Aspects Of Distribution Research Articles

Large donor CRISPR for whole-CDS replacement of cell adhesion molecule LRRTM2.

The cell adhesion molecule Leucine-Rich Repeat Transmembrane neuronal protein 2 (LRRTM2) is crucial for synapse development and function. However, our understanding of its endogenous trafficking has been limited due to difficulties in manipulating its coding sequence (CDS) using standard genome editing techniques. Instead, we replaced the entire LRRTM2 CDS by adapting a two-guide CRISPR knock-in method, enabling complete control of LRRTM2. In primary rat hippocampal cultures dissociated from embryos of both sexes, N-terminally tagged, endogenous LRRTM2 was found in 80% of synapses, and synaptic LRRTM2 content correlated with PSD-95 and AMPAR levels. LRRTM2 was also enriched with AMPARs outside synapses, demonstrating the sensitivity of this method to detect relevant new biology. Finally, we leveraged total genomic control to increase the synaptic levels of LRRTM2 via simultaneous mutation of its C-terminal domain, which did not correspondingly increase AMPAR enrichment. The coding region of thousands of genes span lengths suitable for whole-CDS replacement, suggesting this simple approach will enable straightforward structure-function analysis in neurons.Significance Statement Synaptic cell adhesion molecules are transmembrane proteins vital for neurotransmission, and their genes are frequently linked to disease. Mechanistic studies are challenging, however, because overexpression alters their protein trafficking and perturbs neuronal function, yet traditional gene-editing techniques typically permit manipulation at just single sites. Here, we replaced the entire coding sequence (CDS) of the critical adhesion molecule Leucine-Rich Repeat Transmembrane protein 2 (LRRTM2) with a freely editable custom donor sequence, and made the approach even more versatile through introduction of knock-in-dependent cell markers. Using whole-CDS replacement, we discover new aspects of LRRTM2 subcellular distribution and test its role in regulating synaptic proteins. The approach should be suited to structure-function analysis of many other neuronal proteins in their endogenous genetic locus.

Examining health equity in Nepal’s climate change and health policies through the lens of environmental justice: insights from a content analysis

ABSTRACT Background Climate change presents a multifaceted challenge with unequal health implications, particularly for vulnerable populations with limited adaptive capacity. Socioeconomic factors are intricately linked with environmental health outcomes and environmental factors significantly exacerbate existing health inequities. Health equity as a goal of environmental justice can address these issues. Objective To examine the integration of health equity within climate change and health policy documents in Nepal. Methods Using a qualitative content analysis approach based on Schlosberg’s framework of environmental justice, we analyzed the coverage of health equity considerations in climate and health policies, assessing aspects of distribution, recognition, and participation. Results Twenty-one national-level policies, strategies, and plans/guidelines on climate change and health were analyzed. Nepal’s policy documents lack clear definitions of health equity in relation to climate change, and related terms are used inconsistently. Health vulnerability is often addressed broadly rather than specifically. Health equity-related statements from environmental justice viewpoint vary across sectors. Many documents emphasize equitable distribution of resources and benefits, with participation in decision-making processes being the least discussed. Conclusions In Nepal, lack of shared understanding of health equity across sectors hinders coordinated policy efforts. There is an urgent need to expand climate change responses to consider specific health vulnerabilities. By positioning health equity as a key element of environmental justice, this study provides a broader perspective on climate change-related health equity that could encourage collaborative action between the environment and health sectors.

Fat Distribution as a Determinant of Vitamin D Status: A Cross-Sectional Study of Adults in the United States

