Background and Aim: The Liaoning Cashmere goat (LCG) is a dual-purpose breed of major economic importance in China, valued for its high cashmere yield and meat quality. Cashmere fineness (CF) remains a primary target for genetic improvement because fiber diameter directly determines textile value and market price. This study examined the sex-specific effects of single-nucleotide polymorphisms in the guanosine monophosphate synthase (GMPS) and steroid receptor coactivator (SRC) genes on CF and a broad spectrum of production traits to identify functional markers for marker-assisted selection.
Materials and Methods: A total of 1,160 healthy LCGs (89 bucks and 1,071 does, 2–4 years of age) from the same nucleus herd were included. The C31799T locus in GMPS and the C34197G locus in SRC were genotyped by polymerase chain reaction (PCR) amplification followed by bidirectional Sanger sequencing. Genotype–trait associations were tested using general linear mixed models, with genotype, sex, and age as fixed effects, and pedigree information incorporated to control for relatedness. Haplotype phases were inferred separately for each sex with the SHEsis platform. Phenotypes recorded comprised cashmere production traits (fineness, length, yield), body size measurements, slaughter performance, meat quality attributes, milk composition, and lambing rate. Data normality, homoscedasticity, and multicollinearity were verified prior to analysis; statistical significance was declared at p < 0.05.
Results: The TT genotype at the GMPS C31799T locus and the CG genotype at the SRC C34197G locus were significantly associated with finer cashmere fibers (p < 0.05). Sex-stratified analyses showed that the GMPS TT genotype conferred superior CF in does (p < 0.01) and longer staple length in both sexes (p < 0.01), whereas the SRC CG genotype improved fineness specifically in does (p < 0.01). Haplotype analysis identified CCCC as the optimal combination for finer cashmere in bucks and TTGG in does. Pleiotropic effects were evident: the GMPS CC genotype favored larger body dimensions, the GMPS TT genotype enhanced carcass traits in bucks, and the SRC CG genotype improved lactation performance. CF exhibited positive correlations with cashmere yield (bucks: r = 0.412; does: r = 0.384; p < 0.01) and negative associations with several slaughter traits. Path and stepwise regression analyses clarified direct and indirect effects, underscoring sex-dependent genetic trade-offs between fiber quality and meat production.
Conclusion: This is the first study to establish GMPS and SRC as key candidate genes influencing CF in goats. The identified superior genotypes and haplotypes provide sex-specific molecular markers that can be immediately deployed in marker-assisted selection programs to accelerate genetic gains in cashmere quality while safeguarding meat production potential in LCG breeding. Validation in independent populations will further strengthen their utility for precision breeding.
Asmaa A. Darwish, Huda A. Alqahtani, Amin Tahoun
et al.
Sheep pox, caused by sheep pox virus (SPV), is a transboundary disease that threatens sheep production and trade. This study aimed to identify genetic, immunological, and biochemical markers associated with susceptibility to SPV in Barki ewes. A total of 100 adult ewes were examined, including 50 clinically healthy and 50 naturally infected animals. PCR detected SPV DNA in 60% of suspected scab samples, highlighting diagnostic challenges in field investigations. Blood samples were analyzed for hematological indices, cytokine profiles, acute phase proteins, oxidative stress biomarkers, iron metabolism, and hormonal parameters. Expression profiles and single-nucleotide polymorphisms (SNPs) in 15 immune and antioxidant genes were characterized from cDNA-derived sequences. Infected animals exhibited microcytic hypochromic anemia, leukocytosis, elevated proinflammatory cytokines, and reduced IL-10. Acute phase proteins, oxidative stress markers, and cortisol were increased, whereas antioxidant capacity and transferrin were reduced. Twenty-three SNPs were identified, including non-synonymous variants, which showed promising but unvalidated associations with disease status. These findings highlight immune, oxidative, and genetic alterations in SPV-infected sheep, but further longitudinal and cross-validated studies are needed to establish their diagnostic or breeding utility.
