Miracle-dz/UniFAR-FTUs huggingface dataset:
Probability of cancer in lung nodules using sequential volumetric screening up to 12 months: the UKLS trial

Background Estimation of the clinical probability of malignancy in patients with pulmonary nodules will facilitate early diagnosis, determine optimum patient management strategies and reduce overall costs. Methods Data from the UK Lung Cancer Screening trial were analysed. Multivariable logistic regression models were used to identify independent predictors and to develop a parsimonious model to estimate the probability of lung cancer in lung nodules detected at baseline and at 3-month and 12-month repeat screening. Results Of 1994 participants who underwent CT scan, 1013 participants had a total of 5063 lung nodules and 52 (2.6%) of the participants developed lung cancer during a median follow-up of 4 years. Covariates that predict lung cancer in our model included female gender, asthma, bronchitis, asbestos exposure, history of cancer, early and late onset of family history of lung cancer, smoking duration, FVC, nodule type (pure ground-glass and part-solid) and volume as measured by semiautomated volumetry. The final model incorporating all predictors had excellent discrimination: area under the receiver operating characteristic curve (AUC 0.885, 95% CI 0.880 to 0.889). Internal validation suggested that the model will discriminate well when applied to new data (optimism-corrected AUC 0.882, 95% CI 0.848 to 0.907). The risk model had a good calibration (goodness-of-fit χ[8] 8.13, p=0.42). Conclusions Our model may be used in estimating the probability of lung cancer in nodules detected at baseline and at 3 months and 12 months from baseline, allowing more efficient stratification of follow-up in population-based lung cancer screening programmes. Trial registration number 78513845.
Food-Related Health Emergency-Disaster Risk Reduction in Rural Ethnic Minority Communities: A Pilot Study of Knowledge, Awareness and Practice of Food Labelling and Salt-intake Reduction in a Kunge Community in China

Food safety and unhealthy dietary pattern are important global health problems. Understanding food-related health needs and providing corresponding support are important to health risk reduction. A needs assessment, education intervention for food labelling, and another intervention for salt-intake reduction were conducted in a rural Kunge community in Yunnan, China in 2014, 2015 and 2016, respectively. Not checking the expiry date of packaged food (37.1%) and a high salt diet (53.9%) were the most common problems in the community. Both topics were selected for education intervention. Pre- and post-intervention questionnaires were used to evaluate the effectiveness. Education interventions were found effective in improving food-health-related knowledge, changing attitudes toward behaviors such as willingness to read food labels before buying and consuming packaged food. However, no significant improvements were found for the attitudes toward not consuming expired food, controlling salt-intake, and decreasing the consumption of cured food. Health education was shown to be effective in promoting food-health-related knowledge but was limited in changing relevant behaviors in a rural ethnic minority community.
DOA and channel parameter estimation for wideband CDMA systems

We consider the uplink of a direct-sequence code-division multiple-access system and we assume that the base station is endowed with a linear antenna array. Transmission takes place over a multipath channel and the goal is to estimate the channel parameters (path gains and delays) and the directions of arrival of the signal echoes from a user entering the network. We propose an estimator that operates in an iterative fashion and exploits knowledge of the transmitted symbols (training sequence). Compared to other existing schemes, it is simpler to implement as it reduces a complicated multidimensional optimization problem to a sequence of one-dimensional searches. Computer simulations indicate that the proposed scheme is useful even in applications over rapidly varying channels where the training sequence must be short compared with the channel decorrelation time.
An improved indoor localization based on RSSI and feedback correction of anchor node for WSN

Received signal strength indicator (RSSI)-based localization attracting a great deal of research interest since it requires a relatively low configuration, battery power and easy control. However, the indoor localization algorithm based on RSSI is easy to be influenced by the channel interference and the environment. In this paper, a novel method is presented for improving the accuracy of indoor localization, which is based on anchor node feedback correction. First, the whole environment is divided before positioning, after the minimum location area is determined, the model parameters of the path loss in the region are estimated, then the distance between nodes is calculated accurately, and the feedback of neighbor anchor nodes is used to improve the accuracy further. The simulation results indicate that the method improves the accuracy of node localization and lower the delay and energy consumption of networks compared with conventional RSSI-based algorithm.
SCAPACH: Scalable Password-Changing Protocol for Smart Grid Device Authentication

