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  • Rural Digital Europe
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  • Authors: Hilary, Gilles; Serret, Vanessa;

    International audience; The article aims to summarize the current knowledge on governance and digital transformation, focusing on strategic and operational dimensions. It identifies research gaps in linking governance, innovation, and the digital transition, attributing limitations to the challenge of accessing confidential organizational data. It suggests using detailed clinical cases for fruitful research, particularly in exploring the operational aspects of governance. Emphasizing the multidisciplinary nature of this research, it acknowledges complexities in conducting studies across financial, operational, and legal domains. However, it sees this as an opportunity to contribute significantly to understanding governance in the context of digital transformation.; L'article vise à résumer les connaissances actuelles sur la gouvernance et la transformation numérique, en se concentrant sur les dimensions stratégiques et opérationnelles. Il identifie des lacunes en ce qui concerne le lien entre gouvernance, innovation et transition numérique, attribuant ces limitations au défi d'accéder aux données organisationnelles confidentielles. Il suggère d'utiliser des cas cliniques détaillés pour une recherche fructueuse, en particulier pour explorer les aspects opérationnels de la gouvernance. Soulignant la nature multidisciplinaire de cette recherche, il reconnaît les complexités liées à la réalisation d'études dans les domaines financier, opérationnel et juridique. Cependant, il considère cela comme une opportunité de contribuer de manière significative à la compréhension de la gouvernance dans le contexte de la transformation numérique.

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    Authors: Khushi Singh; Prachi Parashar;

    The case study aims to highlight the existing problems and challenges in the primary education system prevalent in Rural India, from the lens of Chikana Village, in the Tonk district of Rajasthan, India. The case study brings to light prevalent practices, concerns and beliefs that govern the process of imparting primary-level education to the children of Chikana. The points made in the course of the study, though derived from this particular village, can be used as a general idea for most schools in rural India. The researchers have taken into consideration the prevalent schemes started by state and central governments for the enhancement of the quality of education in Rural India and have built points on the impact and significance these schemes have made so far. The study is qualitative in nature and uses both secondary and primary data sets. Secondary data is used in the form of old schemes and impact reports on Indian primary education, while primary data is incorporated in the form of observation and interview schedules. The time frame of all secondary data is limited to the last 5 years (February 2018- February 2023). The sample size for the interview schedule is 40 participants, these included students from ranging age groups, teachers and school authorities of the ‘Rajkiya Ucch Prathmik Vidyalay, Chikana'. The study aims to raise considerable awareness among the readers of this study about the existing trends in education in rural India and to highlight the gap in urban and rural education systems. The study goes on to find major loopholes in the ongoing educational practices prevalent in rural India. It brings to light the different dimensions of the primary education system and the opinions of different stakeholders on the progression of the sector. It comments on the implementation of policies designed to cater to the needs of children. The study also offers the author's conclusion derived from the curated data sets which clearly presents the condition of the sector as more bad than good, however, stressing enough of the good and stating that progress is expected in the years to come. The study is a comprehensive work, which gives a 180-degree view of the education provided to children in rural parts of the country.

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    Asian Research Journal of Arts & Social Sciences
    Article . 2024 . Peer-reviewed
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    SSRN Electronic Journal
    Article . 2024 . Peer-reviewed
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      Asian Research Journal of Arts & Social Sciences
      Article . 2024 . Peer-reviewed
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      SSRN Electronic Journal
      Article . 2024 . Peer-reviewed
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    Authors: Albert Sanchez-Graells;