Trades are important objects in combinatorial design theory that may be realized as certain elements of kernels of inclusion matrices. Total trades were introduced recently by Ghorbani, Kamali and Khosravshahi, who showed that over a field of characteristic zero the vector space of trades decomposes into a direct sum of spaces of total trades. In this paper, we show that the vector space spanned by the permutations of a total trade is an irreducible representation of the symmetric group. As a corollary, the previous decomposition theorem is recovered. Also, a basis is obtained for the module of total trades in the spirit of Specht polynomials. More generally, in the second part of the paper we consider intersection matrices and determine the irreducible decompositions of their images. This generalizes previously known results concerning ranks of special cases.
This study investigates the effectiveness of Large Language Models (LLMs) for the extraction of structured knowledge in the form of Subject-Predicate-Object triples. We apply the setup for the domain of Economics application. The findings can be applied to a wide range of scenarios, including the creation of economic trade knowledge graphs from natural language legal trade agreement texts. As a use case, we apply the model to regional trade agreement texts to extract trade-related information triples. In particular, we explore the zero-shot, one-shot and few-shot prompting techniques, incorporating positive and negative examples, and evaluate their performance based on quantitative and qualitative metrics. Specifically, we used Llama 3.1 model to process the unstructured regional trade agreement texts and extract triples. We discuss key insights, challenges, and potential future directions, emphasizing the significance of language models in economic applications.
Overseas investment and trade can be daunting for beginners due to the vast amount of complex information. This paper presents a chatbot system that integrates natural language processing and information retrieval techniques to simplify the document retrieval process. The proposed system identifies the most relevant content, enabling users to navigate the intricate landscape of foreign trade and investment more efficiently. Our methodology combines the BM25 model and a deep learning model to rank and retrieve documents, aiming to reduce noise in the document content and enhance the accuracy of the results. Experiments with Thai natural language queries have demonstrated the effectiveness of our system in retrieving pertinent documents. A user satisfaction survey further validated the system's effectiveness. Most respondents found the system helpful and agreed with the suggested documents, indicating its potential as a valuable tool for Thai entrepreneurs navigating foreign trade and investment.
Joachim D’Hondt, Laurent Chapelle, Chris Bishop
et al.
Abstract Background The presence of inter-limb asymmetry in the human body has traditionally been perceived to be detrimental for athletic performance. However, a systematic review addressing and comprehensively assessing the association of asymmetry between the lower limbs and middle- and long-distance running performance-related metrics is currently lacking. Objective The main purpose of this systematic review was to examine the relationship between lower inter-limb asymmetry and determinants of running performance in healthy middle- and long-distance runners. The secondary objective was to identify possible avenues for further research in this area. Methods PubMed, Web of Science and SPORTDiscus were systematically searched for studies investigating the relationship between lower inter-limb asymmetry and (determinants of) running performance in healthy and injury-free middle- and long-distance runners. The quality of studies eligible for inclusion was assessed using the Downs and Black Quality Index Tool. Results Out of 4817 articles screened, 8 studies were included in this review which assessed the association between functional, morphological, kinematic and kinetic asymmetry and running performance-related metrics. The quality score of the included research varied between 5/10 and 9/10. Our results revealed mixed findings, showing both significant negative (n = 16) and positive (n = 1) associations as well as no significant associations (n = 30) between inter-limb asymmetry and running performance-related metrics. Conclusions A high heterogeneity across study methods and outcomes was apparent, making it difficult to draw a straightforward conclusion. Our results indicate that the majority of metrics of functional, morphological, kinematic and kinetic inter-limb asymmetry are negatively or not associated with running performance (and/or its determinants). Thus, a more extensive high-quality body of research using standardised asymmetry magnitude metrics is essential to determine whether, and to what extent asymmetry between the lower limbs could affect middle- and long-distance running performance. Future studies should establish potential trade-off values to help practitioners develop evidence-based training programs. Key Points In the majority of the metrics, the magnitude of lower inter-limb asymmetry was negatively or not associated with middle- and long-distance running performance. Coaches, athletes and researchers should be attentive of the task, time- and metric-specificity as well as the inter- and intra- individual variability of magnitude outcomes, when assessing inter-limb asymmetries.
