Miracle-dz/UniFAR-FTUs huggingface dataset:
Neuronal extracellular microRNAs miR‐124 and miR‐9 mediate cell–cell communication between neurons and microglia

In contrast to peripheral macrophages, microglia in the central nervous system (CNS) exhibit a specific deactivated phenotype; however, it is not clear how this phenotype is maintained. Two alternative hypotheses were postulated recently: (a) microglia differ from peripheral macrophages being derived from the yolk sac (YS), whereas peripheral macrophages originate from bone marrow (BM); (b) microglia acquire a specific phenotype under the influence of the CNS microenvironment. We have previously shown that microglia express miR‐124, which was also induced in BM‐derived macrophages co‐cultured with a neurons. We here investigated the possibility of horizontal transfer of the neuron‐specific microRNAs miR‐124 and miR‐9 from primary neurons to microglia/macrophages. We found that after incubation with neuronal conditioned media (NCM), macrophages downregulated activation markers MHC class II and CD45. Neither cultured adult microglia nor YS‐ and BM‐derived macrophages demonstrated intrinsic levels of miR‐124 expression. However, after incubation with NCM, miR‐124 was induced in both YS‐ and BM‐derived macrophages. Biochemical analysis demonstrated that the NCM contained miR‐124 and miR‐9 in complex with small proteins, large high‐density lipoproteins (HDLs), and exosomes. MiR‐124 and miR‐9 were promptly released from neurons, and this process was inhibited by tetrodotoxin, indicating an important role of neuronal electric activity in secretion of these microRNAs. Incubation of macrophages with exogenous miR‐124 resulted in efficient translocation of miR‐124 into the cytoplasm. This study demonstrates an important role of neuronal miRNAs in communication of neurons with microglia, which favors the hypothesis that microglia acquire a specific phenotype under the influence of the CNS microenvironment.
LRW-1000: A Naturally-Distributed Large-Scale Benchmark for Lip Reading in the Wild

Large-scale datasets have successively proven their fundamental importance in several research fields, especially for early progress in some emerging topics. In this paper, we focus on the problem of visual speech recognition, also known as lip-reading, which has received increasing interest in recent years. We present a naturally-distributed large-scale benchmark for lip-reading in the wild, named LRW-1000, which contains 1,000 classes with 718,018 samples from more than 2,000 individual speakers. Each class corresponds to the syllables of a Mandarin word composed of one or several Chinese characters. To the best of our knowledge, it is currently the largest word-level lipreading dataset and also the only public large-scale Mandarin lip-reading dataset. This dataset aims at covering a "natural" variability over different speech modes and imaging conditions to incorporate challenges encountered in practical applications. It has shown a large variation in this benchmark in several aspects, including the number of samples in each class, video resolution, lighting conditions, and speakers’ attributes such as pose, age, gender, and make-up. Besides providing a detailed description of the dataset and its collection pipeline, we evaluate several typical popular lip-reading methods and perform a thorough analysis of the results from several aspects. The results demonstrate the consistency and challenges of our dataset, which may open up some new promising directions for future work.
CHANGE: Cardiac Health Analysis Using Graph Eigenvalues

Coronary Artery Disease (CAD) is an important problem in cardiac health and is a leading cause of human mortality. Prior arts have shown that features extracted from non-invasive Photoplethysmogram (PPG) signal are effective in classifying CAD. In this paper, we represent cardiac health as a graph (CHG) in order to exploit the dependencies of PPG features as well as the metadata features. We then compute spectral features from the eigenvalues of the graph Laplacian of CHG. Finally, k-means algorithm is employed for classifying the data into CAD and non-CAD. Unsupervised experiments on a cohort with 32 participants yields 88% accuracy and demonstrates advantage of the proposed formulation over a baseline and two state-of-the-art approaches.
Errors of Upright Perception in Patients With Vestibular Migraine

