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We investigate connections between the development of Fintech and the blue economy from September 14th, 2020, to August 11th, 2023.

In this research, we use a cutting-edge model-free connectedness approach to investigate the relationships between FinTech and blue bond volatility. Our work is the first to investigate the effects of unknown events, such as the COVID-19 pandemic and Ukraine–Russia conflicts, on the interconnection of volatility derived from FinTech development and blue bond volatility.

Our results highlight the two-way relationship between the development of Fintech and the blue economy during our sample period. The net total connectedness shows that the blue economy index is a net shock receiver, especially in late 2021 and the second half of 2022, while most of the fintech indexes in our sample are mainly net shock transmitters. The Ukraine–Russia tension threatens the development of a sustainable blue economy. The development of Fintech plays an important role in promoting the blue economy.

Our results have important policy implications for investors and governments, as well as methods from the spillovers across the various indicators and their interconnections. Sharp information on the primary contagions among these indicators aids politicians in designing the most appropriate policies.

Our paper contributes to the literature in at least four ways. First, as previously stated, our article is the first to investigate the relationship between FinTech and blue bond volatility. Second, this study presented a framework for studying volatility interconnections between distinct variables that is more suited to analyzing these interconnections. In this research, we use a cutting-edge model-free connectedness approach to investigate the relationships between FinTech and blue bond volatility. Third, our work is the first to investigate the effects of unknown events such as the COVID-19 pandemic and Ukraine–Russia conflicts on the interconnection of volatility deriving from FinTech development and blue bond volatility. Lastly, our research provides a daily dataset for the BNP Paribas Easy ECPI Global ESG Blue Economy UCITS ETF to analyze 50 businesses from various markets that are at the forefront of the responsible application of ocean resources and other ESG standards. The Global X FinTech ETF (FINX) and the ARK FinTech Innovation ETF (ARKF) seek exposure to companies developing financial technology innovations. The development sectors include insurance, investment, fundraising and third-party lending by utilizing cutting-edge mobile and digital technologies. Our time series runs from September 14th, 2020, to August 11th, 2023. By using this database, we provide a comprehensive analysis of the link between the volatilities arising from various markets.

This paper aims to present the design development and measurement of two aerodynamic slotted X-bands back-to-back planer substrate-integrated rectangular waveguide (SIRWG/SIW) to Microstrip (MS) line transition for satellite and RADAR applications. It facilitates the realization of nonplanar (waveguide-based) circuits into planar form for easy integration with other planar (microstrip) devices, circuits and systems. This paper describes the design of a SIW to microstrip transition. The transition is broadband covering the frequency range of 8–12 GHz. The design and interconnection of microwave components like filters, power dividers, resonators, satellite dishes, sensors, transmitters and transponders are further aided by these transitions. A common planar interconnect is designed with better reflection coefficient/return loss (RL) (S₁₁/S₂₂ ≤ 10 dB), transmission coefficient/insertion loss (IL) (S₁₂/S₂₁: 0–3.0 dB) and ultra-wideband bandwidth on low profile FR-4 substrate for X-band and Ku-band functioning to interconnect modern era MIC/MMIC circuits, components and devices.

Two series of metal via (6 via/row) have been used so that all surface current and electric field vectors are confined within the metallic via-wall in SIW length. Introduced aerodynamic slots in tapered portions achieve excellent impedance matching and tapered junctions with SIW are mitered for fine tuning to achieve minimum reflections and improved transmissions at X-band center frequency.

Using this method, the measured IL and RLs are found in concord with simulated results in full X-band (8.22–12.4 GHz). RLC T-equivalent and p-equivalent electrical circuits of the proposed design are presented at the end.

The measurement of the prototype has been carried out by an available low-cost X-band microwave bench and with a Keysight E4416A power meter in the microwave laboratory.

The transition is fabricated on FR-4 substrate with compact size 14 mm × 21.35 mm × 1.6 mm and hence economical with IL lie within limits 0.6–1 dB and RL is lower than −10 dB in bandwidth 7.05–17.10 GHz. Because of such outstanding fractional bandwidth (FBW: 100.5%), the transition could also be useful for Ku-band with IL close to 1.6 dB.

The final effectiveness of employee voice largely depends on voice endorsement. This study aims to review, assess, analyze and synthesize the emerging literature on voice endorsement by focusing on its antecedents to promote future research from a comprehensive perspective.

Based on an integrative review of the literature, the authors conducted a content analysis of 53 peer-reviewed journal articles.

