Miracle-dz/UniFAR-FTUs huggingface dataset:
From Ordinal Representations to Representational Profiles: A Primer for Describing and Modelling Social Representations of History 1

Social representations theory is rich in explanatory power and broad in scope. This very complexity often leads to cases where predictions derived from the theory are difficult to operationalize and test. We argue that in many cases this is because social representations theory requires statistical models and analytic techniques that are uncommon in other social science traditions. In this chapter we outline a series of analytic methods and describe examples for their use in both improving description and testing predictions relating to social representations of history. We offer this overview as a methods primer for four complementary analytic methods for the study of social representations. These four methods are: (1) ordinal models assessing naming prevalence, (2) dimensional models assessing relational representations, (3) factorial representations focusing on unitary concepts, and the most recent addition to our toolbox: (4) representational profiles: latent class analysis allowing the assessment of representational profiles. We focus much of our primer on this method, and argue that latent class models, and factor mixture modelling in general has immense potential for the empirical assessment of social representations. This is
INVOLVEMENT OF PLANT MICRORNAS IN ABIOTIC STRESS RESPONSES

Crop production is constrained by several biotic and abiotic stresses.Several techniques have been applied by different research groups to unravel themolecular mechanism of tolerance to these stress factors in plants. Recently micro-RNAs have contributed towards understanding the role of micro-RNAs underabiotic stress conditions. Through first reported in animals its abundance in foundin plants even with some difference in biogenesis and mechanism of target generegulation. However, the relationship between micro-RNAs and stress responsesis just beginning to be explored. Micro-RNAs are about 21-24 nucleotide singlestranded non coding RNA often conserved across species suggesting theirevolutionary significance. MiRNAs are either up or down regulated under stressconditions suggesting their involvement in gene expression regulation by posttranscriptional degradation or translational repression in plants. A major categoryof MiRNA target gene consists of transcription factors or other regulatory proteinsthat function in plant development or signal transduction. One our own researchendeavour in this direction revealed the role of MiRNA towards salinity stressresponse in sugarcane. Several researches worldwide is leading to the identificationof thousands of miRNAs, the functional validation of which will help in designingnew strategies for improving tolerance to biotic and abiotic stresses. The currentreview gives the recent status of micro-RNA research towards its role under abioticstress.
First metagenomic analysis of the Andean condor (Vultur gryphus) gut microbiome reveals microbial diversity and wide resistome

Background The Andean condor (Vultur gryphus) is the largest scavenger in South America. This predatory bird plays a crucial role in their ecological niche by removing carcasses. We report the first metagenomic analysis of the Andean condor gut microbiome. Methods This work analyzed shotgun metagenomics data from a mixture of fifteen captive Chilean Andean condors. To filter eukaryote contamination, we employed BWA-MEM v0.7. Taxonomy assignment was performed using Kraken2 and MetaPhlAn v2.0 and all filtered reads were assembled using IDBA-UD v1.1. 3. The two most abundant species were used to perform a genome reference-guided assembly using MetaCompass. Finally, we performed a gene prediction using Prodigal and each gene predicted was functionally annotated. InterproScan v5.31-70.0 was additionally used to detect homology based on protein domains and KEGG mapper software for reconstructing metabolic pathways. Results Our results demonstrate concordance with the other gut microbiome data from New World vultures. In the Andean condor, Firmicutes was the most abundant phylum present, with Clostridium perfringens, a potentially pathogenic bacterium for other animals, as dominating species in the gut microbiome. We assembled all reads corresponding to the top two species found in the condor gut microbiome, finding between 94% to 98% of completeness for Clostridium perfringens and Plesiomonas shigelloides, respectively. Our work highlights the ability of the Andean condor to act as an environmental reservoir and potential vector for critical priority pathogens which contain relevant genetic elements. Among these genetic elements, we found 71 antimicrobial resistance genes and 1,786 virulence factors that we associated with several adaptation processes.
Implementation and performance of a RLWE-based commitment scheme and ZKPoK for its linear and multiplicative relations

