nils-herrmann/clean_scirepeval huggingface dataset:
Fused analytical and iterative reconstruction (AIR) via modified proximal forward backward splitting: a FDK based iterative image reconstruction example for CBCT.
Venue: Physics in medicine and biology

This work is to develop a general framework, namely analytical iterative reconstruction (AIR) method, to incorporate analytical reconstruction (AR) method into iterative reconstruction (IR) method, for enhanced CT image quality and reconstruction efficiency. Specifically, AIR is established based on the modified proximal forward backward splitting (PFBS) algorithm, and its connection to the filtered data fidelity with sparsity regularization is discussed. As a result, AIR decouples data fidelity and image regularization with a two step iterative scheme, during which an AR projection step updates the filtered data fidelity term, while a denoising solver updates the sparsity regularization term. During the AR projection step, the image is projected to the data domain to form the data residual, and then reconstructed by certain AR to a residual image which is then weighted together with previous image iterate to form next image iterate. Intuitively since the eigenvalues of AR projection operator are close to the unity, PFBS based AIR has a fast convergence. Such an advantage is rigorously established through convergence analysis and numerical computation of convergence rate. The proposed AIR method is validated in the setting of circular cone beam CT with AR being FDK and total variation sparsity regularization, and has improved image quality from both AR and IR. For example, AIR has improved visual assessment and quantitative measurement in terms of both contrast and resolution, and reduced axial and half fan artifacts.
A new robust adaptive control method for modified function projective synchronization with unknown bounded parametric uncertainties and external disturbances

This paper investigates the problem of modified function projective synchronization of two different chaotic systems in the presence of parametric uncertainties and external disturbances. A new robust adaptive control is proposed, which is able to attenuate all random uncertainties of the drive and response systems. Moreover, there is no need to know the norm bounds of all random uncertainties, and the compensator gains can be automatically adapted to suitable constants. Numerical examples are provided to show the effectiveness of the proposed method.
Use of arginine to inhibit browning on fresh cut apple and lettuce

and assessed for browning on the cut surface during storage at 5 degC. Arginine delayed the development of browning and hence extended postharvest life. For apple slices, dipping in 50 mM arginine for 10 min resulted in a 15 fold increase in postharvest life over control slices. For lettuce pieces, the postharvest life was doubled by dipping in 100 mM arginine for 5 min. Arginine was found not to affect the taste of apple slices after a 250 mM dip and was more effective on a concentration basis than calcium ascorbate in inhibiting browning. Further studies are warranted to assess the suitability of arginine as a treatment to inhibit browning of fresh cut produce.
Ascorbate and Apple Phenolics Affect Protein Oxidation in Emulsion Type Sausages during Storage and in Vitro Digestion.
Venue: Journal of agricultural and food chemistry

The effect of sodium ascorbate and apple phenolics on the oxidative stability of emulsion type sausages during storage and digestion was investigated. Emulsion type sausages containing 0.05% sodium ascorbate or 3% freeze dried apple pomace were subjected to chilled illuminated storage and subsequent in vitro digestion. Lipid oxidation was assessed as TBARS, and protein oxidation was evaluated as thiol oxidation, total carbonyls, and g glutamic and a amino adipic semialdehyde. Proteolysis was measured after digestion to evaluate protein digestibility. The results suggest the presence of protein ascorbate and protein phenol interactions, which may decrease protein digestibility and may interfere with spectrophotometric methods for measuring oxidation.
Translation of Tempura specifications to eCST

eCST is an innovative, language independent intermediate source code representation designed as a basis of approach applied in development of SSQSA framework. This framework provides an infrastructure for consistent static software analysis. Tempura is a formal specification language, while Tempura programs are executable ITL (Interval Temporal Logic) specifications. This paper describes required steps to enable generation of eCST representation of Tempura code which leads to an incorporation of Tempura language in the infrastructure of SSQSA framework. This incorporation serves as a proof of concept that a formal specification language (like Tempura) can be successfully represented with an intermediate language representation (like eCST) that was primarily aimed for representation of "classical" programming languages.
Mobile Cloud Computing Techniques for Extending Computation and Resources in Mobile Devices
Venue: 2016 4th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)

