Understanding interdependency through complex information sharing

The interactions between three or more random variables are often nontrivial, poorly understood, and yet, are paramount for future advances in fields such as network information theory, neuroscience, genetics and many others. In this work, we propose to analyze these interactions as different modes of information sharing. Towards this end, we introduce a novel axiomatic framework for decomposing the joint entropy, which characterizes the various ways in which random variables can share information. The key contribution of our framework is to distinguish between interdependencies where the information is shared redundantly, and synergistic interdependencies where the sharing structure exists in the whole but not between the parts. We show that our axioms determine unique formulas for all the terms of the proposed decomposition for a number of cases of interest. Moreover, we show how these results can be applied to several network information theory problems, providing a more intuitive understanding of their fundamental limits.Comment: 39 pages, 4 figure

Tracking the dynamic nature of learner individual differences: Initial results from a longitudinal study

Individual differences (IDs) have long been considered one of the most important factors explaining variable rates and outcomes in second language acquisition (Dewaele, 2013). While traditional operationalizations of IDs have, explicitly or implicitly, assumed that IDs are static traits that are stable through time, more recent research inspired by complex dynamic systems theory (Larsen-Freeman, 1997, 2020) demonstrates that many IDs are dynamic and variable through time and across contexts, a theme echoed throughout the current issue. This study reports the initial semester of a diachronic project investigating the dynamicity of four learner IDs: motivation, personality, learning and cognitive styles, and working memory. In the initial semester, data from 323 participants in their first year of university-level Spanish were collected and analyzed to determine what type of variability may be present across learners with respect to the four IDs studied at one time point and to discern possible learner profiles in the data or patterns via which the data may be otherwise meaningfully described. The results revealed four types of learner profiles present in the dataset

Assessing environmental profiles: An analysis of water consumption and waste recycling habits

Individual pro-environmental attitudes and behaviors are determinant for long-term sustainability. We assessed profiles of an exclusive sample of 1351 households in the municipality of Gijón, Spain, in terms of their water consumption and recycling patterns using Latent Class Analysis (LCA). This methodology allows for households to be classified into groups without imposing any ad hoc criteria and provides information on the determinants of belonging to each group. The database includes the water consumption, self-reported environmental attitudes, and socioeconomic characteristics of the households. The results showed four significant household groups, where smaller families located in urban areas containing at least one homemaker and equipped with water efficient devices are more likely to present the best pro-environmental attitudes and behaviors related to water use and recycling habits. Furthermore, we found that providing better information in terms of water billing and the environmental impact of human behavior also fosters environmentally friendly habits

PENGEMBANGAN MODEL PEMBELAJARAN EVALUASI PENDIDIKAN DAN AUTENTIK ASSESMEN BERBASIS KEBUN SEKOLAH UNTUK MENGEMBANGKAN KEMAMPUAN BERPIKIR KRITIS DAN KARAKTER MAHASISWA PGSD

Global climate change is expected to have major effects on host-parasite dynamics, with potentially enormous consequences for entire ecosystems. To develop an accurate prognostic framework, theoretical models must be supported by empirical research. We investigated potential changes in host-parasite dynamics between a fish parasite, the eyefluke Diplostomum baeri, and an intermediate host, the European perch Perca fluviatilis, in a large-scale semi-enclosed area in the Baltic Sea, the Biotest Lake, which since 1980 receives heated water from a nuclear power plant. Two sample screenings, in two consecutive years, showed that fish from the warmer Biotest Lake were now less parasitized than fish from the Baltic Sea. These results are contrasting previous screenings performed six years after the temperature change, which showed the inverse situation. An experimental infection, by which perch from both populations were exposed to D. baeri from the Baltic Sea, revealed that perch from the Baltic Sea were successfully infected, while Biotest fish were not. These findings suggest that the elevated temperature may have resulted, among other outcomes, in an extremely rapid evolutionary change through which fish from the experimental Biotest Lake have gained resistance to the parasite. Our results confirm the need to account for both rapid evolutionary adaptation and biotic interactions in predictive models, and highlight the importance of empirical research in order to validate future projections

