Miracle-dz/UniFAR-FTUs huggingface dataset:
D2-Tree: A Distributed Double-Layer Namespace Tree Partition Scheme for Metadata Management in Large-Scale Storage Systems

The behavior of metadata server (MDS) cluster is critically important to the overall performance of today's petabyte-scale or even exabyte-scale distributed file system. How to maintain a high level of both system locality and load balancing is a significant challenge to MDS clusters. However, traditional metadata management schemes, including hash-based mapping and subtree partitioning, have severe bias on either system locality or load balancing. In this paper, we propose D^2-Tree, a distributed double-layer namespace tree partition scheme, for metadata management in large-scale storage systems. The innovative idea is to design a greedy strategy to split the namespace tree into global layer and local layer subtrees, of which global layer is replicated to maintain load balancing and the lower-half subtrees are allocated separately to MDS's by a mirror division method to preserve locality. Both theoretical analysis based on empirical cumulative distribution and extensive experiments are provided to validate the efficiency of D^2-Tree. Experiments using actual trace data on Amazon EC2 also exhibit the superior performance of D^2-Tree compared with much previous literature.
Regulation of Ferredoxin-NADP+ Oxidoreductase to Cyclic Electron Transport in High Salinity Stressed Pyropia yezoensis

Pyropia yezoensis can survive the severe water loss that occurs during low tide, making it an ideal species to investigate the acclimation mechanism of intertidal seaweed to special extreme environments. In this study, we determined the effects of high salinity on photosynthesis using increasing salinity around algal tissues. Both electron transport rates, ETR (I) and ETR (II), showed continuous decreases as the salinity increased. However, the difference between these factors remained relatively stable, similar to the control. Inhibitor experiments illustrated that there were at least three different cyclic electron transport pathways. Under conditions of severe salinity, NAD(P)H could be exploited as an endogenous electron donor to reduce the plastoquinone pool in Py. yezoensis. Based on these findings, we next examined how these different cyclic electron transport (CETs) pathways were coordinated by cloning the gene (HM370553) for ferredoxin-NADP+ oxidoreductase (FNR). A phylogenetic tree was constructed, and the evolutionary relationships among different FNRs were evaluated. The results indicated that the Py. yezoensis FNR showed a closer relationship with cyanobacterial FNR. The results of both real-time polymerase chain reaction and western blotting showed that the enzyme was upregulated under 90–120‰ salinity. Due to the structure-function correlations in organism, Py. yezoensis FNR was proposed to be involved in NAD(P)H-dependent Fd+ reduction under severe salinity conditions. Thus, through the connection between different donors bridged by FNR, electrons were channeled toward distinct routes according to the different metabolic demands. This was expected to make the electron transfer in the chloroplasts become more flexible and to contribute greatly to acclimation of Py. yezoensis to the extreme variable environments in the intertidal zone.
Meta-analytic comparison of trial- versus questionnaire-based vividness reportability across behavioral, cognitive and neural measurements of imagery

Abstract Vividness is an aspect of consciousness related to mental imagery and prospective episodic memory. Despite being harshly criticized in the past for failing to demonstrate robust correlations with behavioral measures, currently this construct is attracting a resurgent interest in cognitive neuroscience. Therefore, an updated examination of the validity of this construct is timely. A corpus of peer-reviewed literature was analyzed through meta-analysis, which compared the two main formats used to measure vividness [trial-by-trial vividness ratings (VR) and the Vividness of Visual Imagery Questionnaire (VVIQ)]. These two formats were compared in relation to all available behavioral/cognitive (BC) and neuroscience (NS) measures in Phase 1 (3542 statistical observations representing 393 journal articles); and then in relation to all available BC, EEG and fMRI literature in Phase 2 (3624 observations representing 402 articles). Both Phases observed significantly larger effect size estimates (ESEs) for VR than VVIQ, and larger ESEs for NS than BC measures. ESEs for EEG and fMRI were not significantly different in Phase 2, but were greater than BC ESEs. These data suggest VR are a more reliable self-report measure than VVIQ, and may reflect a more direct route of reportability than the latter. Furthermore, both VR and VVIQ are more strongly associated with the neural, than the cognitive and behavioural correlates of imagery. If one establishes neuroscience measures as the criterion variable, then self-reports of vividness show higher construct validity than behavioural/cognitive measures of imagery. We discuss how the present findings contribute to current issues on measurement of reportability; and how this study advances our understanding of vividness as a phenomenological characteristic of imagery, and other forms of conscious experience which do not necessarily involve imagery.
Falcon: A Practical Log-Based Analysis Tool for Distributed Systems

