Miracle-dz/UniFAR-FTUs huggingface dataset:
The use of INS/GPS in a highway survey system

The integration of an inertial navigation system (INS) and Global Positioning System (GPS) receivers in differential mode is investigated for application to highway survey systems. A mobile highway inventory system (MHIS) operated by Alberta Transportation is used as a first step in the realization of an all-purpose kinematic survey system. MHIS requirements of approximately 0.5 m in position, 10 cm-s/sup -1/ in velocity, 0.5% in slope, and 0.2 degrees in curvature appear obtainable with the integrated system. If these requirements can be surpassed, INS/GPS can be used for road surveys, possibly replacing conventional survey techniques. The authors briefly describe the MHIS and outline the benefits of using INS/GPS for accurate and reliable geometric data collection. They outline the mathematical models for INS/GPS integration. Road tests performed using INS/GPS over a well-controlled traverse are discussed, and results are given. <<ETX>>
Contrasting subduction structures within the Philippine Sea plate: Hydrous oceanic crust and anhydrous volcanic arc crust

We show contrasting subduction structures within the Philippine Sea plate inferred from active‐source wide‐angle reflection data. Previous studies showed that large‐amplitude reflections from the slab are observed in southwest Japan and indicated that a thin low‐velocity layer with a high fluid content is formed along the top of the subducting oceanic crust. On the contrary, we found that the slab reflections have smaller amplitudes in the Izu collision zone, central Japan, where the Izu‐Bonin volcanic arc has been colliding/subducting, suggesting that such a low‐velocity layer does not exist beneath the collision zone. This structural difference is also supported by P‐wave and S‐wave velocity anomalies by passive‐source tomography and electrical conductivity, and correlates with the regional distribution of deep tremors and intraslab earthquakes, both of which are induced by dehydration processes within the downgoing slab. Based on these comparisons, we suggest that the original structure of the incoming plate controls the contrasting subducting systems: typical oceanic plate absorbs water by hydrothermal circulation at spreading centers and/or seawater infiltration at outer rises, whereas volcanic arc crust consumes a large amount of hydrous minerals for melt production and metamorphoses to more stable, anhydrous forms before subduction.
Kinetics of the smectite to illite transformation in the Denver Basin: Clay mineral, K-Ar data, and mathematical model results

Clay mineral data, potassium-argon (K-Ar) ages, and mathematical model simulations indicate the important kinetic factors controlling the smectite to illite transformation ("illitization") in Upper Cretaceous Mowry and Niobrara core and outcrop bentonites from the Denver basin. The data also provide additional information on the thermal history of the basin. Data show that both the percentages of illite layers and the K-Ar ages of mixed layer illite-smectite (I/S) increase with increasing depths of burial, and this trend was simulated mathematically employing a very simplified burial model with a fifth-order overall kinetic expression for the formation of illite. For most of the basin, the data is compatible with I/S having been formed in response to increased temperature from progressive burial, because the oldest K-Ar ages of I/S are from the deepest buried I/S along the basin axis. In addition, these data qualitatively suggest that I/S even as small as <0.1 micrometer retains radiogenic argon under Denver basin burial temperatures. I/S separated from drill core bentonites from the Wattenberg gas field, astride the basin axis and known to have been subjected to an anomalously high temperature history, are the most illitic and among the oldest measured from core in this study. The ages of illitization (about 60 Ma) are coincident with the Laramide time of structural development of the basin and uplift of the Front Range. The reconstructions of the burial history, and the modelling of the timing and extent of illitization, suggest that the area of the Wattenberg gas field was an upper Cretaceous depocenter, an area of relatively deeper burial along the basin axis. However, the data can not rule out the possibility that these sediments at and near the Wattenberg gas field were heated not only by burial but also by i neous and related hydrothermal activity associated with the Colorado mineral belt during the Laramide uplift (70-45 Ma) of the Front Range. Likewise, the anomalously illitic I/S in outcrop bentonites along the Front Range adjacent to the Wattenberg gas field may have been formed in response either to deep burial and/or by Laramide-age secondary heating superimposed on burial.
Degenerated CRISPRs widely regulate Cas expression to balance immunity and cost

