Crossover Value Research Articles

AI techniques applied to network intrusion detection system by using genetic approaches

The ability to identify and assess potential security risks to a communication network is a critical function of network intrusion detection systems. The data it provides regarding the frequency and type of assaults is a valuable addition to other network security measures, including firewalls. Typically, an NIDS will have a sensor that scans all incoming and outgoing packets on the monitored network, flags those that seem suspicious, and then sends the flagged packets and an alert message to a server system, which will then store them and analyse them in conjunction with other events. First, we standardised the protocol structure. Then, we used a genetic approach to generate mutation and cross-over values for device identification. Finally, we used a modified J48 decision tree algorithm to conduct our search. The developed algorithms/ones outperform the existing methods in terms of performance. As an initial step in detecting an intrusion, the 64-byte structured protocol standardisation technique is created. The wire shark tool is used to monitor the communication process network, taking into account all potential transactions. An array is created from the recorded packets. Included in the array are details about the frames, as well as the protocol type, hardware device type, source and destination IP addresses, MAC addresses, and data. This information is transformed by the 64-byte protocol structured standardisation. Because all of the necessary attributes are determined in the same place by this common protocol structure procedure, finding the MAC and IP addresses in packets should take as little time as possible. As a second step, the product and device details are supplied by the least and most important 16 bits of the MAC address. Using the cross-over and mutation functions, the genetic iv method compares the invader device to the Current Active Directory List (CADL).

On the discrepancy between crossovers of solubility in supercritical carbon dioxide and retention in supercritical fluid chromatography

Various crossover phenomena are immanent to supercritical fluids due to multidirectional temperature effects in highly compressible supercritical fluid media. Solubility crossover, i.e. controversial effect of temperature on solubility at different pressures, is probably the most well-known among them. A curious discrepancy in upper crossover pressure values between solubility in supercritical carbon dioxide and retention in supercritical fluid chromatography with pure CO2 as an eluent was unexpectedly observed for several non-polar compounds on different stationary phases. In some cases, retention crossover was found to happen at pressures almost twice as high as pressures for solubility crossover for the same compound. Retention data for three solutes with known solubility crossovers: anthracene, benzoic acid and vanillin, were collected at different pressures and temperatures for several stationary phases. The existence of upper retention crossovers, i.e. such pressure values beyond which temperature increase starts decreasing retention, were registered for all solute-sorbent combinations.Using known thermodynamic models of temperature effect on retention in supercritical fluid chromatography and on solubility in supercritical carbon dioxide, possible reasoning for the observed discrepancies is discussed. Major contribution of the balance between adsorption and partition retention mechanisms in defining retention crossover values is hypothesized.

Efeitos do robenacoxibe na concentração alveolar mínima do isofluorano em felinos domésticos

ABSTRACT Robenacoxib is a selective non-steroidal anti-inflammatory drug indicated for pain control in felines. The objective was to evaluate the effect of robenacoxib on the minimum alveolar concentration of isoflurane in cats. There were 30 cats that used one of the 3 treatments through therapy: GM - meloxicam (0.2 mg/kg), GR - robenacoxib (2 mg/kg) or GC - 0.9% saline solution (0.1 ml/kg) kg). We waited 30 minutes, and the animals were induced to general anesthesia with isoflurane in an induction box, intubated and anesthetized with 1.5 V% isoflurane. All animals were secured to a supramaximal nociceptive stimulus (tail pinch). Positive response was defined as proposed movement of the head and/or limbs. The method for determining MAC was up and down to Dixon, and calculation of the average of crossover values according to Monteiro (2016). The mean and standard deviation of ISOMAC was 2.10±0.15%, 1.95±0.14%, and 1.7±0.15% in GC, GM, and GR, respectively. Robenacoxib reduced to 19.1% and 12.8% ISOMAC when compared to a control group and a group that received meloxicam, respectively.

