Miracle-dz/UniFAR-FTUs huggingface dataset:
Striatal dopamine reflects individual long-term learning trajectories

Learning from naïve to expert occurs over long periods of time, accompanied by changes in the brain’s neuronal signals. The principles governing behavioural and neuronal dynamics during long-term learning remain unknown. We developed a psychophysical visual decision task for mice that allowed for studying learning trajectories from naïve to expert. Mice adopted sequences of strategies that became more stimulus-dependent over time, showing substantial diversity in the strategies they transitioned through and settled on. Remarkably, these transitions were systematic; the initial strategy of naïve mice predicted their strategy several weeks later. Longitudinal imaging of dopamine release in dorsal striatum demonstrated that dopamine signals evolved over learning, reflecting stimulus-choice associations linked to each individual’s strategy. A deep neural network model trained on the task with reinforcement learning captured behavioural and dopamine trajectories. The model’s learning dynamics accounted for the mice’s diverse and systematic learning trajectories through a hierarchy of saddle points. The model used prediction errors mirroring recorded dopamine signals to update its parameters, offering a concrete account of striatal dopamine’s role in long-term learning. Our results demonstrate that long-term learning is governed by diverse yet systematic transitions through behavioural strategies, and that dopamine signals exhibit key characteristics to support this learning.
Java sparrow song conforms to Menzerath’s Law but not Zipf’s Law of Abbreviation

Linguistic laws, which describe common statistical patterns in human language, are often studied in animal communication systems. Despite good evidence for the existence of these laws in non-human primates, data is still limited for other taxa. Birdsong is often used as a model for human language development due to similarities in vocal learning and production. Therefore, it is useful to explore features of human language in birdsong to determine the value and limitations of such comparisons. Here, we looked for patterns consistent with Menzerath’s law, the tendency for longer sequences to be made up of smaller constituent parts, and Zipf’s Law of Abbreviation, the tendency for more frequently used elements to be shorter in length, in the songs of Java sparrows (Padda oryzivora). We found that songs conformed to Menzerath’s law at both the population and individual level; longer sequences were made up of shorter notes, and this pattern was achieved through note selection, rather than shortening existing notes. This adherence to Menzerath’s law may reflect species-specific constraints on song durations. However, we found no evidence to support adherence to Zipf’s Law of Abbreviation, either at population or individual level; more frequently used notes were not shorter in length. As they are used in courtship, songs may experience different selection pressure to other parts of the vocal repertoire, which could act against compression. Whilst there may be some limitations in applying linguistic laws designed for human language to birdsong, especially Zipf’s Law of Abbreviation, these laws may still provide insights into animal and human communication systems.
Allantoic fluid-based qPCR for early-onset in ovo sexing

The culling of day-old male chickens remains an important welfare issue in the poultry industry. Several governments (e.g., Germany, France or Italy) have prohibited this practice, pushing the hatcheries to look for alternatives. Although different solutions exist for solving this problem, sex determination during embryo’s incubation (so called in ovo sexing) is considered the most suitable both for consumers and the industry since it aligns with the increasing demand for ethical and sustainable agriculture. However, to be applied in the market, in ovo sexing technologies have to meet a number of requirements, such as being compatible with all egg colors and early developmental stages, while maintaining high hatchability rate and accuracy at low cost and high throughput. To meet these requirements, we studied the use of the sexual genes HINTW (female-specific) and DMRT-1 (present in both males and females) between incubation days 6 and 9. By utilizing quantitative polymerase chain reaction (qPCR) as analysis method and allantoic fluid (AF) as sample, our study confirmed specific detection of these genes in AF, remarkably already at day 6 of development. In a blind study performed with 80 eggs, we achieved a 95% accuracy rate in sorting embryos when using the HINTW gene alone and an outstanding 100% accuracy rate when using Δλ values (difference between the HINTW and DMRT-1 qPCR cycle threshold (Ct)). Importantly, the AF sampling procedure did not reveal any significant detrimental effects on hatchability or embryo development, revealing high potential for this understudied type of sample to be used. In conclusion, the developed assay can provide more in-depth information about AF as a sample for genomic in ovo sexing and open new industrial possibilities for developing faster and cheaper assays. Research highlights A highly reliable and accurate method for in ovo sexing in early incubation stages is established. Allantoic fluid can be easily extracted with minimal invasiveness while providing the necessary genomic material for sexual sorting. HINTW was found to be present in both female and male samples due to possible maternal contamination. HINTW alone or combined with DMRT-1 gene enables early-onset sexing with 100% accuracy.
A proteolytic AAA+ machine poised to unfold a protein substrate