Patients with vestibular migraine (VM) often report dizziness with changes in the head or body position. Such symptoms raise the possibility of dysfunction in neural mechanisms underlying spatial orientation in these patients. Here we addressed this issue by investigating the effect of static head tilts on errors of upright perception in a group of 27 VM patients in comparison with a group of 27 healthy controls. Perception of upright was measured in a dark room using a subjective visual vertical (SVV) paradigm at three head tilt positions (upright, ±20°). VM patients were also surveyed about the quality of their dizziness and spatial symptoms during daily activities. In the upright head position, SVV errors were within the normal range for VM patients and healthy controls (within 2° from true vertical). During the static head tilts of 20° to the right, VM patients showed larger SVV errors consistent with overestimation of the tilt magnitude (i.e., as if they felt further tilted toward the right side) (VM: −3.21° ± 0.93 vs. Control: 0.52° ± 0.70; p = 0.002). During the head tilt to the left, SVV errors in VM patients did not differ significantly from controls (VM: 0.77° ± 1.05 vs. Control: −0.04° ± 0.68; p = 0.52). There was no significant difference in SVV precision between the VM patients and healthy controls at any head tilt position. Consistent with the direction of the SVV errors in VM patients, they largely reported spatial symptoms toward the right side. These findings suggest an abnormal sensory integration for spatial orientation in vestibular migraine, related to daily dizziness in these patients.
Enhanced Photocatalytic and Antimicrobial Performance of Cuprous Oxide/Titania: The Effect of Titania Matrix

A simple, low-cost method was applied to prepare hybrid photocatalysts of copper (I) oxide/titania. Five different TiO2 powders were used to perform the study of the effect of titania matrix on the photocatalytic and antimicrobial properties of prepared nanocomposites. The photocatalytic efficiency of such a dual heterojunction system was tested in three reaction systems: ultraviolet-visible (UV-Vis)-induced methanol dehydrogenation and oxidation of acetic acid, and 2-propanol oxidation under visible light irradiation. In all the reaction systems considered, the crucial enhancement of photocatalytic activity in relation to corresponding bare titania was observed. The reaction mechanism for a specific reaction and the influence of titania matrix were discussed. Furthermore, antimicrobial (bactericidal and fungicidal) properties of Cu2O/TiO2 materials were analyzed. The antimicrobial activity was found under UV, visible and solar irradiation, and even for dark conditions. The origin of antimicrobial properties with emphasis on the role of titania matrix was also discussed.
Hepatitis B core antigen regulates dendritic cell proliferation and apoptosis through regulation of PKC/NF‑κB signaling pathway.

Hepatitis B core antigen (HBcAg) possesses unusual immunologic features. However, the biological roles and mechanisms of HBcAg in dendritic cell proliferation and apoptosis remain to be elucidated. In the present study, DC2.4 cells were treated with different concentrations of HBcAg (10, 20 and 30 µg/ml). MTT assay and flow cytometry (Annexin V/propidium iodide analysis) were performed to investigate changes in cell proliferation and apoptosis. Western blot analysis was conducted to examine the changes in nuclear factor (NF)‑κB and protein kinase C (PKC) signaling pathways. NF‑κB inhibitor pyrrolidine dithiocarbamate (PDTC) and PKC inhibitor Chelerythrine were used to block these two signaling pathways. It was identified that HBcAg increased proliferation and decreased apoptosis in a dose‑dependent manner. Western blotting results demonstrated that HBcAg upregulated p‑PKC, p‑IκB, p‑P65, tumor necrosis factor‑α and B‑cell lymphoma 2 (Bcl‑2) levels, and downregulated cleaved caspase 3, demonstrating that HBcAg activated the PKC and NF‑κB signaling pathways. NF‑κB inhibitor PDTC reduced the effects of HBcAg on DC2.4 proliferation (0.6 fold vs. 0.25 fold) and apoptosis (0.43 fold vs. 0.17 fold), and on Bcl‑2 expression levels. PKC inhibitor Chelerythrine reduced the biological effects of HBcAg; it reduced proliferation (0.67 fold vs. 0.23 fold) and upregulated apoptosis (0.43 fold vs. 0.13 fold). Chelerythrine also blocked NF‑κB activity and the HBcAg‑induced Bcl‑2 increase, suggesting the effect on Bcl‑2 from HBcAg was dependent on the PKC/NF‑κB signaling pathway. In conclusion, HBcAg promoted proliferation and inhibited apoptosis through the PKC/NF‑κB/Bcl‑2 signaling pathway in DC2.4 cells.
Porous Silicon Photonic Crystals Coated with Ag Nanoparticles as Efficient Substrates for Detecting Trace Explosives Using SERS

