Miracle-dz/UniFAR-FTUs huggingface dataset:
Reverse Differentiation via Predictive Coding

Deep learning has redefined AI thanks to the rise of artificial neural networks, which are inspired by neuronal networks in the brain. Through the years, these interactions between AI and neuroscience have brought immense benefits to both fields, allowing neural networks to be used in a plethora of applications. Neural networks use an efficient implementation of reverse differentiation, called backpropagation (BP). This algorithm, however, is often criticized for its biological implausibility (e.g., lack of local update rules for the parameters). Therefore, biologically plausible learning methods that rely on predictive coding (PC), a framework for describing information processing in the brain, are increasingly studied. Recent works prove that these methods can approximate BP up to a certain margin on multilayer perceptrons (MLPs), and asymptotically on any other complex model, and that zerodivergence inference learning (Z-IL), a variant of PC, is able to exactly implement BP on MLPs. However, the recent literature shows also that there is no biologically plausible method yet that can exactly replicate the weight update of BP on complex models. To fill this gap, in this paper, we generalize (PC and) Z-IL by directly defining it on computational graphs, and show that it can perform exact reverse differentiation. What results is the first PC (and so biologically plausible) algorithm that is equivalent to BP in the way of updating parameters on any neural network, providing a bridge between the interdisciplinary research of neuroscience and deep learning. Furthermore, the above results in particular also immediately provide a novel local and parallel implementation of BP.
Measuring the Biases and Effectiveness of Content-Style Disentanglement

A recent spate of state-of-the-art semi- and un-supervised solutions disentangle and encode image"content"into a spatial tensor and image appearance or"style"into a vector, to achieve good performance in spatially equivariant tasks (e.g. image-to-image translation). To achieve this, they employ different model design, learning objective, and data biases. While considerable effort has been made to measure disentanglement in vector representations, and assess its impact on task performance, such analysis for (spatial) content - style disentanglement is lacking. In this paper, we conduct an empirical study to investigate the role of different biases in content-style disentanglement settings and unveil the relationship between the degree of disentanglement and task performance. In particular, we consider the setting where we: (i) identify key design choices and learning constraints for three popular content-style disentanglement models; (ii) relax or remove such constraints in an ablation fashion; and (iii) use two metrics to measure the degree of disentanglement and assess its effect on each task performance. Our experiments reveal that there is a"sweet spot"between disentanglement, task performance and - surprisingly - content interpretability, suggesting that blindly forcing for higher disentanglement can hurt model performance and content factors semanticness. Our findings, as well as the used task-independent metrics, can be used to guide the design and selection of new models for tasks where content-style representations are useful.
Deep Learning for Micro-Expression Recognition: A Survey

Micro-expressions (MEs) are involuntary facial movements revealing people's hidden feelings in high-stake situations and have practical importance in various fields. Early methods for Micro-expression Recognition (MER) are mainly based on traditional features. Recently, with the success of Deep Learning (DL) in various tasks, neural networks have received increasing interest in MER. Different from macro-expressions, MEs are spontaneous, subtle, and rapid facial movements, leading to difficult data collection and annotation, thus publicly available datasets are usually small-scale. Currently, various DL approaches have been proposed to solve the ME issues and improve MER performance. In this survey, we provide a comprehensive review of deep MER and define a new taxonomy for the field encompassing all aspects of MER based on DL, including datasets, each step of the deep MER pipeline, and performance comparisons of the most influential methods. The basic approaches and advanced developments are summarized and discussed for each aspect. Additionally, we conclude the remaining challenges and potential directions for the design of robust MER systems. Finally, ethical considerations in MER are discussed. To the best of our knowledge, this is the first survey of deep MER methods, and this survey can serve as a reference point for future MER research.
Decay Estimations of Higher Derivatives of Solutions to Nonlinear Dirac Equation with Spin Null Structure

In 1928, Paul Adrien Maurice Dirac, a British physicist, proposed a relativistic quantum mechanical equation of electron motion, namely, the Dirac equation([8]). The equation predicted the existence of antiparticles and was later confirmed by Carl Anderson’s discovery of positrons in 1932. Except for the physical meanings, this equation is also very important in math. From the point of view of partial differential equation, Dirac equation is the linearization of the famous Klein-Gordon equation. From geometric and algebraic point of view, the study of Dirac equation stimulated the development of Clifford algebra. From the point of view of
The young massive stellar cluster Westerlund 1 in γ rays as seen with

Massive stellar clusters have recently been hypothesised as candidates for the acceleration of hadronic cosmic rays up to PeV energies. Previously, the H.E. S.S. Collaboration has reported about very extended γ-ray emission around Westerlund 1, a massive young stellar cluster in the Milky Way. In this contribution we present an updated analysis that employs a new analysis technique and is based on a much larger data set, allowing us to constrain better the morphology and the energy spectrum of the emission. The analysis technique used is a three-dimensional likelihood analysis, which is especially well suited for largely extended sources. The origin of the γ-ray emission will be discussed in light of multi-wavelength observations.
Media Dependency during COVID-19 Pandemic and Trust in Government: The Case of Bahrain (preprint)

