Software vulnerabilities,when actively exploited by malicious parties,can lead to catastrophic consequences.Proper handling of software vulnerabilities is essential in the industrial context,particularly when the soft...Software vulnerabilities,when actively exploited by malicious parties,can lead to catastrophic consequences.Proper handling of software vulnerabilities is essential in the industrial context,particularly when the software is deployed in critical infrastructures.Therefore,several industrial standards mandate secure coding guidelines and industrial software developers’training,as software quality is a significant contributor to secure software.CyberSecurity Challenges(CSC)form a method that combines serious game techniques with cybersecurity and secure coding guidelines to raise secure coding awareness of software developers in the industry.These cybersecurity awareness events have been used with success in industrial environments.However,until now,these coached events took place on-site.In the present work,we briefly introduce cybersecurity challenges and propose a novel platform that allows these events to take place online.The introduced cybersecurity awareness platform,which the authors call Sifu,performs automatic assessment of challenges in compliance to secure coding guidelines,and uses an artificial intelligence method to provide players with solution-guiding hints.Furthermore,due to its characteristics,the Sifu platform allows for remote(online)learning,in times of social distancing.The CyberSecurity Challenges events based on the Sifu platform were evaluated during four online real-life CSC events.We report on three surveys showing that the Sifu platform’s CSC events are adequate to raise industry software developers awareness on secure coding.展开更多
Software vulnerabilities,when actively exploited by malicious parties,can lead to catastrophic consequences.Proper handling of software vulnerabilities is essential in the industrial context,particularly when the soft...Software vulnerabilities,when actively exploited by malicious parties,can lead to catastrophic consequences.Proper handling of software vulnerabilities is essential in the industrial context,particularly when the software is deployed in critical infrastructures.Therefore,several industrial standards mandate secure coding guidelines and industrial software developers’training,as software quality is a significant contributor to secure software.CyberSecurity Challenges(CSC)form a method that combines serious game techniques with cybersecurity and secure coding guidelines to raise secure coding awareness of software developers in the industry.These cybersecurity awareness events have been used with success in industrial environments.However,until now,these coached events took place on-site.In the present work,we briefly introduce cybersecurity challenges and propose a novel platform that allows these events to take place online.The introduced cybersecurity awareness platform,which the authors call Sifu,performs automatic assessment of challenges in compliance to secure coding guidelines,and uses an artificial intelligence method to provide players with solution-guiding hints.Furthermore,due to its characteristics,the Sifu platform allows for remote(online)learning,in times of social distancing.The CyberSecurity Challenges events based on the Sifu platform were evaluated during four online real-life CSC events.We report on three surveys showing that the Sifu platform’s CSC events are adequate to raise industry software developers awareness on secure coding.展开更多
Boron neutron capture therapy (BNCT) is based on the incorporation of boron-containing drugs to cancer cells and the nuclear reaction of 10B atoms by thermal neutron irradiation results in tumor degeneration. For the ...Boron neutron capture therapy (BNCT) is based on the incorporation of boron-containing drugs to cancer cells and the nuclear reaction of 10B atoms by thermal neutron irradiation results in tumor degeneration. For the development of this therapy, currently, long time and high cost consuming experiments using many animals are required. In this study, we constructed a new in vitro evaluation system for BNCT by combination of an artificial tumor tissue model, comprised of normal human dermal-derived fibroblast (NHDF) and human pancreatic cancer cell line BxPC3, and the optical plastic material CR-39 as a solid state nuclear track detector. Administration of boronophenylalanine (10BPA) as a boron-containing drug and neutron irradiation up to 2.52 × 1012 n/cm2 to the control tissue constructed by NHDF (NHDF3D) and BxPC3 cell loaded tissue (NHDF3D/BxPC3) resulted in detection of 1.6 times higher number of α-ray/recoiled Li particle tracks in NHDF3D/BxPC3 in comparison to NHDF3D, demonstrating that putative irradiation damage to cancer cells can be evaluated by this system. On a cellular level, the hit number of α-ray/recoiled Li particle tracks per single BxPC3 cells and NHDF was evaluated as 5.46 and 1.71, respectively. The tumor and normal tissue ratio (T/N ratio) was 3.19, which was corresponded with those of BPA as 2 - 4 that reported in the previous studies. This new in vitro evaluation system may provide a useful tool for a low cost, labor-saving, and non-animal method for the development of new boron-containing drugs or improvement of BNCT conditions.展开更多
