bluuebunny/crossref_metadata_2025 huggingface dataset:
Massive Open Online Course Versus Flipped Instruction: Impacts on Foreign Language Speaking Anxiety, Foreign Language Learning Motivation, and Learning Attitude
Authors: Pan Hui , Xia Fang , Kumar Tribhuwan , Li Xiang , Shamsy Atefeh
Published: February 2022

This study inspected the effect of Massive Open Online Course (MOOC) and flipped instruction on EFL learners’ foreign language speaking anxiety, foreign language learning motivation, and attitude toward English learning. To fulfill this objective, the Oxford Quick Placement Test was given to 160 Iranian EFL learners, of whom 120 upper-intermediate participants were chosen and divided into two experimental groups—MOOC (n = 40) and flipped (n = 40)—and one control group (n = 40). After that, all selected participants were administered a speaking anxiety questionnaire and a motivation questionnaire as the pre-test of the research. Then, one of the experimental groups received an online-based instruction via Skype: one conversation was instructed to this group online every session. The other experimental group received the treatment via flipped-based instruction. The audio files and the texts of the conversations were sent to this group via the WhatsApp application because they all had easy access to it. On the other hand, the control group did not receive any Internet-delivered treatment yet was trained through a face-to-face method. This process continued until the last session, and after the treatment period, the post-tests of speaking anxiety and motivation were given to all three groups to determine the effectiveness of the treatment. Moreover, two attitude questionnaires were administered to the experimental groups to examine their attitudes toward the MOOC and the flipped models of instructions. The findings of the One-way ANOVA test, Post-hoc Scheffe test, and paired samples t-test showed that there were significant differences between the post-test of the experimental groups and the control group. The results indicated that the experimental groups significantly outflanked the control group after the treatment. Lastly, the outcomes showed that participants in both experimental groups had positive attitudes toward technological-based instructional environments.
Leptin Methylation and mRNA Expression Associated With Psychopathology in Schizophrenia Inpatients
Authors: Song Jiaqi , Chen Yan , Zhao Qing , Li Hongna , Li Wei , Chen Ke , Yu Jianjin , Fu Weihong , Chen Dachun
Published: February 2022

Leptin involved in the regulation of dopaminergic neurons of the central nervous system may confirm the hypothesis of neurodevelopment in schizophrenic patients. However, specific genetic mechanisms are undefined. Therefore, we aimed to explore the regulation of DNA methylation of leptin promoters and mRNA expression in patients with schizophrenia. A cross-sectional study enrolled 40 patients and 40 healthy controls from the Beijing Huilongguan Hospital in China. The leptin methylation levels and mRNA expression were examined by highly sensitive mass spectrometry based on the MassARRAY System and real-time quantitative polymerase chain reaction (qPCR). The Positive and Negative Symptoms Scale (PANSS) was applied to estimate the clinical symptoms of patients. The LEP-CpG7 and CpG15 methylation in patients were significantly higher than in healthy controls (P < 0.05). The LEP-CpG11, CpG33.34.35, CpG36 methylation, and mRNA expression decreased significantly in patients compared with healthy controls (P < 0.05). After controlling gender, age, BMI, dose of antipsychotic and duration of illness, LEP-CpG7 methylation was negatively associated with PANSS positive symptoms subscore (r = −0.485, P = 0.005). In addition, LEP-mRNA expression was negatively correlated with PANSS total score (r = −0.385, P = 0.03) and positive subscale (r = −0.392, P = 0.026). Nevertheless, only the LEP-CpG7 methylation level remained negatively correlated to the PANSS positive subscore following multiple stepwise regression (β = −17.071, P = 0.037). These results suggest that leptin methylation and mRNA expression might contribute to the pathogenesis of schizophrenia. LEP-CpG7 methylation may be negatively associated with positive symptoms in patients with schizophrenia.
Common Data Elements to Facilitate Sharing and Re-use of Participant-Level Data: Assessment of Psychiatric Comorbidity Across Brain Disorders
Authors: Vaccarino Anthony L. , Beaton Derek , Black Sandra E. , Blier Pierre , Farzan Farnak , Finger Elizabeth , Foster Jane A. , Freedman Morris , Frey Benicio N. , Gilbert Evans Susan , Ho Keith , Javadi Mojib , Kennedy Sidney H. , Lam Raymond W. , Lang Anthony E. , Lasalandra Bianca , Latour Sara , Masellis Mario , Milev Roumen V. , Müller Daniel J. , Munoz Douglas P. , Parikh Sagar V. , Placenza Franca , Rotzinger Susan , Soares Claudio N. , Sparks Alana , Strother Stephen C. , Swartz Richard H. , Tan Brian , Tartaglia Maria Carmela , Taylor Valerie H. , Theriault Elizabeth , Turecki Gustavo , Uher Rudolf , Zinman Lorne , Evans Kenneth R.
Published: February 2022

