The Transformation of Trust in China’s Alternative Food Networks: Disruption, Reconstruction, and Development

Food safety issues in China have received much scholarly attention, yet few studies systematically examined this matter through the lens of trust. More importantly, little is known about the transformation of different types of trust in the dynamic process of food production, provision, and consumption. We consider trust as an evolving interdependent relationship between different actors. We used the Beijing County Fair, a prominent ecological farmers’ market in China, as an example to examine the transformation of trust in China’s alternative food networks. We argue that although there has been a disruption of institutional trust among the general public since 2008 when the melamine-tainted milk scandal broke out, reconstruction of individual trust and development of organizational trust have been observed, along with the emergence and increasing popularity of alternative food networks. Based on more than six months of fieldwork on the emerging ecological agriculture sector in 13 provinces across China as well as monitoring of online discussions and posts, we analyze how various social factors—including but not limited to direct and indirect reciprocity, information, endogenous institutions, and altruism—have simultaneously contributed to the transformation of trust in China’s alternative food networks. The findings not only complement current social theories of trust, but also highlight an important yet understudied phenomenon whereby informal social mechanisms have been partially substituting for formal institutions and gradually have been building trust against the backdrop of the food safety crisis in China

DeepFuzzer: Accelerated Deep Greybox Fuzzing

Fuzzing is one of the most effective vulnerability detection techniques, widely used in practice. However, the performance of fuzzers may be limited by their inability to pass complicated checks, inappropriate mutation frequency, arbitrary mutation strategy, or the variability of the environment. In this paper, we present DeepFuzzer, an enhanced greybox fuzzer with qualified seed generation, balanced seed selection, and hybrid seed mutation. First, we use symbolic execution in a lightweight approach to generate qualified initial seeds which then guide the fuzzer through complex checks. Second, we apply a statistical seed selection algorithm to balance the mutation frequency between different seeds. Further, we develop a hybrid mutation strategy. The random and restricted mutation strategies are combined to maintain a dynamic balance between global exploration and deep search. We evaluate DeepFuzzer on the widely used benchmark Google fuzzer-test-suite which consists of real-world programs. Compared with AFL, AFLFast, FairFuzz, QSYM, and MOPT in the 24-hour experiment, DeepFuzzer discovers 30%, 240%, 102%, 147%, and 257% more unique crashes, executes 40%, 36%, 36%, 98%, and 15% more paths, and covers 37%, 34%, 34%, 101%, and 11% more branches, respectively. Furthermore, we present the practice of fuzzing a message middleware from Huawei with DeepFuzzer, and 9 new vulnerabilities are reported

Multi-dimensional data indexing and range query processing via Voronoi diagram for internet of things

In a typical Internet of Things (IoT) deployment such as smart cities and Industry 4.0, the amount of sensory data collected from physical world is significant and wide-ranging. Processing large amount of real-time data from the diverse IoT devices is challenging. For example, in IoT environment, wireless sensor networks (WSN) are typically used for the monitoring and collecting of data in some geographic area. Spatial range queries with location constraints to facilitate data indexing are traditionally employed in such applications, which allows the querying and managing the data based on SQL structure. One particular challenge is to minimize communication cost and storage requirements in multi-dimensional data indexing approaches. In this paper, we present an energy- and time-efficient multidimensional data indexing scheme, which is designed to answer range query. Specifically, we propose data indexing methods which utilize hierarchical indexing structures, using binary space partitioning (BSP), such as kd-tree, quad-tree, k-means clustering, and Voronoi-based methods to provide more efficient routing with less latency. Simulation results demonstrate that the Voronoi Diagram-based algorithm minimizes the average energy consumption and query response time

Patterns and Distributions of Urban Expansion in Global Watersheds

Abstract Understanding urban expansion at the watershed scale is important because watersheds are important carriers of ecological and environmental impacts. However, current analyses are mainly restricted to administrative units only. Here, we used a long‐term multitemporal data set of urban land to quantify the spatiotemporal trends in the extent and form of urban expansion from 1992 to 2016 in endorheic and exoreic watersheds, globally. Overall, urban expansion in 70% of watersheds (154/220) showed a decelerating trend. The average urban expansion speed of these watersheds in the last 6 years was approximately half of that in the last 24 years. Urban expansion speed in endorheic watersheds lagged behind the counterparts in exoreic watersheds, with the former approximately 1/4 of the latter. More importantly, the pattern of urban expansion in endorheic watersheds was following the low‐density and sprawling trend in exoreic watersheds, which could exert far‐reaching impacts on the sustainability of endorheic watersheds located in arid lands. These findings suggest the need to look beyond administrative city boundaries for land use planning and policies in the context of watershed management