    Public sector digitalisation is transforming public governance at an accelerating rate. Digitalisation is outpacing the evolution of the legal framework. Despite several strands of international efforts to adjust good administration guarantees to new modes of digital public governance, progress has so far been slow and tepid. The increasing automation of decision-making processes puts significant pressure on traditional good administration guarantees, jeopardises individual due process rights, and risks eroding public trust. Automated decision-making has, so far, attracted the bulk of scholarly attention, especially in the European context. However, most analyses seek to reconcile existing duties towards individuals under the right to good administration with the challenges arising from digitalisation. Taking a critical and technology-centred doctrinal approach to developments under the law of the European Union and the Council of Europe, this paper goes beyond current debates to challenge the sufficiency of existing good administration duties. By stressing the mass effects that can derive from automated decision-making by the public sector, the paper advances the need to adapt good administration guarantees to a collective dimension through an extension and a broadening of the public sector’s good administration duties: that is, through an extended ex ante control of organisational risk-taking, and a broader ex post duty of automated redress. These legal modifications should be urgently implemented.

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    Laws
    Article . 2024 . Peer-reviewed
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    Laws
    Article . 2024
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    SSRN Electronic Journal
    Article . 2024 . Peer-reviewed
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      Laws
      Article . 2024 . Peer-reviewed
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      Laws
      Article . 2024
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      SSRN Electronic Journal
      Article . 2024 . Peer-reviewed
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    Authors: Xiangwu Deng; Long Qi; Zhuwen Liu; Song Liang; +2 Authors

    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.

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    PLoS ONE
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    Article . 2022
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    PLoS ONE
    Article . 2023 . Peer-reviewed
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    Authors: Ebenezer Donkor; Emmanuel Dela Amegbe; Tomas Ratinger; Jiri Hejkrlik;

    Producer groups are influential in Ghana’s cocoa value chain. They facilitate training, extension, education and inputs to their members. Still, there is no study on the impact of these producer groups on the technical efficiency and productivity of smallholder cocoa farmers. Using data from 217 and 199 members and non-members of cocoa producer groups, this study aimed to analyse producer groups’ impact on smallholder farmers’ technical efficiency and yield. The truncated normal distribution stochastic frontier model was adopted to estimate the farmers’ technical efficiency. Since the model showed an issue of inefficiency among the farmers, we added socio-demographic and institutional variables to account for determinants of inefficiency. Finally, we adopted an endogenous treatment regression model to analyse producer groups’ impact on the farmers’ technical efficiency by accounting for observed and unobserved biases. The study results show that farm size, labour, and capital significantly positively impact the partial elasticity of production. Age, education, use of hybrid cocoa, involvement in off-farm jobs, extension access, and producer group membership significantly affect inefficiency. The results further show that producer group membership significantly impacts technical efficiency and yield from the endogenous treatment regression model. To deal with the issues of non-participating in the producer groups, the study recommends that producer groups should be made accessible to farmers. Policymakers can promote the formation and strengthening of producer groups, leading to improved productivity and technical efficiency among cocoa farmers. This approach empowers farmers, enhances their access to resources and knowledge, and enables them to collectively address common challenges, ultimately contributing to sustainable cocoa production and better livelihoods for cocoa farming communities.

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    Authors: Jung-Bin Su;

    This study employs a bivariate GARCH model to examine the influence of the COVID-19 pandemic on the interactions of the commodities in the agricultural market via a connectedness network approach. Empirical results show that this pandemic alters the commodities’ roles—the activators, net transmitters, and net receivers—in the volatility and return connectedness but not for the activators in the correlation connectedness. Moreover, this pandemic enhances the interactive degree of the unidirectional negative return spillovers and the bidirectional distinct-sign volatility spillovers but doesn’t for the interactive degree of correlation. Thus, the COVID-19 pandemic, a short-term drastic event, can influence short-term interactions like volatility and return spillovers but can’t affect one long-term interaction like the correlation. Nevertheless, this pandemic raises the intensity of the correlation as well as volatility and return spillovers. The findings provide policymakers to make short- and long-term investment strategies in the agriculture market.