In this paper we provide the implementation details and performance analysis of the lattice-based post-quantum commitment scheme introduced by Mart́ınez and Morillo in their work titled RLWE-Based ZeroKnowledge Proofs for Linear and Multiplicative Relations together with the corresponding Zero-Knowledge Proofs of Knowledge (ZKPoK) of valid openings, linear and multiplicative relations among committed elements. We bridge the gap between the existing theoretical proposals and practical applications, thoroughly revisiting the security proofs of the aforementioned paper to obtain tight conditions that allow us to find the best sets of parameters for actual instantiations of the commitment scheme and its companion ZKPoK. Our implementation is very flexible and its parameters can be adjusted to obtain a trade-off between speed and memory usage, analyzing how suitable for practical use are the underlying latticebased techniques. Moreover, our implementation further extends the literature of exact Zero-Knowledge proofs, providing ZKPoK of committed elements without any soundness slack. Keywords— Lattice-based Cryptography, Post-Quantum Cryptography, Implementation, Commitment Scheme, Zero-Knowledge Proofs of Knowledge.
An Analysis of Requirements and Privacy Threats in Mobile Data Donations

In recent years, personal and medical data collected through mobile apps has become a useful data source for researchers. Platforms like Apple ResearchKit try to make it as easy as possible for non-experts to set up such data collection campaigns. However, since the collected data is sensitive, it must be well protected. Methods that provide technical privacy guarantees often limit the usefulness of the data and results. In this paper, we model and analyze mobile data donation to better understand the requirements that must be fulfilled by privacy-preserving approaches. To this end, we give an overview of the functionalities researchers require from data donation apps by analyzing existing apps. We also create a model of the current practice and analyze it using the LINDDUN privacy framework to identify privacy threats.
Designations of Astronomical Sources and the IAU Task Group On Designations

The purpose of the IAU Task Group on (astronomical) Designations is to promote clear and unambiguous identification of all astronomical objects outside the solar system. Several documents exist on the World Wide Web to assist astronomers in designating their sources. Developments undertaken by the Task Group in the last three years include: establishing a "Registry for New Acronyms" and organizing (with Commission 26 Double and Multiple Stars) an all-day multi-commission meeting on Designations of Stellar Companions at the IAU General Assembly held in August 2000 in Manchester, UK.
Optimized L1 Adaptive Controller for Trajectory Tracking of an Indoor Quadrotor

This paper proposes a systematic analysis and synthesis method for the optimal design of filters for L1 adaptive output feedback controllers. In the L1 adaptive feedback structure, the low-pass filter is the key to the tradeoff between the performance and robustness of the closed-loop system. Although the filter design for the L1 adaptive architecture has been studied in previous papers, the need for a numerically tractable synthesis method is yet to be fulfilled. In this paper, the L1 adaptive controller with an optimized filter is used for precision trajectory tracking control of a small quadrotor (Crazyflie) in an experimental setup. The controller demonstrates robustness to time delay, noise, disturbances, radio transmission, and uncertainties in the modeling of quadrotor.
Antioxidant capacity and cytotoxic effects of Cymbopogon citratus (DC.) Stapf and Azadirachta indica L.

Cymbopogon citratus (DC.) Stapf and Azadirachta indica L. leaves are traditionally used for the treatment of many diseases. Although they contain antioxidant compounds with free radical scavenging ability, their safety also needs to be considered. This study aims to evaluate and compare the antioxidant capacity and potential toxicity of their leaves' aqueous extracts to determine their preference for therapeutic use. Antioxidant properties were evaluated by determining the DPPH assay, nitric oxide scavenging activity (NSA), ferric reducing antioxidant power (FRAP), ascorbic acid content (AAC), total flavonoid content (TFC), total phenolic content (TPC) and total antioxidant capacity (TAC). Their potential cytotoxic effects were evaluated using Artemia salina larvae. Cymbopogon citratus exhibited higher TFC, TAC and antioxidant activities, while A. indica had a higher TPC. LC50 of C. citratus was lower than that observed for A. indica. The results showed that C. citratus possesses higher antioxidant properties and it is less toxic than A. indica.
Import and Export of Beef Products in Tajikistan and Its Impact on the Domestic Market

