nils-herrmann/clean_scirepeval huggingface dataset:
A new steroidal saponin, furotrilliumoside from Trillium tschonoskii inhibits lipopolysaccharide induced inflammation in Raw264.7 cells by targeting PI3K/Akt, MARK and Nrf2/HO 1 pathways.
Venue: Fitoterapia

A new steroidal saponin, furotrilliumoside (FT) was isolated from the roots and rhizomes of Trillium tschonoskii Maxim. Its structure was elucidated on the basis of 1D and 2D NMR spectroscopic data as well as HR ESI MS analysis. FT showed superior activity of inhibiting NO production of RAW264.7 cells induced by lipopolysaccharide (LPS) in the preliminary biological screening. In order to develop novel therapeutic drug for acute and chronic inflammatory disorders, the anti inflammatory activity and underlying mechanism of FT were investigated in LPS induced RAW264.7 cells. The results showed that FT could reduce LPS induced expression of inducible nitric oxide synthase (iNOS) and then resulted in the decrement of NO production. More meaningful, FT could down regulate the expression of cyclooxygenase 2 (COX 2) and decrease the expressions of pro inflammatory cytokines, tumor necrosis factor a (TNF a) interleukin 6 (IL 6) and interleukin 1b (IL 1b) in both gene and protein levels. In mechanism study, FT blocked the LPS induced upregulation of phosphorylated phosphoinositide 3 kinase and Akt (PI3K/Akt) Furthermore, FT inhibited the translocation of nuclear factor kappa B (NF kB) through the prevention of inhibitory factor kappa B alpha (IkBa) phosphorylation and degradation and also suppressed the mitogen activated protein kinases (MAPK) signaling pathway in LPS stimulated RAW264.7 macrophages. In addition, FT upregulated heme oxygenase 1 (HO 1) expression via nuclear translocation of nuclear factor E2 related factor 2 (Nrf2) Taken together, FT might act as a natural agent to treat some inflammatory diseases by targeting PI3K/Akt, MARK and Nrf2/HO 1 pathways.
Deep Kernel Learning
Venue: AISTATS

We introduce scalable deep kernels, which combine the structural properties of deep learning architectures with the non parametric flexibility of kernel methods. Specifically, we transform the inputs of a spectral mixture base kernel with a deep architecture, using local kernel interpolation, inducing points, and structure exploiting (Kronecker and Toeplitz) algebra for a scalable kernel representation. These closed form kernels can be used as drop in replacements for standard kernels, with benefits in expressive power and scalability. We jointly learn the properties of these kernels through the marginal likelihood of a Gaussian process. Inference and learning cost $O(n) for $n$ training points, and predictions cost $O(1) per test point. On a large and diverse collection of applications, including a dataset with 2 million examples, we show improved performance over scalable Gaussian processes with flexible kernel learning models, and stand alone deep architectures.
Stochastic Variational Deep Kernel Learning
Venue: NIPS

Deep kernel learning combines the non parametric flexibility of kernel methods with the inductive biases of deep learning architectures. We propose a novel deep kernel learning model and stochastic variational inference procedure which generalizes deep kernel learning approaches to enable classification, multi task learning, additive covariance structures, and stochastic gradient training. Specifically, we apply additive base kernels to subsets of output features from deep neural architectures, and jointly learn the parameters of the base kernels and deep network through a Gaussian process marginal likelihood objective. Within this framework, we derive an efficient form of stochastic variational inference which leverages local kernel interpolation, inducing points, and structure exploiting algebra. We show improved performance over stand alone deep networks, SVMs, and state of the art scalable Gaussian processes on several classification benchmarks, including an airline delay dataset containing 6 million training points, CIFAR, and ImageNet.
NETWORK INTRUSION DETECTION PREVENTION SYSTEM USING FUZZY LOGIC AND GENETIC ALGORITHM

Now a day is very important to maintain a high level security to keep information safe and secure between different organizations. The data communication over internet is always under threat of intrusions and misuses. Thus the intrusion Detection Systems have become a need in network security. Fuzzy logic and Genetic Algorithm are two techniques that can use combine to classify network attack information. Fuzzy rule is a machine learning algorithm that can classify network attack data, while a genetic algorithm is an optimization algorithm that can use to find appropriate fuzzy rule and give the best solution. The objective of this paper is to describe a fuzzy genetic based learning algorithm and discuss its usage to detect intrusion in a computer network.
Deep Variational Canonical Correlation Analysis
Venue: ArXiv

