bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Delicate Balance between Antiferromagnetism and Ferromagnetism: Theoretical and Experimental Studies of A2MRu5B2 (A=Zr, Hf; M=Fe, Mn) Metal Borides
Authors: Shankhari Pritam , Bakshi Nika G. , Zhang Yuemei , Stekovic Dejan , Itkis Mikhail E. , Fokwa Boniface P. T. 
Published: November 2019

AbstractMetal‐rich borides with the Ti3Co5B2‐type structure represent an ideal playground for tuning magnetic interactions through chemical substitutions. In this work, density functional theory (DFT) and experimental studies of Ru‐rich quaternary borides with the general composition A2MRu5B2 (A=Zr, Hf, M=Fe, Mn) are presented. Total energy calculations show that the phases Zr2FeRu5B2 and Hf2FeRu5B2 prefer ground states with strong antiferromagnetic (AFM) interactions between ferromagnetic (FM) M‐chains. Manganese substitution for iron lowers these antiferromagnetic interchain interactions dramatically and creates a strong competition between FM and AFM states with a slight preference for AFM in Zr2MnRu5B2 and for FM in Hf2MnRu5B2. Magnetic property measurements show a field dependence of the AFM transition (TN): TN is found at 0.1 T for all phases with predicted AFM states whereas for the predicted FM phase it is found at a much lower magnetic field (0.005 T). Furthermore, TN is lowest for a Hf‐based phase (20 K) and highest for a Zr‐based one (28 K), in accordance with DFT predictions of weaker AFM interactions in the Hf‐based phases. Interestingly, the AFM transitions vanish in all compounds at higher fields (>1 T) in favor of FM transitions, indicating metamagnetic behaviors for these Ru‐rich phases.
Chiral Imidazolidin‐4‐one with catalytic amount of Dicationic ionic liquid act as a recoverable and reusable Organocatalyst for asymmetric Diels‐Alder reaction
Authors: Deepa  , Yadav Geeta Devi , Chaudhary Pooja , Aalam Mohd Jubair , Meena Dhan Raj , Singh Surendra 
Published: November 2019

AbstractImidazolidin‐4‐one is used as a recoverable organocatalyst for the asymmetric Diels‐Alder reaction in the presence of catalytic amount of dicationic ionic liquid and trifluoroacetic acid as a co‐catalyst. The Diels‐Alder reaction between model substrate cyclopentadiene and crotonaldehyde gave the product in 95% conversion and 87% ee of the endo‐product. The catalyst was shown better reusability when the 20 mol% of dicationic ionic liquid was used and catalyst was reused upto 5 cycles, conversion remains upto 3 recycles but ee of endo‐9 was slightly droped.
Ir/Phase‐Transfer‐Catalysis Cooperatively Catalyzed Asymmetric Cascade Allylation/2‐aza‐Cope Rearrangement: An Efficient Route to Homoallylic Amines from Aldimine Esters†
Authors: Wei Liang , Xiao Lu , Wang Zuo‐Fei , Tao Hai‐Yan , Wang Chun‐Jiang 
Published: November 2019

Summary of main observation and conclusionHerein, we developed an Ir/phase‐transfer‐catalysis cooperatively catalyzed asymmetric cascade allylation/2‐aza‐Cope rearrangement of aldimine esters to prepare synthetically important homoallylic amines in good yields with excellent enantioselectivities. Compared with the bimetallic catalytic system to realize this transformation, the current cooperative Ir/tetrabutyl ammonium bromide catalytic system provides an alternative but more practical approach, which not only simplify the manipulation process but also increase the cost efficiency.
Physical activity is reduced prior to ventricular arrhythmias in patients with a wearable cardioverter defibrillator
Authors: Burch Ashley E. , D'Souza Benjamin , Gimbel J. Rod , Rohrer Ursula , Masuda Tsuyoshi , Sears Samuel , Scherr Daniel 
Published: November 2019

