Miracle-dz/UniFAR-FTUs huggingface dataset:
TequilaGAN: How to easily identify GAN samples

In this paper we show strategies to easily identify fake samples generated with the Generative Adversarial Network framework. One strategy is based on the statistical analysis and comparison of raw pixel values and features extracted from them. The other strategy learns formal specifications from the real data and shows that fake samples violate the specifications of the real data. We show that fake samples produced with GANs have a universal signature that can be used to identify fake samples. We provide results on MNIST, CIFAR10, music and speech data.
Synergetic Effects of Plasmodium, Hookworm, and Schistosoma mansoni Infections on Hemoglobin Level among Febrile School Age Children in Jawe Worda, Northwest Ethiopia

Plasmodium coinfection with hookworm and/or Schistosoma mansoni has detrimental effects on human's hemoglobin level. This study aimed to determine the effects of plasmodium, hookworm, and S. mansoni infections on hemoglobin level among febrile school age children in Northwest Ethiopia. A cross-sectional study was conducted from April 2016 to August 2016. Plasmodium and helminths infections were detected using Giemsa stain and formol-ether concentration techniques, respectively. Hemoglobin level was determined using Hemocue method. Among 333 children, 143 (42.9%), 49 (14.75%), and 22 (6.6%) had Plasmodium, hookworm, and Schistosoma mansoni infections, respectively. The prevalence of Plasmodium-hookworm and Plasmodium-Schistosoma mansoni coinfections was 18 (12.6%) and 4 (2.8%) in children, respectively. The overall prevalence of anaemia in children was 41.4%. Effect of Plasmodium, hookworm, and Schistosoma mansoni on hemoglobin level was high. Therefore, febrile children should be screened for Plasmodium, hookworm, Schistosoma mansoni, and anaemia simultaneously in malaria endemic areas.
Catecholaminergic manipulation alters dynamic network topology across cognitive states

The human brain is able to flexibly adapt its information processing capacity to meet a variety of cognitive challenges. Recent evidence suggests that this flexibility is reflected in the dynamic reorganization of the functional connectome. The ascending catecholaminergic arousal systems of the brain are a plausible candidate mechanism for driving alterations in network architecture, enabling efficient deployment of cognitive resources when the environment demands them. We tested this hypothesis by analyzing both resting-state and task-based fMRI data following the administration of atomoxetine, a noradrenaline reuptake inhibitor, compared with placebo, in two separate human fMRI studies. Our results demonstrate that the manipulation of central catecholamine levels leads to a reorganization of the functional connectome in a manner that is sensitive to ongoing cognitive demands. Author Summary There is emerging evidence that the flexible network structure of the brain is related to activity within the ascending arousal systems of the brain, such as the noradrenergic locus coeruleus. Here, we explored the role of catecholaminergic activity on network architecture by analyzing the graph structure of the brain measured using functional MRI following the administration of atomoxetine, a selective noradrenaline reuptake inhibitor. We estimated functional network topology in two double-blind, placebo-controlled datasets: one from the resting state and another from a parametric N-back task. Our results demonstrate that the nature of catecholaminergic network reconfiguration is differentially related to cognitive state and provide confirmatory evidence for the hypothesis that the functional network signature of the brain is sensitive to the ascending catecholaminergic arousal system.
Effects of Matricaria Recutita (L.) in the Treatment of Oral Mucositis

