This study investigates the influence of knowledge management (KM) and merger and acquisition (M&A) networks on the effectiveness of innovation networks within mature entrepreneurial firms. By focusing on a sample of 4139 firms listed on the Chinese stock market and analyzing 8563 M&A transactions from the mid-2000s to 2023, the research aims to explore how these strategic networks shape entrepreneurial innovation, with particular attention to the moderating role of absorptive capacity (AC) and the impact of entrepreneurial uncertainty. A mixed-method approach, combining structural equation modelling (SEM) and qualitative interviews, was employed to evaluate the relationships between KM, M&A, and innovation networks. SEM facilitated the assessment of hypothesized connections and mediation effects, while interviews with key stakeholders provided qualitative insights into the practical nuances of network interactions and strategies in mature firms. The study finds that KM practices, such as effective planning and knowledge acquisition, alongside M&A networks, collectively enhance the effectiveness of innovation networks. While KM promotes operational and strategic alignment, M&A networks support stakeholder decision-making, thus reinforcing firm operations. Absorptive capacity (AC) significantly mediates the relationship between KM, M&A networks, and innovation network effectiveness. However, entrepreneurial uncertainty diminishes the effectiveness of KM and M&A networks but simultaneously enhances innovation networks' outcomes, underscoring mature firms' adaptability in uncertain environments. This research deepens the understanding of innovation networks in mature entrepreneurial firms by applying the Knowledge-Based View (KBV) framework, highlighting the strategic role of KM and M&A networks. It offers new insights into how mature firms in emerging economies can leverage knowledge assets for sustained innovation and competitive advantage. The findings provide implications for practice and policy, suggesting that mature firms strategically manage KM and M&A activities to enhance innovation networks, even under varying levels of entrepreneurial uncertainty.
Cristiano Manetti da Cruz, Mercia Pandolfo Provin, Ana Laura de Sene Amâncio Zara
Objectives: To identify expenses with the purchase of medicines and supplies by the Municipal Health Department of Canguçu/RS, through legal proceedings, from 2017 to 2021. Methods: It is a quantitative, descriptive, and retrospective study, using the docu-ment analysis technique. Secondary data on public costs, available on the Transparency Portal, were used. The amounts spent and the origins of the resources used for the acqui-sition of these drugs were analyzed. Results: There was an increase of 297.93% in spen-ding on legal proceedings for the acquisition of medicines and pharmaceutical supplies through judicial blockades. Of these, more than 76% refer to antineoplastic medications. The basic care budget increased by 132.41% in this period and the costs of pharmaceu-tical assistance almost doubled from R$ 854,248.86, in 2017, to R$ 1,524,871.92, in 2021, with a significant increase during the pandemic period. Comparing the expen-diture on purchasing medicines through blockages by court permits in 2021 and the amount spent on pharmaceutical assistance in the same period, it is noted that the cost is very similar, but a small portion of the population is served through judicialization. Conclusions: There was a considerable increase in spending on purchasing medicines due to court decisions. The Municipal Health Department is obliged to acquire medicines that do not belong to the Municipal Medication List, through judicial blocking of public accounts, because the government of the State of Rio Grande do Sul does not send these medicines to users with approved lawsuits.
Pharmacy and materia medica, Pharmaceutical industry
Using a comprehensive matched employer-employee dataset for U.S. financial advisers from 2008 to 2018, we revisit established evidence on labor market penalties following financial misconduct. Prior studies report that female advisers are 20% more likely to exit their firms following misconduct and that similar disparities exist for non-white advisers. However, by disaggregating misconduct into distinct disclosure events - differentiating those that nearly always trigger job terminations from those that do not - we show that the apparent gender gap vanishes, while significant racial disparities persist. Specifically, non-white advisers face approximately 24% higher job separation rates than their white counterparts. Robustness checks confirm these findings across alternative specifications, suggesting that race-based differential treatment in the labor market is a distinct phenomenon warranting further investigation.
