Miracle-dz/UniFAR-FTUs huggingface dataset:
PET/MRI in the Presence of Metal Implants: Completion of the Attenuation Map from PET Emission Data

We present a novel technique for accurate whole-body attenuation correction in the presence of metallic endoprosthesis, on integrated non–time-of-flight (non-TOF) PET/MRI scanners. The proposed implant PET-based attenuation map completion (IPAC) method performs a joint reconstruction of radioactivity and attenuation from the emission data to determine the position, shape, and linear attenuation coefficient (LAC) of metallic implants. Methods: The initial estimate of the attenuation map was obtained using the MR Dixon method currently available on the Siemens Biograph mMR scanner. The attenuation coefficients in the area of the MR image subjected to metal susceptibility artifacts are then reconstructed from the PET emission data using the IPAC algorithm. The method was tested on 11 subjects presenting 13 different metallic implants, who underwent CT and PET/MR scans. Relative mean LACs and Dice similarity coefficients were calculated to determine the accuracy of the reconstructed attenuation values and the shape of the metal implant, respectively. The reconstructed PET images were compared with those obtained using the reference CT-based approach and the Dixon-based method. Absolute relative change (aRC) images were generated in each case, and voxel-based analyses were performed. Results: The error in implant LAC estimation, using the proposed IPAC algorithm, was 15.7% ± 7.8%, which was significantly smaller than the Dixon- (100%) and CT- (39%) derived values. A mean Dice similarity coefficient of 73% ± 9% was obtained when comparing the IPAC- with the CT-derived implant shape. The voxel-based analysis of the reconstructed PET images revealed quantification errors (aRC) of 13.2% ± 22.1% for the IPAC- with respect to CT-corrected images. The Dixon-based method performed substantially worse, with a mean aRC of 23.1% ± 38.4%. Conclusion: We have presented a non-TOF emission-based approach for estimating the attenuation map in the presence of metallic implants, to be used for whole-body attenuation correction in integrated PET/MR scanners. The Graphics Processing Unit implementation of the algorithm will be included in the open-source reconstruction toolbox Occiput.io.
GSN: A Graph-Structured Network for Multi-Party Dialogues

Existing neural models for dialogue response generation assume that utterances are sequentially organized. However, many real-world dialogues involve multiple interlocutors (i.e., multi-party dialogues), where the assumption does not hold as utterances from different interlocutors can occur ``in parallel. '' This paper generalizes existing sequence-based models to a Graph-Structured neural Network (GSN) for dialogue modeling. The core of GSN is a graph-based encoder that can model the information flow along the graph-structured dialogues (two-party sequential dialogues are a special case). Experimental results show that GSN significantly outperforms existing sequence-based models.
Double-Head RCNN: Rethinking Classification and Localization for Object Detection

Modern R-CNN based detectors apply a head to extract Region of Interest (RoI) features for both classiﬁcation and localization tasks. In contrast, we found that these two tasks have opposite preferences towards two widely used head structures (i.e. fully connected head and convolution head). Speciﬁcally, the fully connected head is more suitable for the classiﬁcation task, while the convolution head is more suitable for the localization task. Therefore, we propose a Double-Head method, which has a fully connected head focusing on classiﬁcation and a convolution head to pay more attention to bounding box regression. In addition, we have two ﬁndings for the unfocused tasks (i.e. classiﬁcation in the convolution head, and bounding box regression in the fully connected head): (a) adding classiﬁcation to the convolution head is complementary to the classiﬁcation in the fully connected head, and (b) bounding box regression provides auxiliary supervision for the fully connected head. Without bells and whistles, our method gains +3.5 and +2.8 AP on MS COCO dataset from Feature Pyramid Network (FPN) baselines with ResNet-50 and ResNet-101 backbones, respectively.
Identifying Cache-Based Side Channels through Secret-Augmented Abstract Interpretation

