Process In Many Fields Research Articles

Reproducibility and explainability in digital pathology: The need to make black-box artificial intelligence systems more transparent

Artificial intelligence (AI), and more specifically Machine Learning (ML) and Deep learning (DL), has permeated the digital pathology field in recent years, with many algorithms successfully applied as new advanced tools to analyze pathological tissues. The introduction of high-resolution scanners in histopathology services has represented a real revolution for pathologists, allowing the analysis of digital whole-slide images (WSI) on a screen without a microscope at hand. However, it means a transition from microscope to algorithms in the absence of specific training for most pathologists involved in clinical practice. The WSI approach represents a major transformation, even from a computational point of view. The multiple ML and DL tools specifically developed for WSI analysis may enhance the diagnostic process in many fields of human pathology. AI-driven models allow the achievement of more consistent results, providing valid support for detecting, from H&E-stained sections, multiple biomarkers, including microsatellite instability, that are missed by expert pathologists.

Modeling bacterial adhesion on the nanopatterned surface by varying contact area

Bacterial adhesion is a critical process in many fields, such as implant infections, microbiologically influenced corrosion and bioelectricity generation in microbial fuel cells. During bacterial adhesion, the contact area between the attached bacteria and the patterned surface plays an important role. In this study, different surface topographies and treatments were employed to simulate three circumstances with different contact areas. A nanostripe structure with a period of 576.9 nm and a height of 203.5 nm was fabricated on pure titanium by femtosecond laser ablation. Bacteria in liquid attached to the peaks of the nanostripe structure and were stretched on the two adjacent nanostripes. Compared with the polished surface, the contact area between bacteria and the nanostripe surface was reduced to 50 %, resulting in a reduction (about 50 %) in the coverage rate of attached bacteria. In addition, the nanostripe surface was a hydrophobic surface with a water contact angle (WCA) of 112.1°, and the surface potential of the nanostripe surface was higher than that of the polished surface. However, the surface potential and wettability of the nanostripe surface played a minor role in the bacterial adhesion due to the reduced contact area. Upon drying, the attached bacteria on the nanostripe surface sank into the valley region and the contact area was about 40 % larger than that on the polished surface. The lateral strength of bacterial adhesion on nanostripe surfaces was higher than that on polished surfaces, due to the larger contact area. Upon applying a lateral force of 10.0 nN, the percentage of bacteria remaining on the nanostripe surface (31.1 %) was higher than that on the polished surface (11.9 %). Hence, the bacterial adhesion on the nanopatterned surface was mainly determined by the contact area. The in-depth exploration of the relation between bacterial adhesion on the nanopatterned surface and the contact area enables the rational surface designs of biomaterials to regulate bacterial adhesion.

Regulating evaporation of a water nanofilm by applying a terahertz alternating electric field.

The evaporation of water nanofilms on a solid surface is a widespread and important process in many fields. Herein, we utilize molecular dynamics simulations to demonstrate that the evaporation of a water nanofilm is regulated by applying an alternating electric field (AEF). An AEF at a specific frequency can be resonantly absorbed by the water film. Consequently, the AEF with sufficient strength significantly increases the evaporation rate of the water film (R). In contrast, an AEF of a different frequency and polarization direction decreases R sharply, which is closely related to the strengthened hydrogen bond network and the reduced kinetic energy of the outermost water of the water film. When the maximum amplitude of the AEFs is 0.9 V/nm, which is achievable in a laboratory setting, R spans six orders of magnitude. The effects of applying the AEFs are quite distinct from those of changing the temperature. Notably, the polarization direction of the AEF plays an important role in the water evaporation. To the best of our knowledge, this is the first report on regulating the evaporation rate of a water film, showing that it is possible to use AEFs to tune the properties of nanoscaled water, such as the wettability.

