Physical Memory Research Articles

Reconfigurable training and reservoir computing in an artificial spin-vortex ice via spin-wave fingerprinting.

Strongly interacting artificial spin systems are moving beyond mimicking naturally occurring materials to emerge as versatile functional platforms, from reconfigurable magnonics to neuromorphic computing. Typically, artificial spin systems comprise nanomagnets with a single magnetization texture: collinear macrospins or chiral vortices. By tuning nanoarray dimensions we have achieved macrospin-vortex bistability and demonstrated a four-state metamaterial spin system, the 'artificial spin-vortex ice' (ASVI). ASVI can host Ising-like macrospins with strong ice-like vertex interactions and weakly coupled vortices with low stray dipolar field. Vortices and macrospins exhibit starkly differing spin-wave spectra with analogue mode amplitude control and mode frequency shifts of Δf = 3.8 GHz. The enhanced bitextural microstate space gives rise to emergent physical memory phenomena, with ratchet-like vortex injection and history-dependent non-linear fading memory when driven through global magnetic field cycles. We employed spin-wave microstate fingerprinting for rapid, scalable readout of vortex and macrospin populations, and leveraged this for spin-wave reservoir computation. ASVI performs non-linear mapping transformations of diverse input and target signals in addition to chaotic time-series forecasting.

Rapidly and Repeatedly Reprogrammable Liquid Crystalline Elastomer via a Shape Memory Mechanism

Realization of muscle-like actuation for a liquid crystal elastomer (LCE) requires mesogen alignment, which is typically achieved/fixed chemically during the synthesis. Post-synthesis regulation of the alignment in a convenient and repeatable manner is highly desirable yet challenging. Here, a dual-phase LCE network is designed and synthesized with a crystalline melting transition above a liquid crystalline transition. The crystalline phase can serve as an "alignment frame" to fix any mechanical deformation via a shape memory mechanism, leading to corresponding mesogen alignment in the liquid crystalline phase. The alignment can be erased by melting, which can be the starting point for reprogramming. This strategy that relies on a physical shape memory transition for mesogen alignment permits repeated reprogramming in a timescale of seconds, in stark contrast to typical methods. It further leads to unusual versatility in designing 3D printed LCE with unlimited programmable actuation modes.

STUDY OF THE INFLUENCE OF DISTANCE FORM OF LEARNING ON THE LIFE ACTIVITIES OF STUDENTS OF PHARMACISTS IN THE CONVENTION OF THE COVID-19 PANDEMIC

Currently, the problem of distance learning covers almost all institutions of higher education in Ukraine. The Ministries of Education of all countries of the world, without exception, are forced to respond quickly to changes in everyday life caused by the pandemic, and make adaptive decisions on the organization of the educational process and the provision of distance learning. Distance education is now seen as the only form of education possible in a pandemic caused by COVID-19. As it is unknown how long we will be in quarantine zones, and the educational process must continue, therefore, it is important to study the impact of distance learning on the lives of higher education in Ukraine in a pandemic. To this end, we conducted a voluntary anonymous survey of 56 domestic full-time students of the Department of Pharmacy of Ivano-Frankivsk National Medical University. Theoretical, empirical and statistical research methods were used during the research.
 The article analyzes the results of online surveys of students on the impact of distance learning on their lives. The results show that half of the students surveyed said that nothing had changed for them in terms of workload during distance learning, more than a third said that the workload had increased significantly, and almost a fifth admitted that the workload during distance learning had become less.
 Most students noted that distance learning had a negative effect on their sleep, they could not organize the daily routine so as to go to bed on time. Almost a third of students said that distance learning had a positive effect on the quality and mode of sleep, due to increased time spent at home. One-fifth said that distance learning did not affect their sleep patterns.
 The majority of respondents noted that distance learning had a positive effect on eating due to being at home and increasing the time for healthy cooking. Instead, a third of respondents said that distance learning did not affect their diet.
 Most pharmacy students reported that their physical activity decreased due to reduced leisure time and limited mobility, and only a few students said that this form of study did not affect their activity. None of the respondents noted an increase in physical activity during distance learning.
 Most respondents voted to impair the ability to memorize all kinds of information, while about one-fifth said that distance learning did not affect the quality of memorization.
 More than half of the students surveyed said that it is much harder to focus on a class that is online than on a regular class. The students noted that they felt significant emotional stress when attending distance learning classes. One third of the students answered that they did not feel any stress.
 Almost half of the respondents consider full-time learning to be the best option, more than a third of students preferred blended learning, while the rest are satisfied with distance learning.
 Three-quarters of the pharmacy students surveyed want to return to their usual routine as soon as possible.
 So, summarizing the above, we can conclude that more than a third of students reported a significant increase in workload and emotional stress when attending distance learning. Most students noted the negative impact of distance learning on physical activity, sleep and memory. Most respondents noted the positive impact of distance learning on their diet. Half of the respondents think that the best way to master the material is full-time education and want to return to the usual mode of study as soon as possible.

