Miracle-dz/UniFAR-FTUs huggingface dataset:
Quercetin and a plant substance, identified using a multi-copy number of DNA topoisomerase I in recombinant Pichia pastoris, inhibited MDA-MB-231 proliferation via different manners.

The study employed an in vivo strategy to construct a multi-copy number of human DNA topoisomerase I (hTopI) gene using pPIC3.5K vector in GS115 strain of Pichia. The yeast transformant (GS115-pPIC3.5K-hTopI; clone) was then used to investigate the preliminary growth effect of a pure compound (quercetin) and a standardised subfraction of ethanolic red onion peel extract (F1). The clones’ cell density was likely to be unaffected; only the total protein expression and enzyme activity were increased following the increased copy number of hTop1 in the host. The clone that showed the target enzyme's highest activity is said to respond specifically to growth inhibitors, whereby both quercetin and F1 were proven to be potential growth inhibitors as assessed by the MTT assay. In the process, quercetin reduced cell proliferation by inducing apoptosis and cell cycle arrest (S phase only), whereas F1 reduced cell proliferation by inducing cell cycle arrest only (S and G2 phases). Quercetin and F1 induced CYP1A1 and CYP1B1 (carcinogenicity) gene mRNA expression, but only F1 induced CYP2S1 (cytotoxicity) gene mRNA expression in the treated cells, suggesting that both quercetin and F1 inhibited the cell proliferation of MDA-MB-231 via different manners. The newly developed GS115-pPIC3.5K-hTopI can be used to select various potential substances for breast cancer treatment in the future.
Study on Cold Resistance of Snake Fruit by Application of Electrical Conductivity and Logistic Equation

The cold-resistance of four snake fruit varieties(Bali,Pondoh,Galing and M9) at different low temperatures was studied,the result showed that 4 varieties had the following order in cold resistance:Pondoh Gading M9 Bali.The relative conductivity of snake fruit increased along with the decrease of temperature.Leaf damage rate(%) of snake fruit was obviously increased below 5 ℃. Difference analysis indicated that the relative conductivity of Bali and M9 showed significant difference at significance level of 0.05,the similar changes of leaf damage rate were also observed.LT50 of snake fruit leaves ranged from 4 ℃ to 6 ℃. The result showed that application of electrical conductivity had better effect for estimating the cold-resistance of snake fruit,the lowest tolerant temperature of snake fruit could be deduced when the application of electrical conductivity was cooperated with Logistic equation.
New design of wideband microstrip branch line coupler using T-shape and open stub for 5G application

A new design of wideband branch-line coupler (BLC) using T-shape with open stub microstrip line is proposed. The branch line coupler is integrated with low and high impedance λ/4 transmission lines to achieve the comparatively compact size of (27.2 mm × 16.5 mm). operating the bandwidth in simulated of BLC from 2.9 to 4 GHz is obtained 30.22% with a frequency center of 3.5 GHz. Meanwhile, the measured bandwidth of the BLC is cover from 2.8 GHz to 4.22 GHz is equal 33.40% at the center frequency 3.55 GHz respectively. The BLC simulated has low isolation and high return loss of -29.28 dB and -30.69 dB at the center frequency 3.5 GHz.Whereas, the measured result has a simple difference in the return loss and isolation are -27.43dB and -24.46 dB at the frequency 3.55GHz respectively. This BLC design has a good coupling factor of -2.97 and insertion loss of -3.65 dB. Furthermore, it obtains an excellent amplitude and phases different between two output of ±0.1 and 93.6°±3.4° with high performance. There is a good agreement between the simulated result and the measured result. This branch line coupler design used for 5G applications for future wireless communication systems.
A Hybrid Pilot Beamforming and Channel Tracking Scheme for Massive MIMO Systems

In massive MIMO systems, the effective channel state information (CSI) is an essential prerequisite for the beamforming (BF) design. While there is a handful of previously proposed compressive sensing (CS)-based channel estimation algorithms in the literature, the large BF gain provided by the massive MIMO array has not been fully exploited in the channel estimation stage. In order to obtain higher BF gain and better estimation performance with less pilot overhead, we study the joint design of the transmitting and receiving hybrid pilot BF as well as the associated channel tracking scheme. Specifically, a Markov prior is used to model the temporal correlation in massive MIMO channels over different time slots. Then, the hybrid pilot BF is optimized by maximizing the mutual information between the channel measurements and the corresponding downlink sparse channels with the Markov prior. Following, we derive an efficient channel tracking algorithm called Turbo Bayesian Inference (Turbo-BI) to solve the resulting CS problem and generate the channel prior information required to calculate the mutual information for the optimization of hybrid pilot BF in the next time slot. The proposed Turbo-BI can exploit both the sparsity and the temporal correlation of massive MIMO channels to enhance the estimation performance. Finally, simulations show that our proposed algorithm can achieve significant gain over the existing state-of-the-art baselines.
A Two‐Phase, Pore‐Scale Reactive Transport Model for the Kinetic Interface‐Sensitive Tracer

