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Poor research reporting is a major contributing factor to low study reproducibility, financial and animal waste. The ARRIVE (Animal Research: Reporting of In Vivo Experiments) guidelines were developed to improve reporting quality and many journals support these guidelines. The influence of this support is unknown. We hypothesized that papers published in journals supporting the ARRIVE guidelines would show improved reporting compared with those in non-supporting journals. In a retrospective, observational cohort study, papers from 5 ARRIVE supporting (SUPP) and 2 non-supporting (nonSUPP) journals, published before (2009) and 5 years after (2015) the ARRIVE guidelines, were selected. Adherence to the ARRIVE checklist of 20 items was independently evaluated by two reviewers and items assessed as fully, partially or not reported. Mean percentages of items reported were compared between journal types and years with an unequal variance t-test. Individual items and sub-items were compared with a chi-square test. From an initial cohort of 956, 236 papers were included: 120 from 2009 (SUPP; n = 52, nonSUPP; n = 68), 116 from 2015 (SUPP; n = 61, nonSUPP; n = 55). The percentage of fully reported items was similar between journal types in 2009 (SUPP: 55.3 ± 11.5% [SD]; nonSUPP: 51.8 ± 9.0%; p = 0.07, 95% CI of mean difference -0.3–7.3%) and 2015 (SUPP: 60.5 ± 11.2%; nonSUPP; 60.2 ± 10.0%; p = 0.89, 95%CI -3.6–4.2%). The small increase in fully reported items between years was similar for both journal types (p = 0.09, 95% CI -0.5–4.3%). No paper fully reported 100% of items on the ARRIVE checklist and measures associated with bias were poorly reported. These results suggest that journal support for the ARRIVE guidelines has not resulted in a meaningful improvement in reporting quality, contributing to ongoing waste in animal research. [ABSTRACT FROM AUTHOR]

Biodiversity is in rapid decline globally with agriculture being one of the leading causes. Within agricultural landscapes, some features provide a benefit to biodiversity that is disproportionate to their spatial area. An interesting example is artificial ponds–or farm dams–which can support a large variety of taxa. Here, we present a global review of farm dam research related to biodiversity conservation objectives to provide an overview of the topics, key research insights, and the characteristics of current research. We used a three-stage process to screen literature and identified 104 relevant papers across 27 countries encompassing studies of 13 different taxa. Most of the studies were short-term (less than 5 years) with small sample sizes (less than 20 sites). Of the 104 papers, 88 were focussed primarily on ecological outcomes, such as species richness or abundance, and 15 on primary production outcomes, such as crop and livestock yield, despite addressing or measuring ecological metrics. Only one study measured both ecological and primary production outcomes. Studies frequently examined how the features of dams (79 studies) and attributes of the surrounding landscape (47 studies) impact particular species and communities. Terrestrial mammals (1 study) were under-represented in the literature with macrophytes (28 studies), macroinvertebrates (26 studies), and amphibians (19 studies) receiving the most attention. Our results reveal a growing trend towards recognizing farm dams as habitats for various taxa, including amphibians, beetles, dragonflies, and other macroinvertebrates within agricultural environments. Significant knowledge gaps exist in understanding how dam age, invasive species, and effective management practices impact the biodiversity conservation values of farm dams. Future research should emphasize enhancing biodiversity by collaborating with landholders to increase habitat through strategic vegetation planning, minimizing runoff and nutrient inflow, and restricting stock access. [ABSTRACT FROM AUTHOR]

Lumpy skin disease (LSD) is a critical problem for cattle populations, affecting both individual cows and the entire herd. Given cattle's critical role in meeting human needs, effective management of this disease is essential to prevent significant losses. The study proposes a deep learning approach using the MobileNetV2 model and the RMSprop optimizer to address this challenge. Tests on a dataset of healthy and lumpy cattle images show an impressive accuracy of 95%, outperforming existing benchmarks by 4–10%. These results underline the potential of the proposed methodology to revolutionize the diagnosis and management of skin diseases in cattle farming. Researchers and graduate students are the audience for our paper. [ABSTRACT FROM AUTHOR]

It is important to implement detection and assessment of plant diseases based on remotely sensed data for disease monitoring and control. Hyperspectral data of healthy leaves, leaves in incubation period and leaves in diseased period of wheat stripe rust and wheat leaf rust were collected under in-field conditions using a black-paper-based measuring method developed in this study. After data preprocessing, the models to identify the diseases were built using distinguished partial least squares (DPLS) and support vector machine (SVM), and the disease severity inversion models of stripe rust and the disease severity inversion models of leaf rust were built using quantitative partial least squares (QPLS) and support vector regression (SVR). All the models were validated by using leave-one-out cross validation and external validation. The diseases could be discriminated using both distinguished partial least squares and support vector machine with the accuracies of more than 99%. For each wheat rust, disease severity levels were accurately retrieved using both the optimal QPLS models and the optimal SVR models with the coefficients of determination (R2) of more than 0.90 and the root mean square errors (RMSE) of less than 0.15. The results demonstrated that identification and severity evaluation of stripe rust and leaf rust at the leaf level could be implemented based on the hyperspectral data acquired using the developed method. A scientific basis was provided for implementing disease monitoring by using aerial and space remote sensing technologies. [ABSTRACT FROM AUTHOR]

The Zarafshan River runs from the mountains of Tajikistan and terminates in the sands of the Kyzyl-Kum Desert in Uzbekistan; it served as a communication route and homeland for the Sogdians. The Sogdians are historically depicted as merchants existing from the end of the first millennium BC through the first millennium AD. While recent research has provided the first glimpse into cultivation, commerce, communication, and consumption in the Lower Zarafshan, the agricultural heartland of the Middle Zarafshan Basin has remained unstudied. This paper presents the results of archaeobotanical investigations conducted at five ancient urban sites/areas spanning the fifth to the twelfth centuries AD: Kainar (Penjikent citadel), Penjikent (shahristan), Sanjar-Shah, Kuk-Tosh (pre-Mongol Penjikent), and Afrasiab. Collectively, these data show that cereals, legumes, oil/fiber crops, fruits, and nuts were cultivated on the fertile Zarafshan floodplains. In this paper, we discuss evidence for the diversification of the agricultural assemblage over time, including the introduction of new staple crops and fruits into an already complex cultivation system. In addition, we contrast our data with previously published results from sites along the course of the Zarafshan to determine whether there is a dietary difference between pre-and post-Islamic conquest periods at settlements located along the river. [ABSTRACT FROM AUTHOR]

Sustainable agricultural economic development is the core task for achieving the objective of rural revitalization strategy in China, which cannot be separated from the support and guidance of fiscal policy, and agricultural industry integration is a key path for the fiscal promotion of sustainable agricultural economic development. This paper systematically examines the interaction mechanism between fiscal agricultural expenditures and sustainable agricultural economic development by using 31 provincial panel data in China from 2008 to 2020 and adopting a two-way fixed effect model, a panel quantile model, and a mediating effect model, respectively. The results show that the impact of fiscal agricultural expenditures on sustainable agricultural economic development is significantly positive, and appears a dynamic increasing trend with the agricultural development stage upgrading. Moreover, heterogeneity analysis shows that the effect of fiscal agricultural expenditures is more obvious for the samples in the central region and with a high share of primary industry. Further, a mediating effect test finds that agricultural industry integration plays a mediating mechanism between fiscal agricultural expenditures and sustainable agricultural economic development. Therefore, this paper proposes constructing a long-term investment mechanism for fiscal agricultural expenditures, formulating differentiated fiscal support policies for agriculture, and prioritizing support for agricultural industry integration, which provides theoretical support and policy inspiration for promoting sustainable agricultural economic development. [ABSTRACT FROM AUTHOR]

