mathematics (STEM) education to engage students in the design and making process. Both cognitive engagement and emotional engagement of students can be promoted through satisfying the psychological need of relatedness that concerns a sense of connection and belonging. How to support relatedness would influence the effective development of students’ cognitive competencies, namely creativity and critical thinking, and non-cognitive characteristics, namely interest and identity. Therefore, the present study investigated how two relatedness support strategies—real-world problems (RWP) and mentoring influence the development of student’s STEM-related cognitive competencies and non-cognitive characteristics in STEM marker activities. We implemented a 7-week intervention study with three classes of Grade 9 students (aged 13–15 years) in Hong Kong (n = 95). Three intervention conditions were designed in the experiment, comprising textbook problem (TBP), RWP, and RWP with mentoring (RWPM). Our analysis showed that (i) the differences in creativity among the three groups were non-significant, (ii) the RWP and RWPM groups showed stronger critical thinking than the TBP group, and (iii) the RWPM group exhibited stronger STEM interest and identity than the other two groups. This study revealed the effectiveness of adopting RWP strategy in developing secondary students’ perceived cognitive competencies (e.g., creativity and critical thinking) and the feasibility of employing a mentoring mechanism for cultivating learners’ perceived non-cognitive characteristics (e.g., STEM identity and interest). Hence, we also offered practical suggestions for teachers.
Tracking Study on the Relapse and Aftercare Effect of Drug Patients Released From a Compulsory Isolated Detoxification Center
Authors: Liu Nian , Lu Zekai , Xie Ying
Published: January 2022

Background and Aims

There are no accurate statistical data on the relapse rate of drug abstainers after compulsory detoxification in China. This study aimed to collect relapse data for drug abstainers through follow-up visits, verify the effectiveness of professional social worker services and explore significant factors affecting relapse.

Design and Setting

The drug abstainers released from Guangzhou T Compulsory Isolated Detoxification Center were randomly divided into two groups. The difference between the experimental group and the control group is that assistance services were provided by social workers to the former.

Participants

The study included 510 drug abstainers released from T Center, including 153 in the experimental group and 357 in the control group.

Measurements

Demographic information, history of drug abuse, and motivation for drug rehabilitation (SOCRATES) were collected 1 month prior to drug abstainer release from compulsory detoxification. Then, the relapse situation after their release was tracked according to fixed time points.

Findings

The overall relapse rate of 510 drug abstainers after their release from compulsory detoxification was 47.6%. The average survival time to relapse based on survival analysis was 220 days (N = 486), as calculated with Bayesian estimation by the MCMC method. The average survival times to relapse of the experimental group and control group were 393 and 175 days, respectively. By taking the specific survival time as the dependent variable and the group as the control variable (OR = 25.362), logistic regression analysis showed that marital status (OR = 2.666), previous compulsory detoxification experience (OR = 2.329) and location of household registration (OR = 1.557) had a significant impact on the survival time to relapse.

Conclusions

The occurrence of relapse among drug patients released from compulsory detoxification can be delayed effectively through the intervention of professional social worker services. Regardless of whether patients receive aftercare after compulsory detoxification, drug-using patients who are single, have multiple detoxification experiences and whose households are registered in other provinces deserve special attention. Relevant suggestions to avoid relapse are provided.
The Impact of COVID-19 Pandemic on Weight and Body Mass Index in Saudi Arabia: A Longitudinal Study
Authors: Alshahrani Saeed Mastour , Alghannam Abdullah F. , Taha Nada , Alqahtani Shurouq Saeed , Al-Mutairi Abrar , Al-Saud Nouf , Alghnam Suliman
Published: January 2022

