In the world of Information Technology, new computing paradigms, driven by requirements of different classes of problems and applications, emerge rapidly. These new computing paradigms pose many new research challenges. Researchers from different disciplines are working together to develop innovative solutions addressing them. In newer research areas with many unknowns, creating roadmaps, enabling

We define and study logics in the framework of probabilistic team semantics and over metafinite structures. Our work is paralleled by the recent development of novel axiomatizable and tractable logics in team semantics that are closed under the Boolean negation. Our logics employ new probabilistic atoms that resemble so-called extended atoms from the team semantics literature. We also define counterparts

Constrained Horn Clauses (CHCs) are an intermediate program representation that can be generated by several verification tools, and that can be processed and solved by a number of Horn solvers. One of the main challenges when using CHCs in verification is the encoding of heap-allocated data-structures: such data-structures are today either represented explicitly using the theory of arrays, or transformed

In this paper, we present GMG-BCU  — a local search algorithm based on block coordinate update for estimating a generalized median graph for a given collection of labeled or unlabeled input graphs. Unlike all competitors, GMG-BCU is designed for both discrete and continuous label spaces and can be configured to run in linear time w. r. t. the size of the graph collection whenever median node and edge

Momentary photography is enjoyed by many smartphone users, especially with the popularity of apps such as Snapchat and Instagram. Many traditional positive psychology interventions focus on lengthy writing tasks to express positive emotions experienced during past events, acts of kindness and gratuitous situations. In this work we developed SnapAppy, a smartphone application to integrate momentary

When inferring sentiments, using verbal clues only is problematic because of the ambiguity. Adding related vocal and visual contexts as complements for verbal clues can be helpful. To infer sentiments from multi-modal temporal sequences, we need to identify both sentiment-related clues and their cross-modal interactions. However, sentiment-related behaviors of different modalities may not occur at

In the stabilizing consensus problem each agent of a networked system has an input value and is repeatedly writing an output value; it is required that eventually all the output values stabilize to the same value which, moreover, must be one of the input values. We study this problem for a synchronous model with identical and anonymous agents that are connected by a time-varying topology and may join

In this study, we demonstrate how we can quantify environmental implications of large-scale events and traffic (e.g., human movement) in public spaces, and identify specific regions of a city that are impacted. We develop an innovative data fusion framework that synthesises the state-of-the-art techniques in extracting pollution episodes and detecting events from citizen-contributed, city-specific

Supported by an environment that is increasingly immersed in digital transformation, universities are facing important organizational changes in both tangible and intangible structures. Digital transformation isn’t all about technology, there is a human side of the story. Leadership is seen as a key issue in any process of change. However, leaders of professional and knowledge-based institutions, like

The Tomita’s Generalized LR(1) parsing algorithm (GLR), later improved in many ways, runs in a linear time on LR(1) grammars, and degrades to a polynomial-time bound if the grammar is not deterministic. We address a useful feature not present in the current GLR(1) methods: the ability to accept grammars of the Extended BNF type (EBNF), the rules of which contain regular expressions. An EBNF grammar

In contrast to their reliable and lossy-error counterparts whose termination problems are either undecidable or non-primitive recursive, the termination problem for counter machines with incrementing errors is shown to be ExpSpace-complete. It is also shown that the structural termination problem—deciding whether every run terminates from any starting configuration—for counter machines with incrementing

Processing and classification of Electromyography (EMG) signals is a common practice in prosthetic arm design for hand amputees. This study investigates how reliable classification results may be obtained from less muscle data, as is the case for the muscle loss in hand amputees. In order to increase classification performance, features from gyroscopic data, not previously used in studies in the literature

Chore division is a class of fair division problems in which some undesirable "resource" must be shared among a set of participants, with each participant wanting to get as little as possible. Typically the set of participants is fixed and known at the outset. This paper introduces a novel variant, called sequential online chore division (SOCD), in which participants arrive and depart online, while

