Miracle-dz/UniFAR-FTUs huggingface dataset:
A model for the Twitter sentiment curve

Twitter is among the most used online platforms for the political communications, due to the concision of its messages (which is particularly suitable for political slogans) and the quick diffusion of messages. Especially when the argument stimulate the emotionality of users, the content on Twitter is shared with extreme speed and thus studying the tweet sentiment if of utmost importance to predict the evolution of the discussions and the register of the relative narratives. In this article, we present a model able to reproduce the dynamics of the sentiments of tweets related to specific topics and periods and to provide a prediction of the sentiment of the future posts based on the observed past. The model is a recent variant of the Pólya urn, introduced and studied in Aletti and Crimaldi (2019, 2020), which is characterized by a “local” reinforcement, i.e. a reinforcement mechanism mainly based on the most recent observations, and by a random persistent fluctuation of the predictive mean. In particular, this latter feature is capable of capturing the trend fluctuations in the sentiment curve. While the proposed model is extremely general and may be also employed in other contexts, it has been tested on several Twitter data sets and demonstrated greater performances compared to the standard Pólya urn model. Moreover, the different performances on different data sets highlight different emotional sensitivities respect to a public event.
Solution to the Equity Premium Puzzle

This study provides a solution of the equity premium puzzle. Questioning the validity of the Arrow-Pratt measure of relative risk aversion for detecting the risk behavior of investors under all conditions, a new tool, that is, the sufficiency factor of the model was developed to analyze the risk behavior of investors. The calculations of this newly tested model show that the value of the coefficient of relative risk aversion is 1.033526 by assuming the value of the subjective time discount factor as 0.99. Since these values are compatible with the existing empirical studies, they confirm the validity of the newly derived model that provides a solution to the equity premium puzzle.
Star formation history of the solar neighbourhood as told by Gaia

The Gaia DR2 catalog is the best source of stellar astrometric and photometric data available today. The history of the Milky Way galaxy is written in stone in this data set. Parallaxes and photometry tell us where the stars are today, when were they formed, and with what chemical content, i.e. their star formation history (SFH). We develop a Bayesian hierarchical model suited to reconstruct the SFH of a resolved stellar population. We study the stars brighter than $G\,=\,15$ within 100 pc of the Sun in Gaia DR2 and derive a SFH of the solar neighbourhood in agreement with previous determinations and improving upon them because we detect chemical enrichment. Our results show a maximum of star formation activity about 10 Gyr ago, producing large numbers of stars with slightly below solar metallicity (Z=0.014), followed by a decrease in star formation up to a minimum level occurring around 8 Gyr ago. After a quiet period, star formation rises to a maximum at about 5 Gyr ago, forming stars of solar metallicity (Z=0.017). Finally, star formation has been decreasing until the present, forming stars of Z=0.03 at a residual level. We test the effects introduced in the inferred SFH by ignoring the presence of unresolved binary stars in the sample, reducing the apparent limiting magnitude, and modifying the stellar initial mass function.
Data association framework based on biconnected gated recurrent unit network for multiple object tracking

Abstract. In the tracking-by-detection scheme of multiple object tracking (MOT), the data association process in which existing tracking data and new detections are matched over time is very important. A framework is proposed to solve the data association problem in MOT in scenarios where there are potential target interactions and occlusions in crowded environments. This framework consists of an input layer and an association layer. The input layer is an end-to-end feature-map extraction model that incorporates a simplified Siamese convolutional neural network, which effectively distinguishes similar objects based on their appearance and motion. The association layer is composed of a bidirectional gated recurrent unit network with three layers of fully connected networks (FCNs), whose outputs are fed into the FCNs and transformed into an association matrix that reflects the matching scores between the detections and existing tracks. The matrix is then used to minimize the loss of the framework. The experimental results show that the proposed framework demonstrates outstanding performance for MOT, with its accuracy and precision in MOT reaching values as high as 26.1% and 71.2%, respectively.
Brucella abortus BspJ Is a Nucleomodulin That Inhibits Macrophage Apoptosis and Promotes Intracellular Survival of Brucella

