Miracle-dz/UniFAR-FTUs huggingface dataset:
Reframing the Challenge of Global Wildfire Threats to Water Supplies

The timing, extent, and severity of forest wildfires have increased in many parts of the world in recent decades. These wildfires can have substantial and devastating impacts on water supply, ecohydrological systems, and sociohydrosystems. Existing frameworks to assess the magnitude and spatial extent of these effects generally focus on local processes or services and are not readily transferable to other regions. However, there is a growing need for regional, continental, and global scale indices to assess the potential effect of wildfires on freshwater availability and water supply resilience. Such indices must consider both the individual and compound effects of wildfires. In so doing, this will enable comprehensive insights on the water security paradigm and the value of hydrological services in fire‐affected areas around the globe.
Joint Sparse and Low-Rank Representation for Emotion Recognition

We present an approach to emotion recognition applying a join sparse and low rank decomposition. Previous sparse-based approaches to this problem require of explicitly provided neutral faces to assist the recognition task. Our model trade the neutral face requirement by a sound prior: neutral face can be capture as the low rank component of frame sequence with moderate variation. Satisfactory recognition rates were attained on 7 different emotions.
Absorption of sunlight by dust as inferred from satellite and ground‐based remote sensing

Dust absorption of solar radiation is not well known due to limitations in the accuracy of in situ measurements. Here we report two new independent remote sensing techniques that provide sensitive measurements of dust absorption. One uses satellite spectral measurements, the second ground based sky measurements. Both techniques demonstrate that Saharan dust absorption of solar radiation is several times smaller than the current international standards. For example, at wavelength of 0.64 µm the dust single scattering albedo is reported here as 0.97±0.02 rather than 0.87±0.04 in recent review.
Taxes, Wage Capitalization and the Ability of States to Redistribute Income

Local and state governments attempt to lessen after-tax income inequality via progressive taxation. Migration responses of capital and labor undermine such attempts. Location theory predicts that cross-state migration will continue until the redistributive effects from taxation are fully capitalized into gross wages leaving after-tax wages unchanged. Empirical evidence has not reached a consensus on this issue. At one extreme, Feldstein and Wrobel (1998) report evidence of full tax capitalization for US states. At the other extreme, Leigh (2008) reports very little to no wage capitalization. We revisit this question by creating a pseudo panel from CPS data spanning years 1997 to 2015. Our “best” estimate is that pre-tax wages adjust in response to redistributive state and local taxes, negating roughly 50 percent of effect compared to counterfactual with no behavioral responses.
Discovery of a precessing jet nozzle in BL Lacertae

We present the results of a multiwavelength campaign during which BL Lac was observed at 17 regular epochs from 1998.23 to 2001.28. We used the Very Long Baseline Array (VLBA) in an observing mode sensitive to linear polarization at wavelength 7 mm with a resolution of the order of 0.2 mas. For the first time such observations were complemented by near-simultaneous polarization-sensitive James Clerk Maxwell Telescope (JCMT) observations at a wavelength close to 1 mm. Optical polarimetry was also obtained for the final year of observations. The VLBA images reveal a remarkable oscillating ‘nozzle’ structure with a period of ∼2 yr. The orientation of the nozzle tracks the polarization position angle measured at the JCMT, in which we detect a very similar period. We argue that these results require the same jet direction at the small scale probed by the 1-mm emission as at the larger scale probed by the 7-mm emission; there is no evidence to suggest wiggling of the jet between these scales. The picture that emerges is of a straight but precessing jet where the components form a straight line near the core, but form an apparently curved locus at larger separations where components were ejected in different directions. Two further lines of evidence support this view. First, tracing the evolution of bright components showed straight paths and ejection angles consistent with the nozzle direction at the ejection time. Secondly, a simple model of a precessing nozzle was used to predict the inner jet structure. At most epochs the agreement between the model and data was good. On angular scales >2 mas from the core a transition occurs and most components bend to follow the usual southeasterly direction on deca-milliarcsecond scales. This precession is clearly analogous to that found in the galactic jet source SS 433 albeit with a higher jet speed and a smaller precession cone opening angle. The precession observed in SS 433 is believed to be caused by the interaction of a companion star with the accretion disc around the compact object. This suggests the possibility that the black hole from which the jet from BL Lac emerges is part of a binary system.
On isoparametric elements