Picric acid (PA) is an organic substance widely used in industry and military, which poses a great threat to the environment and security due to its unstable, toxic, and explosive properties. Trace detection of PA is also a challenging task because of its highly acidic and anionic character. In this work, silver nanoparticles (AgNPs)-decorated porous silicon photonic crystals (PS PCs) were controllably prepared as surface-enhanced Raman scattering (SERS) substrates using the immersion plating solution. PA and Rhodamine 6G dye (R6G) were used as the analyte to explore the detection performance. As compared with single layer porous silicon, the enhancement factor of PS PCs substrates is increased to 3.58 times at the concentration of 10−6 mol/L (R6G). This additional enhancement was greatly beneficial to the trace-amount-detection of target molecules. Under the optimized assay condition, the platform shows a distinguished sensitivity with the limit of detection of PA as low as 10−8 mol/L, the linear range from 10−4 to 10−7 mol/L, and a decent reproducibility with a relative standard deviation (RSD) of ca. 8%. These results show that the AgNPs-modified PS PCs substrates could also find further applications in biomedical and environmental sensing.
PDGFRα monoclonal antibody: Assessment of embryo-fetal toxicity and time-dependent placental transfer of a murine surrogate antibody of olaratumab in mice.

BACKGROUND Olaratumab (Lartruvo™) is a recombinant human IgG1 monoclonal antibody that specifically binds PDGFRα. The maternal and in utero embryo-fetal toxicity and toxicokinetics of a human anti-mouse PDGFRα antibody (LSN3338786) were investigated in pregnant mice. METHODS A pilot study was used to set doses for the definitive study. In the definitive study, mice were administered vehicle, 5, 50, or 150 mg/kg LSN3338786 by intravenous injection on gestation days (GD) 6, 9, 12, and 15. Fetal tissues and/or serum samples were collected on GD 10, 12, 15, and 18 to evaluate exposure of antibody. RESULTS There were no adverse maternal effects at 50 and 150 mg/kg although maternal deaths and adverse clinical signs were observed at 5 mg/kg. LSN3338786 crossed the placenta as early as GD 10 during organogenesis. Elimination half-life of LSN3338786 in dams decreased between GD 6 and 15. On GD 18, fetal serum concentrations of antibody were substantially higher than maternal serum concentrations at all doses. Increased incidences of malformations consisting of open and partially open eye and increased incidences of skeletal variation frontal/parietal additional ossification site occurred in fetuses from mid- and high-dose groups. CONCLUSIONS The majority of transplacental migration of antibody occurred in concert with rapid maternal serum clearance before parturition. The no-observed effect level for teratogenicity of 5 mg/kg was associated with GD 15 maternal serum concentrations 3-11 times lower than clinical exposure of olaratumab, suggesting that olaratumab may cause fetal harm when administered to pregnant women.
The N400/FN400 and Lateralized Readiness Potential Neural Correlates of Valence and Origin of Words’ Affective Connotations in Ambiguous Task Processing

