bluuebunny/crossref_metadata_2025 huggingface dataset:
Haematococcus pluvialis Accumulated Lipid and Astaxanthin in a Moderate and Sustainable Way by the Self-Protection Mechanism of Salicylic Acid Under Sodium Acetate Stress
Authors: Hu Qunju , Song Mingjian , Huang Danqiong , Hu Zhangli , Wu Yan , Wang Chaogang
Published: November 2021

To elucidate the mechanism underlying increased fatty acid and astaxanthin accumulation in Haematococcus pluvialis, transcriptome analysis was performed to gain insights into the multiple defensive systems elicited by salicylic acid combined with sodium acetate (SAHS) stresses with a time course. Totally, 112,886 unigenes and 61,323 non-repeat genes were identified, and genes involved in carbon metabolism, primary and secondary metabolism, and immune system responses were identified. The results revealed that SA and NaAC provide both energy and precursors to improve cell growth of H. pluvialis and enhance carbon assimilation, astaxanthin, and fatty acids production in this microalga with an effective mechanism. Interestingly, SA was considered to play an important role in lowering transcriptional activity of the fatty acid and astaxanthin biosynthesis genes through self-protection metabolism in H. pluvialis, leading to its adaption to HS stress and finally avoiding massive cell death. Moreover, positive correlations between 15 key genes involved in astaxanthin and fatty acid biosynthesis pathways were found, revealing cooperative relation between these pathways at the transcription level. These results not only enriched our knowledge of the astaxanthin accumulation mechanism in H. pluvialis but also provided a new view on increasing astaxanthin production in H. pluvialis by a moderate and sustainable way in the future.
Why Do Individuals Seek Information? A Selectionist Perspective
Authors: Borgstede Matthias
Published: November 2021

Several authors have proposed that mechanisms of adaptive behavior, and reinforcement learning in particular, can be explained by an innate tendency of individuals to seek information about the local environment. In this article, I argue that these approaches adhere to an essentialist view of learning that avoids the question why information seeking should be favorable in the first place. I propose a selectionist account of adaptive behavior that explains why individuals behave as if they had a tendency to seek information without resorting to essentialist explanations. I develop my argument using a formal selectionist framework for adaptive behavior, the multilevel model of behavioral selection (MLBS). The MLBS has been introduced recently as a formal theory of behavioral selection that links reinforcement learning to natural selection within a single unified model. I show that the MLBS implies an average gain in information about the availability of reinforcement. Formally, this means that behavior reaches an equilibrium state, if and only if the Fisher information of the conditional probability of reinforcement is maximized. This coincides with a reduction in the randomness of the expected environmental feedback as captured by the information theoretic concept of expected surprise (i.e., entropy). The main result is that behavioral selection maximizes the information about the expected fitness consequences of behavior, which, in turn, minimizes average surprise. In contrast to existing attempts to link adaptive behavior to information theoretic concepts (e.g., the free energy principle), neither information gain nor surprise minimization is treated as a first principle. Instead, the result is formally deduced from the MLBS and therefore constitutes a mathematical property of the more general principle of behavioral selection. Thus, if reinforcement learning is understood as a selection process, there is no need to assume an active agent with an innate tendency to seek information or minimize surprise. Instead, information gain and surprise minimization emerge naturally because it lies in the very nature of selection to produce order from randomness.
Fuzzy Lexical Representations in Adult Second Language Speakers
Authors: Gor Kira , Cook Svetlana , Bordag Denisa , Chrabaszcz Anna , Opitz Andreas
Published: November 2021

We propose the fuzzy lexical representations (FLRs) hypothesis that regards fuzziness as a core property of nonnative (L2) lexical representations (LRs). Fuzziness refers to imprecise encoding at different levels of LRs and interacts with input frequency during lexical processing and learning in adult L2 speakers. The FLR hypothesis primarily focuses on the encoding of spoken L2 words. We discuss the causes of fuzzy encoding of phonological form and meaning as well as fuzzy form-meaning mappings and the consequences of fuzzy encoding for word storage and retrieval. A central factor contributing to the fuzziness of L2 LRs is the fact that the L2 lexicon is acquired when the L1 lexicon is already in place. There are two immediate consequences of such sequential learning. First, L2 phonological categorization difficulties lead to fuzzy phonological form encoding. Second, the acquisition of L2 word forms subsequently to their meanings, which had already been acquired together with the L1 word forms, leads to weak L2 form-meaning mappings. The FLR hypothesis accounts for a range of phenomena observed in L2 lexical processing, including lexical confusions, slow lexical access, retrieval of incorrect lexical entries, weak lexical competition, reliance on sublexical rather than lexical heuristics in word recognition, the precedence of word form over meaning, and the prominence of detailed, even if imprecisely encoded, information about LRs in episodic memory. The main claim of the FLR hypothesis – that the quality of lexical encoding is a product of a complex interplay between fuzziness and input frequency – can contribute to increasing the efficiency of the existing models of LRs and lexical access.
Creating a Corpus of Multilingual Parent-Child Speech Remotely: Lessons Learned in a Large-Scale Onscreen Picturebook Sharing Task
Authors: Woon Fei Ting , Yogarrajah Eshwaaree C. , Fong Seraphina , Salleh Nur Sakinah Mohd , Sundaray Shamala , Styles Suzy J.
Published: November 2021