In this paper, artificial neural networks are used for predicting single fiber efficiency in the process of removing smaller particles from gas stream by fiber filters. For this, numerical simulations are obtained of ...In this paper, artificial neural networks are used for predicting single fiber efficiency in the process of removing smaller particles from gas stream by fiber filters. For this, numerical simulations are obtained of a classic model of literature for fiber efficiency, which is numerically solved along with the convection diffusion equation in polar coordinates for particle concentration, with associated initial and boundary conditions. A sufficient number of examples from two numerical simulations are employed to construct a database, from which parameters of a novel neural model are adjusted. This model is constructed based on the back propagation algorithm in order to map two features, namely Peclet number and packing density, which are extracted from the numerical simulations into the corresponding single fiber efficiency. The results indicate that the developed neural model can be trained in a reasonable computational time and is capable of estimating single fiber efficiency from examples of the test set with a maximum error of 1.7%.展开更多
One of the important matters that must be determined in advance when performing BNCT treatment is the optimization of neutron irradiation time and dose. In this article, following the previous article (2.52 × 101...One of the important matters that must be determined in advance when performing BNCT treatment is the optimization of neutron irradiation time and dose. In this article, following the previous article (2.52 × 1012 n/cm2) (Case 1), double irradiation (5.04 × 1012 n/cm2) was further performed (Case 2) by verifying the radiation sensitivity performance of the artificial tumor tissue NHDF3D/BxPC3 and the possibility of evaluating the optimum neutron dose required for treatment was examined. As a result, although the radiation damage rate in the normal tissue NHDF3D and the tumor tissue BxPC3 increased in proportion to the irradiation dose due to heavy irradiation in Case 1 or more, the increase in the damage rate in the normal tissue exceeded the tumor tissue. Furthermore, the tumor/normal tissue damage ratio T/N ratio showed the maximum value in Case 1, and the dose ratio in Case 2 with a higher dose showed a tendency to decrease. From the above experimental facts, it was shown that irradiation dose optimization is possible to some extent by an evaluation method using an artificial tumor tissue.展开更多
文摘Software vulnerabilities,when actively exploited by malicious parties,can lead to catastrophic consequences.Proper handling of software vulnerabilities is essential in the industrial context,particularly when the software is deployed in critical infrastructures.Therefore,several industrial standards mandate secure coding guidelines and industrial software developers’training,as software quality is a significant contributor to secure software.CyberSecurity Challenges(CSC)form a method that combines serious game techniques with cybersecurity and secure coding guidelines to raise secure coding awareness of software developers in the industry.These cybersecurity awareness events have been used with success in industrial environments.However,until now,these coached events took place on-site.In the present work,we briefly introduce cybersecurity challenges and propose a novel platform that allows these events to take place online.The introduced cybersecurity awareness platform,which the authors call Sifu,performs automatic assessment of challenges in compliance to secure coding guidelines,and uses an artificial intelligence method to provide players with solution-guiding hints.Furthermore,due to its characteristics,the Sifu platform allows for remote(online)learning,in times of social distancing.The CyberSecurity Challenges events based on the Sifu platform were evaluated during four online real-life CSC events.We report on three surveys showing that the Sifu platform’s CSC events are adequate to raise industry software developers awareness on secure coding.
