Integration Efforts Research Articles

Regional economic integration in the Eurasian Economic Union: theory, lessons from the past and new opportunities

The article shows that the processes of world development initiate changes in various areas of international cooperation both at the global and regional levels. This is also happening within the framework of regional economic integration cooperation. The author proves that the modern transformation of integration processes has an impact on the development of the Eurasian Economic Union (EAEU). This process requires a comprehensive theoretical analysis and systematization. The purpose of the article is to analyze and evaluate integration processes in the EAEU. The scientific novelty of the article is the systematization of new phenomena and characteristics in regional economic integration in the world in the 21st century. The author also tries to formulate new tasks for the EAEU in building a progressive integration process. Another point of view, which the author substantiates in the article, is that the foundation for the development of integration in the EAEU should be taking into account ongoing global changes, previous experience of economic integration within the framework of the Council for Mutual Economic Assistance (Comecon) and the development of industrial cooperation between the EAEU countries and non-regional partners both in industry, and in agriculture, that means, in the real sectors of the economy. The author concludes that it is production cooperation in the real sectors of the economy in the EAEU that will ensure the necessary stability of both national economies and the progressive development of the integration process in the current conditions of the world economic process increased turbulence and the global system transformation. And since the EAEU faces such large-scale and vital tasks, then, according to the author, a reassessment and some redirection of integration efforts are required. It is on this basis that an adequate formation of new principles of financial cooperation in the EAEU is possible.

The Influence of European Identity on Integration Efforts

The EU's recurrent crises underline its complex and debated nature. Truly grasping its intricacies is key to understanding the tie between European identity and integration. Central to the discourse are questions on whether a shared European identity influences member selection or if the emphasis is on upholding democratic values. Academic discussions have often overlooked a holistic examination of integration processes, treating EU expansions as standalone events without delving deep into the relationship between integration and European identity. This paper posits that the absence of a unified European identity, and subsequently, citizens' disassociation from Europe and its political structures, steers the course of integration, potentially causing stagnation or progression. It seeks to unravel: the nature of EU expansion, the current meaning of European identity versus EU identity, and the influence of identity (or its absence) on integration. Concludingly, it suggests that the EU identity's role in integration is a balance between constructivism and rationalism. Support for the EU seems rooted in citizens' perceived overarching benefits, encompassing peace, democracy, human rights, and the rule of law.
 
 Received: 05 May 2023 / Accepted: 21 June 2023 / Published: 23 July 2023

What Can We Learn about Migration and Migrants from Southern Scholars? A Brief Discussion

Within the United States, there is a dominant focus on international migration and international migrants' assimilation and integration efforts, along with separate conversations on intersecting structures that marginalize non‐white migrants and citizens. Trafficking and refugee studies are relatively small and distinct fields that mostly remain outside dominant scholarly conversations on migration, especially in sociology. This essay presents one strand of conversation by scholars in the global South who center forced migration and conceptualize all migrants, internal to international, as part of one model. The discussions by the Calcutta Research group open up complex histories, social inequalities, and the need to discard the colonial logics embedded in the study of migration and migrants.

Morphological and DNA-based description of Trichophoromyia peixotoi n. sp. (Diptera: Psychodidae), a new sand fly species from the Brazilian Amazon

Background Phlebotomine sand flies of the genus Trichophoromyia Barretto, 1962 are of great relevance to public health as vectors of Leishmania protozoans. A new phlebotomine species named Trichophoromyia peixotoi n. sp. is here described based on both male morphology and COI DNA barcodes.MethodsThe sand fly specimens were collected in the Parque Nacional da Amazônia (PNA), situated in the municipality of Itaituba, state of Pará, Brazil. Morphological description was done based on 10 male specimens. Five specimens were DNA barcoded for the COI gene.ResultsThe morphological and molecular analyses allowed the delimitation of this new species from others of Trichophoromyia. Trichophoromyia peixotoi n. sp. is closely related to other species with aedeagal ducts > 4 times the length of the sperm pump, from which it may be distinguished by the gonocoxite bristles and paramere shape.ConclusionsThe description of T. peixotoi n. sp. brings the number of species of Trichophoromyia to 45, including 24 for Brazil. The integrative taxonomy effort through the analysis of COI barcodes proved to be effective in the species delimitation of some Trichophoromyia spp.Graphical

Valveless On-Chip Aliquoting for Molecular Diagnosis.