Agricultural non-point source pollution control (ANSPC) is a complex, long-term and dynamic environmental protection process. In order to motivate multiple subjects to participate in ANSPC, this paper constructs a tripartite evolutionary game model of local government, village collectives and farmers, which explores the strategic choices and influencing factors of different subjects through simulation analysis. The results indicate that: There are five stable strategy points in the ANSPC game system, which can be divided into four stages based on subject interactions. Village collectives should play an intermediary role in ANSPC and try to coordinate the behaviour of different subjects. The ideal and stable evolution state is "weak supervise, positive response, and active participate", but it cannot be realized at present. The strategy selection of subjects is determined by relative net income. Providing penalties requires considering the heterogeneity of subjects, but incentives are beneficial for achieving tripartite governance. This study provides new evidence for understanding the role of multi-agency participation in agricultural non-point source pollution control, and provides theoretical guidance for the government to formulate differentiated intervention mechanisms, which is an important reference for achieving sustainable development goals. [ABSTRACT FROM AUTHOR]

Agricultural ecological efficiency is an important tool with which to measure the coordination of the sustainable development of agricultural economies and ecological environments. In this paper, a super-efficiency slacks-based measures model was used to measure the agricultural ecological efficiency in Hebei Province. The characteristics of spatial and temporal evolution patterns were explored using a spatial Markov transfer matrix. The results showed that (i) based on measurements, the agricultural ecological efficiency in Hebei Province showed regional differences in four regions (eastern, northern, central and southern Hebei) and 141 counties; (ii) from the perspective of evolutionary characteristics of agricultural ecological efficiency, the overall development of in Hebei Province was good, with more concentrated spatial distribution and more obvious direction, while the type of transfer of agricultural ecological efficiency in Hebei Province showed strong stability that was significantly affected by geographical neighborhood conditions and the club convergence phenomenon; (iii) from the perspective of the long-term evolutionary trend of agricultural ecological efficiency, the areas adjacent to counties with low efficiency had limited potential for improvement, and the areas adjacent to counties with high grade had great potential. However, it was difficult to achieve large-scale improvement in agricultural ecological efficiency in Hebei Province, whether the impact of geospatial backgrounds was considered or not. [ABSTRACT FROM AUTHOR]

Because the complexity of the external environment has put great pressure on the agricultural economy, making it vulnerable, it is necessary to promote a system of resilience in the agricultural economy so that Chinese agriculture can continue to persevere in the face of serious external uncertainties. Therefore, this paper investigates the spatio-temporal pattern and evolution of the distributional dynamics of China's county-level agricultural economic resilience based on 2000–2020 data covering 2,545 counties. The results are as follows: first, from 2000 to 2020, the mean value of China's county-level agricultural economic resilience showed an obvious upward trend, which indicates that China's agricultural economy gradually increased its ability to resist risks and continued to develop in a favourable manner. Specifically, the county-level agricultural economic resilience index of the northeast region grew the most significantly, while the index of county units in the western region was relatively low. Second, the centre of gravity of the spatial distribution of China's agricultural economic resilience gradually migrated to the northwest, showing a dominant direction from northeast to southwest and a tendency to develop from southeast to northwest. Third, the spatial differences in China's agricultural economic resilience generally showed an upward trend, while county-level differences were the main source of the overall differences, followed by inter-provincial differences, inter-municipal differences and inter-regional differences. Additionally, the contribution of county-level differences to the overall differences fluctuated within the range of 54%-58%. Fourth, there is a possibility of localized convergence in China's agricultural economic resilience, which is continuous in spatial effects and has obvious positively correlated spatial effects at different times and in different county spaces. [ABSTRACT FROM AUTHOR]

Vietnam's agricultural exports to China have remained strong, with the country maintaining its position as the top destination for Agri-products. This article primarily utilizes the Revealed Comparative Advantage (RCA) Index, and Trade Complementarity (TC) index to examine the trade comparative advantage, and the complementary of twenty major agricultural products between China and Vietnam from 2012 to 2021. The study results showed that Vietnam and China frequently exchange agricultural products. Vietnam has more stronger competitiveness than China in terms of agricultural products. China's exports to Vietnam were highly complementary to Vietnam's imports in category 0 whiles Vietnam's exports to China showed strong complementarity with China's imports in category 2. This paper analyzes the complementarity and comparative advantages of agricultural trade between China and Vietnam, and proposes informed suggestions for policy-making to promote agricultural trade between the countries. The proposed suggestions aim to expand agricultural trade between the two countries, reduce the trade imbalance, and achieve mutual benefit and win-win results. [ABSTRACT FROM AUTHOR]

Using the panel data of 31 provinces in China between 2000 and 2018, this study theoretically and empirically analyses the impact of environmental regulations on the adjustment of the agriculture industrial structure from the perspectives of rationalisation and optimisation. Overall, variability in the impact of environmental regulation on the adjustment of the agricultural industrial structure is identified: a negative influence on the rationalisation of agricultural industrial structure and a positive influence on the optimisation of agricultural industrial structure. The impact of environmental regulations on the adjustment of agricultural industrial structure also reflects "large country characteristics": environmental regulations are more significant at the medium and low industrial structure levels. Environmental regulation significantly impacts the rationalisation of agricultural industrial structure in central and western regions and its optimisation in eastern and central regions. Through the panel threshold model test, this paper further finds that the effect of environmental regulations on the adjustment of agricultural industrial structure is not invariant. However, there is a non-linear relationship with significant threshold characteristics. Based on the above results, some countermeasures are suggested. [ABSTRACT FROM AUTHOR]

Introduction: As one of the agglomeration models targeting cluster-based rural development, cluster farming has been promoted in Ethiopia and it is already reported to have significant welfare implications, but participation rates are not as high as expected. This study examines the role of land as a constraint to the development of cluster-based development in Ethiopia both using extensive and intensive measures of cluster farming. The study further disaggregates farm households based on their farm size to better understand potential heterogeneities in the relationship between farm size and cluster farming. The paper also documents other household socio-economic and network characteristics that may matter in cluster farming. Methods: We use a large-scale farm household data from 3,969 households coupled with some expert insights on cluster farming in Ethiopia. Households in the study areas grow major staples such as maize, wheat, teff, malt barley, and sesame in four main regions of Ethiopia. We employ a double hurdle model to examine both the decision to participate and the extent to which households participate in cluster farming. By extent of participation, we refer to the amount of land and share of land farm households contribute to cluster farming. For robustness purposes, we also estimate the Tobit and Linear Probability Models. Results: We show a positive association between farm size and cluster farming both at the extensive and intensive margins. This relationship turns negative for large amounts of land. This shows that cluster farming increases with farm size up to a threshold beyond which it declines. We also find suggestive evidence that participation rates are lower for small-scale farms, but also declines for large-scale farms. In addition, we show that access to information and network characteristics also matter in enabling cluster farming. Conclusion: The findings of this study are relevant in the framework of plans to upscale the cluster-based development initiative in Ethiopia. Attention to landholding issues is key and may be an important area where policy action can be geared to boost cluster farming. Moreover, our results inform potential targeting plans that aim to increase the participation of small-scale farmers who are usually the intended targets of such programs. [ABSTRACT FROM AUTHOR]

