Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting Changes in User Preferences using Hidden Markov Models for Sequential Recommendation Tasks

Recommender systems help users find relevant items of interest based on the past preferences of those users. In many domains, however, the tastes and preferences of users change over time due to a variety of factors and recommender systems should capture these dynamics in user preferences in order to remain tuned to the most current interests of users. In this work we present a recommendation framework based on Hidden Markov Models (HMM) which takes into account the dynamics of user preferences. We propose a HMM-based approach to change point detection in the sequence of user interactions which reflect significant changes in preference according to the sequential behavior of all the users in the data. The proposed framework leverages the identified change points to generate recommendations in two ways. In one approach change points are used to create a sequence-aware non-negative matrix factorization model to generate recommendations that are aligned with the current tastes of user. In the second approach the HMM is used directly to generate recommendations taking into account the identified change points. These models are evaluated in terms of accuracy of change point detection and also the effectiveness of recommendations using a real music streaming dataset.
MeDI: Measurement-based Device Identification Framework for Internet of Things

IoT systems may provide information from different sensors that may reveal potentially confidential data, such as a person’s presence or not. The primary question to address is how we can identify the sensors and other devices in a reliable way before receiving data from them and using or sharing it. In other words, we need to verify the identity of sensors and devices. A malicious device could claim that it is the legitimate sensor and trigger security problems. For instance, it might send false data about the environment, harmfully affecting the outputs and behavior of the system. For this purpose, using only primary identity values such as IP address, MAC address, and even the public-key cryptography key pair is not enough since IPs can be dynamic, MACs can be spoofed, and cryptography key pairs can be stolen. Therefore, the server requires supplementary security considerations such as contextual features to verify the device identity. This paper presents a measurement-based method to detect and alert false data reports during the reception process by means of sensor behavior. As a proof of concept, we develop a classification-based methodology for device identification, which can be implemented in a real IoT scenario.
Podejmowanie decyzji o oszczędzaniu długookresowym – perspektywa ekonomiczna i behawioralna

który może owocować unikaniem tematu starości i emerytury, a w efekcie unikaniem jakichkolwiek informacji w tym zakresie oraz zaniechaniem podejmowania działań, aby się na ten okres życia zabezpieczyć. Summary: Recent pension forecasts are more than distressing, so economically active people should seek additional strategies to secure an adequate standard of living in their post-retire-ment period of life. However, the research indicates a low level of Poles’ retirement awareness. It is manifested in the fact that, in spite of having knowledge about the risk of receiving low pensions, as well as having the opportunity to save, Poles still do not do it. The aim of the article is to present both theoretical and empirical achievements of behavioral economics in the scope of long-term savings decision making. A number of psychological factors that can affect the low propensity to save is presented. Moreover, the article describes the phenomenon of “retirement anxiety”, which, in turn, may cause the desire to avoid the subject of old age and retirement, and as a result, to avoid any information and action to protect this period of life.
Conformational Dynamics in the Core of Human Y145Stop Prion Protein Amyloid Probed by Relaxation Dispersion NMR.

Microsecond to millisecond timescale backbone dynamics of the amyloid core residues in Y145Stop human prion protein (PrP) fibrils were investigated by using 15 N rotating frame (R1ρ ) relaxation dispersion solid-state nuclear magnetic resonance spectroscopy over a wide range of spin-lock fields. Numerical simulations enabled the experimental relaxation dispersion profiles for most of the fibril core residues to be modelled by using a two-state exchange process with a common exchange rate of 1000 s-1 , corresponding to protein backbone motion on the timescale of 1 ms, and an excited-state population of 2 %. We also found that the relaxation dispersion profiles for several amino acids positioned near the edges of the most structured regions of the amyloid core were better modelled by assuming somewhat higher excited-state populations (∼5-15 %) and faster exchange rate constants, corresponding to protein backbone motions on the timescale of ∼100-300 μs. The slow backbone dynamics of the core residues were evaluated in the context of the structural model of human Y145Stop PrP amyloid.
And then there were none: a stall-free real-time garbage collector for reconfigurable hardware