The detection of nucleic acids as specific markers of infectious diseases is commonly implemented in molecular biology laboratories. The translation of these benchtop assays to a lab-on-a-chip format demands huge efforts of integration and automation. The present work is motivated by a strong requirement often posed by molecular assays that combine isothermal amplification and CRISPR/Cas-based detection: after amplification, a 2-8 microliter aliquot of the reaction products must be taken for the subsequent reaction. In order to fulfill this technical problem, we have designed and prototyped a microfluidic device that is able to meter and aliquot in the required range during the stepped assay. The operation is achieved by integrating a porous material that retains the desired amount of liquid after removing the excess reaction products, an innovative solution that avoids valving and external actuation. The prototypes were calibrated and experimentally tested to demonstrate the overall performance (general fluidics, metering, aliquoting, mixing and reaction). The proposed aliquoting method is fully compatible with additional functions, such as sample concentration or reagent storage, and could be further employed in alternative applications beyond molecular diagnosis.

CANLay: A Network Virtualized Testbed for Vehicle Systems – Improving System Integration and Verification Efforts

AbstractIntegration and Verification activities for cyber physical system networks is a complex task requiring multiple iterations of hardware and software configurations and topologies. Such testing is crucial for the system's functionality, safety, and security during operation. A proficient approach to swiftly generate various testing setups is to employ a software‐defined system, vehicle in this case, and encapsulate in‐vehicle networking messages in a switched packet network, like Ethernet. This paper introduces CANLay, the networking foundation of a software‐defined vehicle that serves as a virtualized test bed for in‐vehicle network examination. CANLay carries controller area network data and sensor signals originating from vehicle control units and simulator systems. It functions as a communication medium between a vehicle simulator and real‐world electronic control units situated on distinct network segments. CANLay's efficacy is demonstrated for heavy vehicle network performance testing in a versatile digital engineering environment, facilitating streamlined system integration and verification efforts.

An integrative effort: Bridging motivational intensity theory and recent neurocomputational and neuronal models of effort and control allocation.

An increasing number of cognitive, neurobiological, and computational models have been proposed in the last decade, seeking to explain how humans allocate physical or cognitive effort. Most models share conceptual similarities with motivational intensity theory (MIT), an influential classic psychological theory of motivation. Yet, little effort has been made to integrate such models, which remain confined within the explanatory level for which they were developed, that is, psychological, computational, neurobiological, and neuronal. In this critical review, we derive novel analyses of three recent computational and neuronal models of effort allocation-the expected value of control theory, the reinforcement meta-learner (RML) model, and the neuronal model of attentional effort-and establish a formal relationship between these models and MIT. Our analyses reveal striking similarities between predictions made by these models, with a shared key tenet: a nonmonotonic relationship between perceived task difficulty and effort, following a sawtooth or inverted U shape. In addition, the models converge on the proposition that the dorsal anterior cingulate cortex may be responsible for determining the allocation of effort and cognitive control. We conclude by discussing the distinct contributions and strengths of each theory toward understanding neurocomputational processes of effort allocation. Finally, we highlight the necessity for a unified understanding of effort allocation, by drawing novel connections between different theorizing of adaptive effort allocation as described by the presented models. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Research Activities at Faculty of Chemical Technology, Hanoi University of Industry ‐ 20 Years of Growth and Development

AbstractHanoi University of Industry, with a 125‐year history of construction and development, is the leading institution for training and applied scientific research in Vietnam. It offers a wide range of disciplines, types, and levels of education to produce high‐quality human resources for the country's industrialization, national modernization, and international integration efforts. The university currently boasts over 1,500 staff and lecturers, three campuses covering nearly 50 hectares, and a student population of more than 30,000. Hanoi University of Industry provides multidisciplinary training, providing high‐quality human resources for society. In which, the Faculty of Chemical Technology was established on March 1, 2003, in 20 years of construction and development, the faculty has constantly grown, annually providing the society with many high‐quality human resources, with many fields of study diverse, learning, training: Chemical engineering technology, Environmental engineering technology, Food technology and Pharmaceutical chemistry. Besides, the faculty, students and students of the faculty have made great efforts in training, studying and doing scientific research, achieving many excellent achievements.

