MicroRNAs modulation in lung cancer: exploring dual mechanisms and clinical prospects

The global incidence of lung cancer is marked by a considerably elevated mortality rate.MicroRNAs(miRNAs)exert pivotal influence in the intricate orchestration of gene regulation,and their dysregulation can precipitate dire consequences,notably cancer.Within this context,miRNAs encapsulated in exosomes manifest a diversified impact on the landscape of lung cancer,wherein their actions may either foster angiogenesis,cell proliferation,and metastasis,or counteract these processes.This comprehensive review article discerns potential targets for the prospective development of therapeutic agents tailored for lung cancer.Tumor-suppressive miRNAs,such as miR-204,miR-192,miR-30a,miR-34a,miR-34b,miR-203,and miR-212,exhibit heightened expression and demonstrate the capacity to inhibit cellular proliferation and invasiveness.Conversely,the deleterious effects of tumor-promoting miRNAs like miR-21,miR-106a,miR-155,miR-205,and miR-210 can be attenuated through the application of their respective inhibitors.Distinct miRNAs selectively target various oncogenes,including NUAK Family Kinase 1(NUAK1),Snail Family Transcriptional Repressor 1(Snai1),Astrocyte elevated gene-1(AEG-1),Vimentin,Proliferation and apoptosis adaptor protein 15(PEA-15/PED),Hypoxia-inducible factor 1-alpha(HIF1),as well as tumor suppressor genes such as phosphatase and tensin homolog(PTEN),Suppressor of cytokine signaling 1(SOCS1),Tumor protein P53 binding protein 1(TP53BP1),and PH Domain and Leucine Rich Repeat Protein Phosphatase 2(PHLP22).This investigative approach proves invaluable in elucidating the specific miRNAs implicated in the deregulation of crucial genes pivotal to the pathogenesis of cancer.

Herding behavior in Ramadan and financial crises: the case of the Pakistani stock market

This study examines herding behavior in the Pakistani Stock Market under different market conditions,focusing on the Ramadan effect and Crisis period by using data from 2004 to 2014.Two regression models of Christie and Huang(Financ Analysts J 51:31-37,1995)and Chang et al.,(J Bank Finance 24:1651-1679,2000)are used for herding estimations.Results based on daily stock data reveal that there is an absence of herding behavior during rising(up)and falling(down)market as well as during high and low volatility in market.While herding behavior is detected during low trading volume days.Yearly analysis shows that herding existed during 2005,2006 and 2007,while it is not evident during rest of the period.However,herding behavior is not detected during Ramadan.Furthermore,during financial crisis of 2007-08,Pakistani Stock Market exhibits herding behavior due to higher uncertainty and information asymmetry.

Optical sensors based on the NiPc-CoPc composite films deposited by drop casting and under the action of centrifugal force

In this study, solution processed composite films of nickel phthalocyanine（NiPc） and cobalt phthalocyanine（CoPc）are deposited by drop casting and under centrifugal force. The films are deposited on surface-type inter-digitated silver electrodes on ceramic alumina substrates. The effects of illumination on the impedance and capacitance of the NiPc–CoPc composite samples are investigated. The samples deposited under centrifugal force show better conductivity than the samples deposited by drop casting technique. In terms of impedance and capacitance sensitivities the samples fabricated under centrifugal force are more sensitive than the drop casting samples. The values of impedance sensitivity（Sz）are equal to（-1.83） MΩ·cm^2/mW and（-5.365） MΩ·cm^2/mW for the samples fabricated using drop casting and under centrifugal force, respectively. Similarly, the values of capacitance sensitivity（Sc） are equal to 0.083 pF·cm^2/mW and 0.185 pF·cm～2/mW for the samples fabricated by drop casting and under centrifugal force. The films deposited using the different procedures could potentially be viable for different operational modes（i.e., conductive or capacitive） of the optical sensors. Both experimental and simulated results are discussed.