文摘Software vulnerabilities,when actively exploited by malicious parties,can lead to catastrophic consequences.Proper handling of software vulnerabilities is essential in the industrial context,particularly when the software is deployed in critical infrastructures.Therefore,several industrial standards mandate secure coding guidelines and industrial software developers’training,as software quality is a significant contributor to secure software.CyberSecurity Challenges(CSC)form a method that combines serious game techniques with cybersecurity and secure coding guidelines to raise secure coding awareness of software developers in the industry.These cybersecurity awareness events have been used with success in industrial environments.However,until now,these coached events took place on-site.In the present work,we briefly introduce cybersecurity challenges and propose a novel platform that allows these events to take place online.The introduced cybersecurity awareness platform,which the authors call Sifu,performs automatic assessment of challenges in compliance to secure coding guidelines,and uses an artificial intelligence method to provide players with solution-guiding hints.Furthermore,due to its characteristics,the Sifu platform allows for remote(online)learning,in times of social distancing.The CyberSecurity Challenges events based on the Sifu platform were evaluated during four online real-life CSC events.We report on three surveys showing that the Sifu platform’s CSC events are adequate to raise industry software developers awareness on secure coding.
文摘Boron neutron capture therapy (BNCT) is based on the incorporation of boron-containing drugs to cancer cells and the nuclear reaction of 10B atoms by thermal neutron irradiation results in tumor degeneration. For the development of this therapy, currently, long time and high cost consuming experiments using many animals are required. In this study, we constructed a new in vitro evaluation system for BNCT by combination of an artificial tumor tissue model, comprised of normal human dermal-derived fibroblast (NHDF) and human pancreatic cancer cell line BxPC3, and the optical plastic material CR-39 as a solid state nuclear track detector. Administration of boronophenylalanine (10BPA) as a boron-containing drug and neutron irradiation up to 2.52 × 1012 n/cm2 to the control tissue constructed by NHDF (NHDF3D) and BxPC3 cell loaded tissue (NHDF3D/BxPC3) resulted in detection of 1.6 times higher number of α-ray/recoiled Li particle tracks in NHDF3D/BxPC3 in comparison to NHDF3D, demonstrating that putative irradiation damage to cancer cells can be evaluated by this system. On a cellular level, the hit number of α-ray/recoiled Li particle tracks per single BxPC3 cells and NHDF was evaluated as 5.46 and 1.71, respectively. The tumor and normal tissue ratio (T/N ratio) was 3.19, which was corresponded with those of BPA as 2 - 4 that reported in the previous studies. This new in vitro evaluation system may provide a useful tool for a low cost, labor-saving, and non-animal method for the development of new boron-containing drugs or improvement of BNCT conditions.
文摘In this paper, artificial neural networks are used for predicting single fiber efficiency in the process of removing smaller particles from gas stream by fiber filters. For this, numerical simulations are obtained of a classic model of literature for fiber efficiency, which is numerically solved along with the convection diffusion equation in polar coordinates for particle concentration, with associated initial and boundary conditions. A sufficient number of examples from two numerical simulations are employed to construct a database, from which parameters of a novel neural model are adjusted. This model is constructed based on the back propagation algorithm in order to map two features, namely Peclet number and packing density, which are extracted from the numerical simulations into the corresponding single fiber efficiency. The results indicate that the developed neural model can be trained in a reasonable computational time and is capable of estimating single fiber efficiency from examples of the test set with a maximum error of 1.7%.
文摘One of the important matters that must be determined in advance when performing BNCT treatment is the optimization of neutron irradiation time and dose. In this article, following the previous article (2.52 × 1012 n/cm2) (Case 1), double irradiation (5.04 × 1012 n/cm2) was further performed (Case 2) by verifying the radiation sensitivity performance of the artificial tumor tissue NHDF3D/BxPC3 and the possibility of evaluating the optimum neutron dose required for treatment was examined. As a result, although the radiation damage rate in the normal tissue NHDF3D and the tumor tissue BxPC3 increased in proportion to the irradiation dose due to heavy irradiation in Case 1 or more, the increase in the damage rate in the normal tissue exceeded the tumor tissue. Furthermore, the tumor/normal tissue damage ratio T/N ratio showed the maximum value in Case 1, and the dose ratio in Case 2 with a higher dose showed a tendency to decrease. From the above experimental facts, it was shown that irradiation dose optimization is possible to some extent by an evaluation method using an artificial tumor tissue.
