Search Results (52,557)

It is estimated that nearly five billion people do not have access to surgical care. Approximately 94% of individuals in low- and middle-income countries (LMICs) lack access to surgery in comparison to 14.9% in high-income countries (HICs). There are several urologic conditions requiring surgical intervention that are not treated because of the limited number of expert urologists in LMICs. Telesurgery is a concept that connects patients and surgeons in different locations through the use of a robotic surgery system. In this review, we explain the origins of telesurgery as well as the benefits and obstacles to its global implementation. Telesurgery can reduce travel times and the dangers associated with traveling for surgical care in LMICs. Additionally, telesurgery allows patients in LMICs to gain access to expert urologists while also providing effective training to upcoming surgeons. However, LMICs require substantial investment to improve digital infrastructure that will support urologic telesurgery. There will also be ethical, legal, and policy considerations that will need to be resolved for safe and equitable urologic telesurgery to occur. There have been multiple successful applications of urologic telesurgery, suggesting that the technology for this to become routine is already available. The time for international collaboration must begin now to reduce global disparities in access to urologic surgery. Full article

Connexin-43 (Cx43) is the most characterized gap junction protein, primarily involved in the Gap Junctional Intercellular Communication (GJIC) between adjacent cells to facilitate molecule exchange and the formation of a signaling network. It is increasingly evident that the importance of Cx43 is not only limited to its GJIC function, but rather includes its role in connecting the intracellular and extracellular environment by forming membrane hemichannels, as well as its intracellular signaling function mediated by its C-terminal tail (Cx43-CT). Notably, Cx43 has been implicated in a variety of cancers, with earlier notions suggesting a tumor-suppressor function, whereas new studies shed light on its pro-tumorigenic role. Moreover, apart from GJIC-based activities, the relevance of the non-canonical functions of Cx43 in tumor progression is being actively studied. This review provides an analysis of the current research on the pro-tumorigenic roles of Cx43, with a focus on Cx43-CT interactions and the function of hemichannels in cancer progression. A better understanding of the multifaceted functions of Cx43 in cancer biology could foster its recognition as a pivotal target for the development of innovative therapeutic strategies. Full article

Social media analysis aims to collect and analyze social media user information and communication content. When people communicate through messages, phone calls, emails, and social media platforms, they leave various records on their devices and the Internet, forming a huge social network. Community detection can help investigators analyze group leaders and community structure, which is significant to further crime control, identifying coordinated campaigns, and analyzing social network dynamics. This paper proposes the application of deep learning methods for community detection. Our main idea is to utilize social network topology and social network communication content to construct user features. The proposed end-to-end community detection framework is the implementation of Graph Convolution Network and can display the social network topology, locate the core members of the community, and show the connections between users. We evaluate our framework on the Enron email dataset. Experimental results indicate that our proposed model achieves a 1.1% higher modularity score than the unsupervised benchmark methods. We also concluded that the community detection framework should be able to analyze social networks, enabling investigators to reveal connections between people. Full article

This paper introduces a new concept of a connected-image set for a mapping, which extends the notion of edge-preserving properties with respect to mapping. We also present novel definitions of connected-image contractions, with a focus on fixed-point theorems involving auxiliary functions in b-metric spaces. The relationships between these mathematical concepts are explored, along with their applications to solving differential and integral equations. In particular, we discuss existence results for solving integral equations and second-order ordinary differential equations with inhomogeneous Dirichlet boundary conditions, as well as theorems related to contractions of the integral type. Full article

