Miracle-dz/UniFAR-FTUs huggingface dataset:
A consistency mechanism for NVM-Based in-memory file systems

Non-Volatile Memory (NVM) has evolved to achieve non-volatility and byte-addressability with latency comparable to DRAM. This inspires the development of a new generation of file systems, namely NVM-based in-memory file systems, which include NVM on memory bus and allow in-NVM data to be directly accessed like DRAM. Meanwhile, an important issue, the consistency problem, arises as a new challenge. That is, the direct modification to the in-NVM data can be interrupted by arbitrary crashes in the system, which results in part of the modification being durable and others being lost. Traditional consistency mechanisms assume the existence of DRAM buffering and hence cannot be applied to this hybrid memory architecture. While several consistency methods have been proposed for NVM-based in-memory file systems, most of them have side-effects including unfriendliness to DRAM and penalties on concurrency control, which degrade the system performance. In this paper, we propose a novel mechanism to guarantee the consistency of NVM-based in-memory file systems. We abstract the storage area as a layered structure and employ a lazy-validated snapshot strategy to achieve a high consistency level. Since every consistency method comes with a cost, we introduce several algorithms to efficiently deal with block-sharing and reduce the overhead of consistency mechanism. The experimental results show that our mechanism incurs negligible consistency overhead and outperforms a state-of-the-art snapshot file system by reducing the latency of snapshot taking and removal by 95% and 60% respectively.
A Data-Driven Approach to Efficient Character Articulation

In this paper, we propose a data-driven approach for realistic deformation of articulated meshes: the wide availability of pose data makes such an approach feasible. We use multiple reference models, combined with a fast linear blending skinning (LBS) method in local spaces. By exploiting information from the reference models, realistic deformation is achieved, yet with computational efficiency comparable to traditional blending methods-our approach is suitable for real-time applications. We demonstrate the effectiveness of our algorithm using various examples.
Usefulness of the pediatric electrocardiogram in detecting left ventricular hypertrophy: results from the Prospective Pediatric Pulmonary and Cardiovascular Complications of Vertically Transmitted HIV Infection (P2C2 HIV) multicenter study.

BACKGROUND A shortcoming of the pediatric electrocardiogram (ECG) appears to be its inability to accurately detect left ventricular hypertrophy (LVH). This study prospectively assesses the usefulness of the pediatric ECG as a screening modality for LVH. METHODS Concomitant echocardiograms and ECGs from a large cohort of children who were exposed to the human immunodeficiency virus (HIV; uninfected) and children who were infected with HIV were compared. By use of the values of Davignon et al, qualitative determination of LVH and quantitative criteria for LVH (RV6, SV1, RV6+SV1, QV6, and Q(III) >98% for age, R/SV1 <98% for age, and [-]TV6) were compared to body surface area adjusted for left ventricular (LV) mass z score. Results were then stratified according to weight and weight-for-height z scores. New age-adjusted predicted values were then constructed from children of a mixed race who were HIV-uninfected, < or =6 years old, and similarly assessed. RESULTS The sensitivity rate was <20% for detecting increased LV mass, irrespective of HIV status; the specificity rate was 88% to 92%. The sensitivity rate of the individual criteria ranged from 0 to 35%; the specificity rate was 76% to 99%. Test sensitivities remained low when stratified by weight and weight-for-height z scores. Areas under the receiver operator characteristic curves were between 0.59 and 0.70, also suggesting poor accuracy of the ECG criteria. By use of new age-adjusted predicted values, the sensitivity rate decreased to <17%, and the specificity rate increased to 94% to 100%. CONCLUSION The ECG is a poor screening tool for identifying LVH in children. Sensitivity is not improved with revision of current criteria.
Accurate Text Localization in Natural Image with Cascaded Convolutional Text Network

