Automatic Data Augmentation Learning using Bilevel Optimization for Histopathological Images

Training a deep learning model to classify histopathological images is challenging, because of the color and shape variability of the cells and tissues, and the reduced amount of available data, which does not allow proper learning of those variations. Variations can come from the image acquisition process, for example, due to different cell staining protocols or tissue deformation. To tackle this challenge, Data Augmentation (DA) can be used during training to generate additional samples by applying transformations to existing ones, to help the model become invariant to those color and shape transformations. The problem with DA is that it is not only dataset-specific but it also requires domain knowledge, which is not always available. Without this knowledge, selecting the right transformations can only be done using heuristics or through a computationally demanding search. To address this, we propose an automatic DA learning method. In this method, the DA parameters, i.e. the transformation parameters needed to improve the model training, are considered learnable and are learned automatically using a bilevel optimization approach in a quick and efficient way using truncated backpropagation. We validated the method on six different datasets. Experimental results show that our model can learn color and affine transformations that are more helpful to train an image classifier than predefined DA transformations, which are also more expensive as they need to be selected before the training by grid search on a validation set. We also show that similarly to a model trained with RandAugment, our model has also only a few method-specific hyperparameters to tune but is performing better. This makes our model a good solution for learning the best DA parameters, especially in the context of histopathological images, where defining potentially useful transformation heuristically is not trivial.Comment: arXiv admin note: text overlap with arXiv:2006.1469

Analytical Study Of The Impact Of Syrian Imports On The National Economy During The Period (1995-2017)

This research deals with the impact of the qualitative structure of imports on the economic growth in Syria during the period (1995-2017). Its role as one of the important factors affecting the economic growth rate in Syria during the period     (1995-2017), thus trying to achieve the greatest possible benefit from imports in securing the needs and requirements of economic development and reconstruction. One of the most significant results reached is that Syrian imports of raw materials and intermediate goods ranked the most important imports in GDP before the war on Syria, while imports of manufactured materials and intermediate goods were the most influential in GDP during the war on Syria. تناولت هذه الدراسة أثر الهيكل النوعي للواردات في النمو الاقتصادي في سورية خلال الفترة (1995-2017), وذلك بالاعتماد على الناتج المحلي الإجمالي كمؤشر لقياس النمو الاقتصادي, وهدفت إلى تسليط الضوء على واقع الواردات السورية وتحليل هيكليتها قبل وخلال فترة الحرب على سورية, وإبراز دورها كأحد العوامل الهامة والمؤثرة في معدل النمو الاقتصادي في سورية خلال الفترة (1995-2017), وبالتالي محاولة تحقيق أكبر استفادة ممكنة من الواردات في تأمين احتياجات ومتطلبات عمليات التنمية الاقتصادية وإعادة الإعمار. ومن أبرز النتائج التي تم الوصول إليها أنّ الواردات السورية من المواد الخام ومن السلع الوسيطة احتلتا مرتبة الواردات الأكثر تأثيراً في الناتج المحلي الإجمالي قبل الحرب على سورية, في حين كانت الواردات من المواد المصنّعة والسلع الوسيطة هي الأكثر تأثيراً في الناتج المحلي الإجمالي خلال فترة الحرب على سورية

One pot preparation of CeO2@Alginate composite beads for the catalytic reduction of MB dye: Effect of cerium percentage

This study focuses on the preparation of composite beads CeO2@Alginate using a one-pot method. Ce(III) was used as a crosslinking agent and then was modified with a base to transform it into CeO2 encapsulated in the alginate matrix. To study the catalytic behavior of this material the reduction of MB dye in the presence of NaBH4 was selected as a model reaction. Several parameters affecting the reduction of the MB dye were studied such as the effect of cerium content in the composite beads, the concentration of NaBH4 and the concentration of the MB dye. The results showed that the dispersion of alginate in a solution containing Ce(III) leads to the formation of hydrogel beads. The treatment of the beads with a basic solution leads to the in-situ formation of CeO2 inside the beads with a porous structure. The catalytic activity of composite beads has shown interesting results via the reduction of MB dye. The reduction of MB dye catalyzed by CeO2@ALG(2%) was total in 2 min and the associated rate constant was 2.3 min–1. The reuse tests were studied during five successive cycles, in which it was shown that the CeO2@ALG(2%) catalyst was stable without losing its effectiveness

Catalytic behavior and antibacterial/antifungal activities of new MNPs/zeolite@alginate composite beads

In this paper, a new family of composite materials was prepared based on calcium alginate and metal nanoparticle-loaded zeolite omega. Different types of metal nanoparticles (NPs), namely Cu, Co and Fe, were loaded onto zeolite omega to test the performance of the resulting metal/zeolite@alginate composites towards the catalytic reduction of methylene blue dye. To examine their application field as broadly as possible, these composite beads were also tested as antibacterial and antifungal agents against several types of bacteria. Several techniques such as XRD, XRF, FTIR, XPS, SEM and TGA were used to characterize the samples. The obtained results showed that all the composite bead samples were effective in the reduction of MB dye. The composite Co/Zeolite@ALG with relatively low Co nanoparticle (NP) content was selected as the best performing catalyst due to its reduction of MB dye being completely achieved in 3 min with a rate constant of 0.02 min-1, which was attributed to its highly porous structure. The reuse tests conducted on the best-performing catalyst showed good results which persisted through five successive cycles. For antibacterial and antifungal activities, the Cu/Zeolite@ALG and Fe/Zeolite@ALG composites showed good activity with significant inhibition zones