We present deep variational canonical correlation analysis (VCCA) a deep multi view learning model that extends the latent variable model interpretation of linear CCA to nonlinear observation models parameterized by deep neural networks. We derive variational lower bounds of the data likelihood by parameterizing the posterior probability of the latent variables from the view that is available at test time. We also propose a variant of VCCA called VCCA private that can, in addition to the "common variables" underlying both views, extract the "private variables" within each view, and disentangles the shared and private information for multi view data without hard supervision. Experimental results on real world datasets show that our methods are competitive across domains.
Moderating Effects of Online Platform Business Ecosystems between Customer Participation and Psychological Ownership: A Comparison of Kakao and Facebook Ecosystems

The business ecosystem perspective offers a new lens in which to view customers. Customers as the member of business ecosystems influence firms by participating in both the firm level activities and the business ecosystem level activities. For example, customers participate in the business ecosystems by forming interest groups, allowing their voice to be heard the within business ecosystems. Customers can also, turn public opinion around and foster the business ecosystems favorable to firms. On the other hand, as an extreme case of customer participation, customers can engage in community activities to boycott the purchase of products or services from certain firms or business ecosystems.  This study views content creation and feedback activities as customer participation in the firm level. On the other hand, word of mouth (WOM) and boycott activities are considered as customer participation in the business ecosystem level. This study presents a research model regarding the relationships among customer socialization, customer participation, and psychological ownership. The proposed model is validated through an empirical analysis on online platform business ecosystems.  When the two business ecosystems are compared, different results were drawn. In the Facebook ecosystem, boycott and psychological ownership did not have a significant relationship. However, in the Kakao ecosystem, the two had a significant positive relationship. The mediating effect of the business ecosystem type sheds a light on the mission, purpose, vision, and other values associated with the theory of the business on the customer firm relationship. Further implications for theory and practice were discussed in this study.
A remote sensing aided multi layer perceptron Markov chain analysis for land use and land cover change prediction in Patna district (Bihar) India
Venue: Arabian Journal of Geosciences

Land use and land cover (LULC) changes are recognized as one of the most significant driver of environmental changes, mainly due to rapid urbanization. In this paper, an attempt has been made to appraise the ability of multi layer perceptron Markov chain analysis (MLP MCA) integrated method to monitor and predict the future LULC change scenarios in Patna district, Bihar using remote sensing images. A supervised maximum likelihood classification method was applied to derive LULC maps from 1988, 2001, and 2013 Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+/Operational Land Imager (OLI) images, respectively. The LULC maps of 1988 and 2001 were employed to predict the LULC scenario for 2013 using MLP MCA method. The predicted result was compared with the observed LULC map of 2013 to validate the method using kappa index statistics. Finally, based on the results, the future LULC change prediction for 2038 and 2050 was performed. The outcomes of this study reveal the rapid growth in built up area results in continuous decrease in agricultural lands.
Electronically Controlled Beam Steering through Vanadium Dioxide Metasurfaces
Venue: Scientific reports

Engineered metamaterials offer unique functionalities for manipulating the spectral and spatial properties of electromagnetic waves in unconventional ways. Here, we report a novel approach for making reconfigurable metasurfaces capable of deflecting electromagnetic waves in an electronically controllable fashion. This is accomplished by tilting the phase front of waves through a two dimensional array of resonant metasurface unit cells with electronically controlled phase change materials embedded inside. Such metasurfaces can be placed at the output facet of any electromagnetic radiation source to deflect electromagnetic waves at a desired frequency, ranging from millimeter wave to far infrared frequencies. Our design does not use any mechanical elements, external light sources, or reflectarrays, creating, for the first time, a highly robust and fully integrated beam steering device solution. We demonstrate a proof of concept beam steering metasurface optimized for operation at 100 GHz, offering up to 44deg beam deflection in both horizontal and vertical directions. Dynamic control of electromagnetic wave propagation direction through this unique platform could be transformative for various imaging, sensing, and communication applications, among others.
Survey of Beam Steering Techniques Available for Millimeter Wave Applications

Pattern reconfigurable antennas (beam steerable antennas) are essential for various applications in electronic engineering such as telecommunication and radar. They mitigate interference by channelling the antenna's radiation to the direction of interest. This ability is vital for millimetre wave frequency applications such as small cell backhaul links where high path loss, attenuation from obstacles, and misalignment due to wind sway and accidents are prevalent. Several techniques have been used to implement beam steering over the years, most of which achieves steering at the expense of antenna performance. In this article, we surveyed the various techniques used in achieving beam steering and analyse each based on some figures of merit with the aim of identifying areas of improvements for each beam steering technique.
Advanced Integration Techniques on Broadband Millimeter Wave Beam Steering for 5G Wireless Networks and Beyond
Venue: IEEE Journal of Quantum Electronics