1. 引言 处理器频率增长时代的终结已经驱使着架构师和开发 人员追求并行性以实现性能的提升, 但是, 通用的 多指令多数据流并行技术较低效, 并且功耗极高, 功率很快成为限制因素。 鉴于此方面的局限性, 业 界为追求性能开始采用非传统芯片架构如 GPU, 以 及其他更激进的硬件架构。 其中最激进的计算平台 是以现场可编程门阵列 (FPGA) 为形式出现的可重构 硬件。 目前 FPGA 可带有超过一百万个可编程逻辑单 元, 以及 8MB 的片上 “RAM 内存块”, 依靠这 些优势, 其可提供极高的比特级并行性, 以及可在 单周期内访问片上内存的能力。 而且, 由于内存是 按 36Kb 为单位分布在芯片上, 因此潜在的内部带宽 非常宽。 但是, 适合 FPGA 的编程技术却是滞后于它们的 容量, 这样就降低了这种硬件架构的适用性, 使其 难以用于通用计算应用。 而此领域共同的语言仍然是 硬件描述语言 (VHDL 及 Verilog), 这些语言仅提供限 于比特、 比特阵列、 寄存器、 数据线等等的抽象。 而整个对这类硬件进行编程的方法是以可重构的芯片 综合为中心的, 不同于通用设备编程方法。 最近的研究专注于将这类硬件编程语言的抽象等 级和可编程性提高到用于软件的高级编程语言 ( 如基 于 Scala 的 Chisel 框架语言 、 基于 C# 的 Kiwi 项 目 10 以及 Liquid Metal 项目 ( 该项目以 Java 为基础 开发了 Lime 语言 )) 的水平。 但是, 到目前为止, 无论程序员们是用低级的硬件描述语言还是高级语言 如 Chisel 和 Lime 进行编程, 对动态内存管理技术 使用的探索才只是刚刚开始 8, , 并且业界还没有使 用垃圾收集技术。 在本文中, 我们提出了一种直接与硬件综合的 垃圾收集器, 其可以完全并行的方式收集大量的统 一对象。 这些统一对象堆 ( 迷你对象堆 ) 完全由固 定大小的对象组成。 因此, 每个对象的数据字段 大小及指针位置都是固定的。 为了在收集器性能上 获得较大提升, 我们牺牲了内存布局上的一些灵活 性。 而在 FPGA 领域, 这种牺牲是有意义的: 由 于 FPGA 架构中内存采用分布式布局, 因此采用流 水线设计是常用的做法, 在这类设计中, 流水线每 级都保留了其自己的内部数据结构, 这些数据结构 能与其他流水线级并行访问其局部 RAM 模块。 而 且, 由于利用固定的数据布局可开发出每个时钟循 环处理一个作业的设计, 因此这种数据布局就带来 了性能上的数量级提升。 在算法上, 我们的收集器是一种采用了 Yuasa 风 格 snapshot-at-the-beginning (初始快照) 算法的 收集器 , 带有线性清扫功能。 利用诸如双端口内 存硬件结构、 以及在单个循环内同时读写寄存器和在 整个系统中原子地发布控制信号的能力, 我们能开发 出一种永远不会与应用程序相干扰的收集器。 而且, 应用程序能在单个时钟周期内访问内存。 仲裁电路会 优先考虑应用程序的操作, 而将收集器某些操作延迟 一个时钟周期, 但是即使在应用程序每个时钟周期执 行一个内存操作时 ( 但内存分配只能隔一个周期执行 一次 ), 收集器也能保持与应用程序的同步。 我们的无延迟收集器可直接与采用硬件描述语言 手写的程序一起使用。 另外, 其也可以作为包括动 态内存分配在内的高级语言 3, 10 系统使用的硬件 “运 行时系统” 的一部分。 为了进行评估, 我们实现 了采用停止一切操作 (stop-the-world) 方法的收集器 的变体以及 malloc/free 式系统。 通过使用一个需频 繁进行内存分配的应用程序, 我们对三种收集器在 内存使用率、 时钟频率、 吞吐量 ( 周期数和物理时 间 ) 和应用程序延迟方面的性能进行了比较。 另外, 我们还提出了无延迟实时性能所需最小堆大小的封闭 式最差情况界, 对这些边界值, 我们进行了实际验 证。 进一步的详细信息, 如该收集器的功耗和额外 基准测试, 可于原始论文中获得。 6
A Preliminary Study about the Music Influence on EEG and ECG Signals

In this work, music is used to elicit emotions and the impact produced by it on the electrocardiogram and electroencephalogram signals is measured. Test consists a sequence of 12 songs where each one is played during 1 minute. Songs were grouped in 4 sets based on pleasant/activation level. In this preliminary study, 6 male subjects realized the trial. Individuals scored each song using Self-Assessment Manikin (SAM) survey. Biosignal parameters were analyzed with Kruskal-Wallis test (KWT). Although the sample of the subjects on whom the test was performed is small, significant variation is observed in 3 parameters extracted from the electrocardiogram when features are grouped using SAM values from survey filled in by subjects. These parameters show an increasing of heart rate with arousal level and when songs are not totally matched with individual preferences. The use of information extracted from biosignals in therapies for individuals with low interaction is proposed for future studies.
CHET: Compiler and Runtime for Homomorphic Evaluation of Tensor Programs