Previous laboratory experiments with the kinetic interface sensitive (KIS) tracers have shown promising results with respect to the quantification of the fluid‐fluid interfacial area (IFA) under dynamic, two‐phase flow conditions. However, pore‐scale effects relevant to two‐phase flow (e.g., the formation of hydrodynamically stagnant/immobile zones) are not yet fully understood, and quantitative information about how far these effects influence the transport of the tracer reaction products is not yet available. Therefore, a pore‐scale numerical model that includes two‐phase, reactive flow, and transport of the KIS tracer at the fluid‐fluid interface is developed. We propose a new method to quantitatively analyze how the mass of the KIS‐tracer reaction product in the flowing water is affected by the presence of the immobile zones. The model employs the phase field method (PFM) and a new continuous mass transfer formulation, consistent with the PFM. We verify the model with the analytical solutions of transport involving advection, reaction and diffusion processes. The model is tested for two‐phase flow conditions in a conceptual 2D slit. The applicability of the model is demonstrated in NAPL/water drainage scenarios in a conceptual porous domain, comparing the results in terms of the spatial distribution of the phases and solute concentration. Furthermore, we distinguish the mobile and immobile zones based on the local Péclet number, and the corresponding IFA, and solute mass in these two zones is quantified. Finally, we show that the solute mass in flowing water can be employed to selectively determine the mobile part of the IFA.
U NSUPERVISED D ISCOVERY OF 3D P HYSICAL O BJECTS FROM V IDEO

We study the problem of unsupervised physical object discovery. While existing frameworks aim to decompose scenes into 2D segments based off each object’s appearance, we explore how physics, especially object interactions, facilitates dis-entangling of 3D geometry and position of objects from video, in an unsupervised manner. Drawing inspiration from developmental psychology, our Physical Object Discovery Network (POD-Net) uses both multi-scale pixel cues and physical motion cues to accurately segment observable and partially occluded objects of varying sizes, and infer properties of those objects. Our model reliably segments objects on both synthetic and real scenes. The discovered object properties can also be used to reason about physical events
Balanced biosynthesis and trigger threshold resulting in a double adder mechanism of cell size control

How cells accomplish cell size homeostasis is a fascinating topic, and several cell size regulation mechanisms were proposed: timer, sizer, and adder. Recently the adder model has received a great deal of attention. Adder property was also found in the DNA replication cycle. This paper aims to explain the adder phenomenon both in the division-centric picture and replication-centric picture at the molecular level. We established a self-replication model, and the system reached a steady state quickly based on evolution rules. We collected tens of thousands of cells in the same trajectory and calculated the Pearson correlation coefficient between biological variables to decide which regulatory mechanism was adopted by cells. Our simulation results confirmed the double-adder mechanism. Chromosome replication initiation and cell division control are independent and regulated by respective proteins. Cell size homeostasis originates from division control and has nothing to do with replication initiation control. At a slow growth rate, the deviation from adder toward sizer comes from a significant division protein degradation rate when division protein is auto-inhibited. Our results indicated the two necessary conditions in the double-adder mechanism: one is balanced biosynthesis, and the other is that there is a protein trigger threshold to inspire DNA replication initiation and cell division. Our results give insight to the regulatory mechanism of cell size and instructive to synthetic biology.
Feature curve extraction from data points

In the present work, study is done for the extraction of feature curves from data points lying on the surface of object or model. Here, the reconstruction of feature curves is proposed by intersection of plane pairs. These plane pairs approximate the adjacent regions of the feature. Feature of the object may be its edges, corners, holes, sudden jerks, slits etc. Points cloud is generated from the snapshots of the object taken from various viewing angles. Clustering work is extended from K-means clustering to combined K-means and Normal (attribute) approach based clustering as it utilizes the benefits of both K-means and attribute based method and segmented the data points so that a cluster is represented with similar normal vector. Planes are fitted to all clusters based on Least Square Plane Fitting (LSPF) method and line segments from their intersection are identified, highlighted and collected as feature lines i.e. edges and corners based on developed algorithm.
Improvement of projection-based LiDAR data segmentation algorithms using object-contextual representations