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    Authors: Gopika Ajaykumar; Gregory D. Hager; Chien-Ming Huang;

    Non-expert users can now program robots using various end-user robot programming methods, which have widened the use of robots and lowered barriers preventing robot use by laypeople. Kinesthetic teaching is a common form of end-user robot programming, allowing users to forgo writing code by physically guiding the robot to demonstrate behaviors. Although it can be more accessible than writing code, kinesthetic teaching is difficult in practice because of users’ unfamiliarity with kinematics or limitations of robots and programming interfaces. Developing good kinesthetic demonstrations requires physical and cognitive skills, such as the ability to plan effective grasps for different task objects and constraints, to overcome programming difficulties. How to help users learn these skills remains a largely unexplored question, with users conventionally learning through self-guided practice. Our study compares how self-guided practice compares with curriculum-based training in building users’ programming proficiency. While we found no significant differences between study participants who learned through practice compared to participants who learned through our curriculum, our study reveals insights into factors contributing to end-user robot programmers’ confidence and success during programming and how learning interventions may contribute to such factors. Our work paves the way for further research on how to best structure training interventions for end-user robot programmers.

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    Authors: Yu Li; Zhiheng Zhang;

    Tobacco farmers often adopt additional multiple agricultural technologies (AMATs) in addition to implementing the standardized technical system in China. Based on the cross-sectional micro data of 346 households of Chongqing, China, this paper assesses the determinants and impacts of the adoption of AMATs on income by using a multinomial endogenous treatment effects model to correct for selection bias and endogeneity caused by observed and unobserved heterogeneity. The results show that (1) the adoption of combinations of AMATs is determined by the household head’s education level, experience in tobacco growing, the shortest distance to nearby town, the amount of technical training, the ratio of land available for mechanical cultivation to tobacco land, the distance to extension station, and the ratio of leased land. (2) The adoption of combinations of AMATs has heterogeneous effects on farmers’ income through yield and quality improvement. (3) The comprehensive combination of AMATs is not necessarily the best option for farmers. Due to the interaction between technologies such as complementary, substitute or supplementary effects, the moderate implementation of fertilizers and soil improvement is the most effective combination. The results of this research provide a scientific basis for improving the adoption efficiency of AMATs in China.

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    Authors: Mahdi Moudi; Qiuyan Gai; He Yuan; Li Guiqing; +3 Authors

    In general, the sustainability of the water supply system is indicative of an adaptive operational approach, wherein the decision-maker adjusts the system’s performance based on the availability of water resources in a given time frame. In light of this, a novel framework is proposed in this study to evaluate sustainability, including three key indicators: resilience, reliability, and vulnerability. To address stressors that may lead to system failure, a multisectoral water allocation optimization is undertaken. In order to account for the future implications of climate change on the hydrological cycle, a simulation step, is incorporated, utilizing the Soil and Water Assessment Tool (SWAT) under various emission scenarios (RCP4.5 and RCP8.5), prior to integrating the streamflow data into our proposed optimal framework. To calibrate and validate historical data (2014–2019) and simulate future streamflow patterns (2025–2085), the Sistan Basin, located in an arid region of Iran, is analyzed as a case study. In light of the anticipated adverse impacts on the water supply system, certain adaptation measures, such as demand shrinkage scenarios, are considered to further appraise the proposed framework. Based on the final output, it is evident that the agricultural and industrial sectors, being the primary water consumers, are more susceptible to negative impacts resulting from the reduction in system sustainability. This susceptibility is primarily attributed to their highest vulnerability and comparatively lower reliability.

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    Authors: Swaraj Shukla; Kamilla Sadykova; Jinjin Tian;

    This paper presents a comprehensive analysis of the agriculture trade dynamic between India and China from 2002–2021. It employed the Revealed Comparative Advantage (RCA) and Revealed Symmetric Comparative Advantage (RSCA) indices and various statistical analyses to assess the trade performance and provide an enhanced comprehension of the specialization pattern. The study has selected 45 agricultural commodities, categorized into seven sections according to the HS Nomenclature 2017. The findings revealed that India boasts a more diversified export portfolio compared to China, with a more significant number of agriculture chapters demonstrating a comparative advantage. Conversely, China’s export basket is more concentrated, featuring fewer chapters with a comparative advantage but higher values of RCA and RSCA. The paper also identified the prospective areas for agriculture-trade cooperation and collaboration between the two countries and put forward recommendations. This research aims to offer valuable insights for policymakers, researchers, and traders to enhance bilateral ties and mutual benefits in the agriculture sector.