The Ontario Brain Institute's “Brain-CODE” is a large-scale informatics platform designed to support the collection, storage and integration of diverse types of data across several brain disorders as a means to understand underlying causes of brain dysfunction and developing novel approaches to treatment. By providing access to aggregated datasets on participants with and without different brain disorders, Brain-CODE will facilitate analyses both within and across diseases and cover multiple brain disorders and a wide array of data, including clinical, neuroimaging, and molecular. To help achieve these goals, consensus methodology was used to identify a set of core demographic and clinical variables that should be routinely collected across all participating programs. Establishment of Common Data Elements within Brain-CODE is critical to enable a high degree of consistency in data collection across studies and thus optimize the ability of investigators to analyze pooled participant-level data within and across brain disorders. Results are also presented using selected common data elements pooled across three studies to better understand psychiatric comorbidity in neurological disease (Alzheimer's disease/amnesic mild cognitive impairment, amyotrophic lateral sclerosis, cerebrovascular disease, frontotemporal dementia, and Parkinson's disease).
Revisiting the Effects of Organized Mammography Programs on Inequalities in Breast Screening Uptake: A Multilevel Analysis of Nationwide Data From 1997 to 2017
Authors: Jolidon Vladimir , De Prez Vincent , Bracke Piet , Bell Andrew , Burton-Jeangros Claudine , Cullati Stéphane
Published: February 2022

This study revisits the effects of mammography screening programs on inequalities in breast screening uptake in Switzerland. The progressive introduction of regional mammography programs by 12 out of the 26 Swiss cantons (regions) since 1999 offers an opportunity to perform an ecological quasi-experimental study. We examine absolute income and marital status inequalities in mammography uptake, and whether the cantons' implementation of mammography programs moderate these inequalities, as previous research has devoted little attention to this. We use five waves of the Swiss Health Interview Survey covering the 1997–2017 period and comprising data on 14,267 women aged 50–70. Both up-to-date and ever-screening outcomes are analyzed with multilevel models which assess the mammography programs' within-canton effect. Findings show that higher income women and married women (compared to unmarried women) had significantly higher mammography uptake probabilities. Mammography programs did not moderate absolute income differences in up-to-date screening; however, they were associated with smaller absolute income differences in ever-screening uptake. Mammography programs related to higher screening uptake for married women, more than for unmarried women. In conclusion, we showed absolute income inequalities in mammography uptake which were not revealed by previous studies using relative inequality measures. Mammography programs may have contributed to reducing income inequalities in ever-screening, yet this was not observed for up-to-date screening. This study has implication for preventive health interventions—e.g., cancer screening promotion should pay attention to women's marital status since screening programs may widen the screening gap between married and unmarried women.
Toward an Integrative Approach for Making Sense Distinctions
Authors: McCrae John P. , Fransen Theodorus , Ahmadi Sina , Buitelaar Paul , Goswami Koustava
Published: February 2022

Word senses are the fundamental unit of description in lexicography, yet it is rarely the case that different dictionaries reach any agreement on the number and definition of senses in a language. With the recent rise in natural language processing and other computational approaches there is an increasing demand for quantitatively validated sense catalogues of words, yet no consensus methodology exists. In this paper, we look at four main approaches to making sense distinctions: formal, cognitive, distributional, and intercultural and examine the strengths and weaknesses of each approach. We then consider how these may be combined into a single sound methodology. We illustrate this by examining two English words, “wing” and “fish,” using existing resources for each of these four approaches and illustrate the weaknesses of each. We then look at the impact of such an integrated method and provide some future perspectives on the research that is necessary to reach a principled method for making sense distinctions.
Catastrophic Forgetting in Deep Graph Networks: A Graph Classification Benchmark
Authors: Carta Antonio , Cossu Andrea , Errica Federico , Bacciu Davide
Published: February 2022

In this work, we study the phenomenon of catastrophic forgetting in the graph representation learning scenario. The primary objective of the analysis is to understand whether classical continual learning techniques for flat and sequential data have a tangible impact on performances when applied to graph data. To do so, we experiment with a structure-agnostic model and a deep graph network in a robust and controlled environment on three different datasets. The benchmark is complemented by an investigation on the effect of structure-preserving regularization techniques on catastrophic forgetting. We find that replay is the most effective strategy in so far, which also benefits the most from the use of regularization. Our findings suggest interesting future research at the intersection of the continual and graph representation learning fields. Finally, we provide researchers with a flexible software framework to reproduce our results and carry out further experiments.
Countries Response for People With Disabilities During the COVID-19 Pandemic
Authors: Lugo-Agudelo LH , Spir Brunal Maria A , Posada Borrero Ana M , Cruz Sarmiento Kelly M , Velasquez Correa Juan C , Di Dio Castagna Iannini Rosarita , Gonzalez Zuluaga Manuela , Ospina Victor A , Patiño Lugo Daniel F , Mesa Franco Luisa F , Gutenbrunner Christoph
Published: February 2022

Background and Objectives

During the Coronavirus disease 19 (COVID-19) pandemic, isolation and prevention measures to reduce COVID-19 contagions are essential for the care of all people; these measures should comply with the principles of inclusion and accessibility for people with disabilities (PWD), with all kinds of deficiencies and levels of dependency. Thereby, the aim of this article is to present the measures adopted for PWD or people with rehabilitation needs, for containment, mitigation, or suppression of the SARS-CoV-2 virus in different countries of all continents and of all income levels.

Methods

A narrative approach was used in this article. First, a broad search was carried out in the 193 member states of the UN, and then 98 countries that issued any document, report, or information related to disability and COVID-19 were selected. Finally, 32 countries were included in this article because they presented official information. We considered official sources, the information available in the government, or on the health ministry page of the country. In this way, the countries that presented information which did not correspond to an official source were excluded. The search was conducted in August 2020 and updated in March 2021.