Optimal order error estimates in H, for the Q1 isoparametric interpolation, were obtained in [2] for a very general class of degenerate convex quadrilateral elements. In this work we show that the same conlusions are valid in W 1,p for 1 ≤ p < 3 and we give a counterexample for the case p ≥ 3, showing that the result can not be generalized for more regular functions. Despite this fact, we show that optimal order error estimates are valid for any p ≥ 1, keeping the interior angles of the element bounded away from 0 and π, independently of the aspect ratio. We also show that the restriction on the maximum angle is sharp for p ≥ 3.
Induced Myogenesis in Long-Term Permanent Denervation: Perspective Role in Functional Electrical Stimulation of Denervated Legs in Humans

Long-term permanent denervation (LT-PD) induces severe atrophy of skeletal muscle accompanied by apoptotic loss of myonuclei. Morphologic characteristics of the long-term denervated muscle suggest that the original fibers are lost and those seen are the results of repeated cycles of cell death and regeneration. Myoblasts and myotubes express peculiar myosins. Light and heavy chains of embryonic myosin are sensitive indicators of myogenic events in adult muscles. Electrical stimulation of permanent denervated muscle increases the mean size of the myofibers, maintains the sarcomeres and possibly prevents secondary degeneration and apoptosis/necrosis. Mechanisms underlying the recruitment of satellite cells for regenerative or hypertrophic processes have not been established, but cytokine interactions among macrophages and satellite cells seem to be essential. Here we show that long-term denervated muscles increase in size and change their myosin content after full regeneration is induced by bupivacaine treatment. After transient expression of embryonic myosin, fast myosins prevail in all the experimental muscles. In spite of a severe atrophy (around 90%), ten days after injury the regenerated muscles have twice the area at the muscle belly of the respective long-term denervated muscles. Since satellite cells activity is required for extreme hypertrophy of overloaded adult muscles or eutrophy after severe atrophy in recovering muscles, positive regulation of activation, division and fusion of myoblasts could be an important tool to understand limits of recovery of neurogenic muscle myopathies by functional electrical stimulation (FES). Pilot studies in humans show that standing up with denervated muscles using functional electrical stimulation is a reality in permanent complete denervation.
Modification of single-walled carbon nanotube electrodes by layer-by-layer assembly for electrochromic devices

We have studied the morphological properties and electrochromic (EC) performance of polythiophene multilayer films on single wall carbon nanotube (SWCNT) conductive electrodes. The morphology for different numbers of layer-by-layer (LbL) bilayer on the SWCNT electrode has been characterized with atomic force microscopy and scanning electron microscope, and it was found that the LbL multilayers significantly decrease the surface roughness of the nanoporous nanotube films. The controlled surface roughness of transparent nanotube electrodes could be beneficial for their device applications. We have also fabricated EC devices with LbL films of poly[2-(3-thienyl) ethoxy-4-butylsulfonate∕poly(allylamine hydrochloride) on SWCNT electrodes, which not only have high EC contrast but also sustain higher applied voltage without showing any degradation for more than 20000cycles, which is not possible in the case of indium tin oxide electrodes. Cyclic voltammetry of the LbL films formed on SWCNT shows higher current at.
Survey on relational database watermarking techniques

