Access Patterns Research Articles

Transport Accessibility and Poverty Alleviation in Guizhou Province of China: Spatiotemporal Pattern and Impact Analysis

Both transport development and poverty alleviation are vital for sustainable development. However, due to the lack of long-term, comparable, county-level transport accessibility and poverty incidence data, the spatiotemporal patterns of these factors have rarely been accurately revealed in the poverty-stricken regions of China, causing the impacts of transport accessibility on poverty alleviation to be difficult to quantify. Taking Guizhou Province in China as the study area, this study revealed the spatiotemporal patterns of transport accessibility and poverty alleviation in 88 counties from 2000 to 2018 based on multisource data, including nighttime light data, LandScan population data, and transport network data. It was found that the transport accessibility decreased from 4.9 h to 3.3 h, and the poverty index decreased from 0.75 to 0.29 on average. All these factors exhibited a “core–periphery” spatial pattern. Furthermore, the panel data regression analysis suggested that transport accessibility has played a dominant role in poverty alleviation, with an elasticity coefficient of 0.839. In the future, policies concerned to integrate transport development with rural industries such as agriculture, e-commence, and tourism are recommended for poverty alleviation and rural revitalization, which are especially significant for promoting sustainable development, securing a win–win of economic growth and social equity.

Enhancing intercity transportation will improve the equitable distribution of high-quality health care in China

With the implementation of the patient-mobility policy and the development of intercity transportation in China, interprovincial patient mobility has become an important phenomenon. However, little is known whether or to what extent intercity transportation reshapes the delivery of high-quality health care. This study mapped the accessibility of 41,259 township-level divisions to 1152 tertiary hospitals in multiple patient-mobility scenarios according to whether to seek interprovincial health care and whether to adopt intercity transportation. Our analysis included different transportation systems, such as conventional rail, high-speed rail (HSR), and air transport. Then the geographical detector model was used to contrast the spatial influences of different accessibility patterns on mortality. Our results show that HSR had the largest influence on the utilization of high-quality health care, while air transport was statistically insignificant. HSR can promote the equitable distribution of high-quality health care in that HSR decreases the Gini index and urban-rural disparity in accessibility by 9.52% and 13.25%, respectively. Further, a synergistic effect exists between the intercity transportation and the patient-mobility policy, which could reduce the Gini index and urban-rural disparity in accessibility by an additional 5.07% and 22.50%, respectively. Achieving high-quality universal health coverage relies on sustainable transportation policies and services.

Planning and designing universal access to social services. A pioneering local program on welfare spaces in Italy

The combined effect of socio-economic and demographic changes exerts pressure on the welfare systems and makes it more urgent to provide appropriate answers to increasing and diversifying needs with scanter resources. Local social services are strongly committed to such challenges. The physical features of the spaces of welfare, often neglected both by research and by implementation, play a fundamental role in the attempt to innovate and extend access to social assistance services. The article analyses how, at the urban level, the interplay between urban planning and welfare policies might contribute to reshaping the traditional physical structures of social welfare services and, through these, the patterns of access to local welfare. Building on an experimental project tested and then consolidated in Milan, the article analyses the role of the spatial dimensions of welfare places, namely the contexts, settings and artefacts, in increasing accessibility, lowering the threshold, reducing stigmatization, ensuring (or not) the coherence between policies and programmes’ objectives and approaches and the features of the spaces where such programmes and policies are implemented and where citizens experience them. Moreover, it discusses alternative planning strategies and tools in use to design the current spaces for welfare and to govern their distribution and organisation at the city level.

Enabling privacy-preserving multi-server collaborative search in smart healthcare

With the advancement of smart healthcare, each medical institution stores huge amounts of users’ medical data in its cloud server for diagnosis and treatment. However, the traditional storage structure has obstacles to reasonable medical resources access and medical data circulation, such as data security, query privacy, and isolated data island problems. An intuitive solution is to store all the encrypted medical data in a central server. But this method absolutely depends on the central server, causing more performance disadvantages and privacy risks. Therefore, it is urgent to construct a secure and proper medical data retrieval scheme. Based on the existing data storage model, we build a multi-server search scheme to collaboratively perform diagnostic institution location, medical data search, and even cross-domain data search in this paper. The multi-server architecture solves problems of destructiveness and information over-centralization caused by the single server and enhances the reliability and practicality of the system. The utilization of hidden vector encryption, secret sharing, and secure multi-party computation realizes efficient search, identity privacy, search pattern security, and access pattern security. Security analysis demonstrates that identity privacy and query security are protected. Extensive experiments show that the scheme has better data search and data add efficiency through horizontal and vertical comparisons.