Cache-based side channels enable a dedicated attacker to reveal program secrets by measuring the cache access patterns. Practical attacks have been shown against real-world crypto algorithm implementations such as RSA, AES, and ElGamal. By far, identifying information leaks due to cache-based side channels, either in a static or dynamic manner, remains a challenge: the existing approaches fail to offer high precision, full coverage, and good scalability simultaneously, thus impeding their practical use in real-world scenarios. In this paper, we propose a novel static analysis method on binaries to detect cache-based side channels. We use abstract interpretation to reason on program states with respect to abstract values at each program point. To make such abstract interpretation scalable to real-world cryptosystems while offering high precision and full coverage, we propose a novel abstract domain called the Secret-Augmented Symbolic domain (SAS). SAS tracks program secrets and dependencies on them for precision, while it tracks only coarse-grained public information for scalability. We have implemented the proposed technique into a practical tool named CacheS and evaluated it on the implementations of widely-used cryptographic algorithms in real-world crypto libraries, including Libgcrypt, OpenSSL, and mbedTLS. CacheS successfully confirmed a total of 154 information leaks reported by previous research and 54 leaks that were previously unknown. We have reported our findings to the developers. And they confirmed that many of those unknown information leaks do lead to potential side channels.
MOLECULAR CHARACTERIZATION OF THE ONCOGENIC POTENTIAL AND MECHANISMS OF CYTOMEGALOVIRUS INFECTING MRC-5 CELLS

Background Human cytomegalovirus (HCMV), a member of herpes virus family, is associated with different cancers in humans, including breast and colorectal cancers. Objectives To shed light on the possible oncogenic mechanisms exerted by HCMV on tissues at the genetic level. Methods HCMV was propagated in medical research council-5 (MRC-5) cell line and cytopathic effects of HCMV were checked for confirming infection. Oncogenic mechanism that exerted by HCMV was screened using high-throughput real-time qPCR microarray to investigate the mRNA expression of 983 genes in 16 gene families associated with oncogenesis in human cells. Results Twenty differentially expressed genes. Upregulated genes (SCGB1A1, MAP2K3, ITGB3, TGFB1, PTN, MMP2, AKT1, AKT2, BCL2L10, CKS1B, SERPINB4, CASP4, TOLLIP, BCL-2, SERPINB5) were mostly of oncogenic or oncopromoting activity, involved mainly in MAPK, PI3K/Akt, inflammation, and angiogenesis pathways while downregulated genes (STAT3, BAK1, BLM, RB1, and IGF2R) were mostly tumor suppressor, proapoptotic, and DNA damage repair genes. Conclusion The current study revealed that HCMV might have an oncogenic or oncomodulating activity on normal infected cells by different intracellular pathways.
Reducing Tail Latency via Safe and Simple Duplication

Duplication can be a powerful strategy for overcoming stragglers in cloud services, but is often used conservatively because of the risk of overloading the system. We present duplicate-aware scheduling or DAS, which makes duplication safe and easy to use, by leveraging the two well-known primitives of prioritization and purging. To support DAS across diverse layers of a cloud system (e.g., network, storage, etc), we propose the D-Stage abstraction, which decouples the duplication policy from the mechanism, and facilitates working with legacy layers of a system. Using this abstraction, we evaluate the benefits of DAS for two data parallel applications (HDFS, an in-memory workload generator) and a network function (snort-based IDS cluster). Our experiments on the public cloud and Emulab show that DAS is safe to use, and the tail latency improvement holds across a wide range of workloads
Scaffold-based molecular design with a graph generative model

Searching for new molecules in areas like drug discovery often starts from the core structures of known molecules. Such a method has called for a strategy of designing derivative compounds retaining a particular scaffold as a substructure. On this account, our present work proposes a graph generative model that targets its use in scaffold-based molecular design. Our model accepts a molecular scaffold as input and extends it by sequentially adding atoms and bonds. The generated molecules are then guaranteed to contain the scaffold with certainty, and their properties can be controlled by conditioning the generation process on desired properties. The learned rule of extending molecules can well generalize to arbitrary kinds of scaffolds, including those unseen during learning. In the conditional generation of molecules, our model can simultaneously control multiple chemical properties despite the search space constrained by fixing the substructure. As a demonstration, we applied our model to designing inhibitors of the epidermal growth factor receptor and show that our model can employ a simple semi-supervised extension to broaden its applicability to situations where only a small amount of data is available.
Exact sampling of determinantal point processes with sublinear time preprocessing

