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Abstract Uracil-DNA glycosylase (UDG) is the first enzyme in the base-excision repair (BER) pathway, acting on uracil bases in DNA. How UDG finds its targets has not been conclusively resolved yet. Based on available structural and other experimental evidence, two possible pathways are under discussion. In one, the action of UDG on the DNA bases is believed to follow a ‘pinch-push-pull’ model, in which UDG generates the base-flip in an active manner. A second scenario is based on the exploitation of bases flipping out thermally from the DNA. Recent molecular dynamics (MD) studies of DNA in trinucleosome arrays have shown that base-flipping can be readily induced by the action of mechanical forces on DNA alone. This alternative mechanism could possibly enhance the probability for the second scenario of UDG-uracil interaction via the formation of a recognition complex of UDG with flipped-out base. In this work, we describe DNA structures with flipped-out uracil bases generated by MD simulations which we then subject to docking simulations with the UDG enzyme. Our results for the UDG-uracil recognition complex support the view that base-flipping induced by DNA mechanics can be a relevant mechanism of uracil base recognition by the UDG glycosylase in chromatin.

Multi-stable behavior at the microscopic length-scale is fundamental for phase transformation phenomena observed in many materials. These phenomena can be driven not only by external mechanical forces but are also crucially influenced by disorder and thermal fluctuations. Disorder, arising from structural defects or fluctuations in external stimuli, disrupts the homogeneity of the material and can significantly alter the system’s response, often leading to the suppression of cooperativity in the phase transition. Temperature can further introduce novel effects, modifying energy barriers and transition rates. The study of the effects of fluctuations requires the use of a framework that naturally incorporates the interaction of the system with the environment, such as Statistical Mechanics to account for the role of temperature. In the case of complex phenomena induced by disorder, advanced methods such as the replica method (to derive analytical formulas) or refined numerical methods based, for instance, on Monte Carlo techniques, may be needed. In particular, employing models that incorporate the main features of the physical system under investigation and allow for analytical results that can be compared with experimental data is of paramount importance for describing many realistic physical phenomena, which are often studied while neglecting the critical effect of randomness or by utilizing numerical techniques. Additionally, it is fundamental to efficiently derive the macroscopic material behavior from microscale properties, rather than relying solely on phenomenological approaches. In this perspective, we focus on a paradigmatic model that includes both nearest-neighbor interactions with multi-stable (elastic) energy terms and linear long-range interactions, capable of ensuring the presence of an ordered phase. Specifically, to study the effect of environmental noise on the control of the system, we include random fluctuation in external forces. We numerically analyze, on a small-size system, how the interplay of temperature and disorder can significantly alter the system’s phase transition behavior. Moreover, by mapping the model onto a modified version of the Random Field Ising Model, we utilize the replica method approach in the thermodynamic limit to justify the numerical results through analytical insights.

The agricultural sector is amidst an industrial revolution driven by the integration of sensing, communication, and artificial intelligence (AI). Within this context, the internet of things (IoT) takes center stage, particularly in facilitating remote livestock monitoring. Challenges persist, particularly in effective field communication, adequate coverage, and long-range data transmission. This study focuses on employing LoRa communication for livestock monitoring in mountainous pastures in the north-western Alps in Italy. The empirical assessment tackles the complexity of predicting LoRa path loss attributed to diverse land-cover types, highlighting the subtle difficulty of gateway deployment to ensure reliable coverage in real-world scenarios. Moreover, the high expense of densely deploying end devices makes it difficult to fully analyze LoRa link behavior, hindering a complete understanding of networking coverage in mountainous environments. This study aims to elucidate the stability of LoRa link performance in spatial dimensions and ascertain the extent of reliable communication coverage achievable by gateways in mountainous environments. Additionally, an innovative deep learning approach was proposed to accurately estimate path loss across challenging terrains. Remote sensing contributes to land-cover recognition, while Bidirectional Long Short-Term Memory (Bi-LSTM) enhances the path loss model’s precision. Through rigorous implementation and comprehensive evaluation using collected experimental data, this deep learning approach significantly curtails estimation errors, outperforming established models. Our results demonstrate that our prediction model outperforms established models with a reduction in estimation error to less than 5 dB, marking a 2X improvement over state-of-the-art models. Overall, this study signifies a substantial advancement in IoT-driven livestock monitoring, presenting robust communication and precise path loss prediction in rugged landscapes.

