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● Gasification of cow dung was evaluated using Aspen Plus software.● Optimum reaction conditions were utilized to maximize hydrogen production.● Steam gasification can effectively increase hydrogen production.● Optimum hydrogen production was achieved at 800 °C and steam/biomass of 1.5 and 0.1 MPa. In this study, a biomass gasification model was developed and simulated based on Gibbs free energy minimization by using software Aspen Plus. Two reactors, RYIELD and RGIBBS, were moslty used. The biomass feedstock used was cow dung. The model was validated. The composition, H2/CO ratio and low heating value (LHV) of the resulting synthetic gas (also known as syngas) was estimated by changing the operating parameters of gasification temperatures, steam and biomass ratios and pressures. Simulation results showed that increased gasification temperature helped to elevate H2 and CO content and H2 peaked at 900 °C. When steam increased as the gasification agent, H2 production increased. However, the steam/biomass (S/B) ratio negatively affected CO and CH4, resulting in lower LHV. The optimal S/B ratio was 1.5. An increase in pressure lead to a decrease in H2 and CO content, so the optimal pressure for gasification was 0.1 MPa.

To achieve large-scale development of triboelectric nanogenerators (TENGs) for water wave energy harvesting and powering the colossal sensors widely distributed in the ocean, facile and scalable TENGs with high output are urgently required. Here, an elastic self-recovering hybrid nanogenerator (ES-HNG) is proposed for water wave energy harvesting and marine environmental monitoring. The elastic skeletal support of the ES-HNG is manufactured using three-dimensional (3D) printing technology, which is more conducive to the large-scale integration of the ES-HNG. Moreover, the combination of a TENG and an electromagnetic generator (EMG) optimizes the utilization of device space, leading to enhanced energy harvesting efficiency. Experimental results demonstrate that the TENG achieves a peak power output of 42.68 mW, and the EMG reaches a peak power output of 4.40 mW. Furthermore, various marine environment monitoring sensors, such as a self-powered wireless meteorological monitoring system, a wireless alarm system, and a water quality monitoring pen, have been successfully powered by the sophisticated ES-HNG. This work introduces an ES-HNG for water wave energy harvesting, which demonstrates potential in marine environment monitoring and offers a new solution for the sustainable development of the marine internet of things. [ABSTRACT FROM AUTHOR]

Escalating global climate change and the intensification of urban heatwaves have led to an increase in summer air conditioning cooling energy consumption. This phenomenon is particularly critical in tropical regions, as it may trigger an energy crisis. The rational setting of indoor thermal design parameters can help conserve energy to the maximum extent while ensuring thermal comfort for occupants. This study selected Haikou City, a unique tropical city in China, as the research location. Indoor environment measurements and a questionnaire survey were conducted with participants, and the outdoor thermal environment sensitivity, population attributes and differences in thermal sensation, thermal neutral temperature, and comfort range were calculated and analyzed. The following results were obtained. Based on the overall population, long-term residence, and temporary residence classification, the indoor thermal comfort needs of residents in tropical cities in Haikou were effectively identified. The actual thermal neutral temperature of the overall population is 25.7 °C, and 90% of the acceptable thermal comfort temperature range is 23.2 °C–28.0 °C. The actual thermal neutral temperature of the regular residents is 27.3 °C, and 90% of the acceptable thermal comfort temperature range is 23.3 °C–31.4 °C. The actual thermal neutral temperature of the temporary population is 25.5 °C, and 90% of the acceptable thermal comfort temperature range is 23.0 °C–28.0 °C. These research results have an important reference value for improving the setting of the temperature of air conditioning in tropical areas in summer and further reducing energy consumption, which is conducive to sustainable development. [ABSTRACT FROM AUTHOR]

