Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection and Molecular Characterization of Circulating Tumour Cells: Challenges for the Clinical Setting

Simple Summary Liquid biopsy provides important information through the analysis of circulating tumour cells (CTCs) and circulating tumour-derived material, such as circulating tumour DNA (ctDNA), circulating miRNAs (cfmiRNAs) and extracellular vehicles (EVs). CTC analysis has already had an important impact on the prognosis, detection of minimal residual disease (MRD), treatment selection and monitoring of cancer patients. The purpose of this review is to summarize the latest findings on the clinical significance of CTCs for the management of breast, prostate and non-small-cell lung cancer patients. Abstract Over the last decade, liquid biopsy has gained much attention as a powerful tool in personalized medicine since it enables monitoring cancer evolution and follow-up of cancer patients in real time. Through minimally invasive procedures, liquid biopsy provides important information through the analysis of circulating tumour cells (CTCs) and circulating tumour-derived material, such as circulating tumour DNA (ctDNA), circulating miRNAs (cfmiRNAs) and extracellular vehicles (EVs). CTC analysis has already had an important impact on the prognosis, detection of minimal residual disease (MRD), treatment selection and monitoring of cancer patients. Numerous clinical trials nowadays include a liquid biopsy arm. CTC analysis is now an exponentially expanding field in almost all types of solid cancers. Functional studies, mainly based on CTC-derived cell-lines and CTC-derived explants (CDx), provide important insights into the metastatic process. The purpose of this review is to summarize the latest findings on the clinical significance of CTCs for the management of cancer patients, covering the last four years. This review focuses on providing a comprehensive overview of CTC analysis in breast, prostate and non-small-cell lung cancer. The unique potential of CTC single-cell analysis for understanding metastasis biology, and the importance of quality control and standardization of methodologies used in this field, is also discussed.
On The Comparison of Two Methods of Analyzing Panel Data Using Simulated Data

The study focus on the use of simulated panel data to compare the performance of two methods of analyzing such data. Features of the ordinary least squares model that uses pooled data and fixed effects of the least square dummy variable (LSDV) model were discussed. The samples of size 60 and 100 were generated and replicated five and ten periods respectively. Several statistics (R2, Standard error, t and f distributions) were used in comparing the result of the estimates obtained from the two methods applied to two sample sizes.The comparison of the results showed that the analysis based on the bigger sample is more consistent and efficient than the one based on the smaller sample size and this made the least square dummy variables to be more superior than the pooled data model. The conclusion is that the fixed effects model (LSDV) is superior and better in the analysis of panel data.The study focus on the use of simulated panel data to compare the performance of two methods of analyzing such data. Features of the ordinary least squares model that uses pooled data and fixed effects of the least square dummy variable (LSDV) model were discussed. The samples of size 60 and 100 were generated and replicated five and ten periods respectively. Several statistics (R2, Standard error, t and f distributions) were used in comparing the result of the estimates obtained from the two methods applied to two sample sizes.The comparison of the results showed that the analysis based on the bigger sample is more consistent and efficient than the one based on the smaller sample size and this made the least square dummy variables to be more superior than the pooled data model. The conclusion is that the fixed effects model (LSDV) is superior and better in the analysis of panel data.
A study on vortex shedding from spheres in a uniform flow.

Vortex shedding from spheres at Reynolds numbers from 3×102 to 6×104 in a uniform flow was experimentally investigated. Standard hot-wire techniques were used to measure the vortex shedding frequency form spheres in a low-speed wind tunnel. Flow-visualization experiments were carried out in a water channel. Important findings resulting from the investigation were that (i) the variation of the Strouhal number St (=fD/U0, U0 : free-stream velocity, D : diameter of sphere, f : vortex shedding frequency) with the Reynolds number Re (=U0D/ν, ν : kinematic viscosity) can be classified into four regions, (ii) the critical Reynolds number at which the horseshoe-shaped vortex loops are shed periodically is about 300, (iii) the vortex loops diffuse very rapidly and the wake structure of the sphere is not shown clearly when a Reynolds number of about 800 is reached, and (iv) at Reynolds numbers ranging from 8×102 to 1.5×104, the higher and lower frequency modes of the Strouhal number which are caused by the periodic fluctuation in the vortex sheet separating from the surface of the sphere and in a wake with progressive wave motion are coexisted.
A Multivariate Model for Multinomial Choices

__Abstract__ Multinomial choices of individuals are likely to be correlated. Nonetheless, econometric models for this phenomenon are scarce. A problem of multivariate multinomial choice models is that the number of potential outcomes can become very large which makes parameter interpretation and inference difficult. We propose a novel Multivariate Multinomial Logit specification, where (i) the number of parameters stays limited; (ii) there is a clear interpretation of the parameters in terms of odds ratios; (iii) zero restrictions on parameters result in independence between the multinomial choices and; (iv) parameter inference is feasible using a composite likelihood approach even if the multivariate dimension is large. Finally, these nice properties are also valid in a fixed-effects panel version of the model.
Polarization behavior of paints doped with silicone light diffusion agent

