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1. Stroke classification using Virtual Hybrid Edge Detection from in silico electrical impedance tomography data

Author

Agnelli, Juan Pablo, Moura, Fernando S., Rautio, Siiri, Alsaker, Melody, Murthy, Rashmi, Lassas, Matti, and Siltanen, Samuli

Subjects
Mathematics - Analysis of PDEs, Computer Science - Computer Vision and Pattern Recognition, Mathematics - Numerical Analysis
Abstract

Electrical impedance tomography (EIT) is a non-invasive imaging method for recovering the internal conductivity of a physical body from electric boundary measurements. EIT combined with machine learning has shown promise for the classification of strokes. However, most previous works have used raw EIT voltage data as network inputs. We build upon a recent development which suggested the use of special noise-robust Virtual Hybrid Edge Detection (VHED) functions as network inputs, although that work used only highly simplified and mathematically ideal models. In this work we strengthen the case for the use of EIT, and VHED functions especially, for stroke classification. We design models with high detail and mathematical realism to test the use of VHED functions as inputs. Virtual patients are created using a physically detailed 2D head model which includes features known to create challenges in real-world imaging scenarios. Conductivity values are drawn from statistically realistic distributions, and phantoms are afflicted with either hemorrhagic or ischemic strokes of various shapes and sizes. Simulated noisy EIT electrode data, generated using the realistic Complete Electrode Model (CEM) as opposed to the mathematically ideal continuum model, is processed to obtain VHED functions. We compare the use of VHED functions as inputs against the alternative paradigm of using raw EIT voltages. Our results show that (i) stroke classification can be performed with high accuracy using 2D EIT data from physically detailed and mathematically realistic models, and (ii) in the presence of noise, VHED functions outperform raw data as network inputs., Comment: 21 pages, 5 figures

Published
2025

2. Splitting of nonequilibrium phase transitions in driven Ising models

Author

Forão, Gustavo A. L., Filho, Fernando S., Vieira, André P., Cleuren, Bart, Busiello, Daniel M., and Fiore, Carlos E.

Subjects
Condensed Matter - Statistical Mechanics, Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Other Condensed Matter, Condensed Matter - Soft Condensed Matter
Abstract

Spontaneous symmetry breaking occurs in various equilibrium and nonequilibrium systems, where phase transitions are typically marked by a single critical point that separates ordered and disordered regimes. We reveal a novel phenomenon in which the interplay between different temperatures and driving forces splits the order-disorder transition into two distinct transition points depending on which ordered state initially dominates. Crucially, these two emerging phases have distinct scaling behaviors and thermodynamic properties. To study this, we propose a minimal variant of the Ising model where spins are coupled to two thermal baths and subjected to two opposite driving forces associated to them. Our findings, robust both for all-to-all interactions (where exact solutions are possible) and nearest-neighbor couplings on a square lattice, uncover unique nonequilibrium behaviors and scaling laws for crucial thermodynamic quantities, such as efficiency, dissipation, power and its fluctuations, that are different between the two ordered phases. We also highlight that one of these emerging phases enables heat-engine operations that are less dissipative and show reduced fluctuations. In this setup, the system can also operate near maximum power and efficiency over a wide parameter range. Our results offer new insights into the relevance of phase transitions under nonequilibrium conditions., Comment: 5+6 pages, 4 figures

Published
2024

3. Studying the nature of the lightest charmed axial mesons via femtoscopy

Author

Abreu, Luciano M., Khemchandani, Kanchan P., Torres, Alberto Martínez, and Navarra, Fernando S.

Subjects
High Energy Physics - Phenomenology
Abstract

In this work we discuss how femtoscopic analysis can shed light on the nature of the two lightest axial charmed mesons, denominated as $D_1(2430)$ and $D_1(2420)$, whose masses are similar but widths are different. Their properties are reasonably described taking into account meson-meson coupled channel dynamics and a bare quark-model pole constituting the lowest-order amplitudes. Two different bare quark-model states are used in order to accommodate the different scattering lengths coming from the lattice QCD calculations for the $D\pi$ and $D^*\pi$ systems and the data from the ALICE Collaboration on the $D\pi$ system. The amplitudes are employed as inputs to determine the correlation functions for the $D^{*}\pi$ and $D\rho$ channels and identify the signatures associated with the lowest-lying axial charmed mesons., Comment: 6 pages; 2 figures; Proceedings of The 10th International Conference on Quarks and Nuclear Physics, (QNP 2024) Jul 8-12, 2024, Barcelona, Spain

Published
2024

4. Control, bi-stability and preference for chaos in time-dependent vaccination campaign

Author

Gabrick, Enrique C., Brugnago, Eduardo L., de Moraes, Ana L. R., Protachevicz, Paulo R., da Silva, Sidney T., Borges, Fernando S., Caldas, Iberê L., Batista, Antonio M., and Kurths, Jürgen

Subjects
Physics - Biological Physics, Nonlinear Sciences - Chaotic Dynamics
Abstract

In this work, effects of constant and time-dependent vaccination rates on the Susceptible-Exposed-Infected-Recovered-Susceptible (SEIRS) seasonal model are studied. Computing the Lyapunov exponent, we show that typical complex structures, such as shrimps, emerge for given combinations of constant vaccination rate and another model parameter. In some specific cases, the constant vaccination does not act as a chaotic suppressor and chaotic bands can exist for high levels of vaccination (e.g., $> 0.95$). Moreover, we obtain linear and non-linear relationships between one control parameter and constant vaccination to establish a disease-free solution. We also verify that the total infected number does not change whether the dynamics is chaotic or periodic. The introduction of a time-dependent vaccine is made by the inclusion of a periodic function with a defined amplitude and frequency. For this case, we investigate the effects of different amplitudes and frequencies on chaotic attractors, yielding low, medium, and high seasonality degrees of contacts. Depending on the parameters of the time-dependent vaccination function, chaotic structures can be controlled and become periodic structures. For a given set of parameters, these structures are accessed mostly via crisis and in some cases via period-doubling. After that, we investigate how the time-dependent vaccine acts in bi-stable dynamics when chaotic and periodic attractors coexist. We identify that this kind of vaccination acts as a control by destroying almost all the periodic basins. We explain this by the fact that chaotic attractors exhibit more desirable characteristics for epidemics than periodic ones in a bi-stable state.

Published
2024

5. Insights on Microservice Architecture Through the Eyes of Industry Practitioners

Author

Nogueira, Vinicius L., Felizardo, Fernando S., Amaral, Aline M. M. M., Assuncao, Wesley K. G., and Colanzi, Thelma E.

Subjects
Computer Science - Software Engineering
Abstract

The adoption of microservice architecture has seen a considerable upswing in recent years, mainly driven by the need to modernize legacy systems and address their limitations. Legacy systems, typically designed as monolithic applications, often struggle with maintenance, scalability, and deployment inefficiencies. This study investigates the motivations, activities, and challenges associated with migrating from monolithic legacy systems to microservices, aiming to shed light on common practices and challenges from a practitioner's point of view. We conducted a comprehensive study with 53 software practitioners who use microservices, expanding upon previous research by incorporating diverse international perspectives. Our mixed-methods approach includes quantitative and qualitative analyses, focusing on four main aspects: (i) the driving forces behind migration, (ii) the activities to conduct the migration, (iii) strategies for managing data consistency, and (iv) the prevalent challenges. Thus, our results reveal diverse practices and challenges practitioners face when migrating to microservices. Companies are interested in technical benefits, enhancing maintenance, scalability, and deployment processes. Testing in microservice environments remains complex, and extensive monitoring is crucial to managing the dynamic nature of microservices. Database management remains challenging. While most participants prefer decentralized databases for autonomy and scalability, challenges persist in ensuring data consistency. Additionally, many companies leverage modern cloud technologies to mitigate network overhead, showcasing the importance of cloud infrastructure in facilitating efficient microservice communication.

Published
2024

6. Remote Tube-based MPC for Tracking Over Lossy Networks

Author

Umsonst, David and Barbosa, Fernando S.