Integrating Artificial Intelligence and Wearable IoT System in Long-Term Care Environments

With the rapid advancement of information and communication technology (ICT), big data, and artificial intelligence (AI), intelligent healthcare systems have emerged, including the integration of healthcare systems with capital, the introduction of healthcare systems into long-term care institutions, and the integration of measurement data for care or exposure. These systems provide comprehensive communication and home exposure reports and enable the involvement of rehabilitation specialists and other experts. Silver technology enables the realization of health management in long-term care services, workplace care, and health applications, facilitating disease prevention and control, improving disease management, reducing home isolation, alleviating family burden in terms of nursing, and promoting health and disease control. Research and development efforts in forward-looking cross-domain precision health technology, system construction, testing, and integration are carried out. This integrated project consists of two main components. The Integrated Intelligent Long-Term Care Service Management System focuses on building a personalized care service system for the elderly, encompassing health, nutrition, diet, and health education aspects. The Wearable Internet of Things Care System primarily supports the development of portable physiological signal detection devices and electronic fences.

Sustaining the Integration of Social Objectives Over Time: A Case-Based Analysis of Access to Medicine in the Pharmaceutical Industry

Companies increasingly seek to strategically integrate social objectives in commercial activities to address societal challenges, yet little is known about how companies can sustain such a commitment over time. To address this question, we conduct a case-based, abductive study of two pharmaceutical companies widely considered industry leaders in facilitating access to medicine over a 20-year period (2000–2019). We identify product and operation-level integration as distinct types of integration efforts enacted by these companies. Tracing the intraorganizational dynamics associated with these efforts, we theorize that sustained integration is contingent on companies’ ability to respond to and address the challenges specific to product and operation-level integration. The theoretical framework we develop contributes to an emerging debate on the potential of companies to make progress on societal challenges by strategically integrating social objectives, including but not limited to those related to global health.

Symbolic knowledge injection meets intelligent agents: QoS metrics and experiments

Bridging intelligent symbolic agents and sub-symbolic predictors is a long-standing research goal in AI. Among the recent integration efforts, symbolic knowledge injection (SKI) proposes algorithms aimed at steering sub-symbolic predictors’ learning towards compliance w.r.t. pre-existing symbolic knowledge bases. However, state-of-the-art contributions about SKI mostly tackle injection from a foundational perspective, often focussing solely on improving the predictive performance of the sub-symbolic predictors undergoing injection. Technical contributions, in turn, are tailored on individual methods/experiments and therefore poorly interoperable with agent technologies as well as among each others. Intelligent agents may exploit SKI to serve many purposes other than predictive performance alone—provided that, of course, adequate technological support exists: for instance, SKI may allow agents to tune computational, energetic, or data requirements of sub-symbolic predictors. Given that different algorithms may exist to serve all those many purposes, some criteria for algorithm selection as well as a suitable technology should be available to let agents dynamically select and exploit the most suitable algorithm for the problem at hand. Along this line, in this work we design a set of quality-of-service (QoS) metrics for SKI, and a general-purpose software API to enable their application to various SKI algorithms—namely, platform for symbolic knowledge injection (PSyKI). We provide an abstract formulation of four QoS metrics for SKI, and describe the design of PSyKI according to a software engineering perspective. Then we discuss how our QoS metrics are supported by PSyKI. Finally, we demonstrate the effectiveness of both our QoS metrics and PSyKI via a number of experiments, where SKI is both applied and assessed via our proposed API. Our empirical analysis demonstrates both the soundness of our proposed metrics and the versatility of PSyKI as the first software tool supporting the application, interchange, and numerical assessment of SKI techniques. To the best of our knowledge, our proposals represent the first attempt to introduce QoS metrics for SKI, and the software tools enabling their practical exploitation for both human and computational agents. In particular, our contributions could be exploited to automate and/or compare the manifold SKI algorithms from the state of the art. Hence moving a concrete step forward the engineering of efficient, robust, and trustworthy software applications that integrate symbolic agents and sub-symbolic predictors.