Recent behavioral studies revealed an interesting phenomenon concerning the influence of affect on the interpretation of ambiguous stimuli. In a paradigm, where the participants’ task was to read a word, remember its meaning for a while, and then choose one of two pictorial-alphabet-like graphical signs best representing the word sense, we observed that the decisions involving trials with reflective-originated verbal stimuli were performed significantly longer than decisions concerning other stimuli (i.e., automatic-originated). The origin of an affective reaction is a dimension which allows speaking of an affect as automatic (you feel it in your guts) or reflective (you feel it comes from your mind). The automatic affective reaction represents the immediate and inescapable as opposed to the reflective, i.e., the delayed and controllable affective responses to stimuli. In the current experiment, we investigated the neural correlates of performance in an QR-signs-selection ambiguous task. We found the effects of valence and origin in the N400/FN400 potential by means of a stimuli-locked analysis of the initial part of the task, that is, the remembering of a certain word stimulus in a working memory. The N400/FN400 effects were separated in space on scalp distribution. Reflective originated stimuli elicited more negative FN400 than other conditions, which means that such stimuli indeed are associated with conceptual incongruence or higher affective complexity of meaning, but distinct from purely cognitive concreteness. Moreover, the amplitude of the potential preceding the decision, analyzed in the response-locked way, was shaped by the origin of an affective state but not valence. Trials involving decisions concerning reflective-originated words were characterized by a more negative amplitude than trials involving automatic-originated and control word stimuli. This corresponds to the observed pattern of response latencies, where we found that latencies for reflective stimuli were longer than for automatic originated or control ones. Additionally, this study demonstrates that the proposed new ambiguous paradigm is useful in studies concerning the influence of affect on decisions.
Adaptability of Li-Ion Single Particle Model for Lifetime Simulation Using LFP and LMO Cells

For battery lifetime simulation and control, often a conflict between accuracy and the long simulation horizon arises. A single particle model (SPM) is therefore introduced, which combines the benefits of electrochemical models, which take internal states and concentrations into account, with time efficient empirical approaches in neglecting or averaging unimportant and CPU-intensive effects. Based on existing LiFePO4 (LFP) cell measurements and models by [1], an average SPM consisting of the basic cell kinematics and potentials, as well as a thermal and aging model is described. The aging model is based on solid electrolyte layer (SEI) growth, which is one of the main aging effects. Although such models already exist, they are often designed for one cell chemistry and with intensive measurements. The presented SPM is validated using LFP cell data and then adapted to fit other cell chemistry as well. It is shown that by merely adapting few parameters of the positive electrode using literature values as well as measured voltage, temperature and aging curves, the aging behavior of a LiMn204 (LMO) cell and possibly other Li-ion cell chemistry can also be predicted well. By adding a current and voltage dependent diffusion coefficient, also side effects like Mn-dissolution for LMO cells are implemented to improve the model.
Hunting Algorithm Visualization and Performance Evaluation Through BDI Agent Simulation

This paper presents an agent-based simulation approach to evaluating hunting algorithm performance using Netlogo and the Belief, Desire, and Intent (BDI) architecture. Netlogo was customized to a number of two-dimensional scenarios with both hunting agents and prey agents interacting with each other and with the obstacles within the scenarios. The agents were developed with the flexibility to instantiate many types of hunters and prey. The differences in both the hunting agent and prey agents are with their skills (communications, perception, speed, etc.) and their cognitive abilities. To evaluate the viability of the approach, it was used to evaluate two hunting algorithms: the Lion Optimization Algorithm (LOA) and the Grey Wolf Optimization (GWO) algorithm. The experimental results show that the LOA was more resilient to obstacles than was the GWO. In the presence of obstacles, the lionesses are more reliable in completing joint convergence onto the prey. While the wolves have a lower convergence rate, they display an ability to recover from the confusion caused by obstacles to finally close in on their prey. The research concludes that the NetLogo programming environment is successfully adapted to the BDI architecture and is very effective in structuring a large agent-based system.
Improving Pseudorandom Generator on Cellular Automata with Bent Functions

Nowadays the practice of researching pseudorandom number generators (PRNG) becomes more scalable because of its spreading in many spheres of computer science and, especially, cybersecurity. The problem is that existing generators are still have many disadvantages in terms of velocity, complexity or flexibility. Thus, the area of researching new algorithms of generating pseudorandom sequences is more than just applicable method, but the target for multiplying cybersecurity from the hardware to application level. This leads to make the set of available and useful PRNG larger and better by their features, like velocity, performance, simplicity in realization. These features match PRNG, based on cellular automata (CA), but not all rules, used in CA are appropriate for their transition functions. Bent functions are perfectly complement statistical weakness of some rules because of their non-linearity without loss of other features.
Simulating Disability in Universal Design Teaching: A Critique - Abandoning Try-It-Yourself in Teaching Universal Design in Architecture