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

This paper addresses the problem of controlling constrained systems subject to disturbances in the case where controller and system are connected over a lossy network. To do so, we propose a novel framework that splits the concept of tube-based model predictive control into two parts. One runs locally on the system and is responsible for disturbance rejection, while the other runs remotely and provides optimal input trajectories that satisfy the system's state and input constraints. Key to our approach is the presence of a nominal model and an ancillary controller on the local system. Theoretical guarantees regarding the recursive feasibility and the tracking capabilities in the presence of disturbances and packet losses in both directions are provided. To test the efficacy of the proposed approach, we compare it to a state-of-the-art solution in the case of controlling a cartpole system. Extensive simulations are carried out with both linearized and nonlinear system dynamics, as well as different packet loss probabilities and disturbances. The code for this work is available at https://github.com/EricssonResearch/Robust-Tracking-MPC-over-Lossy-Networks, Comment: Accepted at the Conference on Decision and Control 2024, 8 pages, 6 figures

Published
2024

7. Genomics yields biological and phenotypic insights into bipolar disorder

Author

O’Connell, Kevin S., Koromina, Maria, van der Veen, Tracey, Boltz, Toni, David, Friederike S., Yang, Jessica Mei Kay, Lin, Keng-Han, Wang, Xin, Coleman, Jonathan R. I., Mitchell, Brittany L., McGrouther, Caroline C., Rangan, Aaditya V., Lind, Penelope A., Koch, Elise, Harder, Arvid, Parker, Nadine, Bendl, Jaroslav, Adorjan, Kristina, Agerbo, Esben, Albani, Diego, Alemany, Silvia, Alliey-Rodriguez, Ney, Als, Thomas D., Andlauer, Till F. M., Antoniou, Anastasia, Ask, Helga, Bass, Nicholas, Bauer, Michael, Beins, Eva C., Bigdeli, Tim B., Pedersen, Carsten Bøcker, Boks, Marco P., Børte, Sigrid, Bosch, Rosa, Brum, Murielle, Brumpton, Ben M., Brunkhorst-Kanaan, Nathalie, Budde, Monika, Bybjerg-Grauholm, Jonas, Byerley, William, Cabana-Domínguez, Judit, Cairns, Murray J., Carpiniello, Bernardo, Casas, Miquel, Cervantes, Pablo, Chatzinakos, Chris, Chen, Hsi-Chung, Clarence, Tereza, Clarke, Toni-Kim, Claus, Isabelle, Coombes, Brandon, Corfield, Elizabeth C., Cruceanu, Cristiana, Cuellar-Barboza, Alfredo, Czerski, Piotr M., Dafnas, Konstantinos, Dale, Anders M., Dalkner, Nina, Degenhardt, Franziska, DePaulo, J. Raymond, Djurovic, Srdjan, Drange, Ole Kristian, Escott-Price, Valentina, Fanous, Ayman H., Fellendorf, Frederike T., Ferrier, I. Nicol, Forty, Liz, Frank, Josef, Frei, Oleksandr, Freimer, Nelson B., Fullard, John F., Garnham, Julie, Gizer, Ian R., Gordon, Scott D., Gordon-Smith, Katherine, Greenwood, Tiffany A., Grove, Jakob, Guzman-Parra, José, Ha, Tae Hyon, Hahn, Tim, Haraldsson, Magnus, Hautzinger, Martin, Havdahl, Alexandra, Heilbronner, Urs, Hellgren, Dennis, Herms, Stefan, Hickie, Ian B., Hoffmann, Per, Holmans, Peter A., Huang, Ming-Chyi, Ikeda, Masashi, Jamain, Stéphane, Johnson, Jessica S., Jonsson, Lina, Kalman, Janos L., Kamatani, Yoichiro, Kennedy, James L., Kim, Euitae, Kim, Jaeyoung, Kittel-Schneider, Sarah, Knowles, James A., Kogevinas, Manolis, Kranz, Thorsten M., Krebs, Kristi, Kushner, Steven A., Lavebratt, Catharina, Lawrence, Jacob, Leber, Markus, Lee, Heon-Jeong, Liao, Calwing, Lucae, Susanne, Lundberg, Martin, MacIntyre, Donald J., Maier, Wolfgang, Maihofer, Adam X., Malaspina, Dolores, Manchia, Mirko, Maratou, Eirini, Martinsson, Lina, Mattheisen, Manuel, McGregor, Nathaniel W., McInnis, Melvin G., McKay, James D., Medeiros, Helena, Meyer-Lindenberg, Andreas, Millischer, Vincent, Morris, Derek W., Moutsatsou, Paraskevi, Mühleisen, Thomas W., O’Donovan, Claire, Olsen, Catherine M., Panagiotaropoulou, Georgia, Papiol, Sergi, Pardiñas, Antonio F., Park, Hye Youn, Perry, Amy, Pfennig, Andrea, Pisanu, Claudia, Potash, James B., Quested, Digby, Rapaport, Mark H., Regeer, Eline J., Rice, John P., Rivera, Margarita, Schulte, Eva C., Senner, Fanny, Shadrin, Alexey, Shilling, Paul D., Sigurdsson, Engilbert, Sindermann, Lisa, Sirignano, Lea, Siskind, Dan, Slaney, Claire, Sloofman, Laura G., Smeland, Olav B., Smith, Daniel J., Sobell, Janet L., Soler Artigas, Maria, Stein, Dan J., Stein, Frederike, Su, Mei-Hsin, Sung, Heejong, Świątkowska, Beata, Terao, Chikashi, Tesfaye, Markos, Tesli, Martin, Thorgeirsson, Thorgeir E., Thorp, Jackson G., Toma, Claudio, Tondo, Leonardo, Tooney, Paul A., Tsai, Shih-Jen, Tsermpini, Evangelia Eirini, Vawter, Marquis P., Vedder, Helmut, Vreeker, Annabel, Walters, James T. R., Winsvold, Bendik S., Witt, Stephanie H., Won, Hong-Hee, Ye, Robert, Young, Allan H., Zandi, Peter P., Zillich, Lea, Adolfsson, Rolf, Alda, Martin, Alfredsson, Lars, Backlund, Lena, Baune, Bernhard T., Bellivier, Frank, Bengesser, Susanne, Berrettini, Wade H., Biernacka, Joanna M., Boehnke, Michael, Børglum, Anders D., Breen, Gerome, Carr, Vaughan J., Catts, Stanley, Cichon, Sven, Corvin, Aiden, Craddock, Nicholas, Dannlowski, Udo, Dikeos, Dimitris, Etain, Bruno, Ferentinos, Panagiotis, Frye, Mark, Fullerton, Janice M., Gawlik, Micha, Gershon, Elliot S., Goes, Fernando S., Green, Melissa J., Grigoroiu-Serbanescu, Maria, Hauser, Joanna, Henskens, Frans A., Hjerling-Leffler, Jens, Hougaard, David M., Hveem, Kristian, Iwata, Nakao, Jones, Ian, Jones, Lisa A., Kahn, René S., Kelsoe, John R., Kircher, Tilo, Kirov, George, Kuo, Po-Hsiu, Landén, Mikael, Leboyer, Marion, Li, Qingqin S., Lissowska, Jolanta, Lochner, Christine, Loughland, Carmel, Luykx, Jurjen J., Martin, Nicholas G., Mathews, Carol A., Mayoral, Fermin, McElroy, Susan L., McIntosh, Andrew M., McMahon, Francis J., Medland, Sarah E., Melle, Ingrid, Milani, Lili, Mitchell, Philip B., Morken, Gunnar, Mors, Ole, Mortensen, Preben Bo, Müller-Myhsok, Bertram, Myers, Richard M., Myung, Woojae, Neale, Benjamin M., Nievergelt, Caroline M., Nordentoft, Merete, Nöthen, Markus M., Nurnberger, John I., O’Donovan, Michael C., Oedegaard, Ketil J., Olsson, Tomas, Owen, Michael J., Paciga, Sara A., Pantelis, Christos, Pato, Carlos N., Pato, Michele T., Patrinos, George P., Pawlak, Joanna M., Ramos-Quiroga, Josep Antoni, Reif, Andreas, Reininghaus, Eva Z., Ribasés, Marta, Rietschel, Marcella, Ripke, Stephan, Rouleau, Guy A., Roussos, Panos, Saito, Takeo, Schall, Ulrich, Schalling, Martin, Schofield, Peter R., Schulze, Thomas G., Scott, Laura J., Scott, Rodney J., Serretti, Alessandro, Smoller, Jordan W., Squassina, Alessio, Stahl, Eli A., Stefansson, Hreinn, Stefansson, Kari, Stordal, Eystein, Streit, Fabian, Sullivan, Patrick F., Turecki, Gustavo, Vaaler, Arne E., Vieta, Eduard, Vincent, John B., Waldman, Irwin D., Weickert, Cynthia S., Weickert, Thomas W., Werge, Thomas, Whiteman, David C., Zwart, John-Anker, Edenberg, Howard J., McQuillin, Andrew, Forstner, Andreas J., Mullins, Niamh, Di Florio, Arianna, Ophoff, Roel A., and Andreassen, Ole A.