CAPMIG: Coherence-Aware Block Placement and Migration in Multiretention STT-RAM Caches

In recent years, the increased working set size of applications craves more memory demand in terms of large-sized last-level caches (LLCs). To fulfill this, one of the promising technology is STTRAM. However, high write energy and write latency make it challenging to adopt it on a wide scale. Multiretention STTRAM caches have been considered an improvisation over standard STTRAM caches by reducing their retention time which reduces the write latency. Here, we have to negotiate with a refresh operation by applying various refresh management techniques. However, its retention period consumes significant refresh energy in the periodic refresh. In this article, we take help from the coherence protocol and decide the best retention type for each block. A block loaded on a write access is likely to get more writes in the future and is therefore loaded in the lowest retention time region. Similarly, instruction blocks are loaded in the highest retention time region. This helps in reducing the number of refreshes incurred by the blocks. During runtime, the blocks may change their access patterns, requiring a change in their retention region. This article also proposes a migration policy to relocate the blocks to appropriate regions during runtime. Identification of zero data value blocks and not refreshing them is an additional augmentation to our proposal. The experimental result using full system simulation shows a good reduction in the number of refreshes and energy consumption over the baseline designs.

RLTiering: A Cost-Driven Auto-Tiering System for Two-Tier Cloud Storage Using Deep Reinforcement Learning

The cloud storage boom has prompted providers to offer two storage tiers, i.e., hot and cold tiers, which are respectively purpose-built to provide the lowest cost for frequent and infrequent access patterns. However, for cloud users, it is non-trivial to determine cost-effective tiers because it is hard to obtain future access patterns in advance and is difficult to predict them exactly. The lack of future information poses a risk of increasing costs instead of saving costs. This is not the only challenge encountered when it comes to cost optimization. In this article, we take Amazon S3 as an example to analyze the pricing of two-tier cloud storage and derive several major challenges faced by cost optimization. Then, assuming a priori knowledge of future access patterns, we propose an optimal offline algorithm based on dynamic programming to determine cost-effective tiers for each time slot. Further, to handle online workload arrivals, we formulate the problem using Markov decision processes and propose RLTiering based on deep reinforcement learning. Eventually, the cost performance of RLTiering is evaluated based on real-world traces and prevalent Amazon S3 pricing, and the results show that it achieves significant cost-savings.

Deploying Computational Storage for HTAP DBMSs Takes More Than Just Computation Offloading

Hybrid transactional/analytical processing (HTAP) would overload database systems. To alleviate performance interference between transactions and analytics, recent research pursues the potential of in-storage processing (ISP) using commodity computational storage devices (CSDs). However, in-storage query processing faces technical challenges in HTAP environments. Continuously updated data versions pose two hurdles: (1) data items keep changing, and (2) finding visible data versions incurs excessive data access in CSDs. Such access patterns dominate the cost of query processing, which may hinder the active deployment of CSDs. This paper addresses the core issues by proposing an a nalyt i c offloa d e ngine (AIDE) that transforms engine-specific query execution logic into vendor-neutral computation through a canonical interface. At the core of AIDE are the canonical representation of vendor-specific data and the separate management of data locators. It enables any CSD to execute vendor-neutral operations on canonical tuples with separate indexes, regardless of host databases. To eliminate excessive data access, we prescreen the indexes before offloading; thus, host-side prescreening can obviate the need for running costly version searching in CSDs and boost analytics. We implemented our prototype for PostgreSQL and MyRocks, demonstrating that AIDE supports efficient ISP for two databases using the same FPGA logic. Evaluation results show that AIDE improves query latency up to 42× on PostgreSQL and 34× on MyRocks.

Chromatin profile-based identification of a novel ER-positive breast cancer subgroup with reduced ER-responsive element accessibility

BackgroundOestrogen receptor (ER) signalling-dependent cancer cell growth is one of the major features of ER-positive breast cancer (BC). Inhibition of ER function is a standard and effective treatment for ER-positive tumours; however, ~20% of patients with ER-positive BC experience early or late recurrence. In this study, we examined intertumour heterogeneity from an epigenetic perspective based on the hypothesis that the intrinsic difference in epigenetic states around ER signalling pathway underlies endocrine therapy resistance.MethodsWe performed transposase-accessible chromatin sequencing (ATAC-seq) analysis of 42 BC samples, including 35 ER-positive(+) human epidermal growth factor receptor 2 (HER2)-negative(−) and 7 triple-negative tumours. We also reanalysed ATAC-seq data of 45 ER + /HER2 − tumours in the Cancer Genome Atlas (TCGA) BC cohort to validate our observations.ResultsWe conducted a comprehensive analysis of cis-regulatory elements (CREs) using ATAC-seq, identifying three subgroups based on chromatin accessibility profiles. We identified a subgroup of ER-positive BCs with a distinctive chromatin accessibility pattern including reduced accessibility to ER-responsive elements (EREs). The same subgroup was also observed in TCGA BC cohort. Despite the reduced accessibility to EREs, the expression of ER and potential ER target genes were not decreased in these tumours.ConclusionOur findings highlight the existence of a subset of ER-positive BCs with unchanged ER expression but reduced EREs accessibility that cannot be distinguished by conventional immunostaining for ER. Future studies should determine whether these tumours are associated with resistance to endocrine therapy.