We introduce a new top-down pipeline for scene text detection. We propose a novel Cascaded Convolutional Text Network (CCTN) that joints two customized convolutional networks for coarse-to-fine text localization. The CCTN fast detects text regions roughly from a low-resolution image, and then accurately localizes text lines from each enlarged region. We cast previous character based detection into direct text region estimation, avoiding multiple bottom- up post-processing steps. It exhibits surprising robustness and discriminative power by considering whole text region as detection object which provides strong semantic information. We customize convolutional network by develop- ing rectangle convolutions and multiple in-network fusions. This enables it to handle multi-shape and multi-scale text efficiently. Furthermore, the CCTN is computationally efficient by sharing convolutional computations, and high-level property allows it to be invariant to various languages and multiple orientations. It achieves 0.84 and 0.86 F-measures on the ICDAR 2011 and ICDAR 2013, delivering substantial improvements over state-of-the-art results [23, 1].
Validity and Reliability of the Hausa Version of Multidimensional Scale of Perceived Social Support Index

Background: Social support has been identified as one of the key factors for enhancing the quality of life after stroke. However, a scientific tool that is valid for evaluating social support among stroke survivors in Nigeria has not been developed so far. Objectives: The objective of this study was to examine the psychometric properties of the Hausa translated versions of the Multidimensional Scale of Perceived Social Support (MSPSS) and to validate it for future use in clinical research in Nigeria. Patients and Methods: This cross-sectional study was conducted on a sample of 140 adult stroke survivors attending rehabilitation services at stroke referral centers in Kano, Nigeria. The psychometric analysis of the Hausa-MSPSS involved face, content, criterion and construct validity tests, as well as internal and test-retest reliability. Confirmatory factor analysis was performed to assess validity of the three-factor (Family, Friends and Significant others) model for the Hausa-MSPSS. Results: Based on expert panel, clinicians’ review and patients’ feedback, the 12 item Hausa-MSPSS had sufficient face, content and criterion validity. In reliability analysis, the Cronbach’s alpha was 0.781. In test-retest reliability analysis, the minimum kappa value was 0.673. In Confirmatory factor analysis, the three-factor model was not acceptable. An alternative two-factor model with Family and Friends, as the two domain was found to be acceptable (Chi-square/df < 3, TLI, CFI > 0.9, RMSEA < 0.08). The average variances extracted for the two constructs were 0.5 and 0.7, respectively. The R-squared value between the two constructs was 0.397. Cross validity tested using 1000 bootstrap resamples gave satisfactory results (P = 0.079). Conclusions: The 11 item Hausa-MSPSS index is valid for the assessment of perceived social support among stroke survivors in Nigeria.
The survival of the fittest: an evolutionary approach to deploying adaptive functionality in peer-to-peer systems

The heterogeneous, large-scale and decentralised nature of peer-to-peer systems creates significant issues when deploying new functionality and adapting peer behaviour. The ability to autonomously deploy new adaptive functionality is therefore highly beneficial. This paper investigates middleware support for evolving and adapting peers in divergent systems through reflective component based design. This approach allows self-contained functionality to exist in the network as a primary entity. This functionality is autonomously propagated to suitable peers, allowing nodes to be evolved and adapted to their individual constraints and the specific requirements of their environment. This results in effective functionality flourishing whilst suboptimal functionality dies out. By this, a self-managed infrastructure is created that supports the deployment of functionality following the evolutionary theory of natural selection. This approach is evaluated through simulations to highlight the potential of using natural selection for the deployment and management of software evolution.
Practice Makes Efficient: Cortical Alpha Oscillations Are Associated With Improved Golf Putting Performance

Practice of a motor skill results in improved performance and decreased movement awareness. The psychomotor efficiency hypothesis proposes that the development of motor expertise through practice is accompanied by physiological refinements whereby irrelevant processes are suppressed and relevant processes are enhanced. The present study employed a test–retest design to evaluate the presence of greater neurophysiological efficiency with practice and mediation analyses to identify the factors accounting for performance improvements, in a golf putting task. Putting performance, movement-specific conscious processing, electroencephalographic alpha power and alpha connectivity were measured from 12 right-handed recreational golfers (age: M = 21 years; handicap: M = 23) before and after 3 practice sessions. As expected, performance improved and conscious processing decreased with training. Mediation analyses revealed that improvements in performance were partly attributable to increased regional gating of alpha power and reduced cross-regional alpha connectivity. However, changes in conscious processing were not associated with performance improvements. Increased efficiency was manifested at the neurophysiological level as selective inhibition and functional isolation of task-irrelevant cortical regions (temporal regions) and concomitant functional activation of task-relevant regions (central regions). These findings provide preliminary evidence for the development of greater psychomotor efficiency with practice in a precision aiming task.
Looking for Gold in the Sands: Stock Prediction Using Financial News and Social Media

