gebhart/patrepeval huggingface dataset:
Dual polarity voltage imaging reveals subthreshold dynamics and concurrent spiking patterns of multiple neuron-types (2021)

Abstract Genetically encoded fluorescent voltage indicators are ideally suited to reveal the millisecond-scale interactions among and between distinct, targeted cell populations. However, current indicator families lack the requisite sensitivity for in vivo multipopulation imaging. We describe high-performance green and red sensors, Ace-mNeon2 and VARNAM2, and their reverse response-polarity variants, pAce and pAceR. Our indicators enable 0.4-1 kHz voltage recordings from &gt;50 neurons per field-of-view in awake mice and ∼30-min continuous imaging in flies. Using dual-polarity multiplexed imaging, we uncovered behavioral state-dependent interactions between distinct neocortical subclasses, as well as contributions to hippocampal field potentials from non-overlapping projection neuronal ensembles. By combining three mutually compatible indicators, we demonstrate concurrent triple-population voltage imaging. Our approach will empower investigations of the dynamic interplay between neuronal subclasses at single-spike resolution. One Sentence Summary A new suite of voltage sensors enables simultaneous cellular-resolution activity imaging from multiple, targeted neuron-types in awake animals.
Revisiting Self-Supervised Visual Representation Learning (2019)

Unsupervised visual representation learning remains a largely unsolved problem in computer vision research. Among a big body of recently proposed approaches for unsupervised learning of visual representations, a class of self-supervised techniques achieves superior performance on many challenging benchmarks. A large number of the pretext tasks for self-supervised learning have been studied, but other important aspects, such as the choice of convolutional neural networks (CNN), has not received equal attention. Therefore, we revisit numerous previously proposed self-supervised models, conduct a thorough large scale study and, as a result, uncover multiple crucial insights. We challenge a number of common practices in self-supervised visual representation learning and observe that standard recipes for CNN design do not always translate to self-supervised representation learning. As part of our study, we drastically boost the performance of previously proposed techniques and outperform previously published state-of-the-art results by a large margin. We will release the code for reproducing our experiments when the anonymity requirements are lifted.
A time sequential simulation method for making electric energy monthly trade schedule incorporating multiple energy resources (2016)

The power system with multiple energy sources has complicated mathematic models, numerous variables, long simulation time and high computing requirements. The existing electric energy monthly trade schedules study only on one single conventional energy resource and cannot solve the electric energy monthly trade schedule incorporating multiple energy sources effectively. Based on this, the time sequential simulation method is proposed in this paper. The method has considered the output characteristics of wind power and conventional units, load characteristics, unit peaking characteristics and start-up mode. The power balance of the power grid with new energy is optimized hour by hour and the model of electric energy monthly trade schedule that meets the energy-saving generation dispatching is established. The result of the computing example verifies the rationality of the time sequential simulation model and the correctness of the theoretical analysis and achieves the target of the lowest integrative cost of monthly power generation. The model has strong social benefits and can provide a reference for making monthly trade schedule.
Classification of pathological disorders in children using random forest algorithm (2020)

The massive technological expansions in modern healthcare solutions have substantially influenced the development of several unfolding research fields. One such interesting area involves the therapeutic prognosis of pathological conditions in patients by using knowledge engineering techniques. These techniques have inevitably assisted in the growth of healthcare systems. In this paper, we provide a comprehensive classification framework for identification of pathological disorders in children. We consider a real dataset to study the accuracy in prediction of different classification algorithms for the identification of seven different pathological conditions. We then present an experimental analysis corresponding to the performance of each algorithm. This framework can be used for the early detection of diseases and for suggesting appropriate precautionary measures. Further a more stratified understanding of the demographics of a patient’s pathological conditions can be determined and appropriate treatment can be recommended.
Effect of Varidase (Streptodornase) on Biofilm Formed by <i>Pseudomonas aeruginosa</i> (2003)

