Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of Zika Virus Serological Testing Strategies in New York State

ABSTRACT The recent outbreak of Zika virus (ZIKV) in the Americas has challenged diagnostic laboratory testing strategies. At the Wadsworth Center, ZIKV serological testing was performed for over 10,000 specimens, using a combination of an enzyme-linked immunosorbent assay (ELISA) for IgM antibodies (Abs) to ZIKV, a polyvalent microsphere immunoassay (MIA) to detect Abs broadly reactive with flaviviruses, and a plaque reduction neutralization test (PRNT) for further testing. Overall, 42% of patients showed serological evidence of flavivirus infection (primarily past dengue virus [DENV] infection), while 7% possessed IgM Abs to ZIKV and/or DENV. ZIKV IgM Abs typically arose within 3 to 4 days, with only one instance of duration beyond 100 days after reported symptoms. PRNT analysis of 826 IgM-positive specimens showed 7% positive neutralization to ZIKV alone, 9% to DENV alone, and 85% to both ZIKV and DENV. Thus, the extensive Ab cross-reactivity among flaviviruses significantly reduced the value of performing PRNT analysis, especially when a traditional paired serum algorithm with viral neutralization titering was used. Nevertheless, the finding of a negative ZIKV result by PRNT was invaluable for reassuring both physicians and patients. The MIA detected both IgM and IgG, which enabled us to identify patients who presented without IgM anti-ZIKV Abs but still had ZIKV-specific neutralizing Abs. On the basis of these results, a new algorithm, which included an IgM Ab capture (MAC)-ELISA to detect recent infection, a flavivirus MIA to identify patients no longer producing IgM, and a single-dilution PRNT for ZIKV exclusion and occasional discrimination of ZIKV and DENV, was implemented.
Chinese-thai cross-language topic extraction and alignment

Cross-language topic extraction aims at extracting related topics from texts in different languages. A widely used approach is to build a topic model from a set of parallel or comparable texts in different languages. However, for resource-lean languages such as Thai, such texts may be unavailable. An alternative approach is to construct separate topic models for different languages, and then to align them. We investigate this approach in this paper for Chinese-Thai texts. A key problem to align topics in different languages is to estimate their similarity, which requires the translation of topic words between the two languages. Unfortunately, the translation between Chinese and Thai is not accurate enough for this task. Therefore, we use English as pivot language, through which the topics in Chinese and Thai are aligned. In addition, the representative topic words are filtered so that only those that are specific for the topic are kept. Experimental results performed on a set of news articles in Chinese and Thai show that our approach achieves a higher effectiveness than a traditional method.
Bandgap engineering of graphene by corrugation on lattice-mismatched MgO (111)

The corrugation pattern and electronic structure of graphene on MgO (111), which is a lattice-mismatched substrate, were investigated using the ab initio method. On Mg-terminated octo-polar reconstructed MgO (111), graphene was physisorbed and shaped into a stripe-like corrugation pattern. Due to weak charge transfer at the interface, the graphene was of the n-type doped, and its low effective mass was preserved. On the other hand, graphene on O-terminated octo-polar reconstructed MgO (111) showed a larger corrugation triggered by periodic oxygen–carbon chemisorption. In addition, a band-gap opening, which was induced by the periodic chemisorption, of 0.294 eV was observed. The results indicate that a corrugation structure induced by the lattice-mismatched substrate is highly effective for band-gap engineering treatment.
Performance comparison of massive MIMO and conventional MIMO using channel parameters