Recent advances in remote sensing technology have made submeter resolution imagery increasingly accessible, offering remarkable detail for fine-grained land cover analysis. However, its full potential remains underutilized - particularly for large-scale land cover mapping - due to the lack of sufficient, high-quality annotated datasets. Existing labels are typically derived from pre-existing products or manual annotation, which are often unreliable or prohibitively expensive, particularly given the rich visual detail and massive data volumes of submeter imagery. Inspired by the spatial autocorrelation principle, which suggests that objects of the same class tend to co-occur with similar visual features in local neighborhoods, we propose the Mask Clustering-based Annotation Engine (MCAE), which treats semantically consistent mask groups as the minimal annotating units to enable efficient, simultaneous annotation of multiple instances. It significantly improves annotation efficiency by one to two orders of magnitude, while preserving label quality, semantic diversity, and spatial representativeness. With MCAE, we build a high-quality annotated dataset of about 14 billion labeled pixels, referred to as HiCity-LC, which supports the generation of city-scale land cover maps across five major Chinese cities with classification accuracies above 85%. It is the first publicly available submeter resolution city-level land cover benchmark, highlighting the scalability and practical utility of MCAE for large-scale, submeter resolution mapping. The dataset is available at https://github.com/chenhaocs/MCAE
Autonomous landing on sloped terrain poses significant challenges for small, lightweight spacecraft, such as rotorcraft and landers. These vehicles have limited processing capability and payload capacity, which makes advanced deep learning methods and heavy sensors impractical. Flying insects, such as bees, achieve remarkable landings with minimal neural and sensory resources, relying heavily on optical flow. By regulating flow divergence, a measure of vertical velocity divided by height, they perform smooth landings in which velocity and height decay exponentially together. However, adapting this bio-inspired strategy for spacecraft landings on sloped terrain presents two key challenges: global flow-divergence estimates obscure terrain inclination, and the nonlinear nature of divergence-based control can lead to instability when using conventional controllers. This paper proposes a nonlinear control strategy that leverages two distinct local flow divergence estimates to regulate both thrust and attitude during vertical landings. The control law is formulated based on Incremental Nonlinear Dynamic Inversion to handle the nonlinear flow divergence. The thrust control ensures a smooth vertical descent by keeping a constant average of the local flow divergence estimates, while the attitude control aligns the vehicle with the inclined surface at touchdown by exploiting their difference. The approach is evaluated in numerical simulations using a simplified 2D spacecraft model across varying slopes and divergence setpoints. Results show that regulating the average divergence yields stable landings with exponential decay of velocity and height, and using the divergence difference enables effective alignment with inclined terrain. Overall, the method offers a robust, low-resource landing strategy that enhances the feasibility of autonomous planetary missions with small spacecraft.
Dante Ayaviri Nina, Gabith Quispe Fernández, Alba Isabel Maldonado Núñez
et al.
Los sistemas productivos, en el contexto rural, adquieren una importancia desde la perspectiva social y económica; su abordaje como un fenómeno de estudio permite observar e identificar debilidades y oportunidades en el accionar de la actividad productiva local. Así, el sistema productivo del cantón Guano en Ecuador es un conjunto estructurado de actividades agrícolas, pecuarias y, en menor proporción, industrial. La investigación pretende determinar las estrategias de generación de unidades de negocios en la actividad productiva rural del cantón Guano, se apoya en un método de investigación no experimental, de tipo descriptivo, y asume un enfoque cualitativo y cuantitativo. La muestra fue de 244 productores de una población de 21 851. Para la obtención de datos, se aplicó una encuesta con preguntas de tipo dicotómica, estructurada y de escala de Likert. Los resultados reflejan que la organización familiar, la inversión y los incentivos al sector productivo rural son las estrategias que contribuyen de forma significativa en el establecimiento de unidades productivas. En consecuencia, es relevante la importancia de las unidades productivas en el desarrollo rural del cantón Guano.
