dataesr/scientific-paragraphs-categorization huggingface dataset:
MNPR empowers our stylization pipelines in watercolor, oil and charcoal, but can easily be extended by developers due to its cross-stylistic and open-source nature. To summarize, we make the following contributions: (1) an art-directed approach towards covering the interaction spectrum in expressive NPR of 3D computer graphics (Section 3. 1); (2) generalized control semantics to guide cross-stylistic art-direction (Section 3. 2), which is exemplified for three styles; (3) the implementation insights and source code of MNPR (Section 3. 3) as part of its public release; (4) a user study with experienced artists and engineers to evaluate the usefulness of each level of control (Section 4). The remainder of this paper consists of related work (Section 2), the proposed levels of control and generalized control semantics with implementation details (Section 3), evaluations (Section 4), results (Section 5), and drawn conclusions with potential future work (Section 6).
Tools for different levels of control. Within MNPR, broken down in the schematic of Figure  11 , the 3D scene interaction is entirely managed by Maya. However, enabling the different levels of control for our stylization pipeline required us to develop multiple custom tools, which were developed using Python and PySide2. Proxy control. In 3D space, we handle the creation of proxy controls from any mesh object, by first disabling the casting and receiving of shadows so that these are not present in the shadow map calculation. We then assign a custom proxy material, which will only render the proxy object to the control maps, once the application data is rasterized. A proxy material preset, loaded from our custom material presets tool, automatically performs these changes, so that the user is only concerned with the art-direction of the "invisible" object.
Stylization pipeline. Once all the data is rendered from the 3D scene, a series of image processing operations, driven by shaders (HLSL or GLSL), are defined and run. These operations conform to the stylization pipeline, which is further driven by the global control parameters and any other external data (e. g. , substrate). While the exact implementation of each stylization pipeline is under constant evolution and out of the scope of this paper, we encourage the interested reader to check the code available at the project's Git repository (see Section 6). The stylization pipeline, powered by our custom plugin, uses the Maya C++ API and takes advantage of the Viewport 2. 0 API. However, we extended some API classes and methods to design and abstract a modular framework. This facilitates the creation of stylization pipelines for people who are not used to working with the Maya API, enabling a simple adaptation of art-directed NPR stylization pipelines in three steps: • define and create attributes for global effect parameters; • outline the custom stylization pipeline; • define NoiseFX and PaintFX controls (Python).
Lessons learned. While working with Maya has propelled the set of features and the pool of artists that we can access, developing for this closed-source software has its caveats. We would like to share a brief list of lessons learned, for any developers or researchers looking into using and expanding MNPR. • Documentation, example code and user-base of the Viewport 2. 0 API is limited. • Maya will not return certain shader errors when working with GLSL shaders. This led us to develop in HLSL first and then port to GLSL afterwards. • Keep hardware limitations in mind when rendering to multiple render targets (8 max). • Packing control parameters into 32 bit floating point targets will not support a simple accumulation of parameters from different levels of control. • Maya's internal texture painting tool will not work on custom materials, which drove us to map to vertex colors instead.
A particular challenge was porting over the procedural impasto marks in a coherent way under animation. In this pursuit, we extended MNPR to include a way to extract the motion of each vertex by calculating the deltas with their previous position (after deformations) and made use of coherent noise  [Kass and Pesare 2011]  to advect the procedural noise along the object's motion. While the results are promising, calculating per vertex motion of fully deformable objects is slow and only enabled when real-time interaction is not required. The charcoal stylization took understandably longer to develop, as it was not a full-time effort, there was no prior shader code and it involved a significant learning journey into image processing and shader development from the developer. Nonetheless, our framework managed to abstract the development process of a graphics engine, allowing to concentrate on the image processing operations and the interplay between them.
MNPR successfully supported both development efforts through the example code/documentation to embed the art-directed parameters within the image-processing operations, following the control scheme at Table  1. Once these parameters were incorporated, the expressive control tools were managed by our framework by simply defining the code to manipulate them. Both of these additional stylization pipelines are featured in our results, showcasing the successful adaptation of styles into MNPR, as well as the cross-stylistic support of art-directed effects. In general, the feedback from these development efforts was quite positive and allowed us to iterate on our framework to improve upon it and extend its functionality.