This study evaluates the key drivers of green logistics performance and their impact on economic growth in African countries. The study employs a quantitative approach using panel data analysis for African countries from 2007 to 2022. Impulse Response Function and Variance Decomposition methods are utilized to examine the dynamic relationships among variables, including economic growth, Logistics Performance Indicators (LPI), fossil fuel consumption, and greenhouse gas emissions. The findings reveal significant positive relationships between green logistics performance indicators, such as the ability to track and trace consignments, logistics service quality, and trade infrastructure, with economic growth. Conversely, fossil fuel consumption and greenhouse gas emissions exhibit negative associations with economic growth and environmental sustainability. The results underscore the importance of embracing green logistics practices and sustainable development strategies in African economies. By improving logistics infrastructure, enhancing service quality, and reducing environmental impacts, countries can foster economic growth while mitigating adverse effects on the environment. Future research could explore region-specific factors influencing green logistics adoption and examine the role of policies and regulations in promoting sustainable practices. The findings have implications for policymakers, industry stakeholders, and regulatory bodies in developing targeted strategies to align economic progress with environmental responsibility in African nations.
This article examines the transformation of employers’ associations in the German metal and electrical industry from the perspective of the power resources approach. It argues that, as a result of changing economic conditions and the decline of trade union countervailing power, the institutional power resources of employers’ associations have been relativised, which in turn has led to a reassessment of employers’ associations by capital. Employers’ associations have responded by extending exclusive services to their members. Using the power resources approach, the article makes a concrete determination of the relationship between companies and employers’ associations. In doing so, the article contributes to a better understanding of the function, role and development of employers’ associations. At the same time, it contributes to the debate on the further development of the power resources approach and its extension to the analysis of employers’ power.
We explore brokerage between traders in an online learning framework. At any round $t$, two traders meet to exchange an asset, provided the exchange is mutually beneficial. The broker proposes a trading price, and each trader tries to sell their asset or buy the asset from the other party, depending on whether the price is higher or lower than their private valuations. A trade happens if one trader is willing to sell and the other is willing to buy at the proposed price. Previous work provided guidance to a broker aiming at enhancing traders' total earnings by maximizing the gain from trade, defined as the sum of the traders' net utilities after each interaction. In contrast, we investigate how the broker should behave to maximize the trading volume, i.e., the total number of trades. We model the traders' valuations as an i.i.d. process with an unknown distribution. If the traders' valuations are revealed after each interaction (full-feedback), and the traders' valuations cumulative distribution function (cdf) is continuous, we provide an algorithm achieving logarithmic regret and show its optimality up to constant factors. If only their willingness to sell or buy at the proposed price is revealed after each interaction ($2$-bit feedback), we provide an algorithm achieving poly-logarithmic regret when the traders' valuations cdf is Lipschitz and show that this rate is near-optimal. We complement our results by analyzing the implications of dropping the regularity assumptions on the unknown traders' valuations cdf. If we drop the continuous cdf assumption, the regret rate degrades to $Θ(\sqrt{T})$ in the full-feedback case, where $T$ is the time horizon. If we drop the Lipschitz cdf assumption, learning becomes impossible in the $2$-bit feedback case.
This paper studies optimal mechanisms for collecting and trading data. Consumers benefit from revealing information about their tastes to a service provider because this improves the service. However, the information is also valuable to a third party as it may extract more revenue from the consumer in another market called the product market. The paper characterizes the constrained optimal mechanism for the service provider subject to incentive feasibility. It is shown that although the service provider sometimes sells no information or only partial information in order to preserve profits in the service market, selling full information is optimal when the data-sourcing market is highly differentiated. Moreover, a ban on data trade may reduce social welfare because it makes it harder to price discriminate in the product market. Instead, reducing the intermediary's bargaining power can protect privacy without hurting social welfare, which suggests that the regulation of market power is more efficient than the regulation of data sharing.