Programmers and support engineers typically rely on log data to narrow down the root cause of unexpected behaviors in dependable distributed systems. Unfortunately, the inherently distributed nature and complexity of such distributed executions often leads to multiple independent logs, scattered across different physical machines, with thousands or millions entries poorly correlated in terms of event causality. This renders log-based debugging a tedious, time-consuming, and potentially inconclusive task. We present Falcon, a tool aimed at making log-based analysis of distributed systems practical and effective. Falcon's modular architecture, designed as an extensible pipeline, allows it to seamlessly combine several distinct logging sources and generate a coherent space-time diagram of distributed executions. To preserve event causality, even in the presence of logs collected from independent unsynchronized machines, Falcon introduces a novel happens-before symbolic formulation and relies on an off-the-shelf constraint solver to obtain a coherent event schedule. Our case study with the popular distributed coordination service Apache Zookeeper shows that Falcon eases the log-based analysis of complex distributed protocols and is helpful in bridging the gap between protocol design and implementation.
Formal Verification of Automotive Embedded Software

The ever-increasing complexity of automotive embedded systems and the need for safe advanced driver assistance systems (ADAS) represent a great challenge for car manufacturers. Furthermore, we expect that in the near future, authorities require a software certification in order to get convinced that ADAS are safe enough. Theoretical research and experience show that when using conventional design approaches it is impossible to guarantee high confidence to those systems. The way taken by some industries (e.g. aerospace, railway, nuclear) was by partially using formal verification techniques. In this paper, we first present a background of the formal verification techniques and how they can contribute to achieve the requirements of some safety standards. Next, we share our experience with the application of those techniques that seem to be mature enough to be used in an industrial context: Static analysis based on Abstract Interpretation, SMT-based software Model checking and Deductive proof. Finally, we make a detailed analysis about our experiments and propose an approach introducing formal methods into the development of automotive embedded software.
Measuring Cybersecurity Wellness Index of Critical Organisations

The concept of wellness in cybersecurity has not been widely discussed and this perspective is still new to date. In this paper we will discuss on this concept of cybersecurity wellness and the ability to generate an index of critical organisations through measuring cybersecurity wellness vital signs. The definition of Critical Organisation is also briefly discussed. Qualitative research using Constructive Research Approach was chosen on 20 critical organisations through a purposeful sampling and evaluated using the framework developed. Index scorecard of all cybersecurity vital signs of each organisations were collected and measured using Likert Scale value from zero to three. A composite index was then generated for each sampling organisations and group index were also computed using all 20 organisations to demonstrate the ability of measuring cybersecurity wellness of one and many organisations. The application of this research work can be used to measure the cybersecurity wellness index of critical sectors of the industry, as well as comparative analysis at national and international levels if applied accordingly.
Automatic Tag Recommendation for Software Development Video Tutorials

Software development video tutorials are emerging as a new resource for developers to support their information needs. However, when trying to find the right video to watch for a task at hand, developers have little information at their disposal to quickly decide if they found the right video or not. This can lead to missing the best tutorials or wasting time watching irrelevant ones. Other external sources of information for developers, such as StackOverflow, have benefited from the existence of informative tags, which help developers to quickly gauge the relevance of posts and find related ones. We argue that the same is valid also for videos and propose the first set of approaches to automatically generate tags describing the contents of software development video tutorials. We investigate seven tagging approaches for this purpose, some using information retrieval techniques and leveraging only the information in the videos, others relying on external sources of information, such as StackOverflow, as well as two out-of-the-box commercial video tagging approaches. We evaluated 19 different configurations of these tagging approaches and the results of a user study showed that some of the information retrieval-based approaches performed the best and were able to recommend tags that developers consider relevant for describing programming videos.
Translating Between the Roots of the Identity in Quantum Computers

The Clifford+T quantum computing gate library for single qubit gates can create all unitary matrices that are generated by the group H, T. The matrix T can be considered the fourth root of Pauli Z, since T4 = Z or also the eighth root of the identity I. The Hadamard matrix H can be used to translate between the Pauli matrices, since (HTH)4 gives Pauli X. We are generalizing both these roots of the Pauli matrices (or roots of the identity) and translation matrices to investigate the groups they generate: the so-called Pauli root groups. In this work we introduce a formalization of such groups, study finiteness and infiniteness properties, and precisely determine equality and subgroup relations.
Re-Thinking: Design and Development of Mobility Aware Applications in Smart and Connected Communities

