Search results for: small signal model

Authors: Luo Jiaoyang, Yu Hongyang

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In this paper, we explore a method that can be used in the working scene of intelligent industrial robots to confirm the identity information of operators to ensure that the robot executes instructions in a sufficiently safe environment. This approach uses three information modalities, namely visible light, depth, and sound. We explored a variety of fusion modes for the three modalities and finally used the joint feature learning method to improve the performance of the model in the case of noise compared with the single-modal case, making the maximum noise in the experiment. It can also maintain an accuracy rate of more than 90%.

Keywords: multimodal, kinect, machine learning, distance image

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Authors: Alemayehu Agizew Woldeamanuel, Mekonnen Maschal Tarekegn, Raj Mohan Balakrishina

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Composting is one of the conventional techniques adopted for organic waste management, but the practice is very limited in emerging cities despite the most of the waste generated is organic. This paper aims to examine the viability of composting for organic waste management in the emerging city of Addis Ababa, Ethiopia, by addressing the composting practice, quality of compost, and application of compost in urban agriculture. The study collects data using compost laboratory testing and urban farm households’ survey and uses descriptive analysis on the state of compost production and application, physicochemical analysis of the compost samples, and regression analysis on the urban farmer’s willingness to pay for compost. The findings of the study indicated that there is composting practice at a small scale, most of the producers use unsorted feedstock materials, aerobic composting is dominantly used, and the maturation period ranged from four to ten weeks. The carbon content of the compost ranges from 30.8 to 277.1 due to the type of feedstock applied, and this surpasses the ideal proportions for C:N ratio. The total nitrogen, pH, organic matter, and moisture content are relatively optimal. The levels of heavy metals measured for Mn, Cu, Pb, Cd and Cr⁶⁺ in the compost samples are also insignificant. In the urban agriculture sector, chemical fertilizer is the dominant type of soil input in crop productions but vegetable producers use a combination of both fertilizer and other organic inputs, including compost. The willingness to pay for compost depends on income, household size, gender, type of soil inputs, monitoring soil fertility, the main product of the farm, farming method and farm ownership. Finally, this study recommends the need for collaboration among stakeholders’ along the value chain of waste, awareness creation on the benefits of composting and addressing challenges faced by both compost producers and users.

Keywords: composting, emerging city, organic waste management, urban agriculture

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Authors: Jae-Yong Park, Yeo-Kyeong Lee, Hee-Sun Kim

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Purpose: This study aims at investigating the mechanical behaviors of mastication, according to various teeth movement. There are three masticatory cases which are general case and 2 cases of teeth movement. General case includes the common arrange of all teeth and 2 cases of teeth movement are that one is the half movement location case of molar teeth in no. 14 tooth seat after extraction of no. 14 tooth and the other is no. 14 tooth seat location case of molar teeth after extraction in the same case before. Materials and Methods: In order to analyze these cases, 3 dimensional finite element (FE) model of the skull were generated based on computed tomography images, 964 dicom files of 38 year old male having normal occlusion status. An FE model in general occlusal case was used to develop CAE procedure. This procedure was applied to FE models in other occlusal cases. The displacement controls according to loading condition were applied effectively to simulate occlusal behaviors in all cases. From the FE analyses, von Mises stress distribution of skull and teeth was observed. The von Mises stress, effective stress, had been widely used to determine the absolute stress value, regardless of stress direction and yield characteristics of materials. Results: High stress was distributed over the periodontal area of mandible under molar teeth when the mandible was transmitted to the coronal-apical direction in the general occlusal case. According to the stress propagation from teeth to cranium, stress distribution decreased as the distribution propagated from molar teeth to infratemporal crest of the greater wing of the sphenoid bone and lateral pterygoid plate in general case. In 2 cases of teeth movement, there were observed that high stresses were distributed over the periodontal area of mandible under teeth where they are located under the moved molar teeth in cranium. Conclusion: The predictions of the mechanical behaviors of general case and 2 cases of teeth movement during the masticatory process were investigated including qualitative validation. The displacement controls as the loading condition were applied effectively to simulate occlusal behaviors in 2 cases of teeth movement of molar teeth.

Keywords: cranium, finite element analysis, mandible, masticatory action, occlusal force

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Authors: Hamid Reza Shariatmadari

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The Muslims who believe in twelve Imams and believe that their twelfth Imam is now hidden, because of their kind of consideration of immune Imam as their unique canonical authority for interpretation of Islam, are subject of these important questions; how can you be democratic? And can you speak of democracy as the best model of governing? Answering this question, we can talk firstly about the nature of democracy and realize it as a way and mechanism not as a philosophy of identity and secondly we can refer to the nature and functions of Imam in Shiism and thirdly we will focus on the age of Ghaybah (Or concealment of Imam). In such a time we can or have to combine domination of Islamic Faqis (Islamic Jurists) and democracy which is known in Shiite Iran for instance as religious democracy.