Flare: A Fast, Secure, and Memory-Efficient Distributed Analytics Framework

As big data processing in the cloud becomes prevalent today, data privacy on such public platforms raises critical concerns. Hardware-based trusted execution environments (TEEs) provide promising and practical platforms for low-cost privacy-preserving data processing. However, using TEEs to enhance the security of data analytics frameworks like Apache Spark involves challenging issues when separating various framework components into trusted and untrusted domains, demanding meticulous considerations for programmability, performance, and security. Based on Intel SGX, we build Flare, a fast, secure, and memory-efficient data analytics framework with a familiar user programming interface and useful functionalities similar to Apache Spark. Flare ensures confidentiality and integrity by keeping sensitive data and computations encrypted and authenticated. It also supports oblivious processing to protect against access pattern side channels. The main innovations of Flare include a novel abstraction paradigm of shadow operators and shadow tasks to minimize trusted components and reduce domain switch overheads, memory-efficient data processing with proper granularities for different operators, and adaptive parallelization based on memory allocation intensity for better scalability. Flare outperforms the state-of-the-art secure framework by 3.0× to 176.1×, and is also 2.8× to 28.3× faster than a monolithic libOS-based integration approach.

Comparing SYCL data transfer strategies for tracking use cases

The aim of this work is to compare the performance and ease of programming of the various data transfer strategies provided by SYCL 2020: buffers/accessors on one hand and the different storage types exposed by Unified Shared Memory (USM) on the other hand. We measured the relative performance of USM exclusively located either on the host (USM host) or on the device (USM device), or automatically managed and moved (USM shared). We also tried to quantify the impact of formatting data in a GPU-friendly manner as opposed to using a regular pointer-based structure in which the C++ allocator was replaced by the SYCL allocator sycl::malloc. We first made a PCIe-bound micro-benchmark to test the SYCL memory models with a simple access pattern. We then switched to a real use-case provided by Traccc, a research project associated to the ACTS particle tracking library. The algorithm of interest is SparseCCL, a clustering algorithm used on the first step of track reconstruction. For consistency, all tests were made on a single hardware architecture: a recent server having a discrete GPU with dedicated VRAM, representative of the hardware currently used by the ACTS team.

Towards an integrated garden. Gardeners of all types, unite!

Urban gardens are focal in metropolitan social-ecological infrastructure and yet they are spaces often threatened by urban development. In Berlin and Warsaw, major urban changes have prompted citizens to alter their attitudes toward the use of existing garden areas. This study tackles the socio-spatial phenomena of emerging grassroots projects and practices jointly implemented by groups of allotment and community gardeners, which are instrumental in envisioning new forms of common management and protection of garden spaces along urban transformations. The article investigates how cooperation between gardeners of different backgrounds influences allotments’ patterns of property and public accessibility. The focus is on a possible change of perspective regarding the use of closed allotment structures and the conceptualisation of a new form of hybrid urban landscape: an integrated garden. Our findings fit into the general debate on gardens as commons and new forms of green space selfgovernance.

Unequal periurban mobility: Travel patterns, modal choices and urban core dependence in Latin America

Latin America is a highly urbanized region characterized by remarkable inequality levels, also reflected in an uneven distribution of opportunities, making socio-economic segregation quite visible. Since the individual possibility to travel and therefore access to urban opportunities strongly depends on socio-economic status and the distances to overcome, highly unequal patterns of mobility and accessibility emerge. The continuous expansion of Latin American cities originates specific mobility-related inequalities visible in periurban areas, which tend to lack some key urban opportunities and public transport services usually available in cities. Due to established and new patterns of territorial segregation, these areas may generate new forms of marginality in relation to mobility, posing challenges for public action and territorial governance. Our paper considers if and how periurban areas experience different forms of mobility-related inequalities in three Latin American metropolises in Brazil, Chile, and Colombia (São Paulo, Santiago, and Bogotá, respectively). We do so by examining the differences among urban core and periurban zones based on four elements: socio-demographic features, access to the public transport system, spatial continuity, and functional dependence. Our analysis shows that the three metropolitan regions have different structures: while Bogotá and Santiago appear to be more dependent on the urban core, São Paulo shows more autonomous and self-sufficient periurban zones. The analysis also highlights different forms of peripherality, defined by differentiated mobility patterns and modal choices that suggest that city-specific lines for public action might be needed.