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  • Authors: Hilary, Gilles; Serret, Vanessa;

    International audience; The article aims to summarize the current knowledge on governance and digital transformation, focusing on strategic and operational dimensions. It identifies research gaps in linking governance, innovation, and the digital transition, attributing limitations to the challenge of accessing confidential organizational data. It suggests using detailed clinical cases for fruitful research, particularly in exploring the operational aspects of governance. Emphasizing the multidisciplinary nature of this research, it acknowledges complexities in conducting studies across financial, operational, and legal domains. However, it sees this as an opportunity to contribute significantly to understanding governance in the context of digital transformation.; L'article vise à résumer les connaissances actuelles sur la gouvernance et la transformation numérique, en se concentrant sur les dimensions stratégiques et opérationnelles. Il identifie des lacunes en ce qui concerne le lien entre gouvernance, innovation et transition numérique, attribuant ces limitations au défi d'accéder aux données organisationnelles confidentielles. Il suggère d'utiliser des cas cliniques détaillés pour une recherche fructueuse, en particulier pour explorer les aspects opérationnels de la gouvernance. Soulignant la nature multidisciplinaire de cette recherche, il reconnaît les complexités liées à la réalisation d'études dans les domaines financier, opérationnel et juridique. Cependant, il considère cela comme une opportunité de contribuer de manière significative à la compréhension de la gouvernance dans le contexte de la transformation numérique.

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    Authors: Khushi Singh; Prachi Parashar;

    The case study aims to highlight the existing problems and challenges in the primary education system prevalent in Rural India, from the lens of Chikana Village, in the Tonk district of Rajasthan, India. The case study brings to light prevalent practices, concerns and beliefs that govern the process of imparting primary-level education to the children of Chikana. The points made in the course of the study, though derived from this particular village, can be used as a general idea for most schools in rural India. The researchers have taken into consideration the prevalent schemes started by state and central governments for the enhancement of the quality of education in Rural India and have built points on the impact and significance these schemes have made so far. The study is qualitative in nature and uses both secondary and primary data sets. Secondary data is used in the form of old schemes and impact reports on Indian primary education, while primary data is incorporated in the form of observation and interview schedules. The time frame of all secondary data is limited to the last 5 years (February 2018- February 2023). The sample size for the interview schedule is 40 participants, these included students from ranging age groups, teachers and school authorities of the ‘Rajkiya Ucch Prathmik Vidyalay, Chikana'. The study aims to raise considerable awareness among the readers of this study about the existing trends in education in rural India and to highlight the gap in urban and rural education systems. The study goes on to find major loopholes in the ongoing educational practices prevalent in rural India. It brings to light the different dimensions of the primary education system and the opinions of different stakeholders on the progression of the sector. It comments on the implementation of policies designed to cater to the needs of children. The study also offers the author's conclusion derived from the curated data sets which clearly presents the condition of the sector as more bad than good, however, stressing enough of the good and stating that progress is expected in the years to come. The study is a comprehensive work, which gives a 180-degree view of the education provided to children in rural parts of the country.