Big data analytics in Cloud computing: an overview

Big Data and Cloud Computing as two mainstream technologies, are at the center of concern in the IT field. Every day a huge amount of data is produced from different sources. This data is so big in size that traditional processing tools are unable to deal with them. Besides being big, this data moves fast and has a lot of variety. Big Data is a concept that deals with storing, processing and analyzing large amounts of data. Cloud computing on the other hand is about offering the infrastructure to enable such processes in a cost-effective and efficient manner. Many sectors, including among others businesses (small or large), healthcare, education, etc. are trying to leverage the power of Big Data. In healthcare, for example, Big Data is being used to reduce costs of treatment, predict outbreaks of pandemics, prevent diseases etc. This paper, presents an overview of Big Data Analytics as a crucial process in many fields and sectors. We start by a brief introduction to the concept of Big Data, the amount of data that is generated on a daily bases, features and characteristics of Big Data. We then delve into Big Data Analytics were we discuss issues such as analytics cycle, analytics benefits and the movement from ETL to ELT paradigm as a result of Big Data analytics in Cloud. As a case study we analyze Google’s BigQuery which is a fully-managed, serverless data warehouse that enables scalable analysis over petabytes of data. As a Platform as a Service (PaaS) supports querying using ANSI SQL. We use the tool to perform different experiments such as average read, average compute, average write, on different sizes of datasets.

Quantum Chemical Calculation of Excited-State Properties of Porphyrin-Fullerene Linked Systems

Electron transfer (ET) is a fundamental process in many fields. Especially, photoinduced ET is crucial for natural and artificial photosynthesis because long-lived charge separation (CS) states are needed for the high efficiency of the chemical reaction and light-to-electricity conversion. To investigate the photoinduced ET properties accurately, the donor-acceptor linked systems have gathered more attention. Porphyrin-fullerene linked systems, such as ZnP-xyn-C60 (n=1-5), are often experimentally investigated because of their excellent ET properties. In the ZnP-xyn-C60 systems, zinc porphyrin, as an electron donor, and fullerene, as an electron acceptor, are connected with one or more oligo-p-xylene groups, as a linked moiety. Because the linked moiety is a rectilinear rigid bridge, the systems exhibit a length-independent electronic structure for local excited states of porphyrin and fullerene. Therefore, these systems are suitable for evaluating distance-dependent CS properties. The photorelaxation pathways of ZnP-xyn-C60 in benzonitrile (PhCN) solution were characterized by the time-resolved transient absorption (TRTA) spectroscopy. The final CS efficiency is changed by the length of the linked moiety and has a maximum value at n=2. The reason is not well known, and for a detailed analysis of the photoinduced ET process, it is necessary first of all to understand the excited-state properties. However, it is difficult to quantitatively evaluate these excited states, especially the CS states, with theoretical methods. The relaxations of both system structure and solvation shell can greatly affect the stability of the CS state, and thus a proper treatment is required. The purpose of this study is to examine the excited-state properties of donor-acceptor linked molecules, ZnP-xy2-C60, with the largest final CS efficiency in PhCN solution. To reduce the computational cost, long side chains of porphyrin are replaced with smaller ones. We perform the time-dependent density functional theory (TDDFT) calculation at LC-ωHPBE and ωB97XD/6-31G(d) level. We apply the Tamm-Dancoff approximation to avoid negative excitation energies in triplet states. For the solvent effect, we first employ the linear response SMD polarizable continuum model, in which solvation is in equilibrium to the ground-state solute electronic structure, and the solvation effect at the excited state is taken into account within the linear response theory. It is found that ωB97XD is more suitable for the evaluations of local excited states. However, the calculated CS-state energies are much higher than the local excited states, even if the relaxations of both system structure and solvation are considered, indicating that the linear response solvation model is insufficient. In addition, we apply , in which solvation response to the excited-state solute electronic structure is partly included. Nevertheless, the results are only slightly improved. Therefore, it is considered that a more sophisticated method which treats solvent molecules explicitly, such as the QM/MM method, is essential for the proper description of CS states. Further analyses are presented in the poster session.