The COVID-19 pandemic has had a major impact on various health conditions. The objective of this study was to assess the impact of the COVID-19 pandemic on body weight and body mass index (BMI) in Saudi Arabia. We used electronic health records obtained from a healthcare system representing five hospitals in three different regions in the Kingdom to examine the change in weight utilizing a longitudinal design. The study included all adults who had visited outpatient clinics in two different time points, pre-2020 (years 2018 and 2019 prior to COVID-19) and post-2020 (the year 2021). Weight and BMI changes in percentages were described. Also, bivariate chi-square test, paired t-test, and multivariable multinomial logistic regression model were used for the analyses. A total of 165,279 individuals were included in the study. On average, a significant weight gain of 0.33 kg (95% CI: 0.29–0.36) was observed in our study. Approximately 10% of the population had shifted to either overweight or obese BMI classes during the study period, as 4.8% of those with normal BMI pre-2020 had shifted to overweight or obese classes at post-2020, and 5.1% of those who were overweight had shifted to obese class. Also, 23.1% of the population had gained 5% or more of their pre-2020 weight, while 17% had lost 5% or more. Young individuals were over three times more likely to gain 5% or more than older individuals (OR: 3.34; 95% CI: 3.12–3.56). Females had 24% higher odds to gain 5% or more of their pre-2020 weight than males (OR: 1.24; 95% CI: 1.21–1.27). Diabetics were 27% more likely to lose 5% or more than non-diabetics (OR: 1.27; 95% CI: 1.23–1.31). Our findings provide insights into the impact of COVID-19 on weight and population health. Further investment in interventions for weight management is warranted during similar circumstances such as lockdowns due to infection waves or new variants. Future studies are also needed to explore the modifications that have occurred during the pandemic in the weight-related lifestyle factors such as dietary choices and physical activity levels.
Profile and Predictors of Maternal Quality of Life During Physiological Pregnancy: A Cross-Sectional Analysis
Authors: Ishaq Rabia , Shoaib Maryam , Baloch Nosheen Sikander , Sadiq Abdul , Raziq Abdul , Huma Zil e , Raza Shanaz , Batool Fakhra , Haider Sajjad , Saleem Fahad , Ahmad Nafees , Iqbal Qaiser , Khan Amer Hayat
Published: January 2022

Background

Quality of Life (QoL) and its determinants are significant in all stages of life, including pregnancy. The physical and emotional changes during pregnancy affect the QoL of pregnant women, affecting both maternal and infant health. Hence, assessing the QoL of pregnant women is gaining interest in literature. We, therefore, aimed to describe the QoL of pregnant women during physiological pregnancy and to identify its associated predictors in women attending a public healthcare institute of Quetta city, Pakistan.

Methods

A cross-sectional study was conducted at the Obstetrics and Gynecology Department of Sandeman Provincial Hospital Quetta city, Pakistan. The respondents were asked to answer the Urdu (lingua franca of Pakistan) version of the Quality of Life Questionnaire for Physiological Pregnancy. Data were coded and analyzed by SPPS v 21. The Kolmogorov–Smirnov test was used to establish normality of the data and non-parametric tests were used accordingly. Quality of Life was assessed as proposed by the developers. The Chi-square test was used to identify significant associations and linear regression was used to identify the predictors of QoL. For all analyses,p< 0.05 was taken significantly.

Results

Four hundred and three pregnant women participated in the study with a response rate of 98%. The mean QoL score was 19.85 ± 4.89 indicating very good QoL in the current cohort. The Chi-Square analysis reported a significant association between age, education, occupation, income, marital status, and trimester. Education was reported as a positive predictor for QoL (p= 0.006, β = 2.157). On the other hand, trimester was reported as a negative predictor of QoL (p= 0.013, β = −1.123).

Conclusion

Improving the QoL among pregnant women requires better identification of their difficulties and guidance. The current study highlighted educational status and trimester as the predictors of QoL in pregnant women. Health care professionals and policymakers should consider the identified factors while designing therapeutic plans and interventions for pregnant women.
Atmospheric, Geomorphological, and Compositional Analysis of Martian Asimov and Hale Craters: Implications for Recurring Slope Lineae
Authors: Howari Fares M. , Sharma Manish , Xavier Cijo M. , Nazzal Yousef , Alaydaroos Fatima
Published: January 2022

Recurring slope lineae (RSL) are small, dark, seasonal albedo features lengthening down “warm” Martian steep slopes. Their origin has been attributed to both liquid and dry processes, hence representing one of the major open science questions on present day Mars. In the present study, we report a catalog of previous literature and newly added RSL sites making a total of 940 sites globally on Mars along with the detailed geological and compositional investigation of the Hale and Asimov craters with their RSL features. We also estimate temperature and atmospheric water abundances in the study area, which are two of the main factors to explain the origin and formation of RSL. The study found that the Asimov crater’s local temperatures are high enough to allow either the melting of brines or deliquescence of calcium perchlorate and other salts during the HiRISE observation period and found the water vapor column to be nearly five times higher than those measured “before RSL appearance.” This supports the theory of deliquescence as one of the mechanisms for the regolith-atmosphere interaction and RSL formation in the studied crater, which suggests that minerals absorb moisture from the environment until the minerals dissolve in the absorbed water and yield a solution. We also used compact reconnaissance imaging spectrometer for Mars–derived browse products for a compositional study associated with RSL features hosting craters and surface characteristics of Mars.
Calculating the Social Return on Investment of a Japanese Professional Soccer Team's Corporate Social Responsibility Activities
Authors: Oshimi Daichi , Yamaguchi Shiro , Fukuhara Takayuki , Tagami Yoshifumi
Published: January 2022

