A holistic digital forensic analysis of Discord - Storage, memory, and network perspectives.

In the last decade, the market share and user base of social media applications have witnessed significant growth. However, this surge in popularity has inadvertently drawn the attention of criminals aiming to exploit these platforms for illicit activities. The forensic examination of these applications emerges as a pivotal avenue for uncovering valuable insights into criminal behavior and identifying suspects. Discord, a social media platform, has become a significant focal point for such illicit activities. In this paper, we examine the remnants of Discord on both Windows and Linux operating systems, employing storage, memory, and network analysis techniques to review the remnants of Discord. Our investigation reveals a range of crucial artifacts that have been successfully recovered across all three areas of analysis, including login and payment details, chat history, account information, and much more. Collectively, these artifacts constitute a valuable resource for forensic investigations, allowing the reconstruction of most of the user's activity.

Exploring the Potential of Essential Oil from Plectranthus amboinicus Leaves against Breast Cancer: In vitro and In silico Analysis.

Plectranthus amboinicus leaves were subjected to hydrodistillation to obtain essential oil (EO). Phytochemical analysis using gas chromatography-mass spectrometry revealed a diverse range of compounds in the EO, with p-cymen-4-ol (18.57%) emerging as the most predominant, followed by isocaryophyllene (12.18%). The in vitro antiproliferative activity of EO against breast cancer was assessed in MCF-7 and MDA-MB-231 cell lines. The MTT assay results revealed that EO showed IC50 values of 42.25 µg/mL and 13.44 µg/mL in MCF-7 cells and 63.67 µg/mL and 26.58 µg/mL in MDA-MB-231 cells after 24 and 48 h, respectively. The in silico physicochemical and pharmacokinetic profiles of the EO constituents were within acceptable limits. Molecular docking was conducted to investigate the interactions between the constituents of the EO and protein Aromatase (PDB ID:3S79). Among the EO constituents, 4-tert-butyl-2-(5-tert-butyl-2-hydroxyphenyl)phenol (4BHP) exhibited the highest dock score of -6.580 kcal/mol when compared to the reference drug, Letrozole (-5.694 kcal/mol), but was slightly lesser than Anastrozole (-7.08 kcal/mol). Molecular dynamics simulation studies (100 ns) of the 4BHP complex were performed to study its stability patterns. The RMSD and RMSF values of the 4BHP protein complex were found to be 2.03 Å and 4.46 Å, respectively. The binding free energy calculations revealed that 4BHP displayed the highest negative binding energy of -43 kcal/mol with aromatase protein, compared to Anastrozole (-40.59 kcal/mol) and Letrozole (-44.54 kcal/mol). However, further research is required to determine the safety, efficacy, and mechanism of action of the volatile oil. Taking into consideration the key findings of the present work, the development of a formulation of essential oil remains a challenging task and novel drug delivery systems may lead to site-specific and targeted delivery for the effective treatment of breast cancer.

Phytometabolites as modulators of breast cancer: a comprehensive review of mechanistic insights.

Breast cancer (BC) is a highly debilitating malignancy affecting females globally and imposing a substantial burden on healthcare systems in both developed and developing nations. Despite the application of conventional therapeutic modalities such as chemotherapy, radiation therapy, and hormonal intervention, BC frequently exhibits resistance, necessitating the urgent development of novel, cost-effective, and accessible treatment strategies. In this context, there is a growing scientific interest in exploring the pharmacological potential of chemical compounds derived from botanical sources, which often exhibit notable biological activity. Extensive in vitro and in vivo investigations have revealed the capacity of these compounds, referred to as phytochemicals, to attenuate the metastatic cascade and reduce the risk of cancer dissemination. These phytochemicals exert their effects through modulation of key molecular and metabolic processes, including regulation of the cell cycle, induction of apoptotic cell death, inhibition of angiogenesis, and suppression of metastatic progression. To shed light on the latest advancements in this field, a comprehensive review of the scientific literature has been conducted, focusing on secondary metabolite agents that have recently been investigated and have demonstrated promising anticancer properties. This review aims to delineate their underlying mechanisms of action and elucidate the associated signaling pathways, thereby contributing to a deeper understanding of their therapeutic potential in the context of BC management.

Polycystic ovary syndrome: Current scenario and future insights.