With lockdowns and social distancing measures in place, research teams looking to collect naturalistic parent-child speech interactions have to develop alternatives to in-lab recordings and observational studies with long-stretch recordings. We designed a novel micro-longitudinal study, the Talk Together Study, which allowed us to create a rich corpus of parent-child speech interactions in a fully online environment (N participants = 142, N recordings = 410). In this paper, we discuss the methods we used, and the lessons learned during adapting and running the study. These lessons learned cover nine domains of research design, monitoring and feedback: Recruitment strategies, Surveys and Questionnaires, Video-call scheduling, Speech elicitation tools, Videocall protocols, Participant remuneration strategies, Project monitoring, Participant retention, and Data Quality, and may be used as a primer for teams planning to conduct remote studies in the future.
Socioeconomic Status, Culture, and Reading Comprehension in Immigrant Students
Authors: Ibáñez-Alfonso Joaquín A. , Hernández-Cabrera Juan Andrés , Duñabeitia Jon Andoni , Estévez Adelina , Macizo Pedro , Bajo María Teresa , Fuentes Luis J. , Saldaña David
Published: November 2021

Research on reading comprehension in immigrant students is heterogeneous and conflicting. Differences in socioeconomic status and cultural origins are very likely confounds in determining whether differences to native pupils can be attributed to immigrant status. We collected data on 312 Spanish students of Native, of Hispanic origin–therefore with the same family language as native students- and Non-Hispanic origin, while controlling for socioeconomic status, non-verbal reasoning and school membership. We measured reading comprehension, knowledge of syntax, sentence comprehension monitoring, and vocabulary. Differences among groups appeared only in vocabulary and syntax (with poorer performance in the non-Hispanic group), with no differences in reading comprehension. However, regression analyses showed that most of the variability in reading comprehension was predicted by age, socioeconomic status, non-verbal reasoning, and comprehension monitoring. Group membership did not significantly contribute to explain reading comprehension variability. The present study supports the idea that socioeconomically disadvantaged students, both native and immigrants from diverse cultural backgrounds, irrespective of the language of origin, are probably equally at risk of poor reading comprehension.
More Effort, Less Fatigue: The Role of Interest in Increasing Effort and Reducing Mental Fatigue
Authors: Milyavskaya Marina , Galla Brian M. , Inzlicht Michael , Duckworth Angela L.
Published: November 2021

People generally prefer easier over more difficult mental tasks. Using two different adaptations of a demand selection task, we show that interest can influence this effect, such that participants choose options with a higher cognitive workload. Interest was also associated with lower feelings of fatigue. In two studies, participants (N = 63 and N = 158) repeatedly made a choice between completing a difficult or easy math problem. Results show that liking math predicts choosing more difficult (vs. easy) math problems (even after controlling for perceived math skill). Two additional studies used the Academic Diligence Task (Galla et al., 2014), where high school students (N = 447 and N = 884) could toggle between a math task and playing a video game/watching videos. In these studies, we again find that math interest relates to greater proportion of time spent on the math problems. Three of these four studies also examined perceived fatigue, finding that interest relates to lower fatigue. An internal meta-analysis of the four studies finds a small but robust effect of interest on both the willingness to exert greater effort and the experience of less fatigue (despite engaging in more effort).
Poles Apart? The Extent of Similarity Between Online Extremist and Non-extremist Message Content
Authors: Prentice Sheryl , Taylor Paul J.
Published: November 2021

Within studies of extremism, extremist and non-extremist messages are generally treated as two sets of competing constructed narratives. However, some research has argued that these message forms are not dichotomous and that non-extremist narratives demonstrate overlap with extremist master narratives. The aim of this paper is to test this hypothesis empirically by comparing 250 extremist, 250 mainstream and 250 counter-extremist messages. The paper finds considerable overlap between extremist and non-extremist material. However, an analysis of underlying content suggests that this overlap may not be so much due to the extensive adoption of an extremist master narrative by non-extremist authors, but rather a question of resistance and positioning, specifically, who are authors resisting and why? The findings have implications for counter-extremism policy.
Advanced Age Is Associated With Catatonia in Critical Illness: Results From the Delirium and Catatonia Prospective Cohort Investigation
Authors: Connell Jennifer , Kim Ahra , Brummel Nathan E. , Patel Mayur B. , Vandekar Simon N. , Pandharipande Pratik , Dittus Robert S. , Heckers Stephan , Ely E. Wes , Wilson Jo Ellen
Published: November 2021

Introduction: Catatonia, characterized by motor, behavioral and affective abnormalities, frequently co-occurs with delirium during critical illness. Advanced age is a known risk factor for development of delirium. However, the association between age and catatonia has not been described. We aim to describe the occurrence of catatonia, delirium, and coma by age group in a critically ill, adult population.

Design: Convenience cohort, nested within two clinical trials and two observational cohort studies.

Setting: Intensive care units in an academic medical center in Nashville, TN.