Dual pH and microbial-sensitive galactosylated polymeric nanocargoes for multi-level targeting to combat ulcerative colitis

Ulcerative colitis(UC)is a type of inflammatory bowel disease characterized by inflammation,ulcers and irritation of the mucosal lining.Oral drug delivery in UC encounters challenges because of multifaceted barriers.Dexamethasone-loaded galactosylated-PLGA/Eudragit S100/pullulan nanocargoes(Dexa-GP/ES/Pu NCs)have been developed with a dual stimuli-sensitive coating responsive to both colonic pH and microbiota,and an underneath galactosylated-PLGA core(GP).The galactose ligand of the GP preferentially binds to the macrophage galactose type-lectin-C(MGL-2)surface receptor.Therefore,both stimuli and ligand-mediated targeting facilitate nanocargoes to deliver Dexa specifically to the colon with enhanced macrophage uptake.Modified emulsion method coupled with a solvent evaporation coating technique was employed to prepare Dexa-GP/ES/Pu NCs.The nanocargoes were tested using in vitro,ex vivo techniques and dextran sodium sulfate(DSS)induced UC model.Prepared nanocargoes had desired physicochemical properties,drug release,cell uptake and cellular viability.Investigations using a DSS-colitis model showed high localization and mitigation of colitis with downregulation of NF-ĸB and COX-2,and restoration of clinical,histopathological,biochemical indices,antioxidant balance,microbial alterations,FTIR spectra,and epithelial junctions’integrity.Thus,Dexa-GP/ES/Pu NCs found to be biocompatible nanocargoes capable of delivering drugs to the inflamed colon with unique targeting properties for prolonged duration.

Appearance Based Dynamic Hand Gesture Recognition Using 3D Separable Convolutional Neural Network

Appearance-based dynamic Hand Gesture Recognition(HGR)remains a prominent area of research in Human-Computer Interaction(HCI).Numerous environmental and computational constraints limit its real-time deployment.In addition,the performance of a model decreases as the subject’s distance from the camera increases.This study proposes a 3D separable Convolutional Neural Network(CNN),considering the model’s computa-tional complexity and recognition accuracy.The 20BN-Jester dataset was used to train the model for six gesture classes.After achieving the best offline recognition accuracy of 94.39%,the model was deployed in real-time while considering the subject’s attention,the instant of performing a gesture,and the subject’s distance from the camera.Despite being discussed in numerous research articles,the distance factor remains unresolved in real-time deployment,which leads to degraded recognition results.In the proposed approach,the distance calculation substantially improves the classification performance by reducing the impact of the subject’s distance from the camera.Additionally,the capability of feature extraction,degree of relevance,and statistical significance of the proposed model against other state-of-the-art models were validated using t-distributed Stochastic Neighbor Embedding(t-SNE),Mathew’s Correlation Coefficient(MCC),and the McNemar test,respectively.We observed that the proposed model exhibits state-of-the-art outcomes and a comparatively high significance level.

Improved Belief Propagation Decoder for LDPC-CRC-Polar Codes with Bit-Freezing

Though belief propagation bit-flip(BPBF)decoding improves the error correction performance of polar codes,it uses the exhaustive flips method to achieve the error correction performance of CA-SCL decoding,thus resulting in high decoding complexity and latency.To alleviate this issue,we incorporate the LDPC-CRC-Polar coding scheme with BPBF and propose an improved belief propagation decoder for LDPC-CRC-Polar codes with bit-freezing(LDPCCRC-Polar codes BPBFz).The proposed LDPCCRC-Polar codes BPBFz employs the LDPC code to ensure the reliability of the flipping set,i.e.,critical set(CS),and dynamically update it.The modified CS is further utilized for the identification of error-prone bits.The proposed LDPC-CRC-Polar codes BPBFz obtains remarkable error correction performance and is comparable to that of the CA-SCL(L=16)decoder under medium-to-high signal-to-noise ratio(SNR)regions.It gains up to 1.2dB and 0.9dB at a fixed BLER=10-4compared with BP and BPBF(CS-1),respectively.In addition,the proposed LDPC-CRC-Polar codes BPBFz has lower decoding latency compared with CA-SCL and BPBF,i.e.,it is 15 times faster than CA-SCL(L=16)at high SNR regions.