Published
2025
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8. Thermodynamics of underdamped Brownian collisional engines: New insights and resonant phenomena

Author

Forão, Gustavo A. L., Filho, Fernando S., Akasaki, Bruno A. N., and Fiore, Carlos E.

Subjects
Condensed Matter - Statistical Mechanics, Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Other Condensed Matter, Condensed Matter - Soft Condensed Matter
Abstract

Collisional Brownian engines have been proposed as alternatives for nonequilibrium nanoscale engines. However, most studies have focused on the simpler overdamped case, leaving the role of inertia much less explored. In this work, we introduce the idea of collisional engines to underdamped Brownian particles, where each stage is sequentially subjected to a distinct driving force. A careful comparison between the performance of underdamped and overdamped Brownian work-to-work engines has been undertaken. The results show that underdamped Brownian engines generally outperform their overdamped counterparts. A key difference is the presence of a resonant regime in underdamped engines, in which both efficiency and power output are enhanced across a broad set of parameters. Our study highlights the importance of carefully selecting dynamics and driving protocols to achieve optimal engine performance., Comment: Comments are welcome

Published
2024

10. MPC-CBF with Adaptive Safety Margins for Safety-critical Teleoperation over Imperfect Network Connections

Author

Periotto, Riccardo, Ferizbegovic, Mina, Barbosa, Fernando S., and Sundin, Roberto C.

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

The paper focuses on the design of a control strategy for safety-critical remote teleoperation. The main goal is to make the controlled system track the desired velocity specified by an operator while avoiding obstacles despite communication delays. Control Barrier Functions (CBFs) are used to define the safety constraints that the system has to respect to avoid obstacles, while Model Predictive Control (MPC) provides the framework for adjusting the desired input, taking the constraints into account. The resulting input is sent to the remote system, where appropriate low-level velocity controllers translate it into system-specific commands. The main novelty of the paper is a method to make the CBFs robust against the uncertainties caused by the network delays affecting the system's state and do so in a less conservative manner. The results show how the proposed method successfully solves the safety-critical teleoperation problem, making the controlled systems avoid obstacles with different types of network delay. The controller has also been tested in simulation and on a real manipulator, demonstrating its general applicability when reliable low-level velocity controllers are available., Comment: Accepted for publication in the 2024 European Control Conference (ECC)

Published
2024
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11. Spiral wave dynamics in a neuronal network model

Author

Souza, Diogo L. M., Borges, Fernando S., Gabrick, Enrique C., Bentivoglio, Lucas E., Protachevicz, Paulo R., Santos, Vagner dos, Viana, Ricardo L., Caldas, Ibere L., Iarosz, Kelly C., Batista, Antonio M., and Kurths, Jürgen

Subjects
Physics - Biological Physics, Physics - Medical Physics, Quantitative Biology - Neurons and Cognition
Abstract

Spiral waves are spatial-temporal patterns that can emerge in different systems as heart tissues, chemical oscillators, ecological networks and the brain. These waves have been identified in the neocortex of turtles, rats, and humans, particularly during sleep-like states. Although their functions in cognitive activities remain until now poorly understood, these patterns are related to cortical activity modulation and contribute to cortical processing. In this work, we construct a neuronal network layer based on the spatial distribution of pyramidal neurons. Our main goal is to investigate how local connectivity and coupling strength are associated with the emergence of spiral waves. Therefore, we propose a trustworthy method capable of detecting different wave patterns, based on local and global phase order parameters. As a result, we find that the range of connection radius (R) plays a crucial role in the appearance of spiral waves. For R < 20 {\mu}m, only asynchronous activity is observed due to small number of connections. The coupling strength (gsyn ) greatly influences the pattern transitions for higher R, where spikes and bursts firing patterns can be observed in spiral and non-spiral waves. Finally, we show that for some values of R and gsyn bistable states of wave patterns are obtained.

Published
2024

12. Adaptive Exponential Integrate-and-Fire Model with Fractal Extension

Author

Souza, Diogo L. M., Gabrick, Enrique C., Protachevicz, Paulo R., Borges, Fernando S., Trobia, José, Iarosz, Kelly C., Batista, Antonio M., Caldas, Iberê L., and Lenzi, Ervin K.

Subjects
Physics - Biological Physics, Nonlinear Sciences - Adaptation and Self-Organizing Systems
Abstract

The description of neuronal activity has been of great importance in neuroscience. In this field, mathematical models are useful to describe the electrophysical behaviour of neurons. One successful model used for this purpose is the Adaptive Exponential Integrate-and-Fire (Adex), which is composed of two ordinary differential equations. Usually, this model is considered in his standard formulation, i.e., with integer order derivatives. In this work, we propose and study the fractal extension of Adex model, which in simple terms corresponds to replacing the integer derivative by non-integer. As non-integer operators, we choose the fractal derivatives. We explore the effects of equal and different orders of fractal derivatives in the firing patterns and mean frequency of the neuron described by the Adex model. Previous results suggest that fractal derivatives can provide a more realistic representation due to the fact that the standard operators are generalized. Our findings show that the fractal order influences the inter-spike intervals and changes the mean firing frequency. In addition, the firing patterns depend not only on the neuronal parameters but also on the order of respective fractal operators. As our main conclusion, the fractal order below the unit value increases the influence of the adaptation mechanism in the spike firing patterns.

Published
2024
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13. Real-Time Line-Based Room Segmentation and Continuous Euclidean Distance Fields

Author

Warberg, Erik, Miksits, Adam, and Barbosa, Fernando S.

Subjects
Computer Science - Robotics
Abstract

Continuous maps representations, as opposed to traditional discrete ones such as grid maps, have been gaining traction in the research community. However, current approaches still suffer from high computation costs, making them unable to be used in large environments without sacrificing precision. In this paper, a scalable method building upon Gaussian Process-based Euclidean Distance Fields (GP-EDFs) is proposed. By leveraging structure inherent to indoor environments, namely walls and rooms, we achieve an accurate continuous map representation that is fast enough to be updated and used in real-time. This is possible thanks to a novel line-based room segmentation algorithm, enabling the creation of smaller local GP-EDFs for each room, which in turn also use line segments as its shape priors, thus representing the map more efficiently with fewer data points. We evaluate this method in simulation experiments, and make the code available open-source., Comment: Open-source code: https://github.com/EricssonResearch/Line-Based-Room-Segmentation-and-EDF

