Miracle-dz/UniFAR-FTUs huggingface dataset:
Low-quality Fingerprint Classification

Fingerprint recognition systems mainly use minutiae points information. As shown in many previous research works, fingerprint images do not always have good quality to be used by automatic fingerprint recognition systems. To tackle this challenge, in this thesis, we are focusing on very low-quality fingerprint images, which contain several well-known distortions such as dryness, wetness, physical damage, presence of dots, and blurriness. We develop an efficient, with high accuracy, deep neural network algorithm, which recognizes such low-quality fingerprints. The experimental results have been conducted on real low-quality fingerprint database, and the achieved results show the high performance and robustness of the introduced deep network technique. The VGG16 based deep network achieves the highest performance of 93% for dry and the lowest of 84% for blurred fingerprint classes.
Efficacy of Vaginally Administered Gel Containing Emtricitabine and Tenofovir Against Repeated Rectal Simian Human Immunodeficiency Virus Exposures in Macaques

Vaginal microbicides containing antiretrovirals (ARVs) have shown to prevent vaginally acquired human immunodeficiency virus (HIV), but these products may not protect women who engage in anal sex. Intravaginal dosing with ARVs has shown to result in drug exposures in rectal tissues, thus raising the possibility of dual compartment protection. To test this concept, we investigated whether intravaginal dosing with emtricitabine (FTC)/tenofovir (TFV) gel, which fully protected macaques against repeated vaginal exposures to simian human immunodeficiency virus (SHIV), protects against rectal SHIV exposures. Pharmacokinetic studies revealed rapid distribution of FTC and TFV to rectal tissues and luminal fluids, albeit at concentrations 1-2 log10 lower than those in the vaginal compartment. Efficacy measurements against repeated rectal SHIV challenges demonstrated a 4.5-fold reduction in risk of infection in macaques that received intravaginal FTC/TFV compared to placebo gel (P = .047; log-rank test). These data support the concept of dual compartment protection by vaginal dosing and warrants developing ARV-based vaginal products with improved bidirectional dosing.
Blind Predicting Similar Quality Map for Image Quality Assessment

A key problem in blind image quality assessment (BIQA) is how to effectively model the properties of human visual system in a data-driven manner. In this paper, we propose a simple and efficient BIQA model based on a novel framework which consists of a fully convolutional neural network (FCNN) and a pooling network to solve this problem. In principle, FCNN is capable of predicting a pixel-by-pixel similar quality map only from a distorted image by using the intermediate similarity maps derived from conventional full-reference image quality assessment methods. The predicted pixel-by-pixel quality maps have good consistency with the distortion correlations between the reference and distorted images. Finally, a deep pooling network regresses the quality map into a score. Experiments have demonstrated that our predictions outperform many state-of-the-art BIQA methods.
Non-linear Heart Rate Variability as a Discriminator of Internalizing Psychopathology and Negative Affect in Children With Internalizing Problems and Healthy Controls