In response to the lack of evidence for visualizing the monetary value of professional sport teams' CSR-related social impact, this study aimed to calculate the social impact of a Japanese professional soccer team's corporate social responsibility (CSR) activity (i.e., community soccer/physical activity program) by using a social return on investment (SROI) framework. Specifically, Matsumoto Yamaga Football Club was used for the estimation. This professional soccer team was ranked in the top division of the league (J1) during the estimation period and engaged in CSR activities at 129 community soccer schools in a year (2019–2020). The SROI calculation involved five stages: (1) identifying key stakeholders, (2) mapping inputs, outputs, and outcomes, (3) measuring and valuing outcomes, (4) establishing impact, and (5) calculating SROI. For the first step, we specified seven major stakeholders (soccer team, nursery school children, parents, coaches, teachers, local governments, and local football associations) and conducted interview investigations with each stakeholder. Our result showed that the social value of the teams' targeted community soccer school was USD 54,160, and the total financial and non-financial inputs to the school were USD 10,134, meaning an SROI ratio of 5.3. This means that for every USD invested in a community soccer school, social benefit worth USD 5.3 was generated. This study contributes to advancing social impact research in sport by shedding light on the monetary value of the social impact of professional sport teams' CSR activities. In addition, it also has practical implications for team managers looking to utilize CSR activities as a management strategy, through cost-effective investment and optimization of resources.
meta.shrinkage: An R Package for Meta-Analyses for Simultaneously Estimating Individual Means
Authors: Taketomi Nanami , Michimae Hirofumi , Chang Yuan-Tsung , Emura Takeshi
Published: January 2022

Meta-analysis is an indispensable tool for synthesizing statistical results obtained from individual studies. Recently, non-Bayesian estimators for individual means were proposed by applying three methods: the James–Stein (JS) shrinkage estimator, isotonic regression estimator, and pretest (PT) estimator. In order to make these methods available to users, we develop a new R package meta.shrinkage. Our package can compute seven estimators (named JS, JS+, RML, RJS, RJS+, PT, and GPT). We introduce this R package along with the usage of the R functions and the “average-min-max” steps for the pool-adjacent violators algorithm. We conduct Monte Carlo simulations to validate the proposed R package to ensure that the package can work properly in a variety of scenarios. We also analyze a data example to show the ability of the R package.
Review: The Effects of Supersonic Aviation on Ozone and Climate
Authors: Matthes Sigrun , Lee David S. , De Leon Ruben Rodriguez , Lim Ling , Owen Bethan , Skowron Agnieszka , Thor Robin N. , Terrenoire Etienne
Published: January 2022

When working towards regulation of supersonic aviation, a comprehensive understanding of the global climate effect of supersonic aviation is required in order to develop future regulatory issues. Such research requires a comprehensive overview of existing scientific literature having explored the climate effect of aviation. This review article provides an overview on earlier studies assessing the climate effects of supersonic aviation, comprising non-CO2 effects. An overview on the historical evaluation of research focussing on supersonic aviation and its environmental impacts is provided, followed by an overview on concepts explored and construction of emission inventories. Quantitative estimates provided for individual effects are presented and compared. Subsequently, regulatory issues related to supersonic transport are summarised. Finally, requirements for future studies, e.g., in emission scenario construction or numerical modelling of climate effects, are summarised and main conclusions discussed.
Jet Impingement Heat Transfer Characteristics with Variable Extended Jet Holes under Strong Crossflow Conditions
Authors: Yang Xing , Wu Hang , Feng Zhenping
Published: January 2022

In this paper, detailed flow patterns and heat transfer characteristics of a jet impingement system with extended jet holes are experimentally and numerically studied. The jet holes in the jet plate present an inline array of 16 × 5 rows in the streamwise (i.e., the crossflow direction) and spanwise directions, where the streamwise and spanwise distances between adjacent holes, which are normalized by the jet hole diameter (xn/d and yn/d), are 8 and 5, respectively. The jets impinge onto a smooth target plate with a normalized distance (zn/d) of 3.5 apart from the jet plate. The jet holes are extended by inserting stainless tubes throughout the jet holes and the extended lengths are varied in a range of 1.0d–2.5d, depending on the jet position in the streamwise direction. The experimental data is obtained by using the transient thermochromic liquid crystal (TLC) technique for wide operating jet Reynolds numbers of (1.0 × 104)–(3.0 × 104). The numerical simulations are well-validated using the experimental data and provide further insight into the flow physics within the jet impingement system. Comparisons with a traditional baseline jet impingement scheme show that the extended jet holes generate much higher local heat transfer levels and provide more uniform heat transfer distributions over the target plate, resulting in the highest improvement of approximately 36% in the Nusselt number. Although the extended jet hole configuration requires a higher pumping power to drive the flow through the impingement system, the gain of heat transfer prevails over the penalty of flow losses. At the same pumping power consumption, the extended jet hole design also has more than 10% higher heat transfer than the baseline scheme.
Development of African Swine Fever in Poland
Authors: Szymańska Elżbieta Jadwiga , Dziwulaki Mariusz
Published: January 2022

