Miracle-dz/UniFAR-FTUs huggingface dataset:
Interpretation of negative birefringence observed in strong-field optical pump-probe experiments: High-order Kerr and plasma grating effects

The analysis of negative birefringence optically induced in major air components (Loriot et al., [1, 2]) is revisited in light of the recently reported plasma grating-induced phase-shift effect predicted for strong field pump-probe experiments (Wahlstrand and Milchberg, [3]). The nonlinear birefrin- gence induced by a short and intense laser pulse in argon is measured by femtosecond time-resolved polarimetry. The experiments are performed with degenerate colors, where the pump and probe beam share the same spectrum, or with two different colors and non-overlapping spectra. The in- terpretation of the experimental results is substantiated using a numerical 3D+1 model accounting for nonlinear propagation effects, cross-beam geometry of the interacting laser pulses, and detec- tion technique. The model also includes the ionization rate of argon and high-order Kerr indices introduced by Loriot et al. enabling to assess the contribution of both terms to the observed effect. The results show that the ionization-induced phase-shift has a minor contribution compared to the high-order Kerr effect formerly introduced, the latter allowing a reasonably good reproduction of the experimental data for the present conditions.
Vision-Based Algorithm for Augmented Reality Registration

Instead of computely redacting the real world as a Virtual Reality(VR) system does, the user can see computer-generated 3D model superimposed on the real world with an Augmented Reality(AR) system. One of the key technologies of AR is the real-time 3D registration of objects in the real world. This paper describes a vision-based method for AR registration and its application in an AR system with See-Through Head Mounted Display(STHMD). The scheme has a simple structure, which employs one color CCD camera and several mark points with different colors. The real world coordinates of the markers are known, and their screen coordinates are obtained through color filtering of the input video stream. If all the markers are successfully tracked, a translation matrix and an orientation matrix can be uniquely determined using projective transform relations. The algorithm requires only linear equation solving with small calculation errors and little computation time consumption. Therefore it has good real-time performance characteristics and can be employed with either graphic workstations or ordinary PCs. The method can work at long ranges and is applicable to outdoor augmented reality systems.
Codifier: A Programmer-Centric Search User Interface

Search tools have transformed knowledge discovery by exposing information from previously hidden repositories to the workers who need it. Search engines like Google and Live.com provide search capabilities via a simple one-line text query box, and present results in a paged HTML list. When the repository being searched contains structured information with extractable metadata (e.g. program source code), it can be advantageous to index the metadata and use it to enable queries that are more task-centric and suitable for an domain-specific audience.
An investigation into whether poaching creates an ecological trap for white rhinoceros in Hluhluwe-iMfolozi Park, South Africa

In an ecological trap, animals choose habitat based upon cues that once led members of their species to optimal habitat, but now lead to habitat where individual fitness is reduced because of changing conditions. The southern white rhinoceros (Ceratotherium simum) is a threatened species due to poaching for its keratin horn. Here, I investigate the degree to which poaching creates an ecological trap for white rhinoceros in South Africa’s Hluhluwe-iMfolozi Park. To this end, I develop a model for white rhino habitat preference and analyse rhino movement through time over the gradient of habitat preference and poaching risk. Three aspects of the ecological trap scenario were assessed: environmental habitat quality in hotspots relative to cold-spots for poaching, rhino movement into high-quality habitat regardless of poaching risk, and the impact of poaching on white rhino fitness at the population level. I found that while high quality habitat exists in poaching hotspots, net colonization was higher into high quality habitat in low-risk areas for poaching than in high-risk poaching hotspots. Further, fitness has declined for rhino populations in hotspots relative to cold-spots of the same quality, and likely represents a loss in fitness to the park population as a whole. While at this time there is little evidence to suggest rhino are pulled away from high quality cold-spots to areas at high risk for poaching, continued monitoring of the habitat quality-risk gradient is crucial to understanding and managing the white rhino population in Hluhluwe-iMfolozi Park.
Design of a planar eleven antenna as wideband MIMO micro-base station antenna with genetic algorithm

