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Adopting open-source SD-WAN: a comprehensive analysis of performance, cost, and security benefits over traditional WAN architectures
Full text linkMany enterprises are using cloud computing innovation and remote services to the maximum. Working from home is becoming the norm. Favored legacy Wide Area Networks (WANs) are not up to the tasks, as they are suffering due to lack of scalability with their traditional non-virtualized form as it still requires a lot of physical components. Update and maintenance of fickle hardware costs a lot. There is a need for more flexible and scalable networking solutions. Many enterprise solutions offer proprietary form of SD-WANs (Software-Defined Wide Area Networks), but they are costly and inflexible, which means they are not practical for all applications. This paper proposes an Open-source SD-WAN with OpenDaylight platform as core that we have tested in a simulated environment along with Mininet and Oracle Virtual Box to study various scenarios. Test results show that it provides a 35% increase in throughput, decreases 40% in latency, and reduces packet loss by 50%, compared to traditional WANs. Additionally with Open-Source nature, it has a 20% lower operational coupled with the problem mitigation factors listed above, which makes it a more potential solution for the current woes of businesses
Beyond polarity: forecasting consumer sentiment with aspect- and topic-conditioned time series models
Full text linkExisting approaches to social media sentiment analysis typically focus on static classification, offering limited foresight into how public opinion evolves. This study addresses that gap by introducing the Multi-Feature Sentiment-Driven Forecasting (MFSF) framework, a novel pipeline that enhances sentiment trend prediction by integrating rich contextual information from text. Using state-of-the-art transformer models on the Sentiment140 dataset, our framework extracts three concurrent signals from each tweet: sentiment polarity, aspect-based scores (e.g., ‘price’ and ‘service’), and topic embeddings. These features are aggregated into a daily multivariate time series. We then employ a SARIMAX model to forecast future sentiment, using the extracted aspect and topic data as predictive exogenous variables. Our results, validated on the historical Sentiment140 Twitter dataset, demonstrate the framework’s superior performance. The proposed multivariate model achieved a 26.6% improvement in forecasting accuracy (RMSE) over a traditional univariate ARIMA baseline. The analysis confirmed that conversational aspects like ‘service’ and ‘quality’ are statistically significant predictors of future sentiment. By leveraging the contextual drivers of conversation, the MFSF framework provides a more accurate and interpretable tool for businesses and policymakers to proactively monitor and anticipate shifts in public opinion
Regenerative supply chains in Vietnamese agriculture: extending natural resource theory through collective waste utilization and social benefit
Full text linkOur research explores how firms create sustainable competitive advantage when adopting regenerative practices in the Vietnamese agricultural sector. We define regenerative supply chains (RSCs) and extend natural resource-based theory through the lens of new revenue streams, ecosystem restoration and social innovation. A multiple-case research design inducts theory from business strategy and natural resource theory, utilizing data from three firms engaged in RSC to create theoretical constructs and propositions. We find that firms in Vietnam that engage in regenerative practices adopt collaborative activities involving waste utilization, leading to social benefits in local communities and international trade. The research also reveals that traditional and modern technological practices coexist in RSC, which has implications for resource transferability between firms. We propose a more nuanced approach to RSC development, which emphasizes the importance of adaptability and context-specific strategies for sustainable competitive advantage that connects the supply chain with community and natural ecosystems
Astragalus polysaccharides protect against Di-n-butyl phthalate-induced testicular damage by modulating oxidative stress, apoptosis, and the PI3K/Akt/mTOR pathway in rats
Full text linkIntroduction: Di-n-butyl phthalate (DBP), a common plasticizer, is associated with oxidative stress and male reproductive toxicity. Astragalus polysaccharides (APS) have known antioxidative and anti-inflammatory properties, but their role in male reproductive health has not been fully elucidated.
Methods: Twenty-four male rats were randomly assigned to four groups (n = 6 each): control, DBP-only (500 mg/kg/day), APS-only (200 mg/kg/day), and APS + DBP (500 mg/kg/day DBP + 200 mg/kg/day APS). Treatments were administered orally for 8 weeks. Biochemical, histological, and molecular analyses were conducted to evaluate testicular function, oxidative stress markers, and gene expression.
Results: DBP exposure significantly decreased serum testosterone levels, catalase (CAT) activity, lactate dehydrogenase (LDH) activity, and sperm quality, while increasing malondialdehyde (MDA) levels and apoptotic markers Casp3, Casp9. APS co-treatment significantly restored antioxidant enzyme activity, improved sperm parameters, reduced MDA levels, and alleviated histopathological damage. Gene expression analysis revealed upregulation of Nrf2 and SOD, and modulation of the PI3K/AKT/mTOR signaling pathway.