Both traditional finance and behavioral finance theory have reached a consensus that the news media de facto influence stock prices to some extent. There is also evidence that investors are not only subject to the sentiment of related news articles but also the public opinions. The challenge lies on how to quantify such sentimental information to predict the movement of stock market. To measure the sentiments of articles and capture the public mood from postings, we construct and maintain a sentiment dictionary. We utilize both the official information from news articles and user postings in discussion boards to predict firm-specific stock price, and differentiate various types of news articles in the predictive model. Our experiments on CSI 100 stocks during a six week period show a predictive performance in closeness to the actual future stock price is 0.03503 in terms of mean squared error, the same direction of price movement as the future price is 67.6%. Among all seven news topic categories, restructuring news of enterprises has the best predicting performance with direction accuracy of 68.18%.
Anaerobic Nitrogen Turnover by Sinking Diatom Aggregates at Varying Ambient Oxygen Levels

In the world’s oceans, even relatively low oxygen levels inhibit anaerobic nitrogen cycling by free-living microbes. Sinking organic aggregates, however, might provide oxygen-depleted microbial hotspots in otherwise oxygenated surface waters. Here, we show that sinking diatom aggregates can host anaerobic nitrogen cycling at ambient oxygen levels well above the hypoxic threshold. Aggregates were produced from the ubiquitous diatom Skeletonema marinoi and the natural microbial community of seawater. Microsensor profiling through the center of sinking aggregates revealed internal anoxia at ambient 40% air saturation (∼100 μmol O2 L-1) and below. Accordingly, anaerobic nitrate turnover inside the aggregates was evident within this range of ambient oxygen levels. In incubations with 15N-labeled nitrate, individual Skeletonema aggregates produced NO2- (up to 10.7 nmol N h-1 per aggregate), N2 (up to 7.1 nmol N h-1), NH4+ (up to 2.0 nmol N h-1), and N2O (up to 0.2 nmol N h-1). Intriguingly, nitrate stored inside the diatom cells served as an additional, internal nitrate source for dinitrogen production, which may partially uncouple anaerobic nitrate turnover by diatom aggregates from direct ambient nitrate supply. Sinking diatom aggregates can contribute directly to fixed-nitrogen loss in low-oxygen environments in the ocean and vastly expand the ocean volume in which anaerobic nitrogen turnover is possible, despite relatively high ambient oxygen levels. Depending on the extent of intracellular nitrate consumption during the sinking process, diatom aggregates may also be involved in the long-distance export of nitrate to the deep ocean.
An Investigation of Primary Transmitter Detection Techniques in Cognitive Radio Networks from Network Optimization Perspective

In this paper, we investigate the problem of primary user detection in cognitive radio networks. Compared with related work that aims to propose techniques at different layers of the network protocol stack for detecting primary users, we aim to investigate the capabilities and limitations of different primary user detection techniques from the perspective of network optimization. The goal is to understand fundamental performance tradeoffs of these techniques without being limited by existing cognitive radio software and hardware platforms. To proceed, we first identify several dimensions for designing primary transmitter detection techniques in cognitive radio networks, including transmitter side vs. receiver side detection, and collaborative vs. non-collaborative detection. We then formulate primary transmitter detection techniques along these dimensions using mixed-integer nonlinear programming (MINLP). Evaluation results show the benefits of using the proposed optimization framework to profile the fundamental characteristics of primary transmitter detection techniques, thus motivating future research along this direction.
Electrospray ionization mass spectrometry of zinc, cadmium, and copper metallothioneins: Evidence for metal‐binding cooperativity