Alexandra Barro-Chale, Patricia Rivera-Castañeda, Maria Jeanett Ramos-Cavero
et al.
Fair trade initiatives represent an essential support for the scarce opportunities that have arisen in the agricultural sector, as they cover various areas that contribute to increasing good trade practices. It is essential to highlight the contribution of fair trade in urban and rural areas, as it becomes a valuable incentive for differentiation. The main objective of this study was to determine how Fair Trade is applied in the socioeconomic and ecological sphere in an association of sustainable agricultural producers in the Peruvian jungle. This is quantitative research with a non-experimental cross-sectional design. The survey technique was used, and a questionnaire was applied to 99 agricultural producers in the Amazon region of northern Peru, because it would help to analyze the new challenges of fair trade. In addition, data analysis and processing was carried out with Microsoft Office Excel and SPSS. The results show that 51% of the producers surveyed have been sensitized to adopt socially responsible actions aimed at strengthening sustainable development, social responsibility and good practices for fair trade in favor of the preservation of the resources of the Peruvian Amazon, as well as the socioeconomic development of farmers and the region itself. Forty-seven percent carry out social responsibility activities under the guidance of the Fairtrade organization, which has accompanied farmers to obtain Fairtrade certification. In addition, 59% of respondents say that they engage in healthy competition that generates trust among farmers. Fairtrade enables associated farmers to improve their ethical behavior and respect for their rights as well as those of the entire community.
Laís Amaral Mais, Mélissa Mialon, Mélissa Mialon
et al.
IntroductionIn 2020, Brazil approved the introduction of a new front-of-package nutrition labeling (FoPNL) in the format of a magnifying glass (MG) after years of discussion. There is currently a lack of understanding of the role of the food industry in that process. This study aimed to describe the corporate political activity (CPA) of the food industry and conflicts of interest situations, as they happened during the development and approval of a new FoPNL system in Brazil.Materials and methodsWe undertook bibliographical and documentary searches using material from food companies, trade associations and front groups involved in the regulatory process. We (1) collected information about the case study context, (2) collected data from documentary sources, and (3) prepared a synthesis of the results and a timeline of key events.Results/DiscussionDuring the FoPNL regulatory process in Brazil, the food industry opposed the introduction of warning labels, a model supported by health authorities and implemented with success in other countries in Latin America. The food industry rather promoted a traffic-light labeling system, known to be less effective at guiding individuals to make healthier food choices. Later in the process, when it was evident that its preferred model would not be used, and a MG would rather be introduced, the food industry argued for the use of a different version of this FoPNL model. We found that the food industry, all along the process, was directly involved in and influenced the development of the FoPNL, by providing technical support, advising and lobbying policymakers. The food industry also established relationships with a consumer non-governmental organization and nutrition professional societies. The food industry also produced and disseminated information supporting its position in order to influence public opinion and high-level decision makers, and used the legal system to delay the process.ConclusionThe FoPNL in Brazil is neither aligned with the recommendations of international health organizations nor with existing independent scientific evidence. The new FoPNL, as adopted in Brazil, reflects some of the preferences of the industry; it is likely that the influence of that sector during the legislative process was pivotal, even if its initial proposal was not adopted.
The objective of this paper is to investigate a more efficient cross-border payment and document handling process for the export of Indian goods to Brazil. The paper is structured into two sections: first, to explain the problems unique to the India-Brazil international trade corridor by highlighting the obstacles of compliance, speed, and payments; and second, to propose a digital solution for India-brazil trade utilizing Supernets, focusing on the use case of Indian exports. The solution assumes that stakeholders will be onboarded as permissioned actors (i.e. nodes) on a Polygon Supernet. By engaging trade and banking stakeholders, we ensure that the digital solution results in export benefits for Indian exporters, and a lawful channel to receive hard currency payments. The involvement of Brazilian and Indian banks ensures that Letter of Credit (LC) processing time and document handling occur at the speed of blockchain technology. The ultimate goal is to achieve faster settlement and negotiation period while maintaining a regulatory-compliant outcome, so that the end result is faster and easier, yet otherwise identical to the real-world process in terms of export benefits and compliance.
