Miracle-dz/UniFAR-FTUs huggingface dataset:
Intractable problems require novel solutions: it's time to get serious about developing a gonorrhoea vaccine

Neisseria gonorrhoeae , the causative agent of the sexually transmitted infection gonorrhoea, is an ancient disease with biblical references.1 Despite ongoing efforts towards treatment and prevention, gonorrhoea remains a major public health problem worldwide with an estimated global incidence of 106 million cases/year,2 leading to direct and indirect costs that exceed $1 billion/year in the USA alone.3 The clinical outcomes of gonococcal infection range from asymptomatic infection to severe sequelae (reviewed in refs. 4, 5). Symptomatic infection typically presents as urethritis in males and cervicitis in females; however, mucosal infections of the rectum, pharynx and eye are also reported. In addition, asymptomatic infections occur in 50–80% of infected females and 1%–40% of infected males, which, if left undiagnosed or untreated, can lead to sequelae that include urogenital tract abscesses, pelvic inflammatory disease, adverse pregnancy outcomes, infertility and neonatal complications. Infection with N. gonorrhoeae also increases the risk of acquiring and transmitting HIV. Current attempts to control gonorrhoea include safe-sex education, as well as prompt diagnosis and antibiotic treatment of infected persons and their recent sex partners. While diagnostics (ie, nucleic acid amplification tests or bacterial culture) are highly sensitive and specific,6 education and routine screening are not sufficient to stem the spread of gonorrhoea.7 This is especially true in light of the fact that extensively drug-resistant strains with high-level resistance to the expanded-spectrum cephalosporins (ie, ceftriaxone and cefixime) have been isolated from around the world.1 Cephalosporins are the last line of defence for treating gonorrhoea, and the emergence of resistance to these drugs means that more costly and invasive treatment is now required. The current recommendations for the treatment of uncomplicated infections include the use of dual antibiotic therapy with ceftriaxone (250 mg intramuscular injection in a single dose) …
Hybrid dose calculation: a dose calculation algorithm for microbeam radiation therapy

Microbeam radiation therapy (MRT) is still a preclinical approach in radiation oncology that uses planar micrometre wide beamlets with extremely high peak doses, separated by a few hundred micrometre wide low dose regions. Abundant preclinical evidence demonstrates that MRT spares normal tissue more effectively than conventional radiation therapy, at equivalent tumour control. In order to launch first clinical trials, accurate and efficient dose calculation methods are an inevitable prerequisite. In this work a hybrid dose calculation approach is presented that is based on a combination of Monte Carlo and kernel based dose calculation. In various examples the performance of the algorithm is compared to purely Monte Carlo and purely kernel based dose calculations. The accuracy of the developed algorithm is comparable to conventional pure Monte Carlo calculations. In particular for inhomogeneous materials the hybrid dose calculation algorithm out-performs purely convolution based dose calculation approaches. It is demonstrated that the hybrid algorithm can efficiently calculate even complicated pencil beam and cross firing beam geometries. The required calculation times are substantially lower than for pure Monte Carlo calculations.
Analysis of opportunistic localization algorithms based on the linear matrix inequality method

With the increasing spread of use of mobile devices there is a growing demand for location-aware services in a wide variety of contexts. Yet providing an accurate location estimation is difficult when considering cheap off-the-shelf mobile devices, particularly in indoors or urban environments. In this paper we define and compare different localization algorithms based on an opportunistic paradigm. In particular, we focus on range-free and range-based localization techniques that are based on the solution of a Linear Matrix Inequalities (LMI) problem. The performance achievable with this approach is analyzed in different scenarios, through extensive simulation campaign. Results show that LMI-based schemes, especially the range-based one, are potentially capable of yielding very accurate localization even after a limited number of opportunistic exchange, though performance is rather sensitive to the accuracy of the other nodes' self-localization and to the randomness of the radio channel.
VERTIcal Grid lOgistic regression (VERTIGO)

OBJECTIVE To develop an accurate logistic regression (LR) algorithm to support federated data analysis of vertically partitioned distributed data sets. MATERIAL AND METHODS We propose a novel technique that solves the binary LR problem by dual optimization to obtain a global solution for vertically partitioned data. We evaluated this new method, VERTIcal Grid lOgistic regression (VERTIGO), in artificial and real-world medical classification problems in terms of the area under the receiver operating characteristic curve, calibration, and computational complexity. We assumed that the institutions could "align" patient records (through patient identifiers or hashed "privacy-protecting" identifiers), and also that they both had access to the values for the dependent variable in the LR model (eg, that if the model predicts death, both institutions would have the same information about death). RESULTS The solution derived by VERTIGO has the same estimated parameters as the solution derived by applying classical LR. The same is true for discrimination and calibration over both simulated and real data sets. In addition, the computational cost of VERTIGO is not prohibitive in practice. DISCUSSION There is a technical challenge in scaling up federated LR for vertically partitioned data. When the number of patients m is large, our algorithm has to invert a large Hessian matrix. This is an expensive operation of time complexity O(m(3)) that may require large amounts of memory for storage and exchange of information. The algorithm may also not work well when the number of observations in each class is highly imbalanced. CONCLUSION The proposed VERTIGO algorithm can generate accurate global models to support federated data analysis of vertically partitioned data.
Integer overflow vulnerabilities detection in software binary code

