Polyanhydrides are considered as important biomaterials for use in drug delivery systems, due to their biodegradability, biocompatibility and appropriate release kinetics of active substances. They can be obtained by melt polycondensation of compounds containing two carboxylic groups, e.g. disuccinate betulin. Disuccinate betulin exhibits biological activity, including anticancer and antiviral one, while being non-toxic to normal cells. Nanoparticles prepared from betulin-based polyanhydrides may have significant application in drug delivery systems. The aim of this study was to obtain polymeric nanoparticles from polyanhydride based on betulin disuccinate and to evaluate the influence of the preparation conditions (homogenization time, type and concentration of surfactant, concentration of the polymer solution) on the shape, morphology and size of the particles. Nanoparticles were obtained by two methods: by nanoprecipitation and by emulsion solvent evaporation (ESE) method. Both methods allow to obtain particles with a diameter of less than 1 µm. ESE method provided regularly spherical particles, while among the particles obtained from the nanoprecipitation method, many irregular ones were observed. In ESE method, the size of the particles depended on the type and concentration of surfactant (in the water phase) and the polymer concentration (in the organic phase). The best results were obtained with ionic surfactants, however, the use of such compounds may accelerate the degradation process of polymers. In nanoprecipitation method, the ratio of solvent (methylene chloride) to non-solvent (hexane) has a significant influence on the particle size. The smallest particles were obtained with a solvent to non-solvent ratio of 1 : 150.

Remote sensing is critical for a wide range of applications, including ocean and wave monitoring, planetary exploration, agriculture, and astronomy. We demonstrated a polariscopy concept which is able to determine orientation of patterns below the optical resolution limit of a system. This technique relies on measuring at least 4 different polarisation angles and calculating the orientation from the set of intensity information. It was initially demonstrated on the infrared microspectroscopy beamline at the Australian Synchrotron using IR light in transmission. Using a Thorlabs CS505MUP monochrome polarising camera, it was shown that it also worked in optical transmission. This camera was mounted onto a drone as a remote sensing platform and orientation information was extracted from reflection images taken at an altitude where conventional imaging could not resolve the test patterns. In the interest of moving towards high-speed data acquisition and processing, two methods for processing the image are compared.

Incoherent holography systems, in general, require complicated optical configurations to generate two mutually coherent object beams and create a stable self-interference hologram [1]. The invention of Fresnel incoherent correlation holography (FINCH) created possibilities to implement incoherent holography methods autonomously and also integrated them into other imaging methods easily [2, 3]. Coded aperture imaging methods (CAI) which were developed in the 20^th century, have been rebooted during the last five years for three-dimensional [4-6] and four-dimensional imaging [7] after the development of novel computational reconstruction methods. In CAI methods, the light from an object is scattered by a coded phase mask, and the scattered intensity distribution is recorded. The object intensity distributions are reconstructed using point spread holograms (PSHs) pre-recorded using a point object at all depths and spectrum using the same scatterer under identical experimental conditions. In FINCH, new imaging characteristics can be introduced by modulating the object wave by the corresponding phase function and interfering it with the unmodulated object wave [8]. This is because, in FINCH, the reconstruction mechanism by computational Fresnel back propagation does not change with respect to the modulating function. Therefore, the relative variations of the new optical fields are manifested during reconstruction. In CAI methods, however, the above approach cannot work as the reconstruction is carried out by cross-correlation with the PSH, which is dependent upon the modulation function. Consequently, the beam characteristics were not manifested during reconstruction [9]. In this study, we have developed a post-processing approach involving synthetic PSHs generated using a new iterative algorithm that can be applied to both FINCH-like as well as CAI methods efficiently. We believe that the proposed computational approach is a valuable tool for introducing unconventional imaging characteristics virtually to imaging systems [10].

