Miracle-dz/UniFAR-FTUs huggingface dataset:
Road markers classification using binary scanning and slope contours

Road markers guide the driver while driving on the road to control the traffic for the safety of the road users. With the booming autonomous car technology, the road markers classification is important in its vision segment to navigate the autonomous car. A new method is proposed in this paper to classify five types of road markers namely dashed, single, double, solid-dashed and dashed-solid which are commonly found on the two lane single carriageway. The classification is using unique feature acquired from the binary image by scanning on each of the images to calculate the frequency of binary transition. Another feature which is the slopes between the two centroids which allow the proposed method, to perform the classification within the same video frame period. This proposed method has been observed to achieve an accuracy value of at least 93%, which is higher than the accuracy value achieved by the existing methods.
Substitution of rifapentine for rifampin during intensive phase treatment of pulmonary tuberculosis: study 29 of the tuberculosis trials consortium.

BACKGROUND Rifapentine administered 5 days per week has potent activity in mouse models of antituberculosis chemotherapy, but efficacy and safety data are limited in humans. We compared the antimicrobial activity and safety of rifapentine vs rifampin during the first 8 weeks of pulmonary tuberculosis treatment. METHODS In total, 531 adults with sputum smear-positive pulmonary tuberculosis were randomized to rifapentine 10 mg/kg/dose or rifampin 10 mg/kg/dose, administered 5 days per week for 8 weeks (intensive phase), with isoniazid, pyrazinamide, and ethambutol. Coprimary outcomes were negative sputum culture on liquid and on solid media at completion of intensive phase. RESULTS Negative cultures on solid media occurred in 145 of 174 participants (83.3%) in the rifampin group and 171 of 198 participants (86.4%) in the rifapentine group (difference, 3.0%; 95% confidence interval [CI]: -4.3, 10.5); negative cultures in liquid media occurred in 110 of 169 (65.1%) in the rifampin group and 133 of 196 (67.9%) in the rifapentine group (difference, 2.8%; 95% CI: -6.9, 12.4). Among 529 participants who received study therapy, 40 of 254 participants (15.7%) in the rifampin group and 40 of 275 participants (14.5%) in the rifapentine group prematurely discontinued treatment (P=.79). CONCLUSIONS The rifapentine regimen was safe but not significantly more active than a standard rifampin regimen, by the surrogate endpoint of culture status at completion of intensive phase. Assessment of higher exposures to rifapentine for tuberculosis treatment is warranted. CLINICAL TRIALS REGISTRATION NCT00694629.
Digital Rights Management system design and implementation issues

We live in the digital information age. The growth of new technologies for communication infrastructure and the wide availability of digital storage devices resulted in most data being produced, distributed and ultimately consumed by end users in digital form. The intrinsic nature of digital data makes the task of manipulating, replicating and distributing digital copies extremely easy. Publishing content covered by intellectual property or copyright is then faced by the challenge of countering illegal access to the digital good, while still enabling consumers to exercise their usage rights on purchased contents. Digital rights management (DRM) systems consist of architectures, protocols and technologies aimed at providing satisfactory solutions to the above problem. Broadcast encryption is a cryptographic primitive that a DRM system designer should investigate carefully. This paper aims to guide DRM system designers through the realm of broadcast encryption mechanisms and hence choose a suitable one for the application in hand.
MemoryBook: generating narratives from lifelogs

Automatic capture of life logging data can be extremely information rich, large and varied. Extracting a narrative from this data can be difficult because not all of the data is conducive to producing interesting narratives. Life logging data can be enriched by linking to the Semantic Web and narratives can be enriched with data extracted from Semantic Web knowledge stores. In this paper, we present MemoryBook which is a web interface that automatically generates narratives from life logging data in RDF form and from Semantic Web knowledge stores, and highlights maps and images which are associated with events in the narrative.
Shell structure and electron-electron interaction in self-assembled InAs quantum dots