The predictive value of preoperative frailty screening for postoperative outcomes in older patients undergoing surgery for non-metastatic colorectal cancer

The predictive value of preoperative frailty screening for postoperative outcomes in older patients undergoing surgery for non-metastatic colorectal cancer

Prospective Associations between Physical Activity and Memory in the Canadian Longitudinal Study on Aging: Examining Social Determinants.

ObjectivesTo examine associations between physical activity (PA) and prospectively assessed memory in a cohort of cognitively healthy adults, after accounting for understudied social determinants.MethodsWe used data from the Canadian Longitudinal Study on Aging (CLSA). PA (exposure) and memory (outcome) were assessed using validated measures in 2013–2015 and 2015–2018, respectively. Respondents reported their daily number of hours spent engaging in five different PAs. We conducted multiple imputation and used linear regression (n = 41,394), adjusting for five categories of covariates: demographics, sensory health characteristics, health behaviors, health status, and social determinants (sex/gender, education, income, social support, perceived social standing, race, and sexual orientation).ResultsIn crude models, nearly every intensity and duration of PA was associated with better memory. In fully adjusted models, protective associations were attenuated; however, some associations held: all durations of walking, most durations of light activities, moderate activities for ≥1 hour, and strenuous activities for 1 to <2 hours.DiscussionSome forms of PA may be associated with better memory. The benefits of higher intensity PA may only be realized after social determinants are addressed.

Distributed Quantized Consensus With Recursive Channel Filters Over Directed Networks

This brief investigates the quantized consensus in discrete-time multi-agent systems over directed networks with limited bandwidths of communication channels and limited capacities of physical memories. A dynamic consensus protocol based on the first-order recursive channel filter is proposed. Several conditions for preserving the asymptotic consensus are obtained, which are dependent on the filter parameters, the sampling period and the topologies of the communication networks. Then, by describing the closed-loop multi-agent system via a higher-order state-space model, the effects of the probabilistic quantization are analyzed. We prove that the quantized consensus is reached under the proposed protocol with quantized communications. Moreover, the distributed PI based protocol is discussed as a special case of the proposed dynamic protocol.

VPipe: A Virtualized Acceleration System for Achieving Efficient and Scalable Pipeline Parallel DNN Training

The increasing computational complexity of DNNs achieved unprecedented successes in various areas such as machine vision and natural language processing (NLP), e.g., the recent advanced Transformer has billions of parameters. However, as large-scale DNNs significantly exceed GPU's physical memory limit, they cannot be trained by conventional methods such as data parallelism. Pipeline parallelism that partitions a large DNN into small subnets and trains them on different GPUs is a plausible solution. Unfortunately, the layer partitioning and memory management in existing pipeline parallel systems are fixed during training, making them easily impeded by out-of-memory errors and the GPU under-utilization. These drawbacks amplify when performing neural architecture search (NAS) such as the evolved Transformer, where different network architectures of Transformer needed to be trained repeatedly. vPipe is the first system that transparently provides dynamic layer partitioning and memory management for pipeline parallelism. vPipe has two unique contributions, including (1) an online algorithm for searching a near-optimal layer partitioning and memory management plan, and (2) a live layer migration protocol for re-balancing the layer distribution across a training pipeline. vPipe improved the training throughput of two notable baselines (Pipedream and GPipe) by 61.4-463.4 percent and 24.8-291.3 percent on various large DNNs and training settings.