Discussion: APS exerts protective effects against DBP-induced testicular damage by enhancing antioxidant defenses and regulating key molecular pathways. These findings highlight the therapeutic potential of APS in preventing male infertility associated with environmental toxicants
When do environmental regulations lead to green practices? the role of resource commitment and corporate entrepreneurship
Full text linkEnvironmental regulations increasingly pressure firms to adopt green practices, yet their effectiveness remains debated. Drawing on institutional theory and resource-based view, this study investigates the mechanisms linking environmental regulations to green supply chain management (GSCM) practices. We propose and test a moderated mediation model using data from 231 Chinese manufacturers. Results show that circular-oriented resource commitment mediates the regulation-GSCM relationship, while corporate entrepreneurship selectively moderates the path from regulations to resource commitment. These findings extend theory by showing how regulatory pressures shape resource deployment in environmental management and how entrepreneurial orientation enhances firms' ability to transform regulatory requirements into strategic resource commitments
CANDIDS: CAN/CAN-FD deep learning-based intrusion detection systems
Full text linkThe automotive industry has experienced a surge in technological advancements, resulting in a significant increase in the connectivity and functionality of modern vehicles. In-vehicle networks, which serve as the backbone of communication between various Electronic Control Units (ECUs), rely on protocols such as the Controller Area Network (CAN) and its successor, CAN with Flexible Data Rate (CAN-FD). However, the lack of robust security measures in these industry-standard protocols has left systems increasingly vulnerable to cyber threats. By implementing Intrusion Detection Systems (IDS), automotive security could be significantly enhanced with minimal disruption to the vehicle's infrastructure. The integration of advanced machine learning algorithms offers significant promise in enhancing the effectiveness of IDS. In this paper, we propose a deep learning-based IDS, named CANDIDS, which is capable of operating effectively not only for the conventional CAN protocol, but also for the most recent CAN-FD one commonly found in modern vehicles. The proposed approach enables the system to identify abnormal network traffic and categorize various types of attack. The experimental results show that CANDIDS achieves 99.47% and 99.87% detection and multiclass classification accuracy for CAN and CAN-FD respectively, illustrating its effectiveness in anomaly detection. Additionally, CANDIDS achieves low latency intrusion detection, completing the process in 2 and 3 milliseconds for CAN and CAN-FD meeting the strict timing demands crucial for the safe and efficient operation of networked automotive and self-driving vehicle applications
Epigenetics and gut microbiome of reptiles can reveal potential targets to improve human health and performance
Full text linkIt is widely acknowledged that the gut microbiome plays a crucial role in both human and animal health. Nutrition, genetic predisposition, environmental factors, and epigenetic alterations significantly influence the microbiome and its interactions with the host. Epigenetic modifications include DNA methylation, histone modification and regulation of non-coding RNAs. Given the ability of reptiles to survive, thrive and adapt over millions of years, it is logical to be associated with their robust immune system and unique gut microbiome/epigenetic alterations, and it is a worthy area of investigation. As up to 80% of the immune system resides in the gut, the reptilian gut microbiome represents a unique potential resource for discovery of novel molecules that impact the host epigenome. Herein, we discuss the role of epigenetics and the gut microbiome, with a focus on long-lived reptiles such as crocodiles. Finally, epigenetic gut microbial modulation strategies are deliberated upon
Fair switch selection for large scale software defined networks in next generation internet of things
Full text linkSoftware Defined Networking has been pivotal in enabling on-demand resource utilization and is poised to have an incredible impact on the next phase of the Internet of Things. Its ability to furnish a versatile and expandable network framework is instrumental in accommodating the overwhelming surge of IoT devices and applications. The combination of static mapping and the dynamic flow of traffic over time and space creates an uneven distribution of loads across SDN controllers. Dynamic migration is a solution aimed at rectifying this imbalance by redistributing the load between SDN controllers. Communication for control between switches and controllers becomes burdensome when the matching rules are absent from the table. Our prior research has addressed this issue by employing burst aggregation focused on consolidating similar destinations to reduce the control overhead. In this study, our focus is on ensuring fairness during migration and selecting the appropriate switch. We model a fair switch selection (FSS) algorithm tailored for large-scale software-defined networks. Unlike traditional methods using packets as a basis, FSS utilizes bursts as its input. This model prioritizes bursts considering both their distance and destination, ensuring that switches select bursts with the highest priority to maintain quality of service. Our research delves into evaluating the performance of the proposed algorithm in comparison to four baseline algorithms: round robin, exhaustive search, multi-protocol TCP (MPTCP), and random search. Through extensive simulations, we analyze experimental results based on cost, performance, packet loss, average throughput, and execution time. Experimental results demonstrated a reduction in packet loss by 30% with an average 25% throughput improvement
CAET world forum: integrative applications - frontiers and trends
No full textI was invited by the International Creative Arts Education and Therapy Associations to take part as an invited guest to their world forum series. To talk about the trends and development of dramatherapy its history and current practice in the U
Voicing the Other (at Galleria Duet, Helsinki)
Full text linkAngela Bartram and Jaana Erkkilä-Hill create shared spaces of experience inspired by their interaction between species. 'Voicing the Other' combines text and still images, and is installed in relation to the gallery site. Through a process of letter writing and reading, the research find ways to develop interspecies communication that is non discriminatory, denying human-centric cultural privileging. Specifically, the species this work relates to, is horses, dogs and humans.
The work is the result of a close collaboration between the two artist-researchers, together with a horse (in the UK) and a dog (in Finland), for this exhibition at Galleria Duetto, Helsinki, April-May 2025. This presents the second iteration of this research, with the first being in 'How to Live Together in Sound', Gallery Hamara, Rovaniemi, 2025