As natural medicines in complementary and alternative medicine, edible and medicinal resources are being gradually recognized throughout the world. According to statistics from the World Health Organization, about 80% of the worldwide population has used edible and medicinal resource products to prevent and treat diseases. Polysaccharides, one of the main effective components in edible and medicinal resources, are considered ideal regulators of various biological responses due to their high effectiveness and low toxicity, and they have a wide range of possible applications for the development of functional foods for the regulation of common, frequently occurring, chronic and severe diseases. Such applications include the development of polysaccharide products for the prevention and treatment of neurodegenerative diseases that are difficult to control by a single treatment, which is of great value to the aging population. Therefore, we evaluated the potential of polysaccharides to prevent neurodegeneration by their regulation of behavioral and major pathologies, including abnormal protein aggregation and neuronal damage caused by neuronal apoptosis, autophagy, oxidative damage, neuroinflammation, unbalanced neurotransmitters, and poor synaptic plasticity. This includes multi-target and multi-pathway regulation involving the mitochondrial pathway, MAPK pathway, NF-κB pathway, Nrf2 pathway, mTOR pathway, PI3K/AKT pathway, P53/P21 pathway, and BDNF/TrkB/CREB pathway. In this paper, research into edible and medicinal resource polysaccharides for neurodegenerative diseases was reviewed in order to provide a basis for the development and application of polysaccharide health products and promote the recognition of functional products of edible and medicinal resources. [ABSTRACT FROM AUTHOR]

This study evaluates ice particle size distribution and aspect ratio φ Multi-Radar Multi-Sensor (MRMS) dual-polarization radar retrievals through a direct comparison with two legs of observational aircraft data obtained during a winter storm case from the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. In situ cloud probes, satellite, and MRMS observations illustrate that the often-observed Kdp and ZDR enhancement regions in the dendritic growth layer can either indicate a local number concentration increase of dry ice particles or the presence of ice particles mixed with a significant number of supercooled liquid droplets. Relative to in situ measurements, MRMS retrievals on average underestimated mean volume diameters by 50% and overestimated number concentrations by over 100%. IWC retrievals using ZDR and Kdp within the dendritic growth layer were minimally biased relative to in situ calculations where retrievals yielded −2% median relative error for the entire aircraft leg. Incorporating φ retrievals decreased both the magnitude and spread of polarimetric retrievals below the dendritic growth layer. While φ radar retrievals suggest that observed dendritic growth layer particles were nonspherical (0.1 ≤ φ ≤ 0.2), in situ projected aspect ratios, idealized numerical simulations, and habit classifications from cloud probe images suggest that the population mean φ was generally much higher. Coordinated aircraft radar reflectivity with in situ observations suggests that the MRMS systematically underestimated reflectivity and could not resolve local peaks in mean volume diameter sizes. These results highlight the need to consider particle assumptions and radar limitations when performing retrievals. significance statement: Developing snow is often detectable using weather radars. Meteorologists combine these radar measurements with mathematical equations to study how snow forms in order to determine how much snow will fall. This study evaluates current methods for estimating the total number and mass, sizes, and shapes of snowflakes from radar using images of individual snowflakes taken during two aircraft legs. Radar estimates of snowflake properties were most consistent with aircraft data inside regions with prominent radar signatures. However, radar estimates of snowflake shapes were not consistent with observed shapes estimated from the snowflake images. Although additional research is needed, these results bolster understanding of snow-growth physics and uncertainties between radar measurements and snow production that can improve future snowfall forecasting. [ABSTRACT FROM AUTHOR]

