Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning A Shared Transform Model for Skull to Digital Face Image Matching

Human skull identification is an arduous task, traditionally requiring the expertise of forensic artists and anthropologists. This paper is an effort to automate the process of matching skull images to digital face images, thereby establishing an identity of the skeletal remains. In order to achieve this, a novel Shared Transform Model is proposed for learning discriminative representations. The model learns robust features while reducing the intra-class variations between skulls and digital face images. Such a model can assist law enforcement agencies by speeding up the process of skull identification, and reducing the manual load. Experimental evaluation performed on two pre-defined protocols of the publicly available IdentifyMe dataset demonstrates the efficacy of the proposed model.
A Channel Model and Simulation Technique for Reproducing Channel Realizations With Predefined Stationary or Non-Stationary PSD

Recent communications standards, such as vehicle-to-vehicle and fifth generation, include applications where the transmitted signal encounters rapid changes of propagation scenarios, resulting in wireless links characterized as non-stationary (NS) channels. Hence, channel models that correctly explain and represent the measured time-varying channel statistics, and their associated simulation methods for testing purposes, are all required. Although the body of works devoted to NS channel modeling is vast, due to the complexity and variety of this problem, the provided NS statistics are defined only within a limited observation time, and therefore, the generated channel realizations do not include the changes between scenarios. In light of this problem, this paper introduces a channel model that mimics the continuous change of the mobile propagation channel via a continual renewal of channel parameters, in which all stationary and NS channels are represented under a unified structure. Theoretical and simulation results provided in this paper confirm that the proposed model reproduces stationary models with high accuracy. In addition, NS channel realizations with predefined time-varying power spectral density and time-varying envelope distributions are also shown in this paper, providing a means for testing modern communications systems.
Exploring the Mechanism of Flavonoids Through Systematic Bioinformatics Analysis

Flavonoids are the largest class of plant polyphenols, with common structure of diphenylpropanes, consisting of two aromatic rings linked through three carbons and are abundant in both daily diets and medicinal plants. Fueled by the recognition of consuming flavonoids to get better health, researchers became interested in deciphering how flavonoids alter the functions of human body. Here, systematic studies were performed on 679 flavonoid compounds and 481 corresponding targets through bioinformatics analysis. Multiple human diseases related pathways including cancers, neuro-disease, diabetes, and infectious diseases were significantly regulated by flavonoids. Specific functions of each flavonoid subclass were further analyzed in both target and pathway level. Flavones and isoflavones were significantly enriched in multi-cancer related pathways, flavan-3-ols were found focusing on cellular processing and lymphocyte regulation, flavones preferred to act on cardiovascular related activities and isoflavones were closely related with cell multisystem disorders. Relationship between chemical constitution fragment and biological effects indicated that different side chain could significantly affect the biological functions of flavonoids subclasses. Results will highlight the common and preference functions of flavonoids and their subclasses, which concerning their pharmacological and biological properties.
Novel acridine-based thiosemicarbazones as ‘turn-on' chemosensors for selective recognition of fluoride anion: a spectroscopic and theoretical study

New thiosemicarbazide-linked acridines 3a–c were prepared and investigated as chemosensors for the detection of biologically and environmentally important anions. The compounds 3a–c were found selective for fluoride (F−) with no affinity for other anions, i.e. −OAc, Br−, I−, HSO4−, SO42−, PO43−, ClO3−, ClO4−, CN− and SCN−. Further, upon the gradual addition of a fluoride anion (F−) source (tetrabutylammonium fluoride), a well-defined change in colour of the solution of probes 3a–c was observed. The anion-sensing process was studied in detail via UV–visible absorption, fluorescence and 1H-NMR experiments. Moreover, during the synthesis of acridine probes 3a–c nickel fluoride (NiF2), a rarely explored transition metal fluoride salt, was used as the catalyst. Theoretical studies via density functional theory were also carried out to further investigate the sensing and anion (F−) selectivity pattern of these probes.
Moving Target Defense Techniques: A Survey