Diffuse X-ray Emissions from Dynamic Planetary Nebulae

We present theoretical results of a piecewise isothermal shock wind model devised for predicting the luminosity and surface brightness profile of diffuse X-ray emissions primarily from the inner shocked downstream wind zone of a planetary nebula (PN) surrounded by self-similar shocked dense shell and outer slow AGB wind envelope involving self-gravity and compare/fit our computational model results with available observations of a few grossly spherical X-ray emitting PNe. Matching shocked piecewise isothermal self-similar void (ISSV) solutions with self-gravity of Lou & Zhai (LZ) for the outer zone and a stationary isothermal fast tenuous wind with a reverse shock for the inner zone across an expanding contact discontinuity, we can consistently construct dynamic evolution models of PNe with diffuse X-ray emissions. On the basis of such a chosen dynamic wind interaction model, both X-ray luminosity and radial X-ray brightness profile are determined by three key parameters, namely the so-called X-ray parameter $X$, two radii $R_{rs}$ and $R_c$ of the reverse shock and the contact discontinuity. We find that morphologies of X-ray emissions would appear in the forms of either a central luminous sphere or a bright ring embedded within optically bright shells. In contrast to previous adiabatic models, the X-ray brightness peaks around the reverse shock, instead of the contact discontinuity surface just inside the outer shocked dense shell. Diffuse X-ray emissions of a few observed PNe appear to support this wind-wind dynamic interaction scenario.Comment: 13 pages, 8 figures, accepted by Mon. Not. R. Astron. Soc. Accepted 2010 June 2. Received 2010 May 28; in original form 2010 May

Li Intercalation into Graphite: Direct Optical Imaging and Cahn–Hilliard Reaction Dynamics

Lithium intercalation into graphite is a critical process in energy storage technology. Studies of Li intercalation kinetics have proved challenging due to structural and phase complexity, and sample heterogeneity. Here we report direct time- and space-resolved, all-optical measurement of Li intercalation. We use a single crystal graphite electrode with lithographically defined disc geometry. All-optical, Raman and reflectance measurements distinguish the intrinsic intercalation process from side reactions, and provide new insight into the microscopic intercalation process. The recently proposed Cahn–Hilliard reaction (CHR) theory quantitatively captures the observed phase front spatial patterns and dynamics, using a two-layer free-energy model with novel, generalized Butler–Volmer kinetics. This approach unites Cahn–Hilliard and electrochemical kinetics, using a thermodynamically consistent description of the Li injection reaction at the crystal edge that involves a cooperative opening of graphene planes. The excellent agreement between experiment and theory presented here, with single-crystal resolution, provides strong support for the CHR theory of solid-state reactions.United States. Dept. of Energy. Office of Basic Energy Sciences (DE-SC0001085

Neurological abnormalities and neurocognitive functions in healthy elder people: A structural equation modeling analysis

Background/Aims: Neurological abnormalities have been reported in normal aging population. However, most of them were limited to extrapyramidal signs and soft signs such as motor coordination and sensory integration have received much less attention. Very little is known about the relationship between neurological soft signs and neurocognitive function in healthy elder people. The current study aimed to examine the underlying relationships between neurological soft signs and neurocognition in a group of healthy elderly

Automated measurement of cell motility and proliferation

BACKGROUND: Time-lapse microscopic imaging provides a powerful approach for following changes in cell phenotype over time. Visible responses of whole cells can yield insight into functional changes that underlie physiological processes in health and disease. For example, features of cell motility accompany molecular changes that are central to the immune response, to carcinogenesis and metastasis, to wound healing and tissue regeneration, and to the myriad developmental processes that generate an organism. Previously reported image processing methods for motility analysis required custom viewing devices and manual interactions that may introduce bias, that slow throughput, and that constrain the scope of experiments in terms of the number of treatment variables, time period of observation, replication and statistical options. Here we describe a fully automated system in which images are acquired 24/7 from 384 well plates and are automatically processed to yield high-content motility and morphological data. RESULTS: We have applied this technology to study the effects of different extracellular matrix compounds on human osteoblast-like cell lines to explore functional changes that may underlie processes involved in bone formation and maintenance. We show dose-response and kinetic data for induction of increased motility by laminin and collagen type I without significant effects on growth rate. Differential motility response was evident within 4 hours of plating cells; long-term responses differed depending upon cell type and surface coating. Average velocities were increased approximately 0.1 um/min by ten-fold increases in laminin coating concentration in some cases. Comparison with manual tracking demonstrated the accuracy of the automated method and highlighted the comparative imprecision of human tracking for analysis of cell motility data. Quality statistics are reported that associate with stage noise, interference by non-cell objects, and uncertainty in the outlining and positioning of cells by automated image analysis. Exponential growth, as monitored by total cell area, did not linearly correlate with absolute cell number, but proved valuable for selection of reliable tracking data and for disclosing between-experiment variations in cell growth. CONCLUSION: These results demonstrate the applicability of a system that uses fully automated image acquisition and analysis to study cell motility and growth. Cellular motility response is determined in an unbiased and comparatively high throughput manner. Abundant ancillary data provide opportunities for uniform filtering according to criteria that select for biological relevance and for providing insight into features of system performance. Data quality measures have been developed that can serve as a basis for the design and quality control of experiments that are facilitated by automation and the 384 well plate format. This system is applicable to large-scale studies such as drug screening and research into effects of complex combinations of factors and matrices on cell phenotype