Access Patterns Research Articles

Student access patterns for an online clinical skills procedural video library

ABSTRACT Clinical relevance Clinical skills training is essential in optometry curricula to develop core graduate entry competencies, including self-directed learning to facilitate life-long learning. Efficient and efficacious approaches are required to optimise student and educator time and resources. Background A video library of optometric clinical skills was created in 2012 to support self-directed student learning and face-to-face training. Use of videos in higher education generally increased during the COVID-19 pandemic and has remained above pre-pandemic levels. This study aimed to capture and evaluate student access patterns in the library to determine which videos were accessed most, and if this changed with training stage and following the pandemic. Methods Data on student viewing and critique submission were extracted for 71 videos from a clinical skills video library from 2018 to 2023. The number of videos viewed by students was analysed by year, cohort, video type (gold standard, scripted errors, summary, and student generated) and video category (history, screening, refraction, anterior segment, posterior segment and tonometry). Results First-year students viewed the most videos, and this decreased significantly during and following the pandemic. Overall, the number of videos viewed decreased with increasing course stage. Video access, by category, aligned with the curriculum. Views were highest for gold standard and student videos. Viewing of scripted error videos and submission of critiques of procedural videos was low for all course stages and years. Conclusion A web-based video library of optometric clinical skills was used for self-directed learning, mostly by students early in their training. Similar resources developed in the future should align with curriculum and include exemplar and student-based videos. Exploration of student and educator perspectives regarding factors that impact engagement with the online library warrants investigation to facilitate optimal integration in post-pandemic times.

Analyzing spatiotemporal features of Suzhou's old canal city: an optimized composite space syntax model based on multifaceted historical-modern data

AbstractRivers and road systems play crucial roles in urban development and in shaping the vitality of cities. The present study focuses on the spatiotemporal development patterns of canal cities. Taking Suzhou as an example, employing various spatial measurement methods combined with multidimensional spatiotemporal data, it clearly demonstrates the urban morphological patterns and societal characteristics related to the road and river network systems at different stages of urban development. Utilizing data extracted from historical and modern maps of Suzhou and employing the YOLO (You Only Look Once) algorithm, this study establishes a spatiotemporal dataset for Suzhou's ancient city, a representative Chinese canal city. An optimized space syntax algorithm for public service facilities, utilizing Python library like Geopandas, Numpy, is proposed to analyze the river and road system's impact on historical development and urban morphology. With multiple spatial econometric models applied to maps from various periods, this research explores the following findings: (1) By controlling rivers as a variable, it quantitatively confirms that rivers were crucial components of urban systems in ancient cities, playing a significant role in urban development and activities, though gradually overlooked in modern times. (2) Public service facilities of different types demonstrate patterns of Accessibility and Integration within the river-road system across various periods. (3) Changes in the distribution of public service facilities correspond to phased shifts in the center of Suzhou’s ancient city, mutually validating the authenticity of realistic paintings, historical maps, and the methodologies used in this study. This study emphasizes a broader historical and spatiotemporal perspective, augmented by quantitative research methods. It investigates the distribution and developmental characteristics of various types of public service facilities across different periods. The research aim is to understand the impact of river and road systems on urban development, as well as the morphological and social changes in historical cities that arise from urban activities.

Exploring the Spatial Patterns of Accessibility to Metro Services Considering the Locations of Station Entrances/Exits

Accessibility to metro services is often evaluated based on the locations of stations. However, compared to the location of station itself, focusing on its entrances/exits offers a more accurate approach to assessing station supply and demand levels. Despite this, research focusing on the supply of and demand for metro services concerning metro entrances and exits remains limited. This study employed multi-source geospatial data from Xiamen, China, to examine the supply and demand dynamics of metro stations with a particular emphasis on entrances/exits. In the first phase, we treated entrances/exits as supply facilities and used land plot boundaries as the fundamental spatial units for accessibility calculations. Taking into account the layout characteristics of entrances/exits, along with the traffic generation of various land-use types, we employed the Gaussian two-step floating catchment area (G2SFCA) method to gauge the supply and demand levels of plots. Subsequently, we computed the spatial supply-and-demand relationships of station entrances/exits for both station-level and shared usage level of entrances/exits. We found that the accessibility from plots to entrances/exits diverged from previously observed spatial distribution trends, being higher in city centers, regional boundaries, and terminal stations and lower in transitional areas. Moreover, “metro accessibility” and the “imbalance index of entrances/exits” are associated with the primary functions of stations and the surrounding urban development; yet they exhibit spatial heterogeneity. The stations with a high value for “imbalanced index of entrances/exits” were always near some business parks, and “metro accessibility” seemed to be more easily affected by location factors. Based on two metrics, stations were categorized into four types, each displaying unique characteristics regarding location distributions, entrance/exit configurations, and commuting passenger sources. This research aims to identify the phenomenon of unfair transport in metro service from the perspective of their entrances, inform the optimization of metro station designs, and tailor planning recommendations, ultimately enhancing transport equity and contributing to sustainable urban built environments.

