Key Patterns Research Articles

Research Trends in English Writing: A Semantic Network Analysis

This study explores the shifting landscape of English writing research from 2001 to 2020, utilizing a large-scale, data-driven methodology. Data from 1495 articles published in Korea over these two decades was collected and preprocessed with the Biblio data collector, then analyzed with Netminer. The approach involved four stages of semantic analysis: frequency, centrality, network, and modularity analyses. The findings highlight dynamic shifts in research focus. While keywords like ‘test’, ‘college students’, ‘vocabulary’, and ‘level-based’ remained consistent, the 2010s saw emerging themes like ‘task’, ‘textbook analysis’, ‘corpus analysis,’ 'peer feedback’, and ‘genre-based approach’. Centrality analysis showed that in the 2000s, alongside ‘sentence’, ‘questionnaire’ held a central position with multiple nodes linked to it. In the 2010s, ‘questionnaire’ persisted as a central theme but was joined by ‘relationship.’ Network maps generated with Spring 2D and PFnet depicted these evolving interconnections. In the second period, ‘feedback’ emerged as a central theme, yet directly connected to only two nodes: ‘error’ and ‘peer feedback.’ Modularity analysis identified six research groups in each period, with the ‘questionnaire group’ being most significant in the 2000s and the ‘peer feedback group’ gaining prominence in the 2010s. This research illuminates the evolving trends in English writing research, underscoring the potential of big data-driven approaches to uncover key insights and patterns.

Hinterlands, City Formation and Growth: Evidence from the U.S. Westward Expansion

Abstract I study how geography shaped city formation and aggregate development in the U.S. prior to the Civil War. To guide my analysis, I present a conjecture that cities’ farm hinterlands fostered both city development and aggregate growth: the hinterland hypothesis. The hinterland hypothesis has rich implications on how various elements of U.S. geography—railroads, changes in U.S. political borders, and international trade—affected city formation and U.S. growth. To evaluate the hinterland hypothesis and its implications, I assemble a novel historical dataset on population, trading routes, and agricultural productivity at a high spatial resolution. I combine the data with a dynamic quantitative model of economic geography that yields the hinterland hypothesis as a prediction. I find evidence for the hinterland hypothesis by showing that the model can replicate the key patterns of U.S. urbanization and city formation. Finally, I conduct a series of counterfactuals in the model to quantify the effect of geography on cities and growth, guided by the implications of the hinterland hypothesis. Results indicate that railroads were responsible for 1.8% of urban population in 1860 and for 25% of real GDP growth between 1830 and 1860. The effect of international trade was similar in magnitude, while the effect of political border changes was small during the period.

Efficient feature based video retrieval and indexing using pattern change with invariance algorithm

The amount of audio visual content kept in networked repositories has increased dramatically in recent years. Many video hosting websites exist, such as YouTube, Metacafe, and Google Video. Currently, indexing and categorising these videos is a time-consuming task. The system either asks the user to provide tags for the videos they submit, or manual labelling is used. The aim of this research is to develop a classifier that can accurately identify videos. Every video has content that is either visual, audio, or text. Researchers categorised the videos based on any of these three variables. With the Pattern Change with Size Invariance (PCSI) algorithm, this study provides a hybrid model that takes into account all three components of the video: audio, visual, and textual content. This study tries to classify videos into broad categories such as education, sports, movies, and amateur videos. Key feature extraction and pattern matching would be used to accomplish this. A fuzzy logic and ranking system would be used to assign the tag to the video. The proposed system is tested only on a virtual device in addition a legitimate distributed cluster for the aim of reviewing real-time performance, especially once the amount and duration of films are considerable. The efficiency of video retrieval is measured with metrics like accuracy, precision, and recall is over 99% success.