Due to limited infrastructure and remote locations, rural areas often need help providing reliable and high-quality network connectivity. We propose an innovative approach that leverages Software-Defined Wide Area Network (SD-WAN) architecture to enhance reliability in such challenging rural scenarios. Our study focuses on cases in which network resources are limited to network solutions such as Long-Term Evolution (LTE) and a Low-Earth-Orbit satellite connection. The SD-WAN implementation compares three tunnel selection algorithms that leverage real-time network performance monitoring: Deterministic, Random, and Deep Q-learning. The results offer valuable insights into the practical implementation of SD-WAN for rural connectivity scenarios, showing its potential to bridge the digital divide in underserved areas.

Sacrificial bonds have been observed in several biological materials and structures and can increase their toughness, i.e., their resistance to fracture. They provide a reversible mechanism for dissipating mechanical energy before the possible system rupture. From a structural point of view, sacrificial bonds consist of short polymer chains that short-circuit parts of a main macromolecular chain (generating hidden lengths) and absorb energy by breaking them instead of the main chain. The toughness increase due to the presence of sacrificial bonds is typically named extra-toughness. Here, we developed a statistical mechanics and thermodynamics-based theory able to estimate the force–extension relation for chains with sacrificial bonds and to calculate the corresponding extra-toughness. The model is useful to better understand the sacrificial bond effects in biomaterials but also to apply the biomimetic paradigm and foster the development of high-performance artificial polymeric materials.

In recent years, edge computing has become an essential technology for real-time application development by moving processing and storage capabilities close to end devices, thereby reducing latency, improving response time and ensuring secure data exchange. In this work, we focus on a Smart Agriculture application that aims to protect crops from ungulate attacks, and therefore to significantly reduce production losses, through the creation of virtual fences that take advantage of computer vision and ultrasound emission. Starting with an innovative device capable of generating ultrasound to drive away ungulates and thus protect crops from their attack, this work provides a comprehensive description of the design, development and assessment of an intelligent animal repulsion system that allows to detect and recognize the ungulates as well as generate ultrasonic signals tailored to each species of the ungulate. Taking into account the constraints coming from the rural environment in terms of energy supply and network connectivity, the proposed system is based on IoT platforms that provide a satisfactory compromise between performance, cost and energy consumption. More specifically, in this work, we deployed and evaluated various edge computing devices (Raspberry Pi, with or without a neural compute stick, and NVIDIA Jetson Nano) running real-time object detector (YOLO and Tiny-YOLO) with custom-trained models to identify the most suitable animal recognition HW/SW platform to be integrated with the ultrasound generator. Experimental results show the feasibility of the intelligent animal repelling system through the deployment of the animal detectors on power efficient edge computing devices without compromising the mean average precision and also satisfying real-time requirements. In addition, for each HW/SW platform, the experimental study provides a cost/performance analysis, as well as measurements of the average and peak CPU temperature. Best practices are also discussed and lastly, this article discusses how the combined technology used can help farmers and agronomists in their decision making and management process.

Phase nucleation and propagation phenomena can be characterized by a cooperative behavior regulated by non local interactions between the multistable domains and with the loading device. Cooperativity is often macroscopically witnessed by a stress-peak, distinguishing the nucleation from the propagation stress, and by a larger size of the first nucleated domain. When low dimensional scales are considered, both in nanostructures or single molecule behaviors, the interfacial energy can compete with entropic effects, leading to the experimental observation of a temperature dependent phase transition strategy. We propose a fully analytical model, in the framework of equilibrium Statistical Mechanics, measuring such energetic competition and temperature dependent behavior, that well reproduces important experimental evidences. The effectiveness of the model is successfully tested in predicting the temperature dependent phase transition behavior of shape memory nanowires.

