Stable Connectivity Research Articles

Mimicking the Architecture and Dissolution Chemistry of Cancellous Bone Tissue to Optimize the Biocompatibility of Bioactive Scaffolds.

Synthesis of mechanically stable porous scaffolds with an architecture analogous to cancellous bone tissue poses significant challenges to bioactive glass (BG) based scaffolds. This is primarily due to densification and crystallization of the BG's during heat treatment. This study presents a modified BG series (42SiO2-xTiO2-24Na2O-21CaO-13P2O5, where x = 8 and 16 TiO2). TiO2 replaced the SiO2 concentration in the glass and was incorporated due to its biocompatibility and influence on glass structure. Material characterization determined that TiO2 did not induce crystallization within the glass but did increase the glass transition temperature (Tg) from 520°C to 600°C thereby indicating a more stable network connectivity. Scaffolds were synthesized using the foam replication method, resulting in scaffolds with a pore size of approximately 500 μm with the BG-4 composition (30SiO2-12TiO2-24Na2O-21CaO-13P2O5) retaining its amorphous character post-heat treatment. Scaffold ion release was monitored over 5-60 days in simulated body fluid (SBF). Si4+ release was found to decrease, while Ca2+ levels increased in SBF as TiO2 replaced SiO2 within the glass series. Cytocompatibility studies revealed that MC3T3 Osteoblast cells proliferated on the BG-4 scaffold surface and at its interface within culture media, and cell numbers were not significantly reduced.

UTILIZING LED USAGE ON FORTIMANAGER DEVICE AS A SOFTWARE MONITORING INDICATOR FOR FORTINET ACCESS POINTS

In today's digital era, stable connectivity and fast troubleshooting are crucial to support corporate, academic, and research activities. One important component in network infrastructure is the access point (AP) which functions to provide a wireless connection. With the large number of Access Points (AP) provided by campuses or offices, it is required to be easy to monitor and troubleshoot all Access Point (AP) devices. Fortigate, as a solution provider, offers access point and switch monitoring features using LED Usage. This study aims to explain how access point monitoring can be implemented effectively through the FortiManager device and is important to ensure that network devices are functioning properly. FortiManager devices can monitor switches that are connected with active or inactive status, how many active access points are on each switch are monitored, all of which clients are connected to the network can be monitored. Thus, FortiManager devices are very much needed by administrators and network technical teams to facilitate monitoring and troubleshooting.

Stable isotopy connectivity of gradient-like diffeomorphisms of 2-torus

One of the most important problems in the theory of dynamical systems (mentioned in the Palis-Pugh list) is the construction of a stable arc between structural stable diffeomorphisms in the space of diffeomorphisms. The paper considers the gradient-like diffeomorphisms of 2-torus that induce an isomorphism of fundamental groups determined by a matrix (−100−1). We prove that all such diffeomorphisms are stable isotopy connected.

Evaluating the Implementation of Automated Malaria Rapid Diagnostic Test Readers in Health Facilities in the Democratic Republic of Congo: Process, Challenges, and Lessons Learned.

The WHO's Global Technical Strategy for malaria emphasizes the importance of reliable malaria surveillance systems to track disease burden and measure progress. A key indicator, the test positivity rate (TPR), largely depends on healthcare providers' adherence to rapid diagnostic test (RDT) results and their accurate reporting. To minimize healthcare providers' bias, this study explored the feasibility of using artificial intelligence (AI)-driven Deki Reader devices in the Democratic Republic of Congo. The devices were deployed in 144 health facilities across Haut Katanga, Kasai Central, and Sud Kivu provinces from January to December 2022. Healthcare providers performed malaria diagnostic tests using RDTs and reported the results through the routine system. In addition, they used the Deki Reader device, which automatically read, recorded, and transmitted the AI interpretation into a cloud database. The study compared TPRs from both sources to identify discrepancies. The study revealed the feasibility of using these devices but also identified several logistic and technical challenges. These included delays in device procurement due to COVID-19 pandemic and customs issues, emphasizing the need for better planning and coordination in future rollouts. Device malfunctions and the reliance on stable internet connectivity highlighted the importance of robust support systems and contingency plans. This study demonstrated both the benefits and challenges of implementing such digital health technologies in primary health facilities. Key considerations for successful deployment include careful planning, adequate training and supervision, and taking into account local infrastructure, especially internet connectivity.