Associations of cardiorespiratory fitness and moderate-to-vigorous physical activity with latent cognitive abilities in older adults

It has been demonstrated that physical activity has a small but positive effect on cognition in old age, which suggests that it may be possible to alter the trajectory of age-related cognitive decline. However, our understanding of which aspects of physical activity that are important for modifying cognition remains incomplete. Adopting an exploratory approach in a sample of 115 healthy older adults (65–75 years), the present cross-sectional study used structural equation modelling to investigate the dissociable associations of physical activity (moderate-to-vigorous activity, derived from 7-day accelerometry) and cardiorespiratory fitness (VO2 max, derived from maximal treadmill ergometer test) with multiple latent cognitive abilities (working memory, episodic memory, spatial and verbal reasoning). The results showed a significant positive association between fitness and working memory, when physical activity was statistically controlled for, and a positive association of similar point magnitude between physical activity and episodic memory, when fitness was statistically controlled for, although the latter association did not reach statistical significance. The results add to the foundation for a more careful investigation of the dissociable associations of moderate-to-vigorous physical activity and fitness with cognition in old age, and encourages future research to test the hypothesis that cardiorespiratory fitness benefits working memory via general cerebrovascular effects on grey matter volume, whilst moderate-to-vigorous physical activity benefits episodic memory via effects on neuroplastic processes.

Dynamics of Information Erasure and Extension of Landauer's Bound to Fast Processes.

Using a double-well potential as a physical memory, we study with experiments and numerical simulations the energy exchanges during erasure processes, and model quantitatively the cost of fast operation. Within the stochastic thermodynamics framework we find the origins of the overhead to Landauer's bound required for fast operations: in the overdamped regime this term mainly comes from the dissipation, while in the underdamped regime it stems from the heating of the memory. Indeed, the system is thermalized with its environment at all times during quasistatic protocols, but for fast ones, the inefficient heat transfer to the thermostat is delayed with respect to the work influx, resulting in a transient temperature rise. The warming, quantitatively described by a comprehensive statistical physics description of the erasure process, is noticeable on both the kinetic and potential energy: they no longer comply with equipartition. The mean work and heat to erase the information therefore increase accordingly. They are both bounded by an effective Landauer's limit k_{B}T_{eff}ln2, where T_{eff} is a weighted average of the actual temperature of the memory during the process.

Physical Activity and Memory Function among Older Adults in Lebanon: Differences by Sex and Rural-Urban Living

Introduction: The increase in the population of 60 years and above has led to an increase in dementia. Middle East and North Africa region (MENA) has one of the highest prevalence of dementia. One of the factors revealing promising results in reducing the burden of dementia, yet not researched in MENA and in other parts of the world, is physical activity. Objective: We aimed to assess the association between subjective and objective physical activity, and memory recall of older adults with no dementia in Lebanon. We also investigated the moderating effect of sex and place of residence on this association. Methods: This is a secondary data analysis of a cross-sectional study conducted in 2013 on a community of 502 older adults 65 years of age and above, selected randomly from two areas, Lebanon’s capital, Beirut, and Mount Lebanon. After excluding those who had dementia diagnoses and who did not have data on physical activity, the eligible sample was 459 persons. Physical activity was assessed by three indicators: physical activity perception, walking half a kilometer, and 2-minute step test (2MST). Memory recall, defined as episodic memory, was measured using a 10-word list-learning test with two outcomes: immediate and delayed. Regression models were performed adjusting for cluster effect. Additionally, associations between main exposures and memory recall were stratified by sex and rural/urban residence at the univariate and multivariate levels. Results: The findings of this study revealed that the three measures of physical activity were significantly associated with higher memory function, at a significance level of 0.05. The data demonstrated that sex and place of residence did not modify the association between physical activity measures and immediate and delayed memory recall. Conclusion: Physical activity of older adults should be promoted for a variety of health reasons including improvement of memory recall. Further research is needed to determine the long-term impact on the relationship between physical activity and episodic memory.