Background: This study aimed to elucidate correlations between obesity-related indicators and vitamin D (VD) status in a nationally representative sample of U.S. adults. Methods: We analysed data from 9168 adults aged 20–59 years obtained from the 2011–2018 National Health and Nutrition Examination Survey. Serum 25 hydroxyvitamin D [25(OH)D] levels were measured and categorised into quartiles. Anthropometric measurements, including weight, waist circumference, and fat mass in various body regions quantified through dual-energy X-ray absorptiometry, were collected. Multiple imputation was employed to replace missing data. The importance of obesity-related indicators and serum 25(OH)D concentration was explored using multiple linear regression adjusted for demographics, lifestyle factors, dietary intake, and clinical biomarkers, and stepwise regression. Results: Weight, waist circumference, and fat mass across all body regions were inversely associated with serum 25(OH)D levels (all p < 0.001). Notable differences were observed between men and women. Stepwise regression revealed a strong inverse correlation between visceral adipose tissue and serum 25(OH)D concentration in men [β 95% CI: –13.04 (–18.10, –7.99), p < 0.001], whereas in women, only weight was significantly correlated with serum 25(OH)D concentration [β 95% CI: –0.20 (–0.28, –0.12), p < 0.001]. Demographic attributes, seasonal sunlight exposure, dietary VD, calcium, phosphorus, and magnesium intake, and biomarkers including alkaline phosphatase and creatinine also emerged as significant predictors. Conclusions: Besides conventional obesity measures, abdominal fat metrics exhibit robust associations with VD deficiency, especially in men. Public health initiatives and clinical management strategies for hypovitaminosis D in obese populations should consider nuanced aspects of adiposity distribution alongside other demographic, lifestyle, and dietary factors influencing VD.

Dosimetric comparison of M6 CyberKnife plans optimized with Precision and RayStation 12A treatment planning systems.

Treatment planning for CyberKnife (CK) (Accuray, USA) can be performed with Precision (Accuray, USA) or RayStation (RS) (RaySearch Laboratories, Sweden) treatment planning systems (TPS). RaySearch recently released a new version of the CK module in RS 12A. The objective of the study was to compare plan quality between RS 12A and Precision. Fifty nine plans were optimized with both TPS and compared; 39 were for brain metastases and 20 were for vertebral metastases. To avoid bias in plan comparison, Precision plans were recomputed in RS with the dose algorithm and beam model of RS, and then compared to RS plans. The comparison was divided into 3 parts in order to reflect the potential of RS and the differences with Precision, in terms of technical aspects of delivery efficiency and dose distribution. We compared the dose to the target and to the organs at risk (OAR), the conformity index (CI), the gradient, as well as the number of monitor units (MU), and the number of beams and nodes. Finally, a global plan quality index (PQI) was calculated. RS plans showed an equivalent target coverage for brain metastases but worse for vertebrae. OAR sparing was improved in RS but with a lower CI compared to Precision. Using an appropriate planning methodology in RS, plans with comparable quality to Precision could be obtained, but at the cost of a longer optimization time. The PQI obtained with RS was better than Precision, except for some brain cases. RS is an adequate alternative for CK planning as it is possible to obtain plan quality comparable to Precision. However, the optimization time is longer compared to Precision and more attention must be paid to the choice of the initial conditions in terms of the number of beams and nodes.

Current status and trends in thalassemia burden across South, East and Southeast Asia, 1990–2021 a systematic analysis for the global burden of disease study 2021

ObjectiveThalassemia, an inherited hemoglobin synthesis disorder, imposes a significant health burden in Asian regions with high prevalence. Detailed patterns and trends of the disease across countries and territories within these regions remain underexplored. Our study focuses on the disease burden indices of thalassemia within the four GBD-defined Asian regions and the twenty-five included countries and territories. It provides insights into the gender-age distribution, temporal changes, and economic aspects of the thalassemia burden.MethodsData on thalassemia prevalence, incidence, mortality, and Disability-Adjusted Life Years (DALYs) were extracted from the Global Burden of Disease (GBD) 2021 study for South, East, Southeast, and high-income Asia regions, encompassing the relevant countries and territories from 1990 to 2021. The Average Annual Percent Change (AAPC) in age-standardized rates of thalassemia was determined to assess temporal trends. Age-gender cohort proportions were considered. The economic aspect of the disease burden and frontier analysis were evaluated using the GBD Socio-Demographic Index and Global Health Expenditure data.ResultsSoutheast Asia exhibited notably high age-standardized mortality rate (ASMR), age-standardized prevalence rate (ASPR), and age-standardized DALYs rate among the four studied Asian regions in 2021. The East Asia region had recorded the highest age-standardized incidence rate (ASIR). A general decline in disease burden indices across the four regions from 1990 to 2021 was evident, with the exception of ASIR in Southeast Asia. The ASMR was highest among pediatric population under five years old, with a significant male preponderance. An unusual increase in ASMR was detected among females of childbearing age and the elderly within the studied region. Further analysis had identified six high-burden countries and territories, particularly those with low-middle Socio-Demographic Index (SDI) rankings and limited health expenditure.ConclusionAlthough the overall burden of thalassemia has decreased substantially, the disease burden was influenced by gender, age, geography, temporal trends, and economic factors in distinct manners. Based on the current SDI, many countries and regions still have greater improvement potential in the disease burden. There is a necessity for enhanced attention and resource allocation, particularly in low-middle and low SDI countries, with an emphasis on policies that promote early diagnosis and comprehensive care.

