Abstract
In this letter, a new configuration based on two fiber loop mirrors in series using a 3x3 coupler is demonstrated. This configuration is compact and can explore the Vernier effect. The results obtained were a sensitivity of 74.9 +/- 0.2 pm/ mu epsilon for the Vernier envelope and 6.41 +/- 0.01 pm/mu epsilon for the Vernier carrier. These results were compared to the sensitivity of the setup using only one fiber loop mirror interferometer, obtaining 14.41 +/- 0.01 pm/mu epsilon. This means a magnification factor of 5.2 for the Vernier envelope. Theoretical treatment of the system was carried out, using Jones matrix calculus, and the subsequent simulation results are also presented, having obtained good agreement with the experimental data.

Abstract
Future telecommunications aim to be ubiquitous and efficient, as widely deployed connectivity will allow for a variety of edge/fog based services. Challenges are numerous, e.g., spectrum overuse, energy efficiency, latency and bandwidth, battery life and computing power of edge devices. Addressing these challenges is key to compose the backbone for the future Internet-of-Things (IoT). Among IoT applications are Indoor Positioning System and indoor Real-Time-Location-Systems systems, which are needed where GPS is unviable. The Bluetooth Low Energy (BLE) 5.1 specification introduced Direction Finding to the protocol, allowing for BLE devices with antenna arrays to derive the Angle-of-Arrival (AoA) of transmissions. Well known algorithms for AoA calculation are computationally demanding, so recent works have addressed this, since the low-cost of BLE devices may provide efficient solutions for indoor localization. In this paper, we present a system topology and algorithms for self-localization where a receiver with an antenna array utilizes the AoAs from fixed battery powered beacons to self-localize, without a centralized system or wall-power infrastructure. We conduct two main experiments using a BLE receiver of our own design. Firstly, we validate the expected behaviour in an anechoic chamber, computing the AoA with an RMSE of 10.7 degrees conduct a test in an outdoor area of 12 by 12 meters using four beacons, and present pre-processing steps prior to computing the AoAs, followed by position estimations achieving a mean absolute error of 3.6 m for 21 map positions, with a minimum as low as 1.1 m.

Abstract
Agricultural cooperatives remain a significant component of the food and agriculture industry to help the stakeholders to provide services and have opportunities for themselves. One of the aims of an agricultural cooperative is to answer to the needs within the communities of the farmers. Agricultural cooperatives enable individual farmers to increase productivity and maximise their social welfare. Together the farmer members of an agricultural cooperative can buy input supplies cheaper and sell more of their products in larger markets at higher prices, which is not possible for an individual smallholder farmer otherwise. Some studies have shown that farmers who were members of cooperatives have gained higher revenue for their products and spent less on input. However, organising the hundreds of farmers into smaller groups to perform collective farming and marketing is crucial to strengthening their position in the food and agriculture industry. Thereby, in our work, we consider an agricultural cooperative of smallholder farmers as a multi-agent based coalitional model, where coalitions are formed based on the similarity among the smallholder farmers. In this paper, we propose a model and implement a heuristic-based algorithm to find the disjoint partition of the agents set. We evaluate the model and the algorithm based on the following criteria: (i) individual gain, (ii) runtime analysis, (iii) solution quality, and (iv) scalability. We theoretically prove that our coalitional model of an agricultural cooperative has conciseness, expressiveness and efficiency properties. Experimental results confirm that our algorithm is time efficient and scalable. We show, both empirically and theoretically, that our algorithm generates a solution within a bound of the optimal solution. We also show that our coalition model generates positive revenue for the smallholder farmers and the payoff division rule is individual rational. In addition, we generate a new dataset in the context of an agricultural cooperative to show the effectiveness and efficiency of the proposed coalitional model of the cooperative.

Abstract
Digital transformation creates a number of barriers that need to be surpassed by companies from the technological and organizational points of view. Concurrently, the complexity and nature of current market environments often demand new products, services, processes and business models, oftentimes supported by digital technologies. The objective of this paper is to contribute to a better understanding on the impact of a severe global crisis on the digital technologies' adoption process (and their associate drivers and barriers), with a special look on the strategies adopted by companies in terms of supply chain resilience. Specificities of the Portuguese industry are discussed through the analysis of five case studies.

Abstract
Sustainable mobility has become one of the most pressing issues in modern society. The need to raise awareness of climate change, combined with the overcrowding of metropolitan and urban areas, has produced a situation that requires an urgent solution. Some earlier approaches dealt primarily with transport-related issues, while some conceptual models attempted to increase the appeal of public transport by linking the services provided by public transport operators to a variety of city services. A practical and empirical answer, on the other hand, has not yet been given. This research addrebes these issues by taking a holistic approach and presenting a personalized recommendation system based on users' everyday activities as well as their mobility profiles. The crossing of both sources of information allows for a more user-centric experience, ensuring that the offers presented are adapted to the tastes of customers. The potential of such a system is proven using data from Porto, Portugal. Two types of data sources were used to obtain more accurate results: data from the automated fare collection system of the Porto Metropolitan Area, Portugal, and data from city services taken from Google Places. The fundamental idea behind tackling this problem is to encourage people to use public transport by providing them with incentives such as discounts, promotions and service offers to encourage them to use cleaner and more efficient modes of transport. © 2023 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)

Abstract
We present DIO, a generic tool for observing inefficient and erroneous I/O interactions between applications and in-kernel storage systems that lead to performance, dependability, and correctness issues. DIO facilitates the analysis and enables near real-time visualization of complex I/O patterns for data-intensive applications generating millions of storage requests. This is achieved by non-intrusively intercepting system calls, enriching collected data with relevant context, and providing timely analysis and visualization for traced events. We demonstrate its usefulness by analyzing two production-level applications. Results show that DIO enables diagnosing resource contention in multi-threaded I/O that leads to high tail latency and erroneous file accesses that cause data loss.