We study the complexity of sampling from a distribution over all index subsets of the set $\{1,. ,n\}$ with the probability of a subset $S$ proportional to the determinant of the submatrix $\mathbf{L}_S$ of some $n\times n$ p.s. d. matrix $\mathbf{L}$, where $\mathbf{L}_S$ corresponds to the entries of $\mathbf{L}$ indexed by $S$. Known as a determinantal point process, this distribution is used in machine learning to induce diversity in subset selection. In practice, we often wish to sample multiple subsets $S$ with small expected size $k = E[|S|] \ll n$ from a very large matrix $\mathbf{L}$, so it is important to minimize the preprocessing cost of the procedure (performed once) as well as the sampling cost (performed repeatedly). For this purpose, we propose a new algorithm which, given access to $\mathbf{L}$, samples exactly from a determinantal point process while satisfying the following two properties: (1) its preprocessing cost is $n \cdot \text{poly}(k)$, i.e., sublinear in the size of $\mathbf{L}$, and (2) its sampling cost is $\text{poly}(k)$, i.e., independent of the size of $\mathbf{L}$. Prior to our results, state-of-the-art exact samplers required $O(n^3)$ preprocessing time and sampling time linear in $n$ or dependent on the spectral properties of $\mathbf{L}$. We also give a reduction which allows using our algorithm for exact sampling from cardinality constrained determinantal point processes with $n\cdot\text{poly}(k)$ time preprocessing.
Prosocial Behavior Mitigates the Negative Effects of Stress in Everyday Life

Recent theories of stress reactivity posit that, when stressed, individuals tend to seek out opportunities to affiliate with and nurture others to prevent or mitigate the negative effects of stress. However, few studies have tested empirically the role of prosocial behavior in reducing negative emotional responses to stress. The current analyses used daily diary data to investigate whether engaging in prosocial behavior buffered the negative effects of naturally occurring stressors on emotional well-being. Results showed that on a given day, prosocial behavior moderated the effects of stress on positive affect, negative affect, and overall mental health. Findings suggest that affiliative behavior may be an important component of coping with stress and indicate that engaging in prosocial behavior might be an effective strategy for reducing the impact of stress on emotional functioning.
Anisotropic Jc-/spl thetav/ measurements at low fields on a-MoSi thin films: evidence of a two-dimensional regime

Transport critical current versus applied field inclination (Jc-/spl thetav/ plots) have been made on a-MoSi thin films in low fields of order 0.04 T. The applied field was rotated (at fixed magnitude) in a plane both parallel (/spl phi/=0/spl deg/) and perpendicular (/spl phi/=90/spl deg/) to the film's longitudinal axis. The results indicate a Jc governed by the perpendicular component of the applied field as is sometimes observed in the layered high-temperature superconducting (HTS) thin films. These results also suggest that the peaks in the Jc-/spl thetav/ occur when the vortex density coming from external sources becomes comparable to that induced internally from the self field of the transport current. A broad peak in the Jc when the field is incident perpendicular to the film surface is observed on the silicon substrate film but not on the sapphire substrate film. Possible reasons for this broad peak are discussed.
GORE-TEX VASCULAR GRAFT FOR MACULAR BUCKLING IN HIGH MYOPIA EYES

Purpose: To evaluate a new application of an expanded polytetrafluoroethylene (Gore-Tex) vascular graft for use in macular buckling surgery for treatment of highly myopic eyes. Methods: The Gore-Tex vascular graft was used as a macular buckling material in eight consecutive cases of myopic macular diseases which included fovea detachment, foveoschisis, or macular hole retinal detachment. Results: Retinal reattachment was achieved in all cases except one which had partial resolution (88%). The postoperative best-corrected visual acuity ranged from 20/2000 to 20/100 depending on the degree preexisting macular degeneration, and significant better than the preoperative best-corrected visual acuity (P = 0.048, paired t-test). During the follow-up period, which ranged from 8 months to 3 years, no eye developed buckle-related complications such as infection or dislocation. Conclusion: The initial pilot results from this series using a Gore-Tex graft for macular buckling is promising. Throughout the follow-up period, the Gore-Tex was well tolerated in the highly myopic eyes. Large scale and long-term follow-up is warranted.
Privacy-Preserving Detection of IoT Devices Connected Behind a NAT in a Smart Home Setup