Published
2024

15. Cross-ancestry atlas of gene, isoform, and splicing regulation in the developing human brain

Author

Wen, Cindy, Margolis, Michael, Dai, Rujia, Zhang, Pan, Przytycki, Pawel F, Vo, Daniel D, Bhattacharya, Arjun, Matoba, Nana, Tang, Miao, Jiao, Chuan, Kim, Minsoo, Tsai, Ellen, Hoh, Celine, Aygün, Nil, Walker, Rebecca L, Chatzinakos, Christos, Clarke, Declan, Pratt, Henry, Peters, Mette A, Gerstein, Mark, Daskalakis, Nikolaos P, Weng, Zhiping, Jaffe, Andrew E, Kleinman, Joel E, Hyde, Thomas M, Weinberger, Daniel R, Bray, Nicholas J, Sestan, Nenad, Geschwind, Daniel H, Roeder, Kathryn, Gusev, Alexander, Pasaniuc, Bogdan, Stein, Jason L, Love, Michael I, Pollard, Katherine S, Liu, Chunyu, Gandal, Michael J, Akbarian, Schahram, Abyzov, Alexej, Ahituv, Nadav, Arasappan, Dhivya, Almagro Armenteros, Jose Juan, Beliveau, Brian J, Bendl, Jaroslav, Berretta, Sabina, Bharadwaj, Rahul A, Bicks, Lucy, Brennand, Kristen, Capauto, Davide, Champagne, Frances A, Chatterjee, Tanima, Chatzinakos, Chris, Chen, Yuhang, Chen, H Isaac, Cheng, Yuyan, Cheng, Lijun, Chess, Andrew, Chien, Jo-fan, Chu, Zhiyuan, Clement, Ashley, Collado-Torres, Leonardo, Cooper, Gregory M, Crawford, Gregory E, Davila-Velderrain, Jose, Deep-Soboslay, Amy, Deng, Chengyu, DiPietro, Christopher P, Dracheva, Stella, Drusinsky, Shiron, Duan, Ziheng, Duong, Duc, Dursun, Cagatay, Eagles, Nicholas J, Edelstein, Jonathan, Emani, Prashant S, Fullard, John F, Galani, Kiki, Galeev, Timur, Gaynor, Sophia, Girdhar, Kiran, Goes, Fernando S, Greenleaf, William, Grundman, Jennifer, Guo, Hanmin, Guo, Qiuyu, Gupta, Chirag, Hadas, Yoav, Hallmayer, Joachim, Han, Xikun, Haroutunian, Vahram, Hawken, Natalie, He, Chuan, Henry, Ella, Hicks, Stephanie C, Ho, Marcus, Ho, Li-Lun, Hoffman, Gabriel E, Huang, Yiling, Huuki-Myers, Louise A, and Hwang, Ahyeon

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Biological Psychology, Psychology, Mental Illness, Mental Health, Human Genome, Neurosciences, Brain Disorders, Mental health, Humans, Alternative Splicing, Atlases as Topic, Autism Spectrum Disorder, Brain, Gene Expression Regulation, Developmental, Gene Regulatory Networks, Genome-Wide Association Study, Protein Isoforms, Quantitative Trait Loci, Schizophrenia, Transcriptome, Mental Disorders, PsychENCODE Consortium†, PsychENCODE Consortium, General Science & Technology
Abstract

Neuropsychiatric genome-wide association studies (GWASs), including those for autism spectrum disorder and schizophrenia, show strong enrichment for regulatory elements in the developing brain. However, prioritizing risk genes and mechanisms is challenging without a unified regulatory atlas. Across 672 diverse developing human brains, we identified 15,752 genes harboring gene, isoform, and/or splicing quantitative trait loci, mapping 3739 to cellular contexts. Gene expression heritability drops during development, likely reflecting both increasing cellular heterogeneity and the intrinsic properties of neuronal maturation. Isoform-level regulation, particularly in the second trimester, mediated the largest proportion of GWAS heritability. Through colocalization, we prioritized mechanisms for about 60% of GWAS loci across five disorders, exceeding adult brain findings. Finally, we contextualized results within gene and isoform coexpression networks, revealing the comprehensive landscape of transcriptome regulation in development and disease.

Published
2024

16. Massively parallel characterization of regulatory elements in the developing human cortex

Author

Deng, Chengyu, Whalen, Sean, Steyert, Marilyn, Ziffra, Ryan, Przytycki, Pawel F, Inoue, Fumitaka, Pereira, Daniela A, Capauto, Davide, Norton, Scott, Vaccarino, Flora M, Pollen, Alex A, Nowakowski, Tomasz J, Ahituv, Nadav, Pollard, Katherine S, Akbarian, Schahram, Abyzov, Alexej, Arasappan, Dhivya, Almagro Armenteros, Jose Juan, Beliveau, Brian J, Bendl, Jaroslav, Berretta, Sabina, Bharadwaj, Rahul A, Bhattacharya, Arjun, Bicks, Lucy, Brennand, Kristen, Champagne, Frances A, Chatterjee, Tanima, Chatzinakos, Chris, Chen, Yuhang, Chen, H Isaac, Cheng, Yuyan, Cheng, Lijun, Chess, Andrew, Chien, Jo-fan, Chu, Zhiyuan, Clarke, Declan, Clement, Ashley, Collado-Torres, Leonardo, Cooper, Gregory M, Crawford, Gregory E, Dai, Rujia, Daskalakis, Nikolaos P, Davila-Velderrain, Jose, Deep-Soboslay, Amy, DiPietro, Christopher P, Dracheva, Stella, Drusinsky, Shiron, Duan, Ziheng, Duong, Duc, Dursun, Cagatay, Eagles, Nicholas J, Edelstein, Jonathan, Emani, Prashant S, Fullard, John F, Galani, Kiki, Galeev, Timur, Gandal, Michael J, Gaynor, Sophia, Gerstein, Mark, Geschwind, Daniel H, Girdhar, Kiran, Goes, Fernando S, Greenleaf, William, Grundman, Jennifer, Guo, Hanmin, Guo, Qiuyu, Gupta, Chirag, Hadas, Yoav, Hallmayer, Joachim, Han, Xikun, Haroutunian, Vahram, Hawken, Natalie, He, Chuan, Henry, Ella, Hicks, Stephanie C, Ho, Marcus, Ho, Li-Lun, Hoffman, Gabriel E, Huang, Yiling, Huuki-Myers, Louise A, Hwang, Ahyeon, Hyde, Thomas M, Iatrou, Artemis, Jajoo, Aarti, Jensen, Matthew, Jiang, Lihua, Jin, Peng, Jin, Ting, Jops, Connor, Jourdon, Alexandre, Kawaguchi, Riki, Kellis, Manolis, Khullar, Saniya, Kleinman, Joel E, Kleopoulos, Steven P, and Kozlenkov, Alex

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Biomedical and Clinical Sciences, Stem Cell Research - Embryonic - Human, Stem Cell Research, Human Genome, Genetics, Neurosciences, Underpinning research, Aetiology, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Neurological, Humans, Cerebral Cortex, Chromatin, Deep Learning, Enhancer Elements, Genetic, Gene Expression Regulation, Developmental, Neurogenesis, Neurons, Organoids, Regulatory Sequences, Nucleic Acid, Promoter Regions, Genetic, Regulatory Elements, Transcriptional, PsychENCODE Consortium‡, PsychENCODE Consortium, General Science & Technology
Abstract

Nucleotide changes in gene regulatory elements are important determinants of neuronal development and diseases. Using massively parallel reporter assays in primary human cells from mid-gestation cortex and cerebral organoids, we interrogated the cis-regulatory activity of 102,767 open chromatin regions, including thousands of sequences with cell type-specific accessibility and variants associated with brain gene regulation. In primary cells, we identified 46,802 active enhancer sequences and 164 variants that alter enhancer activity. Activity was comparable in organoids and primary cells, suggesting that organoids provide an adequate model for the developing cortex. Using deep learning we decoded the sequence basis and upstream regulators of enhancer activity. This work establishes a comprehensive catalog of functional gene regulatory elements and variants in human neuronal development.

Published
2024

17. The Human Phenotype Ontology in 2024: phenotypes around the world

Author

Gargano, Michael A, Matentzoglu, Nicolas, Coleman, Ben, Addo-Lartey, Eunice B, Anagnostopoulos, Anna V, Anderton, Joel, Avillach, Paul, Bagley, Anita M, Bakštein, Eduard, Balhoff, James P, Baynam, Gareth, Bello, Susan M, Berk, Michael, Bertram, Holli, Bishop, Somer, Blau, Hannah, Bodenstein, David F, Botas, Pablo, Boztug, Kaan, Čady, Jolana, Callahan, Tiffany J, Cameron, Rhiannon, Carbon, Seth J, Castellanos, Francisco, Caufield, J Harry, Chan, Lauren E, Chute, Christopher G, Cruz-Rojo, Jaime, Dahan-Oliel, Noémi, Davids, Jon R, de Dieuleveult, Maud, de Souza, Vinicius, de Vries, Bert BA, de Vries, Esther, DePaulo, J Raymond, Derfalvi, Beata, Dhombres, Ferdinand, Diaz-Byrd, Claudia, Dingemans, Alexander JM, Donadille, Bruno, Duyzend, Michael, Elfeky, Reem, Essaid, Shahim, Fabrizzi, Carolina, Fico, Giovanna, Firth, Helen V, Freudenberg-Hua, Yun, Fullerton, Janice M, Gabriel, Davera L, Gilmour, Kimberly, Giordano, Jessica, Goes, Fernando S, Moses, Rachel Gore, Green, Ian, Griese, Matthias, Groza, Tudor, Gu, Weihong, Guthrie, Julia, Gyori, Benjamin, Hamosh, Ada, Hanauer, Marc, Hanušová, Kateřina, He, Yongqun, Hegde, Harshad, Helbig, Ingo, Holasová, Kateřina, Hoyt, Charles Tapley, Huang, Shangzhi, Hurwitz, Eric, Jacobsen, Julius OB, Jiang, Xiaofeng, Joseph, Lisa, Keramatian, Kamyar, King, Bryan, Knoflach, Katrin, Koolen, David A, Kraus, Megan L, Kroll, Carlo, Kusters, Maaike, Ladewig, Markus S, Lagorce, David, Lai, Meng-Chuan, Lapunzina, Pablo, Laraway, Bryan, Lewis-Smith, David, Li, Xiarong, Lucano, Caterina, Majd, Marzieh, Marazita, Mary L, Martinez-Glez, Victor, McHenry, Toby H, McInnis, Melvin G, McMurry, Julie A, Mihulová, Michaela, Millett, Caitlin E, Mitchell, Philip B, Moslerová, Veronika, Narutomi, Kenji, Nematollahi, Shahrzad, and Nevado, Julian