References

1. Rosen, J.; Vijayakumar, A.; Kumar, M.; Rai, M.R.; Kelner, R.; Kashter, Y.; Bulbul, A.; Mukherjee, S. Recent advances in self-interference incoherent digital holography. Opt. Photonics2019, 11, 1–66.
2. Rosen, ; Brooker, G. Digital spatially incoherent Fresnel holography. Opt. Lett. 2007, 32, 912–914.
3. Kashter, Y.; Vijayakumar, A.; Rosen, J. Resolving images by blurring: Superresolution method with a scattering mask between the observed objects and the hologram recorder. Optica2017, 4, 932–939.
4. Lee, K.; Park, Y. Exploiting the speckle-correlation scattering matrix for a compact reference-free holographic image sensor. Commun.2016, 7, 13359.
5. Vijayakumar, ; Rosen, J. Interferenceless coded aperture correlation holography—A new technique for recording incoherent digital holograms without two-wave interference. Opt. Express 2017, 25, 13883–13896.
6. Antipa, N.; Kuo, G.; Heckel, R.; Mildenhall, B.; Bostan, E.; Ng, R.; Waller, L. DiffuserCam: Lensless single-exposure 3D imaging. Optica2018, 5, 1–9.
7. Anand, ; Ng, S.H.; Maksimovic, J.; Linklater, D.; Katkus, T.; Ivanova, E.P.; Juodkazis, S. Single shot multispectral multidimensional imaging using chaotic waves. Sci. Rep. 2020, 10, 1–13.
8. Bouchal, ; Bouchal, Z. Selective edge enhancement in three-dimensional vortex imaging with incoherent light. Opt. Lett. 2012, 37, 2949–2951.
9. Anand, ; Katkus, T.; Ng, S.H.; Juodkazis, S. Review of Fresnel incoherent correlation holography with linear and non-linear correlations. Chin. Opt. Lett. 2021, 19, 020501.
10. Anand, V.; Rosen, J.; Ng, S.H.; Katkus, T.; Linklater, D.P.; Ivanova, E.P.; Juodkazis, S. Edge and Contrast Enhancement Using Spatially Incoherent Correlation Holography Techniques. Photonics2021, 8, 224.

Traditional tablets are not an ideal dosage form. Many groups of patients, e.g. pediatric or geriatric, experience problems with swallowing or simply are not willing to take tablets, consequently reducing patient’s compliance. Therefore, to overcome these inconveniences, orally disintegrating tablets (OTDs) were introduced into the drug market. One of the methods of preparing ODTs is a direct compression, which is cost-efficient and simple. However, many factors are affecting the disintegration time of ODTs, which are usually optimized in a laboratory during the try-and-error assays.

We curated and greatly enhanced the database presented by Han et al. [1]. Moreover, we introduced chemical descriptors as active pharmaceutical ingredient (API) characteristics. We used H2O AutoML platform [2, 3] in order to develop a model and SHAP method to explain its predictions [4].

Based on the obtained DeepLearning model with NRMSE of 8.1% and R2 of 0.84, we have identified critical parameters affecting the process of disintegration of directly compressed ODTs.

1. R. Han, Y. Yang, X. Li, D. Ouyang. Predicting oral disintegrating tablet formulations by neural network techniques. Asian J. Pharm. Sci., 134 (2018), pp. 336-342

2. Szlęk J. 2021. h2o_AutoML_Python, Python script for AutoML in h2o. Available online: https://github.com/jszlek/h2o_AutoML_ Python (accessed on 10 April 2021).

3. LeDell, E.; Poirier, S. H2O AutoML: Scalable Automatic Machine Learning. 7th ICML Workshop on Automated Machine Learning. 2020.

4. Lundberg, S. M.; Erion, G.G; Lee S.I. Consistent Individualized Feature Attribution for Tree Ensembles. arXiv preprint arXiv:1802.03888. 2018.

Geopolymerisation is widely used in the construction sector for its characteristics of strong compressive strength, quick hardening, long term durability, fire and erosion resistance. Most studies focused on raw materials fly ash, RHA, and slag to form geopolymer. Meanwhile, Coal Bottom Ash (CBA) is a new waste that can be easily acquired from thermal power plants, alleviating environmental concerns and dumping site shortages. This paper will review the effects of CBA and additives in producing geopolymer. Those additives that are critical based on their engineering properties performance can be specified as CBA only, CBA with fly ash (FA) , CBA with rice husk ash (RHA). By combining RHA and CBA, the material is deemed lightweight, has improved compressive strength in 28 days, and has excellent water absorption. In terms of utilising CBA alone, it was discovered that the presence of CBA in concrete affects the workability of concrete and substantially rises in terms of strength after 14 days of curing. Increases in compressive strength but a lower fly ash to bottom ash ratio resulted in greater drying shrinkage due to the lower degree of geopolymerisation for the fly ash and bottom ash combination. The findings of these researches indicate that coal bottom ash geopolymer has discovered a viable material for replacing the usage of fine and coarse aggregate in the building sector, particularly in mortar and concrete, and that additional research into industrialisation is necessary.