AAA+ proteolytic machines unfold proteins prior to degradation. Cryo-EM of a ClpXP-substrate complex reveals a postulated but heretofore unseen intermediate in substrate unfolding/degradation. The natively folded substrate is drawn tightly against the ClpX channel by interactions between axial pore loops and the substrate degron tail, and by contacts with the native substrate that are, in part, enabled by movement of one ClpX subunit out of the typically observed hexameric spiral.
Kit Ligand and Kit receptor tyrosine kinase sustain synaptic inhibition of Purkinje Cells

The cell-type specific expression of ligand/receptor and cell-adhesion molecules is a fundamental mechanism through which neurons regulate connectivity. Here we determine a functional relevance of the long-established mutually exclusive expression of the receptor tyrosine kinase Kit and the trans-membrane protein Kit Ligand by discrete populations of neurons in the mammalian brain. Kit is enriched in molecular layer interneurons (MLIs) of the cerebellar cortex (i.e., stellate and basket cells), while cerebellar Kit Ligand is selectively expressed by a target of their inhibition, Purkinje cells (PCs). By in vivo genetic manipulation spanning embryonic development through adulthood, we demonstrate that PC Kit Ligand and MLI Kit are required for, and capable of driving changes in, inhibition of PCs. Collectively, these works in mice demonstrate that the Kit Ligand/Kit receptor dyad sustains mammalian central synapse function and suggest a rationale for the affiliation of Kit mutation with neurodevelopmental disorders. Visual Abstract
Mitigation of Torque Ripple and Vibration in Switched Reluctance Motor Drives: A Switching Optimization

Supervising Professor: Luiz Eduardo Borges da Silva, Dr. Switched reluctance motor (SRM) drives represents an attractive solution for industrial, transportation and domestic applications due to their rugged structure, independence from rare earth metals, modular design, wide speed range, and tolerance to harsh environments. Despite these advantages, the adequacy of SRM drives for many applications has been overshadowed by its relative high levels of torque pulsation and vibration/acoustic noise. This research aims to investigate and propose control strategies to mitigate these adverse features. To reach this goal the current shaping and switching optimization have been proposed. Two modeling methods were used in this process: i) field reconstruction method (FRM) to model the electromagnetic behavior; and ii) mechanical impulse response to model the structural behavior. This two-modeling procedure are the key innovative tools in this dissertation, since those are techniques recently proposed in the literature. Moreover, these two methods have been combined to simultaneously mitigation of torque ripple and radial vibration. Firstly, the structural vibration was investigated in detail for an 8/6 SRM. The modal analysis is carried out experimentally and through finite element model in ANSYS. Then, the mechanical impulse response concept was applied to develop a vibration prediction model that, after validated, was introduced in an optimization algorithm developed in MATLAB to design the precise switching instants to have active vibration cancellation. The method is focused on SRM operating under current control (low speed region). The experimental results show a significantly reduction. This technique is sensitive to timing without adverse impact on productivity and efficiency of the SRM drive. Moreover, the vibration mitigation also has contributed to acoustic noise reduction.
Yawning and Cortisol as a Potential Biomarker for Early Detection of Multiple Sclerosis