Multiple-input multiple-output (MIMO) technology is becoming mature in wireless communication systems. It has led to third and fourth generation wireless systems, which has been providing good range, reliability and higher data rates. For the increased demand of much higher data rates, coverage, spectral efficiency, capacity and reduced latency, the evolution of the next generation i.e., the fifth generation technology is necessary. Massive MIMO technology is one of the most promising solution for the above-mentioned challenge. In massive MIMO, the base station is incorporated with hundreds to thousands of antenna array wherein the degrees of freedom can be exploited and the energy can be efficiently used due to the fact that the extra antennas at the base station helps focus the energy into the smaller regions of space. To reap the benefits provided by the extra antennas, the channel information is necessary which makes it possible to have a reliable communication. Therefore, to acquire the channel knowledge, channel state information is required at the base station and estimating the channel parameters plays an important role. In this paper, we concentrate on estimating the channel parameters for conventional MIMO and massive MIMO based on training-based and blind channel estimation techniques wherein the performance of both is compared.
Value of Information Analysis Applied to the Economic Evaluation of Interventions Aimed at Reducing Juvenile Delinquency: An Illustration

Objectives To investigate whether a value of information analysis, commonly applied in health care evaluations, is feasible and meaningful in the field of crime prevention. Methods Interventions aimed at reducing juvenile delinquency are increasingly being evaluated according to their cost-effectiveness. Results of cost-effectiveness models are subject to uncertainty in their cost and effect estimates. Further research can reduce that parameter uncertainty. The value of such further research can be estimated using a value of information analysis, as illustrated in the current study. We built upon an earlier published cost-effectiveness model that demonstrated the comparison of two interventions aimed at reducing juvenile delinquency. Outcomes were presented as costs per criminal activity free year. Results At a societal willingness-to-pay of €71,700 per criminal activity free year, further research to eliminate parameter uncertainty was valued at €176 million. Therefore, in this illustrative analysis, the value of information analysis determined that society should be willing to spend a maximum of €176 million in reducing decision uncertainty in the cost-effectiveness of the two interventions. Moreover, the results suggest that reducing uncertainty in some specific model parameters might be more valuable than in others. Conclusions Using a value of information framework to assess the value of conducting further research in the field of crime prevention proved to be feasible. The results were meaningful and can be interpreted according to health care evaluation studies. This analysis can be helpful in justifying additional research funds to further inform the reimbursement decision in regard to interventions for juvenile delinquents.
The Risk and Timing of Tuberculosis Diagnosed in Smear-Negative TB Suspects: A 12 Month Cohort Study in Harare, Zimbabwe

Background Cases of smear-negative TB have increased dramatically in high prevalence HIV settings and pose considerable diagnostic and management challenges. Methods and Findings Between February 2006 and July 2007, a cohort study nested within a cluster-randomised trial of community-based case finding strategies for TB in Harare, Zimbabwe was undertaken. Participants who had negative sputum smears and remained symptomatic of TB were follow-up for one year with standardised investigations including HIV testing, repeat sputum smears, TB culture and chest radiography. Defaulters were actively traced to the community. The objectives were to investigate the incidence and risk factors for TB. TB was diagnosed in 218 (18.2%) participants, of which 39.4% was bacteriologically confirmed. Most cases (84.2%) were diagnosed within 3 months, but TB incidence remained high thereafter (111.3 per 1000 person-years, 95% CI: 86.6 to 146.3). HIV prevalence was 63.3%, and HIV-infected individuals had a 3.5-fold higher risk of tuberculosis than HIV-negative individuals. Conclusion We found that diagnosis of TB was insensitive and slow, even with early radiography and culture. Until more sensitive and rapid diagnostic tests become widely available, a much more proactive and integrated approach towards prompt initiation of ART, ideally from within TB clinics and without waiting for TB to be excluded, is needed to minimise the risk and consequences of diagnostic delay.
Process variation and temperature aware adaptive scrubbing for retention failures in STT-MRAM

