Miracle-dz/UniFAR-FTUs huggingface dataset:
Constitutive activity of ionotropic glutamate receptors via hydrophobic substitutions in the ligand-binding domain

Neurotransmitter ligands electrically excite neurons by activating ionotropic glutamate receptor (iGluR) ion channels. Knowledge of the iGluR amino acid residues that dominate ligand-induced activation would enable the prediction of function from sequence. We therefore explored the molecular determinants of activity in rat NMDA-type iGluRs (NMDA receptors), complex heteromeric iGluRs comprising two glycine-binding GluN1 and two glutamate-binding GluN2 subunits, using amino acid sequence analysis, mutagenesis, and electrophysiology. We find that a broadly conserved aspartate residue controls both ligand potency and channel activity, to the extent that certain substitutions at this position bypass the need for ligand-binding in GluN1 subunits, generating NMDA receptors activated solely by glutamate. Furthermore, we identify a homomeric iGluR from the placozoan Trichoplax adhaerens that has utilized native mutations of this crucial residue to evolve into a leak channel that is inhibited by neurotransmitter binding, pointing to a dominant role of this residue throughout the iGluR superfamily.
Distributed Decisions: The Example of Child Access to Primary Health Care

Confronted with uncertainty, who within social networks makes decisions and how? This article suggests a framework for answering these questions. It suggests that decision-making is distributed over time within and among network members. These ‘distributed decisions’ originate in, and develop from, initial decisions, termed ‘proto-decisions’. The process of development of distributed decisions is not merely a social activity. It involves the development over time of mental events by one or more persons through interaction. This framework is illustrated through specific reference to the example of who decides about child access to primary health care, and how. At the same time, it elaborates existing models of health service use. It questions the focus of the Social Organisation Strategy framework on one agent deciding about service utilization (albeit within limits set by the structure and content of social network ties) and on social relationships as the dominant influence on decision-making in social life.
OCTREE 3D VISUALIZATION MAPPING BASED ON CAMERA INFORMATION

Today, computer science and robotics have been highly developed. Simultaneous Localization and Mapping (SLAM) is widely used in mobile robot navigation, game design, and autonomous vehicles. It can be said that in the future, most scenarios where mobile robots are applied will require localization and mapping. Among them, the construction of three-dimensional(3D) maps is particularly important for environment visualization which is the focus of this research. In this project, the data used for visualization was collected using a vision sensor. The data collected by the vision sensor is processed by ORB-SLAM2 to generate the 3D cloud point maps of the environment. Because, there are a lot of noise in the map points cloud, filters are used to remove the noise. The generated map points are processed by the straight-through filter to cut off the points out of the specific range. Statistical filters are then used to remove sparse outlier noise. Thereafter, in order to improve the calculation efficiency and retain the necessary terrain details, a voxel filter is used for downsampling. In order to improve the composition effect, it is necessary to appropriately increase the sampling amount to increase surface smoothness. Finally, the processed map points are visualized using Octomap. The implementation utilizes the services provided by the Robot Operating System (ROS). The powerful Rviz software on the ROS platform is used. The processed map points as cloud data are published in ROS and visualized using Octomap. Simulation results confirm that Octomap can show the terrain details well in the 3D visualization of the environment. After the simulations, visualization experiments for two environments of different complexity are performed. The experimental results show that the approach can mitigate the influence of noise on the visualization results to a certain extent. It is shown that for static high-precision point clouds, Octomap provides a good visualization. The simulation and experimental results demonstrate the applicably of the approach to visualize 3D map points for the purpose of autonomous navigation.
Indexing the Trajectories of Moving Objects

Ontologies are set to play a key role in the “Semantic Web”, extending syntactic interoperability to semantic interoperability by providing a source of shared and precisely defined terms. DAML+OIL is an ontology language specifically designed for use on the Web; it exploits existing Web standards (XML and RDF), adding the familiar ontological primitives of object oriented and frame based systems, and the formal rigor of a very expressive description logic. The logical basis of the language means that reasoning services can be provided, both to support ontology design and to make DAML+OIL described Web resources more accessible to automated processes.
The Cascades Framework for Query Optimization.