Patients: 378 critically ill adult patients on mechanical ventilation and/or vasopressors.

Measurements and Main Results: Patients were assessed for catatonia, delirium, and coma by independent and blinded personnel, the Bush Francis Catatonia Rating Scale, the Confusion Assessment Method for the Intensive Care Unit (ICU) and the Richmond Agitation and Sedation Scale. Of 378 patients, 23% met diagnostic criteria for catatonia, 66% experienced delirium, and 52% experienced coma during the period of observation. There was no relationship found between age and catatonia severity or age and presence of specific catatonia items. The prevalence of catatonia was strongly associated with age in the setting of critical illness (p < 0.05). Delirium and comas' association with age was limited to the setting of catatonia.

Conclusion: Given the significant relationship between age and catatonia independent of coma and delirium status, these data demonstrate catatonia's association with advanced age in the setting of critical illness. Future studies can explore the causative factors for this association and further elucidate the risk factors for acute brain dysfunction across the age spectrum.
Association of Cigarette Smoking With Male Cognitive Impairment and Metal Ions in Cerebrospinal Fluid
Authors: Li Hui , Mu Qingshuang , Kang Yimin , Yang Xiaoyu , Shan Ligang , Wang Meiling , Li Cunbao , Liu Yanlong , Wang Fan
Published: November 2021

Objective: Cigarette smoking might accelerate cognitive impairment; however, this has never been investigated using human cerebrospinal fluid (CSF). We conducted this study to investigate the association between cigarette smoking and cognitive impairment through metal ions in CSF.

Methods: We obtained 5-ml CSF samples from routine lumbar puncture procedures in patients undergoing anterior cruciate ligament reconstruction before surgery in China. A total of 180 Chinese males were recruited (80 active smokers and 100 non-smokers). We measured specific cigarette-related neurotoxic metal ions in CSF, including iron, copper, zinc, lead, aluminum, and manganese. Sociodemographic data and history of smoking were obtained. The Montreal Cognitive Assessment (MoCA) was applied.

Results: Active smokers had fewer years of education (11.83 ± 3.13 vs. 13.17 ± 2.60, p = 0.01), and higher age (33.70 ± 10.20 vs. 29.76 ± 9.58, p = 0.01) and body mass index (25.84 ± 3.52 vs. 24.98 ± 4.06, p =0.03) than non-smokers. Compared to non-smokers, active smokers had significantly higher CSF levels of iron, zinc, lead, and aluminum and lower MoCA scores (all p < 0.05). Average daily numbers of cigarettes smoked negatively correlated with the MoCA scores (r = −0.244, p = 0.048). In young smokers, CSF manganese levels negatively correlated with MoCA scores (r = −0.373, p = 0.009).

Conclusions and Relevance: Cigarette smoking might be associated with male cognitive impairment, as shown by lower MoCA scores and higher levels of CSF iron, zinc, lead, and aluminum in active smokers. This might be early evidence of cigarette smoking accelerating male cognitive impairment.
Neuropsychiatric Symptoms Exacerbate the Cognitive Impairments in Patients With Late-Life Depression
Authors: Zhang Min , Chen Ben , Zhong Xiaomei , Zhou Huarong , Wang Qiang , Mai Naikeng , Wu Zhangying , Chen Xinru , Peng Qi , Zhang Si , Yang Minfeng , Lin Gaohong , Ning Yuping
Published: November 2021

Background: Neuropsychiatric symptoms (NPS) and cognitive impairments are both common in patients with late-life depression (LLD). However, the relationship between NPS and cognitive functions in LLD patients remains unclear. The current study aims to explore the effects of NPS on cognitive impairments in LLD patients.

Methods: Two hundred and sixty-two LLD patients and 141 normal controls (NC) were recruited. Exploratory factor analysis was used to extract factors from the Neuropsychiatric Inventory (NPI). Correlation, mediation, and moderation analyses were used to explore whether NPS exacerbated the cognitive impairments in LLD and whether NPS exhibited different effects on cognitive impairments in acute-state LLD (aLLD) and recovery-state LLD (rLLD).

Results: Three main factors were extracted from the NPI, including emotional, behavioral, and psychotic factors. The patients with LLD exhibited worse cognition and higher NPI scores, and the scores of NPI-total and three extracted factors were negatively associated with cognitive scores. The mediation analyses exhibited that NPI-total and behavioral factor scores increase the difference in cognition scores between LLD and NC groups. The mediation analyses exhibited that behavioral factor score played a greater effect on impairing MMSE in the rLLD group than in the aLLD group. Additionally, behavioral factor score was in a trend to be negatively associated with Mini-Mental State Examination (MMSE) score changes at a one-year follow-up (p = 0.051).