Research on Flower Pattern and Roll Positioning Optimization for Roll Forming Process of TA4 Coiled Tubing.

Titanium alloy coiled tubing (CT) has great superiority while operating in deep wells with severe conditions, but it faces serious challenges during roll forming like high springback, edge cracking and surface wearing. In order to utilize the high precision and high efficiency production of titanium alloy CT, it is urgently necessary to develop a detailed process design. Based on the W-forming strategy and the cubic curve of the strip edge projection, the flower pattern and roll design for the 21-pass roll forming process were completed. Different tube dimensions and roll positionings were researched regarding the aspects of contact state, stress-strain distribution and geometry ovality using numerical simulation. The thickness/diameter ratio of the tube that can be formed should be within an effective range: exceeding the range leads to edge cracking, and an insufficient ratio leads to high springback. Roll positioning significantly affects the contact state and stress distribution, but leads to no major differences in the tube geometry. Finally, the trial production of the TA4 titanium CT with a size of Φ50.8 × 4 mm was completed successfully and was consistent with the simulation results.

A Decade in Transition: Forms of Recalibration in the Italian Regional Health Systems

ABSTRACTStarting in the 1990s, healthcare legislation in Italy gradually expanded the powers and responsibilities of the regions. In this context, focusing solely on the National Health Service (NHS) may have limited our understanding of regional‐level transformations over the past decade. This article examines the restructuring of Italian Regional Health Services (SSR) from 2011 to 2021. We specifically analyse two key dimensions of healthcare: ordinary hospital beds and territorial structures, paying close attention to their composition and the public‐private nature of the offer. Our article aims to achieve two main objectives. Firstly, it describes the changes that have occurred in different SSRs over the past decade, deepening the functional, institutional and distributive aspects of ‘recalibration’. Secondly, we explore whether homogeneous clusters of SSRs emerged or if, on the contrary, the recalibration process has given rise to a kaleidoscope of health systems, underscoring the significant regional differentiation that has long characterised Italian healthcare.

Meningkatkan Penalaran Statistik melalui Mengerjakan Soal Latihan Secara Aktif pada Mahasiswa Kesehatan Masyarakat Universitas Airlangga

Purpose: Statistical reasoning is the way people reason with ideas, relate one concept to another, and can interpret statistical results. Doing tasks actively to develop cognitive abilities. The aim is to build statistical reasoning so that participants can explore data, be able to see data as aggregates, how to organize and interpret results. Research: The form of activity is to provide training through giving exercise/doing assignments that require active participants to develop cognitive abilities. a model of cognitive development that incorporates statistical processes. There are four statistical processes, namely explaining or describing data, organizing or reducing data, representing data, analyzing and interpreting data. Results: Ability to explain data, most have difficulty reasoning about different data. The average is 64.44. The training results showed that there was understanding in explaining data in different situations, the average is 71.85. The ability to organize data shows that participants have knowledge about how to observe data according to statistical procedures. The average value is 76.67. Data presentation skills show that participants can display and interpret data. The average is 78.89. The ability to analyze and interpret data shows that participants can consider various aspects of distributions to find statistical values. The average is 72.96. Limitation: Since the study is focused on a specific geographic area (Gurabati Subdistrict), the findings may not be directly applicable to other regions with different urban planning, waste collection practices, or traffic conditions. The results may only be useful for this particular subdistrict or areas with similar characteristics. Contribution: The results of the assignment concluded that the practice of analyzing data influenced the participants' knowledge insight.