Sequentialized Virtual File System: A Virtual File System Enabling Address Sequentialization for Flash-Based Solid State Drives

Solid-state drives (SSDs) are widely adopted in mobile devices, desktop PCs, and data centers since they offer higher throughput, lower latency, and lower power consumption to modern computing systems and applications compared with hard disk drives (HDDs). However, the performance of the SSDs can be degraded depending on the I/O access pattern due to the unique characteristics of SSDs. For example, random I/O operation degrades the SSD performance since it reduces the spatial locality and induces garbage collection (GC) overhead. In this paper, we present an address reshaping scheme in a virtual file system (VFS) called sVFS for improving performance and easy deployment. To do this, it first sequentializes a random access pattern in the VFS layer which is an abstract layer on top of a more concrete file system. Thus, our scheme is independent and easily deployed on any concrete file systems, block layer configuration (e.g., RAID), and devices. Second, we adopt a mapping table for managing sequentialized addresses, which guarantees correct read operations. Third, we support transaction processing for updating the mapping table to avoid sacrificing the consistency. We implement our scheme at the VFS layer in Linux kernel 5.15.34. The evaluation results show that our scheme improve the random write throughput by up to 27%, 36%, 34%, and 2.35× using the microbenchmark and 25%, 22%, 20%, and 3.51× using the macrobenchmark compared with the existing scheme in the case of EXT4, F2FS, XFS, and BTRFS, respectively.

RanSMAP: Open dataset of Ransomware Storage and Memory Access Patterns for creating deep learning based ransomware detectors

RanSMAP: Open dataset of Ransomware Storage and Memory Access Patterns for creating deep learning based ransomware detectors

Competitive cost-effective memory access predictor through short-term online SVM and dynamic vocabularies

In recent years, there has been a significant increase in the processing of massive amounts of data, driven by the growing demands of mobile systems, parallel and distributed architectures, and real-time systems. This applies to various types of platforms, both specific and general-purpose. Despite numerous advancements in Computer Systems, a critical challenge remains: the efficiency and speed of memory access. This bottleneck is being addressed through cache prefetching, that is, by predicting the next memory address to be accessed and then by having always prefetched in the cache system those data to be used shortly by the processor. This paper explores established intelligent techniques for address prediction, examining their limitations and analyzing the memory access patterns of popular software applications. Building on the successes of previous intelligent predictors based on Machine and Deep Learning models, we introduce a new predictor, SVM4AP (Support Vector Machine For Address Prediction), designed to overcome the identified drawbacks of its predecessors. The architecture of SVM4AP improves the trade-off between performance and cost, compared to those previous proposals in the literature, achieving high accuracy through short-term learning. Comparisons are made with two prominent predictors from the literature: the classical DFCM (Differential Finite Context Method) and the contemporary Deep Learning-based DCLSTM (Doubly Compressed Long-Short Term Memory). The results demonstrate that SVM4AP achieves superior cost-effectiveness across various configurations. Simulations reveal that SVM4AP configurations dominate both DFCM and DCLSTM counterparts, forming the majority of the first Paretto front. Particularly noteworthy is the significant advantage of our proposal for small-size predictors. Furthermore, we release an open-source tool enabling the scientific community to reproduce the results presented in this paper using a set of benchmark traces.

Analysis of Secondary School Infrastructure Distributions in Osogbo Metropolis, Nigeria

This study analysed the geospatial distribution of secondary schools infrastructure in the Osogbo metropolis, Nigeria, with a focus on evaluating accessibility and spatial patterns of school locations. By examining the spatial distribution, travel distances, and clustering of schools, this research offers a novel contribution to the educational planning literature. The data were collected through both primary and secondary sources, utilizing total enumeration for spatial data and a sampling frame of 17,595 students and 452 teachers across 120 public and private secondary schools. Using a balloting approach, at 15%, 19 schools were sampled, followed by a random sampling technique to choose 5% of students and staff, resulting in a total of 906 respondents (880 students and 26 teachers). The analysis, employing Moran's I Index, revealed a value of 0.75 and a p-value of 0.14, indicating a random distribution of schools with a z-score of 1.45, falling within the expected range. The average distance traveled to schools was 1.582 km, reflecting spatial inequities in accessibility. This study provides critical insights for policymakers, emphasizing the need for both public and private stakeholders to ensure equitable distribution and accessibility of secondary schools across Osogbo metropolis.