Digital watermarking has been in multimedia data use over the past years. Recently it has become applicable in relational database system not only to secure copyright ownership but also to ensure data contents integrity. Further, it is used in locating tampered and modified places. However, the watermarkingrelational database has its own requirements, challenges, attacks and limitations. This paper, surveys recent database watermarking techniques focusing on the importance of watermarking relational database, the difference between watermarking relational database and multimedia objects, the issues in watermarking relational database, type of attacks on watermarked database, classifications, distortion introduced and the embedded information. The comparative study shows that watermarking relational database can be an effective tool for copyright protection, tampered detection, and hacker tracing while maintaining the integrity of data contents. In addition, this study explores the current issues in watermarking relational database as well as the significant differences between watermarking multimedia data and relational database contents. Finally, it provides a classification of database watermarking techniques according to the way of selecting the candidate key attributes and tuples, distortion introduced and decoding methods used.
Local symmetries and perfect transmission in aperiodic photonic multilayers

We develop a classification of perfectly transmitting resonances occuring in effectively onedimensional optical media which are decomposable into locally reflection symmetric parts. The local symmetries of the medium are shown to yield piecewise translation-invariant quantities, which are used to distinguish resonances with arbitrary field profile from resonances following the medium symmetries. Focusing on light scattering in aperiodic multilayer structures, we demonstrate this classification for representative setups, providing insight into the origin of perfect transmission. We further show how local symmetries can be utilized for the design of optical devices with perfect transmission at prescribed energies. Providing a link between resonant scattering and local symmetries of the underlying medium, the proposed approach may contribute to the understanding of optical response in complex systems.
Multi View Learning Through Different Levels of Abstraction Extracted by Deep Neural Networks

The present work focuses on combining two novel approaches that are becoming more and more important nowa- days, namely neural networks (NN) and multi-view learning. Thanks to the contribution of Geoffrey Hinton, neural networks, in particular deep learning approaches, became increasingly important to the point of being a key part in various systems for different disciplines. For instance, the convolutional neural network (CNN) is the best performing architecture for visual recognition tasks. On the other hand, nowadays, we have different sources to gather data and information for a tasks of our interest. For example, on a website we can have both images and texts that describe the same event, or various newspapers can refer to the same story so we will have different points of view. The goal of multi view learning (MVL) is to increase the performance and improve the results by exploiting the agreement and complementary information between different sources. However, even if we have large datasets, sometimes it is too expensive to collect data from different sources or simply, we do not have them. It is possible that there is not enough information or there is access only to one view. To avoid this problem, different techniques were developed in order to extract multiple views from one single view. This research combines NN with MVL techniques based on the following intuition. Usually, in a deep neural network (DNN) we use only the ”features” of the last layer to make a prediction ignoring all the features that we can extract from the previous hidden layers. The underlying idea of this thesis is to treat each layer as a different view of the original object and combine them to improve the performance of the classic DNN. For the best of my knowledge, this is the first attempt in the literature and different possibilities of such approach are explored in this work.
IN A DISCRETE TARGET PROPAGATION SETTING

Learning deep neural networks with hard-threshold activation has recently become an important problem due to the proliferation of resource-constrained computing devices. In order to circumvent the inability to train with backpropagation in the present of hard-threshold activations, Friesen & Domingos (2018) introduced a discrete target propagation framework for training hard-threshold networks in a layer-by-layer fashion. Rather than using a gradient-based target heuristic, we explore the use of search methods for solving the target setting problem. Building on both traditional combinatorial optimization algorithms and gradient-based techniques, we develop a novel search algorithm Guided Random Local Search (GRLS). We demonstrate the effectiveness of our algorithm in training small networks on several datasets and evaluate our target-setting algorithm compared to simpler search methods and gradient-based techniques. Our results indicate that combinatorial optimization is a viable method for training hard-threshold networks that may have the potential to eventually surpass gradient-based methods in many settings.
Genetic diversity of shiga toxin-producing prophages among Escherichia coli isolated from cattle in multiple herds