To date, a variety of Brucella effector proteins have been found to mediate host cell secretion, autophagy, inflammation, and other signal pathways, but nuclear effector proteins have not yet been reported. We identified the first Brucella nucleomodulin, BspJ, and we screened out the BspJ interaction host proteins NME/NM23 nucleoside diphosphate kinase 2 (NME2) and creatine kinase B (CKB) through yeast two-hybrid and co-immunoprecipitation assays. These proteins are related to the host cell energy synthesis, metabolism, and apoptosis pathways. Brucella nucleomodulin BspJ will decrease the expression level of NME2 and CKB. In addition, BspJ gene deletion strains promoted the apoptosis of macrophages and reduced the intracellular survival of Brucella in host cells. In short, we found nucleomodulin BspJ may directly or indirectly regulate host cell apoptosis through the interaction with NME2 and CKB by mediating energy metabolism pathways in response to the intracellular circulation of Brucella infection, but the mechanism needs further study.
Phase-Synchronized Learning of Periodic Compliant Movement Primitives (P-CMPs)

Autonomous trajectory and torque profile synthesis through modulation and generalization require a database of motion with accompanying dynamics, which is typically difficult and time-consuming to obtain. Inspired by adaptive control strategies, this paper presents a novel method for learning and synthesizing Periodic Compliant Movement Primitives (P-CMPs). P-CMPs combine periodic trajectories encoded as Periodic Dynamic Movement Primitives (P-DMPs) with accompanying task-specific Periodic Torque Primitives (P-TPs). The state-of-the-art approach requires to learn TPs for each variation of the task, e.g., modulation of frequency. Comparatively, in this paper, we propose a novel P-TPs framework, which is both frequency and phase-dependent. Thereby, the executed P-CMPs can be easily modulated, and consequently, the learning rate can be improved. Moreover, both the kinematic and the dynamic profiles are parameterized, thus enabling the representation of skills using corresponding parameters. The proposed framework was evaluated on two robot systems, i.e., Kuka LWR-4 and Franka Emika Panda. The evaluation of the proposed approach on a Kuka LWR-4 robot performing a swinging motion and on Franka Emika Panda performing an exercise for elbow rehabilitation shows fast P-CTPs acquisition and accurate and compliant motion in real-world scenarios.
A Neurocinematic Study of the Suspense Effects in Hitchcock's Psycho

As a new and rapidly emerging cross-disciplinary research field, neurocinematics focuses on movie research from an empirical perspective, adopting functional magnetic resonance imaging (fMRI), and other cognitive neuroscience technologies as well as theoretical methods. By verifying and exploring relevant film concepts, neurocinematics tries to establish a scientific basis for the movie theory and better understand frontier subjects in movie studies. We designed this experiment to detect audiences' brain activity when watching movies and verify the manipulation power of narrative film. We selected the shower murder scene in Hitchcock's Psycho as the experimental material. The results of the experiment showed that the trends of the audiences' brain activity were almost consistent with the specific movie plots. By observing audiences' brain activity while watching the movie, the experiment verified the specific effect of Hitchcock's set-up of suspense and explored the neurocognitive brain mechanisms behind the suspense effect.
The Opportunity Cost Of Travel Time In Recreational Fishing Demand Analysis: A South African Case Study

The value individuals place on travel time to recreation sites constitutes an important component of the total travel cost variable in recreational demand analysis. Failure to include the opportunity cost of travel time in travel cost models will lead to an underestimate of the demand and benefit valuation of recreation sites. Using a count data model, this paper calculates the opportunity cost of travel time by inferring it within a recreational fishing demand model estimated. The paper shows that the estimated opportunity cost of travel time for recreational fishing in South Africa is 28 percent of the wage rate or R118,72 per hour. This is somewhat less than the fraction of the wage rate, namely 33 percent, most often employed in TCM studies.
Majority based antenna selection schemes in downlink NOMA network with channel estimation errors and feedback delay