Using far-infrared spectroscopy, we investigate the excitations of self-organized InAs quantum dots as a function of the electron number per dot, 1 ≤ ne ≤ 6, which is monitored in situ by capacitance spectroscopy. Whereas the well-known two-mode spectrum is observed when the lowest (s-) states are filled, we find a rich excitation spectrum for ne ≥ 3, which reflects the importance of electron-electron interaction in the present, strongly non-parabolic confining potential. From capacitance spectroscopy we find that the electronic shell structure in our dots gives rise to a distinct pattern in the charging energies which strongly deviates from the monotonic behavior of the Coulomb blockade found in mesoscopic or metallic structures.
Comparison of two Markov chain Monte Carlo (MCMC) methods

As the world advances, statisticians/mathematicians are being involved into more and more complex surveys for the development of society and human beings. Consequently, these complex survey data requires complicated and high-dimensional models for final analysis. We need sophisticated and efficient statistical/mathematical tools for estimation and prediction of these models. Frequently, we simulate samples from these complicated models to estimate parameters because direct estimation is sometimes not efficient. Markov chain Monte Carlo (MCMC) methods have been developed for simulation and efficient estimation. In these times of availability of highspeed computing facilities, MCMC methods are popular tools to generate samples from these complex and high-dimensional distributions. There are some MCMC methods available for application, for instance, Gibbs sampler, Metropolis-Hastings algorithm, etc. In this paper we compare the performance of two MCMC methods, namely the Hybrid (HY) algorithm and the Random Walk Metropolis-Hastings (M-H) algorithm, by employing two logistic regression models and a multivariate normal distribution. We get data used in one of the examples from a Prostate Cancer Study presented in a book by D.W. Hosmer and S. Lemeshow. The Bayesian approach is followed to fit the two logistic regression models. Evaluation of performance is based on convergence of Markov chains, efficiency of estimation and Monte Carlo error variances of the two methods.
Analog Behavioral Models and the Design of Analog Emulation Engines for Power System Computation

This paper addresses the use of Analog Behav- ioral Models (ABMs) in an efficient strategy for designing analog emulation engines for large scale power system com- putation. Through discussion of historical development of analog computation in power system analysis and its present resurgence, we present the need for, and application of ABMs for model verification and validation prior to full structural design and implementation. Results of PSpice simulations of these emulation circuits are also presented and compared with industrial grade numerical simulations for validation.
Hybrid MPI/OpenMP power-aware computing

Power-aware execution of parallel programs is now a primary concern in large-scale HPC environments. Prior research in this area has explored models and algorithms based on dynamic voltage and frequency scaling (DVFS) and dynamic concurrency throttling (DCT) to achieve power-aware execution of programs written in a single programming model, typically MPI or OpenMP. However, hybrid programming models combining MPI and OpenMP are growing in popularity as emerging large-scale systems have many nodes with several processors per node and multiple cores per process or. In th is paper we present and evaluate solutions for power-efficient execution of programs written in this hybrid model targeting large-scale distributed systems with multicore nodes. We use a new power-aware performance prediction model of hybrid MPI/OpenMP applications to derive a novel algorithm for power-efficient execution of realis tic applications from th e ASCS equoia and N PB MZ bench marks. Our new algorithm yields substantial energy savings (4.18% on average and up to 13.8%) with either negligible performance loss or performance gain (up to 7.2%).
Discrete Moyal-type representations for a spin

In Moyal's formulation of quantum mechanics, a quantum spin s is described in terms of continuous symbols, i.e., by smooth functions on a two-dimensional sphere. Such prescriptions to associate operators with Wigner functions, P or Q symbols, are conveniently expressed in terms of operator kernels satisfying the Stratonovich-Weyl postulates. In analogy to this approach, a discrete Moyal formalism is defined on the basis of a modified set of postulates. It is shown that appropriately modified postulates single out a well-defined set of kernels that give rise to discrete symbols. Now operators are represented by functions taking values on ${(2s+1)}^{2}$ points of the sphere. The discrete symbols contain no redundant information, contrary to the continuous ones. The properties of the resulting discrete Moyal formalism for a quantum spin are worked out in detail and compared to the continuous formalism.
Disclosing victimisation to healthcare professionals in Sweden: a constructivist grounded theory study of experiences among men exposed to interpersonal violence