Abstract. We report on the polarization behavior of painted samples doped with a silicone light diffusion agent and illuminated by linearly polarized laser light centered at 532 and 650 nm. Reflection spectra of the painted samples with dopant concentration of 0 and 12.2 wt. % were examined. The degree of depolarization increases from 0.35 to 0.8 under laser illumination at 650 nm and from 0.5 to 0.94 under laser illumination at 532 nm with an increasing concentration of light diffusion agent. The polarization behavior of painted samples was described, taking into account contribution of both surface scattering and volume scattering.
EFFECT OF DOSE AND TIME OF POTASSIUM APPLICATION ON YIELD AND QUALITY OF BABY CORN

A field experiment was conducted to study the effect of dose and time of K application on yield and quality of baby corn. Two doses of K viz., 40 and 50 kg ha −1 were tried in three split doses Le. basal, 15 DAS and 30 DAS. The yield and yield components were significantly improved by the application of 50 kg K ha −1 applied in three splits, as basal, 15 DAS and 30 DAS. The nutrient uptake and crude protein content were also improved significantly
Capital structure and stock price of non-financial firms listed in Viet Nam

The aim of our paper is to consider the non-linear effect of the capital structure represented by debt ratio on stock prices of non-financial firms listed in Vietnam. The research sample in this paper is 458 firms, which was selected by the purposive sampling method. The research data has been extracted from audited financial statements of the firms at the end of every year over the period from 2015 to 2019 and processed correspondingly with stock price statistics from FiinPro Data. According to the panel data of our paper, we used Pooled Ordinary Least Squares (POLS), Fixed Effects Model (FEM) and Random Effects Model (REM), but we only selected FEM after using Redundant Fixed Effects test, Breusch-Pagan test and Hausman test. However, the Wald test’s result showed that the heteroscedasticity does exist in the model; therefore, we adjusted by using Generalized Least Squares (GLS) method. The final estimation results based on GLS show that capital structure has a positive effect on stock price within a limit of debt ratio and will have a negative effect when this limit has been exceeded. This implies that capital structure has an inverted-U-shaped effect on stock price, and we identify the debt ratio threshold of capital structure of 22.07%. The findings are expected to provide useful information for financial managers when making financing decisions with the expectation of maximizing shareholder value and also for investors when analyzing and investing in stocks. The limitations of this research are that the research sample does not include all non-financial firms listed in Vietnam and the research model has not considered the moderating or intervening relationship between factors; according to that, future studies may consider these.
Designing for Modern Learning: Beyond ADDIE and SAM, Association for Talent Development, June 30th 2020, Lisa M.D. Owens, Crystal Kadakia

The book of Lisa M.D. Owens and Crystal Kadakia is addressing a critical topic of learning and development (L&D) activities mostly as performed in business areas but also with parts applicable in learning in general. The authors are describing both details of the evolution of L&D and, also, they make a proposal for a model of work in adapting to new and rapidly changing needs of learners.
Automated animation pipeline for visualizing in silico tumor growth models

While there is increased interest in medical and scientific computational modeling tools for generating in silico medical datasets, tools for visualizing the volumetric data present with hurdles for those without previous experience in graphics rendering. We describe an open-source automatedworkflowto visualize volumetric computational medical imaging datasets with a focus on cancer lesion growth models. Simulated raw data for the growth of a tumor were generated at 50 time points using a previously described growth algorithm that considers the surrounding anatomy to affect tumor morphology. The voxelized models were converted to the VDB volume format for rendering using an automated Python script within the software Houdini. The visualization of volume data allows for detailed inspection and improved understanding of the spatial configuration of the tumor and surrounding anatomy affecting the growth.
An Overview of the Agricultural Development in Tamil Nadu From 2010 to 2021, Focusing on the Area and Production of Major Crops

In the process of economic development in less developed countries like India, agriculture is crucial. In addition to producing food for the country, agriculture also employs people, saves money, boosts the market for industrial goods, and generates foreign exchange. Insome ways, the green revolution helped alleviate the early 1960s food crisis, but it also increased regional inequities in resource use, productivity, and cropping patterns. Promoting certain cash crop sat higher prices causes shortages in other crops. Farm income and livelihoods are becoming more and more vulnerable as environmental, economic, and technological variables change. The purpose of the current research was to assess Tamil Nadu's agricultural production and are a under cultivation from 2010 to 2021. Agriculture is the primary source of food and means of subsistence for the vast majority of people in the world, according to the 2011 census. Increasing revenue prospects in the agricultural sector is a key strategy for reducing poverty because the majority of the population relies on it. Examining the area under cultivation and the production of important crops in TamilNadu is main of the study's objectives. From this data, conclusions regarding the elements that have increased output or improved resource usage may be drawn. How well a system will function across places with similar topography or crop production is another question that needs to be addressed. The article's content is urgently required, socially relevant, and current based on the aforementioned criteria. As a consequence, the article's main focus is on the area and crop production of TamilNadu's major crops from2010 to 2021 as well as their economic implications on the agriculture sector.
PET image reconstruction with parallax correction based on a distance-driven deep neural network