Keywords: Shiism, concealment of Imam, Islamic Jurists, Democracy

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Authors: Adam J. Carinci

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Background: The opioid epidemic is the most pressing healthcare crisis of our time. There is increasing recognition that opioids have limited long-term efficacy and are associated with hyperalgesia, addiction, and increased morbidity and mortality. Therefore, alternative strategies to combat chronic pain are paramount. We initiated a multicenter retrospective case series to review the efficacy of DRG stimulation in facilitating opioid tapering, opioid discontinuation and as a viable alternative to chronic opioid therapy. Purpose: The dorsal root ganglion (DRG) plays a key role in the development and maintenance of pain. Recent innovations in neuromodulation, specifically, dorsal root ganglion stimulation, offers an effective alternative to opioids in the treatment of chronic pain. This retrospective case series demonstrates preliminary evidence that DRG stimulation facilitates opioid tapering, opioid discontinuation and presents a viable alternative to chronic opioid therapy. Procedure: This small multicenter retrospective case series provides preliminary evidence that DRG stimulation facilitates opioid weaning, opioid tapering and is a viable option to opioid therapy in the treatment of chronic pain. A retrospective analysis was completed. Visual analog scale pain scores and pain medication usage were collected at the baseline visit and after four weeks, 3 months and 6 months of treatment. Ten consecutive patients across two study centers were included. The pain was rated 7.38 at baseline and decreased to 1.50 at the 4-week follow-up, a reduction of 79.5%. All patients significantly decreased their opioid pain medication use with an average > 30% reduction in morphine equivalents and four were able to discontinue their medications entirely. Conclusion: This Retrospective case series demonstrates preliminary evidence that DRG stimulation facilitates opioid tapering, opioid discontinuation and presents a viable alternative to chronic opioid therapy.

Keywords: dorsal root ganglion, neuromodulation, opioid sparing, stimulation

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Authors: Juan Alfredo Guevara Carrio, Swamy Toolahalli Thipperudra, Riddhi Naik Dharmeshbhai, Sergio Graniero Echeverrigaray, Jose Vitorio Emiliano, Antonio Helio Castro

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In order to advance the hydrogen economy, several industrial sectors can potentially benefit from the trillions of stimulus spending for post-coronavirus. Blending hydrogen into natural gas pipeline networks has been proposed as a means of delivering it during the early market development phase, using separation and purification technologies downstream to extract the pure H₂ close to the point of end-use. This first step has been mentioned around the world as an opportunity to use existing infrastructures for immediate decarbonisation pathways. Among current technologies used to extract hydrogen from mixtures in pipelines or liquid carriers, membrane separation can achieve the highest selectivity. The most efficient approach for the separation of H₂ from other substances by membranes is offered from the research of 2D layered materials due to their exceptional physical and chemical properties. Graphene-based membranes, with their distribution of pore sizes in nanometers and angstrom range, have shown fundamental and economic advantages over other materials. Their combination with the structure of ceramic and geopolymeric materials enabled the synthesis of nanocomposites and the fabrication of membranes with long-term stability and robustness in a relevant range of physical and chemical conditions. Versatile separation modules have been developed for hydrogen separation, which adaptability allows their integration in industrial prototypes for applications in heavy transport, steel, and cement production, as well as small installations at end-user stations of pipeline networks. The developed membranes and prototypes are a practical contribution to the technological challenge of supply pure H₂ for the mentioned industries as well as hydrogen energy-based fuel cells.

Keywords: graphene nano-composite membranes, hydrogen separation and purification, separation modules, indsutrial prototype

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Authors: Alaa Morsy, Youssef Ibrahim

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Earthquake is one of the most catastrophic events, which makes enormous harm to properties and human lives. As a piece of a safe building configuration, reinforced concrete walls are given in structures to decrease horizontal displacements under seismic load. Shear walls are additionally used to oppose the horizontal loads that might be incited by the impact of wind. Reinforced concrete walls in residential buildings might have openings that are required for windows in outside walls or for doors in inside walls or different states of openings due to architectural purposes. The size, position, and area of openings may fluctuate from an engineering perspective. Shear walls can encounter harm around corners of entryways and windows because of advancement of stress concentration under the impact of vertical or horizontal loads. The openings cause a diminishing in shear wall capacity. It might have an unfavorable impact on the stiffness of reinforced concrete wall and on the seismic reaction of structures. Finite Element Method using software package ‘ANSYS ver. 12’ becomes an essential approach in analyzing civil engineering problems numerically. Now we can make various models with different parameters in short time by using ANSYS instead of doing it experimentally, which consumes a lot of time and money. Finite element modeling approach has been conducted to study the effect of opening shape, size and position in RC wall with different thicknesses under axial and lateral static loads. The proposed finite element approach has been verified with experimental programme conducted by the researchers and validated by their variables. A very good correlation has been observed between the model and experimental results including load capacity, failure mode, and lateral displacement. A parametric study is applied to investigate the effect of opening size, shape, position on different reinforced concrete wall thicknesses. The results may be useful for improving existing design models and to be applied in practice, as it satisfies both the architectural and the structural requirements.

Keywords: Ansys, concrete walls, openings, out of plane behavior, seismic, shear wall

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Authors: A. Douara, N. Kermas, B. Djellouli

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In this study, we report calculations of gate capacitance of AlGaN/GaN HEMTs with nextnano device simulation software. We have used a physical gate capacitance model for III-V FETs that incorporates quantum capacitance and centroid capacitance in the channel. These simulations explore various device structures with different values of barrier thickness and channel thickness. A detailed understanding of the impact of gate capacitance in HEMTs will allow us to determine their role in future 10 nm physical gate length node.

