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The Routing Protocol for Low-Power and Lossy Networks (RPL) is a novel routing protocol standardized for constrained environments such as 6LoWPAN networks. Providing security in IPv6/RPL connected 6LoWPANs is challenging because the devices are connected to the untrusted Internet and are resource constrained, the communication links are lossy, and the devices use a set of novel IoT technologies such as RPL, 6LoWPAN, and CoAP/CoAPs. In this paper we provide a comprehensive analysis of IoT technologies and their new security capabilities that can be exploited by attackers or IDSs. One of the major contributions in this paper is our implementation and demonstration of well-known routing attacks against 6LoWPAN networks running RPL as a routing protocol. We implement these attacks in the RPL implementation in the Contiki operating system and demonstrate these attacks in the Cooja simulator. Furthermore, we highlight novel security features in the IPv6 protocol and exemplify the use of these features for intrusion detection in the IoT by implementing a lightweight heartbeat protocol.

Artificial intelligence (AI) is the use of mathematical algorithms to mimic human cognitive abilities and to address difficult healthcare challenges including complex biological abnormalities like cancer. The exponential growth of AI in the last decade is evidenced to be the potential platform for optimal decision-making by super-intelligence, where the human mind is limited to process huge data in a narrow time range. Cancer is a complex and multifaced disorder with thousands of genetic and epigenetic variations. AI-based algorithms hold great promise to pave the way to identify these genetic mutations and aberrant protein interactions at a very early stage. Modern biomedical research is also focused to bring AI technology to the clinics safely and ethically. AI-based assistance to pathologists and physicians could be the great leap forward towards prediction for disease risk, diagnosis, prognosis, and treatments. Clinical applications of AI and Machine Learning (ML) in cancer diagnosis and treatment are the future of medical guidance towards faster mapping of a new treatment for every individual. By using AI base system approach, researchers can collaborate in real-time and share knowledge digitally to potentially heal millions. In this review, we focused to present game-changing technology of the future in clinics, by connecting biology with Artificial Intelligence and explain how AI-based assistance help oncologist for precise treatment.

This study investigates current research trends in co-production studies and discusses conceptual approaches. The conceptual paper contains studies on co-production in the field of public administration. This study identifies significant gaps in the field of study by systematically examining 32 co-production research works. The study’s contributions include (1) defining two common characteristics of co-production, (2) classifying three forms of co-production by end-users, and (3) discovering that the aims and performance of co-production are more effective for service providers when the strategy is citizen-centric. Future research should (1) concentrate on the reasons for co-production failures or successes, (2) identify additional barriers to co-production in service production, (3) investigate influences on service providers as well as structural impacts on the co-production process, and (4) provide practical assessments of co-production research.

The gaps between the complex nature of cancer and therapeutics have been narrowed down due to extensive research in molecular oncology. Despite gathering massive insight into the mysteries of tumor heterogeneity and the molecular framework of tumor cells, therapy resistance and adverse side effects of current therapeutic remain the major challenge. This has shifted the attention towards therapeutics with less toxicity and high efficacy. Myricetin a natural flavonoid has been under the spotlight for its anti-cancer, anti-oxidant, and anti-inflammatory properties. The cutting-edge molecular techniques have shed light on the interplay between myricetin and dysregulated signaling cascades in cancer progression, invasion, and metastasis. However, there are limited data available regarding the nano-delivery platforms composed of myricetin in cancer. In this review, we have provided a comprehensive detail of myricetin-mediated regulation of different cellular pathways, its implications in cancer prevention, preclinical and clinical trials, and its current available nano-formulations for the treatment of various cancers.

Recent technological advances in nanoscience and material designing have led to the development of point-of-care devices for biomolecule sensing and cancer diagnosis. In situ and portable sensing devices for bedside, diagnosis can effectively improve the patient’s clinical outcomes and reduce the mortality rate. Detection of exosomal RNAs by immuno-biochip with increased sensitivity and specificity to diagnose cancer has raised the understanding of the tumor microenvironment and many other technology-based biosensing devices hold great promise for clinical innovations to conquer the unbeatable fort of cancer metastasis. Electrochemical biosensors are the most sensitive category of biomolecule detection sensors with significantly low concentrations down to the atomic level. In this sense, this review addresses the recent advances in cancer detection and diagnosis by developing significant biological sensing devices that are believed to have better sensing potential than existing facilities.

The rapid advancement of digital technology has transformed how investors gather financial information, with platforms like Google Trends providing valuable insights into investor behavior through the Google Search Volume Index (GSVI). While the relationship between the GSVI and market behavior has been explored in developed markets, its application in emerging markets like Pakistan remains underexplored. This study investigates how investor attention, measured by the GSVI, influences market volatility, liquidity, and stock price movements in the Pakistan Stock Exchange (PSX), using weekly data from the KSE-100 Index between 2019 and 2024. The findings reveal that the GSVI significantly impacts market volatility and liquidity, particularly in retail-driven markets with high information asymmetry. Additionally, this research shows that the GSVI is a reliable predictor for stock price fluctuations, with heightened investor attention correlating with increased market activity. Despite the limitations of the GSVI in fully capturing investor sentiment, this study contributes to behavioral finance literature by demonstrating the role of digital information flows in shaping market behavior in emerging markets. It offers actionable insights for investors, financial institutions, and policymakers in Pakistan while suggesting areas for future research in applying the GSVI to global contexts and exploring alternative proxies for investor sentiment in emerging economies.

