Miracle-dz/UniFAR-FTUs huggingface dataset:
Bonkers Borders - A Serious AR Game of Boundaries Unfitting and Consequences Unwitting

Bonkers Borders is a serious Augmented Reality (AR) game that depicts a territorial struggle between rival imperial factions to lay claim to a newly discovered fictional continent. The project aims to be a satirical simulation of the detached imperialist approaches when carving up land borders on maps. The goal is to create a people-centric territory control game inspired by real-world events that could also be used to broaden the fields of serious and hybrid games, by providing an engaging and immersive experience with pedagogical, ludological, and technological relevance. The project takes the form of a hybrid physical-digital game that allows players to shape the game world through actions and objectively view the consequences of their decisions through a companion app. The implementation of this hybrid game was evaluated by players, with findings indicating significant interest in the potential for technology in tabletop games. The key aspects of such an application include computation, hidden information management, and immersion in the form of AR to realize a stationary 2D world in 3D. These findings also bode well for the nascent field of hybrid games.
Mice Mutated in the Third Fibronectin Domain of L1 Show Enhanced Hippocampal Neuronal Cell Death, Astrogliosis and Alterations in Behavior

Adhesion molecules play major roles in cell proliferation, migration, survival, neurite outgrowth and synapse formation during nervous system development and in adulthood. The neural cell adhesion molecule L1 contributes to these functions during development and in synapse formation and synaptic plasticity after trauma in adulthood. Mutations of L1 in humans result in L1 syndrome, which is associated with mild-to-severe brain malformations and mental disabilities. Furthermore, mutations in the extracellular domain were shown to cause a severe phenotype more often than mutations in the intracellular domain. To explore the outcome of a mutation in the extracellular domain, we generated mice with disruption of the dibasic sequences RK and KR that localize to position 858RKHSKR863 in the third fibronectin type III domain of murine L1. These mice exhibit alterations in exploratory behavior and enhanced marble burying activity. Mutant mice display higher numbers of caspase 3-positive neurons, a reduced number of principle neurons in the hippocampus, and an enhanced number of glial cells. Experiments suggest that disruption of the dibasic sequence in L1 results in subtle impairments in brain structure and functions leading to obsessive-like behavior in males and reduced anxiety in females.
Dimensionality of Upper Elementary Mathematics Instruction: Exploring Factors across Two Observational Instruments.

Authors and Affiliations: Andrew Bacher-Hicks, Harvard Kennedy School of Government (abacherhicks@g.harvard.edu) David Blazar, Harvard Graduate School of Education (dlb239@mail.harvard.edu) David Braslow, Harvard Graduate School of Education (dab736@mail.harvard.edu) Charalambos Y. Charalambous, University of Cyprus (charalambous.y.charalambos1@ucy.ac.cy) Mark Chin, Harvard Graduate School of Education (mark_chin@gse.harvard.edu) Dan Goldhaber, CALDER, American Institutes for Research (dgoldhab@u.washington.edu) Thomas J. Kane, Harvard Graduate School of Education (tom_kane@gse.harvard.edu) Douglas O. Staiger, Dartmouth College (douglas.o.staiger@dartmouth.edu)
Cooperative Adaptive PID-Like Voltage Regulation in Inverter-Based Islanded Microgrids Under Unknown Uncertainties

As modern distributed generators (DGs) always involve heterogeneous and unknown disturbances, a lack of accurate knowledge about the entire microgrid (MG) dynamics arises. Hence, an appropriate secondary control strategy is helpful to improve the voltage regulation process in an uncertain and unknown environment. To this aim, in this article, we suggest a novel distributed adaptive proportional–integral–derivative (PID)-like controller able to counteract unknown uncertainties arising from external disturbances and parameter mismatches, as well as unavoidable deviations induced by primary droop control while recovering the desired voltage reference value. By leveraging Lyapunov theory, an adaptive mechanism is provided to adjust control parameters for dealing with different operating conditions. The stability of the entire MG, analytically derived by also exploiting the Barbalat lemma, proves that all DGs within the electrical grid track the reference signal despite the presence of unknown uncertainties, with bounded adaptive control gains in steady-state phases. A detailed simulation analysis confirms the theoretical derivation and the effectiveness of the proposed controller in ensuring the voltage restoration in different troublesome scenarios, where both reference/loads variations and plug-and-play phenomena occur.
Wind comfort and emotion can be changed by the cross-modal presentation of audio-visual stimuli of indoor and outdoor environments