African swine fever (ASF) is a major problem in the production of live pigs in many EU countries. The aim of this research is to identify the causes and effects of this disease in Poland. The study used data from various institutions in Poland and from the EU Animal Diseases Information System (ADIS). Within the range of causes for ASF development, we considered the transmission of the ASF virus by wild boars and human activity. The article presents the number and distribution of ASF cases in wild boars, and the outbreaks of ASF in domestic pigs, in the years 2014–2020. The relationship between these variables was determined with a rectilinear regression analysis. The analysis of data for poviats where ASF cases in wild boards and ASF outbreaks in domestic pigs have been reported shows a certain periodicity of ASF occurrence in the country. This research shows that, despite the actions taken by veterinary services, hunting associations and the involvement of state administration bodies, the disease spreads rapidly. The occurrence of ASF outbreaks in domestic pigs concerns both small and large scale farms. However, due to the fragmented nature of pig farming in Poland, ASF is more prevalent in smaller holdings. Among the main reasons for the development of this disease in the country are the insufficient bio-insurance coverage of pig holdings, and the presence of the virus in the wild boar population. The process of ridding the country of the ASF virus is long and costly.
Observed Changes in Agroclimate Metrics Relevant for Specialty Crop Production in California
Authors: Parker Lauren E. , Zhang Ning , Abatzoglou John T. , Ostoja Steven M. , Pathak Tapan B.
Published: January 2022

Every decade, a suite of standardized climatological metrics known as climate normals are updated, providing averages of temperature and precipitation data over the previous 30-year period. Although some of these climate normals are directly applicable to agricultural producers, there are additional agroclimate metrics calculated from meteorological data that provide physiologically relevant information for on-farm management decisions. In this study, we identified a suite of energy-based agroclimate metrics and calculated changes over the two most recent normal periods (1981–2010 and 1991–2020), focusing on specialty crop production regions in California. Observed changes in agroclimate metrics were largely consistent with broader global warming trends. While most metrics showed small changes between the two periods, during the 1991–2020 period, the last spring freeze occurred ~5 days earlier as compared to the 1981–2010 period, contributing to a >6 day longer frost-free period in the Sacramento and Salinas Valleys; likewise an additional 6.4 tropical nights (Tn > 20 °C) occurred in the Coachella Valley during the 1991–2020 period. A complementary trend analysis of the agroclimate metrics over the 1981–2020 period showed significant increases in growing degree days across all agricultural regions, while significant increases in heat exposure were found for the Salinas and Imperial Valleys and over the Central Coast region. Moreover, summer reference evapotranspiration increased approximately 40 mm in California’s Central Valley during 1981–2020, with implications for agricultural water resources. Quantifying the shifts in these agroclimate metrics between the two most recent 30-year normal periods and the accompanying 40-year trends provides context for understanding and communicating around changing climatic baselines and underscores the need for adaptation to meet the challenge that climate change poses to agriculture both in the future and in the present.
Control of Substrate Water Availability Using Soil Sensors and Effects of Water Deficit on the Morphology and Physiology of Potted Hebe andersonii
Authors: Bañón Daniel , Lorente Beatriz , Bañón Sebastián , Ortuño María Fernanda , Sánchez-Blanco María Jesús , Alarcón Juan José
Published: January 2022

Many plant producers tend to overwater crops to prevent water stress and salt-induced damage. These practices waste irrigation water and cause leaching that harms the environment and increases production costs. In order to optimize water consumption and minimize the environmental impact of plant production, this study aimed to determine the physiological and morphological responses of Hebe andersonii to three substrate volumetric water contents (49%, 39%, and 32%). The experiment was conducted in a greenhouse with an irrigation protocol that consisted of adding small volumes of water to avoid leaching while monitoring substrate moisture with dielectric soil sensors. The results showed that moderately low substrate moisture improved the water-use efficiency, while growth was significantly reduced under more severe water deficit conditions (but without leaf chlorosis or abscission). The photosynthetic activity of Hebe was primarily controlled by the stomatal aperture, which was co-determined by the substrate moisture and seasonal temperature. Hebe leaves promoted non-photochemical quenching when carbon assimilation was limited by a water deficit, and accumulated solutes through an osmotic adjustment process (especially Cl−, Na+, and K+) to maintain their water status. Overall, Hebe andersoni cv. Variegata could successfully grow and improve its water-use efficiency in low substrate moisture and under a non-draining irrigation regime.
Estimating Nutrient Uptake Requirements for Melon Based on the QUEFTS Model
Authors: Wen Meijuan , Yang Sicun , Huo Lin , He Ping , Xu Xinpeng , Wang Chengbao , Zhang Yueqiang , Zhou Wei
Published: January 2022