Artists' evaluation We aimed to grant artists the widest range of control in objectspace and, thereby, evaluate their preferences and uses at each level of control. For this purpose, we conducted a user study involving experienced artists and engineers to evaluate the usefulness of each control and gather feedback on how to improve them. A total of 65 users registered their interest to take part in our study and received MNPR with a watercolor stylization pipeline. To bring everyone to the same level of proficiency using the framework  and its tools, we included tutorials for each level of control and how to use them effectively. After a period of two weeks, 20 participants answered an online questionnaire that helped us gather their usage data and analyze their feedback. The individual responses are available within the supplementary materials of this paper, of which we have consolidated the following.
Overall, the participants tended to agree that they achieved their stylistic goal using our framework (I). We also asked the participants if they previously used other NPR solutions, for their current workflow; and if they would have achieved their desired stylization faster using our framework. While they were mostly using offline workflows-which involve several stages with different software-their answers were mostly neutral, but with a tendency towards agreeing. We believe these responses were positive, considering that stylistic goals may differ widely between users and that they were constrained to only one stylization pipeline within our framework, with limited learning time. We expect this to change when more stylization pipelines are developed and MNPR matures in the public domain.
Finally, we have shared some insight towards our implementation in Autodesk ® Maya ® and are hereby releasing the source code to augment this contribution and motivate adoption in the Expressive community-as a practical answer to Isenberg's 2016 call towards designing the interaction with, or for algorithmic support. The source code can be found at our institutional data repository  [Montesdeoca 2018 ] and at the project's Git repository (http://github. com/semontesdeoca/MNPR). With this work, we hope to make Expressive research more accessible for the target users, validating our methods and inspiring new contributions from the research community. Limitations and future work. While MNPR provides a useful starting point towards bringing NPR research to the hands of artists, it still remains to be tested and refined with other styles and in production.
ACKNOWLEDGMENTS Special thanks go to  Yee Xin Chiew  and all the participants in our user study for testing MNPR, sharing their feedback and enduring the hiccups during its development process. We also thank  Hans-Martin Rall  and  Jürgen Döllner  for their support during this endeavor. Our gratitude is also with our colleagues for their comments and suggestions, together with the anonymous reviewers for their constructive feedback. We would like to thank the  Multi-plAtform Game and Innovation Centre (MAGIC)  and the  Hasso Plattner Institute for Digital Engineering (HPI)  for supporting this international collaboration. This research is supported by the  Interdisciplinary Graduate School (IGS)  and the  School of Computer.
In addition, following  (Yuan et al. , 2016)  torsional restraints on the c 1 of Leu277 at position 9 0 were introduced to keep these hydrophobic side chains away from the pore lumen. The initial equilibration (10 ns) was followed by a second 50-ns equilibration with no symmetry restraint and 300 ns of unbiased MD. Since there is a large separation between the M2 helices in the wide-open state, this equilibration protocol allows for a gentle relaxation of the cryo-EM structure in explicit solvent/membrane MD. The results in Figure  2A  indicate that the relaxation of the wide-open structure is indeed slower (black line), with the pore visiting a number of configurations before converging to a state that is nonpermeable to chloride (orange line). However, at $200 ns the simulation captured a spontaneous transition to a wider openpore configuration (blue line), which is stable for >100 ns and whose radius at the position À2 0 is comparable with the one measured in the semi-open cryo-EM structure (PDB: 3JAF).
STAR+METHODS Detailed methods are provided in the online version of this paper and include the following: missing. Initial coordinates for GLY were modeled by manual docking to the orthosteric site using the binding mode of L-glutamate in the X-ray structure of GluCl active (PDB:3RIF) as a template. After several ns of MD relaxation, a binding mode similar to the one suggested in  (Yu et al. , 2014)  and  (Huang et al. , 2017a)  with a water molecule mediating the interaction with the protein was stabilized. d KEY RESOURCE.