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    Asian Research Journal of Arts & Social Sciences
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      Asian Research Journal of Arts & Social Sciences
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    Authors: Albert Sanchez-Graells;

    Public sector digitalisation is transforming public governance at an accelerating rate. Digitalisation is outpacing the evolution of the legal framework. Despite several strands of international efforts to adjust good administration guarantees to new modes of digital public governance, progress has so far been slow and tepid. The increasing automation of decision-making processes puts significant pressure on traditional good administration guarantees, jeopardises individual due process rights, and risks eroding public trust. Automated decision-making has, so far, attracted the bulk of scholarly attention, especially in the European context. However, most analyses seek to reconcile existing duties towards individuals under the right to good administration with the challenges arising from digitalisation. Taking a critical and technology-centred doctrinal approach to developments under the law of the European Union and the Council of Europe, this paper goes beyond current debates to challenge the sufficiency of existing good administration duties. By stressing the mass effects that can derive from automated decision-making by the public sector, the paper advances the need to adapt good administration guarantees to a collective dimension through an extension and a broadening of the public sector’s good administration duties: that is, through an extended ex ante control of organisational risk-taking, and a broader ex post duty of automated redress. These legal modifications should be urgently implemented.

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    Laws
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    Laws
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    Authors: Xiangwu Deng; Long Qi; Zhuwen Liu; Song Liang; +2 Authors

    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.

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    Authors: Ebenezer Donkor; Emmanuel Dela Amegbe; Tomas Ratinger; Jiri Hejkrlik;

    Producer groups are influential in Ghana’s cocoa value chain. They facilitate training, extension, education and inputs to their members. Still, there is no study on the impact of these producer groups on the technical efficiency and productivity of smallholder cocoa farmers. Using data from 217 and 199 members and non-members of cocoa producer groups, this study aimed to analyse producer groups’ impact on smallholder farmers’ technical efficiency and yield. The truncated normal distribution stochastic frontier model was adopted to estimate the farmers’ technical efficiency. Since the model showed an issue of inefficiency among the farmers, we added socio-demographic and institutional variables to account for determinants of inefficiency. Finally, we adopted an endogenous treatment regression model to analyse producer groups’ impact on the farmers’ technical efficiency by accounting for observed and unobserved biases. The study results show that farm size, labour, and capital significantly positively impact the partial elasticity of production. Age, education, use of hybrid cocoa, involvement in off-farm jobs, extension access, and producer group membership significantly affect inefficiency. The results further show that producer group membership significantly impacts technical efficiency and yield from the endogenous treatment regression model. To deal with the issues of non-participating in the producer groups, the study recommends that producer groups should be made accessible to farmers. Policymakers can promote the formation and strengthening of producer groups, leading to improved productivity and technical efficiency among cocoa farmers. This approach empowers farmers, enhances their access to resources and knowledge, and enables them to collectively address common challenges, ultimately contributing to sustainable cocoa production and better livelihoods for cocoa farming communities.

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    Authors: Jung-Bin Su;

    This study employs a bivariate GARCH model to examine the influence of the COVID-19 pandemic on the interactions of the commodities in the agricultural market via a connectedness network approach. Empirical results show that this pandemic alters the commodities’ roles—the activators, net transmitters, and net receivers—in the volatility and return connectedness but not for the activators in the correlation connectedness. Moreover, this pandemic enhances the interactive degree of the unidirectional negative return spillovers and the bidirectional distinct-sign volatility spillovers but doesn’t for the interactive degree of correlation. Thus, the COVID-19 pandemic, a short-term drastic event, can influence short-term interactions like volatility and return spillovers but can’t affect one long-term interaction like the correlation. Nevertheless, this pandemic raises the intensity of the correlation as well as volatility and return spillovers. The findings provide policymakers to make short- and long-term investment strategies in the agriculture market.

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    Authors: Gopika Ajaykumar; Gregory D. Hager; Chien-Ming Huang;

    Non-expert users can now program robots using various end-user robot programming methods, which have widened the use of robots and lowered barriers preventing robot use by laypeople. Kinesthetic teaching is a common form of end-user robot programming, allowing users to forgo writing code by physically guiding the robot to demonstrate behaviors. Although it can be more accessible than writing code, kinesthetic teaching is difficult in practice because of users’ unfamiliarity with kinematics or limitations of robots and programming interfaces. Developing good kinesthetic demonstrations requires physical and cognitive skills, such as the ability to plan effective grasps for different task objects and constraints, to overcome programming difficulties. How to help users learn these skills remains a largely unexplored question, with users conventionally learning through self-guided practice. Our study compares how self-guided practice compares with curriculum-based training in building users’ programming proficiency. While we found no significant differences between study participants who learned through practice compared to participants who learned through our curriculum, our study reveals insights into factors contributing to end-user robot programmers’ confidence and success during programming and how learning interventions may contribute to such factors. Our work paves the way for further research on how to best structure training interventions for end-user robot programmers.