Keywords: gate capacitance, AlGaN/GaN, HEMTs, quantum capacitance, centroid capacitance

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Authors: Tridipa Biswas, Kamal Pandey

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A Digital Elevation Model (DEM) is a simple representation of a surface in 3 dimensional space with elevation as the third dimension along with X (horizontal coordinates) and Y (vertical coordinates) in rectangular coordinates. DEM has wide applications in various fields like disaster management, hydrology and watershed management, geomorphology, urban development, map creation and resource management etc. Cartosat-1 or IRS P5 (Indian Remote Sensing Satellite) is a state-of-the-art remote sensing satellite built by ISRO (May 5, 2005) which is mainly intended for cartographic applications.Cartosat-1 is equipped with two panchromatic cameras capable of simultaneous acquiring images of 2.5 meters spatial resolution. One camera is looking at +26 degrees forward while another looks at –5 degrees backward to acquire stereoscopic imagery with base to height ratio of 0.62. The time difference between acquiring of the stereopair images is approximately 52 seconds. The high resolution stereo data have great potential to produce high-quality DEM. The high-resolution Cartosat-1 stereo image data is expected to have significant impact in topographic mapping and watershed applications. The objective of the present study is to generate high-resolution DEM, quality evaluation in different elevation strata, generation of ortho-rectified image and associated accuracy assessment from CARTOSAT-1 data based Ground Control Points (GCPs) for Aglar watershed (Tehri-Garhwal and Dehradun district, Uttarakhand, India). The present study reveals that generated DEMs (10m and 30m) derived from the CARTOSAT-1 stereo pair is much better and accurate when compared with existing DEMs (ASTER and CARTO DEM) also for different terrain parameters like slope, aspect, drainage, watershed boundaries etc., which are derived from the generated DEMs, have better accuracy and results when compared with the other two (ASTER and CARTO) DEMs derived terrain parameters.

Keywords: ASTER-DEM, CARTO-DEM, CARTOSAT-1, digital elevation model (DEM), ortho-rectified image, photogrammetry, RPC, stereo pair, terrain parameters

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Authors: S. Sadallah

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In this paper, dynamic programming is used to determine the optimal management of financial resources in company. Solution of the problem by consider into simpler substructures is constructed. The optimal management of internal capital of company are simulated. The tools applied in this development are based on graph theory. The software of given problems is built by using greedy algorithm. The obtained model and program maintenance enable us to define the optimal version of management of proper financial flows by using visual diagram on each level of investment.

Keywords: management, software, optimal, greedy algorithm, graph-diagram

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Authors: Omuvwie R. Ewien

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Palm oil production in Delta State, Nigeria, is a significant economic activity. However, ensuring its sustainability is crucial to mitigate environmental impacts, promote social equity, and maintain long-term economic viability. This abstract provides an overview of palm oil production sustainability in Delta State, focusing on environmental, social, and economic aspects. In terms of environmental sustainability, the impact of palm oil plantations on deforestation and biodiversity loss is explored. The adoption of sustainable land use practices and measures to reduce greenhouse gas emissions, such as conserving high conservation value areas and utilizing methane capture systems, are highlighted. Social sustainability considerations encompass the inclusion and empowerment of smallholders, ensuring fair labor practices and community engagement. Supporting small-scale farmers, promoting fair working conditions, and investing in local infrastructure and services are identified as key strategies. Economic sustainability is emphasized through yield improvement, efficiency, and value addition. Enhancing productivity and profitability for farmers, promoting downstream processing and market diversification, and building economic resilience is crucial for long-term sustainability. Government policies, including regulatory frameworks and public-private collaborations, play a pivotal role in promoting sustainable palm oil production. Enabling policies and partnerships with industry stakeholders and NGOs facilitates the adoption of sustainable practices. Challenges such as illegal activities, the need to balance economic development with environmental conservation, and leveraging technology for sustainability are discussed. The abstract concludes by emphasizing the importance of stakeholders' commitment to prioritize sustainable palm oil production in Delta State, Nigeria, for a sustainable future.

Keywords: palm oil production, environmental sustainability, community development, yield improvement, future outlook

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Authors: Rabindranath Jana, Plabani Basu, Keka Rana

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Nucleating agents are widely used to modify the properties of various polymers. The rate of crystallization and the size of the crystals have a strong impact on mechanical and optical properties of a polymer. The addition of nucleating agents to the semi-crystalline polymers provides a surface on which the crystal growth can start easily. As a consequence, fast crystal formation will result in many small crystal domains so that the cycle times for injection molding may be reduced. Moreover, the mechanical properties e.g., modulus, tensile strength, heat distortion temperature and hardness may increase. In the present work, multi-walled carbon nanotubes (MWNTs) as nucleating agents for the crystallization of poly (e-caprolactone)diol (PCL). Thus nanocomposites of PCL filled with MWNTs were prepared by solution blending. Differential scanning calorimetry (DSC) tests were carried out to study the effect of CNTs on on-isothermal crystallization of PCL. The polarizing optical microscopy (POM), and wide-angle X-ray diffraction (WAXD) were used to study the morphology and crystal structure of PCL and its nanocomposites. It is found that MWNTs act as effective nucleating agents that significantly shorten the induction period of crystallization and however, decrease the crystallization rate of PCL, exhibiting a remarkable decrease in the Avrami exponent n, surface folding energy σe and crystallization activation energy ΔE. The carbon-based fillers act as templates for hard block chains of PCL to form an ordered structure on the surface of nanoparticles during the induction period, bringing about some increase in equilibrium temperature. The melting process of PCL and its nanocomposites are also studied; the nanocomposites exhibit two melting peaks at higher crystallization temperature which mainly refer to the melting of the crystals with different crystal sizes however, PCL shows only one melting temperature.