Positron emission tomography (PET) is a widely used molecular imaging technology. However, the inability of conventional PET systems without depth of interaction (DOI) information to precisely locate gamma rays leads to parallax error, which further results in the non-uniform resolution in reconstructed images. The existing methods enable PET systems to acquire DOI information by adding more hardwares, which are generally at the cost of higher prices and degradation of other performances. To overcome these shortcomings, we proposed a novel distance-driven cascade framework containing a bi-directional long short-term memory (Bi-LSTM) module and an encoder-decoder module. Especially, the distance-driven preprocessing was realized by splitting the sinogram into one-dimensional vectors according to radial distance and inputting them sequentially. In this approach, the bins in the same sinogram row had related features,thus were processed at the same time. Furthermore, sinogram rows used the mutual implicit information extracted by Bi-LSTM to achieve better transformation before processed by the encoder-decoder module. To test the proposed method, we conducted the network training and testing on a dataset simulated using the open-source Geant4 toolkit GATE. Compared to the DeepPET, which is a typical PET reconstruction method based on deep learning, our method acquired an obvious promotion in structural similarity (SSIM) and peak signal-to-noise ratio (PSNR) on the test dataset. It proves that our method is superior in perceptual performance and efficiency.
Electrospun Nanofiber Membrane: An Efficient and Environmentally Friendly Material for the Removal of Metals and Dyes

With the rapid development of nanotechnology, electrospun nanofiber membranes (ENM) application and preparation methods have attracted attention. With many advantages such as high specific surface area, obvious interconnected structure, and high porosity, ENM has been widely used in many fields, especially in water treatment, with more advantages. ENM solves the shortcomings of traditional means, such as low efficiency, high energy consumption, and difficulty in recycling, and it is suitable for recycling and treatment of industrial wastewater. This review begins with a description of electrospinning technology, describing the structure, preparation methods, and factors of common ENMs. At the same time, the removal of heavy metal ions and dyes by ENMs is introduced. The mechanism of ENM adsorption on heavy metal ions and dyes is chelation or electrostatic attraction, which has excellent adsorption and filtration ability for heavy metal ions and dyes, and the adsorption capacity of ENMs for heavy metal ions and dyes can be improved by increasing the metal chelation sites. Therefore, this technology and mechanism can be exploited to develop new, better, and more effective separation methods for the removal of harmful pollutants to cope with the gradually increasing water scarcity and pollution. Finally, it is hoped that this review will provide some guidance and direction for research on wastewater treatment and industrial production.
Stability phenomena far beyond the Nusselt flow – Revealed by experimental asymptotics

The present article contributes detailed experimental results on the linear stability of gravity-driven viscous films flowing down periodically corrugated inclines. We asymptotically left the well-known Nusselt flow by gradually increasing the topography’s amplitude. Systematic variations of the channel’s inclination and the fluid’s viscosity followed. That way, we revealed non-trivial stability charts and phenomena far beyond the limits of the Nusselt regime. For the sake of understanding these phenomena, we thoroughly measured the steady-state free surfaces and velocity fields of the respective flows. This comprehensive approach provided us with the exceptional opportunity to unveil that the complex shape, which stability charts of film flows over strongly corrugated inclines exhibit, can be attributed to the simultaneous presence of stabilizing as well as destabilizing effects provoked by the topography. We proved that the stabilization of the flow due to an increased film thickness and the destabiliza.
From resin formulation and process parameters to the final mechanical properties of 3D printed acrylate materials

Photopolymerizable resins are increasingly used to generate complex 3D printed parts through stereo lithography, digital light processing (DLP) and liquid crystal display (LCD) 3D printing. Many challenges relating to the resin chemistry and printing parameters still exist and must be addressed in order to entirely control the properties of parts after printing. This work reviews the current knowledge and describes the potential of DLP/LCD methods for printed acrylate resins, as well as the steps necessary to achieve a better control over the mechanical properties of printed materials. Graphical abstract
Heterojunction Effect on Spectral and Frequency Responses in InP/InGaAsP/InGaAs APD