Objective To develop a theoretical model concerning male victims' processes of disclosing experiences of victimisation to healthcare professionals in Sweden. Design Qualitative interview study. Setting Informants were recruited from the general population and a primary healthcare centre in Sweden. Participants Informants were recruited by means of theoretical sampling among respondents in a previous quantitative study. Eligible for this study were men reporting sexual, physical and/or emotional violence victimisation by any perpetrator and reporting that they either had talked to a healthcare provider about their victimisation or had wanted to do so. Method Constructivist grounded theory. 12 interviews were performed and saturation was reached after 9. Results Several factors influencing the process of disclosing victimisation can be recognised from previous studies concerning female victims, including shame, fear of negative consequences of disclosing, specifics of the patient–provider relationship and time constraints within the healthcare system. However, this study extends previous knowledge by identifying strong negative effects of adherence to masculinity norms for victimised men and healthcare professionals on the process of disclosing. It is also emphasised that the process of disclosing cannot be separated from other, even seemingly unrelated, circumstances in the men's lives. Conclusions The process of disclosing victimisation to healthcare professionals was a complex process involving the men's experiences of victimisation, adherence to gender norms, their life circumstances and the dynamics of the actual healthcare encounter.
Nutritional assessment of community-dwelling older adults in rural Nepal

Background Demographic transition in Nepal, like in many developing countries, has resulted in a burgeoning elderly population whose health status is not currently monitored. One pillar of health is adequate nutrition. Yet, little is known about the nutritional health status of the elderly in Nepal. The financial, material, and personnel limitations in Nepal’s health delivery services necessitate health screening instruments that require minimal clinical staff and resources. To our knowledge, no such nutritional assessment tool has been validated in Nepal. Therefore, our aims are two-fold: To assess the nutritional status of the elderly population in one typical Nepali village, Okharpauwa, in Nuwakot District, Nepal; and concurrently, to validate the Mini Nutritional Assessment (MNA) tool. Methods A cross-sectional field study was conducted with a sample of 242 elderly people in Okharpauwa, Nepal to obtain prevalence of malnutrition. Differences in demographic and lifestyle factors between these who were malnourished, those at risk of malnourishment, and those who had adequate nutritional status were analyzed. The MNA tool was evaluated using receiver operating characteristic (ROC) curve analysis; sensitivity, specificity, and diagnostic accuracy were calculated. Results 111 males and 131 females, with a mean age of 69.8±7.4 years, participated in this study. The mean BMI of the participants was 21.4±3.9 kg/m2; the mean MNA score was 19.3±4.2. BMI was significantly correlated with the total MNA score (r = 0.58; p<0.001). The diagnostic accuracy, sensitivity and specificity of MNA were 81%, 86% and 67% respectively. Of the 242 elderly sampled, 24% were malnourished and 65% were at risk of malnutrition. Malnutrition was more prevalent among females (29%) than males (18%), and most prevalent among the marginalized Dalit ethnic group (40%). Elderly persons who were married and literate had better nutritional health than their counterparts. Conclusions The MNA appears to be a valid and sensitive tool for rapid nutritional screening of the elderly in Nepal. The prevalence of malnutrition was high among Nepalese elderly in the Okharpauwa VDC, which requires urgent health monitoring and management attention.
Reconstruction independent component analysis-based methods for intelligent fault diagnosis

Based on machine learning techniques, this paper presents a novel intelligent fault diagnosis method, which is an integrated framework concerning reconstruction independent component analysis (RICA) and multiclass relevance vector machine (MRVM). In this method, the RICA is first used to automatically extract features from raw vibration signals. Then, the learned features are used as the input data of MRVM for the classification of different health conditions of machines. The proposed method is applied to the fault diagnosis of locomotive rolling bearings. According to the diagnosis results, it is verified that the proposed method is able to reliably classify different health conditions. By comparing with diagnosis method based on time-domain statistical analysis and wavelet transformation, the proposed method shows its superiority in automatic features extraction from raw signals.
Pedestrian action prediction using static image feature

