Cover Image, Volume 93, Issue 11

The paper proposes—and argues in favor of an alternative model to account for the dipole geomagnetic field in which a hitherto unrecognized piezomagnetic effect is the actual cause. This model offers a plausible explanation for the observed field reversals, the westward drift, and the secularly decreasing field strength. It is consistent with recent satellite data, and capable of generalization to planets other than Earth. It also accounts for the fact that the dipole axis is displaced from the geographic axis, and that the center of the dipole is displaced from the geographic center.

Front Cover: The cover image is based on the Review Genome-wide transcriptomic and proteomic studies of Retisyndrome mouse models identify common signaling pathways and cellular functions as potential therapeutic targets by Rahul Krishnaraj et al., https://doi.org/10.1002/humu.23887. Cover image © Florencia Haase Images.

Transient receptor potential (TRP) cation channels are unique cellular sensors that are involved in multiple cellular functions, ranging from transduction of sensory signals to the regulation of Ca2+ and Mg2+ homoeostasis. Malfunctioning of TRP channels is now recognized as the cause of several hereditary and acquired human diseases. At the time of cloning of the first Drosophila TRP channel, a close connection between gating and phosphatidylinositol phosphates (PIPs) was already recognized. In this review, we summarize current knowledge about the mechanisms of interaction between TRP channels and PIPs, and discuss the possible functional implications of TRP–PIP interactions to human physiology and pathophysiology.

A comparative study of different viscosity models for unsteady flow over a decelerating rotating disk with variable physical properties

Information security involves various services like availability, cryptography, and integrity which help to protect data. Nowadays everyone store his/her important data on various cloud environments for easy access without much thinking of data privacy. Still most individual or many companies prefer to store their business or individual level information in computer but connected to Internet. There are well-known algorithms available which help to secure data by using some secret key. Hackers are simply capable to interrupt the key with the assistance of recent high end computing machines. Hence information needs to be secured in more powerful way that no longer to be abused by folks that aren't entitled to. The security of data can be increased by hybridization of these well-known algorithms. The paper provides the generic models of various hybrid cryptographic models which improves the security of data. The paper also provides the comparative study of various traditional and hybrid models used heavily for providing security to data. The hybrid model can provide enhanced security than AES and should be selected if extreme security is required.KeywordsAESFile split encryption modelCascaded encryptionHybrid cryptographySymmetric encryption

PurposeThis study aims to numerically study the buoyant convective flow of two different nanofluids in a porous annular domain. A uniformly heated inner cylinder, cooled outer cylindrical boundary and adiabatic horizontal surfaces are considered because of many industrial applications of this geometry. The analysis also addresses the comparative study of different porous media models governing fluid flow and heat transport.Design/methodology/approachThe finite difference method has been used in the current simulation work to obtain the numerical solution of coupled partial differential equations. In particular, the alternating direction implicit method is used for solving transient equations, and the successive line over relaxation iterative method is used to solve time-independent equation by choosing an optimum value for relaxation parameter. Simpson’s rule is adopted to estimate average Nusselt number involving numerical integration. Various grid sensitivity checks have been performed to assess the sufficiency of grid size to obtain accurate results. In this analysis, a general porous media model has been considered, and a comparative study between three different models has been investigated.FindingsNumerical simulations are performed for different combinations of the control parameters and interesting results are obtained. It has been found that the an increase in Darcy and Rayleigh numbers enhances the thermal transport rate and strengthens the nanofluid movement in porous annulus. Also, higher flow circulation rate and thermal transport has been detected for Darcy model as compared to non-Darcy models. Thermal mixing could be enhanced by considering a non-Darcy model.Research limitations/implicationsThe present results could be effectively used in many practical applications under the limiting conditions of two-dimensionality and axi-symmetry conditions. The only drawback of the current study is it does not include the three-dimensional effects.Practical implicationsThe results could be used as a first-hand information for the design of any thermal systems. This will help the design engineer to have fewer trial-and-run cases for the new design.Originality/valueA pioneering numerical investigation on the buoyant convective flow of two different nanofluids in an annular porous domain has been carried out by using a general Darcy–Brinkman–Forchheimer model to govern fluid flow in porous matrix. The results obtained from current investigation are novel and original, with numerous practical applications of nanofluid saturated porous annular enclosure in the modern industry.

This article examines the nature and functioning of trust signals in digital branding, focusing on visual identity and social proof. The relevance of the study is driven by increasing consumer dependence on online platforms, where a brand’s ability to establish credibility quickly is a decisive competitive advantage. The methodology is based on comparative analysis, structural modeling, and case studies of educational platforms. The author analyzes how design, logos, and social signals (reviews, endorsements) influence users. A three-tier architecture of trust is formulated, comprising visual, social, and institutional signals. Using Coursera as a case study, the article demonstrates the transformation of a brand into a trusted infrastructure. A framework for evaluating the effectiveness of trust signals is proposed, taking into account cultural contexts and ethical challenges. The results emphasize that digital trust is a function of alignment between visual coherence, social validation, and institutional integrity.

