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ZEJQOY : bis(N'-[2,2-dimethyl-1-(oxo)propyl]-N-methyl-N-phenylcarbamimidothioato)-platinum(ii) Title of Journal (Source) The Cambridge Crystallographic Data Centre (CCDC)

(2022-06)

The dataset (Experimental Crystal Structure Determination) is linked to the following study: Three new platinum(II) complexes derived from asymmetrically di-substituted pivaloylthiourea ligands (L1–3) are synthesized and characterized by 1H, and 195Pt{1H} NMR. The ligands and PtL1–3 complexes display configurational E,Z isomerism evinced by distinct sets of 1H, 195Pt{1H} NMR resonances observed in dichloromethane‑d2. Single-crystal X-ray diffraction studies reveal a bidentate cis-PtL1–3 coordination mode, in which two sulfur and oxygen donor atoms bind to Pt(II) forming a six-membered chelate. In addition, the EE isomers were preferentially isolated in acetonitrile for cis-PtL1 and cis-PtL2, while ZZ was obtained for cis-PtL3 with N-phenyl substituent. The relative energies of the cis-ZZ-Pt-L1–3, cis-EZ-Pt-L1–3, cis-EE-Pt-L1–3 configurational isomers are obtained by DFT analysis at the M06-2X/def2-SVP level of theory using an implicit acetonitrile solvent. Moreover, the structural studies indicate a potential intra-electron transfer from dz2 (HOMO) to dx2-y2 (LUMO), with a reduced electron affinity at the LUMO level for the cis-ZZ/ZE/EE-Pt-L1–3 structures. The antioxidant capacity of the L1–3 ligands and cis-PtL1–3 were evaluated using the ORAC, DPPH radical scavenging and FRAP methods. The free L1–3 ligands showed higher antioxidant activities in comparison to their coordinated cis-PtL1–3 complexes.

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An analysis of a cryptocurrency giveaway scam: Use case

(2024-06) Botha, Johannes G; Leenen, L

A giveaway scam is a type of fraud leveraging social media platforms and phishing campaigns. These scams have become increasingly common and are now also prevalent in the crypto community where attackers attempt to gain crypto-enthusiasts’ trust with the promise of high-yield giveaways. Giveaway scams target individuals who lack technical familiarity with the blockchain. They take on various forms, often presenting as genuine cryptocurrency giveaways endorsed by prominent figures or organizations within the blockchain community. Scammers entice victims by promising substantial returns on a nominal investment. Victims are manipulated into sending cryptocurrency under the pretext of paying for "verification" or "processing fees." However, once the funds have been sent, the scammers disappear and leave victims empty-handed. This study employs essential blockchain tools and techniques to explore the mechanics of giveaway scams. A crucial aspect of an investigation is to meticulously trace the movement of funds within the blockchain so that illicit gains resulting from these scams can be tracked. At some point a scammer wants to “cash-out” by transferring the funds to an off-ramp, for example, an exchange. If the investigator can establish a link to such an exchange, the identity of the owner of cryptocurrency address could be revealed. However, in organised scams, criminals make use of mules and do not use their own identities. The authors of this paper select a use case and then illustrate a comprehensive approach to investigate the selected scam. This paper contributes to the understanding and mitigation of giveaway scams in the cryptocurrency realm. By leveraging the mechanics of blockchain technology, dissecting scammer tactics, and utilizing investigative techniques and tools, the paper aims to contribute to the protection of investors, the industry, and the overall integrity of the blockchain ecosystem. This research sheds light on the intricate workings of giveaway scams and proposes effective strategies to counteract them.

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Uncovering influential factors of civil unrest in South Africa: A machine learning and OSINT approach

(2023-12) Ndlovu, Lungisani; De Kock, Antonie J; Mkuzangwe, Nenekazi NP; Thwala, Ntombizodwa; Mokoena, Chantel JM; Matimatjatji, Rethabile J

Continuous monitoring of the risk of civil unrest events and predicting their occurrence is of paramount importance. This task involves identifying and understanding the primary factors that contribute to such events, especially in regions with unique dynamics, such as South Africa. Although many global and South African-specific studies have conducted research on predicting the frequency or probability of these events, there is a notable gap in identifying the influential factors behind them. This study unveiled several contributing factors, including demanding behaviour, power outages, service delivery, wage disputes, acts of violence, gender-based conflicts, and unemployment rates. These factors, individually or collectively, contribute to the complexity of civil unrest in the region. The 2021 South African unrest, also known as the July 2021 riots, the Zuma unrest, or Zuma riots, serves as an example. This event was triggered by the imprisonment of former president Jacob Zuma for contempt of court, inciting his followers to demand his release, a situation aligning with the 'demanding behaviour' influential factor identified in our study. We used advanced data analysis and machine learning techniques to explore these factors. Specifically, the Logit model was used to determine the coefficients that optimally fit the data, establishing significant relationships between these factors and incidents of civil unrest. Our research not only offers insights on influential factors, but also presents a predictive framework. We evaluated logistic regression, support vector clustering, decision tree classifier, and random forest classifier models to predict civil unrest. The results showed that the decision tree and the random forest classifiers perform better, achieving an accuracy of 98%, compared to logistic regression and support vector clustering, which have an accuracy of 97%.

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A comprehensive exploration of digital forensics investigations in embedded systems, ubiquitous computing, fog computing, and edge computing

(2024-08) Nelufule, Nthatheni; Singano, Zothile T; Masango, Mfundo G

The rapid evolution of digital ecosystems, characterized by the intricate interplay of diverse technologies, has necessitated a shift in the digital forensics’ paradigm. Traditional investigative methods are inadequate to perform digital forensic exercises in the new paradigm of dynamic digital ecosystem landscapes. The emergence of complex digital ecosystems encompassing an array of interconnected devices and data repositories poses formidable challenges for conventional digital forensics. There is a dire need to adapt and advance digital forensic methodologies to effectively combat cybercrime because the evolving landscape of digital ecosystems presents a critical juncture for the field of digital forensics. This study proposes a systematic literature review to understand the extent of these challenges and proposes a collaborative and innovative approach to digital forensic investigation within the context of digital ecosystems. The proposed approach emphasizes collaboration across diverse sectors and integration of innovative technologies by combining a spectrum of digital forensic experts, technologists, and legal professionals to produce a massive wealth of collective intelligence.

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Optimisation of the heat treatment profile for powder-bed Fusion built AlSi10Mg by age hardening and ice-water quenching

(2024-02) Mfusi, Busisiwe J; Popoola, PA; Mathe, Ntombizodwa R

During powder-bed fusion (PBF), the irradiated material causes undesirable thermal stresses while experiencing large temperature oscillations over a rapid period. This requires the components produced by this technique to undergo thermal treatment. The characteristics of additively manufactured materials, which are rapid heating and cooling, do not accept conventional methods, such as thermal treatment, that alleviate stress for the removal of thermal stresses. In this research, the thermal treatment of age hardening is explored, in which AlSi10Mg is subjected to lower temperatures for longer periods of time. Other samples were thermally treated at 300 C and 400 C for various hours and quenched in ice water. This is conducted to identify the acceptable temperature and conditions that will improve the properties after thermal treatment without jeopardising other properties of the material and to investigate the effects of the thermal treatment profiles on the microstructural and mechanical characteristics of the AlSi10Mg samples.