Results

First, the non-pharmacological general interventions for PWD included informative measures and general recommendations during the stay at home, isolation, and biosecurity measures, contagion prevention, detection of positive cases, mobilization measures, and measures implemented in institutions or residences of PWD. Second, we identified the economic and social benefits provided to PWD during the pandemic. Finally, we identified the measures taken by countries according to the type of impairment (visual, hearing, physical, mental, and cardiopulmonary impairment) during the COVID-19 pandemic.

Conclusion

In response to the COVID-19 pandemic, only 50% of countries from the five world regions created and implemented specific measures for PWD to containment, mitigation, or suppression of the SARS-CoV-2 virus. There is very little specific information available about the measures to continue with the care of people with rehabilitation needs and the long-term follow-up of PWD, and for the prevention and response to violence, especially for women with disabilities.
Supply Chain Management of Mango (Mangifera indica L.) Fruit: A Review With a Focus on Product Quality During Postharvest
Authors: Le Truong Dang , Viet Nguyen Thanh , Muoi Nguyen Van , Toan Ha Thanh , Lan Nguyen Mai , Pham Tri Nhut
Published: February 2022

Mango (Mangifera indicaL.) is a widely consumed fruit in tropical/subtropical regions around the world due to its excellent flavor and taste, and valuable source of nutrients and phytochemical compounds. As a climacteric fruit, mango is easily perishable after harvesting due to the ripening process, environmental conditions, and improper postharvest handling, leading to significant quality losses as well as economic loss throughout a supply chain. Postharvest losses are attributed to harvesting at an improper maturity stage, poor postharvest pretreatment, improper packing and packaging, inappropriate storage temperature and distribution conditions. These caused mechanical damage, sap burn, spongy tissue, weight loss, fruit softening, decay, chilling injury, and postharvest diseases. Currently, each step in the supply chain has been applied many postharvest technologies to reduce the quality losses of mango fruits as well as improving their marketability with the highest retention of quality. This review documented available possible causes for the quality losses and observed the physicochemical changes of mango fruit when applying postharvest technologies at each critical step in the mango supply chain from harvesting, pre-treatment, packaging, storage, to distribution. The summarized information is expected to provide comprehensive quality changes of mango fruits and point out the proper technology at each step of the supply chain.
Internal Ring Defect Closure Technique in Laparoscopic Mesh Hernioplasty for Indirect Inguinal Hernia
Authors: Li Binggen , Shi Shange , Qin Changfu , Yu Jiwei , Gong Duhui , Nie Xiangyang , Miao Jinchao , Lai Zeru , Cui Wenbo , Li Guoxin
Published: February 2022

Purpose

The best way to reduce seroma formation after laparoscopic indirect hernia repair is debated. We noticed that internal ring defect closure in laparoscopic mesh hernioplasty could provide promising outcomes with an effect on diminishing seroma formation. We introduce our closure technique and report our experience.

Methods

This prospective study was conducted from May 2019 to May 2021. Patients with European Hernia Society classification L3 indirect or scrotal hernia were recruited and underwent laparoscopic transabdominal patch plasty (TAPP). Hernia defect closure was performed before mesh deployment. The primary outcomes were seroma formation, postoperative pain, and hernia recurrence. Perioperative data and postoperative complications were also recorded.

Results

Consecutive 77 patients with 89 indirect hernias (including 51 scrotal hernias) were recruited in two regional tertiary hospitals. All operations were successful without open conversion. The mean size of the hernia defect was 3.7 ± 0.5 cm (range, 2.5–5.0 cm). The mean operative time for each hernia repair (peritoneum to peritoneum) was 48.3 ± 10.8 min (range, 33–72 min), and the mean time required for internal ring closure was 6.7 ± 2.2 min (range, 4–10 min). Intraoperative bleeding was minimal. The mean visual analog scale pain score at rest on the first postoperative day was 2.2 (range, 1–4). The average postoperative length of hospital stay was 18 h (range, 14–46 h). During a mean follow-up period of 9.4 months (range, 3–23 months), no hernia recurrence or chronic pain were noted. Seroma formation was detected on six sides of unilateral hernias (6.7%) on postoperative day 7, with a mean volume of 45.8 ml (range, 24–80 ml). All seromas were mild and resolved spontaneously within 3 months, with no need for evacuation or other treatment and without major impact on the final outcome.