Cortisol is essential to the regulation of the immune system and yawning is a pathological symptom of multiple sclerosis (MS). Electromyography activity (EMG) in the jaw muscles typically rises when the muscles are moved and with yawning is highly correlated with cortisol levels in healthy people. Saliva samples from 59 participants were collected at the start and after yawning, or at the end of the presentation of yawning-provoking stimuli, in the absence of a yawn, together with EMG data and questionnaire data: Hospital Anxiety and Depression Scale, Yawning Susceptibility Scale, General Health Questionnaire, demographic, health details. Exclusion criteria: chronic fatigue, diabetes, fibromyalgia, heart condition, high blood pressure, hormone replacement therapy, multiple sclerosis, stroke. Significant differences were found between the saliva cortisol samples for the yawners, t (23) = -4.263, p = 0.000, as compared with the non-yawners between rest and post-stimuli, which was nonsignificant. Significant evidence was found to support the Thompson Cortisol Hypothesis suggesting that rises in cortisol levels are associated with yawning. Further research is exploring the use of cortisol as an early diagnostic tool for MS. Ethics approval granted and professional code of conduct, confidentiality, and safety issues are approved therein. Keywords—Cortisol, Multiple Sclerosis, Yawning, Thompson’s Cortisol Hypothesis.
How Organizations can Enhance the Effectiveness of Internal Controls in Response to Changes in the Business Environment Since the Sarbanes-Oxley act: An analysis of the COSO Framework

This research topic explores the evolution of the business environment since the enactment of the Sarbanes-Oxley Act, the impact of these changes on the effectiveness of internal controls, and how organizations can adapt their internal control systems to improve their quality. The study will use the COSO framework to analyze the factors that influence the effectiveness of internal controls and suggest ways to enhance them to meet the challenges of the current business landscape. The research will also examine the implications of the ineffective internal controls and explore new strategies and best practices to strengthen internal controls under the SOX Act.
Predicting Word Vectors for Microtext

The use of computer-mediated communication has resulted in a new form of written text called Microtext, which is very different from well-written text. Most previous approaches deal with microtext at the character level rather than just words resulting in increased processing time. In this paper, we propose to transform static word vectors to dynamic form by modelling the effect of neighbouring words and their sentiment strength in the AffectiveSpace. To evaluate the approach, we crawled Tweets from diverse topics and human annotation was used to label their sentiments. We also normalised the tweets to ﬁx phonetic variations, spelling errors and abbreviations manually. A total of 1432 out-of-vocabulary (OOV) texts and their IV texts made it to the ﬁnal corpus with their corresponding polarity. To assess the quality of the corpus, we used several OOV classiﬁers such as linear regression and observed over 90% accuracy. Next, we inferred word vectors using a novel four-gram model based on sentiment intensity and reported accuracy on both open domain and closed domain sentiment classiﬁers. We observed an improvement in the range of 4-20% on Twitter, Movie and Airline reviews over baselines.
ArabiziVec: A Set of Arabizi Word Embeddings for Informal Arabic Sentiment Analysis

The current circumstances of the Arab world have provided bloggers and commenters with various subjects to discuss. Therefore, Arabic-generated content in social media is ramping up continuously. An informal written form of spoken Arabic called Arabizi has recently emerged as a commonly used language in the Arabic space, attracting great interest for sentiment analysis tasks. However, only a few sentiment resources exist
The SICT/Plasma Tech/Tribology 2022 International Joint Conference Hybrid event - Apr 27 to 29

It is widely known that tribological systems operating in vacuum environments face significant challenges. MoS 2 is a well-known material for its low friction properties in both ambient and vacuum environments. However, it has a low wear resistance and a limited ability to withstand higher contact pressures. A possible alternative to MoS 2 are super-hard hydrogen-free tetrahedral amorphous carbon coatings (ta-C). In normal atmospheric conditions, they have low friction and wear properties, but their performance in vacuum is limited. In this work, ta-C coatings are paired with brass in high vacuum conditions. Long-term tribological performance tests are conducted and analyzed using triboscopic imaging. It was found that the brass/ta-C friction pair exhibited an increase of the friction coefficient in the long term (up to 0.52) due to a change in wear mechanism. Different wear and healing behaviors could be found for both the brass counterbody and the ta-C discs using triboscopy.
Suggerimenti per una eucalitticoltura clonale sostenibile nelle aree a clima mediterraneo dell’Italia centro-meridionale

