Miracle-dz/UniFAR-FTUs huggingface dataset:
A few lessons learned in reinforcement learning for quadcopter attitude control

In the context of developing safe air transportation, our work is focused on understanding how Reinforcement Learning methods can improve the state of the art in traditional control, in nominal as well as non-nominal cases. The end goal is to train provably safe controllers, by improving both training and verification methods. In this paper, we explore this path for controlling the attitude of a quadcopter: we discuss theoretical as well as practical aspects of training neural nets for controlling a crazyflie 2.0 drone. In particular we describe thoroughly the choices in training algorithms, neural net architecture, hyperparameters, observation space etc. We also discuss the robustness of the obtained controllers, both to partial loss of power for one rotor and to wind gusts. Finally, we measure the performance of the approach by using a robust form of a signal temporal logic to quantitatively evaluate the vehicle's behavior.
Automated detection of artefacts in neonatal EEG with residual neural networks

Background and Objective To develop a computational algorithm that detects and identifies different artefact types in neonatal electroencephalography (EEG) signals. Methods As part of a larger algorithm, we trained a Residual Deep Neural Network on expert human annotations of EEG recordings from 79 term infants recorded in a neonatal intensive care unit (112 h of 18-channel recording). The network was trained using 10 fold cross validation in Matlab. Artefact types included: device interference, EMG, movement, electrode pop, and non-cortical biological rhythms. Performance was assessed by prediction statistics and further validated on a separate independent dataset of 13 term infants (143 h of 3-channel recording). EEG pre-processing steps, and other post-processing steps such as averaging probability over a temporal window, were also included in the algorithm. Results The Residual Deep Neural Network showed high accuracy (95%) when distinguishing periods of clean, artefact-free EEG from any kind of artefact, with a median accuracy for individual patient of 91% (IQR: 81%-96%). The accuracy in identifying the five different types of artefacts ranged from 57%-92%, with electrode pop being the hardest to detect and EMG being the easiest. This reflected the proportion of artefact available in the training dataset. Misclassification as clean was low for each artefact type, ranging from 1%-11%. The detection accuracy was lower on the validation set (87%). We used the algorithm to show that EEG channels located near the vertex were the least susceptible to artefact. Conclusion Artefacts can be accurately and reliably identified in the neonatal EEG using a deep learning algorithm. Artefact detection algorithms can provide continuous bedside quality assessment and support EEG review by clinicians or analysis algorithms. Highlights We applied a Residual Deep Neural Network as part of an artefact detection algorithm in neonatal electroencephalograms. The algorithm shows high accuracy in identifying artefactual data in general and for specific artefact types. EEG channels near the top of the head are less prone to artefact.
Controllable drug release of pH-sensitive liposomes encapsulating artificial cytosol system

The fabrication of cell model containing artificial cytosol is challenging. Herein we constructed an artificial cytosol contained cell model by electroformation method. Agarose was selected as the main component of the artificial cytosol. Sucrose was added into agarose to regulate the sol viscosity and phase transition temperature (Tm). The viscosity of the sol with the mass ratio (agarose-sucrose) 1:9 was closest to the natural cytosolic. DSPC/20 mol% Chol was used to form large unilamellar vesicle (LUV) as cell model compartment. The rhodamine release experiment confirmed that the release of rhodamine from LUVs containing artificial cytosol took more time than that from LUVs containing pure water. The unique release profile makes agarose-sucrose@LUVs suitable as a drug carrier. Doxorubicin (DOX) is loaded in the agarose-sucrose@LUVs, and their half maximum inhibition concentration on HeLa cells is 0.015 μmol L−1, which means 31.7 times increase in inhibition efficiency over free DOX.
A defined medium based on R2A for cultivation and exometabolite profiling of soil bacteria