Conclusions

Defect closure in laparoscopic mesh hernioplasty for large indirect hernias is safe and feasible and can significantly reduce postoperative seroma formation and relative complications. This approach is recommended in large indirect or scrotal hernia repair.
Determinants of Ruminant Farmers' Use of Sustainable Production Practices for Climate Change Adaptation and Mitigation in Enugu State, Nigeria
Authors: Nwobodo Cynthia Ebere , Nwokolo Blessing , Iwuchukwu Juliana Chinasa , Ohagwu Violet Amarachukwu , Ozioko Remigius Ikechukwu
Published: February 2022

A sustainable ruminant production system ensures economically viable livestock systems that meet the current and future demands of animal products as well as the environmental safety of current and future generations. The study analyzed the determinants of ruminant farmers' use of sustainable production practices for climate change adaptation and mitigation in Enugu State, Nigeria. Multistage sampling procedure was used to select ninety six (96) ruminant farmers that constituted the sample for the study. Semi-structured interview schedule with open ended questions was used in data collection. Data were analyzed using multiple regression and Pearson Moment Correlation statistics. Access to veterinary services (t= 2.056,p= 0.044), monthly household income (t= 3.582,p= 0.001) and annual income from ruminant production (t= −2.635,p= 0.011) were socio-economic factors that significantly influenced use of sustainable practices. The adjusted R- square implies that the three factors were able to explain 24% of variance in use of sustainable practices. There is a significant positive correlation (r= 0.426,p= 0.000) between knowledge level of farmers and their use of sustainable production practices. Schemes for financial inclusion such as payment for ecosystem services can spur farmers to adopt mitigation strategies. Improved climate change knowledge can enhance ruminant farmer's resilience to the increasing impacts of climate change.
Illness Perceptions and Medication Nonadherence to Immunosuppressants After Successful Kidney Transplantation: A Cross-Sectional Study
Authors: Wang Yiman , Veltkamp Denise M. J. , van der Boog Paul J. M. , Hemmelder Marc H. , Dekker Friedo W. , de Vries Aiko P. J. , Meuleman Yvette
Published: February 2022

Background: Medication nonadherence to immunosuppressants is a well-known risk factor for suboptimal health outcomes in kidney transplant recipients (KTRs). This study examined the relationship between illness perceptions and medication nonadherence in prevalent Dutch KTRs and whether this relationship depended on post-transplant time.

Methods: Eligible KTRs transplanted in Leiden University Medical Center were invited for this cross-sectional study. The illness perceptions and medication nonadherence were measured via validated questionnaires. Associations between illness perceptions and medication nonadherence were investigated using multivariable logistic regression models.

Results: For the study, 627 participating KTRs were analyzed. 203 (32.4%) KTRs were considered nonadherent to their immunosuppressants with “taking medication more than 2 h from the prescribed dosing time” as the most prevalent nonadherent behaviour (n = 171; 27.3%). Three illness perceptions were significantly associated with medication nonadherence: illness identity (adjusted odds ratio [ORadj] = 1.07; 95% confidence interval [CI], 1.00–1.14), concern (ORadj = 1.07; 95%CI,1.00–1.14), and illness coherence (ORadj = 1.11; 95%CI,1.01–1.22). The relationships between illness perceptions and medication nonadherence did not differ depending on post-transplant time (p-values ranged from 0.48 to 0.96).

Conclusion: Stronger negative illness perceptions are associated with medication nonadherence to immunosuppressants. Targeting negative illness perceptions by means of psychoeducational interventions could optimize medication adherence and consequently improve health outcomes in KTRs.
Matching Donor and Recipient Size in Pediatric Heart Transplantation
Authors: Singh Tajinder P. , Colan Steven D. , Gauvreau Kimberlee
Published: February 2022

Previous analyses in pediatric heart transplant (HT) recipients using weight or height have not found donor-recipient size-mismatch to be associated with post-transplant mortality. A recent study in 3,215 normal US children developed an equation for left ventricular (LV) mass using body surface area (BSA). We assessed whether donor-recipient size match using predicted LV mass (PLM) is associated with post-transplant in-hospital mortality or 1-year graft survival. We identified 4,717 children <18 yrs old who received primary HT in the US during 01/2000 to 03/2015 and divided them into five groups [10%, 10%, 60% (reference group), 10% and 10%, respectively] with increasing donor-recipient PLM ratio. In adjusted analysis, group 1 children (PLM ratio ≤.90) were at higher risk of post-transplant in-hospital mortality [Odds Ratio (OR) 1.55, 95% CI 1.04, 2.31]. This association of the most undersized donors with recipient in-hospital mortality was similar when donor-recipient weight ratio<.88 or BSA ratio<.92 (lowest decile) were used instead. There was no difference in 1-year graft survival among groups. Utilizing donors with donor-recipient PLM ratio ≤.90 is associated with higher risk of early post-transplant mortality in pediatric HT recipients. However, this metric is not superior to donor-recipient weight ratio or BSA ratio for assessing size match.
Precision-Based Weighted Blending Distributed Ensemble Model for Emotion Classification
Authors: Soman Gayathri , Vivek M. V. , Judy M. V. , Papageorgiou Elpiniki , Gerogiannis Vassilis C.
Published: February 2022