This study examines the influence of imports and exports of beef products on Tajikistan’s domestic market. Data from reputable sources covering the period 1999-2019, including the World Bank, Federal Bureau of Statistics, and International Financial Statistics, are utilized. The Vector Error Correction Model (VECM) and Granger causality methodology are employed to analyze the relationship between beef product imports, exports, their determinants, and the domestic market. The empirical analysis reveals that macroeconomic variables (GDP, foreign direct investment, inflation, and beef production) and the openness of the economy play a crucial role in determining the impact of imports and exports on Tajikistan’s domestic market. E-views and Stata software are used for data analysis. The findings indicate that Tajikistan imports more beef products than it exports, demonstrating a growing reliance on imported beef over the 1999-2019 period, implying a lack of competitive domestic beef production. Additionally, excessive beef exports can negatively affect domestic production and the economy. To ensure stability and sustainable economic growth, policy measures are recommended. These include implementing import tariffs to protect local producers, providing subsidies and support programs to enhance domestic production, and strategic planning to meet domestic beef demand before considering exports. By adopting these measures, Tajikistan can achieve a balanced and prosperous domestic market. These findings underscore the importance of considering the impact of beef imports and exports and implementing appropriate policies and regulations to promote a thriving domestic market.
Immediate Loaded Full-Arch Mandibular Rehabilitations in Younger vs. Elderly Patients: A Comparative Retrospective Study with 7-Year Follow-Up

The aim of this comparative retrospective clinical study was to assess the effect of age on immediate loaded full-arch mandibular rehabilitation in younger vs. elderly patients. Patients with an age between 45 and 60 years (younger group, YG) or with an age more or equal to 75 years (older group, OG), requiring a mandibular full-arch rehabilitation were scheduled for the present study. Implant and prosthetic failure, biological and prosthetic complications, and peri-implant marginal bone level changes were recorded until a 7-year follow-up. Sixty-six patients were included in the study; a total of 264 implants were placed and, in total, 66 “all-on-four” rehabilitations were delivered. In total, 33 patients were scheduled in the YG and 33 patients in the OG. At the 7-year follow-up, an overall implant failure rate of 1.14% was reported. Moreover, at the 7-year radiographic evaluation, peri-implant crestal bone loss averaged 1.12 ± 0.91 mm for the YG and 1.04 ± 1.01 mm for the OG. No statistically significant differences were found between the YG and OG except for the rate of peri-implantitis, which was statistically higher in the YG. The present study reported that immediate fixed mandibular full-arch rehabilitation is a viable procedure in elderly people of equal or more than 75 years of age.
Synergies between spectroscopic and asteroseismic surveys for the Kepler field with LAMOST

Abstract The NASA Kepler satellite has provided unprecedented high duty-cycle, high-precision light curves for a large number of stars by continuously monitoring a field of view in Cygnus-Lyra region, leading to great progress in both discovering exoplanets and characterizing planet-hosting stars by means of asteroseismic methods. The asteroseismic survey allows the investigation of stars covering the whole H-R diagram. However, the low precision of effective temperatures and surface gravities in the KIC catalogue and the lack of information on chemical composition, metallicity and rotation rate prevent asteroseismic modeling, requiring spectroscopic observations for thousands of asteroseismic targets in the Kepler field in a homogeneous way.
Boosting the Development of Smart Cities with the Blockchain

