Integration Patterns Research Articles

Retinal vascular morphological characteristics in diabetic retinopathy: an artificial intelligence study using a transfer learning system to analyze ultra-wide field images.

To investigate the morphological characteristics of retinal vessels in patients with different severity of diabetic retinopathy (DR) and in patients with or without diabetic macular edema (DME). The 239 eyes of DR patients and 100 eyes of healthy individuals were recruited for the study. The severity of DR patients was graded as mild, moderate and severe non-proliferative diabetic retinopathy (NPDR) according to the international clinical diabetic retinopathy (ICDR) disease severity scale classification, and retinal vascular morphology was quantitatively analyzed in ultra-wide field images using RU-net and transfer learning methods. The presence of DME was determined by optical coherence tomography (OCT), and differences in vascular morphological characteristics were compared between patients with and without DME. Retinal vessel segmentation using RU-net and transfer learning system had an accuracy of 99% and a Dice metric of 0.76. Compared with the healthy group, the DR group had smaller vessel angles (33.68±3.01 vs 37.78±1.60), smaller fractal dimension (Df) values (1.33±0.05 vs 1.41±0.03), less vessel density (1.12±0.44 vs 2.09±0.36) and fewer vascular branches (206.1±88.8 vs 396.5±91.3), all P<0.001. As the severity of DR increased, Df values decreased, P=0.031. No significant difference between the DME and non-DME groups were observed in vascular morphological characteristics. In this study, an artificial intelligence retinal vessel segmentation system is used with 99% accuracy, thus providing with relatively satisfactory performance in the evaluation of quantitative vascular morphology. DR patients have a tendency of vascular occlusion and dropout. The presence of DME does not compromise the integral retinal vascular pattern.

INTEGRATION OF TECHNOLOGY IN THE PRE-SERVICE TEACHERS FOR EDUCATIONAL MANAGEMENT; THROUGH CURRICULUM IN GHANA

This study aims to investigate the integration of technology in the preparation of prospective teachers for educational management through the curriculum in Ghana. Utilizing a qualitative approach, the study analyzes how technology is embedded in learning and how prospective teachers respond to it in the context of education management. The main focus of this research is on the concept and use of technology in the educational process to enhance the understanding and skills of prospective teachers. However, the study found that the curriculum policies, structure, and guidelines for pre-service teachers lack a clear vision for effectively integrating technology. Interviews with policymakers indicated their recognition of the importance of technology integration but also revealed the lack of investment hindered its progress. Drawing on the study's findings and existing research, context-specific recommendations are proposed, focusing on promoting innovative technology-based pedagogical models and developing effective leadership. The study involved participants from a teacher preparation program in Ghana, with data collection conducted through in-depth interviews, classroom observations, and curriculum document analysis. Data were analyzed using an inductive approach to identify common patterns in technology integration and prospective teachers' responses to it. The results of this study are expected to provide insights into the extent to which technology is integrated in the teacher preparation curriculum in Ghana, as well as its impact on teacher candidates' readiness to manage education. The practical implications of this study can provide recommendations for improving the teacher education curriculum, adapting teaching strategies to technological developments, and increasing the effectiveness of teacher preparation in the digital era. The findings can provide valuable guidance for policy makers, educational institutions and educators to ensure that prospective teachers have the relevant and necessary skills to face future educational demands.

HBV integrations reshaping genomic structures promote hepatocellular carcinoma

ObjectiveHepatitis B virus (HBV)-related hepatocellular carcinoma (HCC), mostly characterised by HBV integrations, is prevalent worldwide. Previous HBV studies mainly focused on a few hotspot integrations. However, the oncogenic role of...

Connectivity of EEG and fMRI network in the resting state in healthy people and patients with post-traumatic disorder of consciousness

Recovery of consciousness in patients with post-comatose unconscious states after severe traumatic brain injury and the search for their objective markers are among the urgent medical and social problems. To clarify the information content and the degree of consistency of changes in hemodynamic and bioelectrical parameters, in this work we carried out comparative studies of fMRI networks and EEG connectivity at rest in healthy subjects, as well as in patients with post-traumatic disorders of consciousness before and after therapeutic rhythmic transcranial magnetic stimulation (rTMS). It was shown that the characteristics of the functional connectivity of fMRI and EEG at rest are among the informative markers of neuroplasticity during depression of consciousness. A certain topographic correspondence between the fMRI networks and the EEG integral connectivity pattern at rest was established, regardless of the modification of the latter assessment: in the continuous recording mode or pseudo-EP. At the same time, the method of independent fMRI components more clearly reveals the features of the state of individual neural networks, and the indicators of EEG functional connectivity (range 1–15 Hz) are more informative in assessing the integral neural network characteristics and their changes during treatment.