We present a simple and robust implementation of the phase field fracture method in Abaqus. Unlike previous works, only a user material (UMAT) subroutine is used. This is achieved by exploiting the analogy between the phase field balance equation and heat transfer, which avoids the need for a user element mesh and enables taking advantage of Abaqus' in-built features. A unified theoretical framework

Optimizing the design of solar cell metallizations is one of the ways to improve the performance of solar cells. Recently, it has been shown that Topology Optimization (TO) can be used to design complex metallization patterns for solar cells that lead to improved performance. TO generates unconventional design patterns that cannot be obtained with the traditional shape optimization methods. In this

In this work, we review the framework of the Virtual Element Method (VEM) for a model in magneto-hydrodynamics (MHD), that incorporates a coupling between electromagnetics and fluid flow, and allows us to construct novel discretizations for simulating realistic phenomenon in MHD. First, we study two chains of spaces approximating the electromagnetic and fluid flow components of the model. Then, we

The eigenfunctions of the Laplace-Beltrami operator have widespread applications in a number of disciplines of engineering, computer vision/graphics, machine learning, etc. These eigenfunctions or manifold harmonics, provide the means to smoothly interpolate data on a manifold. They are highly effective, specifically as it relates to geometry representation and editing; manifold harmonics form a natural

In this article we construct a compact Riemannian manifold of high dimension on which the time dependent Euler equations are Turing complete. More precisely, the halting of any Turing machine with a given input is equivalent to a certain global solution of the Euler equations entering a certain open set in the space of divergence-free vector fields. In particular, this implies the undecidability of

A Correction to this paper has been published: https://doi.org/10.1038/s41586-021-03286-9.

The global emergence of SARS-CoV-2 urgently requires an in-depth understanding of molecular functions of viral proteins and their interactions with the host proteome. Several individual omics studies have extended our knowledge of COVID-19 pathophysiology1–10. Integration of such datasets to obtain a holistic view of virus-host interactions and to define the pathogenic properties of SARS-CoV-2 is limited

Hannah Franklin is one of 300 staff members at the Francis Crick Institute in London, helping to bring the pandemic to an end.

Letter to the Editor

Letter to the Editor

The controversy over Majorana particles is eroding confidence in the field. More accountability and openness are needed — from authors, reviewers and journal editors.

Restrictive travel policies could further privilege global-health professionals from high-income countries. Plus: Joe Biden’s plans to increase science funding, and why our brains favour adding over subtraction.

The global dearth of safe sewage systems needs innovation and advocacy.

Researchers are starting to delve into possible rare side effects of COVID-19 vaccines. Plus: the month’s best science images, and everything you need to know about Plan S.

Ewing sarcoma (ES) is a malignant tumor that occurs mostly in children. However, the underlying mechanisms of ES are still unknown. Analyzing the results of two previous miRNA array reports, we found that miR-146b-5p might be an onco-miRNA in ES progression. To test this hypothesis, we detected the expression levels of miR-146b-5p by real-time PCR and observed the effects of miR-146b-5p on the progression

Wireless sensor networks consist of many sensor nodes with limited resources and computing capability. Thus, managing energy consumption to prolong network lifetime is a critical issue. Several approaches have been proposed to extend the network lifetime, one of which involves deploying relay nodes to transfer data from sensors to the base station. However, the limited number of relay nodes is a challenge

To solve dynamic multi-objective optimization problems, a dynamic multi-objective evolutionary algorithm (DMOEA) must be able to deal with the dynamics of the environment, and such modifications can lead to new optimal solutions over time. Various algorithms have been proposed that modify the way a change is handled. Among them, prediction-based methods are promising for solving this kind of problem

In this research work, an efficient robust video steganography in compressed domain is presented based on discrete cosine transform (DCT) encoded with H.264 codec. In this method, a compressed video (.mp4) of different resolutions, frame rates and sizes are used as a cover and RGB image is used as a secret message. Using appropriate stego key, the secret frames from the sequence of video frames are

