Miracle-dz/UniFAR-FTUs huggingface dataset:
Interfacial and Foaming Properties of Tailor-Made Glycolipids—Influence of the Hydrophilic Head Group and Functional Groups in the Hydrophobic Tail

Glycolipids are a class of biodegradable surfactants less harmful to the environment than petrochemically derived surfactants. Here we discuss interfacial properties, foam stability, characterized in terms of transient foam height, gas volume fraction and bubble diameter as well as texture of seven enzymatically synthesized surfactants for the first time. Glycolipids consisting of different head groups, namely glucose, sorbitol, glucuronic acid and sorbose, combined with different C10 acyl chains, namely decanoate, dec-9-enoate and 4-methyl-nonanoate are compared. Equilibrium interfacial tension values vary between 24.3 and 29.6 mN/m, critical micelle concentration varies between 0.7 and 3.0 mM. In both cases highest values were found for the surfactants with unsaturated or branched tail groups. Interfacial elasticity and viscosity, however, were significantly reduced in these cases. Head and tail group both affect foam stability. Foams from glycolipids with sorbose and glucuronic acid derived head groups showed higher stability than those from surfactants with glucose head group, sorbitol provided lowest foam stability. We attribute this to different head group hydration also showing up in the time to reach equilibrium interfacial adsorption. Unsaturated tail groups reduced whereas branching enhanced foam stability compared to the systems with linear, saturated tail. Moreover, the tail group strongly influences foam texture. Glycolipids with unsaturated tail groups produced foams quickly collapsing even at smallest shear loads, whereas the branched tail group yielded a higher modulus than the linear tails. Normalized shear moduli for the systems with different head groups varied in a narrow range, with the highest value found for decylglucuronate.
DeepPilot: A CNN for Autonomous Drone Racing

Autonomous Drone Racing (ADR) was first proposed in IROS 2016. It called for the development of an autonomous drone capable of beating a human in a drone race. After almost five years, several teams have proposed different solutions with a common pipeline: gate detection; drone localization; and stable flight control. Recently, Deep Learning (DL) has been used for gate detection and localization of the drone regarding the gate. However, recent competitions such as the Game of Drones, held at NeurIPS 2019, called for solutions where DL played a more significant role. Motivated by the latter, in this work, we propose a CNN approach called DeepPilot that takes camera images as input and predicts flight commands as output. These flight commands represent: the angular position of the drone’s body frame in the roll and pitch angles, thus producing translation motion in those angles; rotational speed in the yaw angle; and vertical speed referred as altitude h. Values for these 4 flight commands, predicted by DeepPilot, are passed to the drone’s inner controller, thus enabling the drone to navigate autonomously through the gates in the racetrack. For this, we assume that the next gate becomes visible immediately after the current gate has been crossed. We present evaluations in simulated racetrack environments where DeepPilot is run several times successfully to prove repeatability. In average, DeepPilot runs at 25 frames per second (fps). We also present a thorough evaluation of what we called a temporal approach, which consists of creating a mosaic image, with consecutive camera frames, that is passed as input to the DeepPilot. We argue that this helps to learn the drone’s motion trend regarding the gate, thus acting as a local memory that leverages the prediction of the flight commands. Our results indicate that this purely DL-based artificial pilot is feasible to be used for the ADR challenge.
Cortical Tracking of Speech in Delta Band Relates to Individual Differences in Speech in Noise Comprehension in Older Adults.

OBJECTIVES Understanding speech in adverse listening environments is challenging for older adults. Individual differences in pure tone averages and working memory are known to be critical indicators of speech in noise comprehension. Recent studies have suggested that tracking of the speech envelope in cortical oscillations <8 Hz may be an important mechanism related to speech comprehension by segmenting speech into words and phrases (delta, 1 to 4 Hz) or phonemes and syllables (theta, 4 to 8 Hz). The purpose of this study was to investigate the extent to which individual differences in pure tone averages, working memory, and cortical tracking of the speech envelope relate to speech in noise comprehension in older adults. DESIGN Cortical tracking of continuous speech was assessed using electroencephalography in older adults (60 to 80 years). Participants listened to speech in quiet and in the presence of noise (time-reversed speech) and answered comprehension questions. Participants completed Forward Digit Span and Backward Digit Span as measures of working memory, and pure tone averages were collected. An index of reduction in noise (RIN) was calculated by normalizing the difference between raw cortical tracking in quiet and in noise. RESULTS Comprehension question performance was greater for speech in quiet than for speech in noise. The relationship between RIN and speech in noise comprehension was assessed while controlling for the effects of individual differences in pure tone averages and working memory. Delta band RIN correlated with speech in noise comprehension, while theta band RIN did not. CONCLUSIONS Cortical tracking by delta oscillations is robust to the effects of noise. These findings demonstrate that the magnitude of delta band RIN relates to individual differences in speech in noise comprehension in older adults. Delta band RIN may serve as a neural metric of speech in noise comprehension beyond the effects of pure tone averages and working memory.
Pre-Clinical Cell Therapeutic Approaches for Repair of Volumetric Muscle Loss