TrustSAMP: Securing Streaming Music Against Multivector Attacks on ARM Platform

Streaming music has dominated the digital music industry in recent years, which allows users to enjoy a huge music library online with a low subscription price. Terminal-side audio DRM (Digital Right Management) is very critical for streaming music industry, compromising of which will cause unrestricted listening, dumping and unauthorized secondary distribution. However, existing DRM protection schemes mainly focus on defeating software attacks but lack complete shielding against the physical memory disclosure attacks, which may even be launched by the owner of the terminal device. In this paper, we propose a terminal-side audio DRM solution called TrustSAMP to protect the copyrighted audio data against both software attacks and physical memory disclosure attacks. The basic idea is to process the audio data plaintext only in certain on-SoC components secured by ARM TrustZone. To minimize the TCB (Trusted Computing Base) of the secure world, we separate the control flow and the data flow of the Linux audio subsystem and port only the codes used for audio data decryption and plaintext transfer into the secure world. Moreover, we leave most driver codes of the audio-associated on-SoC components in the rich OS (i.e., in the normal world), and introduce a tiny proxy in the secure world to control the associated registers according to the requests from the normal-world drivers. The prototype implemented on real hardware shows that TrustSAMP can play a variety of wav-format audio with very small overhead and negligible loss of audio quality.

Memory Optimization System for SGXv2 Trusted Execution Environment

PDF HTML XML Export Cite reminder Memory Optimization System for SGXv2 Trusted Execution Environment DOI: 10.21655/ijsi.1673-7288.00287 Author: Affiliation: Clc Number: Fund Project: Article | Figures | Metrics | Reference | Related | Cited by | Materials | Comments Abstract:Trusted Execution Environment (TEE) is an architectural solution for secure computing that requires confidentiality and integrity for private data and code. In recent years, TEE has become the research hotspot for machine learning privacy protection, encrypted database, blockchain security, etc. This paper addresses the performance problem of the system under this new trusted hardware. We analyze the performance of the new trusted hardware, i.e., Intel SGXv2. We find that the paging overhead in SGXv1 is no longer the main issue in SGXv2 under the premise of configuring large secure memory. However, the setup of large secure memory leads to two new problems. First, the available range of normal memory is narrowed down, which increases the memory pressure of normal applications, especially big data applications. Second, secure memory is usually underutilized, resulting in low overall physical memory utilization. To solve the above problems, this paper proposes a new lightweight code migration approach, which dynamically migrates the code of normal applications into secure memory, while leaving the data in place. The migrated code can use secure memory and avoid the drastic performance degradation caused by disk swapping. Experimental results show that the proposed approach can reduce the runtime overhead of normal applications by 73.2\% to 98.7\% without affecting the isolation and the use of secure applications. Reference Related Cited by

Understanding Ransomware Actions Through Behavioral Feature Analysis

Crypto ransomware attacks have substantially increased in recent years, and owing to their highly profitable&nbsp; nature, this growth will evidently escalate in the future. To better understand this malware and help developers of ransomware detection systems build more robust and reliable solutions, this study investigates ransomware actions during the destruction phase through behavioral feature analysis. We used a dataset with 1524 samples and 30 967 features representing the actions conducted using 582 types of ransomware and 942 good applications (goodware). Six representative and widely used classification algorithms were applied as auxiliary tools to investigate the behavior of these attacks: Naive Bayes (NB), K-Nearest Neighbors (KNN), Logistic Regression (LR), Random Forest (RF), Stochastic Gradient Descent (SGD), and Support Vector Machine (SVM). We achieved an accuracy of 98.48%, balanced accuracy of 98.35%, precision of 98.17%, recall of 97.82%, F-measure of 97.98%, and ROC AUC of 99.87% by using RF for 462 features of the resultant dataset. We propose a new criterion to determine the feature group relevance and a method to distinguish the features that are most related to ransomware and goodware. Our main conclusions are as follows: Application Programming Interface (API) calls are the most relevant feature group, achieving alone a balanced accuracy of 96.49%; native encryption Windows APIs are not crucial for ransomware classification; and the most significant features of ransomware tend to involve handling the thread/process, physical memory operation, and communication, whereas goodware features are more likely to indicate virtual memory, files, directories, and resource operations.