Exometabolomics is an approach to assess how microorganisms alter their environments through the depletion and secretion of chemical compounds. Comparisons of inoculated with uninoculated media can be used to provide direct biochemical observations on depleted and secreted metabolites which can be used to predict resource competition, cross-feeding and secondary metabolite production in microbial isolates and communities. This approach is most powerful when used with defined media that enable tracking of all depleted metabolites. However, microbial growth media have traditionally been developed for the isolation and growth of microorganisms but not metabolite utilization profiling through LC-MS/MS. Here, we describe the construction of a defined medium, the Northen Lab Defined Medium (NLDM), that not only supports the growth of diverse bacteria but is defined and therefore suited for exometabolomic experiments. Metabolites included in NLDM were selected based on their presence in R2A medium and soil, elemental stoichiometry requirements, as well as knowledge of metabolite usage by different bacteria. We found that NLDM supported the growth of 53 phylogenetically diverse soil bacterial isolates and all of its metabolites were trackable through LC–MS/MS analysis. These results demonstrate the viability and utility of the constructed NLDM medium for cultivating and characterizing diverse microbial isolates and communities. Originality-Significance Statement We build a defined medium based on the metabolite composition of R2A medium and soil, elemental stoichiometry requirements, and knowledge of metabolite usage by different bacteria. The newly formulated defined medium was evaluated on its ability to support the growth of soil isolates and its application for metabolite utilization profiling. We found that of 53 phylogenetically diverse soil bacterial isolates grew on the defined medium and all of its metabolites were trackable through LC–MS/MS analysis. This demonstrates the viability and utility of the constructed defined medium for cultivating and characterizing diverse microbial isolates and communities.
Natural variation in a short region of the Acidovorax citrulli type III-secreted effector AopW1 is associated with differences in cytotoxicity

Bacterial fruit blotch (BFB) is a serious disease of melon and watermelon caused by the Gram-negative bacterium Acidovorax citrulli. The strains of the pathogen can be divided into two major genetic groups, I and II. While group I strains are strongly associated with melon, group II strains are more aggressive on watermelon. Like many pathogenic bacteria, A. citrulli secretes a variety of protein effectors to the host cell via the type III secretion system. In the present study, we characterized AopW1, an A. citrulli type III-secreted effector that shares similarity with the actin cytoskeletondisrupting effector HopW1 of Pseudomonas syringae and with effectors from other plant-pathogenic bacterial species. aopW1 is present in group I and II strains, encoding products of 485 amino acids. Although highly conserved in most of the sequence, AopW1 has a highly variable region (HVR) within amino acid positions 147 to 192, including 14 amino acid differences between groups. Here we show that group I AopW1 is more toxic to yeast and plant cells than group II AopW1, having a stronger actin filament disruption activity, and increased ability to reduce plant callose deposition. We demonstrate the role of some of these 14 amino acid positions in determining the phenotypic differences between the two versions of the effector. Moreover, cellular analyses revealed that in addition to the interaction with actin filaments, AopW1 is localized to the endoplasmic reticulum, chloroplasts, and early and recycling plant endosomes, with differences observed between the two AopW1 versions. Finally, we show that overexpression of the endosome-associated protein EHD1 that increases cellular recycling, attenuates the toxic effects exerted by AopW1 and increases defence responses. This study provides insights into the HopW1 family of bacterial effectors and their interactions with the plant cell and provides first evidence on the involvement of EHD1 in response to biotic stress.
The Molecular Logic Organizing the Functional Compartmentalization of Reciprocal Synapses

Reciprocal synapses are formed by neighboring dendritic processes that create the smallest possible neural circuit. Reciprocal synapses are widespread in brain and essential for information processing, but constitute a conceptual conundrum: How are adjacent pre- and post-synaptic specializations maintained as separate functional units? Here, we reveal an organizational principle for reciprocal synapses, using dendrodendritic synapses between mitral and granule cells in the mouse olfactory bulb as a paradigm. We show that mitral cells secrete cerebellin-1 to block the cis-interaction of mitral cell neurexins with neuroligins, thereby enabling their separate trans-interactions. Ablating either cerebellin-1 or neuroligins in mitral cells severely impaired granule cell→mitral cell synapses, as did overexpression of postsynaptic neurexins that form cis-complexes with neuroligins, but not of mutant neurexins unable to bind to neuroligins. Our data uncover a cis/trans-protein interaction network as a general design principle that organizes reciprocal dendro-dendritic synapses by compartmentalizing neurexin-based trans-synaptic protein complexes.
Evidence for Deleterious Original Antigenic Sin in SARS-CoV-2 Immune Response