The biofilm of Pseudomonas aeruginosa could be removed by Varidase (streptodornase) that was used as defibrinating drug. After cultivating the biofilm on a silicone chip in a modified alginate-producing medium in vitro, it was treated with Varidase or DNase I. In both treatments, the biofilm was removed depending on the concentration of the reagents. Varidase was apparently effective under the condition that the biofilm was exposed to more than 625 U/ml (a quarter of the concentration of the medical use) for 3 h, twice, at 37 degrees C. The result of this experiment indicates that (a) the DNases, DNase I and Varidase, were effective in destroying the biofilm of P. aeruginosa in vitro, and (b) in a clinical field, Varidase could be useful for P. aeruginosa focal infection, such as urinary tract infection, by removing the biofilm.
A Practical Link Budget for I-UWB Systems (2009)

This paper proposes a practical alternative to the traditional link budget approach for impulse-based UWB systems (I-UWB), which is based on the Friis formula. The proposed link budget approach overcomes the narrowband limitations of the traditional link budget by proposing the use of an antenna-pulse coupling gain. This gain is specific for an antenna tx-rx pair and the I-UWB pulse used and can be easily determined by taking a frequency or a time domain measurement. The paper introduces the approach and then verifies its accuracy by presenting the results of several measurements at distances ranging from 1 to 20 m.
A General Approach Towards Triazole‐Linked Adenosine Diphosphate Ribosylated Peptides and Proteins (2017)

Abstract Current methods to prepare adenosine diphosphate ribosylated (ADPr) peptides are not generally applicable due to the labile nature of this post‐translational modification and its incompatibility with strong acidic conditions used in standard solid‐phase peptide synthesis. A general strategy is presented to prepare ADPr peptide analogues based on a copper‐catalyzed click reaction between an azide‐modified peptide and an alkyne‐modified ADPr counterpart. The scope of this approach was expanded to proteins by preparing two ubiquitin ADPr analogues carrying the biological relevant α‐glycosidic linkage. Biochemical validation using Legionella effector enzyme SdeA shows that clicked ubiquitin ADPr is well‐tolerated and highlights the potential of this strategy to prepare ADPr proteins.
A Method to Study the Impact of Chemically-induced Ovarian Failure on Exercise Capacity and Cardiac Adaptation in Mice (2014)

The risk of cardiovascular disease (CVD) increases in post-menopausal women, yet, the role of exercise, as a preventative measure for CVD risk in post-menopausal women has not been adequately studied. Accordingly, we investigated the impact of voluntary cage-wheel exercise and forced treadmill exercise on cardiac adaptation in menopausal mice. The most commonly used inducible model for mimicking menopause in women is the ovariectomized (OVX) rodent. However, the OVX model has a few dissimilarities from menopause in humans. In this study, we administered 4-vinylcyclohexene diepoxide (VCD) to female mice, which accelerates ovarian failure as an alternative menopause model to study the impact of exercise in menopausal mice. VCD selectively accelerates the loss of primary and primordial follicles resulting in an endocrine state that closely mimics the natural progression from pre- to peri- to post-menopause in humans. To determine the impact of exercise on exercise capacity and cardiac adaptation in VCD-treated female mice, two methods were used. First, we exposed a group of VCD-treated and untreated mice to a voluntary cage wheel. Second, we used forced treadmill exercise to determine exercise capacity in a separate group VCD-treated and untreated mice measured as a tolerance to exercise intensity and endurance.
Germanium(II) Dications Stabilized by Azamacrocycles and Crown Ethers (2009)

A crown for germanium: Neutral aza- and oxamacrocycles enable stabilization of halide-free germanium(II) dications (see structure, Ge teal, N blue, C gray). The resulting structures show a marked dependence upon the denticity, donor type, and ring size of the macrocycle.
FeNi Cubic Cage@N-Doped Carbon Coupled with N-Doped Graphene toward Efficient Electrochemical Water Oxidation (2018)