Precision Spectroscopy of Fast, Hot Exotic Isotopes Using Machine Learning Assisted Event-by-Event Doppler Correction

We propose an experimental scheme for performing sensitive, high-precision laser spectroscopy studies on fast exotic isotopes. By inducing a step-wise resonant ionization of the atoms travelling inside an electric field and subsequently detecting the ion and the corresponding electron, time- and position-sensitive measurements of the resulting particles can be performed. Using a Mixture Density Network (MDN), we can leverage this information to predict the initial energy of individual atoms and thus apply a Doppler correction of the observed transition frequencies on an event-by-event basis. We conduct numerical simulations of the proposed experimental scheme and show that kHz-level uncertainties can be achieved for ion beams produced at extreme temperatures ($> 10^8$ K), with energy spreads as large as $10$ keV and non-uniform velocity distributions. The ability to perform in-flight spectroscopy, directly on highly energetic beams, offers unique opportunities to studying short-lived isotopes with lifetimes in the millisecond range and below, produced in low quantities, in hot and highly contaminated environments, without the need for cooling techniques. Such species are of marked interest for nuclear structure, astrophysics, and new physics searches

Ergonomic work analysis application in a small shoe business

This paper aims to presentthe results after conducting an Ergonomic Work Analysis (EWA) in a smallbusiness located in Porto Alegre. The ergonomic intervention was performed basedon Guérin et al. (2001) and aimed to analyze the process organization and thelayout of the shoemaker workstations to provide improvements to these areas.The starting point was the account of the small shoe business owner’s need hadto hire one more shoemaker without increasing the company physical space. The EWAwas used focusing the work organization, how the flow of information ran fromthe entry of an order to the final stage of the product repairing. Thediagnosis showed the company main problems were related to the shop assistantsdependence on the shoemakers to provide budget information and delivery time tocustomers and the layout organization. Among the results, a temporal analysisof two company recurrent tasks was performed in order to ascertain possiblelosses related to the displacement and the search for material. A new layoutscheme was also proposed, aiming to organize the work stations, making easierthe stock, tools and equipment removal, providing a free space to make possiblethe hiring of the new shoemakers within the current company boundaries

Vulnerability of Smart Grid-enabled Protection Relays to IEMI

The electricity sector has been undergoing transformations towards the smart grid concept, which aims to improve the robustness, efficiency, and flexibility of the power system. This transition has been achieved by the introduction of smart electronic devices (SEDs) and advanced automatic control and communication systems. Despite the benefits of such modernization, safety issues have emerged with significant concern by experts and entities worldwide. One of these issues is known as Intentional Electromagnetic Interference (IEMI), where offenders employ high-power electromagnetic sources to maliciously disrupt or damage electronic devices. One of the possible gateways for IEMI attacks targeting the smart grids is the microprocessor-based protection relays. On the one hand, the malfunctioning of these devices can lead to equipment damage, including high-voltage equipment (e.g., power transformers), which represent one of the most high-cost items of energy infrastructure. On the other hand, a possible misleading triggering of these devices could cause cascading effects along the various nodes of the power system, resulting in widespread blackouts. Thus, this study presents the possible recurring effects of IEMI exposure of a typical protection relay used in smart grid substations as part of the SCADA (Supervisory Control and Data Acquisition) system. For this purpose, a test setup containing a smart grid protective unit, a monitoring box, and the device's wiring harness is exposed to radiated IEMI threats with high-power narrowband signals using a TEM waveguide and horn antennas. The effects during the test campaigns are observed by means of an IEMI-hardened camera system and a software developed to real-time monitor the device's fibre optic communication link, which is established according to the IEC 60870-5-105 protocol. The results revealed failures ranging from display deviation to various types of protection relay shutdown. Moreover, the consequences of the identified failures in a power substation are discussed to feed into a risk analysis regarding the threat of IEMI to power infrastructures