Conclusions: NPS, especially behavioral symptoms, exacerbate cognitive impairments in LLD and may contribute to residual cognitive impairment in rLLD patients. Early intervention for behavioral symptoms in LLD patients may be beneficial to their long-term clinical prognosis.
Sleep Quality and Mental Health of Medical Students in Greece During the COVID-19 Pandemic
Authors: Eleftheriou Anna , Rokou Aikaterini , Arvaniti Aikaterini , Nena Evangelia , Steiropoulos Paschalis
Published: November 2021

Background-Aim: Medical students have been greatly affected by the COVID-19 pandemic due to their educational program, which comprises theoretical knowledge and also clinical duties, making them vulnerable to viral exposures and possibly affecting their everyday life. The aim of this study was to explore changes in sleep and mental health parameters among medical students in Greece during the second year of the pandemic.

Methods: This cross-sectional study comprised students of all medical schools in Greece (n = 7), using an anonymous online survey. Participants completed the following questionnaires: Pittsburgh Sleep Quality Index (PSQI), Athens Insomnia Scale (AIS), Fatigue Severity Scale (FSS), General Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-9 (PHQ-9). Statistical analysis was conducted with the use of SPSS v.26 (IBM SPSS, Armonk NY, USA).

Results: Out of the 562 received responses, 559 met the inclusion criteria. The largest proportion of the respondents came from 4th-year (27.8%) and the majority of the sample were females (69.8%). Only 5.9% of the participants reported having been infected by SARS-COV-2. Most of the respondents experienced insomnia (65.9%, mean AIS score: 7.59 ± 4.24), poor sleep quality (52.4%, mean PSQI score: 6.6 ± 3.25) and increased fatigue (48.5%, mean 35.82 ± 11.74). Moderate to severe symptoms of anxiety (mean 9.04 ± 5.66) and depression (mean 9.36 ± 6.15) were noted. Suicidal ideation was found in 16.7% of the sample, while use of sleeping pills in the previous month was reported by 8.8% (n = 47). Further analysis revealed independent associations between sleep and mental health parameters. Higher AIS score was associated with greater FSS score; higher PSQI scores with higher GAD-7 and PHQ-9 scores. Additionally, female students were found to be significantly more affected than males by the COVID-19 pandemic, displaying higher levels of insomnia, sleep disturbances, anxiety and depression. In addition, those with a history of COVID-19 infection or in close proximity with a positive case reported significantly more significant post-traumatic symptoms in IES-COVID-19 questionnaire.

Conclusions: In the aftermath of the COVID-19 pandemic, prevalence of sleep and mental health disorders among Greek medical students is significant, highlighting the need for better surveillance of students' wellbeing and subsequent counseling, with special focus on female students and other affected groups.
The Association Between Psychological Symptoms and Self-Reported Temporomandibular Disorders Pain Symptoms in Children and Adolescents
Authors: Al-Khotani Amal , Meisha Dalia E. , Al Sayegh Samaa , Hedenberg-Magnusson Britt , Ernberg Malin , Christidis Nikolaos
Published: November 2021

Background: Several studies have reported an association between temporomandibular disorder pain (TMD-P) and emotional disorders in children and adolescents. However, no studies have reported if self-reported TMD-P in Saudi Arabia is associated with psychosocial symptoms. Therefore, the current study aimed to evaluate the association between self-reported TMD-P with depression, anxiety and somatic problems in children and adolescents in Saudi Arabia. The hypothesis was that there is an association between self-reported TMD-P and psychological symptoms among children and adolescents.

Materials and Methods: The included participants were randomly selected boys and girls aged between 10 and 18 years, with a mean (SD) age of 14.0 (2.3) years. Out of 633 children and adolescents that were invited to participate, 509 voluntarily agreed to participate, and 466 completed all questionnaires. The questionnaires included items retrieved from the Youth Self Report (YSR) and Axis II of the Research Diagnostic Criteria for TMD (RDC/TMD) besides demographic data, medical history, and presence of oral parafunctions. To assess the presence of self-reported TMD-Pain, each participant was verbally asked two validated questions regarding the presence of TMD-P and dysfunction (2Q-TMD).

Results: Self-reported TMD-P in children and adolescents was significantly associated with anxiety, depression, somatic symptoms, and social problems (P < 0.0001). Further, the frequencies of anxiety, depression, and somatic disorders were more evident among children and adolescents who suffered from TMD-P (P < 0.0001). The odds of reporting TMD-P in children and adolescents was 1.4 times for border line and clinical diagnosis scores for anxiety and withdrawal depression domains, and 2.6 times for the somatic symptoms' domains. However, in the multiple regression model after controlling for possible confounders, only somatic symptoms and social scores were significant. Moreover, self-reported TMD-P was twice as prevalent among girls compared to boys.

Conclusion: This study reports a significant association between psychosocial burden and presence of self-reported TMD-Pain, with a stronger impact on girls than boys. There were significantly higher number of participants with self-reported TMD-P reporting a poor oral and general health. In addition, self-reported TMD-P was higher among those with borderline and clinically diagnosed anxiety/depression scores. Based on this finding, the current study supports that an early approach and recognition of children and adolescents with anxiety, depression, somatic symptoms, and TMD problems. This could result in a lesser burden for these children and adolescents both in regard to pain and psychosocial implications with increased quality of life.
Development of a Machine-Learning-Based Classifier for the Identification of Head and Body Impacts in Elite Level Australian Rules Football Players
Authors: Goodin Peter , Gardner Andrew J. , Dokani Nasim , Nizette Ben , Ahmadizadeh Saeed , Edwards Suzi , Iverson Grant L.
Published: November 2021

Background: Exposure to thousands of head and body impacts during a career in contact and collision sports may contribute to current or later life issues related to brain health. Wearable technology enables the measurement of impact exposure. The validation of impact detection is required for accurate exposure monitoring. In this study, we present a method of automatic identification (classification) of head and body impacts using an instrumented mouthguard, video-verified impacts, and machine-learning algorithms.