Flow Rate Dependency of Steady-State Two-Phase Flows in Pore Networks: Universal, Relative Permeability Scaling Function and System-Characteristic Invariants

The phenomenology of steady-state two-phase flow in porous media is conventionally recorded by the relative permeability diagrams in terms of saturation. Yet, theoretical, numerical and laboratory studies of flow in artificial pore network models and natural porous media have revealed a significant dependency on the flow rates—especially when the flow regime is capillary to capillary/viscous and part of the disconnected non-wetting phase remains mobile. These studies suggest that relative permeability models should incorporate the functional dependence on flow intensities. In the present work, a systematic dependence of the pressure gradient and the relative permeabilities on flow rate intensity is revealed. It is based on extensive simulations of steady-state, fully developed, two-phase flows within a typical 3D model pore network, implementing the DeProF mechanistic–stochastic model algorithm. Simulations were performed across flow conditions spanning 5 orders of magnitude, both in the capillary number, Ca, and the flow rate ratio, r, and for different favorable /unfavorable viscosity ratio fluid systems. The systematic, flow rate dependency of the relative permeabilities can be described analytically by a universal scaling function along the entire domain of the independent variables of the process, Ca and r. This universal scaling comprises a kernel function of the capillary number, Ca, that describes the asymmetric effects of capillarity across the entire flow regime—from capillarity-dominated to mixed capillarity/viscosity- to viscosity-dominated flows. It is shown that the kernel function, as well as the locus of the cross-over relative permeability values, are single-variable functions of the capillary number; they are both identified as viscosity ratio invariants of the system. Both invariants can be correlated with the structure of the pore network, through a function of Ca. Consequently, the correlation is associated with the wettability characteristics of the system. Among the potential applications, the proposed, universal, flow rate dependency scaling laws are the improvement of core analysis and dynamic rock-typing protocols, as well as integration into field-scale simulators or associated machine learning interventions for improved specificity/accuracy.

Machine Learning Model For Stunting Prediction

This study aims to find the best Supervised Machine Learning (SML) model for stunting prediction. This research was conducted using an experimental approach using 192 infant data with a composition of 183 normal infant data and 9 stunted infant data using a custom dataset. The conclusion obtained from this study can be concluded that the combination of the Random Forest classification algorithm with Support Vector Machine Weighting and the Genetic Algorithm Feature Selection has the best performance. The parameters with the best performance are: The training and testing data distribution is 90% of the training data and 10% of the testing data. The number of trees in the random forest algorithm is 100, and the Gain Ratio criterion and max_depth is 10. In the Genetic Algorithm, the best parameters are: The Roulette Wheel selection method, the population is 20, the mutation value is 0.03, and the crossover value is 0.9. The validation method uses k-fold cross validation with a value of k = 10. Another conclusion is that there are 44 supporting factors for stunting, which, if we take a ranking of 10 in order of magnitude from largest to smallest, the supporting factors for stunting are 1.Baby's weight at birth. 2.Baby’s Height at Birth. 3.Number of meal per day. 4.Breast Milk. 5.Diarrhe times per 3 month. 6.Child development examination during covid by Health Worker at home. 7.Mother's age at birth. 8.Mother height at birth. 9.Number of sibling. 10.Age when the first food was given. This research has the disadvantage of no test on other datasets. So researchers do not know the reliability of findings is on different datasets

Rational tailoring of architectures and microenvironment on MOFs/natural clay hybrid materials for efficiently boosted performance of hybrid proton exchange membranes

AbstractMetal–organic frameworks (MOFs) is now becoming the most fascinating conductive materials due to designable structure and pores at molecular level, and available crystal structure for the study of conduction mechanism. Nevertheless, comparing to the design of molecular structures of MOFs, the hybrid of MOFs with special micro/nano‐structured materials is considered to be a more effective approach for improved properties. In this study, the PAT@UiO‐66‐SO3H hybrid material was constructed with high conductive UiO‐66‐SO3H, a famous kind of MOFs, and polydopamine‐coated natural clay attapulgite (PAT), then the prepared hybrid material was blended with chitosan (CS) to prepare proton exchange membranes (PEMs). Owing to the special architectures and microenvironment, combining with the advantages of composition with UiO‐66‐SO3H and attapulgite, the prepared composite membranes showed considerable improved performances, including tensile strength, thermal and structural stability, fuel resistance ability, conduction and single cell performances. The CS/PAT@UiO‐66‐SO3H‐5 composite membrane exhibited the highly enhanced tensile strength of 67 MPa and improved thermal stability with Tg value of 235°C, as well as the lowest methanol crossover value of 1.2 × 10−6 cm2 s−1. Besides, the highest proton conductivity of 38.8 mS cm−1 at 80°C and power density of 37.9 mWcm−2 was achieved with CS/PAT@UiO‐66‐SO3H‐3 composite membrane, these performances were higher than pristine CS of 22.7 mS cm−1 and 32.2 mW cm−2 respectively. Our investigation reveals great application potential of MOFs based hybrid materials in fabricating of high performance composite PEMs.Highlights PAT@UiO‐66‐SO3H hybrid materials were constructed from MOFs and natural clay. The hybrid materials possessed special architectures and microenvironment. The PAT@UiO‐66‐SO3H introduced consecutive channels and proton sites. The hybrid membranes achieved excellent performances.