The Optimization of the Regional Distribution of COVID-19 Vaccinations, Taking into Account Logistical and Quality Concerns

Abstract The effective and fair allocation of COVID-19 vaccinations within a certain geographical area presents a complex issue, requiring a thorough optimization approach that considers logistical and quality considerations. This abstract offers a succinct summary of the primary factors and goals involved in tackling the intricacies of vaccine distribution. The global COVID-19 immunization campaign, characterized by its unparalleled magnitude and time sensitivity, highlights the necessity of developing strategic plans that are specifically designed to address the distinctive conditions of each location. The successful management of logistical obstacles, such as supply chain operations, final-stage delivery, and live monitoring, is essential in conjunction with the crucial task of preserving vaccine quality by strictly adhering to cold chain regulations. The objective of this study is to devise tailored optimization approaches that effectively manage the trade-off between efficiency and quality assurance during the distribution of COVID-19 vaccinations within a defined geographical area. This study aims to investigate the influence of geographical characteristics, population density, and pre-existing healthcare infrastructure on the logistical aspects of distribution. Additionally, it seeks to provide novel strategies to effectively tackle these issues. Achieving equitable distribution necessitates the implementation of specific strategies aimed at reaching populations that are vulnerable and excluded. The primary aim of this research is to provide valuable insights that can aid in the development of distribution hubs, the incorporation of modern technology for real-time monitoring, the fostering of collaboration with local healthcare providers, and the implementation of community engagement activities. These efforts are intended to improve vaccine acceptance rates. This project aims to provide adaptive distribution frameworks by integrating data-driven insights and a nuanced awareness of the local situation. The primary objective is to support policymakers, healthcare professionals, and stakeholders in maximizing the allocation of COVID-19 vaccinations, so making a valuable contribution to the worldwide endeavor to alleviate the consequences of the pandemic. The mathematical model described in this study offers a comprehensive framework for optimizing the allocation of COVID-19 vaccinations within a certain geographical region, taking into account various logistical and quality considerations. The achievement of its successful execution necessitates the engagement of pertinent stakeholders and the ongoing improvement of the approach through the utilization of empirical data and adaptation to changing circumstances. Engage in collaborative efforts with healthcare authorities and decision-makers to incorporate the model within the decision-making framework for the distribution of COVID-19 vaccines. The optimization challenge aims to determine the most efficient allocation of vaccine doses to various locations, with the objective of decreasing overall costs while ensuring compliance with logistical and quality requirements.

Cooking pottery as indicator of resilience and change in Early Medieval Cyprus. An archaeometric approach

The early medieval times in Cyprus are signified, conventionally, by the Arab invasions of the mid-seventh century (649/650CE). Past research viewed those events as the catalyst which led to a transformation from a prosperous province to a marginal territory balancing between two antagonising empires. Recently, studies have shifted their focus on reassessing this period’s scant -yet present- material culture. In pottery studies, despite the advances in typological and distribution aspects, few have explored technological issues of early medieval ceramic production through instrumental analysis. This study focuses on the compositional and technological characterisation of cooking vessels through ceramic petrography (TL-OM), found in relevant contexts in Cyprus, representing both wheel-thrown and handmade traditions. Sherds coming from five major early-medieval sites of the island (sites of Kophinou, Kalavasos-Kopetra, Akrotiri, Yeroskipou-Ayioi Pente and Dhiorios), outlined a picture of two parallel trends transversing across sites, i.e., an inter-regional shared sense of shape uniformity smoothening the local variances and a strong regionalism in terms of raw material procurement. Wheel-thrown cookware -found in every site and strongly represented by the Dhiorios workshop- showed the survival of Late Antique shapes well into the Early Middle Ages, in fabrics related mainly to the broader area of Dhiorios. In addition, handmade vessels of a "shared repertoire" showed a variety of local clays for their manufacture. When integrated into their archaeological context in Cyprus, the results support the idea of a ceramic koine persisting through the beginning of the Byzantine Early Middle Ages on an intra and inter-regional level.