Small- to medium-sized mammals show greater morphological disparity in cervical than lumbar vertebrae across different terrestrial modes of locomotion.

During mammalian terrestrial locomotion, body flexibility facilitated by the vertebral column is expected to be correlated with observed modes of locomotion, known as gait (e.g., sprawl, trot, hop, bound, gallop). In small- to medium-sized mammals (average weight up to 5 kg), the relationship between locomotive mode and vertebral morphology is largely unexplored. Here we studied the vertebral column from 46 small- to medium-sized mammals. Nine vertebrae across cervical, thoracic, and lumbar regions were chosen to represent the whole vertebral column. Vertebra shape was analysed using three-dimensional geometric morphometrics with the phylogenetic comparative method. We also applied the multi-block method, which can consider all vertebrae as a single structure for analysis. We calculated morphological disparity, phylogenetic signal, and evaluated the effects of allometry and gait on vertebral shape. We also investigated the pattern of integration in the column. We found the cervical vertebrae show the highest degree of morphological disparity, and the first thoracic vertebra shows the highest phylogenetic signal. A significant effect of gait type on vertebrae shape was found, with the lumbar vertebrae having the strongest correlation; but this effect was not significant after taking phylogeny into account. On the other hand, allometry has a significant effect on all vertebrae regardless of the contribution from phylogeny. The regions showed differing degrees of integration, with cervical vertebrae most strongly correlated. With these results, we have revealed novel information that cannot be captured from study of a single vertebra alone: although the lumbar vertebrae are the most correlated with gait, the cervical vertebrae are more morphologically diverse and drive the diversity among species when considering whole column shape.

Identification of transcriptionally-active human papillomavirus integrants through nanopore sequencing reveals viable targets for gene therapy against cervical cancer.

Integration of the human papillomavirus (HPV) genome into the cellular genome is a key event that leads to constitutive expression of viral oncoprotein E6/E7 and drives the progression of cervical cancer. However, HPV integration patterns differ on a case-by-case basis among related malignancies. Next-generation sequencing technologies still face challenges for interrogating HPV integration sites. In this study, utilizing Nanopore long-read sequencing, we identified 452 and 108 potential integration sites from the cervical cancer cell lines (CaSki and HeLa) and five tissue samples, respectively. Based on long Nanopore chimeric reads, we were able to analyze the methylation status of the HPV long control region (LCR), which controls oncogene E6/E7 expression, and to identify transcriptionally-active integrants among the numerous integrants. As a proof of concept, we identified an active HPV integrant in between RUNX2 and CLIC5 on chromosome 6 in the CaSki cell line, which was supported by ATAC-seq, H3K27Ac ChIP-seq, and RNA-seq analysis. Knockout of the active HPV integrant, by the CRISPR/Cas9 system, dramatically crippled cell proliferation and induced cell senescence. In conclusion, identifying transcriptionally-active HPV integrants with Nanopore sequencing can provide viable targets for gene therapy against HPV-associated cancers.

Convective Phenomenes in the Context of Meso-β-scale Convective Structures

This review article presents the results of radar studies of convective phenomena in Moldavia and the North Caucasus using Eulerian (ECS) and Lagrangian (LCS) coordinate systems. Application of the Lagrangian approach allowed us to exclude the influence of the tropospheric displacement and to obtain integral grid patterns of thunderstorm-hail processes. These structures are especially well manifested at small wind shears (up to 1 m/sec/km). At large shears, the mesh structures are transformed predominantly into linear structures. The methodology for obtaining integral pictures of radio echoes of thunderstorm processes is described. Intersections of linear elements, which we call faces, occur at nodes. The latter plays a particularly important role in the dynamics and kinematics of convective storms. The latter play a particularly important role in the dynamics and kinematics of convective storms. The development of storms occurs along the facets and at the nodes of meso-β-scale convective structures (MMCS), which explains the mechanisms of splitting and merging of storms: in the first case the facets diverge, in the second case they converge. The relations of motion vectors for different types of storms are obtained. It is shown that the direction of the radio echo canopy coincides with the storm motion trajectory; the evolution vector (propagation) for the most powerful storms deviates from the storm displacement direction by 80°–135°. The structure of the updated band within which the Flanking Line is formed for supercells and multicells is studied. Mnemonic rules have been derived that allow one to infer from instantaneous patterns of anvil orientation and the mutual location of storms whether they are converging or diverging, and to identify left- or right-moving storms. A hypothesis on the internal structure of the cold front of the 2nd kind is stated. The main conclusion of the work is that the evolution of storms is determined by the configuration of meso-β-scale convective structures. This explains various convective phenomena from unified positions. The results are applicable in works on modification of convective cloudiness, for ultra-short-term forecasts of dangerous phenomena, storm warnings of the population, rescue services, etc.