Nowadays self-driving cars and such unmanned aerial vehicles as drones are one of the most actively developed technologies, where machine learning algorithms play an irreplaceable role especially in the perception problem, which is the context of this research. To be applicable in self-driving cars and especially drones such algorithms should not only have good output quality, but also be real-time. For this reason, in the case of LiDAR data segmentation problem we pay special attention to algorithms that are based on point cloud projections because of their speed superiority over other heavy algorithms that process input point cloud directly. The main drawback of projection-based algorithms is their lower segmentation accuracy, so in this paper we show that it can be improved by integrating contextual representation module inside segmentation algorithm architecture. In our work we consider SalsaNext as a segmentation algorithm and OCR as a context representation module because these methods are among the highest in the corresponding datasets’ leaderboards. We provide results from quantitative evaluation on the Semantic-KITTI dataset, which demonstrate that the proposed SalsaNext modification gives 6.2% mean intersection over union metric improvement with no speed reduction.
Modelling of the process of a program compilation according to the training sample data using the collective intelligence of the simplest computers

The description of the system intended for genetic programming and consisting of a large number of elementary computers is given. Commands and data are placed in a cell consisting of four fields – the first address field, the second address field, the arithmetic field and the result field. This architecture made it possible to place a software binary tree formed by commands and addresses into sequentially located cells of an elementary computer. This technique made it possible to simplify the crossover and mutation operators, as well as the coding of the problem without involving complex programming systems and supercomputers. In the future, it is planned to use table processors tested on complex problems of genetic programming to significantly reduce power consumption in on-board computers of aviation and space technology.
Technique of considering the material anisotropy in topology optimization of short fibers composite structures

The use of composite materials in the aerospace industry has been increasing in the past 20 years. The application of short fiber reinforced composite as materials for aerospace components can solve the delamination problem by substituting the laminates, reduce the weight and the cost of the component. The design of short fiber reinforced composite structures requires obtaining the optimal structure geometry which is a function of the injection molding process. The novelty of this work is the development of a topology optimization algorithm that considers the material anisotropy by simulating the injection molding process at intermediate steps of topology optimization on a reduced mesh of the design area. It is shown that the consideration of the material anisotropy within topology optimization leads to a susceptible change in the topology of the structure and made it possible to increase the stiffness of the aerospace bracket molded from short fiber reinforced polymers.
A Modeling of Lead-Acid Battery for Electric Vehicles and Simulation Utilizing C MEX S-Function in Matlab/Simulink

Nowadays, the need for better performance of batteries as an energy source is increasing following the growth of electrical vehicles (EVs). Therefore, modeling the battery system is important to analyze how the battery is able to perform better so that further increases the EV’s performance. This study is addressed to analyze and simulate circuit modeling of lead-acid battery into a pretty complex RLC circuit, voltage source of battery itself, and a connected load with provided conditions for obtaining varying parameters which are used by the battery with a permanent initial state of charge (SoC). This circuit is simulated using C/C++ programming where it is implemented to some connected C MEX S-Function blocks in Simulink. The result of the study is proved that series circuits increase their voltage and parallel circuits increase their ampere. For satisfying the EV’s specs such as V ou t = 400 V and the capacity = 100 Ah, arranging batteries in 400 series since n = 15 produce around 13 V.
Grey wolf optimizer and other metaheuristic optimization techniques with image processing as their applications: a review

Image processing is an evolutionary field in the domain of computer vision that currently has a comprehensive spectrum of applications. It is being employed in image segmentation, image classification, medical imaging, image compression, etc. A lot of real-world prominent issues are tackling employed through these application techniques. These techniques can be employed by means of various algorithms; however, these offered immensely dominant outcomes with existing and modified optimization algorithms. Some of the metaheuristic optimization algorithms applied during the above techniques include Ant Colony Optimization (ACO), Genetic Algorithm (GA), Bat Algorithm (BA), Grey Wolf Optimizer (GWO), Evolutionary Strategy (ES), Particle Swarm Optimization (PSO), Genetic Programming (GP), and so forth. Hence, this manuscript’s main objective is that the study of several applied optimization algorithms and their variants thus lead to the various domain of image processing concludes it work more efficiently and robustly.
Design and optimization of piezo resistors for a graphene based MEMS ICP sensor

Modeling and simulation of MEMS Intracranial pressure sensor using Graphene as the structural layer is defined. At normal health condition, the ICP pressure is in the range of 10-15 mmHg. Any variation from this range will signify the abnormalities such as neural system malfunction, nausea, vomiting, paralysis, brain tumor rupturing, and excitement.For Intracranial pressure sensing applications, to measure this slight variation of pressure a sensor having high sensitivity need to be employed and is solely depends on membrane used. properties of high young’s modulus, high thermal stability and electrical conductivity, inertness and zero band gap made it biocompatible to fabricate Intracranial piezoresistive pressure (ICP) sensor with membrane as graphene. COMSOL Multiphysics tool which is a finite element analysis (FEA) is deployed to optimize the dimensions and parameters for using graphene as a structural layer for pressure sensor diaphragm. A variability study of piezo resistors with three different meander shape are designed and simulated in COMSOL. The optimum design is further analyzed for three different type of pressure sensor specifications as conventional, with n-type dopant and graphene as a structural layer. The design with three meander resistance and graphene as a structural layer provides a strain induced of 0.14 with the pressure input of 10 mmHg.
Developing a teacher professional learning workshop on the general theory of relativity

