Miracle-dz/UniFAR-FTUs huggingface dataset:
RESTRICTED ISOMETRY PROPERTY FOR LOW-DIMENSIONAL SUBSPACES AND ITS APPLICATION IN COMPRESSED SUBSPACE CLUSTERING

Utilizing random matrix to reduce the dimension of data has become an attractive method in signal processing and machine learning since the boom of Compressed Sensing. One important example is compressed subspace clustering (CSC), a powerful unsupervised learning algorithm, which performs subspace clustering after random projection. In our previous work, motivated by the importance of affinity in CSC and the conjecture about whether the similarity (distance) between any two given subspaces can remain almost unchanged after random projection, we first prove the restricted isometry property of Gaussian random matrix for compressing subspaces, providing strong theoretical guarantee for the performance of CSC. However, the estimated probability bound in that work doesn't match well with the forms of RIP in other fields, e.g., compressed sensing, because the analysis skills we use are too coarse. To address this issue, we rigorously derive a nearly optimal probability bound in this paper, which can provide a more solid theoretical foundation for CSC and other subspace related problems.
Causally Regularized Learning with Agnostic Data Selection Bias

Most of previous machine learning algorithms are proposed based on the i.i. d. hypothesis. However, this ideal assumption is often violated in real applications, where selection bias may arise between training and testing process. Moreover, in many scenarios, the testing data is not even available during the training process, which makes the traditional methods like transfer learning infeasible due to their need on prior of test distribution. Therefore, how to address the agnostic selection bias for robust model learning is of paramount importance for both academic research and real applications. In this paper, under the assumption that causal relationships among variables are robust across domains, we incorporate causal technique into predictive modeling and propose a novel Causally Regularized Logistic Regression (CRLR) algorithm by jointly optimize global confounder balancing and weighted logistic regression. Global confounder balancing helps to identify causal features, whose causal effect on outcome are stable across domains, then performing logistic regression on those causal features constructs a robust predictive model against the agnostic bias. To validate the effectiveness of our CRLR algorithm, we conduct comprehensive experiments on both synthetic and real world datasets. Experimental results clearly demonstrate that our CRLR algorithm outperforms the state-of-the-art methods, and the interpretability of our method can be fully depicted by the feature visualization.
Recent chapters of Neotropical history overlooked in phylogeography: Shallow divergence explains phenotype and genotype uncoupling in Antilophia manakins

Establishing links between phenotypic and genotypic variation is a central goal of evolutionary biology, as they might provide important insights into evolutionary processes shaping genetic and species diversity in nature. One of the more intriguing possibilities is when no genetic divergence is found to be associated with conspicuous phenotypic divergence. In that case, speciation theory predicts that phenotypic divergence may still occur in the presence of significant gene flow—thereby resulting in little genomic divergence—when genetic loci underpinning phenotypes are under strong divergent selection. However, a finding of phenotypic distinctiveness with weak or no population genetic structure may simply result from low statistical power to detect shallow genetic divergences when small data sets are used. Here, we used a subgenomic data set of 2,386 ultraconserved elements to explore genomewide divergence between two species of Antilophia manakins, which are phenotypically distinct yet evidently lack strong genetic differentiation according to previous studies based on a limited number of loci. Our results revealed clear population structure that matches the two phenotypes, supporting the idea that smaller data sets lacked the power to detect this recent divergence event (likely <100 k ya). Indeed, we found little or no introgression between the species, as well as evidence of genomewide divergence. One implication of our study is that the Araripe plateau may be a hot spot of cryptic‐diverging forest Cerrado populations. Besides their use in biogeography, subgenomic data sets may help redefine local conservation programmes by revealing cryptic population structure that may be key to population management.
A New Sclera Segmentation and Vessels Extraction Method for Sclera Recognition

As a unique biometric trait, the research of sclera blood vessels have becomes active recently, because the sclera vessels can be captured under visible-wavelength light condition rather than near infrared light condition. However, the performance of sclera identification system degrades a lot due to unsatisfactory sclera segmentation and tedious extraction process. In this paper, we propose a novel sclera segmentation algorithm and an improved sclera vessels extraction method. The accurate and efficient sclera segmentation method is proposed based on improved OSTU algorithm. Besides, the vessels extraction method is put forward by adaptive histogram equalization method and Gabor filters. The experimental results on UBIRIS.vl database prove that the proposed sclera vessels extraction algorithm performs well and the sclera segmentation method has an obvious improvement in terms of efficiency and accuracy over than other segmentation algorithms.
Mutation-independent rhodopsin gene therapy by knockdown and replacement with a single AAV vector