Severe regional haze events, which are characterized by exceedingly high levels of fine particulate matter (PM), occur frequently in many developing countries (such as China and India), with profound implications for human health, weather, and climate. The occurrence of the haze extremes involves a complex interplay between primary emissions, secondary formation, and conducive meteorological conditions, and the relative contributions of the various processes remain unclear. Here we investigated severe regional haze episodes in 2013 over the Northern China Plain (NCP), by evaluating the PM production and the interactions between elevated PM and the planetary boundary layer (PBL). Analysis of the ground-based measurements and satellite observations of PM properties shows nearly synchronized temporal PM variations among the three megacities (Beijing, Baoding, and Shijiazhuang) in this region and a coincidence of the aerosol optical depth (AOD) hotspots with the three megacities during the polluted period. During the clean-to-hazy transition, the measured oxygenated organic aerosol concentration ([OOA]) well correlates with the odd-oxygen concentration ([Ox]=[O3]+[NO2]), and the mean [OOA] / [ Ox ] ratio in Beijing is much larger than those in other megacities (such as Mexico City and Houston), indicating highly efficient photochemical activity. Simulations using the Weather Research and Forecasting (WRF) model coupled with an explicit aerosol radiative module reveal that strong aerosol–PBL interaction during the polluted period results in a suppressed and stabilized PBL and elevated humidity, triggering a positive feedback to amplify the haze severity at the ground level. Model sensitivity study illustrates the importance of black carbon (BC) in the haze–PBL interaction and the aerosol regional climatic effect, contributing to more than 30 % of the PBL collapse and about half of the positive radiative forcing on the top of the atmosphere. Overall, severe regional haze exhibits strong negative radiative forcing (cooling) of - 63 to - 88 Wm-2 at the surface and strong positive radiative forcing (warming) of 57 to 82 Wm-2 in the atmosphere, with a slightly negative net radiative forcing of about - 6 Wm-2 on the top of the atmosphere. Our work establishes a synthetic view for the dominant regional features during severe haze events, unraveling rapid in situ PM production and inefficient transport, both of which are amplified by atmospheric stagnation. On the other hand, regional transport sufficiently disperses gaseous aerosol precursors (e.g., sulfur dioxide, nitrogen oxides, volatile organic compounds, and ammonia) during the clean period, which subsequently result in rapid in situ PM production via photochemistry during the transition period and via multiphase chemistry during the polluted period. Our findings highlight the co-benefits for reduction in BC emissions, which not only improve local and regional air quality by minimizing air stagnation but also mitigate the global warming by alleviating the positive direct radiative forcing. [ABSTRACT FROM AUTHOR]

Severe regional haze events, which are characterized by exceedingly high levels of fine particulate matter (PM), occur frequently in many developing countries (such as China and India), with profound implications for human health, weather, and climate. The occurrence of the haze extremes involves a complex interplay between primary emissions, secondary formation, and conducive meteorological conditions, and the relative contributions of the various processes remains unclear. Here we investigated severe regional haze episodes in 2013 over the Northern China Plain (NCP), by evaluating the PM production and the interactions between elevated PM and the planetary boundary layer (PBL). Analysis of the ground-based measurements and satellite observations of PM properties shows nearly synchronized temporal PM variations among the three megacities (Beijing, Baoding, and Shijiazhuang) in this region and a coincidence of the aerosol optical depth (AOD) hotspots with the three megacities during the polluted period. During the clean-to-hazy transition, the measured