Methods: Time series data were collected via the Nexus A9 mouthguard from 60 elite level men (mean age = 26.33; SD = 3.79) and four women (mean age = 25.50; SD = 5.91) from the Australian Rules Football players from eight clubs, participating in 119 games during the 2020 season. Ground truth data labeling on the captures used in this machine learning study was performed through the analysis of game footage by two expert video reviewers using SportCode and Catapult Vision. The visual labeling process occurred independently of the mouthguard time series data. True positive captures (captures where the reviewer directly observed contact between the mouthguard wearer and another player, the ball, or the ground) were defined as hits. Spectral and convolutional kernel based features were extracted from time series data. Performances of untuned classification algorithms from scikit-learn in addition to XGBoost were assessed to select the best performing baseline method for tuning.

Results: Based on performance, XGBoost was selected as the classifier algorithm for tuning. A total of 13,712 video verified captures were collected and used to train and validate the classifier. True positive detection ranged from 94.67% in the Test set to 100% in the hold out set. True negatives ranged from 95.65 to 96.83% in the test and rest sets, respectively.

Discussion and conclusion: This study suggests the potential for high performing impact classification models to be used for Australian Rules Football and highlights the importance of frequencies <150 Hz for the identification of these impacts.
Compost Quality and Markets Are Pivotal for Sustainability in Circular Food-Nutrient Systems: A Case Study of Sri Lanka
Authors: Roy Eric D. , Esham Mohamed , Jayathilake Nilanthi , Otoo Miriam , Koliba Christopher , Wijethunga Isuru B. , Fein-Cole Maya J.
Published: November 2021

Sustainable management of municipal solid waste (MSW) is a critical issue around the world, especially in South Asia where waste generation is expected to double by 2050. Closing the food-nutrient cycle through composting biodegradable MSW has the potential to meet human needs, including sanitation and food security, while protecting the environment. We use an interdisciplinary case study approach including systems thinking to assess Sri Lanka's national MSW composting system, which primarily receives residential and commercial food waste. We embed quantitative compost quality analysis and interviews at 20 composting facilities within a broader qualitative assessment informed by ~60 stakeholders in total. This approach yields insights on how institutional, economic, social, and biophysical aspects of the system are interrelated, and how challenges and solutions can create undesirable and desirable cascading effects, respectively. Such dynamics can create risks of composting facility failure and unintended consequences, diminishing the chances of achieving a sustainable circular food–nutrient system. Compost quality, which was variable, plays a pivotal role within the system—a function of program design and implementation, as well as a determinant of value capture in a circular economy. We make several recommendations to inform future efforts to sustainably manage biodegradable MSW using composting, drawing on our case study of Sri Lanka and prior case studies from other nations. Key among these is the need for increased emphasis on compost product quality and markets in policy and program design and implementation. Targeted measures are needed to improve waste separation, boost compost quality, effectively use compost standards, encourage compost market development, ringfence the revenues generated at municipal compost plants, and identify efficient modes of compost distribution. Such measures require adequate space and infrastructure for composting, resource investment, local expertise to guide effective system management, strong links with the agriculture sector, and continued political support.
Adapting a Participatory and Ecosystem-Based Assessment Impacted by the Pandemic: Lessons Learned With Farmers in Tajikistan
Authors: Spies Michael , Schick Axel , Karomatov Sharofiddin , Bakokhoja Bobozoda , Zikriyokhon Khaidarov , Jobirov Shonazar , Bloch Ralf , Ibisch Pierre L.
Published: November 2021

The paper presents a systemic and participatory assessment approach and scrutinizes how methodological changes necessitated during the Covid-19 pandemic implicated the process and its outcomes. The approach was applied in rural Tajikistan to evaluate changes effected by a development project that promoted the enhancement of biodiversity and ecosystem services in agrarian landscapes. The central building block of the assessment consisted of participatory workshops in 2018 and 2020 with farmers and other stakeholders to develop a systemic knowledge map and to evaluate the promoted strategies based on local expertise. The methodological basis was MARISCO (adaptive MAnagement of vulnerability and RISk at COnservation sites), a holistic and participatory approach to ecosystem-based assessment and management that requires well-trained facilitators. While the activities in 2018 could be implemented as planned, major changes in the work plan were necessary in 2020 due to severe travel restrictions and social distancing rules. Conducting virtual workshops was not possible, as it would have excluded key stakeholders from the process. Instead of conducting a comprehensive assessment workshop guided by two German MARISCO facilitators as originally planned, a series of short and small workshops could be realized. These workshops were facilitated by Tajik scientists after receiving virtual training from their German colleagues. Although it was possible to bring the assessment to a satisfactory conclusion, the methodological changes revealed significant drawbacks. Radical simplifications of the methods were necessary that led to reduced depth of the assessment and missed learning opportunities for participants. Limited experience in workshop guidance by the new facilitators posed challenges to the participatory process and the quality of its outcomes. While the adapted method created training effects that would otherwise have been missed, it also put additional pressure on the capacities of local partners. Our experience during the pandemic offers valuable lessons learned for future applications of systemic-participatory approaches. Whereas, a complete shift to remote applications is problematic, there is a need to put greater emphasis on capacitating local partners. Methodological trade-offs are necessary for partially remote working processes, but principles of participation and systemic thinking should not be compromised.
Decomposition of Random Sequences into Mixtures of Simpler Ones and Its Application in Network Analysis
Authors: Faragó András
Published: November 2021