BackgroundLung cancer is the major cause of mortality worldwide. Major signalling pathways that could play significant role in lung cancer therapy include (1) Growth promoting pathways (Epidermal Growth Factor Receptor/Ras/ PhosphatidylInositol 3-Kinase) (2) Growth inhibitory pathways (p53/Rb/P14ARF, STK11) (3) Apoptotic pathways (Bcl-2/Bax/Fas/FasL). Insilico strategy was implemented to solve the mystery behind selected lung cancer pathway by applying comparative modeling and molecular docking studies.ResultsYASARA [v 12.4.1] was utilized to predict structural models of P16-INK4 and RB1 genes using template 4ELJ-A and 1MX6-B respectively. WHAT CHECK evaluation tool demonstrated overall quality of predicted P16-INK4 and RB1 with Z-score of −0.132 and −0.007 respectively which showed a strong indication of reliable structure prediction. Protein-protein interactions were explored by utilizing STRING server, illustrated that CDK4 and E2F1 showed strong interaction with P16-INK4 and RB1 based on confidence score of 0.999 and 0.999 respectively. In order to facilitate a comprehensive understanding of the complex interactions between candidate genes with their functional interactors, GRAMM-X server was used. Protein-protein docking investigation of P16-INK4 revealed four ionic bonds illustrating Arg47, Arg80,Cys72 and Met1 residues as actively participating in interactions with CDK4 while docking results of RB1 showed four hydrogen bonds involving Glu864, Ser567, Asp36 and Arg861 residues which interact strongly with its respective functional interactor E2F1.ConclusionThis research may provide a basis for understanding biological insights of P16-INK4 and RB1 proteins which will be helpful in future to design a suitable drug to inhibit the disease pathogenesis as we have determined the interacting amino acids which can be targeted in order to design a ligand in-vitro to propose a drug for clinical trials. Protein -protein docking of candidate genes and their important interacting residues likely to be provide a gateway for developing computer aided drug designing.

Deciphering the fluorescence resonance energy transfer from denatured transport protein to anthracene 1,5 disulphonate in reverse micellar environment

This paper presents a comprehensive investigation into the classification of Sundanese news articles, focusing on the evaluation of various classification models and feature extraction methods. Using a dataset obtained from Sundanese news websites, this study conducts a systematic comparison of Naive Bayes and Logistic Regression classifiers combined with TF-IDF and Bag-of-Words feature extraction methods. The research process involves critical steps such as data preprocessing, model training, hyperparameter optimization, and performance assessment based on standard metrics, including accuracy, precision, recall, and F1-score. Results demonstrate high accuracy across all combinations, with the Logistic Regression model using Bag-of-Words feature extraction achieving the highest accuracy of 98.20%. Beyond model evaluation, the research delves into qualitative data analysis. Word clouds and TF-IDF weighting are employed to uncover prominent themes and topics within the news articles, highlighting recurring patterns in the Sundanese language. The study identifies key challenges, including the scarcity of annotated datasets for low-resource languages like Sundanese and the limitations of traditional models in capturing complex linguistic structures. Future opportunities are highlighted, such as leveraging deep learning models, including transformers, to enhance classification performance and address current limitations. Additionally, ensemble methods and domain-specific adaptations could further improve accuracy. Overall, this research contributes to advancing Sundanese language processing and provides a roadmap for future innovations in text classification and natural language processing applications.

The use of fiber-reinforced polymer (FRP) composites for strengthening and/or rehabilitation of concrete structures is gaining increasing popularity in the civil engineering community. One of the most attractive applications of FRP materials is their use as confining devices for concrete columns, which may result in remarkable increases of strength and ductility as indicated by numerous published experimental results. Despite a large research effort, a proper analytical tool to predict the behavior of FRP-confined concrete has not yet been established. Most of the available models are empirical in nature and have been calibrated against their own sets of experimental data. On the other hand, the experimental results available in the literature encompass a wide range of values of the significant variables. The objective of this work is a systematic assessment of the performance of the existing models on confinement of concrete columns with FRP materials. The study is conducted in the following steps: the experimental data on confinement of concrete cylinders with FRP available in the technical literature are classified according to the values of the significant variables; the existing empirical and analytical models are reviewed, pointing out their distinct features; the whole set of available experimental results is compared with the whole set of analytical models; strengths and weaknesses of the various models are analyzed. Finally, a new equation is proposed to evaluate the axial strain at peak stress of FRP-confined concrete cylinders.

기업이 물류비용을 절감할 수 있는 정교한 수요 예측 모형은 그동안 수많은 연구를 통해 다양한 방법들이 제시되었다. 이러한 연구들은 주로 수요 패턴에 의해서 적용 가능한 수요 예측 모형을 결정하고, 통계적 검증을 통해서 모형의 정확성을 판단하였다. 수요 패턴은 크게 규칙성과 불규칙성으로 나뉘어 질 수 있다. 규칙적인 패턴은 주문이 정기적이고 주문량이 일정한 경우를 의미한다. 이러한 경우에는 주로 회귀모형이나 시계열 모형을 통해서 수요를 예측하는 방법들이 사용된다. 그러나 불규칙적이고 주문량의 변동 폭이 큰 경우는 간헐적 수요(Intermittent Demand)라고 하는데, 기존의 회귀 모형이나 시계열 모형으로는 수요 예측의 오류 발생 가능성이 높기 때문이다. 간헐적 수요를 보이는 품목에 대해서는 주로 Croston모형 혹은 Holts모형 등을 사용하여 수요를 예측한다. 본 연구에서는 간헐적 수요 패턴을 보이는 항공 화물의 다양한 품목에 대해서 수요 패턴을 분석하고, 다양한 모형을 통해 수요를 예측하여 각 모형의 예측력을 비교 분석하였다. 이 과정에서 항공 화물의 품목별, 지역별로 다양한 모형의 적합도를 분석하여 항공사가 가장 효율적으로 운영할 수 있는 항공 화물의 수요 예측 모형에 대한 개발 방향을 제시하고자 함이 본 논문의 목적이다.

Sorption and electrokinetic properties of ASR product and C-S-H: A comparative modelling study

Neuraminidase inhibitors for treatment of human and avian strain influenza: A comparative modeling study

Noble gas impurity balance and exhaust model for DIII-D and JET