Objective The objective of this study was to review the effects of the Matricaria recutita (L.) in the treatment of oral mucositis. Methodology The online search was performed in the period from June 2016 to April 2018 by means of databases LILACS (Latin American and Caribbean Center on Health Sciences Information), SciELO (Scientific Electronic Library Online), and MEDLINE (Medical Literature Analysis and Retrieval System Online). The consultation was restricted to the years 1991 to 2018 with the aim of elucidating the effects of Matricaria recutita in the treatment of oral mucositis. Results The final sample consisted of 21 studies, of which 10 were developed in animals and 11 in humans, published from 1991 to 2017, with a total sample of 644 patients. The total number of patients treated with Matricaria included in 11 studies was 364, while in the control groups the total number was 280. In experimental studies, animal models used were rats and the sample size ranged between 36 and 105 animals submitted to the induction of oral mucositis, where 4 studies used an intraperitoneal injection of 5-fluorouracil, while 7 induced lesion in the mucosa. From the data collected, it should be noted that both studies with humans and with animals showed significant effects. In this way, there is strong evidence for the discussion on the therapy; however, it should be noted that more studies are developed in order to clarify the most appropriate protocol for the prevention and treatment of injuries. Conclusion According to the results found in this study, Matricaria recutita appeared to be a promising alternative for the treatment of oral mucositis. However, due to the great variability in the various types of intervention, more controlled double-blind randomized clinical studies are necessary to ensure the best protocol for treating oral mucositis.
Artificial Intelligence for Long-Term Robot Autonomy: A Survey

Autonomous systems will play an essential role in many applications across diverse domains including space, marine, air, field, road, and service robotics. They will assist us in our daily routines and perform dangerous, dirty, and dull tasks. However, enabling robotic systems to perform autonomously in complex, real-world scenarios over extended time periods (i.e., weeks, months, or years) poses many challenges. Some of these have been investigated by subdisciplines of Artificial Intelligence (AI) including navigation and mapping, perception, knowledge representation and reasoning, planning, interaction, and learning. The different subdisciplines have developed techniques that, when re-integrated within an autonomous system, can enable robots to operate effectively in complex, long-term scenarios. In this letter, we survey and discuss AI techniques as “enablers” for long-term robot autonomy, current progress in integrating these techniques within long-running robotic systems, and the future challenges and opportunities for AI in long-term autonomy.
Diagnosis of Superficial Gastric Lesions Together with Six Gastric Lymphoma Cases via Probe-Based Confocal Laser Endomicroscopy: A Retrospective Observational Study

Objective To evaluate the performance of probe-based confocal laser endomicroscopy (pCLE) in diagnosis of gastric lesions. Methods An outpatient department- (OPD-) based retrospective study was conducted for patients with suspected upper gastrointestinal (GI) tract lesions who underwent pCLE between 2014 and 2016 at a tertiary hospital in China. Final diagnosis was based on the histopathological reports. CLE reports were compared to histopathological reports to evaluate the diagnostic ability, including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy. Results 322 of 380 patients were diagnosed with gastric lesions via pCLE, including inflammation and benign ulcers (n = 110), atrophy and intestinal metaplasia (n = 152), intraepithelial neoplasia (n = 27), adenocarcinoma (n = 27), and lymphoma (n = 6). In total, the diagnostic ability of CLE in evaluation of gastric lesions showed sensitivity 72.4% (95% confidence interval (CI): 67.1–77.2%); specificity 93.1% (95% CI: 5.6–8.4%); PPV 72.4% (95% CI: 67.1–77.2%); NPV 93.1% (95% CI: 5.6–8.4%); and accuracy 88.9% (95% CI: 87.3–90.4%), respectively. We further observed the capability of pCLE in diagnosing six gastric lymphoma showing those affected mucosa densely infiltrated with identical and round-shaped abnormal cells. Immunohistochemistry analysis confirmed one patient with diffuse large B-cell non-Hodgkin's lymphoma (DLBCL) and five with mucosa-associated lymphoid tissue (MALT) lymphoma. Conclusion pCLE is an accurate tool for the detection of gastric lesions and shows optimal values of sensitivity and negative predictivity. Moreover, combining pCLE with white light endoscopy (WLE) may be a promising adjunct to conventional biopsy sampling in evaluating GI tract with suspected lymphoma.
Improving Real-Life Estimates of Emotion Based on Heart Rate: A Perspective on Taking Metabolic Heart Rate Into Account