Oxygen evolution reaction (OER) is of great significance in electrochemical water splitting on industrial scale, which suffers from the slow kinetics and large overpotential, thus setting the main obstacle for efficient water electrolysis. To pursue cost-effective OER electrocatalysts with high activity and durable stability, we here set a facile strategy to prepare N-doped graphene supported core–shell FeNi alloy@N-doped carbon nanocages (FeNi@NC-NG) by annealing graphene oxides supported Prussian blue analogues under H2/Ar atmosphere. Based on the specific structural benefits, the present catalyst shows superior OER catalytic activity than precious metal catalyst of RuO2 and Ir/C, with a low overpotential of 270 mV for 10 mA cm–2, as well as high stability. The simple synthesis process and outstanding electrocatalytic performances show great potential of FeNi@NC-NG to replace the noble metal-based catalysts toward electrochemical water oxidation.
THE EFFECT OF LIGHT-INDUCED METASTABLE DEFECTS ON THE MAGNETO-CONDUCTANCE OF POLY(PHENYLENE-VINYLENE) DIODES (2014)

We studied the changes in the magneto-conductance (MC) response in bipolar and unipolar organic diodes based on the π-conjugated polymer poly[2-methoxy-5-(2-ethylhexyl-oxy)-1,4-phenylene-vinylene] (MEH-PPV), upon prolonged illumination of light in the Visible–UV range. We found that the MC response in the hole-unipolar device gradually changes sign from negative to positive upon illumination, caused by the photogeneration of metastable donor-like defects in the MEH-PPV layer. This conclusion is supported by photoinduced absorption spectroscopy of pristine MEH-PPV film. In contrast, we found very little change in the MC response upon illumination of electron-unipolar devices; however, the MC response substantially increases in bipolar devices. We interpret the sign change in the MC response of hole-unipolar devices as due to illumination induced change in the spin-pairs that participate in the MC, from spin pairs of same charge to spin pairs of opposite charges.
Searching for interacting features (2007)

Feature interaction presents a challenge to feature selection for classification. A feature by itself may have little correlation with the target concept, but when it is combined with some other features, they can be strongly correlated with the target concept. Unintentional removal of these features can result in poor classification performance. Handling feature interaction can be computationally intractable. Recognizing the presence of feature interaction, we propose to efficiently handle feature interaction to achieve efficient feature selection and present extensive experimental results of evaluation.
Effect of conductive magnetic field concentrators on the performance of anisotropic magnetoresistors in high frequency contactless current sensing (2017)

High frequency power electronic converters require lossless, accurate and isolated current measurement. High frequency currents through a Printed Circuit Board (PCB) trace generates a non-uniform magnetic field around the trace. The non-uniform magnetic fields can be normalized by means of utilizing Magnetic Field Concentrators (MCON) using conductive materials. In this work, the effect of different magnetic field concentrators (MCONs) on the performance of Anisotropic Magnetoresistor (AMR) sensors for high frequency contactless current detection has been investigated. The performance of the AMR sensor equipped with different MCONs is demonstrated experimentally with respect to a fast rise step current. A detailed frequency analysis is performed on the sensor response with different MCONs to determine the effect on the detection bandwidth of the current sensors.
Regulation of swelling-activated Cl- current by angiotensin II signalling and NADPH oxidase in rabbit ventricle (2007)

Activation of I Cl,swell by osmotic swelling is controlled by the AngII-ROS cascade, the same pathway previously implicated in I Cl,swell activation by integrin stretch. This in part explains why I Cl,swell is persistently activated in several models of cardiac disease.
Evaluation of nacelle drag using computational fluid dynamics (2010)

Thrust and drag components must be defined and properly accounted in order to estimate aircraft performance, and this hard task is particularty essential for propulsion system where drag components are functions of engine operating conditions.The present work describes a numerical method used to calculate the drag in different nacelles, long and short ducted.Two-and three-dimensional calculations were performed, solving the Reynolds Averaged Navier-Stokes (RANS) equations with a commercial Computational Fluid Dynamics (CFD) code.It is then possible to obtain four drag components: wave, induced, viscous and spurious drag using a far-field formulation.An expression in terms of entropy variations was shown and drag for different nacelle geometries was estimated.
Saddle point method for JPDA and related filters (2015)

The Bayes posterior probability distribution of many multitarget tracking filters can be written in terms of the mixed derivatives of an appropriately defined generating function. Using the Cauchy Residue Theorem for several complex variables, it is shown that these derivatives can be approximated using the saddle point method, a classical technique in analytic combinatorics. The method gives approximate weights for the particles of sequential Monte Carlo filter implementations. For JPDA the approximate particle weights are seen to be accurate to within one or two percent of the exact weights, after a global scaling factor is applied. The saddle point method has polynomial computational complexity in the number of targets and measurements, assuming that a bounded number of iterations are needed to find the saddle point.
Robotics in Neurosurgery: Evolution, Current Challenges, and Compromises (2015)

