Implications For Engineering Research Articles

Loops are geometric catalysts for DNA integration.

The insertion of DNA elements within genomes underpins both genetic diversity and disease when unregulated. Most of DNA insertions are not random and the physical mechanisms underlying the integration site selection are poorly understood. Here, we perform Molecular Dynamics simulations to study the insertion of DNA elements, such as viral DNA or transposons, into naked DNA or chromatin substrates. More specifically, we explore the role of loops within the polymeric substrate and discover that they act as 'geometric catalysts' for DNA integration by reducing the energy barrier for substrate deformation. Additionally, we discover that the 1D pattern and 3D conformation of loops have a marked effect on the distribution of integration sites. Finally, we show that loops may compete with nucleosomes to attract DNA integrations. These results may be tested in vitro and they may help to understand patterns of DNA insertions with implications in genome evolution and engineering.

Teaching old dogs new tricks: genetic engineering methanogens.

Methanogenic archaea, which are integral to global carbon and nitrogen cycling, currently face challenges in genetic manipulation due to unique physiology and limited genetic tools. This review provides a survey of current and past developments in the genetic engineering of methanogens, including selection and counterselection markers, reporter systems, shuttle vectors, mutagenesis methods, markerless genetic exchange, and gene expression control. This review discusses genetic tools and emphasizes challenges tied to tool scarcity for specific methanogenic species. Mutagenesis techniques for methanogens, including physicochemical, transposon-mediated, liposome-mediated mutagenesis, and natural transformation, are outlined, along with achievements and challenges. Markerless genetic exchange strategies, such as homologous recombination and CRISPR/Cas-mediated genome editing, are also detailed. Finally, the review concludes by examining the control of gene expression in methanogens. The information presented underscores the urgent need for refined genetic tools in archaeal research. Despite historical challenges, recent advancements, notably CRISPR-based systems, hold promise for overcoming obstacles, with implications for global health, agriculture, climate change, and environmental engineering. This comprehensive review aims to bridge existing gaps in the literature, guiding future research in the expanding field of archaeal genetic engineering.

Analytical Investigation of Thermal Radiation Effects on Electroosmotic Propulsion of Electrically Conducting Ionic Nanofluid with Single-Walled Carbon Nanotube Interaction in Ciliated Channels

This study examines the behavior of single-walled carbon nanotubes (SWCNTs) suspended in a water-based ionic solution, driven by the combined mechanisms of electroosmosis and peristalsis through ciliated media. The inclusion of nanoparticles in ionic fluid expands the range of potential applications and allows for the tailoring of properties to suit specific needs. This interaction between ionic fluids and nanomaterials results in advancements in various fields, including energy storage, electronics, biomedical engineering, and environmental remediation. The analysis investigates the influence of a transverse magnetic field, thermal radiation, and mixed convection acting on the channel walls. The novel physical outcomes include enhanced propulsion efficiency due to SWCNTs, understanding the influence of thermal radiation on fluid behavior and heat exchange, elucidation of the interactions between SWCNTs and the nanofluid, and recognizing implications for microfluidics and biomedical engineering. The Poisson–Boltzmann ionic distribution is linearized using the modified Debye–Hückel approximation. By employing real-world approximations, the governing equations are simplified using long-wavelength and low-Reynolds-number approximation. Conducting sensitivity analyses or exploring the impact of higher-order corrections on the model’s predictions in recent literature might alter the results significantly. This acknowledges the complexities of the modeling process and sets the groundwork for further enhancement and investigation. The resulting nonlinear system of equations is solved through regular perturbation techniques, and graphical representations showcase the variation in significant physical parameters. This study also discusses pumping and trapping phenomena in the context of relevant parameters.

Enhancing transmission and coupling efficiency in Cassegrain optical systems with four-petal Gaussian beams

This study investigates the propagation characteristics of four-petal Gaussian beams through Cassegrain optical systems. With the properties of this new type of beam, the problem of masking loss in the Cassegrain optical system can be well solved. Analytical expressions of the optical field for beams after propagating the optical system are derived, considering atmospheric turbulence effects and random jitter on coupling efficiency. Simulation tests explore various factors affecting transmission efficiency. Acceptable axial mounting error tolerance and significant efficiency drops beyond specific communication distances under different turbulence conditions (). Achieving over 80 coupling efficiency is feasible with specific lens parameters (f = 0.4 − 0.5 mm, receiving position after 4 km) using standardized lenses. This work offers a theoretical model for four-petal Gaussian beams, aiding optical communication design and application, with practical engineering implications.