20 CRISPR RNAs (crRNAs) and Cas proteins together provide prokaryotes with adaptive immunity against genetic invaders. How Cas expression is fine-tuned to avoid energy burden while satisfying the dynamic need of crRNAs remains poorly understood. Here we experimentally demonstrated widespread degenerated mini-CRISPRs encode CreR (Cas-regulating) RNAs to mediate autorepression of type 25 I-B, I-E and V-A Cas proteins, based on their partial complementarity to cas promoters. This autorepression decreases energy burden and autoimmune risks, thus mitigating the fitness cost on host cell, and remarkably, senses and responds to alterations in the volume of canonical crRNAs, which compete with CreR for Cas proteins. Moreover, CreR-guided Cas autorepression can be subverted by 30 diverse anti-CRISPR (Acr) proteins that destruct Cas proteins, which in turn replenishes the weapon depot. Our data unveil a general degenerated crRNA-guided autorepression paradigm for diverse Cas effectors, which highlights the intricate (self-)regulation of CRISPR-Cas and its transcriptional counterstrategy against Acr attack
All (k;g)-cages are k-edge-connected

A (k;g)-cage is a k-regular graph with girth g and with the least possible number of vertices. In this paper, we prove that (k;g)-cages are k-edge-connected if g is even. Earlier, Wang, Xu, and Wang proved that (k;g)-cages are k-edge-connected if g is odd. Combining our results, we conclude that the (k;g)-cages are k-edge-connected. © 2005 Wiley Periodicals, Inc. J Graph Theory 48: 219–227, 2005
Tectonic Framework and Evolution of the Dabie Mountains in Anhui, Eastern China

The Dabie Mountains are believed to be a collisional orogenic belt between the Yangtze amd Sino-Korean continental plates. It is composed of the foreland fold-thrust zone, the subducting cover and basement of the Yangtze continental plate, the coesite- and diamond-bearing ultra-high pressure metamorphic zone and the meta-ophiolitic melange zone in the subducting basement, the fore-arc flysch nappe and the back thrust zone occurring respectively on the southern and northern margins of the Sino-Korean continental plate and the inherited basin with molassic deposits on the northern margin. When the palaeo-Dabie oceanic plate subducted northward in the Early Palaeozoic, volcanic arc and back arc basin probably formed on the southern margin of the Sino-Korean continental plate. The Sm / Nd isotopic dating of the strata and eclogite which were drawn into the foreland fold-thrust zone indicates that the intense collision of the two continental plates took place in the Early Mesozoic.
Oblique-slip deformation in extensional terrains: A case study of the lakes Tanganyika and Malawi Rift Zones

