Miracle-dz/UniFAR-FTUs huggingface dataset:
Antibacterial/Antifungal Activity and Synergistic Interactions between Polyprenols and Other Lipids Isolated from Ginkgo Biloba L. Leaves

Polyprenols separated from lipids are promising new components from Ginkgo biloba L. leaves (GBL). In this paper, ginkgo lipids were isolated by extraction with petroleum ether, saponification, and molecular distillation. Eight known compounds: isophytol (1), nerolidol (2), linalool (3), β-sitosterol acetate (4), β-sitosterol (5), stigmasterol (6), ergosterol (7), β-sitosterol-3-O-β-D-glucopyranoside (8) and Ginkgo biloba polyprenols (GBP) were separated from GBL by chromatography and identified mainly by NMR. The separated and identified compounds 1, 2 and 3 are reported here for the first time in GBL. The 3D-DAD-HPLC-chromatogram (190–232 nm) of GBP was recorded. This study provides new evidence as there are no previous reports on antibacterial/antifungal activities and synergistic interactions between GBP and the compounds separated from GBL lipids against Salmonella enterica, Staphylocococus aureus and Aspergillus niger. Nerolidol (2) showed the highest activity among all the tested samples and of all mixture groups tested the GBP with isophytol (1) mixture had the strongest synergistic effect against Salmonella enterica among the three tested strains. A proportion of isophytol and GBP of 38.19%:61.81% (wt/wt) was determined by mixture design as the optimal proportion for the synergistic effect of GBP with isophytol against Salmonella enterica.
Subunit-Specific Association of Protein Kinase C and the Receptor for Activated C Kinase with GABA Type A Receptors

GABA receptors (GABAA) are the major sites of fast synaptic inhibition in the brain and can be assembled from five subunit classes: α, β, γ, δ, and ε. Receptor function can be regulated by direct phosphorylation of β and γ2 subunits, but how kinases are targeted to GABAA receptors is unknown. Here we show that protein kinase C-βII (PKC-βII) is capable of directly binding to the intracellular domain of the receptor β1 and β3 subunits, but not to those of the α1 or γ2 subunits. Moreover, associating PKC-βII is capable of specifically phosphorylating serine 409 in β1 subunit and serines 408/409 within the β3 subunit, key residues for modulating GABAAreceptor function. The receptor for activated C kinase (RACK-1) was found also to bind to the β1 subunit intracellular domain, but PKC binding appeared to be independent of this protein. Using immunoprecipitation, the association of PKC isoforms and RACK-1 with neuronal GABAA receptors was seen. Furthermore, PKC isoforms associating with neuronal receptors were capable of phosphorylating the receptor β3 subunit. Together, these observations suggest GABAA receptors are intimately associated with PKC isoforms via a direct interaction with receptor β subunits. This interaction may serve to localize PKC activity to GABAA receptors in neurons allowing the rapid regulation of receptor activity by cell-signaling pathways that modify PKC activity.
DeepHash for Image Instance Retrieval: Getting Regularization, Depth and Fine-Tuning Right

This work focuses on representing very high-dimensional global image descriptors using very compact 64-1024 bit binary hashes for instance retrieval. We propose DeepHash: a hashing scheme based on deep networks. Key to making DeepHash work at extremely low bitrates are three important considerations -- regularization, depth and fine-tuning -- each requiring solutions specific to the hashing problem. In-depth evaluation shows that our scheme outperforms state-of-the-art methods over several benchmark datasets for both Fisher Vectors and Deep Convolutional Neural Network features, by up to 8.5% over other schemes. The retrieval performance with 256-bit hashes is close to that of the uncompressed floating point features -- a remarkable 512x compression.
Frontal EEG Asymmetry and Sport Motivation