Spin Transfer Torque Magnetic Random Access Memory (STT-MRAM) is an emerging memory technology, which is seen as a promising replacement for CMOS based on-chip memories. It has several distinctive advantages such as nonvolatility, high endurance, high density, CMOS compatibility and scalability among others. However, retention failure has emerged as a major reliability concern for this technology due to the large variations in retention time because of process variations and temperature effects. The conventional solution to mitigate retention failures is to use scrubbing at regular intervals to prevent accumulation of errors, based on the worst case retention time of the memory array. But this leads to large performance and energy overheads. In this work, we propose a process variation and temperature aware scrubbing technique, where we cluster the cache lines into different groups based on their retention times and use different scrubbing intervals for each of these groups. In addition, the scrubbing interval is adjusted at run-time based on the operating temperature, to guarantee target error rate requirements. Our results show that for a 512KB cache, a group size of 4 can reduce the performance and dynamic energy overheads of scrubbing by 97%, under the same error rate constraint.
Benchmarking Projects: How to Apply It on Non-Industrial Projects

This case study is an example to demonstrate the application and potential strength of benchmarking and its application on non-industrial projects. The paper provides a review of the benchmarking system, benchmarking process, benefit of benchmarking, benchmarking types and barrier of benchmarking. It also describes the use of benchmarking in different knowledge areas. The research shows example of planned contingency and schedule growth results from oil and gas projects executed in Alberta phases 1 & 2 in CII/COAA database. The CII/COAA benchmarking approach was used to improve performance in projects executed in Alberta. The use of the benchmarking system can contribute to a better project performance on non-industrial projects. It is concluded that this approach can be used to benchmark other kinds of projects on non-industrial projects.
Improving Odometric Accuracy for an Autonomous Electric Cart

In this paper, a study of the odometric system for the autonomous cart Verdino, which is an electric vehicle based on a golf cart, is presented. A mathematical model of the odometric system is derived from cart movement equations, and is used to compute the vehicle position and orientation. The inputs of the system are the odometry encoders, and the model uses the wheels diameter and distance between wheels as parameters. With this model, a least square minimization is made in order to get the nominal best parameters. This model is updated, including a real time wheel diameter measurement improving the accuracy of the results. A neural network model is used in order to learn the odometric model from data. Tests are made using this neural network in several configurations and the results are compared to the mathematical model, showing that the neural network can outperform the first proposed model.
Self-Learning for a Humanoid Robotic Ping-Pong Player

Imitating the learning process of a human playing ping-pong is extremely complex. This work proposes a suitable learning strategy. First, an inverse kinematics solution is presented to obtain the smooth joint angles of a redundant anthropomorphic robot arm in order to imitate the paddle motion of a human ping-pong player. As humans instinctively determine which posture is suitable for striking a ball, this work proposes two novel processes: (i) estimating ball states and predicting trajectory using a fuzzy adaptive resonance theory network, and (ii) self-learning the behavior for each strike using a self-organizing map-based reinforcement learning network that imitates human learning behavior. Experimental results demonstrate that the proposed algorithms work effectively when applied to an actual humanoid robot playing ping-pong.
Interference of transcription across H‐NS binding sites and repression by H‐NS

Nucleoid‐associated protein H‐NS represses transcription by forming extended DNA–H‐NS complexes. Repression by H‐NS operates mostly at the level of transcription initiation. Less is known about how DNA–H‐NS complexes interfere with transcription elongation. In vitro H‐NS has been shown to enhance RNA polymerase pausing and to promote Rho‐dependent termination, while in vivo inhibition of Rho resulted in a decrease of the genome occupancy by H‐NS. Here we show that transcription directed across H‐NS binding regions relieves H‐NS (and H‐NS/StpA) mediated repression of promoters in these regions. Further, we observed a correlation of transcription across the H‐NS‐bound region and de‐repression. The data suggest that the transcribing RNA polymerase is able to remodel the H‐NS complex and/or dislodge H‐NS from the DNA and thus relieve repression. Such an interference of transcription and H‐NS mediated repression may imply that poorly transcribed AT‐rich loci are prone to be repressed by H‐NS, while efficiently transcribed loci escape repression.
Joint demosaicing and denoising of noisy bayer images with ADMM