Today, telecommunication service providers (telcos) are exposed to cyber-attacks executed by compromised IoT devices connected to their customers' networks. Such attacks might have severe effects not only on the target of attacks but also on the telcos themselves. To mitigate those risks we propose a machine learning based method that can detect devices of specific vulnerable IoT models connected behind a domestic NAT, thereby identifying home networks that pose a risk to the telco's infrastructure and availability of services. As part of the effort to preserve the domestic customers' privacy, our method relies on NetFlow data solely, refraining from inspecting the payload. To promote future research in this domain we share our novel dataset, collected in our lab from numerous and various commercial IoT devices.
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization

We study gradient compression methods to alleviate the communication bottleneck in data-parallel distributed optimization. Despite the significant attention received, current compression schemes either do not scale well or fail to achieve the target test accuracy. We propose a new low-rank gradient compressor based on power iteration that can i) compress gradients rapidly, ii) efficiently aggregate the compressed gradients using all-reduce, and iii) achieve test performance on par with SGD. The proposed algorithm is the only method evaluated that achieves consistent wall-clock speedups when benchmarked against regular SGD with an optimized communication backend. We demonstrate reduced training times for convolutional networks as well as LSTMs on common datasets. Our code is available at this https URL.
Classification of low-luminosity stellar X-ray sources in the field of the Draco dwarf spheroidal galaxy

Aims. A previous study of the X-ray luminosity function of the X-ray sources in the Draco dwarf spheroidal (dSph) galaxy field indicates the presence of a population of unknown X-ray sources in the soft energy range of 0.5–2 keV. In 2015, there were twenty-six further deep XMM-Newton observations of Draco dSph, providing an opportunity for a new study of the as yet unclassified sources. Methods. We applied the classification criteria presented in our previous multi-wavelength study of the X-ray sources of the Draco dSph to the sources detected in the combined 2009 and 2015 XMM-Newton data set. These criteria are based on X-ray studies and properties of the optical, near-infrared, and mid-infrared counterparts and allows us to distinguish background active galactic nuclei (AGNs) and galaxies from other types of X-ray sources. In this work we performed X-ray spectral and timing analyses for fifteen sources in the field of Draco dSph with stellar counterparts. Results. We present the classification of X-ray sources, for which the counterpart is identified as a stellar object based on our criteria from multi-wavelength data. We identify three new symbiotic stars in the Draco dSph with X-ray luminosities between ∼3.5 × 1034 erg s−1 and 5.5 × 1034 erg s−1. The X-ray spectral analysis shows that two of the classified symbiotic stars are β-type. This is the first identification of this class of symbiotic stars in a nearby galaxy. Eight sources are classified as Galactic M dwarfs in the field of the Draco dSph. These M dwarfs are between ∼140 and 800 pc distant, with X-ray luminosities are between 1028 and 1029 erg s−1 and logarithmic ratios of X-ray to bolometric luminosity, log(LX/Lbol), between −3.4 and −2.1. The multiple observations allowed us to investigate flare activity of the M dwarfs. For 5 M dwarfs flare(s) are observed with a significance of > 3σ level of confidence. Moreover, we classified three foreground sources, located at distances of the order of ∼1–3 kpc in the field of the Draco dSph. Based on both the X-ray luminosities of these foreground sources (> 1030 erg s−1) and their optical counterparts (late type G or K stars), these X-ray sources are classified as candidates of contact binary systems. Conclusions. Our study of X-ray sources of the Draco dSph shows that accreting white dwarfs are the most promising X-ray population of dSphs, which is in line with theoretical expectations. The number of Galactic M dwarfs detected at our X-ray sensitivity limit is consistent with the expectation based on the space density of M dwarfs.
FUNSD: A Dataset for Form Understanding in Noisy Scanned Documents