Entropy analysis of SWCNT & MWCNT flow induced by collecting beating of cilia with porous medium

In this article, we considers the thermodynamics analysis of creeping viscous nanofluid flow in a horizontal ciliated tube under the effects of a uniform magnetic field and porous medium. Moreover, energy analysis is performed in the presence of an internal heat source and thermal radiation phenomena. The thermal conductivity of base fluid water is strengthened by considering the carbon nanotubes (CNTs). Mathematical formulation operated, results in a set of non-linear coupled partial differential equations. The governed differential system is transformed into an ordinary differential system by considering suitable similarity variables. Exact solutions in the closed form are computed for the temperature, momentum and pressure gradient profiles. In this study, special attention is devoted to the electrical conductivity of the CNTs. Streamlines patterns are also discussed to witness the flow lines for different parameters. Thermodynamics analysis shows that entropy of the current flow system is an increasing function of Brinkmann number, magnetic parameter, nanoparticle concentration parameter and Darcy number.

Effect of family control on corporate dividend policy of firms in Pakistan

This study examines the impact of family control on the dividend policy of firms in Pakistan,covering the period from 2009 to 2016.It also investigates whether family control moderates the impact of firm-specific factors on the dividend policy.The GMM model for panel data estimation is used.The mean difference univariate analysis shows that family firms differ from nonfamily firms based on financial characteristics.The multivariate analysis shows that family firms pay lower dividends than nonfamily firms.Besides,firm size inversely affects the dividend policy,whereas tangibility positively affects it.Moreover,family control does not moderate the impact of all firm-specific factors on the dividend policy.Overall,family control,size,and tangibility are found to be the main determinants of the dividend policy in Pakistan.

Bioconvection Mangnetohydrodynamic Tangent Hyperbolic Nanofluid Flow with Quartic Chemical Reaction Past a Paraboloid Surface

In this numerical study,the effect of quartic autocatalysis type of chemical reaction,buoyancy force and thermal radiation phenomenon and magnetic effect on tangent hyperbolic nanofluid past an upper horizontal surface of a paraboloid has been studied.By considering the Buongiorno model approach,a diffusion of unequal coefficients in the presence of gyrotactic microorganism is discussed.Implementation of microorganism’s idea is used to stabilize the nanoparticles through bioconvection.The modeled PDEs of the problems are converted into nonlinear ODEs with the assistant of the similarity transformations.To tackle nonlinear ODEs,MATLAB package bvp4c is used.In addition,a hallmark of the Matlab code with the reported results in the literature is achieved by benchmarking.The variations in motion,concentration,temperature,and motile density due to sundry parameters have been analyzed in-depth via graphs.Our analysis shows that the density profile of motile of microorganism is hiked with an increment in the bioconvection Rayleigh number but decreases for higher thermal Grashof number.

Blockchain Based Enhanced ERP Transaction Integrity Architecture and PoET Consensus

Enterprise Resource Planning(ERP)software is extensively used for the management of business processes.ERP offers a system of integrated applications with a shared central database.Storing all business-critical information in a central place raises various issues such as data integrity assurance and a single point of failure,which makes the database vulnerable.This paper investigates database and Blockchain integration,where the Blockchain network works in synchronization with the database system,and offers a mechanism to validate the transactions and ensure data integrity.Limited research exists on Blockchain-based solutions for the single point of failure in ERP.We established in our study that for concurrent access control andmonitoring of ERP,private permissioned Blockchain using Proof of Elapsed Time consensus is more suitable.The study also investigated the bottleneck issue of transaction processing rates(TPR)of Blockchain consensus,specifically ERP’s TPR.The paper presents systemarchitecture that integrates Blockchain with an ERP system using an application interface.