Weeds are one of the greatest threats to the growth of rice, and the loss of crops is greater in the early stage of rice growth. Traditional large-area spraying cannot selectively spray weeds and can easily cause herbicide waste and environmental pollution. To realize the transformation from large-area spraying to precision spraying in rice fields, it is necessary to quickly and efficiently detect the distribution of weeds. Benefiting from the rapid development of vision technology and deep learning, this study applies a computer vision method based on deep-learning-driven rice field weed target detection. To address the need to identify small dense targets at the rice seedling stage in paddy fields, this study propose a method for weed target detection based on YOLOX, which is composed of a CSPDarknet backbone network, a feature pyramid network (FPN) enhanced feature extraction network and a YOLO Head detector. The CSPDarknet backbone network extracts feature layers with dimensions of 80 pixels ⊆ 80 pixels, 40 pixels ⊆ 40 pixels and 20 pixels ⊆ 20 pixels. The FPN fuses the features from these three scales, and YOLO Head realizes the regression of the object classification and prediction boxes. In performance comparisons of different models, including YOLOv3, YOLOv4-tiny, YOLOv5-s, SSD and several models of the YOLOX series, namely, YOLOX-s, YOLOX-m, YOLOX-nano, and YOLOX-tiny, the results show that the YOLOX-tiny model performs best. The mAP, F1, and recall values from the YOLOX-tiny model are 0.980, 0.95, and 0.983, respectively. Meanwhile, the intermediate variable memory generated during the model calculation of YOLOX-tiny is only 259.62 MB, making it suitable for deployment in intelligent agricultural devices. However, although the YOLOX-tiny model is the best on the dataset in this paper, this is not true in general. The experimental results suggest that the method proposed in this paper can improve the model performance for the small target detection of sheltered weeds and dense weeds at the rice seedling stage in paddy fields. A weed target detection model suitable for embedded computing platforms is obtained by comparing different single-stage target detection models, thereby laying a foundation for the realization of unmanned targeted herbicide spraying performed by agricultural robots. [ABSTRACT FROM AUTHOR]

The long-term and stable development of agriculture is the key to China's economic development and social stability. Agricultural total factor productivity and the digital economy have become new kinetic energy and new engines driving agricultural high-quality development. It is of great significance to verify whether there are significant spatial and threshold effects in the process of high-quality development of agriculture and to explore the intrinsic relationship between high-quality development of agriculture and agricultural total factor productivity and digital economy. This paper takes 31 provinces in China from 2011 to 2020 as the research object. The coefficient of variation method is used to estimate the comprehensive evaluation index of agricultural high-quality development and digital economy. And Dea-Malmquist index method is used to estimate agricultural total factor productivity. On this basis, the spatial Durbin model and threshold regression model are constructed to explore the spatial and threshold effects of agricultural total factor productivity, digital economy and other factors and high-quality agricultural development. The conclusion is as follows: the high-quality development of agriculture has significant spatial autocorrelation. Agricultural total factor productivity and digital economy have significant direct effect and indirect spillover effect on the high-quality development of agriculture. Agricultural total factor productivity has stage differences in each range of digital economy level, but its influence on agricultural high-quality development shows a positive state. Based on this, the paper puts forward some countermeasures to promote the high-quality development of agriculture. [ABSTRACT FROM AUTHOR]

Stockmanship is an important determinant for good animal welfare and health. The goal of the FarmMERGE project is to investigate the associations between farmer health and work environment, and the health, productivity and welfare of their livestock. We merged several livestock industry databases with a major total population-based health study in Norway (The Trøndelag Health Study 2017–2019 (HUNT4)). This paper describes the project's collection and merging of data, and the cohort of farmers and farms that were identified as a result of our registry merge. There were 56,042 participants of HUNT4 (Nord-Trøndelag County participants only, participation rate: 54.0%). We merged a list of HUNT4 participants whose self-reported main occupation was "farmer" (n = 2,407) with agricultural databases containing production and health data from sheep, swine, dairy and beef cattle from 2017–2020. The Central Coordinating Register for Legal Entities was used as an intermediary step to achieve a link between the farmer and farming enterprise data. We identified 816 farmers (89.5% male, mean age 51.3 years) who had roles in 771 farming enterprises with documented animal production. The cohort included 675 unique farmer-farm combinations in cattle production, 139 in sheep, and 125 in swine. We linked at least one HUNT4 participant to approximately 63% of the dairy farms, 53% of the beef cattle farms, 30% of the sheep farms, and 38% of the swine farms in Nord-Trøndelag County in the 2017–2019 period. Using existing databases may be an efficient way of collecting large amounts of data for research, and using total population-based human health surveys may decrease response bias. However, the quality of the resulting research data will depend on the quality of the databases used, and thorough knowledge of the databases is required. [ABSTRACT FROM AUTHOR]

To facilitate accurate prediction and empirical research on regional agricultural carbon emissions, this paper uses the LLE-PSO-XGBoost carbon emission model, which combines the Local Linear Embedding (LLE), Particle Swarm Algorithm (PSO) and Extreme Gradient Boosting Algorithm (XGBoost), to forecast regional agricultural carbon emissions in Anhui Province under different scenarios. The results show that the regional agricultural carbon emissions in Anhui Province generally show an upward and then downward trend during 2000–2021, and the regional agricultural carbon emissions in Anhui Province in 2030 are expected to fluctuate between 11,342,100 tones and 14,445,700 tones under five different set scenarios. The projections of regional agricultural carbon emissions can play an important role in supporting the development of local regional agriculture, helping to guide the input and policy guidance of local rural low-carbon agriculture and promoting the development of rural areas towards a resource-saving and environment-friendly society. [ABSTRACT FROM AUTHOR]

Nitrous oxide (N2O) and ammonia (NH3) volatilization (AV) are the major pathways of nitrogen (N) loss in soil, and recently, N2O and NH3 mitigation has become urgently needed in agricultural systems worldwide. However, the influence of straw incorporation (SI) and biochar addition (BC) on N2O and NH3 emissions are still unclear. To fill this knowledge gap, a soil column experiment was conducted with two management strategies using straw ‐ straw incorporation (S1) and straw removal (S0) ‐ and four biochar application rates (0 (C0), 15 (C1), 30 (C2), and 45 t ha−1 (C3)) to evaluate the impacts of their interactions on N2O and NH3 emissions. The results showed that NO3−−N concentration and pH was the major contributors to affect the N2O and NH3 losses. Without biochar addition, N2O emissions was decreased by 59.6% (P<0.05) but AV was increased by 97.3% (P<0.05) under SI when compared to SR. Biochar was beneficial for N2O mitigation when straw was removed, but increased N2O emission by 39.4%−83.8% when straw was incorporated. Additionally, biochar stimulated AV by 27.9%−60.4% under S0 and 78.6%−170.3% under S1. Consequently, SI was found to significantly interact with BC in terms of affecting N2O (P<0.001) and NH3 (P<0.001) emissions; co-application of SI and BC promoted N2O emissions and offset the mitigation potential by SI or BC alone. The indirect N2O emissions caused by AV, however, might offset the reduction of direct N2O caused by SI or BC, thus leading to an increase in overall N2O emission. This paper recommended that SI combined BC at the amount of 8.2 t ha−1 for maintaining a lower overall N2O emission for future agriculture practices, but the long-term impacts of straw incorporation and biochar addition on the trade-off between N2O and NH3 emissions and reactive N losses should be further examined and assessed. [ABSTRACT FROM AUTHOR]