A classic and fundamental result about the decomposition of random sequences into a mixture of simpler ones is de Finetti’s Theorem. In its original form, it applies to infinite 0–1 valued sequences with the special property that the distribution is invariant to permutations (called an exchangeable sequence). Later it was extended and generalized in numerous directions. After reviewing this line of development, we present our new decomposition theorem, covering cases that have not been previously considered. We also introduce a novel way of applying these types of results in the analysis of random networks. For self-containment, we provide the introductory exposition in more detail than usual, with the intent of making it also accessible to readers who may not be closely familiar with the subject.
Development Indicators and Soybean Production in Brazil
Authors: Toloi Marley Nunes Vituri , Bonilla Silvia Helena , Toloi Rodrigo Carlo , Silva Helton Raimundo Oliveira , Nääs Irenilza de Alencar
Published: November 2021

Due to its agricultural potential, land extensions, and favorable climate, Brazil is one of the largest producers and exporters of various agricultural products. A significant part of this production is placed in Mato Grosso, the primary national producer of several agricultural commodities. The soybean complex alone produced more than 33 million tons of soybean for the 2019/2020 harvest, representing 27% of national production. The economic potential that the soybean commodity represents is linked to the increase in demand for inputs, planted area, production, and productivity. Given these factors, the present study aims to analyze how the largest municipalities of soybean production behave, and the degree of interaction and positive associations between the economic potential promoted by soybean production and the economic/social development and environmental impacts in the Mato Grosso State, Brazil. The methodology was to categorize the thirty largest soybean producing municipalities, using the factor analysis method for selected indicators. The interpretation is made through the adoption of the Driver-Pressure-State-Impact-Response (DPSIR) framework. The results indicated that the groups formed are not homogeneous in terms of socio-economic and environmental development. The three factors that formed, were interpreted using the DPSIR are characterized by the significant influence of the population, reflect on its development, how economic activities are other and not just agriculture. The second also belongs to the driver in the DPSRI framework group. It is associated with the soybean production indicator, implying larger planting areas, generating jobs focused on agricultural activities. The interpretation is made through the adoption of the Driver-Pressure-State-Impact-Response (DPSIR) framework. The results indicated that the groups formed are not homogeneous in terms of socio-economic and environmental development. The significant influence of the population characterizes the three found factors. The first reflects on the region’s development and how other economic activities (not just agriculture) are carried on. The second also belongs to the driver in the DPSRI framework group, and it is associated with the soybean production indicator, generating jobs focused on agricultural activities. The third group, formed by municipalities in the Amazon region, with environmental factors associated with large geographical areas, extensive native forests, and more significant carbon sequestration, considers the DPSRI framework’s impacts. Showing that there are behavior patterns and taking this into account is the optimal way to use the predictors appropriately. Municipalities are expected to be more reactive to some changes than to others to achieve a good level of development.
Grain-Filling Characteristics in Extra-Large Panicle Type of Early-Maturing japonica/indica Hybrids
Authors: Meng Tianyao , Chen Xi , Zhang Xubin , Ge Jialin , Zhou Guisheng , Dai Qigen , Wei Huanhe
Published: November 2021