Numerical study on heat and ion transport characteristics enables optimal design of aqueous thermocells for low-grade heat recovery

As a cutting-edge heat-to-electricity technology, thermogalvanic cells (thermocells) have great prospects in low-grade heat recovery due to its high Seebeck coefficient (Se), high scalability and low cost. Most of previous studies about aqueous thermocells have been focused on the overall performance by experimentally exploring advanced electrode and electrolyte materials, while very few simulation studies were reported before, leading to the unclear mechanisms of heat and ion transport inside the thermocell. In view of these challenges, this study aims to reveal the heat and ion transport characteristics of aqueous thermocells under various critical operating parameters, providing theoretical guidelines for further design and optimization of aqueous thermocells with fixed electrode and electrolyte materials. Firstly, a multi-physical model considering the diffusion, migration and convection was established and validated. Then, the effects of hot electrode temperature, electrode spacing and electrode orientation were evaluated on the thermocell performance from the aspects of distributions of multi-physical fields, overpotentials and overall performance. Finally, a prototype aqueous thermocell was proposed based on the understandings of restrictions associated with these operating parameters. Results indicated that each operating parameter can attribute to the variation of natural convection from the intensity and forms, and then affected the ion transport flux and overpotentials, and thus determined the power density of thermocells. These findings prompted the design and optimization of new aqueous thermocells, and the proposed prototype thermocell delivered the maximum power density of 0.43 W/m2, which was 115 % higher than that of the basic rectangular thermocell.

Nuclear pore complexes undergo Nup221 exchange during blood-stage asexual replication of Plasmodium parasites.

Malaria, caused by Plasmodium species, remains a critical global health challenge, with an estimated 249 million cases and over 600,000 deaths in 2022, primarily affecting children under five. Understanding the nuclear dynamics of Plasmodium parasites, particularly during their unique mitotic processes, is crucial for developing novel therapeutic strategies. Our study leverages advanced microscopy techniques, such as ultrastructure expansion microscopy, to reveal the organization and turnover of nuclear pore complexes (NPCs) during the parasite's asexual replication. By elucidating these previously unknown aspects of NPC distribution and homeostasis, we provide valuable insights into the molecular mechanisms governing parasite mitosis. These findings deepen our understanding of parasite biology and may inform future research aimed at identifying new targets for anti-malarial drug development.

Evaluating What Others Say: The Effect of Accuracy Assessment in Shaping Mental Models of AI Systems

Forming accurate mental models that align with the actual behavior of an AI system is critical for successful user experience and interactions. One way to develop mental models is through information shared by other users. However, this social information can be inaccurate and there is a lack of research examining whether inaccurate social information influences the development of accurate mental models. To address this gap, our study investigates the impact of social information accuracy on mental models, as well as whether prompting users to validate the social information can mitigate the impact. We conducted a between-subject experiment with 39 crowdworkers where each participant interacted with our AI system that automates a workflow given a natural language sentence. We compared participants' mental models between those exposed to social information of how the AI system worked, both correct and incorrect, versus those who formed mental models through their own usage of the system. Specifically, we designed three experimental conditions: 1) validation condition that presented the social information followed by an opportunity to validate its accuracy through testing example utterances, 2) social information condition that presented the social information only, without the validation opportunity, and 3) control condition that allowed users to interact with the system without any social information. Our results revealed that the inclusion of the validation process had a positive impact on the development of accurate mental models, especially around the knowledge distribution aspect of mental models. Furthermore, participants were more willing to share comments with others when they had the chance to validate the social information. The impact of inaccurate social information on altering user mental models was found to be non-significant, while 69.23% of participants incorrectly judged the social information accuracy at least once. We discuss the implications of these findings for designing tools that support the validation of social information and thereby improve human-AI interactions.