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    Authors: Yu Li; Zhiheng Zhang;

    Tobacco farmers often adopt additional multiple agricultural technologies (AMATs) in addition to implementing the standardized technical system in China. Based on the cross-sectional micro data of 346 households of Chongqing, China, this paper assesses the determinants and impacts of the adoption of AMATs on income by using a multinomial endogenous treatment effects model to correct for selection bias and endogeneity caused by observed and unobserved heterogeneity. The results show that (1) the adoption of combinations of AMATs is determined by the household head’s education level, experience in tobacco growing, the shortest distance to nearby town, the amount of technical training, the ratio of land available for mechanical cultivation to tobacco land, the distance to extension station, and the ratio of leased land. (2) The adoption of combinations of AMATs has heterogeneous effects on farmers’ income through yield and quality improvement. (3) The comprehensive combination of AMATs is not necessarily the best option for farmers. Due to the interaction between technologies such as complementary, substitute or supplementary effects, the moderate implementation of fertilizers and soil improvement is the most effective combination. The results of this research provide a scientific basis for improving the adoption efficiency of AMATs in China.

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    Authors: Mahdi Moudi; Qiuyan Gai; He Yuan; Li Guiqing; +3 Authors

    In general, the sustainability of the water supply system is indicative of an adaptive operational approach, wherein the decision-maker adjusts the system’s performance based on the availability of water resources in a given time frame. In light of this, a novel framework is proposed in this study to evaluate sustainability, including three key indicators: resilience, reliability, and vulnerability. To address stressors that may lead to system failure, a multisectoral water allocation optimization is undertaken. In order to account for the future implications of climate change on the hydrological cycle, a simulation step, is incorporated, utilizing the Soil and Water Assessment Tool (SWAT) under various emission scenarios (RCP4.5 and RCP8.5), prior to integrating the streamflow data into our proposed optimal framework. To calibrate and validate historical data (2014–2019) and simulate future streamflow patterns (2025–2085), the Sistan Basin, located in an arid region of Iran, is analyzed as a case study. In light of the anticipated adverse impacts on the water supply system, certain adaptation measures, such as demand shrinkage scenarios, are considered to further appraise the proposed framework. Based on the final output, it is evident that the agricultural and industrial sectors, being the primary water consumers, are more susceptible to negative impacts resulting from the reduction in system sustainability. This susceptibility is primarily attributed to their highest vulnerability and comparatively lower reliability.

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    Authors: Swaraj Shukla; Kamilla Sadykova; Jinjin Tian;

    This paper presents a comprehensive analysis of the agriculture trade dynamic between India and China from 2002–2021. It employed the Revealed Comparative Advantage (RCA) and Revealed Symmetric Comparative Advantage (RSCA) indices and various statistical analyses to assess the trade performance and provide an enhanced comprehension of the specialization pattern. The study has selected 45 agricultural commodities, categorized into seven sections according to the HS Nomenclature 2017. The findings revealed that India boasts a more diversified export portfolio compared to China, with a more significant number of agriculture chapters demonstrating a comparative advantage. Conversely, China’s export basket is more concentrated, featuring fewer chapters with a comparative advantage but higher values of RCA and RSCA. The paper also identified the prospective areas for agriculture-trade cooperation and collaboration between the two countries and put forward recommendations. This research aims to offer valuable insights for policymakers, researchers, and traders to enhance bilateral ties and mutual benefits in the agriculture sector.

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