Long-term evolution (LTE) is a broadband wireless cellular system currently available in about 200 countries. From the mobile network operator point of view, one of the most appealing characteristics of LTE is the possibility of providing the users with mobile broadband services like voice over LTE and video over LTE (ViLTE), with strict quality of service (QoS) guarantees. The success of such services, which usually require a subscription fee, is obviously tightly bound to the users' quality of experience (QoE), that must be significantly better than the quality perceived in case of free services. This paper attempts to evaluate the perceived quality of the ViLTE service. In more detail, we present the results of an experimental test-bed realised at one of the most popular italian MNO, aimed at evaluating the impact of several network layer QoS parameters on the QoE of the ViLTE service.

Internet of Things (IoT) devices play a crucial role in the overall development of IoT in providing countless applications in various areas. Due to the increasing interest and rapid technological growth of sensor technology, which have certainly revolutionized the way we live today, a need to provide a detailed analysis of the embedded platforms and boards is consequential. This paper presents a comprehensive survey of the recent and most-widely used commercial and research embedded systems and boards in different classification emphasizing their key attributes including processing and memory capabilities, security features, connectivity and communication interfaces, size, cost and appearance, operating system support, power specifications, and battery life and listing some interesting projects for each device. Through this exploration and discussion, readers can have an overall understanding on this area and foster more subsequent studies.

Livestock farming is, in most cases in Europe, unsupervised, thus making it difficult to ensure adequate control of the position of the animals for the improvement of animal welfare. In addition, the geographical areas involved in livestock grazing usually have difficult access with harsh orography and lack of communications infrastructure, thus the need to provide a low-power livestock localization and monitoring system is of paramount importance, which is crucial not for a sustainable agriculture, but also for the protection of native breeds and meats thanks to their controlled supervision. In this context, this work presents an Internet of things (IoT)-based system integrating low-power wide area (LPWA) technology, cloud, and virtualization services to provide real-time livestock location monitoring. Taking into account the constraints coming from the environment in terms of energy supply and network connectivity, our proposed system is based on a wearable device equipped with inertial sensors, Global Positioning System (GPS) receiver, and LoRaWAN transceiver, which can provide a satisfactory compromise between performance, cost, and energy consumption. At first, this article provides the state-of-the-art localization techniques and technologies applied to smart livestock. Then, we proceed to provide the hardware and firmware co-design to achieve very low energy consumption, thus providing a significant positive impact to the battery life. The proposed platform has been evaluated in a pilot test in the northern part of Italy, evaluating different configurations in terms of sampling period, experimental duration, and number of devices. The results are analyzed and discussed for packet delivery ratio, energy consumption, localization accuracy, battery discharge measurement, and delay.

Smart agriculture and wildlife monitoring are one of the recent trends of Internet of Things (IoT) applications, which are evolving in providing sustainable solutions from producers. This article details the design, development and assessment of a wildlife monitoring application for IoT animal repelling devices that is able to cover large areas, thanks to the low power wide area networks (LPWAN), which bridge the gap between cellular technologies and short range wireless technologies. LoRa, the global de-facto LPWAN, continues to attract attention given its open specification and ready availability of off-the-shelf hardware, with claims of several kilometers of range in harsh challenging environments. At first, this article presents a survey of the LPWAN for smart agriculture applications. We proceed to evaluate the performance of LoRa transmission technology operating in the 433 MHz and 868 MHz bands, aimed at wildlife monitoring in a forest vegetation area. To characterize the communication link, we mainly use the signal-to-noise ratio (SNR), received signal strength indicator (RSSI) and packet delivery ratio (PDR). Findings from this study show that achievable performance can greatly vary between the 433 MHz and 868 MHz bands, and prompt caution is required when taking numbers at face value, as this can have implications for IoT applications. In addition, our results show that the link reaches up to 860 m in the highly dense forest vegetation environment, while in the not so dense forest vegetation environment, it reaches up to 2050 m.