This paper describes a new extensible query optimization framework that resolves many of the shortcomings of the EXODUS and Volcano optimizer generators. In addition to extensibility, dynamic programming, and memorization based on and extended from the EXODUS and Volcano prototypes, this new optimizer provides (i) manipulation of operator arguments using rules or functions, (ii) operators that are both logical and physical for predicates etc., (iii) schema-specific rules for materialized views, (iv) rules to insert ”enforcers” or ”glue operators,” (v) rule-specific guidance, permitting grouping of rules, (vi) basic facilities that will later permit parallel search, partially ordered cost measures, and dynamic plans, (vii) extensive tracing support, and (viii) a clean interface and implementation making full use of the abstraction mechanisms of C++. We describe and justify our design choices for each of these issues. The optimizer system described here is operational and will serve as the foundation for new query optimizers in Tandem’s NonStop SQL product and in Microsoft’s SQL Server product.
The inverse backscattering for Schrödinger operators for potentials with noncompact support

We consider the inverse backscattering problem for the Schrödinger operator H = −Δ + V on Rn , n ≥ 3, as well as the higher‐order Schrödinger operator ( − Δ)m + V, m = 2,3,…. We show that in some suitable Banach spaces, the map from the potential to the backscattering amplitude is a local diffeomorphism. This kind of problem (for m = 1) was studied by Eskin and Ralston [Comm. Math. Phys., 124(2), 169‐215 (1989)], where they assumed that V∈C0∞ . In this paper, we replace the C0∞ assumption on V with certain decay assumption at infinity.
Improved Character-Based Neural Network for POS Tagging on Morphologically Rich Languages

Since the widespread adoption of deep-learning and related distributed representation, there have been substantial advancements in part-of-speech (POS) tagging for many languages. When training word representations, morphology and shape are typically ignored, as these representations rely primarily on collecting syntactic and semantic aspects of words. However, for tasks like POS tagging, notably in morphologically rich and resource-limited language environments, the intra-word information is essential. In this study, we introduce a deep neural network (DNN) for POS tagging that learns character-level word representations and combines them with general word representations. Using the proposed approach and omitting hand-crafted features, we achieve 90.47%, 80.16%, and 79.32% accuracy on our own dataset for three morphologically rich languages: Uyghur, Uzbek, and Kyrgyz. The experimental results reveal that the presented character-based strategy greatly improves POS tagging performance for several morphologically rich languages (MRL) where character information is significant. Furthermore, when compared to the previously reported state-of-the-art POS tagging results for Turkish on the METU Turkish Treebank dataset, the proposed approach improved on the prior work slightly. As a result, the experimental results indicate that character-based representations outperform word-level representations for MRL performance. Our technique is also robust towards the-out-of-vocabulary issues and performs better on manually edited text.
Detecting Action Attributes using Contextual Constraints 2 . 1 Systematic Overview

In this paper, we are interested in detecting action attributes from sports videos for event understanding and video analysis. Action attribute is a middle layer between low level motion features and high level action classes, which includes various motion patterns of human limbs and bodies and the interaction between human and objects. Successfully detecting action attributes provides a richer video description that facilitates many other important tasks, such action classification, video understanding, automatic video transcript, etc. A naive approach to deal with this challenging problem is to train a classifier for each attribute and then use them to detect attributes in novel videos independently. However, this independence assumption is often too strong, and as we show in our experiments, produces a large number of false positives in practice. We propose a novel approach that incorporates the contextual constraints for activity attribute detection. The temporal contexts within an attribute and the co-occurrence contexts between different attributes are modelled by a factorial conditional random field, which encourages agreement between different time points and attributes. The effectiveness of our methods are clearly illustrated by the experimental evaluations.
MapReduce complements DBMSs since databases are not designed for extract-transform-load