oxygenated organic aerosol concentration ([OOA]) well correlates with the odd-oxygen concentration ([Ox] = [O3] + [NO2]), and the mean [OOA]/[Ox] ratio in Beijing is much larger than those in other megacities (such as Mexico City and Houston), indicating highly efficient photochemical activity. Simulations using the Weather Research and Forecasting (WRF) model coupled with an explicit aerosol radiative module reveal that strong aerosol-PBL interaction during the polluted period results in a suppressed and stabilized PBL and elevated humidity, triggering a positive feedback to amplify the haze severity at the ground level. Model sensitivity study illustrates the importance of black carbon (BC) in the haze-PBL interaction and the aerosol regional climatic effect, contributing to more than 30% of the PBL collapse and about half of the positive radiative forcing on the top of the atmosphere. Overall, severe regional haze exhibits strong negative radiative forcing (cooling) of -63 to -88 W m-2 at the surface and strong positive radiative forcing (warming) of 57 to 82 W m-2 in the atmosphere, with a slightly negative net radiative forcing of about -6 W m-2 on the top of the atmosphere. Our work establishes a synthetic view for the dominant regional features during severe haze events, unraveling rapid in-situ PM production and inefficient transport, both of which are amplified by atmospheric stagnation. On the other hand, regional transport sufficiently disperses gaseous aerosol precursors (e.g., sulfur dioxide, nitrogen oxides, volatile organic compounds, and ammonia) during the clean period, which subsequently result in rapid in-situ PM production via photochemistry during the transition period and via multiphase chemistry during the polluted period. Our findings highlight the co-benefits for reduction in BC emissions, which not only improve local and regional air quality by minimizing air stagnation but also mitigate the global warming by alleviating the positive direct radiative forcing. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the significance of collagen in predicting the aggressiveness of rectal tumors in patients, examined in vivo based on tomoelastography quantified stiffness and ex vivo by histologically measured collagen volume fraction (CVF). Experimental Design: 170 patients with suspected rectal cancer were prospectively enrolled and underwent preoperative magnetic resonance imaging (MRI) and rectal tomoelastography, a technique based on multifrequency magnetic resonance elastography. Histopathologic analysis identified eighty patients with rectal cancer who were divided into subgroups by tumor-node (TN) stage, prognostic stage, and risk level. Rectal tumor stiffness was correlated with histopathologic CVF. Area-under-the-curve (AUC) and contingency analysis were used to evaluate the performance of rectal stiffness in distinguishing tumor stages which was compared to standard clinical MRI Results: In vivo tomoelastography revealed that rectal tumor stiffened significantly with increased TN stage (p<0.05). Tumors with poorly differentiated status, perineural and lymphovascular invasion also displayed higher stiffness than well-to-moderately differentiated, noninvasive tumors (all p<0.05). Similar to in vivo stiffness, CVF indicated an abnormally high collagen content in tumors with perineural invasion and poor differentiation status. CVF was also positively correlated with stiffness (p<0.05). Most importantly, both stiffness (AUROC: 0.82) and CVF (AUROC: 0.89) demonstrated very good diagnostic accuracy in detecting rectal tumors that have high risk for progressing to an aggressive state with poorer prognosis. Conclusion: In human rectal carcinomas, overexpression of collagen is correlated with increased tissue stiffness and high risk for tumor advancing more aggressively. In vivo tomoelastography quantifies rectal tumor stiffness which improves the diagnostic performance of standard MRI in the assessment of lymph nodes metastasis. Therefore, in vivo stiffness mapping by tomoelastography can predict rectal tumor aggressiveness and add diagnostic value to MRI. [ABSTRACT FROM AUTHOR]