In this paper1 we propose a new approach to detect integer overflow vulnerabilities in executable x86-architecture code. The approach is based on symbolic execution of the code and the dual representation of memory. We build truncated control flow graph, based on the machine code. Layers in that graph are checked for the feasibility of vulnerability conditions. The proposed methods were implemented and experimentally tested on executable code.
The shortest matching path based on novel cycle consistency

Category-level image matching is extremely challenging due to various intra-class variations. To tackle the large variations, we propose an algorithm to jointly estimate the dense correspondence for image set, which reformulates image set alignment into the problem of shortest path searching. We propose a novel tri-image cycle-consistency to measure the matching “distance” between two image, which is further used to improve the pair-wise dense correspondence. Meanwhile, we utilize CNN feature pyramid to achieve pair-wise image matching hierarchically. Extensive experiments and analysis demonstrate the superiority of our method in matching images with challenging variations.
A translational silencing function of MCPIP1/Regnase-1 specified by the target site context

Abstract The expression of proteins during inflammatory and immune reactions is coordinated by post-transcriptional mechanisms. A particularly strong suppression of protein expression is exerted by a conserved translational silencing element (TSE) identified in the 3′ UTR of NFKBIZ mRNA, which is among the targets of the RNA-binding proteins Roquin-1/2 and MCPIP1/Regnase-1. We present evidence that in the context of the TSE MCPIP1, so far known for its endonuclease activity toward mRNAs specified by distinct stem–loop (SL) structures, also suppresses translation. Overexpression of MCPIP1 silenced translation in a TSE-dependent manner and reduced ribosome occupancy of the mRNA. Correspondingly, MCPIP1 depletion alleviated silencing and increased polysomal association of the mRNA. Translationally silenced NFKBIZ or reporter mRNAs were mostly capped, polyadenylated and ribosome associated. Furthermore, MCPIP1 silenced also cap-independent, CrPV-IRES-dependent translation. This suggests that MCPIP1 suppresses a post-initiation step. The TSE is predicted to form five SL structures. SL4 and 5 resemble target structures reported for MCPIP1 and together were sufficient for MCPIP1 binding and mRNA destabilization. Translational silencing, however, required SL1–3 in addition. Thus the NFKBIZ TSE functions as an RNA element in which sequences adjacent to the site of interaction with MCPIP1 and dispensable for accelerated mRNA degradation extend the functional repertoire of MCPIP1 to translational silencing.
A Blade Tip Timing Method Based on a Microwave Sensor

Blade tip timing is an effective method for blade vibration measurements in turbomachinery. This method is increasing in popularity because it is non-intrusive and has several advantages over the conventional strain gauge method. Different kinds of sensors have been developed for blade tip timing, including optical, eddy current and capacitance sensors. However, these sensors are unsuitable in environments with contaminants or high temperatures. Microwave sensors offer a promising potential solution to overcome these limitations. In this article, a microwave sensor-based blade tip timing measurement system is proposed. A patch antenna probe is used to transmit and receive the microwave signals. The signal model and process method is analyzed. Zero intermediate frequency structure is employed to maintain timing accuracy and dynamic performance, and the received signal can also be used to measure tip clearance. The timing method uses the rising and falling edges of the signal and an auto-gain control circuit to reduce the effect of tip clearance change. To validate the accuracy of the system, it is compared experimentally with a fiber optic tip timing system. The results show that the microwave tip timing system achieves good accuracy.
The identification of the relationship between the perceived social support, fatigue levels and maternal attachment during the postpartum period