We study the bilateral trade problem where a seller owns a single indivisible item, and a potential buyer seeks to purchase it. Previous mechanisms for this problem only considered the case where the values of the buyer and the seller are drawn from independent distributions. In this paper, we study bilateral trade mechanisms when the values are drawn from a joint distribution. We prove that the buyer-offering mechanism guarantees an approximation ratio of $\frac e {e-1} \approx 1.582$ to the social welfare even if the values are drawn from a joint distribution. The buyer-offering mechanism is Bayesian incentive compatible, but the seller has a dominant strategy. We prove the buyer-offering mechanism is optimal in the sense that no Bayesian mechanism where one of the players has a dominant strategy can obtain an approximation ratio better than $\frac e {e-1}$. We also show that no mechanism in which both sides have a dominant strategy can provide any constant approximation to the social welfare when the values are drawn from a joint distribution. Finally, we prove some impossibility results on the power of general Bayesian incentive compatible mechanisms. In particular, we show that no deterministic Bayesian incentive-compatible mechanism can provide an approximation ratio better than $1+\frac {\ln 2} 2\approx 1.346$.
Sara Lysholm, Johanna F. Lindahl, Johanna F. Lindahl
et al.
Transboundary pathogens pose a threat to livelihood security in countries such as Zambia and Tanzania. This study aimed to investigate the seroprevalence of peste des petits ruminants virus (PPRV), foot and mouth disease virus (FMDV), sheep and goat pox virus (SGPV), Rift Valley fever virus (RVFV) and Brucella spp. in sheep and goats along the Tanzania-Zambia border. Another aim was to assess the association between certain predictor variables and seroprevalence, focusing on trade and proximity to an international border, to a town and to the Tanzania-Zambia highway. During September-October 2018, 486 serum samples from small ruminants in Zambia and 491 in Tanzania were collected and analyzed using enzyme-linked immunosorbent assays (ELISA). A questionnaire focused on management strategies was administered to each household. The animal-level seroprevalence in Zambia was 0.21% [95% confidence interval (CI) (0.01–1.14) for PPRV, 1.03% (95% CI 0.33–2.39) for FMDV, 0% (95% CI 0–0.76) for SGPV, 2.26% (95% CI 1.14–4.01) for RVFV and 1.65% (95% CI 0.71–3.22) for Brucella spp.]. In Tanzania, animal-level seroprevalence was 2.85% (95% CI 1.57–4.74) for PPRV, 16.9% (95% CI 13.7–20.5) for FMDV, 0.20% (95% CI 0.01–1.13) for SGPV, 3.26% (95% CI 1.87–5.24) for RVFV and 20.0% (95% CI 14.5–26.5) for Brucella spp. For PPRV (OR 6.83, 95% CI 1.37–34.0, p = 0.019) and FMDV (OR 5.68, 95% CI 1.58–20.3, p = 0.008), herds situated more than 30 km from an international border were more likely to be seropositive, while being located 10–30 km (OR 4.43, 95% CI 1.22–16.1 p = 0.024) from a border was identified as a risk factor for Brucella spp. For FMDV (OR 79.2, 95% CI 4.52–1388.9, p = 0.003), being situated within 30 km from a town was associated with seropositivity. Furthermore, contact with wild ruminants (OR 18.2, 95% CI 1.36–244), and the presence of sheep in the household (OR 5.20, 95% CI 1.00–26.9, p = 0.049), was associated with seropositivity for PPRV, and FMDV. No significant associations between trade or distance to the Tan-Zam highway and seroprevalence were found. We recommend that the impact of trade and proximity to borders, towns and roads should be further evaluated in larger studies, ideally incorporating aspects such as temporal trade fluctuations.