As an active defense technique to change asymmetry in cyberattack-defense confrontation, moving target defense research has become one of the hot spots. In order to gain better understanding of moving target defense, background knowledge and inspiration are expounded at first. Based on it, the concept of moving target defense is analyzed. Secondly, literature analysis method is adopted to explain the design principles and system architecture of moving target defense. In addition, some relevant key techniques are introduced from the aspects of strategy generation, shuffling implementation, and performance evaluation. After that, the applications of moving target defense in different network architectures are illustrated. Finally, existing problems and future trend in this field are elaborated so as to provide a basis for further study.
Mammalian chromosome–telomere length dynamics

Individual chromosome arms have specific individual telomere lengths (TLs). Past studies within species have shown strong positive correlations between individual chromosome length and TL at that chromosome. While the reasons for these associations are unclear, the strength and consistency of the associations across disparate taxa suggest that this is important to telomere biology and should be explored further. If TL is primarily determined by chromosome length, then chromosome length should be considered and controlled for in cross-species analyses of TL. Here, we employ a cross-species approach to explore whether the chromosome length–TL association observed intraspecifically is a determinant of mean TL across species. Data were compiled from two studies characterizing TL across a range of mammalian taxa and analysed in a phylogenetic framework. We found no significant relationship between TL and chromosome size across mammals or within mammalians orders. The pattern trends in the expected direction and we suggest may be masked by evolutionary lag effects.
Efficient and Secure Access Control Scheme in the Standard Model for Vehicular Cloud Computing

Vehicular networking involves the storage, compute, and analysis of massive vehicular data. Vehicular cloud computing, as a special cloud computing platform, seamlessly combines vehicular ad hoc networks and conventional cloud computing. However, in the vehicular cloud computing, there is still the problem of unauthorized users accessing and stealing data. In the traditional ciphertext-policy attribute-based encryption (CP-ABE) scheme, a trusted central authority is employed to manage attributes and distribute keys. Based on multi-authority (MA) CP-ABE, we propose a secure and revocable access control scheme for vehicular cloud computing in this paper, in which the requester can decrypt the ciphertext with only a small amount of computation. We show that our MA-CP-ABE scheme can prevent static corruption of authorities in the standard model under the decisional q-parallel bilinear Diffie–Hellman exponent assumption. Theoretical analysis and experimental simulation results show that our scheme has lower communication cost and lower computational complexity than other schemes.
A Second-Order Sliding Mode Voltage Oriented Control of Three-Phase Active Front End Rectifier

This paper presents a cascaded proportional-integral and second-order sliding mode Voltage Oriented Control (VOC) for a three-phase Active Front End (AFE) rectifier in presence of operational constraints. The inner-loop is based on Sliding Mode Control (SMC) which controls the direct and quadrature components of line current in order to maintain the input power factor at unity. A proportional-integral (PI) control is employed to regulate the de-link voltage at its reference value. The SMC exhibits an excellent dynamic performance over the complete operating range due to its nonlinear nature and robustness to parametric variations. Moreover, it provides a chattering free control action with finite-time convergence. The performance of the developed controller is verified using simulations in MATLAB/Simulink on a 30kW three-phase AFE for a switching frequency of 5kHz. The results show an excellent dynamic performance both in terms of transient response and steady-state performance.
Attrition in the European Child Cohort IDEFICS/I.Family: Exploring Associations Between Attrition and Body Mass Index