Background: Internalizing psychopathology and dysregulated negative affect are characterized by dysregulation in the autonomic nervous system and reduced heart rate variability (HRV) due to increases in sympathetic activity alongside reduced vagal tone. The neurovisceral system is however, a complex nonlinear system, and nonlinear indices related to psychopathology are so far less studied in children. Essential nonlinear properties of a system can be found in two main domains: the informational domain and the invariant domain. sample entropy (SampEn) is a much-used method from the informational domain, while detrended fluctuation analysis (DFA) represents a widely-used method from the invariant domain. To see if nonlinear HRV can provide information beyond linear indices of autonomic activation, this study investigated SampEn and DFA as discriminators of internalizing psychopathology and negative affect alongside measures of vagally-mediated HRV and sympathetic activation. Material and Methods: Thirty-Two children with internalizing difficulties and 25 healthy controls (aged 9–13) were assessed with the Child Behavior Checklist and the Early Adolescent Temperament Questionnaire, Revised, giving an estimate of internalizing psychopathology, negative affect and effortful control, a protective factor against psychopathology. Five minute electrocardiogram and impedance cardiography recordings were collected during a resting baseline, giving estimates of SampEn, DFA short-term scaling exponent α1, root mean square of successive differences (RMSSD), and pre-ejection period (PEP). Between-group differences and correlations were assessed with parametric and non-parametric tests, and the relationships between cardiac variables, psychopathology and negative affect were assessed using generalized linear modeling. Results: SampEn and DFA were not significantly different between the groups. SampEn was weakly negatively related to heart rate (HR) in the controls, while DFA was moderately negatively related to RMSSD in both groups, and moderately positively related to HR in the clinical sample. SampEn was significantly associated with internalizing psychopathology and negative affect. DFA was significantly related to internalizing psychopathology. Conclusions: Higher invariant self-similarity was linked to less psychopathology. Higher informational entropy was related to less psychopathology and less negative affect, and may provide an index of the organizational flexibility of the neurovisceral system.
Association Between Reappearance of Myeloperoxidase – Antineutrophil Cytoplasmic Antibody and Relapse in Antineutrophil Cytoplasmic Antibody – Associated Vasculitis Subgroup Analysis of Nationwide Prospective Cohort Studies

Haruki Watanabe , Ken-Ei Sada, Yoshinori Matsumoto, Masayoshi Harigai, Koichi Amano, Hiroaki Dobashi, Shouichi Fujimoto, Joichi Usui, Kunihiro Yamagata, Tatsuya Atsumi, Shogo Banno, Takahiko Sugihara, Yoshihiro Arimura, Seiichi Matsuo, Hirofumi Makino, the Japan Research Committee of the Ministry of Health, Labour, and Welfare for Intractable Vasculitis, and the Research Committee of Intractable Renal Disease of the Ministry of Health, Labour, and Welfare of Japan
Temporal hints in the cultural heritage discourse: what can an ontology of time as it is worded reveal?

Time is an indispensable component of cultural heritage (CH) information: implementing appropriate knowledge models carry crucial importance in order to provide deeper understanding of heritage elements' evolution, to uncover concurrences, and to weigh quality factors. It is a challenging task though due to the uncertain characteristics of temporal data, and to the wording of time in the CH discourse. Existing KR models are either not designed for these distinctive characteristics, or spatial aspects tend to upstage the temporal dimension. This research aims at deciphering and proposing a formal representation of the way temporal hints are formalized in historical narratives. An OWL temporal ontology is introduced that provides a core support mechanism allowing for a semantic representation of temporal statements, and for structural analysis. The objective is to facilitate the cross-examination of temporal hints in and across CH collections so that specialists can have extensive reading possibilities of heritage information.
BLAST-XYPlot Viewer: A Tool for Performing BLAST in Whole-Genome Sequenced Bacteria/Archaea and Visualize Whole Results Simultaneously

One of the most commonly used tools to compare protein or DNA sequences against databases is BLAST. We introduce a web tool that allows the performance of BLAST-searches of protein/DNA sequences in whole-genome sequenced bacteria/archaea, and displays a large amount of BLAST-results simultaneously. The circular bacterial replicons are projected as horizontal lines with fixed length of 360, representing the degrees of a circle. A coordinate system is created with length of the replicon along the x-axis and the number of replicon used on the y-axis. When a query sequence matches with a gene/protein of a particular replicon, the BLAST-results are depicted as an “x,y” position in a specially adapted plot. This tool allows the visualization of the results from the whole data to a particular gene/protein in real time with low computational resources.
Recent Advances in Nanosuspension Technology for Drug Delivery.