The development of a teacher professional learning workshop to support the General Relativity section of the Scottish Qualifications Authority Advanced Higher Physics course [1] for 17-18 year old secondary school students is described. This professional learning workshop is designed to support the development of teachers’ subject matter knowledge and pedagogical content knowledge so they are better able to provide a conceptual, non-mathematical approach to teaching curved spacetime, spacetime diagrams and evidence of the tests for General Relativity. The professional learning workshop draws on a number of resources including the educational outreach materials from the Perimeter Institute [2,3,4].
Stress state analysis of laminated shells with piezoelectric layers based on the refined theory

This paper presents stress state analysis of composite cylindrical shells bonded piezoelectric layers in the top and bottom surfaces. The laminated smart shell is subjected to electric potential and mechanical loading. The mathematical model of electroelasticity behaviour is based on the refined theory and virtual work principle. The governing differential equations are reduced to ordinary differential equations by means of trigonometric function expansion for displacement and electric potential. Operative method is used to solution of boundary problem. Stress-strain state of smart cylinder for electromechanical loads with clamped support is provided. Numerical results are presented showing the effect of boundary layer at clamped edges and comparison between the obtained results to the classical theory of the Kirchhoff-Love type is accurate.
DSMC Dissociation Model Based on Two-Temperature Chemical Rate Constant

A novel approach to statistical simulation of high-temperature nonequilibrium chemical reactions is described. Vibrationally speciflc dissociation cross sections are sought solving an integral equation whose right side contains a two-temperature reaction rate constant. An approximate stable solution of this equation is found numerically by Tikhonov regularization method. The class of functions to which the solution belongs is deflned on the basis of physical concepts of the form of the sought cross sections as functions of energy. The approach is illustrated by an example of the model of high-temperature dissociation of nitrogen. All stages of model implementation are considered in detail, namely, the mathematical basis, analysis of the model by comparisons with conventional models both at the level of cross sections and at the level of macroscopic reaction rates, and particular applications to computations of near-continuum reacting ∞ows by the Direct Simulation Monte Carlo method.
Video Transmission In Wireless Multihop Networks

Multi hop wireless networks are being deployed in many video streaming applications because they have several potential features for next generation wireless communications. Though optimal encoding techniques offers significant quality retention in video transmission still it is insufficient to overcome the challenges ahead over wireless network transmission. In order to support wide range video communications in an efficient way certain Quality of service has to be retained in multi hop wireless network. To address this issue, this paper investigates several encoding and routing protocols video delivery over multi hop wireless networks. Specifically, we first investigate several encoding framework for videos and wireless data transmission over WMNs through individual paths; we then investigate the challenges ahead to formulate resistant routing model for least possible video quality dictions which incorporate channel status as well as the encoder properties over video characteristics. In this framework, routing techniques which can maximally used to achieve good video traffic with improved system performance. However, video streaming also have very stringent delay requirements, which makes it difficult to find optimal routes with the least possible distortions. To address this problem, we investigate several enhanced version of packet scheduling techniques for video communications over multi path multi hob multi user wireless network environment.
Development of mathematical models for the forecast and evaluation of the performance of hydropower using transfer function modelling

Poor, inefficient and negligence in the evaluation of the performance of a hydropower plant is the root cause of reduced and inefficient power generation, high maintenance costs and replacement or repairs of machines. With the government’s focus on installing and developing new and better renewable sources of energy, it is also necessary to maintain the existing hydropower projects in order to get efficient power from them. Growth of 2.3% annually between the years 1990 to 2017 indicates the importance of hydropower amongst all other energy sources. Thus, this research aims to assess the performance of Indira Sagar Project (ISP) which is an existing hydropower plant during different years of its working and to forecast the power which may get produced, for known values of inputs like discharge provided to the turbines and previous values of output i.e. power generated, using transfer function modelling. The results of this study indicate that the performance of ISP was found to be worst during the financial year 2013-14 where the performance coefficient was -0.0007 and it is inferred that maintenance of the machines was required during that period. This study will help in assessing the performance and scheduling the maintenance of different units. With, the R2 value 0.997 and Chi2 0.02013 the transfer function model developed to forecast the power, suggests that the model fits well and can be used to forecast the hydropower at ISP.