Multi-input multi-output (MIMO) antennas operating over a wide frequency band are required in future wireless communication systems, such as in the 5G communication system. The Eleven antenna is a dual-polarized ultra-wideband (UWB) antenna with a decade bandwidth. A new low-profile planar eleven antenna is designed as a wideband MIMO antenna for micro-base stations in future wireless communication systems. The design criterion is to minimize both the reflection coefficient and the ratio of the required average received power over the threshold for 95% of the total probability of detection (PoD) in the Rich Isotropic Multipath (RIMP) and random Line-of-Sight (RLOS) scenarios of both one-bit stream and two-bit stream. The design is performed via optimization with a genetic algorithm. Acknowledgements Firstly, I want to thank my examiner Professor Per-Simon Kildal for giving me the chance to do this master thesis project in the division of antenna systems. It is the most precious experience during the years at Chalmers University of Technology and also a invaluable experience in my life. It’s a big pity that he passed away suddenly and unexpectedly before I finished the final data processing of this thesis. I would like to thank my supervisor associate Professor Jian Yang for the guidance and help all the way from the beginning to the end of this thesis project. I was a student who only knew abstract theories and concepts from antenna books and only relied on formulas and derivation of equations to analyze antenna problems before doing this thesis project. I learned many engineer’s thoughts and problem solving techniques for the real antenna design from doing the thesis project under Jian’s supervision, which can never be obtained from books. I would like to thank Dr. Ulf Calberg from Qamcom Research & Technology in Gothenburg for the help on the ViRMLab code for the simulation of the antenna. It’s hard to imagine how much more time I would have to spend on this thesis project without his help. I learned a lot of ideas and tricks of programming from him. I would like to thank PhD student in the division of antenna systems Sadegh Mansouri Moghaddam for detailed instruction on using the reverberation chamber for the radiation efficiency measurement, discussion on the probability of detection, help on the coverage pattern and a lot of other things that I’m not able to name one by one. I would like to thank PhD student Madeleine Kildal for the help on using the Bluetest software for the reverberation chamber. Last but not least, I would like to thank my friends Weihua Wang and Junfei Tang at Chalmers University of Technology for accompany. Wenjie Yu Kunming, China, December 16, 2016
The middle Miocene in southern California: Mammals, environments, and tectonics of the Barstow, Crowder, and Cajon Valley formations—Field Trip of the North American Paleontological Convention, June 22, 2019

Author(s): Loughney, Katharine; Smiley, Tara | Abstract: The Mojave Region preserves a rich and continuous Miocene mammal-fossil record that formed during a time of significant tectonic activity and climate change. We will visit exposures of the Crowder, Cajon Valley, and Barstow formations to look at the evolution of three different sedimentary basins through the middle Miocene. Participants will learn how depositional environments and habitats changed through time in relation to tectonics and climate and how they influenced patterns of mammal diversity and biostratigraphy.
Multilingual Articulatory Features for Speech Recognition

Ore, Brian . M.S., Department of Electrical Engineering, Wright State University, 2007 . Multilingual Articulatory Features for Speech Recognition. Articulatory features describe the way in which the speech organs are used when producing speech sounds. Research has shown that incorporating this information into speech recognizers can lead to an improvement in system performance. The majority of previous work, however, has been limited to detecting articulatory features in a single language. In this thesis, Gaussian Mixture Models (GMMs) and Multi-Layer Perceptrons (MLPs) were used to detect articulatory features in English, German, Spanish, and Japanese. The outputs of the detectors were used to form the feature set for a Hidden Markov Model (HMM)-based phoneme recognizer. The best overall detection and recognition performance was obtained using MLPs with context. Compared to Mel-Frequency Cepstral Coefficient (MFCC)-based systems, the proposed feature sets yielded an increase of up to 4.39% correct and 5.37% accuracy when using monophone models, and an increase of up to 3.22% correct and 2.60% accuracy with triphone models. On a word recognition task, however, the MFCC systems performed better. Multilingual articulatory feature detectors were also created for all four languages using MLPs. An additional feature set was created using the multilingual detectors and evaluated on the same phoneme recognition task. Compared to the feature sets created with the languagedependent MLP detectors, the maximum decrease in system performance with monophone models was 1.44% correct and 1.72% accuracy on Japanese, and the maximum improvement in system performance with triphone models was 0.75% correct and 0.40% accuracy on Spanish. On a word recognition task, the feature sets created with the multilingual MLP detectors yielded a decrease of up to 3.75% correct and 6.01% accuracy. As a final experiment, two different procedures were investigated for combining the scores from the English GMM and MLP articulatory feature detectors. It was found that the detection performance for each articulatory feature can be improved by combining the scores from all GMM and MLP detectors.
Fracture Network Imaging on Rock Slope Instabilities Using Resonance Mode Analysis

We performed modal analysis using frequency domain decomposition of ambient seismic vibration data collected on large rock slope instabilities. This technique enables a robust detection of resonance frequencies and provides the corresponding mode shape vectors. We applied the technique to synthetic and field data sets acquired by seismometer arrays on two rock instabilities in Switzerland. We found that, at the fundamental mode, the entire instability vibrates in‐phase with the dominant mode shape vector oriented perpendicular to dominant fracture systems. At higher frequencies, different compartments of the instability resonate antiphase. Therefore, delineating the zero crossings between the phases allows dominant fractures to be efficiently mapped. Approximately 1 hr of ambient vibration data suffices to apply the method successfully. The method also potentially detects hidden fractures that cannot be observed by geological field mapping. In addition, this approach combines classic amplification and polarization analysis into one technique, simplifying data processing efforts.
Edinburgh Research Explorer Segmentation of SLAR Imagery with Convolutional LSTM Selectional AutoEncoders