In this study, we propose a method to predict how the pedestrian move (run or walk) in the future by using only appearance-based image features. Such kind of motion prediction significantly contributes to intelligent braking system in cars; knowing that the objects will run in several seconds such as for crossing streets, the car can start braking in advance, to effectively reduce the risk for crash accidents. In the proposed method, we empirically evaluate which frames preceding the target action, ‘running’ in this case, are effective for predicting it in the framework of feature selection. By using the most effective frames at which the image features are extracted, we can build the action prediction method. In the experiments, those frames are found around 0.37 second before running action and we also show that they are closely related to human motion phases from walking to running via biomechanical analysis.
A search for electron cyclotron maser emission from compact binaries

Unipolar induction (UI) is a fundamental physical process, which occurs when a conducting body transverses a magnetic field. It has been suggested that UI is operating in RX J0806+15 and RX J1914+24, which are believed to be ultracompact binaries with orbital periods of 5.4 and 9.6 min, respectively. The UI model predicts that those two sources may be electron cyclotron maser sources at radio wavelengths. Other systems in which UI has been predicted to occur are short period extrasolar terrestrial planets with conducting cores. If UI is present, circularly polarized radio emission is predicted to be emitted. We have searched for this predicted radio emission from short period binaries using the Very Large Array (VLA) and Australian Telescope Compact Array (ATCA). In one epoch, we find evidence for a radio source, coincident in position with the optical position of RX J0806+15. Although we cannot completely exclude that this is a chance alignment between the position of RX J0806+15 and an artefact in the data reduction process, the fact that it was detected at a significance level of 5.8 sigma and found to be transient suggests that it is more likely that RX J0806+15 is a transient radio source. We find an upper limit on the degree of circular polarization to be similar to 50 per cent. The inferred brightness temperature exceeds 10(18) K, which is too high for any known incoherent process, but is consistent with maser emission and UI being the driving mechanism. We did not detect radio emission from ES Cet, RX J1914+24 or Gliese 876.
Smart Grid and Optimization

With urging problem of energy and pollution, smart grid is becoming ever important. By gradually changing the actual power grid system, smart grid may evovle into different systems by means of size, elements and strategies, but its fundamental requirements and objectives will not change such as optimizing production, transmission and consumption. Studying the smart grid through modeling and simulation provides us with valuable results which can not be obtained in real world due to time and cost related constraints. However, due to the complexity of the smart grid, achieving optimization is not an easy task, even using computer models. In this paper, we propose an complex system based approach to the smart grid modeling, accentuating on the optimization by combining game theoretical and classical methods in different levels. Thanks to this combination, the optimization can be achieved with flexibility and scalability, while keeping its generality.
Send Orders of Reprints at Reprints@benthamscience.org Lung Injury in Asphyxiated Newborn Pigs Resuscitated from Cardiac Arrest -the Impact of Supplementary Oxygen, Longer Ventilation Intervals and Chest Compressions at Different Compression-to- Ventilation Ratios