The aim of this paper is to examine the connections among time–frequency dependencies associated with electrical power consumption (EPC), economic growth, and financial development (FD) in Portugal, Italy, Greece, and Spain during the period 1970–2014. Using monthly data collected from the World Bank (WB) and Federal Reserve Bank of St. Louis (FRED), the wavelet analysis is applied, which allows for assessing the co-movement between these variables. As a first step, a classical time-domain approach is used to alternatively test the connection, including unit-root tests and cointegration. To achieve a comprehensive understanding of the relationships between EPC, economic growth, and FD, we employ Wavelet Transform Coherency (WTC) and Partial Wavelet Coherency (PWC) to explore both their temporal and phase-based dynamics. The main findings show that EPC leads FD, but in the short term, and periods dominated by economic stagnations and political crises. Otherwise, FD drives EPC in the medium term, under economic expansion periods. In both cases, economic growth is crucial, being a strong binding force of the interaction between EPC and FD. The difference in the applied results provides alternative policy implications, justifying the use of the wavelet approach. Full article

The widespread reliance on paper-based currency poses significant drawbacks, such as counterfeiting, lack of transparency, and environmental impacts. While Central Bank Digital Currencies (CBDCs) address many of these issues, their dependence on continuous internet connectivity limits their usability in scenarios with poor or no network access. To overcome such limitations, this paper introduces ElasticPay, a novel Peer-to-Peer (P2P) Offline Digital Payment System that leverages advanced hardware security measures realised through Trusted Platform Modules (TPMs), Trusted Execution Environments (TEEs), and Secure Elements (SEs). ElasticPay ensures transaction privacy, unforgeability, and immediate settlement while preventing double spending. Our approach integrates robust recovery mechanisms and provides a scalable solution for diverse environments. Extensive experimentation validates the system’s reliability and practicality, highlighting its potential to advance secure and inclusive CBDC ecosystems. We demonstrate the proposed solution implementation on the iPhone mobilephone because it has an inbuilt Secure Enclave, which is an integrated implementation of the necessary TPM, TEE, and SE functionalities. Full article

We develop a novel key routing algorithm for quantum key distribution (QKD) networks that utilizes a distribution of keys between remote nodes, i.e., not directly connected by a QKD link, through multiple non-overlapping paths. This approach focuses on the security of a QKD network by minimizing potential vulnerabilities associated with individual trusted nodes. The algorithm ensures a balanced allocation of the workload across the QKD network links, while aiming for the target key generation rate between directly connected and remote nodes. We present the results of testing the algorithm on two QKD network models consisting of 6 and 10 nodes. The testing demonstrates the ability of the algorithm to distribute secure keys among the nodes of the network in an all-to-all manner, ensuring that the information-theoretic security of the keys between remote nodes is maintained even when one of the trusted nodes is compromised. These results highlight the potential of the algorithm to improve the performance of QKD networks. Full article

Studies on selenium (Se) and silicon (Si) foliar biostimulation of different plants have been shown to affect concentrations of phenolic compounds. However, their effects on olive (Olea europaea L.) primary and secondary metabolites have not been fully investigated. Therefore, the effects of foliar sprayed Si and Se and their combination on the concentration of phenols, selected metabolites involved in the phenol biosynthesis, and mineral elements concentrations were determined in olive leaves of the field-grown cultivar Leccino. During the summer period, leaves were foliar sprayed three times, after which were sampled 30 days after the corresponding application. In general, foliar treatment of Si or Se increased the concentrations of several predominant phenolic compounds, such as oleuropein, oleacein, and specific flavonoids. The effects were especially pronounced after the third application in the harvest time sampling time. Amino acids and other phenol precursors were also significantly affected. The effects were phenol-specific and depended on the treatment, sampling time, and treatment × sampling time interaction. The response of verbascoside to the applied treatments appeared to be closely linked to corresponding changes in its amino acid precursors, such as tyrosine, while its connection with tryptophan and IAA has to be cautiously considered. In contrast, for other phenolic compounds like secoiridoids, a clear interdependence with their precursors was not identified, likely due to the more complex nature of their biosynthesis. The effects on the concentrations of elements other than Se and Si were milder. Full article