Dynamic simulation of non-Newtonian boundary layer flow: An enhanced exponential time integrator approach with spatially and temporally variable heat sources

Abstract Scientific inquiry into effective numerical methods for modelling complex physical processes has led to the investigation of fluid dynamics, mainly when non-Newtonian properties and complex heat sources are involved. This paper presents an enhanced exponential time integrator approach to dynamically simulate non-Newtonian boundary layer flow with spatially and temporally varying heat sources. We propose an explicit scheme with second-order accuracy in time, demonstrated to be stable through Fourier series analysis, for solving time-dependent partial differential equations (PDEs). Utilizing this scheme, we construct and solve dimensionless PDEs representing the flow of Williamson fluid under the influence of space- and temperature-dependent heat sources. The scheme discretizes the continuity equation of incompressible fluid and Navier–Stokes, energy, and concentration equations using the central difference in space. Our analysis illuminates how factors affect velocity, temperature, and concentration profiles. Specifically, we observe a rise in temperature profile with enhanced coefficients of space and temperature terms in the heat source. Non-Newtonian behaviours and geographical/temporal variations in heat sources are critical factors influencing overall dynamics. The novelty of our work lies in developing an explicit exponential integrator approach, offering stability and second-order accuracy, for solving time-dependent PDEs in non-Newtonian boundary layer flow with variable heat sources. Our results provide valuable quantitative insights for understanding and controlling complex fluid dynamics phenomena. By addressing these challenges, our study advances numerical techniques for modelling real-world systems with implications for various engineering and scientific applications.

Investigating the Creep Damage and Permeability Evolution Mechanism of Phyllite Considering Non-Darcy’s Flow

This study investigates the intricate interplay of hydraulic coupling, creep damage, and permeability evolution mechanisms in phyllite, focusing on their relevance to tunnel engineering design and long-term stability in soft rock formations. To achieve this, conventional triaxial tests were conducted on saturated phyllite specimens under creep-seepage acoustic emission conditions. The results were systematically analyzed to unveil the inherent characteristics of creep deformation, seepage rate evolution, and damage progression in phyllite when subjected to stress–seepage coupling. Furthermore, a permeability model for representative volume element (RVE) was developed based on meso-mechanics principles, considering the distinctive attributes of low-permeability non-Darcy’s flow in rock. Consequently, a novel relationship between effective damage and permeability was established. We determined that seepage pressure induces three key effects on the creep damage mechanism of phyllite samples: (1) It adds to the existing stress through the superposition of osmotic pressure and axial load, (2) it induces tensile expansion stress because of pore water pressure, and (3) it softens the fracture surfaces to some extent. More importantly, this study validates the relationship between effective damage and permeability through the fitting of creep and damage parameters, which were obtained from the test results, and it reveals a square relationship between subsequent damage and permeability under stress conditions. The findings of this study provide a robust theoretical foundation for comprehending the evolution of damage and permeability characteristics during the creep process of rock under seepage conditions. We obtained essential insights and quantitative analyses for comprehending the damage mechanisms in rock creep under hydraulic coupling, which has significant implications for tunnel engineering and long-term rock stability assessments in soft rock environments.

