Sedimentation of Harbors and Counter-Measures in the Greek and Roman Era

Artificial Intelligence (AI) has emerged as a breakthrough technology which is astonishingly impressive. Major world powers are rapidly integrating AI in their military doctrines. This trend of militarization of AI can be seen in the South Asian region as well. Following the theoretical approach of offensive realism, China and India are in full swing to revolutionize their militaries with this emerging trend in order to accumulate maximum power and to satisfy their various interests. Consequently, Indian military modernization has the potential to provoke Pakistan to take counter measures. Pakistan is already encountering a number of challenges in economic sector and will face the strenuous task of accommodating a handsome financial share for the development of its AI capabilities. South Asia is a very turbulent region characterized by arch rivals who are also nuclear powers and have repeatedly indulged in various crises over the years. Introduction of AI in South Asia will have significant repercussions as it will trigger an arms race and at the same time disturb the strategic balance in the region.

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Security of Blockchain-Based Supply Chain Management Systems: Challenges and Opportunities

Applied Sciences ◽

10.3390/app11125585 ◽

2021 ◽

Vol 11 (12) ◽

pp. 5585

Author(s):

Sana Al-Farsi ◽

Muhammad Mazhar Rathore ◽

Spiros Bakiras

Keyword(s):

Supply Chain ◽

Supply Chain Management ◽

Information Exchange ◽

Cyber Attacks ◽

Management Systems ◽

Chain Management ◽

Counter Measures ◽

Starting Point ◽

Challenges And Opportunities ◽

Unique Approach

Blockchain is a revolutionary technology that is being used in many applications, including supply chain management. Although, the primary motive of using a blockchain for supply chain management is to reduce the overall production cost while providing the comprehensive security to the system. However, current blockchain-based supply-chain management (BC-SCM) systems still hold the possibility of cyber attacks. Therefore, the goal of this study is to investigate practical threats and vulnerabilities in the design of BC-SCM systems. As a starting point, we first establish key requirements for the reliability and security of supply chain management systems, i.e., transparency, privacy and traceability, and then discern a threat model that includes two distinctive but practical threats including computational (i.e., the ones that threaten the functionality of the application) and communication (i.e., the ones that threaten information exchange among interconnected services of the application). For investigation, we follow a unique approach based on the hypothesis that reliability is pre-requisite of security and identify the threats considering (i) design of smart contracts and associated supply chain management applications, (ii) underlying blockchain execution environment and (iii) trust between all interconnected supply management services. Moreover, we consider both academic and industry solutions to identify the threats. We identify several challenges that hinder to establish reliability and security of the BC-SCM systems. Importantly, we also highlight research gaps that can help to establish desired security of the BC-SCM. To the best of our knowledge, this paper is the first effort that identifies practical threats to blockchain-based supply chain management systems and provides their counter measures. Finally, this work establishes foundation for future investigation towards practical security of BC-SCM system.

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WBAN for e-Healthcare Application: Systematic Review, Challenges, and Counter Measures

2021 International Conference on Computer Communication and Informatics (ICCCI) ◽

10.1109/iccci50826.2021.9402276 ◽

2021 ◽

Author(s):

U. Hariharan ◽

K. Rajkumar ◽

A. Ponmalar

Keyword(s):

Systematic Review ◽

Counter Measures ◽

Healthcare Application

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Amantadine Inhibits SARS-CoV-2 In Vitro

Viruses ◽

10.3390/v13040539 ◽

2021 ◽

Vol 13 (4) ◽

pp. 539

Author(s):

Klaus Fink ◽

Andreas Nitsche ◽

Markus Neumann ◽

Marica Grossegesse ◽

Karl-Heinz Eisele ◽

...

Keyword(s):

