Search

For a simple, finite, and connected graph G, the spherical maximal operator is defined as ... where ... is the sphere with center at t and having radius r. In this paper, we consider the spherical maximal operator ... on ... spaces and calculate the ... for ... and estimate the ... for ..., when G is Km. Furthermore, We establish the maximum and minimum bounds for the spherical maximum operator on finite graphs and indicate the graphs that achieve these bounds. [ABSTRACT FROM AUTHOR]

This paper presents an innovative approach to enhance the querying capability of ChatGPT, a conversational artificial intelligence model, by incorporating voice-based interaction and a convolutional neural network (CNN)-based impaired vision detection model. The proposed system aims to improve user experience and accessibility by allowing users to interact with ChatGPT using voice commands. Additionally, a CNN-based model is employed to detect impairments in user vision, enabling the system to adapt its responses and provide appropriate assistance. This research tackles head-on the challenges of user experience and inclusivity in artificial intelligence (AI). It underscores our commitment to overcoming these obstacles, making ChatGPT more accessible and valuable for a broader audience. The integration of voice-based interaction and impaired vision detection represents a novel approach to conversational AI. Notably, this innovation transcends novelty; it carries the potential to profoundly impact the lives of users, particularly those with visual impairments. The modular approach to system design ensures adaptability and scalability, critical for the practical implementation of these advancements. Crucially, the solution places the user at its core. Customizing responses for those with visual impairments demonstrates AI's potential to not only understand but also accommodate individual needs and preferences. [ABSTRACT FROM AUTHOR]

Advances in electro‐ionic soft actuators hold significant potential as next‐generation bioelectronic interfaces due to mechanical compliance and operation in agreement with soft biological tissues and low voltages. However, current devices call for encapsulation strategies to accommodate high mechanical demands and long‐term stability in environmental changes. In this study, a durability of polyvinylidene‐fluoride‐co‐hexafluoropropylene (PVDF‐co‐HFP) honeycomb skeleton electrolyte encapsulated with a biocompatible polyisobutylene (PIB) thin film is being investigated. A low water vapor transmission rate (0.61 g m−2 day−1) and elastic modulus (10 kPa) are measured from a 7.5 µm‐thick thin‐modified PIB‐encapsulation layer. The PIB‐encapsulated soft actuator maintains 68% of its mechanical durability after 40 000 cycles of zero‐to‐tension fatigue loading at room temperature. A cantilever actuation test of the PIB‐encapsulated 3mm‐wide 30mm‐long actuator film shows a large tip displacement (15.90 mm) at a low voltage (±1.5 V) under 0.1 Hz, 37 °C, 50% relative humidity (RH). Most importantly, while the unencapsulated actuator immediately degrades in a few cycles at 37 °C, 50%RH, and 0.1% applied strain, PIB‐encapsulated soft actuator performs up to 6500 dynamic actuation cycles without any functionality degradation. Exceptional durability against mechanical fatigue and stability at elevated temperature and humidity meet the prerequisite for future soft biomedical robots that enable long‐lasting safe operations. [ABSTRACT FROM AUTHOR]

This paper examines the propagation of M-shape solitons and their interactions with kink waves to the (2 + 1)-dimensional integrable Schwarz-Korteweg-de Vries (ISKdV) problem by applying the symbolic computation with ansatz functions technique and logarithmic transformation. The governing model usually appears in the nonlinear shallow water waves and fluid mechanics. We discuss various nonlinear waves like multiwave solutions (MSs), homoclinic breather (HB), M-shape solitons, single exponential form (one-kink), and double exponential form (two-kink). These waves have lot of applications in fluid dynamics, nonlinear optics, chemical reaction networks, biological systems, climate science, and material science. We also study interaction among M-shape solitons with kink wave. At the end, we discuss the stability characteristics of all solutions. [ABSTRACT FROM AUTHOR]

Low oxygen tension, or hypoxia is the driving force behind tumor aggressiveness, leading to therapy resistance, metastasis, and stemness in solid cancers including breast cancer, which now stands as the leading cause of cancer-related mortality in women. With the great advancements in exploring the regulatory roles of the non-coding genome in recent years, the wide spectrum of hypoxia-responsive genome is not limited to just protein-coding genes but also includes multiple types of non-coding RNAs, such as micro RNAs, long non-coding RNAs, and circular RNAs. Over the years, these hypoxia-responsive non-coding molecules have been greatly implicated in breast cancer. Hypoxia drives the expression of these non-coding RNAs as upstream modulators and downstream effectors of hypoxia inducible factor signaling in the favor of breast cancer through a myriad of molecular mechanisms. These non-coding RNAs then contribute in orchestrating aggressive hypoxic tumor environment and regulate cancer associated cellular processes such as proliferation, evasion of apoptotic death, extracellular matrix remodeling, angiogenesis, migration, invasion, epithelial-tomesenchymal transition, metastasis, therapy resistance, stemness, and evasion of the immune system in breast cancer. In addition, the interplay between hypoxia-driven non-coding RNAs as well as feedback and feedforward loops between these ncRNAs and HIFs further contribute to breast cancer progression. Although the current clinical implications of hypoxia-driven non-coding RNAs are limited to prognostics and diagnostics in breast cancer, extensive explorations have established some of these hypoxia-driven non-coding RNAs as promising targets to treat aggressive breast cancers, and future scientific endeavors hold great promise in targeting hypoxia-driven ncRNAs at clinics to treat breast cancer and limit global cancer burden. [ABSTRACT FROM AUTHOR]