Blindfolding people and providing them with white cane or placing them in a manual wheelchair for 20-60 minutes is a much used and classic exercise when teaching architects and other professionals the basics of user needs related to disability. This method, called try-it-yourself, is the most prevalent method where universal design in taught in the Nordic region. While the exercise is often praised for ensuring an effective 'eye-opening' outcome, the ethical aspects, the absence of the users themselves or the possibilities of alternative methods for teaching user needs appear to be non-existing. The article is based on literature studies and 1:1 experience gained from our Master program in universal design, where the try-it-yourself exercise is analyzed and discussed. The article argues that the exercise, as opposed to its original intention, appears to increase disability stigma and ethical dilemmas. Hence, it needs to be challenged as the prevalent exercise used for teaching universal design and accessibility. The article also discusses alternative methods for teaching user needs. Furthermore, the article discusses the tacit cultural acceptance of the exercise, as well as the ethical dilemmas in the non-existing debate of what is actually being tried-yourself in the exercise. The article also presents possible reasons for the significant absence of an open critical debate about the pros and cons of the exercise, as it is being used non-critically in the Nordic region.
A clinical training model for students: intensive treatment of stuttering using prolonged speech.

PURPOSE This study describes a practical model for improving the quality of Speech-Language Pathology (SLP) education on a clinical setting in a Bulgarian University. During this study, adults who stutter (AWS) received intensive treatment (IT) to increase fluent speech. The intensive treatment was delivered by students trained in the SLP Master's degree program "Logopedics Management in Fluency and Voice Disorders". METHODS The La Trobe University intensive program of prolonged speech was implemented. SLP students were trained and delivered the IT for AWS, under supervision in all stages. The treatment followed a clinical modeling pattern. RESULTS The primary outcomes were measured according to (i) percent of syllables stuttered (%SS) within and outside the stuttering research center of the university; (ii) self-reported inventory scores; and (iii) speech naturalness score evaluations from pre-treatment, immediately following treatment, 11 months post-treatment, and 18 months after the intensive treatment using stutter-free speech samples. The outcomes were reported for the overall IT program delivered by the SLP Master students. CONCLUSION The treatment delivered by students can ensure objective speech outcomes. The evidence-based practice model allowed students to develop and master specific clinical skills in establishing fluent speech by applying a prolonged speech technique. During the IT experience, students began to incorporate elements of evidence-based practice (EBP), clinical expertise, and consider values held by AWS. After four outcome-sessions, the AWS developed self-consciousness about the quality of their prolonged speech during controlled fluent patterns. The participants produced objective speech fluency data and statistically significant differences before and immediately after the IT regarding %SS and overall speech naturalness.
Discrete Heat Kernel Smoothing in Irregular Image Domains

We present the discrete version of heat kernel smoothing on graph data structure. The method is used to smooth data in an irregularly shaped domains in 3D images. New statistical properties of heat kernel smoothing are derived. As an application, we show how to filter out noisy data in the lung blood vessel trees obtained from computed tomography. The method can be further used in representing the complex vessel trees parametrically as a linear combination of basis functions and extracting the skeleton representation of the trees.
Packing Graphs of Bounded Codegree

Two graphs G1 and G2 on n vertices are said to pack if there exist injective mappings of their vertex sets into [n] such that the images of their edge sets are disjoint. A longstanding conjecture due to Bollobás and Eldridge and, independently, Catlin, asserts that if (Δ(G1) + 1)(Δ(G2) + 1) ⩽ n + 1, then G1 and G2 pack. We consider the validity of this assertion under the additional assumption that G1 or G2 has bounded codegree. In particular, we prove for all t ⩾ 2 that if G1 contains no copy of the complete bipartite graph K2,t and Δ(G1) > 17t · Δ(G2), then (Δ(G1) + 1)(Δ(G2) + 1) ⩽ n + 1 implies that G1 and G2 pack. We also provide a mild improvement if moreover G2 contains no copy of the complete tripartite graph K1,1,s, s ⩾ 1.