An interchange is a pivotal traffic facility that connects highways and controls access. It is necessary to study their dynamic response characteristics to analyze the operational safety of ramp bridges on interchanges. Based on the numerical simulation results of the finite element model of the Fuxing Interchange Bridge, non-destructive measurement techniques were used to conduct field dynamic load tests on the bridge, including ramp strain testing and acceleration testing. These tests aimed to study the dynamic response characteristics of the ramp bridge under moving loads. Due to the design speed limitation of the ramp bridge, the grey prediction GM(1, 1) model was used to predict the maximum dynamic deflection, maximum dynamic strain, and vibration acceleration when the vehicle speed was 60 km/h. Subsequently, finite element software was used to simulate the dynamic deflection under vehicle speeds ranging from 30 to 60 km/h. The simulated value was compared with the predicted value, and the difference between the simulated value and the predicted value was slight. This model can evaluate the operational safety performance of off-ramps at different speeds. Full article

The simplified tax system is the most common special tax regime in the Russian Federation in terms of the number of taxpayers. Tax revenues from the simplified tax system account for 6% of the structure of tax revenues of the consolidated budgets of the constituent entities of the Russian Federation and more than 93% of the structure of tax revenues from special tax regimes. The purpose of this study is to identify and assess the factors influencing tax revenues from the tax levied in connection with applying the simplified system of taxation (taxable object—income reduced by the amount of expenses). The objective of this study is to determine a set of factors used by economists to model the level of tax revenues and to conduct a corresponding econometric analysis of the influence of the selected factors on the dependent variable to identify characteristics of the simplified taxation system functioning in the Russian Federation. The object of this study is the per capita tax revenue from the tax levied in connection with applying the simplified system of taxation (the object of taxation is income reduced by expenses) in the Russian Federation. The subject of the research is a set of economic relations, which arise because of tax-legal relations between tax authorities and taxpayers in relation to the calculation of the tax levied in connection with the application of the simplified taxation system. This study’s hypothesis is that the amount of tax revenues is influenced by factors characterizing the economic situation and development of small and medium businesses in the constituent territories of the Russian Federation. This study was conducted in 83 constituent territories of the Russian Federation in 2020–2022. The research methods are statistical analysis and econometric modeling on panel data. During this study, six econometric models were constructed. Based on the results of specification tests, the least squares dummy variables model was selected. The results of the modeling show that the tax rate, the number of taxpayers, and the real average per capita monetary income of the population have a statistically significant impact on the per capita tax revenue under the simplified tax system (the object of taxation is income reduced by the number of expenses). As a result, the focus of economic policy at both macro and meso levels should be on the support of small and medium-sized enterprises in the early stages of their life cycle, as well as on the increase of the purchasing power of the population. Based on the results obtained, it is possible to forecast the revenue side of the budgets of the constituent entities of the Russian Federation. Full article

This study examines the prevalent practice of recycling patinated flint tools (“double patina”) of 18 lithic assemblages from three Late Lower Paleolithic sites in Israel. Determined as recycled from ‘old’ patinated items using visual observation, these tools, bearing both old, patinated surfaces and new modifications, offer insights into lithic strategies, cultural behaviors, and memory preservation. The study shows that the collection and recycling of ‘old’ patinated items into new tools was ubiquitously practiced, ranging from 41% at Late Acheulian Jaljulia and 11–17% at Acheulo-Yabrudian Qesem Cave. Two main recycling methods were identified, with variations across sites reflecting diverse cultural norms and functional needs (Type A–B). The type-B recycling trajectory was found to be the most prominent, as it prioritizes the preservation of the tool’s original appearance, patinated surfaces, and old scars. Following these features, the study additionally suggests that type-B recycling likely stemmed from necessity, cultural preferences, and a choice to connect with the past and preserve it, thus emphasizing the complex interplay of practicality, culture, and memory in the Late Lower Paleolithic period. Full article