AbstractIntroductionThe utility of accelerometer‐based activity data to identify patients at risk of sustained ventricular tachycardia (VT) or ventricular fibrillation (VF) has not previously been investigated. The aim of the current study was to determine whether physical activity is associated with manifesting spontaneous sustained VT/VF requiring emergent defibrillation in patients with an ejection fraction of ≤35%.MethodsPatients consecutively prescribed a wearable cardioverter defibrillator (WCD) from April 2015 to May 2018 were included. Shock data and 4 weeks of physical activity data, beginning with the first week of WCD wear, were analyzed.ResultsBased on the ROC curve outcome generated from 4057 patients, average daily step count during the first week accurately predicted those patients with sustained VT/VF compared to those without (shocked (n = 81) vs nonshocked (n = 3976) area under the curve, c‐index = 0.71, 95% CI = 0.65‐0.77, P < .001). An average cutoff of 3637 daily steps during week 1 separated the groups. Patients who averaged fewer than 3637 steps per day during the first week of WCD use were 4.3 times more likely to experience a shock than those who walked more than 3637 steps per day (OR = 4.29, 95% CI = 2.58‐7.15, P < .001).DiscussionAverage daily step counts are lower in WCD patients who manifest spontaneous VT/VF. Whether these findings represent a causal or correlational relationship, future studies to encourage a minimum daily step count in high‐risk patients may impact the incidence of sustained VT/VF.
Novel approaches for glioblastoma treatment: Focus on tumor heterogeneity, treatment resistance, and computational tools
Authors: Valdebenito Silvana , D'Amico Daniela , Eugenin Eliseo 
Published: November 2019

AbstractBackgroundGlioblastoma (GBM) is a highly aggressive primary brain tumor. Currently, the suggested line of action is the surgical resection followed by radiotherapy and treatment with the adjuvant temozolomide, a DNA alkylating agent. However, the ability of tumor cells to deeply infiltrate the surrounding tissue makes complete resection quite impossible, and, in consequence, the probability of tumor recurrence is high, and the prognosis is not positive. GBM is highly heterogeneous and adapts to treatment in most individuals. Nevertheless, these mechanisms of adaption are unknown.Recent findingsIn this review, we will discuss the recent discoveries in molecular and cellular heterogeneity, mechanisms of therapeutic resistance, and new technological approaches to identify new treatments for GBM. The combination of biology and computer resources allow the use of algorithms to apply artificial intelligence and machine learning approaches to identify potential therapeutic pathways and to identify new drug candidates.ConclusionThese new approaches will generate a better understanding of GBM pathogenesis and will result in novel treatments to reduce or block the devastating consequences of brain cancers.
HEMA 3 Staining: A Simple Alternative for the Assessment of Myoblast Differentiation
Authors: Levitt Danielle E. , Adler Katherine A. , Simon Liz 
Published: November 2019

AbstractSkeletal muscle tissue regeneration requires quiescent satellite cell activation, proliferation, and differentiation. Regenerative capacity of satellite cells can be studied in vitro by differentiating under low‐serum conditions (2% to 5%) to form multinucleated myotubes. Myotubes are fixed and stained, and indices of differentiation are quantified. Jenner and Giemsa stains are typically used for myotube staining; however, this staining process can be variable depending on factors such as stain pH, staining time, and time since stain preparation. This article includes protocols for myoblast isolation, proliferation, and differentiation in vitro; Jenner‐Giemsa staining; HEMA 3 staining; and quantification. Representative images using each staining method and quantification are included. The protocols identify critical steps and considerations for cell culture and each staining method and provide an even simpler alternative to Jenner‐Giemsa staining. © 2019 by John Wiley & Sons, Inc.Basic Protocol 1: Primary myoblast isolationAlternate Protocol 1: Plating cryopreserved myoblastsBasic Protocol 2: Myoblast passage and expansionBasic Protocol 3: Myoblast differentiationBasic Protocol 4: HEMA 3 stainingAlternate Protocol 2: Jenner‐Giemsa stainingBasic Protocol 5: Quantification of myotube densityBasic Protocol 6: Quantification of fusion indexBasic Protocol 7: Quantification of myotubes per field
An efficient and lightweight multi‐scroll chaos‐based hardware solution for protecting fingerprint biometric templates
Authors: Azzaz Mohamed Salah , Tanougast Camel , Maali Abdelmadjid , Benssalah Mustapha 
Published: November 2019

