Miracle-dz/UniFAR-FTUs huggingface dataset:
Observational Learning in Low-Functioning Children With Autism Spectrum Disorders: A Behavioral and Neuroimaging Study

New skills may be learned from the outcomes of their own internally generated actions (experiential learning) or from the observation of the consequences of externally generated actions (observational learning). Observational learning requires the coordination of cognitive functions and the processing of social information. Due to the “social” abilities underlying observational learning, the study of this process in individuals with limited social abilities such as those affected by Autism Spectrum Disorders (ASD) is worthy of being investigated. We asked a group of 16 low-functioning young children with ASD and group of 16 sex- and mental age-matched typically developing (TD) children to build a house with a set of bricks after a video-demonstration showing an actor who built the house (observational task – OBS task) and then to build by trial and error another house (experiential task – EXP task). For ASD group, performances in learning tasks were correlated with measures of cortical thickness of specific Regions of Interest (ROI) and volume of deep gray matter structures known to be related with such kinds of learning. According to our a priori hypothesis, for OBS task we selected the following ROI: frontal lobe (pars opercularis, pars triangularis, and premotor area), parietal lobe (inferior parietal gyrus), temporal lobe (superior temporal gyrus), cerebellar hemispheres. For EXP task, we selected the following ROI: precentral frontal gyrus and superior frontal gyrus, cerebellar hemispheres, basal ganglia, thalamus. Although performances of ASD and TD children improved in both OBS and EXP tasks, children with ASD obtained lower scores of goal achievement than TD children in both learning tasks. Only in ASD group, goal achievement scores positively correlated with hyperimitations indicating that children with ASD tended to have a “copy-all” approach that facilitated the goal achievement. Moreover, the marked hyperimitative tendencies of children with ASD were positively associated with the thickness of left pars opercularis, left premotor area, and right superior temporal gyrus, areas belonging to mirror neuron system, and with the volume of both cerebellar hemispheres. These findings suggest that in children with ASD the hyperimitation can represent a learning strategy that might be related to the mirror neuron system.
Neural Network Connectivity During Post-encoding Rest: Linking Episodic Memory Encoding and Retrieval

Commonly, a switch between networks mediating memory encoding and those mediating retrieval is observed. This may not only be due to differential involvement of neural resources due to distinct cognitive processes but could also reflect the formation of new memory traces and their dynamic change during consolidation. We used resting state fMRI to measure functional connectivity (FC) changes during post-encoding rest, hypothesizing that during this phase, new functional connections between encoding- and retrieval-related regions are created. Interfering and reminding tasks served as experimental modulators to corroborate that the observed FC differences indeed reflect changes specific to post-encoding rest. The right inferior occipital and fusiform gyri (active during encoding) showed increased FC with the left inferior frontal gyrus and the left middle temporal gyrus (MTG) during post-encoding rest. Importantly, the left MTG subsequently also mediated successful retrieval. This finding might reflect the formation of functional connections between encoding- and retrieval-related regions during undisturbed post-encoding rest. These connections were vulnerable to experimental modulation: Cognitive interference disrupted FC changes during post-encoding rest resulting in poorer memory performance. The presentation of reminders also inhibited FC increases but without affecting memory performance. Our results contribute to a better understanding of the mechanisms by which post-encoding rest bridges the gap between encoding- and retrieval-related networks.
Respiratory Virus Infections in Hematopoietic Cell Transplant Recipients