ThermalBleed: A Practical Thermal Side-Channel Attack

Modern OSs expose an interface for monitoring CPU temperature to unprivileged users for effective user decision-based thermal management. Due to the low sampling rate and resolution, thermal sensors have generally been restricted to the construction of covert channels. However, exposing the thermal interface to unprivileged users may be problematic, because the heat emission inside a CPU core is affected by program execution on the core; an attacker may be able to infer the secret information of the program by exploiting the thermal interface as a side-channel. In this paper, we extensively analyze digital thermal sensors in Intel CPUs and show that it is possible to implement a software-based thermal side-channel attack. Specifically, by analyzing some properties of the thermal sensors, we inferred that the thermal sensor makes it possible to distinguish between a cache hit and a physical memory access in memory load operations. Based on the analysis results, we implement ThermalBleed, a thermal side-channel attack that breaks kernel address space layout randomization (KASLR) in Linux systems. Moreover, by conducting an in-depth analysis, we identify useful hidden properties of the Intel thermal sensors. Our analysis establishes a stepping stone to build a more precise and effective thermal side-channel attack in the future. To the best of our knowledge, this is the first work that extends a thermal covert channel to a practical side-channel attack by exploring the properties of Intel digital thermal sensors.

Physical Memory of Astrocytes

Physical Memory of Astrocytes

Effect of Dietary Habits on Mental and Physical Health: A Systemic Review

Mental and physical health issues have increased over the past few decades. Individual’s lifestyle, environment, dietary habits, physical and mental fitness are associated with each other. Generally, youngsters adopt unhealthy dietary habits, such as poor diet, little or no milk intake, meal skipping, preference for energy dense over nutrient dense diet, and inadequate intake of vegetables and fruits. During their university life, students face many changes including poor dietary choices, study stress, anxiety, depression, food insecurity, skipping meals, poor fruit and milk consumption. All of this may lead to many chronic diseases later in life. Processed food causes a lot of health issues. Individuals are more susceptible to irritable bowel syndrome, liver disorders, and amenorrhea due to unhealthy dietary consumption. For this reason, moderation in diet is necessary. A well-balanced nutritious diet consists of five food groups including whole-grains, milk, fruits and vegetables, meat and nuts, and oil which lower disease risk and increase the lifespan. Body size idealism is also the lead cause of eating disorder, especially among teenage girls. The objective of this study was to overview the association of dietary habits with the physical and mental health of people by analyzing the findings of previously published literature. Poor dietary choices and habits lead to poor physical health, classroom performance, and memory retention. It also leads to psychological issues, such as anxiety and depression.

The prospective association between physical activity and memory in the Canadian Longitudinal Study on Aging (CLSA)

AbstractBackgroundPhysical activity is a recommended health behaviour and there exists a literature base linking physical activity and cognition in mid‐life and older adulthood. Yet, longitudinal study of physical activity and cognition is needed in order to account for determinants of health which may affect participation in physical activity and attenuate previously observed relationships. The aim of this study was to examine the longitudinal relationship between different intensities of physical activity and memory at first three‐year follow‐up in a large prospective survey of Canadian adults.MethodData were drawn from the Canadian Longitudinal Study of Aging (CLSA), an ongoing prospective cohort study. Participants self‐reported a number of health behaviours, health‐professional diagnosed conditions, and social and demographic factors. Physical activity was measured using the Physical Activity Scale for the Elderly (PASE). Past‐week activity was classified according to type of intensity (e.g., strenuous) and duration (e.g., minutes [mins] and hours [hrs]). Memory was assessed using the Rey Auditory Verbal Learning Test, with higher scores reflective of better memory performance. We used linear regression modelling to examine associations between physical activity at baseline and memory three‐years later, after adjustment for an array of potential confounders.ResultIn fully adjusted models, the pattern of findings across type of activity and duration was mixed. We observed a protective relationship of physical activity at some levels of walking (30mins to &lt;1 hr: b= 0.14, p=0.021, 1hr to &lt;2 hrs: b= 0.14, p=0.029), light activity (1hr to &lt;2 hrs: b= 0.17, p=0.035, 2 hours or more: b= 0.15, p=0.050), moderate activity (1hr to &lt;2 hrs: b= 0.38, p&lt;0.001, 2 hours or more: b= 0.35, p&lt;0.001), and strenuous activity (1hr to &lt;2 hrs: b= 0.18, p=0.004). No prospective relationships were observed for strength‐based activities.ConclusionCertain types of physical activity were associated with better memory at follow‐up. On average, activities within the 1 to 2 hour range were most beneficial. Potential benefits of physical activity on memory may only be realized after other health considerations are first considered.