Gender Access Pattern of Education in Rural Area: A Cross Sectional Study of Barak Valley of North- East India of Elderly People

Education is playing a significant role for the development of the rural society in various dimensions, such as gender, racial discrimination, economic growth and sustainable development of the society. It creates involvement and adaptive ability among different sections of the society in terms of gender in rural society

EPSILOD: efficient parallel skeleton for generic iterative stencil computations in distributed GPUs

Iterative stencil computations are widely used in numerical simulations. They present a high degree of parallelism, high locality and mostly-coalesced memory access patterns. Therefore, GPUs are good candidates to speed up their computation. However, the development of stencil programs that can work with huge grids in distributed systems with multiple GPUs is not straightforward, since it requires solving problems related to the partition of the grid across nodes and devices, and the synchronization and data movement across remote GPUs. In this work, we present EPSILOD, a high-productivity parallel programming skeleton for iterative stencil computations on distributed multi-GPUs, of the same or different vendors that supports any type of n-dimensional geometric stencils of any order. It uses an abstract specification of the stencil pattern (neighbors and weights) to internally derive the data partition, synchronizations and communications. Computation is split to better overlap with communications. This paper describes the underlying architecture of EPSILOD, its main components, and presents an experimental evaluation to show the benefits of our approach, including a comparison with another state-of-the-art solution. The experimental results show that EPSILOD is faster and shows good strong and weak scalability for platforms with both homogeneous and heterogeneous types of GPU.

Measuring Spatializing Inequalities of Transport Accessibility and Urban Development Patterns: Focus on Megacity Urbanization, Thailand

The metropolis of Bangkok is characterized as a primate city because of its role as the capital of Thailand. Its suburbanization spreads to five surrounding provinces. Compared to other provinces in Thailand, it has highly concentrated urban development, without disparity between urban and rural areas. Furthermore, the travel volume in Bangkok and its surrounding areas is the highest in the country, with the majority related to private vehicle usage. This is why Bangkok is ranked as the world’s most congested city. To solve this problem and sustain the urbanization of the capital, it is necessary to understand the urban development patterns in Bangkok and their associated factors in measuring the accessibility of transportation. This research applied factor analysis and cluster analysis to characterize the different district contexts of the Bangkok Metropolitan Region, by selecting the Bangkok Metropolitan Administration (BMA) as the capital city area and Pathum Thani Province as a suburbanized area. Consequently, their transport accessibility could be represented by the level of accessibility in terms of the inequalities in the existing transportation system. Furthermore, by clustering the districts according to their economic and social factors, the causes of these inequalities could be identified by spatializing and geographically highlighting them. These findings should be integrated into the urban planning and development policies to overcome urban development challenges and create a city with more accessible and affordable public transport opportunities.

Uphill resampling for particle filter and its implementation on graphics processing unit

We introduce a new resampling method, named Uphill, that is free from numerical instability and suitable for parallel implementation on graphics processing unit (GPU). Common resampling algorithms such as Systematic suffer from numerical instability when single precision floating point numbers are used. This is due to cumulative summation over the weights of particles when the weights differ widely or the number of particles is large. The Metropolis and Rejection resampling algorithms do not suffer from numerical instability as they only calculate the ratios of weights pairwise rather than perform collective operations over the weights. They are more suitable for the GPU implementation of the particle filter. However, they undergo non-coalesced global memory access patterns which cause their speed deteriorate rapidly as the number of particles gets large. Uphill also does not suffer from numerical instability but, experiences the same non-coalesced global memory access problem with Metropolis and Rejection. We introduce its faster version named Uphill-Fast which eliminates this problem. We make comparisons of Uphill and Uphill-Fast with the Systematic, Metropolis, Metropolis-C2 and Rejection resampling methods with respect to quality and speed. We also compare them on a highly non-linear system. Uphill-Fast runs faster and attains similar quality, in terms of RMSE, in comparison with Metropolis and Rejection when the number of particles is very large. Uphill-Fast runs with roughly same speed as Metropolis-C2 with better variance and MSE when the number of particles is very large.