Conjugate natural convection of non-Newtonian hybrid nanofluid in wavy-shaped enclosure

The present study concerns the modelization and numerical simulation for the heat and flow exchange characteristics in a novel configuration saturated with a nonNewtonian Ag-MgO hybrid nanofluid.The wavy shaped enclosure is equipped with onequarter of a conducting solid cylinder.The system of equations resulting from the mathematical modeling of the physical problem in its dimensionless form is discretized via the higher-order Galerkin-based finite element method(GFEM).The dependency of various factors and their interrelationships affecting the hydro-thermal behavior and heat exchange rate are delineated.The numerical experiments reveal that the best heat transfer rate is achieved for the pseudo-plastic hybrid nanoliquid with high Rayleigh number and thermal conductivity ratio and low Hartmann number.Besides,the power-law index has a major effect in deteriorating the heat convection at high Rayleigh number.

Supportive tactics for innovative and sustainability performance in emerging SMEs

For this research,we examined the influence of access to domestic and international financing on sustainability performance with a mediating role of innovative performance and a moderating role of access to government support.Data were collected from 317 small and medium-sized enterprises(SMEs)through structured questionnaires.The results indicated that access to domestic and international financing significantly contributes to sustainability and innovative performances.Accordingly,we found a partial mediating role of innovative performance between access to domestic financing and sustainability performance as well as between access to international financing and sustainability performance.Access to government support significantly moderates the relationship between access to domestic finances and innovative performance as well as between access to international finances and innovative performance.Practitioners and policymakers should encourage national and international financial institutions and banks to facilitate SMEs by lending them funds for innovative activities and sustainability performance.Moreover,the government should support SMEs,so that they can contribute to economic growth and the gross domestic product.The implications from these matters will be further discussed in this paper.

黏弹性Jeffery-Hamel流的磁-微结构分析

本文通过拉伸/收缩具有独立移动能力大分子的非平行通道,对磁流体的动力学进行数值分析。通过麦克斯韦方法建立了外磁场对黏弹性流体流动影响的数学模型,在经典流体动力动量方程中表现为体力。为了完整描述微观结构现象,利用角动量方程对数学模型进行强化。用凯勒盒有限差分法对所得到的非线性问题进行数值处理。求解如Hartmann数(1≤Ha≤5)、拉伸参数(-4≤C≤4)、旋转参数(3≤K≤9)、Weissenberg数(0.3≤Wi≤0.9)、Reynolds数(50≤Re≤150)等物理量的微分方程形式,并以图表形式表示出来。在所有讨论的情况中,只有发散通道中的角速度随着Hartmann数的增加而增加,这表明微结构旋转是由强磁场激发的。

磁流体动力压缩黏性流体在多孔介质中的流动分析

本文通过数值分析,讨论了倾斜磁场效应下压缩黏性流体流动特征的意义。对于高效传热现象,温度方程中还考虑了黏性耗散和焦耳热效应。利用打靶法求解了无量纲守恒方程。对模型中所考虑的特定参数对流体运动、传热能量分配率和表面阻力系数的行为进行了图解和详细讨论。倾斜磁场效应对流体速度和换热速率的影响非常重要。从模拟结果可知,当普朗特常数从1增加到5时,热传导率增加了56%,而当倾斜磁参数γ从π/8增加到π/2时,热传导率下降了9.7%。实验还发现,随着挤压参数的增大,换热速率减小,而下板拉伸参数的增大则趋势相反。