Fully Homomorphic Encryption (FHE) refers to a set of encryption schemes that allow computations to be applied directly on encrypted data without requiring a secret key. This enables novel application scenarios where a client can safely offload storage and computation to a third-party cloud provider without having to trust the software and the hardware vendors with the decryption keys. Recent advances in both FHE schemes and implementations have moved such applications from theoretical possibilities into the realm of practicalities. This paper proposes a compact and well-reasoned interface called the Homomorphic Instruction Set Architecture (HISA) for developing FHE applications. Just as the hardware ISA interface enabled hardware advances to proceed independent of software advances in the compiler and language runtimes, HISA decouples compiler optimizations and runtimes for supporting FHE applications from advancements in the underlying FHE schemes. This paper demonstrates the capabilities of HISA by building an end-to-end software stack for evaluating neural network models on encrypted data. Our stack includes an end-to-end compiler, runtime, and a set of optimizations. Our approach shows generated code, on a set of popular neural network architectures, is faster than hand-optimized implementations.
Computerized Tomography–Based Morphometric Analysis of Subaxial Cervical Spine Pedicle in Asymptomatic Indian Population

ABSTRACT Background: The purpose of this study was to analyze morphometry of the subaxial cervical spine pedicles in an Indian population based on computed tomography (CT), and thus assess the safety and feasibility of cervical pedicle screw in the subaxial cervical spine. Methods: CT scans of 500 subaxial cervical spine vertebrae were analyzed from 100 patients presenting to our institution and undergoing cervical spine CT scan for an unrelated cause as part of ATLS protocol. Pedicle width (PW), pedicle axis length (PAL), pedicle transverse angulation (PTA), and lateral pedicle distance (LPD) were calculated on axial CT scans, and pedicle height (PH), pedicle length (PL), superior pedicle distance (SPD), and pedicle sagittal angulation (PSA) were calculated on sagittal CT scans. Results: The mean PW ranged from 4.3 mm at C3 to 5.7 mm at C7. Mean PH ranged from 5.5 mm at C3 to 6.1 mm at C7. Mean PTA ranged from 44.5° at C3 to 37.1° at C7. PSA ranged from 16.65° at C3 to 3.29° at C7. Mean LPD ranged from 1.6 mm at C3 to 3.4 mm at C6. Mean SPD ranged from 3.5 mm at C3 to 1.15 mm at C7. Mean PAL ranged from 29.6 mm at C3 to 33.04 mm at C7. Mean PL ranged from 5.2 mm at C3 to 5.78 mm at C7. Conclusions: Our CT-based morphometric study confirms that cervical pedicle screw placement is possible in most of the Indian population except at C3 in females. A thorough understanding of pedicle anatomy with proper CT-based preoperative planning can mitigate the risk associated with pedicle screw placement in subaxial cervical spine.
OpenSpace: Bringing NASA Missions to the Public

This viewpoint presents OpenSpace, an open-source astrovisualization software project designed to bridge the gap between scientific discoveries and their public dissemination. A wealth of data exists for space missions from NASA and other sources. OpenSpace brings together this data and combines it in a range of immersive settings. Through non-linear storytelling and guided exploration, interactive immersive experiences help the public to engage with advanced space mission data and models, and thus be better informed and educated about NASA missions, the solar system and outer space. We demonstrate this capability by exploring the OSIRIS-Rex mission.
Collaborative target-tracking control using multiple autonomous fixed-wing UAVs with constant speeds: Theory and experiments

This paper considers a collaborative tracking control problem using a group of fixed-wing UAVs with constant and non-identical speeds. The dynamics of fixed-wing UAVs are modelled by unicycle-type equations, with nonholonomic constraints by assuming that UAVs fly at constant attitudes in the nominal operation mode. The control focus is on the design of a collective tracking controller such that all fixed-wing UAVs as a group can collaboratively track a desired target's position and velocity. We construct a reference velocity that includes both the target's velocity and position as feedback, which is to be tracked by the group centroid. In this way, all vehicles' headings are controlled such that the group centroid follows a reference trajectory that successfully tracks the target's trajectory. We consider three cases of reference velocity tracking: the constant velocity case, the turning velocity case with constant speed, and the time-varying velocity case. An additive spacing controller is further devised to ensure that all vehicles stay close to the group centroid trajectory. Trade-offs and performance limitations of the target tracking control due to the constant-speed constraint are also discussed in detail. Experimental results with three fixed-wing UAVs tracking a target rotorcraft are shown to validate the effectiveness and performance of the proposed tracking controllers.
VALIDITY AND RELIABILITY OF THE FITBIT FLEX™ AND ACTIGRAPH GT3X+ AT JOGGING AND RUNNING SPEEDS.