Quantifying the colors of objects is useful in a wide range of applications, including medical diagnosis, agricultural monitoring, and food safety. Accurate colorimetric measurement of objects is a laborious process normally performed through a color matching test in the laboratory. A promising alternative is to use digital images for colorimetric measurement, due to their portability and ease of use. However, image-based measurements suffer from errors caused by the non-linear image formation process and unpredictable environmental lighting. Solutions to this problem often perform relative color correction among multiple images through discrete color reference boards, which may yield biased results due to the lack of continuous observation. In this paper, we propose a smartphone-based solution, that couples a designated color reference board with a novel color correction algorithm, to achieve accurate and absolute color measurements. Our color reference board contains multiple color stripes with continuous color sampling at the sides. A novel correction algorithm is proposed to utilize a first-order spatial varying regression model to perform the color correction, which leverages both the absolute color magnitude and scale to maximize the correction accuracy. The proposed algorithm is implemented as a "human-in-the-loop" smartphone application, where users are guided by an augmented reality scheme with a marker tracking module to take images at an angle that minimizes the impact of non-Lambertian reflectance. Our experimental results show that our colorimetric measurement is device independent and can reduce up to 90% color variance for images collected under different lighting conditions. In the application of reading pH values from test papers, we show that our system performs 200% better than human reading. The designed color reference board, the correction algorithm, and our augmented reality guiding approach form an integrated system as a novel solution to measure color with increased accuracy. This technique has the flexibility to improve color reading performance in systems beyond existing applications, evidenced by both qualitative and quantitative experiments on example applications such as pH-test reading. [ABSTRACT FROM AUTHOR]

Introduction: Latinos are the fastest growing aging population in the U.S. However, there has been limited attention to conceptualizing successful aging among Latinos, especially those residing in rural communities. Latinos are the largest racial or ethnic group residing in rural underserved communities and rural Latinos experience significant structural barriers to access the conditions they need to age well. The goal of this study is to make unique contributions to the successful aging literature by describing what successful aging means for middle-aged Latinas residing in a rural community. Methods: This qualitative paper used inductive thematic content analysis to examine definitions of successful aging among Latina women (n = 40) residing in an underserved agricultural community and entering mid-life (mean = 49 years old; age range 40–64). Results: With regards to definitions of successful aging, four themes emerged: 1) Having good health; 2) maintaining an active lifestyle; 3) the wellbeing of one's children; and 4) being independent. Discussion: Participants' definitions of successful aging aligned to some extent with existing frameworks, specifically related to health and independence. However, middle-aged Latina participants' unique definitions of successful aging also diverged from existing frameworks, especially around the wellbeing of their children and the importance of work as a way of maintaining an active lifestyle. More research is needed to understand the unique social context and circumstances of middle-aged Latinos residing in rural communities and how they influence their aging journeys. This can provide important information for the development of culturally sensitive services, interventions, and policies to help Latinos age well. [ABSTRACT FROM AUTHOR]

Plant protection drones are fast and efficient application machines that are characterised by high application efficiency and no damage to crops. They are particularly suitable for small areas of farmland and mountainous terrain in regions such as Asia and are currently the dominant insecticide application technology in China. The presence of wind is a prerequisite for the spread and dissemination of airborne diseases and it can directly influence the distance and height of ascent of pathogenic spores. This paper investigates the effect of downwash airflow generated by the flight altitude of a plant protection drone on the horizontal distribution, vertical distribution and ground distribution of powdery mildew spores in wheat. Monitoring the changing dynamics of airborne powdery mildew conidia using spore traps. The test results show that: the number of powdery mildew pathogenic spores is related to various factors such as weather, relative humidity and wind speed; the release of spores is greatly influenced by airflow disturbances but has little effect at the early stages of sporulation; the disease is caused by the accumulation process of pathogenic spores and in the control of powdery mildew in wheat, preventive spraying should be carried out within 2–3 days of the germination of pathogenic spores. The study lays the foundation for further in-depth research on the spread of powdery mildew spores and improved pest control, and provides a basis for scientific and rational spraying and control by agricultural drones. [ABSTRACT FROM AUTHOR]

In Tunisia, agriculture is the main source of livelihood for more than 75% of small and subsistence farmers with minimal use of technology. The use of information and communication technology (ICT),such as mobile applications, represents a pertinent opportunity for these smallholders to access agricultural innovation and market information and improve their farming technologies and farm management. Thus, ICT can act as a replacement to foster access to innovation for this category of farmers. Unfortunately, the underuse of mobile applications has contributed to low and slow adoption of agricultural innovation and consequently the benefits of this technology have not been attained. The purpose of this study is to identify the factors affecting the adoption of Short Message Service (SMS) through a contextual ICT model for livestock, olive crop, and beekeeping. Data were collected from 200 small-scale beekeepers, 225 olive growers, and 140 livestock breeders selected in Jendouba, Kairouan, and Zaghouan in Tunisia. The objective of this paper is to examine the factors that influence mobile applications using the partial least squares structural equation modelling technique, for livestock, olive crop, and beekeeping agricultural activities. The results showed that the final ICT-induced structural models were highly predictive of the use of SMS and its increased adoption. Factors affecting the use of SMS differed according to the farming system. The major perceived factor affecting the use of SMS was 'observability' for livestock farmers, 'compatibility' for olive growers, and 'information quality' for beekeepers. Understanding these factors by taking into account the specificity of the agricultural activity leads to a better understanding of the adoption of ICT tools by smallholder farmers in Tunisia. [ABSTRACT FROM AUTHOR]

The integration of rural industries will inevitably lead to new business forms and new models, which put forward new requirements for traditional agricultural finance. The development of digital inclusive finance will provide new momentum for the integration of rural industries. Based on the provincial panel data from 2011 to 2020, the evaluation index system is constructed from three dimensions: industrial integration method, integration subject and integration format, and the development index of rural industrial integration is calculated. This paper establishes double fixed effect model and intermediary effect model to test the effect and path of digital inclusive finance on the integration of rural industries, and further explores the regulatory role and spatial difference of financial support. The results show that: (1) The integration of rural industries shows a growing trend, the eastern region develops more rapidly, while the central and western regions develop more slowly; (2) The digital inclusive finance can promote the integration of rural industries, digitization degree is remarkable, but coverage breadth and using depth are not significant, increasing the rate of per capita electricity consumption and urbanization can promote the integration of rural industries, consumption has limited pulling effect on the integration of rural industries, the per capita investment in fixed assets has no significant effects on the integration of rural industries; (3) The financial availability and the agricultural digitization play a complete intermediary effect; (4) Financial support has a negative moderating effect on the relationship between the two; (5) The eastern and central regions have a significant promoting effect, while the western region has a negative effect. [ABSTRACT FROM AUTHOR]

Improving the interest linkage models between new farmers and small farmers is an important measure to realize the organic connection between small farmers and modern agricultural development. Based on the survey data of 572 new farmers in 16 provinces in China, this study uses the ordered probit model to empirically analyze the impact of entrepreneurial organization form on the interest linkage models between new farmers and small farmers. The results show that: (1) The choice of different entrepreneurial organization forms such as individual operation, cooperative operation, partner operation and company operation by new farmers will significantly affect the degree of interest linkage and then the linkage models. Partner operation and company operation have significantly improved the tightness of interest linkage between new farmers and small farmers. (2) The form of entrepreneurial organization significantly impacts the interest linkage between new farmers and small farmers. The higher the stability of entrepreneurial organization form, the closer the interest linkage and the more significant the impact on the interest linkage models. This effect remains significant after considering potential endogeneity issues and robustness tests. (3) In addition, further research also found significant regional differences and group differences in the impact of entrepreneurial organization form on the new farmers and small farmers' interest linkage models. The impact of the western region is more significant than that of the eastern and central regions, and government entrepreneurship support policies can significantly strengthen the interest linkage models. The research results of this paper have vital reference significance for exploring the path of agricultural modernization under the "big country with small farmers". [ABSTRACT FROM AUTHOR]