Focusing on emotion recognition, this paper addresses the task of emotion classification and its performance with respect to accuracy, by investigating the capabilities of a distributed ensemble model using precision-based weighted blending. Research on emotion recognition and classification refers to the detection of an individual’s emotional state by considering various types of data as input features, such as textual data, facial expressions, vocal, gesture and physiological signal recognition, electrocardiogram (ECG) and electrodermography (EDG)/galvanic skin response (GSR). The extraction of effective emotional features from different types of input data, as well as the analysis of large volume of real-time data, have become increasingly important tasks in order to perform accurate classification. Taking into consideration the volume and variety of the examined problem, a machine learning model that works in a distributed manner is essential. In this direction, we propose a precision-based weighted blending distributed ensemble model for emotion classification. The suggested ensemble model can work well in a distributed manner using the concepts of Spark’s resilient distributed datasets, which provide quick in-memory processing capabilities and also perform iterative computations effectively. Regarding model validation set, weights are assigned to different classifiers in the ensemble model, based on their precision value. Each weight determines the importance of the respective classifier in terms of its performing prediction, while a new model is built upon the derived weights. The produced model performs the task of final prediction on the test dataset. The results disclose that the proposed ensemble model is sufficiently accurate in differentiating between primary emotions (such as sadness, fear, and anger) and secondary emotions. The suggested ensemble model achieved accuracy of 76.2%, 99.4%, and 99.6% on the FER-2013, CK+, and FERG-DB datasets, respectively.
Magnetic Suspension System with Large Distance of 82 mm Using Persistent Current in Superconducting Coil
Authors: Komori Mochimitsu , Imada Shun , Nemoto Kaoru , Asami Ken-ichi
Published: February 2022

Superconducting techniques are applied to a superconducting magnetic suspension system. A superconducting coil, copper coils, a magnetically suspended object, a photo sensor, a PID controller, and power amplifiers are the main components of the suspension system. A persistent current in the superconducting coil and a control current in the copper coils are used for suspending the object and controlling the object, respectively. This paper discusses a large gap trial for the suspension system, and the static and dynamic characteristics of the suspension system are studied. As a result, it is found that the magnetically suspended object continues to be suspended at a distance of 82 mm for more than 60 s. Since a superconducting persistent current has a maximum limit for the suspension system, a persistent current of 50 A is adopted. The details of the superconducting persistent current are studied for the performance of the suspension system. There are few reports about such a suspension system with a large gap of more than 80 mm using a superconducting persistent current.
Research on Maize Seed Classification and Recognition Based on Machine Vision and Deep Learning
Authors: Xu Peng , Tan Qian , Zhang Yunpeng , Zha Xiantao , Yang Songmei , Yang Ranbing
Published: February 2022

Maize is one of the essential crops for food supply. Accurate sorting of seeds is critical for cultivation and marketing purposes, while the traditional methods of variety identification are time-consuming, inefficient, and easily damaged. This study proposes a rapid classification method for maize seeds using a combination of machine vision and deep learning. 8080 maize seeds of five varieties were collected, and then the sample images were classified into training and validation sets in the proportion of 8:2, and the data were enhanced. The proposed improved network architecture, namely P-ResNet, was fine-tuned for transfer learning to recognize and categorize maize seeds, and then it compares the performance of the models. The results show that the overall classification accuracy was determined as 97.91, 96.44, 99.70, 97.84, 98.58, 97.13, 96.59, and 98.28% for AlexNet, VGGNet, P-ResNet, GoogLeNet, MobileNet, DenseNet, ShuffleNet, and EfficientNet, respectively. The highest classification accuracy result was obtained with P-ResNet, and the model loss remained at around 0.01. This model obtained the accuracy of classifications for BaoQiu, ShanCu, XinNuo, LiaoGe, and KouXian varieties, which reached 99.74, 99.68, 99.68, 99.61, and 99.80%, respectively. The experimental results demonstrated that the convolutional neural network model proposed enables the effective classification of maize seeds. It can provide a reference for identifying seeds of other crops and be applied to consumer use and the food industry.
Optimized Nitrogen Rate, Plant Density, and Regulated Irrigation Improved Grain, Biomass Yields, and Water Use Efficiency of Maize at the Oasis Irrigation Region of China
Authors: Asibi Aziiba Emmanuel , Hu Falong , Fan Zhilong , Chai Qiang
Published: February 2022

Nitrogen is a key factor in maize (Zea mays L.) grain and biomass production. Inappropriate application with sub-optimum plant density and irrigation can lead to low productivity and inefficient use. A two-year field experiment was conducted to determine which nitrogen rate, plant density, and irrigation level optimize grain, biomass yield, and water use efficiency. Three nitrogen rates of urea (46–0–0 of N–P2O5–K2O) (N0 = 0 kg N ha−1, N1 = 270 kg N ha−1, and N2 = 360 kg N ha−1), with three maize densities (D1 = 75,000 plants ha−1, D2 = 97,500 plants ha−1, and D3 = 120,000 plants ha−1), and two irrigation levels (W1 = 5250 m3/hm2 and W2 = 4740 m3/hm2) were investigated. The results show that both grain and biomass yields were affected by the main factors. The interaction between nitrogen rate and irrigation level significantly (p < 0.001) affected grain yield but not biomass. It was observed that the grain yield increased correspondingly with nitrogen rate and plant density, while it decreased as the irrigation level increased. Water use efficiency was significantly (p < 0.001) affected by the main factors and their interactions. Nevertheless, water use efficiency was highest at (5250 m3/hm2) × 270 kg N ha−1; × 360 kg N ha−1 × 120,000 plants ha−1 and increased from 62% to 68%. In addition, the highest biomass yield was recorded at 5250 m3/hm2 × 270 kg N ha−1; × 360 kg N ha−1 × 120,000 plants ha−1 while the interaction of either irrigation level with 0 and 270 kg ha−1 or 97,500 and 120,000 plants ha−1 yielded the lowest water use efficiency. Thus, optimized nitrogen rates, plant density, and alternate irrigation levels can support optimum grain and biomass yields. It can also improve nitrogen and water use efficiency in maize production.
Agronomical and Physiological Responses of Faba Bean Genotypes to Salt Stress
Authors: Afzal Muhammad , Alghamdi Salem S. , Migdadi Hussein H. , El-Harty Ehab , Al-Faifi Sulieman A.
Published: February 2022