Extracting information about emotion from heart rate in real life is challenged by the concurrent effect of physical activity on heart rate caused by metabolic need. “Non-metabolic heart rate,” which refers to the heart rate that is caused by factors other than physical activity, may be a more sensitive and more universally applicable correlate of emotion than heart rate itself. The aim of the present article is to explore the evidence that non-metabolic heart rate, as it has been determined up until now, indeed reflects emotion. We focus on methods using accelerometry since these sensors are readily available in devices suitable for daily life usage. The evidence that non-metabolic heart rate as determined by existing methods reflect emotion is limited. Alternative possible routes are explored. We conclude that for real-life cases, estimating the type and intensity of activities based on accelerometry (and other information), and in turn use those to determine the non-metabolic heart rate for emotion is most promising.
Synthesis, Anti-Inflammatory Activity, and In Silico Study of Novel Diclofenac and Isatin Conjugates

The design, synthesis, and development of novel non-steroidal anti-inflammatory drugs (NSAIDs) with better activity and lower side effects are respectable area of research. Novel Diclofenac Schiff's bases (M1, M2, M4, M7, and M8) were designed and synthesized, and their respective chemical structures were deduced using various spectral tools (IR, 1H NMR, 13C NMR, and MS). The compounds were synthesized via Schiff's condensation reaction and their anti-inflammatory activity was investigated applying the Carrageenan-induced paw edema model against Diclofenac as positive control. Percentage inhibition of edema indicated that all compounds were exhibiting a comparable anti-inflammatory activity as Diclofenac. Moreover, the anti-inflammatory activity was supported via virtual screening using molecular docking study. Interestingly compound M2 showed the highest in vivo activity (61.32% inhibition) when compared to standard Diclofenac (51.36% inhibition) as well as the best binding energy score (-10.765) and the virtual screening docking score (-12.142).
Learning naturalistic temporal structure in the posterior medial network

The posterior medial network is at the apex of a temporal integration hierarchy in the brain, integrating information over many seconds of viewing intact, but not scrambled, movies. This has been interpreted as an effect of temporal structure. Such structure in movies depends on pre-existing event schemas, but temporal structure can also arise de novo from learning. Here we examined the relative role of schema-consistent temporal structure and arbitrary but consistent temporal structure on the human posterior medial network. We tested whether, with repeated viewing, the network becomes engaged by scrambled movies with temporal structure. Replicating prior studies, posterior medial regions were immediately locked to stimulus structure upon exposure to intact but not scrambled movies. However, for temporally structured scrambled movies, functional coupling within the network increased across stimulus repetitions, rising to the level of intact movies. Thus, temporal structure is a key determinant of network dynamics and function.
Serum neurofilament light chain is increased in hereditary spastic paraplegias

Blood biomarkers are still largely missing in hereditary spastic paraplegias (HSPs). We here explored Neurofilament light chain (NfL) as a biomarker in HSP. Serum NfL was assessed in 96 HSP (63 genetically confirmed), 96 healthy control, and 33 ALS subjects by single molecule array (Simoa). Compared to controls, NfL was increased in HSP (P < 0.001), correlating with cross‐sectional disease progression (ρ = 0.28). Levels were lower than in ALS (P < 0.001), allowing to differentiate HSP from ALS (AUC = 0.91). Serum NfL might serve as a biomarker in HSP indicating neuronal damage and, if confirmed longitudinally, disease progression. It might also support differentiating HSP from ALS.
Blood-Contacting Biomaterials: In Vitro Evaluation of the Hemocompatibility

Hemocompatibility of blood-contacting biomaterials is one of the most important criteria for their successful in vivo applicability. Thus, extensive in vitro analyses according to ISO 10993-4 are required prior to clinical applications. In this review, we summarize essential aspects regarding the evaluation of the hemocompatibility of biomaterials and the required in vitro analyses for determining the blood compatibility. Static, agitated, or shear flow models are used to perform hemocompatibility studies. Before and after the incubation of the test material with fresh human blood, hemolysis, cell counts, and the activation of platelets, leukocytes, coagulation and complement system are analyzed. Furthermore, the surface of biomaterials are evaluated concerning attachment of blood cells, adsorption of proteins, and generation of thrombus and fibrin networks.
Single Bout Exercise in Children with Juvenile Idiopathic Arthritis: Impact on Inflammatory Markers