Significance A number of gene-augmentation strategies are entering clinical trials for the treatment of inherited retinal blindness. Gene therapy for autosomal dominant diseases faces significant obstacles that include allelic heterogeneity and the potential need to silence the mutated gene. Here we show that a single-gene therapy vector that combines knockdown of the causative gene with its replacement by a resistant wild-type copy can prevent photoreceptor cell death and vision loss in a canine model of autosomal dominant retinitis pigmentosa. Inherited retinal degenerations are caused by mutations in >250 genes that affect photoreceptor cells or the retinal pigment epithelium and result in vision loss. For autosomal recessive and X-linked retinal degenerations, significant progress has been achieved in the field of gene therapy as evidenced by the growing number of clinical trials and the recent commercialization of the first gene therapy for a form of congenital blindness. However, despite significant efforts to develop a treatment for the most common form of autosomal dominant retinitis pigmentosa (adRP) caused by >150 mutations in the rhodopsin (RHO) gene, translation to the clinic has stalled. Here, we identified a highly efficient shRNA that targets human (and canine) RHO in a mutation-independent manner. In a single adeno-associated viral (AAV) vector we combined this shRNA with a human RHO replacement cDNA made resistant to RNA interference and tested this construct in a naturally occurring canine model of RHO-adRP. Subretinal vector injections led to nearly complete suppression of endogenous canine RHO RNA, while the human RHO replacement cDNA resulted in up to 30% of normal RHO protein levels. Noninvasive retinal imaging showed photoreceptors in treated areas were completely protected from retinal degeneration. Histopathology confirmed retention of normal photoreceptor structure and RHO expression in rod outer segments. Long-term (>8 mo) follow-up by retinal imaging and electroretinography indicated stable structural and functional preservation. The efficacy of this gene therapy in a clinically relevant large-animal model paves the way for treating patients with RHO-adRP.
The Secure Socket API: TLS as an Operating System Service

TLS APIs are often complex, leading to developer mistakes. In addition, even with well-written applications, security administrators lack control over how TLS is used on their machines and don’t have the ability to ensure applications follow best practices. Our solution is to provide a Secure Socket API that is integrated into the well-known POSIX sockets API. This is both simple for developers to use and allows system administrators to set device policy for TLS. In this article, we both explain and demonstrate how the Secure Socket API works.
Cardiac Hemodynamic Monitoring in the Subcutaneous Space : A pre-clinical proof-of-concept

Measuring cardiac hemodynamics subcutaneously offers a novel and minimally-invasive means of monitoring mechanical heart performance. Four accelerometer-based hemodynamic sensors were implanted at various subcutaneous sites of the thorax in one dog. Three of the sensors were on the tips of cardiac pacing leads, one was embedded inside an inactive pacemaker device can. The first heart sound could be well identified and its amplitude quantified in all subcutaneous sensors on a beat-to-beat basis. Its magnitude was comparable to that of the external signal, and about half that of the intracardiac signal. It also correlated well to cardiac contractility during transient pharmacologically induced hemodynamic challenges. This is the first evidence that heart sounds can be measured in the subcutaneous space to monitor heart function.
XL-NBT: A Cross-lingual Neural Belief Tracking Framework

Task-oriented dialog systems are becoming pervasive, and many companies heavily rely on them to complement human agents for customer service in call centers. With globalization, the need for providing cross-lingual customer support becomes more urgent than ever. However, cross-lingual support poses great challenges—it requires a large amount of additional annotated data from native speakers. In order to bypass the expensive human annotation and achieve the first step towards the ultimate goal of building a universal dialog system, we set out to build a cross-lingual state tracking framework. Specifically, we assume that there exists a source language with dialog belief tracking annotations while the target languages have no annotated dialog data of any form. Then, we pre-train a state tracker for the source language as a teacher, which is able to exploit easy-to-access parallel data. We then distill and transfer its own knowledge to the student state tracker in target languages. We specifically discuss two types of common parallel resources: bilingual corpus and bilingual dictionary, and design different transfer learning strategies accordingly. Experimentally, we successfully use English state tracker as the teacher to transfer its knowledge to both Italian and German trackers and achieve promising results.
Genome-wide identification and characterization of non-specific lipid transfer proteins in cabbage

Plant non-specific lipid transfer proteins (nsLTPs) are a group of small, secreted proteins that can reversibly bind and transport hydrophobic molecules. NsLTPs play an important role in plant development and resistance to stress. To date, little is known about the nsLTP family in cabbage. In this study, a total of 89 nsLTP genes were identified via comprehensive research on the cabbage genome. These cabbage nsLTPs were classified into six types (1, 2, C, D, E and G). The gene structure, physical and chemical characteristics, homology, conserved motifs, subcellular localization, tertiary structure and phylogeny of the cabbage nsLTPs were comprehensively investigated. Spatial expression analysis revealed that most of the identified nsLTP genes were positively expressed in cabbage, and many of them exhibited patterns of differential and tissue-specific expression. The expression patterns of the nsLTP genes in response to biotic and abiotic stresses were also investigated. Numerous nsLTP genes in cabbage were found to be related to the resistance to stress. Moreover, the expression patterns of some nsLTP paralogs in cabbage showed evident divergence. This study promotes the understanding of nsLTPs characteristics in cabbage and lays the foundation for further functional studies investigating cabbage nsLTPs.
Circulating Tumor DNA Measurements As Early Outcome Predictors in Diffuse Large B-Cell Lymphoma.