Expansive agents are used to reduce cracking caused by drying shrinkage in concrete structures such as slabs, beams, columns and pavement constructions. It also utilised in specific situations such as water leakage prevention in water retaining structures such as water tank, dam, etc. Although CaO and Sulphoaluminate based expansive cement have been used for decades, MgO-based expansive agents have demonstrated superior performance since 1970, especially for concrete dam structures. While other expansive agents have some disadvantages such as poor thermal stability and uncontrollable hydration pace, MgO-based expansive concrete has mitigated all these limitations while enhancing strength and durability. It has been proven that compensating shrinkage with MgO expansion efficiently prevents thermal cracking of mass concrete, reduces the expense of temperature control systems, and speeds up the construction process. This paper briefly reviews the factors of MgO-based expansive agents that affect the characteristics of expansive concrete. The review indicates several parameters named as reactivity, thickness of water film, curing condition, additive ratio, and calcination condition that affects the expansibility, strength, soundness, durability, flowability, interior pores, crystal size, and hydration activity. Thus, comparative studies show the practicality of its usage while discussing future improvements.

The paper introduces the experimental research results of superplastic forming of AA7075 aluminum alloy sheet. The experimental planning with 3 elements and 3 levels based on the orthogonal matrix 2 has been formulated, giving a second order regression equation describing the relationship between the relative height of the product and the main technological parameters: forming pressure of 0.7-0.9 MPa, deformation temperature of 500-5300C and forming time of 20-40 minutes. The experimental results are consistent with the general trend of the superplastic forming process: the relative height of the product increases with increasing pressure, temperature, and forming time. However, there exist limit values of forming time, where the law of the influence of temperature and forming pressure on relative height is reversed. Therefore, in each specific machining case, it is necessary to select the range of appropriate process parameters to get the desired results.

Surface textures are geometric features that collectively refer to surface roughness and scratches. The surface textures are highly relevant to the geometric specifications such as mechanical properties and appearance of the product. Therefore, the quantitative quality control of the surface texture is necessary. The surface textures are important for bearings are used in automobiles and other products. The material ratio curve of the surface texture is used as an effective evaluation method for the quality control of bearings and other products. The material ratio curve shows the ratio of the material part and the void part of the surface profile in the height direction. The computational algorithms to obtain the material ratio curve have been proposed by the ISO/JIS standard and previous research. The computational algorithm proposed in ISO 13565-2 for calculating material ratio curve is a method of slicing the roughness profile (hereafter referred to as “slice method”). The slice method has problems that the calculating time increases as the slicing number increases. Therefore, in this study, the sort method is proposed as a computational algorithm for time reduction. The sort method is a method to sort data in ascending order. As a result, the sort method was successful in reducing the calculating time on the material ratio curve. However, depending on the form of the surface profile, the computational algorithm of the proposed sort method has a problem that calculation errors occur. Therefore, in this paper, we report a new improved algorithm that solves this problem. This algorithm can contribute to improve the efficiency of quality control through rational analysis and evaluation.

The internal surfaces of automobile engine bores should have strong resistance against friction and wear to reduce environmental impact. Surfaces with smoothed tops of surface irregularities are used to meet this requirement. Such surfaces are known as plateau surfaces because of their plateau-like shape. The roughness parameters obtained by analyzing the surface roughness of the plateau surface can assist in evaluating the frictional state and performance of the plateau surface. In addition, the understanding of the plateau surface conditions can contribute to the realization of fuel efficiency. Currently, plateau surface analysis methods are defined in ISO standards and JIS. However, these methods require complex computational algorithms and a significant amount of analysis time. Therefore, previous studies have proposed several methods using simple computational algorithms to solve this problem. Sakakibara et al., the authors of the previous study, proposed a method based on the concept of RANSAC. This method achieved high analysis accuracy for the plateau surface by setting detailed conditions. However, the optimal conditions are set manually, the productivity is low owing to the manpower and time required. This study proposes a new method that automates the setting of the conditions. This method does not require human intervention and is expected to contribute to the improvement of productivity at production sites.

Images taken by digital cameras include noise. The image quality is reduced with increasing noise. In addition, the image recognition rate decreases with increasing noise. Currently, image recognition is used in security technology through face recognition and in image inspection at production sites. Therefore, the accuracy of image recognition needs to be improved. Reducing noise is essential to improve the accuracy of image recognition. Low-pass filters such as a Gaussian filter (GF), are often used to reduce noise from images. Low-pass filters can reduce noise, however low-pass filters always blur the edges. As the edge blur becomes stronger, the accuracy of edge and feature detection of image recognition worsens. In order to solve this problem, a non-local mean filter (NLMF) was proposed as noise reduction filter for images that can preserve edges in previous research. The NLMF has high denoising performance against weak noise, while low denoising performance against strong noise. Therefore, in this research, we propose a noise reduction filter for images that can preserve edges which combining the GF and L2-norm. The proposed method is expected to simultaneously achieve high denoising and edge preservation performances against weak and strong noise. Therefore, the proposed method is expected to improve the image quality and, consequently, the accuracy of image recognition.