The Catalogue for Astrophysical Turbulence Simulations (CATS)

Abstract Turbulence is a key process in many fields of astrophysics. Advances in numerical simulations of fluids over the last several decades have revolutionized our understanding of turbulence and related processes such as star formation and cosmic ray propagation. However, data from numerical simulations of astrophysical turbulence are often not made public. We introduce a new simulation-oriented database for the astronomical community: the Catalogue for Astrophysical Turbulence Simulations (CATS), located at www.mhdturbulence.com. CATS includes magnetohydrodynamic (MHD) turbulent box simulation data products generated by the public codes athena++, arepo, enzo, and flash. CATS also includes several synthetic observational data sets, such as turbulent HI data cubes. We also include measured power spectra and three-point correlation functions from some of these data. We discuss the importance of open-source statistical and visualization tools for the analysis of turbulence simulations such as those found in CATS.

Speckle noise reduction and image segmentation based on a modified mean filter

Image segmentation is an essential process in many fields involving digital images. In general, segmentation is the process of dividing the image into objects and background image. Image segmentation is an important step in the object detection process. It becomes more critical if a given image is corrupted by noise. Most digital images are corrupted by noises such as salt and pepper noise, Gaussian noise, Poisson noise, speckle noise, etc. Speckle noise is a multiplicative noise that affects pixels in a gray-scale image, and mainly occurs in low level luminance images such as Synthetic Aperture Radar (SAR) images and Magnetic Resonance Image (MRI) images. Image enhancement is an essential task to reduce specklenoise prior to performing further image processing such as object detection, image segmentation, edge detection, etc. Here, we propose a neighborhood-based algorithm to reduce speckle noise in gray-scale images. The main aim of the noise reduction technique is to segment the noisy image. So that the proposed algorithm applies some luminance to the original image. The proposed technique performs well at maximum noise variance. Finally, the segmentation process is done by the modified mean filter. The proposed technique has three phases. In phase 1, the speckle noise is reduced and the contrast adjustment is made. In phase 2, the segmentation of the enhanced image is processed. Finally, in phase 3, the isolated pixels in the segmented image are eliminated and the final segmented image is generated. This technique does not require any threshold value to segment the image; it will be automatically calculated based on the mean value.

Azopolymer-Based Nanoimprint Lithography: Recent Developments in Methodology and Applications.

Nanofabrication on soft polymeric surfaces is an essential process in many fields, for example, chip manufacturing, microfluidics, high efficiency solar cells, and anticounterfeiting. In order to achieve these applications, various nanofabrication methods have been explored. Among them, nanoimprint lithography (NIL) has drawn worldwide attention because of its cheap and fast processability. In this minireview, an overview of azopolymer-based NIL is provided. Since their discovery, azopolymers have demonstrated versatile photoresponsive characteristics due to their unique physical and chemical properties that originate from the photoisomerization of azobenzene chromophores. As such, two aspects are reported in this minireview. On the one hand, various azopolymers showing photofluidization and photoswitchable glass transition temperatures have been developed, thus facilitating methodological advancements in NIL. On the other hand, these on-demand NIL methods provide greater opportunities for azopolymer-based applications, such as templating of optics, directional photo-manipulation of nanopatterns, and micro photo-actuators. Also the challenges are discussed that remain in this field.