Abstract Objective: This study aims to determinate the relationship between social support perceived by women, fatigue levels and maternal attachment in postpartum period. Methods: The sample of this descriptive study consists of 181 women who gave birth in the study period. The data was collected by the socio-demographic characteristics forms; “Multidimensional Scale of Perceived Social Support” (MSPSS); “Multidimensional Assessment of Fatigue Scale” (MAFS) and “Maternal Attachment Scale” (MAS) on the postpartum first days and 30–40th days. Results: MSPSS scores of women who had university or higher education, employed, had their first pregnancy, have 12 months or less between two pregnancies, were found to be significantly higher than others. MAS scores of women at the end of the postpartum first month were significantly increased. MAFS scores of women at the end of the postpartum first month were significantly decreased. The correlation between the fatigue levels and maternal attachment levels at the end of the postpartum first month was found to be negative and significant. Conclusion: In the postpartum period, the care of the mother should include social support, maternal attachment and fatigue assessment. Mothers should be encouraged to use social support resources. The continuity of social support systems should be provided.
Molecular discrimination of toxic and non-toxic Alexandrium species (Dinophyta) in natural phytoplankton assemblages from the Scottish coast of the North Sea

Molecular methods provide promising tools for routine detection and quantification of toxic microalgae in plankton samples. To this end, novel TaqMan minor groove binding probes and primers targeting the small (SSU) or large (LSU) ribosomal subunit (rRNA) were developed for two species of the marine dinoflagellate genus Alexandrium (A. minutum, A. tamutum) and for three groups/ribotypes of the A. tamarense species complex: Group I/North American (NA), Group II/Mediterranean (ME) and Group III/Western European (WE). Primers and probes for real-time quantitative PCR (qPCR) were species-specific and highly efficient when tested in qPCR assays for cross-validation with pure DNA from cultured Alexandrium strains. Suitability of the qPCR assays as molecular tools for the detection and estimation of relative cell abundances of Alexandrium species and groups was evaluated from samples of natural plankton assemblages along the Scottish east coast. The results were compared with inverted microscope cell counts (Utermöhl technique) of Alexandrium spp. and associated paralytic shellfish poisoning (PSP) toxin concentrations. The qPCR assays indicated that A. tamarense (Group I) and A. tamutum were the most abundant Alexandrium taxa and both were highly positively correlated with PSP toxin content of plankton samples. Cells of A. tamarense (Group III) were present at nearly all stations but in low abundance. Alexandrium minutum and A. tamarense (Group II) cells were not detected in any of the samples, thereby arguing for their absence from the specific North Sea region, at least at the time of the survey. The sympatric occurrence of A. tamarense Group I and Group III gives further support to the hypothesis that the groups/ribotypes of the A. tamarense species complex are cryptic species rather than variants belonging to the same species.
Health care applications: a solution based on the internet of things

This paper proposes the Internet of Things communication framework as the main enabler for distributed worldwide health care applications. Starting from the recent availability of wireless medical sensor prototypes and the growing diffusion of electronic health care record databases, we analyze the requirements of a unified communication framework. Our investigation takes the move by decomposing the storyline of a day in Robert's life, our unlucky character in the not so far future, into simple processes and their interactions. Subsequently, we devise the main communication requirements for those processes and for their integration in the Internet as web services. Finally, we present the Internet of Things protocol stack and the advantages it brings to health care scenarios in terms of the identified requirements.
Automatic LPI Radar Waveform Recognition Using CNN

Detecting and classifying the modulation scheme of the intercepted noisy low probability of intercept (LPI) radar signals in real time is a necessary survival technique required in the electronic warfare systems. Therefore, LPI radar waveform recognition technique (LWRT) has gained an increasing attention recently. In this paper, we propose a convolutional neural network (CNN)-based LWRT, where the input and hyperparameters of the CNN, such as the input size, number of filters, filter size, and number of neurons are designed based on various signal conditions to guarantee the maximum classification performance. In addition, we propose a sample averaging technique to efficiently reduce the large computational cost required when the intercept receiver needs to process a large amount of signal samples to improve the detection sensitivity. We demonstrate the performance of the proposed LWRT with numerous Monte Carlo simulations based on the simulation conditions used in the recent LWRTs introduced in the literature. It is testified that the proposed LWRT offers significant improvement, such as robustness to noise and recognition accuracy, over the recent LWRTs.
Application of Closure Concept to Estimation of Lifetime of Fatigue Crack Propagating Under Random Load

A stochastic approach describing fatigue crack growth under random loads and incorporating the closure concept for assessment of load interaction effects is presented. Two extreme loading histories are considered: (a) the superposition of overloads, random in time and magnitude, on base-line constant—amplitude cyclic loading, and (b) Random sequence of load peaks. In the first case the model is based on presentation of the delay time due to retardation effects associated with the overloads as a purely discontinuous Markov process. A numerical procedure developed is based on application of Kolmogarov—Feller integrodifferential equation. An expression for failure probability is derived. In the second case the load peaks are considered as a sequence of equally distributed noncorrelated random variables The crack opening stress, determined for an arbitrary i t h cycle, is estimated on the basis of the highest maximum and the lowest trough observed in η preceding cycles. It is shown that in this case some characteristic integral of crack length is normally distributed. Numerical procedure developed accounts for stochastic nature of both the load and the material. Examples illustrate the application of the proposed procedures.
The Nepean Belief Scale: preliminary reliability and validity in obsessive–compulsive disorder

