Miracle-dz/UniFAR-FTUs huggingface dataset:
Large-scale isolation and cytotoxicity of extracellular vesicles derived from activated human natural killer cells

ABSTRACT Extracellular vesicles (EVs) have been the focus of great interest, as they appear to be involved in numerous important cellular processes. They deliver bioactive macromolecules such as proteins, lipids, and nucleic acids, allowing intercellular communication in multicellular organisms. EVs are secreted by all cell types, including immune cells such as natural killer cells (NK), and they may play important roles in the immune system. Currently, a large-scale procedure to obtain functional NK EVs is lacking, limiting their use clinically. In this report, we present a simple, robust, and cost-effective method to isolate a large quantity of NK EVs. After propagating and activating NK cells ex vivo and then incubating them in exosome-free medium for 48 h, EVs were isolated using a polymer precipitation method. The isolated vesicles contain the tetraspanin CD63, an EV marker, and associated proteins (fibronectin), but are devoid of cytochrome C, a cytoplasmic marker. Nanoparticle tracking analysis showed a size distribution between 100 and 200 nm while transmission electron microscopy imaging displayed vesicles with an oval shape and comparable sizes, fulfilling the definition of EV. Importantly, isolated EV fractions were cytotoxic against cancer cells. Furthermore, our results demonstrate for the first time that isolated activated NK (aNK) cell EVs contain the cytotoxic proteins perforin, granulysin, and granzymes A and B, incorporated from the aNK cells. Activation of caspase -3, -7 and -9 was detected in cancer cells incubated with aNK EVs, and caspase inhibitors blocked aNK EV-induced cytotoxicity, suggesting that aNK EVs activate caspase pathways in target cells. The ability to isolate functional aNK EVs on a large scale may lead to new clinical applications. Abbreviations: NK: natural killer cells; activated NK (aNK) cells; EVs: extracellular vesicles; ALL: acute lymphoblastic leukaemia; aAPC: artificial antigen-presenting cell; TEM: transmission electron microscope; PBMC: peripheral blood mononuclear cells; FBS: foetal bovine serum.
A study on the effects of example familiarity and modality on design fixation

Abstract Design fixation is a factor that negatively influences the generation of novel design concepts (Jansson & Smith, 1991). When designers fixate, they tend to reproduce example features or features from their initial ideas. In order to mitigate design fixation, it is crucial to identify the factors that influence the extent of design fixation. This paper investigates two such factors: the modality of examples and the familiarity of designers with the example features. To investigate this, an experiment is conducted with mechanical engineering students who were asked to generate ideas to solve a peanut sheller design problem. The students generated ideas in five different experimental conditions: control, where no example was given; the first example given in a sketch form; the first example given as a nonfunctional prototype; a second example in sketch form; and the second example in a working prototype form. The first example was a nonfeasible solution, but it contained several features familiar to the participants. The second example was a feasible solution, but it contained less familiar features. In order to understand the extent of fixation triggered by the examples, three metrics were utilized to compare across the experimental conditions: the quantity of nonredundant ideas generated by the participants, the presence of example features in their solutions, and their fixation to the example's energy source. The results showed that in the case of the familiar example, the example modality did play an important role in the extent of design fixation. Across the examples, it was found that the first example containing several familiar features caused more fixation than the second one. Overall, this paper shows that the modality in which the example was communicated and the presence of familiar features in an example influenced the fixation caused by those examples.
Brain Functional Correlates of Working Memory: Reduced Load-Modulated Activation and Deactivation in Aging without Hyperactivation or Functional Reorganization

Abstract We aimed to identify brain functional correlates of working memory performance in aging, in hopes of facilitating understanding of mechanisms that promote better versus worse working memory in late-life. Among 64 healthy adults, aged 23 to 78, we examined the relationship between age, working memory performance, and brain functional response during task performance. We focused on the association between working memory load-modulated functional response and individual differences in performance and whether these function-performance relationships differed with age. As expected, older age was associated with poorer working memory performance. Older age was also associated with reduced load-modulated activation including in bilateral prefrontal and parietal regions and left caudate as well as reduced deactivation including in the medial prefrontal cortex. Contrary to findings of hyperactivation in aging, we found no evidence of increased activation with older age. Positive associations identified between brain response and performance did not differ with age. Our findings suggest that the neural mechanisms underlying better versus worse working memory performance are age-invariant across adulthood, and argue against a pattern of functional reorganization in aging. Results are discussed within the broader literature, in which significant heterogeneity in findings between studies has been common. (JINS, 2014, 20, 1–6)
Signature of an anticipatory response in area VI as modeled by a probabilistic model and a spiking neural network