Polycystic ovary syndrome (PCOS) prevails in approximately 33% of females of reproductive age globally. Although the root cause of the disease is unknown, attempts are made to clinically manage the disturbed hormone levels and symptoms arising due to hyperandrogenism, a hallmark of PCOS. This review presents detailed insights on the etiology, risk factors, current treatment strategies, and challenges therein. Medicinal agents currently in clinical trials and those in the development pipeline are emphasized. The significance of the inclusion of herbal supplements in PCOS and the benefits of improved lifestyle are also explained. Last, emerging therapeutic targets for treating PCOS are elaborated. The present review will assist the research fraternity working in the concerned domain to access significant knowledge associated with PCOS.

Smart Transportation: An Overview of Technologies and Applications.

As technology continues to evolve, our society is becoming enriched with more intelligent devices that help us perform our daily activities more efficiently and effectively. One of the most significant technological advancements of our time is the Internet of Things (IoT), which interconnects various smart devices (such as smart mobiles, intelligent refrigerators, smartwatches, smart fire alarms, smart door locks, and many more) allowing them to communicate with each other and exchange data seamlessly. We now use IoT technology to carry out our daily activities, for example, transportation. In particular, the field of smart transportation has intrigued researchers due to its potential to revolutionize the way we move people and goods. IoT provides drivers in a smart city with many benefits, including traffic management, improved logistics, efficient parking systems, and enhanced safety measures. Smart transportation is the integration of all these benefits into applications for transportation systems. However, as a way of further improving the benefits provided by smart transportation, other technologies have been explored, such as machine learning, big data, and distributed ledgers. Some examples of their application are the optimization of routes, parking, street lighting, accident prevention, detection of abnormal traffic conditions, and maintenance of roads. In this paper, we aim to provide a detailed understanding of the developments in the applications mentioned earlier and examine current researches that base their applications on these sectors. We aim to conduct a self-contained review of the different technologies used in smart transportation today and their respective challenges. Our methodology encompassed identifying and screening articles on smart transportation technologies and its applications. To identify articles addressing our topic of review, we searched for articles in the four significant databases: IEEE Xplore, ACM Digital Library, Science Direct, and Springer. Consequently, we examined the communication mechanisms, architectures, and frameworks that enable these smart transportation applications and systems. We also explored the communication protocols enabling smart transportation, including Wi-Fi, Bluetooth, and cellular networks, and how they contribute to seamless data exchange. We delved into the different architectures and frameworks used in smart transportation, including cloud computing, edge computing, and fog computing. Lastly, we outlined current challenges in the smart transportation field and suggested potential future research directions. We will examine data privacy and security issues, network scalability, and interoperability between different IoT devices.

A Review of Automated Bioacoustics and General Acoustics Classification Research.

Automated bioacoustics classification has received increasing attention from the research community in recent years due its cross-disciplinary nature and its diverse application. Applications in bioacoustics classification range from smart acoustic sensor networks that investigate the effects of acoustic vocalizations on species to context-aware edge devices that anticipate changes in their environment adapt their sensing and processing accordingly. The research described here is an in-depth survey of the current state of bioacoustics classification and monitoring. The survey examines bioacoustics classification alongside general acoustics to provide a representative picture of the research landscape. The survey reviewed 124 studies spanning eight years of research. The survey identifies the key application areas in bioacoustics research and the techniques used in audio transformation and feature extraction. The survey also examines the classification algorithms used in bioacoustics systems. Lastly, the survey examines current challenges, possible opportunities, and future directions in bioacoustics.

Visual Dialog.

We introduce the task of Visual Dialog, which requires an AI agent to hold a meaningful dialog with humans in natural, conversational language about visual content. Specifically, given an image, a dialog history, and a question about the image, the agent has to ground the question in image, infer context from history, and answer the question accurately. Visual Dialog is disentangled enough from a specific downstream task so as to serve as a general test of machine intelligence, while being sufficiently grounded in vision to allow objective evaluation of individual responses and benchmark progress. We develop a novel two-person real-time chat data-collection protocol to curate a large-scale Visual Dialog dataset (VisDial). VisDial v0.9 has been released and consists of dialog question-answer pairs from 10-round, human-human dialogs grounded in images from the COCO dataset.