Imbalanced and excessive fertilizer application has resulted in low yields and reduced nutrient use efficiency for melon production in China. Estimating nutrient requirements is crucial for effectively developing site-specific fertilizer recommendations for increasing yield and profit while reducing negative environmental impacts. Relationships between the yield and nutrient uptake requirements of above-ground dry matter were assessed using 1127 on-farm observations (2000–2020) from melon production regions of China. The quantitative evaluation of fertility of tropical soils (QUEFTS) model was used to estimate nutrient requirements. It predicted a linear increase in yield at balanced nutrient uptake levels until the yield reached approximately 60–80% of the potential yield. In order to produce 1000 kg of fruit, 2.9, 0.4 and 3.2 kg/ha of N, P and K (7.2:1.0:7.8), respectively, were required for above-ground parts, while the corresponding nutrient internal efficiencies were 345.3, 2612.6 and 310.0 kg per kg N, P and K, respectively, whereas 1.4, 0.2 and 1.9 kg of N, P and K were required to replace nutrients removed after harvest. The corresponding fruit absorption rates were 47.0%, 59.5% and 58.2%, respectively. Field validation experiments confirmed the consistency between observed and simulated uptake rates, indicating that this model could estimate nutrient requirements. These findings will help develop fertilizer recommendations for improving melon yield and nutrient use efficiency.
Exploiting Plant Functional Diversity in Durum Wheat–Lentil Relay Intercropping to Stabilize Crop Yields under Contrasting Climatic Conditions
Authors: Koskey Gilbert , Leoni Federico , Carlesi Stefano , Avio Luciano , Bàrberi Paolo
Published: January 2022

Relay intercropping is considered a valuable agroecological practice to increase and stabilize crop yields while ensuring the provision of several ecosystem services as well as sustainability and resilience to changing climatic conditions. However, farmers are still reluctant in the use of intercropping practices since there is a huge knowledge gap regarding the time of sowing, sowing ratio, crop stand density, and cultivar choice. In this study, we carried out a 3-year field experiment in Central Italy to assess the effect of relay intercropping on the agronomic performance and competitiveness of winter durum wheat (Triticum durum Desf. cv. Minosse) and spring lentil (Lens culinaris Medik. cv. Elsa) under a low-input management system, comparing different crop stand types (monocrop vs. intercrop) and target plant densities (350 plants m2—full dose vs. 116 plants m2—1/3 dose). The results revealed that intercropping increased grain yield compared to monocropping: significantly (p < 0.0001) against both monocrops in 2021 and non-significantly against durum wheat in 2019 and 2020. Yield advantage in both intercropping systems ranged between 164 and 648%. Durum wheat competitiveness was stronger in 2019 and 2021, while lentil was the most competitive component in 2020. Intercropping favored P accumulation in durum wheat shoots. There was no difference in grain yield of both crops between the highly- and lowly-dense system in 2020 and 2021. Both intercropping strategies were as effective as mechanical hoeing in controlling weeds and proved beneficial in stabilizing lentil productivity. Further economic analysis capturing the additional costs incurred in intercropping and mechanical weeding would highlight the magnitude of profitability of these systems.
A Deep Learning-Based Sensor Modeling for Smart Irrigation System
Authors: Sami Maira , Khan Saad Qasim , Khurram Muhammad , Farooq Muhammad Umar , Anjum Rukhshanda , Aziz Saddam , Qureshi Rizwan , Sadak Ferhat
Published: January 2022