Extensive damage to skeletal muscle tissue due to volumetric muscle loss (VML) is beyond the inherent regenerative capacity of the body, and results in permanent functional debilitation. Current clinical treatments fail to fully restore native muscle function. Recently, cell-based therapies have emerged as a promising approach to promote skeletal muscle regeneration following injury and/or disease. Stem cell populations, such as muscle stem cells, mesenchymal stem cells and induced pluripotent stem cells (iPSCs), have shown a promising capacity for muscle differentiation. Support cells, such as endothelial cells, nerve cells or immune cells, play a pivotal role in providing paracrine signaling cues for myogenesis, along with modulating the processes of inflammation, angiogenesis and innervation. The efficacy of cell therapies relies on the provision of instructive microenvironmental cues and appropriate intercellular interactions. This review describes the recent developments of cell-based therapies for the treatment of VML, with a focus on preclinical testing and future trends in the field.
The Hippocampus Maps Concept Space, Not Feature Space

The hippocampal formation encodes maps of space and a key question in neuroscience is whether its spatial coding principles also provide a universal metric for the organization of nonspatial, conceptual information. Previous work demonstrated directional coding during navigation through a continuous stimulus feature space as well as mapping of distances in a feature space that was relevant for concept learning. Here we provide the first unambiguous evidence for a hippocampal representation of the actual concept space, by showing that the hippocampal distance signal selectively reflects the mapping of specifically conceptually relevant rather than of all feature dimensions. During fMRI scanning of 32 human participants (21 females), we presented everyday objects, which had beforehand been associated with specific values on three continuous feature dimensions. Crucially, only two dimensions were relevant to prior concept learning. We find that hippocampal responses to the objects reflect their relative distances in a space defined along conceptually relevant dimensions compared with distances in a space defined along all feature dimensions. These findings suggest that the hippocampus supports knowledge acquisition by dynamically encoding information in a space spanned along dimensions that are relevant in relation to define concepts. SIGNIFICANCE STATEMENT How are neural representations of conceptual knowledge organized, such that humans are able to infer never experienced relations or categorize new exemplars? Map-like representations as supported by the hippocampal formation to encode physical space during navigation have been suggested as a suitable format. Here we provide the first evidence for a hippocampal representation of a conceptual space compared with a general feature-based space.
HYBRIDIZATION AS AN EVOLUTIONARY STIMULUS

One of the most spectacular facets of the newer studies of evolution has been the demonstration that evolution has not proceeded by slow, even steps but that seen in the large there have been bursts of creative activity. Some of the evidence for these bursts is from paleontology; Simpson (1953) has recently assembled a wealth of data concerning them and has discussed in detail their possible causes. Paleobotanists are equally aware of such events as the great upsurge of angiosperms in the Cretaceous, and of primitive vascular plants in the Devonian period. Other evidence for evolutionary bursts comes from the existence of large clusters of related endemic species and genera in the modern fauna and flora of certain regions, particularly oceanic islands and fresh water lakes. The snails (Achatinellidae) and honey sucker birds (Drepanidae) of Hawaii are classical examples, as are also the Gammarid crustaceans of Lake Baikal. and the fishes of Lakes Tanganyika and Nyasa in Africa, and particularly of Lake Lanao in the Philippines (see Brooks, 1950 for a summary and discussion of the data). It is true that some of these examples may represent normal rates of evolution occurring in a restricted area which has been isolated for a very long time, but there can be little doubt that in the case of others evolution has been phenomenally rapid. As Simpson (1944, 1953) has clearly stated, the cause of this rapid evolution is to be sought in the organism-environment relationship. Along with most authors, however, he has tended to emphasize the peculiar environment present during these evolutionary bursts, and has suggested that one need not postulate
In Vivo Optogenetic Modulation with Simultaneous Neural Detection Using Microelectrode Array Integrated with Optical Fiber