Comprehensive Identification and Characterization of HML-9 Group in Chimpanzee Genome.

Endogenous retroviruses (ERVs) are related to long terminal repeat (LTR) retrotransposons, comprising gene sequences of exogenous retroviruses integrated into the host genome and inherited according to Mendelian law. They are considered to have contributed greatly to the evolution of host genome structure and function. We previously characterized HERV-K HML-9 in the human genome. However, the biological function of this type of element in the genome of the chimpanzee, which is the closest living relative of humans, largely remains elusive. Therefore, the current study aims to characterize HML-9 in the chimpanzee genome and to compare the results with those in the human genome. Firstly, we report the distribution and genetic structural characterization of the 26 proviral elements and 38 solo LTR elements of HML-9 in the chimpanzee genome. The results showed that the distribution of these elements displayed a non-random integration pattern, and only six elements maintained a relatively complete structure. Then, we analyze their phylogeny and reveal that the identified elements all cluster together with HML-9 references and with those identified in the human genome. The HML-9 integration time was estimated based on the 2-LTR approach, and the results showed that HML-9 elements were integrated into the chimpanzee genome between 14 and 36 million years ago and into the human genome between 18 and 49 mya. In addition, conserved motifs, cis-regulatory regions, and enriched PBS sequence features in the chimpanzee genome were predicted based on bioinformatics. The results show that pathways significantly enriched for ERV LTR-regulated genes found in the chimpanzee genome are closely associated with disease development, including neurological and neurodevelopmental psychiatric disorders. In summary, the identification, characterization, and genomics of HML-9 presented here not only contribute to our understanding of the role of ERVs in primate evolution but also to our understanding of their biofunctional significance.

Core Technology Topic Identification and Evolution Analysis Based on Patent Text Mining—A Case Study of Unmanned Ship

Accurate identification and evolutionary analysis of core technology topics within patent texts play a crucial role in enabling enterprises to discern the development trajectory of core technologies, optimize research and development (R&amp;D) strategies, and foster technological innovation. Based on the perspective of time series dynamic analysis, this study uses the Latent Dirichlet Allocation (LDA) topic modeling and TF-IDF text vectorization methods to comprehensively mine and identify patent technology topics in the field of unmanned ships. This study deeply analyzes the dynamic evolution of unmanned ship technology topics from two aspects: the evolution of technology theme intensity and the evolution of technology theme content. We refine the development characteristics and future development directions of unmanned ship technology. The findings reveal two hot technologies, six growth technologies, and six declining technologies in unmanned ship technology. Furthermore, the analysis of technical topic evolution illustrates a pattern of fragmentation, inheritance, and integration. This study advances the methodologies used for identifying and analyzing patent technology topics and helps to grasp the development rules and evolutionary trends of core technologies. In addition, this paper has reference value for the research and practice of core technology topic identification and evolution analysis methods based on patent text mining.

Research on the Key Paths of Enterprise Integration of Domestic and Foreign Trade from the Perspective of Knowledge Transfer

The issue of inefficient industry innovation caused by the segmentation of domestic and foreign trade markets has been prominent, leading to a long-standing "productivity paradox" between domestic and foreign trade. "Constructing a new pattern of integration of domestic and foreign trade with the domestic cycle as the main body and the mutual promotion of domestic and international cycles" is a strategic deployment of the Party Central Committee and the State Council. This paper investigates the problems and intrinsic mechanisms faced in the process of enterprise integration of domestic and foreign trade from the perspective of knowledge transfer. It clarifies that the primary task of integrating domestic and foreign trade is to solve the problem of inefficient knowledge transfer between domestic and foreign trade. At the same time, the study shows that: On the one hand, by constructing a horizontal system of knowledge transfer between domestic and foreign trade, it is possible to effectively enable foreign trade enterprises to enjoy the dividends of unified large market reforms, better integrate resources and standards with the domestic trade market, and promote the transfer of knowledge achievements of foreign trade enterprises to the domestic market. On the other hand, through vertical industrial ecological knowledge embedding, it can promote domestic enterprises to leverage the advantages of domestic consumption scale, integrate technology, channels, and platform resources, achieve knowledge embedding of enterprises in the vertical ecological chain of industries, and ultimately achieve the goal of integrated development of domestic and foreign trade.