12 (Phillips et al. , 2005) ; see  (Calimet et al. , 2013)  for details. In the initial simulations, the system was equilibrated at 300K and 1 atm for 2 ns while removing positional restraints on the backbone atoms, followed by 50 and 350 ns production for the wide-open and the semi-open state, respectively. Additional simulations of the wide-open state were carried out by introducing symmetry restraints on the pentameric organization with force constants of 0. 25 and 1. 0 kcal. mol À1 A ˚À2 for the ECD and TMD, respectively, using the symmetryRestraints module in NAMD and torsional restraints on the c 1 angle of Leu277 (at position 9 0 ) with half-harmonic boundary potentials at 280 and 300 degrees (force constant 0. 1 kcal. mol À1 deg À2 ) to keep the hydrophobic chain of Leu277 away from the pore lumen.
Torsional restraints were implemented using the colvars module in NAMD  (Fiorin et al. , 2013). In these runs, the equilibration was elongated from 2 to 10 ns, followed by 50 ns of biased MD with torsional restraints on Leu277 (position 9 0 ) before 300 ns of unbiased production. Production runs were executed on Haswell CPUs (E5-2690 V3) at a rate of $25ns/day using 504 CPU-cores. For a total of $1. 2ms of cumulated simulations using $600,000 CPU-hours.
The electric field was introduced using the External Electric Field module in NAMD. The value of E Z was set to generate a membrane potential of +150 or +250 mV. Of note, the semi-open structure is not permeable under physiological voltages but increasing the voltage to the extreme value of +1V allowed us to observe few permeation events. Estimates of the anionic and cationic currents per simulation were obtained by counting the number of anions or cations permeating the pore per nanosecond using the FLUX module in Wordom  (Seeber et al. , 2007 (Seeber et al. , , 2011)). The total current is computed from the summation of permeation events within triplicate simulations for each setup (structure/restrains/voltage). Currents are given ± the error s assuming a Poisson distribution of the permeation events such that s = I ffiffiffi ffi N p with N the number of events  (Sotomayor et al.
HOLE Analysis The configuration of the ion pore in anionic pLGICs available from X-ray, cryo-EM, and MD simulations was compared using the program HOLE  (Smart et al. , 1996). The following structures were analyzed: (i. ) the glycine receptor a1 in complex with strychnine (PDB:3JAD) or glycine with (PDB:3JAF) and without (PDB:3JAE) ivermectin; (ii. ) the glycine receptor a3 in complex with strychnine (PDB:5CFB) or glycine and the allosteric potentiator AM3607 with (PDB:5VDH) and without (PDB:5TIO) ivermectin; (iii. ) the glutamate-gated chloride channel GluCl in complex with glutamate and ivermectin (PDB:3RIF) or with ivermectin only (PDB:3RHW); and (iv. ) the GABA A receptor in complex with the agonist benzamidine (PDB:4COF). All these structures were aligned using PyMol  (Schro ¨dinger, 2015)  and their hydrogens generated by the same software.
The HOLE profiles were produced using an efficient implementation in the program Wordom  (Seeber et al. , 2007 (Seeber et al. , , 2011) )  with incremental steps of 0. 1 A ˚. Average HOLE profiles per cluster were computed with Numpy  (Jones et al. , 2001)  in a Python script. The mean value was calculated for each value of Z ± the standard deviation.
ACKNOWLEDGMENTS This project has received funding from the  European Union 's  Horizon 2020 Research and Innovation Program  under grant agreement no. 720270  ( HBP SGA1 ). The work was granted access to the  HPC resources of CCRT/CINES  under the allocation  2016-[076644 ] made by  GENCI  ( Grand Equipement National de Calcul Intensif ). Research leading to these results has in parts been carried out on the  Human Brain Project PCP Pilot Systems at the Juelich Supercomputing Center , which received co-funding from the  European Union  (grant agreement no. 604102 ). Financial support from the  International Center for Frontier Research in Chemistry (icFRC)  and the  Agence Nationale de la Recherche  through the  LabEx  project  Chemistry of Complex Systems  ( CSC-MCE-13 ) to M. C. is gratefully acknowledged.