Recently, China has exerted great efforts to develop agro-industrial agglomerations and optimize the agricultural industry's regional distribution to increase farmers' income. This study posits that agro-industrial agglomeration should be "dual body," provides a theoretical framework for agro-industrial agglomeration's effects on farmer income, and uses a spatial panel model to prove its influence on farmers' income and the spatial spillover effect. The results show that agro-industrial agglomeration in a specific region significantly impacts farmers' income and also has a spillover effect on income in adjacent regions. Further research shows that, contrary to traditional agglomeration theory, agricultural industry agglomeration has little impact on farmers' agricultural production but primarily promotes the establishment and development of agricultural organizations, thus improving farmers' income. Finally, the paper discusses the positive and negative effects of agro-industrial agglomeration on the Global Sustainable Development Goals(SDGs), and proposes some useful suggestions. [ABSTRACT FROM AUTHOR]

Different diseases are observed in vegetables, fruits, cereals, and commercial crops by farmers and agricultural experts. Nonetheless, this evaluation process is time-consuming, and initial symptoms are primarily visible at microscopic levels, limiting the possibility of an accurate diagnosis. This paper proposes an innovative method for identifying and classifying infected brinjal leaves using Deep Convolutional Neural Networks (DCNN) and Radial Basis Feed Forward Neural Networks (RBFNN). We collected 1100 images of brinjal leaf disease that were caused by five different species (Pseudomonas solanacearum, Cercospora solani, Alternaria melongenea, Pythium aphanidermatum, and Tobacco Mosaic Virus) and 400 images of healthy leaves from India's agricultural form. First, the original plant leaf is preprocessed by a Gaussian filter to reduce the noise and improve the quality of the image through image enhancement. A segmentation method based on expectation and maximization (EM) is then utilized to segment the leaf's-diseased regions. Next, the discrete Shearlet transform is used to extract the main features of the images such as texture, color, and structure, which are then merged to produce vectors. Lastly, DCNN and RBFNN are used to classify brinjal leaves based on their disease types. The DCNN achieved a mean accuracy of 93.30% (with fusion) and 76.70% (without fusion) compared to the RBFNN (82%—without fusion, 87%—with fusion) in classifying leaf diseases. [ABSTRACT FROM AUTHOR]

The feeding amount of bass farming is closely related to the number of bass. It is of great significance to master the number of bass to achieve accurate feeding and improve the economic benefits of the farm. In view of the interference caused by the problems of multiple targets and target occlusion in bass data for bass detection, this paper proposes a bass target detection model based on improved YOLOV5 in circulating water system. Firstly, acquiring by HD cameras, Mosaic-8, a data augmentation method, is utilized to expand datasets and improve the generalization ability of the model. And K-means clustering algorithm is applied to generate suitable coordinates of prior boxes to improve training efficiency. Secondly, Coordinate Attention mechanism (CA) is introduced into backbone feature extraction network and neck feature fusion network to enhance attention to targets of interest. Finally, Soft-NMS algorithm replaces Non-Maximum Suppression algorithm (NMS) to re-screen prediction boxes and keep targets with higher overlap, which effectively solves the problems of missed detection and false detection. The experiments show that the proposed model can reach 98.09% in detection accuracy and detection speed reaches 13.4ms. The proposed model can help bass farmers under the circulating water system to accurately grasp the number of bass, which has important application value to realize accurate feeding and water conservation. [ABSTRACT FROM AUTHOR]

Measuring regional differences in agricultural green total factor productivity (AGTFP) provides a basis for policy guidance on agricultural green development in the Yangtze River Delta (YRD) region. By constructing a two-period Malmquist–Luenberger index under the carbon emission constraint, we measure the AGTFP of cities in the YRD region from 2001 to 2019. Furthermore, adopting the Moran index method and the hot spot analysis method, this paper analyzes the global spatial correlation and local spatial correlation of AGTFP in this region. Moreover, we investigate its spatial convergence. The results show that the AGTFP of 41 cities in the YRD region is on an increasing trend; the growth of AGTFP in the eastern cities is mainly driven by green technical efficiency, while this growth in the southern cities is mainly stimulated by green technical efficiency and green technological progress. We also find a significant spatial correlation between cities' AGTFP in the YRD region from 2001 to 2019, but with certain fluctuations, showing a U-shaped trend of "strong-weak-strong". In addition, absolute β convergence of the AGTFP exists in the YRD region, and this convergence speed is accelerated with the addition of spatial factors. This evidence provides support for implementing the regional integration development strategy and optimizing the regional agricultural spatial layout. Our findings offer implications for promoting the transfer of green agricultural technology to the southwest of the YRD region, strengthening the construction of agricultural economic belts and agricultural economic circles, and improving the efficiency of agricultural resource use. [ABSTRACT FROM AUTHOR]

Effective prevention and control of agricultural non-point source pollution is a major challenge faced by the Chinese local government in the context of rural revitalization, and clarifying the game relationship between stakeholders in agricultural non-point source pollution control actions will help achieve multiple co-governance better. Accordingly, this paper discusses the interactive decision-making relationships between local government and livestock and poultry breeding enterprise (LPBE) under the participation of Environmental non-government organizations (ENGOs) and public, by constructing an evolutionary game model, as well as analyzing evolutionary cooperative stability strategies and realizing the simulation of evolution processes in different scenarios by MATLAB. The results show that government subsidy has an incentive effect on LPBE to adopt the purifying strategy, yet reduces the enthusiasm of local government for supervision. Improving the participation degree and right space of ENGOs is conducive to the realization of multiple co-governance models. Furthermore, the impact of public participation on multiple co-governance of agricultural non-point source pollution is related to the local government's investigation rate and the public reporting fairness; strengthening the local government's supervision capacity and improving the public reporting fairness can achieve better collaborative governance effects. [ABSTRACT FROM AUTHOR]

China's agricultural economy is developing rapidly, but the unbalanced regional development is still a key issue that needs to be discussed today. By studying the total factor productivity of green agriculture and its factors, this paper analyzes the regional differences in time and space changes between the eastern, central and western parts of China. In this paper, the total factor productivity of green agriculture is calculated and decomposed by Metafrontier Malmquist-Luenberger index based on directional distance function. The results are as follows: First, the total factor productivity level of green agriculture in China is increasing year by year, but the overall level is still at a low level and has greater volatility; Second, although the total factor productivity of green agriculture shows an upward trend, the three regions show a downward trend in turn, which has great differences; Third, there are obvious differences in technological efficiency, optimal production potential and technological gap between the eastern, central and western regions, and there are great differences in productivity among regions and provinces. Based on the results, this paper puts forward policy recommendations, according to the regional heterogeneity, from a number of angles to rely on the joint efforts of many parties to improve the level of total factor productivity of green agriculture. [ABSTRACT FROM AUTHOR]

The use of elasticities of substitution between inputs is a standard method for addressing the effect of a change in the mix of inputs used for production from a technical or cost standpoint. Most estimation methods use parametric production or cost functions or frontiers to estimate these elasticities. A potentially useful nonparametric alternative is data envelopment analysis (DEA). The purpose of this paper is to derive elasticities of input substitution for both technical and cost frontiers using DEA, extending the use of this approach in the field of economics and associated fields. The paper provides derivations for both Hicksian (production and cost frontier) and Morishima (cost frontier) elasticities of input substitution, as well as a parsimonious method for estimating them using DEA. The derivations are presented using an agricultural example form Kansas, USA. [ABSTRACT FROM AUTHOR]