Attrition may lead to bias in epidemiological cohorts, since participants who are healthier and have a higher social position are less likely to drop out. We investigated possible selection effects regarding key exposures and outcomes in the IDEFICS/I.Family study, a large European cohort on the etiology of overweight, obesity and related disorders during childhood and adulthood. We applied multilevel logistic regression to investigate associations of attrition with sociodemographic variables, weight status, and study compliance and assessed attrition across time regarding children's weight status and variations of attrition across participating countries. We investigated selection effects with regard to social position, adherence to key messages concerning a healthy lifestyle, and children's weight status. Attrition was associated with a higher weight status of children, lower children's study compliance, older age, lower parental education, and parent's migration background, consistent across time and participating countries. Although overweight (odds ratio 1.17, 99% confidence interval 1.05–1.29) or obese children (odds ratio 1.18, 99% confidence interval 1.03–1.36) were more prone to drop-out, attrition only seemed to slightly distort the distribution of children's BMI at the upper tail. Restricting the sample to subgroups with different attrition characteristics only marginally affected exposure-outcome associations. Our results suggest that IDEFICS/I.Family provides valid estimates of relations between socio-economic position, health-related behaviors, and weight status.
Harnessing the Cloud for Secure and Efficient Outsourcing of Non-negative Matrix Factorization

Non-negative matrix factorization (NMF) is the task of factoring a non-negative matrix into the product of two (smaller) non-negative matrices. As an important data analysis technique, NMF finds applications in many areas of science and engineering. Real-world NMF tasks often involve large-scale matrices and incur expensive computation costs. Consequently, we consider the cloud computing paradigm, where a resource-constrained client outsources the NMF task to a powerful but untrustworthy cloud. In many applications, the input of and the solution to the NMF task usually contain the client’s private information, which necessitates privacy-preserving outsourcing. In this paper, we first reveal the privacy breaches of a recent NMF outsourcing scheme. Then, for enhanced privacy protection, we employ certain matrix transformations and present a new construction, which can solve the NMF task in a masked yet verifiable manner. Theoretical analysis shows that our proposal is cheating-resistant, recoverable, and privacy-preserving. Experiments on synthetic and real-world data demonstrate that our proposal not only brings significant cost savings to a client but also accelerates the task solving.
On the Testability of Graph Partition Properties

In this work we study the testability of a family of graph partition properties that generalizes a family previously studied by Goldreich, Goldwasser, and Ron (Journal of the ACM, 1998 ). While the family studied by Goldreich et al. includes a variety of natural properties, such as k-colorability and containing a large cut, it does not include other properties, such as split graphs, and more generally (p, q)-colorable graphs, that should clearly be regarded as graph partition properties. The generalization we consider better captures the idea of partition properties by allowing to impose constraints on the edge-densities within and between parts (relative to the sizes of the parts). We denote the family studied in this work by GPP. We rst show that all properties in GPP have a testing algorithm whose query complexity is polynomial in 1/ , where is the given proximity parameter (and there is no dependence on the size of the graph). As the testing algorithm has two-sided error, we next address the question of which properties in GPP can be tested with one-sided error and query complexity polynomial in 1/ . We answer this question by establishing a characterization result. Namely, we de ne a subfamily GPP0,1 of GPP and show that every property P ∈ GPP0,1 is testable by a one-sided error algorithm that has query complexity poly(1/ ) and that if P ∈ GPP\GPP0,1 then it cannot have a one-sided error testing algorithm whose query complexity is independent of the input graph's size. ∗Tel Aviv University, yonatannakar@mail.tau.ac.il. †Tel Aviv University, danaron@tau.ac.il. ISSN 1433-8092 Electronic Colloquium on Computational Complexity, Report No. 185 (2018)
A Smart Transformer-Rectifier Unit for the More Electric Aircraft

In the framework of the More Electric Aircraft (MEA), an efficient and flexible power distribution system is of paramount importance. Considering the presence of both AC and DC loads at multiple voltage levels, the distribution system of the most modern aircrafts is intrinsically hybrid. In this scenario, the different buses are connected by AC/DC converters. The simplest approach is to use a Transformer-Rectifier Unit (TRU) based on a low-frequency transformer followed by passive rectifiers to perform the AC/DC conversion. This solution, however, is intrinsically uni-directional, introduces current harmonics in the AC side and can have a considerable size. This paper proposes the use of a Smart-TRU, based on a Cascaded H-Bridge topology and a multi-port DC/DC converter, to solve the issues of the traditional TRU, increasing the controllability of the system. Experiments show how the proposed STRU is resilient to faults in the AC side.
Primal Meaning Recommendation for Chinese Words and Phrases via Descriptions in On-line Encyclopedia

