bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modern discontinuous Galerkin methods for the simulation of transitional and turbulent flows in biomedical engineering: A comprehensive LES study of the FDA benchmark nozzle model
Authors: Fehn Niklas , Wall Wolfgang A. , Kronbichler Martin 
Published: June 2019

AbstractThis work uses high‐order discontinuous Galerkin discretization techniques to simulate transitional and turbulent flows through medical devices. Flows through medical devices are characterized by moderate Reynolds numbers and typically involve different flow regimes such as laminar, transitional, and turbulent flows. Previous studies for the FDA benchmark nozzle model revealed limitations of Reynolds‐averaged Navier‐Stokes turbulence models when applied to more complex flow scenarios. Recent works based on large‐eddy simulation approaches indicate that these limitations can be overcome but also highlight potential limitations due to a high sensitivity with respect to numerical parameters. The methodology presented in this work introduces two novel ingredients compared with previous studies. Firstly, we use high‐order discontinuous Galerkin methods for discretization in space. The inherent dissipation and dispersion properties of high‐order discontinuous Galerkin discretizations are expected to render this approach well suited for transitional and turbulent flow simulations. Secondly, to mimic blinded CFD studies, we propose to use a precursor simulation approach in order to predict the inflow boundary condition for laminar, transitional, and turbulent flow regimes instead of prescribing analytical velocity profiles at the inflow. We investigate the whole range of Reynolds numbers as suggested by the FDA benchmark nozzle problem and compare the numerical results to experimental data obtained by particle image velocimetry in order to critically assess the predictive capabilities of the solver on the one hand and the suitability of the FDA nozzle problem as a benchmark in computational fluid dynamics on the other hand.
Person re‐identification in the edge computing system: A deep square similarity learning approach
Authors: Chen Xin , Li Zhuo , Tang Chao , Xiao Shenglong , Chen Ying 
Published: June 2019

SummaryThe proliferation of mobile phones and webcams has led to an exponential increase in video data. One of the key technologies of video surveillance systems is Person Re‐identification (Re‐ID). The Re‐ID is used to identify whether the target pedestrian is the same person, and through scene matching, cross‐field tracking and track prediction of suspected pedestrians can be achieved. The edge computing has become the first choice for video analysis and processing, because of shorter response time and more efficient processing. In this paper, we propose a deep square similarity learning (DSSL), which considers the difference correlation, first‐order correlation, and two‐order correlation of image pairs. The training data automatically adjusts the network parameters and the weights of the three correlations to minimize the loss of the training set. Moreover, we conducted experiments on the challenging Re‐ID databases CuHK03 and Male1501. Compared with algorithm IDLA and DHSL, the first recognition rate is increased by 18% and 40%, respectively, in CuHK03, and 22% and 80% in Male1501. Then, we propose an online deep square similarity learning (ODSSL) algorithm to solve problem of data updating after the model is established by DSSL strategy. Meanwhile, ODSSL shows shorter update time and more efficient processing.
Intracluster cooperative communication in smart home scenario through stable election protocol
Authors: Immanuvel Arokia James K. , Prabakaran R. 
Published: June 2019

SummaryA wireless sensor network (WSN) can give a coordinated and minimal effort checking and control answer for such keen emotionally supportive systems. In this paper, we have discussed about the SEP in comparison with LEACH for smart home applications. Smart home scenario of an industry is taken into consideration in our research. The normal sink node is represented in the name of link node that connects the multiple sectors in the smart home scenario. In addition, it will act as a cluster head for the entire smart home setup. Moreover, the present research work proposes the plan of a low energy and high throughput and various levelled cluster‐based directing convention for smart home sensor organize application. Proposed protocol performs dynamic cluster head choice in light of various node qualities like node enduring energy, remoteness of the node from the link (sink), and average distance of the node from various neighbor nodes. Cluster head appropriation is even and brings about upgraded organization lifetime. Sensor nodes process the sense information utilizing nearby on‐board processors and exclude the repetitive information from transmission. In the final section, the energy level and the through put can be compared with the LEACH for getting a better understanding. The simulation results of the proposed technique clarify the energy consumed and the energy remaining in the stream. The energy will be measured in Joules. Moreover, the dead node will be tracked and intimated through our proposed work. The packet delivery and the delayed process of each and every node will be discussed in the proposed simulation result. The energy level remained will be calculated in Joules measurement. The SEP level will be more when compared with LEACH protocol. The energy level will be improved in case of SEP as 5, 10, 15, and 20 J/ ms.
Ant colony optimization‐induced route optimization for enhancing driving range of electric vehicles
Authors: Manogaran Gunasekaran , Shakeel P. Mohamed , Priyan R Vishnu , Chilamkurti Naveen , Srivastava Abhishekh 
Published: June 2019

