Hasil untuk "Trade associations"

Charles M. C. Lee, M. Ready

Z. H. Munim, H. Schramm

Considering 91 countries with seaports, this study conducted an empirical inquiry into the broader economic contribution of seaborne trade, from a port infrastructure quality and logistics performance perspective. Investment in quality improvement of port infrastructure and its contribution to economy are often questioned by politicians, investors and general public. A structural equation model (SEM) is used to provide empirical evidence of significant economic impacts of port infrastructure quality and logistics performance. Furthermore, analysis of a multi-group SEM is performed by dividing countries into developed and developing economy groups. The results reveal that it is vital for developing countries to continuously improve the quality of port infrastructure as it contributes to better logistics performance, leading to higher seaborne trade, yielding higher economic growth. However, this association weakens as the developing countries become richer.

M. '. Sas-Rolfes, D. Challender, A. Hinsley et al.

Illegal wildlife trade (IWT) has increased in profile in recent years as a global policy issue, largely because of its association with declines in prominent internationally trafficked species. In this review, we explore the scale of IWT, associated threats to biodiversity, and appropriate responses to these threats. We discuss the historical development of IWT research and highlight the uncertainties that plague the evidence base, emphasizing the need for more systematic approaches to addressing evidence gaps in a way that minimizes the risk of unethical or counterproductive outcomes for wildlife and people. We highlight the need for evaluating interventions in order to learn, and the importance of sharing datasets and lessons learned. A more collaborative approach to linking IWT research, practice, and policy would better align public policy discourse and action with research evidence. This in turn would enable more effective policy making that contributes to reducing the threat to biodiversity that IWT represents.

Changjie Hu, Zhu Chen, Ting Cao

This study investigates credit unions’ expansion into non-core lending and its association with risk and financial resilience. Using US credit union call report data from 1994 to 2024, we measure the share of purchased loans, lease receivables, and loans held for sale in non-core lending. We document robust conditional, within-credit-union associations that point to a clear risk trade-off. Credit unions with higher non-core exposure grow faster in terms of loans and membership but exhibit weaker financial buffers, including lower net worth ratios and weaker economic solvency, alongside higher delinquency. Decomposition tests indicate that loans held for sale are most strongly associated with adverse buffer and asset quality patterns, while purchased loans and lease receivables display smaller and less uniform relationships. Scale interactions suggest that these associations are generally weaker for larger institutions for both membership and assets. Post-COVID estimates indicate that the baseline relationships are broadly stable, while the growth link is becoming stronger.

Ariadna Fosch, Alberto Aleta, Roger Cremades et al.

Recent global food trade disruptions have evidenced how local shocks can cascade into global security threats. While the capacity of food systems to absorb spillovers depends heavily on its underlying trade networks, few studies quantify how their temporal evolution reshapes systemic vulnerability over time. Here, we evaluate how changes in global connectivity from 1986 to 2022 reshaped responses to production shocks. Using FAO data, we built yearly multiplex representations of the food trade system and quantified robustness through a stochastic shock-propagation model with dynamic export bans. We find that while increasing globalization intensified inter-dependencies and amplified cascades, robustness trends remain heterogeneous. Grain trade has become more decentralized and resilient to targeted shocks; conversely, Animal and Vegetable Fats exhibit growing centralization and fragility around key exporters like Indonesia and Malaysia. These structural transformations caused diverging shifts in systemic vulnerability, disproportionately threatening already vulnerable regions such as Africa and Southern Asia.

Gavin G. Cotterill, Eric K. Cole, Paul C. Cross et al.