Category-Based Effect on False Memory of People with Down Syndrome.

Background: People with Down syndrome (DS) are deficient in verbal memory but relatively preserved in visuospatial perception. Verbal memories are related to semantic knowledge. Receptive ability is better than expressive ability in people with DS but still seriously lags behind their age-matched controls. This lag may result in the weak semantic integration of people with DS. Aims: This study aimed to examine the ability of semantic integration of people with DS by using false-memory tasks. Possible differences in the number of false memories induced by nouns and verbs were of focus. Methods and Procedures: Two phases were involved in the false-memory task. In the study phase, ten-word lists with semantically related associates were presented. In the recognition phase, judgments were to be made about whether the words presented had been heard before. Three types of words were tested: previously presented associates, semantically related lures, and semantically unrelated new words. Outcomes and Results: People with DS overall showed the lowest accuracy among groups in response to tested word types. In the processing of lures, people with DS were worse in recognition than MA controls. In processing unrelated words, people with DS responded least accurately to all types of words compared to control groups. In the processing of associates, people with DS showed similar recognition rates as the MA controls but were less accurate than the CA controls. No difference was observed between nouns and verbs in recognizing word types among groups, though faster responses to nouns than to verbs emerged in college students. Further analyses on topic-wised comparisons of errors across syntactic categories revealed differences in specific concepts among groups, suggesting people with DS were atypical in semantic organization. Conclusions and Implications: People with DS showed mixed patterns in semantic integration by false-memory tasks with delay to associates and deviance to lures together with unrelated words. People with DS showed distinct patterns in processing nouns and verbs while conducting topic-wise comparisons, suggesting that they formed false memories differently based on distinct syntactic categories. We concluded that people with DS develop a deviant semantic structure, hence showing problems in language and social cognition. Category-based rehabilitation is suggested to be implemented for people with DS to improve their semantic knowledge through lexical connections.

Evolutionary trends in the elasmobranch neurocranium

The neurocranium (braincase) is one of the defining vertebrate characters. Housing the brain and other key sensory organs, articulating with the jaws and contributing to the shape of the anteriormost portion of the body, the braincase is undoubtedly of great functional importance. Through studying relationships between braincase shape and ecology we can gain an improved understanding of form-function relationships in extant and fossil taxa. Elasmobranchii (sharks and rays) represent an important case study of vertebrate braincase diversity as their neurocranium is simplified and somewhat decoupled from other components of the cranium relative to other vertebrates. Little is known about the associations between ecology and braincase shape in this clade. In this study we report patterns of mosaic cranial evolution in Elasmobranchii that differ significantly from those present in other clades. The degree of evolutionary modularity also differs between Selachii and Batoidea. In both cases innovation in the jaw suspension appears to have driven shifts in patterns of integration and modularity, subsequently facilitating ecological diversification. Our results confirm the importance of water depth and biogeography as drivers of elasmobranch cranial diversity and indicate that skeletal articulation between the neurocranium and jaws represents a major constraint upon the evolution of braincase shape in vertebrates.

The mystery of rich human gut antibiotic resistome in the Yellow River with hyper-concentrated sediment-laden flow

Human gut antibiotic resistome widely occur in anoxic environments characterized by high density of bacterial cells and frequent transmission of antibiotic resistance genes (ARGs). Such resistome is greatly diluted, degraded, and restrained in the aerobic habitats within most natural rivers (regarded as “terrestrial guts”) connecting continents and the oceans. Here we implemented a large-scale monitoring campaign extending 5,200 km along the Yellow River, and provide the first integral biogeographic pattern for both ARGs and their hosts. We identified plentiful ARGs (24 types and 809 subtypes) and their hosts (24 phyla and 757 MAGs) in three media (water, suspended particulate matter (SPM), and sediment). Unexpectedly, we found diverse human gut bacteria (HGB) acting as supercarriers of ARGs in this oxygen-rich river. We further discovered that numerous microhabitats were created within stratified biofilms that surround SPMs, particularly regarding the aggregation of anaerobic HGB. These microhabitats provide numerous ideal sinks for anaerobic bacteria and facilitate horizontal transfer of ARGs within the stratified biofilms, Furthermore, the stratification of biofilms surrounding SPMs has facilitated synergy between human gut flora and denitrifiers for propagation of ARGs in the anoxic atmospheres, leading to high occurrence of human gut antibiotic resistome. SPMs play active roles in the dynamic interactions of river water and sediment, thus accelerating the evolution of riverine resistome and transmission of human gut antibiotic resistome. This study revealed the special contribution of SPMs to the propagation of ARGs, and highlighted the necessity of making alternative strategies for sustainable management of large rivers with hyper-concentrated sediment-laden flows.