We present a new dataset for form understanding in noisy scanned documents (FUNSD) that aims at extracting and structuring the textual content of forms. The dataset comprises 199 real, fully annotated, scanned forms. The documents are noisy and vary widely in appearance, making form understanding (FoUn) a challenging task. The proposed dataset can be used for various tasks, including text detection, optical character recognition, spatial layout analysis, and entity labeling/linking. To the best of our knowledge, this is the first publicly available dataset with comprehensive annotations to address FoUn task. We also present a set of baselines and introduce metrics to evaluate performance on the FUNSD dataset, which can be downloaded at https://guillaumejaume.github. io/FUNSD.
Parallel Tempering via Simulated Tempering Without Normalizing Constants.

In this paper we develop a new general Bayesian methodology that simultaneously estimates parameters of interest and the marginal likelihood of the model. The proposed methodology builds on Simulated Tempering, which is a powerful algorithm that enables sampling from multi-modal distributions. However, Simulated Tempering comes with the practical limitation of needing to specify a prior for the temperature along a chosen discretization schedule that will allow calculation of normalizing constants at each temperature. Our proposed model defines the prior for the temperature so as to remove the need for calculating normalizing constants at each temperature and thereby enables a continuous temperature schedule, while preserving the sampling efficiency of the Simulated Tempering algorithm. The resulting algorithm simultaneously estimates parameters while estimating marginal likelihoods through thermodynamic integration. We illustrate the applicability of the new algorithm to different examples involving mixture models of Gaussian distributions and ordinary differential equation models.
Lexical and Frequency Effects on Keystroke Timing: Challenges to a Lexical Search Account From a Type-To-Copy Task

We explore how timing in identical keystroke sequences of a stem morpheme is influenced by linguistic knowledge by manipulating lexical status and morphological complexity of words in a type-to-copy task. Starting from the second keystroke, we find that average keystroke latency within a stem morpheme varies according to whole-word frequency (Experiment1) and lexicality defined by compatibility of the upcoming suffix (e.g., IZE vs IST) with the stem (e.g., NORMAL) to form a string (e.g., RENORMALIZE vs. RENORMAL; RENORMALIZE vs. RENORMALIST in Experiments 2 & 3 respectively). Further, although lexical and frequency effects persist over the string as a whole, nonlinear mixed-effects regressions reveal position varying lexical effects on keystroke latencies within the stem morpheme. In addition, whole word frequency effects on the first keystroke were present. These results challenge hierarchical accounts of production with modular motor programs where the same letter sequence (for a morpheme) is realized independently of and only after lexical access to the word in which the letters occur (cf. Crump & Logan, 2010; Logan & Crump 2011).
Transvaginal Ultrasound for Identifying Endometrial Abnormality

Transvaginal ultrasound was used preoperatively to evaluate the endometrium in 96 patients referred for dilatation and curettage. The sonographic display was correlated to the histopathologic diagnosis. In 45 patients with postmenopausal bleeding, 4 patients had adenocarcinoma of the endometrium. All were identified by ultrasound. None of the 22 patients with a normal sonographic appearance had an abnormal histopathologic diagnosis. An endometrial thickness (single layer) cut‐off point of ≥ 4 mm precluded any missed malignancies but halves the number of dilatations and curettages in this post‐meno‐pausal group. The sensitivity of ultrasound in diagnosing endometrial pathology was 100% and the specificity was 61%. The positive and negative predictive values were 39% and 100% respectively. In 51 premenopausal women there was good agreement between histology and ultrasound. In this group a cut‐off point of ≥ 8 mm was used. The sensitivity in diagnosing endometrial pathology was 67% and the specificity 75%. The positive and negative predictive values were 14% and 97%. With further experience, transvaginal ultrasound might be used in clinical routine for diagnosing endometrial pathology.