As it is confronted to inherent neural delays, how does the visual system create a coherent representation of a rapidly changing environment? In this paper, we investigate the role of motion-based prediction in estimating motion trajectories compensating for delayed information sampling. In particular, we investigate how anisotropic diffusion of information may explain the development of anticipatory response as recorded in a neural populations to an approaching stimulus. We validate this using an abstract probabilistic framework and a spiking neural network (SNN) model. Inspired by a mechanism proposed by Nijhawan [1], we first use a Bayesian particle filter framework and introduce a diagonal motion-based prediction model which extrapolates the estimated response to a delayed stimulus in the direction of the trajectory. In the SNN implementation, we have used this pattern of anisotropic, recurrent connections between excitatory cells as mechanism for motion-extrapolation. Consistent with recent experimental data collected in extracellular recordings of macaque primary visual cortex [2], we have simulated different trajectory lengths and have explored how anticipatory responses may be dependent on the information accumulated along the trajectory. We show that both our probabilistic framework and the SNN model can replicate the experimental data qualitatively. Most importantly, we highlight requirements for the development of a trajectory-dependent anticipatory response, and in particular the anisotropic nature of the connectivity pattern which leads to the motion extrapolation mechanism.
Mechanics of a shear cutting process

Meissner, Stephen C, "Mechanics of a Shear Cutting Process" A unique laboratory device, the Laboratory Shear, has been designed and built to simulate and examine the shear angle cutting process, which is the predominant method used in many cutting operations. The device is capable of force and velocity measurements of the shear angle cutting process with the abilities to vary cutting speed, knife preload, and blade geometry. The dimensions of the device are such that mobility to and from conditioning rooms in the laboratory environment are not limited. Assembly and disassembly ease as well as automatic versus manual operation options were incorporated for greater experimental flexibility. The device has the ability to evaluate products at a shear velocity of 200 inches per second, which equates to nearly 1000 feet per minute on a conventional slitter with 10 shear angle. The force measurement capability is 10 pounds, which is sufficient to handle the majority ofKodak films. Knife preload can be adjusted to provide preloads from 2 lbs to 12 lbs, in increments of 2 lbs. Debug of the Lab Shear Device was conducted and included knife sharpness measurement as well as calibration of the load cell and velocity transducer. The upper (moving) knife was found to have a cutting tip radius of approximately 0.0002 inch and the lower (stationary) knife was found to have a cutting tip radius of approximately 0.0001 inch. Both knives could be considered as "medium dull" based on the Kodak standard for slitting knife sharpness (X < 0.0001 inch = sharp, X > 0.0005 inch = dull). Edges for both knives appeared smooth and defect free as viewed with SEM. Load cell and velocity transducer calibration resulted in less than 10% standard deviation, which was within acceptable limits. Variability of the system was assessed through several experiments using polycarbonate film. Overall system variability was determined to be within 10%, which was acceptable for the device's intended use. A linear relationship between the average cutting force and the average sample thickness was observed, similar to the linear relationship between tearing force and film thickness reported during the trouser-tearing of films. Given this observed linear relationship, tearing of polycarbonate seems to be the dominant failure process despite that the shear angle cutting is a mixed mode fracture process. Fracture morphology examination was performed and proved to be beneficial, showing the ability of the device to generate consistent fractures associated with a specific speed-preload combination. For the polycarbonate tested, fracture morphologies observed tend to be independent of speed and dependent on preload. Finite Element Analysis (FEA) was applied to gain a better understanding of the cutting system mechanics and frictional mechanisms of the Lab Shear Device. Analysis provided explanation for an observed force shift during cutting in addition to providing a model for further examination.
High efficiency Indirect Matrix Converter topologies

This paper discusses new three-phase ac-ac Indirect Matrix Converter (IMC) topologies featuring higher power efficiency than conventional IMCs. Initially, a new Inverting-link Matrix Converter (ILMC) with lower conduction power losses than a standard ILMC for voltage step-down operation is proposed. New Ultra-Sparse Matrix Converters (USMCs) well-suited for voltage step-down applications are also presented. These circuits have redundant current paths to distribute the impressed dc-link current to the input terminals which can be potentially used to reduce semiconductor losses. A voltage step-up USMC, referred to as delta-switch USMC (Δ-USMC), well-suited for wind power generation systems, where low inductance machines are used, is also analyzed. In order to benefit from the best features of the proposed IMCs, standard and new space vector modulations featuring distinctive commutation schemes are presented. Finally, to demonstrate the advantages of the studied IMCs, power loss comparisons of these solutions and standard IMCs rated to 10 kW are shown.
A Fine-Grained Notation for Lambda Terms and Its Use in Intensional Operations