The development of methods to simulate the sensation of wind that can promote relaxation and elicit positive emotional responses has become a topic of interest with the widespread adoption of virtual and augmented reality systems. Previous studies have simulated natural wind by varying wind speed in a controlled environment or moving a large flow of air through an area. In contrast to such approaches to modulate physical airflow, the use of multisensory stimuli to alter the impression and sense of comfort provided by a simulated wind has rarely been considered in previous research. If visual and auditory stimuli affect wind comfort, a multisensory design should be considered for relaxation systems that use wind effects. Therefore, we experimentally measured wind comfort and associated emotions when participants experienced outdoor and indoor virtual environments through immersive virtual reality to investigate whether cross-modal effects of variations in audio-visual stimuli would impact the relaxation effects associated with a virtual wind. The results show that the virtual environment of an outdoor meadow and the sound of natural wind significantly improved users' subjective experience of comfort and openness associated with the wind, as well as their emotional state. Simulated natural wind reduced mental stress compared to a condition without wind, as shown by questionnaires and biometric data. The results of this study indicate that multisensory stimuli conveying natural impressions and simulated natural wind are effective for wind-based relaxation.
Advantages and Disadvantages of Computational Dosimetry Strategies in the Low mmW Range: Comparison Between Multilayer Slab and Anthropomorphic Models

Wireless technologies spanning at the higher bands of microwave range (i.e., Ka-band) are gaining increasing importance in everyday life. Most recent wireless power transfer (WPT) applications work in the microwave and millimeter wave (mmW) frequencies, overlapping with the new frequency bands of the fifth-generation (5G) mobile technology. The spread of such novel electromagnetic (EM) sources raised the need to investigate their possible effects on population’s health. Numerical dosimetry is fundamental to assess the exposure of the human body. In the range 24–28 GHz, i.e., the low-band spectrum of the mmW, and bridge between microwaves and mmW, there is poor consensus on the best strategy to model the human body. This article proposes a comparison between the two numerical methodologies typically adopted for this frequency range: the use of multilayer planar slabs and realistic anthropomorphic numerical models. The aim is to highlight the advantages and limits of each method, by comparing EM exposure results obtained on the Virtual Population (ViP) model Duke with several multilayer planar slabs. The differences between the two methods are non-negligible, suggesting the need of further studies and the necessity of improving both modeling approaches, depending on the frequency of work and the investigated application.
Empirical Validation of an Agent-Based Model of Emotion Contagion

In recent years, many agent-based models of human groups have implemented a mechanism of emotion contagion, yet empirical validation is lagging behind. The aim of the present paper is to validate an agent-based model of emotion contagion at the level of group emotion, by comparing simulations against the emotional development of real people in small groups. To study the effect of emotion contagion, the participants interacted via a video call, where they were virtually placed in different social environments while they played a quiz. This allowed the exchange of emotion among all, some or none of the participants. The patterns of emotional development in the empirical results supported our hypotheses based on literature of emotion contagion and social norms. Further, the simulations with the complete model resembled many of these patterns. When emotion contagion was disabled in the model, the resemblance decreased. These results give a first indication that emotion contagion occurs in groups that meet via video calls, and can in-part be predicted by the proposed model of emotion contagion. Yet, further study with a larger and more diverse empirical sample is needed, as well as comparisons across contagion mechanisms, to draw stronger conclusions and ultimately justify societal application.
AKAP1 Regulates Mitochondrial Dynamics during the Fatty-Acid-Promoted Maturation of Human-Induced Pluripotent Stem Cell-Derived Cardiomyocytes as Indicated by Proteomics Sequencing

Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are cells with promising applications. However, their immaturity has restricted their use in cell therapy, disease modeling, and other studies. Therefore, the current study focused on inducing the maturation of CMs. We supplemented hiPSC-CMs with fatty acids (FAs) to promote their phenotypic maturity. Proteomic sequencing was performed to identify regulators critical for promoting the maturation of hiPSC-CMs. AKAP1 was found to be significantly increased in FA-treated hiPSC-CMs, and the results were verified. Therefore, we inhibited AKAP1 expression in the FA-treated cells and analyzed the outcomes. FA supplementation promoted the morphological and functional maturation of the hiPSC-CMs, which was accompanied by the development of a mitochondrial network. Proteomic analysis results revealed that AKAP1 expression was significantly higher in FA-treated hiPSC-CMs than in control cells. In addition, increased phosphorylation of the mitochondrial dynamin Drp1 and an increased mitochondrial fusion rate were found in FA-treated hiPSC-CMs. After AKAP1 was knocked down, the level of DRP1 phosphorylation in the cell was decreased, and the mitochondrial fusion rate was reduced. FA supplementation effectively promoted the maturation of hiPSC-CMs, and in these cells, AKAP1 regulated mitochondrial dynamics, possibly playing a significant role.
A Study on Speaker Recognition Using Orthogonal Gaussian Mixture Models