The detection of neuroelectrophysiology while performing optogenetic modulation can provide more reliable and useful information for neural research. In this study, an optical fiber and a microelectrode array were integrated through hot-melt adhesive bonding, which combined optogenetics and electrophysiological detection technology to achieve neuromodulation and neuronal activity recording. We carried out the experiments on the activation and electrophysiological detection of infected neurons at the depth range of 900–1250 μm in the brain which covers hippocampal CA1 and a part of the upper cortical area, analyzed a possible local inhibition circuit by combining opotogenetic modulation and electrophysiological characteristics and explored the effects of different optical patterns and light powers on the neuromodulation. It was found that optogenetics, combined with neural recording technology, could provide more information and ideas for neural circuit recognition. In this study, the optical stimulation with low frequency and large duty cycle induces more intense neuronal activity and larger light power induced more action potentials of neurons within a certain power range (1.032 mW–1.584 mW). The present study provided an efficient method for the detection and modulation of neurons in vivo and an effective tool to study neural circuit in the brain.
Chemical Fingerprinting and Biological Evaluation of the Endemic Chilean Fruit Greigia sphacelata (Ruiz and Pav.) Regel (Bromeliaceae) by UHPLC-PDA-Orbitrap-Mass Spectrometry

Greigia sphacelata (Ruiz and Pav.) Regel (Bromeliaceae) is a Chilean endemic plant popularly known as “quiscal” and produces an edible fruit consumed by the local Mapuche communities named as “chupón”. In this study, several metabolites including phenolic acids, organic acids, sugar derivatives, catechins, proanthocyanidins, fatty acids, iridoids, coumarins, benzophenone, flavonoids, and terpenes were identified in G. sphacelata fruits using ultrahigh performance liquid chromatography-photodiode array detection coupled with a Orbitrap mass spectrometry (UHPLC-PDA-Orbitrap-MS) analysis for the first time. The fruits showed moderate antioxidant capacities (i.e., 487.11 ± 26.22 μmol TE/g dry weight) in the stable radical DPPH assay, 169.08 ± 9.81 TE/g dry weight in the ferric reducing power assay, 190.32 ± 6.23 TE/g dry weight in the ABTS assay, and 76.46 ± 3.18% inhibition in the superoxide anion scavenging assay. The cholinesterase inhibitory potential was evaluated against acetylcholinesterase (AChE) and butyrylcholinesterase (BChE). From the findings, promising results were observed for pulp and seeds. Our findings suggest that G. sphacelata fruits are a rich source of diverse secondary metabolites with antioxidant capacities. In addition, the inhibitory effects against AChE and BChE suggest that natural products or food supplements derived from G. sphacelata fruits are of interest for their neuroprotective potential.
Interactive Low Back Pain Intervention Module Based on the Back School Program: A Cluster-Randomized Experimental Study Evaluating Its Effectiveness among Nurses in Public Hospitals

The prevalence of low back pain (LBP) among nurses is high. The main aim of this study was to evaluate the effectiveness of an interactive LBP module based on the Back School Program in improving Oswestry Disability Scores (ODSs) among nurses in government hospitals in Penang, Malaysia. A cluster-randomized experimental study was conducted within four public hospitals. These hospitals were randomized to intervention and control groups. A total of 284 nurses from the selected hospitals were randomly selected (142 in each group). An interactive LBP intervention module based on the Back School Program was designed and prescribed. Both the intervention and control groups were assessed using the Oswestry Disability Questionnaire at baseline and at the end of the third and sixth weeks. Out of 284 participants, 281 completed this study. A between-group comparison revealed that ODSs were significantly lower in the intervention group than in the control group at the ends of the third (p = 0.006) and sixth weeks (p < 0.001). Within-group changes revealed a significant reduction in ODSs within the intervention group from baseline to the third (p < 0.001) and sixth weeks (p < 0.001) of the intervention. This simple interactive LBP module was effective in reducing symptoms of LBP among nurses as early as three weeks, and this effect was sustained until the sixth week of the intervention.
Microfluidic Technology for the Production of Well-Ordered Porous Polymer Scaffolds

Advances in tissue engineering (TE) have revealed that porosity architectures, such as pore shape, pore size and pore interconnectivity are the key morphological properties of scaffolds. Well-ordered porous polymer scaffolds, which have uniform pore size, regular geometric shape, high porosity and good pore interconnectivity, facilitate the loading and distribution of active biomolecules, as well as cell adhesion, proliferation and migration. However, these are difficult to prepare by traditional methods and the existing well-ordered porous scaffold preparation methods require expensive experimental equipment or cumbersome preparation steps. Generally, droplet-based microfluidics, which generates and manipulates discrete droplets through immiscible multiphase flows inside microchannels, has emerged as a versatile tool for generation of well-ordered porous materials. This short review details this novel method and the latest developments in well-ordered porous scaffold preparation via microfluidic technology. The pore structure and properties of microfluidic scaffolds are discussed in depth, laying the foundation for further research and application in TE. Furthermore, we outline the bottlenecks and future developments in this particular field, and a brief outlook on the future development of microfluidic technique for scaffold fabrication is presented.
Proteomic as an Exploratory Approach to Develop Vaccines Against Tick-Borne Diseases Using Lyme Borreliosis as a Test Case