Evaluating brain volume segmentation accuracy and reliability of FreeSurfer and Neurophet AQUA at variations in MRI magnetic field strengths.

We aimed to compare the accuracy and reliability of two segmentation tools for magnetic resonance (MR) volumetry (FreeSurfer and Neurophet AQUA) at two magnetic field strengths (1.5T and 3T). We included 101 patients for the 1.5T-3T dataset and 112 for the 3T-3T dataset from three hospitals and five open-source datasets. The mean volume difference and average volume difference percentage with the change in magnetic field strength were compared between the methods. The hippocampus volume was larger with FreeSurfer than the Neurophet AQUA. In most brain regions, the Neurophet AQUA yielded a smaller average volume difference percentage (all < 10%) than FreeSurfer (all > 10%). The Neurophet AQUA exhibited more stable connectivity and regularity of the segmented components. Regarding volume, the Neurophet AQUA had effect sizes and ICCs comparable to those of FreeSurfer across the magnetic field strengths. With FreeSurfer, the original volume difference was small, whereas the average volume difference percentage was small with the Neurophet AQUA. Image segmentation took 1h with FreeSurfer and 5min with the Neurophet AQUA. When choosing an automatic segmentation method, the differences in image processing time and volume variability due to changes in the magnetic field strength of these methods should be considered.

Semaforización Inteligente: Un Análisis a los Desafíos en la Implementación de Tecnologías y Algoritmos IoT

Intelligent traffic signalization is a traffic control system designed to improve road safety and promote sustainable mobility. In this regard, an exhaustive literature review has examined the technologies, algorithms, and challenges associated with this system. For this purpose, 22 studies published between 2019 and 2023 were selected, following the PRISMA methodology along three phases: Planning, Implementation, and Documentation. The results highlight the implementation of technologies such as WI-FI and CCTV, which are predominantly used for connectivity and surveillance. In terms of algorithms, YOLO emerges as the most applied, addressing key challenges such as the need for stable connectivity and protection of data confidentiality. However, significant limitations are also identified, such as associated costs and social acceptance. Thus, it is inferred that technical innovations can counteract both the challenges and inherent limitations, therefore contributing to more efficient traffic management and life protection.

On-device Training: A First Overview on Existing Systems

The recent breakthroughs in machine learning (ML) and deep learning (DL) have catalyzed the design and development of various intelligent systems over wide application domains. While most existing machine learning models require large memory and computing power, efforts have been made to deploy some models on resource-constrained devices as well. A majority of the early application systems focused on exploiting the inference capabilities of ML and DL models, where data captured from different mobile and embedded sensing components are processed through these models for application goals such as classification and segmentation. More recently, the concept of exploiting the mobile and embedded computing resources for ML/DL model training has gained attention, as such capabilities allow (i) the training of models via local data without the need to share data over wireless links, thus enabling privacy-preserving computation by design, (ii) model personalization and environment adaptation, and (iii) deployment of accurate models in remote and hardly accessible locations without stable internet connectivity. This work summarizes and analyzes state-of-the-art systems research that allows such on-device model training capabilities and provides a survey of on-device training from a systems perspective.

Altered dynamic large-scale brain networks and combined machine learning in primary angle-closure glaucoma

Primary angle-closure glaucoma (PACG) is a severe and irreversible blinding eye disease characterized by progressive retinal ganglion cell death. However, prior research has predominantly focused on static brain activity changes, neglecting the exploration of how PACG impacts the dynamic characteristics of functional brain networks. This study enrolled forty-four patients diagnosed with PACG and forty-four age, gender, and education level-matched healthy controls (HCs). The study employed Independent Component Analysis (ICA) techniques to extract resting-state networks (RSNs) from resting-state functional magnetic resonance imaging (rs-fMRI) data. Subsequently, the RSNs was utilized as the basis for examining and comparing the functional connectivity variations within and between the two groups of resting-state networks. To further explore, a combination of sliding time window and k-means cluster analyses identified seven stable and repetitive dynamic functional network connectivity (dFNC) states. This approach facilitated the comparison of dynamic functional network connectivity and temporal metrics between PACG patients and HCs for each state. Subsequently, a support vector machine (SVM) model leveraging functional connectivity (FC) and FNC was applied to differentiate PACG patients from HCs. Our study underscores the presence of modified functional connectivity within large-scale brain networks and abnormalities in dynamic temporal metrics among PACG patients. By elucidating the impact of changes in large-scale brain networks on disease evolution, researchers may enhance the development of targeted therapies and interventions to preserve vision and cognitive function in PACG.