Polyphenol synergistic cerium oxide surface engineering constructed core-shell nanostructures as antioxidants for durable and high-performance proton exchange membrane fuel cells

The chemical degradation of proton exchange membranes (PEMs) suffering from radical attack is a crucial issue in the development of proton exchange membrane fuel cells (PEMFCs), while incorporating cerium oxide (CeO2) nanoparticles (NPs) with regenerative redox properties to eliminate radicals could effectively alleviate degradation. However, the low stability and restricted activity of CeO2 in the PEMFC operating condition and the poor compatibility with PEM due to CeO2 agglomeration stimulate the urgency for structural modulation of CeO2. Achieving a balance of membrane performance and oxidation resistance through a rational surface modification strategy of CeO2 is important for expanding PEMFC applications. Herein, polyphenols surface functionalized CeO2 core-shell structure (CeO2@TP) were constructed via assembling oxidation-induced coupling tea polyphenols (TP) on CeO2 NPs. The TP oligomeric shell as a protective layer enhances the stability of CeO2, mitigating radical scavenging activity degradation and improving compatibility with PEMs. Physicochemical characterisation shows that the overall performance of the nanocomposite membrane is improved due to the interaction of CeO2@TP nanoparticles with the polymer matrix. Gratifyingly, the phenolic hydroxyl-rich reductive TP oligomeric shell accelerates the regeneration of Ce(IV) to Ce(III), increasing the proportion of Ce(III) and oxygen vacancies on the CeO2 surface, thus boosting antioxidation efficiency. As a result, the CeO2@TP-based PEMs exhibited an OCV decay rate of 0.22 mV h−1, a maximum power density of 1.06 W cm−2, an H2 crossover value of 2.18 mA cm−2, thickness retention (91.1%), and negligible Ce migration after 404 h of accelerated degradation testing. It is proven that the desired consequences of doping antioxidants in PFSA matrix can be intensified by surface modulation of the physicochemical properties of CeO2.

Runtime Analysis for the NSGA-II: Provable Speed-Ups from Crossover

Very recently, the first mathematical runtime analyses for the NSGA-II, the most common multi-objective evolutionary algorithm, have been conducted. Continuing this research direction, we prove that the NSGA-II optimizes the OneJumpZeroJump benchmark asymptotically faster when crossover is employed. Together with a parallel independent work by Dang, Opris, Salehi, and Sudholt, this is the first time such an advantage of crossover is proven for the NSGA-II. Our arguments can be transferred to single-objective optimization. They then prove that crossover can speed up the (mu+1) genetic algorithm in a different way and more pronounced than known before. Our experiments confirm the added value of crossover and show that the observed advantages are even larger than what our proofs can guarantee.

SOLUTION APPROACH TO P-MEDIAN FACILITY LOCATION PROBLEM WITH INTEGRATED PROGRAMMING AND GENETIC ALGORITHM

In the study, the P-median problem that Hakimi brought to science was discussed. With this problem, in short, it is ensured that the locations for the supply of n demand points of p facilities with the lowest cost are determined and the demand points to be served are allocated to these locations. The solution of the p-median problem with the integer programming approach is in the NP (Non-Polynominal) difficult class, and the solution time increases exponentially as the size of the problem increases. For this, the use of heuristic approaches in the P-median problem significantly shortens the solution time of large-sized problems. The data used in the application were taken from the Operation Research-Library site. In practice, the P-median is considered as capacity-constrained and unconstrained. Euclidean distances were calculated in Excel. The solution of mixed integer programming is obtained by using the CPLEX program. In addition to mixed integer programming, genetic algorithm, which is a meta-heuristic method, is applied to the capacity-constrained P-median problem. Different solutions were obtained by changing the population size, maximum number of iterations, crossover and mutation probability values. It has been observed that there is more than one optimum solution in repeated studies. When working with larger data sets, this algorithm will be less likely to find the global optimum. However, when compared to mixed integer programming, the genetic algorithm gave results very close to the optimum result. The use of heuristic algorithms in real-world complex problems will both shorten the solution time considerably compared to the integer programming method and provide results that are very close to the optimum result.