We discuss issues relevant to the practical use of a previously proposed notation for lambda terms in contexts where the intensions of such terms have to be manipulated. This notation uses the `nameless'' scheme of de Bruijn, includes expressions for encoding terms together with substitutions to be performed on them and contains a mechanism for combining such substitutions so that they can be effected in a common structure traversal. The combination mechanism is a general one and consequently difficult to implement. We propose a simplification to it that retains its functionality in situations that occur commonly in beta reduction. We then describe a system for annotating terms to determine if they can be affected by substitutions generated by external beta contractions. These annotations can lead to a conservation of space and time in implementations of reduction by permitting substitutions to be performed trivially in certain situations. The use of the resulting notation in the reduction and comparison of terms is examined. Notions of head normal forms and head reduction sequences are defined in its context and shown to be useful in equality computations. Our head reduction sequences generalize the usual ones for lambda terms so that they subsume the sequences of terms produced by a variety of graph- and environment-based reduction procedures for the lambda calculus. They can therefore be used in correctness arguments for such procedures. This fact and the efficacy of our notation are illustrated in the context of a particular reduction procedure that we present. The relevance of the present discussions to the unification of lambda terms is also outlined.
Towards a Fluid Spectrum Market for Exclusive Usage Rights

This paper focuses on highly fluid markets for trading exclusive spectrum usage-rights. The purpose of the paper is to underline the need for flexible usage-rights policies, as a core facilitator of such markets as well as to stress the need for a greater technical input to the debate. The paper builds on current work in the field of spectrum property rights and exclusive usage-rights. The first half of the paper captures the current state-of-play and presents a framework for visualizing the concepts involved. The paper goes on to make a clear distinction between the defining of a set of exclusive usage-rights and the exercising of those rights. This leads to a discussion of policies that are not alone about defining metrics and setting their desired values but are also about behaviors that involve negotiation and interaction. Through-out the paper the evolution of technology and its affect on the progress towards the goal of fluid spectrum markets is emphasized, as is the need for a very multifaceted approach to the challenges involved.
Effects of psychiatric history on cognitive performance in old-age depression

Cognitive deficits in old-age depression vary as a function of multiple factors; one rarely examined factor is long-term psychiatric history. We investigated effects of psychiatric history on cognitive performance in old-age depression and in remitted persons. In the population-based Swedish National Study on Aging and Care in Kungsholmen study, older persons (≥60 years) without dementia were tested with a cognitive battery and matched to the Swedish National Inpatient Register (starting 1969). Participants were grouped according to current depression status and psychiatric history and compared to healthy controls (n = 96). Group differences were observed for processing speed, attention, executive functions, and verbal fluency. Persons with depression and psychiatric inpatient history (n = 20) and late-onset depression (n = 49) performed at the lowest levels, whereas cognitive performance in persons with self-reported recurrent unipolar depression (n = 52) was intermediate. Remitted persons with inpatient history of unipolar depression (n = 38) exhibited no cognitive deficits. Heart disease burden, physical inactivity, and cumulative inpatient days modulated the observed group differences in cognitive performance. Among currently depressed persons, those with inpatient history, and late onset performed at the lowest levels. Importantly, remitted persons showed no cognitive deficits, possibly reflecting the extended time since the last admission (m = 15.6 years). Thus, the present data suggest that cognitive deficits in unipolar depression may be more state- than trait-related. Information on profiles of cognitive performance, psychiatric history, and health behaviors may be useful in tailoring individualized treatment.
In Silico Prediction for Intestinal Absorption and Brain Penetration of Chemical Pesticides in Humans

Intestinal absorption and brain permeation constitute key parameters of toxicokinetics for pesticides, conditioning their toxicity, including neurotoxicity. However, they remain poorly characterized in humans. The present study was therefore designed to evaluate human intestine and brain permeation for a large set of pesticides (n = 338) belonging to various chemical classes, using an in silico graphical BOILED-Egg/SwissADME online method based on lipophilicity and polarity that was initially developed for drugs. A high percentage of the pesticides (81.4%) was predicted to exhibit high intestinal absorption, with a high accuracy (96%), whereas a lower, but substantial, percentage (38.5%) displayed brain permeation. Among the pesticide classes, organochlorines (n = 30) constitute the class with the lowest percentage of intestine-permeant members (40%), whereas that of the organophosphorus compounds (n = 99) has the lowest percentage of brain-permeant chemicals (9%). The predictions of the permeations for the pesticides were additionally shown to be significantly associated with various molecular descriptors well-known to discriminate between permeant and non-permeant drugs. Overall, our in silico data suggest that human exposure to pesticides through the oral way is likely to result in an intake of these dietary contaminants for most of them and brain permeation for some of them, thus supporting the idea that they have toxic effects on human health, including neurotoxic effects.
A Numerically Efficient Finite Element Analysis of Reinforced Concrete Members Subjected to Blasts