THE MAPREDUCE7 (MR) PARADIGM has been hailed as a revolutionary new platform for large-scale, massively parallel data access.16 Some proponents claim the extreme scalability of MR will relegate relational database management systems (DBMS) to the status of legacy technology. At least one enterprise, Facebook, has implemented a large data warehouse system using MR technology rather than a DBMS.14 Here, we argue that using MR systems to perform tasks that are best suited for DBMSs yields less than satisfactory results,17 concluding that MR is more like an extract-transform-load (ETL) system than a DOI:10.1145/1629175.1629197
Role of 2-dimensional speckle tracking echocardiography in diagnosis of coronary artery stenosis instable angina pectoris patients

Background and methods: In this work, 120 patients suspected of having stable angina pectoris were included. They were presented for evaluation of chest pain and to whom clinical evaluation, echocardiography, nuclear scanning and coronary angiography were done. They were classified into group (A) 40 control patients considered as a control group with normal coronaries, and group (B) 80 patients with significant CAD. â Results: The study showed that regarding the Echo. Parameters, there were statistically significant difference between the 2 groups regarding the A wave, E/A ration, DT, Em and E/EM. Also regarding SLSS and GLS 17 and GLS 12 as well as SLSr, GLSr 17 and GLSr 12. Significant difference was present regarding number of vessels affected in regard to GLS 12, GLSr 12 and GLSr 17. In comparison with the results of MPI, there was a positive correlation between the number of segments affected in MPI and GLS 12 and GLSr 12. A statistically significant correlation was also found between the 17 segments in MPI and SLSS and SLSr parameters. â Conclusion: Myocardial strain by speckle tracking is superior to conventional Echo. Parameters measurements of global and segmental LS using 2DSE and it is a more sensitive tool in the identification of WMA at rest than visual analysis and that support its use to risk stratify atherosclerotic CAD. It may help in identifying which coronary artery is affected.
Scalability and accuracy in a large-scale network emulator

Experimental distributed services are difficult to evaluate due to their scale and the complexity of the Internet. The lack of an accepted evaluation methodology that predicts real behavior is a key obstacle to progress in distributed services research. ModelNet is a network emulation environment for evaluating distributed services across largescale networks. A key research contribution of ModelNet is the development of a number of novel techniques for large-scale network emulation that trade accuracy for scalability.
2.01.90 Navigated Transcranial Magnetic Stimulation

Policy [TOP] Navigated transcranial magnetic stimulation (nTMS) is considered investigational for all purposes, including but not limited to the preoperative evaluation of patients being considered for brain surgery, when localization of eloquent areas of the brain (e.g., controlling verbal or motor function) is an important consideration in surgical planning.
Misleading Generalized Itemset Discovery

Frequent generalized itemset mining is a data mining technique utilized to discover a high-level view of interesting knowledge hidden in the analyzed data. By exploiting a taxonomy, patterns are usually extracted at any level of abstraction. However, some misleading high-level patterns could be included in the mined set. This paper proposes a novel generalized itemset type, namely theMisleading Generalized Itemset (MGI). Each MGI, denoted as X ⊲ E , represents a frequent generalized itemset X and its set E of low-level frequent descendants for which the correlation type is in contrast to the one of X. To allow experts to analyze the misleading high-level data correlations separately and exploit such knowledge by making different decisions, MGIs are extracted only if the low-level descendant itemsets that represent contrasting correlations cover almost the same portion of data as the high-level (misleading) ancestor. An algorithm to mine MGIs at the top of traditional generalized itemsets is also proposed. ∗Corresponding author. Tel. : +39 011 090 7084. Fax: +39 011 090 7099. Email addresses: luca.cagliero@polito.it (Luca Cagliero), tania.cerquitelli@polito.it (Tania Cerquitelli), paolo.garza@polito.it (Paolo Garza), luigi.grimaudo@polito.it (Luigi Grimaudo) Preprint submitted to The experiments performed on both real and synthetic datasets demonstrate the effectiveness and efficiency of the proposed approach.
7.01.109 Magnetic Resonance-Guided Focused Ultrasound