Research on cutting characteristics of fiber bundle with high-speed photography

Cutting is an essential and complicated process in many fields. Efficient and low-consumption cutting operations are of great significance for environmental protection and energy conservation. The development of high performance cutting parts relies on a deep understanding of the cutting process and cutting mechanism. In this research, a new type of cutting test bench with high-speed photography was developed, and the cutting tests were conducted on the jute fiber bundle from quasi-static cutting at 10 mm/s to dynamic cutting in the speed range of 0.6-2.4 m/s. The cutting process was captured by a high-speed camera. Analysis shows that compression exists before quasi-static cutting, and the compression force curve with respect to the compression ratio follows an exponential function. The cutting speed has a significant effect on cutting energy. The cutting energy consumption is not a monotonous function of cutting speed owing to the combined effect of elastic deformation and friction of fibers. The cutting energy increases with increasing cutting speed in the range of 0.6-1.2 m/s due to the increase of the friction within fibers and the friction between the blade and fibers. The cutting energy decreases with increasing cutting speed in the range of 1.2-1.8 m/s, and tends to be a fixed value when the cutting speed exceeds 1.8 m/s due to the stabilized elastic deformation and friction coefficient. From the perspective of energy saving, it is meaningless to increase the blade speed excessively when cutting fiber bundles. Keywords: jute fiber, cutting, high-speed photography, energy consumption, friction DOI: 10.25165/j.ijabe.20201303.5677 Citation: He Z T, Ding H L, Du S M, Li Z, Ji J T, Li J, et al. Research on cutting characteristics of fiber bundle with high-speed photography. Int J Agric & Biol Eng, 2020; 13(3): 94–99.

Research on cutting characteristics of fiber bundle with high-speed photography

Cutting is an essential and complicated process in many fields. Efficient and low-consumption cutting operations are of great significance for environmental protection and energy conservation. The development of high performance cutting parts relies on a deep understanding of the cutting process and cutting mechanism. In this research, a new type of cutting test bench with high-speed photography was developed, and the cutting tests were conducted on the jute fiber bundle from quasi-static cutting at 10 mm/s to dynamic cutting in the speed range of 0.6-2.4 m/s. The cutting process was captured by a high-speed camera. Analysis shows that compression exists before quasi-static cutting, and the compression force curve with respect to the compression ratio follows an exponential function. The cutting speed has a significant effect on cutting energy. The cutting energy consumption is not a monotonous function of cutting speed owing to the combined effect of elastic deformation and friction of fibers. The cutting energy increases with increasing cutting speed in the range of 0.6-1.2 m/s due to the increase of the friction within fibers and the friction between the blade and fibers. The cutting energy decreases with increasing cutting speed in the range of 1.2-1.8 m/s, and tends to be a fixed value when the cutting speed exceeds 1.8 m/s due to the stabilized elastic deformation and friction coefficient. From the perspective of energy saving, it is meaningless to increase the blade speed excessively when cutting fiber bundles. Keywords: jute fiber, cutting, high-speed photography, energy consumption, friction DOI: 10.25165/j.ijabe.20201303.5677 Citation: He Z T, Ding H L, Du S M, Li Z, Ji J T, Li J, et al. Research on cutting characteristics of fiber bundle with high-speed photography. Int J Agric & Biol Eng, 2020; 13(3): 94–99.

A model of solute diffusion in unsaturated double-porosity medium by homogenization

Solute diffusion is a key process in many fields like for example material science or environmental engineering. Diffusion mechanism in porous media is often described by Fick’s law. However, we could not use this law for nonstandard diffusion behaviors occurring in cases of heterogeneous media. The conception of double-porosity medium can be applied to a class of such media. The double-porosity medium is characterized by two distinct pore sizes: macro-porosity domain and micro-porosity domain, respectively, having the contrasted hydraulic properties. This paper presents the development of a macroscopic model for the solute diffusion in unsaturated double-porosity medium, by using homogenization method. The obtained macroscopic model is a system of two equations coupling on the interface of the macro- and micro-porosity domain for diffusion. This model contains the effective diffusion tensor representing for the entire medium. The developed model is verified by comparing with the reference solution of the fine scale model through a 3D numerical example of hydrogeology problem.