Highly immunocompromised pediatric and adult hematopoietic cell transplant (HCT) recipients frequently experience respiratory infections caused by viruses that are less virulent in immunocompetent individuals. Most of these infections, with the exception of rhinovirus as well as adenovirus and parainfluenza virus in tropical areas, are seasonal variable and occur before and after HCT. Infectious disease management includes sampling of respiratory specimens from nasopharyngeal washes or swabs as well as sputum and tracheal or tracheobronchial lavages. These are subjected to improved diagnostic tools including multiplex PCR assays that are routinely used allowing for expedient detection of all respiratory viruses. Disease progression along with high mortality is frequently associated with respiratory syncytial virus, parainfluenza virus, influenza virus, and metapneumovirus infections. In this review, we discuss clinical findings and the appropriate use of diagnostic measures. Additionally, we also discuss treatment options and suggest new drug formulations that might prove useful in treating respiratory viral infections. Finally, we shed light on the role of the state of immune reconstitution and on the use of immunosuppressive drugs on the outcome of infection.
PKR: A Kinase to Remember

Aging is a major risk factor for many diseases including metabolic syndrome, cancer, inflammation, and neurodegeneration. Identifying mechanistic common denominators underlying the impact of aging is essential for our fundamental understanding of age-related diseases and the possibility to propose new ways to fight them. One can define aging biochemically as prolonged metabolic stress, the innate cellular and molecular programs responding to it, and the new stable or unstable state of equilibrium between the two. A candidate to play a role in the process is protein kinase R (PKR), first identified as a cellular protector against viral infection and today known as a major regulator of central cellular processes including mRNA translation, transcriptional control, regulation of apoptosis, and cell proliferation. Prolonged imbalance in PKR activation is both affected by biochemical and metabolic parameters and affects them in turn to create a feedforward loop. Here, we portray the central role of PKR in transferring metabolic information and regulating cellular function with a focus on cancer, inflammation, and brain function. Later, we integrate information from open data sources and discuss current knowledge and gaps in the literature about the signaling cascades upstream and downstream of PKR in different cell types and function. Finally, we summarize current major points and biological means to manipulate PKR expression and/or activation and propose PKR as a therapeutic target to shift age/metabolic-dependent undesired steady states.
Variations in Soil Bacterial Composition and Diversity in Newly Formed Coastal Wetlands

Coastal ecosystems experience some of the most active land–ocean interactions in the world, and they are characterized by high primary productivity and biological diversity in the sediment. Given the roles of microorganisms in soil biogeochemical cycling and their multifaceted influence on soil ecosystems, it is critical to understand the variations and drivers of soil microbial communities across coastal ecosystems. Here, we studied soil bacterial community dynamics at different sites (from seawater to freshwater) in the Yellow River Delta, China. Bacterial community composition and diversity over four seasons were analyzed through 16S rRNA genes. Notably, the bacterial community near the ocean had the lowest alpha-diversity when compared with the other sites. No significant differences in bacterial communities among seasons were found, indicating that seasonal variation in temperature had little influence on bacterial community in the newly formed wetlands in the Yellow River Delta. Bacterial community structure changed substantially along the salinity gradient, revealing a clear ecological replacement along the gradual transformation gradient from freshwater to seawater environment. Redundancy analysis revealed that salinity was the main driver of variations in bacterial community structure and explained 17.5% of the variability. Our study provides a better understanding of spatiotemporally determined bacterial community dynamics in coastal ecosystems.
Clinical Relevance of Galectin-1 and Galectin-3 in Rheumatoid Arthritis Patients: Differential Regulation and Correlation With Disease Activity

Galectins, a family of animal lectins, play central roles in immune system regulation, shaping both innate and adaptive responses in physiological and pathological processes. These include rheumatoid arthritis (RA), a chronic multifactorial autoimmune disease characterized by inflammatory responses that affects both articular and extra-articular tissues. Galectins have been reported to play central roles in RA and its experimental animal models. In this perspective article we present new data highlighting the regulated expression of galectin-1 (Gal-1) and galectin-3 (Gal-3) in sera from RA patients under disease-modifying anti-rheumatic drugs (DMARDs) and/or corticoid treatment in the context of a more comprehensive discussion that summarizes the roles of galectins in joint inflammation. We found that Gal-1 levels markedly increase in sera from RA patients and positively correlate with erythrocyte sedimentation rate (ERS) and disease activity score 28 (DAS-28) parameters. On the other hand, Gal-3 is downregulated in RA patients, but positively correlates with health assessment questionnaire parameter (HAQ). Finally, by generating receiver-operator characteristic (ROC) curves, we found that Gal-1 and Gal-3 serum levels constitute good parameters to discriminate patients with RA from healthy individuals. Our findings uncover a differential regulation of Gal-1 and Gal-3 which might contribute to the anti-inflammatory effects elicited by DMARDs and corticoid treatment in RA patients.
Glucose Homeostasis Is Not Affected in a Murine Model of Parkinson’s Disease Induced by 6-OHDA