A common approach for predicting member response under blast loading is through the use of a finite element software package. Such an analysis typically requires the implementation of a three dimensional mesh and, therefore, requires significant computational effort. In this paper, it is shown how a displacement based segmental moment-rotation (M/θ) analysis can be used to simulate the cracking and softening behavior of reinforced concrete over a segment of a member using the mechanics of partial interaction and shear friction. It is then shown how the M/θ behavior extracted from the segmental analysis can be simplified into an equivalent one dimensional moment curvature relationship which can then be incorporated into a fast running one dimensional finite element approach to determine the response of reinforced concrete slabs subjected to blast loading. Then, results determined using the approach are compared against those obtained from blast experiments and the numerical efficiency of the model is discussed.
Hebbian learning in a model with dynamic rate-coded neurons: An alternative to the generative model approach for learning receptive fields from natural scenes

Most computational models of coding are based on a generative model according to which the feedback signal aims to reconstruct the visual scene as close as possible. We here explore an alternative model of feedback. It is derived from studies of attention and thus, probably more flexible with respect to attentive processing in higher brain areas. According to this model, feedback implements a gain increase of the feedforward signal. We use a dynamic model with presynaptic inhibition and Hebbian learning to simultaneously learn feedforward and feedback weights. The weights converge to localized, oriented, and bandpass filters similar as the ones found in V1. Due to presynaptic inhibition the model predicts the organization of receptive fields within the feedforward pathway, whereas feedback primarily serves to tune early visual processing according to the needs of the task.
The Advanced Computing Systems Association Extending File Systems Using Stackable Templates Extending File Systems Using Stackable Templates

Extending file system functionality is not a new idea, but a desirable one nonetheless[6, 14, 18]. In the several years since stackable file systems were first proposed, only a handful are in use[12, 19]. Impediments to writing new file systems include the complexity of operating systems, the difficulty of writing kernel-based code, the lack of a true stackable vnode interface[14], and the challenges of porting one file system to another operating system. We advocate writing new stackable file systems as kernel modules. As a starting point, we propose a portable, stackable template file system we call Wrapfs (wrapper file system). Wrapfs is a canonical, minimal stackable file system that can be used as a pattern across a wide range of operating systems and file systems. Given Wrapfs, developers can add or modify only that which is necessary to achieve the desired functionality. Wrapfs takes care of the rest, and frees developers from the details of operating systems. Wrapfs templates exist for several common operating systems (Solaris, Linux, and FreeBSD), thus alleviating portability concerns. Wrapfs can be ported to any operating system with a vnode interface that provides a private data pointer for each data structure used in the interface. The overhead imposed by Wrapfs is only 5–7%. This paper describes the design and implementation of Wrapfs, explores portability issues, and shows how the implementation was achieved without changing client file systems or operating systems. We discuss several examples of file systems written using Wrapfs.
Randomized, controlled trial of cannabis-based medicine in central pain in multiple sclerosis

Background: Central pain in multiple sclerosis (MS) is common and often refractory to treatment. Methods: We conducted a single-center, 5-week (1-week run-in, 4-week treatment), randomized, double-blind, placebo-controlled, parallel-group trial in 66 patients with MS and central pain states (59 dysesthetic, seven painful spasms) of a whole-plant cannabis-based medicine (CBM), containing delta-9-tetrahydrocannabinol:cannabidiol (THC:CBD) delivered via an oromucosal spray, as adjunctive analgesic treatment. Each spray delivered 2.7 mg of THC and 2.5 of CBD, and patients could gradually self-titrate to a maximum of 48 sprays in 24 hours. Results: Sixty-four patients (97%) completed the trial, 34 received CBM. In week 4, the mean number of daily sprays taken of CBM (n = 32) was 9.6 (range 2 to 25, SD = 6.0) and of placebo (n = 31) was 19.1 (range 1 to 47, SD = 12.9). Pain and sleep disturbance were recorded daily on an 11-point numerical rating scale. CBM was superior to placebo in reducing the mean intensity of pain (CBM mean change −2.7, 95% CI: −3.4 to −2.0, placebo –1.4 95% CI: −2.0 to −0.8, comparison between groups, p = 0.005) and sleep disturbance (CBM mean change –2.5, 95% CI: −3.4 to −1.7, placebo –0.8, 95% CI: −1.5 to −0.1, comparison between groups, p = 0.003). CBM was generally well tolerated, although more patients on CBM than placebo reported dizziness, dry mouth, and somnolence. Cognitive side effects were limited to long-term memory storage. Conclusions: Cannabis-based medicine is effective in reducing pain and sleep disturbance in patients with multiple sclerosis related central neuropathic pain and is mostly well tolerated.