The Ifugao Rice Terraces have been the Philippines’ first and only Globally Important Agricultural Heritage System (GIAHS) since 2011. More than a decade later, this study assesses whether Ifugao farmers find this designation beneficial and if it enhances their sense of involvement. Through a cross-sectional survey of GIAHS farmers in Banaue, Ifugao, this study examines perceived benefits and involvement, along with views on youth participation in agriculture, farmer livelihoods, and tourism management in Ifugao. The findings reveal that 65.1% of farmers see the GIAHS designation as beneficial and 58.7% feel involved. Farmers who perceive limited tourism benefits from the GIAHS are more likely to feel uninvolved, while those who value the designation’s potential for improving income and consumer demand for Ifugao rice report higher involvement. Cultural heritage and ancestral values are significant motivators, with some farmers viewing the GIAHS as a means of preserving traditions. Support from local government, subsidies, and media enhances involvement, particularly among those practicing rituals or growing the traditional Tinawon rice, which strengthens ties to the GIAHS. Additionally, farmers involved in discussions or training on Environmental Conservation Agriculture (ECA) report a stronger connection to the GIAHS, as ECA practices align with their traditional, sustainable approaches. Overall, this study highlights the complex role of the GIAHS as a bridge between cultural heritage, livelihood, and sustainability, underscoring the need to integrate farmer perspectives more closely into GIAHS initiatives in Ifugao. Full article

Double photoionization (DPI) allows for a sensitive and direct probe of electron correlation, which governs the structure of all matter. For atoms, much of the work in theory and experiment that informs our fullest understanding of this process has been conducted on helium, and efforts continue to explore many-electron targets with the same level of detail to understand the angular distributions of the ejected electrons in full dimensionality. Expanding on previous results, we consider here the double photoionization of two $2p$ valence electrons of atomic carbon and neon and explore the possible continuum states that are connected by dipole selection rules to the coupling of the outgoing electrons in ³P, ¹D, and ¹S initial states of the target atoms. Carbon and neon share these possible symmetries for the coupling of their valence electrons. Results are presented for the energy-sharing single differential cross section (SDCS) and triple differential cross section (TDCS), further elucidating the impact of the initial state symmetry in determining the angular distributions that are impacted by the correlation that drives the DPI process. Full article

The system inertia insufficiency brought on by a high percentage of wind power access to a power grid can be effectively resolved by wind-storage collaborative participation in primary frequency regulation (PFR). However, the impact of energy storage participation in system-frequency regulation is significantly influenced by its state of charge (SOC). In this paper, considering the SOC of energy storage (ES) and the stochastic characteristics of wind turbine (WT) output, the control strategy of wind-storage collaborative participation in the PFR of a system is proposed. Firstly, a WT adaptive inertia control and a model of storage droop control were constructed. Additionally, to prevent the problem of secondary frequency drop brought on by a separate rotational kinetic energy control, a wind-storage collaborative frequency-regulation control scheme was constructed. Secondly, considering changes in wind speed and the SOC of ES, an improved dynamic droop-control strategy for ES is proposed. This strategy was combined with the adaptive inertia control of the WT to establish the PFR of the WT collaborative participation system. Lastly, a simulation example of a two-region, four-machine system was used to validate the efficacy of the frequency-control strategy presented in this paper. The results show that a significant percentage of WTs connected to a power grid can effectively have their frequency-response ability improved by wind-storage collaborative control. Full article

The rapid development of Industrial Internet of Things (IIoT) technology has highlighted the critical role of wireless sensor networks in enabling intelligent production and equipment monitoring. Effective sensor deployment is essential for ensuring communication quality and transmission speed in IIoT environments. This paper presents a novel sensor deployment strategy that integrates four key metrics: deployment cost, energy consumption, network connectivity, and sensing probability. To address the challenges of multi-dimensional optimization, the proposed method normalizes these metrics and assigns appropriate weights based on their relative importance. A major innovation of this approach is the inclusion of larger-scale environmental obstacles, which enhances its adaptability to diverse industrial settings and specific deployment scenarios. Through a comprehensive set of simulation experiments across different scenarios, the proposed particle swarm/genetic hybrid algorithm demonstrates superior performance compared to existing methods, even surpassing 10% in performance. Specifically, it excels in optimizing the newly introduced network performance metric and significantly improves search convergence time, making it a highly efficient and effective solution for sensor network optimization in IIoT applications. Full article