BACKGROUND Discovery and development of BCS class 1 drugs through high throughput screening is one of the biggest challenge faced by formulation scientist. METHODS There are a number of approaches that have been exploited to enhance the solubility and permeability of drugs. Among them, development of nanosuspension has offered several benefits. These techniques may increase effective surface area due to nanonization of drug particles and further increases saturation solubility and dissolution properties for improved bioavailability. Various development methods are patented which are cost effective and easy to scale up. CONCLUSION Several unique features of nanosuspension make it a versatile delivery system for different routes of administration including oral, dermal, ocular, parenteral and pulmonary. The present review is focused on preparatory techniques and formulation considerations of nanosuspension. Brief information about evaluation parameters, applications of nanosuspension in drug delivery and patented and marketed products available is also discussed.
Human Body Poses Recognition Using Neural Networks with Class Based Data Augmentation

Information technologies and continuous development of information technologies have made it possible for computers to see and learn. What we see with our eyes, can be divided into pixels and fed to a computer, giving the computer the ability to see and learn based on the pixel values. Based on the input values computers can learn to recognize different objects depending on the examples taught to them. There are many possible applications for computers to see and learn in order to solve new tasks. In this thesis, we propose a framework, capable of automatically recognizing human body poses from a single image, obtained with a traditional low-cost camera. Our approach combines computer vision with neural networks to detect a human from an image. This process starts by extracting the silhouette from an image and then using a neural network to recognize body poses based on the extracted silhouettes. In order to match detected silhouettes with body poses, the neural network was trained with an already classified augmented dataset of preprocessed images depicting silhouettes. According to our results, we show that the proposed method provides promising results with acceptable accuracy.
Fully Understanding the Hashing Trick

Feature hashing, also known as {\em the hashing trick}, introduced by Weinberger et al. (2009), is one of the key techniques used in scaling-up machine learning algorithms. Loosely speaking, feature hashing uses a random sparse projection matrix $A : \mathbb{R}^n \to \mathbb{R}^m$ (where $m \ll n$) in order to reduce the dimension of the data from $n$ to $m$ while approximately preserving the Euclidean norm. Every column of $A$ contains exactly one non-zero entry, equals to either $-1$ or $1$. Weinberger et al. showed tail bounds on $\|Ax\|_2^2$. Specifically they showed that for every $\varepsilon, \delta$, if $\|x\|_{\infty} / \|x\|_2$ is sufficiently small, and $m$ is sufficiently large, then $$\Pr[ \; | \;\|Ax\|_2^2 - \|x\|_2^2\; | < \varepsilon \|x\|_2^2 \;] \ge 1 - \delta \;. $$ These bounds were later extended by Dasgupta \etal (2010) and most recently refined by Dahlgaard et al. (2017), however, the true nature of the performance of this key technique, and specifically the correct tradeoff between the pivotal parameters $\|x\|_{\infty} / \|x\|_2, m, \varepsilon, \delta$ remained an open question. We settle this question by giving tight asymptotic bounds on the exact tradeoff between the central parameters, thus providing a complete understanding of the performance of feature hashing. We complement the asymptotic bound with empirical data, which shows that the constants "hiding" in the asymptotic notation are, in fact, very close to $1$, thus further illustrating the tightness of the presented bounds in practice.
Venous Thromboembolism After Intraventricular Hemorrhage: Results From the CLEAR III Trial