A previous report demonstrated the strong association between the presence of antibodies binding to an epitope region from SARS-CoV-2 nucleocapsid, termed Ep9, and COVID-19 disease severity. Patients with anti-Ep9 antibodies (Abs) had hallmarks of original antigenic sin (OAS), including early IgG upregulation and cytokine-associated injury. Thus, the immunological memory of a previous infection was hypothesized to drive formation of suboptimal anti-Ep9 Abs in severe COVID-19 infections. This study identifies a putative original antigen capable of stimulating production of cross-reactive, anti-Ep9 Abs. From bioinformatics analysis, 21 potential “original” epitope regions were identified. Binding assays with patient blood samples directly show cross-reactivity between Abs binding to Ep9 and only one homologous potential antigen, a sequence derived from the neuraminidase protein of H3N2 Influenza A virus. This cross-reactive binding affinity is highly virus strain specific and sensitive to even single amino acid changes in epitope sequence. The neuraminidase protein is not present in the influenza vaccine, and the anti-Ep9 Abs likely resulted from the widespread influenza infection in 2014. Therefore, OAS from a previous infection could underlie some cases of COVID-19 disease severity and explain the diversity observed in disease outcomes.
Antioxidant, color and sensory properties of sorghum bran in pre-cooked ground beef patties varying in fat and iron content

Antioxidant, Color and Sensory Properties of Sorghum Bran in Pre-Cooked Ground Beef Patties Varying in Fat and Iron Content. (December 2006) Dae Keun Shin, B.S., Jeonbuk National University; M.S., Seoul National University Co-Chairs of Advisory Committee: Dr. Rhonda K. Miller Dr. Jimmy T. Keeton The effect of currently used antioxidants and sorghum bran in pre-cooked beef patties was evaluated at two different fat levels (10 and 27%, w/w). Pre-formulated ground beef was purchased at a retail store on three different processing days. Within each fat level, ground beef portions were weighed and randomly assigned to control, butylated hydroxanisole (BHA) and butylated hydroxytoluene (BHT) (0.001%), rosemary (0.25%) or sorghum bran (0.25, 0.5 or 1.0%). After mixing in the appropriate antioxidant, 200-g patties were formed, and pH and objective color measurements for each raw patty were performed. Patties were cooked to an internal temperature of 73C. Cooked patties were packaged and stored at 4C. Two patties per treatment were sampled after 0, 1, 3 and 5 d of storage and analyzed for 2-thiobarbituric acid reactive substances (TBARS), non-heme iron, pH, instrumental color and trained flavor and texture descriptive attributes. The addition of BHA/BHT and rosemary extract to patties reduced non-heme iron, TBARS values, and cooked beef fat flavor attributes, but increased beef/brothy flavor attributes relative to control patties (P<0.05). As sorghum bran level increased, cooked beef patties were darker (P<0.05), less yellow (P<0.05), had higher non-heme iron
Effective properties of piezoceramics with metal inclusions: numerical analysis

Abstract The paper considers the problem of determining the effective properties of piezoceramics with metal inclusions. The homogenization problem was numerically solved in the representative volume with closed structure of inclusions. The effective moduli behavior was analyzed depending on the fraction of inclusions for piezoceramic PZT-5A with platinum inclusions. An increase in the effective stiffness moduli, the longitudinal and shear piezoelectric stress coefficients, and a considerable increase in the dielectric permittivities were discovered with the growth of the metal inclusions fraction. The effective dielectric permittivities grew for the same fraction of inclusions when the relative size of inclusions increased.
Ultrafine Titania Photocatalytic Materials Synthesized by High Temperature Reaction in TiCl_4-O_2 System

Ultrafine titania particles were synthesized by the gas-phase oxidation of titanium tetrachloride in a high temperature tubular aerosol flow reactor. The measurement of EDS, TG-DTA,TEM, XRD and BET surface area was used to characterize the particles. The effect of residencetime and reaction temperature on the morphology of titania particles was investigated. The resultsshowed the average particle size of titania became larger and rutile weight fraction increased as theresidence time increased, and the maximum rutile weight fraction was attained at 1300 and theparticle size increased with increasing temperature. The prepared particles and commercial TiO2were employed for photocatalytic degradation of azo dye active red X--3B in aerated solution. Theresults showed that the photoactivity of the titania particles of average size 35.3nm and 18.97%rutile fraction was higher than that of P25 and SH--1.
Wnt3 Is Lipidated at Conserved Cysteine and Serine Residues in Zebrafish Neural Tissue