Recently, several problems concerning smart and connected communities (S&CC) have been studied. In many S&CC applications such as autonomous driving, mobile crowdsourcing and crowd sensing, the mobility of vehicles and pedestrians has large impact on their performance and reliability. Many research works have used mobility generators to simulate realistic mobility, and evaluated the performance and reliability of the proposed applications and protocols. Although such mobility generators might be useful for producing typical mobility patterns, those mobility patterns are just snapshots and they cover only some part in the possible mobility patterns. Since many S&CC applications are used as social systems, their reliability and efficiency are very important. In order to improve the reliability of such mobility aware applications and accurately evaluate their performance, we need to collect many mobility patterns via simulation and/or observation from the real world, analyze their mobility influence statistically and provide adequate design platforms. In this paper, we first show the fact that many research works adopt snapshot-based mobility analyses. Then we propose a technique to reproduce a large part of possible mobility patterns, and provide a design platform to analyze their features and develop high-reliable mobility aware applications for S&CC. Some experimental results are also given.
SnapTask: Towards Efficient Visual Crowdsourcing for Indoor Mapping

Visual crowdsourcing (VCS) offers an inexpensive method to collect visual data for implementing tasks, such as 3D mapping and place detection, thanks to the prevalence of smartphone cameras. However, without proper guidance, participants may not always collect data from desired locations with a required Quality-of-Information (QoI). This often causes either a lack of data in certain areas, or extra overheads for processing unnecessary redundancy. In this work, we propose SnapTask, a participatory VCS system that aims at creating complete indoor maps by guiding participants to efficiently collect visual data of high QoI. It applies Structure-from-Motion (SfM) techniques to reconstruct 3D models of indoor environments, which are then converted into indoor maps. To increase coverage with minimal redundancy, SnapTask determines locations for the next data collection tasks by analyzing the coverage of the generated 3D model and the camera views of the collected images. In addition, it overcomes the limitations of SfM techniques by utilizing crowdsourced annotations to reconstruct featureless surfaces (e.g. glass walls) in the 3D model. According to a field test in a library, the indoor map generated by SnapTask successfully reconstructs 100% of the library walls and 98.12% of objects and traversal areas within the library. With the same amount of input data our design of guided data collection increases the map coverage by 20.72% and 34.45%, respectively, compared with unguided participatory and opportunistic VCS.
Lung Nodule Classification via Deep Transfer Learning in CT Lung Images

Lung cancer corresponds to 26% of all deaths due to cancer in 2017, accounting more than 1.5 million deaths globally. Considering this challenging situation, several computeraided diagnosis systems have been developed to detect lung cancer at early stages, which increases the patients’ survival rate. Motivated by the success of deep learning in natural and medical image classification tasks, the proposed approach aims to explore the performance of deep transfer learning for lung nodules malignancy classification. For this, convolutional neural networks (CNN), such as VGG16, VGG19, MobileNet, Xception, InceptionV3, ResNet50, Inception-ResNet-V2, DenseNet169, DenseNet201, NASNetMobile and NASNetLarge, were used as features extractors to process the Lung Image Database Consortium and Image Database Resource Initiative (LIDC/IDRI). Next, the deep features returned were classified using Naive Bayes, MultiLayer Perceptron (MLP), Support Vector Machine (SVM), Near Neighbors (KNN) and Random Forest (RF) classifiers. Additionally, to compare the classifiers performance with themselves and with other ones in literature, the evaluation metrics Accuracy (ACC), Area Under the Curve (AUC), True Positive Rate (TPR), Precision (PPV), and F1-Score were computed. Finally, the best combination of deep extractor and classifier was CNN-ResNet50 with SVM-RBF, which achieved ACC of 88.41% and AUC of 93.19%. These results are equivalent to related works, even just using a CNN pre-trained on non-medical images. For this reason, deep transfer learning proved to be a relevant strategy to extract representative imaging biomarkers for lung nodule malignancy classification in chest CT images.
Was Self-Admitted Technical Debt Removal a Real Removal? An In-Depth Perspective

Technical Debt (TD) has been defined as "code being not quite right yet", and its presence is often self-admitted by developers through comments. The purpose of such comments is to keep track of TD and appropriately address it when possible. Building on a previous quantitative investigation by Maldonado et al. on the removal of self-admitted technical debt (SATD), in this paper we perform an in-depth quantitative and qualitative study of how SATD is addressed in five Java open source projects. On the one hand, we look at whether SATD is "accidentally" removed, and the extent to which the SATD removal is being documented. We found that that (i) between 20% and 50% of SATD comments are accidentally removed while entire classes or methods are dropped, (ii) 8% of the SATD removal is acknowledged in commit messages, and (iii) while most of the changes addressing SATD require complex source code changes, very often SATD is addressed by specific changes to method calls or conditionals. Our results can be used to better plan TD management or learn patterns for addressing certain kinds of TD and provide recommendations to developers.
The dual role of chloride in synaptic vesicle glutamate transport