METHOD DETAILS Preparation of Structures Initial coordinates were extracted from the cryo-EM reconstructions of the Zebrafish GlyR a1 in the wide-open (PDB:3JAE) and the semi-open (PDB:3JAF) states. The M3-M4 loop, which was missing in the wide-open structure, was reconstructed by the program MODELLER  (Sali and Blundell, 1993)  using the semi-open structure as template. Complete models including hydrogens were built using the program CHARMM with the CHARMM27 force field  (Mackerell, 2004)  and the CHARMM36 lipid parameter set  (Klauda et al. , 2010)  to model the energetics. The protonation state of the ionizable residues was determined by pK a calculations based on continuum electrostatics and the multi-site titration approach as described previously  (Calimet et al. , 2013). For the wide-open structure, the following residues were predicted in the non-standard (deprotonated) form at pH 7: D100, D113, D164, D339, K297 and K362.
Materials and Methods The literature was first searched using the scientific databases of Scopus and Web of Science. For MLU, we used as search tags "multifunctional land use" and "multifunctional landscapes" combined with urban/city/cities. This resulted in a total of 161 papers. For CUM, a search for "circular urban metabolism" only resulted in two papers. Even though the concept is widely used by practitioners and institutional bodies (see for instance  [18] [19] [20] [21] [22] ) when talking about best practices in sustainable urban development, scholars prefer using more specific concepts, such as sustainable implant, zero-waste, self-reliant city, urban harvest, cyclic design, city as ecosystem, circular urban systems, or territorial ecology. These reflect the specific aims of the paper which may be to close cycles locally, harvest local resources, decrease the dependency on an external resource, or minimize waste.
, 2010; Jiang et al. , 2012; Xu et al. , 2012; Kreuze, 2014; Rajeswaran et al. , 2014a; Hong et al. , 2015; Wu J. et al. , 2015; Xu and Zhou, 2017; Yang et al. , 2017; Jimenez et al. , 2018; Lan et al. , 2018;  see Supplementary Table  S1  and Supplementary List S1), the failure to identify RTSV-specific siRNAs can be explained by low titer of the virus. In this and other similar cases, deeper sequencing of small RNA-ome could have helped to uncover viral siRNAs. Indeed, a recent systematic study has established that, under low sequencing depths, most bioinformatic pipelines that use de novo assembly of small RNAs fail to identify lowtiter persistent viruses in apple and grapevine, while those viruses can be readily identified at higher sequencing depths  (Massart et al. , 2018). In another study that compared small RNA-seq with long RNA-seq, a member of the genus Cytorhabdovirus (Rhabdoviridae) could be identified by de novo assembly only in the long RNA dataset, because of low abundance of the viral reads in the small RNA dataset  (Pecman et al.
, 2014). A recently developed tool VirusDetect  (Zheng et al. , 2017a)  implements for small RNA-seq datasets both filtering through a host genome and mapping onto a database of viral reference genomes to enrich for viral reads before assembly. The latter approach may not be applicable for identification of novel viruses with low homology to any known virus in the reference database. Other issues concerning reliability, reproducibility and sensitivity of virus diagnostics by small RNA sequencing and bioinformatics analysis have been recently investigated and discussed by  Massart et al. (2018). Importantly, the sensitivity of small RNA-seq for detection of potyviruses (Potyviridae) in N. tabacum is reportedly 10 times higher than that of quantitative RT-PCR  (Santala and Valkonen, 2018). Likewise, sweet potato feathery mottle virus (Potyvirus, Potyviridae) with extremely low titer (below immune detection) and symptomless in sweet potato could be assembled by sequencing viral small RNAs that covered the complete reference genome at an average 470 reads per nucleotide  (Kreuze et al.