Special Section on 2D Materials for Electrochemical Energy Storage and Conversion

Electrochemical energy storage and conversion are currently one of the most critical challenges due to the increasing energy demand. Therefore, discovering novel materials to develop low-cost and more efficient energy storage technologies is urgently necessary. Among various novel materials, two-dimensional (2D) materials have attracted intensive research activities in multiple fields due to their fascinating physical and chemical properties. The 2D materials having a higher surface-to-volume ratio are beneficial to developing low-cost and large-scale energy storage systems for practical applications. There have been many promising concepts of 2D material-based real-life energy applications recently in batteries, supercapacitors, fuel cells, solar cells, thermoelectric, triboelectric generators, etc. Despite recent progress, significant efforts are still needed to investigate the fundamentals of 2D materials for electrochemical energy storage and conversion. Over the past few years, there has been substantial progress in modeling, theories, and experimental characterizations of 2D materials for energy storage and conversion. This timely Special Section issue addressed some recent advances in this critical area. We have selected eight papers covering a gamut of electrochemical-centric research in 2D materials for energy storage and conversion.In this issue, Qu et al. reported the electrochemical evaluation of helical carbon nanofibers (HCNFs) prepared by the ethanol flame method as anode materials of lithium-ion batteries. Their results show that HCNFs possess high reversible capacity, good rate performance, and excellent cycling stability. Farma et al. investigated a simple and cost-effective method to generate porous carbon activation from Palmae plant waste biomass, namely, areca leaf midrib (ALM). They showed that the electrochemical properties of activated carbon supercapacitor cells derived from ALM biomass have the highest specific capacitance value and scan rate in a two-electrode system. Arumugam et al. discussed a ternary composite made up of graphene oxide, polyaniline, and zinc oxide as an electrode material for supercapacitors with its structural and electrochemical properties. The ternary composite exhibited the highest specific capacitance. Metzger et al. focused on using graphene-coated proton exchange membrane (PEM) to reduce fuel crossover. They found that the adhesion of graphene on PEMs is insufficient for prolonging fuel cell operation, resulting in graphene delamination at high temperatures and higher fuel crossover values compared to lower temperature testing. Zaidi et al. reported the superior performance of graphene nanosheet (GNS) materials over Vulcan XC incorporated as a cathode catalyst in Li-O2 battery. The GNS catalysts demonstrated promising performance at higher current densities and with various organic electrolytes. Pandey et al. synthesized a mechanically stable, proton-conducting, and very cost-effective nanocomposite membrane using a simple and scalable phase-inversion approach. The synthesized proton-conducting nanocomposite membrane was demonstrated as a potential advanced functional solid electrolyte for possible application in proton exchange membrane fuel cells. Fauzi et al. reported the thermophysical properties of N,N-diethylethanolammonium chloride/ethylene glycol-DES (deep eutectic solvent) for the replacement of ionic liquid. They studied the physical properties of DES, which are thermal conductivity, viscosity, and surface tension. Finally, the review article by Zeng et al. provided an overview of the application of conductive diamond in electrocatalytic reduction and outlined the improvement of electrochemical properties by employing metal particles to modify the surface.We believe that this Special Section issue will be a valuable contribution to the energy storage and conversion literature and open new frontiers for researchers. The interdisciplinary field of 2D material-based energy storage is rapidly evolving. Our Special Section issue will motivate many researchers to implement novel techniques, such as artificial intelligence, digital twins, and automated advanced manufacturing, in this field and initiate new collaborations between experimentalists, theorists, and modelers. We would like to thank all contributors to this Special Section issue for submitting their latest high-impact work. Also, special thanks would go out to the invited reviewers for helping us further enhance the quality of the articles.