A discourse analysis of suicide ideation assessment among first year health professional students enrolled in a communications course

Background: Suicide risk assessments require a complex set of skills around a sensitive matter which can be difficult for providers. Aim: Research investigating communication techniques and the language choices used to assess for suicide ideation is limited. Methods: We analyzed 121 video-recorded and transcribed final exams from a communication skills course for first year health professional students to identify patterns and variation in the language choices made to assess for suicidal ideation in standardized patients exhibiting symptoms of depression. Results: We found that 66 of the 121 (55%) interviews included a suicide assessment. We noted key patterns and variation around when the assessments took place (while exploring depressive symptoms or as a topic shift), how they were prefaced (with ubiquity statements, normalization statements, or expressions of care and concern), and how the question itself was structured (with a negative preference structure, in a non-polar format, or ambiguously). Conclusions: Assessing for suicide is a delicate task for both patients and providers, both of whom may be reluctant to engage around the topic. Utilizing normalization statements as well as statements of care and concern is a good approach to assess suicide idation while exploring depressive symptoms.

Service Use Patterns by Children With Down Syndrome in a Canadian Region.

Children with Down syndrome require services from different sectors over time to optimize health and development, however, there is little information on longitudinal, cross-sector service use. Parents of children with Down syndrome attending a Canadian children's hospital participated in semistructured interviews covering life-time multiple sector service use. Five key service patterns were identified: (1) primary care physicians playing a circumscribed role; (2) a marked shift in public habilitative service receipt from development agencies in the preschool years to exclusive school delivery after school entry; (3) families obtaining private services to address gaps from public sector services; (4) a prominent role for parents to identify additional services; and (5) service variability as a function of timing and severity of medical comorbidity.

Transmission routes and patterns of helicobacter pylori

Helicobacter pylori (H.pylori), a gram-negative bacterium that colonizes the stomach, can cause chronic gastritis and peptic ulcers, as well as gastric cancer as a Class I carcinogen. However, the modes of H.pylori transmission are not clear. This review aims to clarify the transmission routes and patterns of H.pylori and identify efficacious prevention measures. Studies of H.pylori transmission were identified using PubMed, the Web of Science, and Cochrane Central; the retrieval deadline was October 2022. The transmission routes of H.pylori are discussed, focusing on the five primary transmission routes, namely fecal-oral, oral-oral, gastric-oral, anal-oral, and genital-oral. We propose that H.pylori is contracted through multiple transmission routes. Additionally, we summarize the key transmission patterns of H.pylori, including person-to-person and animal-to-human transmission, as well as foodborne and occupational exposure. Fecal-oral appears to be the most common H.pylori transmission routes. Although the oral-oral pathway is also important, the evidence does not support that this route of transmission is universal. The gastric-oral route occurs primarily in children and patients who are prone to vomiting. Meanwhile, the anal-oral and genital-oral routes remain hypothetical. Person-to-person and foodborne infections represent the predominant transmission patterns of H.pylori, whereas strong environmental and occupational limitations are associated with animal-to-human and occupational exposure.

Deterministic multi-level spin orbit torque switching using focused He+ ion beam irradiation

He+ ion irradiation is used to pattern multiple areas of Pt/Co/W films with different irradiation doses in Hall bars. The resulting perpendicular magnetic anisotropy landscape enables selective multilevel current-induced switching with full deterministic control of the position and order of the individual switching elements. Key pattern design parameters are specified, opening a way to scalable multi-level switching devices.

Comprehensive analysis of immune parameters, mRNA and miRNA profiles, and immune genes expression in the gill of rainbow trout infected with infectious hematopoietic necrosis virus (IHNV)