Abstract The continued decline of long‐distance ungulate migrations threatens to decouple important ecological processes that increase biodiversity and wildlife abundance. Past research has focused on preserving migration paths where habitat fragmentation and loss disrupt movement corridors. However, shifting residency‐migration trade‐offs are the stronger driver of migration loss in some populations. Suburban residential developments may provide ungulates with anthropogenic food sources and refuge from predators, which can increase population growth among short‐distance migrants relative to long‐distance migrants. This trend can increase wildlife vehicle collisions and other human–wildlife conflicts while simultaneously reducing hunting opportunities. Yet, individual animals vary in their tolerance of human disturbance. We investigated how interindividual variation relative to conflict and human habituation influences elk migration and space use on shared winter range. We used a clustering algorithm applied to GPS collar data to identify elk use of anthropogenic food resources in suburban habitat. Cluster locations identified all known anthropogenic subsidy locations during the study period. Elk that used suburban anthropogenic food sources also migrated 60% shorter distances between summer and winter ranges than elk with no known use of these food subsidies. Elk use of protected wintering grounds was spatially structured such that conflict‐prone, short‐distance migrants disproportionately used areas with more human activity. Clustering algorithms applied to GPS collar data may allow managers to identify foci of concentrated use that generates human–wildlife conflict, and where prion deposition and environmental contamination facilitate the spread of chronic wasting disease, particularly in suburban areas with anthropogenic food subsidies. The apparent spatial structuring of shared winter range according to the conflict potential and migration strategy of individual elk may also permit managers to assess relative recruitment among cryptic population segments using different migration strategies and facilitate targeted, adaptive management actions. These associations between conflict, human habituation, and migration shed light on the urbanization of wildlife species, inform efforts to manage human–wildlife conflict and disease spread, and emphasize that a multipronged approach beyond maintaining habitat corridors may be necessary to conserve long‐distance migrations for species that can become human‐habituated.

Sona Mahrokhi, MD, Sara Sakowitz, MD, Esteban Aguayo, MD et al.

Background: Pylorus-preserving pancreaticoduodenectomy (PPPD) was developed to improve postoperative gastrointestinal function while maintaining oncologic adequacy. However, conflicting evidence and concerns persist regarding increased delayed gastric emptying, warranting a national-level investigation. Methods: This retrospective cohort study analyzed 40,063 adult pancreaticoduodenectomy procedures from the ACS NSQIP database (2014–2023). Patients were stratified into pylorus-preserving and non-pylorus-preserving groups. Multivariable regression models evaluated independent associations between pylorus-preserving status and clinical outcomes including infectious complications, blood transfusions, delayed gastric emptying, and length of stay. Results: Of 40,063 pancreaticoduodenectomy procedures, 13,882 (34.6 %) were pylorus-preserving. PPPD was associated with lower rates of infectious complications (25.9 vs 27.5 %, P = 0.01) and blood transfusions (13.6 vs 16.4 %, P < 0.001), but higher delayed gastric emptying rates (17.1 vs 16.1 %, P = 0.02) and shorter length of stay (7 vs 8 days, P = 0.01). Readmission rates were similar (17.4 vs 17.9 %, P = 0.16). Following risk adjustment, PPPD remained associated with reduced infectious complications (AOR 0.94, 95 % CI 0.89–0.99) and blood transfusions (AOR 0.88, 95 % CI 0.82–0.95), but increased delayed gastric emptying (AOR 1.12, 95 % CI 1.04–1.21). Conclusion: Despite declining utilization over the study period, PPPD offers significant advantages in reducing infectious complications and blood transfusion requirements while shortening operative times and hospital stay. However, the trade-off of increased delayed gastric emptying requires careful consideration in surgical decision-making. These findings support individualized approach selection based on patient complexity and surgeon expertise to optimize perioperative outcomes.

Huitong Zhou, Lingrong Bai, Shaobin Li et al.

The wool of sheep consists of structurally intricate natural fibres that can be processed and manufactured into a range of products. It is prized for its insulation, moisture-buffering capability, flame resistance, and biodegradability. These features arise from its unique fibre architecture and specialised protein composition, which set it apart from most other natural and synthetic fibres. However, despite these novel characteristics, wool fibre variation hampers its uses and reduces its ability to compete with other fibres. This review summarises our current knowledge of wool fibre biology. It begins with a description of wool’s functional properties and performance attributes, then explores the structural foundations of these properties, the molecular basis of fibre trait variation, and prospects for improving fibre quality using genetic approaches. Particular attention is given to the wool keratin and keratin-associated protein genes, their spatiotemporal expression patterns, and genetic polymorphism that may influence fibre characteristics. Opportunities for the genetic improvement of sheep are discussed, including the use of genetic modification and marker-assisted selection. Challenges in interpreting gene–trait associations, particularly from high-throughput omics studies, are highlighted, along with the need for functionally validated genetic markers. Potential trade-offs between wool characteristics and other production and reproductive traits are considered, emphasising the need for balanced breeding approaches. By integrating insights from structural biology, molecular genetics, and breeding strategies, this review provides a foundation for wool fibre improvement.