In smart grid, the scale of pole devices that monitor the health of power line is very large. Moreover, with the upgrade of smart grid, the number of these resource-constrained (in terms of memory and computation) devices is further increasing. These devices are easy targets to security attacks as they are accessible via wireless network, and use weak passwords for authentication and transferring telemetric data to the pole maintenance personnel. In this paper, we present a SCalable and Automated PAssword- CHanging protocol, SCAPACH, for unique authentication of human personnel (operator) and secure collection of telemetric data from a large number of pole devices. SCAPACH employs physical per- operator, per-pole-device information as well as changeable secret salts to generate new unique passwords and secret keys every time a pole device is accessed. Our experiments confirm that the password-changing protocol authenticates and transmits pole device data securely and in real-time under varying maintenance scenarios.
Robot Motion Planning in Eight Directions

this paper, we investigate the problem of 8-directional robot motion planning where the goal is to find a collision-free path from the starting to the target position in the 2D space containing point and rectangular obstacles. In contrast to the traditional approaches frequently based on decomposition methods combined with heuristic methods, we propose a method for solving this problem using rectilinear Voronoi diagrams whose bisectors are restricted only to horizontal, vertical and diagonal directions.
Optimal Reconstruction Might be Hard

Given as input a point set $$\mathcal S $$ that samples a shape $$\mathcal A $$, the condition required for inferring Betti numbers of $$\mathcal A $$ from $$\mathcal S $$ in polynomial time is much weaker than the conditions required by any known polynomial time algorithm for producing a topologically correct approximation of $$\mathcal A $$ from $$\mathcal S $$. Under the former condition which we call the weak precondition, we investigate the question whether a polynomial time algorithm for reconstruction exists. As a first step, we provide an algorithm which outputs an approximation of the shape with the correct Betti numbers under a slightly stronger condition than the weak precondition. Unfortunately, even though our algorithm terminates, its time complexity is unbounded. We then identify at the heart of our algorithm a test which requires answering the following question: given 2 two-dimensional simplicial complexes $$L \subset K$$, does there exist a simplicial complex containing $$L$$ and contained in $$K$$ which realizes the persistent homology of $$L$$ into $$K$$? We call this problem the homological simplification of the pair $$(K,L)$$ and prove that this problem is NP-complete, using a reduction from 3SAT.
A Multiantigenic DNA Vaccine That Induces Broad Hepatitis C Virus-Specific T-Cell Responses in Mice

ABSTRACT There are 3 to 4 million new hepatitis C virus (HCV) infections annually around the world, but no vaccine is available. Robust T-cell mediated responses are necessary for effective clearance of the virus, and DNA vaccines result in a cell-mediated bias. Adjuvants are often required for effective vaccination, but during natural lytic viral infections damage-associated molecular patterns (DAMPs) are released, which act as natural adjuvants. Hence, a vaccine that induces cell necrosis and releases DAMPs will result in cell-mediated immunity (CMI), similar to that resulting from natural lytic viral infection. We have generated a DNA vaccine with the ability to elicit strong CMI against the HCV nonstructural (NS) proteins (3, 4A, 4B, and 5B) by encoding a cytolytic protein, perforin (PRF), and the antigens on a single plasmid. We examined the efficacy of the vaccines in C57BL/6 mice, as determined by gamma interferon enzyme-linked immunosorbent spot assay, cell proliferation studies, and intracellular cytokine production. Initially, we showed that encoding the NS4A protein in a vaccine which encoded only NS3 reduced the immunogenicity of NS3, whereas including PRF increased NS3 immunogenicity. In contrast, the inclusion of NS4A increased the immunogenicity of the NS3, NS4B, andNS5B proteins, when encoded in a DNA vaccine that also encoded PRF. Finally, vaccines that also encoded PRF elicited similar levels of CMI against each protein after vaccination with DNA encoding NS3, NS4A, NS4B, and NS5B compared to mice vaccinated with DNA encoding only NS3 or NS4B/5B. Thus, we have developed a promising “multiantigen” vaccine that elicits robust CMI. IMPORTANCE Since their development, vaccines have reduced the global burden of disease. One strategy for vaccine development is to use commercially viable DNA technology, which has the potential to generate robust immune responses. Hepatitis C virus causes chronic liver infection and is a leading cause of liver cancer. To date, no vaccine is currently available, and treatment is costly and often results in side effects, limiting the number of patients who are treated. Despite recent advances in treatment, prevention remains the key to efficient control and elimination of this virus. Here, we describe a novel DNA vaccine against hepatitis C virus that is capable of inducing robust cell-mediated immune responses in mice and is a promising vaccine candidate for humans.
Automatic Differentiation Adjoint of the Reynolds-Averaged Navier-Stokes Equations with a Turbulence Model