Polarimetric radar observations from the NEXRAD WSR-88D operational radar network in the contiguous United States, routinely available since 2013, are used to reveal three prominent microphysical signatures in landfalling tropical cyclones: 1) hydrometeor size sorting within the eyewall convection, 2) vertical displacement of the melting layer within the inner core, and 3) dendritic growth layers within stratiform regions of the inner core. Size sorting signatures within eyewall convection are observed with greater frequency and prominence in more intense hurricanes, and are observed predominantly within the deep-layer environmental wind shear vector-relative quadrants that harbor the greatest frequency of deep convection (i.e., downshear and left-of-shear). Melting-layer displacements are shown that exceed 1 km in altitude compared to melting-layer altitudes in outer rainbands and are complemented by analyses of archived dropsonde data. Dendritic growth and attendant snow aggregation signatures in the inner core are found to occur more often when echo-top altitudes are low (≤10 km MSL), nearer the −15°C isotherm commonly associated with dendritic growth. These signatures, uniquely observed by polarimetric radar, provide greater insight into the physical structure and thermodynamic characteristics of tropical cyclones, which are important for improving rainfall estimation and the representation of tropical cyclones in numerical models. [ABSTRACT FROM AUTHOR]

Changes in land cover and aerosols resulting from urbanization may impact convective clouds and precipitation. Here we investigate how Houston urbanization can modify sea-breeze-induced convective cloud and precipitation through the urban land effect and anthropogenic aerosol effect. The simulations are carried out with the Chemistry version of the Weather Research and Forecasting model (WRF-Chem), which is coupled with spectral-bin microphysics (SBM) and the multilayer urban model with a building energy model (BEM-BEP). We find that Houston urbanization (the joint effect of both urban land and anthropogenic aerosols) notably enhances storm intensity (by ∼ 75 % in maximum vertical velocity) and precipitation intensity (up to 45 %), with the anthropogenic aerosol effect more significant than the urban land effect. Urban land effect modifies convective evolution: speed up the transition from the warm cloud to mixed-phase cloud, thus initiating surface rain earlier but slowing down the convective cell dissipation, all of which result from urban heating-induced stronger sea-breeze circulation. The anthropogenic aerosol effect becomes evident after the cloud evolves into the mixed-phase cloud, accelerating the development of storm from the mixed-phase cloud to deep cloud by ∼ 40 min. Through aerosol–cloud interaction (ACI), aerosols boost convective intensity and precipitation mainly by activating numerous ultrafine particles at the mixed-phase and deep cloud stages. This work shows the importance of considering both the urban land and anthropogenic aerosol effects for understanding urbanization effects on convective clouds and precipitation. [ABSTRACT FROM AUTHOR]

Graphene lateral spin valves (LSVs) are promising devices for future memory and magnetic field sensing applications. In this article, we study the dependence of the nonlocal spin resistance, $\Delta {R}_{{\text {NL}}}$ , and the baseline resistance, ${R}_{{\text {BS}}}$ , as a function of the graphene channel width, ${W}$. The scaling trend is quantitatively assessed by using graphene deposited by chemical vapor deposition, which provides a large number of devices with consistent performance. As ${W}$ is scaled from 10 to $0.5~\mu \text{m}$ , the change in $\Delta {R}_{{\text {NL}}}$ matches the theory of contact-induced spin relaxation with a current spin polarization of 3%–5% and a spin diffusion length of $\lambda _{s} = 1.5$ – $2.5~\mu \text{m}$. We also observe a systematic and dramatic decrease in ${R}_{{\text {BS}}}$ , which we attribute to the reduction in charge current spreading. However, we find in the narrowest devices that a small ${R}_{{\text {BS}}}$ remains that arises due to thermoelectric effects, and this trend is confirmed using gate voltage- and charge current-dependent analyses. Finally, we introduce a nonideality factor, ${m} = \vert {R}_{{\text {BS}}} / \Delta {R}_{{\text {NL}}}\vert $ , as a figure of merit to describe the suppression of the baseline relative to the spin signal. In an LSV with ${L} = {1.5}\,\,\mu \text{m}$ , ${W} = {0.5}\,\,\mu \text{m}$ , and n-type conduction, the nonideality factor is as low as ${m} = {0.0252}\,\,\pm \,\,0.0202$ at room temperature showing that nearly ideal bipolar and symmetric spin signals can be achieved in graphene LSVs. [ABSTRACT FROM AUTHOR]

Polarimetric radars make it possible to retrieve information on hydrometeors types, sizes and concentrations. Additional information on cloud electrification can be obtained from Lightning Mapping Arrays (LMAs). To study the development time and height of the hydrometeors and electrification require tracking their evolution within the lifecycle of convective cells. A new methodology for multi-cell identification and tracking (MCIT) is presented in this study. The algorithm in this study is different from traditional tracking methods; this new algorithm is applied to time series of radar volume scans. It tracks local maxima of vertically integrated liquid (VIL) water by identifying the two cells in consecutive radar scans that have maximum common VIL. The vertical profile of the polarimetric variables is used for constructing the time-height cross section of the cells' microphysical properties around the peak reflectivity as a function of height. The LMA sources that occur within the cell area are integrated as a function of height as well for each time step, as determined by the radar volume scans. The result of the tracking can provide insights on the evolution of storms, hydrometer types, precipitation initiation and cloud electrification under different thermodynamic and aerosol conditions. The details of the MCIT algorithm, its products and their performance for different type of storms are described in this paper. • Development of a novel cloud cell tracking algorithm. • Tracking cloud types include: convective and stratiform, isolated and clustered. • Tracking cloud cells through maturation into stratiform storm elements. • Use a synergy of polarimetric radar, satellite, lightning detection and model data. • Algorithm has flexible output options and possibilities for further studies. [ABSTRACT FROM AUTHOR]