Trust in government indicates a general perception of the government's competence in dealing with crises effectively, which impact political stability. Grounded in the media system dependency theory, this study examines the impact of traditional and new media dependency on trust in government in the context of Bahrain. Therefore, this study proposes to fill this gap by providing empirical evidence leading to advancement in the understanding of media role during covid-19 in enhancing trust in government. To achieve this, the questionnaire was distributed electronically by using google forms. A sample of 463 Bahrainis was selected using non-random sampling methods. The results of this study revealed that the Newspaper and Radio dependency have no impact in predicting trust in government during the covid-19 pandemic. Further, the findings showed a positive relationship between news website dependency and trust in government. However, the relationship was found to be negative between Television and social media dependency and trust in government.
Accuracy of health‐related information regarding COVID‐19 on Twitter during a global pandemic

Abstract This study was performed to analyze the accuracy of health‐related information on Twitter during the coronavirus disease 2019 (COVID‐19) pandemic. Authors queried Twitter on three dates for information regarding COVID‐19 and five terms (cure, emergency or emergency room, prevent or prevention, treat or treatments, vitamins or supplements) assessing the first 25 results with health‐related information. Tweets were authoritative if written by governments, hospitals, or physicians. Two physicians assessed each tweet for accuracy. Metrics were compared between accurate and inaccurate tweets using χ 2 analysis and Mann–Whitney U. A total of 25.4% of tweets were inaccurate. Accurate tweets were more likely written by Twitter authenticated authors (49.8% vs. 20.9%, 28.9% difference, 95% confidence interval [CI]: 17.7–38.2) with accurate tweet authors having more followers (19,491 vs. 7346; 3446 difference, 95% CI: 234–14,054) versus inaccurate tweet authors. Likes, retweets, tweet length, botometer scores, writing grade level, and rank order did not differ between accurate and inaccurate tweets. We found 1/4 of health‐related COVID‐19 tweets inaccurate indicating that the public should not rely on COVID‐19 health information written on Twitter. Ideally, improved government regulatory authority, public/private industry oversight, independent fact‐checking, and artificial intelligence algorithms are needed to ensure inaccurate information on Twitter is removed.
Biodiagnostics in an era of global pandemics—From biosensing materials to data management

The novel corona virus SARS‐CoV‐2 (COVID‐19) has exposed the world to challenges never before seen in fast diagnostics, monitoring, and prevention of the outbreak. As a result, different approaches for fast diagnostic and screening are made and yet to find the ideal way. The current mini‐review provides and examines evidence‐based innovative and rapid chemical sensing and related biodiagnostic solutions to deal with infectious disease and related pandemic emergencies, which could offer the best possible care for the general population and improve the approachability of the pandemic information, insights, and surrounding contexts. The review discusses how integration of sensing devices with big data analysis, artificial Intelligence or machine learning, and clinical decision support system, could improve the accuracy of the recorded patterns of the disease conditions within an ocean of information. At the end, the mini‐review provides a prospective on the requirements to improve our coping of the pandemic‐related biodiagnostics as well as future opportunities.
Selenium inhibits growth of trastuzumab-resistant human breast cancer cells via downregulation of Akt and beclin-1

The response rate to treatment with trastuzumab (Tz), a recombinant humanized anti-HER2 monoclonal antibody, is only 12–34% despite demonstrated effectiveness on improving the survival of patients with HER2-positive breast cancers. Selenium has an antitumor effect against cancer cells and can play a cytoprotective role on normal cells. This study investigated the effect of selenium on HER2-positive breast cancer cells and the mechanism in relation to the response of the cells to Tz. HER2-positive breast cancer cell lines, SK-BR-3 as trastuzumab-sensitive cells, and JIMT-1 as Tz-resistant cells were treated with Tz and sodium selenite (selenite). Cell survival rates and expression of Her2, Akt, and autophagy-related proteins, including LC3B and beclin 1, in both cell lines 72 h after treatment were evaluated. Significant cell death was induced at different concentrations of selenite in both cell lines. A combined effect of selenite and Tz at 72 h was similar to or significantly greater than each drug alone. The expression of phosphorylated Akt (p-Akt) was decreased in JIMT-1 after combination treatment compared to that after only Tz treatment, while p-Akt expression was increased in SK-BR-3. The expression of beclin1 increased particularly in JIMT-1 after only Tz treatment and was downregulated by combination treatment. These results showed that combination of Tz and selenite had an antitumor effect in Tz-resistant breast cancer cells through downregulation of phosphorylated Akt and beclin1-related autophagy. Selenite might be a potent drug to treat Tz-resistant breast cancer by several mechanisms.
Glycosaminoglycan from Ostrea rivularis attenuates hyperlipidemia and regulates gut microbiota in high‐cholesterol diet‐fed zebrafish