This paper addresses whether Mobile Cloud Computing models can be used to extend the capabilities of resource constrained mobile devices to provide the illusion of infinite, elastic resources on demand. We identify five key limited resources as being CPU, memory, battery, data usage and time. Existing solutions for these limitations are explored, and we identify offloading computation and storage from the device as a possible solution. Offloading techniques mainly support two types of offloading, offloading to a remote cloud and to a peer device. Four different modes of execution are analysed, local SQL database, local NoSQL database, cloud NoSQL database and NoSQL peer to peer database. We develop a prototype which showcases these execution scenarios. Healthcare is identified as an ideal use case for our prototype due to the varied purposes it provides (e.g. in a hospital, in a clinic, on site etc. An open dataset of anonymised healthcare data is used as test data on which a set of experiments are run. Data generated via monitoring and logging of the prototype is collected and evaluated in terms of different execution scenarios. Using existing research we determine that Mobile Cloud Computing is a useful model for extending computation and resources in mobile devices. We identify that the discrepancy between our test results and existing research is due to the research approach, which evaluates results on a limited set of criteria and does not expand to other factors. Industries that would benefit from Mobile Cloud Computing include e commerce, healthcare and e learning, as well as education, finance, point of sale and transportation.
High Fidelity Quantum Logic Gates Using Trapped Ion Hyperfine Qubits.
Venue: Physical review letters

We demonstrate laser driven two qubit and single qubit logic gates with respective fidelities 99.9(1) and 99.9934(3) significantly above the 99% minimum threshold level required for fault tolerant quantum computation, using qubits stored in hyperfine ground states of calcium 43 ions held in a room temperature trap. We study the speed fidelity trade off for the two qubit gate, for gate times between 3.8 ms and 520 ms, and develop a theoretical error model which is consistent with the data and which allows us to identify the principal technical sources of infidelity.
Nuclear magnetic resonance detection and spectroscopy of single proteins using quantum logic
Venue: Science

Sensing single proteins with diamonds Nuclear magnetic resonance is a powerful technique for medical imaging and the structural analysis of materials, but is usually associated with large volume samples. Lovchinsky et al. exploited the magnetic properties of a single spin associated with a defect in diamond and manipulated it with a quantum logic protocol. They demonstrated the magnetic resonance detection and spectroscopy of multiple nuclear species within individual ubiquitin proteins attached to a specially treated diamond surface at room temperature. Science, this issue p. 836 The quantum properties of diamond are used for magnetic resonance spectroscopy of single proteins. Nuclear magnetic resonance spectroscopy is a powerful tool for the structural analysis of organic compounds and biomolecules but typically requires macroscopic sample quantities. We use a sensor, which consists of two quantum bits corresponding to an electronic spin and an ancillary nuclear spin, to demonstrate room temperature magnetic resonance detection and spectroscopy of multiple nuclear species within individual ubiquitin proteins attached to the diamond surface. Using quantum logic to improve readout fidelity and a surface treatment technique to extend the spin coherence time of shallow nitrogen vacancy centers, we demonstrate magnetic field sensitivity sufficient to detect individual proton spins within 1 second of integration. This gain in sensitivity enables high confidence detection of individual proteins and allows us to observe spectral features that reveal information about their chemical composition.
Trapped Ion Quantum Logic with Global Radiation Fields.
Venue: Physical review letters

Trapped ions are a promising tool for building a large scale quantum computer. However, the number of required radiation fields for the realization of quantum gates in any proposed ion based architecture scales with the number of ions within the quantum computer, posing a major obstacle when imagining a device with millions of ions. Here, we present a fundamentally different approach for trapped ion quantum computing where this detrimental scaling vanishes. The method is based on individually controlled voltages applied to each logic gate location to facilitate the actual gate operation analogous to a traditional transistor architecture within a classical computer processor. To demonstrate the key principle of this approach we implement a versatile quantum gate method based on long wavelength radiation and use this method to generate a maximally entangled state of two quantum engineered clock qubits with fidelity 0.985(12) This quantum gate also constitutes a simple to implement tool for quantum metrology, sensing, and simulation.
Fast compressive tracking with improved classifiers
Venue: 2016 Chinese Control and Decision Conference (CCDC)

Visual tracking in a video is a challenging problem in computer vision. The core component of object tracker based on tracking by detection framework is a discriminative classifier, tasked with distinguishing between the target and the surrounding environment. Fast compressive tracking algorithm is utilized to cope with real time tracking which trained a classifier to distinguish foreground and background, however, it does not take into account the influence of previous positive samples, when target occluded, it is easy lead to tracking fail or drifting problem. This paper proposed a new samples extracted method which take the previous positive samples into classifier training, two sub classifier are trained and combined to a strong classifier which is used to distinguish target. Experimental results demonstrated the effectiveness of our method.
Single object tracking system using fast compressive tracking
Venue: 2016 IEEE International Conference on Consumer Electronics Asia (ICCE Asia)