The East African Rift system (EAR) is the archetypal continental rift and a widely proposed analogue for the early stages of evolution of passive continental margins. The three-dimensional structure of parts of the EAR has been recently elucidated by a multifold seismic (MFS) survey of Lakes Tanganyika and Malawi (Project PROBE). Analysis of fault geometries displayed on the PROBE MFS data coupled with the more extensive 28-kHz echosounder data has improved understanding of the geometry and kinematics of the linked fault systems that underlie the lakes. In particular, it has been recognized that profiles across (i.e., at high angles to) the rift elongation commonly display fault geometries that are not readily retrodeformable. There must therefore be significant displacement out of the plane of what would conventionally be regarded as “dip” lines, that is, perpendicular to rift elongation and parallel to the tectonic transport or extension direction. Careful determination of fault plane dip and the dip of synrift reflectors in the hanging wall demonstrates that the dip directions of the shallowest faults and the steepest hanging wall sediment dips are oriented either NW or SE. This defines the direction of maximum fault block rotation and therefore the direction of extension or tectonic transport as NW/SE, oblique to the trend of the regional rift axis and to the apparent strike of many of the major border faults in the survey area. The border faults and many other faults imaged on the PROBE MFS data must therefore have significant components of strike-slip motion and the Tanganyika and Malawi rift zones have undergone extension oblique to and not perpendicular to their axes. Near dip-slip normal faults, steeply dipping oblique-slip faults and subvertical strike-slip or transfer faults have all been recognized in a complex, linked fault system that accomplishes the extension. The overall orientation of the rift lakes and their internal segmentation are influenced by major, preexisting, subvertical fault zones within the basement. Complex accommodation zones act principally as transfer zones that allow switches in gross polarity of the border fault system. The detailed geometries of the accommodation zones result from the specific relations between juxtaposed half-graben and the strike and internal geometry of the influencing basement structure. The variations in fault geometry, subsidence, water depth and basin or rift morphology can be better explained by an oblique-slip extensional model influenced by basement structures than by a simple orthogonal extensional model.
Painlev\'e I double scaling limit in the cubic random matrix model

We obtain the double scaling asymptotic behavior of the recurrence coefficients and the partition function at the critical point of the $N\times N$ Hermitian random matrix model with cubic potential. We prove that the recurrence coefficients admit an asymptotic expansion in powers of $N^{-2/5}$, and in the leading order the asymptotic behavior of the recurrence coefficients is given by a Boutroux tronqu\'ee solution to the Painlev\'e I equation. We also obtain the double scaling limit of the partition function, and we prove that the poles of the tronqu\'ee solution are limits of zeros of the partition function. The tools used include the Riemann--Hilbert approach and the Deift--Zhou nonlinear steepest descent method for the corresponding family of complex orthogonal polynomials and their recurrence coefficients, together with the Toda equation in the parameter space.
On the risk of manual annotations in 3D confocal microscopy image segmentation

Image segmentation in 3D confocal fluorescence microscopy images is a common problem in many biomedical studies. Deep learning-based methods have achieved great success on such tasks. In the literature, manual 3D annotations are still commonly used for model training or performance evaluation. But, due to the nature of the lens-based optical instruments, diffraction of light always occurs, which can lead to obscure boundaries of the biomedical structures being imaged. For example, when analyzing nuclei from 3D fluorescence microscopy images of cells marked by DNA dyes, the exact boundaries are usually not clearly identifiable, especially along Z. This makes accurate segmentation, both manually and automatically, very challenging. For applications where the boundary accuracy is crucial, the downstream analyses can thus be significantly compromised. This problem can be addressed with special experimental-computational co-design to acquire the "biological ground truth". For the nuclei example, we can take cells expressing mEGFP tagged lamin B1, from which we can acquire both the DNA dye channel (nucleus) and the lamin B1 channel (nuclear envelope). Lamin B1 signals clearly mark the nuclei boundary and can thus serve as the real truth. We demonstrate that training a deep learning-based nuclei instance segmentation model with biological ground truth and manual annotations will result in significant differences in various metrics, such as volume or application-specific measurements. Also, we show the universalness of such issues with manual annotations by testing different state-of-the-art deep learning-based methods. We hope our work can raise within the biomedical image analysis community the awareness of (1) the importance of interdisciplinary collaborations, e.g., computational-experimental co-design for biological ground truth collection, and (2) potentially significant issues with manual annotation in training or evaluating deep learning-based segmentation models.
A novel chronic wound biofilm model sustaining coexistence of Pseudomonas aeruginosa and Staphylococcus aureus suitable for testing of antibiofilm effect of antimicrobial solutions and wound dressings