New record of Camel Spider Galeodes indicus Pocock, 1900 (Arachnida: Solifugae: Galeodidae) from Chhatarpur, Madhya Pradesh and additional records from Jaisalmer, Rajasthan (India), with systematic account, distribution and other aspects

New record of Camel Spider Galeodes indicus Pocock, 1900 (Arachnida: Solifugae: Galeodidae) from Chhatarpur, Madhya Pradesh and additional records from Jaisalmer, Rajasthan (India), with systematic account, distribution and other aspects

Implementasi Strategi Marketing Mix Syariah pada Produk Obu Jamu di CV. Dua Laba Batam dan Manfaatnya

This study aims to investigate the implementation of the sharia marketing mix strategy on CV. Two Profits in Batam City for OBU Jamu products and their benefits for the surrounding community. Using a qualitative approach and case studies, this study involves an in-depth analysis of the sharia marketing strategy implemented by CV. Two Profits, including in the aspects of product, price, distribution, and promotion. The basic concept of sharia marketing and the characteristics of OBU Jamu products are also the focus of this research. Through interviews, observations, and document analysis, this study found that CV. Dua Laba has successfully implemented a sharia marketing strategy on their OBU Jamu products well. Packaging that is in accordance with sharia principles, fair and transparent pricing, distribution through channels that are in accordance with sharia principles, and promotions that prioritize sharia values are integral parts of their marketing strategy. The impact of this implementation is also felt by the surrounding community, including increased awareness of sharia products, local economic empowerment, and positive social and cultural impacts. The results of this study contribute to the understanding of sharia marketing in the context of the herbal medicine industry in Indonesia, as well as provide insights for other companies that want to implement sharia marketing strategies. Practical recommendations are also recommended for CVs. Dua Laba and other stakeholders in optimizing the implementation of sharia marketing strategies on their OBU Jamu products.

Assessment of spatial distribution of schools in the northern area of Riyadh city

This paper aims to study the distribution of three types of schools in the northern area of Riyadh city in Saudi Arabia in order to uncover the aspects of imbalance distribution of schools over the 4 districts of the study area (Almalqa, Sahafa, Jasmine and Narges neighborhoods) in addition to assess the extent of compatibility between the number of schools in each district and the density of population residing in it. The used dataset is built up of mainly tow datasets for schools and districts covering the study area. This research has utilized MS Excel, ArcGIS and QGIS software and applied the Point-to-Polygon overlay to locate the three types of schools in their corresponding districts and three types of analysis were applied which are the average nearest neighbor, heat map, and district classification based on population ratio with the aim of exploring the clustering patterns of schools as well as classifying the districts based on the density of schools relative to population. The study concludes that there is a spatial disparity in the distribution of schools, mainly in terms of their density, in the different districts due to the variation in population. Moreover, a notable inequality of the distribution of schools with respect to the population has been found.

Epigaeic spiders (Araneae) from three habitats at Stryn, Nordfjord, Western Norway

One year of pitfall sampling in (A) a narrow strip of vegetation (junipers, Rosa sp., small pines) close to a river bank, (B) a cultivated medium humid meadow and (C) a humid deciduous forest (Alnus) with some grass on the ground collected a total of 25, 48 and 32 species, respectively (in total 67 species). Shannon indices of general diversity (ln e) were 1.8, 2.1 and 3.1, respectively. The three sites shared only 9 species, 57% of all species were found in only one locality. Similarity indices were low, especially between loc. A and C. Linyphiidae and Lycosidae were dominant. The latter were scarce in loc. B and C but common at loc. A (Pardosa palustris and P. amentata together comprising 43.5% of total) and net building species more scarce. The local distribution, co-existence, ecological and habitat preferences, seasonal activity and body size of some common species are briefly discussed. For some species, aspects of geographical distribution are discussed.