GENETIC DIVERSITY OF SHIGA TOXIN-PRODUCING PROPHAGES AMONG ESCHERICHIA COLI ISOLATED FROM CATTLE IN MULTIPLE HERDS By Yi-An Yang Shiga toxin-producing Escherichia coli (STEC) arise after the insertion of a group of bacteriophages encoding the Stx gene. Shiga toxin-producing bacteriophages (Stx phages), notably, are heterogeneous with mosaic genomic structures. However, little is known of the genetic diversity of Stx phages across STEC populations. Here, we examined the diversity of Stx prophages among E. coli isolated from 52 animals from 4 Michigan cattle herds between 2011 and 2012 using a novel long range PCR-based restriction fragment length polymorphism (RFLP) method that targets a distinct region (ciii-stx, 10-17 kb) within three Stx phage subtypes. Sixteen Stx phage types (PT) were identified; 10 of the 16 Stx PT encoded Stx1, while three encoded Stx2a and another three encoded Stx2c. Interestingly, the same Stx PT was frequently identified within each cattle herd; despite the STEC genotypes are diverse in the herd. These data suggest that transmission of both STEC and Stx phages occurs regularly and provides insight into the diversity and dynamics of specific Stx phages within and across herds. Identifying the distribution of Stx PT present in the cattle reservoir would enable the linkage to STEC epidemiology study, and to further determine whether specific Stx PT contribute to higher virulence in STEC infection.
A Method to Improve the Accuracy of K-Nearest Neighbor Algorithm

K-Nearest Neighbor Algorithm (Knn) is one of the best and most widely used classification algorithms with a variety of applications. One of the most important challenges to the application of the algorithm is the same impact of all characteristics in doing the classification, while some of the characteristics are less important for classification; this may deviate the process of classification and reduce the accuracy of the Knn algorithm. Using a new method in this study, a certain weight is allocated to various features based on their importance, so that the same effect of all features is avoided in doing the classification and deviation of classification process, thereby increasing the accuracy of Knn algorithm classification. The comparison of the results of the proposed algorithm implementation and five other classification algorithms on 10 datasets selected from UCI repository indicated the considerable improvement of the classification by the algorithm.
of Geophysical Research : Atmospheres Vertical Structure and Radiative Forcing of Monsoon Clouds Over Kanpur During the 2016 INCOMPASS Field Campaign

An overview of cloud vertical structure (CVS) and cloud radiative forcing (CRF) during Indian summer monsoon is obtained over Kanpur, through observations made during the Interaction of Convective Organisation and Monsoon Precipitation, Atmosphere, Surface and Sea field campaign of 2016. Associations of CVS parameters with CRF at surface and top of atmosphere (TOA) are also investigated. One hundred thirty-seven radiosondes were launched at Indian Institute of Technology Kanpur, between 5 and 28 July 2016. CVS is determined using an algorithm that identifies cloud layers from vertical profiles of relative humidity, with altitude-dependent relative humidity thresholds. CVS is analyzed by separating the campaign period on the basis of presence and absence of depressions/low-pressure systems. Compared to nondepression periods, low-pressure events showed significant difference in all CVS and CRF parameters except cloud top height. CVS was multilayered in ∼75% launches, with deep, mixed-phase clouds being present in ∼70% launches. CRF was calculated from clear-sky measurements and TOA observations from Clouds and the Earth’s Radiant Energy System satellite retrievals, and surface measurements. A net cooling effect was found overall, with instantaneous shortwave CRF (mean values of −95.92 and −101.89 W/m2 at surface and TOA, respectively) dominating longwave cloud radiative forcing (LWCRF) (mean values of 15.33 and 66.55 W/m2 at surface and TOA, respectively). Results suggest that shortwave CRF depends on total depth of cloud layers and is independent of cloud altitude, whereas LWCRF depends on both depth and vertical location of cloud layers, with base and top heights regulating LWCRF at surface and TOA, respectively. Plain Language Summary Cloud vertical structure (CVS) and cloud radiative forcing (CRF) are important parameters in our understanding of clouds and climate prediction. CVS includes details about number of cloud layers present in the atmosphere and the base and top height of these layers. CRF is the extent of change caused in Earth’s energy balance due to the presence of clouds. This study is the first of its kind from India, which provides information regarding CVS during the Indian monsoon, by using data from weather balloons. The results of the study show that most of the time, there are multiple layers of clouds present and that most are deep clouds. Indian monsoons are characterized by large-scale events called depressions, when the pressure of air over land drops. Periods with such low-pressure events showed a significant difference in all CVS details except cloud top height, when compared to nondepression periods. CRF values were calculated, and an overview of CRF during Indian summer monsoon is presented. It is also observed that the parameters of CVS had a range of significant influences on CRF. The results of this study can be used as information to be provided to models, which will help in the understanding of monsoons.
Construction materials in estuaries: reduction in the epibiotic community on chromated copper arsenate (CCA) treated wood