Chronic wounds are a large burden to patients and healthcare systems. Biofilm infections in chronic wounds are crucial factors leading to non-healing of wounds. It is important to study biofilm in wounds and to develop effective interventions against wound biofilm. This study presents a novel in vitro biofilm model mimicking infected chronic wounds. The novel layered chronic wound biofilm model uses woundlike media and includes both Pseudomonas aeruginosa and Staphylococcus aureus , which have been identified as the most important pathogens in wounds. The model sustains their coexistence for at least 96 h. Microscopy of the model revealed microbial growth in non-surface attached microcolonies as previously observed in vivo. The model was used to determine log 10 -reduction for the use of an antimicrobial solution and antimicrobial dressings (containing silver or honey) showing moderate-to-low antibiofilm effect, which indicates better concordance with the observed clinical performance of this type of treatment than other widely used standard tests.
Short-term effects on brain functional network caused by focused-attention meditation revealed by Tucker3 clustering on graph theoretical metrics

This study examines the short-term effects of focused-attention meditation on functional brain state in novice meditators. There are a number of feature metrics for functional brain states, such as functional connectivity, graph theoretical metrics, and amplitude of low frequency fluctuation (ALFF). It is necessary to choose appropriate metrics and also to specify the region of interests (ROIs) from a number of brain regions. Here, we use a Tucker3 clustering method, which simultaneously selects the feature vectors (graph theoretical metrics and fractional ALFF) and the ROIs that can discriminate between resting and meditative states based on the characteristics of the given data. In this study, breath-counting meditation, one of the most popular forms of focused-attention meditation, was used and brain activities during resting and meditation states were measured by functional magnetic resonance imaging. The results indicated that the clustering coefficients of eight brain regions tended to increase through the meditation. Our results reveal that short-term effects of breath-counting meditation can be explained by network density changes in these eight brain regions.
Combating Coronary Calcium Scoring Bias for Non-gated CT by Semantic Learning on Gated CT

Coronary calcium scoring (CCS) can be quantified on non-gated or gated computed tomography (CT) for screening cardiovascular disease (CVD). And non-gated CT is used for routine coronary artery calcium (CAC) screening due to its affordability. However, artifacts of non-gated CT imaging, pose a significant challenge for automatic scoring. To combat the scoring bias caused by artifacts, we develop a novel semantic-prompt scoring siamese (SPSS) network for automatic CCS of non-gated CT. In SPSS, we establish a sharing network with regression supervised learning and semantic supervised learning. We train the SPSS by mixing non-gated CT without CAC mask and gated CT with CAC mask. In regression supervised learning, the network is trained to predict the CCS of non-gated CT. To combat the influence of motion artifacts, we introduce semantic supervised learning. We utilize gated CT to train the network to learn more accurate CAC semantic features. By integrating regression supervised learning and semantic supervised learning, the semantic information can prompt the regression supervised learning to accurately predict the CCS of non-gated CT. By conducting extensive experiments on publicly available dataset, we prove that the SPSS can alleviate the potential scoring bias introduced by pixel-wise artifact labels. Moreover, our experimental results show that the SPSS establishes state-of-the-art performance.
The role of public–private partnerships in promoting smallholder access to livestock markets in developing countries

Rising demands for quality and safety measures in high-value agriculture and livestock markets have necessitated the creation of increasingly complex supply chains to manage the flow of goods and information among channel actors. Public–private partnerships (PPPs) can play a key role in strengthening links within the supply chain, particularly where market failures impede access by the poor. This paper examines the potential of PPPs in promoting smallholder access to such supply chains. A conceptual model is presented that highlights the need to generate chain-level benefits for all channel participants in order for PPPs to be sustainable and to adequately address market failures. A case of both a successful and a failed PPP in livestock markets illustrates the utility of this model.
Data from selected U.S. Geological Survey national stream water-quality monitoring networks (WQN) on CD-ROM