The use of Internet of things (IoT)-based physical sensors to perceive the environment is a prevalent and global approach. However, one major problem is the reliability of physical sensors’ nodes, which creates difficulty in a real-time system to identify whether the physical sensor is transmitting correct values or malfunctioning due to external disturbances affecting the system, such as noise. In this paper, the use of Long Short-Term Memory (LSTM)-based neural networks is proposed as an alternate approach to address this problem. The proposed solution is tested for a smart irrigation system, where a physical sensor is replaced by a neural sensor. The Smart Irrigation System (SIS) contains several physical sensors, which transmit temperature, humidity, and soil moisture data to calculate the transpiration in a particular field. The real-world values are taken from an agriculture field, located in a field of lemons near the Ghadap Sindh province of Pakistan. The LM35 sensor is used for temperature, DHT-22 for humidity, and we designed a customized sensor in our lab for the acquisition of moisture values. The results of the experiment show that the proposed deep learning-based neural sensor predicts the real-time values with high accuracy, especially the temperature values. The humidity and moisture values are also in an acceptable range. Our results highlight the possibility of using a neural network, referred to as a neural sensor here, to complement the functioning of a physical sensor deployed in an agriculture field in order to make smart irrigation systems more reliable.
Estimate Cotton Water Consumption from Shallow Groundwater under Different Irrigation Schedules
Authors: Zhang Guohua , Li Xinhu
Published: January 2022

Shallow groundwater is considered an important water resource to meet crop irrigation demands. However, limited information is available on the application of models to investigate the impact of irrigation schedules on shallow groundwater depth and estimate evaporation while considering the interaction between meteorological factors and the surface soil water content (SWC). Based on the Richards equation, we develop a model to simultaneously estimate crop water consumption of shallow groundwater and determine the optimal irrigation schedule in association with a shallow groundwater depth. A new soil evaporation function was established, and the control factors were calculated by using only the days after sowing. In this study, two irrigation scheduling methods were considered. In Method A, irrigation was managed based on the soil water content; in Method B, irrigation was based on the crop water demand. In comparison with Method B, Method A was more rational because it could use more groundwater, and the ratio of soil evaporation to total evapotranspiration was low. In this model, the interaction between meteorological factors and the SWC was considered to better reflect the real condition; therefore, the model provided a better way to estimate the crop water consumption.
Novel Sequencing and Genomic Technologies Revolutionized Rice Genomic Study and Breeding
Authors: Gu Haiyong , Liang Shihu , Zhao Junliang
Published: January 2022

Rice is one of the most important food crops worldwide. Population growth and climate change posed great challenges for further rice production. In the past decade, we have witnessed an explosive development in novel sequencing and genomic technologies. These technologies have been widely applied in rice genomic study and improvement processes, and contributed greatly to increase the efficiency and accuracy of rice breeding. On the other hand, novel sequencing and genomic technologies also promote the shift of breeding schemes from conventional field selection processes to genomic assisted breeding. These technologies have revolutionized almost every aspect of rice study and breeding. Here, we systematically sorted out and reviewed the progress and advancements of sequencing and genomic technologies. We further discussed how these technologies were incorporated into rice breeding practices and helped accelerate the rice improvement process. Finally, we reflected on how to further utilize novel sequencing and genomic technologies in rice genetic improvement, as well as the future trends of advancement for these technologies. It can be expected that, as the sequencing and genomic technologies will develop much more quickly in the future, and be combined with novel bioinformatics tools, rice breeding will move forward into the genomic assisted era.
Remediation of Agricultural Soils with Long-Term Contamination of Arsenic and Copper in Two Chilean Mediterranean Areas
Authors: Mondaca Pedro , Valenzuela Patricio , Roldán Nicole , Quiroz Waldo , Valdenegro Mónika , Celis-Diez Juan L.
Published: January 2022

Soil amendments may decrease trace element accumulation in vegetables, improving food security and allowing the recovery of contaminated farmlands. Despite some promising results in the laboratory, validation of soil amendments in field conditions are scarce, especially in aerobic soils. Here, we assessed the effect of different potential soil amendments on arsenic (As) accumulation in lettuces. Then, we compared them in terms of food security and the associated investment (efficacy and efficiency, respectively). We also hypothesized that the soil amendments do not lead to side effects, such as yield decrease, phytotoxicity of Cu, or undesired changes in soil properties. Thereby, we assessed lettuces grown on untreated contaminated soils (C+), treated contaminated soils, and untreated uncontaminated soils (C−) in two contrasting soil types (sandy and loamy soils). The treated contaminated soils consisted of multiple soil amendments. Soil amendments were: diammonium phosphate (DP), iron sulfate (IS), ferrous phosphate (FP), calcium peroxide (CP), and organic matter (OM). We found that phosphate amendments (DP and FP) reduced the As in edible tissues of lettuce in both areas, while CP only reduced As accumulation in the sandy soils area. The As intake through lettuces grown on these amended soils was about 30% lower than on the unamended ones. Cu concentrations in lettuces above 25 mg kg−1 grown in contaminated soils without reducing growth were found, a result that differed from non-field studies.
16S rRNA Gene-Based Metagenomic Analysis of Rhizosphere Soil Bacteria in Arkansas Rice Crop Fields
Authors: Oliveira Cássia , Shakiba Ehsan , North Dustin , McGraw Madison , Ballard Ethan , Barrett-D’Amico Marissa , Glazko Galina , Rahmatallah Yasir
Published: January 2022