The Role of Heat Transfer Limitations in Polymer Pyrolysis at the Microscale

Thermal degradation of synthetic and natural polymers is an important process in many fields of engineering such as fire safety, thermal recycling, and biomass power generation. The kinetics of thermal degradation is usually studied by thermogravimetric analysis (TGA), which is based on measuring the mass loss rate of a microscale sample and the temperature of the surrounding fluid during controlled heating. The literature is rich in TGA measurements, which are commonly assumed to be governed solely by kinetics. Heat and mass transfer effects, however, can occur when the sample is insufficiently small in size. Only a few studies quantify a threshold for this maximum size. These thresholds vary due to different input parameters and formulations of the used model. Here, we aim to systematically analyse the role of heat transfer in TGA experiments, quantify the uncertainty of current models, and provide a novel threshold for maximum sample size. We focused on the natural polymer cellulose, a surrogate for biomass, and split the problem into heat transfer within the sample (intraparticle) and between the sample and the fluid (interparticle). Using dimensional analysis we derived two upper bound thresholds for the initial sample mass as a function of heating rate above these thresholds heat transfer effects are significant. One threshold is calculated based on interparticle heat transfer and depends on flow conditions, material and fluid properties. The other is calculated based on intraparticle heat transfer and only depends on material properties. Both thresholds were validated with experiments and previous studies from the literature. Comparing both thresholds shows that the maximum sample mass in a TGA is always limited by interparticle heat transfer. These results enable the selection of appropriate samples masses and heating condition in TGA experiments, which in turn will lead to a better understanding of the pyrolysis chemistry of polymers.

From computer edit geometric design education to virtual worlds: Advantages and pitfalls of Computer‐Based Education

AbstractNowadays, computers are an integral part of the education process in many fields and levels. Although numerous research has been done on Computer‐Based Education (CBE), there are still open questions that have to be answered. Authors have faced some of those important questions over the years while developing the teaching applications from various areas. In this paper, those questions are presented, while the authors' approaches and obtained results offer some answers to those questions. The paper identifies the areas where special attention is needed in order to preserve the effectiveness of the applications in the teaching process. Practical examples of their work are used to demonstrate how the integration level of computers in the teaching process and teaching goals, along with other factors, can affect the effectiveness of teaching applications. With the comparison of the findings with other authors, some crude guidelines are given on how to achieve the best teaching results.

The mechanism of the oxidation of light oil

ABSTRACTHigh pressure air injection (HPAI) has been proven as an enhanced oil recovery process in many fields. The reactions associated with crude oil and oxygen are the main difference between HPAI and other gas injection processes. In order to study the reaction schemes, different experiments, such as the combustion tube, kinetic cell, accelerating rate calorimeter, and thermogravimetry analysis, are conducted. In this paper, a reaction scheme is build that includes three classes of reactions: low-temperature oxidation, cracking, and combustion. We then use simulation models with the proposed reaction scheme included to history match the data from a combustion tube experiment and a kinetic cell experiment. It is demonstrated that the reaction scheme is valid. Based on this study, lumping the crude oil into four pseudocomponents brings a good matching result, and the kinetic parameters are obtained through matching the experimental results.

Precise and Accurate Measurements of Strong-Field Photoionization and a Transferable Laser Intensity Calibration Standard.

Ionization of atoms and molecules in strong laser fields is a fundamental process in many fields of research, especially in the emerging field of attosecond science. So far, demonstrably accurate data have only been acquired for atomic hydrogen (H), a species that is accessible to few investigators. Here, we present measurements of the ionization yield for argon, krypton, and xenon with percent-level accuracy, calibrated using H, in a laser regime widely used in attosecond science. We derive a transferable calibration standard for laser peak intensity, accurate to 1.3%, that is based on a simple reference curve. In addition, our measurements provide a much needed benchmark for testing models of ionization in noble-gas atoms, such as the widely employed single-active electron approximation.

