Current computing platforms encourage the integration of thousands of processing cores, and their interconnections, into a single chip. Mobile smartphones, IoT, embedded devices, desktops, and data centers use Many-Core Systems-on-Chip (SoCs) to exploit their compute power and parallelism to meet the dynamic workload requirements. Networks-on-Chip (NoCs) lead to scalable connectivity for diverse applications with distinct traffic patterns and data dependencies. However, when the system executes various applications in traditional NoCs—optimized and fixed at synthesis time—the interconnection nonconformity with the different applications’ requirements generates limitations in the performance. In the literature, NoC designs embraced the Software-Defined Networking (SDN) strategy to evolve into an adaptable interconnection solution for future chips. However, the works surveyed implement a partial Software-Defined Network-on-Chip (SDNoC) approach, leaving aside the SDN layered architecture that brings interoperability in conventional networking. This paper explores the SDNoC literature and classifies it regarding the desired SDN features that each work presents. Then, we described the challenges and opportunities detected from the literature survey. Moreover, we explain the motivation for an SDNoC approach, and we expose both SDN and SDNoC concepts and architectures. We observe that works in the literature employed an uncomplete layered SDNoC approach. This fact creates various fertile areas in the SDNoC architecture where researchers may contribute to Many-Core SoCs designs.

Managing Multi-Processor Systems-on-Chip (MPSoCs) is becoming increasingly complex as demands for advanced capabilities rise. This complexity is due to the involvement of more processing elements and resources, leading to a higher degree of heterogeneity throughout the system. Over time, management schemes have evolved from simple to autonomous systems with continuous control and monitoring of various parameters such as power distribution, thermal events, fault tolerance, and system security. Autonomous management integrates self-awareness into the system, making it aware of its environment, behavior, and objectives. Self-Aware Cyber-Physical Systems-on-Chip (SA-CPSoCs) have emerged as a concept to achieve highly autonomous management. Communication infrastructure is also vital to SoCs, and Software-Defined Networks-on-Chip (SDNoCs) can serve as a base structure for self-aware systems-on-chip. This paper presents a survey of the evolution of MPSoC management over the last two decades, categorizing research works according to their objectives and improvements. It also discusses the characteristics and properties of SA-CPSoCs and explains why SDNoCs are crucial for these systems.

Heavy metal contamination of foods remains a persistent global challenge for food safety and public health, driven by industrialization, mining activities, intensive agriculture, and ongoing environmental degradation. This scoping review synthesizes peer-reviewed literature on the occurrence of priority toxic metals—arsenic, cadmium, lead, mercury, and nickel—in food matrices, with emphasis on contamination pathways, analytical detection strategies, and documented human health effects. The reviewed studies reveal widespread accumulation of heavy metals in staple foods, including cereals, vegetables, seafood, and processed products, with concentrations frequently approaching or exceeding international regulatory limits, particularly in regions exposed to strong anthropogenic pressure. Conventional laboratory-based techniques, such as atomic absorption spectrometry and inductively coupled plasma methods, remain the reference standards for quantitative determination and regulatory compliance; however, their application to large-scale or continuous monitoring is often constrained by cost, infrastructure, and operational complexity. Consequently, increasing attention has been directed toward emerging detection approaches, including portable X-Ray fluorescence, Raman/SERS spectroscopy, electrochemical biosensors, electronic tongues, and in situ magnetic measurements, as complementary tools for rapid screening and field-based surveillance. Among these, environmental magnetism and in situ magnetic techniques stand out as non-destructive, low-cost proxies capable of identifying metal-associated particulate contamination linked to food production systems. Chronic dietary exposure to heavy metals is consistently associated with neurotoxicity, nephrotoxicity, carcinogenicity, and oxidative stress, underscoring the need for integrated, multi-tiered monitoring frameworks to support early detection, risk assessment, and prevention.