Electronic states of a disordered two-dimensional quasiperiodic tiling: From critical states to Anderson localization

We consider critical eigenstates in a two dimensional quasicrystal and their evolution as a function of disorder. By exact diagonalization of finite size systems we show that the evolution of properties of a typical wave-function is non-monotonic. That is, disorder leads to states delocalizing, until a certain crossover disorder strength is attained, after which they start to localize. Although this non-monotonic behavior is only present in finite-size systems and vanishes in the thermodynamic limit, the crossover disorder strength decreases logarithmically slowly with system size, and is quite large even for very large approximants. The non-monotonic evolution of spatial properties of eigenstates can be observed in the anomalous dimensions of the wave-function amplitudes, in their multifractal spectra, and in their dynamical properties. We compute the two-point correlation functions of wave-function amplitudes and show that these follow power laws in distance and energy, consistent with the idea that wave-functions retain their multifractal structure on a scale which depends on disorder strength. Dynamical properties are studied as a function of disorder. We find that the diffusion exponents do not reflect the non-monotonic wave-function evolution. Instead, they are essentially independent of disorder until disorder increases beyond the crossover value, after which they decrease rapidly, until the strong localization regime is reached. The differences between our results and earlier studies on geometrically disordered ``phason-flip'' models lead us to propose that the two models are in different universality classes. We conclude by discussing some implications of our results for transport and a proposal for a Mott hopping mechanism between power law localized wave-functions, in moderately disordered quasicrystals.

Analysis Of The Sirs Model Of The Spread Of Dengue Hemorrhagic Fever Using Runge-Kutta Method And Genetic Algorithm

Dengue Hemorrhagic Fever is a contagious disease that often occurs in Indonesia. Dengue Hemorrhagic Fever, caused by the Dengue Virus, has four serotypes : DEN-1, DEN-2, DEN-3 and DEN-4. Someone can be infected four times, once for each serotype. After recovering from one serotype, a person gets a lifetime of immunity against that serotype. In this paper a model will be created for modeling the spread of Dengue Hemorrhagic Fever with assumption there are only two serotypes, namely DEN-1 and DEN-2. Model formed based on SIR Model (Susceptible, Infected, Recovered) and SIRS Model (Susceptible, Infected, Recovered, Susceptible). The changes in populations over time are written into a system of differential equations. The system of differential equations is then used to do an equilibrium point analysis. The numerical solution for the system of differential equations can be found using the Runge-Kutta Method. Genetic Algorithm are used to find the values of parameters in the model that are unknown. A series of simulations are performed to get the combination that produces the Genetic Algorithm system that will produce the best approximation solution. The combination includes population size, selection value, crossover value and mutation value. This best combination then will produce an approximation solution with the smallest error.

Experimental Studies of Graphene-Coated Polymer Electrolyte Membranes for Direct Methanol Fuel Cells

Abstract The two main technical limitations of direct methanol fuel cells (DMFCs) are the slow kinetic reactions of the methanol oxidation reaction (MOR) in the anode and the crossing over of unreacted methanol through the proton exchange membrane (PEM). It is a common practice to use Nafion membranes as PEMs, which have high ion exchange capacity. However, Nafion-based membranes also have high fuel permeability, decreasing fuel utilization, and reducing the potential power density. This article focuses on using graphene-coated (Gr-coated) PEMs to reduce fuel crossover. Protons can permeate across graphene, and thus, it can be employed in various devices as a proton conductive membrane. Here, we report the efficiency of Gr-coated Nafions. We tested performance and crossover at three different temperatures with four different fuel concentrations and compared it to a Nafion PEM that underwent the same test conditions. We found that the adhesion of Gr on to PEMs is insufficient for prolonging fuel cell operation, resulting in Gr delamination at high temperatures and higher fuel crossover values compared to lower temperature testing. The results for 7.5M methanol fuel show a reduction of up to 25% in methanol crossover, translating to a peak power density that increases from 3.9 to 9.5 mW/cm2 when using a Gr-coated PEM compared to a Nafion PEM at 30 °C.