Human Verification over Activity Analysis via Deep Data Mining

Human verification and activity analysis(HVAA)are primarily employed to observe,track,and monitor human motion patterns using redgreen-blue(RGB)images and videos.Interpreting human interaction using RGB images is one of the most complex machine learning tasks in recent times.Numerous models rely on various parameters,such as the detection rate,position,and direction of human body components in RGB images.This paper presents robust human activity analysis for event recognition via the extraction of contextual intelligence-based features.To use human interaction image sequences as input data,we first perform a few denoising steps.Then,human-to-human analyses are employed to deliver more precise results.This phase follows feature engineering techniques,including diverse feature selection.Next,we used the graph mining method for feature optimization and AdaBoost for classification.We tested our proposed HVAA model on two benchmark datasets.The testing of the proposed HVAA system exhibited a mean accuracy of 92.15%for the Sport Videos in theWild(SVW)dataset.The second benchmark dataset,UT-interaction,had a mean accuracy of 92.83%.Therefore,these results demonstrated a better recognition rate and outperformed other novel techniques in body part tracking and event detection.The proposed HVAA system can be utilized in numerous real-world applications including,healthcare,surveillance,task monitoring,atomic actions,gesture and posture analysis.

Fractional Processing Based Adaptive Beamforming Algorithm

Fractional order algorithms have shown promising results in various signal processing applications due to their ability to improve performance without significantly increasing complexity.The goal of this work is to inves-tigate the use of fractional order algorithm in the field of adaptive beam-forming,with a focus on improving performance while keeping complexity lower.The effectiveness of the algorithm will be studied and evaluated in this context.In this paper,a fractional order least mean square(FLMS)algorithm is proposed for adaptive beamforming in wireless applications for effective utilization of resources.This algorithm aims to improve upon existing beam-forming algorithms,which are inefficient in performance,by offering faster convergence,better accuracy,and comparable computational complexity.The FLMS algorithm uses fractional order gradient in addition to the standard ordered gradient in weight adaptation.The derivation of the algorithm is provided and supported by mathematical convergence analysis.Performance is evaluated through simulations using mean square error(MSE)minimization as a metric and compared with the standard LMS algorithm for various parameters.The results,obtained through Matlab simulations,show that the FLMS algorithm outperforms the standard LMS in terms of convergence speed,beampattern accuracy and scatter plots.FLMS outperforms LMS in terms of convergence speed by 34%.From this,it can be concluded that FLMS is a better candidate for adaptive beamforming and other signal processing applications.

Effects of Variable Thermal Conductivity and Non-linear Thermal Radiation Past an Eyring Powell Nanofluid Flow with Chemical Reaction

Present analysis discusses the boundary layer flow of Eyring Powell nanofluid past a constantly moving surface under the influence of nonlinear thermal radiation. Heat and mass transfer mechanisms are examined under the physically suitable convective boundary condition. Effects of variable thermal conductivity and chemical reaction are also considered. Series solutions of all involved distributions using Homotopy Analysis method(HAM) are obtained.Impacts of dominating embedded flow parameters are discussed through graphical illustrations. It is observed that thermal radiation parameter shows increasing tendency in relation to temperature profile. However, chemical reaction parameter exhibits decreasing behavior versus concentration distribution.

Rol genes enhance content of artemisinin and other secondary metabolites in Shennong hybrid of Artemisia annua