The rhizomicrobiome is composed of microbes that live in association with plant roots. From nutrient cycling to carbon sequestration, soil microorganisms have provided a solid base for natural and agricultural ecosystems to function. The relationship between plant roots and soil microorganisms is especially relevant in food staples such as rice (Oryza sativa L.), as the various properties of these microbes can influence crop yield and plant health, thereby affecting a major portion of the food supply for an ever-growing world population. In this study, we used 16S rRNA gene-based metagenomic analysis to investigate the impact of crop rotation and soil cultivation methods (no-till or tillage) on rhizosphere bacterial diversity and composition in eight crop fields in Arkansas. Illumina MiSeq sequencing revealed 56 Phyla, with four major Phyla: Proteobacteria, Acidobacteria, Actinobacteria, and Bacteroidetes. Soil microbial communities in the samples studied were phylogenetically diverse but with a stable community structure. Crop rotation and tillage did not significantly affect bacterial diversity.
A Modified Memetic Algorithm with an Application to Gene Selection in a Sheep Body Weight Study
Authors: Miao Maoxuan , Wu Jinran , Cai Fengjing , Wang You-Gan
Published: January 2022

Selecting the minimal best subset out of a huge number of factors for influencing the response is a fundamental and very challenging NP-hard problem because the presence of many redundant genes results in over-fitting easily while missing an important gene can more detrimental impact on predictions, and computation is prohibitive for exhaust search. We propose a modified memetic algorithm (MA) based on an improved splicing method to overcome the problems in the traditional genetic algorithm exploitation capability and dimension reduction in the predictor variables. The new algorithm accelerates the search in identifying the minimal best subset of genes by incorporating it into the new local search operator and hence improving the splicing method. The improvement is also due to another two novel aspects: (a) updating subsets of genes iteratively until the no more reduction in the loss function by splicing and increasing the probability of selecting the true subsets of genes; and (b) introducing add and del operators based on backward sacrifice into the splicing method to limit the size of gene subsets. Additionally, according to the experimental results, our proposed optimizer can obtain a better minimal subset of genes with a few iterations, compared with all considered algorithms. Moreover, the mutation operator is replaced by it to enhance exploitation capability and initial individuals are improved by it to enhance efficiency of search. A dataset of the body weight of Hu sheep was used to evaluate the superiority of the modified MA against the genetic algorithm. According to our experimental results, our proposed optimizer can obtain a better minimal subset of genes with a few iterations, compared with all considered algorithms including the most advanced adaptive best-subset selection algorithm.
Tranquillizing Effect of Passiflora incarnata Extract: Outcome on Behavioral and Physiological Indicators in Weaning Pigs with Intact Tails
Authors: Pastorelli Grazia , Serra Valentina , Turin Lauretta , Redaelli Veronica , Luzi Fabio , Barbieri Sara
Published: January 2022

Tail docking has been used in the pig industry to decrease the occurrence of tail biting behavior. This abnormal behavior has a multifactorial origin since it is a response to simultaneous environmental, nutritional and management changes. Given the calming properties of Passiflora incarnata, we hypothesized that dietary supplementation with the extract in weaned pigs could result in a modification of behavior and physiologic indicators linked to stress. Weaned piglets (n = 120, mean body weight 9.07 ± 2.30 kg) were randomly allocated to one of two dietary treatments: control diet (CON) and CON supplemented with 1 kg/t of P. incarnata (PAS). The trial was 28 days long. The presence of skin lesions was assessed at d-1, d-10, d-19, and d-28, and saliva samples were collected for IgA and cortisol determinations at the same sampling times. Results showed the PAS group was characterized by equal growth performance as the CON group, fewer ear lesions (p < 0.05), less aggressive behavior (p < 0.001), higher enrichment exploration (p < 0.001) and lower cortisol levels (p < 0.01). Time effect was observed for tail lesions (p < 0.001) and behavioral observations (p < 0.001). Additional research is required to determine the effect of P. incarnata extract using a larger number of animals and longer period of supplementation when risks associated with tail biting are uncontrolled.
Characterization of RNA Editome in the Mammary Gland of Yaks during the Lactation and Dry Periods
Authors: Wu Xiaoyun , Ayalew Wondossen , Chu Min , Pei Jie , Liang Chunnian , Bao Pengjia , Guo Xian , Yan Ping
Published: January 2022