There is a mutual relationship between metabolic and neurodegenerative diseases. However, the causal relationship in this crosstalk is unclear and whether Parkinson’s disease (PD) causes a posterior impact on metabolism remains unknown. Considering that, this study aimed to evaluate the appearance of possible changes in metabolic homeostasis due to 6-hydroxydopamine (6-OHDA) administration, a neurotoxin that damage dopaminergic neurons leading to motor impairments that resemble the ones observed in PD. For this, male Wistar rats received bilateral 6-OHDA administration in the dorsolateral striatum, and the motor and metabolic outcomes were assessed at 7, 21, or 35 days post-surgical procedure. Dexamethasone, a diabetogenic glucocorticoid (GC), was intraperitoneally administered in the last 6 days to challenge the metabolism and reveal possible metabolic vulnerabilities caused by 6-OHDA. Controls received only vehicles. The 6-OHDA-treated rats displayed a significant decrease in locomotor activity, exploratory behavior, and motor coordination 7 and 35 days after neurotoxin administration. These motor impairments paralleled with no significant alteration in body mass, food intake, glucose tolerance, insulin sensitivity, and biochemical parameters (plasma insulin, triacylglycerol, and total cholesterol levels) until the end of the experimental protocol on days 35–38 post-6-OHDA administration. Moreover, hepatic glycogen and fat content, as well as the endocrine pancreas mass, were not altered in rats treated with 6-OHDA at the day of euthanasia (38th day after neurotoxin administration). None of the diabetogenic effects caused by dexamethasone were exacerbated in rats previously treated with 6-OHDA. Thus, we conclude that bilateral 6-OHDA administration in the striatum causes motor deficits in rats with no impact on glucose and lipid homeostasis and does not exacerbate the adverse effects caused by excess GC. These observations indicate that neurodegeneration of dopaminergic circuits in the 6-OHDA rats does not affect the metabolic outcomes.
Influence of Lactobacillus plantarum P-8 on Fermented Milk Flavor and Storage Stability

Previously, we demonstrated that the flavor of milk fermented with Lactobacillus delbrueckii subsp. bulgaricus (IMAU20401) and Streptococcus thermophilus (IMAU40133) at a 1:1000 ratio was superior to that of other ratios of the two strains. In this study, Lactobacillus plantarum P-8 was used as the probiotic bacterium. Six ratios (1:1, 1:5, 1:10, 1:50, 1:100, and 1:1000) of L. plantarum P-8 to yogurt starter were evaluated. A total of 66 volatile compounds including aldehydes, ketones, acids, alcohols, esters, alcohols, and aromatic compounds were identified in milk fermented with the six different L. plantarum P-8 to yogurt starter ratios at 0 d of storage. In particular, key flavor compounds, such as 3-methylbutanal, hexanal, (E)-2-octenal, nonanal, 2-heptanone, 2-nonanone, and acetoin, were identified in the 1:100 ratio treatment. Furthermore, the viable cell count, pH, titratable acidity, viscosity, and syneresis of the milk samples were analyzed during fermentation over 14 d of storage at 4°C. The results indicated that milk can be fermented with L. plantarum P-8 in combination with S. thermophilus and L. delbrueckii subsp. bulgaricus, and the physicochemical characteristics of the milk were not affected by the probiotic bacteria.
Entrepreneurial Passion and Personality: The Case of Academic Entrepreneurship