SYNTHESIS AND CHARACTERIZATION OF CdS IN DIOL VANILIN LIQUID CRYSTAL MONOMER

Nanocomposites comprising diol-vanilin and cadmium sulfide (CdS) has been synthesized via chemical precipitation method in ethanol at refluxed temperature (160 oC) for 12 hours. CdCl2. 2.5H2O and thiourea as cadmium and sulfide precursors respectively were employed. Diol vanilin is a thermotropic liquid crystal monomer which exhibits enantiotropic nematic metaphase texture when observed under polarizing microscope and confirmed by DSC thermal stability study. A series of different mass composition  of diol vanilin and CdS nanocomposites ranging from  0.1:1.0 till 1.0:1.0(w/w) were prepared and characterized using XRD, TEM, SEM-EDX, POM and DSC. The X-ray diffraction pattern (XRD) showed broad peaks due to the formation of cubic CdS nanoparticles in diol vanilin matrix. The nanocomposites at low mass composition  of CdS still maintained their nematic phase. However, the liquid crystal property was affected when the mass  composition  of CdS in nanocomposite was increased and the liquid crystal characteristic vanished when the mass composition  was at 0.6:1.0. .    Keywords: CdS, diol vanilin, thermotropic liquid crystal, nanocomposite

Synthesis and application of metal nanoparticles-loaded mesoporous silica toward the reduction of organic pollutants in a simple and binary system

In this work, mesoporous silica MCM-41 was prepared by hydrothermal route, and the obtained as-synthesized material (CTA-MCM-41) was modified by two different methods using silver and cerium assisted by thermal treatment. The modified materials were characterized by XRD, FTIR, XRF, XPS, nitrogen sorption measurements at −196 °C, SEM, and TEM analyses. The modified materials were tested as catalysts in a simple and binary system via the reduction reaction of Methylene Blue (MB), Congo Red (CR), 4-Nitrophenol (4-NP), Methyl Orange (MO), Orange G (OG) in the presence of NaBH4. The effect of the nanoparticles size, their dispersions, the nature of the organic pollutant, the initial concentration of the organic pollutant, and the concentration of the reducing agent NaBH4 have been studied and discussed. The obtained results confirmed that the preparation method plays an important role in the content and nature of nanoparticles, their sizes, their dispersions, and also on their catalytic performance. The Ag-Ce-MCM-2 material was selected as the best catalyst due to the synergistic effect between AgNPs and CeO2. The rate constant calculated in the simple system for the different pollutants was as follows: 0.1829 s−1, 0.1762 s−1, 0.0606 s−1, 0.0585 s−1, 0.0556 s−1 for MO, OG, MB, 4-NP, CR, respectively. The reduction in a binary system containing CR and MB or MO and MB was in competition, in which the CR or MO degrades together with the MB dye. Whereas for the other binary systems containing 4-NP/MB or OG/MB, the catalyst Ag-Ce-MCM-2 was more selective towards the MB dye. This catalyst demonstrated efficiency and reusability across different cycles, in which the conversion of the MB dye was complete in each reuse

Determinants of information security awareness and behaviour strategies in public sector organizations among employees

In this digital era, protecting an organisation's sensitive information system assets against cyberattacks is challenging. Globally, organisations spend heavily on information security (InfoSec) technological countermeasures. Public and private sectors often fail to secure their information assets because they depend primarily on technical solutions. Human components create the bulk of cybersecurity incidents directly or indirectly, causing many organisational information security breaches. Employees' information security awareness (ISA) is crucial to preventing poor information security behaviours. Until recently, there was little combined information on how to improve ISA and how investigated factors influencing employees' ISA levels were. This paper proposed a comprehensive theoretical model based on the Protection Motivation Theory, the Theory of Planned Behaviour, the General Deterrence Theory, and Facilitating Conditions for assessing public sector employees' ISA intentions for information security behaviour. Using a survey and the structural equation modelling (SEM) method, this research reveals that the utilised factors are positively associated with actual information security behaviour adoption, except for perceived sanction certainty. The findings suggest that the three theories and facilitating conditions provide the most influential theoretical framework for explaining public sector employees' information security adoption behaviour. These findings support previous empirical research on why employees' information on security behaviours vary. Consistent with earlier research, these psychological factors are just as critical as facilitating conditions in ensuring more significant behavioural intention to engage in ISA activities, ensuring information security behaviour. The study recommends that public-sector organisations invest in their employees' applied information security training

Catalytic Reduction of Dyes and Antibacterial Activity of AgNPs@Zn@Alginate Composite Aerogel Beads

This work focuses on the preparation of aerogel composite beads based on Zn(II)-crosslinked alginate and loaded with different percentages of AgNPs using a simple approach. The obtained samples were evaluated in two different applications: the first application consists in their use as catalysts for the reduction of MB, MO, OG and CR dyes in a simple and binary system under the presence of NaBH4. For this, several parameters affecting the catalytic behavior of these catalysts have been investigated and discussed such as the catalyst mass, AgNPs content, dye nature, and the selectivity of the catalyst in a binary system. The second application concerns their antibacterial activities towards two Gram-negative bacteria Escherichia coli (ATCC 25922), and Pseudomonas aeruginosa (ATCC 27853), and a Gram-positive bacteria Staphylococcus aureus (ATCC 25923). The physico-chemical properties of different samples were characterized by XRD, FTIR, SEM/EDS, and TGA analysis. The obtained results confirmed the presence of AgNPs on a highly porous alginate structure. The dispersion of a high percentage of AgNPs leads to the formation of nanoparticles on the outer surface of the alginate which led to their leaching after the catalytic test, while the composite having a low percentage of AgNPs showed good results through all dyes without leaching of AgNPs. For the antibacterial application of the different samples, it was shown that a composite with a higher percentage of AgNPs was the most effective against all bacteria