Early-maturing japonica/indica hybrids (EJIH) have recently been released, performing a yield potential of 13.5 t ha−1 and greater yield increase over conventional japonica rice (CJ) and hybrid indica rice (HI) in production. More spikelets per panicle and improved grain-filling efficiency underlined the basis for the superior yield performance of EJIH. However, few studies are available on the panicle traits and grain-filling characteristics of EJIH, as well as their differences to CJ and HI. In our study, two EJIH, two CJ, and two HI cultivars with similar growth patterns were grown in the same fields. EJIH had a 12.2–18.8% increased (p < 0.05) grain yield relative to CJ and HI, mainly attributed to their higher daily grain yield. Although it had a lower panicle per m2, EJIH exhibited 28.0–38.3% more (p < 0.05) spikelets per m2 from an increase of 58.0–87.8% (p < 0.05) in spikelets per panicle than CJ and HI. Compared with CJ and HI, EJIH had a higher single panicle weight and more grains in the six parts of the panicle, especially in the upper secondary branches (US) and middle secondary branches (MS). EJIH exhibited a higher leaf area index (LAI), leaf area duration (LAD), leaf photosynthetic rate, and SPAD values after heading, which helped increase shoot biomass weight at heading and maturity and post-heading biomass accumulation. For CJ and HI, the grain-filling dynamics of grains in the six parts were all well simulated by the Richards equation. For EJIH, the grain-filling dynamics of grains in the lower secondary branches (LS) were well fitted by the logistics equation, with the Richards equation simulating grain positioning on the other five parts. EJIH had a lower mean grain-filling rate (GRmean) and longer days and grain filling amounts (GFA) during early, middle, and late stages than CJ and HI. Our results suggest EJIH gave a yield advantage over CJ and HI through a higher daily grain yield. The panicle traits and grain-filling characteristics differed greatly among the three cultivar types. Compared with CJ and HI, EJIH had lower GRmean and higher days and more grains in the panicle during early, middle, and late stages, which contributed to an increased GFA after heading, improved filled-grain efficiency, and higher grain yield.
Crop Models: Important Tools in Decision Support System to Manage Wheat Production under Vulnerable Environments
Authors: Wajid Aftab , Hussain Khalid , Ilyas Ayesha , Habib-ur-Rahman Muhammad , Shakil Qamar , Hoogenboom Gerrit
Published: November 2021

Decision support systems are key for yield improvement in modern agriculture. Crop models are decision support tools for crop management to increase crop yield and reduce production risks. Decision Support System for Agrotechnology Transfer (DSSAT) and an Agricultural System simulator (APSIM), intercomparisons were done to evaluate their performance for wheat simulation. Two-year field experimental data were used for model parameterization. The first year was used for calibration and the second-year data were used for model evaluation and intercomparison. Calibrated models were then evaluated with 155 farmers’ fields surveyed for data in rice-wheat cropping systems. Both models simulated crop phenology, leaf area index (LAI), total dry matter and yield with high goodness of fit to the measured data during both years of evaluation. DSSAT better predicted yield compared to APSIM with a goodness of fit of 64% and 37% during evaluation of 155 farmers’ data. Comparison of individual farmer’s yields showed that the model simulated wheat yield with percent differences (PDs) of −25% to 17% and −26% to 40%, Root Mean Square Errors (RMSEs) of 436 and 592 kg ha−1 with reasonable d-statistics of 0.87 and 0.72 for DSSAT and APSIM, respectively. Both models were used successfully as decision support system tools for crop improvement under vulnerable environments.
Establishment and First Year Yield of Interseeded Alfalfa as Influenced by Corn Plant Density and Treatment with Prohexadione, Fungicide and Insecticide
Authors: Grabber John H. , Smith Damon L. , Osterholz William R. , Renz Mark J.
Published: November 2021

Interseeding alfalfa (Medicago sativa L.) into a silage corn (Zea mays L.) companion crop can increase the yield and profitability of forage production and reduce the risk of nutrient and soil loss from cropland, but unreliable establishment of alfalfa hampers the adoption of this practice on dairy farms. This study evaluated plant survival, foliar health, and dry matter yields of two alfalfa varieties when established in corn sown at populations ranging from about 47,500 to 100,000 plants per ha−1 and when treated with prohexadione (PHD), PHD followed by fungicide and insecticide (PHD-FI), or not treated with agrichemicals. The plant density of alfalfa during establishment was adversely impacted by above average precipitation and high corn populations, but substantially improved by PHD-FI treatment, which limited alfalfa etiolation, disease, and defoliation. First-cut dry-matter yields of interseeded alfalfa after corn were maximized at a stand density of approximately 200 plants m−2 or 850 stems m−2 and total first year yield exceeded conventionally spring-seeded alfalfa by 59 to 75%. Overall, our results indicated that PHD-FI treatment promoted good establishment and subsequent forage production of interseeded alfalfa. Applications of PHD-FI must, however, be fine-tuned, and additional management practices must be developed to ensure both good yields of corn silage and reliable establishment of interseeded alfalfa, especially during wet growing conditions.
Assessment and Prediction of Maize Production Considering Climate Change by Extreme Learning Machine in Czechia
Authors: Maitah Mansoor , Malec Karel , Ge Ying , Gebeltová Zdeňka , Smutka Luboš , Blažek Vojtěch , Pánková Ludmila , Maitah Kamil , Mach Jiří
Published: November 2021

Machine learning algorithms have been applied in the agriculture field to forecast crop productivity. Previous studies mainly focused on the whole crop growth period while different time windows on yield prediction were still unknown. The entire growth period was separated into each month to assess their corresponding predictive ability by taking maize production (silage and grain) in Czechia. We present a thorough assessment of county-level maize yield prediction in Czechia using a machine learning algorithm (extreme learning machine (ELM)) and an extensive set of weather data and maize yields from 2002 to 2018. Results show that sunshine in June and water deficit in July were vastly influential factors for silage maize yield. The two primary climate parameters for grain maize yield are minimum temperature in September and water deficit in May. The average absolute relative deviation (AARD), root mean square error (RMSE), and coefficient (R2) of the proposed models are 6.565–32.148%, 1.006–1.071%, 0.641–0.716, respectively. Based on the results, silage yield will decrease by 1.367 t/ha (3.826% loss), and grain yield will increase by 0.337 t/ha (5.394% increase) when the max temperature in May increases by 2 °C. In conclusion, ELM models show a great potential application for predicting maize yield.
Effect of Spatial-Temporal Light Competition on Cotton Yield and Yield Distribution
Authors: Wang Qingru , Chen Huanxuan , Han Yingchun , Xing Fangfang , Wang Zhanbiao , Feng Lu , Wang Guoping , Yang Beifang , Lei Yaping , Xiong Shiwu , Li Xiaofei , Xin Minghua , Du Wenli , Li Yabing
Published: November 2021