Economics as a science, Economic history and conditions
The transition of agriculture to recovery is only possible with large-scale and high-quality financial support. Currently, the model of development of the national agrarian sphere is focused mainly on the extensive use of available resources to increase the volume of production of the maximum raw component of agricultural products to maximize profits in the short term and, accordingly, attracting investments aimed mainly at replenishing working capital and simple reproduction of production capacities, exhausts itself in terms of environmental and social consequences and the long run can lead to negative economic results. The traditional sources of financial support for the functioning of the agrarian sphere are state funding, credit resources, and investments, which become more inaccessible under martial law. That is why conducting an economic diagnosis of the development of the agrarian sphere during martial law and the formation of management tasks is quite relevant. The article aims to carry out an economic diagnosis of the development of the agrarian sphere and the formation of management tasks in martial law conditions. An economic diagnosis of the development of the agrarian sphere was carried out, and the task of managing it in martial law conditions was formed. An analysis of investment support for developing the agrarian sphere was carried out across Ukraine according to indicators of the concentration of investments (calculated for one labor and performed per 1 ha of cultivated land) as the primary tool for recovery in martial law conditions. Regional investment leaders have been identified, including in 2021 Vinnytsia (3,139.7 million UAH), Kyiv (4,609.6 million UAH), Poltava (3,175.9 million UAH), Kirovohrad (3,629 million UAH), Chernihiv (3,081.6) million UAH) and Cherkasy (2952.2 million UAH) region. Conclusions. It has been proven that the solution to the problem of the modern restoration of the agrarian sphere requires supplementing the Comprehensive Strategy for the Development of Agriculture with functional and resource strategies that contribute to the implementation of strategic priorities, as well as a more detailed structuring of goals, tasks, resources, and executors across industries and regions. Keywords: economic diagnosis, agrarian sphere, martial law, sources of financing, management tasks.
Introduction/Main Objectives: The study proposed is written based on the results of quantitative research and the analysis of the theory and practice of leadership. The study's main objective is to determine the essential traits of a leader for effective interaction with team members. Background Problems: Most research on this topic chose a leader's traits based on analyzing literary sources rather than on empirical research. Novelty: The traits for the most effective collaboration between leader and team members were chosen by potential and actual members of the leader's team, namely students and teachers of the University. Research Methods: We conducted a questionnaire survey of 103 teachers and 421 Bogomolets National Medical University (Kyiv) students. The statistical analysis was carried out using Wald Test. Finding/Results: The research confirmed that both respondent categories admitted the importance of all leadership traits. At the same time, such traits as passion, effectiveness, self-confidence, determination, and ability to take risks appeared to be more significant for the students than for the teachers. The teachers ranked such a trait as decency higher than the students did. Also, such issues as the importance of organizational culture, ethical aspects of leadership, and the most effective leadership style for productive interaction with team members were examined. Conclusion: This study proposed complex recommendations for creating the most productive model of the interaction between the leader and team members based on the data obtained.
The article presents the factors of the international policy of publication and provision of school textbooks at the national, regional and local levels in the context of modern requirements for the quality of education. Such research methods as analytical review, comparison, analysis, generalization, interpretation, synthesis were used. An analysis of existing problems and possible ways of improving the quality and objectivity of the system of textbook provision was carried out. The scientific and methodological approaches and practical recommendations of international organizations on the formation of textbook publishing policy, the role of central authorities, local self-government, private organizations, the public and parents of students in the financing, development and distribution of textbooks are considered. The peculiarities of textbook publishing in countries working with the system of centralized state publication, state approval of a list of textbooks by choice, mixed system and open market are analyzed. The similarities and differences of the main changes over the last 20-30 years in the position of countries regarding textbooks (with an emphasis on leading Asian countries) are identified in terms of types of policies, processes of approval and control of production, distribution of textbooks, priorities in providing students with textbooks. The analysis confirmed that in most countries there is a change in the role of central and local self-government, the private sector, parents and the public in the development and distribution of textbooks, as well as the interaction of subjects of educational book publishing. Recommendations for improving the process of textbook publishing have been developed based on the experience of the outlined work in the countries of the world.
Valeriy Shevchenko, Daria Taniushkina, Aleksander Lukashevich
et al.
The United Nations has identified improving food security and reducing hunger as essential components of its sustainable development goals. As of 2021, approximately 828 million people worldwide are experiencing hunger and malnutrition, with numerous fatalities reported. Climate change significantly impacts agricultural land suitability, potentially leading to severe food shortages and subsequent social and political conflicts. To address this pressing issue, we have developed a machine learning-based approach to predict the risk of substantial land suitability degradation and changes in irrigation patterns. Our study focuses on Central Eurasia, a region burdened with economic and social challenges. This study represents a pioneering effort in utilizing machine learning methods to assess the impact of climate change on agricultural land suitability under various carbon emissions scenarios. Through comprehensive feature importance analysis, we unveil specific climate and terrain characteristics that exert influence on land suitability. Our approach achieves remarkable accuracy, offering policymakers invaluable insights to facilitate informed decisions aimed at averting a humanitarian crisis, including strategies such as the provision of additional water and fertilizers. This research underscores the tremendous potential of machine learning in addressing global challenges, with a particular emphasis on mitigating hunger and malnutrition.