Assessing population viability and management strategies for species recovery of the critically endangered Puerto Rican parrot

AbstractRecovery of endangered species is challenging and lengthy, especially when it involves reintroduction and dynamic environmental conditions. Because managers often need to decide between many management strategies with uncertain outcomes, periodically assessing progress toward recovery using population viability analysis (PVA) can help guide decision‐making. We developed a PVA for the critically endangered Puerto Rican parrot (Amazona vittata) to evaluate current status and potential future management strategies to reach goals set in the Recovery Plan. Having grown from their nadir of 13 birds in 1976 to 686 in 2021, the recovery effort has made great progress. Using 15 years of data, we built an individual‐based PVA that included interactions between two captive and three wild populations connected via annual releases. If management continues as planned, the wild populations have no to moderate risks of extinction (0–32%) over the next 100 years. However, wild populations remain dependent on releases to sustain growth, and recovery targets for stable population growth and connectivity have not yet been reached. Our analysis suggests that hurricanes are an impediment to reaching recovery targets and impact some wild populations more than others based on geography. Projections with climate‐change‐induced higher hurricane impact resulted in wild populations being less likely to stabilize. We identified demographic rates and associated management strategies that could positively impact wild populations: increasing reproduction (e.g., via increasing artificial nests, improving nest success) and decreasing first‐year mortality (e.g., via targeted predator control). Based on our current understanding of Puerto Rican parrot demographics, species recovery will continue to be management‐dependent unless demographic rates can be altered. As more data are gathered, especially for data‐sparse populations and in the face of environmental change, future iterations of this model can re‐evaluate progress, update management strategies, and provide support for deciding if and when to delist this iconic species.

INFORMATION SEEKING STRATEGIES AND FACTORS INFLUENCING INFORMATION UTILISATION BY FEMALE LIBRARIANS IN UNIVERSITIES IN KANO STATE, NIGERIA

The study investigated information seeking strategies and factors influencing information utilisation by female librarians in universities in Kano State, Nigeria. Preliminary observations showed that many female librarians do not seem to be using the library to seek required information, which may be due to lack of awareness and utilisation of library resources and services, searching skills, Internet connectivity and assistance from their male colleagues. Thus, the study set out to ascertain the information seeking strategies and identify the factors that influencing the utilisation of information resources of female librarians in universities in Kano State. The study employed qualitative methodological approach using a narrative-based design. The population comprised 10 female librarians with highest academic qualifications. The study found out that attending professional conferences, seminars and workshops, using shelf-guides to locate materials, searching e-databases, browsing Google, and seeking assistance from colleagues were the adopted strategies. It was also found that awareness of resources’ availability, conducive environment, proximity, accuracy and reliability, among others, facilitated the resources’ utilisation. Based on these findings, the study concludes that for female librarians to discharge their duties effectively and efficiently, there is a need to develop a good seeking strategies as a professional solely responsible for information processing and information services delivery to information users at different levels. Thus, the study recommended the need to provide adequate funds, organise seminars, conferences and workshops; providing solar energy as an alternative to epileptic nature of power sources, university managements should provide stable Internet connectivity.