Muhammad Sukri Bin Ramli

New methods are needed to monitor environmental treaties, like the Montreal Protocol, by reviewing large, complex customs datasets. This paper introduces a framework using unsupervised machine learning to systematically detect suspicious trade patterns and highlight activities for review. Our methodology, applied to 100,000 trade records, combines several ML techniques. Unsupervised Clustering (K-Means) discovers natural trade archetypes based on shipment value and weight. Anomaly Detection (Isolation Forest and IQR) identifies rare "mega-trades" and shipments with commercially unusual price-per-kilogram values. This is supplemented by Heuristic Flagging to find tactics like vague shipment descriptions. These layers are combined into a priority score, which successfully identified 1,351 price outliers and 1,288 high-priority shipments for customs review. A key finding is that high-priority commodities show a different and more valuable value-to-weight ratio than general goods. This was validated using Explainable AI (SHAP), which confirmed vague descriptions and high value as the most significant risk predictors. The model's sensitivity was validated by its detection of a massive spike in "mega-trades" in early 2021, correlating directly with the real-world regulatory impact of the US AIM Act. This work presents a repeatable unsupervised learning pipeline to turn raw trade data into prioritized, usable intelligence for regulatory groups.

Justus Preusser

This paper studies learning in markets with aggregate uncertainty about whether trade is efficient. A long-lived seller offers prices to buyers, who are short-lived and arrive according to a Poisson process. A hidden state determines whether the buyers' common value exceeds the seller's reservation value. All parties observe noisy, private signals about the state. With small intertemporal frictions and when the seller has commitment power, the seller waits for a buyer with the most favorable signal to arrive up to an exit time that depends on the seller's private information. This strategy profile maximizes both the seller's profit and the expected surplus. Without commitment, the commitment profit is unattainable. Instead, there is an equilibrium in which the seller also waits for a buyer with the most favorable signal, but, relative to the commitment case, the seller exits inefficiently late, and the trade probability is inefficiently high.

Hashim Zameer, Humaira Yasmeen, Muhammad Wasif Zafar et al.

D. Angus

This Viewpoint discusses the tensions between evaluating treatments (learning) and just treating patients (doing) during the coronavirus disease 2019 (COVID-19) pandemic, and proposes actions the clinical research and practice communities can take to support each other's imperatives so that both can "learn from doing" in a more integrated patient care approach [ABSTRACT FROM AUTHOR] Copyright of JAMA: Journal of the American Medical Association is the property of American Medical Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission However, users may print, download, or email articles for individual use This abstract may be abridged No warranty is given about the accuracy of the copy Users should refer to the original published version of the material for the full abstract (Copyright applies to all Abstracts )

Yacouba Kassouri, Halil Altıntaş

How to improve environmental quality and achieve human development remains major sustainability issues, particularly in the MENA region (the Middle East and North Africa). Most of the empirical literature fails to consider human well-being and environmental quality together although these concepts are fundamentally similar in their concern for distributive justice. This inquiry uses panel data for 13 MENA countries over the period 1990-2016 to examine the association between human development and ecological footprint and test whether trade-off nexus holds between these two sustainability-based indicators. To increase the policy relevance of this inquiry, the MENA region is divided into two sub-groups of countries: seven oil exporting countries and six non-oil exporting countries. The highlights pointed out the presence of a strong trade-off between the ecological footprint and human well-being captured by human development index for the whole sample and across the two subsamples. The crucial role played by economic institutions may help the MENA countries to mitigate the trade-offs to achieve simultaneously both targets of human well-being and environmental protection. Our empirical insights have important implications for achieving human development sustainability through the pursuit of the individual SDG targets.