Subjects
Biological Sciences, Genetics, Human Genome, Machine Learning and Artificial Intelligence, Networking and Information Technology R&D (NITRD), 4.1 Discovery and preclinical testing of markers and technologies, Generic health relevance, Good Health and Well Being, Humans, Biological Ontologies, Phenotype, Genomics, Algorithms, Rare Diseases, Environmental Sciences, Information and Computing Sciences, Developmental Biology, Biological sciences, Chemical sciences, Environmental sciences
Abstract

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs.

Published
2024

18. Focal adhesion is associated with lithium response in bipolar disorder: evidence from a network-based multi-omics analysis

Author

Niemsiri, Vipavee, Rosenthal, Sara Brin, Nievergelt, Caroline M, Maihofer, Adam X, Marchetto, Maria C, Santos, Renata, Shekhtman, Tatyana, Alliey-Rodriguez, Ney, Anand, Amit, Balaraman, Yokesh, Berrettini, Wade H, Bertram, Holli, Burdick, Katherine E, Calabrese, Joseph R, Calkin, Cynthia V, Conroy, Carla, Coryell, William H, DeModena, Anna, Eyler, Lisa T, Feeder, Scott, Fisher, Carrie, Frazier, Nicole, Frye, Mark A, Gao, Keming, Garnham, Julie, Gershon, Elliot S, Goes, Fernando S, Goto, Toyomi, Harrington, Gloria J, Jakobsen, Petter, Kamali, Masoud, Kelly, Marisa, Leckband, Susan G, Lohoff, Falk W, McCarthy, Michael J, McInnis, Melvin G, Craig, David, Millett, Caitlin E, Mondimore, Francis, Morken, Gunnar, Nurnberger, John I, Donovan, Claire O’, Øedegaard, Ketil J, Ryan, Kelly, Schinagle, Martha, Shilling, Paul D, Slaney, Claire, Stapp, Emma K, Stautland, Andrea, Tarwater, Bruce, Zandi, Peter P, Alda, Martin, Fisch, Kathleen M, Gage, Fred H, and Kelsoe, John R

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical and Health Psychology, Clinical Sciences, Psychology, Human Genome, Bipolar Disorder, Mental Health, Brain Disorders, Serious Mental Illness, Precision Medicine, Mental Illness, Genetics, Mental health, Humans, Lithium, Gene Regulatory Networks, Focal Adhesions, Transcriptome, Genome-Wide Association Study, Neurons, Induced Pluripotent Stem Cells, Pharmacogenetics, Antimanic Agents, Male, Female, Lithium Compounds, Gene Expression Profiling, Genomics, Multiomics, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Lithium (Li) is one of the most effective drugs for treating bipolar disorder (BD), however, there is presently no way to predict response to guide treatment. The aim of this study is to identify functional genes and pathways that distinguish BD Li responders (LR) from BD Li non-responders (NR). An initial Pharmacogenomics of Bipolar Disorder study (PGBD) GWAS of lithium response did not provide any significant results. As a result, we then employed network-based integrative analysis of transcriptomic and genomic data. In transcriptomic study of iPSC-derived neurons, 41 significantly differentially expressed (DE) genes were identified in LR vs NR regardless of lithium exposure. In the PGBD, post-GWAS gene prioritization using the GWA-boosting (GWAB) approach identified 1119 candidate genes. Following DE-derived network propagation, there was a highly significant overlap of genes between the top 500- and top 2000-proximal gene networks and the GWAB gene list (Phypergeometric = 1.28E-09 and 4.10E-18, respectively). Functional enrichment analyses of the top 500 proximal network genes identified focal adhesion and the extracellular matrix (ECM) as the most significant functions. Our findings suggest that the difference between LR and NR was a much greater effect than that of lithium. The direct impact of dysregulation of focal adhesion on axon guidance and neuronal circuits could underpin mechanisms of response to lithium, as well as underlying BD. It also highlights the power of integrative multi-omics analysis of transcriptomic and genomic profiling to gain molecular insights into lithium response in BD.

Published
2024

22. Personalized use of ketamine and esketamine for treatment-resistant depression

Author

Gustavo C. Medeiros, Isabella Demo, Fernando S. Goes, Carlos A. Zarate, and Todd D. Gould

Subjects
Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Abstract A large and disproportionate portion of the burden associated with major depressive disorder (MDD) is due to treatment-resistant depression (TRD). Intravenous (R,S)-ketamine (ketamine) and intranasal (S)-ketamine (esketamine) are rapid-acting antidepressants that can effectively treat TRD. However, there is variability in response to ketamine/esketamine, and a personalized approach to their use will increase success rates in the treatment of TRD. There is a growing literature on the precision use of ketamine in TRD, and the body of evidence on esketamine is still relatively small. The identification of reliable predictors of response to ketamine/esketamine that are easily translatable to clinical practice is urgently needed. Potential clinical predictors of a robust response to ketamine include a pre-treatment positive family history of alcohol use disorder and a pre-treatment positive history of clinically significant childhood trauma. Pre-treatment versus post-treatment increases in gamma power in frontoparietal brain regions, observed in electroencephalogram (EEG) studies, is a promising brain-based biomarker of response to ketamine, given its time of onset and general applicability. Blood-based biomarkers have shown limited usefulness, with small-effect increases in brain-derived neurotrophic factor (BDNF) being the most consistent indicator of ketamine response. The severity of treatment-emergent dissociative symptoms is typically not associated with a response either to ketamine or esketamine. Future studies should ensure that biomarkers and clinical variables are obtained in a similar manner across studies to allow appropriate comparison across trials and to reduce the signal-to-noise ratio. Most predictors of response to ketamine/esketamine have modest effect sizes; therefore, the use of multivariate predictive models will be needed.

Published
2024
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24. Exploring the genetics of lithium response in bipolar disorders