Considering the importance of salinity stress and genotype screening under stress conditions, the current study evaluated faba bean genotypes in response to saline stress and identified those that were tolerant and determined the influential ratio of each yield component on seed yield under both conditions. As a result, 12 faba bean genotypes were tested under 2 levels of salt stress (100 mM and 200 mM) and a control. The study was analyzed with multivariate (descriptive, ANOVA, PCA, biplot, cluster analysis, and indices) analysis techniques to determine the tolerance level of each genotype. Similarly, the cluster analysis results reported that faba bean genotypes were divided into two groups under the control and 100 mM salinity levels; however, the 200 mM salinity level recorded three groups of faba bean genotypes, showing that salinity stress may limit phenotypic variability among faba bean genotypes. The descriptive analysis results showed a wide range of diversity among the studied characteristics under control and salinity stress conditions. The number of seeds/plants recorded a significant association with plant height (cm) (PH), stomatal conductance (SC), days to flowering (DF), the number of pods, and seed weight (g) (SW); however, an insignificant association was recorded with leaf temperature (LT), fresh weight (g) (FW), Na+, K+, and Na/K ratio. The first three principal components (PCs) represent 81.45% of the variance among the studied traits. The most significant characteristics that contributed the most to the diversity were (PH, leaf area, SPAD reading, stomatal conductance, DF, number of pods/plants, number of seeds/pods, SW, K, and total chlorophyll content); however, the significant genotypes (Hassawi-2, Sakha, ILB-4347, Misr-3, FLIP12501FB) were present in PC1 under both conditions. The results predicted that Hassawi-2, ILB-4347, Sakha, Misr-3, and Flip12501FB were the significant (tolerant) genotypes. However, FLIP12504FB represents a sensitive genotype based on its final grain yield. The results of the indices also recorded significant index correlations with grain yield, demonstrating that these indices are effective tools for screening faba bean-tolerant genotypes under salinity stress conditions.
Spatial Variability of Soil Properties and Its Effect on Maize Yields within Field—A Case Study in Hungary
Authors: Nyéki Anikó , Daróczy Bálint , Kerepesi Csaba , Neményi Miklós , Kovács Attila József
Published: February 2022

To better understand the potential of soils, understanding how soil properties vary over time and in-field is essential to optimize the cultivation and site-specific technologies in crop production. This article aimed at determining the within-field mapping of soil chemical and physical properties, vegetation index, and yield of maize in 2002, 2006, 2010, 2013, and 2017, respectively. The objectives of this five-year field study were: (i) to assess the spatial and temporal variability of attributes related to the maize yield; and (ii) to analyse the temporal stability of management zones. The experiment was carried out in a 15.3 ha research field in Hungary. The soil measurements included sand, silt, clay content (%), pH, phosphorous (P2O5), potassium (K2O), and zinc (Zn) in the topsoil (30 cm). The apparent soil electrical conductivity was measured in two layers (0–30 cm and 30–90 cm, mS/m) in 2010, in 2013, and in 2017. The soil properties and maize yields were evaluated in 62 management zones, covering the whole research area. The properties were characterized as the spatial-temporal variability of these parameters and crop yields. Classic statistics and geostatistics were used to analyze the results. The maize yields were significantly positively correlated (r = 0.62–0.73) with the apparent electrical conductivity (Veris_N3, Veris_N4) in 2013 and 2017, and with clay content (r = 0.56–0.81) in 2002, 2013, and 2017.
Nutritional Characteristics of the Seed Protein in 23 Mediterranean Legumes
Authors: Elamine Youssef , Alaiz Manuel , Girón-Calle Julio , Guiné Raquel P. F. , Vioque Javier
Published: February 2022

The search for new sources of plant protein for food and animal feed is driven by an increasing demand in developing countries and the interest in healthy alternatives to animal protein. Seeds from 23 different wild legumes belonging to tribes Gallegeae, Trifolieae, and Loteae were collected in southern Spain and their total amino acid composition was analyzed, by reverse phase-high performance liquid chromatography (RP-HPLC), in order to explore their nutritional value. Protein content in the seeds ranged from 15.5% in Tripodium tetraphyllum to 37.9% and 41.3% in Medicago minima and Medicago polymorpha, respectively. Species belonging to tribe Trifolieae, such as Melilotus elegans and Trifolium spp., showed the most equilibrated amino acid composition and the best theoretical nutritional values, although all species were deficient in sulfur amino acids. The amino acid composition of the seeds from some of these legumes was characterized by high levels of the anticancer non-proteic amino acid canavanine This amino acid was found free in the seeds from some of the species belonging to each of the three tribes included in the present work. Astragalus pelecinus in tribe Gallegea, Trifolium angustifolium in tribe Trifolieae, and Anthyllis vulneraria in tribe Loteae have 3.2%, 3.7%, and 7.2% canavanine, respectively. Seeds from Anthyllis vulneraria, Hymenocarpus lotoides, and Hymenocarpos cornicina have the highest contents in canavanine overall. In conclusion, the seeds from some of these legumes could be used for human consumption and for feeding animals because they contain protein of good nutritional quality. These plants could be useful in domestication and breeding programs for production of new varieties with improved nutritional and functional properties. In addition, some of these species may be of interest as a source of the bioactive compound canavanine.
Growth and Antioxidant Responses of Lettuce (Lactuca sativa L.) to Arbuscular Mycorrhiza Inoculation and Seaweed Extract Foliar Application
Authors: Rasouli Farzad , Amini Trifa , Asadi Mohammad , Hassanpouraghdam Mohammad Bagher , Aazami Mohammad Ali , Ercisli Sezai , Skrovankova Sona , Mlcek Jiri
Published: February 2022