We present a method to detect maritime oil spills from Side-Looking Airborne Radar (SLAR) sensors mounted on aircraft in order to enable a quick response of emergency services when an oil spill occurs. The proposed approach intro-duces a new type of neural architecture named Convolutional Long Short Term Memory Selectional AutoEncoders (CMSAE) which allows the simultaneous segmentation of multiple classes such as coast, oil spill and ships. Unlike previous works using full SLAR images, in this work only a few scanlines from the beam-scanning of radar are needed to perform the detection. The main objec-tive is to develop a method that performs accurate segmentation using only the current and previous sensor information, in order to return a real-time response during the ﬂight. The proposed architecture uses a series of CMSAE networks to process in parallel each of the objectives deﬁned as diﬀerent classes. The output of these networks are given to a machine learning classiﬁer to perform the ﬁnal detection. Results show that the proposed approach can reliably detect oil spills and other maritime objects in SLAR sequences, outperforming the accuracy of previous state-of-the-art methods and with a response time of only 0.76 s.
Disaster Risk Mitigation of Landslide for Sustainability of Geothermal Production in Bandung Regency, West Java Province, Indonesia

Indonesia, an archipelagic nation which lies on the tectonic plate namely pacific ring of fire, it addresses for how Indonesia has 129 active volcanic mountains. Although it geologically prone for endangered areas for earthquake and volcanic eruption, but beneath the vicinity of mountain edifice, lies geothermal potential energy. Most of Indonesian geothermal located on the mountain hills and a slope, that condition makes geothermal area prone to landslide. One of which can be found in Bandung Regency, West Java Province, Indonesia. The increasing risk landslide phenomena in Indonesia are related to natural physical factor and socio-economic conditions. The aims of this research are to analyze the risk level of landslide disaster which is reviewed by the aspects of hazard threat, vulnerability and capacity, and to give mitigation alternatives. The method of this research has been conducted by assessment of weight and scoring technique as well as spatial analysis using Geographical Information System (GIS). The result of the study shows most of the area of the study is in medium risk level that is prone to landslide occurrence with the broad of 7,420.4 Ha or 57% of the study area. Mitigation effort in facing landslide in the study area is aimed to maintain the sustainability of utilization of renewable energy which is geothermal energy that will be reviewed from three aspects sustainability, namely environmental, economic, and social.
Kernel Credal Classification Rule – Application on Road Safety

A credal partition based on belief functions has been proposed in the literature for data clustering. It allows the objects to belong; with different masses of belief; not only to the specific classes, but also to the sets of classes called meta-class which correspond to the disjunction of several specific classes. In this paper, a kernel version of the credal classification rule (CCR) is proposed to perform the classification in feature space of higher dimension. Each singleton class or meta-class is characterized by a center that can be obtained using many way. The kernels based approaches have become popular for several years to solve supervised or unsupervised learning problems. In this paper, our method is extended to the CCR. It is realized by replacing the inner product with an appropriate positive definite function, implicitly perform a nonlinear mapping of the input data into a high-dimensional feature space, and the corresponding algorithm is called kernel Credal Classification Rule( KCCR). We present in this work KCCR algorithm to powerful corresponding nonlinear form using Mercer kernels. The approach is applied for the classification of experimental data collected from a system called Vehicle-Infrastructure-Driver (VID), based on several representative trajectories observations made in a bend, to obtain adequate results with data experimentally realized based on the instructions given to drivers. The test on real experimental data shows the value of the exploratory analysis method of data. Another experiments using the generated and real data form benchmark database are presented to evaluate and compare the performance of the KCCR method with other classification approaches.
Hysteretic response of sap flow in Scots pine (Pinus sylvestris) to meteorological forcing in a humid low‐energy headwater catchment