Recently, the desired very high throughput of 5G wireless networks drives millimeter wave (mm wave) communication into practical applications. A phased array technique is required to increase the effective antenna aperture at mm wave frequency. Integrated solutions of beamforming/beam steering are extremely attractive for practical implementations. After a discussion on the basic principles of radio beam steering, we review and explore the recent advanced integration techniques of silicon based electronic integrated circuits (EICs) photonic integrated circuits (PICs) and antenna on chip (AoC) For EIC, the latest advanced designs of on chip true time delay (TTD) are explored. Even with such advances, the fundamental loss of a silicon based EIC still exists, which can be solved by advanced PIC solutions with ultra broad bandwidth and low loss. Advanced PIC designs for mm wave beam steering are then reviewed with emphasis on an optical TTD. Different from the mature silicon based EIC, the photonic integration technology for PIC is still under development. In this paper, we review and explore the potential photonic integration platforms and discuss how a monolithic integration based on photonic membranes fits the photonic mm wave beam steering application, especially for the ease of EIC and PIC integration on a single chip. To combine EIC, for its accurate and mature fabrication techniques, with PIC, for its ultra broad bandwidth and low loss, a hierarchical mm wave beam steering chip with large array delays realized in PIC and sub array delays realized in EIC can be a future proof solution. Moreover, the antenna units can be further integrated on such a chip using AoC techniques. Among the mentioned techniques, the integration trends on device and system levels are discussed extensively.
Detection of Inner Corrosion of Steel Construction Using Magnetic Resistance Sensor and Magnetic Spectroscopy Analysis
Venue: IEEE Transactions on Magnetics

The detection of the inner corrosion of steel construction, specifically backside corrosion of a steel plate, is highly demanded to maintain safety. Eddy current testing (ECT) is widely used as a nondestructive testing and an evaluation method for detecting surface and subsurface flaws. However, the ECT is usually applied to non ferromagnetic materials, but has difficulties when applied to ferromagnetic materials with high permeability, since the skin depth is smaller, and the signal to noise ratio (SNR) decreases due to magnetic flux fluctuation. In this paper, we developed a magnetic probe using an anisotropic magnetic resistance (AMR) sensor with the sensitivity of 1 nT/Hz that can detect inner corrosion at extremely low frequency. We also developed an analysis method using magnetic spectroscopy to delete the magnetic flux fluctuation. To improve the SNR of the detected signal, a small cancellation coil around the AMR sensor canceled the applied magnetic field directly coupled to the sensor. The frequency of the applied magnetic field ranged from 1 Hz to 1 kHz. The sensor output at each frequency was lock in detected. The weak ac magnetic field was applied to the initial permeability region of the magnetization curve. The obtained magnetic vector signal consisting of a real part and an imaginary part at each frequency was plotted as magnetic spectroscopy, and the magnetic component of the eddy current and the magnetic component of the magnetization of the steel were separated. By using the magnetic component of the eddy current, the thickness of an iron steel plate thinner than 16 mm could be measured. Moreover, the shape of the back side corrosion was determined by scanning with the magnetic probe.
Electrochemical enzyme sensor arrays for the detection of the biogenic amines histamine, putrescine and cadaverine using magnetic beads as immobilisation supports
Venue: Microchimica Acta

AbstractElectrochemical biosensors based on diamine oxidase (DAO) conjugated to magnetic beads (MBs) were developed for the detection of histamine (Hist) putrescine (Put) and cadaverine (Cad) the most relevant biogenic amines (BAs) related to food safety and quality. DAO MBs were immobilised on Co(II) phthalocyanine/carbon and Prussian Blue/carbon electrodes to obtain mono enzymatic biosensors, and on Os wired HRP modified carbon electrodes to obtain bi enzymatic biosensors. The three sensor have low working potentials +0.4 V, 0.1 V and 0.05 V vs Ag/AgCl, respectively) a linear range of two orders of magnitude (from 0.01 to 1 mM BA) good reproducibility (variability lower than 10 high repeatability (up to 8 consecutive measurements) limits of detection in the uM concentration range for Hist and in the sub uM concentration range for Put and Cad, and no response from possible interfering compounds. The DAO MB conjugates display excellent long term stability (at least 3 months) The biosensor has been applied to the determination of BAs in spiked and naturally spoiled fish, demonstrating its suitability both as screening tool and for BAs quantification. The use of MBs as supports for enzyme immobilisation is advantageous because the resulting biosensors are simple, fast, stable, affordable, and can be integrated into array platforms. This makes them suitable for high throughput analysis of BAs in the food industry. Graphical AbstractMagnetic beads are used as diamine oxidase immobilisation supports for the development of amperometric biosensors for the detection of histamine, putrescine and cadaverine. Fast, low cost, stable and easy to use biosensors for high throughput monitoring of biogenic amines are achieved. Biogenic Amine; DAO: Diamine oxidase; HRP: Horseradish peroxidase.
DNA magnetic bead detection using disposable cards and the anisotropic magnetoresistive sensor