Technologies of protest in Irish abortion activism

ABSTRACTIn the decades before the historic legalization of abortion in the Republic of Ireland in 2018, activists used creative methods to educate, agitate, and advocate for changes in abortion law and access. In the 2000s, the availability of the “abortion pills,” mifepristone and misoprostol, began to affect patterns of illegal abortion access, as well as the methods of protest used by those advocating for legal abortion. This article examines protest actions orchestrated by Irish abortion activists from 2014 to 2018 that used abortion pills as technologies of protest. I argue that abortion pill protests introduced a new “protest logic” to abortion activism, both in Ireland and around the world (De Zordo, Mishtal, and Anton 2017). By using abortion pills as a central object in public protests, activists repackaged abortion pills from “technologies of access” to “technologies of protest.” These new tactics were not without controversy. I suggest that the conflicts that emerged from abortion pill protests helped shape new activist claims about abortion access and ultimately led to positive social and legislative change. As abortion pill use increases globally in the face of growing restrictions, the use of pills as technologies of protest will continue to affect abortion activism and other social movements.

Changing patterns of mobility and accessibility to culture and leisure: Paradox of inequalities

The aim of this paper is to present an overarching theoretical perspective on the paradox of inequalities and the paradigm shift in mobilities by reflecting on the challenges and opportunities in urban areas faced by the COVID-19 measures. The question of blurring boundaries between the human and the technological aspects and the ways in which they alter the form of communication and action is tackled reflecting on the digital divide and socio-spatial inequalities. In order to connect theory and practice, implications from different cases are provided for shedding light on the expected impacts and scenarios for the changing patterns of mobility and accessibility. The results indicate hybridization of the on-site and online forms of mobilities, as well as new approaches to make culture and leisure more inclusive and accessible. Promoting local integration, emerging forms of local tourism such as staycations, using digital tools to foster co-creation, co-curation, and audience engagement, developing new models of business and consumption reflect the changing patterns of mobility and accessibility. There are avenues for further research that revolve around the questions of inequalities, over-consumption, sociality and sustainability. • COVID-19 accelerated the plans for eco-friendly and sustainable transportation. • More leisure activities have been provided for the local urban communities. • Cultural tourism (im)mobility is mainly promoted by virtual tours. • Digitalization had a major impact on accessing content and learning opportunities. • The lack of equipment and/or knowledge prevent access.

Higher Education funding, Justice and Equity - Critical Perspectives

How governments choose to fund students in higher education (HE) is inextricably linked to the sector’s sustainability and efforts to achieve a just and equitable HE experience and outcomes for all students. The way funding mechanisms are structured and subsequently enacted within the university, has far-reaching consequences, with the implications reaching far beyond the walls of the institution (Shermer, 2021). In the context of austerity, marketisation, credentialisation and related neoliberal conceptions of education and society, student funding models have greatly transformed the sector and its role in enabling or hindering efforts to achieve a more just and equitable society (Quinlan, 2014). However, despite well-intentioned global and national-level policy commitments to achieving justice and equity in and through HE, the persistent effects of geography, race, wealth, gender, and class-based disparities in patterns of access, participation and attainment rates have undermined the idea of HE as a vehicle for just and equitable futures and transformation (Boliver, 2017). Higher education institutions globally find themselves at a crossroads of trying to maintain their core purpose as a public good on the one hand and compliance with global neoliberal policies, which are foundational to the modern university on the other. The tension between these contested and seemingly contradicting paradigms is made visible in how universities respond to issues of inclusion, equity and in how and what they choose to fund.

SetRkNN: Efficient and Privacy-Preserving Set Reverse kNN Query in Cloud

The advance of cloud computing has driven a new paradigm of outsourcing large-scale data and data-driven services to public clouds. Due to the increased awareness of privacy protection, many studies have focused on addressing security and privacy issues in outsourced query services. Although many privacy-preserving schemes have been proposed for various query types, the set reverse k nearest neighbors (RkNN) query is still an unexplored area. Even if some existing schemes can be adapted to achieve privacy-preserving set RkNN queries, they will suffer from linear search efficiency. As a steppingstone, in this paper, we propose an efficient and privacy-preserving set RkNN query scheme over encrypted data with sublinear query efficiency. Specifically, we first design an inverted prefix index to organize the set dataset and propose an algorithm to traverse the index with sublinear search efficiency. Then, we propose two oblivious data comparison protocols based on a symmetric homomorphic encryption (SHE) scheme and design the private filter/refinement protocols to preserve the privacy of index searching. After that, we propose an access pattern privacy-preserving set RkNN query scheme by using private filter/refinement protocols. Rigorous security analysis demonstrates that our scheme can protect data privacy and access pattern privacy. Experimental results indicate that our scheme is more efficient than the available naive solution in terms of computational costs and communication overheads.