Examining the Causal Relationship between Screen Size and Cellular Data Consumption

This study utilizes a terabyte dataset from a telecommunications company to examine the relationship between screen size and cellular data consumption for a large number of phone and tablet users. We find the relationship exhibits a different pattern within the two device categories of phones and tablets. For phone users, there is an overall positive and significant relationship over the range of screen size from 1 inch to below 7 inches, which is, however, mainly driven by the dramatic decrease in usage on traditional phones with screens less than 3 inches. Particularly for smartphones with screens 3.5 inches or higher, we do not find a significant relationship between screen size and cellular data consumption measured by either the time spent on the mobile network or the amount of data transmitted. For tablet users, we find evidence that suggests that people spend less time on tablets with bigger screens, which could potentially be due to the reduced portability of large tablets. Our findings can provide important implications for mobile network operators in promoting data plans to users with different devices

Practical Stabilization of Uncertain Nonholonomic Mobile Robots Based on Visual Servoing Model with Uncalibrated Camera Parameters

The practical stabilization problem is addressed for a class of uncertain nonholonomic mobile robots with uncalibrated visual parameters. Based on the visual servoing kinematic model, a new switching controller is presented in the presence of parametric uncertainties associated with the camera system. In comparison with existing methods, the new design method is directly used to control the original system without any state or input transformation, which is effective to avoid singularity. Under the proposed control law, it is rigorously proved that all the states of closed-loop system can be stabilized to a prescribed arbitrarily small neighborhood of the zero equilibrium point. Furthermore, this switching control technique can be applied to solve the practical stabilization problem of a kind of mobile robots with uncertain parameters (and angle measurement disturbance) which appeared in some literatures such as Morin et al. (1998), Hespanha et al. (1999), Jiang (2000), and Hong et al. (2005). Finally, the simulation results show the effectiveness of the proposed controller design approach

Utilizing Geospatial Information in Cellular Data Usage for Key Location Prediction

Previous research on the identification of key locations (e.g., home and workplace) for a user largely relies on call detail records (CDRs). Recently, cellular data usage (i.e., mobile internet) is growing rapidly and offers fine-grained insights into various human behavior patterns. In this study, we introduce a novel dataset containing both voice and mobile data usage records of mobile users. We then construct a new feature based on the geospatial distribution of cell towers connected by mobile users and employ bivariate kernel density estimation to help predict users’ key locations. The evaluation results suggest that augmented features based on both voice and mobile data usage improve the prediction precision and recall

Nonlinear Model and Qualitative Analysis for Coupled Axial/Torsional Vibrations of Drill String

A nonlinear dynamics model and qualitative analysis are presented to study the key effective factors for coupled axial/torsional vibrations of a drill string, which is described as a simplified, equivalent, flexible shell under axial rotation. Here, after dimensionless processing, the mathematical models are obtained accounting for the coupling of axial and torsional vibrations using the nonlinear dynamics qualitative method, in which excitation loads and boundary conditions of the drill string are simplified to a rotating, flexible shell. The analysis of dynamics responses is performed by means of the Runge-Kutta-Fehlberg method, in which the rules that govern the changing of the torsional and axial excitation are revealed, and suggestions for engineering applications are also given. The simulation analysis shows that when the drill string is in a lower-speed rotation zone, the torsional excitation is the key factor in the coupling vibration, and increasing the torsional stress of the drill string more easily leads to the coupling vibration; however, when the drill string is in a higher-speed rotating zone, the axial excitation is a key factor in the coupling vibration, and the axial stress in a particular interval more easily leads to the coupling vibration of the drill string

Rational design and characterization of nitric oxide biosensors in E. coli Nissle 1917 and Mini SimCells

Nitric oxide (NO) is an important disease biomarker found in many chronic inflammatory diseases and cancers. A well-characterized nitric sensing system is useful to aid the rapid development of bacteria therapy and synthetic biology. In this work, we engineered a set of NO-responsive biosensors based on the PnorV promoter and its NorR regulator in the norRVW operon; the circuits were characterized and optimized in probiotic Escherichia coli Nissle 1917 and mini SimCells (minicells containing designed gene circuits for specific tasks). Interestingly, the expression level of NorR displayed an inverse correlation to the PnorV promoter activation, as a strong expression of the NorR regulator resulted in a low amplitude of NO-inducible gene expression. This could be explained by a competitive binding mechanism where the activated and inactivated NorR competitively bind to the same site on the PnorV promoter. To overcome such issues, the NO induction performance was further improved by making a positive feedback loop that fine-tuned the level of NorR. In addition, by examining two integration host factor (IHF) binding sites of the PnorV promoter, we demonstrated that the deletion of the second IHF site increased the maximum signal output by 25% (500 μM DETA/NO) with no notable increase in the basal expression level. The optimized NO-sensing gene circuit in anucleate mini SimCells exhibited increased robustness against external fluctuation in medium composition. The NO detection limit of the optimized gene circuit pPnorVβ was also improved from 25.6 to 1.3 nM in mini SimCells. Moreover, lyophilized mini SimCells can maintain function for over 2 months. Hence, SimCell-based NO biosensors could be used as safe sensor chassis for synthetic biology