Rainbow trout (Oncorhynchus mykiss) is a species of cold-water fish with important economic values, widely cultivated worldwide. However, the outbreak of infectious hematopoietic necrosis virus (IHNV) caused the large-scale death of rainbow trout and seriously restricted the development of the trout farming industry. In this study, the changes of immune parameters in different periods (6-, 12-, 24-, 48-, 72-, 96-, 120-, and 144 h post-infection (hpi)), transcriptome profiles of 48 hpi (T48G) compared to control (C48G), and key immune-related genes expression patterns were measured in rainbow trout gill following IHNV challenge through biochemical methods, RNA sequencing (RNA-seq), and quantitative real-time polymerase chain reaction (qRT-PCR). The results showed that alkaline phosphatase (AKP), acid phosphatase (ACP), total superoxide dismutase (T-SOD), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) activities, as well as lysozyme (LZM) and malonaldehyde (MDA) content decreased and then increased during infection, and remained at a high level after 48 hpi (P < 0.05), whereas catalase (CAT) activity showed a significant peak at 48 hpi (P < 0.05). The mRNA and miRNA analysis identified 4343 differentially expressed genes (DEGs) and 11 differentially expressed miRNAs (DEMs), and numerous immune-related DEGs involved in the Toll-like receptor signaling pathway, apoptosis, DNA replication, p53 signaling, RIG-I-like receptor signaling pathway, and NOD-like receptor signaling pathway and expression were significantly up-regulated in T48Gm group, including tlr3, tlr7, tlr8, traf3, ifih1, trim25, dhx58, ddh58, hsp90a.1, nlrc3, nlrc5, socs3, irf3, irf7, casp7, mx1, and vig2. The integrated analysis identified several important miRNAs (ola-miR-27d-3p_R+5, gmo-miR-124-3-5p, ssa-miR-301a-5p_L+2, and ssa-miR-146d-3p) that targeted key immune-related DEGs. Expression analysis showed that tlr3, tlr7, traf3, ifih1, dhx58, hap90a.1, irf3, irf7, and mx1 genes increased and then decreased during infection, and peaked at 72 hpi (P < 0.05). However, trim25 expression peaked at 96 hpi (P < 0.05). This study contributes to understanding immune response of rainbow trout against IHNV infection, and provides new insights into the immune regulation mechanisms and disease resistance breeding studies.

Association of Tear Cytokine Concentrations with Symptoms and Signs of Dry Eye Disease: Baseline Data from the Dry Eye Assessment and Management (DREAM) Study

Purpose To describe tear concentrations of IL-1β, Il-6, IL-8, IL-10, IL-17A, IFNγ and TNFα in tears, collected by microcapillaries, and their correlation with symptoms and signs in subjects with dry eye disease (DED) in the DREAM Study. Methods Cytokine levels of patients with moderate to severe DED were determined using a magnetic bead assay. Scores for Ocular Surface Disease Index, corneal and conjunctival staining, tear break-up time (TBUT), and Schirmer’s test were obtained using standardized procedures. Associations of cytokines with each other and signs/symptoms were assessed with Spearman correlation coefficients (r). Results Assay results from 131 patient samples from 10 sites with tear volumes ≥ 4 ul were analyzed. Cytokine concentrations did not correlate with each other in a generally acknowledged pro-inflammatory/anti-inflammatory pattern, such as proinflammatory IL-17A and IFNγ were not inversely correlated to anti-inflammatory cytokine IL-10, and cytokines did not correlate with DED symptoms. Lower corneal staining was correlated with higher concentrations of IL-17A (r= −0.24, p = 0.006), IL-10 (r= −0.25, p = 0.005) and IFNγ (r= −0.33, p = 0.0001). Higher concentrations of IFNγ were associated with lower conjunctival staining (r= −0.18, p = 0.03). Higher concentrations of IL-17A were associated with higher TBUT scores (r = 0.19 p = 0.02). Conclusions Cytokines IL-10, IL-17A and IFNγ were highly correlated with each other but weakly correlated with some DED signs. No key cytokines or definitive expression patterns were identified in this study of moderate to severe DED patients. Further studies addressing various biases, including methodological and sampling biases, and standardization of methodology for inter-laboratory consistency are needed to confirm and establish pathological and clinical relevance of tear cytokines in DED.