This paper introduces the Orthogonal Gaussian mixture model (OGMM) and the application in the speaker recognition Standard GMM assumes diagonal covariance matrices, and needs a large number of mixture components to obtain good approximation which leads to greater training time. This paper proposes a modification to the standard diagonal GMM approach: feature vectors are first transformed to the space spanned by the eigenvectors of the covariance matrix before being applied to the diagonal GMM. An OGMM based speaker recognition experiments show that the performance is better than the standard GMM and has better prospects.
Expert System for Diagnosis Fever with Rash Diseases for Pediatric Age Group using Adaptive Neuro- Fuzzy Inference System

Fever accompanied by a skin rash is the most common disease of the pediatric age group. They are diverse and characterized by similar symptom, which makes it difficult to distinguish between them. This work presents an Adaptive Neuro-Fuzzy Inference System (ANFIS) to diagnoses five diseases (measles, rubella, infantile rosella, scarlet fever, and chickenpox). Dataset about symptoms and diagnosis were collected from specialized physicians then they were analyzed using the Chi-Square test to identify symptoms that play a significant role in the diagnosis process including shared symptoms like temperature, type of rash and its location. In addition, some several distinctive signs such as Koplik's spots, lymphadenopathy, tongue color and itching. This paper proposed a hybrid method between Mamdani's fuzzy inference controller and multi-layered neural network to overcome the drawbacks of using each technique alone and enhance the classification process. Finally, the model was validated using 250 real-world cases and the experimental results showed that the proposed system succeeded in detecting and recognizing diseases with high accuracy close to that of human diagnosis with an average accuracy of 95.50%. The results were compared with the accuracy obtained using the fuzzy logic technique separately and with the results of previous studies.
A Ka-Band 64-Element Deployable Active Phased-Array TX on a Flexible Hetero Segmented Liquid Crystal Polymer for Small Satellites

A $Ka$ -band 64-element deployable active phased-array transmitter (TX) on a hetero segment liquid crystal polymer (LCP) substrate for small satellites is proposed. The proposed phased-array TX achieved a large array size implementation and a small form factor with integrated six-layer and two-layer LCP substrates. Antenna and transmission line designs considering hetero layer structure are presented in detail. Achieving 46.7 dBm electronically isotropically radiated power (EIRP), the proposed phased-array TX can support 256-APSK DVB-S2X. As a result, the proposed deployable active phased-array TX successfully realizes low-launch cost with a 9.65 g lightweight and large antenna aperture size with superior EVM performance.
10-bit SAR ADC for Biomedical Sensor Applications

The need for battery powered wearable gadgets has risen dramatically as the healthcare system has progressed. Unfortunately, these bio-medical signals are analog in nature and needs to be transformed to digital form before further processing. In a bio-medical sensor system, the bio-medical signal is first given to an analog front-end to raise signal amplitude and pre-process it. Later, it is converted in digital form to make use of digital signal processors (DSPs) with the help of analog to digital converter (ADC). One of the main blocks of ADC is SAR logic which uses D flip flops for realization. In this paper, a new logic ("D Logic") has been proposed which reduces the number of transistors required to implement the SAR logic by 18.53%, as well as power dissipation. The 10-bit ADC has been designed in 90 nm CMOS process using Cadence Virtuoso. The overall power consumption of the proposed SAR ADC is 67.53 µW.
Accurate solution of structured linear systems via rank-revealing decompositions

Linear systems of equations Ax = b, where the matrix A has some particular structure, arise frequently in applications. Very often structured matrices have huge condition numbers κ(A) = ‖A−1‖‖A‖ and, therefore, standard algorithms fail to compute accurate solutions of Ax = b. We say in this paper that a computed solution x is accurate if ‖x− x‖/‖x‖ = O(u), being u the unit roundoff. In this work, we introduce a framework that allows to solve accurately many classes of structured linear systems, independently of the condition number of A and efficiently, that is, with cost O(n3). For most of these classes no algorithms are known that are both accurate and efficient. The approach in this work relies on computing first an accurate rank-revealing decomposition of A, an idea that has been widely used in the last decades to compute singular value and eigenvalue decompositions of structured matrices with high relative accuracy. In particular, we illustrate the new method solving accurately Cauchy and Vandermonde linear systems with any distribution of nodes, i.e., without requiring A to be totally positive, for most right-hand sides b.
Salinity Impacts the Functional mcrA and dsrA Gene Abundances in Everglades Marshes