Since entrepreneurial thinking and acting within organizations is increasingly important for the success of organizations, entrepreneurial passion is an emerging key construct in the study of organizational behavior. Here we quantify effects of personality traits on entrepreneurial passion in organizations, thereby comparing a person- vs. variable-oriented trait approach and testing such effects against alternative explanation models (rational choice approach, social learning approach, and social identity approach). Analyzing data from N = 137 German scientists across two measurement occasions, structural equation modeling revealed that an entrepreneurial Big Five profile (person-oriented approach), but none of the single Big Five traits (variable-oriented approach), predicted entrepreneurial passion (which in turn mediated the link between this domain-specific personality profile and entrepreneurial behavior). Likewise, the entrepreneurial personality profile, but not the single Big Five traits, predicted the simultaneous occurrence of entrepreneurial passion and behavior (passionate entrepreneurial behavior). Interestingly, the alternative explanation models (rational choice approach, social learning approach, and social identity approach) failed to predict entrepreneurial passion and passionate entrepreneurial behavior. The results suggest that the basic entrepreneurial personality character of a person contributes to the shaping of his or her entrepreneurial passion, which is relevant for actual entrepreneurial activity. The results thus illustrate how a person-oriented trait approach can inform the study, and concepts of, entrepreneurial passion.
The Invisibility of Women's Organizations in Decision Making Process and Governance in Nigeria

The most fascinating development in politics has been the increase in women’s political participation globally. Women are becoming more engaged in variety of institutional decision making processes and Africa appears to be leading in women’s parliamentary representation. Since the re-birth of democracy in Nigeria in 1999, women have tried to gain access to decision making positions by contesting at various political levels and representation of women’s organizations on various policy debates have increased at local and national levels. However, their efforts appear not to be greeted with much gains as the result seems not very encouraging. What is problematic is whether the representation of women’s organization in democracy and decision making in Nigeria is descriptive or substantive. Even when women’s organizations are represented in the decision making arena, it appears that their influence were not much felt. This paper will investigate the invisibility or otherwise of women’s organizations in decision making process and governance in Nigeria, its implications and Challenges. The study employed descriptive survey research design. Purposive sampling technique was used to select the six South Western States in Nigeria and 150 respondents from women’s organizations who were willing to participate in the study. A self-designed instrument was used to gather data for the study. The research instrument was validated and texted for its level of reliability, using Pearson Product Moment Correlation Analysis for its co-efficient. Nine research questions were generated to guide the study. The data obtained were analyzed using descriptive analysis, frequency counts and percentages. The findings revealed that the roles played by women’s organizations in decision making arena was significant but not visible and unappreciated. It was therefore, recommended that women’s organizations should do all they can to be more active in governance and encourage more women to be fully involved in decision making process in Nigeria for national development. Keywords: Women’s organizations, decision making, invisibility, descriptive, substantive representation.
Venue matching in social network APIs using neural networks

A multitude of social media APIs from popular services such as Facebook, Twitter and Google, allow programmers access to user generated data that is pertinent to physical venues represented within these services. In our paper, we attempt to address the issue of automatically matching venue representations from these diverse APIs, in order to obtain a more complete representation of user cyber-physical interaction with these venues. We present our work comparing a neural network approach against Nearest Point and Longest Common Substring algorithms.
Detecting anomalies in Kotlin code

This paper discusses code anomalies - code fragments that are written in some way that is not typical for the programming language community. Such code fragments are useful for language creators as performance tests, or they could provide insights on how to improve the language. With Kotlin as the target language, we discuss how the task of detecting code anomalies for a very large codebase could be solved using well-known anomaly detection techniques. We outline and discuss approaches to obtain code vector representation and to perform anomaly detection on such vectorized data. The paper concludes with our preliminary results.
A Quantitative and Comparative Study of Network-Level Efficiency for Cloud Storage Services