Security and Data Privacy of Medical Information in Blockchain Using Lightweight Cryptographic System

In the healthcare system and hospital environment, the data security and the data connectivity are the major factors to consider for patient data management system. For that, there are several techniques are used to preserve and arrange the patient data with enhanced security system. In that, Blockchain structure of data management improves the secure data storage and transmission process. In the data security system, the quality measure can be validate by means of the size of key that are used for the encryption process. Combined with the blockchain, the encryption model is to be improved for the solve the problem in data security system. This also needs to focus on the size reduction of data storage due to the large key size of encrypted data. In the proposed work, Intuitionistic Derivative Symmetrical Encryption (IDSE) Algorithm based security algorithm along with blockchain function was integrated to form the authorized data storage and transmission process. For the key pattern generation, Differential Hashing Pattern (DHP) based key pattern extraction model was used for high speed data transmission and to reduce the size of data that are encrypted. The features that are considered for the appropriate security system are the data transmission pattern with respect to the time and the hashing model of key generation. In the result analysis, the performance of the IDSE-DHP are validated with the parameters of data transmission and loss rate in the Blockchain and with the throughput related features.

Inequitable Interactions: A Critical Quantitative Analysis of Mentorship and Psychosocial Development Within Computing Graduate School Pathways

Mentorship is vital to increasing graduate school access in computing; however, mentorship must be structured in power-conscious, developmental ways to ensure equitable access to and support within computing graduate pathways. I engage a critical quantitative lens to examine mentoring support among undergraduates with reported graduate aspirations, taking a nuanced look at departmental mentorship to investigate how organizational power in computing may maintain inequitable mentoring outcomes. Descriptive and regression analyses draw from a longitudinal sample of 442 graduate aspirants in computing who completed an introductory course survey (between 2015–2017) and a follow-up survey (fall 2019). Results document significant variation in forms of mentoring support and disciplinary psychosocial beliefs (i.e., computing identity and self-efficacy), with key patterns across graduate aspirants’ social identities and mentors’ organizational power (via their departmental roles). I conclude by discussing structural and social inequities in mentorship, which may underscore disparities in students’ realization of their computing graduate aspirations.

Multi-level Attack with Dynamic S-box Variable key Pattern Generation for Key Cohort Using AES

In recent times, data transmission in electronic medium is found to be more susceptible to several attacks. The study aims to control the multi-level attacks in encryption and decryption process by using Advanced Encryption Standard (AES) algorithm based S box operations. In AES based variable key generation pattern, every round generates the new key. The generation of multiple keys strengthen the operation of AES-dynamic S box. The AES algorithm performs operation on a 128 bit plain text and utilizes identical key for decryption and encryption process. The proposed algorithm shows significant improvements in the quality of encryption and decryption. The performance of the proposed system has been analysed in accordance with delay, power consumption and number of slices. Further the efficiency of the proposed system has been compared with other existing methods such as Positive Polarity Reed Muller (PPRM), Modified Positive Polarity Reed Muller (MPPRM) Twisted Binary Decision Diagram (TBDD) and Composite Field (CF) architecture. The results exposed that the proposed system outperforms with superior performance.

Bamenda Grassland Elites in the Race for Titles within the Multiparty Liberal Space in Cameroon

The decade spanning from the 1990s inaugurated the Cameroon Political outfit with trans-mutations and opportunities under the New Deal Regime that commands special attention. Each of these new adjustments warranted alternative positioning by the emerging political elites who had been circumstantially trapped within the threshold of so many opportunities that this liberal landscape was brandishing. One interesting outgrowth in this changing atmosphere was the fact that; traditional titles plus modern credentials turned out to be one of the key elements required for positioning and lobbying by these opportunistic elites. This article combines evidence combed from primary and secondary sources to answer key questions patterning to the tussle for titles by grassland elites in the guise of positioning themselves in the hub of opportunities that the somewhat liberal phase of the Cameroon New Deal era offered as from the 1990s. It particularly seeks to situate (a) The special climate that engineered these paradigmatic shifts by those presumed to be sufficiently savvy of tradition (b) the different categories of titles these elites raced for as well the reasons behind such a mad rush (c) the methods plus raison d’être of title conferment as well as (d) the impact of such deals in political positioning. Away from the positions/opportunities that were gained and lost by elites of this niche in this title drama, the paper proffer that the race to own titles and the politics around it played a big role in washing away the authority /command that titled men carried before this time not only within the grasslands but largely everywhere in Cameroon where such gimmicks became part of the game for gaining space in the realm of power. In all, it submits that this game rather polarized the elites against each other since each title holders proofed to be so ready to play or perform any mean deal so as to get appointed or other forms of compensations that mattered in the realm of opportunities. It opines therefore that such moves disgracefully eclipsed other genuine methods of getting the right people into the power trail on the basis of merit thereby, ruining the political space with wrong people from hence and any time after.