The sustainable development of the aquaculture industry is of great significance for national food security within the context of increasing consumer demand, scarce land resources, and continuous ecological and environmental deterioration. China is a major shrimp farming country. It is crucial to investigate the spatiotemporal variations in the characteristics of shrimp aquaculture for the stability and sustainable development of China’s shrimp aquaculture industry, as well as to explore an optimization strategy for the spatial layout of this industry. Existing research mainly focuses on the fluctuations in shrimp production and their influencing factors, while studies on the spatiotemporal variations of shrimp aquaculture and their influencing mechanisms are few. In this study, we analyzed the patterns of spatiotemporal variation in shrimp aquaculture in China and further explored their influencing factors using standard deviational ellipse and Geodetector, based on China’s shrimp aquaculture production data from 2003 to 2020. The results show that (1) there has been a steady upward trend in shrimp aquaculture production in China over the past 18 years, with a growth rate of 128% and an average annual growth rate of 5.2%; (2) the spatial distribution range of shrimp farms has expanded, showing a zonal distribution pattern from the northeast to southwest, and the center of the shrimp aquaculture industry has generally shifted southward; and (3) the level of development within the fishing industry, labor quantity, and per capita income are the main factors affecting the spatial distribution variability of shrimp aquaculture. The degree of influence of each different factor on spatial distribution of shrimp aquaculture varied temporally.
The agriculture of the Soviet Union, incorporated into the closed economy, significantly lagged behind the Western countries in terms of productivity and labor efficiency due to its extensive nature. Soviet mega-project – the development of virgin and fallow lands in the eastern regions of the country, was not trigger. The purpose of this project was to solve the problem of providing the population with bread. This article considers the underlying causes that led to the initially given vector of extensive development of the virgin agricultural space of Northern Kazakhstan, despite the colossal funds invested in the development of the steppe frontier. The article researches the post-Soviet institutional transformations in the agriculture of the republic, which affected, first of all, the agriculture of the grain belt. Used descriptive and research statistical tools made possible determination of the factors of the post-crisis transition of agricultural formations to the cultivation of industrial (oilseeds) crops as the most highly profitable in modern conditions. Our results showed a significant time and space dynamics of the structure of sown areas and a qualitative transformation of agriculture on the example of an integral part of the virgin frontier – North Kazakhstan region, as a result of the transition to an agrarian landscape system of land management in combination with the digitalization of the industry and the diversification of crops. Innovative and paternalistic measures of further mesoterritorial intensification of agriculture are proposed.
Olívia Prado Schiavon, Márcia Ramos May, Andréa Torres Barros Batinga de Mendonça
Purpose – The study aims to understand how dynamic capabilities (DCs) contribute to business model innovation (BMI) in sustainable family farming. The agrifood sector has been seeking solutions for the development of agroecological markets. Thus, the authors have analyzed the challenges imposed to innovation and sustainability strategic management and the value proposition to sustain the business over the years. Design/methodology/approach – Considering the complexity of organizations and through an exploratory multiple case study of initiatives identified in the Organic Fair of Curitiba’s Passeio Público, it was possible to analyze the evolution of the business models (BMs) and the fair itself. Furthermore, it was possible to identify the DCs within the influence of agroecosystem elements on the innovation development. Findings – Analyzing each case individually, the authors understood the different dimensions of the evolution of BMs considering the organizational complexity. The authors conclude that the balance between organizational practices and changes in the environment, engagement and learning plays a significant role in the developing competitive advantage. The same applies to the patterns that precede the development of DCs and BMs. Originality/value – The article investigates innovation in agroecological BMs from a dynamic capability perspective. The agroecological BM is a subject that is still little discussed in the literature. In addition, the authors chose a context that includes socioenvironmental aspects and a few specificities of family farming in Brazil.