Robotic-assisted surgery is a promising field in neurosurgery, but improvements and breakthroughs in minimally invasive and endoscopic robotic-assisted surgical systems must occur before robotic assistance becomes commonplace in the neurosurgical field.
CARACAL: a versatile passive acoustic monitoring tool for wildlife research and conservation (2019)

Acoustic localisation technology has been widely tested and applied for passive acoustic monitoring and ecological research, however, hardware costs of commercially available devices limit scalability. Furthermore, few studies have explored its use with low-density arrays. We present a low-cost, custom-designed hardware and software system termed ‘CARACAL’ that is able to extract and localise weak acoustic signals. The key to this is the use of four microphones on each logger, allowing for phase-based measurements and the ability to enhance signal-to-noise ratio through beamforming. As a proof of concept, we test the functionality of the CARACAL system by conducting a gunshot localisation experiment and demonstrate animal call detection and localisation from a lion predation event. Results show the system could locate gunshots with an average accuracy of 33.2 ± 15.3 m within an array of 7 stations 500 m apart. When applied to animal call positioning, we show long range (> 1 km) localisation of three different species’ calls, Cape buffalo, chacma baboon and spotted hyaena. With a cost of approximately £150 per unit, the CARACAL system provides a cost-effective solution for acoustic localisation over large areas. The system is open source and can be customised to suit a variety of wildlife research applications.
The recent trend of high density magnetic disks. (1987)

The recent trend of high density magnetic disks was reviewed. The magnetic hard disk and head were introduced from the standpoint of the manufacturing process and material. Recent future in the field was briefly discussed.
Planar and Three-Dimensional Printing of Conductive Inks (2011)

Printed electronics rely on low-cost, large-area fabrication routes to create flexible or multidimensional electronic, optoelectronic, and biomedical devices1-3. In this paper, we focus on one- (1D), two- (2D), and three-dimensional (3D) printing of conductive metallic inks in the form of flexible, stretchable, and spanning microelectrodes. Direct-write assembly4,5 is a 1-to-3D printing technique that enables the fabrication of features ranging from simple lines to complex structures by the deposition of concentrated inks through fine nozzles (~0.1 - 250 μm). This printing method consists of a computer-controlled 3-axis translation stage, an ink reservoir and nozzle, and 10x telescopic lens for visualization. Unlike inkjet printing, a droplet-based process, direct-write assembly involves the extrusion of ink filaments either in- or out-of-plane. The printed filaments typically conform to the nozzle size. Hence, microscale features (< 1 μm) can be patterned and assembled into larger arrays and multidimensional architectures. In this paper, we first synthesize a highly concentrated silver nanoparticle ink for planar and 3D printing via direct-write assembly. Next, a standard protocol for printing microelectrodes in multidimensional motifs is demonstrated. Finally, applications of printed microelectrodes for electrically small antennas, solar cells, and light-emitting diodes are highlighted.
High-Affinity Epidermal Growth Factor Receptor (EGFR) Irreversible Inhibitors with Diminished Chemical Reactivities as Positron Emission Tomography (PET)-Imaging Agent Candidates of EGFR Overexpressing Tumors (2005)

Previous studies with the anilinoquinazoline epidermal growth factor receptor (EGFR) irreversible inhibitor [(11)C]-ML03 demonstrated a rapid metabolism of the tracer, which led to its low in vivo accumulation in EGFR overexpressing tumors. To enhance tumor uptake, the chemical structure of the compound was modified, and four new groups of EGFR inhibitors with a wide range of chemical reactivities were synthesized. Chemical reactivity assay of the compounds, performed with reduced glutathione (GSH), revealed that the group C (4-(dimethylamino)-but-2-enoic amide) derivative was the least chemically reactive against the nucleophilic attack of GSH. Nonetheless, it demonstrated a high inhibitory potency and bound irreversibly to the EGFR. Consequently, the blood stability of the group C compound (5a, ML04) labeled with (11)C was studied. In a time frame of 60 min, no radioactive metabolites were detected in blood. The stability of [(11)C]-5a, as indicated both from in vitro blood-stability assays and injection into nude rats, was significantly higher as compared to [(11)C]-ML03. Since group C presented a greater promise for tumor accumulation, it represents, to date, the most suitable candidate for radiolabeling with long-lived positron emission tomography (PET) radioisotopes.
Fast Response Variable Focal-Length Lenses Using KTa1-xNbxO3Crystals (2011)