Wnt proteins are a family of hydrophobic cysteine-rich secreted glycoproteins that regulate a gamut of physiological processes involved in embryonic development and tissue homeostasis. Wnt ligands are post-translationally lipidated in the endoplasmic reticulum (ER), a step essential for its membrane targeting, association with lipid domains, secretion and interaction with receptors. However, at which residue(s) Wnts are lipidated remains an open question. Initially it was proposed that Wnts are lipid-modified at their conserved cysteine and serine residues (C77 and S209 in mWnt3a), and mutations in either residue impedes its secretion and activity. Conversely, some studies suggested that serine is the only lipidated residue in Wnts, and substitution of serine with alanine leads to retention of Wnts in the ER. In this work, we investigate whether in zebrafish neural tissues Wnt3 is lipidated at one or both conserved residues. To this end, we substitute the homologous cysteine and serine residues of zebrafish Wnt3 with alanine (C80A and S212A) and investigate their influence on Wnt3 membrane organization, secretion, interaction and signaling activity. Collectively, our results indicate that Wnt3 is lipid modified at its C80 and S212 residues. Further, we find that lipid addition at either C80 or S212 is sufficient for its secretion and membrane organization, while the lipid modification at S212 is indispensable for receptor interaction and signaling.
Parathyroid Changes After RAI in Patients With Differentiated Thyroid Carcinoma

Objective The purpose of this study was to investigate parathyroid hormone (PTH), serum calcium, phosphorus, and 25-hydroxyvitamin D (25-OH-VD) changes before and after radioactive iodine (RAI) in differentiated thyroid carcinoma (DTC) patients at different time points. Methods A total of 259 DTC patients who received RAI were prospectively enrolled. We evaluated PTH, serum calcium, phosphorus, and 25-OH-VD levels at baseline pre-RAI, five days, six weeks, and six months post-RAI, respectively. We analyzed the risk factors of hypocalcemia at five days post-RAI. Results The mean PTH, serum calcium and phosphorus values decreased five days post-RAI compared with pre-RAI (PTH 4.18 ± 1.23 pmol/L vs. 3.95 ± 1.41 pmol/L; calcium 2.27 ± 0.09 mmol/L vs. 2.20 ± 0.11 mmol/L; phosphorus 1.25 ± 0.17 vs. 0.98 ± 0.20 mmol/L, P < 0.05), and the differences were statistically significant. The mean 25-OH-VD levels did not significantly decrease at five days post-RAI. 21.2% (55/259) of patients had hypocalcemia at five days post-RAI, and all of them were given oral calcium supplements. At six weeks post-RAI, all of the above parameters were higher than those at five days post-RAI. Multivariate regression analysis showed that baseline pre-RAI serum calcium < 2.27 mmol/L, PTH < 4.18 pmol/L and negative 99mTcO4 - thyroid imaging were risk factors for hypocalcemia at five days post-RAI. Conclusion For DTC patients with normal PTH and serum calcium levels at pre-RAI, their PTH, serum calcium, and phosphorus levels decreased at five days post-RAI. About one-fifth of patients could have hypocalcemia at five days post-RAI. Lower baseline pre-RAI serum calcium and PTH levels and negative 99mTcO4 - thyroid imaging were risk factors for hypocalcemia five days post-RAI.
Advances in Screening, Early Diagnosis and Accurate Staging of Diabetic Neuropathy