BACKGROUND Venous thromboembolism (VTE) after intracerebral hemorrhage is well studied, but data on patients with spontaneous intraventricular hemorrhage (IVH) are limited. OBJECTIVE To study the factors associated with VTE, association between VTE and clinical outcomes in IVH, and safety of VTE chemoprophylaxis in IVH treated with intraventricular catheters and thrombolysis. METHODS Retrospective cohort study of patients enrolled in the CLEAR III trial, a multicenter, randomized trial comparing external ventricular drainage, with administration of intraventricular alteplase vs placebo, for obstructive IVH. Predictor variable was incident VTE in the first 30 d. Outcome measures were factors associated with VTE, and death/severe disability (modified Rankin Score 4-6) at 6 mo. RESULTS Of the 500 patients with IVH, VTE occurred in 59 patients (11.8%) within the first 30 d. VTE chemoprophylaxis was initiated in 412 (82.4%) patients, but before VTE diagnosis in only 401 (80.2%) at median of 4 d (interquartile range, 1-8) from IVH onset, and was not associated with intracranial bleeding or catheter tract hemorrhage. In the multivariate logistic regression analysis, infection within 30 d (odds ratio, 1.80; confidence interval, 1.03-3.17) was significantly associated with higher odds of VTE occurrence. Starting VTE chemoprophylaxis after 72 h was additionally associated with VTE occurrence after the first week. CONCLUSION Infection and delay in timely initiation of VTE chemoprophylaxis were associated with VTE occurrence. VTE chemoprophylaxis in IVH appears safe and should not be delayed beyond standard care policies for ICH including when intraventricular catheter placement and thrombolytic therapy are performed.
Mechanistic kinetic modeling generates system-independent P-glycoprotein mediated transport elementary rate constants for inhibition and, in combination with 3D SIM microscopy, elucidates the importance of microvilli morphology on P-glycoprotein mediated efflux activity

ABSTRACT Introduction: In vitro transporter kinetics are typically analyzed by steady-state Michaelis-Menten approximations. However, no clear evidence exists that these approximations, applied to multiple transporters in biological membranes, yield system-independent mechanistic parameters needed for reliable in vivo hypothesis generation and testing. Areas covered: The classical mass action model has been developed for P-glycoprotein (P-gp) mediated transport across confluent polarized cell monolayers. Numerical integration of the mass action equations for transport using a stable global optimization program yields fitted elementary rate constants that are system-independent. The efflux active P-gp was defined by the rate at which P-gp delivers drugs to the apical chamber, since as much as 90% of drugs effluxed by P-gp partition back into nearby microvilli prior to reaching the apical chamber. The efflux active P-gp concentration was 10-fold smaller than the total expressed P-gp for Caco-2 cells, due to their microvilli membrane morphology. The mechanistic insights from this analysis are readily extrapolated to P-gp mediated transport in vivo. Expert opinion: In vitro system-independent elementary rate constants for transporters are essential for the generation and validation of robust mechanistic PBPK models. Our modeling approach and programs have broad application potential. They can be used for any drug transporter with minor adaptations.
Development and Performance Evaluation of a Concurrency Control Technique in Object-Oriented Database Systems

In this work, we propose a concurrency control scheme in object-oriented database (OODB). Since an OODB provides complex modeling power than the conventional relational databases, a concurrency control technique in OODB is also rather complicated and has influence on the overall performance. Thus, it is very important to develop a concurrency control technique with less overhead. The proposed scheme deals with class hierarchy that is a key concept in OODBs. The proposed scheme is developed on implicit locking scheme. Also, the proposed scheme is designed using data access frequency in order to reduce locking overhead than implicit locking. It means that, if access frequency information is not available, the proposed scheme works just like the existing implicit locking, In our work, the correctness of the proposed scheme is proved. The performance is analyzed depending on access types. Also, it is proved that our scheme performs works much better than the implicit locking does.
Adaptive finite element technique for cutting in surgical simulation (Cum Laude Poster Award)

Pre-computed finite element methods are valuable because of their extreme speed and high accuracy for soft tissue modeling, but they are not suitable for surgical incision simulation. In this paper we present an adaptive algorithm for finite element computation based on a preprocessing approach. It inverts the global stiffness matrix in a pre-computing stage and then simulates each cutting step by updating two lists of basic components iteratively with some localization techniques. This method allows a fast and physically accurate simulation of incision procedures.
Cost-Sensitive Multitask Active Learning for Characterization of Urban Environments With Remote Sensing