Author

Herrera-Rivero, Marisol, Adli, Mazda, Akiyama, Kazufumi, Akula, Nirmala, Amare, Azmeraw T., Ardau, Raffaella, Arias, Bárbara, Aubry, Jean-Michel, Backlund, Lena, Bellivier, Frank, Benabarre, Antonio, Bengesser, Susanne, Bhattacharjee, Abesh Kumar, Biernacka, Joanna M., Birner, Armin, Cearns, Micah, Cervantes, Pablo, Chen, Hsi-Chung, Chillotti, Caterina, Cichon, Sven, Clark, Scott R., Colom, Francesc, Cruceanu, Cristiana, Czerski, Piotr M., Dalkner, Nina, Degenhardt, Franziska, Del Zompo, Maria, DePaulo, J. Raymond, Etain, Bruno, Falkai, Peter, Ferensztajn-Rochowiak, Ewa, Forstner, Andreas J., Frank, Josef, Frisén, Louise, Frye, Mark A., Fullerton, Janice M., Gallo, Carla, Gard, Sébastien, Garnham, Julie S., Goes, Fernando S., Grigoroiu-Serbanescu, Maria, Grof, Paul, Hashimoto, Ryota, Hasler, Roland, Hauser, Joanna, Heilbronner, Urs, Herms, Stefan, Hoffmann, Per, Hou, Liping, Hsu, Yi-Hsiang, Jamain, Stephane, Jiménez, Esther, Kahn, Jean-Pierre, Kassem, Layla, Kato, Tadafumi, Kelsoe, John, Kittel-Schneider, Sarah, Kuo, Po-Hsiu, Kusumi, Ichiro, König, Barbara, Laje, Gonzalo, Landén, Mikael, Lavebratt, Catharina, Leboyer, Marion, Leckband, Susan G., Maj, Mario, Manchia, Mirko, Marie-Claire, Cynthia, Martinsson, Lina, McCarthy, Michael J., McElroy, Susan L., Millischer, Vincent, Mitjans, Marina, Mondimore, Francis M., Monteleone, Palmiero, Nievergelt, Caroline M., Novák, Tomas, Nöthen, Markus M., O’Donovan, Claire, Ozaki, Norio, Papiol, Sergi, Pfennig, Andrea, Pisanu, Claudia, Potash, James B., Reif, Andreas, Reininghaus, Eva, Richard-Lepouriel, Hélène, Roberts, Gloria, Rouleau, Guy A., Rybakowski, Janusz K., Schalling, Martin, Schofield, Peter R., Schubert, Klaus Oliver, Schulte, Eva C., Schweizer, Barbara W., Severino, Giovanni, Shekhtman, Tatyana, Shilling, Paul D., Shimoda, Katzutaka, Simhandl, Christian, Slaney, Claire M., Squassina, Alessio, Stamm, Thomas, Stopkova, Pavla, Streit, Fabian, Tekola-Ayele, Fasil, Thalamuthu, Anbupalam, Tortorella, Alfonso, Turecki, Gustavo, Veeh, Julia, Vieta, Eduard, Viswanath, Biju, Witt, Stephanie H., Zandi, Peter P., Alda, Martin, Bauer, Michael, McMahon, Francis J., Mitchell, Philip B., Rietschel, Marcella, Schulze, Thomas G., and Baune, Bernhard T.

Published
2024
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25. Lithium response in bipolar disorder is associated with focal adhesion and PI3K-Akt networks: a multi-omics replication study

Author

Ou, Anna H., Rosenthal, Sara B., Adli, Mazda, Akiyama, Kazufumi, Akula, Nirmala, Alda, Martin, Amare, Azmeraw T., Ardau, Raffaella, Arias, Bárbara, Aubry, Jean-Michel, Backlund, Lena, Bauer, Michael, Baune, Bernhard T., Bellivier, Frank, Benabarre, Antonio, Bengesser, Susanne, Bhattacharjee, Abesh Kumar, Biernacka, Joanna M., Cervantes, Pablo, Chen, Guo-Bo, Chen, Hsi-Chung, Chillotti, Caterina, Cichon, Sven, Clark, Scott R., Colom, Francesc, Cousins, David A., Cruceanu, Cristiana, Czerski, Piotr M., Dantas, Clarissa R., Dayer, Alexandre, Del Zompo, Maria, Degenhardt, Franziska, DePaulo, J. Raymond, Étain, Bruno, Falkai, Peter, Fellendorf, Frederike Tabea, Ferensztajn-Rochowiak, Ewa, Forstner, Andreas J., Frisén, Louise, Frye, Mark A., Fullerton, Janice M., Gard, Sébastien, Garnham, Julie S., Goes, Fernando S., Grigoroiu-Serbanescu, Maria, Grof, Paul, Gruber, Oliver, Hashimoto, Ryota, Hauser, Joanna, Heilbronner, Urs, Herms, Stefan, Hoffmann, Per, Hofmann, Andrea, Hou, Liping, Jamain, Stephane, Jiménez, Esther, Kahn, Jean-Pierre, Kassem, Layla, Kato, Tadafumi, Kittel-Schneider, Sarah, König, Barbara, Kuo, Po-Hsiu, Kusumi, Ichiro, Lackner, Nina, Laje, Gonzalo, Landén, Mikael, Lavebratt, Catharina, Leboyer, Marion, Leckband, Susan G., Jaramillo, Carlos A. López, MacQueen, Glenda, Maj, Mario, Manchia, Mirko, Marie-Claire, Cynthia, Martinsson, Lina, Mattheisen, Manuel, McCarthy, Michael J., McElroy, Susan L., McMahon, Francis J., Mitchell, Philip B., Mitjans, Marina, Mondimore, Francis M., Monteleone, Palmiero, Nievergelt, Caroline M., Nöthen, Markus M., Novák, Tomas, Ösby, Urban, Ozaki, Norio, Papiol, Sergi, Perlis, Roy H., Pisanu, Claudia, Potash, James B., Pfennig, Andrea, Reich-Erkelenz, Daniela, Reif, Andreas, Reininghaus, Eva Z., Rietschel, Marcella, Rouleau, Guy A., Rybakowski, Janusz K., Schalling, Martin, Schofield, Peter R., Schubert, K. Oliver, Schulze, Thomas G., Schweizer, Barbara W., Seemüller, Florian, Severino, Giovanni, Shekhtman, Tatyana, Shilling, Paul D., Shimoda, Kazutaka, Simhandl, Christian, Slaney, Claire M., Squassina, Alessio, Stamm, Thomas, Stopkova, Pavla, Tighe, Sarah K., Tortorella, Alfonso, Turecki, Gustavo, Vieta, Eduard, Volkert, Julia, Witt, Stephanie, Wray, Naomi R., Wright, Adam, Young, L. Trevor, Zandi, Peter P., and Kelsoe, John R.

Published
2024
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26. Powerful ordered collective heat engines

Author

Filho, Fernando S., Forão, Gustavo A. L., Busiello, D. M., Cleuren, B., and Fiore, Carlos E.

Subjects
Condensed Matter - Statistical Mechanics, Condensed Matter - Soft Condensed Matter, Nonlinear Sciences - Cellular Automata and Lattice Gases, Quantum Physics
Abstract

We introduce a class of stochastic engines in which the regime of units operating synchronously can boost the performance. Our approach encompasses a minimal setup composed of $N$ interacting units placed in contact with two thermal baths and subjected to a constant driving worksource. The interplay between unit synchronization and interaction leads to an efficiency at maximum power between the Carnot, $\eta_{c}$, and the Curzon-Ahlborn bound, $\eta_{CA}$. Moreover, these limits can be respectively saturated maximizing the efficiency, and by simultaneous optimization of power and efficiency. We show that the interplay between Ising-like interactions and a collective ordered regime is crucial to operate as a heat engine. The main system features are investigated by means of a linear analysis near equilibrium, and developing an effective discrete-state model that captures the effects of the synchronous phase. The present framework paves the way for the building of promising nonequilibrium thermal machines based on ordered structures., Comment: Improved main text and supplemental material. Some figures and new analysis were performed

Published
2023

29. Interpretability and accessibility of machine learning in selected food processing, agriculture and health applications

Author

Ranasinghe, N., Ramanan, A., Fernando, S., Hameed, P. N., Herath, D., Malepathirana, T., Suganthan, P., Niranjan, M., and Halgamuge, S.