Abstract Hyperlipidemia an immense group of acquired or genetic metabolic disorders that is characterized by an excess of lipids in the bloodstream. Altogether, they have a high prevalence worldwide and constitute a major threat to human health. Glycosaminoglycans (GAG) are natural biomolecules that have hypolipidemic activity. The purpose of this study was to investigate the potential hypolipidemic effect of glycosaminoglycans extracted from Ostrea rivularis (OGAG) on hyperlipidemic zebrafish, as well as the possible underlying mechanism of such effect. Dietary supplementation with OGAG during 4 weeks significantly reduced the serum and hepatic lipid levels and the hepatosomatic index in hyperlipidemic zebrafish. In addition, histopathological showed that OGAG supplementation decreases the volume and number of lipid droplets in hepatocytes. Transcriptome and real‐time quantitative polymerase chain reaction analysis revealed that the gene expression levels of PPARγ, SCD, HMGRA, ACAT2, HMGCS, and HMGCR were significantly downregulated by OGAG treatment in hepatocytes, whereas those of CD36, FABP2, FABP6, ABCG5, and CYP7A1 were significantly upregulated. This suggests that the hypolipidemic effect of OGAG relies on increasing the ketogenic metabolism of fatty acids, inhibiting cholesterol synthesis, and enhancing the transformation of cholesterol to bile acid. Furthermore, OGAG treatment improved gut microbiota imbalance by reducing the Firmicutes‐to‐Bacteroidetes ratio, increasing the relative abundance of beneficial bacteria (Bacteroidetes, Verrucomicrobia, Acidobacteria, and Sphingomonas), and reducing the relative abundance of harmful bacteria (Proteobacteria, Cohaesibacter, Vibrio, and Terrisporobacter). These findings highlight the potential benefit of implementing OGAG as a dietary supplement to prevent and treat hyperlipidemia.
Selenium sulfide disrupts the PLAGL2/C‐MET/STAT3‐induced resistance against mitochondrial apoptosis in hepatocellular carcinoma

Abstract Background Hepatocellular carcinoma (HCC) is the third leading cause of cancer‐related deaths worldwide. Overexpression of pleomorphic adenoma gene like‐2 (PLAGL2) is associated with tumorigenesis. However, its function in HCC is unclear, and there are currently no anti‐HCC drugs that target PLAGL2. Drug repositioning may facilitate the development of PLAGL2‐targeted drug candidates. Methods The expression of PLAGL2 in HCC clinical tissue samples and HCC cell lines was analyzed by western blotting. The constructed HCC cell models were used to confirm the underlying function of PLAGL2 as a therapeutic target. Multiple in vitro and in vivo assays were conducted to determine the anti‐proliferative and apoptosis‐inducing effects of selenium sulfide (SeS2), which is clinically used for the treatment of seborrheic dermatitis and tinea versicolor. Results PLAGL2 expression was higher in HCC tumor tissues than in normal adjacent tissues. Its overexpression promoted the resistance of HCC cells of mitochondrial apoptosis through the regulation of the downstream C‐MET/STAT3 signaling axis. SeS2 exerted significant anti‐proliferative and apoptosis‐inducing effects on HCC cells in a PLAGL2‐dependent manner. Mechanistically, SeS2 suppressed C‐MET/STAT3, AKT/mTOR, and MAPK signaling and triggered Bcl‐2/Cyto C/Caspase‐mediated intrinsic mitochondrial apoptosis both in vitro and in vivo. Conclusions Our data reveal an important role of PLAGL2 in apoptosis resistance in HCC and highlight the potential of using SeS2 as a PLAGL2 inhibitor in patients with HCC.
A mixed-methods approach to conceptualizing friendships in anorexia nervosa