The incidence of both type 1 and type 2 diabetes is increasing worldwide. Diabetic peripheral neuropathy (DPN) is among the most distressing and costly of all the chronic complications of diabetes and is a cause of significant disability and poor quality of life. This incurs a significant burden on health care costs and society, especially as these young people enter their peak working and earning capacity at the time when diabetes-related complications most often first occur. DPN is often asymptomatic during the early stages; however, once symptoms and overt deficits have developed, it cannot be reversed. Therefore, early diagnosis and timely intervention are essential to prevent the development and progression of diabetic neuropathy. The diagnosis of DPN, the determination of the global prevalence, and incidence rates of DPN remain challenging. The opinions vary about the effectiveness of the expansion of screenings to enable early diagnosis and treatment initiation before disease onset and progression. Although research has evolved over the years, DPN still represents an enormous burden for clinicians and health systems worldwide due to its difficult diagnosis, high costs related to treatment, and the multidisciplinary approach required for effective management. Therefore, there is an unmet need for reliable surrogate biomarkers to monitor the onset and progression of early neuropathic changes in DPN and facilitate drug discovery. In this review paper, the aim was to assess the currently available tests for DPN’s sensitivity and performance.
Altered Gut Microbiota in a Fragile X Syndrome Mouse Model

The human gut microbiome is the ecosystem of microorganisms that live in the human digestive system. Several studies have related gut microbiome variants to metabolic, immune and nervous system disorders. Fragile X syndrome (FXS) is a neurodevelopmental disorder considered the most common cause of inherited intellectual disability and the leading monogenetic cause of autism. The role of the gut microbiome in FXS remains largely unexplored. Here, we report the results of a gut microbiome analysis using a FXS mouse model and 16S ribosomal RNA gene sequencing. We identified alterations in the fmr1 KO2 gut microbiome associated with different bacterial species, including those in the genera Akkermansia, Sutterella, Allobaculum, Bifidobacterium, Odoribacter, Turicibacter, Flexispira, Bacteroides, and Oscillospira. Several gut bacterial metabolic pathways were significantly altered in fmr1 KO2 mice, including menaquinone degradation, catechol degradation, vitamin B6 biosynthesis, fatty acid biosynthesis, and nucleotide metabolism. Several of these metabolic pathways, including catechol degradation, nucleotide metabolism and fatty acid biosynthesis, were previously reported to be altered in children and adults with autism. The present study reports a potential association of the gut microbiome with FXS, thereby opening new possibilities for exploring reliable treatments and non-invasive biomarkers.
Generalized Structure Functions and Multifractal Detrended Fluctuation Analysis Applied to Vegetation Index Time Series: An Arid Rangeland Study

Estimates suggest that more than 70% of the world’s rangelands are degraded. The Normalized Difference Vegetation Index (NDVI) is commonly used by ecologists and agriculturalists to monitor vegetation and contribute to more sustainable rangeland management. This paper aims to explore the scaling character of NDVI and NDVI anomaly (NDVIa) time series by applying three fractal analyses: generalized structure function (GSF), multifractal detrended fluctuation analysis (MF-DFA), and Hurst index (HI). The study was conducted in four study areas in Southeastern Spain. Results suggest a multifractal character influenced by different land uses and spatial diversity. MF-DFA indicated an antipersistent character in study areas, while GSF and HI results indicated a persistent character. Different behaviors of generalized Hurst and scaling exponents were found between herbaceous and tree dominated areas. MF-DFA and surrogate and shuffle series allow us to study multifractal sources, reflecting the importance of long-range correlations in these areas. Two types of long-range correlation appear to be in place due to short-term memory reflecting seasonality and longer-term memory based on a time scale of a year or longer. The comparison of these series also provides us with a differentiating profile to distinguish among our four study areas that can improve land use and risk management in arid rangelands.
FTRLIM: Distributed Instance Matching Framework for Large-Scale Knowledge Graph Fusion

Instance matching is a key task in knowledge graph fusion, and it is critical to improving the efficiency of instance matching, given the increasing scale of knowledge graphs. Blocking algorithms selecting candidate instance pairs for comparison is one of the effective methods to achieve the goal. In this paper, we propose a novel blocking algorithm named MultiObJ, which constructs indexes for instances based on the Ordered Joint of Multiple Objects’ features to limit the number of candidate instance pairs. Based on MultiObJ, we further propose a distributed framework named Follow-the-Regular-Leader Instance Matching (FTRLIM), which matches instances between large-scale knowledge graphs with approximately linear time complexity. FTRLIM has participated in OAEI 2019 and achieved the best matching quality with significantly efficiency. In this research, we construct three data collections based on a real-world large-scale knowledge graph. Experiment results on the constructed data collections and two real-world datasets indicate that MultiObJ and FTRLIM outperform other state-of-the-art methods.