SPATIAL ANALYSIS OF PHYSICAL ACCESSIBILITY TO PUBLIC PRIMARY HEALTHCARE CENTERS IN KADUNA STATE, NIGERIA

The rising call for spatial justice in the distribution and access to public facilities especially health necessitated this study. The study sets out to assess the spatial patterns of physical accessibility to PPHCs in Kaduna State. Four physical accessibility parameters were used in this study: travel time, travel distance to the nearest Public Primary Healthcare Centers (PPHCs), mean distances between and within PPHCs, and effective geographic catchment area coverage of PPHCs. Both travel time and distance to the nearest PPHC were evaluated using a questionnaire. The mean distance between and within PPHCs for LGAs was estimated from the Nearest Neighbor Analysis. The effective geographic catchment area of a PPHC was determined using the geospatial Thiessen polygon method. Findings showed that 42% of the respondents, live close (< 2 km) to a PPHC facility. The proximity of the respondents from Igabi (52%), Zaria (49%), and Zangon-Kataf (51%) is closer than the other LGAs. Thiessen catchment area showed a wide range of variations with some PPHCs with very large areas (426 -615 km2) mostly found in the central senatorial zone, especially in Birnin Gwari and Chikun LGAs. The most widespread are PPHCs with relatively moderate catchment sizes of (187–339 km2) found across parts of northern, central, and southern senatorial and LGAs. The study concludes that areal and topographic factors as revealed by the polygon-derived catchment areas should also guide the decision for the siting of PPHCs in the state. Hence, additional PPHCs are recommended especially LGAs with extensive land masses.

Road network disruptions during extreme flooding events and their impact on the access to emergency medical services: A spatiotemporal vulnerability analysis

The impact of extreme floods can be significant, affecting humans, the environment and any type of human-built infrastructure. A further consequence of flooding is restricted access to medical facilities, including constraints to access more dedicated emergency medical services (EMS). To date, there has been a lack of investigation into EMS accessibility dynamics during extreme floods. The objective of this study is to gain a deeper understanding of the spatiotemporal changes in accessibility-based vulnerability related to EMS during a representative extreme flood event, which was simulated over a period of six days. The study assesses the spatial accessibility of EMS centres to populations located within 15-, 30-, 45-, and 60-minute travel time thresholds in Canton Bern, Switzerland, and applies floating catchment area method. The dynamic aspects of EMS access vulnerability during extreme floods were assessed in two different ways. Firstly, the ratios between accessibility change and accessibility under normal conditions in 1 km grid cells were calculated at hourly moments, t. Subsequently, the resulting values were used to calculate the average vulnerability score. Secondly, percentage changes of affected populations were evaluated for different accessibility classes during the flood event and under all-time high static flood conditions. Varied spatial patterns of accessibility were generally observed with respect to the road network and population distributions in the hilly and mountainous landscape. Extending evaluations to consider temporal dynamics revealed a complex pattern of accessibility gains and losses in different regions of the study area, including those where no direct flood impacts occurred on the road network. The application of a static, all-time high flood condition resulted in an overestimation of accessibility limits to EMS centres. While this overestimation was not considered to be critical, the application of a spatiotemporal accessibility-based vulnerability analysis method to EMS is considered to be more holistic. Insights from this study can be used to evaluate the effectiveness of EMS risk management plans with respect to evolving extreme flood scenarios.

Iterating Pointers: Enabling Static Analysis for Loop-based Pointers

Pointers are an integral part of C and other programming languages. They enable substantial flexibility from the programmer’s standpoint, allowing the user fine, unmediated control over data access patterns. However, accesses done through pointers are often hard to track, and challenging to understand for optimizers, compilers, and sometimes, even for the developers themselves because of the direct memory access they provide. We alleviate this problem by exposing additional information to analyzers and compilers. By separating the concept of a pointer into a data container and an offset, we can optimize C programs beyond what other state-of-the-art approaches are capable of, in some cases even enabling auto-parallelization. Using this process, we are able to successfully analyze and optimize code from OpenSSL, the Mantevo benchmark suite, and the Lempel–Ziv–Oberhumer compression algorithm. We provide the only automatic approach able to find all parallelization opportunities in the HPCCG benchmark from the Mantevo suite the developers identified and even outperform the reference implementation by up to 18%, as well as speed up the PBKDF2 algorithm implementation from OpenSSL by up to 11x.