Abstract: The cultivation of eucalyptus clones in areas of central-southern Italy with a Mediterranean climate has become necessary in order to meet, albeit in part, the strong domestic demand of woody biomass for energy use (wood chips, firewood, charcoal, pellets). In the last ten years, in fact, Italy has become one of the world’s largest importers of woody biomass for energy use. In our country the eucalyptus can be grown following the principles and methods of planted forest systems. The aim of the present paper is to point out the main problems that this culture can face in the national pedoclimatic context, together with their possible solution. Among the possible solutions, the most sustainable are suggested, which may contribute to both economic and energy savings for the culture and for other human activities. These solutions, widely used in various contexts, are briefly described, and references to the literature of the sector are provided for a deeper insight.
Use of gradient anticipatory nasal coarticulatory cues for lexical perception in French

The current study examines anticipatory nasal coarticulation in French, a language which is known to exhibit a) quality differences between phonemically oral and nasal vowels and b) relatively low amounts of nasal coarticulation in CVN contexts. In a production study, thirty native Northern Metropolitan (Parisian) French speakers produced seven sets of CṼ-CVC-CVN words (e.g., [sɛd] cède , [sɛn] scènes, [sæ̃] saint ). Consistent with previous studies, results indicated quality differences between the vowels in CṼ versus CVC and CVN words, and also that acoustic nasalization in CVN contexts was relatively small; nevertheless, it was still significantly greater than in CVC contexts, and variable across speakers. In a perception study, the CV portions of the production recordings were played to fifty French listeners, who identified the corresponding word in a forced-choice task. Results showed that stimuli from CVN contexts were highly confusable with CVC items, but not with CṼ items. Most importantly, increased degree of acoustic nasalization on individual CVN stimuli significantly correlated with accuracy. We conclude that, despite the overall relative weakness of coarticulatory cues to nasality, French listeners can nevertheless employ these cues when they are present.
UvA-DARE (Digital Academic Repository) Investigating the in-solution photodegradation pathway of Diamond Green G by chromatography and mass spectrometry

Diamond Green G (CI 42040, Basic Green 1) is a triarylmethane dye mostly employed in the industrial dyeing of miscellaneous natural and artificial textile fibres, in the production of printing inks and as an anti-fungal agent for aquaculture products. Diamond Green (DG) tends to fade under light irradiation, similar to several other dyes and pigments belonging to the triarylmethane family. In this paper, an in-solution degradation study was carried out to shed light on DG photostability. The experiments were performed by artificially irradiating DG in water and dimethyl sulphoxide, and analysing aliquots sampled at different time intervals by ultra-high performance liquid chromatography coupled with diode array detector quadrupole and time of flight tandem mass spectrometry. The degradation products formed were characterised and the production spectra discussed and interpreted. On the basis of the structure of the identified compounds and their kinetic trend in relation to the accelerated ageing time, degradation mechanisms were proposed for DG, taking into account the role played by the solvent. Finally, the dyeing formulation of an historical textile sample, collected from a stage costume worn in a Zeffirelli lyric opera, was determined utilising the information collected from the analysis of irradiated DG solutions.
Exploring User-level Gradient Inversion with a Diﬀusion Prior

We explore user-level gradient inversion as a new attack surface in distributed learning. We ﬁrst investigate existing attacks on their ability to make inferences about private information info beyond training data reconstruction. Motivated by the low reconstruction quality of existing methods, we propose a novel gradient inversion attack that applies a denoising diﬀusion model as a strong image prior in order to enhance recovery in the large batch setting. Unlike traditional attacks, which aim to reconstruct individual samples and suﬀer at large batch and image sizes, our approach instead aims to recover a representative image that captures the sensitive shared semantic information corresponding to the underlying user. Our experiments with face images demonstrate the ability of our methods to recover realistic facial images along with private user attributes
Deep PDE Solvers for Subgrid Modelling and Out-of-Distribution Generalization