Keywords: poly(e-caprolactone)diol, multiwalled carbon nanotubes, composite materials, nonisothermal crystallization, crystal structure, nucleation

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Authors: Cesar Augusto Hoil Rosas, José Luis Vázquez Burgos, José Juan Carbajal Hernandez

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White fish (Chirostoma estor estor) is an endemic species that habits in the Patzcuaro Lake, located in Michoacan, Mexico; being an important source of gastronomic and cultural wealth of the area. Actually, it have undergone an immense depopulation of individuals, due to the high fishing, contamination and eutrophication of the lake water, resulting in the possible extinction of this important species. This work proposes a new computational model for monitoring and assessment of critical environmental parameters of the white fish ecosystem. According to an Analytical Hierarchy Process, a mathematical model is built assigning weights to each environmental parameter depending on their water quality importance on the ecosystem. Then, a development of an advanced system for the monitoring, analysis and control of water quality is built using the virtual environment of LabVIEW. As results, we have obtained a global score that indicates the condition level of the water quality in the Chirostoma estor ecosystem (excellent, good, regular and poor), allowing to provide an effective decision making about the environmental parameters that affect the proper culture of the white fish such as temperature, pH and dissolved oxygen. In situ evaluations show regular conditions for a success reproduction and growth rates of this species where the water quality tends to have regular levels. This system emerges as a suitable tool for the water management, where future laws for white fish fishery regulations will result in the reduction of the mortality rate in the early stages of development of the species, which represent the most critical phase. This can guarantees better population sizes than those currently obtained in the aquiculture crop. The main benefit will be seen as a contribution to maintain the cultural and gastronomic wealth of the area and for its inhabitants, since white fish is an important food and economical income of the region, but the species is endangered.

Keywords: Chirostoma estor estor, computational system, lab view, white fish

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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Authors: Hamed Kalhori, Lin Ye

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In this study, an inverse method was developed to reconstruct the magnitude and duration of impact forces exerted to a rectangular carbon fibre-epoxy composite honeycomb sandwich panel. The dynamic signals captured by Piezoelectric (PZT) sensors installed on the panel remotely from the impact locations were utilized to reconstruct the impact force generated by an instrumented hammer through an extended deconvolution approach. Two discretized forms of convolution integral are considered; the traditional one with an explicit transfer function and the modified one without an explicit transfer function. Deconvolution, usually applied to reconstruct the time history (e.g. magnitude) of a stochastic force at a defined location, is extended to identify both the location and magnitude of the impact force among a number of potential impact locations. It is assumed that a number of impact forces are simultaneously exerted to all potential locations, but the magnitude of all forces except one is zero, implicating that the impact occurs only at one location. The extended deconvolution is then applied to determine the magnitude as well as location (among the potential ones), incorporating the linear superposition of responses resulted from impact at each potential location. The problem can be categorized into under-determined (the number of sensors is less than that of impact locations), even-determined (the number of sensors equals that of impact locations), or over-determined (the number of sensors is greater than that of impact locations) cases. For an under-determined case, it comprises three potential impact locations and one PZT sensor for the rectangular carbon fibre-epoxy composite honeycomb sandwich panel. Assessments are conducted to evaluate the factors affecting the precision of the reconstructed force. Truncated Singular Value Decomposition (TSVD) and the Tikhonov regularization are independently chosen to regularize the problem to find the most suitable method for this system. The selection of optimal value of the regularization parameter is investigated through L-curve and Generalized Cross Validation (GCV) methods. In addition, the effect of different width of signal windows on the reconstructed force is examined. It is observed that the impact force generated by the instrumented impact hammer is sensitive to the impact locations of the structure, having a shape from a simple half-sine to a complicated one. The accuracy of the reconstructed impact force is evaluated using the correlation co-efficient between the reconstructed force and the actual one. Based on this criterion, it is concluded that the forces reconstructed by using the extended deconvolution without an explicit transfer function together with Tikhonov regularization match well with the actual forces in terms of magnitude and duration.

Keywords: honeycomb composite panel, deconvolution, impact localization, force reconstruction

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Authors: Felipe Azocar Simonet, Luis Acosta Espejo

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In this article, we will try to find an efficient boundary approximation for the bi-objective location problem with coherent coverage for two levels of hierarchy (CCLP). We present the mathematical formulation of the model used. Supported efficient solutions and unsupported efficient solutions are obtained by solving the bi-objective combinatorial problem through the weights method using a Lagrangean heuristic. Subsequently, the results are validated through the DEA analysis with the GEM index (Global efficiency measurement).

Keywords: coherent covering location problem, efficient frontier, lagragian relaxation, data envelopment analysis

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Authors: Breanna Macumber, Victor A. Huayamave, Emir A. Vela, Wangdo Kim, Tamara T. Chamber, Esteban Centeno

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Spina bifida is a type of neural tube defect that affects the nervous system and can lead to problems such as total leg paralysis. Treatment requires physical therapy and rehabilitation. Robotic exoskeletons have been used for rehabilitation to train muscle movement and assist in injury recovery; however, current models focus on the adult populations and not on the infant population. The proposed framework aims to couple a musculoskeletal infant model with a robotic exoskeleton using vacuum-powered artificial muscles to provide rehabilitation to infants affected by spina bifida. The study that drove the input values for the robotic exoskeleton used motion capture technology to collect data from the spontaneous kicking movement of a 2.4-month-old infant lying supine. OpenSim was used to develop the musculoskeletal model, and Inverse kinematics was used to estimate hip joint angles. A total of 4 kicks (A, B, C, D) were selected, and the selection was based on range, transient response, and stable response. Kicks had at least 5° of range of motion with a smooth transient response and a stable period. The robotic exoskeleton used a Vacuum-Powered Artificial Muscle (VPAM) the structure comprised of cells that were clipped in a collapsed state and unclipped when desired to simulate infant’s age. The artificial muscle works with vacuum pressure. When air is removed, the muscle contracts and when air is added, the muscle relaxes. Bench testing was performed using a 6-month-old infant mannequin. The previously developed exoskeleton worked really well with controlled ranges of motion and frequencies, which are typical of rehabilitation protocols for infants suffering with spina bifida. However, the random kicking motion in this study contained high frequency kicks and was not able to accurately replicate all the investigated kicks. Kick 'A' had a greater error when compared to the other kicks. This study has the potential to advance the infant rehabilitation field.