A. V. Toropygin, A. V. Nikolaenko

The Eurasian Economic Union (EAEU) is a rapidly developing integration structure. Its main priority in activities is economic development, even more precisely, trade. At the same time, at the beginning of its activities, the main attention of the member states of the association was focused on the development of domestic trade. The creation of a customs union and a single economic space basically solved this problem. The current development of the structure, in accordance with the global trend, was the expansion of trade relations with border, regional and non-regional partners. Thus, there is a process of integration of integrations, i.e. interaction at the level of integration structures and individual states. Since the EAEU’s main activity is the economy, first of all, we are talking about the creation of Free Trade Zones (FTAs).Aim. The purpose of the article is to identify the dynamics and directions of the development of relations between the EAEU and the countries of Latin America and the Caribbean.Tasks. Consider the main trends and stages of interaction between the LACB countries and the EAEU; identify new directions for the development of Eurasian integration.Methods. The use of a systematic approach made it possible to analyze integration processes taking into account various directions. The method of historical and comparative analysis was used to compare the concepts of the development of integration. Situational analysis made it possible to demonstrate the dynamics of the development of Eurasian integration and the formation of interaction with external actors.The sociological approach made it possible to consider as a special variety of international structures with the characteristics of both intergovernmental bodies and organizations.Results. Against the background of the development of economic interaction, new areas of interaction have been identified.Conclusions. In the current third stage of cooperation between the EAEU and the LKA, the element of political communication of the organization’s information function is strengthened, which is a response to the political crisis on the one hand, and on the other, opposition to Western sanctions in terms of attempts to isolate Russia in the world.

Akanksha A. Marphatia, Naomi M. Saville, Dharma S. Manandhar et al.

Background Women’s underage marriage (<18 years) is associated with adverse maternal and child health outcomes. Poverty in the natal household has been widely considered to be a key risk factor for underage marriage, but the evidence base is unreliable. When investigating this issue, most studies use marital wealth inappropriately, as a proxy for wealth in the natal household. In contrast, we investigated whether the timing of women’s marriage was associated with the wealth of the households they marry into, and how this may vary by women’s education level. This approach allows us to explore a different set of research questions which help to understand the economic value placed on the timing of women’s marriage. Methods We used data on 3,102 women aged 12–34 years, surveyed within 1 year of marriage, from the cluster-randomized Low Birth Weight South Asia Trial in lowland rural Nepal. Linear mixed-effects regression models investigated independent associations of women’s marriage age and education level with marital household wealth, and their interactive effects. Models adjusted for marital household traits. We analysed the full sample, and then only the uneducated women, who comprised a substantial proportion in our sample. Results In the full sample, we found that each later year of women’s marriage was associated with 1.5% lower asset score for those with primary education, and with 0.3% and 1.3% higher asset score for those with lower secondary or secondary/higher education, respectively. For uneducated women, relative to marrying ≤14 years, marrying at 15, 16, 17 and ≥18 years was associated with 1.5%, 4.4%, 2.4% and 6.2% greater marital asset score respectively. Conclusion On average, marrying ≥18 years was associated with greater marital assets for secondary-educated women. There were only very modest benefits in terms of marital household wealth for delaying marriage beyond 16 years for uneducated women or those with low education. These findings elucidate potential trade-offs faced by families, including decisions over how much education, if any, to provide to daughters. They may help to understand the economic rationale underpinning the timing of marriage, and why early marriage remains common despite efforts to delay it.

Indra Saktia Octaviana, Yuki Mahardhito Adhitya Wardhana, Udi Syahnoedi Hamzah

Background: Natural and technological disasters cause significant societal and economic harm, making effective disaster prevention and management essential. Communities and industries are key actors, each contributing unique resources and knowledge to enhance resilience and mitigate disaster impacts. Objectives: This study examined the role of community and industry in disaster prevention and management. It analysed how collaboration between these segments advances readiness, reaction, and flexibility and investigated procedures to reinforce future fiasco administration approaches. Methodology: This study is a systematic review conducted using the PICO (Patient, Problem, or Population; Intervention; Comparison, Control, or Comparator; and Outcomes) framework that analyses literature sourced from the SCOPUS database. The investigation centres on assessing the unmistakable and shared parts of communities and industries in the fiasco disaster. Results: Industries contribute by identifying risks, supplying resources, and managing disruptions, while communities enhance resilience through local knowledge, social networks, and active involvement in response efforts. Effective disaster management is achieved through coordinated efforts supported by government policies, which bridge industrial and community capabilities. Unique Contribution: The study presents a system where community and industry collaboration is seen as central to building a stronger and more versatile disaster management show. It highlights the virtual stages' role in advancing information trade between partners.  Conclusion: Successful disaster management relies on the cooperation between industries, communities, and governments. This study demonstrates how their combined efforts can strengthen preparedness and reduce disaster impacts. Key Recommendation: Future research should centre on creating collaborative procedures and leveraging innovation to upgrade disaster management associations between industries and communities, particularly in the face of expanding disaster complexity.