We fabricated variable focal length lenses with fast responses by using the strong Kerr effect of KTa1-xNbxO3 single crystals. We observed focus shifts of about 40 mm with the assistance of a 250-mm-focal-length lens, which corresponds to a focus shift from infinity to 1.56 m without the assisting lens. The time response was as fast as 1 µs.
Pb nanoparticles produced by ion implantation in Si and Al (2010)

status: Published
Enrichment of Biologically Active Compounds from Selected Plants Using Adsorptive Bubble Separation (2004)

In this research, foam fractionation a method belonging to the Adsorptive Bubble Separation Methods, was employed to enrich the following active principles contained in medically valuable plants: Faradiol esters from Calendula officinalis, catechins from Camellia sinensis, tryptanthrin from Isatis Tinctoria and cannabinoids from Cannabis sativa. The enrichment methods have been developed in the batch mode for these principles aqueous dilute solutions, based on their physicochemical nature and the process parameters and conditions. The hydrophobicity of faradiol esters, tryptanthrin, cannabinoids and catechins complexes with caffeine, permitted their enrichments. Optimisation was achieved for foam fractionation columns with high residence times, the utilisation of additives and by adjusting the solutions pH values
Practical network attack situation analysis using sliding window cache scheme (2004)

With the growing deployment of intrusion detection systems, managing reports from these systems become critically important. In situations where there are intensive intrusive actions, not only will actual alerts be mixed with false alerts, but the amount of alerts will also become unmanageable. As a result, it is difficult for human users or intrusion response systems to understand the intrusions behind the alerts and to take appropriate actions. Even if isolated events are not considered significant, the set of events may be critical. The alert correlation analysis is related to examine meaningful relationships between alert messages. The situation analysis is a branch of the alert correlation analysis. It is to observe attack activities by aggregating alerts that have certain characteristics in common. In this paper, we present an effective and practical situation analysis scheme that provides realtime analysis capability.
ChemInform Abstract: MRI Contrast Agents: Synthesis, Applications and Perspectives (2013)

Abstract Review: 104 refs.
Hydroperoxyditerpenoids from Octocorals (2019)

Abstract The structures, names, bioactivities, and references of 75 marine diterpenoids from octocorals possessing a hydroperoxy group, including 46 cembranes, 8 eunicellins, 5 briaranes, 5 dolabellanes, 4 germacranes, 3 xenicins, 2 caryophyllanes, 1 decalin, and 1 pseudopterosin, are summarized in this review article. All the hydroperoxyditerpenoids mentioned in this review were isolated from octocorals from Alcyonacea (Briareum excavatum, Briareum polyanthes, Briareum violaceum, Briareum sp., Cespitularia sp., Cladiella tuberculosa, Cladiella sp., Clavularia inflata, Klyxum simplex, Lemnalia sp., Lobophytum crassum, Lobophytum sp., Nephthea pacifica, Sarcophyton cherbonnieri, Sarcophyton crassocaule, Sarcophyton glaucum, Sarcophyton mililatensis, Sarcophyton trocheliophorum, Sarcophyton sp., Sinularia arborea, Sinularia erecta, Sinilaria flexibilis, Sinularia gibberosa, Sinularia manaarensis, Xenia umbellata) and Gorgonacea (Astrogorgia sp., Eunicea calyculata, Eunicea pinta, Eunicea succinea, Eunicea sp., Pseudopterogorgia sp.). Among these isolates, 41 compounds exhibited potential biomedical activities, including cytotoxicity, antimalarial activity, anti‐inflammatory activity, and antibacterial activity.