Introduction The importance of emotion in sport and human performance seems beyond dispute. At every stage of engagement, sport selection, training, and competition, emotional and motivational factors contribute massively to speed, strength, endurance, and degree of acquired skill. Few would disagree that attitude and affective evaluation are critical to both competitive success and defeat (Lang, 2000). However, the neural mechanisms and neurocircuitry of motivational substrates responsible for this effect are rarely investigated and not well understood in sport psychology. This is unfortunate, because until sport psychologists can better understand these neural mechanisms, intervention then can be based on a more solid neuroscience theoretical foundation than on anecdotal evidence and traditional self-report measures. After all, self-report measures in the long run will prove to be inadequate to capture the core characteristics of affective style that are governed by brain neural affective circuits (Davidson, 1998). In neuroscience, it was proposed that motivation could be conceptualized as brain activity that processes " input " information about the internal state of the individual and external environment and determines behavioural " output " , and motivation could be restricted to the operations of appetitive " go " processes that ordinarily result in behaviour which carries forward an action (Pribram, 2003). In Gray' s motivation theory, motivational systems were divided into appetitive (behavioural activation system or BAS) and aversive (behavioural inhibition system or BIS) (Fowles, 1988). Various lines of evidence suggested that medial prefrontal cortex might be involved in the interpretation of emotional and motivational factors and the use of these to guide behavior (Elliott & Dolan, 2003). Results of frontal lobes studies also indicated that each anterior hemisphere is part of a specific affective/motivational brain system (Davidson & Tomarken, 1989). On the basis of their psychophysiological evidence from experiments, Davidson and colleagues proposed a diathesis-stress model of anterior asymmetry and emotion. Specifically, the left frontal region was conceptualized as a major site within a brain circuit mediating approach-related behavior and the corresponding region in the right hemisphere was described as a major site within a circuit mediating withdrawal behavior (Wheeler, Davidson, & Tomarken, 1993). A sizable literature supports the approach/withdrawal model of frontal EEG alpha asymmetry, motivation, and emotion (Coan, & Allen, 2003). Many past studies suggested that resting anterior EEG asymmetry in the alpha (8-13Hz) frequency band (serving as the indicator of cortical deactivation) might be a biological marker of emotional predispositions or traits …
Risk Factors Related to Inflammation and Endothelial Dysfunction in the DCCT/EDIC Cohort and Their Relationship With Nephropathy and Macrovascular Complications

OBJECTIVE—Because endothelial cell dysfunction and inflammation are key contributors to the development of complications in type 1 diabetes, we studied risk factors related to endothelial dysfunction and inflammation (C-reactive protein and fibrinogen, soluble vascular cell adhesion molecule-1, intracellular adhesion molecule-1, and E-selectin, and fibrinolytic markers) in a subgroup of patients from the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Intervention and Complications (EDIC) study cohort. RESEARCH DESIGN AND METHODS—We determined which of these risk factors or clusters thereof are associated with the presence of and subsequent development of nephropathy and macrovascular complications (reflected by carotid intima-media thickness [IMT]). RESULTS—After adjustment for conventional risk factors (age, sex, DCCT treatment group, diabetes duration, A1C, systolic blood pressure, waist-to-hip ratio, total and HDL cholesterol, and smoking status), fibrinogen remained strongly associated with progression of internal and common carotid IMT (P < 0.01) and soluble E-selectin had a strong association with nephropathy (P < 0.01). CONCLUSIONS—The best predictor for IMT progression in the DCCT/EDIC cohort was plasma fibrinogen, and the levels of soluble E-selectin discriminate patients with albuminuria better than conventional risk factors.
Pre-extraction of hemicelluloses and subsequent kraft pulping
Part I: alkaline extraction

A mild alkaline treatment was applied to aspen chips prior to kraft pulping in order to extract hemicelluloses for use as biofuels. The extraction was performed at 50-90° C, and did not require costly pressurized reaction vessels. It resulted in a recovery of 40-50 kg of hemicellulose per ton of chips, and yielded the same amount of pulp after subsequent pulping of the extracted chips residue, as compared to a control cook. The pre-extraction process requires careful optimization of the pulping process, and allows shorter cooking time and lower chemical charges. Kraft pulps obtained from pre-extracted chips have a slightly higher cellulose/hemicellulose ratio, and demonstrate a small decrease in tensile index (~10%), but improved brightness and shive content. While the hemicellulose yield for this process is low, this problem is outweighed by the fact that pulp properties and pulping yield can be maintained at a high level. The recovered hemicellulose can be concentrated/isolated more easily than furfural-containing smaller fragments obtained by autohydrolysis or dilute-acid treatment.
Genetic Breeding._of~novel Neural Architectures ~ng-tak Zhan