Consumer knowledge of the goods produced or processed by the numerous suppliers and processors is still relatively low due to the growing complexity of the structure of pharmaceutical supply chains. Information asymmetry in the pharmaceutical sector has an effect on welfare, sustainability, and health. (1) Background: In this respect, we wanted to develop a productive structure for a pharmaceutical supply chain that satisfies the consumer information needs and fosters consumer confidence in the pharmacy goods they buy. By using blockchain technology, the main goals were to develop and implement a pharmaceutical supply chain. (2) Objectives: The main objectives of this work were to leverage an Ethereum platform for the development of a tractability system in a pharmaceutical supply chain environment and to analyze the efficiency of MSMAChain with respect to the cost and execution of transactions based on our designed smart contracts. (3) Results: This research looked into a variety of issues related to the value, viability, and effects of blockchain technology for use in supply chain applications. The methods and creations in this environment were monitored and researched. It is vital to identify a number of crucial subjects including future research areas, in order to achieve the widespread acceptance of the supply chain traceability provided by blockchain technology. (4) Conclusions: MSMAChain, an Ethereum blockchain-based approach, leverages smart contracts and decentralized off-chain storage for efficient product traceability in terms of the cost and execution of transaction for a health care supply chain. [ABSTRACT FROM AUTHOR]

In this paper, we will define a new metric space called n-gonal graphical b-metric space. We will also prove some fixed point theorems in said metric space and give suitable examples to illustrate our results. These results will help to solve many nonlinear convex models in machine learning and optimization by formulating them in fixed point schemes of optimization. Our paper opens the door for researchers to work in the intersecting area of machine learning and functional analysis in the frame work of n -gonal graphical b -metric space. [ABSTRACT FROM AUTHOR]

Content naming and lookup are decisive functions of the future architecture named data network (NDN). The core concept of NDN is the content distribution between consumers and content providers. The NDN supports advance vehicular networks that is famous with vehicular-named data network (VNDN) with different naming schemes such as hybrid, flat, attribute-based, and hierarchical names. These schemes are used in a static way for vehicular network, in summary, the hybrid, flat, and attribute-based makes a complex structure, and on the other hand, hierarchical names long in length and name lookup performance are a bottleneck in NDN, which can directly affect the network performance. Therefore, we introduce a dynamic naming scheme and lookup method (DNSL) for VNDN to mitigate these issues. We argue that the dynamic naming scheme is a better approach to VNDN, while the static name is a cost-effective, hefty, integrated fashion, and improper for the vehicular network. This study focuses on (1) a dynamic naming scheme using dynamic-tag and (2) a lookup method based on node partition of trie; the trie approach is very famed in data structure and extensively used for the lookup content, insertion, and deletion processes. Our experimental evaluation shows that the DNSL scheme is highly efficient, scalable, and provably correct for VNDN. [ABSTRACT FROM AUTHOR]

Managing the integrity of products and processes in a multi-stakeholder supply chain environment is a significant challenge. Many current solutions suffer from data fragmentation, lack of reliable provenance, and diverse protocol regulations across multiple distributions and processes. Amongst other solutions, Blockchain has emerged as a leading technology, since it provides secure traceability and control, immutability, and trust creation among stakeholders in a low cost IT solution. Although Blockchain is making a significant impact in many areas, there are many impediments to its widespread adoption in supply chains. This article is the first survey of its kind, with detailed analysis of the challenges and future directions in Blockchain-enabled supply chains. We review the existing digitalization of the supply chain including the role of GS1 standards and technologies. Current use cases and startups in the field of Blockchain-enabled supply chains are reviewed and presented in tabulated form. Technical and non-technical challenges in the adoption of Blockchain for supply chain applications are critically analyzed, along with the suitability of various consensus algorithms for applications in the supply chain. The tools and technologies in the Blockchain ecosystem are depicted and analyzed. Some key areas as future research directions are also identified which must be addressed to realize mass adoption of Blockchain-based in supply chain traceability. Finally, we propose MOHBSChain, a novel framework for Blockchain-enabled supply chains. [ABSTRACT FROM AUTHOR]