Irrigation in the Earth system

Irrigation accounts for ~70% of global freshwater withdrawals and ~90% of consumptive water use, driving myriad Earth system impacts. In this Review, we summarize how irrigation currently impacts key components of the Earth system. Estimates suggest that more than 3.6 million km2 of currently irrigated land, with hot spots in the intensively cultivated US High Plains, California Central Valley, Indo-Gangetic Basin and northern China. Process-based models estimate that ~2,700 ± 540 km3 irrigation water is withdrawn globally each year, broadly consistent with country-reported values despite these estimates embedding substantial uncertainties. Expansive irrigation has modified surface energy balance and biogeochemical cycling. A shift from sensible to latent heat fluxes, and resulting land–atmosphere feedbacks, generally reduce regional growing season surface temperatures by ~1–3 °C. Irrigation can ameliorate temperature extremes in some regions, but conversely exacerbates moist heat stress. Modelled precipitation responses are more varied, with some intensive cropping regions exhibiting suppressed local precipitation but enhanced precipitation downstream owing to atmospheric circulation interactions. Additionally, irrigation could enhance cropland carbon uptake; however, it can also contribute to elevated methane fluxes in rice systems and mobilize nitrogen loading to groundwater. Cross-disciplinary, integrative research efforts can help advance understanding of these irrigation–Earth system interactions, and identify and reduce uncertainties, biases and limitations. Irrigation accounts for a substantial proportion of global water usage and can have biophysical and biogeochemical impacts on Earth systems. This Review outlines key irrigation–Earth system interactions, and discusses the effect of future climate and socioeconomic changes on irrigation patterns and their interaction.

Context matters: Secondary science teachers' integration of process‐based, unplugged computational thinking into science curriculum

AbstractThere is growing recognition in the education community that the problem‐solving practices that comprise computational thinking (CT) are a fundamental component of both life and work in the twenty‐first century. Historically, opportunities to learn CT have been confined to computer science (CS) and elective courses that lack racial, ethnic, and gender diversity. To combat this inequity, a number of scholars have proposed integrating CT practices into core curriculum——especially science, technology, engineering, and math curriculum. Successfully achieving the goal of integrated CT, however, depends on frameworks to guide integration, professional development for teachers, exemplars of successful integrations, and identifications of the barriers teachers encounter. Research pertaining to each of these areas is in its infancy. This study addresses these needs through a collective case study of 10 secondary science teachers' implementations of a novel, process‐based, unplugged approach to CT/science integration and the factors that supported or hindered their CT/science integration efforts. The results of this work reveal that: (1) an unplugged and process‐based approach to CT/science integration shows promise as a vehicle for infusing CT into diverse science classrooms; (2) educators' teaching context exerts a strong influence on their CT‐integration efforts and persistence; and (3) special attention is needed to support teachers in their CT/science integrations including algorithm creation. This study also demonstrates the utility of the Fraillon et al.'s CT framework as a guide for CT/science integration efforts and sheds light on the unique affordances of unplugged strategies for implementing CT‐integrated science curricula.

Light‐touch integration: A study on cross‐border acquisitions by emerging market multinationals