Policy [TOP] Magnetic resonance ‒ guided high-intensity ultrasound ablation may be considered medically necessary for pain palliation in adult patients with metastatic bone cancer who failed or are not candidates for radiotherapy. Magnetic resonance-guided high-intensity ultrasound ablation is considered investigational in all other situations including but not limited to:  Treatment of uterine fibroids;  Treatment of other tumors e.g., brain cancer, prostate cancer and breast cancer.
Stochastic Memory for Sequence Models

State of the art lossless compression techniques typically use memory intensive data structures which grow on the order of O(N) in the input size. Memory is an expensive resource, and many computing environments cannot afford O(N) memory scaling for typical workloads. There are several techniques that attempt to impose O(1) space restrictions on existing lossless compression techniques, which are similar in that they delete portions of their backing data structures. A novel approach presented in this thesis is to not delete the data structure, but instead allow contamination of statistics where each occurrence counter tracks an arbitrary number of entities. The behaviour of a contaminating compressor is explored sparsely in contemporary literature. This thesis serves to document the characteristics of an implementation of a contaminating scheme when applied to several existing suffix tree-based compressors.
Erfassung der SARS-CoV-2-Testzahlen in Deutschland

Daten zur Anzahl der durchgeführten Testungen zu SARS-CoV-2 sowie zur Anzahl der Personen mit den jeweiligen Testergebnissen und den Testkapazitäten werden aktuell über verschiedene Netzwerke bzw. Umfragen erhoben und in einer Übersicht vom Robert Koch-Institut (RKI) zusammengestellt. Neben einer internetbasierten Umfrage des RKI über Voxco (RKI-Testlaborabfrage) werden Daten vom Netzwerk für respiratorische Viren (RespVir), der am RKI etablierten Antibiotika-Resistenz-Surveillance (ARS) und dem Interessenverband der akkreditierten medizinischen Labore in Deutschland (ALM e. V.) erfasst und wöchentlich am RKI zusammengeführt. Zusätzlich werden über die RKI-Testlaborabfrage und der Abfrage aus ALM e. V. die maximalen Testkapazitäten der Labore für die kommende Kalenderwoche (KW) sowie eventuelle Lieferengpässe für Reagenzien sowie Probenrückstaus erfasst. Die Testzahlen der vorangegangenen Kalenderwoche werden mittwochs im Lagebericht des RKI veröffentlicht.
A New Value-Weighted Total Return Index for the Finnish Stock Market 1912-1969

This paper presents a new monthly value-weighted, all-share total return index for the Finnish stock market. The index covers the period from the establishment of the Helsinki Stock Exchange in October 1912 to the beginning of 1970, after which the WI index by Berglund et al. (1983) and later in 1990 the HEX index become available. When combined, they can be used to study continuously the development of the Finnish equity market from the beginning of the stock market until the present day. We also provide a detailed description of the construction methodology and a comparison between our index and those available earlier. The index also replaces the Unitas price index which has been the only index available for long-term studies from 1928 onwards. The new index also provides an alternative to the book equity weighted Poutvaara (1996) price index for the period 1912-1929.
Speculation at Fault: Modeling and Testing Microarchitectural Leakage of CPU Exceptions

Microarchitectural leakage models provide effective tools to prevent vulnerabilities such as Spectre and Meltdown via secure co-design: For software, they provide a foundation for secure compilation and verification; for hardware, they provide a target specification to test and verify against. Unfortunately, existing leakage models are severely limited: None of them covers CPU exceptions, which are essential to implement security abstractions such as virtualization and memory protection, and which are the source of critical vulnerabilities such as Meltdown, MDS, and Foreshadow. In this paper, we provide the first leakage models for CPU exceptions, together with new tools for testing black-box CPUs against them. We run extensive experiments and successively refine these models, until we precisely capture the leakage for a representative subset of exceptions on four different x86 microarchitectures. In the process, we contradict, refine, and corroborate a large number of findings from prior work, and we uncover three novel transient leaks affecting stores to non-canonical addresses, stores to read-only memory, and divisions by zero.
Statistica Sinica Preprint No: SS-2019-0412