Background: Breast cancer (BC), the most common cause of cancer death in women, overtook lung cancer as the leading cause of cancer worldwide in 2020. Although many studies have proposed KIN17 as a biomarker of tumorigenesis in different cancer types, its role in tumor metastasis, particularly in BC metastasis, has been underexplored. This study aimed to explore the role of KIN17 in BC metastasis. Methods: Survival analyses was performed to identify the association between KIN17 expression and BC patient survival in silico. Using lentivirus constructs, we developed bidirectional KIN17 expression (KD, knockdown; OE, overexpression) cellular models of luminal‐A (Lum‐A) breast cancer MCF‐7 cells. We performed in vitro wound healing, transwell with and without Matrigel assays, and in vivo tail‐vein metastasis assay to evaluate the migration and invasion abilities of MCF‐7 with stable KIN17 knockdown or overexpression. Western blotting was performed to compare the changes in protein expression. Results: We found that KIN17 expression was associated with poor overall survival (OS), relapse‐free survival (RFS), distant metastasis‐free survival (DMFS) and post‐progression survival (PPS), particularly in Lum‐A breast cancer patients. Later, we found that KIN17 knockdown inhibited migration and invasion of MCF‐7 cells via regulating EMT‐associated signaling pathways in vitro and decreases metastatic spread of the disease in vivo. In contrast, KIN17 overexpression promoted migration and invasion of MCF‐7 cells in vitro and increased the metastatic spread of the disease in vivo. Conclusions: Overall, our findings provide preliminary data which suggests KIN17 of importance to target in metastatic Lum‐A patients. [ABSTRACT FROM AUTHOR]

In order to promote the electrochemical reduction of CO2 into valuable products and chemical feedstock, the refinement of inexpensive, functioning, highly discerning catalysts is of utmost importance to alleviate inordinate carbon dioxide emissions in the atmosphere. This study presents an innovative electrocatalyst composed of MnO and CuO nanoparticles anchored onto Mn: Cu(1:2)@MOF. These nanocomposites offer multiple active sites for electrochemical carbon dioxide reduction, resulting in a striking current density of almost − 58 mAcm−2 at − 2 V vs. Ag/AgCl (reference electrode) in 0.1 M aqueous KHCO3 electrolyte with faradic efficiency of nearly 52% for CO and 54% for methane at − 1.5 V and − 1.4 V vs. Ag/AgCl, respectively. This performance is in stark contrast to the Mn: Cu(1:1)@MOF and Mn: Cu(2:1)@MOF, which exhibit current densities of − 56 mAcm−2 and − 51 mAcm−2 respectively under similar cathodic voltages. The excellent catalytic accomplishment can be credited to the interaction between nanoparticles and MOFs, which allows enhanced absorption and activation for CO2 molecules due to approachable metallic components and matchless 2-D formation of Mn: Cu(1:2)@MOF. These finding presents a straightforward approach to promote CO2 to valuable products through the analytical formulation of MOF alloy. [ABSTRACT FROM AUTHOR]

Pulmonary arterial hypertension (PAH) is a disease with complex pathobiology, significant morbidity and mortality, and remains without a cure. It is characterized by vascular remodelling associated with uncontrolled proliferation of pulmonary artery smooth muscle cells, endothelial cell proliferation and dysfunction, and endothelial-to-mesenchymal transition, leading to narrowing of the vascular lumen, increased vascular resistance and pulmonary arterial pressure, which inevitably results in right heart failure and death. There are multiple molecules and signalling pathways that are involved in the vascular remodelling, including non-coding RNAs, i.e. microRNAs and long non-coding RNAs (lncRNAs). It is only in recent years that the role of lncRNAs in the pathobiology of pulmonary vascular remodelling and right ventricular dysfunction is being vigorously investigated. In this review, we have summarized the current state of knowledge about the role of lncRNAs as key drivers and gatekeepers in regulating major cellular and molecular trafficking involved in the pathogenesis of PAH. In addition, we have discussed the limitations and challenges in translating lncRNA research in vivo and in therapeutic applications of lncRNAs in PAH. [ABSTRACT FROM AUTHOR]

The objective of this article is to establish some Hermite–Hadamard-type inequalities via harmonic s , m -convex functions in the framework of conformal fractional integral. [ABSTRACT FROM AUTHOR]