The mammary gland is a complicated organ comprising several types of cells, and it undergoes extensive morphogenetic and metabolic changes during the female reproductive cycle. RNA editing is a posttranscriptional modification event occurring at the RNA nucleotide level, and it drives transcriptomic and proteomic diversities, with potential functional consequences. RNA editing in the mammary gland of yaks, however, remains poorly understood. Here, we used REDItools to identify RNA editing sites in mammary gland tissues in yaks during the lactation period (LP, n = 2) and dry period (DP, n = 3). Totally, 82,872 unique RNA editing sites were identified, most of which were detected in the noncoding regions with a low editing degree. In the coding regions (CDS), we detected 5235 editing sites, among which 1884 caused nonsynonymous amino acid changes. Of these RNA editing sites, 486 were found to generate novel possible miRNA target sites or interfere with the initial miRNA binding sites, indicating that RNA editing was related to gene regulation mediated by miRNA. A total of 14,159 RNA editing sites (involving 3238 common genes) showed a significant differential editing level in the LP when compared with that in the DP through Tukey’s Honest Significant Difference method (p < 0.05). According to the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, genes that showed different RNA editing levels mainly participated in pathways highly related to mammary gland development, including MAPK, PI3K-Akt, FoxO, and GnRH signaling pathways. Collectively, this work demonstrated for the first time the dynamic RNA editome profiles in the mammary gland of yaks and shed more light on the mechanism that regulates lactation together with mammary gland development.
Spawning Performance and Sex Steroid Levels in Female Pikeperch Sander lucioperca Treated with Poly(lactic-co-glycolic acid) Microparticles
Authors: Knowles Jindřiška , Vysloužil Jakub , Policar Tomáš , Milla Sylvain , Holická Martina , Podhorec Peter
Published: January 2022

Pikeperch Sander lucioperca is a piscivorous species considered a promising candidate for the diversification of intensive aquaculture. This study aimed to determine the effect of a sustained-release delivery system incorporating mammalian gonadotropin-releasing hormone agonist (mGnRHa) into poly(lactic-co-glycolic acid) (PLGA) microparticles on the sex steroid levels and aspects of artificial reproduction of pikeperch. Fish were divided into four groups and injected with 20 µg mGnRHa/kg, 5-day release microparticles encapsulated with 5 µg GnRHa/kg BW (PLGA 5), 20 µg GnRHa/kg (PLGA 20), or 1 mL/kg 0.9% NaCl (control). Cumulative percentage ovulation was 100% in the PLGA 5 group, significantly higher than in other tested groups. No differences among groups were observed in latency or fecundity. The level of 11-ketotestosterone (11-KT) peaked at 40 h post-injection, and was sustained during ovulation, in all treated groups. The 17β-estradiol (E2) concentration increased in the mGnRHa-only group immediately after hormone injection, while both PLGA groups showed a reduction in E2 after injection, continuing to decrease until ovulation. A low dose of mGnRHa in PLGA microparticles significantly improves induction of ovulation and results in acceptable reproductive performance, which may positively affect pikeperch production under controlled conditions.
The Use of Attractants to Stimulate Neonatal Piglet Interest in Rope Enrichment
Authors: Sundman Emiline R. , Gabler Nicholas K. , Millman Suzanne T. , Stalder Kenneth J. , Karriker Locke A. , Johnson Anna K.
Published: January 2022

In the United States swine industry, preweaning mortality represents the highest mortality rate of any production phase, nearly half attributed to crushing. The overarching aim of this study was to determine if enrichment ropes would entice neonatal piglets away from the sow and reduce preweaning mortality. Rope enrichments were provided to 161 piglets from 26 sows after farrowing. Ropes were dipped in sunflower oil (n = 7), semiochemical (n = 8), or milky cheese (n = 11). Piglet purposeful rope investigations, weight gain, and mortality were recorded. On Day 2, 75% of piglets touched the enrichment at least once, and frequency ranged from 1 to 21 investigations across all treatments. Frequency (p = 0.20) and duration (p = 0.21) of investigations were not affected by treatment. Preweaning litter average weight gain did not differ between treatments (p = 0.71). MC (milky cheese) piglets had the lowest percent mortality when the enrichment ropes were present (Days 2 to 5, p = 0.01), and SC (semiochemical) piglets had the lowest percent mortality after the enrichment ropes were removed (Days 6 to weaning, p < 0.0001). This proof-of-concept study highlights the potential value of neonatal piglet environmental enrichment.