Higher general intelligence is associated with stable, efficient, and typical dynamic functional brain connectivity patterns

Abstract General intelligence, referred to as g, is hypothesized to emerge from the capacity to dynamically and adaptively reorganize macroscale brain connectivity. Temporal reconfiguration can be assessed using dynamic functional connectivity (dFC), which captures the propensity of brain connectivity to transition between a recurring repertoire of distinct states. Conventional dFC metrics commonly focus on categorical state switching frequencies which do not fully assess individual variation in continuous connectivity reconfiguration. Here, we supplement frequency measures by quantifying within-state connectivity consistency, dissimilarity between connectivity across states, and conformity of individual connectivity to group-average state connectivity. We utilized resting-state functional magnetic resonance imaging (fMRI) data from the large-scale Human Connectome Project and applied data-driven multivariate Partial Least Squares Correlation to explore emergent associations between dynamic network properties and cognitive ability. Our findings reveal a positive association between g and the stable maintenance of states characterized by distinct connectivity between higher-order networks, efficient reconfiguration (i.e., minimal connectivity changes during transitions between similar states, large connectivity changes between dissimilar states), and ability to sustain connectivity close to group-average state connectivity. This hints at fundamental properties of brain–behavior organization, suggesting that general cognitive processing capacity may be supported by the ability to efficiently reconfigure between stable and population-typical connectivity patterns.

Analysing Customers’ Perception on QR Payment in Kathmandu Valley: An Empirical Study using UTAUT and PLS-SEM

Background: The growing use of the Fintech industry significantly impacts the popularity of QR payment. The easy and convenient use of digital payment systems has increased the adoption of QR payments. The study analyses customers' perceptions of QR payment in the Kathmandu Valley. Methods: The study uses explanatory research design to analyse the connections and causal effects between the determinants that affect the customer perceptions of using the QR payment system in the Kathmandu Valley. Non-probability sampling with convenient sampling is used for the study. Data is collected from 280 customers who have used QR payment services using the Structural Questionnaire through the Kobo Toolbox. Similarly, the Structural Equation Modeling (SEM) using the Partial Least Square (PLS) version 4.0 is adopted for analysis. Results: The study highlights a growing trend among respondents, with an increasing number habitually using QR payments for 1-3 years. E-sewa, Fone pay, and Connect IPS are popular choices for activities like fund transfers and bill payments. Despite facing challenges such as technical glitches and debited funds from failed transactions, respondents view QR payments as a convenient method. However, these challenges can be addressed through regular maintenance, enhanced internet infrastructure, transaction flexibility, stable connectivity, and improved system performance. Conclusions: The result shows a significant relationship between the independent variables, such as performance expectation and facilitating conditions and the dependent variable, i.e., customer perception. It indicates that when users perceive higher performance benefits from QR payment, their overall perception improves. Similarly, when users perceive a favourable environment for QR payment adoption, their perception is positively influenced, enforcing the increasing use of QR payment. Paper Type: Research Type

Spatial and temporal change of hydrological connectivity in the Wusuli River Basin

Study regionThe study region of this paper is the Wusuli River basin, which is comprised of nine sub-basins. The basin is located on the border between China and Russia. Study focusWe investigated the hydrological connectivity of the Wusuli River basin, an international boundary river that has received little attention. The spatial and temporal evolution of hydrological connectivity over the last 38 years was characterized using a geostatistical connectivity function combined with the remote sensing technique. In particular, some key sub-basins were identified to help strengthen China-Russian cooperation on ecological protection of the basin. New hydrological insights for the regionThe results show that the hydrological connectivity in the northwestern region of the Wusuli River basin was unstable with several surges from 1984 to 2021. Analyzed from a temporal perspective, the effective range of hydrological connectivity is expanding and connectivity is showing an overall upward trend due to increased fluctuations in rainfall. Analyzed from a spatial perspective, the connectivity of the right bank of the Wusuli River is better than that of the left bank due to the influence of topography. Stable connectivity pathways are a must for efficient hydrological connectivity within a watershed. Another finding is that the capacity of the Wusuli River basin to resist extreme rainfall is weakening.