In this work we focused on the application aspect of object tracking for pan tilt zoom (PTZ) camera using ordinary webcam mounted on custom made motor assembly and found that our system is not only robust to illumination conditions but also cost effective in comparison with PTZ cameras. For object tracking we utilized Fast Compressive Tracking (FCT) algorithm because of its attractive features e.g. online learning, fast computation and robust performance. A PC program interfaced with embedded system through serial RS232 commands motors, hence camera, to real time track desired object in world such that object being tracked remains in the center of image.
An Improved Fast Compressive Tracking Algorithm Based on Online Random Forest Classifier

The fast compressive tracking (FCT) algorithm is a simple and efficient algorithm, which is proposed in recent years. But, it is difficult to deal with the factors such as occlusion, appearance changes, pose variation, etc in processing. The reasons are that, Firstly, even if the naive Bayes classifier is fast in training, it is not robust concerning the noise. Secondly, the parameters are required to vary with the unique environment for accurate tracking. In this paper, we propose an improved fast compressive tracking algorithm based on online random forest (FCT ORF) for robust visual tracking. Firstly, we combine ideas with the adaptive compressive sensing theory regarding the weighted random projection to exploit both local and discriminative information of the object. The second reason is the online random forest classifier for online tracking which is demonstrated with more robust to the noise adaptively and high computational efficiency. The experimental results show that the algorithm we have proposed has a better performance in the field of occlusion, appearance changes, and pose variation than the fast compressive tracking algorithm's contribution.
Untangling taxonomy: a DNA barcode reference library for Canadian spiders
Venue: Molecular ecology resources

Approximately 1460 species of spiders have been reported from Canada, 3% of the global fauna. This study provides a DNA barcode reference library for 1018 of these species based upon the analysis of more than 30 000 specimens. The sequence results show a clear barcode gap in most cases with a mean intraspecific divergence of 0.78% vs. a minimum nearest neighbour (NN) distance averaging 7.85% The sequences were assigned to 1359 Barcode index numbers (BINs) with 1344 of these BINs composed of specimens belonging to a single currently recognized species. There was a perfect correspondence between BIN membership and a known species in 795 cases, while another 197 species were assigned to two or more BINs (556 in total) A few other species (26) were involved in BIN merges or in a combination of merges and splits. There was only a weak relationship between the number of specimens analysed for a species and its BIN count. However, three species were clear outliers with their specimens being placed in 11 22 BINs. Although all BIN splits need further study to clarify the taxonomic status of the entities involved, DNA barcodes discriminated 98% of the 1018 species. The present survey conservatively revealed 16 species new to science, 52 species new to Canada and major range extensions for 426 species. However, if most BIN splits detected in this study reflect cryptic taxa, the true species count for Canadian spiders could be 30 50% higher than currently recognized.
Recent progress in half Heusler thermoelectric materials

Half Heusler (HH) thermoelectric (TE) materials have been attracting extensive research interest over the last two decades, owing to their thermal stability, mechanical strength, and moderate ZT This material system are potential candidates for medium to high temperature applications, which is close to the temperature range of most industrial waste heat sources. In this mini review article, we briefly summarize the recent progress and advances in HH thermoelectric materials. Some effectively available approaches, such as HH nanocomposites to reduce thermal conductivity, using larger atomic mass and size differences to enhance phonon scattering to further reduce the thermal conductivity, forming ternary systems following the cost effective approach. In addition, new thermoelectric HH members are also discussed in this article, which points out that many new HH compounds may be possible for TE applications.
Genomic epidemiology of artemisinin resistant malaria.
Venue: eLife

The current epidemic of artemisinin resistant Plasmodium falciparum in Southeast Asia is the result of a soft selective sweep involving at least 20 independent kelch13 mutations. In a large global survey, we find that kelch13 mutations which cause resistance in Southeast Asia are present at low frequency in Africa. We show that African kelch13 mutations have originated locally, and that kelch13 shows a normal variation pattern relative to other genes in Africa, whereas in Southeast Asia there is a great excess of non synonymous mutations, many of which cause radical amino acid changes. Thus, kelch13 is not currently undergoing strong selection in Africa, despite a deep reservoir of variations that could potentially allow resistance to emerge rapidly. The practical implications are that public health surveillance for artemisinin resistance should not rely on kelch13 data alone, and interventions to prevent resistance must account for local evolutionary conditions, shown by genomic epidemiology to differ greatly between geographical regions.
CrossCheck: toward passive sensing and detection of mental health changes in people with schizophrenia
Venue: UbiComp