A disposable card incorporating specific DNA probes targeting the 16 S rRNA gene of Streptococcus suis was developed for magnetically labeled target DNA detection. A single stranded target DNA was hybridized with the DNA probe on the SPA/APTES/PDMS/Si as prepared card, which was subsequently magnetically labeled with superparamagnetic beads for detection using an anisotropic magnetoresistive (AMR) sensor. An almost linear response between the output signal of the AMR sensor and amount of single stranded target DNA varied from 4.5 to 18 pmol was identified. From the sensor output signal response towards the mass of magnetic beads which were directly immobilized on the disposable card surface, the limit of detection was estimated about 312 ng ferrites, which corresponds to 3.8 memu. In comparison with DNA detection by conventional biosensor based on magnetic bead labeling, disposable cards are featured with higher efficiency and performances, ease of use and less running cost with respects to consumables for biosensor in biomedical analysis systems operating with immobilized bioreceptor.
Interactive online choreography for a multi quadrotor system

We present a full system for online control of multiple quadrotors. Rather than following scripted directions, our system interprets user instructions and modifies quadrotor behavior online, allowing a user to issue instructions at any time to easily control and modify flight. Handling multiple quadrotors is done through grouping to allow a user to reduce a number of individual robots into scaleably sized collectives as needed. Instructions are specified from a simple enumeration of potential action combinations governing formation shape, flight speed and style, and overall group tasking (travel to target, aim spotlight, etc) which combinatorially yield over 8000 possible behaviors. The system interprets all user commands into dynamically feasible, non colliding trajectories, and results are shown for over 100 behavior instructions issued online to a multi quadrotor hardware system used for a theatrical performance.
Maximizing post stroke upper limb rehabilitation using a novel telerehabilitation interactive virtual reality system in the patient's home: study protocol of a randomized clinical trial.
Venue: Contemporary clinical trials

Telerehabilitation (TR) or the provision of rehabilitation services from a distance using telecommunication tools such as the Internet, can contribute to ensure that patients receive the best care at the right time. This study aims to assess the effect of an interactive virtual reality (VR) system that allows ongoing rehabilitation of the upper extremity (UE) following a stroke, while the person is in their own home, with offline monitoring and feedback from a therapist at a distance.  A single blind (evaluator is blind to group assignment) two arm randomized controlled trial is proposed, with participants who have had a stroke and are no longer receiving rehabilitation services randomly allocated to: (1) 4 week written home exercise program, i.e. usual care discharge home program or (2) a 4 week home based TR exercise program using VR in addition to usual care i.e. treatment group. Motor recovery of the UE will be assessed using the Fugl Meyer Assessment UE and the Box and Block tests. To determine the efficacy of the system in terms of functional recovery, the Motor Activity Log, a self reported measure of UE use will be used. Impact on quality of life will be determined using the Stroke Impact Scale 16. Lastly, a preliminary cost effectiveness analysis will be conducted using costs and outcomes for all groups.  Findings will contribute to evidence regarding the use of TR and VR to provide stroke rehabilitation services from a distance. This approach can enhance continuity of care once patients are discharged from rehabilitation, in order to maximize their recovery beyond the current available services.
Teaching By Principles An Interactive Approach To Language Pedagogy

In undergoing this life, many people always try to do and get the best. New knowledge, experience, lesson, and everything that can improve the life will be done. However, many people sometimes feel confused to get those things. Feeling the limited of experience and sources to be better is one of the lacks to own. However, there is a very simple thing that can be done. This is what your teacher always manoeuvres you to do this one. Yeah, reading is the answer. Reading a book as this teaching by principles an interactive approach to language pedagogy 3rd edition paperback and other references can enrich your life quality. How can it be?
Twin robotic x ray system for 2D radiographic and 3D cone beam CT imaging
Venue: SPIE Medical Imaging

In this work, we provide an initial characterization of a novel twin robotic X ray system. This system is equipped with two motor driven telescopic arms carrying X ray tube and flat panel detector, respectively. 2D radiographs and fluoroscopic image sequences can be obtained from different viewing angles. Projection data for 3D cone beam CT reconstruction can be acquired during simultaneous movement of the arms along dedicated scanning trajectories. We provide an initial evaluation of the 3D image quality based on phantom scans and clinical images. Furthermore, initial evaluation of patient dose is conducted. The results show that the system delivers high image quality for a range of medical applications. In particular, high spatial resolution enables adequate visualization of bone structures. This system allows 3D X ray scanning of patients in standing and weight bearing position. It could enable new 2D/3D imaging workflows in musculoskeletal imaging and improve diagnosis of musculoskeletal disorders.