MANAGEMENT - DIGITAL TRANSFORMATION – CYBERSECURITY LINK: AN EMERGING RESEARCH TOPIC?

As our world continues to become more digitally oriented, modern business operations are increasingly reliant on cybersecurity, management, and digital transformation as critical components. This paper aims to investigate the relationship between cybersecurity, management, and digital transformation as reflected in the existing literature. Using bibliometric analysis as the primary methodology, this study examines a variety of academic works to gain a comprehensive understanding of the intersection of these three fields. The main objective is to identify key trends and patterns regarding the ways in which cybersecurity, management, and digital transformation are interconnected. By using the Scopus database, we identified 93 documents that could be analyzed starting with 2016, suggesting that the management – digital transformation – cybersecurity is an emerging topic.

Mechanism of kisspeptin neuron synchronization for pulsatile hormone secretion in male mice

The mechanism by which arcuate nucleus kisspeptin (ARNKISS) neurons co-expressing glutamate, neurokinin B, and dynorphin intermittently synchronize their activity to generate pulsatile hormone secretion remains unknown. An acute brain slice preparation maintaining synchronized ARNKISS neuron burst firing was used alongside invivo GCaMP GRIN lens microendoscope and fiber photometry imaging coupled with intra-ARN microinfusion. Studies in intact and gonadectomized male mice revealed that ARNKISS neuron synchronizations result from near-random emergent network activity within the population and that this was critically dependent on local glutamate-AMPA signaling. Whereas neurokinin B operated to potentiate glutamate-generated synchronizations, dynorphin-kappa opioid tone within the network served as a gate for synchronization initiation. These observations force a departure from the existing "KNDy hypothesis" for ARNKISS neuron synchronization. A "glutamate two-transition" mechanism is proposed to underlie synchronizations in this key hypothalamic central pattern generator driving mammalian fertility.

A meta-synthesis of research on in-service EFL teachers' needs for inset programs in Türkiye

The professionalization of teachers has become increasingly prevalent in recent years, leading to increased interest in the training, working conditions, and status of educators. This study addresses this interest by examining the in-service education and training (INSET) needs of English as a foreign language teachers in Türkiye. Despite recognizing the importance of in-service interventions for teacher development, educators often express concerns about the shortcomings of existing INSET programs. Key themes and patterns are identified through a meta-synthesis of ten relevant studies conducted between 2010-2021, including methodology, language skills, technology use, instructional practices, classroom environment, and material development. The analysis employs content and thematic analysis methods, enhancing the understanding of effective in-service training for English as a foreign language teachers and contributing to broader discussions on educators' training, working conditions, and status. The findings underscore the significance of designing INSET programs that address specific teacher needs, promote the practical application of new methods, and foster collaboration between the Ministry of National Education and teacher educators for successful implementation.

Deep Learning of Sparse Patterns in Medical IoT for Efficient Big Data Harnessing

The long-term and continuous streaming of big data from medical Internet of Things (IoT), poses a great challenge for the battery-limited tiny devices. To address this challenge, we propose a novel framework for medical IoT data sparsification, leveraging both deep learning and optimal space searching. More specifically, the deep sparsification networks are designed to learn to extract key sparse patterns in the medical IoT data, by projecting the original data stream to a sparsified data representation. Further, the principles for designing deep encoding networks have been analyzed by an optimal space searching strategy, aiming to determine the best deep sparsification architecture that meets the energy constraint or sparsification error constraint. Compared with state-of-the-art approaches, our deep learning-based and space search-optimized framework shows a dramatic capability to tackle the power hungriness problem on medical IoT big data. This novel study, by enabling energy-efficient medical IoT big data sparsification, is expected to boost the continuous and long-term medical IoT applications, such as cardiac monitoring, thereby advancing precision medicine.