Youth mental health care use during COVID-19: Evidence from administrative data in Alberta, Canada

Abstract Background The COVID-19 pandemic affected health care service delivery and accessibility. Our study examined how Canadian youth used mental health services before and during the COVID-19 pandemic, and whether youth access and use patterns differed for subgroups based on social determinants previously associated with health care access. Methods Cross-sectional population-based administrative health care data from the province of Alberta in Canada was used to examine youth (ages 15-24) mental health care use from 2018/19 to 2021/22. Data was analyzed using an interrupted time series design and segmented regression modeling on type of mental health care use. Outcome measures were mental health care use for: general physician visits, psychiatrist visits, emergency department, hospitalization, and different mental health diagnoses. We stratified by factors related to social determinants, including gender and socioeconomic status. Results The analysis indicates an overall increase in the proportion of youth that used mental health care from 2018/19 to 2021/22 (14.4% vs 17.5%, respectively). There was an immediate drop in use with the onset of the COVID-19 pandemic in Canada, followed by a steady rise during the pandemic years, which was largely due to an increase in general physician visits. This rise was seen for most mental health diagnoses of study (i.e., anxiety, adjustment, attention-deficit/hyperactivity disorder, schizophrenia, and self-harm disorders). Service use increased for young women/girls compared to young men/boys and for youth from wealthier neighborhoods. Conclusions This study provides evidence to support health services planning and delivery to respond to the mental health needs of youth and to prepare for future public health emergencies. Key messages • Our study findings indicate changes in health care use for mental health among Canadian youth (ages 15-24) during the COVID-19 pandemic, with use patterns differing for youth subgroups. • Administrative health data can provide evidence to support health services planning and delivery to respond to the mental health needs of youth and to prepare for future public health emergencies.

Understanding the complex chromatin dynamics in primary human neutrophils during PMA-induced NET formation.

Primary human neutrophils play a pivotal role in innate immunity, mainly through the formation of neutrophil extracellular traps (NETs) in a process known as NETosis. This cell-death pathway is crucial for combating infections but is also implicated in many inflammatory diseases, such as sepsis, systemic lupus erythematosus, and rheumatoid arthritis. The study presented here investigates chromatin dynamics during NET formation by stimulating primary human neutrophils with phorbol 12-myristate 13-acetate (PMA). We adapt the ATAC-Seq (assay for transposase-accessible chromatin using sequencing) method to isolated neutrophils and characterize a time-dependent chromatin response. We found that chromatin accessibility patterns are consistent across individual donors and most chromatin changes occur within 30 min, with many continuing across the 90 min assessed in this study. Regulatory regions gaining accessibility were associated with the activity of pathways that have been implicated in NOX-dependent NET formation. Our findings increase the understanding of the chromatin changes underlying NET formation and also identify potential early-acting targets for modulating this process in inflammatory diseases.

Chronic interferon-stimulated gene transcription promotes oncogene-induced breast cancer.

The MRE11 complex (comprising MRE11, RAD50, and NBS1) is integral to the maintenance of genome stability. We previously showed that a hypomorphic Mre11 mutant mouse strain (Mre11 ATLD1/ATLD1 ) was highly susceptible to oncogene-induced breast cancer. Here we used a mammary organoid system to examine which MRE11-dependent responses are tumor-suppressive. We found that Mre11 ATLD1/ATLD1 organoids exhibited an elevated interferon-stimulated gene (ISG) signature and sustained changes in chromatin accessibility. This Mre11 ATLD1/ATLD1 phenotype depended on DNA binding of a nuclear innate immune sensor, IFI205. Ablation of Ifi205 in Mre11 ATLD1/ATLD1 organoids restored baseline and oncogene-induced chromatin accessibility patterns to those observed in WT. Implantation of Mre11 ATLD1/ATLD1 organoids and activation of the oncogene led to aggressive metastatic breast cancer. This outcome was reversed in implanted Ifi205 -/- Mre11 ATLD1/ATLD1 organoids. These data reveal a connection between innate immune signaling and tumor development in the mammary epithelium. Given the abundance of aberrant DNA structures that arise in the context of genome instability syndromes, the data further suggest that cancer predisposition in those contexts may be partially attributable to chronic innate immune transcriptional programs.