A reductionistic or holistic approach? The impacts of fit patterns of supplier and customer integration on company and supply chain performance

The increasing prevalence and complexity of supply chain integration raise a question on how to concurrently adopt different dimensions of integration rather than a singular dimension. While extant literature extensively examined the isolated impacts of supplier and customer integration on performance, the exploration of conceptualizing and evaluating the fit between supplier and customer integration remains an issue under active investigation. Drawing on the dynamic capability view, this study conceptualizes and operationalizes fit patterns (e.g., fit as moderation and matching) of supplier and customer integration to understand the synergistic effects of supplier and customer integration on both company and supply chain performance and establish dynamic capabilities containing fit sensing, seizing, and transformation. Using the survey data collected from 824 firms from China Mainland, Hong Kong, and Taiwan, the study reveals distinct effects of two fit patterns on company and supply chain performance. Fit as moderation is positively related to both company and supply chain performance, while fit as matching is negatively related to company performance and is not significantly related to supply chain performance. This study offers profound insights into how to adopt supplier and customer integration concurrently in an efficient and effective manner and provides guidelines for practitioners.

ViroISDC: a method for calling integration sites of hepatitis B virus based on feature encoding

BackgroundHepatitis B virus (HBV) integrates into human chromosomes and can lead to genomic instability and hepatocarcinogenesis. Current tools for HBV integration site detection lack accuracy and stability.ResultsThis study proposes a deep learning-based method, named ViroISDC, for detecting integration sites. ViroISDC generates corresponding grammar rules and encodes the characteristics of the language data to predict integration sites accurately. Compared with Lumpy, Pindel, Seeksv, and SurVirus, ViroISDC exhibits better overall performance and is less sensitive to sequencing depth and integration sequence length, displaying good reliability, stability, and generality. Further downstream analysis of integrated sites detected by ViroISDC reveals the integration patterns and features of HBV. It is observed that HBV integration exhibits specific chromosomal preferences and tends to integrate into cancerous tissue. Moreover, HBV integration frequency was higher in males than females, and high-frequency integration sites were more likely to be present on hepatocarcinogenesis- and anti-cancer-related genes, validating the reliability of the ViroISDC.ConclusionsViroISDC pipeline exhibits superior precision, stability, and reliability across various datasets when compared to similar software. It is invaluable in exploring HBV infection in the human body, holding significant implications for the diagnosis, treatment, and prognosis assessment of HCC.

Integrated machine learning reveals aquatic biological integrity patterns in semi-arid watersheds

Semi-arid regions present unique challenges for maintaining aquatic biological integrity due to their complex evolutionary mechanisms. Uncovering the spatial patterns of aquatic biological integrity in these areas is a challenging research task, especially under the compound environmental stress. Our goal is to address this issue with a scientifically rigorous approach. This study aims to explore the spatial analysis and diagnosis method of aquatic biological based on the combination of machine learning and statistical analysis, so as to reveal the spatial differentiation patterns and causes of changes of aquatic biological integrity in semi-arid regions. To this end, we have introduced an innovative approach that combines XGBoost-SHAP and Fuzzy C-means clustering (FCM), we successfully identified and diagnosed the spatial variations of aquatic biological integrity in the Wei River Basin (WRB). The study reveals significant spatial variations in species number, diversity, and aquatic biological integrity of phytoplankton, serving as a testament to the multifaceted responses of biological communities under the intricate tapestry of environmental gradients. Delving into the depths of the XGBoost-SHAP algorithm, we discerned that Annual average Temperature (AT) stands as the pivotal driver steering the spatial divergence of the Phytoplankton Integrity Index (P-IBI), casting a positive influence on P-IBI when AT is below 11.8 °C. The intricate interactions between hydrological variables (VF and RW) and AT, as well as between water quality parameters (WT, NO3–N, TP, COD) and AT, collectively sculpt the spatial distribution of P-IBI. The fusion of XGBoost-SHAP with FCM unveils pronounced north-south gradient disparities in aquatic biological integrity across the watershed, segmenting the region into four distinct zones. This establishes scientific boundary conditions for the conservation strategies and management practices of aquatic ecosystems in the region, and its flexibility is applicable to the analysis of spatial heterogeneity in other complex environmental contexts.