Genetic algorithms are computational techniques for search, optimization and machine learning that are inspired by the process of natural evolution. Genetic algorithms have been used for neural networks in several ways: to optimize the network architecture and to train the weights of a fixed architecture among others. While most previous work focuses on only one of these two options, this paper describes an alternative evolutionary computational approach in which the architecture and the weights are optimized simultaneously. As opposed to conventional learning algorithms for neural networks, the presented method makes relatively few assumptions about the network types. Thus the same method can also be used to breed other novel network architectures as well as standard ones. We demonstrate the effectiveness of the method on the synthesis of sigma-pi neural networks.
Does caregiver burden mediate the effects of behavioral disturbances on nursing home admission?

OBJECTIVES The primary objective of this study was to determine whether caregiving burden mediated the relationship between specific behavior disturbances and time to nursing home admission (NHA) for persons with dementia (i.e., Alzheimer disease or a related disorder). DESIGN The study used secondary longitudinal data from the Medicare Alzheimer's Disease Demonstration, a Medicare-covered home care benefit and case management program for family caregivers of persons with dementia. Primary caregivers of persons with dementia were assessed via in-person and telephone interviews every 6 months over a 3-year period. SETTING Dementia caregivers were recruited from eight catchment areas throughout the United States. PARTICIPANTS The baseline sample included 5,831 dementia caregivers. Just more than 40% (43.9%; N = 2,556) of persons with dementia permanently entered a nursing home during the 3-year study period. MEASUREMENTS Individual behavior problems were measured with the Memory and Behavior Problem Checklist. Caregiving burden was assessed with a short version of the Zarit Burden Inventory. Key covariates, including sociodemographic background, functional status, and service utilization, were also considered. RESULTS Event history analyses revealed that time-varying measures of caregiver burden fully mediated the relationship between four behavioral disturbances (episodes of combativeness, property destruction, repetitive questions, and reliving the past) and NHA. CONCLUSIONS The findings highlight the multifaceted, complex pathway to NHA for persons with dementia and their family caregivers. The results emphasize the need for comprehensive treatment approaches that incorporate the burden of caregivers and the behavioral/psychiatric symptoms of persons with dementia simultaneously.
Outage Probability and Finite-SNR Diversity–Multiplexing Tradeoff for Two-Way Relay Fading Channels

In this paper, we analyze the outage probability and finite-SNR diversity-multiplexing tradeoff (f-DMT) performance for two-way relay channels (TWRCs). Both amplify-and-forward (AF) and decode-and-forward (DF) relay protocols are considered. The two source nodes are equipped with single antenna, and the relay is equipped with single or multiple antennas. First, we derive lower bounds of outage probability for single- and multiantenna relay AF, upper and lower bounds for multiantenna relay DF, and the exact closed-form expression for single-antenna DF. These results are suitable for arbitrary time-sharing and rate allocation for DF and arbitrary rate allocation for AF. Numerical results show that the derived lower bounds approximate very well the actual outage performance obtained by Monte Carlo simulation. Based on the tight lower bounds, we further derive estimates of the f-DMTs. We find that AF always outperforms DF in terms of f-DMT in all SNR regimes. However, the comparison result of outage performance between AF and DF depends on channel conditions. Finally, we also discuss the impact of relay location, time-sharing, and rate allocation on the outage and f-DMT via numerical examples.
Functional MRI Detects Posterior Shifts in Primary Sensorimotor Cortex Activation After Stroke: Evidence of Local Adaptive Reorganization?