Coastal wetlands, such as the Everglades, are increasingly being exposed to stressors that have the potential to modify their existing ecological processes because of global climate change. Their soil microbiomes include a population of organisms important for biogeochemical cycling, but continual stresses can disturb the community’s composition, causing functional changes. The Everglades feature wetlands with varied salinity levels, implying that they contain microbial communities with a variety of salt tolerances and microbial functions. Therefore, tracking the effects of stresses on these populations in freshwater and brackish marshes is critical. The study addressed this by utilizing next generation sequencing (NGS) to construct a baseline soil microbial community. The carbon and sulfur cycles were studied by sequencing a microbial functional gene involved in each process, the mcrA and dsrA functional genes, respectively. Saline was introduced over two years to observe the taxonomic alterations that occurred after a long-term disturbance such as seawater intrusion. It was observed that saltwater dosing increased sulfite reduction in freshwater peat soils and decreased methylotrophy in brackish peat soils. These findings add to the understanding of microbiomes by demonstrating how changes in soil qualities impact communities both before and after a disturbance such as saltwater intrusion.
Weighted generalised Procrustes analysis of diffusion tensors

Diffusion tensor imaging (DTI) is a specific MRI modality which provides a unique insight into tissue structure and organisation in vivo. In DTI, displacement of water molecules over time is modelled by a zero-mean trivariate Gaussian distribution (Alexander, 2005) with covariance matrix evolving linearly with time and determined by the diffusion tensor (DT), a 3 × 3 symmetric positive-definite matrix. DT inference from observed diffusion MRI data has been commonly carried out using least squares (Koay et al., 2006) and Bayesian (Behrens et al., 2007, Zhou et al., 2008) methods. At each location (voxel) of interest, the principal eigenvector of the tensor estimates the dominant fibre orientation whereas various tensor-derived diffusion anisotropy indices measure local anisotropy. White matter tractography attempts to integrate local estimates into brain connectivity maps which are of interest in neuroscience. In particular, DTI has been used to study stroke (Le Bihan et al., 2001) and a wide range of neurological disorders such as multiple sclerosis, Alzheimer’s and Parkinson’s disease, and schizophrenia (Lenglet et al., 2009).
Coastal Halophytes: Potent Source of Bioactive Molecules from Saline Environment

This study represents a comparative analysis of secondary metabolites content, antioxidant, and antimicrobial activity of 24 halophytes from coastal saline habitats of the Balkan Peninsula (Montenegro, Albania, and Greece). Total content of phenolics, flavonoids, tannins, anthocyanins, antioxidant, and antimicrobial activity was determined for dry methanolic (DME) and crude water extracts (CWE) and compared with well-known medicinal plants. The total phenolic content ranged from 13.23 to 376.08 mg of GA/g of DME, and from 33.68 to 511.10 mg/mL of CWE. The content of flavonoids ranged from 12.63 to 77.36 mg of RU/g of DME, and from 12.13 to 26.35 mg/mL of CWE. Total tannins and anthocyanins varied from 0.05 to 2.44 mg/mL, and from 1.31 to 39.81 µg/L, respectively. The antioxidant activity ranged from 1147.68 to 15.02 µg/mL for DME and from 1613.05 to 21.96 µg/mL for CWE. The best antioxidant properties, and the highest content of phenolic compounds, were determined for Polygonum maritimum and Limonium vulgare with values similar to or higher compared to the medicinal plants. Halophytes with significant antimicrobial potential were Limonium vulgare, L. angustifolium, and Artemisia maritima. Some of the analyzed coastal halophytes can be considered rich natural sources of phenolic compounds, with favorable antioxidative and antimicrobial properties.
Generation of Multipurpose Formal Models from Legacy Code

In this paper a method for generation of formal models from legacy systems code is proposed. The purpose of these models is to have a possibility of their application in different tasks such as automatic generation of executable tests, translation to modern programming languages, reverse engineering. The method pursues goals to decrease complexity of state space search and checking formulas satisfiability in relation to the direct code modeling, and to help legacy systems understanding and implementing in modern technologies. We focused on formalization of Cobol memory model as it is the most common language in legacy systems. Formal model is an attribute transition system with control flow. We proposed an algorithm for building enumerated types for any variables whose usage fulfills certain conditions, including translation procedure of numeric variables to enumerated ones. We considered a problem of translating non-comparable structures which overlap in memory (operator redefines in Cobol), are copied or compared with each other. In opposite to common approach of using union semantics (like union construction in C++), we described a method of structure fields decomposition which has no drawbacks of unions and makes for minimization of bytewise approach. We considered the developed method on the examples of structures as with simple fields as with arrays. We also gave examples of realization of bytewise approach in Java and C++ languages for those variables that cannot be represented as enumerated or numeric attributes. We tried this work for tests generation for middle-sized projects (up to 100 000 lines of code) where it showed efficiency of developed method, also generated formal models were used for debugging of Cobol to Java translator and business rules extraction.