Research on the Measurement and Mechanism of Data Elements Enabling Breakthrough Innovation of Private Enterprises

This research endeavor holds a pivotal role in elucidating the measurement and underlying mechanisms of data elements, which have emerged as pivotal catalysts for fostering breakthrough innovations in private enterprises. Through a meticulous and rigorous analysis of the intricate utilization and integration patterns of these data elements, we aspire to offer a comprehensive and nuanced understanding of how private firms can harness the immense power of data to foster disruptive and transformative innovations. Our study focuses on identifying the crucial factors that underpin the successful execution of data-driven strategies. These strategies augment enterprises' innovative prowess and propel them to the forefront of their respective industries. The insights gained from our research transcend theoretical frameworks, offering practical strategies and profound understandings that serve as a compass for private enterprises navigating today's rapidly evolving, data-driven economy. By harnessing these insights, private enterprises can maintain their competitive edge, seizing growth opportunities in a fiercely competitive environment. Ultimately, this research holds tremendous potential in shaping the future of private enterprises, empowering them to leverage data as a strategic asset and transform their businesses for enduring growth and prosperity.

Responsible composition and optimization of integration processes under correctness preserving guarantees

Enterprise Application Integration deals with the problem of connecting heterogeneous applications, and is the centerpiece of current on-premise, cloud and device integration scenarios. For integration scenarios, structurally correct composition of patterns into processes and improvements of integration processes are crucial. In order to achieve this, we formalize compositions of integration patterns based on their characteristics, and describe optimization strategies that help to reduce the model complexity, and improve the process execution efficiency using design time techniques. Using the formalism of timed DB-nets – a refinement of Petri nets – we model integration logic features such as control- and data flow, transactional data storage, compensation and exception handling, and time aspects that are present in reoccurring solutions as separate integration patterns. We then propose a realization of optimization strategies using graph rewriting, and prove that the optimizations we consider preserve both structural and functional correctness. We evaluate the improvements on a real-world catalog of pattern compositions, containing over 900 integration processes, and illustrate the correctness properties in case studies based on two of these processes.

Evaluation of the urban industrial coupling strategy based on the global production networks theory: A case study of the smart phone industry in the Guangdong-Hong Kong-Macao Greater Bay Area.

In the context of uncertain economic environments urban agglomerations play a crucial role in economic development, reshaping industrial chains and fostering inter-city cooperation. This study employs the Global Production Network (GPN) theory to enhance our understanding of how cities integrate into regions, emphasizing the often-overlooked governmental influence in strategic coupling processes. In examining the evolution of China's smartphone industry within the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) this research categorizes 19,599 smartphone companies into five distinct groups. Through analyzing their spatial distribution and geographical linkage the study identifies four strategic coupling modes based on the localization of assets, considering spatial influence and technological complexity along horizontal and vertical dimensions. Structural and institutional elements within these modes are also explored. The research uncovers unique integration patterns among nine cities in the GBA's mobile industry, revealing distinct spatial clusters rooted in technological, resource and innovation factors. Crucially, local policies play a pivotal role. Cities such as Shenzhen and Dongguan emerge as technology hubs, contrasting with Foshan and Zhongshan, which leverage resource advantages. The spatial impact, contingent on specific assets, underscores the necessity for nuanced top-down coupling methods in regional development. Moreover, the study emphasizes the significance of nurturing innovation links, not only between leading companies but also among midstream and downstream enterprises, enhancing cities' strategic coupling capabilities.

Social Harmony in Wonomulyo, Polewali Mandar Regency

This research aims to determine harmony in Wonomulyo. This research is a qualitative research. Data was obtained through observation and in-depth interviews with informants who had lived for at least 5 years. Validation of data is carried out through member check. The research results show that the integration pattern that is realized is mutual cooperation and cooperation. The people in Wonomulyo, even though they are from different ethnicities, respect each other. Harmony is created through economic and cultural activities. Javanese people display cultural attractions at events commemorating religious holidays and Indonesian independence day events