Compressing Two-Dimensional Routing Tables

We consider an algorithmic problem that arises in the context of routing tables used by Internet routers. The Internet addressing scheme is hierarchical, where a group of hosts are identified by a prefix that is common to all the hosts in that group. Each host machine has a unique 32-bit address. Thus, all traffic between a source group s and a destination group d can be routed along a particular route c by maintaining a routing entry (s, d, c) at all intermediate routers, where s and d are binary bit strings. Many different routing tables can achieve the same routing behavior. In this paper we show how to compute the most compact routing table. In particular, we consider the following optimization problem: given a routing table D with N entries of the form (s, d, c) , determine a conflict-free routing table with fewest entries that has the same routing behavior as D. If the source and destination fields have up to w bits, and there are at most K different route values, then our algorithm runs in worst-case time O( NK w2) .     

A multiobjective thermodynamic optimization of a nanoscale Stirling engine operated with Maxwell‐Boltzmann gas

Recent developments in nanotechnology provided an opportunity to solve many complex problems in the field of energy. Performance investigation of the nanoscale thermal cycles can prove crucial in the development of efficient and less polluting energy system. Due to the influence of boundary phenomenon and quantum degeneracy effects, a nanoscale engine performs according to statistical quantum thermodynamics instead of classical thermodynamics. In this study, a nanoscale Stirling engine operating on an ideal Maxwell‐Boltzmann gas is investigated for multiobjective optimization. Optimization problem of Stirling cycle is formed considering the thermal efficiency, ecological coefficient of performance and entropy generation. An application example of a nanoscale Stirling engine is presented and solved using Heat Transfer Search algorithm. Maxwell‐Boltzmann gas restricted in a finite domain is studied and the effect of different parameters, such as surface area ratio, volume ratio, and temperature ratio of the domain, is investigated. Sensitivity analysis is carried out to identify the effect of design variables on the performance parameters. Further, influence of the source temperature and the number of particles of working fluid on the objective functions is studied and presented.     

A three-dimensional micromechanical model to predict the viscoelastic behavior of woven composites

Polymer matrix based cloth composites are increasingly used in engineering applications. For such composites, significant viscoelastic behavior can be observed for dynamic load conditions. The viscoelastic effect is primarily due to the polymeric matrix used as most of the fibers used in structural applications are elastic. Matrix does not show a major contribution in the axial properties of composites, thus in the traditional modeling its viscoelastic nature is often ignored. However, the effective out of plane properties are influenced by the matrix material and exhibit significant damping characteristics. Therefore, a complete three-dimensional (3-D) model considering the viscoelastic nature of matrix is needed for better understanding of cloth composites. An analytical 3-D micromechanical model based on classical laminate theory (CLT) is verified, in this paper for the prediction of effective elastic and viscoelastic properties of a cloth composite. The method is shown to be accurate. This model is extended to the viscoelastic regime with the use of Laplace transform and correspondence principle. Prony series coefficients for composite cloth are obtained for different volume fractions of fibers in yarn. It is observed from the hysteresis plots that dissipation in out of plane normal and shear modes is significantly higher than the normal directions.     

Speaking their Mind: Populist Style and Antagonistic Messaging in the Tweets of Donald Trump,Narendra Modi,Nigel Farage,and Geert Wilders

The authors in this study examined the function and public reception of critical tweeting in online campaigns of four nationalist populist politicians during major national election campaigns. Using a mix of qualitative coding and case study inductive methods, we analyzed the tweets of Narendra Modi, Nigel Farage, Donald Trump, and Geert Wilders before the 2014 Indian general elections, the 2016 UK Brexit referendum, the 2016 US presidential election, and the 2017 Dutch general election, respectively. Our data show that Trump is a consistent outlier in terms of using critical language on Twitter when compared to Wilders, Farage, and Modi, but that all four leaders show significant investment in various forms of antagonistic messaging including personal insults, sarcasm, and labeling, and that these are rewarded online by higher retweet rates. Building on the work of Murray Edelman and his notion of a political spectacle, we examined Twitter as a performative space for critical rhetoric within the frame of nationalist politics. We found that cultural and political differences among the four settings also impact how each politician employs these tactics. Our work proposes that studies of social media spaces need to bring normative questions into traditional notions of collaboration. As we show here, political actors may benefit from in-group coalescence around antagonistic messaging, which while serving as a call to arms for online collaboration for those ideologically aligned, may on a societal level lead to greater polarization.     