Smart cities take advantage of recent Information and Communication Technology (ICT) developments to provide added value to existing public services and improve quality of life for the citizens. The Internet of Things (IoT) paradigm makes the Internet more pervasive where objects equipped with computing, storage, and sensing capabilities are interconnected with communication technologies. Because of the widespread diffusion of IoT devices, applying the IoT paradigm to smart cities is an excellent solution to build sustainable ICT platforms. Having citizens involved in the process through mobile crowdsensing (MCS) techniques augments capabilities of these ICT platforms without additional costs. For proper operation, MCS systems require the contribution from a large number of participants. Simulations are therefore a candidate tool to assess the performance of MCS systems. In this paper, we illustrate the design of CrowdSenSim, a simulator for mobile crowdsensing. CrowdSenSim is designed specifically for realistic urban environments and smart cities services. We demonstrate the effectiveness of CrowdSenSim for the most popular MCS sensing paradigms (participatory and opportunistic), and we present its applicability using a smart public street lighting scenario.

One of the most challenging tasks for network operators is implementing accurate per-packet monitoring, looking for signs of performance degradation, security threats, and so on. Upon critical event detection, corrective actions must be taken to keep the network running smoothly. Implementing this mechanism requires the analysis of packet streams in a real-time (or close to) fashion. In a softwarized network context, Stream Processing Systems (SPSs) can be adopted for this purpose. Recent solutions based on traditional SPSs, such as Storm and Flink, can support the definition of general complex queries, but they show poor performance at scale. To handle input data rates in the order of gigabits per seconds, programmable switch platforms are typically used, although they offer limited expressiveness. With the proposed approach, we intend to offer high performance and expressive power in a unified framework by solely relying on SPSs for multicores. Captured packets are translated into a proper tuple format, and network monitoring queries are applied to tuple streams. Packet analysis tasks are expressed as streaming pipelines, running on general-purpose programmable network devices, and a second stage of elaboration can process aggregated statistics from different devices. Experiments carried out with an example monitoring application show that the system is able to handle realistic traffic at a 10 Gb/s speed. The same application scales almost up to 20 Gb/s speed thanks to the simple optimizations of the underlying framework. Hence, the approach proves to be viable and calls for the investigation of more extensive optimizations to support more complex elaborations and higher data rates.

This Editorial analyzes the manuscripts accepted, after a careful peer-reviewed process, for the special issue “IoT Sensing Systems for Traffic Monitoring and for Automated and Connected Vehicles” of the Sensors MDPI journal.[...]

We analyze the role of temperature in the rate-independent cohesion and decohesion behavior of an elastic film, mimicked by a one-dimensional mass-spring chain, grounded to an undeformable substrate via a one-dimensional sequence of breakable links. In the framework of equilibrium statistical mechanics, in both isometric (Helmholtz ensemble) and isotensional (Gibbs ensemble) conditions, we prove that the decohesion process can be described as a transition at a load threshold, sensibly depending on temperature. Under the classical assumption of having a single domain wall between attached and detached links (zipper model), we are able to obtain analytical expressions for the temperature dependent decohesion force, qualitatively reproducing important experimental effects in biological adhesion. Interestingly, although the two ensembles exhibit a similar critical behavior, they are not equivalent in the thermodynamic limit since they display dissimilar force-extension curves and, in particular, significantly different decohesion thresholds.

The statistical mechanics and the thermodynamics of small systems are characterized by the non-equivalence of the statistical ensembles. When concerning a polymer chain or an arbitrary chain of independent units, this concept leads to different force-extension responses for the isotensional (Gibbs) and the isometric (Helmholtz) thermodynamic ensembles for a limited number of units (far from the thermodynamic limit). While the average force-extension response has been largely investigated in both Gibbs and Helmholtz ensembles, the full statistical characterization of this thermo-mechanical behavior has not been approached by evaluating the corresponding probability densities. Therefore, we elaborate in this paper a technique for obtaining the probability density of the extension when force is applied (Gibbs ensemble) and the probability density of the force when the extension is prescribed (Helmholtz ensemble). This methodology, here developed at thermodynamic equilibrium, is applied to a specific chain composed of units characterized by a bistable potential energy, which is able to mimic the folding and unfolding of several macromolecules of biological origin.