Single crystalline beta-SiAlON nanowhiskers: preparation and enhanced properties at high temperature

Single crystalline β-SiAlON (z = 1.0) nanowhiskers with uniform morphology were prepared using a reaction sintering method at 1773 K for 6 h under flowing nitrogen atmosphere. The as-synthesized whiskers were well-crystallized with about 100-200 nm in diameter and a few hundred microns in length. According to the thermodynamic calculation, Al(g) and SiO(g) are important intermediate reactants to synthesize β-SiAlON whiskers. In the experiment, the two phases was controlled by changing the flow rate of nitrogen to make β-SiAlON whiskers grow in a stable way. The formation of β-SiAlON whiskers occurred through a vapor-solid (VS) mechanism. SiAlON was found to grow as a single crystal whisker from the (1010) plane of the granule. Furthermore, an enhanced oxidation resistance for β-SiAlON whiskers at high temperature was also observed using the thermogravimetry method (TG), demonstrating that β-SiAlON whiskers with uniform morphology is a promising candidate as a reinforcing agent in composite

Strong Precipitation Suppression by Aerosols in Marine Low Clouds

The adjustment of cloud amount to aerosol effects occurs to a large extent in response to the aerosol effect on precipitation. Here the marine boundary layer clouds were studied by analyzing the dependence of rain intensity measured by Global Precipitation Measurement on cloud properties. We showed that detectable rain initiates when the drop effective radius at the cloud top (re) exceeds 14 μm, and precipitation is strongly suppressed with increasing cloud drop concentration (Nd), which contributes to the strong dependence of cloud amount on aerosols. The rain rate increases sharply with cloud thickness (CGT) and re when re > 14 μm. The dependence of rain rate on re and CGT presents a simple framework for precipitation susceptibility to aerosols, which explains other previously observed relationships. We showed that sorting data by CGT and using alternative cloud condensation nuclei proxy rather than aerosol optical depth are critical for studying aerosol‐cloud‐precipitation interactions.Plain Language SummaryAerosol‐cloud interaction remains the greatest uncertainty in future climate projection. Precipitation is a key process that mediates how the cloud amount responds to aerosol perturbations. Here we combined precipitation measured by the radar onboard the satellite of Global Precipitation Measurement (GPM) and cloud properties retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Aqua satellite for studying the dependence of rain intensity on cloud properties for marine boundary layer water clouds over the Southern Hemisphere Ocean. Our results showed that rain is sharply intensified when droplets at the cloud top grow larger than 14 μm, and precipitation decreases with increasing cloud drop number concentration (Nd). A simple framework to explain the relationship between precipitation and aerosols is proposed here by showing the dependence of precipitation on Nd and cloud geometric thickness. We also discussed why using aerosol optical depth (AOD) as CCN proxy in previous studies could lead to great uncertainties and why sorting cloud geometrical thickness is necessary.Key PointsPrecipitation is strongly suppressed with increasing cloud drop concentrationSorting data by cloud thickness and using alternative CCN proxy rather than AOD are critical for studying aerosol‐cloud interactionsDetectable rain initiates when the drop effective radius at the cloud top exceeds 14 μmPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154630/1/grl60407.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154630/2/grl60407_am.pd

Design of multifunctional color routers with Kerker switching using generative adversarial networks

To achieve optoelectronic devices with high resolution and efficiency, there is a pressing need for optical structural units that possess an ultrasmall footprint yet exhibit strong controllability in both the frequency and spatial domains. For dielectric nanoparticles, the overlap of electric and magnetic dipole moments can scatter light completely forward or backward, which is called Kerker theory. This effect can expand to any multipoles and any directions, re-named as generalized Kerker effect, and realize controllable light manipulation at full space and full spectrum using well-designed dielectric structures. However, the complex situations of multipole couplings make it difficult to achieve structural design. Here, generative artificial intelligence (AI) is utilized to facilitate multi-objective-oriented structural design, wherein we leverage the concept of "combined spectra" that consider both spectra and direction ratios as labels. The proposed generative adversarial network (GAN) is named as DDGAN (double-discriminator GAN) which discriminates both images and spectral labels. Using trained networks, we achieve the simultaneous design for scattering color and directivities, RGB color routers, as well as narrowband light routers. Notably, all generated structures possess a footprint less than 600x600 nm indicating their potential applications in optoelectronic devices with ultrahigh resolution