SummaryElectric vehicles (EVs) are the emerging solution for pollution‐free transportation systems in the modern era. Battery‐operated motor‐powered electric vehicles serve the purpose of transportation with in‐time recharging ability. Routing and traversing locations using EVs demand optimal route selection for retaining delay and power of the vehicle. This manuscript proposes a fitness‐ant colony optimization (FACO)–based route optimization for improving the driving range of EVs. FACO works in two phases: conditional route discovery and range‐sustained traversing to control delay and to deprive EV failures because of earlier power drain. In range‐sustained phase, the fitness of the traversing route is framed by considering the inputs of power and travel time of the EV for ensuring construction of optimal touring paths. The EVs are directed to traverse the paths defined through ACO, after which the available paths are further attuned to identify the most efficient route depending on the braking and battery power of the vehicle. This optimization balances both power and its variants along with travel time for improving the driving range of the EV before it actually drains out. The optimization technique is assessed using arbitrary road and delivery point simulation with real‐time configurations to demonstrate the effectiveness of the proposed method. Experimental results demonstrate the consistency of the proposed FACO by increasing driving distance and delivery point visits. This optimization also achieves lesser power depletion retaining higher charging level with lesser waiting time.
Effects of imperfect channel sensing and estimation on the performance of cognitive radio systems
Authors: Abd El‐Hamid Zahraa , Hassan Emad S. , Zekry Abdelhalim A. , Elagooz Salah S. , Samir Moataz , Abd El‐Samie Fathi E. 
Published: June 2019

SummaryIn realistic scenarios of cognitive radio (CR) systems, imperfect channel sensing may occur due to false alarms and miss detections. Channel estimation between the secondary user transmitter and another secondary user receiver is another challenge in CR systems, especially for frequency‐selective fading channels. In this context, this paper presents a study of the effects of imperfect channel sensing and channel estimation on the performance of CR systems. In particular, different methods of channel estimation are analyzed under channel sensing imperfections. Initially, a CR system model with channel sensing errors is described. Then, the expectation maximization (EM) algorithm is implemented in order to learn the channel fading coefficients. By exploiting the pilot symbols and the detected symbols at the secondary user receiver, we can estimate the channel coefficients. We further compare the proposed EM estimation algorithm with different estimation algorithms such as the least squares (LS) and linear minimum mean square error (LMMSE). The expressions of channel estimates and mean squared errors (MSE) are determined, and their dependencies on channel sensing uncertainty are investigated. Finally, to reduce the complexity of EM algorithm, a sub‐optimal algorithm is also proposed. The obtained results show that the proposed sub‐optimal algorithm provides a comparable bit error rate (BER) performance with that of the optimal one yet with less computational complexity.
Sensitivity and specificity of detection methods for erythropoietin doping in cyclists
Authors: Heuberger Jules A.A.C. , van Eenoo Peter , Rotmans Joris I. , Gal Pim , Stuurman Frederik E. , Post Titiaan E. , Daniels Johannes M.A. , Ram Herman , de Hon Olivier , Burggraaf Jacobus , Cohen Adam F. 
Published: June 2019

AbstractRecombinant human erythropoietin (rHuEPO) is used as doping a substance. Anti‐doping efforts include urine and blood testing and monitoring the athlete biological passport (ABP). As data on the performance of these methods are incomplete, this study aimed to evaluate the performance of two common urine assays and the ABP. In a randomized, double‐blinded, placebo‐controlled trial, 48 trained cyclists received a mean dose of 6000 IU rHuEPO (epoetin β) or placebo by weekly injection for eight weeks. Seven timed urine and blood samples were collected per subject. Urine samples were analyzed by sarcosyl‐PAGE and isoelectric focusing methods in the accredited DoCoLab in Ghent. A selection of samples, including any with false presumptive findings, underwent a second sarcosyl‐PAGE confirmation analysis. Hematological parameters were used to construct a module similar to the ABP and analyzed by two evaluators from an Athlete Passport Management Unit. Sensitivity of the sarcosyl‐PAGE and isoelectric focusing assays for the detection of erythropoietin abuse were 63.8% and 58.6%, respectively, with a false presumptive finding rate of 4.3% and 6%. None of the false presumptive findings tested positive in the confirmation analysis. Sensitivity was highest between 2 and 6 days after dosing, and dropped rapidly outside this window. Sensitivity of the ABP was 91.3%. Specificity of the urine assays was high; however, the detection window of rHuEPO was narrow, leading to questionable sensitivity. The ABP, integrating longitudinal data, is more sensitive, but there are still subjects that evade detection. Combining these methods might improve performance, but will not resolve all observed shortcomings.
Quantitative PCR primer design affects quantification of dsRNA‐mediated gene knockdown
Authors: Onchuru Thomas Ogao , Kaltenpoth Martin 
Published: June 2019