Visible-Light Communication (VLC) application such as traffic lighting requires high-speed data transmission wherein at the receiving end, a fast response and wide bandwidth photodetector should decode the sent data. High-speed detection is achievable through a photoFET such as Optical Field Effect Transistor (OPFET) while maintaining tremendously large photocurrent gain or sensitivity. In this paper

Globally, electronic waste (E-Waste) has grown as a severe concern owing to the increasing quantity of waste and the toxic it. E-Waste includes plastics and metals, which are highly recyclable but which, if not adequately managed, are concerned about the health and the environment by plastic waste and heavy metal traces of additives and chemicals. This article investigates the modeling of game theory

This study aimed to optimize the acidizing efficiency during stimulation treatments with chelating agents. The performance of hydroxylethylethylenediaminetriacetic acid (HEDTA), diethylenetriaminepentaacetic acid (DTPA), and ethylenediaminetetraacetic acid (EDTA) in stimulating carbonate rocks were investigated. In this paper, the effect of injection rate, chemical type, pH, and concentration on the

In order to further explore the discharge characteristics of different shaped particles from the inclined bottom hopper, the discharge of four shaped particles from an inclined bottom rectangular hopper was studied based on the discrete element method (DEM). Non-spherical particles were established based on the multi-spheres method. The effects of geometric parameters, particle properties, and interaction

The vulnerability of deep networks towards adversarial perturbations has motivated the researchers to design detection and mitigation algorithms. Inspired by the dropout and dropconnect algorithms as well as augmentation techniques, this paper presents “PixelMask” based data augmentation as an efficient method of reducing the sensitivity of convolutional neural networks (CNNs) towards adversarial attacks

We present a time-optimal deterministic distributed algorithm for approximating a minimum weight vertex cover in hypergraphs of rank f. This problem is equivalent to the Minimum Weight Set Cover problem in which the frequency of every element is bounded by f. The approximation factor of our algorithm is \((f+\varepsilon )\). Let \(\varDelta \) denote the maximum degree in the hypergraph. Our algorithm

In this work, we propose a new approach to predictive modelling of disease complications development. This approach is based on hybrid methods that have several advantages in comparison with classic methods. The main advantage is the inclusion of the complex information about the dynamics of a patient’s conditions using pathways analysis and graph-based predictive modelling method. Hybrid approaches

Testing helps assure software quality by executing a program and uncovering bugs. Scientific software developers often find it challenging to carry out systematic and automated testing due to reasons like inherent model uncertainties and complex floating-point computations. Extending the recent work on analyzing the unit tests written by the developers of the Storm Water Management Model (SWMM) [32]

Brazilian cerrado biodiversity plays an important role in different areas, such as food and medicine due to the variety of plant species that can be found. However, this has been poorly studied in order to explore aspects related to food and analysis of crude extracts or isolated compounds. In this context, this contribution aims to determine kinetic and phenomenological models to evaluate the mass

Floating geogrid-reinforced piles provide economic solutions when constructing embankments over areas with soft soil. The combination of piles and geogrids allows for the transfer of stress between the piles and adjacent soil through soil arching and tensioned membrane effects. Furthermore, floating geogrid-reinforced pile foundations can also significantly reduce embankment settlement. However, it

Data mining-based scenarios in construction engineering management have become the mainstream, but in the actual application process, big data mining is still affected by many factors, and some construction enterprises have not realized the importance of big data mining for project management. In this paper, aiming at the problems existing in the quality evaluation of construction projects, this paper

Among alternative transport fuels, biodiesel is an eco-friendly substitute for petrodiesel. The quality of biodiesel is dependent on the composition of feedstock oils used for its preparation. The mathematical/statistical tools are used to determine the biodiesel properties, and their outputs are further compared with experimental results for their consistency and reliability. To reduce the cost, efforts

At present, steam-assisted gravity drainage technology has failed to meet the requirement for the large-scale development of abundant oil sands resources due to high production cost and serious environmental pollution caused by huge amounts of carbon emissions. Therefore, this paper proposes a radio frequency technology for heating oil sands and establishes a corresponding mathematical model that considers