Stochastic computing (SC) is a promising technology that can be used for low-cost hardware designs. However, SC suffers from its long latency. Although parallel processing can efficiently shorten the latency, duplicated stochastic number generators (SNGs) are necessary, which cause substantial hardware overhead. This paper proposes a scalable SNG based on the spin-Hall-effect (SHE), which is capable of generating multiple independent stochastic streams simultaneously. The design takes advantages of the efficient charge-to-spin conversion from the Spin-Hall material and the intrinsic stochasticity of nanomagnets. Compared to previous spintronic SNGs, the SHE-SNG can reduce the area by $1.6\times -7.8\times $ and the power by $4.9\times -13\times $ while increasing the degree of parallelism from 1 to 16. Compared to CMOS-based SNGs, the proposed SNG obtained $24\times -120\times $ and $53\times $ reduction in terms of area and power, respectively. Finally, three benchmarks were implemented, and the results indicate that SC implementations with the proposed SHE-SNG can achieve $1.2\times -29\times $ reduction of hardware resources compared to implementations with previous CMOS- and spintronic-based designs while scaling the degree of parallelism from 1 to 64. [ABSTRACT FROM AUTHOR]

An ac small signal model for lateral spin valves (LSVs) is developed, and is applied to two different types of devices: spin transmitters and magnetic field sensors. The small signal models explicitly decouple the charge- and spin-dependent components, which describe the intrinsic RC delay and the ac spin accumulation dynamics, separately. The analysis is applied to graphene LSVs as an example to illustrate the optimization strategies for LSV devices. By using the charge-spin circuit model, the scattering parameters and the reflection coefficients at the output terminals are quantitatively calculated as a function of frequency. This model can be used as a guide for future LSV design and to benchmark performance across different material systems. [ABSTRACT FROM AUTHOR]

A continental cloud complex, consisting of shallow cumuli, a deep convective cloud (DCC), and stratus, is simulated by a cloud-resolving Weather Research and Forecasting Model to investigate the aerosol microphysical effect (AME) and aerosol radiative effect (ARE) on the various cloud regimes and their transitions during the Department of Energy Routine Atmospheric Radiation Measurement Aerial Facility Clouds with Low Optical Water Depths Optical Radiative Observations (RACORO) campaign. Under an elevated aerosol loading with AME only, a reduced cloudiness for the shallow cumuli and stratus resulted from more droplet evaporation competing with suppressed precipitation, but an enhanced cloudiness for the DCC is attributed to more condensation. With the inclusion of ARE, the shallow cumuli are suppressed owing to the thermodynamic effects of light-absorbing aerosols. The responses of DCC and stratus to aerosols are monotonic with AME only but nonmonotonic with both AME and ARE. The DCC is invigorated because of favorable convection and moisture conditions at night induced by daytime ARE, via the so-called aerosol-enhanced conditional instability mechanism. The results reveal that the overall aerosol effects on the cloud complex are distinct from the individual cloud types, highlighting that the aerosol-cloud interactions for diverse cloud regimes and their transitions need to be evaluated to assess the regional and global climatic impacts. [ABSTRACT FROM AUTHOR]

During development, melanopsin-expressing intrinsically photosensitive retinal ganglion cells (ipRGCs) become light sensitive much earlier than rods and cones. IpRGCs project to many subcortical areas, whereas physiological functions of these projections are yet to be fully elucidated. Here, we found that ipRGC-mediated light sensation promotes synaptogenesis of pyramidal neurons in various cortices and the hippocampus. This phenomenon depends on activation of ipRGCs and is mediated by the release of oxytocin from the supraoptic nucleus (SON) and the paraventricular nucleus (PVN) into cerebral-spinal fluid. We further characterized a direct connection between ipRGCs and oxytocin neurons in the SON and mutual projections between oxytocin neurons in the SON and PVN. Moreover, we showed that the lack of ipRGC-mediated, light-promoted early cortical synaptogenesis compromised learning ability in adult mice. Our results highlight the importance of light sensation early in life on the development of learning ability and therefore call attention to suitable light environment for infant care. [Display omitted] • Light sensation through ipRGCs early in life promotes cortical synaptogenesis • Light enhances CSF oxytocin level via an ipRGCs-SON-PVN oxytocin neuron circuit • Oxytocin is essential for light-promoted ipRGC-mediated synaptogenesis • Lack of light sensation in early development impairs learning ability in adult mice Light sensation by intrinsically photosensitive retinal ganglion cells early in life ensures proper learning ability in adult mice by activating oxytocin-releasing neurons, which in turn promotes cortical synaptogenesis. [ABSTRACT FROM AUTHOR]