We propose a novel cost-sensitive multitask active learning (CSMTAL) approach. Cost-sensitive active learning (CSAL) methods were recently introduced to specifically minimize labeling efforts emerging from ground surveys. Here, we build upon a CSAL method but compile a set of unlabeled samples from a learning set which can be considered relevant with respect to multiple target variables. To this purpose, a multitask meta-protocol based on alternating selection is implemented. It comprises a so-called one-sided selection (i.e., single-task AL selection for a reference target variable with simultaneous labeling of the residual target variables) with a changing leading variable in an iterative selection process. Experimental results are obtained for the city of Cologne, Germany. The target variables to be predicted, using features from remote sensing and a support vector machine framework, are “building type” and “roof type. ” Comparative model accuracy evaluations underline the capability of the CSMTAL method to provide beneficial solutions with respect to a random sampling strategy and noncost-sensitive multitask active sampling.
Fluorescent Proteins for Investigating Biological Events in Acidic Environments

The interior lumen of acidic organelles (e.g., endosomes, secretory granules, lysosomes and plant vacuoles) is an important platform for modification, transport and degradation of biomolecules as well as signal transduction, which remains challenging to investigate using conventional fluorescent proteins (FPs). Due to the highly acidic luminal environment (pH ~ 4.5–6.0), most FPs and related sensors are apt to lose their fluorescence. To address the need to image in acidic environments, several research groups have developed acid-tolerant FPs in a wide color range. Furthermore, the engineering of pH insensitive sensors, and their concomitant use with pH sensitive sensors for the purpose of pH-calibration has enabled characterization of the role of luminal ions. In this short review, we summarize the recent development of acid-tolerant FPs and related functional sensors and discuss the future prospects for this field.
Local noise reduction for emphysema scoring in low-dose CT images

Computed Tomography (CT) has become the new reference standard for quantification of emphysema. The most popular measure for emphysema derived from CT is the Pixel Index (PI), which expresses the fraction of the lung volume with abnormally low intensity values. As PI is calculated from a single, fixed threshold on intensity, this measure is strongly influenced by noise. This effect shows up clearly when comparing the PI score for a high-dose scan to the PI score for a low-dose (i.e. noisy) scan of the same subject. This paper presents a class of noise filters that make use of a local noise estimate to specify the filtering strength: Local Noise Variance Weighted Averaging (LNVWA). The performance of the filter is assessed by comparing high-dose and low-dose PI scores for 11 subjects. LNVWA improves the reproducibility of high-dose PI scores: For an emphysema threshold of -910 HU, the root-mean-square difference in PI score drops from 10% of the lung volume to 3.3% of the lung volume if LNVWA is used.
Phase Fault Protection Scheme for Reliable Operation of Microgrids

In a microgrid, the overcurrent relays see significant variation in the short-circuit currents during transition between grid-connected and islanded modes of operation. Further, with the disconnection of one or more distributed generators (DGs), the changes in the short-circuit currents are observed by the relays. As a consequence, the existing protection scheme may either delay the relay operation or fail to operate. This paper proposes an optimal and single protection scheme suitable for all operating modes of microgrid along with every type of phase faults in the system, i.e., three-phase symmetrical ($3\text{-}\phi$ ), line-to-line, and double line-to-ground faults. The optimal setting of the directional overcurrent relays is obtained using a metaheuristic-based optimization algorithm. Moreover, the proposed scheme is validated using GE Multilin, model-750/760, overcurrent relay in ETAP (industrial simulation software) on the modified IEEE 9-bus 4-DG microgrid.
The ZJU-EDL System for Entity Discovery and Linking at TAC KBP 2015

This paper describes a fully pipelined EDL system implemented by ZJU-DCD-EDL team for the TAC 2015 EDL (Entity Discovery and Linking) task. Our system mainly focuses on the linking of English name mentions. It is composed by mention extraction, candidate generation, candidate ranking, query expansion re-ranking, MLP re-ranking and NIL clustering modules. In candidate ranking stage, we propose a simple but effective measure named IWHR (Important Word Hit Rate) to improve the ranking performance. Apart from the approach that is used to deliver the ﬁnal result, this paper also describes some other latest methods that we tried but fail to yield the expected superior results.