Tropical tuna support some of the largest and most valuable artisanal and industrial fisheries worldwide, conducted to a large degree with Fish Aggregating Devices (FADs). Yellowfin, bigeye and skipjack are the main tuna species found in mixed aggregations around FADs and they are simultaneously encircled by the purse seining operation. One of the key challenges that purse seine fleets fishing with drifting FADs face in all oceans is to be able to target species in healthy condition such as skipjack, while reducing impacts on bigeye and yellowfin in areas where there is a need to reduce fishing pressure on these species. The present paper explores a technical solution for selective fishing at FADs by means of acoustic equipment used by purse seiners. Acoustic frequency response of skipjack and bigeye tuna were determined at 38, 120 and 200 kHz. Skipjack showed stronger response at higher frequencies. On the contrary, bigeye showed stronger responses at lower frequencies. The robust pattern shown in frequency responses of the two species demonstrates the potential to predict abundance and species proportions based on purely acoustic measures. The paper also addresses the conditions that need to be met to successfully apply this technology for selective fishing as well as other uses of direct acoustic observations to support tuna conservation. [ABSTRACT FROM AUTHOR]

A diversity of arthropods (myrmecophiles) thrives within ant nests, many of them unmolested though some, such as the specialized Eucharitidae parasitoids, may cause direct damage to their hosts. Ants are known to discriminate between nestmates and non-nestmates, but whether they recognize the strength of a threat and their capacity to adjust their behavior accordingly have not been fully explored. We aimed to determine whether Ectatomma tuberculatum ants exhibited specific behavioral responses to potential or actual intruders posing different threats to the host colony and to contribute to an understanding of complex ant-eucharitid interactions. Behavioral responses differed significantly according to intruder type. Ants evicted intruders that represented a threat to the colony’s health (dead ants) or were not suitable as prey items (filter paper, eucharitid parasitoid wasps, non myrmecophilous adult weevils), but killed potential prey (weevil larvae, termites). The timing of detection was in accordance with the nature and size of the intruder: corpses (a potential source of contamination) were detected faster than any other intruder and transported to the refuse piles within 15 min. The structure and complexity of behavioral sequences differed among those intruders that were discarded. Workers not only recognized and discriminated between several distinct intruders but also adjusted their behavior to the type of intruder encountered. Our results confirm the previously documented recognition capabilities of E. tuberculatum workers and reveal a very fine-tuned intruder discrimination response. Colony-level prophylactic and hygienic behavioral responses through effective removal of inedible intruders appears to be the most general and flexible form of defense in ants against a diverse array of intruders. However, this generalized response to both potentially lethal and harmless intruders might have driven the evolution of ant-eucharitid interactions, opening a window for parasitoid attack and allowing adult parasitoid wasps to quickly leave the natal nest unharmed. [ABSTRACT FROM AUTHOR]

Food safety is a global public health issue, which often arises from asymmetric information between consumers and suppliers. With the development of information technology in human life, building a food traceability information sharing platform is viewed as one of the best ways to overcome the trust crisis and resolve the problem of information asymmetry in China. However, among the myriad information available from the food supply chain, there is a lack of knowledge on consumer preference. Based on the best-worst scaling approach, this paper investigated consumer preferences for vegetable, pork, and dairy product traceability information. Specifically, this paper measured the relative importance that consumers place on the traceable information. The results indicate that consumers have varying priorities for information in different cases. “Pesticide/veterinary use,” “picking/slaughtering date,” and “fertilizer/feed use” are the most preferred traceable information for Chinese consumers in the case of vegetables, while “picking/slaughtering date” and “history of illness and taking protective measures” are the most preferred information in the case of pork. In the case of dairy products, consumers prefer “processing information,” “environmental information of the origin,” and “traceable tag certification information” most. The results of this study call for the direct involvement of the Chinese government in the food safety information sharing system as following. First, given consumers’ diverse preferences, different types of traceable information should be recorded into the information sharing platform depending on food types. Second, the government could promote the step-by-step construction of such a platform based on the priority of consumers’ preferences. Third, new technology should be applied to guarantee the reliability of traceable information. Finally, local preferences in terms of the way consumers receive and understand information should be taken into consideration. [ABSTRACT FROM AUTHOR]

Animal mobility is a common strategy to overcome scarcity of food and the related over-grazing of pastures. It is also essential to reduce the inbreeding rate of animal populations, which is known to have a negative impact on fertility and productivity. The present paper shows the geographic range of sheep provisioning in different phases of occupation at the Iron Age site of Turó de la Font de la Canya (7th to 3rd centuries BC). Strontium isotope ratios from 34 archaeological sheep and goat enamel, two archaeological bones and 14 modern tree leaves are presented. The isotopic results suggest that sheep and goats consumed at the site were reared locally (within a few kilometres radius) during the whole period of occupation. The paper discusses the isotopic results in light of the socio-political structure of this period, as complex, strongly territorial societies developed during the Iron Age in the north-east Iberian Peninsula. [ABSTRACT FROM AUTHOR]

Traffic congestion in freeway network is a prevalent transportation problem and leads to a strong degradation of freeway network facilities. This paper proposes a new coordinated optimization approach for freeway network, aiming to relieve the traffic congestion in freeway network equipped with the coordinated traffic controllers. The challenge is how to solve the problem between the traffic control goals of each path and those of the network. In this paper, the bi-level programming theory is used to address this problem. More exactly, in the path level, the optimal control model is designed to relieve congestion in each path of the test network. Furthermore, in the network level, the optimal model considers the traffic equilibrium and cost optimization. The efficiency of the proposed approach is tested on a well-known traffic network calibrated by the field test data of freeway network. The results show that the proposed approach has positive effects in balancing traffic load and improving the service level of freeway networks. [ABSTRACT FROM AUTHOR]

High-fat diet is associated with hypercholesterolemia and seminal alterations in White New Zealand rabbits. We have previously reported disorders in the development of the manchette-acrosome complex during spermiogenesis and decreased testicular efficiency in hypercholesterolemic rabbits. On the other hand, olive oil incorporated into the diet improves cholesterolemia and semen parameters affected in hypercholesterolemic rabbits. In this paper, we report the recovery—with the addition of olive oil to diet—from the sub-cellular mechanisms involved in the shaping of the sperm cell and testicular efficiency altered in hypercholesterolemic rabbits. Using morphological (structural, ultra-structural and immuno-fluorescence techniques) and cell biology techniques, a reorganization of the manchette and related structures was observed when olive oil was added to the high-fat diet. Specifically, actin filaments, microtubules and lipid rafts—abnormally distributed in hypercholesterolemic rabbits—were recovered with dietary olive oil supplementation. The causes of the decline in sperm count were studied in the previous report and here in more detail. These were attributed to the decrease in the efficiency index and also to the increase in the apoptotic percentage in testis from animals under the high-fat diet. Surprisingly, the addition of olive oil to the diet avoided the sub-cellular, efficiency and apoptosis changes observed in hypercholesterolemic rabbits. This paper reports the positive effects of the olive oil addition to the diet in the recovery of testicular efficiency and normal sperm shaping, mechanisms altered by hypercholesterolemia. [ABSTRACT FROM AUTHOR]

It is widely recognized that increasing agricultural production to the levels needed to feed an expanding world population requires sharply increased public investment in research and development and widespread adoption of new technologies, but funding for national and international agricultural research has rather declined in recent years. In this situation, priority setting has become increasingly important for allocating scarce research resources among competing needs to achieve greater impacts. Using partial equilibrium economic surplus models and poverty impact simulations, this paper assesses cassava research priorities in Africa, Latin America and Caribbean, and Asia based on the potential economic and poverty reduction impacts of alternative research and technology options. The results showed that efficient planting material production and distribution systems and sustainable crop and soil fertility management practices have the greatest expected economic and poverty reduction impacts in the three regions. Lack of clean planting materials is a major constraint to adoption and it is envisaged that efficient production and distribution systems for planting material can accelerate technology adoption by farmers. Similarly, sustainable crop and soil fertility management practices play a key role in closing the observed yield gaps, especially in Africa. The paper discusses the results of the priority assessment for key cassava research options and concludes with the implications for cassava research priorities. [ABSTRACT FROM AUTHOR]