Background and Purpose Further recovery from stroke can occur late, long after the end of the apparent evolution of pathological changes. This observation and evidence obtained from functional imaging for altered patterns of activation after brain injury suggest that cortical reorganization may contribute to recovery. Here, we have tested for potentially adaptive reorganization in the primary sensorimotor cortex. Methods We used functional MRI to study brain activation with dominant hand movement in right-handed healthy control subjects (n=20) and in patients after subcortical ischemic infarcts causing mild to moderate right hemiparesis (n=8). The numbers of pixels activated above threshold and the geometric centers of activation clusters were determined. Results Although random-effects analysis identified some differences in activation maxima, similar regions of the brain were activated with sequential finger tapping in the patient and control groups. However, consistent with the heterogeneity in the locations, sizes, and times after the infarcts, patterns and magnitudes of activation showed some heterogeneity between patients. Nonetheless, for the group as a whole, there was a decreased motor cortex lateralization index (−0.1±0.7 in patients and 0.7±0.3 in control subjects, P =0.05). The geometric center of activation of the primary sensorimotor cortex activation cluster contralateral to the affected hand in patients was also shifted posteriorly (mean 12 mm, P <0.04) relative to that of the control subjects. To confirm the latter observation, the activation response with a simple hand-tapping task was examined in some of the subjects. With this task, there was also a trend (mean 10 mm, P =0.07) toward a more posterior activation in patients. Conclusions These results confirm altered patterns of activation in the contralateral and ipsilateral primary sensorimotor cortices after recovery from strokes causing hemiparesis. These (and other changes) suggest that modulation of widely distributed parts of the cortical network for motor control may contribute to adaptations leading to functional recovery after stroke.
Automated Adaptive Forming Simulations

In this study, an automated adaptive mesh control scheme, based on local mesh modifications, is developed for the finite element simulations of 3D metal forming processes. Error indicators are used to control the mesh discretization errors, and a consecutive h-adaptive procedure is conducted. The mesh size field used in the h-adaptive procedure is processed to control the geometric approximation errors on the evolving workpiece boundary mesh. During the simulations the workpiece mesh is adaptively enriched whenever the mesh is no longer acceptable. Industrial problems are investigated to demonstrate the capabilities of the developed scheme.
Materials with required dielectric properties: Computational development and production of polymer‐ceramic composites

Many applications in wireless communication, microelectronics, and microwave power engineering rely on dielectrics with particular dielectric properties. This article proposes an original approach that can be used for producing materials with required complex permittivity. The technique is based on an inverted power-law mixing rule model computing volume fractions in which three or more prime materials should be taken to get in the resulting homogeneous mixture the required dielectric properties. Functionality of the approach is demonstrated by production of composites from a polymer matrix (polymethyl methacrylate) and two inorganic fillers (silicon and alumina). The composites are made by mechanically mixing the powders and axially hot-pressing and cooling the mixture. Complex permittivity of the samples is measured by a split-post resonator method. Experimental data on dielectric properties of the samples help calibrate the technique; for the used powders, the Looyenga power-law model is found to be most adequate. In the produced samples, the target values of dielectric constant are reached with a higher precision than the ones of the loss factor; however, analysis of the production process and error propagation in the computations suggest that deviations of the resultant complex permittivity fall in the anticipated ranges. Features and issues of both computational and production parts of the technique are finally discussed. POLYM. ENG. SCI., 58:319–326, 2018. VC 2017 Society of Plastics Engineers
Design of a novel simply structured mixed-sensitivity loop-shaping robust controller for a gas-turbine

A previously developed technique for the design of simply structured robust controllers. This is robust in the sense of meeting some given singular value constraint. This is extended to deal with the mixed-sensitivity case. The method presented uses the Gershgorin disks of the system and can result in relatively simple controllers. The method is illustrated by application to the control of an aircraft gas-turbine engine.
Semantics of fractional permissions with nesting

Permissions specify mutable state that can be accessed by a program. Fractions distinguish write access (1) from read access (any smaller fraction). Nesting can model object invariants and ownership. Fractional permissions provides a foundation the meaning of many of access-based annotations: uniqueness, read-only, immutability, method effects, guarded state, etc. The semantics of fractional permissions with nesting is given in terms of “fractional heaps. ” We show that the fraction law Π ≡ 1/2 Π + 1/2 Π permits sound reasoning and that nesting can be carried out safely using only local reasoning.
The NIRSPEC Brown Dwarf Spectroscopic Survey. I. Low-Resolution Near-Infrared Spectra