Electrospray ionization (ESI) mass spectra of both well‐characterized and novel metallothioneins (MTs) from various species were recorded to explore their metal‐ion‐binding modes and stoichiometries. The ESI mass spectra of the zinc‐and cadmium‐binding MTs showed a single main peak corresponding to metal‐to‐protein ratios of 4, 6, or 7. These findings combined with data obtained by other methods suggest that these MTs bind zinc or cadmium in a single predominant form and are consistent with the presence of three‐ and four‐metal clusters. An unstable copper‐specific MT isoform from Roman snails (Helix pomatia) could be isolated intact and was shown to preferentially bind 12 copper ions. To obtain additional information on the formation and relative stability of metal‐thiolate clusters in MTs, a mass spectrometric titration study was conducted. One to seven molar equivalents of zinc or of cadmium were added to metal‐free human MT‐2 at neutral pH, and the resulting complexes were measured by ESI mass spectrometry. These experiments revealed that the formation of the four‐metal cluster and of the thermodynamically less stable three‐metal cluster is sequential and largely cooperative for both zinc and cadmium. Minor intermediate forms between metal‐free MT, Me4MT, and fully reconstituted Me7MT were also observed. The addition of increasing amounts of cadmium to metal‐free blue crab MT‐I resulted in prominent peaks whose masses were consistent with apoMT, Cd3MT, and Cd6MT, reflecting the known structure of this MT with two Me3Cys9 centers. In a similar reconstitution experiment performed with Caenorhabditits elegans MT‐II, a series of signals corresponding to apoMT and Cd3MT to Cd6MT species were observed.
High-motion table tennis ball tracking for umpiring applications

Table-tennis umpiring presents many challenges where technology can be judiciously applied to enhance decision-making, especially in the service facet of the game. This paper presents a system to automatically detect and track the ball during table-tennis services to enable precise judgment over their legitimacy. The system comprises a suite of algorithms that adaptively exploit spatial and temporal information from real match videos, which are generally characterized by high object motion, allied with object blurring and occlusion. Experimental results on various table-tennis test videos corroborate the system performance in facilitating accurate and efficient decision-making over the validity of a service.
Hearing AIDS: Standards, Options, and Limitations

Chapter 1: Electroacoustic Testing of Hearing Aids and Standards George J. Frye, MSEE Chapter 2: Microphone, Telecoil and Receiver Options: Past, Present and Future Stephen C. Thompson, PhD Chapter 3: Amplifiers and Circuit Algorithms for Contemporary Hearing Aids Jeremy Agnew, PhD Chapter 4: Hearing Aid Adjustments Through Potentiometer and Switch Options Jeremy Agnew, PhD Chapter 5: Considerations in Modern Multichannel Nonlinear Hearing Aids Francis K. Kuk, Ph.D. Chapter 6: Earhooks, Tubing, Earmolds, and Shells Michael Valente, PhD Maureen Valente, MS Jane Enrietto, MA Chapter 7: Directional Amplification for Improved Signal-to-Noise Ratio: Strategies, Measurement, and Limitations Todd A. Ricketts, PhD Andrew Burke Dittberner, MS Chapter 8: Review of Research on Digital Signal Processing Craig W. Newman, PhD Sharon A. Sandridge, PhD Chapter 9: Auditory Rehabilitation Technology: Improving Communication For Individuals With Hearing Loss Carl Crandell, PhD Joseph Smaldino, PhD M. Samantha Lewis, MA Brian Kreisman, MS
Uncoordinated Loss of Chromatid Cohesion Is a Common Outcome of Extended Metaphase Arrest