SummaryThis paper presents a new efficient and lightweight approach for enhancing the security of biometric models, namely, fingerprint templates, against possible attacks. The proposed design is based on Vernam stream cipher in which the key generator is designed in the hardware manner. The designed cryptosystem consists of using multi‐scroll chaotic system that is characterized by a large key space and can be generated N×N grid multi‐scroll attractors, with a good behavior of chaotic dynamic. The hardware approach is carried out through describing Euler method by VHDL. Field‐programmable gate array (FPGA) experimental results validate the developed architecture while still providing a good compromise between hardware resources and performance. Indeed, security analysis also shows that the designed encryption algorithm is robust against statistical, brute force, and entropy attacks. Therefore, it can be considered as a lightweight security solution, which could be very useful in many embedded applications namely securing biometric authentication systems.
A statistical forecasting approach to metapopulation viability analysis
Authors: Howell Paige E. , Hossack Blake R. , Muths Erin , Sigafus Brent H. , Chenevert‐Steffler Ann , Chandler Richard B. 
Published: November 2019

AbstractConservation of at‐risk species is aided by reliable forecasts of the consequences of environmental change and management actions on population viability. Forecasts from conventional population viability analysis (PVA) are made using a two‐step procedure in which parameters are estimated, or elicited from expert opinion, and then plugged into a stochastic population model without accounting for parameter uncertainty. Recently developed statistical PVAs differ because forecasts are made conditional on models fitted to empirical data. The statistical forecasting approach allows for uncertainty about parameters, but it has rarely been applied in metapopulation contexts where spatially explicit inference is needed about colonization and extinction dynamics and other forms of stochasticity that influence metapopulation viability. We conducted a statistical metapopulation viability analysis (MPVA) using 11 yr of data on the federally threatened Chiricahua leopard frog (Lithobates chiricahuensis) to forecast responses to landscape heterogeneity, drought, environmental stochasticity, and management. We evaluated several future environmental scenarios and pond restoration options designed to reduce extinction risk. Forecasts over a 50‐yr time horizon indicated that metapopulation extinction risk was <4% for all scenarios, but uncertainty was high. Without pond restoration, extinction risk is forecasted to be 3.9% (95% CI 0–37%) by year 2066. Restoring six ponds by increasing their hydroperiod reduced extinction risk to <1% and greatly reduced uncertainty (95% CI 0–2%). Our results suggest that managers can mitigate the impacts of drought and environmental stochasticity on metapopulation viability by maintaining ponds that hold water throughout the year and keeping them free of invasive predators. Our study illustrates the utility of the spatially explicit statistical forecasting approach to MPVA in conservation planning efforts.
Responses of four dominant dryland plant species to climate change in the Junggar Basin, northwest China
Authors: Xiao Jian , Eziz Anwar , Zhang Heng , Wang Zhiheng , Tang Zhiyao , Fang Jingyun 
Published: November 2019

AbstractAimDryland ecosystems are exceedingly sensitive to climate change. Desertification induced by both climate changes and human activities seriously threatens dryland vegetation. However, the impact of climate change on distribution of dryland plant species has not been well documented. Here, we studied the potential distribution of four representative dryland plant species (Haloxylon ammodendron, Anabasis aphylla, Calligonum mongolicum, and Populus euphratica) under current and future climate scenarios in a temperate desert region, aiming to improve our understanding of the responses of dryland plant species to climate change and provide guidance for dryland conservation and afforestation.LocationJunggar Basin, a large desert region in northwestern China.MethodsOccurrence data of the studied species were collected from an extensive field investigation of 2,516 sampling sites in the Junggar Basin. Ensemble species distribution models using 10 algorithms were developed and used to predict the potential distribution of each studied species under current and future climate scenarios.ResultHaloxylon ammodendron and A. aphylla were likely to lose most of their current suitable habitats under future climate scenarios, while C. mongolicum and P. euphratica were likely to expand their ranges or remain relatively stationary. Variable importance evaluation showed that the most important climate variables influencing species distribution differed across the studied species. These results may be explained by the different ecophysiological characteristics and adaptation strategies to the environment of the four studied species.Main conclusionsWe explored the responses of the representative dryland plant species to climate change in the Junggar Basin in northwestern China. The different changes in suitability of different species imply that policymakers may need to reconsider the selection and combination of the afforestation species used in this area. This study can provide valuable reference for the management and conservation of dryland ecosystems under future climate change scenarios.
Drying landscape and interannual herbivory‐driven habitat degradation control semiaquatic mammal population dynamics
Authors: Ward Ellen M. , Wysong Kelsie , Gorelick Steven M. 
Published: November 2019