AbstractRNA interference (RNAi) is a powerful tool for studying functions of candidate genes in both model and nonmodel organisms and a promising technique for therapeutic applications. Successful application of this technique relies on the accuracy and reliability of methods used to quantify gene knockdown. With the limitation in the availability of antibodies for detecting proteins, quantitative PCR (qPCR) remains the preferred method for quantifying target gene knockdown after dsRNA treatment. We evaluated how qPCR primer binding site and target gene expression levels affect quantification of intact mRNA transcripts following dsRNA‐mediated RNAi. The use of primer pairs targeting the mRNA sequence within the dsRNA target region failed to reveal a significant decrease in target mRNA transcripts for genes with low expression levels, but not for a highly expressed gene. By contrast, significant knockdown was detected in all cases with primer pairs targeting the mRNA sequence extending beyond the dsRNA target region, regardless of the expression levels of the target gene. Our results suggest that at least for genes with low expression levels, quantifying the efficiency of dsRNA‐mediated RNAi with primers amplifying sequences completely contained in the dsRNA target region should be avoided due to the risk of false‐negative results. Instead, primer pairs extending beyond the dsRNA target region of the mRNA transcript sequences should be used for accurate and reliable quantification of silencing efficiency.
Engineered Nanomaterial Assisted Signal‐amplification Strategies for Enhancing Analytical Performance of Electrochemical Biosensors
Authors: Kumar Ashutosh , Purohit Buddhadev , Maurya Pawan Kumar , Pandey Lalit Mohan , Chandra Pranjal 
Published: June 2019

AbstractThe design and development of modern biosensors for sensitive and selective detection of various biomarkers is important in diversified arenas including healthcare, environment, and food industries etc. The requirement of more robust and reliant biosensors lead to the development of various sensing modules. The nanomaterials having specific optical, electrical, and mechanical strength can pave the way towards development of ultrafast, robust, and miniaturized modules for biosensors. It can provide not only the point‐of‐care applicability but also has tremendous commercial as well as industrial justification. In order to improve the performance of the sensor systems, various nanostructure materials have been readily studied and applied for development of novel biosensors. In the last few years, researchers are engaged on harnessing the unique atomic and molecular properties of advance‐engineered materials including carbon nanotubes, graphene nanosheets, metal nanoparticles, metal oxide nanoparticles, and their nano‐conjugates. In view of such recent developments in nanomaterial engineering, the current review has been formulated emphasizing the role of these materials in surface engineering, biomolecule conjugation, and signal amplification for development of various ultrasensitive and robust biosensors having commercial as well as industrial viability. Attention is given on the electrochemical biosensors incorporating various nanomaterials and their conjugates. Importance of nanomaterials in the analytical performance of the various biosensor has also been discussed. To put a perceptive insights on the importance of various nanomaterials, an extended table is incorporated, which includes probe design, analyte, LOD, and dynamic range of various electrochemical biosensors.
Seismic vulnerability of roof systems combining URM gable walls and timber diaphragms
Authors: Tomassetti Umberto , Correia António A. , Graziotti Francesco , Penna Andrea 
Published: June 2019

SummaryTypical low‐rise masonry buildings consist of unreinforced masonry (URM) walls covered with various timber roof configurations generally supported or finished by masonry gables. Post‐earthquake observations and experimental outcomes highlighted the large vulnerability of the URM gables to the development of overturning mechanisms, both because of the inertial out‐of‐plane excitation and the in‐plane timber diaphragm deformability.This paper presents the static and dynamic experimental seismic performance of three full‐scale roofs tested via quasi‐static cyclic and shake table tests. Two of them were tested as part of a whole full scale one‐storey and two‐storey building.A single‐degree‐of‐freedom (SDOF) numerical model is calibrated against experimental data and proposed for the analysis of this roof typology's dynamic behaviour. Several sets of analyses were conducted to assess the vulnerability of these structural components and to study the effect of the whole building's characteristics (eg, number of storeys and structural stiffness and strength) on the seismic performance of this roof typology.
Water Quality Monitoring to Support Cumulative Effects Assessment and Decision Making in the Mackenzie Valley, Northwest Territories, Canada
Authors: Wong Lindsay , Noble Bram , Hanna Kevin 
Published: June 2019