Objective In a context of inflammatory disease such as juvenile idiopathic arthritis (JIA), we do not know what impact physical activity may have on a deregulated immune system. The objective is to measure the impact of a single bout of exercise on plasma inflammatory markers such as calprotectin, IL-6, sIL-6R, sgp130, and the hypothalamic-pituitary-adrenal axis in children with juvenile idiopathic arthritis. Methods Twelve children with JIA performed a nonexercise control day and a consecutive day that included a 20 min exercise bout at 70% of max-HR at 08:30 am. Venous blood samples were taken at 08:30, 08:50, 09:30, 10:30 am, and 12:00 pm to measure plasma concentrations of calprotectin, IL-6, sIL-6R, sgp130, cortisol, and ACTH. Pain was evaluated at 08:30, 08:50 am, and 06:00 pm. Results There was a transient twofold increase in postexercise self-evaluated pain (p = 0.03) that disappeared in the evening. A single bout of exercise resulted in a 1.7-fold increase in plasma calprotectin (p < 0.001) but not IL-6 and its soluble receptors. Calprotectin levels returned to baseline within 3 hours after cessation of exercise. Conclusion Acute exercise in children with JIA induced slightly musculoskeletal leg pain and transient increased plasma calprotectin levels but not IL-6 levels. Trial registration in ClinicalTrials.gov, reference number NCT 02502539, registered on 29 May 2015.
Extracting Contact and Motion from Manipulation Videos

When we physically interact with our environment using our hands, we touch objects and force them to move: contact and motion are defining properties of manipulation. In this paper, we present an active, bottom-up method for the detection of actor-object contacts and the extraction of moved objects and their motions in RGBD videos of manipulation actions. At the core of our approach lies non-rigid registration: we continuously warp a point cloud model of the observed scene to the current video frame, generating a set of dense 3D point trajectories. Under loose assumptions, we employ simple point cloud segmentation techniques to extract the actor and subsequently detect actor-environment contacts based on the estimated trajectories. For each such interaction, using the detected contact as an attention mechanism, we obtain an initial motion segment for the manipulated object by clustering trajectories in the contact area vicinity and then we jointly refine the object segment and estimate its 6DOF pose in all observed frames. Because of its generality and the fundamental, yet highly informative, nature of its outputs, our approach is applicable to a wide range of perception and planning tasks. We qualitatively evaluate our method on a number of input sequences and present a comprehensive robot imitation learning example, in which we demonstrate the crucial role of our outputs in developing action representations/plans from observation.
Dynamical networks: Finding, measuring, and tracking neural population activity using network science

Systems neuroscience is in a head-long rush to record from as many neurons at the same time as possible. As the brain computes and codes using neuron populations, it is hoped these data will uncover the fundamentals of neural computation. But with hundreds, thousands, or more simultaneously recorded neurons comes the inescapable problems of visualising, describing, and quantifying their interactions. Here I argue that network science provides a set of scalable, analytical tools that already solve these problems. By treating neurons as nodes and their interactions as links, a single network can visualise and describe an arbitrarily large recording. I show that with this description we can quantify the effects of manipulating a neural circuit, track changes in population dynamics over time, and quantitatively define theoretical concepts of neural populations such as cell assemblies. Using network science as a core part of analysing population recordings will thus provide both qualitative and quantitative advances to our understanding of neural computation.
New Insights Into Interactions of Presynaptic Calcium Channel Subtypes and SNARE Proteins in Neurotransmitter Release