PURPOSE Outcomes for patients with diffuse large B-cell lymphoma remain heterogeneous, with existing methods failing to consistently predict treatment failure. We examined the additional prognostic value of circulating tumor DNA (ctDNA) before and during therapy for predicting patient outcomes. PATIENTS AND METHODS We studied the dynamics of ctDNA from 217 patients treated at six centers, using a training and validation framework. We densely characterized early ctDNA dynamics during therapy using cancer personalized profiling by deep sequencing to define response-associated thresholds within a discovery set. These thresholds were assessed in two independent validation sets. Finally, we assessed the prognostic value of ctDNA in the context of established risk factors, including the International Prognostic Index and interim positron emission tomography/computed tomography scans. RESULTS Before therapy, ctDNA was detectable in 98% of patients; pretreatment levels were prognostic in both front-line and salvage settings. In the discovery set, ctDNA levels changed rapidly, with a 2-log decrease after one cycle (early molecular response [EMR]) and a 2.5-log decrease after two cycles (major molecular response [MMR]) stratifying outcomes. In the first validation set, patients receiving front-line therapy achieving EMR or MMR had superior outcomes at 24 months (EMR: EFS, 83% v 50%; P = .0015; MMR: EFS, 82% v 46%; P < .001). EMR also predicted superior 24-month outcomes in patients receiving salvage therapy in the first validation set (EFS, 100% v 13%; P = .011). The prognostic value of EMR and MMR was further confirmed in the second validation set. In multivariable analyses including International Prognostic Index and interim positron emission tomography/computed tomography scans across both cohorts, molecular response was independently prognostic of outcomes, including event-free and overall survival. CONCLUSION Pretreatment ctDNA levels and molecular responses are independently prognostic of outcomes in aggressive lymphomas. These risk factors could potentially guide future personalized risk-directed approaches.
Effective Extracting Method for Electromagnetic Parameters of Periodically Loaded Substrate Integrated Waveguide Units

An effective approach for electromagnetic characterization of periodically loaded substrate integrated waveguide (SIW) units is presented. Anisotropic material dispersion analysis is carried out to provide a theoretical basis for extracting the effective permeability tensor of the unit structure. A detailed procedure is described in this paper, and applied to an improved pol-yline-patterned unit cell. The new structure improves the relative effective permeability by 0.25 compared to the original topology over the entire frequency band of interest. Further, a double-layer loading topology is studied and a relative effective permeability of 3.25 is obtained. A set of comparison tests based on SIW resonators loaded with proposed unit cells exhibits an up to 66% size-reduction. Less than 1.4% of the relative error is achieved, illustrating its suitability to explore the miniaturization potentials of any type of unit cell and with it to make an accurate evaluation of periodic loading SIW performance.
Automatic Vehicle type Classification with Convolutional Neural Networks

This paper proposes a convolutional neural network model for classification of vehicle types with low-resolution images from a frontal perspective. This characteristic can be useful to the development of systems with limited resources, like embedded systems. We trained the model as a multinomial logistic regression where cross-entropy of the ground truth labels and the model's prediction estimates the error. To prevent overfitting, we performed data augmentation in the training dataset and regularized the model using the dropout method. Experimental results in a subset of the BIT-Vehicle Dataset with samples uniformly distributed between classes shows that the model achieves an accuracy of 93.90%. We conclude that the model is discriminative and capable of generalizing the patterns of the vehicle type classification task.
Let Me Out! Evaluating the Effectiveness of Quarantining Compromised Users in Walled Gardens

In the fight to clean up malware-infected machines, notifications from Internet Service Providers (ISPs) to their customers play a crucial role. Since stand-alone notifications are routinely ignored, some ISPs have invested in a potentially more effective mechanism: quarantining customers in so-called walled gardens. We present the first empirical study on user behavior and remediation effectiveness of quarantining infected machines in broadband networks. We analyzed 1,736 quarantining actions involving 1,208 retail customers of a medium-sized ISP in the period of April-October 2017. The first two times they are quarantined, users can easily release themselves from the walled garden and around two-thirds of them use this option. Notwithstanding this easy way out, we find that 71% of these users have actually cleaned up the infection during their first quarantine period and, of the recidivists, 48% are cleaned after their second quarantining. Users who do not self-release either contact customer support (30%) or are released automatically after 30 days (3%). They have even higher cleanup rates. Reinfection rates are quite low and most users get quarantined only once. Users that remain infected spend less time in the walled garden during subsequent quarantining events, without a major drop in cleanup rates. This suggests there are positive learning effects, rather than mere habituation to being notified and self-releasing from the walled garden. In the communications with abuse and support staff, a fraction of quarantined users ask for additional help, request a paid technician, voice frustration about being cut off, or threaten to cancel their subscriptions. All in all, walled gardens seem to be a relatively effective and usable mechanism to improve the security of end users. We reflect on our main findings in terms of how to advance this industry best practice for botnet mitigation by ISPs.
A New Synchronization Method for Direct Sequence Spectrum Spread Based Systems