This paper presents an approach for the rapid implementation of an adjoint solver for the ReynoldsAveraged Navier–Stokes equations with a Spalart–Allmaras turbulence model. Automatic differentiation is used to construct the partial derivatives required in the adjoint formulation. The resulting adjoint implementation is computationally efficient and highly accurate. The assembly of each partial derivative in the adjoint formulation is discussed. In addition, a coloring acceleration technique is presented to improve the adjoint efficiency. The RANS adjoint is verified with complex-step method using a flow over a bump case. The RANS-based aerodynamic shape optimization of an ONERA M6 wing is also presented to demonstrate the aerodynamic shape optimization capability. The drag coefficient is reduced by 19% when subject to a lift coefficient constraint. The results are compared with Euler-based aerodynamic shape optimization and previous work. Finally, the effects of the frozenturbulence assumption on the accuracy and computational cost are assessed.
Machine Translation Enhanced Automatic Speech Recognition

In human-mediated translation scenarios, a human interpreter translates between a source and a target language using either a spoken or a written representation of the source language. In this work the recognition performance on the speech of the human translator spoken in the target language (English) is improved by taking advantage of the source language (Spanish) representations. For this, machine translation techniques are used to translate between the source and target language resources and then bias the target language speech recognizer towards the gained knowledge, hence the name Machine Translation Enhanced Automatic Speech Recognition (MTE-ASR). Different basic MTE-ASR techniques are investigated, namely restricting the search vocabulary, selecting hypotheses from n-best lists and applying cache and interpolation schemes to language modeling. Given a written representation of the source language and with the help of a non-iterative combination of the most successful basic techniques, it was possible to outperform the English baseline ASR system by a relative word error rate reduction of 30.6%. In the case of a spoken source language representation, where a source language ASR has to be used at first to create a further processable written representation, the reduction is still 23.2%. With the help of an iterative system design, which recursively applies the improved ASR output to enhance the involved MT system(s) for a further ASR improvement, it was possible to further increase these word error rate reductions to 37.7% and 29.9% respectively.
Lightly Supervised and Data-Driven Approaches to Mandarin Broadcast News Transcription

This paper investigates the use of several lightly supervised and data-driven approaches to Mandarin broadcast news transcription. First, with a consideration of the special structural properties of the Chinese language, a fast acoustic took-ahead technique for estimating the unexplored part of speech utterance was integrated into the lexical tree search to improve the search efficiency, in conjunction with the conventional language model look-ahead technique. Then, a verification-based method for automatic acoustic training data acquisition was developed to make use of the large amount of untranscribed speech data. Finally, two alternative strategies for language model adaptation were further studied for accurate language model estimation. With the above approaches, the system yielded an 11.94% character error rate on the Mandarin broadcast news collected in Taiwan.
Optimizing File Availability in Peer-to-Peer Content Distribution

A fundamental paradigm in peer-to-peer (P2P) content distribution is that of a large community of intermittently-connected nodes that cooperate to share files. Because nodes are intermittently connected, the P2P community must replicate and replace files as a function of their popularity to achieve satisfactory performance. In this paper, we develop an analytical optimization theory for benchmarking the performance of replication/replacement algorithms, including algorithms that employ erasure codes. We also consider a content management algorithm, the Top-K Most Frequently Requested algorithm, and show that in most cases this algorithm converges to an optimal replica profile. Finally, we present two approaches for achieving an evenly balanced load over all the peers in the community.
Synonymous Codon Usage in TTSuV2: Analysis and Comparison with TTSuV1

Two species of the DNA virus Torque teno sus virus (TTSuV), TTSuV1 and TTSuV2, have become widely distributed in pig-farming countries in recent years. In this study, we performed a comprehensive analysis of synonymous codon usage bias in 41 available TTSuV2 coding sequences (CDS), and compared the codon usage patterns of TTSuV2 and TTSuV1. TTSuV codon usage patterns were found to be phylogenetically conserved. Values for the effective number of codons (ENC) indicated that the overall extent of codon usage bias in both TTSuV2 and TTSuV1 was not significant, the most frequently occurring codons had an A or C at the third codon position. Correspondence analysis (COA) was performed and TTSuV2 and TTSuV1 sequences were located in different quadrants of the first two major axes. A plot of the ENC revealed that compositional constraint was the major factor determining the codon usage bias for TTSuV2. In addition, hierarchical cluster analysis of 41 TTSuV2 isolates based on relative synonymous codon usage (RSCU) values suggested that there was no association between geographic distribution and codon bias of TTSuV2 sequences. Finally, the comparison of RSCU for TTSuV2, TTSuV1 and the corresponding host sequence indicated that the codon usage pattern of TTSuV2 was similar to that of TTSuV1. However the similarity was low for each virus and its host. These conclusions provide important insight into the synonymous codon usage pattern of TTSuV2, as well as better understangding of the molecular evolution of TTSuV2 genomes.
Design guidelines for terahertz mixers and detectors