Image demosaicing and denoising are import steps of image signal processing. Sequential executions of demosaicing and denoising have essential drawbacks that they degrade the results of each other. Joint demosaicing and denoising overcomes the difficulties by solving the two problems in one model. This paper introduces a unified object function with hidden priors and a variant of ADMM to recover a full-resolution color image with a noisy Bayer input. Experimental results demonstrate that our method performs better than state-of-the-art methods in both PSNR comparison and human vision. In addition, our method is much more robust to variations of noise level.
Fabrication of Light‐Guiding Core/Sheath Fibers by Coaxial Electrospinning

Light-guiding core/sheath fibers are fabricated from two different refractive index (RI) polymers by coaxial electrospinning. The morphology and fiber diameter are analyzed with scanning electron and fluorescence microscopies. It is found that the diameter of the core and the thickness of the sheath could be varied from 100 to 400 nm by changing the concentration of the outer solution. The incorporation of a chromophore into the inner material confirmed the uniformity of the core/ sheath structure in long segments of the fibers. The boundary is clearly seen: the core diameter and the thickness of the sheath are constant along the fiber axis in fluorescence images. The ejected beam is circular and light-guided along the fiber axis as in an optical fiber.
Genetic and local search algorithms applied to balanced communication networks

In this paper we describe the application of different heuristics to optimise large communication networks. We use Iterated Local Search (ILS), Tabu Search (TS), Simulated Annealing (SA) and Genetic Algorithm (GA) to minimise the link cost to form balanced communication networks. This paper makes a comparison among the effectiveness of ILS, TS, SA and GA on solving large communication networks. Simulation results verify the effectiveness of these algorithms.
Endoscopic, Endonasal Resection of Craniopharyngiomas: Analysis of Outcome Including Extent of Resection, Cerebrospinal Fluid Leak, Return to Preoperative Productivity, and Body Mass Index

BACKGROUND The endoscopic, endonasal, extended transsphenoidal approach is a minimal-access technique for managing craniopharyngiomas. Outcome measures such as return to employment and body mass index (BMI) have not been reported and are necessary for comparison with open transcranial approaches. Most prior reports of the endoscopic, endonasal approach have reported unacceptably high cerebrospinal fluid (CSF) leak rates. OBJECTIVE To assess the outcome of endoscopic, endonasal surgery in a consecutive series of craniopharyngiomas with special attention to extent of resection, CSF leak, return to employment, and BMI. METHODS Twenty-six surgeries were performed on 24 patients at Weill Cornell Medical College-New York Presbyterian Hospital. Five patients had recurrent lesions. Gross-total resection (GTR) was attempted in 21 surgeries. Indications for intended subtotal resection were advanced age, medical comorbidities, preservation of pituitary function, and hypothalamic invasion. RESULTS Mean tumor diameter was 2.9 cm. GTR (18 surgeries) or near-total (>95%) resection (2 surgeries) was achieved in 95% when GTR was the goal. Seven patients received postoperative radiation therapy. Mean follow-up was 35 months with no recurrences in GTR cases and stable disease in all patients at last follow-up. Vision improved in 77%. Diabetes insipidus and panhypopituitarism developed in 42% and 38%, respectively. A more than 9% increase in BMI occurred in 39%; 69% returned to their preoperative profession/schooling. The postoperative CSF leak rate was 3.8%. CONCLUSION Minimal-access, endoscopic, endonasal surgery for craniopharyngioma can achieve high rates of GTR with low rates of CSF leak. Return to employment and obesity rates are comparable to microscope-assisted transcranial and transsphenoidal reports.
Dental approach for Apert syndrome in children: a systematic review