Electrical Conductivity of Multicomponent Systems During Ohmic Heating

During ohmic heating, the heating rate of a product depends on its electrical conductivity, a temperature dependent property. The electrical conductivity of the individual components in a multicomponent food system was determined over the entire sterilization temperature range (25?140°C). The product selected was chicken chowmein, composed of chicken, celery, mushrooms, water chestnuts, bean sprouts, and chowmein-style sauce. A device was developed to measure electrical conductivities of the components over the required temperature range. Results showed that the sauce (2.1 S/m at 27°C to 10.8 S/m at 140°C) was much more conductive than the solid components, i.e., celery (0.1 S/m to 3.4 S/m), water chestnut (0.1 S/m to 2.8 S/m), mushrooms (0.2 S/m to 1.4 S/m), bean sprouts (0.2 S/m to 1.5 S/m) and chicken (0.6 S/m to 3.4 S/m). Variation in electrical conductivity was also observed between different samples of the same component.     

Sandpiper optimization algorithm with cosine similarity based cross-layer routing protocol for smart agriculture in wireless sensor network assisted internet of things systems

The Internet of Things (IoT) has recently attained a prominent role in enabling smooth and effective communication among various networks. Wireless sensor network (WSN) is utilized in IoT to collect peculiar data without interacting with humans in specific applications. Energy is a major problem in WSN-assisted IoT applications, even though better data communication is achieved through cross-layer models. This paper proposes a new cross-layer-based clustering and routing model to provide a scalable and energy-efficient long data communication in WSN-assisted IoT systems for smart agriculture. Initially, the fuzzy k-medoids clustering approach is used to split the network into various clusters since the formation of clusters plays an important role in energy consumption. Then, a new swarm optimization known as enhanced sparrow search algorithm (ESSA), which is the combination of SSA and chameleon swarm algorithm (CSA), has been introduced for optimal cluster head (CH) selection to solve the energy-hole problems in WSN. A cross-layer strategy has been preferred to provide efficient data transmission. Each sensor node parameter of the physical layer, network layer and medium access control (MAC) is considered for processing routing. Finally, a new bio-inspired algorithm is known as the sandpiper optimization algorithm (SOA), and cosine similarity (CS) has been employed to determine the optimal route for efficient data transmission and retransmission. The simulation of the proposed protocol is implemented by network simulator (NS2), and the simulation results are taken in terms of end-to-end delay, PDR, communication overhead, communication cost, average consumed energy, and network lifetime.     

Differentiating the Impacts of Cu2O Initial Low- and High-Index Facets on Their Reconstruction and Catalytic Performance in Electrochemical CO2 Reduction Reaction

Oxide-derived Cu catalysts from Cu₂O microcrystals are capable of electrochemically converting CO₂ into various value-added chemicals. However, their structural transformation and associated preferred products remain unclear, requiring further investigation. Herein, Cu₂O microcrystals with controllable low- and high-index facets exposure are fabricated to differentiate the effects of initial exposed facets on their structural reconstruction and product selectivity in electrochemical CO₂ reduction reaction. Combined in situ characterizations and theoretical investigation reveal the direct correlations of Cu₂O reconstruction and product selectivity to its initial facet exposure. The Cu₂O low-index facet, being more stable with a high energy barrier on material reduction, tends to partially maintain its original crystalline structure and larger Cu₂O particle size throughout the transformation. The derived flatter surface and limited Cu₂O/Cu interfaces result in a favorable selectivity toward 2-electron transfer products. The chemically active Cu₂O high-index facet (311) is energetically favorable to be reduced owing to the feasible protonation process, thus experiencing a drastic reconstruction with rich newly formed Cu nanoparticles and evolved fine Cu₂O grains; Such a reconstruction creates uncoordinated Cu species and abundant boundaries, benefiting charge transfer and increasing the local pH by confining OH⁻, thus leading to a high selectivity toward C₂₊ products.     