P.077 Reducing artifact during in bi-directional brain interfacing

Background: Bi-directional brain interfacing (closed loop DBS) is a modern focus of neuroengineering research. Most current clinical systems are open loop, allowing one way communication from the IPG battery to the brain. Bi-directional systems allow both stimulation and recording of neural activity (local field potential, LFP). The system algorithm can measure known pathologic LFPs to guide change in stimulation. However, recording LFPs from the brain encounters electrical artifact from the heart. Reducing artifact is imperative to accurate measurement of neural activity. Artifact will cause the bi-directional system to miscalculate stimulation parameters. This project evaluated reduction of artifact by moving the IPG further away from the heart in a device implanted into the skull. Methods: LFP data from ongoing clinical trials was collected and analysed for artifact using open source code. Anatomic targets include STN, PPN, CMT, and PAG. Results: Cardiac artifact is reduced in skull mounted DBS as shown by power spectral density of LFPs in each region. Conclusions: This project shows the importance of surgical placement of DBS sensing devices to reduce cardiac artifact in bi-directional brain interfacing. This has important engineering and surgical design implications for safety and performance as the field of closed loop DBS transitions from research to clinical settings.

Spin–orbit magneto-transport in P-type double top-gate devices

The Luttinger Hamiltonian model is employed to investigate spin–orbit magneto-transport in an indium arsenide-based p-type double top-gate device with Rashba and Zeeman effects. The analyses focus particularly on the effects of the top-gate width (L), distance between the top gates (d), potential energy amplitude (U0), and asymmetry of the top-gate width on the formation of electron-like quasi-bound states and hole-like quasi-bound states within the conduction channel. The results confirm the feasibility of controlling the transport characteristics of the charged carriers through an appropriate setting of the gate width and gate potential energy. The findings provide useful insights into the complex transport dynamics of p-type semiconductor systems and have potential implications for device engineering.

Brushstrokes of Thoughts and Perceptions in Science Learning

According to J. Epstein’s (2022) Theory of Overlapping Spheres of Influence, three influential spheres are symbiotic and overlap: school, family, and community. Social networks and social capital are rendered through the implementation of cooperative, interactive partnerships among families, educators, and communities when they are centered on children's growth and development. Additionally, L. S. Vygotsky’s (1978) Theory of Cognitive Development asserts social interaction between learners is central to learners developing understanding, as concepts are first formed on the social level followed by the individual level. This qualitative research study examined the thoughts, perceptions, and acuities of students, parents, and teachers as they partnered during high school science inquiry investigations and their perceptions regarding social interactions and cognition. This qualitative phenomenological study examined the development of social skills in students and influencing factors in motivating students to take ownership of the learning. This study also examined the assimilation and accommodation of cognition in study participants’ perspectives as they engaged in scientific, experiential learning with implications for Science, Technology, Engineering, Art, and Mathematics (STEAM) teaching and learning.

Deciphering the Tax Landscape of EPC Contracts: A Comprehensive Analysis

This document aims to elucidate the tax implications of Engineering, Procurement, and Construction (EPC) contracts within the Indian jurisdiction, offering clarity to stakeholders involved. In recent times, there has been a noticeable surge in Income-tax notices targeting foreign companies engaged in EPC contracts in India, with a central focus on the taxability of offshore supplies.

Oil Heat Treatment of Wood-A Comprehensive Analysis of Physical, Chemical, and Mechanical Modifications.

Wood, a natural material with versatile industrial applications, faces limitations such as low dimensional stability and decay resistance. To address these issues, there has been significant progress in wood modification research. Oil heat treatment has emerged as an effective method among environmentally friendly wood treatment options. Studies have indicated that treating wood with hot vegetable oils yields superior properties compared to traditional methods involving gaseous atmospheres, which is attributed to the synergistic effect of oils and heat. This comprehensive review investigates the physical, chemical, and mechanical modifications induced by the oil heat treatment of wood, along with its impact on biological durability against biotic agents. The review synthesizes recent research findings, elucidates underlying mechanisms, and discusses the implications for wood material science and engineering.

In silico energetic and molecular dynamic simulations studies demonstrate potential effect of the point mutations with implications for protein engineering in BDNF