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

Artificial Intelligence (AI) and its data-centric branch of machine learning (ML) have greatly evolved over the last few decades. However, as AI is used increasingly in real world use cases, the importance of the interpretability of and accessibility to AI systems have become major research areas. The lack of interpretability of ML based systems is a major hindrance to widespread adoption of these powerful algorithms. This is due to many reasons including ethical and regulatory concerns, which have resulted in poorer adoption of ML in some areas. The recent past has seen a surge in research on interpretable ML. Generally, designing a ML system requires good domain understanding combined with expert knowledge. New techniques are emerging to improve ML accessibility through automated model design. This paper provides a review of the work done to improve interpretability and accessibility of machine learning in the context of global problems while also being relevant to developing countries. We review work under multiple levels of interpretability including scientific and mathematical interpretation, statistical interpretation and partial semantic interpretation. This review includes applications in three areas, namely food processing, agriculture and health., Comment: published in the "Journal of the National Science Foundation of Sri Lanka, Volume 50"

Published
2022
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31. Sustainable Construction with Hemp—Toward Net Zero 2050

Author

Ekanayake, C., Mendis, P., Fernando, S., Sofi, M., di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Dissanayake, Ranjith, editor, Mendis, Priyan, editor, De Silva, Sudhira, editor, Fernando, Shiromal, editor, Konthesingha, Chaminda, editor, Attanayake, Upul, editor, and Gajanayake, Pradeep, editor

Published
2024
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32. 2D Time-Difference Electrical Impedance Tomography Image Reconstruction in a Head Model with Regularization by Denoising

Author

Beraldo, Roberto G., Ferreira, Leonardo A., Moura, Fernando S., Takahata, André K., Suyama, Ricardo, Magjarević, Ratko, Series Editor, Ładyżyński, Piotr, Associate Editor, Ibrahim, Fatimah, Associate Editor, Lackovic, Igor, Associate Editor, Rock, Emilio Sacristan, Associate Editor, Marques, Jefferson Luiz Brum, editor, Rodrigues, Cesar Ramos, editor, Suzuki, Daniela Ota Hisayasu, editor, Marino Neto, José, editor, and García Ojeda, Renato, editor

Published
2024
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33. 2D Electrical Impedance Tomography Brain Image Reconstruction Using Deep Image Prior

Author

Ferreira, Leonardo A., Beraldo, Roberto G., Suyama, Ricardo, Moura, Fernando S., Takahata, André K., Magjarević, Ratko, Series Editor, Ładyżyński, Piotr, Associate Editor, Ibrahim, Fatimah, Associate Editor, Lackovic, Igor, Associate Editor, Rock, Emilio Sacristan, Associate Editor, Marques, Jefferson Luiz Brum, editor, Rodrigues, Cesar Ramos, editor, Suzuki, Daniela Ota Hisayasu, editor, Marino Neto, José, editor, and García Ojeda, Renato, editor

Published
2024
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34. Reconstructing Electrical Impedance Tomography 3D Brain Images with Anatomical Atlas and Total Variation Priors

Author

Beraldo, Roberto G., Ferreira, Leonardo A., Moura, Fernando S., Takahata, André K., Suyama, Ricardo, Magjarević, Ratko, Series Editor, Ładyżyński, Piotr, Associate Editor, Ibrahim, Fatimah, Associate Editor, Lackovic, Igor, Associate Editor, Rock, Emilio Sacristan, Associate Editor, Marques, Jefferson Luiz Brum, editor, Rodrigues, Cesar Ramos, editor, Suzuki, Daniela Ota Hisayasu, editor, Marino Neto, José, editor, and García Ojeda, Renato, editor

Published
2024
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37. Trans-ancestry genome-wide study of depression identifies 697 associations implicating cell types and pharmacotherapies

Author

Adams, Mark J., Streit, Fabian, Meng, Xiangrui, Awasthi, Swapnil, Adey, Brett N., Choi, Karmel W., Chundru, V. Kartik, Coleman, Jonathan R.I., Ferwerda, Bart, Foo, Jerome C., Gerring, Zachary F., Giannakopoulou, Olga, Gupta, Priya, Hall, Alisha S.M., Harder, Arvid, Howard, David M., Hübel, Christopher, Kwong, Alex S.F., Levey, Daniel F., Mitchell, Brittany L., Ni, Guiyan, Ota, Vanessa K., Pain, Oliver, Pathak, Gita A., Schulte, Eva C., Shen, Xueyi, Thorp, Jackson G., Walker, Alicia, Yao, Shuyang, Zeng, Jian, Zvrskovec, Johan, Aarsland, Dag, Actkins, Ky'Era V., Adli, Mazda, Agerbo, Esben, Aichholzer, Mareike, Aiello, Allison, Air, Tracy M., Als, Thomas D., Andersson, Evelyn, Andlauer, Till F.M., Arolt, Volker, Ask, Helga, Bäckman, Julia, Badola, Sunita, Ballard, Clive, Banasik, Karina, Bass, Nicholas J., Beekman, Aartjan T.F., Belangero, Sintia, Bigdeli, Tim B., Binder, Elisabeth B., Bjerkeset, Ottar, Bjornsdottir, Gyda, Børte, Sigrid, Bränn, Emma, Braun, Alice, Brodersen, Thorsten, Brückl, Tanja M., Brunak, Søren, Bruun, Mie T., Burmeister, Margit, Buspavanich, Pichit, Bybjerg-Grauholm, Jonas, Byrne, Enda M., Cai, Jianwen, Campbell, Archie, Campbell, Megan L., Campos, Adrian I., Castelao, Enrique, Cervilla, Jorge, Chaumette, Boris, Chen, Chia-Yen, Chen, Hsi-Chung, Chen, Zhengming, Cichon, Sven, Colodro-Conde, Lucía, Corbett, Anne, Corfield, Elizabeth C., Couvy-Duchesne, Baptiste, Craddock, Nick, Dannlowski, Udo, Davies, Gail, de Geus, E.J.C., Deary, Ian J., Degenhardt, Franziska, Dehghan, Abbas, DePaulo, J. Raymond, Deuschle, Michael, Didriksen, Maria, Dinh, Khoa Manh, Direk, Nese, Djurovic, Srdjan, Docherty, Anna R., Domschke, Katharina, Dowsett, Joseph, Drange, Ole Kristian, Dunn, Erin C., Eaton, William, Einarsson, Gudmundur, Eley, Thalia C., Elsheikh, Samar S.M., Engelmann, Jan, Benros, Michael E., Erikstrup, Christian, Escott-Price, Valentina, Fabbri, Chiara, Fang, Yu, Finer, Sarah, Frank, Josef, Free, Robert C., Gallo, Linda, Gao, He, Gill, Michael, Gilles, Maria, Goes, Fernando S., Gordon, Scott Douglas, Grove, Jakob, Gudbjartsson, Daniel F., Gutierrez, Blanca, Hahn, Tim, Hall, Lynsey S., Hansen, Thomas F., Haraldsson, Magnus, Hartman, Catharina A., Havdahl, Alexandra, Hayward, Caroline, Heilmann-Heimbach, Stefanie, Herms, Stefan, Hickie, Ian B., Hjalgrim, Henrik, Hjerling-Leffler, Jens, Hoffmann, Per, Homuth, Georg, Horn, Carsten, Hottenga, Jouke-Jan, Hougaard, David M., Hovatta, Iiris, Huang, Qin Qin, Hucks, Donald, Huider, Floris, Hunt, Karen A., Ialongo, Nicholas S., Ising, Marcus, Isometsä, Erkki, Jansen, Rick, Jiang, Yunxuan, Jones, Ian, Jones, Lisa A., Jonsson, Lina, Kanai, Masahiro, Karlsson, Robert, Kasper, Siegfried, Kendler, Kenneth S., Kessler, Ronald C., Kloiber, Stefan, Knowles, James A., Koen, Nastassja, Kraft, Julia, Kranzler, Henry R., Krebs, Kristi, Kallak, Theodora Kunovac, Kutalik, Zoltán, Lahtela, Elisa, Lake, Marilyn, Larsen, Margit Hørup, Lenze, Eric J., Lewins, Melissa, Lewis, Glyn, Li, Liming, Lin, Bochao Danae, Lin, Kuang, Lind, Penelope A., Liu, Yu-Li, MacIntyre, Donald J., MacKinnon, Dean F., Maher, Brion S., Maier, Wolfgang, Marshe, Victoria S., Martinez-Levy, Gabriela A., Matsuda, Koichi, Mbarek, Hamdi, McGuffin, Peter, Medland, Sarah E., Meinert, Susanne, Mikkelsen, Christina, Mikkelsen, Susan, Milaneschi, Yuri, Millwood, Iona Y., Molina, Esther, Mondimore, Francis M., Mortensen, Preben Bo, Mulsant, Benoit H., Naamanka, Joonas, Najman, Jake M., Nauck, Matthias, Nenadić, Igor, Nielsen, Kasper R., Nolt, Ilja M., Nordentoft, Merete, Nöthen, Markus M., Nyegaard, Mette, O'Donovan, Michael C., Oddsson, Asmundur, Oliveira, Adrielle M., Olsen, Catherine M., Oskarsson, Hogni, Ostrowski, Sisse Rye, Owen, Michael J., Packer, Richard, Palviainen, Teemu, Pan, Pedro M., Pato, Carlos N., Pato, Michele T., Pedersen, Nancy L., Pedersen, Ole Birger, Peyrot, Wouter J., Potash, James B., Preisig, Martin, Preuss, Michael H., Quiroz, Jorge A., Renteria, Miguel E., Reynolds III, Charles F., Rice, John P., Sakaue, Saori, Santoro, Marcos L., Schoevers, Robert A., Schork, Andrew, Schulze, Thomas G., Send, Tabea S., Shi, Jianxin, Sigurdsson, Engilbert, Singh, Kritika, Sinnamon, Grant C.B., Sirignano, Lea, Smeland, Olav B., Smith, Daniel J., Sofer, Tamar, Sørensen, Erik, Srinivasan, Sundararajan, Stefansson, Hreinn, Stefansson, Kari, Straub, Peter, Su, Mei-Hsin, Tadic, André, Teismann, Henning, Teumer, Alexander, Thapar, Anita, Thomson, Pippa A., Thørner, Lise Wegner, Topaloudi, Apostolia, Tsai, Shih-Jen, Tzoulaki, Ioanna, Uhl, George, Uitterlinden, André G., Ullum, Henrik, Umbricht, Daniel, Ursano, Robert J., Van der Auwera, Sandra, van Hemert, Albert M., Veluchamy, Abirami, Viktorin, Alexander, Völzke, Henry, Walters, G. Bragi, Wang, Xiaotong, Wani, Agaz, Weissman, Myrna M., Wellmann, Jürgen, Whiteman, David C., Wildman, Derek, Willemsen, Gonneke, Williams, Alexander T., Winsvold, Bendik S., Witt, Stephanie H., Xiong, Ying, Zillich, Lea, Zwart, John-Anker, Twenty-Three and Me Research Team, China Kadoorie Biobank Collaborative Group, Estonian Biobank Research Team, Genes & Health Research Team, HUNT All-In Psychiatry, The BioBank Japan Project, VA Million Veteran Program, Andreassen, Ole A., Baune, Bernhard T., Berger, Klaus, Boomsma, Dorret I., Børglum, Anders D., Breen, Gerome, Cai, Na, Coon, Hilary, Copeland, William E., Creese, Byron, Cruz-Fuentes, Carlos S., Czamara, Darina, Davis, Lea K., Derks, Eske M., Domenici, Enrico, Elliott, Paul, Forstner, Andreas J., Gawlik, Micha, Gelernter, Joel, Grabe, Hans J., Hamilton, Steven P., Hveem, Kristian, John, Catherine, Kaprio, Jaakko, Kircher, Tilo, Krebs, Marie-Odile, Kuo, Po-Hsiu, Landén, Mikael, Lehto, Kelli, Levinson, Douglas F., Li, Qingqin S., Lieb, Klaus, Loos, Ruth J.F., Lu, Yi, Lucae, Susanne, Luykx, Jurjen J., Maes, Hermine H.M., Magnusson, Patrik K., Martin, Hilary C., Martin, Nicholas G., McQuillin, Andrew, Middeldorp, Christel M., Milani, Lili, Mors, Ole, Müller, Daniel J., Müller-Myhsok, Bertram, Okada, Yukinori, Oldehinkel, Albertine J., Paciga, Sara A., Palmer, Colin N.A., Paschou, Peristera, Penninx, Brenda W.J.H., Perlis, Roy H., Peterson, Roseann E., Pistis, Giorgio, Polimanti, Renato, Porteous, David J., Posthuma, Danielle, Rabinowitz, Jill A., Reichborn-Kjennerud, Ted, Reif, Andreas, Rice, Frances, Ricken, Roland, Rietschel, Marcella, Rivera, Margarita, Rück, Christian, Salum, Giovanni A., Schaefer, Catherine, Sen, Srijan, Serretti, Alessandro, Skalkidou, Alkistis, Smoller, Jordan W., Stein, Dan J., Stein, Frederike, Stein, Murray B., Sullivan, Patrick F., Tesli, Martin, Thorgeirsson, Thorgeir E., Tiemeier, Henning, Timpson, Nicholas J., Uddin, Monica, Uher, Rudolf, van Heel, David A., Verweij, Karin J.H., Walters, Robin G., Wassertheil-Smoller, Sylvia, Wendland, Jens R., Werge, Thomas, Zwinderman, Aeilko H., Kuchenbaecker, Karoline, Wray, Naomi R., Ripke, Stephan, Lewis, Cathryn M., and McIntosh, Andrew M.