Current System-on-Chips (SoCs) execute applications with task dependency that compete for shared resources such as buses, memories, and accelerators. In such a structure, the arbitration policy becomes a critical part of the system to guarantee access and bandwidth suitable for the competing applications. Some strategies proposed in the literature to cope with these issues are Round-Robin, Weighted Round-Robin, Lottery, Time Division Access Multiplexing (TDMA), and combinations. However, a fine-grained bandwidth control arbitration policy is missing from the literature. We propose an innovative arbitration policy based on opportunistic access and a supervised utilization of the bus in terms of transmitted flits (transmission units) that settle the access and fine-grained control. In our proposal, every competing element has a budget. Opportunistic access grants the bus to request even if the component has spent all its flits. Supervised debt accounts a record for every transmitted flit when it has no flits to spend. Our proposal applies to interconnection systems such as buses, switches, and routers. The presented approach achieves deadlock-free behavior even with task dependency applications in the scenarios analyzed through cycle-accurate simulation models. The synergy between opportunistic and supervised debt techniques outperforms Lottery, TDMA, and Weighted Round-Robin in terms of bandwidth control in the experimental studies performed.

Agricultural research and propagation systems often suffer due to a lack of access to affordable, adaptable, and well-structured technological solutions. Traditional plant growth devices typically rely on ad hoc construction, which limits their scalability, reuse, and adaptability. This study employs a user-centered conceptual design methodology based on product platform development and modular architecture to design a growth chamber for plant cuttings. The approach followed three main phases: (i) identification and classification of user needs, (ii) functional modeling of the base system and its variants, and (iii) architectural modularization through heuristic principles. Interviews with researchers yielded 55 functional requirements, of which 26 were defined as essential. Functional models were developed for both a base system and two variant systems incorporating alternative irrigation and sensing technologies. Heuristic analysis identified independent modules, such as irrigation, lighting, environmental monitoring, and control. Subsequently, block diagrams were used to translate functional logic into spatially coherent conceptual designs. The resulting architecture supports modular integration, reconfiguration, and scalability for diverse experimental needs. This work demonstrates that structured design methodologies, which are commonly used in industrial contexts, can be effectively applied in agricultural research settings to produce solutions that are versatile, low-cost, and have enduring value, offering a pathway for innovation, reproducibility, and technology transfer in resource-limited environments.

This study assessed the spatial distribution and composition of airborne particulate matter within a 10 km long urban green corridor in Zacatecas, Mexico, using magnetic biomonitoring with Tillandsia recurvata and SEM-EDS particle characterization. A total of 44 samples were collected from distinct urban park contexts (e.g., commercial zones, malls, bus stops), revealing mass-specific magnetic susceptibility χ values ranging from −6.71 to 61.1 × 10⁻⁸ m³ kg⁻¹. Three compositional groups were identified based on a PCA performed using elemental concentrations from SEM-EDS and magnetic data, which are associated with traffic emissions and industrial inputs. SEM-EDS images confirmed abundant magnetite-like particles (1–8 μm) with hazardous metals including Pb (up to 5.6 wt.%), Ba (up to 67.6 wt.%), and Cr (up to 31.5 wt.%). Wind direction data indicated predominant SSW–NNE transport, correlating with hotspots in central and northeastern park areas. Overall, vegetated zones exhibited markedly lower magnetic loads (mean χ = 8.84 × 10⁻⁸ m³ kg⁻¹) than traffic-exposed sites (mean χ = 17.27 × 10⁻⁸ m³ kg⁻¹), representing an approximate 50% reduction in magnetic particle accumulation, which highlights the effective role of continuous vegetation cover as a functional green barrier that attenuates the lateral transport and deposition of airborne particulate matter within the park. This research highlights the applicability of combined magnetic and microscopic techniques for evaluating the dynamics of airborne pollution in urban parks and supports their use for identifying both pollution hotspots and mitigation zones, reinforcing the role of urban green spaces as biofunctional filters in cities facing vehicular air pollution.