AbstractSemiaquatic muskrat (Ondatra zibethicus) are in decline throughout their native range. We report on the environmental and behavioural mechanisms responsible for a half‐century of muskrat decline in a model system floodplain region of the Peace–Athabasca Delta (“Delta”). Using the Landsat satellite record, trapping and population survey records, and ecological field studies of muskrat, we develop conceptual and quantitative models to investigate mechanisms driving muskrat population decline at Egg Lake, an archetypal Delta region. Simulation results show processes occurring over nested timescales control population decline: Multidecadal drying has diminished shoreline habitat, and inter‐annual shoreline habitat deterioration resulted from excessive herbivory by muskrat thereby exacerbating their die‐off. Simulations without herbivory feedback show peak population values up to 73% higher than simulations with herbivory. Simulation results also suggest that trapping is not the primary cause of declines in muskrat abundance. The process model highlights factors responsible for long‐term decline and rapid die‐off, providing insights into mechanisms for observed muskrat population decline.
Development of highly sensitive environmental DNA methods for the detection of Bull Sharks, Carcharhinus leucas (Müller and Henle, 1839), using Droplet Digital™ PCR
Authors: Schweiss Katherine E. , Lehman Ryan N. , Drymon J. Marcus , Phillips Nicole M. 
Published: November 2019

AbstractBackgroundAs apex and mesopredators, elasmobranchs play a crucial role in maintaining ecosystem function and balance in marine systems. Elasmobranch populations worldwide are in decline as a result of exploitation via direct and indirect fisheries mortalities and habitat degradation; however, a lack of information on distribution, abundance, and population biology for most species hinders their effective management. Environmental DNA analysis has emerged as a cost‐effective and non‐invasive technique to fill some of these data gaps, but often requires the development of species‐specific methodologies.AimsHere, we established eDNA methodology appropriate for targeted species detections of Bull Sharks, Carcharhinus leucas, in estuarine waters in the northern Gulf of Mexico.Materials and MethodsWe compared different QIAGEN®DNeasy® extraction kit protocols and developed a species‐specific Droplet Digital™ PCR (ddPCR) assay by designing primers and an internal probe to amplify a 237 base pair portion of the ND2 gene in the mitochondrial genome of C. leucas. To validate the developed methods, water samples were collected from known C. leucas habitat and from an ex situ closed environment containing a single C. leucas individual. The effectiveness of the assay in an open environment was then assessed by placing one C. leucas into a flow‐through mesocosm system and water samples were collected every 30 min for 3 hr.ResultsThe developed C. leucas ‐specific assay has the ability to detect target DNA concentrations in a reaction as low as 0.6 copies/μl. DdPCR reactions performed on water samples from known habitat and 30 min after a shark was added to the closed environment contained 1.62 copies/μl and 166.6 copies/μl of target C. leucas eDNA, respectively. Carcharhinus leucas eDNA was detected in the flow‐through system within 30 min, but concentrations remained low and variable throughout the duration of the experiment.
Fractal dimension of antibody‐PEG precipitate: Light microscopy for the reconstruction of 3D precipitate structures
Authors: Satzer Peter , Burgstaller Daniel , Krepper Walpurga , Jungbauer Alois 
Published: November 2019

AbstractProtein and in particular antibody precipitation by PEG is a cost‐effective alternative for the first capture step. The 3D structure of precipitates has a large impact on the process parameters for the recovery and dissolution, but current technologies for determination of precipitate structures are either very time consuming (cryo‐TEM) or only generate an average fractal dimension (light scattering). We developed a light microscopy based reconstruction of 3D structures of individual particles with a resolution of 0.1–0.2 µm and used this method to characterize particle populations generated by batch as well as continuous precipitation in different shear stress environments. The resulting precipitate structures show a broad distribution in terms of fractal dimension. While the average fractal dimension is significantly different for batch and continuous precipitation, the distribution is broad and samples overlap significantly. The precipitate flocs were monofractal from micro‐ to nanoscale showing a random but consistent nature of precipitate formation. We showed that the fractal dimension and 3D reconstruction is a valuable tool for characterization of protein precipitate processes. The current switch from batch to continuous manufacturing has to take the 3D structure and population of different protein precipitates into account in their design, engineering, and scale up.
Short‐term failure mechanism triggered by hydraulic fracturing
Authors: Wang Gang , Liu Yixin , Xu Jiang 
Published: November 2019