The photosynthetically active radiation (PAR) of crop canopy is highly related to yield formation, but how it relates to yield and yield distribution is not well understood. The focus of this study was to explore the relationship between light competition under different densities and yield distributions of cotton. The experiment was conducted in 2019 and 2020 at the Cotton Research Institute of the Chinese Academy of Agricultural Sciences in Anyang city, Henan Province, China. A randomized block design was employed, with a total of three repeats. Each repeat had six density treatments: D1: 15,000; D2: 33,000; D3: 51,000; D4: 69,000; D5: 87,000; and D6: 105,000 plants·ha−1. As predicted, the results showed that the canopy light interception, leaf area index, plant height, and biomass of high-density cotton were higher than those of low-density cotton. The aboveground biomass produced by D6 was the highest, and was 12.9, 19.5, 25.4, 46.3, and 69.2% higher in 2019 and 14.3, 19.9, 32.5, 53.7, and 109.9% higher in 2020 than D5, D4, D3, D2, and D1, respectively. Leaf area, plant height, biomass, boll number, and boll weight were significantly correlated with the light interception rate. D5 (87,000 plants·ha−1) had a higher light interception rate and the highest yield. The highest lint yields produced by D5 were 1673.5 and 1375.4 kg·ha−1 in two years, and was 3.2, 4.3, 5.6, 9.7, and 24.7% higher in 2019, and 6.8, 10.6, 13.5, 21.5, and 34.4% higher in 2020 than D6, D4, D3, D2, and D1, respectively. The boll retention of the lower fruit branch under D5 reached 0.51 and 0.57 in two years, respectively. The shedding rate of the upper fruit branch decreased with the increase in cotton density in two years. The boll retention rate and shedding rate in the lower part of cotton plants were most closely related to light interception, with R2 values of 0.91 and 0.96, respectively. Our study shows cotton yield could be improved through higher light interception by optimizing planting density and canopy structure.
Allelopathic Efficiency of Plant Extracts to Control Cyanobacteria in Hydroponic Culture
Authors: Gil Chan Saem , Duan Shucheng , Kim Ji Hye , Eom Seok Hyun
Published: November 2021

Cyanobacteria rapidly form harmful algal blooms (HABs) that cause serious nutritional imbalances in crop production via hydroponics. Allelopathic extracts from plants can be applied as a solution for ecologically sustainable control of algal blooms. In this study, the effects of 11 aqueous extracts of 10 allelopathic plants in controlling Microcystis aeruginosa were evaluated. Among the extracts, walnut husk and rose leaf extracts exhibited high inhibitory levels for efficient control of algae. High inhibitory levels were achieved owing to large amounts of water-soluble tannins, especially tannic acid. The effective extracts were applied to a hydroponic system cultivated on leafy perilla vegetables. Although the severe doses (IC90) did not guarantee complete algal control due to partial algal regrowth, walnut husk and rose leaf extracts only exerted strong persistent effects on algae control. Persistent algae inhibition contributed to the increase in perilla growth and leaf quality. Rose leaf was potentially a more useful resource for controlling algae in a hydroponic system because the application of rose leaf extract efficiently controlled the algae and was less toxic to perilla growth. In contrast, the treatment of walnut husk extract also controlled algae but inhibited perilla growth with pale green leaves.
Exploring Owner Perceptions of the Impacts of Seasonal Weather Variations on Canine Activity and Potential Consequences for Human–Canine Relationships
Authors: Hall Emily J. , Carter Anne J. , Farnworth Mark J.
Published: November 2021

Climate change is leading to more instances of seasonal weather variation. Studies have explored the impact of adverse winter weather on dog walking, but the impact on the dog’s overall activity levels have not been previously considered. This study explored dog owner perceptions of the effects of both summer and winter weather on their dog’s activity levels. An international online survey recruited 3153 respondents between May and December 2018, to explore the impact of summer and winter weather conditions on baseline activity levels. Owners reported their dogs were more impacted by cold (48.2% less likely to exercise their dog in the cold) and ice (64.0% less likely), than rain (25.3% were less likely). In hot weather, over 80% of owners reported reduced exercise duration and vigour for their dogs. Carrying water or walking near water to facilitate activity in the summer was the most popular mitigation strategy (90.8%). Participation in dog sports appeared to reduce the impact of winter weather on canine activity and increase owner awareness of cooling strategies to facilitate summer activity. Strategies to promote safe activity participation are needed to maintain canine activity levels amidst rising global temperatures, including better understanding of cooling strategies for exercising dogs.