Physical Activities and its Effect on memory of The Elderly

Background: Physical activity generally refers to movement that enhances health. Any body movement that works muscles and requires more energy than resting. Aim: the study aimed to assess physical activity and its effect on memory of the elderly Research design: Descriptive analytic design was utilized in this study. Settings: The study was conducted in Geriatric home at Suez Canal University. Subjects: A convenient sample of 60 older adults, from the previous setting at age 60 or higher, without cognitive impairments. Tools of data collection: First tool: Interviewing questionnaire, it was composed of 4 parts, part one: socio-demographic data, part two: Medical history, and nutritional style. Part three: Assess elderly's knowledge regarding to physiological changes, physical activity, and exercise. Part four: Assess elderly's practice regarding to physical activities, and exercise. Second tool: Observational checklist, it was composed of 4 parts, Part one: Assess elderly's general health. Part two: Assess elderly's activities of daily living. Part three: Assess elderly's mini mental state. Results: Regarding to elderly' knowledge, the current study shows that, all 100.0% of the elderly had unsatisfactory knowledge regarding physiological changes, importance of physical activity, exercise, and memory. The present study also shows that, all 100.0% of the elderly had poor practice of physical activity. The current study represents that, few 2.9% of the elderly had poor practice, around one fifth 15.7% had average practice, majority 81.4% had good practice of activity of daily living, and no one of the elderly had stupor, one third 34.3% had drowsy, and two thirds 65.7% had alert of mini mental state. Conclusion: Elderly in the current study lacked appropriate knowledge, practices, activity of daily living, and mini mental state were mostly unsatisfactory. Recommendations: Health team member should be planning and implemented several health educational programs regarding physical activities, which types of eating and drinks that enhancing memory and brain function for elderly people in geriatric home, Conducting physical activity programs for older persons that can be safe, effective in community settings, and low cost therapeutic approach, and members of health team should be planning and implemented several health educational programs regarding physical activities, which types of eating and drinks that enhancing memory and brain function for elderly people in geriatric home

Unified Holistic Memory Management Supporting Multiple Big Data Processing Frameworks over Hybrid Memories

To process real-world datasets, modern data-parallel systems often require extremely large amounts of memory, which are both costly and energy inefficient. Emerging non-volatile memory (NVM) technologies offer high capacity compared to DRAM and low energy compared to SSDs. Hence, NVMs have the potential to fundamentally change the dichotomy between DRAM and durable storage in Big Data processing. However, most Big Data applications are written in managed languages and executed on top of a managed runtime that already performs various dimensions of memory management. Supporting hybrid physical memories adds a new dimension, creating unique challenges in data replacement. This article proposes Panthera, a semantics-aware, fully automated memory management technique for Big Data processing over hybrid memories. Panthera analyzes user programs on a Big Data system to infer their coarse-grained access patterns, which are then passed to the Panthera runtime for efficient data placement and migration. For Big Data applications, the coarse-grained data division information is accurate enough to guide the GC for data layout, which hardly incurs overhead in data monitoring and moving. We implemented Panthera in OpenJDK and Apache Spark. Based on Big Data applications’ memory access pattern, we also implemented a new profiling-guided optimization strategy, which is transparent to applications. With this optimization, our extensive evaluation demonstrates that Panthera reduces energy by 32–53% at less than 1% time overhead on average. To show Panthera’s applicability, we extend it to QuickCached, a pure Java implementation of Memcached. Our evaluation results show that Panthera reduces energy by 28.7% at 5.2% time overhead on average.

Biostable Shape Memory Polymer Foams for Smart Biomaterial Applications

Polyurethane foams provide a wide range of applications as a biomaterial system due to the ability to tune their physical, chemical, and biological properties to meet the requirements of the intended applications. Another key parameter that determines the usability of this biomaterial is its degradability under body conditions. Several current approaches focus on slowing the degradation rate for applications that require the implant to be present for a longer time frame (over 100 days). Here, biostable shape memory polymer (SMP) foams were synthesized with added ether-containing monomers to tune the degradation rates. The physical, thermal and shape memory properties of these foams were characterized along with their cytocompatibility and blood interactions. Degradation profiles were assessed in vitro in oxidative (3% H2O2; real-time) and hydrolytic media (0.1 M NaOH; accelerated) at 37 °C. The resulting foams had tunable degradation rates, with up 15% mass remaining after 108 days, and controlled erosion profiles. These easy-to-use, shape-filling SMP foams have the potential for various biomaterial applications where longer-term stability without the need for implant removal is desired.