Influenza A ◽

Antiviral Agents ◽

Antiviral Drug ◽

Systemic Exposure ◽

Topical Administration ◽

Counter Measures ◽

Travel Restrictions ◽

Drug Treatments ◽

Intranasal Instillation

Since the SARS-CoV-2 pandemic started in late 2019, the search for protective vaccines and for drug treatments has become mandatory to fight the global health emergency. Travel restrictions, social distancing, and face masks are suitable counter measures, but may not bring the pandemic under control because people will inadvertently or at a certain degree of restriction severity or duration become incompliant with the regulations. Even if vaccines are approved, the need for antiviral agents against SARS-CoV-2 will persist. However, unequivocal evidence for efficacy against SARS-CoV-2 has not been demonstrated for any of the repurposed antiviral drugs so far. Amantadine was approved as an antiviral drug against influenza A, and antiviral activity against SARS-CoV-2 has been reasoned by analogy but without data. We tested the efficacy of amantadine in vitro in Vero E6 cells infected with SARS-CoV-2. Indeed, amantadine inhibited SARS-CoV-2 replication in two separate experiments with IC50 concentrations between 83 and 119 µM. Although these IC50 concentrations are above therapeutic amantadine levels after systemic administration, topical administration by inhalation or intranasal instillation may result in sufficient amantadine concentration in the airway epithelium without high systemic exposure. However, further studies in other models are needed to prove this hypothesis.

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A performance-based tabular approach for joint systematic improvement of risk control and resilience applied to telecommunication grid, gas network, and ultrasound localization system

Environment Systems & Decisions ◽

10.1007/s10669-021-09811-5 ◽

2021 ◽

Author(s):

Ivo Häring ◽

Mirjam Fehling-Kaschek ◽

Natalie Miller ◽

Katja Faist ◽

Sebastian Ganter ◽

...

Keyword(s):

Indoor Localization ◽

System Development ◽

Management Practice ◽

Risk Control ◽

System Level ◽

Gas Network ◽

Counter Measures ◽

Ultrasound Localization ◽

Systematic Improvement ◽

Resilience Assessment

AbstractOrganizational and technical approaches have proven successful in increasing the performance and preventing risks at socio-technical systems at all scales. Nevertheless, damaging events are often unavoidable due to a wide and dynamic threat landscape and enabled by the increasing complexity of modern systems. For overall performance and risk control at the system level, resilience can be a versatile option, in particular for reducing resources needed for system development, maintenance, reuse, or disposal. This paper presents a framework for a resilience assessment and management process that builds on existing risk management practice before, during, and after potential and real events. It leverages tabular and matrix correlation methods similar as standardized in the field of risk analysis to fulfill the step-wise resilience assessment and management for critical functions of complex systems. We present data needs for the method implementation and output generation, in particular regarding the assessment of threats and the effects of counter measures. Also included is a discussion of how the results contribute to the advancement of functional risk control and resilience enhancement at system level as well as related practical implications for its efficient implementation. The approach is applied in the domains telecommunication, gas networks, and indoor localization systems. Results and implications are further discussed.

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Early Detection of Exposure to Toxic Chemicals Using Continuously Recorded Multi-Sensor Physiology

Sensors ◽

10.3390/s21113616 ◽

2021 ◽

Vol 21 (11) ◽

pp. 3616

Author(s):

Jan Ubbo van Baardewijk ◽

Sarthak Agarwal ◽

Alex S. Cornelissen ◽

Marloes J. A. Joosen ◽

Jiska Kentrop ◽

...

Keyword(s):

Machine Learning ◽

Early Detection ◽

Physiological Signals ◽

Machine Learning Techniques ◽

Detection Accuracy ◽

Chemical Agent ◽

Counter Measures ◽

Detection And Identification ◽

Life Saving ◽

Future Work

Early detection of exposure to a toxic chemical, e.g., in a military context, can be life-saving. We propose to use machine learning techniques and multiple continuously measured physiological signals to detect exposure, and to identify the chemical agent. Such detection and identification could be used to alert individuals to take appropriate medical counter measures in time. As a first step, we evaluated whether exposure to an opioid (fentanyl) or a nerve agent (VX) could be detected in freely moving guinea pigs using features from respiration, electrocardiography (ECG) and electroencephalography (EEG), where machine learning models were trained and tested on different sets (across subject classification). Results showed this to be possible with close to perfect accuracy, where respiratory features were most relevant. Exposure detection accuracy rose steeply to over 95% correct during the first five minutes after exposure. Additional models were trained to correctly classify an exposed state as being induced either by fentanyl or VX. This was possible with an accuracy of almost 95%, where EEG features proved to be most relevant. Exposure detection models that were trained on subsets of animals generalized to subsets of animals that were exposed to other dosages of different chemicals. While future work is required to validate the principle in other species and to assess the robustness of the approach under different, realistic circumstances, our results indicate that utilizing different continuously measured physiological signals for early detection and identification of toxic agents is promising.

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