Building on the Shannon–Weaver communication model, this paper summarizes that factors influencing voice endorsement can be classified into five prominent aspects: voicer, voiced idea, contextual factors and noises, voice channel (medium) and voice receiver.

This research holds important implications for practice, providing practical guidelines for employees to speak up, for leaders to endorse voice and for organizations to maintain sustainable development by making full use of employee voice.

This review enriches voice endorsement research by introducing a communication framework to synthesize its antecedents and extends the application of the communication model in organization research. Additionally, the authors offer directions for future research.

Automatic dependent surveillance-broadcast (ADS-B) is the foundational technology of the next generation air transportation system defined by Federal Aviation Authority and is one of the most precise ways for tracking aircraft position. ADS-B is intended to provide greater situational awareness to the pilots by displaying the traffic information like aircraft ID, altitude, speed and other critical parameters on the Cockpit Display of Traffic Information displays in the cockpit. Unfortunately, due to the initial proposed nature of ADS-B protocol, it is neither encrypted nor has any other innate security mechanisms, which makes it an easy target for malicious attacks. The system is vulnerable to various active and passive attacks like message ingestion, message deletion, eavesdropping, jamming, etc., which has become an area of concern for the aviation industry. The purpose of this study is to propose a method based on modified advanced encryption standard (AES) algorithm to secure the ADS=B messages and increase the integrity of ADS-B data transmissions.

Though there are various cryptographic and non-cryptographic methods proposed to secure ADS-B data transmissions, it is evident that most of these systems have limitations in terms of cost, implementation or feasibility. The new proposed method implements AES encryption techniques on the ADS-B data on the sender side and correlated decryption mechanism at the receiver end. The system is designed based on the flight schedule data available from any flight planning systems and implementing the AES algorithm on the ADS-B data from each aircraft in the flight schedule.

The suitable hardware was developed using Raspberry pi, ESP32 and Ra-02. Several runs were done to verify the original message, transmitted data and received data. During transmission, encryption algorithm was being developed, which has got very high secured transmission, and during the reception, the data was secured. Field test was conducted to validate the transmission and quality. Several trials were done to validate the transmission process. The authors have successfully shown that the ADS-B data can be encrypted using AES algorithm. The authors are successful in transmitting and receiving the ADS-B data packet using the discussed hardware and software methodology. One major advantage of using the proposed solution is that the information received is encrypted, and the receiver ADS-B system can decrypt the messages on the receiving end. This clearly proves that when the data is received by an unknown receiver, the messages cannot be decrypted, as the receiver is not capable of decrypting the AES-authenticated messages transmitted by the authenticated source. Also, AES encryption is highly unlikely to be decrypted if the encryption key and the associated decryption key are not known.

Implementation of the developed solution in actual onboard avionics systems is not within the scope of this research. Hence, assessing in the real-time distances is not covered.

The authors propose to extend this as a software solution to the onboard avionics systems by considering the required architectural changes. This solution can also bring in positive results for unmanned air vehicles in addition to the commercial aircrafts. Enhancement of security to the key operational and navigation data elements is going to be invaluable for future air traffic management and saving lives of people.

The proposed solution has been practically implemented by developing the hardware and software as part of this research. This has been clearly brought out in the paper. The implementation has been tested using the actual ADS-B data/messages received from using the ADS-B receiver. The solution works perfectly, and this brings immense value to the aircraft-to-aircraft and aircraft-to-ground communications, specifically while using ADS-B data for communicating the position information. With the proposed architecture and minor software updates to the onboard avionics, this solution can enhance safety of flights.

This paper aims to examine the specific findings on the level of technical compliance and operational effectiveness of the national financial intelligence units (FIUs) in 55 members of the Asian Development Bank (ADB) under the mutual evaluations carried out by the Financial Action Task Force (FATF) and its regional bodies (also referred to as FATF-style regional bodies) in connection with the current international standard for combating money laundering and terrorism financing (i.e. the FATF recommendations). It also provides three observations for enhancing the use of financial information and intelligence.

Review of published reports on country mutual evaluations from the FATF and its regional bodies.

A majority of the FIUs from these 55 members of the ADB were rated around the “mid-range” under the FATF methodology used for the mutual evaluations (i.e. “compliant and substantially effective”, “largely compliant and substantially effective”, “compliant and moderately effective” and “largely compliant and moderately effective”). Observations were also provided on cross-cutting areas for enhancing the use of financial information and intelligence.