Biofertilizers, such as arbuscular mycorrhiza fungi (AMF) and seaweed extract (SWE), have been effective in environmental and agricultural ecosystems. In this study, the effects of AMF, SWE, and their co-application were assayed on the growth and antioxidant potential of lettuce plants. The experiment was conducted as a factorial based on a completely randomized design with two factors and four replications under greenhouse conditions. The first factor was AMF (Glomus mosseae) at two levels consisting of AMF application (20 g pot−1), and without using AMF; and the second factor was SWE foliar spraying (Ascophyllum nodosum) at 0.5, 1.5 and 3 g L−1 concentration. The results revealed that the highest root colonization (85%) belonged to AMF and SWE (3 g L−1) × AMF; the lowest colonization rate (65%) was observed for AMF × SWE (0.5 g L−1) treatment. The highest growth parameters (leaf number, shoot and root fresh weight, head diameter), biochemical traits (total soluble proteins, carbohydrates content) and TAA, total antioxidant activity by FRAP method and ascorbic acid, total phenolics, and flavonoids content were obtained with the co-applications. Therefore, the best results of the evaluated traits were achieved with AMF × SWE (3 g L−1). The TAA value was increased three-fold compared to the control. Total phenolics and flavonoids content were 2.24 and 6.59 times higher than the control, respectively. On the other hand, leaf dry weight was decreased with the further growth of the plants. Overall, the co-application of AMF with SWE can be recommended to producers as an alternative and environment-friendly strategy to improve the qualitative and quantitative traits of the lettuce crop.
Postharvest Changes in the Nutritional Properties of Commercial and Traditional Lettuce Varieties in Relation with Overall Visual Quality
Authors: Martínez-Ispizua Eva , Calatayud Ángeles , Marsal Jose Ignacio , Basile Federico , Cannata Claudio , Abdelkhalik Abdelsattar , Soler Salvador , Valcárcel José Vicente , Martínez-Cuenca Mary-Rus
Published: February 2022

Nowadays the cultivation and consumption of traditional lettuce varieties are growing as they are particularly appealing to consumers for their diversity, and high nutraceutical quality. However, lettuce is a highly perishable product, which results in significant nutritional loss from harvest to final consumers. In this work, the content of some bioactive compounds (chlorophylls, carotenoids, anthocyanins, ascorbic acid, phenols), overall antioxidant capacity and mineral content was monitored in five landraces and four commercial lettuce varieties to compare their variation during the storage period. Visual characterization was conducted during the postharvest period, as was the determination of the parameters indicative of oxidative stress, to establish the preservation capacity of their physico-chemical attributes. As a general trend, lettuce varieties showed individualized behavior during the postharvest period, which was not necessarily better in the commercial varieties compared to the landraces. Of all the varieties, landrace L10 stood out for not showing excessive variations in its general appearance or nutritional quality throughout its life cycle. However, in terms of initial concentration of bioactive compounds, the reddest varieties (CL4 and L11) stand out. These results indicate variability among varieties, which emphasizes the potential of lettuce landraces in postharvest practices.
Mapping Ecological Focus Areas within the EU CAP Controls Framework by Copernicus Sentinel-2 Data
Authors: Sarvia Filippo , De Petris Samuele , Borgogno-Mondino Enrico
Published: February 2022

Greening is a Common Agricultural Policy (CAP) subsidy that ensures that all EU farmers receiving income support produce climate and environmental benefits as part of their farming activities. To receive greening support, it is mandatory for the farmer to carry out three agricultural practices that are considered environmentally and climate friendly: (a) crop diversification; (b) maintenance of permanent meadows and pastures; and (c) presence of an Ecological Focus Area (EFA). Contributions are delivered and monitored by paying agencies (PP) that ordinarily perform administrative checks and spot checks. The latter are provided through photo-interpretation of high-resolution satellite or aerial images and, in specific cases, through local ground checks (GC) as well. In this work, stimulated by the Piemonte Regional Agency for Payments in Agriculture (ARPEA), a prototype service to support PPs’ controls within the greening CAP framework was proposed with special concern for EFA detection. The proposed approach is expected to represent a valid alternative or supporting tool for GC. It relies on the analysis of NDVI time series derived from Copernicus Sentinel-2 data. The study was conducted in the provinces of Turin, Asti and Vercelli within the Piedmont Region (NW Italy), and over 12,500 EFA fields were assessed. Since the recent National Report No. 5465 stipulates that mowing and any other soil management operation is prohibited on set-aside land designated as an EFA during the reference period (RP) between 1st March and 30th June, a time series (TS) of NDVI in the same period was generated. Once averaged at plot level, NDVI trends were modelled by a first-order polynomial, and the correspondent statistics (namely, R2, MAE and maximum residual) was computed. These were assumed to play the role of discriminants in EFA detection based on a thresholding approach (Otsu’s method), calibrated with reference to the training dataset. The threshold satisfaction was therefore tested, and, depending on the number of satisfied thresholds out of the possible three, EFA and non-EFA plots were detected with a different degree of reliability. The correspondent EFA map was generated for the area of interest and validated according to GCs as provided by the ARPEA. The results showed an overall accuracy of 84%, indicating that the approach is promising. The authors retain that this procedure represents a valid alternative (or integrating) tool for ground controls by PPs.
Vegetable Trade Flows and Chain Competitiveness Linkage Analysis Based on Spatial Panel Econometric Modelling and Porter’s Diamond Model
Authors: Constantin Marius , Sacală Mihail-Dumitru , Dinu Mihai , Piștalu Maria , Pătărlăgeanu Simona Roxana , Munteanu Irina-Denisa
Published: February 2022