: This paper develops new suboptimal antenna selection (AS) schemes, majority based transmit antenna selection/ maximal ratio combining (TAS-maj/MRC) and joint transmit and receive antenna selection (JTRAS-maj), in a multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) network. The impact of the channel estimation errors (CEEs) and feedback delay (FD) on the performance of the network is studied in Nakagami-m fading channels. First, the outage behavior of the network is investigated in a unified manner for the proposed AS schemes by deriving the closed-form expression of the exact outage probability (OP). Next, in the presence of the CEEs and FD, the corresponding upper bound of the OP is obtained. The OP expression in high signal-to-noise ratio region is then provided to illustrate an error floor value in the presence of the CEEs and FD as well as diversity and array gains in the absence of the CEEs and FD. Finally, the analytical results in the presence and absence of the CEEs and FD are verified by the Monte Carlo simulations. The numerical results show that the proposed majority based AS schemes are superior to both max-max-max and max-min-max based AS schemes and the system performance is more sensitive to the CEE than FD.
Effects of Photographic Reviews on Recollections of the Personal Past: A New Perspective on Benefits and Costs

Empirical studies of the power of photographs on recollections of the personal past have produced a complicated set of results, with reports of both costs and benefits on recollection accuracy. The purpose of the selective review offered in the current paper is to cast in new light this complicated pattern of findings by calling for close attention to the acts of looking, including the timing of the looking in relation to acts of remembering. Incorporating a broad range of scholarly perspectives, the current article’s interdisciplinary component points to specific features of photograph-looking experiences that warrant further study. The current review provides an overview of benefits in memory for event and event details, indexed by enhancements in recall and recognition measures. The overview of costs includes reductions in the amount remembered as well as changes in belief about event occurrences. Reconstruction accounts of the basis for these effects follows the analysis of benefits and costs. The new perspective in the current review leads to intriguing directions for future research involving content of photographs, the ways they are obtained, and aspects of the photograph review experience.
Induction of Salt Tolerance in Arabidopsis thaliana by Volatiles From Bacillus amyloliquefaciens FZB42 via the Jasmonic Acid Signaling Pathway

Previously, we showed that Bacillus amyloliquefaciens FZB42 can confer salt tolerance in plants by root inoculation under salt stress condition, and the FZB42 volatile organic compounds (VOCs) promoted plant growth and development under non-salt stress condition. In the present study, we investigated the mechanism that allows FZB42 VOCs to confer salt tolerance in Arabidopsis without colonization of plant roots. We found that FZB42 VOCs significantly increased the biomass of Arabidopsis and also maintained the leaf chlorophyll content under salt stress condition. Physiological tests showed that the plant anti-oxidation system was activated by FZB42 VOCs, where higher peroxidase (POD), catalase (CAT), and superoxide dismutase (SOD) activities were detected in plants exposed to FZB42 VOCs compared with non-exposed plants. In addition, FZB42 VOCs increased the leaf total soluble sugars (TSS) content but decreased the proline content compared with the non-exposed plants. Moreover, FZB42 VOCs significantly decreased the Na+ contents of the whole plants and induced the expression of genes (NHX1; Na+/H+ exchanger 1 and HKT1; high-affinity K+ transporter 1) that function to alleviate Na+ toxicity. Furthermore, analysis of mutants with defects in specific hormone pathways showed that FZB42 VOCs induced salt tolerance in plants by modulating jasmonic acid (JA) signaling, which was confirmed by the up-regulation of JA synthesis, defense-related genes, and JA biosynthesis inhibitor tests. The results of this study provide new insights into the molecular mechanism related to the interactions between plant growth-promoting rhizobacteria and plants under salt stress condition.
Optimized Electrode Placements for Non-invasive Electrical Stimulation of the Olfactory Bulb and Olfactory Mucosa