Background Monitoring levels of physical activity, as an outcome or in guiding rehabilitation, is challenging for clinicians. Personal activity monitors are increasing in popularity and provide potential to enhance rehabilitation protocols. However, research to support the validity and reliability of these devices at jogging and running speeds is limited. Purpose The purpose of this study was to evaluate the validity of the Fitbit Flex™ and ActiGraph GT3X + for measuring step count at jogging and running speeds. A secondary purpose was to examine inter-device reliability of the Fitbit Flex™. Study Design Cross-sectional study. Methods Thirty healthy participants aged between 19 and 50 years, completed a treadmill protocol at jogging and running speeds (8 km/h to 16 km/h). Treadmill speed was progressively increased by intervals of 2 km/h. Each interval was four minutes in duration with a two minute rest period between stages. Participants were encouraged to continue through the graded exercise test until they reached the maximum running speed that they felt they could maintain for four minutes. Step count data was collected for Fitbit Flex™ devices and the ActiGraph GT3X+. Video analysis of step count was used as the criterion measure. Results At speeds of 8 to 14 km/h Mean Absolute Percentage Errors were ≤1% for the Fitbit Flex™ and the ActiGraph GT3X + when compared to step count via video analysis. Standard Error of Measurement between the three Fitbit Flex™ devices was ≤ 7 steps for speeds of 8 to 14 km/h and varied between 9 to 19 steps at 16 km/h. Fitbit Flex™ devices showed good to excellent between device reliability at speeds of 8 to14 km/h (ICC 0.723 to 0.999; p ≤ 0.001). Greater variability was evident with the low participant numbers at 16 km/h (ICC 0.527 to 0.896; p ≥ 0.02). Conclusion Both the Fitbit Flex™ and the ActiGraph GT3X + provide a valid account of steps taken at jogging and running speeds up to 14 km/hr, attainable by non-elite runners on a treadmill. Fitbit Flex™ devices provide equivalent step count output to each other, enabling comparison between devices during treadmill jogging and running. Level of evidence 2b.
A Comparative Analysis of Algorithmic Music Generation on GPUs and FPGAs

The authors in this paper aim towards comparing the efficiency of Music Generation with Recurrent Neural Networks on GPUs and FPGAs. A more common approach towards Deep Learning has always been the GPUs. However, FPGAs are a new addition to the field of deep learning computations. This paper is aimed at the developing a deep learning module based on Recurrent Neural Networks for algorithmic music generation. It therefore, compares the efficiency of this algorithm on FPGAs and GPUs for finding the best suitable hardware for obtaining maximum efficiency (Abstract)
Selective Harmonic Measurement and Compensation Using Smart Inverters in a Microgrid with Distributed Generation

This paper presents a frequency domain selective harmonic measurement and compensation using smart inverters (SIs) applied to a microgrid with distributed generation. The compensation current is calculated by a main processing unit (MPU), which controls the compensation action of each distributed generation unit (DGU) connected to the microgrid. A single fast Fourier transform (FFT) is implemented to obtain the frequency spectra of the power grid voltages and the currents consumed by the connected loads. Based on the calculated compensation currents and the availability of the DGUs, the MPU establishes the harmonic orders that each DGU should compensate, aiming to equalize the rms current values among the different DGUs. The proposed approach intends to optimize the DGUs efficiency in the microgrid and, additionally, it allows the connection of the converters to the power grid without the need for a synchronization algorithm. A comprehensive description of the implemented FFT algorithm is performed and, finally, the operation of the proposed scheme is verified by simulation results.
Modeling the role of fomites in a norovirus outbreak