IEMI Vulnerability Analysis for Different Smart Grid-enabled Devices

The smart grid concept aims to improve power systems’ robustness, efficiency, and reliability. The transition from conventional power grids to smart grids has been achieved mainly by integrating Smart Electronic Devices (SEDs) and advanced automatic control and communication systems. On the one hand, electronic devices have been integrated to make the system more decentralised from the national electrical grid. On the other hand, from the point of view of protection and control equipment, there is a growing tendency to replace arrays of analog devices with single digital units that perform multiple functions in a more integrated and efficient way. Despite the perceived benefits of such modernisation, security issues have arisen with substantial concern as electronic devices can be susceptible to Intentional Electromagnetic Interference (IEMI) [2]. The number of IEMI sources has grown significantly in recent decades. In 2014, 76 different types were reported, in which 21 sources were conducted, and 55 were irradiated. From a technical perspective, they can present different features, including band type, average / centre frequency, peak voltage (for conducted sources), or peak field (for irradiated sources) [4]. These sources also differ in technology level, associated cost, and mobility in approaching the target system. Therefore, they can be characterized by the easiness of occurrence in a given scenario and the increased probability of successful attacks on a target system. Under this perspective, a self-built jammer built with off-the-shelf components is more likely to be employed by an offender than a High-Power Electromagnetic (HPEM) source. On the other hand, despite being less probable on account of higher technological level, cost and mobility, a HPEM source may have a higher success rate to affect the target system than the self-built jammer. Coupled with this, based on the different characteristics of the IEMI sources, the electronic devices may present distinct effects, which may trigger severe impacts on a smart grid at a higher level [8]. Therefore, this study compares the IEMI vulnerability of three devices used in smart grid applications. The first device is a Wi-Fi-based smart home meter. It can read voltage and current signals of consumer units and remotely display real power, reactive power, and power factor. These measurements can be used in-house or transmitted to a Supervisory Control and Data Acquisition (SCADA) system from Distribution System Operators (DSOs). The second device is a Power Line Communication (PLC) unit, which enables data to be carried over conductors intended primarily for electrical power transmission. This technology is used in buildings to reduce the communication network’s material and installation costs and provide flexibility and faster data communication. The final device considered is a digital protection relay designed to trip circuit breakers when faults are detected. The latest digital relay units feature many protection functionalities, including overload and under-voltage/over-voltage protection, temperature monitoring, fault location, self-reclosure, among others. The three devices are subjected to self-built low-power jamming signals. As an extension, the protection relay is also subjected to a narrowband High Power Electromagnetic (HPEM) source

Integration of CLIP experiments of RNAbinding proteins: a novel approach to predict context-dependent splicing factors from transcriptomic data

Background: Splicing is a genetic process that has important implications in several diseases including cancer. Deciphering the complex rules of splicing regulation is crucial to understand and treat splicing-related diseases. Splicing factors and other RNA-binding proteins (RBPs) play a key role in the regulation of splicing. The specific binding sites of an RBP can be measured using CLIP experiments. However, to unveil which RBPs regulate a condition, it is necessary to have a priori hypotheses, as a single CLIP experiment targets a single protein. Results: In this work, we present a novel methodology to predict context-specific splicing factors from transcriptomic data. For this, we systematically collect, integrate and analyze more than 900 CLIP experiments stored in four CLIP databases: POSTAR2, CLIPdb, DoRiNA and StarBase. The analysis of these experiments shows the strong coherence between the binding sites of RBPs of similar families. Augmenting this information with expression changes, we are able to correctly predict the splicing factors that regulate splicing in two gold-standard experiments in which specific splicing factors are knocked-down. Conclusions: The methodology presented in this study allows the prediction of active splicing factors in either cancer or any other condition by only using the information of transcript expression. This approach opens a wide range of possible studies to understand the splicing regulation of different conditions. A tutorial with the source code and databases is available at https://gitlab.com/fcarazo.m/sfprediction