Beyond Mobile Payments: Exploring the Evolution and Future of Fintech (BY IJISRT)

In today's digital age, FinTech’s have become universal, transforming the way individuals conduct financial transactions. However, with the convenience of Fintech also come challenges that users encounter. This book chapter investigates into the changing landscape of Fintech challenges, drawing insights from a comprehensive survey conducted among various respondents The survey finds three primary obstacles faced by users during Fintech: network issues, time consumption, and privacy concerns. Notably, a significant proportion of respondents reported encountering network-related problems, highlighting the critical role of stable connectivity in facilitating seamless transactions. Moreover, the chapter explores into the foiling experienced by users due to the time-and privacy nature of the payment process, shedding light on the need for streamlined and efficient payment mechanisms. Building upon the survey findings, the chapter offers valuable insights into potential strategies and solutions to address these challenges. By elucidating practical approaches and technological innovations aimed at enhancing Fintech systems' efficiency and security, the chapter equips readers with actionable knowledge to navigate the digital payment landscape effectively. This study's findings add to academic discussion and have practical implications for policymakers, industry practitioners, and educators.

Healthcare workers' perspectives on the availability and use of mobile health technologies for disease diagnosis and treatment support in the Ashanti Region of Ghana.

Considering the usefulness of mobile health (mHealth) technologies in healthcare delivery in low- and middle-income countries, including Ghana; there is a need to explore healthcare professionals' perspectives on the availability and use of mHealth for disease screening and treatment of patients' conditions. The study's main aim is to explore healthcare professionals' perspectives regarding the availability and use of mHealth applications for disease screening and management at point-of-care in Ghana's Ashanti Region. We conducted in-depth interviews with healthcare professionals who use mHealth applications daily between July and September 2020. A purposive sampling strategy was employed to select healthcare professionals who have been using mobile health application tools to support healthcare delivery. The researchers conducted 14 in-depth interviews with healthcare professionals on the availability and use of mHealth applications to support disease diagnosis and treatment of patients' conditions. Data were transcribed, coded, arranged, and analyzed to determine categories and themes. The study results demonstrated that healthcare workers had positive perceptions towards mHealth applications. Healthcare professionals identified significant challenges concerning mHealth applications: the high cost of data; lack of education or limited awareness; poor mobile networks; unstable internet connectivity; erratic power supply; and unavailability of logistics. Healthcare professionals identified the following prerequisite strategies to strengthen the use and scale-up of mHealth applications: stable internet connectivity; creating awareness; supplying logistics; reducing the cost of data; and developing local mobile apps. The study results revealed the availability of mHealth applications at the individual level for disease screening and treatment support of patients' conditions. The study also showed several significant challenges facing mHealth applications which need to be addressed to guarantee the successful implementation and scaling-up of mHealth activities at all levels of healthcare delivery. Hence, future research should incorporate healthcare professionals' perspectives to completely understand mHealth implementation and scaling-up challenges and measures to inform policy regulations.

Measurement and Analysis of 4G/5G Mobile Signal Coverage in a Heavy Industry Environment.

In the evolving landscape of Industry 4.0, the integration of advanced wireless technologies into manufacturing processes holds the promise of unprecedented connectivity and efficiency. In particular, the data transmission in a heavy industry environment needs stable connectivity with mobile operators. This paper deals with the performance study of 4G and 5G mobile signal coverage within a complex factory environment. For this purpose, a cost-effective and portable measurement setup was realized and used to provide long-term measurement campaigns monitoring and recording several key parameter indicators (KPIs) in 4G/5G downlink and upload. To support the reproducibility of the provided study and other research activities, the measured dataset is publicly available for download. Among others findings, the obtained results show how the performance of 4G/5G is influenced by a heavy industry environment and of the time of day on the network load.

Low discrepancy on non-linear sensor deployment in a time-critical linear IIoT network

Linear networks are characterized by their long and narrow topology, which transmits data in a linear manner. For time-critical linear IIoT networks, stable connectivity is paramount. A good deployment strategy ensures stable connectivity in the network and maximize the lifetime and coverage of the network. In order to achieve this goal, deployment strategies should address tunnelling effects in linear networks. The proposed method tackles three major issues: 1. minimizing tunnelling effects using non-linear sensor deployment method, 2. maximizing network coverage by introducing a modified Latin Hypercube Sequence (LHS), and 3. Minimizing data interference in the multichannel TSCH network using a neighbour count-based sensor node deployment technique. The simulation validates the efficacy of the suggested approach in prolonging the network’s lifespan by mitigating the tunnelling effect near the sink. Moreover, it optimally utilizes over 70% of the mean energy within the network system. This is a significant improvement over previous algorithms which often failed to even utilizing 40% of the energy, and many a times much lesser. In terms of network coverage, it surpasses other algorithms. Consequently, the proposed method delivers economic advantages by extending the network’s longevity, achieved through a higher number of nodes concentrated around the sink, and significantly reduces the tunnelling effect in the network.