Abstract
Project proponent- and government-led environmental monitoring are required to identify, understand, and manage cumulative effects (CE), yet such monitoring initiatives are rarely mutually supportive. Notwithstanding the need for a more integrated and complementary approach to monitoring, monitoring efforts are often less effective than intended for addressing CE. This paper examines current monitoring programs in the Mackenzie Valley, Northwest Territories, Canada, based on 7 attributes: consistency, compatibility, observability, detectability, adaptability, accessibility, and usability. Results indicate a tenuous link between and across proponent-led monitoring requirements under project-specific water licenses and government-led monitoring of regional baseline conditions. There is some consistency in what is monitored, but data are often incompatible, insufficient to understand baseline change, not transferable across projects or scales, inaccessible to end users, and ultimately unsuitable to understanding CE. Lessons from the Mackenzie Valley highlight the need for improved alignment of monitoring efforts across programs and scales, characterized by a set of common parameters that are most useful for early detection of cumulative change and supporting regulatory decisions at the project scale. This alignment must be accompanied by more open and accessible data for both proponents and regulators, while protecting the sensitivity of proprietary information. Importantly, there must be conceptual guidance for CE, such that the role of monitoring is clear, providing the types of CE questions to be asked, identifying the hypotheses to be tested, and ensuring timely and meaningful results to support regulatory decisions. © 2019 SETAC
Lens cholesterol biosynthesis inhibition: A common mechanism of cataract formation in laboratory animals by pharmaceutical products
Authors: Aleo Michael D. , Doshna Colleen M. , Baltrukonis Daniel , Fortner Jay H. , Drupa Cynthia A. , Navetta Kimberly A. , Fritz Carol A. , Potter David M. , Verdugo Maria E. , Beierschmitt William P. 
Published: June 2019

AbstractCJ‐12,918, a 5‐lipoxygenase (5‐LO) inhibitor, caused cataracts during a 1‐month safety assessment studies in rats whereas the structurally similar ZD‐2138 was without effect. For CJ‐12,918 analogs, blocking different sites of metabolic liability reduced (CJ‐13,454) and eliminated (CJ‐13,610) cataract formation in both rats and dogs. Using this chemical series as a test set, models and mechanisms of toxicity were first explored by testing the utility of ex vivo rat lens explant cultures as a safety screen. This model overpredicted the cataractogenic potential of ZD‐2138 due to appreciably high lens drug levels and was abandoned in favor of a mechanism‐based screen. Perturbations in lens sterol content, from a decline in lathosterol content, preceded cataract formation suggesting CJ‐12,918 inhibited lens cholesterol biosynthesis (LCB). A 2‐day bioassay in rats using ex vivo LCB assessments showed that the level of LCB inhibition was correlated with incidence of cataract formation in animal studies by these 5‐LO inhibitors. Thereafter, this 2‐day bioassay was applied to other pharmaceutical programs (neuronal nitric oxide synthase, sorbitol dehydrogenase inhibitor, squalene synthetase inhibitor and stearoyl‐CoA desaturase‐1 inhibitors/D4 antagonists) that demonstrated cataract formation in either rats or dogs. LCB inhibition >40% was associated with a high incidence of cataract formation in both rats and dogs that was species specific. Bioassay sensitivity/specificity were further explored with positive (RGH‐6201/ciglitazone/U18666A) and negative (tamoxifen/naphthalene/galactose) mechanistic controls. This body of work over two decades shows that LCB inhibition was a common mechanism of cataract formation by pharmaceutical agents and defined a level of inhibition >40% that was typically associated with causing cataracts in safety assessment studies typically ≥1 month.
Temperature‐dependent structure and compressive mechanical behavior of alginate/polyethylene oxide–poly(propylene oxide)–poly(ethylene oxide) hydrogels
Authors: Quah Suan P. , Nykypanchuk Dmytro , Bhatia Surita R. 
Published: June 2019

AbstractWe report the structural and mechanical behavior of multicomponent hydrogels comprising the commercial poly(ethylene oxide)–poly(propylene oxide)–poly(ethylene oxide) block copolymer F127 and alginate. Previous studies on this system have shown thermoreversible behavior in shear rheology. Here we explore the properties of these materials under compression and large deformations, relevant to applications such as wound dressings that require mechanical robustness. For gels with lower F127 concentration, we find that the stiffness of the gels can be ascribed to the alginate network, and that the Young's modulus and fracture stress do not strongly depend on temperatures. However, for gels with an F127 concentration of 30 wt %, the Young's modulus is enhanced at higher temperatures. Under large deformations, the fracture stress and fracture strain of the materials can be independently varied using the alginate and F127 concentrations, respectively; without the trade‐off in these properties that is often observed in rigid polymer networks. Small‐angle X‐ray scattering shows a power‐law dependence scattering intensity on q arising from the alginate network and scattering peaks consistent with rearranging micelles. For gels with lower F127 concentrations, we find a disordered–body‐centered cubic (BCC)‐face‐centered cubic (FCC) progression of states with temperature, and a BCC/FCC mixture for gels with higher F127 concentrations.