Twin-slot antennas and coplanar waveguide (CPW) are a popular choice for coupling signals to state of the art mixers and detectors at terahertz (THz) frequencies. Although these sensors show promising performance in terms of noise temperature, they usually also show a considerable downward shift in the centre frequency of their spectral response, especially when compared with calculations obtained with commonly used simplified models. In this paper, we describe an accurate and complete electromagnetic model of these detectors which represents a significant improvement over other published approaches. We present the procedure used to obtain a very good agreement between measurements and calculations at THz frequencies both in terms of centre frequency and bandwidth. The wide variety of measured and calculated data also demonstrates the effectiveness and reliability of the electromagnetic model in all the investigated frequency bands.
Comparison of Peak Cardiopulmonary Performance Parameters on a Robotics-Assisted Tilt Table, a Cycle and a Treadmill

Robotics-assisted tilt table (RATT) technology provides body support, cyclical stepping movement and physiological loading. This technology can potentially be used to facilitate the estimation of peak cardiopulmonary performance parameters in patients who have neurological or other problems that may preclude testing on a treadmill or cycle ergometer. The aim of the study was to compare the magnitude of peak cardiopulmonary performance parameters including peak oxygen uptake (VO2peak) and peak heart rate (HRpeak) obtained from a robotics-assisted tilt table (RATT), a cycle ergometer and a treadmill. The strength of correlations between the three devices, test-retest reliability and repeatability were also assessed. Eighteen healthy subjects performed six maximal exercise tests, with two tests on each of the three exercise modalities. Data from the second tests were used for the comparative and correlation analyses. For nine subjects, test-retest reliability and repeatability of VO2peak and HRpeak were assessed. Absolute VO2peak from the RATT, the cycle ergometer and the treadmill was (mean (SD)) 2.2 (0.56), 2.8 (0.80) and 3.2 (0.87) L/min, respectively (p < 0.001). HRpeak from the RATT, the cycle ergometer and the treadmill was 168 (9.5), 179 (7.9) and 184 (6.9) beats/min, respectively (p < 0.001). VO2peak and HRpeak from the RATT vs the cycle ergometer and the RATT vs the treadmill showed strong correlations. Test-retest reliability and repeatability were high for VO2peak and HRpeak for all devices. The results demonstrate that the RATT is a valid and reliable device for exercise testing. There is potential for the RATT to be used in severely impaired subjects who cannot use the standard modalities.
Generalized LRT-Based Voice Activity Detector

A robust and effective voice activity detection (VAD) algorithm is proposed for improving speech recognition performance in noisy environments. The approach is based on well-known statistical tests based on the determination of the speech/non-speech bispectra by means of third-order auto-cumulants. This algorithm differs from many others in the way the decision rule is formulated being the statistical tests built on a multiple observation (MO) window consisting of averaged bispectrum coefficients of the speech signal. Clear improvements in speech/non-speech discrimination accuracy demonstrate the effectiveness of the proposed VAD. It is shown that application of a statistical detection test leads to a better separation of the speech and noise distributions, thus allowing a more effective discrimination and a tradeoff between complexity and performance. The experimental analysis carried out on the AURORA 3 databases provides an extensive performance evaluation together with an exhaustive comparison to the standard VADs, such as ITU G.729, GSM AMR, and ETSI AFE, for distributed speech recognition (DSR) and other recently reported VADs
Offline Signature Verification in Punjabi based on SURF Features and Critical Point Matching using HMM

which refers to identifying an individual based on his or her physiological or behavioral characteristics, has the capabilities to the reliably distinguish between an authorized person and an imposter. The Signature recognition systems can categorized as offline (static) and online (dynamic). This paper presents Surf Feature based recognition of offline signatures system that is trained with low-resolution scanned signature images. The signature of a person is an important biometric attribute of a human being which can be used to authenticate human identity. However the signatures of human can be handled as an image and recognized using computer vision and HMM techniques. With modern computers, there is need to develop fast algorithms for signature recognition. There are multiple techniques are defined to signature recognition with a lot of scope of research. In this paper, (static signature) off-line signature recognition & verification using surf feature with HMM is proposed, where the signature is captured and presented to the user in an image format. Signatures are verified depended on parameters extracted from the signature using various image processing techniques. The Off-line Signature Verification and Recognition is implemented using Mat lab platform. This work has been analyzed or tested and found suitable for its purpose or result. The proposed method performs better than the other recently proposed methods. KeywordsSignature verification, offline signature recognition, signatures, SURF features and HMM.