Railway static power conditioners (RPC) usually improve the power quality of traction power supply systems only according to the active power of the load, which leads to inaccurate compensation. There are two factors that restrict the performance of RPC, one of which is the reactive power of the load, and the other is the system error. In order to eliminate the compensation error, a compensation optimization method is proposed. First, calculate the reactive power compensation value for the reactive power of the load. Second, introduce the amplitudes and phases of the primary currents of the V/v transformer as references for the compensation error caused by the system loss and then use fuzzy control to optimize compensation. The compensation method proposed in this paper is actually a feedforward control. In addition, this method balances the three-phase currents and enables RPC to be used in railway power supply systems with low locomotive power factors. The effectiveness of the method proposed in this paper has been confirmed by the simulation results. [ABSTRACT FROM AUTHOR]

With the arrival of the big data era, mobile phone data have attracted increasing attention due to their rich information and high sampling rate. Currently, researchers have conducted various studies using mobile phone data. However, most existing studies have focused on macroscopic analysis, such as urban hot spot detection and crowd behavior analysis over a short period. With the development of the smart city, personal service and management have become very important, so microscopic portraiture research and mobility pattern of an individual based on big data is necessary. Therefore, this paper first proposes a method to depict the individual mobility pattern, and based on the long-term mobile phone data (from 2007 to 2012) of volunteers from Beijing as part of project Geolife conducted by Microsoft Research Asia, more detailed individual portrait depiction analysis is performed. The conclusions are as follows: (1) Based on high-density cluster identification, the behavior trajectories of volunteers are generalized into three types, and among them, the two-point-one-line trajectory and evenly distributed behavior trajectory were more prevalent in Beijing. (2) By integrating with Google Maps data, five volunteers' behavior trajectories and the activity patterns of individuals were analyzed in detail, and a portrait depiction method for individual characteristics comprehensively considering their attributes, such as occupation and hobbies, is proposed. (3) Based on analysis of the individual characteristics of some volunteers, it is discovered that two-point-one-line individuals are generally white-collar workers working in enterprises or institutions, and the situation of a single cluster mainly exists among college students and home freelancer. The findings of this study are important for individual classification and prediction in the big data era and can also provide useful guidance for targeted services and individualized management of smart cities. [ABSTRACT FROM AUTHOR]

Research Highlights: Soil carbon storage (SOC) decreased due to forest fragmentation through lower proportion of macroaggregate distribution, higher storage of fine roots and litter falls, and lower fine root production rate. Background and Objectives: Globally, forest fragmentation processes lead to enormous losses of SOC in forests. We investigated SOC and its determinants in forest fragments experiencing edge disturbances in south China. Materials and Methods: Soil aggregate characteristics, dynamics of fine roots, and litter fall were studied from forest edges to interiors. Generalized linear mixed models were used to model the contributions of fine root and litter fall dynamics to carbon concentration in aggregates. Results: Large and small macroaggregates had higher proportion of aggregate distribution and contributed more carbon to SOC in all types of plots in the present study. SOC significantly increased from forest edges to interiors due to carbon concentration of these two aggregate types increasing from edges to interiors, while the proportion of different aggregate distributions was similar within each plot. The same trend was found with increasing forest patch size. Fine root biomass storage had the strongest impact on carbon concentration in large macroaggregates and microaggregates, with higher fine root biomass storage associated with lower carbon concentration. In addition, biomass storage and production rates of both fine roots and litter falls decreased from forest interiors to edges. Our results showed that SOC was significantly decreased due to the lower proportion of large and small macroaggregate distribution, and lower fine root production rate in forest fragments. Conclusions: SOC loss due to effects of forest fragmentation and forest edges occurred through decreased concentrations of soil aggregates and fine root production rates. Results from this study will enhance our ability to evaluate soil aggregate, fine root, and leaf litter fall contributions to SOC within forest fragments, and to suggest basic recommendations for the management and conservation of these forest fragments. [ABSTRACT FROM AUTHOR]