Transpiration mediated by physiology is driven by the meteorological variables. Understanding their relationships is crucial to advancing terrestrial ecohydrological studies. Here, we used sap flow measurements in Scots pine to examine the temporal responses of transpiration to temperature (Ta), vapour pressure deficit (VPD), and net radiation (Rn). Seasonal variations and the hysteresis between sap flux density (Js) and meteorological variables were investigated. The results show that VPD and Rn were dominant factors influencing hourly Js. Daily peaks of Js lagged behind peaks of Ta, VPD, and Rn, by ~2–4 hr. Anticlockwise hysteresis loops between Js and Ta and VPD were observed, and the size of loops change with prevailing weather conditions (i.e., rainy or rainless) and seasons. Longer time lags were found in April and September than in other months. The hysteresis is partly related to the low energy, humid nature of the site which resulted in limited moisture stress to the trees, and thus the trees did not necessarily need a conservation mechanism to restrict water loss as proposed by other studies in semi‐arid areas. Release and refill of trunk water storage could plausibly contribute to the hysteresis, although the effect may be entwined with atmospheric demand making it difficult to separate without sophisticated measurements. This study highlights the diversity in plant water relations across temporal scales and seasons and calls for more work across geographic locations and climates.
Radiocarbon Dating of the Transition from the Early to the Middle Bronze Age in Northeastern Syria

ABSTRACT The paper presents radiocarbon (14C) dates of samples collected from the Bronze Age cultural strata (VI–II) excavated within Sector P, Tell Arbid, Khabur Triangle, northern Mesopotamia. These strata contain objects (remains of a caravanserai, pits, graves, pottery kilns, and multi-phase houses) representing the periods of Early Jezirah 4-5, and Old Jezirah I-II. 14C dating of these strata was especially important because of a clearly visible period of abandonment of the area at the onset of 2nd millennium BC, recorded on all Khabur Triangle sites studied so far, and because of the questionable reliability of the chronology derived from scarce historical sources. Of the 29 samples of cereal grains, 9 appeared to contain residual material, while Bayesian-analyzed 14C ages of the remaining 20 allowed us to say that, at the turn of the 3rd millennium BC, Tell Arbid was abandoned later than other sites in the area, and that it was occupied over a distinctly longer period during the early 2nd millennium.
Comparisons of Two Different Grid Systems in the Simulation of Oscillatory Flow Field in a Baffled Reactor

Based on commercial computational fluid dynamics software of CFX,the three dimensional oscillatory flow field in a baffled oscillatory flow reactor(OFR) was simulated using two different grid systems——unstructured grid and structured grid.The visualized computational flow fields and experimental flow field were compared.The results show that the flow pattern of two simulative flow fields are consistent with that of the experimental oscillatory flow fields and CFD is a good tool to study and design OFR;Besides,transformation of flow pattern exists in all the three fields of OFR with the increase of Re_0.
Epidemic Algorithms for Reliability in Mobile Content-based Routing

Acknowledgments We would like to thank our advisors Prof. Gian Pietro Picco and Prof. Gian-paolo Cugola for trusting, encouraging, and supporting us all throughout our thesis work. Through advice and lively discussions, they have contributed a lot to the development of this work. We also want to thank Prof. Carlo Ghezzi for arousing our interest in Software Engineering during his lectures and for his support in many occasions. We developed our research at the Software Engineering Laboratory of Politecnico di Milano. In this environment we had the opportunity to meet people that in so many ways contributed to this work. In addition to the ones we already mentioned, we would like to express our gratitude to Luca Zanolin and many others. We are especially grateful to our class mates for their friendship and support throughout our university career. In particular, we would like to thank
Calreticulin Mutations in Myeloproliferative Neoplasms: Comparison of Three Diagnostic Methods

Calreticulin (CALR) mutations have recently been reported in 70–84% of JAK2V617F-negative myeloproliferative neoplasms (MPN), and this detection has become necessary to improve the diagnosis of MPN. In a large single-centre cohort of 298 patients suffering from Essential Thrombocythemia (ET), the JAK2V617F, CALR and MPL mutations were noted in 179 (60%), 56 (18.5%) and 13 (4.5%) respectively. For the detection of the CALR mutations, three methods were compared in parallel: high-resolution melting-curve analysis (HRM), product-sizing analysis and Sanger sequencing. The sensitivity for the HRM, product-sizing analysis and Sanger sequencing was 96.4%, 98.2% and 89.3% respectively, whereas the specificity was 96.3%, 100% and 100%. In our cohort, the product-sizing analysis was the most sensitive method and was the easiest to interpret, while the HRM was sometimes difficult to interpret. In contrast, when large series of samples were tested, HRM provided results more quickly than did the other methods, which required more time. Finally, the sequencing method, which is the reference method, had the lowest sensitivity but can be used to describe the type of mutation precisely. Altogether, our results suggest that in routine laboratory practice, product-sizing analysis is globally similar to HRM for the detection of CALR mutations, and that both may be used as first-line screening tests. If the results are positive, Sanger sequencing can be used to confirm the mutation and to determine its type. Product-sizing analysis provides sensitive and specific results, moreover, with the quantitative measurement of CALR, which might be useful to monitor specific treatments.