Polysemy is a very common phenomenon in modern languages. Most of previous work treat the multiple meanings of a word equally. However, under many circumstances, there exists a primal meaning for the word. Many of the new appearing meanings of the words are either originated from a primal meaning, or are merely literal references to the original word, e.g., apple (fruit), Apple (Inc), and Apple (movie). When constructing knowledge base from on-line encyclopedia data, it would be more efficient to be aware of the information about the importance of the senses. In this paper, we would like to explore a way to automatically recommend the primal meaning of a word based on the textual descriptions of the multiple meanings of a word from online encyclopedia websites. We propose a hybrid model that captures both the pattern of the description and the relationship between different descriptions with both distantly supervised and unsupervised models. The experiment results show that our method yields very good result with a p@1 score of 80.6%, and a MAP of 89.0%, surpassing the Word-Sum baseline by a big margin (P@1 is 62.7% and MAP is 76.8%).
Empirical study on touchless fingerprint recognition using a phone camera

Abstract. Existing methods for touchless fingerprint recognition using a phone camera have the difficulties to quickly verify and extract fingerprint images with high recognition accuracy. It is because specialized techniques for touchless fingerprint images were not provided for them. To overcome these difficulties, three methods are proposed. First, a finger-shaped guide is displayed on the phone screen to enable the user to position their fingers correctly and to focus the camera on the position to quickly produce a good fingerprint image. Second, the profile line tests at selected points on the guide are proposed to quickly determine whether the user’s fingers are properly placed according to the guide shape and to simplify the segmentation of fingerprint image regions. Third, a existing local structure-based matching method is improved for touchless fingerprint images, and a score-level fusion of the three finger matchings is performed to ensure high recognition accuracy. Experiments were performed using our custom-built database, where touchless fingerprint images were collected using a 13-MP mobile camera in various indoor and outdoor environments. Resulting error rates were between 0.50% and 1.04% depending on whether the image was captured indoors or outdoors.
An Ontology-Based Approach for Mining Radicalization Indicators from Online Messages

Detecting radicalization on social networks is crucial to the fight against violent extremism and terrorism. In most cases, online radicalization has clear warning indicators that can be detected at the early stages of the radicalization process. In this paper, we focus on mining radicalization indicators from online messages by exploiting structured domain knowledge. More precisely, we propose an approach to automatically annotate social messages with concepts from a domain ontology. Annotations are then exploited within an inference phase to identify the messages exhibiting a radicalization indicator. We conducted a set of experiments on a sample extracted from a public dataset that contains radicalized individuals along with their social messages (i.e. Tweets). Obtained results show the effectiveness of our approach compared to a baseline method.
A Three-Dimensional Stabilization Protocol for Time-Slotted Multi-hop Cognitive Radio Networks with Channel Hopping

Cognitive radio networks provide solutions for the coexistence of primary users (license holders) and secondary users within a licensed spectrum. In this paper, we present and assess a three-dimensional stabilization protocol for cognitive radio networks, addressing the dimensions time, channel, and space. For stabilization in time and space, nodes agree on a global time structure consisting of superslots and macroslots. For stabilization of network-wide channel usage, nodes determine and share global schedules, which assign channels of sufficient quality to macroslots. The stabilization protocol realizes a conservative strategy, whereby nodes only transmit on channels that have a sufficient locally measured quality and have been assigned in a recent schedule. Furthermore, the protocol is robust against topology changes. To assess the stabilization capability of the protocol, we introduce the notion of schedule-consistency, and evaluate the protocol performance in a series of ns-3 simulations.
Noninvasive scoring systems predict hepatic and extra-hepatic cancers in patients with nonalcoholic fatty liver disease