: Density ratio models have received increasing attention in recent years, particularly because of its relationship with generalized linear models and applications in missing data analysis. The density-ratio assumption, however, may not be true in some applications and one important limitation is that the standard density ratio model does not accommodate heterogeneity within the underlying population. To address these issues, we propose a new density ratio model by incorporating a stratiﬁcation procedure and dispersion parameters. The resulting stratiﬁed density ratio model 1) retains attractive properties of the standard density ratio model while allowing the density-ratio assumption to be violated for some covariate, and 2) provides a validation tool, via a Kolmogorov-Smirnov-type statistic, to check the modeling assumption. We estimate both the ﬁnite-dimensional and inﬁnite-dimensional parameters simultaneously using an eﬃcient nonparametric maximum likelihood approach. The resulting estimators are shown to be consistent and asymptotically normal. The asymptotic covariance matrix of the estimators for the ﬁnite-dimensional parameters attains the semiparametric eﬃciency bound.
Moral Judgments in Social Dilemmas : How Bad is Free Riding ?

The focus for the Centre is research into individual and strategic decision-making using a combination of theoretical and experimental methods. On the theory side, members of the Centre investigate individual choice under uncertainty, cooperative and non-cooperative game theory, as well as theories of psychology, bounded rationality and evolutionary game theory. Members of the Centre have applied experimental methods in the fields of public economics, individual choice under risk and uncertainty, strategic interaction, and the performance of auctions, markets and other economic institutions. Much of the Centre's research involves collaborative projects with researchers from other departments in the UK and overseas. In the last thirty years economists and other social scientists investigated people's normative views on principles of distributive justice. Here we study people's normative views in social dilemmas, which underlie many situations of economic and social significance. Using insights from moral philosophy and psychology we provide an analysis of the morality of free riding. We use experimental survey methods to investigate people's moral judgments empirically. We vary others' contributions, the framing (" give-some " vs. " take-some ") and whether contributions are simultaneous or sequential. We find that moral judgments depend strongly on others' behaviour; and that failing to give is condemned more strongly than withdrawing all support. A striking recent development in public economics has been its increasing use of data on people's normative attitudes, obtained with surveys and questionnaires. For example, views about distributive justice and the demand for redistribution have 1 In this paper, we extend the empirical investigation of people's normative views to a different economic context, namely social dilemma (public goods) games, and to a different type of normative view, namely moral judgment. 2 More specifically, we report an experiment that, using techniques adapted from moral psychology, explores how individuals judge the morality of a free rider in a social dilemma game. A social dilemma arises when members of a group share the benefits of a common resource but each of them has to decide individually whether, or how much, to contribute to its provision. Contribution is costly to the contributor but helpful to all other group members. Thus, a social dilemma isolates a conflict between personal interest, which militates for free riding, and the collective interest, which requires contribution. The frequent occurrence of social dilemmas in economic and social life makes them important for economics and social science; and the conflict of interests that …
Innovation and sustainability: create the innovative organisation

This paper describes the ecological concept of strategic fit in order to enhance sustainable and innovative organisations. The Ecological System Model integrates concepts of ecology and evolutionary economic theory by comparing organisations and ecosystems at a consistent system level. It introduces a taxonomy of organisations from tundra to tropical rainforest and aligns ‘open innovation’ with the participative concept of people-market-combinations. It wants to contribute to the development of theory and practice of social innovation (creating new richer relations between people and environment) in such a way, that it enhances (business models for) productivity as well as other values.