Early detection of mental health changes in individuals with serious mental illness is critical for effective intervention. CrossCheck is the first step towards the passive monitoring of mental health indicators in patients with schizophrenia and paves the way towards relapse prediction and early intervention. In this paper, we present initial results from an ongoing randomized control trial, where passive smartphone sensor data is collected from 21 outpatients with schizophrenia recently discharged from hospital over a period ranging from 2 8.5 months. Our results indicate that there are statistically significant associations between automatically tracked behavioral features related to sleep, mobility, conversations, smart phone usage and self reported indicators of mental health in schizophrenia. Using these features we build inference models capable of accurately predicting aggregated scores of mental health indicators in schizophrenia with a mean error of 7.6% of the score range. Finally, we discuss results on the level of personalization that is needed to account for the known variations within people. We show that by leveraging knowledge from a population with schizophrenia, it is possible to train accurate personalized models that require fewer individual specific data to quickly adapt to new users.
ELECTROCHEMICAL IMPEDANCE SPECTROSCOPY FOR PALM COOKING OIL DISCRIMINATOR USING PLANAR ELECTROMAGNETIC SENSOR ARRAY

Cooking oil is an important product in the Malaysia food industries. Most of the cooking oil products is based on palm oil. However, there are activities in selling cheaper cooking oil by labelling as high quality in cooking oil product. Traditional methods have been developed to measure the quality of the cooking oil product such as the chromatography technique but the cost for the system setup is expensive and requires a large amount of time to analyse the sample. Thus, a suitable and reliable system with less analysis time is needed for widespread industrial uses. This paper has presented a discriminative technique for palm cooking oil using Electrochemical Impedance Spectroscopy (EIS) with planar electromagnetic sensor array. The sensor consists of a meander sensor and an interdigital sensors which interact with the test samples. Three types of palm cooking oil such as double refined palm oil, refined and deodorized palm oil with peanut and sesame oil, and filtered palm oil were prepared. The results obtained showed that the presented technique was able to differentiate the samples between 20 kHz to 1 Mhz. The results obtained correlate with the theories on EIS technique and planar electromagnetic sensor which are presented in this paper.
Sensors and Instrumentation towards early detection of osteoporosis
Venue: 2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings

A label free non invasive sensing system for detection of C terminal telopeptide of type I collagen (CTX I) has been developed in order to detect bone loss at an early stage, by Electrochemical Impedance Spectroscopy (EIS) A planar interdigital sensor was functionalized by immobilizing streptavidin agarose on the sensing area of the sensor to introduce selectivity for the antigen antibody solution. Different concentrations of CTX I were tested using the functionalized sensing surface to capture the target molecule. Preliminary results are provided in the paper assisted with the respective equivalent circuit of the working technology on the sensor using Complex Non linear Least Square (CNLS) The results are encouraging and will be used to develop a complete system for commercialization complementing the existing systems.
Smart Sensing System for the Prognostic Monitoring of Bone Health
Venue: Sensors

The objective of this paper is to report a novel non invasive, real time, and label free smart assay technique for the prognostic detection of bone loss by electrochemical impedance spectroscopy (EIS) The proposed system incorporated an antibody antigen based sensor functionalization to induce selectivity for the C terminal telopeptide type one collagen (CTx I) molecules a bone loss biomarker. Streptavidin agarose was immobilized on the sensing area of a silicon substrate based planar sensor, patterned with gold interdigital electrodes, to capture the antibody antigen complex. Calibration experiments were conducted with various known CTx I concentrations in a buffer solution to obtain a reference curve that was used to quantify the concentration of an analyte in the unknown serum samples. Multivariate chemometric analyses were done to determine the performance viability of the developed system. The analyses suggested that a frequency of 710 Hz is the most discriminating regarding the system sensitivity. A detection limit of 0.147 ng/mL was achieved for the proposed sensor and the corresponding reference curve was linear in the range of 0.147 ng/mL to 2.669 ng/mL. Two sheep blood samples were tested by the developed technique and the results were validated using enzyme linked immunosorbent assay (ELISA) The results from the proposed technique match those from the ELISA.
Influence Factors for the Shear Strength of Exterior and Interior Reinforced Concrete Beam column Joints

This paper investigates the key influence factors for the shear strength of both exterior and interior reinforced concrete (RC) beam column joints. A database of totally 172 experimental RC beam column connections constructed using the published literature was used in the analysis. Based on the database, the correlation coefficient (CC) between the considered parameters and the tested joint shear strength was computed, and the important level of these parameters was quantified. Results of the analysis showed that five key parameters for the joint shear strength included (1) the concrete compressive strength, (2) the vertical joint shear reinforcement, (3) the beam bars detail index, (4) the horizontal joint shear reinforcement and (5) the column axial stress. Among the influence factors, the concrete compressive strength had the most significant correlation to the joint shear strength and interestingly its correlation was higher for the interior connections with CC 0.8 compared to CC 0.69 for the exterior connections. For the remaining factors, the analysis conversely showed that their correlations to the joint shear strength of exterior joint were stronger than that of the interior joint.