Mobile Learning and Life-long Learning: Nurturing Higher Education Students' Learning in the Face of Uncertainty

Since the beginning of the COVID-19 disease in late 2019, a majority of the learners from Higher Education Institutions (HEI) have resorted to blended and distance learning. There has been extensive discussion concerning distance learning; however, the aspects that motivate learners to use mobile phones for learning are yet to be explored comprehensively. This paper identifies the aspects that could potentially motivate learners to start using mobile devices for learning, which is referred to as mobile learning (m-Learning); it motivates the learners to participate in studies. Such is the case because a majority of the learners need to find time to focus on studies. This is especially significant for remote studying because it brings several challenges like domestic work and work-life balance that need to be ensured along with studies. Furthermore, learners may miss online classes due to lack of stable connectivity. This is where m-Learning has its advantages since it is independent of place and time. With the intent to provide HEI learners with an appropriate learning environment, this paper comprises a review of previous research concerning m-Learning design. It is understood that the situation and age of an HEI learner should be the basis for determining the andragogical factors. It is suggested that future research in this domain focus on assessing the factors that promote m-Learning among HEI learners so that these individuals can continue education despite having physical distance from their peers.

Air–ground integrated artificial intelligence of things with cognition-enhanced interference management

Integrated air–ground network enhances AIoT performance by improving spectral efficiency, achieving high-speed, stable network connectivity, and enabling sensing, learning, and decision-making. However, unmanned aerial vehicles (UAVs) can lead to local spectrum congestion and competition. To address this issue, intelligent signal processing techniques are employed to enhance AIoT system performance and stability through intelligent multi-channel sensing and communication. A novel communication framework inspired by brain cognition for UAV communication in heterogeneous environments is introduced. This framework iteratively determines the importance of signals, effectively eliminating unimportant signals with interference characteristics, and reducing their transmission power. Simulation results demonstrate the superiority of this method in terms of communication performance.

Scenario of stable transition from diffeomorphism of torus isotopic to identity one to skew product of rough transformations of circle

In this paper, we consider gradient-like diffeomorphisms of a two-dimensional torus isotopic to the identical one. The isotopicity of diffeomorphisms $f_0$, $f_1$ on an $n$-manifold $M^n$ means the existence of some arc $\{f_t:M^n\to M^n,t\in[0,1]\}$ connecting them in the space of diffeomorphisms. If isotopic diffeomorphisms are structurally stable (qualitatively not changing their properties with small perturbations), then it is natural to expect the existence of a stable arc (qualitatively not changing its properties under small perturbations) connecting them. In this case, one says that the isotopic diffeomorphisms $f_0$, $f_1$ are stably isotopic or belong to the same class of stable isotopic connectivity. The simplest structurally stable diffeomorphisms on surfaces are gradient-like transformations having a finite hyperbolic non-wandering set, stable and unstable manifolds of various saddle points of which do not intersect. However, even on a two-dimensional sphere, where all orientation-preserving diffeomorphisms are isotopic, gradient-like diffeomorphisms are generally not stably isotopic. The countable number of pairwise different classes of stable isotopic connectivity is constructed on the base of a rough transformation of the circle $\phi_{\frac{k}{m}}$ with exactly two periodic orbits of the period $m$ and the rotation number $\frac{k}{m}$, which can be continued to a diffeomorphism $F_{\frac k m}:\mathbb S^2\to\mathbb S^2$ with two fixed sources at the North and South poles. On the torus $\mathbb T^2$, the model representative in the considered class is the skew products of rough transformations of a circle. We show that any isotopic gradient-like diffeomorphism of a torus is connected by a stable arc with some model transformation.