The olfactory system is known to be dysfunctional in the early stages of Parkinson’s disease (PD) and Alzheimer’s disease (AD). It is also shown that intact olfactory function can be a key role player for regaining consciousness after brain injuries. Modulation of the olfactory regions has been attempted successfully with electrical stimulation over the years, either directly (transethmoidally, intraoperatively, internasally, etc.) or indirectly through the vagus nerve. We sought to develop a means of delivering optimized electrical stimulation to the olfactory region in a non-invasive fashion and in a way that is simpler, easier, and less cumbersome. The ultimate goal was to develop a system that would allow easier testing in future clinical trials presenting an opportunity to fully develop this potential treatment option. We devised six potential electrode placements leveraging commonly accepted facts of electrical stimulation, easier access through relatively higher conductive pathways into the brain, and practicality. Using an ultra-high-resolution finite element model, we screened each one of these montages for their ability to target the olfactory regions primarily and thereafter for select sub-cortical regions implicated in the pathogenesis of PD and AD. Modeling results indicate that some placements do result in inducing meaningful electric field magnitudes in the regions of interest. A practical headgear concept is proposed to realize the most ideal configuration. Our results pave the way for developing the first non-invasive electrical stimulation wearable system for targeting the olfactory regions which can help to alleviate the symptoms or suppress the progression of these neurological disorders.
Caspase-3 Cleaves Extracellular Vesicle Proteins During Auditory Brainstem Development

Sound localization requires extremely precise development of auditory brainstem circuits, the molecular mechanisms of which are largely unknown. We previously demonstrated a novel requirement for non-apoptotic activity of the protease caspase-3 in chick auditory brainstem development. Here, we used mass spectrometry to identify proteolytic substrates of caspase-3 during chick auditory brainstem development. These auditory brainstem caspase-3 substrates were enriched for proteins previously shown to be cleaved by caspase-3, especially in non-apoptotic contexts. Functional annotation analysis revealed that our caspase-3 substrates were also enriched for proteins associated with several protein categories, including proteins found in extracellular vesicles (EVs), membrane-bound nanoparticles that function in intercellular communication. The proteome of EVs isolated from the auditory brainstem was highly enriched for our caspase-3 substrates. Additionally, we identified two caspase-3 substrates with known functions in axon guidance, namely Neural Cell Adhesion Molecule (NCAM) and Neuronal-glial Cell Adhesion Molecule (Ng-CAM), that were found in auditory brainstem EVs and expressed in the auditory pathway alongside cleaved caspase-3. Taken together, these data suggest a novel developmental mechanism whereby caspase-3 influences auditory brainstem circuit formation through the proteolytic cleavage of extracellular vesicle (EV) proteins.
Recovery of Diabetic Rats After Physical Exhaustion: Kinetic Alterations in Muscle Inflammation and Muscle-Signaling Proteins to Atrophy and Hypertrophy

The complexity of the adaptive response of diabetics to intense exercise is still poorly understood. To optimize exercise interventions in diabetics, the chronology of inflammatory mediators in muscle and the signaling involved in muscle hypertrophy/atrophy must be understood. Herein, we studied the kinetic inflammatory profile and cellular signaling pathways modulated by physical exhaustion after the induction of type 1 diabetes by streptozotocin in rats. Soleus muscle samples were obtained from diabetic and control groups at the following moments: baseline (no exercise); immediately after exhaustive exercise; and at 2 h, 24 h, 48 h, and 72 h after a treadmill exhaustive exercise. Kinetic production of cytokines and kinetic activation of proteins related to muscle synthesis (p70S6K and Akt) and degradation (GSK3, MuRF1, and MAFbx) were measured in the soleus muscle. We observed that the muscle TNF-α (0.9-fold; p = 0.0007), IL-1β (0.8-fold; p = 0.01), IL-6 (0.8-fold; p = 0.0013), L-selectin (1.0-fold; p = 0.0019), and CINC-2α/β (0.9-fold; p = 0.04) levels were higher in almost all stages of the study in the diabetic animals compared with the control group. Our data showed that exhaustive exercise decreased MAFbx expression in diabetic animals compared to the control group in a time-dependent manner. The decreased activation ratios of MAFbx were followed by a decrease in TNF-α, IL-1β, and IL-6 levels. p70S6k phosphorylation was also decreased in the diabetic group compared to the control group after physical exhaustion. Regarding the activation of proteins related to muscle synthesis and degradation, we found that the alterations induced by exhaustive exercise in the diabetic rats might involve pathways related to synthesis and muscle breakdown. Moreover, after an exhaustive exercise session, the recovery of the inflammatory response in the diabetic animals was slower than that in the control rats while the return of inflammatory cytokines to baseline levels was more effective in the diabetic animals.
Weakly supervised monocular depth estimation method based on stereo matching labels