—Urbanization is taking place worldwide and fast, so much that 66% of the world population is predicted to live in cities in 2050. This massive movement of people from rural to urban areas pose challenges for municipal governments. Resources used to run services like the municipal transportation or healthcare systems will not keep up with the rhythm of the population’s growth. To meet the growing demand of resources, cities must evolve and build advanced, large-scale networks able to efﬁciently retrieve and distribute the needed resources. Not only, the same citizen should have access to different services that may need to share information to interoperate correctly. Multiple networks will therefore need a common technological layer where conﬁdential data about citizens can be exchanged and stored securely. The emerging technological tool to implement such platform, so to empower the Smart Cities of tomorrow, is the blockchain. But what is a blockchain? How does it work?
Politic Iconography: The Sky and Pants of Nicolas-Antoine Taunay (1755-1830)

 Abstract — Nicolas-Antoine Taunay had everything to have a quiet life with his family, his colleagues from the Paris Academy of Art, and as a renowned painter of the French Court, but the conjuncture was quite complicated in those final years of the eighteenth century and first decades of the 19th century. The painter had to adapt to various political and social ruptures: from royalty to the French Revolution, from the empire of Napoleon Bonaparte to the empire of King John VI. We wish to insert Taunay in its context through the analysis of his portrait made by a colleague of the profession and of a Brazilian landscape painted of his own (1816-1821) and, in which he represented himself. Finally, the intention is to find in these two paintings how Nicolas-Antoine Taunay faced himself and in the middle that surrounded him in the traffic that was forced to make it between Paris and Rio de Janeiro.
Learning a foreign language and locality through an animated documentary film

This paper describes one 4-week long online language learning module which utilizes the animated documentary film My Favorite War (Burkovska-Jakobsen, 2020) and analyzes four students’ final essays. The learning module was created considering ethnographic views of cultural inferences (Spradley, 2016), the framework of social space (Lefebvre, 1991), multimodal theory (Kress & van Leeuwen, 2006), and the model of learning activities, or knowledge processes (Cope & Kalantzis, 2015). It was developed for a Latvian language course at the University of Washington (Seattle, USA) in 2021. Its goals are to help students learn more about the target language and locals’ place-based experiences, and to promote students’ semiotic consciousness while developing their multiliteracies. However, the assignment’s assessment criteria related to the interaction of semiotic resources and of linguistic and non-linguistic information were not shared in order to find out if students would include these issues in their essays. Analysis of students’ essays show that after the learning module, students were able to comprehend (a) some individual compositional elements from the film; (b) symbolic and functional meanings of differently marked spaces; and (c) the main character’s feelings in various social spaces, internal conflicts, relationship models, and thoughts about family, work, war, historical truth, and independence. The described learning model can inspire educators worldwide to develop similar teaching practices for other less commonly taught languages.
Weights Assimilation for Split Manufacturing of printed Neuromorphic Circuits

Due to low manufacturing cost, flexibility, non-toxicity, and excellent performance, printed neuromorphic circuits have attracted increasing attention from multiple emerging areas, such as Internet of Things, wearable devices, and soft-robotics. Regarding printing technologies, high volume manufacturing of printed circuits is usually done by the roll-to-roll printing, where the same circuits can be manufactured in large quantities with high efficiency, leading to an ultra low-cost per circuit. On the other hand, low volume manufacturing methods, such as inkjet printing, are convenient to produce unique parts in low quantity, but with relatively higher cost. In case a large amount of different circuits need to be printed, neither high nor low volume printing technology can be deployed to guarantee high performance and low cost at the same time. However, by deliberate design and adjustment, both manufacturing approaches can be leveraged: high volume manufacturing produces the common parts of different circuits and low volume manufacturing adjust the unique part of each circuit. In this paper, we will present a training framework that uses a special penalty term to attract the most of the weights in neural networks for different tasks close to each other or even coincident. The other advantage of this penalty is that, outlier weights, whose value is far apart from others, will not be attracted, so that the performance of circuits will not be destroyed. With this framework, multiple neuromorphic circuits are prepared for lower production costs almost without reduction in performance.
Equilibrium Figures inside the Dark-Matter Ring and the Shapes of Elliptical Galaxies