Brain tumor segmentation is difficult because of a number of technical problems, including its complex morphology, individual differences in anatomy, irregular shapes, overlapping, homogeneous gray matter and white matter intensity values, abnormalities that might not contrast with normal tissues, and the possibility of additional complications from various modalities. Expert radiologists may make different conclusions as a result of these difficulties. Regarding this, deep learning techniques, particularly CNN models, can be trained to handle these MRI artifacts and automatically extract features that the human eye is unable to detect, such as variations in shape, texture, and color. Deep learning models may effectively learn features across various modalities, but they are data-hungry techniques that could be enhanced with additional annotated data. Yet, data privacy is the main barrier to the real use of data centralization. To deal with these challenges proposed a federated learning approach. The proposed federated learning enables the decentralized learning of a shared model while sharing data. However, the traditional paradigm introduced in the literature involves institutional biases that have an impact on distributed learning. Proposed Fed_WCE_BTD (Federated Learning with Weak Client Elimination for Brain Tumor Detection) is a combination of a modified UNet architecture and federated. In addition, proposed method uses an optimal adaptive client selection strategy by carefully choosing each client based on their unique strengths. Our contribution to this crucial and costly diagnostic is being validated using the BRATS 2021 dataset, taking into account the slicing of brain tumors. The goal of this research is to outperform non-federated learning or perform on par with non-federated environments. At present, the suggested model is outperforming the others by 1% for detection of enhancing tumor and necrosis. The efficiency of the proposed federated learning was demonstrated by considerably higher dice-coefficient of enhancing tumor (p< 0.05) as compared to non-federated learning. However, the edema identification dice coefficient is 80%, which is similar to the baseline.

Cancer is a complex disease orchestrated by various extrinsic and intrinsic pathways. In recent years, there has been a keen interest towards the development of natural extracts-based cancer therapeutics with minimum adverse effects. In pursuit of effective strategy, a wide variety of natural products-derived compounds have been addressed for their anticancer effects. Apigenin is a naturally-occurring flavonoid present abundantly in various fruits and vegetables. Decades of research have delineated the pharmacological and biological properties of apigenin. Specifically, the apigenin-mediated anticancer activities have been documented in various types of cancer, but the generalized scientific evidence encompassing various molecular interactions and processes, such as regulation of the apoptotic machinery, aberrant cell signaling and oncogenic protein network have not been comprehensively covered. In this sense, in this review we have attempted to focus on the apigenin-mediated regulation of oncogenic pathways in various cancers. We have also addressed the cutting-edge research which has unveiled the remarkable abilities of apigenin to interact with microRNAs to modulate key cellular processes, with special emphasis on the nano-formulations of apigenin that can help their targeted delivery and can be a therapeutic solution for the treatment of various cancers.

Repeated sprint ability (RSA) is essential for football performance, especially in maintaining high-intensity efforts throughout a match. Repeated sprint training (RST) improves both aerobic and anaerobic capacities; however, its effects on players in different positional roles remain underexplored, particularly with regard to tailored conditioning protocols. This study assessed the impact of on-field RST on physical performance metrics, including aerobic capacity (VO₂max), sprint speed (10m DASH), vertical jump height (VJH), and power output, with a focus on positional differences among forwards, defenders, and goalkeepers. Forty male football players (aged 18-25 years) were purposively sampled and matched by position before allocation into experimental (RST) and control groups. The experimental group completed a structured four-week RST program, while the control group continued routine football training involving technical, tactical, and endurance drills. Pre- and post-intervention assessments included the Cooper Test (aerobic capacity), VO₂max, VJH, power output, and 10m DASH. After 4 weeks of RST, significant mprovements were observed in the experimental group. VO2max increased by 4.4 ml/kg/min (95% CI: 2.9 to 6.0; p < 0.001, d = 1.31), and 10m sprint time decreased by 0.32 seconds (95% CI: -0.45 to -0.19; p < 0.001, d = 1.36) in forwards. VJH improved significantly (p < 0.001) among defenders (Δ = 3.44 cm, 95% CI: 1.76 to 5.12, d = 1.06), while power improvements were most notable in defenders (Δ = 43.44W, 95% CI: 28.62 to 58.26, d = 1.00). Goalkeepers showed modest, non-significant improvements. Significant positional differences were identified for VJH and power output (p < 0.001). RST significantly enhanced physical performance metrics, particularly for forwards and defenders. The findings emphasize the importance of positional specificity in training programs to optimize football performance.

Cancers are complex diseases orchestrated by a plethora of extrinsic and intrinsic factors. Research spanning over several decades has provided better understanding of complex molecular interactions responsible for the multifaceted nature of cancer. Recent advances in the field of next generation sequencing and functional genomics have brought us closer towards unravelling the complexities of tumor microenvironment (tumor heterogeneity) and deregulated signaling cascades responsible for proliferation and survival of tumor cells. Phytochemicals have begun to emerge as potent beneficial substances aimed to target deregulated signaling pathways. Isoflavonoid genistein is an essential phytochemical involved in regulation of key biological processes including those in different types of cancer. Emerging preclinical evidence have shown its anti-cancer, anti-inflammatory and anti-oxidant properties. Testing of this substance is in various phases of clinical trials. Comprehensive preclinical and clinical trials data is providing insight on genistein as a modulator of various signaling pathways both at transcription and translation levels. In this review we have explained the mechanistic regulation of several key cellular pathways by genistein. We have also addressed in detail various microRNAs regulated by genistein in different types of cancer. Moreover, application of nano-formulations to increase the efficiency of genistein is also discussed. Understanding the pleiotropic potential of genistein to regulate key cellular pathways and development of efficient drug delivery system will bring us a step towards designing better chemotherapeutics.