The transport of glutamate into synaptic vesicles exhibits an unusual form of regulation by Cl- as well as an associated Cl- conductance. To distinguish direct effects of Cl- on the transporter from indirect effects via the driving force Δψ, we used whole endosome recording and report the first currents due to glutamate flux by the vesicular glutamate transporters (VGLUTs). Chloride allosterically activates the VGLUTs from both sides of the membrane, and we find that neutralization of an arginine in transmembrane domain four suffices for the lumenal activation. The dose dependence suggests that Cl- permeates through a channel and glutamate through a transporter. Competition between the anions nonetheless indicates that they use a similar permeation pathway. By controlling both ionic gradients and Δψ, endosome recording isolates different steps in the process of synaptic vesicle filling, suggesting distinct roles for Cl- in both allosteric activation and permeation.
A Physics-Based Compact Model of SiC Junction Barrier Schottky Diode for Circuit Simulation

A physics-based compact model of silicon carbide (SiC) junction barrier Schottky diode for circuit simulation is developed in this paper. The semiconductor physics mechanism in SiC, such as temperature-dependent mobility and incomplete ionization, are considered. The detailed device parameters, including drift region concentration, drift thickness, active area, and Schottky barrier height, are modeled. Then, a datasheet-oriented parameter extraction procedure for the device parameters is presented for three kinds of commercial SiC Schottky diodes with junction barrier structure. The model is implemented in the circuit simulator PSpice. In order to verify this model, the Technology Computer-Aided Design Sentaurus simulation is conducted with the device parameters and physical models, which shows a good agreement with the PSpice simulation.
Retrogradely Transportable Lentivirus Tracers for Mapping Spinal Cord Locomotor Circuits

Retrograde tracing is a key facet of neuroanatomical studies involving long distance projection neurons. Previous groups have utilized a variety of tools ranging from classical chemical tracers to newer methods employing viruses for gene delivery. Here, we highlight the usage of a lentivirus that permits highly efficient retrograde transport (HiRet) from synaptic terminals within the cervical and lumbar enlargements of the spinal cord. By injecting HiRet, we can clearly identify supraspinal and propriospinal circuits innervating motor neuron pools relating to forelimb and hindlimb function. We observed robust labeling of propriospinal neurons, including high fidelity details of dendritic arbors and axon terminals seldom seen with chemical tracers. In addition, we examine changes in interneuronal circuits occurring after a thoracic contusion, highlighting populations that potentially contribute to spontaneous behavioral recovery in this lesion model. Our study demonstrates that the HiRet lentivirus is a unique tool for examining neuronal circuitry within the brain and spinal cord.
Precocious Puberty and the Lin28/Let7 Pathway: The Therapeutic Effect of the Nourishing “Yin” and Purging “Fire” Traditional Chinese Medicine Mixture in a Rat Model

The present study aims to investigate the effects of the nourishing “Yin” and purging “Fire” Traditional Chinese Medicine (TCM) herb mixture on precocious puberty and TCM may act through hypothalamic Lin28/let7 pathway expression in the precocious puberty model rats. Meanwhile, to confirm the relationship between Lin28/let7 pathway and puberty by overexpression Lin28a, in the first part of this study, female rats were randomly allocated into untreated controls, the precocious puberty (PP) model group, the PP control group, and the PP + TCM group. Rats on postnatal day 5 were injected danazol to establish the PP model. From days 15 to 35, the rats in the TCM group were given the TCM twice daily. Vaginal opening, sex-related hormones, and body and reproductive organ weights were measured, and the expressions of hypothalamic Lin28a and Lin28b mRNA and let7a and let7b miRNA were detected. In addition, in the second part, the effects of overexpression of Lin28a on the vaginal opening time were evaluated. In the two parts of the study, we found that, at the onset of puberty, a decrease in ovary weight, an increase in the serum levels of luteinizing hormone and progesterone, and increased expression levels of hypothalamic Lin28b mRNA were observed in the PP + TCM group compared to the PP model group. The vaginal opening time was significantly delayed upon overexpression of Lin28a. Above all, the mechanism by which the TCM treats precocious puberty is thus likely to be associated with inhibition of the hypothalamic Lin28/let7 signaling pathway and our findings provide in-depth insight into the relationship between the overexpression of Lin28a gene in the hypothalamus and the onset of puberty.