Abstract We solve the general problem of the theory of equilibrium figures and analyze two classes of liquid rotating gravitating figures residing inside a gravitating ring or torus. These figures form families of sequences of generalized oblate spheroids and triaxial ellipsoids, which at the lower limit of the tidal parameter α = 0 have the form of the Maclaurin spheroids and the Jacobi ellipsoids. In intermediate cases 0 < α ≤ αmax each new sequence of axisymmetric equilibrium figures has two non-rotating boundary spheroids. At the upper limit αmax/(πGρ) = 0.1867 the sequence degenerates into a single non-rotating spheroid with the eccentricity ecr ≈ 0.96 corresponding to the flattening limit of elliptical galaxies (E7). We also perform a detailed study of the sequences of generalized triaxial ellipsoids and find bifurcation points of triaxial ellipsoids in the sequences of generalized spheroids. We use this method to explain the shapes of E-galaxies. According to observations, very slowly rotating oblate E-type galaxies are known that have the shapes, which, because of instability, cannot be supported by velocity dispersion anisotropy exclusively. The hypothesis of a massive dark-matter outer ring requires no extreme anisotropy of pressure; it not only explains the shape of these elliptical galaxies, but also sheds new light on the riddle of the ellipticity limit (E7) of elliptical galaxies.
Using Deep Convolutional Neural Networks to Optimize Pulmonary Nodule Classification and Localization in Radiograph Imaging for Early Lung Cancer Detection

Preliminary diagnosis of lung cancer has led to countless cases of overtreatment due to false positive classifications made by physicians and radiologists. Most commonly, the misclassification of a benign pulmonary nodule (PN) as malignant from chest X-ray images initiates this process for patients. In the advent of promising machine learning and computer vision models, we investigate the optimization of benign and malignant PN classification using deep convolutional neural networks through transfer learning by fine tuning its convolutional layers. Specifically, we look at how fine-tuning the VGG19 convolutional neural network model differently affects its classification accuracy. With our optimal model, we test its efficacy in localizing and classifying PNs on chest radiographs using a selection search-based scanning method. We found that fine-tuning the last convolutional block yields the highest predictive performance. Using a reserved image test set, our model is able to yield a classification accuracy of 77% compared to published models yielding 68%. This methodology can be easily generalized and applied to other medical imaging tasks.
GATE simulation of a new design of pinhole SPECT system for small animal brain imaging

Small animal SPECT imaging has gained an increased interest over the past decade since it is an excellent tool for developing new drugs and tracers. Therefore, there is a huge effort on the development of cost-effective SPECT detectors with high capabilities. The aim of this study is to simulate the performance characteristics of new designs for a cost effective, stationary SPECT system dedicated to small animal imaging with a focus on mice brain. The conceptual design of this SPECT system platform, Stationary Small Animal SSA-SPECT, is to use many pixelated CsI:TI detector modules with 0.4 mm × 0.4 mm pixels in order to achieve excellent intrinsic detector resolution where each module is backed by a single pinhole collimator with 0.3 mm hole diameter. In this work, we present the simulation results of four variations of the SSA-SPECT platform where the number of detector modules and FOV size is varied while keeping the detector size and collimator hole size constant. Using the NEMA NU-4 protocol, we performed spatial resolution, sensitivity, image quality simulations followed by a Derenzo-like phantom evaluation. The results suggest that all four SSA-SPECT systems can provide better than 0.063% system sensitivity and < 1.5 mm FWHM spatial resolution without resolution recovery or other correction techniques. Specifically, SSA-SPECT-1 showed a system sensitivity of 0.09% in combination with 1.1 mm FWHM spatial resolution.