LSTM-CRP: Algorithm-Hardware Co-Design and Implementation of Cache Replacement Policy Using Long Short-Term Memory

As deep learning has produced dramatic breakthroughs in many areas, it has motivated emerging studies on the combination between neural networks and cache replacement algorithms. However, deep learning is a poor fit for performing cache replacement in hardware implementation because its neural network models are impractically large and slow. Many studies have tried to use the guidance of the Belady algorithm to speed up the prediction of cache replacement. But it is still impractical to accurately predict the characteristics of future access addresses, introducing inaccuracy in the discrimination of complex access patterns. Therefore, this paper presents the LSTM-CRP algorithm as well as its efficient hardware implementation, which employs the long short-term memory (LSTM) for access pattern identification at run-time to guide cache replacement algorithm. LSTM-CRP first converts the address into a novel key according to the frequency of the access address and a virtual capacity of the cache, which has the advantages of low information redundancy and high timeliness. Using the key as the inputs of four offline-trained LSTM network-based predictors, LSTM-CRP can accurately classify different access patterns and identify current cache characteristics in a timely manner via an online set dueling mechanism on sampling caches. For efficient implementation, heterogeneous lightweight LSTM networks are dedicatedly constructed in LSTM-CRP to lower hardware overhead and inference delay. The experimental results show that LSTM-CRP was able to averagely improve the cache hit rate by 20.10%, 15.35%, 12.11% and 8.49% compared with LRU, RRIP, Hawkeye and Glider, respectively. Implemented on Xilinx XCVU9P FPGA at the cost of 15,973 LUTs and 1610 FF registers, LSTM-CRP was running at a 200 MHz frequency with 2.74 W power consumption.

CONTEXTUAL REANALYSIS OF THE ARCHITECTURAL FORM AND SOCIO-ECONOMIC STATUS OF THE PANAGIA HOUSES AT MYCENAE

The Panagia Houses, one of the building complexes at Mycenae, located to the south-west of the Citadel, were interpreted by the excavators as a group of three independent units. They were constructed and occupied during the Late Helladic (LH) IIIB phase, with two main phases distinguishable in the archaeological record, followed by a reoccupation phase. Careful analysis of the archaeological data published by Mylonas-Shear, which focused on the arrangement of individual units, formality of layout, access and movement patterns, and visibility, suggests that the group should be interpreted rather as a single complex, developed during the period of the maximum expansion of the settlement. The building was gradually expanded to form an extended household, with primary living space surrounded by a number of additional rooms for storage, work and habitation. It was composed of a rectangular main unit, surrounded by an extension formed around a small inner courtyard. The movement between the two levels was organised through a system of connected rooftops, with trapdoors and staircases ensuring access to the various rooms of the complex. During the LH IIIB2 Early phase, Mycenae was hit by a devastating earthquake. Much of the town was left in ruin, but the Panagia Houses were rebuilt, although in a smaller form, with the main unit abandoned and the courtyard inside the extension transformed into the main room of the complex. The status of the complex probably changed, but it was still inhabited by a middle-class family, who possessed a number of valuables and took part in the palatial mobilisation system. The household probably suffered in a widespread fire which destroyed Mycenae at the end of LH IIIB. Its remains were then used as two small dwellings by the survivors of the catastrophe. The history of the complex reflects the changing vicissitudes of the Lower Town of Mycenae.

Methodology to define a static allocation mapping based on memory access patterns and the Signature of MPI applications in HPC systems

Tools to identify problems and improve MPI applications performance running on an HPC system require information from the application and the system. In this work we will focus on defining a methodology to analyze how memory usage affects an MPI application performance running on this HPC system. This methodology will obtain valid and comparable data based on different memory access patterns that will allow defining key performance values used to characterize the HPC system behavior in front of these access patterns and to characterize the Application Signature behavior, (PAS2P Signature that obtains the representative phases of the MPI application) in front of these same access patterns. With these key performance values, we will be able to detect memory access application problems, suggest improvements and define a mapping policy for this application in this HPC system to improve its performance and to determine limits to these improvements.