Abstract. Current self-supervised monocular methods only learn effectively by imposing consistency constraints without relying on any geometric constraints or ground truth depth constraints, which makes the accuracy of the estimation result suboptimal. Compared with the monocular algorithm, the stereo matching network usually follows the geometric process of the traditional stereo algorithm, which makes the estimation result more accurate. Inspired by these findings, we proposed a weakly supervised monocular learning approach that makes use of the disparity maps generated by the self-supervised stereo matching model as the “ground truth” labels to train a self-supervised monocular depth estimation model. To obtain more accurate ground truth labels, we improve the layer of geometry and context in self-supervised deep stereo regression by replacing the 3D convolutional layer with a guided aggregation layer. The design can also reduce computational costs and memory consumption. Then, we build our weakly supervised monocular model by improving the U-Net model and designing a loss function composed of a weakly supervised cost and a self-supervised cost. The estimation results obtained using our model outperform those of the existing self-supervised depth estimation methods under the same training conditions on the challenging KITTI dataset, and the results can easily be generalized to the Cityscapes dataset.
Identification and Expression Analysis of Long Non-coding RNA in Large Yellow Croaker (Larimichthys crocea) in Response to Cryptocaryon irritans Infection

Large-scale transcription studies have revealed numerous lncRNAs (long non-coding RNAs). lncRNAs have been proposed to participate in the regulation of a diverse range of biological processes, including transcriptional regulation. Although lncRNAs have attracted increasing attention, the studies in large yellow croaker (Larimichthys crocea) are still rare, and they lack systematic analysis. In this study, 101 RNA-seq datasets varied in ages, sexes, and tissues were retrieved from the NCBI database to generate a comprehensive catalog of large yellow croaker transcriptome database. A set of 14,599 high-confidence lncRNAs from 13,673 loci were identified and characterized. Furthermore, RNA-seq datasets obtained from the infection of C. irritans were employed to investigate the differential expression pattern of lncRNAs and analyze potential biological functions. A total of 77 differentially expressed lncRNAs targeting to 567 protein-coding genes were identified by using expression analysis. Several immune genes, including TLR5, CD2AP, and MMP9, were highlighted. With GO enrichment and KEGG pathway analysis, the immune-related terms or pathways were enriched. This study created a comprehensive dataset of lncRNAs for large yellow croaker, which would be helpful for the researches of functional roles of lncRNAs in large yellow croaker.
Diagnostic Methodologies of Laser-Initiated 11B(p,α)2α Fusion Reactions

The detection of the ionic products of low-rate fusion reactions, and in particular of the 11B(p,α)2α, is one of the recognized main problems in experiments where these reactions are initiated by tailored interaction of intense and high-energy lasers with matter. A thorough description of this important issue, with a critical comparison of the diagnostic opportunities, is indeed so far. In this work, we describe the common diagnostic methodologies used for the detection of the alpha particles generated by the 11B(p,α)2α reaction and, for each, we outline advantages and limitations, with considerations that can also be applied to other low-rate fusion reactions. We show here that, in general, the univocal characterization of the α products coming from this reaction can be achieved by the simultaneous use of several diagnostic tools placed in close proximity.