Protein engineering by directed evolution is time-consuming. Hence, in silico techniques like FoldX-Yasara for ∆∆G calculation, and SNPeffect for predicting propensity for aggregation, amyloid formation, and chaperone binding are employed to design proteins. Here, we used in silico techniques to engineer BDNF-NTF3 interaction and validated it using mutations with known functional implications for NGF dimer. The structures of three mutants representing a positive, negative, or neutral ∆∆G involving two interface residues in BDNF and two mutations representing a neutral and positive ∆∆G in NGF, which is aligned with BDNF, were selected for molecular dynamics (MD) simulation. Our MD results conclude that the secondary structure of individual protomers of the positive and negative mutants displayed a similar or different conformation from the NTF3 monomer, respectively. The positive mutants showed fewer hydrophobic interactions and higher hydrogen bonds compared to the wild-type, negative, and neutral mutants with similar SASA, suggesting solvent-mediated disruption of hydrogen-bonded interactions. Similar results were obtained for mutations with known functional implications for NGF and BDNF. The results suggest that mutations with known effects in homologous proteins could help in validation, and in silico directed evolution experiments could be a viable alternative to the experimental technique used for protein engineering.

Understanding the Utilization of Real-Time Traffic Information during Hurricane Evacuations in Texas

Understanding how evacuees use real-time traffic information is crucial for developing effective emergency evacuation response plans for hurricane-prone areas. This paper investigates how such data were used during past hurricane evacuations and post-evacuation returns in Texas with a survey dataset collected between August 2022 and February 2023. We examined the usage patterns of various platforms, including navigation apps, social media, TV, radio, and information provided by public agencies. We found that a larger household size, longer distance to evacuation destinations, and past experience with hurricane evacuations are associated with greater use of real-time information platforms. Experienced evacuees tend to rely on navigation apps and social media, and those with experience before 2010 are more inclined to use the TV and radio as their primary sources of information. Motivation for using these platforms varies among users of different platforms. Although both navigation app users and social media users value their familiarity with the platform, the former also prioritize the convenience of using it. It was also found that TV users prioritize service accessibility, radio users emphasize service availability, and users of official agency information sources place a high value on data accuracy. These findings have implications for policymakers, emergency planners, and traffic engineers involved with disaster response operations to improve the resilience of transportation systems.

Integrating population and single-cell variations in vaccine responses identifies a naturally adjuvanted human immune setpoint

Multimodal single-cell profiling methods can capture immune cell variations unfolding over time at the molecular, cellular, and population levels. Transforming these data into biological insights remains challenging. Here, we introduce a framework to integrate variations at the human population and single-cell levels in vaccination responses. Comparing responses following AS03-adjuvanted versus unadjuvanted influenza vaccines with CITE-seq revealed AS03-specific early (day 1) response phenotypes, including a B cell signature of elevated germinal center competition. A correlated network of cell-type-specific transcriptional states defined the baseline immune status associated with high antibody responders to the unadjuvanted vaccine. Certain innate subsets in the network appeared "naturally adjuvanted," with transcriptional states resembling those induced uniquely by AS03-adjuvanted vaccination. Consistently, CD14+ monocytes from high responders at baseline had elevated phospho-signaling responses to lipopolysaccharide stimulation. Our findings link baseline immune setpoints to early vaccine responses, with positive implications for adjuvant development and immune response engineering.

Handwritten Calculator Using Contour Detection

This project introduces a novel Handwritten Calculator that merges traditional handwritten calculations with modern computing techniques. By leveraging computer vision, machine learning, and human-computer interaction, the calculator interprets handwritten digits and operators to perform mathematical calculations. Through contour detection and Convolutional Neural Network (CNN) model prediction, the calculator offers users a seamless and intuitive way to compute. The project explores the development, applications, and impact of this innovative technology, with potential implications for education, accessibility, and software engineering. The Handwritten Calculator represents a significant advancement in computational methods, bridging the gap between analog and digital approaches to calculation.

GIS-based methodology for culvert location evaluation on railways: a case study of the Qena–Safaga Track in Egypt

ABSTRACT Railway infrastructure plays a critical role in transportation networks, and ensuring its integrity and resilience is of utmost importance. Culverts are vital components of railway tracks, providing drainage and water management to prevent structural damage and disruptions. Identifying suitable locations for culverts requires careful evaluation and consideration of various factors. A study using GIS techniques was conducted on an existing commercial railway track in the Eastern Desert of Upper Egypt to assess the effectiveness of existing culverts in preventing flash floods. The culvert suitability index map revealed that areas with high slopes and large drainage areas were more susceptible to water accumulation, indicating the need for culverts. The study also highlighted areas where culverts could be installed without significantly impacting existing infrastructure. It was recommended to install culverts in 27 locations along the track where they intersect with watercourses. Existing culverts covered just 93 watercourses, while 5 specialized culverts needed to be relocated. The findings have significant implications for railway engineering, as using GIS techniques streamlines the process of culvert location evaluation, saving time and resources. The systematic approach ensures culverts are installed in the most appropriate locations, minimizing flooding risks and ensuring the safety and efficiency of railway operations.