Keywords: musculoskeletal modeling, soft robotics, rehabilitation, pediatrics

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Authors: Nipun Agarwal, David Paul, Fareed Un Din

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Every organization develops a strategy that needs to be implemented and is undertaken through project delivery. In essence, project requirements should exactly replicate an organization’s strategy. In reality this does not happen, and behavioral factors deviate the project delivery from the strategic objectives. This occurs as project stakeholders can have competing objectives. Resultantly, requirements that are implemented through projects are less aligned to the strategy. This paper develops a game theoretic model to simulate why such deviations occur. That explains the difference between strategy development and implementation.

Keywords: strategy, simulation, project management, game theory

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Authors: Saqib Aziz, Brad Alexander, Christoph Gengnagel, Stefan Weinzierl

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This paper explores a generative design, simulation, and optimization workflow for the integration of acoustical diffuser and/or absorber geometry with embedded coupled Helmholtz-resonators for full-scale 3D printed building components. Large-scale additive manufacturing in conjunction with algorithmic CAD design tools enables a vast amount of control when creating geometry. This is advantageous regarding the increasing demands of comfort standards for indoor spaces and the use of more resourceful and sustainable construction methods and materials. The presented methodology highlights these new technological advancements and offers a multimodal and integrative design solution with the potential for an immediate application in the AEC-Industry. In principle, the methodology can be applied to a wide range of structural elements that can be manufactured by additive manufacturing processes. The current paper focuses on a case study of an application for a biaxial load-bearing beam grillage made of reinforced concrete, which allows for a variety of applications through the combination of additive prefabricated semi-finished parts and in-situ concrete supplementation. The semi-prefabricated parts or formwork bodies form the basic framework of the supporting structure and at the same time have acoustic absorption and diffusion properties that are precisely acoustically programmed for the space underneath the structure. To this end, a hybrid validation strategy is being explored using a digital and cross-platform simulation environment, verified with physical prototyping. The iterative workflow starts with the generation of a parametric design model for the acoustical geometry using the algorithmic visual scripting editor Grasshopper3D inside the building information modeling (BIM) software Revit. Various geometric attributes (i.e., bottleneck and cavity dimensions) of the resonator are parameterized and fed to a numerical optimization algorithm which can modify the geometry with the goal of increasing absorption at resonance and increasing the bandwidth of the effective absorption range. Using Rhino.Inside and LiveLink for Revit, the generative model was imported directly into the Multiphysics simulation environment COMSOL. The geometry was further modified and prepared for simulation in a semi-automated process. The incident and scattered pressure fields were simulated from which the surface normal absorption coefficients were calculated. This reciprocal process was repeated to further optimize the geometric parameters. Subsequently the numerical models were compared to a set of 3D concrete printed physical twin models, which were tested in a .25 m x .25 m impedance tube. The empirical results served to improve the starting parameter settings of the initial numerical model. The geometry resulting from the numerical optimization was finally returned to grasshopper for further implementation in an interdisciplinary study.

Keywords: acoustical design, additive manufacturing, computational design, multimodal optimization

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Authors: Michael Ryan, Rosemary E. Borgerding, Kimberly L. Oliver

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The objective of this study was to assess the effectiveness of a sports nutrition intervention on body composition in high-school athletes. The study aimed to improve the food and water intake of high-school athletes, evaluate the cost-effectiveness of the intervention, and assess changes in body fat. Data were collected through observations, questionnaires, and interviews. Additionally, bioelectrical impedance analysis was performed to assess the body composition of athletes both before and after the intervention. Athletes (n=25) participated in researcher-monitored training sessions three times a week over the course of 12 weeks. During these sessions, in addition to completing their auxiliary sports training, participants were exposed to educational interventions aimed at improving their nutrition. These included discussions regarding current eating habits, nutritional guidelines for athletes, and individualized recommendations. Food was also made available to athletes for consumption before and after practice. Meals of balanced macronutrient composition were prepared and provided to athletes on four separate occasions throughout the intervention, either prior to or following a competitive event such as a tournament or game. A paired t-test was used to determine the statistical significance of the changes in body fat percentage. The results showed that there was a statistically significant difference between pre and post-intervention body fat percentage (p= .006). Cohen's d of 0.603 was calculated, indicating a moderate effect size. In conclusion, this study provides evidence that a sports nutrition intervention that combines food availability, explicit prescription, and education can be effective in improving the body composition of high-school athletes. However, it's worth noting that this study had a small sample size, and the conclusions cannot be generalized to a larger population. Further research is needed to assess the scalability of this study. This preliminary study demonstrated the feasibility of this type of nutritional intervention and laid the groundwork for a larger, more extensive study to be conducted in the future.