Background Apert Syndrome (AS), or type I acrocephalosyndactyly, is a rare, congenital craniosynostosis condition resulting from missense mutations in the gene encoding fibroblast growth factor receptor 2. It is characterized by three specific clinical features: brachycephalic skull; midface hypoplasia, and limb abnormalities (syndactyly of hands and feet). The disorder exhibits variable presentations in bones, brain, skin, internal organs, and in the oral/maxillofacial region. The aim of the present paper was to show the main results from a systematic review of AS. Material and Methods A search of the literature was performed from April to June 2016 in five electronic databases. Clinical interventional or observational studies, reviews, and case reports were included. The present systematic review was carried out strictly following PRISMA and Cochrane Collaboration criteria. Results A total of 129 potential references were identified. After reviewing titles and abstracts, 77 of these did not meet the desired criteria and were discarded. The full text of the remaining 52 manuscripts was critically screened. Finally, 35 relevant papers were identified for inclusion in the present systematic review and classified according to topic type. Conclusions According to the information gathered, dentistry practitioners must be able to supply an early diagnosis through the recognition of AS clinical features and provide correct oral management. Additionally, they should be integrated in a multidisciplinary medical care team in order to improve the quality of life of the affected patients. Key words:Apert syndrome, acrocephalosyndactyly, craniosynostosis, skeletal dysplasias, systematic review.
Efficient Receive Antenna Selection for Pre-Coding Aided Spatial Modulation

Developed from the recently emerged pre-coding aided spatial modulation (PSM) concept, a class of efficient receives antenna selection (ERAS) techniques are devised. Aiming at approaching the optimal RAS performance in context of the PAM system, we derive the upper bound performance of RAS-PAM in two different ways, by utilizing the condition number and eigenvalue and Wishart distribution feature for the channel matrix. Our performance results demonstrate that the proposed ERAS techniques are capable of effectively improving the transmission performance in comparison with conventional RAS-PSM systems.
The singular value decomposition-based anchor word selection method for separable nonnegative matrix factorization

One of the recent methods for the topic modeling is separable nonnegative matrix factorization (SNMF). In general, SNMF consists of three main steps, which are, generating a word co-occurrence matrix, selecting anchor words, and recovering a topic matrix. The anchor words strongly influence the interpretability of extracted topics. In this paper, we propose a new method for selecting the anchor words by using singular value decomposition (SVD). We assume that the most dominant words in each latent semantics created by SVD are the potential candidates for the anchor words. Our simulations show that the SVD-based anchor word selection method can reach better interpretability scores of extracted topics than the common convex hull-based method on two of three datasets.
A hybrid BMI-based exoskeleton for paresis: EMG control for assisting arm movements

Objective. Brain–machine interface (BMI) technologies have succeeded in controlling robotic exoskeletons, enabling some paralyzed people to control their own arms and hands. We have developed an exoskeleton asynchronously controlled by EEG signals. In this study, to enable real-time control of the exoskeleton for paresis, we developed a hybrid system with EEG and EMG signals, and the EMG signals were used to estimate its joint angles. Approach. Eleven able-bodied subjects and two patients with upper cervical spinal cord injuries (SCIs) performed hand and arm movements, and the angles of the metacarpophalangeal (MP) joint of the index finger, wrist, and elbow were estimated from EMG signals using a formula that we derived to calculate joint angles from EMG signals, based on a musculoskeletal model. The formula was exploited to control the elbow of the exoskeleton after automatic adjustments. Four able-bodied subjects and a patient with upper cervical SCI wore an exoskeleton controlled using EMG signals and were required to perform hand and arm movements to carry and release a ball. Main results. Estimated angles of the MP joints of index fingers, wrists, and elbows were correlated well with the measured angles in 11 able-bodied subjects (correlation coefficients were 0.81 ± 0.09, 0.85 ± 0.09, and 0.76 ± 0.13, respectively) and the patients (e.g. 0.91 ± 0.01 in the elbow of a patient). Four able-bodied subjects successfully positioned their arms to adequate angles by extending their elbows and a joint of the exoskeleton, with root-mean-square errors <6°. An upper cervical SCI patient, empowered by the exoskeleton, successfully carried a ball to a goal in all 10 trials. Significance. A BMI-based exoskeleton for paralyzed arms and hands using real-time control was realized by designing a new method to estimate joint angles based on EMG signals, and these may be useful for practical rehabilitation and the support of daily actions.