Graphene is an ideal material for spintronic devices due to its low spin-orbit coupling and high mobility. One of the most important potential applications of graphene spintronics is for use in neuromorphic computing systems, where the tunable spin resistance of graphene can be used to apply analog weighting factors. A key capability needed to achieve spin-based neuromorphic computing systems is to achieve distinct regions of control, where injected and detected spin currents can be tuned independently. Here, we demonstrate the ability to achieve such independent control using a graphene spin valve geometry where the injector and detector regions are modulated by two separate bottom gate electrodes. The spin transport parameters and their dependence on each gate voltage are extracted from Hanle precession measurements. From this analysis, local spin transport parameters and their dependence on the local gate voltage are found, which provide a basis for a spatially-resolved spin resistance network that simulates the device. The data and model are used to calculate the spin currents flowing into, through, and out of the graphene channel. We show that the spin current flowing through the graphene channel can be modulated by 30% using one gate and that the spin current absorbed by the detector can be modulated by 50% using the other gate. This result demonstrates that spin currents can be controlled by locally tuning the spin resistance of graphene. The integration of chemical vapor deposition (CVD) grown graphene with local gates allows for the implementation of large-scale integrated spin-based circuits. [ABSTRACT FROM AUTHOR]

Background Multiparametric MRI is used for depiction of prostate cancer (PCa) but without consideration of the mechanical alteration of prostatic tissue by cancer. Purpose To investigate the diagnostic performance of stiffness and fluidity quantified with tomoelastography, a multifrequency MR elastography technique, for depiction of PCa compared with multiparametric MRI with Prostate Imaging Reporting and Data System (PI-RADS) version 2.1. Materials and Methods Prospective participants suspected to have PCa and healthy controls (HCs) underwent multiparametric MRI and tomoelastography between March 2019 and July 2020. Tomoelastography maps of shear-wave speed ( c ) and loss angle (φ) quantified stiffness and fluidity, respectively, for PCa and benign prostatic disease and for the peripheral and transition zones in HCs. Differences between entities and regions were analyzed by using analysis of variance or Kruskal-Wallis test. Diagnostic performance was assessed with area under the receiver operating characteristic curve (AUC) analysis. Results There were 73 participants with PCa (mean age, 72 years ± 7 [standard deviation]), 82 with benign prostatic disease (66 years ± 7), and 53 HCs (41 years ± 14). Mean ± standard deviation of c and φ were higher in PCa (3.4 m/sec ± 0.6 and 1.3 radian ± 0.2, respectively) than in benign prostatic disease (2.6 m/sec ± 0.3 and 1.0 radian ± 0.2, respectively; P < .001) and age-matched HCs (2.2 m/sec ± 0.1 and 0.8 radian ± 0.1, respectively; P < .001). Incorporating c and φ (AUC, 0.95; 95% CI: 0.92, 0.98) improved the diagnostic performance of PI-RADS version 2.1 (AUC, 0.85; 95% CI: 0.80, 0.91; P < .001). Multiparametric MRI combined with c and φ enabled detection of PCa with 95% (78 of 82 non-PCa) specificity, which was significantly higher than with use of multiparametric MRI alone (77% [63 of 82 non-PCa]; P < .001). In regional analysis, c combined with φ enabled differentiation of transition zone PCa from benign prostatic hyperplasia (AUC, 0.91; 95% CI: 0.83, 0.98) and peripheral zone PCa from chronic prostatitis (AUC, 0.94; 95% CI: 0.88, 1.00). Conclusion Use of tomoelastography-quantified stiffness and fluidity improved the diagnostic performance of multiparametric MRI with Prostate Imaging Reporting and Data System version 2.1 in detecting cancer in both the peripheral and transition zones. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Hectors and Lewis in this issue. An earlier incorrect version of this article appeared online. This article was corrected on March 24, 2021.