Enhanced Electrochemical CO2 Reduction of Cu@CuxO Nanoparticles Decorated on 3D Vertical Graphene with Intrinsic sp3‐type Defect

Defective 3D vertical graphene (VG) with a relatively large surface area, high defect density, and increased surface electrons is synthesized via a scalable plasma enhanced chemical vapor deposition method, together with a postsynthesis Ar‐plasma treatment (VG‐Ar). Subsequently, Cu@Cu_xO nanoparticles are deposited onto VG‐Ar (Cu/VG‐Ar) through a galvanostatic pulsed electrodeposition method. These Cu@Cu_xO nanocatalyst systems exhibit a superior electrochemical CO₂ reduction performance when compared to Cu‐based catalysts supported on commercial graphene paper or pristine VG without postsynthesis Ar‐plasma treatment. The Cu/VG‐Ar achieves the highest CO₂ reduction Faradaic efficiency of 60.6% (83.5% of which are attributed to liquid products, i.e., formate, ethanol, and n‐propanol) with a 5.6 mA cm^?2 partial current density at ?1.2 V versus reversible hydrogen electrode (RHE). The improved CO₂ reduction performance of Cu/VG‐Ar originates from the well‐dispersed Cu@Cu_xO nanoparticles deposited on the defective VG‐Ar. The intrinsic carbon defects on VG‐Ar can suppress the hydrogen evolution reaction as well as tune the interaction between VG and Cu@Cu_xO, thus impeding the excessive oxidation of Cu₂O species deposited on VG‐Ar. The defective VG‐Ar and stabilized Cu@Cu_xO enhances CO₂ adsorption and promotes electron transfer to the adsorbed CO₂ and intermediates on the catalyst surface, thus improving the overall CO₂ reduction performance.     

Liquid-Metal-Templated Synthesis of 2D Graphitic Materials at Room Temperature

Room-temperature synthesis of 2D graphitic materials (2D-GMs) remains an elusive aim, especially with electrochemical means. Here, it is shown that liquid metals render this possible as they offer catalytic activity and an ultrasmooth templating interface that promotes Frank–van der Merwe regime growth, while allowing facile exfoliation due to the absence of interfacial forces as a nonpolar liquid. The 2D-GMs are formed at low onset potential and can be in situ doped depending on the choice of organic precursors and the electrochemical set-up. The materials are tuned to exhibit porous or pinhole-free morphologies and are engineered for their degree of oxidation and number of layers. The proposed liquid-metal-based room-temperature electrochemical route can be expanded to many other 2D materials.     

Residence Time Distribution (RTD) of Particulate Foods in a Continuous Flow Pilot-Scale Ohmic Heater

ABSTRACT:  The residence time distribution (RTD) of a model particulate–fluid mixture (potato in starch solution) in the ohmic heater in a continuous sterilization process was measured using a radio frequency identification (RFID) methodology. The effect of solid concentration and the rotational speed of the agitators on the RTD were studied. The velocity of the fastest particle was 1.62 times the mean product velocity. In general, particle velocity was found to be greater than the product bulk average velocity. Mean particle residence time (MPRT) increased with an increase in the rotational speed of the agitators ( P  < 0.05), and no particular trend was observed between the MPRT and the solid concentration. The distribution curves  E  (θ) were skewed to the right suggesting slow moving zones in the system.