Boards of CCA-treated wood, control (untreated) wood, and recycled plastic 'lumber' were placed into an estuary (Fort Pond, Southampton, NY, USA) in early May and examined monthly for abundance of species. One set of boards was left in the water continuously for 5 mo. Another set was renewed each month; after counting, organisms were removed and analyzed for dry weight and metal concentrations. A further set, placed in Accabonac Harbor, East Hampton, NY, in early July, compared CCA-treated wood that had not been impregnated well (green did not extend to inner portions), wood that had been well impregnated, and control wood. These boards were left in the water for 2 mo, and examined every 2 wk. Treated wood had a reduced number of species, lower diversity index, fewer barnacles (Balanus eburneus) and reduced growth of the barnacles that settled, fewer Membranipora and reduced growth of Membranipora colonies, fewer macroalgae, and fewer amphipods, compared to control wood and plastic The bryozoan Bugula turnta, however, was found at great density on the treated wood Biomass was lower on treated wood compared to control wood and plastic, and accumulations of Cu, Cr, and As were found Barnacles in~tially avoided settling on plastic, but after 1 mo exceeded those on control wood The communities in the 2 estuaries differed: e.g. at Accabonac species number was lower, there was less algae, bryozoans were absent, and barnacles were more dominant.
Criticality and phase separation in a two-dimensional binary colloidal fluid induced by the solvent critical behavior

We present an experimental and theoretical study of the phase behavior of a binary mixture of colloids with opposite adsorption preferences in a critical solvent. As a result of the attractive and repulsive critical Casimir forces, the critical fluctuations of the solvent lead to a further critical point in the colloidal system, i.e. to a critical colloidal-liquid–colloidal-liquid demixing phase transition which is controlled by the solvent temperature. Our experimental findings are in good agreement with calculations based on a simple approximation for the free energy of the system.
Core-hole effects on theoretical electron-energy-loss near-edge structure and near edge x-ray absorption fine structure of MgO

First-principles molecular orbital calculations using model clusters are made in order to reproduce and interpret experimental electron-energy-loss near-edge structure and near-edge x-ray absorption fine structure of MgO at Mg K, ${L}_{2,3}$ and O K edges. Ground-state calculations using a model cluster composed of 125 atoms and by a band-structure method are in good agreement, but they do not reproduce the experimental spectra satisfactory. They are well reproduced only by the cluster calculations for the Slater transition state, where a half-electron is removed from a core orbital and placed into the lowest unoccupied molecular orbital. The core-hole effect is therefore essential for theoretical reproduction of the spectral shapes. A large supercell is required to reproduce the experimental spectra when one uses a band-structure method. The origin of peaks appearing in the experimental spectra is interpreted in terms of orbital interactions using overlap-population diagrams. Some features of the spectra at different edges are pointed out to have common origins. Experimental spectra are aligned accordingly. The transition energies and qualitative features of experimental spectra are found to be reproduced even using a smaller cluster composed of 27 atoms, although some of fine structure is missing.