Published
2025
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39. Reproductive, gestational, and fetal alterations induced by dietary mycotoxins: A systematic review

Author

Pablo O. Silva, Leandra N.Z. Ramalho, Carlos A.F. Oliveira, and Fernando S. Ramalho

Subjects
Mycotoxin-induced gestational alterations, mycotoxin-induced fetal alterations, mycotoxin-induced reproductive alterations, deoxynivalenol, fumonisins, ochratoxin A, patulin, T-2 toxin, zearalenone, Veterinary medicine, SF600-1100
Abstract

ABSTRACT: Mycotoxins are low molecular weight secondary metabolites produced by some fungi genera, such as Aspergillus, Penicillium, Alternaria, Fusarium, and Claviceps, during their growth in foods. These molecules share several common characteristics, including toxicity, carcinogenesis, and teratogenesis in animals and humans. This review addresses the reproductive, gestational and fetal changes induced by ochratoxin A, fumonisins, zearalenone, patulin, deoxynivalenol, and T-2 toxin. A systematic evaluation of scientific articles was conducted on research portals PubMed and Google Scholar using keywords related to the topic. The research articles revealed all the characteristics of toxicity, carcinogenesis, and teratogenesis available in the literature, indicating a growing academic and scientific concern in the deposition of information about these mycotoxins.

Published
2024
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44. Thermodynamics and efficiency of sequentially collisional Brownian particles: The role of drivings

Author

Filho, Fernando S., Akasaki, Bruno A. N., Noa, Carlos E. Fernadéz, Cleuren, Bart, and Fiore, Carlos E.

Subjects
Condensed Matter - Statistical Mechanics, Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Other Condensed Matter
Abstract

Brownian particles placed sequentially in contact with distinct thermal reservoirs and subjected to external driving forces are promising candidates for the construction of reliable thermal engines. In this contribution, we address the role of driving forces for enhancing the machine performance. Analytical expressions for thermodynamic quantities such as power output and efficiency are obtained for general driving schemes. A proper choice of these driving schemes substantially increases both power output and efficiency and extends the working regime. Maximizations of power and efficiency, whether with respect to the strength of the force, driving scheme or both have been considered and exemplified for two kind of drivings: a generic power-law and a periodically drivings.

Published
2022

45. Multiplicity of the doubly charmed state $T_{cc} ^+$ in heavy-ion collisions

Author

Abreu, Luciano M., Navarra, Fernando S., and Vieira, Hildeson P. L.

Subjects
High Energy Physics - Phenomenology
Abstract

We study the evolution of the doubly charmed state $T_{cc}^+$ in a hot hadron gas produced in the late stage of heavy-ion collisions. We use effective Lagrangians to calculate the thermally averaged cross sections of $T_{cc}^+$ production in reactions such as $ D^{(*)} D^{(*)} \rightarrow T_{cc}^+ \pi, T_{cc}^+ \rho $ and its absorption in the corresponding inverse processes. We then solve the rate equation to follow the time evolution of the $T_{cc}^+$ multiplicity, and determine how it is affected by the considered reactions during the expansion of the hadronic matter. We compare the evolution of the $T_{cc}^+$ abundance treated as a hadronic $S$-wave molecule and as a tetraquark state. Our results show that the tetraquark yield increases by a factor of about 2 at freeze-out, but it is still one order of magnitude smaller than the final yield of molecules formed from hadron coalescence. Also, the results indicate that $N_{T_{cc}}$ is more affected by interactions with hadronic medium than $ N_{X(3872)} $ in similar conditions. We also show that yields depend very weakly on the system size, represented by $\mathcal{N} = \left[ d N_{ch} / d \eta (\eta < 0.5)\right]^{1/3}$., Comment: 10 pages; 6 figures; v2: added a new Section (Section IV) with a comprehensive study of the influence of the system size, represented by the density of charged particles measured at midrapidity $\mathcal{N} = \left[ d N_{ch} / d \eta (\eta < 0.5)\right]$, on the results

Published
2022
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