Background Liver fibrosis predicts liver-related morbidity and mortality in patients with non-alcoholic fatty liver disease (NAFLD). Non-invasive scores correlate with the degree of liver fibrosis in these patients. Aims and methods To investigate the accuracy of noninvasive scoring systems in predicting long-term outcomes and cancer incidence of patients with NAFLD, we performed a single-center retrospective study of patients with biopsy proven NAFLD. Mean follow up period was 100 months. Outcomes included liver-related complications, hospitalizations, overall mortality and the development of any malignancies. Results 32 patients had advanced fibrosis (F3-F4) per biopsy at baseline and 121 patients had mild to moderate fibrosis (F0-F2). Both advanced histologic fibrosis stage as well as higher non-invasive scores predicted repeated hospitalizations and longer hospitalization stays. In a multivariate analysis, liver fibrosis (p = 0.002), FIB-4 score (p<0.001), NFS (p<0.001) but not APRI score (p = 0.07) were predictors of overall mortality, and the occurrence of malignancies was associated with higher APRI (p<0.001), FIB-4 (p<0.001) and NFS (p = 0.008) scores, but not with advanced fibrosis, as determined by liver biopsy (p = 0.105). Conclusions In NAFLD patients, noninvasive scoring systems are good predictors of morbidity and mortality and may have an additive value in predicting the development of hepatic and extra-hepatic cancers.
Heritability, selection, and the response to selection in the presence of phenotypic measurement error: effects, cures, and the role of repeated measurements

Quantitative genetic analyses require extensive measurements of phenotypic traits, a task that is often not trivial, especially in wild populations. On top of instrumental measurement error, some traits may undergo transient (i.e. non-persistent) fluctuations that are biologically irrelevant for selection processes. These two sources of variability, which we denote here as measurement error in a broad sense, are possible causes for bias in the estimation of quantitative genetic parameters. We illustrate how in a continuous trait transient effects with a classical measurement error structure may bias estimates of heritability, selection gradients, and the predicted response to selection. We propose strategies to obtain unbiased estimates with the help of repeated measurements taken at an appropriate temporal scale. However, the fact that in quantitative genetic analyses repeated measurements are also used to isolate permanent environmental instead of transient effects, requires a re-assessment of the information content of repeated measurements. To do so, we propose to distinguish “short-term” from “long-term” repeats, where the former capture transient variability and the latter the permanent effects. We show how the inclusion of the corresponding variance components in quantitative genetic models yields unbiased estimates of all quantities of interest, and we illustrate the application of the method to data from a Swiss snow vole population.
Identification of a panel of MYC and Tip60 co-regulated genes functioning primarily in cell cycle and DNA replication

We recently reported that adenovirus E1A enhances MYC association with the NuA4/Tip60 histone acetyltransferase (HAT) complex to activate a panel of genes enriched for DNA replication and cell cycle. Genes from this panel are highly expressed in examined cancer cell lines when compared to normal fibroblasts. To further understand gene regulation in cancer by MYC and the NuA4 complex, we performed RNA-seq analysis of MD-MB231 breast cancer cells following knockdown of MYC or Tip60 - the HAT enzyme of the NuA4 complex. We identify here a panel of 424 genes, referred to as MYC-Tip60 co-regulated panel (MTcoR), that are dependent on both MYC and Tip60 for expression and likely co-regulated by MYC and the NuA4 complex. The MTcoR panel is most significantly enriched in genes involved in cell cycle and/or DNA replication. In contrast, genes repressed by shMYC but not by shTip60 (224 genes) have a low significance of enrichment in identifiable biological processes other than cell cycle and DNA replication. Genes repressed by shTip60 but not by shMYC (102 genes) have no significant identifiable gene enrichment. We propose that MYC cooperates with the NuA4 complex to activate the MTcoR panel of genes to promote DNA replication and cell cycle.