Introduction: Non-specific lung inflammatory events caused by severe asphyxia may be intensified by the way we resuscitate the newly born. Assessing lung injury is potentially important because if alternative resuscitation approaches induces similar inflammatory responses or less lung injury. then we may choose the resuscitation approach that is most gentle, and easiest to perform and learn. We investigated the levels of lung inflammatory markers by comparing different ventilation, chest compression and inhaled oxygen fraction strategies in resuscitation of newly born pigs at cardiac arrest. Materials and methods: Progressive asphyxia in newborn pigs was induced until asystole occurred. With current resuscitation guidelines as a reference group, pigs were randomized to receive initial ventilation before chest compressions for 30s, 60s or 90s, or to compression-to-ventilation ratios 3:1or 9:3, or to resuscitation using pure oxygen or air. We analysed inflammatory markers in bronchoalveolar lavage fluid (BAL), IL8 and TNFα, and lung tissue qPCR for genes matrix metalloproteinases (MMP)2, MMP9, TNFα and ICAM-1. Results: BAL-levels of TNFα and IL8 tended to be higher in the 30s group compared to 60s group (p = 0.028 and p = 0.023, respectively) as was gene expression in lung tissue of ICAM-1 and MMP2 (p=0.012 and p=0.043, respectively). MMP2 expression was slightly higher in the 30s group compared to 90s group (p = 0.020). No differences were found between pigs resuscitated with C:V ratio 9:3 and 3:1 or pure oxygen versus air. Conclusion: Compared to current guidelines, with respect to lung injury, resuscitation with longer initial ventilation should be considered. Longer series of chest compressions did not change the lung inflammatory response, neither did the use of air instead of pure oxygen in severely asphyxiated pigs resuscitated from asystole.
mAMSA resistant human topoisomerase IIβ mutation G465D has reduced ATP hydrolysis activity

Type II Human DNA Topoisomerases (topos II) play an essential role in DNA replication and transcription and are important targets for cancer chemotherapeutic drugs. Topoisomerase II causes transient double-strand breaks in DNA, forming a gate through which another double helix is passed, and acts as a DNA dependent ATPase. Mutations in topoII have been linked to atypical multi-drug resistance. Both human Topoisomerase II isoforms, α and β, are targeted by amsacrine. We have used a forced molecular evolution approach to identify mutations conferring resistance to acridines. Here we report mutation βG465D, which was selected with mAMSA and DACA and is cross-resistant to etoposide, ellipticine and doxorubicin. Resistance to mAMSA appears to decrease over time indicating a previously unreported resistance mechanism. G465D lies within the B′ domain in the region that contacts the cleaved gate helix. There is a 3-fold decrease in ATP affinity and ATP hydrolysis and an altered requirement for magnesium in decatenation assays. The decatenation rate is decreased for the mutated G465D protein. And we report for the first time the use of fluorescence anisotropy with intact human topoisomerase II.
Mimicking Ensemble Learning with Deep Branched Networks

This paper proposes a branched residual network for image classification. It is known that high-level features of deep neural network are more representative than lower-level features. By sharing the low-level features, the network can allocate more memory to high-level features. The upper layers of our proposed network are branched, so that it mimics the ensemble learning. By mimicking ensemble learning with single network, we have achieved better performance on ImageNet classification task.
Transformation of Antisense Chalcone Synthase ( CHS ) Gene into Lotus ( Nelumbo Nucifera Gaertn . ) by Particle Bombardment

Chalcone synthase (CHS) is a key enzyme in the flavonoid biosynthesis pathway. CHS genes were cloned from genomic DNA and cDNA from the petals of 'Buntharik' white lotus and 'Sattabangkacha' pink lotus by the PCR technique using a specific primer of the CHS gene designed from the GenBank database. Semi-quantitative RT-PCR analysis revealed that the highest CHS gene expression was found in the early budding stage of the pink lotus and was reduced in later stages. Shoot tips from embryos of Buntharik and Rachinee lotus were used to induce shoot clusters by cultivation on a MS medium supplemented with 40 μM NAA and 0.5 μM TDZ for 8 weeks and a MS medium supplemented with 50 μM BA for 8 weeks. An antisense CHS gene (450 bp) from the cDNA of Buntharik lotus was used to construct a plant transformation vector; pCAMBIA1302CHSA. The vector construct was transformed into Buntharik and Rachinee shoot clusters by particle bombardment. After transformant selection and regeneration, two transformants of Buntharik shoot clusters showed GFP green spots and existence of the GFP gene and hptII gene in the genomic DNA amplified by the PCR technique. In the Rachinee transformants, 3 of 5 showed the GFP green spots and the GFP and hptII genes were identified in amplification by PCR. After CHS gene expression analyses by semi-quantitative RT-PCR, two transformed Rachinee shoot clusters had a reduction in CHS gene expression.