The maturity level reached by today’s commodity platforms makes even low-cost PCs viable alternatives to dedicated hardware to implement real network functions without sacrificing performance. Indeed, the availability of multi-core processing packages and multi-queue network interfaces that can be managed by accelerated I/O frameworks, provides off-the-shelf servers with the necessary power capability for running a broad variety of network applications with near hardware-class performance. At the same time, the introduction of the Software Defined Networks (SDN) and the Network Functions Virtualization (NFV) paradigms call for new programming abstractions and tools to allow this new class of network devices to be flexibly configured and functionally repurposed from the network control plane. The paper presents the ongoing work towards Enif-Lang (Enhanced Network processIng Functional Language), a functional language for programming network functions over generic middleboxes running the Linux operating system. The language addresses concurrent programming by design and is targeted at developing simple stand-alone applications as well as pre-processing stages of packet elaborations. Enif-Lang is implemented as a Domain Specific Language embedded in the Haskell language and inherits the main principles of its ancestor, including the strong typedness and the concept of function compositions. Complex network functions are implemented by composing a set of elementary operations (primitives) by means of a compact yet expressive language grammar. Throughout the paper, the description of the design principles and features of Enif-Lang are accompanied by examples and use cases. In addition, a preliminary performance assessment is carried out to prove the effectiveness of the language for developing practical applications with the performance level required by 5G systems and the Tactile Internet.

Users of next generation wireless devices will be likely to move across a heterogeneous network environment. Thiswill give them the possibility to always exploit the best connection to the global Internet. In order to keep a seamless connection, the handover between different access technologies, also known as vertical handover, must be as smooth as possible. The current evolution of network architectures toward an all-IP core favours the use of the Mobile IPv6 protocol to handle such handovers. However, this protocol still presents several drawbacks, mainly related to the assumption of static devices and wired connections. Hence we have designed and implemented a software module that exploits information from the lower layers (e.g. physical) to extend the capabilities of Mobile IPv6 to wireless environments. We have then evaluated both the plain Mobile IPv6 and our proposed implementation over an experimental testbed. The outcome of the assessment proves the effectiveness of our solution and reveals the possibility to perform a seamless vertical handover in heterogeneous wireless networks.

The paper deeply analyzes a novel network-wide power management problem, called Power-Aware Routing and Network Design with Bundled Links (PARND-BL), which is able to take into account both the relationship between the power consumption and the traffic throughput of the nodes and to power off both the chassis and even the single Physical Interface Card (PIC) composing each link. The solutions of the PARND-BL model have been analyzed by taking into account different aspects associated with the actual applicability in real network scenarios: (i) the time for obtaining the solution, (ii) the deployed network topology and the resulting topology provided by the solution, (iii) the power behavior of the network elements, (iv) the traffic load, (v) the QoS requirement, and (vi) the number of paths to route each traffic demand. Among the most interesting and novel results, our analysis shows that the strategy of minimizing the number of powered-on network elements through the traffic consolidation does not always produce power savings, and the solution of this kind of problems, in some cases, can lead to spliting a single traffic demand into a high number of paths.

In modern houses, the presence of sensors and actuators is increasing, while communication services and entertainment systems had long since settled into everyday life. The utilization of wireless communication technologies, such as ZigBee, Wi-Fi, and Bluetooth, is attractive because of their short installation times and low costs. The research is moving towards the integration of the various home appliances and devices into a single domotics system, able to exploit the cooperation among the diverse subsystems and offer the end-user a single multiservice platform. In this scenario, the paper presents the experimental evaluation of a domotics framework centered on a SIP-based home gateway (SHG). While SIP is used to build a common control plane, the SHG is in charge of translating the user commands from and to the specific domotics languages. The analysis has been devoted to assess both the performance of the SHG software framework and the negative effects produced by the simultaneous interference among the three widespread wireless technologies.