Background Individuals with anorexia nervosa have reported feelings of loneliness, social anhedonia, and interpersonal difficulties. This study sought to clarify the nature of interpersonal relationships in adults with anorexia, which may help improve existing interventions while also facilitating the attainment of something that might compete with the drive for thinness: friendships. Methods The present study used a mixed-methods approach to investigate friendship experiences in three groups: anorexia (n = 27), participants with a history of anorexia who are weight restored (n = 20), and healthy controls (n = 24). Thematic analysis was used to isolate the most prevalent themes that emerged from an open-ended interview of experiencing friendships in a subset of participants. Three self-report questionnaires investigating friendship valuation and attachment styles were also administered. Results 11 unique themes emerged in the data: social comparison, reciprocity, trust, fear of negative evaluation, perceived skills deficit, logistical barriers, reliability, identity issue, low interest, similarity, and conflict avoidance. Only 17% of those with anorexia reported experiencing friendships as positive, relative to 82% of healthy controls and 52% of weight restored participants. Lastly, on self-report measures, participants with anorexia reported greater reliance on themselves versus others, greater use of care-seeking behaviors, and more fear/anger at the thought of losing an attachment figure (p < .05 in all cases). Conclusion Results suggest that individuals with anorexia have particular challenges which interfere with the formation and maintenance of friendships, such as viewing friendships negatively and struggling with social comparisons in friendships. Assessing and addressing barriers to intimacy may motivate those with anorexia to relinquish dangerous symptoms that maintain the illness.
Chemical Analysis and Antioxidant and Antimicrobial Activity of Essential oils from Artemisia negrei L. against Drug-Resistant Microbes

Background Artemisia negrei L. (A. negrei) is a medicinal and aromatic plant belonging to the family Asteraceae that is more widespread in the folded Middle Atlas Mountains, Morocco. Materials and Methods This study was run to investigate the phytochemical composition and antioxidant, antibacterial, and antifungal activities of Artemisia negrei L. essential oil. This oil was extracted from the fresh plant material by using the Clevenger apparatus. The phytochemical composition was characterized by GC-MS. The antioxidant activity was evaluated using different methods including DPPH, β-carotene bleaching, and total antioxidant capacity. The antibacterial activity was tested vs. multidrug-resistant bacteria including both Gram-negative and Gram-positive using inhibition zones in agar media and minimum inhibitory concentration (MIC) bioassays. The antifungal activity was conducted on Candida albicans, Aspergillus niger, Aspergillus flavus, and Fusarium oxysporum using a solid medium assay. Results The chromatographic characterization of essential oils of A. negrei revealed the presence of 34 compounds constituting 99.91% of the total essential oil. The latter was found to have promising antioxidant activity by all bioassays used such as DPPH, β-carotene bleaching, and total antioxidant capacity. The results obtained showed that our plant oils had potent antibacterial activity towards Gram-negative (E. coli 57, E. coli 97, K. pneumonia, and P. aeruginosa) and Gram-positive (S. aureus), so that the maximum inhibition zones and MIC values were around 18–37 mm and 3.25 to 12.5 mg/mL, respectively. The oil also showed antifungal activity towards Candida albicans, Fusarium oxysporum, and Aspergillus Niger except for flavus species. Conclusion The findings obtained in the work showed that A. negrei can serve as a valuable source of natural compounds that can be used as a new weapon to fight radical damage and resistant microbes.
Sexual Disorders in Women with Overactive Bladder and Urinary Stress Incontinence Compared to Controls: A Prospective Study

Abstract Introduction and Hypothesis Female urinary incontinence (UI) has a negative impact on sexual function and sexual quality of life (QoL) in women. But there is still no consensus on the type of UI or the prevalence of sexual dysfunction (SD). The aim of the study was to evaluate sexual disorders in women with overactive bladder (OAB) compared to patients with urinary stress incontinence (SUI) and healthy controls. Materials and Methods 106 women presenting to a urogynecological outpatient clinic (referral clinic) were investigated using standardized questionnaires and the Female Sexual Function Index (FSFI-d). All 65 incontinent women underwent a full urodynamic examination; the controls (31) were non-incontinent women in the same age range who came for routine check-ups or minor disorders not involving micturition or pelvic floor function. Women with mixed urinary incontinence, a history of previous medical or surgical treatment for UI, recurrent urinary tract infections, previous radiation therapy or pelvic organ prolapse of more than stage 2 on the Pelvic Organ Prolapse Quantification (POP-Q) system were excluded. Results 100 questionnaires could be evaluated (94.3%). Thirty-four women had urinary stress incontinence, 35 had OAB, 31 were controls. Mean age was 56 years, with no significant differences between groups. The scores of the questionnaire ranged from 2 to 35.1 points. The median score of OAB patients was significantly lower (17.6) than the median score of the controls (26.5; p = 0,004). The stress-incontinent women had a score of 21.95, which was lower than that of the controls but statistically non-significant (p = 0.051). In all subdomains, the OAB patients had lower scores than the stress-incontinent women and significantly lower values than the control group. Most striking was the impairment of “sexual interest in the last 4 weeks”. The figure for “none or almost no sexual activity” was 80% for the OAB group, 64.7% for the group of stress-incontinent women and 48% for the control group. Incontinence during intercourse was reported by one OAB patient and 4 stress-incontinent women but did not occur in the control group. Conclusions There is a high prevalence of SD in women with urinary incontinence. Patients with OAB reported a greater negative impact on sexual function and had significantly lower scores for the FSFI questionnaire than patients with stress incontinence or controls.