Chromosome segregation requires coordinated separation of sister chromatids following biorientation of all chromosomes on the mitotic spindle. Chromatid separation at the metaphase-to-anaphase transition is accomplished by cleavage of the cohesin complex that holds chromatids together. Here we show using live-cell imaging that extending the metaphase bioriented state using five independent perturbations (expression of non-degradable Cyclin B, expression of a Spindly point mutant that prevents spindle checkpoint silencing, depletion of the anaphase inducer Cdc20, treatment with a proteasome inhibitor, or treatment with an inhibitor of the mitotic kinesin CENP-E) leads to eventual scattering of chromosomes on the spindle. This scattering phenotype is characterized by uncoordinated loss of cohesion between some, but not all sister chromatids and subsequent spindle defects that include centriole separation. Cells with scattered chromosomes persist long-term in a mitotic state and eventually die or exit. Partial cohesion loss-associated scattering is observed in both transformed cells and in karyotypically normal human cells, albeit at lower penetrance. Suppressing microtubule dynamics reduces scattering, suggesting that cohesion at centromeres is unable to resist dynamic microtubule-dependent pulling forces on the kinetochores. Consistent with this view, strengthening cohesion by inhibiting the two pathways responsible for its removal significantly inhibits scattering. These results establish that chromosome scattering due to uncoordinated partial loss of chromatid cohesion is a common outcome following extended arrest with bioriented chromosomes in human cells. These findings have important implications for analysis of mitotic phenotypes in human cells and for development of anti-mitotic chemotherapeutic approaches in the treatment of cancer.
Simulation of Sliding Mode Impedance Control for a 6 DOF Anthropomorphic Robot

Robust control is a way of dealing with model uncertainties that can render the controller less sensitive to modelling errors and disturbances. Herein, the properties of sliding mode control are applied to impedance control to form a robust impedance con-troller. The proposed controller consists of two parts: a nominal part based on a nominal model of the robot and a robustness part compensating for the difference between model and real robot. Different kinds of robustness parts give differences in chatter-ing, steady–state error and complexity. We can control within certain accuracy, if the uncertainty does not exceed certain up-per bounds. The sliding mode impedance controllers were verified by simu-lations and compared to the old computed torque controller. The parameter uncertainty ranges from 0.5 to 2. Simulations show that the sliding mode controllers have a small impedance error. For these uncertainties the computed torque controller has large errors, or becomes unstable. Some qualitative tests have been carried out showing the control laws have been implemented correctly. However, quantitative experiments need to be done to validate the control laws. Fur-thermore, we recommend to make the boundary layer width adaptive, to always have the highest accuracy possible while keeping robustness
Effects of varying text difficulty levels on second language (L2) reading attitudes and reading comprehension

This study investigated the effects of varying text difficulty on L2 reading attitudes and reading comprehension. To provide the optimal challenge for L2 reading, comprehensible input hypothesis postulates that choosing text slightly harder than the learner's current level will enhance reading comprehension. Fifty-four freshmen from one university in central Taiwan were randomly divided into two groups. Students in the ‘i − 1’ group were given level 3 and level 4 Oxford Graded Readers while students in the ‘i + 1’ group were provided with level 5 and level 6. Quantitative data were obtained via the English Placement Exam and the Reading Attitudes Survey. Results from the pretest and posttest of the Reading Attitudes Survey suggest that the i − 1 group has gained significantly in reading attitudes, whereas no difference in reading attitude was identified with the i + 1 group. Results also indicate that varied difficulty levels of reading text did not significantly affect participants' reading comprehension.
Affine morphological shape stable boundary regions (SSBR) for image representation

This paper presents a new structure-based interest region detector called Shape-Stable Region Boundaries (SSRB) which we use for object class recognition. The SSRB interest operator detects stable boundary regions within the multi-scale morphological image representation [1]. To detect robust boundary regions, we perform multi-scale analysis via anisotropic diffusion operators to preserve boundaries and guarantee invariance to affine transformations. We extract the transition boundaries of the diffusivity velocity map and track their evolution at each level of the scale-space. The stability of the boundary shape is subsequently estimated through a minimization process over different scales. Unlike most state of the art detectors which use the Gaussian scale space for multi-scale image representation, our approach is intrinsically affine invariant [1]. Experiments on different benchmark datasets show that SSRB is comparable or superior to state-of the art detectors for both feature matching and object recognition.