Tick-borne diseases affecting humans and animals are on the rise worldwide. Vaccines constitute an effective control measure, but very few are available. We selected Lyme borreliosis, a bacterial infection transmitted by the hard tick Ixodes, to validate a new concept to identify vaccine candidates. This disease is the most common tick-borne disease in the Northern Hemisphere. Although attempts to develop a vaccine exist, none have been successfully marketed. In tick-borne diseases, the skin constitutes a very specific environment encountered by the pathogen during its co-inoculation with tick saliva. In a mouse model, we developed a proteomic approach to identify vaccine candidates in skin biopsies. We identified 30 bacterial proteins after syringe inoculation or tick inoculation of bacteria. Discovery proteomics using mass spectrometry might be used in various tick-borne diseases to identify pathogen proteins with early skin expression. It should help to better develop sub-unit vaccines based on a cocktail of several antigens, associated with effective adjuvant and delivery systems of antigens. In all vector-borne diseases, the skin deserves further investigation to better define its role in the elaboration of protective immunity against pathogens.
A Novel Mutual Information Based Feature Set for Drivers’ Mental Workload Evaluation Using Machine Learning

Analysis of physiological signals, electroencephalography more specifically, is considered a very promising technique to obtain objective measures for mental workload evaluation, however, it requires a complex apparatus to record, and thus, with poor usability in monitoring in-vehicle drivers’ mental workload. This study proposes a methodology of constructing a novel mutual information-based feature set from the fusion of electroencephalography and vehicular signals acquired through a real driving experiment and deployed in evaluating drivers’ mental workload. Mutual information of electroencephalography and vehicular signals were used as the prime factor for the fusion of features. In order to assess the reliability of the developed feature set mental workload score prediction, classification and event classification tasks were performed using different machine learning models. Moreover, features extracted from electroencephalography were used to compare the performance. In the prediction of mental workload score, expert-defined scores were used as the target values. For classification tasks, true labels were set from contextual information of the experiment. An extensive evaluation of every prediction tasks was carried out using different validation methods. In predicting the mental workload score from the proposed feature set lowest mean absolute error was 0.09 and for classifying mental workload highest accuracy was 94%. According to the outcome of the study, it can be stated that the novel mutual information based features developed through the proposed approach can be employed to classify and monitor in-vehicle drivers’ mental workload.
Nanostructured Polystyrene Doped with Acetylsalicylic Acid and Its Antibacterial Properties

Homogeneous polystyrene foils doped with different concentrations of acetylsalicylic acid were prepared by the solvent casting method. The surface morphology and surface chemistry of as-prepared foils were characterized in detail. Excimer laser (krypton fluoride, a wavelength of 248 nm) was used for surface nanopatterning of doped polystyrene foils. Certain combinations of laser fluence and number of laser pulses led to formation of laser-induced periodic surface structures (LIPSS) on the exposed surface. Formation of the pattern was affected by the presence of a dopant in the polystyrene structure. Significant differences in surface chemistry and morphology of laser-treated foils compared to both pristine and doped polystyrene were detected. The pattern width and height were both affected by selection of input excimer exposure conditions, and the amount of 6000 pulses was determined as optimal. The possibility of nanostructuring of a honeycomb-like pattern doped with acetylsalicylic acid was also demonstrated. Selected nanostructured surfaces were used for study the antibacterial properties for a model bacteria strain of S. aureus. The combination of altered surface chemistry and morphology of polystyrene was confirmed to have an excellent antibacterial properties.
Influence of Psychosocial and Sociodemographic Variables on Sickness Leave and Disability in Patients with Work-Related Neck and Low Back Pain

The purpose of this study was to describe the association between psychosocial factors in patients with work-related neck or low back pain (n = 129), in order to study sickness leave, its duration, the disability reported, and to analyze the relationship of these factors with different sociodemographic variables. This was a descriptive cross-sectional study. Data on kinesiophobia, catastrophizing, disability, and pain were gathered. Sociodemographic variables analyzed included sex, age, occupational, and educational level. Other data such as location of pain, sick leave status and duration of sickness absence were also collected. Educational level (p = 0.001), occupational level (p < 0.001), and kinesiophobia (p < 0.001) were found to be associated with sickness leave; kinesiophobia (b = 1.47, p = 0.002, r = 0.35) and catastrophizing (b = 0.72, p = 0.012, r = 0.28) were associated with the duration of sickness leave. Educational level (p = 0.021), kinesiophobia (b = 1.69, p < 0.000, r = 0.505), catastrophizing (b = 0.76, p < 0.000, r = 0.372), and intensity of pain (b = 4.36, p < 0.000, r = 0.334) were associated with the degree of disability. In the context of occupational insurance providers, educational and occupational factors, as well as kinesiophobia and catastrophizing, may have an influence on sickness leave, its duration and the degree of disability reported.