Sharp hierarchical upper bounds on the critical two-point function for long-range percolation on Zd

Consider long-range Bernoulli percolation on Zd in which we connect each pair of distinct points x and y by an edge with probability 1 − exp(−β‖x − y‖−d−α), where α > 0 is fixed and β ⩾ 0 is a parameter. We prove that if 0 < α < d, then the critical two-point function satisfies 1|Λr|∑x∈ΛrPβc(0↔x)⪯r−d+α for every r ⩾ 1, where Λr=[−r,r]d∩Zd. In other words, the critical two-point function on Zd is always bounded above on average by the critical two-point function on the hierarchical lattice. This upper bound is believed to be sharp for values of α strictly below the crossover value αc(d), where the values of several critical exponents for long-range percolation on Zd and the hierarchical lattice are believed to be equal.

A dynamic approach for parameter tuning in genetic algorithm using crossover and mutation ratios

Genetic algorithm uses the natural selection process for any search process. It is an optimization process where integration among different vital parameters like crossover and mutation plays a major role. The parameters have an impact on the algorithm by their probabilities. In this paper we would review the different strategies used for the selection of crossover and mutation ratios and suggest a dynamic approach for modifying the ratios during runtime. We start with a mutation ratio 0% and crossover ratio 100% where the mutation ratio slowly increases and the crossover ratio decreases (MICD). The final mutation ratio will be 0% and crossover ratio will be 100% at the end of the search process. We also do the reverse process of considering the mutation ratio to be maximum and crossover ratio to be minimum and slowly decrease the mutation ratio and increase the crossover ratio (MDCI). We compare the proposed method with two pre-existing parameter tuning methods and found that this dynamic approach of incrementing the mutation and decrementing the crossover value was more effective when the size of the population was large.

Cardo Polybenzimidazole (PBI-O-PhT) Based Membrane Reinforced with m-polybenzimidazole Electrospun Nanofiber Mat for HT-PEM Fuel Cell Applications.

The further development of high temperature polymer electrolyte membrane (HT-PEM) fuel cells largely depends on the improvement of all components of the membrane–electrode assembly (MEA), especially membranes and electrodes. To improve the membrane characteristics, the cardo-polybenzimidazole (PBI-O-PhT)-based polymer electrolyte complex doped with phosphoric acid is reinforced using an electrospun m-PBI mat. As a result, the PBI-O-PhT/es-m-PBInet · nH3PO4 reinforced membrane is obtained with hydrogen crossover values (~0.2 mA cm−2 atm−1), one order of magnitude lower than the one of the initial PBI-O-PhT membrane (~3 mA cm−2 atm−1) during HT-PEM fuel cell operation with Celtec®P1000 electrodes at 180 °C. Just as importantly, the reinforced membrane resistance was very close to the original one (65–75 mΩ cm2 compared to ~60 mΩ cm2). A stress test that consisted of 20 start–stops, which included cooling to the room temperature and heating back to 180 °C, was applied to the MEAs with the reinforced membrane. More stable operation for the HT-PEM fuel cell was shown when the Celtec®P1000 cathode (based on carbon black) was replaced with the carbon nanofiber cathode (based on the pyrolyzed polyacrylonitrile electrospun nanofiber mat). The obtained data confirm the enhanced characteristics of the PBI-O-PhT/es-m-PBInet · nH3PO4 reinforced membrane.

Phase Growth with Heat Diffusion in a Stochastic Lattice Model

When a stable phase is adjacent to a metastable phase with a planar interface, the stable phase grows. We propose a stochastic lattice model describing the phase growth accompanying heat diffusion. The model is based on an energy-conserving Potts model with a kinetic energy term defined on a two-dimensional lattice, where each site is sparse-randomly connected in one direction and local in the other direction. For this model, we calculate the stable and metastable phases exactly using statistical mechanics. Performing numerical simulations, we measure the displacement of the interface R(t). We observe the scaling relation \(R(t)=L_x \bar{\mathcal {R}} (Dt/L_x^2)\), where D is the thermal diffusion constant and \(L_x\) is the system size between the two heat baths. The scaling function \(\bar{\mathcal {R}}(z)\) shows \(\bar{\mathcal {R}}(z) \simeq z^{0.5}\) for \(z \ll z_c\) and \(\bar{\mathcal {R}}(z) \simeq z^{\alpha }\) for \(z \gg z_c\), where the cross-over value \(z_c\) and exponent \(\alpha \) depend on the temperatures of the baths, and \(0.5\le \alpha \le 1\). We then confirm that a deterministic phase-field model exhibits the same scaling relation. Moreover, numerical simulations of the phase-field model show that the cross-over value \(\bar{\mathcal {R}}(z_c)\) approaches zero when the stable phase becomes neutral.