Deep learning methods have been successfully applied to remote sensing problems for several years. Among these methods, CNN based models have high accuracy in solving the land classification problem using satellite or aerial images. Although these models have high accuracy, this generally comes with large memory size requirements. On the other hand, it is desirable to have small-sized models for applications, such as the ones implemented on unmanned aerial vehicles, with low memory space. Unfortunately, small-sized CNN models do not provide high accuracy as with their large-sized versions. In this study, we propose a novel method to improve the accuracy of CNN models, especially the ones with small size, by injecting traditional features to them. To test the effectiveness of the proposed method, we applied it to the CNN models SqueezeNet, MobileNetV2, ShuffleNetV2, VGG16, and ResNet50V2 having size 0.5 MB to 528 MB. We used the sample mean, gray level co-occurrence matrix features, Hu moments, local binary patterns, histogram of oriented gradients, and color invariants as traditional features for injection. We tested the proposed method on the EuroSAT dataset to perform land classification. Our experimental results show that the proposed method significantly improves the land classification accuracy especially when applied to small-sized CNN models.
We note that Gabber's rigidity theorem for the algebraic K-theory of henselian pairs also holds true for hermitian K-theory with respect to arbitrary form parameters.
Victor M. Ortega-Jimenez, Elio J. Challita, Baekgyeom Kim
et al.
Springtails (Collembola) have been traditionally portrayed as explosive jumpers with incipient directional takeoff and uncontrolled landing. However, for these collembolans who live near the water, such skills are crucial for evading a host of voracious aquatic and terrestrial predators. We discover that semiaquatic springtails Isotomurus retardatus can perform directional jumps, rapid aerial righting, and near-perfect landing on the water surface. They achieve these locomotive controls by adjusting their body attitude and impulse during takeoff, deforming their body in mid-air, and exploiting the hydrophilicity of their ventral tube, known as collophore. Experiments and mathematical modeling indicate that directional-impulse control during takeoff is driven by the collophores adhesion force, the body angle, and the stroke duration produced by their jumping organ, the furcula. In mid-air, springtails curve their bodies to form a U-shape pose, which leverages aerodynamic forces to right themselves in less than 20 ms, the fastest ever measured in animals. A stable equilibrium is facilitated by the water adhered to the collophore. Aerial righting was confirmed by placing springtails in a vertical wind tunnel and through physical models. Due to these aerial responses, springtails land on their ventral side 85% of the time while anchoring via the collophore on the water surface to avoid bouncing. We validated the springtail biophysical principles in a bioinspired jumping robot that reduces in-flight rotation and lands upright 75% of the time. Thus, contrary to common belief, these wingless hexapods can jump, skydive and land with outstanding control that can be fundamental for survival.
Sam Zhang, K. Hunter Wapman, Daniel B. Larremore
et al.
Faculty at prestigious institutions dominate scientific discourse, with the small proportion of researchers at elite universities producing a disproportionate share of all research publications. Environmental prestige is known to drive such epistemic disparity, but the mechanisms by which it causes increased faculty productivity remain unknown. Here we combine employment, publication, and federal survey data for 78,802 tenure-track faculty at 262 PhD-granting institutions in the American university system between 2008--2017 to show through multiple lines of evidence that the greater availability of funded graduate and postdoctoral labor at more prestigious institutions drives the environmental effect of prestige on productivity. In particular, we show that greater environmental prestige leads to larger faculty-led research groups, which drive higher faculty productivity, primarily in disciplines with research group collaboration norms. In contrast, we show that productivity does not increase substantially with prestige for either faculty papers published without group members, nor group members themselves. The disproportionate scientific productivity of elite researchers is thus largely explained by their substantial labor advantage, indicating a more limited role for prestige itself in predicting scientific contributions.
This paper studies the effects of legislation mandating the provision of workplace breastfeeding amenities on the labor force participation of women in the United States. Using both the American Community Survey and the Panel Study of Income Dynamics, in a staggered difference-in-differences framework, I find evidence that workplace breastfeeding legislation significantly increases the likelihood of female labor force participation (FLFP) across both datasets and multiple specifications, by at least 1.5 percentage points. The timing and magnitude of the post-law increases in FLFP differ across the two datasets. I bolster the analyses using the CDC's Infant Feeding Practices Survey and the Childhood and Adoption Supplement to the PSID, which further suggest an influence of the laws on breastfeeding women. Heterogeneity analysis indicates the presence of substantial treatment effect heterogeneity across subgroups, but the findings are specific to the separate datasets. Across both datasets, the legislation appears to be more effective in states where average pre-law FLFP was comparatively low. I also find evidence of a negative spillover effect, whereby women without children and women with older children may have reduced their LFP in response to the legislation.