Action potential (AP) induces presynaptic membrane depolarization and subsequent opening of Ca2+ channels, and then triggers neurotransmitter release at the active zone of presynaptic terminal. Presynaptic Ca2+ channels and SNARE proteins (SNAREs) interactions form a large signal transfer complex, which are core components for exocytosis. Ca2+ channels serve to regulate the activity of Ca2+ channels through direct binding and indirect activation of active zone proteins and SNAREs. The activation of Ca2+ channels promotes synaptic vesicle recruitment, docking, priming, fusion and neurotransmission release. Intracellular calcium increase is a key step for the initiation of vesicle fusion. Various voltage-gated calcium channel (VGCC) subtypes exert different physiological functions. Until now, it has not been clear how different subtypes of calcium channels integrally regulate the release of neurotransmitters within 200 μs of the AP arriving at the active zone of synaptic terminal. In this mini review, we provide a brief overview of the structure and physiological function of Ca2+ channel subtypes, interactions of Ca2+ channels and SNAREs in neurotransmitter release, and dynamic fine-tune Ca2+ channel activities by G proteins (Gβγ), multiple protein kinases and Ca2+ sensor (CaS) proteins.
Outcome and Prospective Factor Analysis of High-dose Therapy Combined with Autologous Peripheral Blood Stem Cell Transplantation in Patients with Peripheral T-cell Lymphomas

Background: For peripheral T-cell lymphomas (PTCLs) patients, high-dose therapy combined with autologous peripheral blood stem cell transplantation (HDT/ASCT) has been an alternative treatment option, due to the lack of efficacy from conventional chemotherapy. While not all PTCLs could have benefit in survival from HDT/ASCT. The aim of this study was to evaluate the value of high-dose therapy combined with autologous peripheral blood stem cell transplantation (HDT/ASCT) in Chinese patients with Peripheral T-cell Lymphomas (PTCLs), in order to determine the cohort most suitable to receive HDT/ASCT. Methods: A total of 79 patients with PTCLs who received HDT/ASCT in Peking University Cancer Hospital & Institute from January 2001 to august 2016 were retrospectively analyzed. Results: At a median follow-up time of 23.6 months, the 2-year progression-free survival (PFS) and 2-year overall survival (OS) of the entire cohort were 75.2% and 83.6% respectively. Patients with first complete remission (CR1) (2-year PFS 85.8%, 2-year OS 94.2%) were superior to others in survival. Patients with second complete remission (CR2) had no advantage in survival compared with those with first partial remission (PR1) (2-year PFS: 43.8% vs. 76.2%, p=0.128; 2-year OS: 72.9% vs. 77.1%, p=0.842). In multivariate analysis, response before HDT/ASCT (p=0.001) and LDH before HDT/ASCT (p=0.047) were highly predictive for PFS, while no factors could independently predict OS. Subgroup analysis revealed that HDT/ASCT could improve the survival of patients with angioimmunoblastic T-cell lymphoma (AITL), especially in patients with chemosensitivity. Patients with natural killer / T-cell lymphoma (NKTCL) who received HDT/ASCT with CR1 also had benefit in survival from HDT/ASCT, while nearly 90% of non-CR1 patients appeared bone marrow involvement after HDT/ASCT. Conclusion: Patients who achieved complete remission after first-line therapy, especially with AITL and NKTCL, should strongly be recommended to receive HDT/ASCT. The future prospective trial is warranted.
Fast Modular Subset Sum using Linear Sketching

Given n positive integers, the Modular Subset Sum problem asks if a subset adds up to a given target t modulo a given integer m. This is a natural generalization of the Subset Sum problem (where m=+\infty) with ties to additive combinatorics and cryptography. Recently, in [Bringmann, SODA'17] and [Koiliaris and Xu, SODA'17], efficient algorithms have been developed for the non-modular case, running in near-linear pseudo-polynomial time. For the modular case, however, the best known algorithm by Koiliaris and Xu [Koiliaris and Xu, SODA'17] runs in time O~(m^{5/4}). In this paper, we present an algorithm running in time O~(m), which matches a recent conditional lower bound of [Abboud et al.'17] based on the Strong Exponential Time Hypothesis. Interestingly, in contrast to most previous results on Subset Sum, our algorithm does not use the Fast Fourier Transform. Instead, it is able to simulate the "textbook" Dynamic Programming algorithm much faster, using ideas from linear sketching. This is one of the first applications of sketching-based techniques to obtain fast algorithms for combinatorial problems in an offline setting.