Crossover From Individual to Collective Magnetism in Dense Nanoparticle Systems: Local Anisotropy Versus Dipolar Interactions.

Dense systems of magnetic nanoparticles may exhibit dipolar collective behavior. However, two fundamental questions remain unsolved: i) whether the transition temperature may be affected by the particle anisotropy or it is essentially determined by the intensity of the interparticle dipolar interactions, and ii) what is the minimum ratio of dipole-dipole interaction (Edd ) to nanoparticle anisotropy (Kef V, anisotropy⋅volume) energies necessary to crossover from individual to collective behavior. A series of particle assemblies with similarly intense dipolar interactions but widely varying anisotropy is studied. TheKef is tuned through different degrees of cobalt-doping in maghemite nanoparticles, resulting in a variation of nearly an order of magnitude. All the bare particle compacts display collective behavior, except the one made with the highest anisotropy particles, which presents "marginal" features. Thus, a threshold of Kef V/Edd ≈ 130 to suppress collective behavior is derived, in good agreement with Monte Carlo simulations. This translates into a crossover value of ≈1.7 for the easily accessible parameter TMAX (interacting)/TMAX (non-interacting) (ratio of the peak temperatures of the zero-field-cooled magnetization curves of interacting and dilute particle systems), which is successfully tested against the literature to predict the individual-like/collective behavior of any given interacting particle assembly comprising relatively uniform particles.

SOL width broadening by spreading of pedestal turbulence

The pedestal turbulence intensity required to convert the thin, laminar H-mode scrape-off layer (SOL) to a broad turbulent SOL is calculated using the theory of turbulence spreading. A lower bound on the pedestal turbulence level to exceed the neoclassical heuristic drift (HD) width is derived. A reduced model of SOL turbulence spreading is used to determine the SOL width as a function of intensity flux from the pedestal to the SOL. The cross-over value for exceeding the HD model width is then calculated. We determine the pedestal turbulence levels—and the critical scalings thereof—required to achieve this level of broadening. Both drift wave and ballooning mode turbulence are considered. A sensitivity analysis reveals that the key competition is that between spreading and linear E × B shear damping. The required pedestal turbulence levels scale with ρ/R.

Anxiety surrounding supracondylar humerus pin removal in children.

Purpose:The purpose of this study was to quantify the anxiety experienced by patients undergoing pin removal in clinic following closed reduction and percutaneous pinning for supracondylar humerus fractures.Methods:We prospectively enrolled 53 patients (3–8 years) treated for supracondylar humerus fracture with closed reduction and percutaneous pinning between July 2018 and February 2020. Demographic and injury data were recorded. Heart rate and the Face, Legs, Activity, Cry, and Consolability scale were measured immediately before pin removal and after pin removal, and crossover control values were obtained at the subsequent follow-up clinic visit.Results:All patients experienced anxiety immediately prior to pin removal (95% confidence interval, 94%–100%) with a median Face, Legs, Activity, Cry, and Consolability score of 7 (interquartile range, 6–8). In addition, 98% of subjects experienced an elevated heart rate (95% confidence interval, 88%–100%). Patients experienced a median 73% reduction in Face, Legs, Activity, Cry, and Consolability score and mean 21% reduction in heart rate from prior to pin removal to after pin removal (p < 0.001). All 45 patients who completed their follow-up visit had a control Face, Legs, Activity, Cry, and Consolability score of 0 and a mean control heart rate of 89.7 bpm. Twenty-five of these 45 subjects (56%) had an elevated control heart rate for their age and sex. Mean heart rate prior to pin removal was 36% higher than control heart rate. There were no sex differences detected in Face, Legs, Activity, Cry, and Consolability scores or heart rate.Conclusions:Pediatric patients experience high levels of anxiety when undergoing pin removal following closed reduction and percutaneous pinning for supracondylar humerus fractures. This is an area of clinical practice where intervention may be warranted to decrease patient anxiety.Level of evidence:II