Abstract Norovirus accounts for a large portion of the gastroenteritis disease burden, and outbreaks have occurred in a wide variety of environments. Understanding the role of fomites in norovirus transmission will inform behavioral interventions, such as hand washing and surface disinfection. The purpose of this study was to estimate the contribution of fomite-mediated exposures to infection and illness risks in outbreaks. A simulation model in discrete time that accounted for hand-to-porous surfaces, hand-to-nonporous surfaces, hand-to-mouth, -eyes, -nose, and hand washing events was used to predict 17 hr of simulated human behavior. Norovirus concentrations originated from monitoring contamination levels on surfaces during an outbreak on houseboats. To predict infection risk, two dose-response models (fractional Poisson and 2F1 hypergeometric) were used to capture a range of infection risks. A triangular distribution describing the conditional probability of illness given an infection was multiplied by modeled infection risks to estimate illness risks. Infection risks ranged from 70.22% to 72.20% and illness risks ranged from 21.29% to 70.36%. A sensitivity analysis revealed that the number of hand-to-mouth contacts and the number of hand washing events had strong relationships with model-predicted doses. Predicted illness risks overlapped with leisure setting and environmental attack rates reported in the literature. In the outbreak associated with the viral concentrations used in this study, attack rates ranged from 50% to 86%. This model suggests that fomites may have accounted for 25% to 82% of illnesses in this outbreak. Fomite-mediated exposures may contribute to a large portion of total attack rates in outbreaks involving multiple transmission modes. The findings of this study reinforce the importance of frequent fomite cleaning and hand washing, especially when ill persons are present.
A 15GHz GaAs HEMT low noise amplifier

This electronic document is a “live” template. The design and simulated performance of a two-stage GaAs HEMT ‘low noise amplifier (LNA)’ designed for 5G communication with an operating frequency of 15GHz have been described in this paper. The 3dB gain bandwidth of the LNA was 2.4GHz which was from 14.86GHz to 17.26GHz. The best gain of the LNA was 24.76dB at 15GHz. The ‘noise figure (NF)’ at 15GHz was 3.2dB with the average noise figure throughout the band being 3.1dB. The S11 and S22 of the amplifier were −17.78dB and −46.59dB respectively at 15GHz. The S12at 15GHz was −28.63dB. The design and simulation of the single stage, as well as the two-stage amplifier, has been discussed. The layout intended for the fabrication of the LNA has also been described.
Role of Inflammatory Risk Factors in the Pathogenesis of Streptococcus pneumoniae

Streptococcus pneumoniae (Spn) is a colonizer of the human nasopharynx (NP), causing a variety of infections in humans including otitis media, pneumonia, sepsis, and meningitis. The NP is an immune permissive site which allows for the persistence of commensal bacteria. Acute or chronic respiratory airway inflammation constitutes a significant risk factor for the manifestation of Spn infections. The inflammatory conditions caused by an upper respiratory viral infection or respiratory conditions such as allergic asthma and chronic obstructive pulmonary disorders (COPDs) are implicated in the dysregulation of airway inflammation and tissue damage, which compromise the respiratory barrier integrity. These immune events promote bacterial outgrowth leading to Spn dissemination and invasion into the bloodstream. Therefore, suppression of inflammation and restoration of respiratory barrier integrity could contain Spn infections manifesting in the backdrop of an inflammatory disease condition. The gained knowledge could be harnessed in the design of novel therapeutic interventions to circumvent Spn bacterial infections.
FOUR WEEKS OF ROLLER MASSAGE TRAINING DID NOT IMPACT RANGE OF MOTION, PAIN PRESSURE THRESHOLD, VOLUNTARY CONTRACTILE PROPERTIES OR JUMP PERFORMANCE.

Background Roller massagers are popular devices that are used to improve range of motion (ROM), enhance recovery from muscle soreness, and reduce pain under acute conditions. However, the effects of roller massage training and training frequency are unknown. Purpose The objective was to compare two different roller massage training frequencies on muscle performance. Study Design Randomized controlled intervention study. Methods Twenty-three recreationally active university students were randomly allocated to three groups: control (n=8;), rolling three (3/W; n=8;) and six (6/W; n=7) times per week for four weeks. The roller massage training consisted of unilateral, dominant limb, quadriceps and hamstrings rolling (4 sets x 30 seconds). Both legs of participants were tested pre- and post-training for active and passive hamstrings and quadriceps range of motion (ROM), electromyography (EMG) activity during a lunge movement, unilateral countermovement jumps (CMJ), as well as quadriceps and hamstrings maximum voluntary isometric contraction (MVIC) forces and electromechanical delay. Finally, they were tested for pain pressure threshold at middle and distal segments of their quadriceps and hamstrings. Results There were no significant training interactions for any measure with the exception that 3/W group exhibited 6.2% (p=0.03; Effect Size: 0.31) higher CMJ height from pre- (38.6 ± 7.1 cm) to post-testing (40.9 ± 8.1 cm) for the non-dominant limb. Conclusions Whereas the literature has demonstrated acute responses to roller massage, the results of the present study demonstrate no consistent significant training-induced changes. The absence of change may highlight a lack of muscle and myofascial morphological or semi-permanent neurophysiological changes with rolling. Levels of Evidence 2c.