Keywords: bioelectrical impedance, body composition, high-school athletes, sports nutrition, sports pedagogy

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Authors: Luigi Pari, Alessandro Suardi, Enrico Santangelo

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In the last decade Jatropha curcas L. (an oleaginous crop native to Central America and part of South America) has raised particular interest owing to of its properties and uses. Its capsules may contain up to 40% in oil and can be used as feedstock for biodiesel production. The harvesting phase is made difficult by the physiological traits of the specie, because fruits are in bunches and do not ripen simultaneously. Three harvesting methodologies are currently diffused and differ for the level of mechanization applied: manual picking, semi-mechanical harvesting, and mechanical harvesting. The manual picking is the most common in the developing countries but it is also the most time consuming and inefficient. Mechanical harvesting carried out with modified grape harvesters has the higher productivity, but it is very costly as initial investment and requires appropriate schemes of cultivation. The semi-mechanical harvesting method is achieved with shaker tools employed to facilitate the fruit detachment. This system resulted much cheaper than the fully mechanized one and quite flexible for small and medium scale applications, but it still requires adjustments for improving the productive performance. CRA-ING, within the European project Jatromed (http://www.jatromed.aua.gr) has carried out preliminary studies on the applicability of such approach, adapting an olive shaker to harvest Jatropha fruits. The work is a survey of the harvesting methods currently available for Jatropha, show the pros and cons of each system, and highlighting the criteria to be considered for choosing one respect another. The harvesting of Jatropha curcas L. remains a big constrains for the spread of the species as energy crop. The approach pursued by CRA-ING can be considered a good compromise between the fully mechanized harvesters and the exclusive manual intervention. It is an attempt to promote a sustainable mechanization suited to the social context of developing countries by encouraging the concrete involvement of local populations.

Keywords: jatropha curcas, energy crop, harvesting, central america, south america

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Authors: Vahid Ramezankhani, Keith J. Stevenson, Stanislav. S. Fedotov

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Lithium-ion batteries (LIBs) play a pivotal role in achieving the key objective “zero-carbon emission” as countries agreed to reach a 1.5ᵒC global warming target according to the Paris agreement. Nowadays, due to the tremendous mobile and stationary consumption of small/large-format LIBs, the demand and consequently the price for such energy storage devices have been raised. The aforementioned challenges originate from the shrinkage of the major applied critical materials in these batteries, such as cobalt (Co), nickel (Ni), Lithium (Li), graphite (G), and manganese (Mn). Therefore, it is imperative to consider alternative elements to address issues corresponding to the limitation of resources around the globe. Potassium (K) is considered an effective alternative to Li since K is a more abundant element, has a higher operating potential, a faster diffusion rate, and the lowest stokes radius in comparison to the closest neighbors in the periodic table (Li and Na). Among all reported materials for metal-ion batteries, some of them possess the general formula AMXO4L [A = Li, Na, K; M = Fe, Ti, V; X = P, S, Si; L= O, F, OH] is of potential to be applied both as anode and cathode and enable researchers to investigate them in the full symmetric battery format. KTiPO4F (KTP structural material) has been previously reported by our group as a promising cathode with decent electronic properties. Herein, we report a synthesis, crystal structure characterization, morphology, as well as K-ion storage properties of KTiPO4F. Our investigation reveals that KTiPO4F delivers discharge capacity > 150 mAh/g at 26.6 mA/g (C/5 current rate) in the potential window of 0.001-3 V. Surprisingly, the cycling performance of C-KTiPO4F//K cell is stable for 1000 cycles at 130 mA/g (C current rate), presenting capacity > 130 mAh/g. More interestingly, we achieved to assemble full symmetric batteries where carbon-coated KTiPO4F serves as both negative and positive electrodes, delivering >70 mAh/g in the potential range of 0.001-4.2V.

Keywords: anode material, potassium battery, chemical characterization, electrochemical properties

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Authors: Amriana Hifizah, Philip Edward Vercoe, Graeme Bruce Martin, Teuku Reza Ferasy, Muhammad Hambal

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Many native forage plant species have been used in Indonesia as feed for ruminants. However, less information is available about how these plants affect productivity, let alone methane emissions. In the province of Aceh, where the traditional practice is to feed local forages to small ruminants, the farmers are not satisfied with the productivity of their livestock, and they attribute this problem to poor availability and too few options for good quality forages. Forage quality is reduced by high environmental temperatures which increase the amount of lignification. In addition to reducing productivity, these factors also increase enteric methane production. A preliminary survey about potential forage species was completed in three different districts, two of low elevation and one of high elevation: Syiah Kuala (05°30’5.08” N to 095°24’7.35” E), elevation 29 m MSL; Kajhu (05°32’34.6” N to 095°21’17.7” E), elevation 30 m MSL; Lembah Seulawah (05°28'06.4" N to 095°43' 14.2" E), elevation 254 m MSL. Information about local plants was collected in a semi-structured interview with scientists, government field officers and local farmers, in the city of Banda Aceh and in those three districts. The outcome was a list 40 species that could be useful, of which 21 were selected for further study. The selection process was based on several criteria: high availability, high protein content, low toxicity, and evidence of secondary metabolites (eg, history of medicinal plants for both human and animals). For some of the selected medicinal plants, there is experimental evidence of effects on methane production during rumen fermentation. Subsequently, the selected forages were tested for their effects on rumen fermentation in vitro, using batch culture. The data produced will be used to identify forages with the potential to reduce CH4 emissions. These candidates will then be assessed for their benefits (fermentability and productivity) and potential deleterious side-effects.