During the past 30 years, the U.S. Geological Survey (USGS) has operated two national stream water-quality networks, the Hydrologic Benchmark Network (HBN) and the National Stream Quality Accounting Network (NASQAN). These networks (Fig. 1) were established to provide national and regional descriptions of stream water-quality conditions and trends, based on uniform monitoring of selected watersheds throughout the United States, and to improve our understanding of the effects of the natural environment and human activities on water quality. The HBN, consisting of 63 relatively small, minimally-disturbed watersheds, provides data for investigating naturally-induced changes in streamflow and water quality and the effects of airborne substances on water quality. These watersheds range in size from 2 to 2,000 square miles with a median drainage basin size of 57 square miles. NASQAN, consisting of 618 larger, more culturallyinfluenced watersheds, provides information for tracking water-quality conditions in major U.S. rivers and streams. Drainage basins range in size from 1 square mile to 1.2 million square miles with a median drainage basin size of about 4,000 square miles. NASQAN and HBN watersheds represent a diverse set of climatic, physiographic, and cultural characteristics. Stream water-quality measurements are available for the approximate periods 1973 to 1995 for NASQAN and 1962 to 1995 for HBN. The data reflect sampling for a variety of water properties over a wide range of streamflow conditions using relatively consistent sampling and analytical methods. Figures 2 and 3 display the number of water-quality analyses by year for NASQAN and HBN, respectively. These data, collectively referred to as Water-Quality Networks (WQN), are contained in the two-CD-ROM set USGS Digital Data Series DDS-37, “Data from Selected U.S. Geological Survey National Stream Water-Quality Monitoring Networks (WQN),” by R.B. Alexander, J.R. Slack, A.S. Ludtke, K.K. Fitzgerald, and T.L. Schertz.
Morphological Analyzers of Arabic Dialects: A survey

— Morphological analysis is a crucial stage in natural language processing. For the Arabic language many attempts have been conducted to build morphological analyzers. Despite the increasing attention paid to Arabic dialects recently, only a few number of morphological analyzers have been built compared to MSA. In addition, those tools often cover a few dialects of Arabic such as Egyptian and Levantine, thereby they don’t currently support all Arabic dialects. In this paper, we present a wide literature review of morphological analyzers processing Arabic dialects. We classify their building approaches and propose some guidelines to adapt them to a specific Arabic dialect. In addition, a quick benchmarking of the available analyzers is given in order to evaluate their performance. Our goal in this paper is to provide a quick reference guide of Arabic dialect morphological analyzers, as well as some recommendations for researchers needing to develop new Arabic dialect morphological analyzers. Results of this survey can be used as baseline for future Arabic dialect morphological analyzers building.
Comment on “Bottlenecks: Sectoral Imbalances and the US Productivity Slowdown”

: Acemoglu, Autor, and Patterson’s paper is thought-provoking and full of rich insights. They propose that TFP growth among industry suppliers has become less balanced over time which, in turn, has reduced innovation spillovers. These reduced spillovers became an increasing drag on growth in the 1977-2007 period. In this comment, we Iirst argue that they are silent on the important changes in trend TFP growth that are apparent since World War II—the slowdown after the early 1970s, the speedup in the mid-1990s, and the subsequent slowdown in the mid-2000s. The issue is that the NBER-CES productivity dataset at the core of their analysis looks very different from other datasets. Second, we explore whether factor-share anomalies in their data affect their results; if anything, correcting those anomalies strengthens their apparent results. Nevertheless, given the unusual properties of their data, we hesitate to give it too much weight on its own. Third, we repeat their analysis with higher quality but, unfortunately, less granular, industry data. These results look very different: Unbalanced upstream innovation is, if anything, good for growth. We conclude that the detrimental effects of unbalanced innovation are an intriguing conjecture but fall short of proven fact.
Generative Adversarial Network (GAN) for Remote Sensing Images unsupervised Learning

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Generative Adversarial Network (GAN) for Remote Sensing Images unsupervised Learning Amina Ben Hamida, A Benoit, Patrick Lambert, Chokri Ben Amar