AbstractResearch SummaryEmerging‐market multinational enterprises (EMNEs) are known for their “light‐touch” integration after cross‐border acquisitions. That is, compared with their developed‐country counterparts, EMNEs are more likely to retain the top management team (TMT) of the target firms. In this paper, we argue that this difference in retention rate can be explained by country, cohort, and firm effects. While the literature mostly associates EMNEs with where they are from (country effect), EMNEs are also new to cross‐border acquisitions (firm effect) and among the first in their peers to venture abroad (cohort effect). Analysis on a sample of 1862 absorption‐type cross‐border acquisitions supports our hypotheses that while the country effect persists, the difference in retention rate narrows significantly as EMNEs and their peers gain more relevant cross‐border acquisition experience.Managerial SummaryThe retention of top management team in target firms is a critical aspect of post‐acquisition integration (PAI). In this study, we examine the reasons behind the curious observation that, compared with acquirers from developed countries, multinational enterprises from emerging markets (EMNEs) are more likely to keep the target firm TMT intact, even in deals where extensive integration is in line with the overall acquisition objectives. Our analyses show that the legitimacy constraints associated with EMNEs' less developed home countries indeed present initial challenges to their integration efforts. However, these differences narrow significantly as EMNEs and their peers accumulate more experience in similar cross‐border acquisitions. This study highlights the dynamic nature of PAI strategies and the large variance among firms beneath the “EMNE” label.

Actualizing Indigenous Knowledge in tribal wildlife management: basic preconditions

AbstractIndigenous Knowledge (IK) is increasingly involved in the contemporary management of natural resources. Tribal wildlife management programs in the United States may be uniquely positioned to effectively and ethically integrate their IK. While a narrow focus on the body of IK and a particular management activity may suffice for project‐level integration efforts, herein we consider how IK integration at the programmatic level may be best supported. We propose a holistic conceptual framework of preconditions including sovereignty, the North American Model management, funding, cultural resources, stakeholder support, and programmatic leadership. We assess the current status and common challenges with each precondition and illustrate their potential roles for a more lasting and pervasive integration of IK into tribal wildlife management programs.

A neuro-symbolic system over knowledge graphs for link prediction

Neuro-Symbolic Artificial Intelligence (AI) focuses on integrating symbolic and sub-symbolic systems to enhance the performance and explainability of predictive models. Symbolic and sub-symbolic approaches differ fundamentally in how they represent data and make use of data features to reach conclusions. Neuro-symbolic systems have recently received significant attention in the scientific community. However, despite efforts in neural-symbolic integration, symbolic processing can still be better exploited, mainly when these hybrid approaches are defined on top of knowledge graphs. This work is built on the statement that knowledge graphs can naturally represent the convergence between data and their contextual meaning (i.e., knowledge). We propose a hybrid system that resorts to symbolic reasoning, expressed as a deductive database, to augment the contextual meaning of entities in a knowledge graph, thus, improving the performance of link prediction implemented using knowledge graph embedding (KGE) models. An entity context is defined as the ego network of the entity in a knowledge graph. Given a link prediction task, the proposed approach deduces new RDF triples in the ego networks of the entities corresponding to the heads and tails of the prediction task on the knowledge graph (KG). Since knowledge graphs may be incomplete and sparse, the facts deduced by the symbolic system not only reduce sparsity but also make explicit meaningful relations among the entities that compose an entity ego network. As a proof of concept, our approach is applied over a KG for lung cancer to predict treatment effectiveness. The empirical results put the deduction power of deductive databases into perspective. They indicate that making explicit deduced relationships in the ego networks empowers all the studied KGE models to generate more accurate links.

Implementation and Testing of Radar Data Assimilation Capabilities Within the Joint Effort for Data Assimilation Integration Framework With Ensemble Transformation Kalman Filter Coupled With FV3‐LAM Model

AbstractCapabilities to directly assimilate radar data are implemented within the local ensemble transform Kalman filter (LETKF) and the gain‐form LETKF (LGETKF) algorithms of the Joint Effort for Data assimilation Integration (JEDI) system. The capabilities are evaluated for the analysis and forecast of a severe convection case of 20 May 2019 in the Southern Great Plains using the limited area model version of the FV3 dynamical core (FV3‐LAM) from a recent release for Short‐Range Weather Application (SRW App). The LETKF and LGETKF implementations are shown to produce analyses and short‐range forecasts comparable to those using the ensemble square‐root Kalman Filter (EnSRF) within the Gridpoint Statistical Interpolation (GSI) framework used by current NCEP operational models. In addition, LGETKF retaining only 60% variances for model‐space vertical localization performs similarly to LGETKF retaining 99% of variance and LETKF using observation error‐based vertical localization. JEDI LETKF shows better parallel scalability than LGETKF and GSI EnSRF.