Assessing the impact of the European Union-Vietnam free trade agreement on labor market and employment in Vietnam

PurposeThis study investigates the impact of the European Union-Vietnam Free Trade Agreement (EVFTA) on Vietnam’s labor market and employment outcomes, considering the potential distributional consequences across various groups of workers and regions.Design/methodology/approachA comprehensive quantitative framework is employed, combining the gravity model of trade to estimate the EVFTA’s effects on trade flows, the CISAF_M1 model to simulate sectoral employment impacts and econometric models to analyze the effects on wages and decent work. The analysis draws upon a rich dataset spanning the period before and after the EVFTA’s implementation.FindingsThe EVFTA has significantly boosted Vietnam’s exports to the EU, leading to substantial job creation in labor-intensive sectors such as textiles, apparel and footwear. The agreement has also contributed to wage growth and improved access to social insurance for workers in export-oriented industries. However, the impact on other aspects of job quality is less clear. The distributional analysis reveals that the EVFTA’s employment effects have been relatively balanced across gender but have favored younger and less skilled workers as well as those in rural areas.Originality/valueThis study provides a comprehensive and nuanced assessment of the EVFTA’s impact on Vietnam’s labor market, addressing a gap in the literature on the employment effects of new-generation free trade agreements in developing countries. The findings highlight the importance of considering distributional aspects when evaluating the socioeconomic implications of trade liberalization and offer valuable insights for policymakers aiming to promote inclusive growth in the context of deepening international economic integration.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2024-0236

Smart City Construction, Artificial Intelligence Development, and the Quality of Export Products: A Study Based on Micro-Level Data of Chinese Enterprises

Quality improvement is essential for a nation’s economy to transition from large to strong. In the 21st century, a new wave of quality development has emerged globally, and upgrading the quality of enterprise export products is a key measure for driving exports and supporting high-quality economic development. The development of artificial intelligence, as the new core engine driving technological revolution and industrial transformation, will profoundly alter various aspects of economic activities, including production, distribution, exchange, and consumption. Exploring and cultivating new artificial intelligence-driven momentum to enhance the quality of enterprise export products is inevitably a major theoretical and practical issue of common interest to governments, enterprises, and academia. This paper uses China, a major developing and export-oriented economy, as a case study to explore the policy measures for stimulating new momentum in artificial intelligence development and their effects and transmission mechanisms on improving the quality of enterprise export products. Specifically, it constructs a theoretical model to examine the relationship between smart city construction, artificial intelligence development, and the quality of enterprise export products. By considering the smart city construction projects launched by the Chinese government as a quasi-natural experiment to facilitate artificial intelligence development, the study employs matched city-enterprise data from 2007 to 2015 and utilizes a difference-in-differences (DID) methodology to empirically test the impact of smart city construction on enhancing the quality of enterprise export products. According to the study, the policy-driven nature of smart city construction significantly enhances the quality of enterprise export products. This beneficial impact is particularly evident in the eastern regions, as well as in labor-intensive and capital-intensive industries, and among foreign-invested and private enterprises. Mechanism tests and additional analyses indicate that artificial intelligence development is significantly more advanced in smart cities than in non-smart cities, with the gap between them steadily widening. The construction of smart cities significantly advances artificial intelligence development, which subsequently enhances the quality of enterprise export products. Furthermore, smart cities can substantially contribute to this improvement by facilitating a more efficient, market-oriented allocation of resources.

Cross-Modal Clustering With Deep Correlated Information Bottleneck Method.

Cross-modal clustering (CMC) intends to improve the clustering accuracy (ACC) by exploiting the correlations across modalities. Although recent research has made impressive advances, it remains a challenge to sufficiently capture the correlations across modalities due to the high-dimensional nonlinear characteristics of individual modalities and the conflicts in heterogeneous modalities. In addition, the meaningless modality-private information in each modality might become dominant in the process of correlation mining, which also interferes with the clustering performance. To tackle these challenges, we devise a novel deep correlated information bottleneck (DCIB) method, which aims at exploring the correlation information between multiple modalities while eliminating the modality-private information in each modality in an end-to-end manner. Specifically, DCIB treats the CMC task as a two-stage data compression procedure, in which the modality-private information in each modality is eliminated under the guidance of the shared representation of multiple modalities. Meanwhile, the correlations between multiple modalities are preserved from the aspects of feature distributions and clustering assignments simultaneously. Finally, the objective of DCIB is formulated as an objective function based on a mutual information measurement, in which a variational optimization approach is proposed to ensure its convergence. Experimental results on four cross-modal datasets validate the superiority of the DCIB. Code is released at https://github.com/Xiaoqiang-Yan/DCIB.