We present the first results of a near-infrared (0.96-2.31 μm) spectroscopic survey of M, L, and T dwarfs obtained with NIRSPEC on the Keck II telescope. Our new survey has a resolving power of R = λ/Δλ ~ 2000 and is comprised of two major data sets: 53 J-band (1.14-1.36 μm) spectra covering all spectral types from M6 to T8 with at least two members in each spectral subclass (wherever possible), and 25 flux-calibrated spectra from 1.14 to 2.31 μm for most spectral classes between M6 and T8. Sixteen of these 25 objects have additional spectral coverage from 0.96 to 1.14 μm to provide overlap with optical spectra. Spectral flux ratio indexes for prominent molecular bands are derived, and equivalent widths (EWs) for several atomic lines are measured. We find that a combination of four H2O and two CH4 band strengths can be used for spectral classification of all these sources in the near-infrared and that the H2O indexes are almost linear with spectral type from M6 to T8. The H2O indexes near 1.79 and 1.96 μm should remain useful beyond T8. In the near-infrared a notable feature at the boundary between the M and L types is the disappearance of relatively weak (EW ~ 1-2 Å) atomic lines of Al I and Ca I, followed by Fe I around L2. At the boundary between L and T dwarfs it is the appearance of CH4 in all near-infrared bands (J, H, and K) that provides a significant spectral change, although we find evidence of CH4 as early as L7 in the K band. The FeH strength and the equivalent width of the K I lines are not monotonic, but in combination with other factors provide useful constraints on spectral type. The K I lines are sensitive to surface gravity. The CO band strength near 2.30 μm is relatively insensitive to spectral class. The peak calibrated flux (Fλ) in the 0.96-2.31 μm region occurs near 1.10 μm at M6 but shifts to about 1.27 μm at T8. In addition, the relative peak flux in the J, H, and K bands is always in the sense J > H > K except around L6, where the differences are small. One object, 2MASS 2244+20 (L6.5), shows normal spectral behavior in the optical but has an infrared spectrum in which the peak flux in J band is less than at H and K.
An inter-laboratory study of the calibration of optical full-field systems for measuring deformation

A calibration of optical full-field systems for measuring deformation is performed using a physical Reference Material that reproduces fields of strain and deformation. Traceability of the measurement results is established by applying a calibrated transducer at a selected point and using an analytic description of the deformation field to extend traceability to the entire gauge area. A Reference Material based on a cantilever together with a protocol for its use had been suggested for both static and dynamic calibrations in a CEN Workshop Agreement. They have been challenged in an inter-laboratory study of calibration conducted on an international scale. We report results of this inter-laboratory study of calibration which prove that the Cantilever Reference Material is sufficiently stable and reproducible to be used as a calibration artefact for displacement and strain fields in static and dynamic loading. Participants applied the Cantilever Reference Material in a range of tip deflections from 2 μm to 4.7 mm. Deformation from static bending is shown to be linear in the tip deflection up to the highest loads applied thus providing evidence that the reference values of the calibration artefact are appropriate. In dynamic loading, the first resonant bending mode has proven especially useful for the purpose of calibration. While the calibration procedure proved to be viable, the feed-back of the participants led to a number of modifications to the relevant chapter of the CEN Workshop Agreement, for example, as to the estimation of calibration uncertainty.
{RAVON} -- The Robust Autonomous Vehicle for Off-road Navigation

Abstract: This chapter describes the work of the Robotics Research Lab at the University of Kaiserslautern in the field of autonomous off-road robotics. It introduces concepts developed for hazard detection, terrain classification, and collision-free autonomous navigation. As an example of a system implementing the described techniques, the mobile off-road robot RAVON is presented. Experiments have been carried out to prove the effectiveness of the approaches.