AbstractHydraulic fracturing may induce or trigger an earthquake while injecting fluid into strata to initiate a new fracture so as to promote oil and gas production. Previous studies have confirmed that the injection of fluids into the formation, especially hydraulic fracturing, is closely related to seismic activity. However, the mechanism through which fluid injection changes the stress field of rock mass and interacts with the in situ stress state is still poorly understood. This study focused on the short‐term mechanism coupling shear stress and hydraulic fracturing in an experimental simulation. Preexisting tension fractures were initiated and propagated by loading shear force. The fracture propagation path of hydraulic fracturing was closely related to the preexisting fractures formed by the preshear stress. Short‐term hydraulic fracturing promoted fracture propagation and acoustic emission events (or microearthquake signals), but it was less likely to cause rock mass instability or a large earthquake. The long‐term fluid injection could saturate preexisting fractures and infiltrate rock mass to increase the pore pressure and change the in situ stress field in a large area to induce an earthquake.
A systematic literature review on formal verification of software‐defined networks
Authors: Souri Alireza , Norouzi Monire , Asghari Parvaneh , Rahmani Amir Masoud , Emadi Ghazaleh 
Published: November 2019

AbstractBy raising evolutionary network connections, a software‐defined network (SDN) offers a well‐managed and flexible novel network topology. The SDN efforts are provided to abstract the original network configuration for business applications and web services. Additionally, the SDN modifies the network management policies such as topology policies, deployment policies, the applicability, and infrastructure maintenance. One of the important features of the SDN is standardizing the network interfaces with the precise functional semantics in application and control flow layers. In another hand, specification and evaluation of the existing network interfaces is a main and significant challenge to prove the correctness of the configurable scenarios in the SDN approach. Recently, formal verification presents a high potential platform to evaluate the main‐layer scenarios of the SDN as the novel perspective in this area. Up to now, there is no survey and state‐of‐the‐art review on the formal verification methods in the SDN. This paper provides a systematic literature review (SLR) for the formal verification methods in the SDN in form of the SDN plans to recognize the state of the art of the open challenges. The presented SLR is classified into three main fields: application plan, data plan, and control plan approaches. The verification mechanisms are compared with each other according to the important factors such as structural properties, quality‐of‐service metrics, applied algorithms, and measurement tools.
Detection of clone scammers in Android markets using IoT‐based edge computing
Authors: Ullah Farhan , Naeem Hamad , Naeem Muhammad Rashid , Jabbar Sohail , Khalid Shehazad , Al‐Turjman Fadi , Abuarqoub Abdelrahman 
Published: November 2019

AbstractPirated application developers find an alternate way to publish pirated versions of the same Android mobile applications (apps) on different Android markets. Therefore, a centralized, automated scrutiny system among multiple app stores is inevitable to prevent publishing pirated or cloned version of these Android applications. In this paper, we proposed an Android clone detection system for Internet of things (IoT) (Droid‐IoT) devices. First, the proposed system receives an original Android application package (APK) file along with possible candidate cloned APKs over the cloud network. The system uses an apkExtractor tool to extract Dalvik Executable (DEX) files for each subject program. The Jdex decompiler is used to extract Java source files from DEXs. Then, the bag‐of‐word model is used to extract tokenized features from source files. Further, the weighting filters are used to zoom the importance of each token. Moreover, Synthetic Minority Oversampling is applied to retrieve balanced features for better training of data. Finally, TensorFlow with Keras deep learning model is designed to predict clones in Android applications. The experimental results have shown that Droid‐IoT can successfully detect cloned apps with an accuracy of up to 96%. The primary purpose of this system is to prevent the publishing of pirated apps among different app stores under different pirated names.