Recreational fishing is often perceived as harmless when it comes to fisheries management, and its impact often estimated to surpass the economic outcomes of e.g. large-scale fisheries. Recreational fisheries are often an indication of political stability and sound ecosystem management. However, despite a high economic impact, the economic costs on traditional and small-scale commercial fishers is yet to be known. This paper answers the question of how unregulated recreational fisheries could rather generate a loss to an economy, and cause unfair competition with existing commercial sectors using the example of Algeria. This paper assesses catches and economic value of recreational fisheries in Algeria, and finds that over 6,000 tonnes reach commercial markets annually, competing directly with the small-scale artisanal sector, while selling recreationally caught fish is still illegal. The paper further finds that the public is thereby deprived—through lost tax, licence income and landed value of $45 million US annually. [ABSTRACT FROM AUTHOR]

This paper investigates the consequences of ignoring the clustered data structure on allometric models. Clustered data, in the form of multiple trees sampled from multiple forest stands is commonly used to develop biomass allometric models. Of 102 reviewed papers published between 2012 and 2016 that reported biomass allometric models, 84 (82%) have used a clustered sampling design. However, in as many as 80% of these, the clustered data structure was ignored, potentially violating the independence assumption in ordinary least squares methods. The consequences of ignoring clustered data structure were empirically validated using two clustered biomass datasets (of 110 and 220 trees, with the cluster size of 5 and 10 trees respectively). We showed that when Intraclass Correlation Coefficient (ICC) was higher than zero, ignoring the clustered data structure returned underestimated standard errors, affecting further the confidence interval and t-test results. The underestimation level depended on ICC (which shows the variance proportion that was caused by the forest stand) and on cluster size (the number of trees sampled from one forest stand). We also showed that using first-order autocorrelation tests, such as the traditional Durbin-Watson statistic, to detect the autocorrelation due to clustered structure could be misleading as the test may show lack of autocorrelation even though ICC is different from zero. In conclusion, when ICC is higher than zero, ignoring the clustered data structure yields over-confident biomass predictions (due to underestimated confidence interval) and/or incorrect research conclusions (due to overestimated evidence against null hypothesis in t-test). Therefore, using a modelling approach that accounts for the hierarchical structure of the data is highly recommended when any form of clustering can be identified, even if the autocorrelation is not significant. [ABSTRACT FROM AUTHOR]

Multi-stakeholder platforms (MSPs) have been playing an increasing role in interventions aiming to generate and scale innovations in agricultural systems. However, the contribution of MSPs in achieving innovations and scaling has been varied, and many factors have been reported to be important for their performance. This paper aims to provide evidence on the contribution of MSPs to innovation and scaling by focusing on three developing country cases in Burundi, Democratic Republic of Congo, and Rwanda. Through social network analysis and logistic models, the paper studies the changes in the characteristics of multi-stakeholder innovation networks targeted by MSPs and identifies factors that play significant roles in triggering these changes. The results demonstrate that MSPs do not necessarily expand and decentralize innovation networks but can lead to contraction and centralization in the initial years of implementation. They show that some of the intended next users of interventions with MSPs–local-level actors–left the innovation networks, whereas the lead organization controlling resource allocation in the MSPs substantially increased its centrality. They also indicate that not all the factors of change in innovation networks are country specific. Initial conditions of innovation networks and funding provided by the MSPs are common factors explaining changes in innovation networks across countries and across different network functions. The study argues that investigating multi-stakeholder innovation network characteristics targeted by the MSP using a network approach in early implementation can contribute to better performance in generating and scaling innovations, and that funding can be an effective implementation tool in developing country contexts. [ABSTRACT FROM AUTHOR]

The challenge of detecting research topics in a specific research field has attracted attention from researchers in the bibliometrics community. In this study, to solve two problems of clustering papers, i.e., the influence of different distributions of citation links and involved textual features on similarity computation, the authors propose a hybrid self-optimized clustering model to detect research topics by extending the hybrid clustering model to identify “core documents”. First, the Amsler network, consisting of bibliographic coupling and co-citation links, is created to calculate the citation-based similarity based on the cosine angle of papers. Second, the cosine similarity is also used to compute the text-based similarity, which consists of the textual statistical and topological features. Then, the cosine angle of the linear combination of citation- and text-based similarity is considered as the hybrid similarity. Finally, the Louvain method is applied to cluster papers, and the terms based on term frequency are used to label clusters. To test the performance of the proposed model, a dataset related to the data envelopment analysis field is used for comparison and analysis of clustering results. Based on the benchmark built, different clustering methods with different citation links or textual features are compared according to evaluation measures. The results show that the proposed model can obtain reasonable and effective clustering results, and the research topics of data envelopment analysis field are also analyzed based on the proposed model. As different features are considered in the proposed model compared with previous hybrid clustering models, the proposed clustering model can provide inspiration for further studies on topic identification by other researchers. [ABSTRACT FROM AUTHOR]

Vagus nerve stimulation (VNS) is an established adjunctive therapy for pharmacologically refractory epilepsy and depression and is currently in active clinical research for other applications. In current clinical studies, VNS is delivered in an open-loop approach, where VNS parameters are defined during a manual titration phase. However, the physiological response to a given VNS configuration shows significant inter and intra-patient variability and may significantly evolve through time. VNS closed-loop approaches, allowing for the optimization of the therapy in an adaptive manner, may be necessary to improve efficacy while reducing side effects. This paper proposes a generic, closed-loop control VNS system that is able to optimize a number of VNS parameters in an adaptive fashion, in order to keep a control variable within a specified range. Although the proposed control method is completely generic, an example application using the cardiac beat to beat interval (RR) as control variable will be developed in this paper. The proposed controller is based on a state transition model (STM) that can be configured using a partially or a fully-connected architecture, different model orders and different state-transition algorithms. The controller is applied to the adaptive regulation of heart rate and evaluated on 6 sheep, for 13 different targets, using partially-connected STM with 10 states. Also, partially and fully-connected STM defined by 30 states were applied to 7 other sheep for the same 10 targets. Results illustrate the interest of the proposed fully-connected STM and the feasibility of integrating this control system into an implantable neuromodulator. [ABSTRACT FROM AUTHOR]

Many countries have some kind of energy-system transformation either planned or ongoing for various reasons, such as to curb carbon emissions or to compensate for the phasing out of nuclear energy. One important component of these transformations is the overall reduction in energy demand. It is generally acknowledged that the domestic sector represents a large share of total energy consumption in many countries. Increased energy efficiency is one factor that reduces energy demand, but behavioral approaches (known as “sufficiency”) and their respective interventions also play important roles. In this paper, we address citizens’ heterogeneity regarding both their current behaviors and their willingness to realize their sufficiency potentials—that is, to reduce their energy consumption through behavioral change. We collaborated with three Swiss cities for this study. A survey conducted in the three cities yielded thematic sets of energy-consumption behavior that various groups of participants rated differently. Using this data, we identified four groups of participants with different patterns of both current behaviors and sufficiency potentials. The paper discusses intervention types and addresses citizens’ heterogeneity and behaviors from a city-based perspective. [ABSTRACT FROM AUTHOR]

Organizations are increasingly using sustainability reports to inform their stakeholders and the public about their sustainability practices. We apply topic modelling to 9,514 sustainability reports published between 1999 and 2015 in order to identify common topics and, thus, the most common practices described in these reports. In particular, we identify forty-two topics that reflect sustainability and focus on the coverage and trends of economic, environmental, and social sustainability topics. Among the first to analyse such a large amount of data on organizations’ sustainability reporting, the paper serves as an example of how to apply natural language processing as a strategy of inquiry in sustainability research. The paper also derives from the data analysis ten propositions for future research and practice that are of immediate value for organizations and researchers. [ABSTRACT FROM AUTHOR]