, 2009). Notably, Potyviridae is among those viral families for which many species from various hosts have been identified by small RNA-seq (see Supplementary Table  S1  and references therein). Concerning identification of novel viruses, analysis of small RNA contigs using BlastN and BlastX is recommended  (Massart et al. , 2018). In this case, any bioinformatics tricks making viral contigs longer, such as those described above and additional ones in  Massart et al. (2018) , should help to identify a virus or viruslike agent with very low homology to known viral sequences available in the NCBI GenBank or other databases. A notable limitation of the small RNA-omics approach is its inability to fully and reliably reconstruct from mixed infections genome sequences of two (or more) strains or genetic variants of the same virus when they share high sequence identity.
Furthermore, restrictions (on the procfs) have already been implemented in Android O  [14] ,  [25]  and are likely to be upstreamed to the main Linux kernel. Consequently, attackers are left with side channels to obtain keystroke timings. Especially microarchitectural attacks allow monitoring memory accesses with a granularity of single cache lines, and thus also allow recovering keystroke timings with a high accuracy. Keystroke timing attacks are hard to mitigate, compared to side-channel attacks on cryptographic implementations. Indeed, attacks on cryptographic implementations can be mitigated with changes in the algorithms, such as making execution paths independent of secret data. On the contrary, user input travels a long way, from the hardware interrupt through the operating system and shared libraries up to the user space application.
A. Linux Interrupt Handling Interrupt handling is one of the low-level tasks of an operating system and thus highly architecture and machine dependent. This section covers the general design of how interrupts and their handling within the Linux kernel work on both x86 PCs and ARMv7 smartphones. 1) Interrupts on x86 and x86 64: Figure  1  shows a highlevel overview of interrupt handling on a dual-core x86 CPU. Interrupts are handled by the Advanced Programmable Interrupt Controller (APIC)  [22]. The APIC receives interrupts from different sources: locally and externally connected I/O devices, inter-processor interrupts, APIC internal interrupts, performance monitoring interrupts, and thermal sensor interrupts. On multi-core systems, every CPU core has a local APIC (LAPIC) to handle interrupts.
The attacker flushes a cache line, lets the victim perform an operation, and then reloads and times the access to the cache line. A low timing indicates that the victim accessed the cache line. While very accurate, it can only be performed on shared memory, i. e. , shared libraries or binary code. Flush+Reload can neither be performed on dynamic buffers in a user program nor on code or data in the kernel. Gruss et al. [17]  presented cache template attacks as a technique based on Flush+Reload to automatically find and exploit cache-based leakage in programs. Prime+Probe. Prime+Probe  [31] ,  [41] ,  [42]  is a technique that allows an attacker to monitor a victim's cache accesses at a granularity of a cache set. The attacker primes a cache set, i. e. , fills the cache set with its own cache lines.
It then lets the victim perform an operation. Finally, it probes its own cache lines i. e. , measures the access time to them. This technique does not require any shared memory between the attacker and the victim, but it is difficult due to the mapping between physical addresses and cache sets and slices. As Prime+Probe only relies on measuring the latency of memory accesses, it can be performed on any part of the software stack. It is possible to perform Prime+Probe on dynamically generated data  [30]  as well as kernel memory  [41]. Preventing Prime+Probe attacks is difficult due to the huge attack surface and the fact that Prime+Probe uses only innocuous operations such as memory accesses on legitimately allocated memory, as well as timing measurements. DRAMA. Besides the cache, the DRAM design also introduces side channels  [43] , i.
Diao et al. [10]  demonstrated high-precision keystroke timing attacks based on /proc/interrupts. However, these attacks are not possible anymore in Android O  [14] ,  [25] , as access to these resources has been restricted. Vila et al. [53]  recovered keystroke timings from timing differences caused by the event queue in the Chrome browser. Based on the native attack we present in Section III-B, Lipp et al. [29]  implemented the same attack in JavaScript. They recovered keystroke timings and identified user-typed URLs. They also showed that users can be distinguished based on this attack. Gruss et al. [17]  demonstrated that Flush+Reload allows distinguishing specific keys or groups of keys based on keydependent data accesses in shared libraries. Ristenpart et al. [46]  demonstrated a keystroke timing attack using Prime+ Probe with a false-negative rate of 5 % while measuring 0.