HybridSA: GPU Acceleration of Multi-pattern Regex Matching using Bit Parallelism

Multi-pattern matching is widely used in modern software for applications requiring high throughput such as protein search, network traffic inspection, virus or spam detection. Graphics Processor Units (GPUs) excel at executing massively parallel workloads. Regular expression (regex) matching is typically performed by simulating the execution of deterministic finite automata (DFAs) or nondeterministic finite automata (NFAs). The natural implementations of these automata simulation algorithms on GPUs are highly inefficient because they give rise to irregular memory access patterns. This paper presents HybridSA, a heterogeneous CPU-GPU parallel engine for multi-pattern matching. HybridSA uses bit parallelism to efficiently simulate NFAs on GPUs, thus reducing the number of memory accesses and increasing the throughput. Our bit-parallel algorithms extend the classical shift-and algorithm for string matching to a large class of regular expressions and reduce automata simulation to a small number of bitwise operations. We have developed a compiler to translate regular expressions into bit masks, perform optimizations, and choose the best algorithms to run on the GPU. The majority of the regular expressions are accelerated on the GPU, while the patterns that exhibit random memory accesses are executed on the CPU in parallel. We evaluate HybridSA against state-of-the-art CPU and GPU engines, as well as a hybrid combination of the two. HybridSA achieves between 4 and 60 times higher throughput than the state-of-the-art CPU engine and between 4 and 233 times better than the state-of-the-art GPU engine across a collection of real-world benchmarks.

Multidimensional patterns of early care and education access through a family centered lens

Despite evidence of the benefits of early care and education (ECE) for child development and family employment, the supply of providers is scarce and variable; leading many families with young children to experience limited and inequitable access. To examine the multidetermined nature of access, this study leverages a multidimensional, family-centered definition and a nationally representative sample of families of preschoolers from the Early Childhood Longitudinal Study – Birth Cohort to examine (1) patterns of access-related features present in preschool-age children's ECE arrangements, and (2) child characteristics, household circumstances, and care setting type that may be related to patterns of access. Latent class analysis model enumeration revealed five latent classes of children's nonparental care arrangements along features of accessibility: High Across Most Access Features (26.4 %), Single, Long-Term Provider (30.1 %), Limited Across Most Access Features (11.6 %), Low Affordability, Multiple Providers (10.1 %), and High Affordability, Recent Transition (21.8 %). These results suggested many children were in ECE that met multiple dimensions of access, with others in care arrangements that reflected trade-offs. Children were also differentially classified into types of ECE arrangements in relation to care setting type, race/ethnicity, income, household urbanicity, and parental employment. The implications of investigating ECE access as a multidimensional construct, and recommendations for how ECE providers and policy can more closely align with family needs are discussed.

Trends in Epidemiologic Characteristics and Clinical Patterns of Vascular Access of Incident Hemodialysis Patients: Nationwide Cohort Study (2006-2019) in Korea

Trends in Epidemiologic Characteristics and Clinical Patterns of Vascular Access of Incident Hemodialysis Patients: Nationwide Cohort Study (2006-2019) in Korea

Definition of regulatory elements and transcription factors controlling porcine immune cell gene expression at single cell resolution using single nucleus ATAC-seq

The transcriptome of porcine peripheral blood mononuclear cells (PBMC) at single cell (sc) resolution is well described, but little is understood about the cis-regulatory mechanism behind scPBMC gene expression. Here, we profiled the open chromatin landscape of porcine PBMC that define cis-regulatory elements and mechanism contributing to the transcription using single nucleus ATAC sequencing (snATAC-seq). Approximately 22 % of the identified peaks overlapped with annotated transcription start sites (TSS). Using clustering based on open chromatin pattern similarity, we demonstrate that cell type annotations using snATAC-seq are highly concordant to that reported for sc RNA sequencing (scRNA-seq). The differentially accessible peaks (DAPs) for each cell type were characterized and the pattern of accessibility of the DAPs near cell type markers across cell types was similar to that of the average gene expression level of corresponding marker genes. Additionally, we found that peaks identified in snATAC-seq have the potential power to predict the cell type specific transcription starting site (TSS). We identified both transcription factors (TFs) whose binding motif were enriched in cell type DAPs of multiple cell types and cell type specific TFs by conducting transcription factor binding motif (TFBM) analysis. Furthermore, we identified the putative enhancer or promoter regions bound by TFs for each differentially expressed gene (DEG) with a DAP that overlapped with its TSS by generating cis-co-accessibility networks (CCAN). To predict the regulators of such DEGs, TFBM analysis was performed for each CCAN. The regulator TF-target DEG pairs predicted in this way were largely consistent with the results reported in the ENCODE Transcription Factor Targets Dataset (TFTD). This snATAC-seq approach provides insights into the regulation of chromatin accessibility landscape of porcine PBMCs and enables discovery of TFs predicted to control DEG through binding regulatory elements whose chromatin accessibility correlates with the DEG promoter region.