Remote and mobile refineries are designed to utilize local groundwater (if abundantly available) to meet their industrial applications and inner uses. However, groundwater usually suffers hardness and salinity. Therefore, reverse osmosis (RO) technology is applied to treat the groundwater before use. The RO concentrate water stream is mixed with other refinery wastewater effluents resulting in a high

This work presents two new CMOS designs of current mode squarer circuits using a 1.5 V supply. The four-quadrant multiplier has also been designed using proposed squarer circuits. To improve bandwidth, the resistive compensation scheme has been exploited. The input and output signals of proposed circuits are of current type and hence exhibit larger dynamic range contrary to voltage mode circuits. Various

Underwater wireless sensor network (UWSN) is a typical application of wireless network in underwater environment, which mainly uses acoustic communication at present. However, due to the characteristics of high bit error rate, very limited bandwidth and high transmission delay, the data transmission collision of underwater communication is very serious. In order to reduce transmission collision and

Online Social Networks (OSNs) are the most popular interactive media for communicating, posting, and sharing indefinite amounts of personal information. However, along with interesting and attractive topics and contents, some users neither like the fact that certain topics that are not among their interests can fill their personal pages nor do they wish to see disappointing negative posts that may

The irregular domain and lack of ordering make it challenging to design deep neural networks for point cloud processing. This paper presents a novel framework named Point Cloud Transformer (PCT) for point cloud learning. PCT is based on Transformer, which achieves huge success in natural language processing and displays great potential in image processing. It is inherently permutation invariant for

In order to improve the quality of experience in executing computation-intensive tasks of real-time IoT applications in a fog-enabled IoT network, resource-constrained IoT devices can offload the tasks to resource-rich nearby fog nodes. It causes a reduction in energy consumption compared with local processing, although it extends task completion time due to communication latency. In this paper, we

Cascade learning with abstention and individualised feature selection is a class of models in high demand in personalised medical applications. The cascade consists of sequential classifiers and rejectors, where the classifiers estimate confidence of prediction, and the rejectors evaluate an expected cost-to-go of features not selected yet. The number of models is exponential in the number of features

Smartphone sensor-based activity recognition seeks broad, high-level knowledge about human behaviors from multitudes of low-level sensor readings, and makes considerable headway in healthcare domain. Our primary contribution is to study the effective pre-processing technique and the extraction of robust features for the classification of sensor data for human activity recognition (HAR). In the pre-processing

In model-based software engineering, models are central artifacts for management, design and implementation. To meet new requirements, engineers need to plan and perform model evolution. So far, model evolution histories are captured using version control systems, e.g., Git. However, these systems are unsuitable for planning model evolution as they do not have a notion of future changes. Furthermore

Many software systems today are highly configurable. They can produce a potentially large variety of related programs (variants) by selecting suitable configuration options (features) at compile time. Recently, specialized variability-aware (lifted, family-based) static analyses based on abstract interpretation have been developed. They allow analyzing all variants of a program family (or, any other

Graph coloring is one of the most famous computational problems with applications in a wide range of areas such as planning and scheduling, resource allocation, and pattern matching. So far coloring problems are mostly studied on static graphs, which often stand in contrast to practice where data is inherently dynamic. A temporal graph has an edge set that changes over time. We present a natural temporal

Ordinary differential equations (ODEs) are important for modelling many problems from science and engineering and efficient ODE solvers are required, for example when solving time-dependent partial differential equations (PDEs) with the method of lines. Since an ODE solver may perform a large number of iteration steps, the execution time for solving an ODE problem might be quite large. Thus, a reduction

Traditional Lattice-Boltzmann modelling of advection–diffusion flow is affected by numerical instability if the advective term becomes dominant over the diffusive (i.e., high-Péclet flow). To overcome the problem, two 3D one-way coupled models are proposed. In a traditional model, a Lattice-Boltzmann Navier–Stokes solver is coupled to a Lattice-Boltzmann advection–diffusion model. In a novel model