Background: Biosensor-based detection provides a rapid and low-cost alternative to conventional analytical methods for revealing the presence of the contaminants in water as well as solid matrices. Although important to be detected, small analytes (few hundreds of Daltons) are an issue in biosensing since the signal they induce in the transducer, and specifically in a Quartz-Crystal Microbalance, is undetectable. A pesticide like parathion (M = 292 Da) is a typical example of contaminant for which a signal amplification procedure is desirable. Methods/Findings: The ballasting of the analyte by gold nanoparticles has been already applied to heavy target as proteins or bacteria to improve the limit of detection. In this paper, we extend the application of such a method to small analytes by showing that once the working surface of a Quartz-Crystal Microbalance (QCM) has been properly functionalized, a limit of detection lower than 1 ppb is reached for parathion. The effective surface functionalization is achieved by immobilizing antibodies upright oriented on the QCM gold surface by a simple photochemical technique (Photonic Immobilization Technique, PIT) based on the UV irradiation of the antibodies, whereas a simple protocol provided by the manufacturer is applied to functionalize the gold nanoparticles. Thus, in a non-competitive approach, the small analyte is made detectable by weighing it down through a “sandwich protocol” with a second antibody tethered to heavy gold nanoparticles. The immunosensor has been proved to be effective against the parathion while showing no cross reaction when a mixture of compounds very similar to parathion is analyzed. Conclusion/Significance: The immunosensor described in this paper can be easily applied to any small molecule for which polyclonal antibodies are available since both the functionalization procedure of the QCM probe surface and gold nanoparticle can be applied to any IgG, thereby making our device of general application in terms of target analyte. [ABSTRACT FROM AUTHOR]

In natural capital accounting, ecosystems are assets that provide ecosystem services to people. Assets can be measured using both physical and monetary units. In the international System of Environmental-Economic Accounting, ecosystem assets are generally valued on the basis of the net present value of the expected flow of ecosystem services. In this paper we argue that several additional conceptualisations of ecosystem assets are needed to understand ecosystems as assets, in support of ecosystem assessments, ecosystem accounting and ecosystem management. In particular, we define ecosystems’ capacity and capability to supply ecosystem services, as well as the potential supply of ecosystem services. Capacity relates to sustainable use levels of multiple ecosystem services, capability involves prioritising the use of one ecosystem service over a basket of services, and potential supply considers the ability of ecosystems to generate services regardless of demand for these services. We ground our definitions in the ecosystem services and accounting literature, and illustrate and compare the concepts of flow, capacity, capability, and potential supply with a range of conceptual and real-world examples drawn from case studies in Europe and North America. Our paper contributes to the development of measurement frameworks for natural capital to support environmental accounting and other assessment frameworks. [ABSTRACT FROM AUTHOR]

This paper reports the results of a zooarchaeological analysis conducted on the occupation layer of a compound structure (Residential Unit 1) of the Pucara de Tilcara archaeological site (Jujuy Province, northwestern Argentina). Its occupation span extends between the 13th and 15th centuries AD, but evidence diagnostic of the Inka Period (AD 1430–1536) is predominant. Residential Unit 1 was a house-workshop that hosted specialized crafts like metallurgy and lapidary during the Inka Period. It was proposed in previous works that artisans living at Pucara de Tilcara were provisioned with agropastoral products by the Inka administration. This paper aims to test that hypothesis against the zooarchaeological evidence of Residential Unit 1. Three variables were used as proxies for state-sponsored distribution: taxonomic diversity (family and species ranks), and skeletal and age profiles of the predominant zoological family (Camelidae) in the assemblage. The results show a high degree of continuity with the regional record, characterized by a herding-hunting strategy focused on domestic and wild species of Camelidae and a mixed mortality pattern. The skeletal profile shows a strong and negative correlation with the desiccation potential of elements, which could be indicative of local production of chalona. Overall, faunal evidence does not show any sign of centralized distribution. [ABSTRACT FROM AUTHOR]

This paper brings advances in weather data collection and modeling, and developments in socioeconomic climate microsimulations to bear on the analysis of the implications of climate change (CC) in the design of public policies to combat food insecurity. It uses new downscaled predictions of future climate in 2050, derived from three Earth System Models calibrated with a new historical weather station dataset for Peru. This climate data is used in a three-stage socioeconomic microsimulation model that includes climate risk, and deals with the endogeneity of incomes and simultaneity of expected food consumption and its variability. We estimate the impact of CC on agricultural yields, and find results consistent and fully bounded within what the global simulations literature has found, with yields falling up to 13% in some regions. However, we show that these drops (and increases) in yields translate to much smaller changes in food consumption, and also surprisingly, to very minor impacts on vulnerability to food insecurity. The document explores what explains this surprising result, showing that in addition to characteristics that are specific to Peru, there are household and market mediating mechanisms that are available in all countries, which explain how changes in yields, and corresponding farm incomes have a reduced impact in vulnerability to food insecurity. Finally, in light of these findings, we explore which policies might have greater impact in reducing food insecurity in contexts of hunger prevalence. [ABSTRACT FROM AUTHOR]

Recently, high-resolution magnetometry surveys have led to the discovery of a special category of buildings–so-called ‘mega-structures’–situated in highly visible positions in the public space of Tripolye giant-settlements of the late 5th and first half of the 4th millennium BCE. In this paper we explore what these buildings actually are and how they can contribute to the understanding of the development of social space in Tripolye giant-settlements. For this investigation, we linked newly obtained excavation data from the giant-settlement Maidanetske, Ukraine, with a much larger sample of such buildings from magnetic plans obtained in the region between the Carpathian foothills and the Dnieper River. Accordingly, Tripolye mega-structures represent a particular kind of integrative building documented in many non-ranked ethnographic contexts. Based on our results we are interpreting that these buildings were used for various ritual and non-ritual activities, joint decision-making, and the storage and consumption of surplus. In Tripolye giant-settlements at least three different categories of mega-structures could be identified which most likely represent different levels of socio-political integration and decision-making. The emergence of this hierarchical system of high-level integrative buildings for the whole community and different low-level integrative architectures for certain segments of local communities was related to the rise of Tripolye mega-sites. The presence of different integrative levels most likely reflects the fusion of different previously independent communities in the giant-settlements. Later in the mega-site development, we observe how low-level integrative buildings increasingly lose their importance indicated by shrinking size and, finally, their disappearance. This observation might indicate that the power which was previously distributed across the community was transferred to a central institution. It is argued that the non-acceptance of this concentration of power and the decline of lower decision-making levels might be a crucial factor for the disintegration of Tripolye giant-settlements around 3600 BCE. [ABSTRACT FROM AUTHOR]

One of the trends in today’s tourism sector is the development of environmentally-friendly tourism activities which rely on natural resources of cultural heritage and on biodiversity. This is definitely the case for agritourism, a form of rural tourism. The purpose of this paper is to identify the development aspects of Polish agritourism with particular emphasis on natural and cultural attractiveness. To demonstrate the relationship between agritourism activities of Polish farms and the cultural and natural attractiveness, the Hellwig’s synthetic development indicator was used. As shown by research, the cultural and natural attractiveness of a destination is an important exogenous development factor. Another finding was that the intensified efforts undertaken by the farmers to access EU funds were not focused on areas with valuable natural or cultural resources and an untapped agritourism potential; instead, they were oriented at regions dominated by semi-subsistence or family farms. For a large part of farmers, the new form of support is about to become a source of additional incomes. [ABSTRACT FROM AUTHOR]