Objective: Artemisia annua is the chief source of artemisinin, a potent antimalarial agent, in which other bioactive phytochemicals are also present. Due to low levels of bioactive compounds including artemisinin and flavonoids, it is necessary to increase the level of the secondary metabolites by regulating the expression of rol genes in the plant.Methods: A hybrid variety of A. annua(Hyb1209 r, Shennong) developed by the Centre for Novel Agricultural Products, University of York, UK, was selected to produce transgenics of rolB and rolC genes. Genetic transformation was carried out via Agrobacterium tumefaciens GV3101 harboring rolB and rolC genes of Agrobacterium rhizogenes cloned separately. HPLC was used for the qualitative and quantitative analysis of flavonoids and artemisinin. Furthermore, thin layer chromatography(TLC) was also used to analyze artemisinin content.Results: Comparative analysis via HPLC revealed considerable enhancement in the phytochemical content of transgenic A. annua plants as compared to the wild type plant. Transgenics of rolB gene showed an average increase of 321% in rutin, 97.2% in caffeic acid, and 218.4% in myricetin, respectively. In the case of rolC gene transgenics, an average increase of 197.5% in rutin, 76.3% in caffeic acid, and 209.3%in myricetin was observed. Transgenics of rolB and rolC genes showed a 14.3%–28.6% and 2.8%–12.7% increase in artemisinin content respectively by HPLC analysis. TLC analysis showed that an average 142.2%and 110.2% enhancement in artemisinin for rolB and rolC transgenics respectively, compared with the wild type. An enhanced production of total flavonoids(average 30.2% and 25.5% increase in rolB and rolC transgenics, respectively) and total phenolics(average 34.3% and 25.8% increase in rolB and rolC transgenics, respectively) was observed as a result of transformation. Transformed A. annua plants showed improved free radical scavenging activity(average 46.5% and 29.1% increase in rolB and rolC transgenics,respectively) and total reducing power(average 32.7% and 26.4% increase in rolB and rolC transgenics,respectively) compared with untransformed plant.Conclusion: rolB and rolC genes were effective for developing A. annua plants with an enhanced level of phytochemicals.

Upshot of Chemical Species and Nonlinear Thermal Radiation on Oldroyd-B Nanofluid Flow Past a Bi-directional Stretched Surface with Heat Generation/Absorption in a Porous Media

A three-dimensional mathematical model is developed to examine the flow of nonlinear thermal radiation Oldroyd-B nanofluid past a bidirectional linearly stretched surface in a porous medium. The flow is induced by temperature dependent thermal conductivity, chemical reaction and convective heat and mass conditions. Novel characteristics of Brownian motion and thermophoresis are accompanied by magnetohydrodynamic and heat generation/absorption.Self-similar transformations are employed to convert the system of nonlinear partial differential equations to a system of ordinary differential equations with high nonlinearity and are solved by strong analytic technique named as Homotopy Analysis method(HAM). Effects of varied arising parameters on involved distributions are reflected through graphical illustrations. From this study, it is perceived that strong magnetic field hinders the fluid's motion and leads to rise in temperature that eventually lowers heat transfer rate from the surface. Further, decrease in heat transfer rate is also observed for enhanced values of thermal radiation parameter. To validate our results, a comparison with already published paper in limiting case is also given and results are found in excellent oncurrence; hence reliable results are being presented.

Autonomous Eyewitness Identification by Employing Linguistic Rules forDisaster Events

Social networking platforms provide a vital source for disseminating information across the globe,particularly in case of disaster.These platforms are great mean to find out the real account of the disaster.Twitter is an example of such platform,which has been extensively utilized by scientific community due to its unidirectional model.It is considered a challenging task to identify eyewitness tweets about the incident from the millions of tweets shared by twitter users.Research community has proposed diverse sets of techniques to identify eyewitness account.A recent state-of-the-art approach has proposed a comprehensive set of features to identify eyewitness account.However,this approach suffers some limitation.Firstly,automatically extracting the feature-words remains a perplexing task against each feature identified by the approach.Secondly,all identified features were not incorporated in the implementation.This paper has utilized the language structure,linguistics,and word relation to achieve automatic extraction of feature-words by creating grammar rules.Additionally,all identified features were implemented which were left out by the state-of-the-art model.A generic approach is taken to cover different types of disaster such as earthquakes,floods,hurricanes,and wildfires.The proposed approach was then evaluated for all disaster-types,including earthquakes,floods,hurricanes,and fire.Based on the static dictionary,the Zahra et al.approach was able to produce an F-Score value of 0.92 for Eyewitness identification in the earthquake category.The proposed approach secured F-Score values of 0.81 in the same category.This score can be considered as a significant score without using a static dictionary.