FIU operations are key to combating money laundering and terrorism financing, and this examination of the level of technical compliance with the international standard and related operational effectiveness provides an useful account of current developments in this space and suggestions for further actions by relevant national authorities and provision of country technical assistance and support by donor partners.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

Automatic modulation recognition (AMR) is a challenging problem in intelligent communication systems and has wide application prospects. At present, although many AMR methods based on deep learning have been proposed, the methods proposed by these works cannot be directly applied to the actual wireless communication scenario, because there are usually two kinds of dilemmas when recognizing the real modulated signal, namely, long sequence and noise. This paper aims to effectively process in-phase quadrature (IQ) sequences of very long signals interfered by noise.

This paper proposes a general model for a modulation classifier based on a two-layer nested structure of long short-term memory (LSTM) networks, called a two-layer nested structure (TLN)-LSTM, which exploits the time sensitivity of LSTM and the ability of the nested network structure to extract more features, and can achieve effective processing of ultra-long signal IQ sequences collected from real wireless communication scenarios that are interfered by noise.

Experimental results show that our proposed model has higher recognition accuracy for five types of modulation signals, including amplitude modulation, frequency modulation, gaussian minimum shift keying, quadrature phase shift keying and differential quadrature phase shift keying, collected from real wireless communication scenarios. The overall classification accuracy of the proposed model for these signals can reach 73.11%, compared with 40.84% for the baseline model. Moreover, this model can also achieve high classification performance for analog signals with the same modulation method in the public data set HKDD_AMC36.

At present, although many AMR methods based on deep learning have been proposed, these works are based on the model’s classification results of various modulated signals in the AMR public data set to evaluate the signal recognition performance of the proposed method rather than collecting real modulated signals for identification in actual wireless communication scenarios. The methods proposed in these works cannot be directly applied to actual wireless communication scenarios. Therefore, this paper proposes a new AMR method, dedicated to the effective processing of the collected ultra-long signal IQ sequences that are interfered by noise.

This chapter is born out of concern about the perception of the physical and symbolic place of the live-in housekeeper, both in socioeconomic, and historical terms, as well as the architectural and social dynamics of the home. An intersectional and teleological analysis of the intrinsic devaluation of paid social reproduction work is carried out, based mainly on gender, race, and class inequalities. Ultimately, the chapter tries to locate the position in which the maid finds herself in the domestic environment, both in family relationships and in the symbolism inherent to the concept of the maid’s room. Based on sociological, philosophical, and anthropological analysis, the ambiguous place of domestic workers becomes clearer, promoting a reflection on the very concept of family and household. Thus, the chapter proposes to achieve a hermeneutic dive into the experience of this working class, revealing a hierarchical system beyond the socioeconomic, but above all, of their subjectivities.

The COVID-19 pandemic affected entire humanity, sustainable development and international trade. Even if international trade is in the recovery phase, COVID-19 pandemic's adverse effects on sustainable development and trade continue to be experienced globally. Furthermore, break out of the war in Ukraine (WIU) further affected not only Ukraine and Russia but also other countries. Countries have started to experience adverse impacts of the WIU more deeply as this war continues. From the global sustainable development and trade perspectives, the WIU impacts' magnitude is affected by the significance of Ukraine and Russia's role in and contribution to the global economy and trade (e.g. agriculture, energy). All countries, including developed, developing and under-developed countries, have started to be affected at different levels due to the adverse impacts of this war. Based on an in-depth literature review, this chapter aims to investigate the WIU's impacts on global sustainable development and international trade. Furthermore, effects of the WIU on climate change and on the fight against climate change are investigated within the scope of this chapter. This chapter is expected to be useful to all stakeholders of sustainable development including politicians and researchers.

This study aims to examine how the theory of planned behaviour and technology acceptance theory can be used to understand the adoption of non-pharmaceutical interventions (NPIs). The relationships between attitudes, behavioural intentions towards using NPIs, actual use of NPIs and word-of-mouth (WOM) were examined and compared between early and late adopters.

A survey was conducted to test the hypotheses with partial least squares structural equation modelling (n = 278).

The results indicate that relationships between attitudes, intentions and behavioural intentions were positive and significant in the whole data set – and that there were differences between the early and late adopters. WOM had no substantial relationship with actual usage and early adopters’ behavioural intentions.

This research gives a better sense of how WOM impacts attitudes, behavioural intentions and actual usage among early and late adopters of NPIs and highlights the effectiveness of WOM, especially among late adopters of NPIs. Furthermore, using the TAM allows us to make specific recommendations regarding encouraging the use of NPIs. A new three-stage communications model is introduced that uses early adopters as influencers to reduce the NPI adoption time by late adopters.