Keywords: batch culture, forage, methane, rumen

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Authors: B. I. Zhumagaliyev, L. Sh. Balgabayeva, G. S. Nabiyeva, B. A. Tulegenova, P. Oralkhan, B. S. Kalenova, S. S. Akhmetov

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The article describes an approach to build competence in research of Bachelor and Master, which is now an important feature of modern specialist in the field of engineering. Provides an example of methodical teaching methods with the research aspect, is including the formulation of the problem, the method of conducting experiments, analysis of the results. Implementation of methods allows the student to better consolidate their knowledge and skills at the same time to get research. Knowledge on the part of the media requires some training in the subject area and teaching methods.

Keywords: professional competence, model of it-specialties, teaching methods, educational technology, decision making

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Authors: Selim M. Khan

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Indoor air quality is strongly influenced by the presence of radioactive radon (222Rn) gas. Indeed, exposure to high 222Rn concentrations is unequivocally linked to DNA damage and lung cancer and is a worsening issue in North American and European built environments, having increased over time within newer housing stocks as a function of as yet unclear variables. Indoor air radon concentration can be influenced by a wide range of environmental, structural, and behavioral factors. As some of these factors are quantitative while others are qualitative, no single statistical model can determine indoor radon level precisely while simultaneously considering all these variables across a complex and highly diverse dataset. The ability of AI- machine (deep) learning to simultaneously analyze multiple quantitative and qualitative features makes it suitable to predict radon with a high degree of precision. Using Canadian and Swedish long-term indoor air radon exposure data, we are using artificial deep neural network models with random weights and polynomial statistical models in MATLAB to assess and predict radon health risk to human as a function of geospatial, human behavioral, and built environmental metrics. Our initial artificial neural network with random weights model run by sigmoid activation tested different combinations of variables and showed the highest prediction accuracy (>96%) within the reasonable iterations. Here, we present details of these emerging methods and discuss strengths and weaknesses compared to the traditional artificial neural network and statistical methods commonly used to predict indoor air quality in different countries. We propose an artificial deep neural network with random weights as a highly effective method for assessing and predicting indoor radon.

Keywords: radon, radiation protection, lung cancer, aI-machine deep learnng, risk assessment, risk prediction, Europe, North America

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Authors: Shoukat Ali, Abdul Qadir Jandga, Amjad Hussain

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Objective: The main purpose of this study is to compare the Percent Depth dose (PDD) and In-plane and cross-plane profiles of Varian Golden beam data to the measured data of 6 and 18 MV photons for the commissioning of Eclipse treatment planning system. Introduction: Commissioning of treatment planning system requires an extensive acquisition of beam data for the clinical use of linear accelerators. Accurate dose delivery require to enter the PDDs, Profiles and dose rate tables for open and wedges fields into treatment planning system, enabling to calculate the MUs and dose distribution. Varian offers a generic set of beam data as a reference data, however not recommend for clinical use. In this study, we compared the generic beam data with the measured beam data to evaluate the reliability of generic beam data to be used for the clinical purpose. Methods and Material: PDDs and Profiles of Open and Wedge fields for different field sizes and at different depths measured as per Varian’s algorithm commissioning guideline. The measurement performed with PTW 3D-scanning water phantom with semi-flex ion chamber and MEPHYSTO software. The online available Varian Golden Beam Data compared with the measured data to evaluate the accuracy of the golden beam data to be used for the commissioning of Eclipse treatment planning system. Results: The deviation between measured vs. golden beam data was in the range of 2% max. In PDDs, the deviation increases more in the deeper depths than the shallower depths. Similarly, profiles have the same trend of increasing deviation at large field sizes and increasing depths. Conclusion: Study shows that the percentage deviation between measured and golden beam data is within the acceptable tolerance and therefore can be used for the commissioning process; however, verification of small subset of acquired data with the golden beam data should be mandatory before clinical use.

Keywords: percent depth dose, flatness, symmetry, golden beam data

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Authors: Islam Nowisser, Noha Farag, Mohamed El Azizi

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Helicobacter pylori is a highly important human pathogen which inhabits about 50% of the population worldwide. Infection with this bacteria is very hard to treat, with high probability of recurrence. H. pylori causes severe gastric diseases, including peptic ulcer, gastritis, and gastric cancer, which has been linked to chronic inflammation. The infection has been reported to be associated with high levels of pro-inflammatory cytokines, especially IL-1β and TNF-α. The aim of the current study is to investigate the molecular mechanisms by which H. pylori activates NLRP3 inflammasome and its contribution to Il-1 β production in an innate cellular model. H. pylori PMSS1 and G27 standard strains, as well as the PMSS1 isogenic mutant strain PMSS1ΔVacA and G27ΔVacA, G27ΔCagA in addition to clinical isolates obtained from biopsy samples from the antrum and corpus mucosa of chronic gastritis patients, were used to establish infection in RAW-264.7 macrophages. The production levels of TNF-α and IL-1β was assessed using ELISA. Since expression of these cytokines is often regulated by the transcription factor complex, nuclear factor-kB (NF-kB), the activation of NF-κB in H. pylori infected cells was also evaluated by luciferase assay. Genomic DNA was extracted from bacterial cultures of H. pylori clinical isolates as well as the standard strains and their corresponding mutants, where they were evaluated for the cagA pathogenicity island and vacA expression. The correlation between these findings and expression of the cagA Pathogenicity Island and vacA in the bacteria was also investigated. The results showed IL-1β, and TNF-α production significantly increased in raw macrophages following H. pylori infection. The cagA+ and vacA+ H. pylori strains induced significant production of IL-1β compared to cagA- and vacA- strains. The activation pattern of NF-κB was correlated in the isolates to their cagA and vacA expression profiles. A similar finding could not be confirmed for TNF-α production. Our study shows the ability of H. pylori to activate NF-kB and induce significant IL-1β production as a possible mechanism for the augmented inflammatory response seen in subjects infected with cagA+ and vacA+ H. pylori strains that would lead to the progression to more severe form of the disease.