Lucas Vicuña

Abstract The genetic architecture of complex diseases affecting populations with Indigenous American ancestries is poorly understood due to their underrepresentation in genomics studies. While most of the genetic diversity associated with disease trait variation is shared among worldwide populations, a fraction of this component is expected to be unique to each continental group, including Indigenous Americans. Here, I describe the current state of knowledge from genome-wide association studies on Indigenous populations, as well as non-Indigenous populations with partial Indigenous ancestries from the American continent, focusing on disease susceptibility and anthropometric traits. While some studies identified risk alleles unique to Indigenous populations, their effects on trait variation are mostly small. I suggest that the associations rendered by many inter-population studies are probably inflated due to the absence of socio-cultural-economic covariates in the association models. I encourage the inclusion of admixed individuals in future GWAS studies to control for inter-ancestry differences in environmental factors. I suggest that some complex diseases might have arisen as trade-off costs of adaptations to past evolutionary selective pressures. Finally, I discuss how expanding panels with Indigenous ancestries in GWAS studies is key to accurately assess genetic risk in populations from the American continent, thus decreasing global health disparities.

Raúl Mínguez, Asier Minondo

This paper documents a new feature of international trade: the increase in the share of low-value transactions in the total volume of transactions. Using Spanish data, we show that the share of low-value transactions in the total number of transactions increased from 9% to 61% in exports and from 14% to 54% in imports between 1997 and 2023. The increase in the number of low-value trade transactions is explained by the rise of e-commerce and direct-to-customer sales facilitated by online retail platforms, and the fast-fashion strategy followed by clothing firms.

Ronak Bhadra, Raghunath Tewari

Kallampally and Tewari showed in 2016 that there can be a trade-off between determinism and time in space-bounded computations. This they did by describing an unambiguous non-deterministic algorithm to solve Directed Graph Reachability that requires O(log^2 n) space and simultaneously runs in polynomial time. Savitch's 1970 algorithm that solves the same problem deterministically also requires O(log^2 n) space but doesn't guarantee polynomial running time and hence the trade off. We describe a new problem for which we can show a similar trade off between determinism and time. We consider a collection P of f directed paths. We show that the problem of finding reachability from one vertex to another in the union G of these path graphs via a path that switches amongst the paths in P at most k times can be solved in O(klog f+log n) space but the algorithm doesn't guarantee polynomial runtime. On the other hand, we also show that the same problem can be solved by an unambiguous non-deterministic algorithm that simultaneously runs in O(klog f+log n) space and polynomial time. Since these two algorithms are not dependent on Savitch, therefore this example sheds new light on how such a trade off between determinism and time happens in space-bounded computations and makes the phenomenon less elusive.

Thiago C. Silva, Paulo V. B. Wilhelm, Diego R. Amancio

This study examines the effects of de-globalization trends on international trade networks and their role in improving forecasts for economic growth. Using section-level trade data from nearly 200 countries from 2010 to 2022, we identify significant shifts in the network topology driven by rising trade policy uncertainty. Our analysis highlights key global players through centrality rankings, with the United States, China, and Germany maintaining consistent dominance. Using a horse race of supervised regressors, we find that network topology descriptors evaluated from section-specific trade networks substantially enhance the quality of a country's GDP growth forecast. We also find that non-linear models, such as Random Forest, XGBoost, and LightGBM, outperform traditional linear models used in the economics literature. Using SHAP values to interpret these non-linear model's predictions, we find that about half of most important features originate from the network descriptors, underscoring their vital role in refining forecasts. Moreover, this study emphasizes the significance of recent economic performance, population growth, and the primary sector's influence in shaping economic growth predictions, offering novel insights into the intricacies of economic growth forecasting.