Creative reindustrialization: Data base as a digital footprint for second-tier cities of the Urals and Siberia

The modern stage of development of research in the field of regional economics involves the application of a wide coverage of regional economic systems data. Their overall totals form a digital trace of the development of the territory. A scientific digital footprint of the key factors and patterns of creative industries in the second-tier cities of Siberia and the Urals, reflected in the web application, allows imagining, comparing and comprehending the current state and perspectives of creative industries in second-tier cities. In this article, considering the demography dynamics and diversification of creative business activity as well as data on created enterprises, the author highlights the cities that are interested in creative reindustrialization the most – oil and gas specialize cities of Khanty-Mansiysk autonomous okrug – Megion, Nefteyugansk, Nizhnevartovsk, Nyagan, and Uray. Second-tier cities that display a relatively higher level of economic activity diversification encompass Novokuznetsk, Biysk, Nyagan, Prokopyevsk, Rubtsovsk, Sysert, and Uray. At the same time large industrial centers in regions provide more favorable conditions for the development of creative enterprises. Whereas in the regional context, the Tomsk region and Altai Krai lag behind other regions in absolute terms. Thus, the first obvious strategical step in municipal development through creative reindustrialization is using the essential opportunities highlighted by demography conditions, mainly in oil and gas towns. Whereas large industrial centers in regions could use more favorable conditions for the development of creative enterprises for its further development.

Parkinson’s Disease Prediction System in Machine Learning

Around the globe, thousands of people worldwide are suffering by Parkinson’s Disease (PD), a central nervous system degenerative condition. Early detection and diagnosis of PD is crucial for successful treatment and management of the disease. In past few years, Machine learning (ML) algorithms has shown great potential in predicting PD based on various physiological and neurological markers. In this disease prediction system, a system is proposed using ML-based approach to predict the presence of PD in patients. The system employs various machine learning models, including Gradient Boosted Tree, random forest, and logistic regression, to identify key markers and patterns associated with the disease. Overall, this disease prediction system provides a valuable tool for early detection and diagnosis of PD, which can lead to better management and treatment of the disease. The proposed approach can also be extended to other neurological disorders, providing a general framework for disease prediction and diagnosis.

ТЕОРЕТИЧНИЙ ДИСКУРС МІЖНАРОДНОЇ ТРУДОВОЇ МІГРАЦІЇ: ЕКОНОМІЧНИЙ ВИМІР

The dominant channels of globalization of the labor market, as one of the determining patterns of its modern structural transformation, are, on the one hand, the convergence of individual subsystems of national labor markets and the elimination of legal, national-ethnic, cultural-humanitarian and other barriers between them, and on the other – international labor migration. Due to its economic nature and the driving forces of development, the cross-border movement of labor resources is an extremely complex process capable of exerting a powerful transformational influence on both the scale and structure of national labor markets, as well as the demographic, professional-qualification, educational, gender, and age composition of the population of states and entire regions. It is no accident that issues related to the regulation of international labor migration processes have become an integral component of global economic policy and the adoption of various political decisions regarding interstate cooperation in recent decades. In this regard, the substantiation of the conceptual design of the global theory of labor migration based on the generalization of its theoretical arsenal and taking into account the most constructive elements of existing theories and concepts acquires significant theoretical and methodological importance. And to generalize the theoretical discourse of international labor migration processes, let us emphasize the following: each of the theories and concepts of cross-border labor movement, having its competitive advantages and methodological flaws, performed an important ontological function in the formation of scientific views on its essence, driving forces, vector orientation, organizational-economic and institutional-regulatory formats, as well as the mechanisms of the impact of migration on global employment and the functioning of national labor markets. Their key methodological principles make it possible to adequately understand the key patterns of the development of international labor migration at various stages of global economic development, to forecast their prospective trends, as well as to develop effective migration policies of states and regional groups. Despite the fact that various aspects of the classical concepts of labor migration to some extent lose their relevance in modern conditions, they are still actively used by states and regional groups to solve a wide range of strategic goals and tasks of competitive development.