Cloud storage services such as Dropbox and OneDrive provide users with a convenient and reliable way to store and share data from anywhere, on any device, and at any time. Their cornerstone is the data synchronization (sync) operation, which automatically maps the changes in users’ local file systems to the cloud via a series of network communications in a timely manner. Without careful design and implementation, however, the data sync mechanisms could generate overwhelming traffic, causing tremendous financial overhead and performance penalties to both service providers and end users. This article addresses a simple yet critical question: Is the current data sync traffic of cloud storage services efficiently used? We first define a novel metric TUE to quantify the Traffic Usage Efficiency of data synchronization. Then, by conducting comprehensive benchmark experiments and reverse engineering the data sync processes of eight widely used cloud storage services, we uncover their manifold practical endeavors for optimizing the TUE, including three intra-file approaches (compression, incremental sync, and interrupted transfer resumption), two cross-file/-user approaches (i.e., deduplication and peer-assisted offloading), two batching approaches (file bundling and sync deferment), and two web-specific approaches (thumbnail views and dynamic content loading). Our measurement results reveal that a considerable portion of the data sync traffic is, in a sense, wasteful and can be effectively avoided or significantly reduced via carefully designed data sync mechanisms. Most importantly, our study not only offers practical, actionable guidance for providers to build more efficient, traffic-economic services, but also helps end users pick appropriate services that best fit their use cases and budgets.
An Apache Spark implementation for graph-based hashtag sentiment classification on Twitter

Sentiment Analysis has been extensively investigated in recent years as a method of human emotions' classification to specific events, products, services etc. It is considered as a very important problem, especially for organizations or companies who want to know the consumers' view about their products and services. In combination with the evolution of social media, it has been established as an interesting domain of research. Through social media, people tend to express their opinions or feelings, such as happiness or sadness on a daily basis. Thus, the vast amount of available data has made the existing solutions inappropriate and the need for automated analysis methods is imperative. In this paper, we examine sentiment polarity analysis on Twitter data in a distributed environment, known as Apache Spark. More specifically, inspired from [23], we propose three classification algorithms for tweet level sentiment analysis in Spark due to its suitability for Big Data processing against its predecessors, MapReduce and Hadoop.
Inconsistent calculation methodology for the eucapnic voluntary hyperpnoea test affects the diagnosis of exercise-induced bronchoconstriction

Introduction The eucapnic voluntary hyperpnoea (EVH) challenge is used to screen for exercise-induced bronchoconstriction. Several criteria have been proposed to determine the decrease in lung function (fall index, FI) following EVH. We compared three published FI calculation methods to determine if they affect the diagnostic classification. Methods The three FIs were calculated for 126 EVH tests. Spirometry was performed in duplicate at baseline and repeated 3, 5, 10, 15 and 20 min following 6 min of EVH. The higher of the two forced expiratory volume in 1 s (FEV1) measures at all time-points post-hyperpnoea was selected for the calculation of the FIs. The FIA was determined as the single lowest of the five postchallenge values, and a test was considered positive if FEV1 decreased ≥10 %. In FIB, a test was considered positive if FEV1 decreased ≥10% at two consecutive post-challenge time-points. The FIC was calculated identically to FIA, but was normalised to the achieved minute ventilation during the EVH challenge. Results Calculation method affected the raw FIs with FIB generating the smallest and FIC generating the highest values (p<0.001) and a within-subject range of 7%±10%. The number of positive tests differed between the calculation criteria: FIA: 62, FIB: 48 and FIC: 70, p<0.001. Nineteen participants (15%) tested positive in one or two FI methods only, indicating that the FI method used determined whether the test was positive or negative. Discussion Inconsistency in methodology of calculating the FI leads to differences in the diagnostic rate of the EVH test, with potential implications in both treatment and research outcomes.