Influence of the valence band discontinuity on the spectral and frequency responses in InP/InGaAsP/InGaAs APDs has been reported. Quantum efficiency showed gradual increases in the wavelength range from 1.0 to 1.3 µm, where the absorption coefficients decrease with increasing wavelength. Frequency response deteriorations, which cannot be explained by usual deterioration mechanisms, were found at around 300 MHz. These two characteristics are due to holes piled up at the heterointerface which was confirmed experimentally. Recombination and thermionic emission of piled up holes cause the deterioration of quantum efficiency and frequency response, respectively. High speed APDs are realized by increasing the electric field of the heterointerface in InP/InGaAsP/InGaAs APDs.
Exploiting Task Tolerances in Mimicry-Based Telemanipulation

We explore task tolerances, i.e., allowable position or rotation inaccuracy, as an important resource to facilitate smooth and effective telemanipulation. Task tolerances provide a robot flexibility to generate smooth and feasible motions; however, in teleoperation, this flexibility may make the user's control less direct. In this work, we implemented a telema-nipulation system that allows a robot to autonomously adjust its configuration within task tolerances. We conducted a user study comparing a telemanipulation paradigm that exploits task tolerances (functional mimicry) to a paradigm that requires the robot to exactly mimic its human operator (exact mimicry), and assess how the choice in paradigm shapes user experience and task performance. Our results show that autonomous adjustments within task tolerances can lead to performance improvements without sacrificing perceived control of the robot. Additionally, we find that users perceive the robot to be more under control, predictable, fluent, and trustworthy in functional mimicry than in exact mimicry.
Hybrid Differential Dynamic Programming with Stochastic Search

Differential dynamic programming (DDP) has been demonstrated as a viable approach to low-thrust trajectory optimization, namely with the recent success of NASA's Dawn mission. The Dawn trajectory was designed with the DDP-based Static/Dynamic Optimal Control algorithm used in the Mystic software.1 Another recently developed method, Hybrid Differential Dynamic Programming (HDDP),2, 3 is a variant of the standard DDP formulation that leverages both first-order and second-order state transition matrices in addition to nonlinear programming (NLP) techniques. Areas of improvement over standard DDP include constraint handling, convergence properties, continuous dynamics, and multi-phase capability. DDP is a gradient based method and will converge to a solution nearby an initial guess. In this study, monotonic basin hopping (MBH) is employed as a stochastic search method to overcome this limitation, by augmenting the HDDP algorithm for a wider search of the solution space.
Degree of a Vertex

A graph G consists of two sets: a set of vertices V and a set of edges E. A vertex is simply a labeled point. An edge is a connection between two vertices. For example, suppose we have vertex set V = {a, b, c, d} and edge set E = {(a, b), (a, c), (a, d), (c, d)}. The coordinate notation (a, b) means an edge connecting vertex a and vertex b. In this way, we can see a visual representation of the corresponding graphG with 4 vertices and 4 edges below:
Locality, Latency and Spatial-Aware Data Placement Strategies at the Edge

The vast data deluge at the network's edge is raising multiple challenges for the edge computing community. One of them is identifying edge storage servers where data from edge devices/sensors have to be stored to ensure low latency access services to emerging edge applications. Existing data placement algorithms mainly focus on locality, latency, and zoning to select edge storage servers under multiple environmental constraints. This paper uses a data placement framework to compare distance-based, latency-based, and spatial-awareness-based data placement strategies, which all share a decision-making system with similar constraints. Based on simulation experiments, we observed that the spatial-awareness-based strategy could provide a quality of service on par with the latency-based and better than the distance-based strategy.
Temporalizing digraphs via linear-size balanced bi-trees

In a directed graph $D$ on vertex set $v_1,\dots ,v_n$, a \emph{forward arc} is an arc $v_iv_j$ where $i<j$. A pair $v_i,v_j$ is \emph{forward connected} if there is a directed path from $v_i$ to $v_j$ consisting of forward arcs. In the {\tt Forward Connected Pairs Problem} ({\tt FCPP}), the input is a strongly connected digraph $D$, and the output is the maximum number of forward connected pairs in some vertex enumeration of $D$. We show that {\tt FCPP} is in APX, as one can efficiently enumerate the vertices of $D$ in order to achieve a quadratic number of forward connected pairs. For this, we construct a linear size balanced bi-tree $T$ (an out-tree and an in-tree with same size which roots are identified). The existence of such a $T$ was left as an open problem motivated by the study of temporal paths in temporal networks. More precisely, $T$ can be constructed in quadratic time (in the number of vertices) and has size at least $n/3$. The algorithm involves a particular depth-first search tree (Left-DFS) of independent interest, and shows that every strongly connected directed graph has a balanced separator which is a circuit. Remarkably, in the request version {\tt RFCPP} of {\tt FCPP}, where the input is a strong digraph $D$ and a set of requests $R$ consisting of pairs $\{x_i,y_i\}$, there is no constant $c>0$ such that one can always find an enumeration realizing $c. |R|$ forward connected pairs $\{x_i,y_i\}$ (in either direction).