The events after 9/11 have changed the conditions, especially for Muslims living in the US. They have been victimized and stereotyped as negative individuals to the extent of being liars and bigots. These semantic and religious sentiments and prejudice have been pervasive at all levels, ranging from public to private, political, and media platforms. These strong sentiments have penetrated the political campaigns in the US, thus creating Islamophobia. Traditionally, the presidential election Campaigns focus on the diversity and address every group and member of the society. The same practice was anticipated in 2016 Electoral Campaigns, but Donald Trump chose a different path. He focused more on anti-minority rhetoric with a particular focus on Muslims. Since the Muslim expats are the second-largest expat community after Jews, in the US, Trump's speeches were considered a direct insult. As a result, the Muslim community reacted vehemently towards such antics. The current study focuses on Muslim sentiments towards Trump's hate speeches. The medium explored is Twitter, where Muslims vent out their sentiments. In addition to the private accounts, the twitter accounts of Muslim representative organizations have been used. The research on the tweets has done through quantitative content analysis. The results reflect the substantial use of words against Trump's speech and his intended policies. The dominant emotions reflected in the tweets were anger, fear, and sadness. Some measures are also suggested after the research for conflict resolution of the effects of such speeches. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is ranked the third deadliest cancer worldwide whose molecular pathogenesis is not fully understood. Although deregulated metabolic pathways have been implicated in HCC onset and progression, the mechanisms triggering this metabolic imbalance are yet to be explored. Here, we identified a gene signature coding catabolic enzymes (Cat-GS) involved in key metabolic pathways like amino acid, lipid, carbohydrate, drug, and retinol metabolism as suppressed in HCC. A higher expression of deregulated Cat-GS is associated with good survival and less aggressive disease state in HCC patients. On the other hand, we identified mTOR signaling as a key determinant in HCC onset and progression, whose hyperactivation is found associated with poor survival and aggressive disease state in HCC patients. Next, out of Cat-GS, we established two key regulators of alcohol metabolism, alcohol dehydrogenase 1A (ADH1A) and aldehyde dehydrogenase 2 (ALDH2), as being transcriptionally suppressed by histone deacetylase 1 (HDAC1) at the downstream of mTORC1 signaling. Suppressed ADH1A and ALDH2 expression aligns well with HCC-specific molecular profile and can efficiently predict disease onset and progression, whereas higher ADH1A and ALDH2 expression is associated with good survival and less aggressive disease state in HCC patients. Overall, our in silico findings suggest that transcriptional suppression of alcohol metabolism regulators, ADH1A and ALDH2, at the downstream of mTOR signaling is, in part, responsible for triggering oncogenic transformation of hepatocytes resulting in disease onset and progression in HCC. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) are 20-22-nucleotide small endogenous non-coding RNAs which regulate gene expression at post-transcriptional level. In the last two decades, identification of almost 2600 miRNAs in human and their potential to be modulated opened a new avenue to target almost all hallmarks of cancer. miRNAs have been classified as tumor suppressors or oncogenes depending on the phenotype they induce, the targets they modulate, and the tissue where they function. miR-200c, an illustrious tumor suppressor, is one of the highly studied miRNAs in terms of development, stemness, proliferation, epithelial-mesenchymal transition (EMT), therapy resistance, and metastasis. In this review, we first focus on the regulation of miR-200c expression and its role in regulating EMT in a ZEB1/E-cadherin axis-dependent and ZEB1/E-cadherin axis-independent manner. We then describe the role of miR-200c in therapy resistance in terms of multidrug resistance, chemoresistance, targeted therapy resistance, and radiotherapy resistance in various cancer types. We highlight the importance of miR-200c at the intersection of EMT and chemoresistance. Furthermore, we show how miR-200c coordinates several important signaling cascades such as TGF-β signaling, PI3K/Akt signaling, Notch signaling, VEGF signaling, and NF-κB signaling. Finally, we discuss miR-200c as a potential prognostic/diagnostic biomarker in several diseases, but mainly focusing on cancer and its potential application in future therapeutics. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) are 20-22 nucleotides long small non-coding RNAs that regulate gene expression post-transcriptionally. Last decade has witnessed emerging evidences of active roles of miRNAs in tumor development, progression, metastasis, and drug resistance. Many factors contribute to their dysregulation in cancer, such as chromosomal aberrations, differential methylation of their own or host genes' promoters and alterations in miRNA biogenesis pathways. miRNAs have been shown to act as tumor suppressors or oncogenes depending on the targets they regulate and the tissue where they are expressed. Because miRNAs can regulate dozens of genes simultaneously and they can function as tumor suppressors or oncogenes, they have been proposed as promising targets for cancer therapy. In this review, we focus on the role of miRNAs in driving drug resistance and metastasis which are associated with stem cell properties of cancer cells. Furthermore, we discuss systems biology approaches to combine experimental and computational methods to study effects of miRNAs on gene or protein networks regulating these processes. Finally, we describe methods to target oncogenic or replace tumor suppressor miRNAs and current delivery strategies to sensitize refractory cells and to prevent metastasis. A holistic understanding of miRNAs' functions in drug resistance and metastasis, which are major causes of cancer-related deaths, and the development of novel strategies to target them efficiently will pave the way towards better translation of miRNAs into clinics and management of cancer therapy. [ABSTRACT FROM AUTHOR]