Abstract For precise indoor localization accurate synchronization is necessary. In this paper we propose a new synchronization method for direct sequence spread spectrum modulation based systems, which enables a more accurate correlation peak detection. We provide comprehensive statistical analysis and numerical results for the decision error probability assuming both coherent and non-coherent receiving via an AWGN channel. The essence of the proposed method is the two overlapping correlators, which allows taking into account the statistically not independent noise components to reduce the error probability of the correlation peak detection.
Vertical Arbitration-Free 3-D NoCs

The vertical interlayer communication channel plays a critical role in defining the performance of a 3-D network-on-chip (NoC). In this paper, an arbitration-free design for the shared vertical channels is proposed. The proposed <italic>vertical arbitration-free</italic> 3-D NoC is compared with other 3-D NoC architectures using traditional synthetic traffic patterns and Rentian traffic emulating applications for chip multiprocessors. The results of the analysis show comparable performance in throughput, energy, and latency compared to a <italic>symmetric</italic> 3-D NoC with savings up to <inline-formula> <tex-math notation="LaTeX">$\approx { 20\%}$ </tex-math></inline-formula> in area. The proposed NoC is superior in performance to a 3-D NoC utilizing vertical arbitration with a similar area footprint.
Production of Physiologically Relevant Quantities of Hemostatic Proteins During Ex Situ Normothermic Machine Perfusion of Human Livers

Ex-situ normothermic machine perfusion (NMP) of donor livers is an emerging innovation in liver transplantation that has made its transition to clinical trials. NMP is applied in an effort to overcome ischemia-reperfusion injury associated with static cold storage, to improve the quality of sub-optimally functioning donor organs and to permit viability testing of potentially transplantable livers. The in-vivo physiological conditions maintained during ex-situ NMP necessitate the need for a perfusion fluid that mimics the composition of whole blood. To date, perfusion fluids used in NMP studies are composed of either plasma-based solutions or plasma-free solutions consisting of colloids such as Gelofusine1 . The latter avoids the use of human plasma which is scarce, costly and logistically challenging. This article is protected by copyright. All rights reserved.
Bragg Gratings Inscription in TS-Doped PMMA POF by Using 248-nm KrF Pulses

We demonstrate the Bragg gratings inscription in the 850-nm spectral region by using trans-4-stilbenemethanol-doped poly methyl methacrylate step-index optical fiber and a 248-nm krypton fluoride (KrF) excimer laser system. The gratings inscription only takes 0.4 s. A detailed study of the grating fabrication process using different pulse repetition rates is also reported. In addition, temperature, humidity, and strain sensitivities are measured to demonstrate the potentiality of these components for different sensing applications.
Propagation Characteristics of Mode-Selective Transmission Line

Propagation characteristics of mode-selective transmission line (MSTL) are systematically investigated in this work. Thanks to the frequency-enabled mode selectivity, different mechanisms are used to determine the phase and attenuation characteristics of MSTL over different frequency ranges. With the fullwave simulations, a direct correlation between phase constants of MSTL and related individual modes of interest is conducted, illustrating well-behaved variable phase characteristics of MSTL. For the attenuation characteristics of MSTL, conductor and dielectric losses are separately examined and compared to those of microstrip line and dielectric-filled rectangular waveguide (RWG). These analysis results are verified by the measured results of fabricated prototypes of MSTL, mlcrostrlp, and RWG up to 110 GHz.
Identifying high-impact operating states in power system reliability analysis

The reliability of a power system depends, among other things, on the operating states of the system. For reliability analysis for long-term planning purposes, it may be necessary to consider a large set of representative operating states, and clustering techniques can be applied to reduce this set to make the analysis computationally tractable. However, the values of reliability indices for the system may be dominated by the contributions from a relatively small number of high-impact operating states that are not easily captured in the analysis. The objective of this paper is to identify high-impact operating states in the context of power system reliability analysis based on clustering techniques. A secondary objective is to characterize features of these operating states to better understand how they could be recognized, prepared for, and if possible avoided. An approach and an algorithm are proposed, and they are illustrated using a reliability analysis case study for a region of the Norwegian transmission grid with realistic operating states for the Nordic power system.