Abstract Objectives: To examine the psychometric characteristics of the Nepean Belief Scale (NBS), a short clinician-administered scale that assesses the characteristics and intensity of beliefs in obsessive–compulsive disorder (OCD). Methods: The NBS was administered by two clinicians to 27 subjects with OCD as part of a larger study that included a comprehensive assessment using the Yale–Brown Obsessive Compulsive Symptom Scale (Y-BOCS), the Overvalued Ideas Scale (OVIS) and the Symptom Checklist 90-Revised (SCL-90R). Test–retest reliability of the NBS was assessed by administering the scale 5 days after initial administration. Results: The 5-item NBS proved easy to use with an assessment time of less than 5 min. Its interrater reliability revealed 99.5% concordance, while the kappa for test–retest reliability was 0.98 (95% CI = 0.95–1.00). Cronbach alpha coefficient for internal consistency was 0.87. The NBS was found to have excellent convergent and discriminant validity. Conclusions: Preliminary results suggest that the NBS could be a useful shorter alternative to the currently more widely used instruments for assessing beliefs such as the OVIS and the Brown Assessment of Belief Scale. The NBS has clear instructions and definitions, excellent interrater reliability and convergent validity, and it more accurately measures belief-related insight.
Pedestrian detection with dynamic iterative bootstrapping

Recent years have seen the increasing importance of pedestrian detection, which is a key problem in computer vision. In this paper, we propose a novel pedestrian detection approach based on Faster R-CNN. In order to obtain high-quality candidate regions, relevant adjustments with more precise anchors are made for region proposal network. To resolve the data imbalance issue in the classifier training, we propose a dynamic iterative bootstrapping method where the hard negative examples are automatically selected and the weights of the network are updated iteratively by them to make the training more effective. The square method is used to optimize the multi-task loss in our approach, which can accelerate convergence and reduce sensitivity. Experimental results on different widely used benchmark datasets show that the proposed approach achieves better performance in comparison with other common methods.
Microwave Dielectric Property and Crystal Structure of R2O3 (R = Rare Earth)-BaO-MO (M = Cu and Zn) System

The microwave dielectric properties of the R2BaMO5 (R= rare earth, M=Cu and Zn) ceramics have been investigated widely in order to clarify the relationships between the microwave dielectric properties and the crystal structure of R2BaMO5 ceramics. The variations in εr are attributed to the increase in the ionic polarizabilities of the R ions. The temperature coefficient of resonant frequency of these ceramics showed a similar tendency to depend on the differences in the ionic radii of the R ions; the optimum value was -1.6 ppm/C in the Dy2BaZnO5 ceramics.
Multimodal fusion via a series of transfers for noise removal

Near-infrared imaging has been considered as a solution to provide high quality photographs in dim lighting conditions. This imaging system captures two types of multimodal images: one is near-infrared gray image (NGI) and the other is the visible color image (VCI). NGI is noise-free but it is grayscale, whereas the VCI has colors but it contains noise. Moreover, there exist serious edge and brightness discrepancies between NGI and VCI. To deal with this problem, a new transfer-based fusion method is proposed for noise removal. Different from conventional fusion approaches, the proposed method conducts a series of transfers: contrast, detail, and color transfers. First, the proposed contrast and detail transfers aim at solving the serious discrepancy problem, thereby creating a new noise-free and detail-preserving NGI. Second, the proposed color transfer models the unknown colors from the denoised VCI via a linear transform, and then transfers natural-looking colors into the newly generated NGI. Experimental results show that the proposed transfer-based fusion method is highly successful in solving the discrepancy problem, thereby describing edges and textures clearly as well as removing noise completely on the fused images. Most of all, the proposed method is superior to conventional fusion methods and guided filtering, and even the state-of-the-art fusion methods based on scale map and layer decomposition.
An experimental evaluation of visible light communication utilizing telecommunications instructional modelling system

This paper experimentally evaluates the potential usage of the Telecommunications Instructional Modelling System (TIMS) for conducting educational experiments for Visible Light Communication (VLC). Two different experiments were conducted and discussed. The first one considers an analog signal to drive a VLC system, while the second one tests a digital modulation scheme. Both experiments showed that TIMS can be easily adapted using simple electronic components to implement educational VLC system, which is much preferred than using traditional discrete electronic components, especially at the early stage of learning this new technology.