Keywords: Helicobacter pylori, IL-1β, inflammatory cytokines, nuclear factor KB, TNF-α

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Authors: H. Ferfera-Harrar, T. Benhalima, D. Lerari

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Contamination of water, due to the discharge of untreated industrial wastewaters into the ecosystem, has become a serious problem for many countries. In this study, bioadsorbents based on chitosan-g-poly(acrylamide) and montmorillonite (MMt) clay (CTS-g-PAAm/MMt) hydrogel nanocomposites were prepared via free‐radical grafting copolymerization and crosslinking of acrylamide monomer (AAm) onto natural polysaccharide chitosan (CTS) as backbone, in presence of various contents of MMt clay as nanofiller. Then, they were hydrolyzed to obtain highly functionalized pH‐sensitive nanomaterials with uppermost swelling properties. Their structure characterization was conducted by X-Ray Diffraction (XRD) and Scanning Electron Microscopy (SEM) analyses. The adsorption performances of the developed nanohybrids were examined for removal of methylene blue (MB) cationic dye from aqueous solutions. The factors affecting the removal of MB, such as clay content, pH medium, adsorbent dose, initial dye concentration and temperature were explored. The adsorption process was found to be highly pH dependent. From adsorption kinetic results, the prepared adsorbents showed remarkable adsorption capacity and fast adsorption rate, mainly more than 88% of MB removal efficiency was reached after 50 min in 200 mg L^-1 of dye solution. In addition, the incorporating of various content of clay has enhanced adsorption capacity of CTS-g-PAAm matrix from 1685 to a highest value of 1749 mg g^-1 for the optimized nanocomposite containing 2 wt.% of MMt. The experimental kinetic data were well described by the pseudo-second-order model, while the equilibrium data were represented perfectly by Langmuir isotherm model. The maximum Langmuir equilibrium adsorption capacity (q_m) was found to increase from 2173 mg g⁻¹ until 2221 mg g⁻¹ by adding 2 wt.% of clay nanofiller. Thermodynamic parameters revealed the spontaneous and endothermic nature of the process. In addition, the reusability study revealed that these bioadsorbents could be well regenerated with desorption efficiency overhead 87% and without any obvious decrease of removal efficiency as compared to starting ones even after four consecutive adsorption/desorption cycles, which exceeded 64%. These results suggest that the optimized nanocomposites are promising as low cost bioadsorbents.

Keywords: chitosan, clay, dye adsorption, hydrogels nanocomposites

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Authors: Fatima Zohra Mahi, Luca Varani

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We present an analytical model for the calculation of the sensitivity, the spectral current noise and the detectivity for an optically illuminated In0.53Ga0.47As n+nn+ diode. The photocurrent due to the excess carrier is obtained by solving the continuity equation. Moreover, the current noise level is evaluated at room temperature and under a constant voltage applied between the diode terminals. The analytical calculation of the current noise in the n+nn+ structure is developed. The responsivity and the detectivity are discussed as functions of the doping concentrations and the emitter layer thickness in one-dimensional homogeneous n+nn+ structure.

Keywords: detectivity, photodetectors, continuity equation, current noise

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Authors: Xinxiu Li, Chuqian Zheng, Yanyan Qian, Hong Fan

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Objectives: In hepatocellular carcinoma (HCC), oncogenes are continuously and robustly transcribed due to aberrant expression of essential components of the trans-acting super-enhancers (SE) complex. Preclinical and clinical trials are now being conducted on small-molecule inhibitors that target core-transcriptional components, including as transcriptional bromodomain protein 4 (BRD4) and cyclin-dependent kinase 7 (CDK7), in a number of malignant tumors. This study aims to explore whether co-overexpression of BRD4 and CDK7 is a potential marker of worse prognosis and a combined therapeutic target in HCC. Methods: The expression pattern of BRD4 and CDK7 and their correlation with prognosis in HCC were analyzed by RNA sequencing data and survival data of HCC patients from TCGA and GEO datasets. The protein levels of BRD4 and CDK7 were determined by immunohistochemistry (IHC), and survival data of patients were analyzed using the Kaplan-Meier method. The mRNA expression levels of genes in HCC cell lines were evaluated by quantitative PCR (q-PCR). CCK-8 and colony formation assays were conducted to assess cell proliferation of HCC upon treatment with BRD4 inhibitor JQ1 or/and CDK7 inhibitor THZ1. Results: It was shown that BRD4 and CDK7 were often overexpressed in HCCs and were associated with poor prognosis of HCC by analyzing the TCGA and GEO datasets. BRD4 or CDK7 overexpression was related to a lower survival rate. It's interesting to note that co-overexpression of CDK7 and BRD4 was a worse prognostic factor in HCC. Treatment with JQ1 or THZ1 alone had an inhibitory effect on cell proliferation; however, when JQ1 and THZ1 were combined, there was a more notable suppression of cell growth. At the same time, the combined use of JQ1 and THZ1 synergistically suppresses the expression of HCC driver genes. Conclusion: Our research revealed that BRD4 and CDK7 coupled can be a useful biomarker in HCC prognosis and the combination of JQ1 and THZ1 can be a promising therapeutic therapy against HCC.

Keywords: BRD4, CDK7, cell proliferation, combined inhibition

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