Quantum enhanced phase retrieval

The retrieval of phases from intensity measurements is a key process in many fields in science, from optical microscopy to x-ray crystallography. Here we study phase retrieval of a one-dimensional multi-phase object that is illuminated by quantum states of light. We generalize the iterative Gerchberg-Saxton algorithm to photon correlation measurements on the output plane, rather than the standard intensity measurements. We report a numerical comparison of classical and quantum phase retrieval of a small one-dimensional object of discrete phases from its far-field diffraction. While the classical algorithm was ambiguous and often converged to wrong solutions, quantum light produced a unique reconstruction with smaller errors and faster convergence. We attribute these improvements to a larger Hilbert space that constrains the algorithm.

Is a three-dimensional-printed tooth filling possible?

Introduction: Three-dimensional (3-D) printing is seen as an innovative production process in many fields of dentistry and medicine. But implantation of this novel production process into the treatment of decayed teeth in dentistry remains lacking. Destruction of dental tissues as a result of dental caries is generally treated with dental resin composite fillings. However, a 3-D-printed tooth filling approach, which could be an alternative to traditional approaches, has a potential to reduce treatment costs and technique-sensitivity of the placement of restorative material. The Hypothesis: Here, the hypothesis that a 3-D-printed tooth filling approach could be an alternative to traditional approaches to treatment of decayed teeth is proposed. Evaluation of the Hypothesis: The actual implementation of the 3-D-printed tooth filling technique in the practice of restorative dentistry was discussed in this manuscript.

Stereo kamera sisteminde aykırılık haritaları yardımıyla nesne uzaklıklarının tespit edilmesi

In this study, it is intended to detect various objects’ depths consequently distances from parallel camera plane with stereo camera system. In the established test setup, there are two fixed cameras for capturing left and right image and a computer for processing the images. After cameras were placed fixedly, they were calibrated with chessboard. Subsequently calibration; the intrinsic parameters, essential and fundamental matrices, rotation and translation matrices between left and right cameras were occurred. Then rectification process performed to the images which captured from left and right cameras. Accordingly, depth map and knowledge of distance has been obtained. It is possible to use the depth knowledge process in many fields involved robot and vehicle distance detect systems to handicapped distance determination.

A microfluidic toolbox for cell fusion

AbstractCellular fusion is a key process in many fields ranging from historical gene mapping studies and monoclonal antibody production, through to cell reprogramming. Traditional methodologies for cell fusion rely on the random pairing of different cell types and generally result in low and variable fusion efficiencies. These approaches become particularly limiting where substantial numbers of bespoke one‐to‐one fusions are required, for example, for in‐depth studies of nuclear reprogramming mechanisms. In recent years, microfluidic technologies have proven valuable in creating platforms where the manipulation of single cells is highly efficient, rapid and controllable. These technologies also allow the integration of different experimental steps and characterisation processes into a single platform. Although the application of microfluidic methodologies to cell fusion studies is promising, current technologies that rely on static trapping are limited both in terms of the overall number of fused cells produced and their experimental accessibility. Here we review some of the most exciting breakthroughs in core microfluidic technologies that will allow the creation of integrated platforms for controlled cell fusion at high throughput. © 2015 Society of Chemical Industry

Ice Nucleation Properties of Oxidized Carbon Nanomaterials.

Heterogeneous ice nucleation is an important process in many fields, particularly atmospheric science, but is still poorly understood. All known inorganic ice nucleating particles are relatively large in size and tend to be hydrophilic. Hence it is not obvious that carbon nanomaterials should nucleate ice. However, in this paper we show that four different readily water-dispersible carbon nanomaterials are capable of nucleating ice. The tested materials were carboxylated graphene nanoflakes, graphene oxide, oxidized single walled carbon nanotubes and oxidized multiwalled carbon nanotubes. The carboxylated graphene nanoflakes have a diameter of ∼30 nm and are among the smallest entities observed so far to nucleate ice. Overall, carbon nanotubes were found to nucleate ice more efficiently than flat graphene species, and less oxidized materials nucleated ice more efficiently than more oxidized species. These well-defined carbon nanomaterials may pave the way to bridging the gap between experimental and computational studies of ice nucleation.