Water vapor content prediction based on neural network model selection and optimal fusion

Accurately predicting the evolution of water vapor content has significant practical engineering implications for accurately determining the timing of artificial rain enhancement operations. However, the nonlinear, unstable, and chaotic nature of water vapor content presents considerable challenges to its precise prediction. To address this, our research proposes a combined prediction model, based on a neural network model selection mechanism and small sample water vapor content data observed by microwave radiometers in the Zhengzhou area. This combined model utilizes seven neural network models as candidate models and dynamically selects the optimal three models as the central prediction components via evaluation indicators. Additionally, we employ the maximum information coefficient method to preserve the optimal input features and use a time-varying rate wave mode decomposition algorithm as the front-end processing module. This module processes the original water vapor content sequence and extracts relevant latent information. Finally, we incorporate the African vulture intelligent optimization algorithm as the backend processing component to optimize the weighted combination coefficients, achieving the integration of prediction results. Experimental results reveal that the Mean Absolute Percentage Errors (MAPE) of the proposed model on three types of water vapor content datasets are 0.208%, 0.876%, and 0.369%, respectively. This suggests a predictive performance improvement of at least 10% compared to existing models. The prediction model proposed in this study not only establishes an accurate and reliable mechanism for predicting water vapor content but also offers more comprehensive decision support information for weather modification operations.

Metal ion metabolism and osteoporosis: possible implications for pharmaceutical biotechnology and tissue engineering.

Metal ion metabolism and osteoporosis: possible implications for pharmaceutical biotechnology and tissue engineering.

Analyzing the impact of flexible shells and sound absorbent lining on acoustic wave behavior in ducts

This study focuses on investigating the propagation of acoustic waves in a cylindrical waveguide with higher‐order derivative‐based boundary conditions and a sound absorbent lining. The mode‐matching method is employed to solve the governing boundary value problem, utilizing continuity conditions for pressure and velocity at waveguide interfaces. The objective is to establish a theoretical framework for analyzing and optimizing the acoustic performance of the waveguide, considering the influence of crucial parameters. The study's findings hold significant practical implications in acoustic engineering and noise control, enabling accurate prediction of acoustic wave behavior and facilitating the design of effective noise reduction measures and optimized sound‐absorbing materials in various applications. Additionally, the numerical techniques developed here can be extended to address more complex waveguide geometries and boundary conditions.

Correlational fractal analysis of the Kaiser effect in rock: implications for salt-cavern engineering under triaxial cyclic loading and unloading

ABSTRACT The Kaiser effect exhibits stress-induced changes in the acoustic properties of rock, so accurately identifying the Kaiser point of rock under complex conditions is essential for understanding the damage and failure mechanisms. In this paper, triaxial loading and unloading tests were conducted on salt rock using MTS815 material testing machine and PCI-II acoustic emission (AE) system. By introducing the Kaiser point calculation approach involving AE signal optimisation, Grassberger-Procaccia (GP) algorithm, K-means clustering, and random sample consensus (RANSAC) algorithm, we achieved enhanced accuracy in analysing the Kaiser effect for salt rock. The cumulative AE energy exhibited a distinct surge point during the cycle number (N) was less than 21, closely aligned with the optimised key AE energy point. For N > 21, the cumulative energy displayed stable changes, rendering conventional method ineffective. By utilising screened AE signals (8796 samples) within the GP algorithm, the surge point of cumulative energy consistently aligned with the sudden drop point of the correlation dimension when N<21, with a maximum error of 6 s. Remarkably, the GP algorithm identified the prominent Kaiser point even when N > 21, suggesting its applicability throughout the loading cycle.