Climate and weather modelling (CWM) is an important area where ML models are used for subgrid modelling: making predictions of processes occurring at scales too small to be resolved by standard solution methods(Brasseur & Jacob, 2017). These models are expected to make accurate predictions, even on out-of-distribution (OOD) data, and are additionally expected to respect important physical constraints of the ground truth model (Kashinath et al., 2021). While many specialized ML PDE solvers have been developed, the particular requirements of CWM models have not been addressed so far. The goal of this work is to address them. We propose and develop a novel architecture, which matches or exceeds the performance of standard ML models, and which demonstrably succeeds in OOD generalization. The architecture is based on expert knowledge of the structure of PDE solution operators, which permits the model to also obey important physical constraints
A Historical and Current Review of Extended Reality Technologies and Applications

This paper provides a review of Extended Reality (ER) technologies and applications. The diﬀerent technologies related to ER, such as Virtual Reality, Augmented Reality and Mixed Reality are introduced and explained, following an historical perspective. The basic technical concepts behind these technologies are brieﬂy explained. Current applications are presented, including references to actual tools and systems, in order to clarify the concepts and the potential of the technologies. ˆA
Comparison of airborne measurements of NO, NO2, HONO, NOy and CO during FIREX-AQ

Abstract. We present a comparison of fast-response instruments installed onboard the NASA DC-8 aircraft that measured nitrogen oxides (NO and NO2), nitrous acid (HONO), total reactive odd nitrogen (measured both as the total (NOy) and from the sum of individually measured species (SNOy)) and carbon monoxide (CO) in the troposphere during the 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign. By targeting smoke from summertime wildfires, prescribed fires and agricultural burns across the continental United States, FIREX-AQ provided a unique opportunity to investigate measurement accuracy in concentrated plumes where hundreds of species coexist. Here, we compare NO measurements by chemiluminescence (CL) and laser induced fluorescence (LIF); NO2 measurements by CL, LIF and cavity enhanced spectroscopy (CES); HONO measurements by CES and iodide-adduct chemical ionization mass spectrometry (CIMS); and CO measurements by tunable diode laser absorption spectrometry (TDLAS) and integrated cavity output spectroscopy (ICOS). Additionally, total NOy measurements using the CL instrument were compared with SNOy (= NO + NO2 + HONO + nitric acid (HNO3) + acyl peroxy nitrates (APNs) + submicron particulate nitrate (pNO3)). The aircraft instrument intercomparisons demonstrate the following: 1) NO measurements by CL and LIF agreed well within instrument uncertainties, but with potentially reduced time response for the CL instrument; 2) NO2 measurements by LIF and CES agreed well within instrument uncertainties, but CL NO2 was on average 10 % higher; 3) CES and CIMS HONO measurements were highly correlated in each fire plume transect, but the correlation slope of CES vs. CIMS for all 1 Hz data during FIREX-AQ was 1.8, which we attribute to a reduction in the CIMS sensitivity to HONO in high temperature environments; 4) NOy budget closure was demonstrated for all flights within the combined instrument uncertainties of 25 %. However, we used a fluid dynamic flow model to estimate that average pNO3 sampling fraction through the NOy inlet in smoke was variable from one flight to another and ranged between 0.36 and 0.99, meaning that approximately 0–24 % on average of the total measured NOy in smoke may have been unaccounted for and may be due to unmeasured species such as organic nitrates; 5) CO measurements by ICOS and TDLAS agreed well within combined instrument uncertainties, but with a systematic offset that averaged 2.87 ppbv; and 6) integrating smoke plumes followed by fitting the integrated values of each plume improved the correlation between independent measurements.
DR AF T Sometimes Average is Best : The Importance of Averaging for Prediction using MCMC Inference in Topic Modeling

Markov chain Monte Carlo (MCMC) approximates the posterior distribution of latent variable models of text by generating a large number of samples and averaging over them. In practice, however, it is often more convenient to cut corners, using only a single sample or following a subop-timal averaging strategy. In this paper, we systematically study different strategies for averaging MCMC samples and show empirically that performing averaging properly leads to significant improvements in prediction performance.