The vegetable sector plays an important role in ensuring food security. Vegetable trade flows in Romania have become a major concern due to constant trade balance deficits despite the country’s agricultural potential. Taking into account the paradox between what could be considered an abundance of factor endowments and poor trade balance results, the objective of this research was to study the linkage between vegetable trade flows and chain competitiveness. Spatial panel econometric methods were used to study the impact of the international vegetable market on the demand in Romania, while the Balassa index and Porter’s diamond modelling techniques were used to study the competitiveness of the vegetable chain at both county and national levels. By applying the spatial regression method to the international trade and national production panel data, it was found that an increase in the quantity of vegetables imported into Romania would cause an even greater decrease in national vegetable production. The results show that Romanian vegetable production is highly and negatively influenced by the growing appetite for imports—therefore leading to a national dependence on the global vegetable chain. Porter’s diamond model results confirm that: (a) growing vegetables is profitable in Romania and the average profit margin is higher in this economic sector than in many others; (b) there is a lack of competitiveness caused by the post-communist excessively fragmented agrarian land structure and poor performance of the irrigation, warehousing, and transportation sectors; (c) the national production of vegetables is generally self-sufficient with the exception of three counties that resort to importing and account for more than 70% of Romania’s total vegetable imports; (d) factor endowments cannot be fully harnessed, and this contributes to the deepening of the trade balance deficits. Improvement is possible by fostering competitiveness through increasing the performance of supporting industries and the logistics infrastructure, as well as removing market access barriers for the many small farmers.
Animal-Assisted Intervention and Health Care Workers’ Psychological Health: A Systematic Review of the Literature
Authors: Acquadro Maran Daniela , Capitanelli Ilaria , Cortese Claudio Giovanni , Ilesanmi Olayinka Stephen , Gianino Maria Michela , Chirico Francesco
Published: February 2022

Healthcare settings have recently increased the use of companion animals in the workplace to provide emotional support to people with disabilities, but there is limited empirical research on the effects of these programs on healthcare workers. However, it is reasonable to speculate that Animal-Assisted Interventions (AAIs) may have positive effects on health care workers (HCWs) by buffering the negative effects of work-related stress and other occupational psychosocial risk factors. The aim of this review was to examine the beneficial effects of AAIs on the psychological well-being of HCWs. A systematic review was conducted in December 2021 to gain insight into the positive effects of pets on HCWs in the workplace. Searches were conducted in the following databases: Scopus, PubMed/Medline, Web of Science, and Google Scholar, including studies between 2001 and December 2021, and 12 articles were included in the review. The results indicate that implementing the AAI program in a busy clinic is feasible and that the program is accepted by medical professionals because of the immense psychological benefits it provides. However, the healthcare professionals disliked the experimental design that forced them to leave their workplaces at a certain time.
Comparative Proteomics Study of Yak Milk from Standard and Naturally Extended Lactation Using iTRAQ Technique
Authors: Cao Mingxing , Huang Lin , Jin Suyu , Zhao Mengbo , Zheng Yucai
Published: February 2022

Extended lactation is a common phenomenon in lactating yaks under grazing and natural reproduction conditions. To elucidate differences in milk protein compositions and mammary gland functions between yaks of standard lactation (TL yaks) and prolonged lactation (HL yaks), whole milk samples of TL yaks and HL yaks (n = 15 each) were collected from a yak pasture at the northwest highland of China. The iTRAQ technique was used to compare the skim milk proteins in the two yak groups. A total of 202 differentially expressed proteins (DEPs) were revealed, among which 109 proteins were up-regulated and 93 were down-regulated in the milk of HL yaks compared to TL yaks. Caseins including κ-casein, αs1-casein, αs2-casein, and β-casein were up-regulated in HL yak milk over 1.43-fold. The GO function annotation analysis showed that HL yaks produced milk with characteristics of milk at the degeneration stage, similar to that of dairy cows. KEGG enrichment showed that the metabolic pathways with the most differences are those that involve carbohydrate metabolism and the biosynthesis of amino acids. The present results highlight detailed differences in skim milk proteins produced by HL yaks and TL yaks and suggest that the mammary gland of HL yak is at the degeneration stage.