Association Between Clinical, Demographic Factors, and Substance Use Among Young Adult Survivors of Childhood Cancer

Purpose of the study: Childhood cancer survivors are at risk for late effects related to their cancer treatment, but little is known about clinical, and demographic associated with substance use behaviors. The purpose of this study is to examine the associations between substance use behaviors (tobacco, marijuana, e-cigarette, and alcohol) and cancer-related follow-up care, treatment intensity, late effects, depressive symptoms, self-rated health, race/ethnicity, and neighborhood socioeconomic status (nSES). Methods: Participants were from the Project Forward cohort, a population-based study of young adult survivors of childhood cancer. Participants (N = 1,166, Mage = 25.1 years) were recruited through the Los Angeles Cancer Surveillance Program (Cancer Registry covering Los Angeles County, California). Multivariate path analyses were performed with substance use as the outcome variables and clinical and demographic factors as independent variables. Covariates included current age and sex. Results: Substance use was positively associated with being at risk for clinical depression, and inversely associated with cancer-related follow-up care, female sex, current age, Hispanic ethnicity, treatment intensity, and self-rated health. Neighborhood SES was inversely associated with tobacco use, while being positively associated with binge drinking and e-cigarette use. Conclusions: The results highlight the interrelationship among the clinical and demographic variables and their associations with different substance use. Findings support effective interventions targeting integrative care and health promotion efforts for polysubstance use behavior among CCS. This will help improve long-term outcomes and mitigate the risk for early morbidity.

Application of Model-Based Systems Engineering for the Integration of Electric Engines in Electrified Aircraft

The objective of green, carbon-neutral flights is propelling the innovation of newer propulsion systems. With this increased development of an interdisciplinary form of propulsion for aircraft, the integration burdens and efforts intensify. In literature, it is estimated that it takes 10-15 years to design and develop an aircraft. The expected date of entry for any hybrid electric aircraft is 2035-2040. Any innovation and effort to cut this time by any degree should be explored and analysed. One of the techniques that have the potential to help fast-track the research and development of interdisciplinary systems is Model-based System Engineering (MBSE). Various studies have shown the benefit of employing a model-based design strategy. The focus case study relates to the integration of the electric machine and the propeller, along with related sub-systems. For Hybrid Electric Propulsion (HEP), the electric machine and propeller need to be integrated and their interaction to be analysed. MBSE is proposed as a methodology that would help streamline the process of design and integration of the two systems. This study documents the exploration of connecting MBSE with current simulation and modelling of sub-systems in order to ensure the fulfilment of stakeholder needs and full system effectiveness. This paper establishes the research problem, and the approach to be pursued, and gives notice of first developments and expected follow-up work.

A survey of pharmacists in integrated care: Benefits, barriers, and facilitators of integration.

While models for pharmacist integration within primary care exist, less is known about their integration into primary care practices with already-embedded behavioral health. An exploratory survey was conducted to characterize examples of pharmacist integration into primary care systems providing dual behavioral and medical care. An electronic survey distributed through email listservs of four national organizations assessed pharmacists' background, training, practice setting and roles, and benefits and challenges of integration. Data were analyzed using descriptive statistics. A chi-square test was used to evaluate relationships between degree of integration and barriers. The survey was completed by 119 pharmacists in primary care practices with integrated behavioral health. Pharmacists reported performing a variety of roles impacting quality of care, access to care, provider and patient satisfaction, and, to a lesser extent, care costs. Barriers to integration were common, including cost, underutilization, lack of role clarity for pharmacists, and space constraints. Mode of communication and workspace location were associated with pharmacist utilization and role clarity. Pharmacists in primary care practices with integrated behavioral health reported improving care quality and access and supporting patient and provider satisfaction. Future work should survey others to confirm pharmacist self-perceptions. While fiscal justification of pharmacists on integrated teams remains challenging, utilizing shared workspace and creating mechanisms for in-person communication facilitate integration efforts by mitigating other barriers such as underutilization and lack of role clarity. (PsycInfo Database Record (c) 2022 APA, all rights reserved).