Emerging Research Directions Research Articles

Colloquium: Incompatible measurements in quantum information science

Some measurements in quantum mechanics disturb each other. This has puzzled physicists since the formulation of the theory, but only in recent decades has the incompatibility of measurements been analyzed in depth and detail, using the notion of joint measurability of generalized measurements. In this Colloquium joint measurability and incompatibility are reviewed from the perspective of quantum information science. The Colloquium starts by discussing the basic definitions and concepts. An overview on applications of incompatibility, such as in measurement uncertainty relations, the characterization of quantum correlations, or information processing tasks like quantum state discrimination, is then presented. Finally, emerging directions of research, such as a resource theory of incompatibility as well as other concepts to grasp the nature of measurements in quantum mechanics, are discussed.

E-Spin: A Stochastic Ising Spin Based on Electrically-Controlled MTJ for Constructing Large-Scale Ising Annealing Systems

With its unique computer paradigm, the Ising annealing machine has become an emerging research direction. The Ising annealing system is highly effective at addressing combinatorial optimization (CO) problems that are difficult for conventional computers to tackle. However, Ising spins, which comprise the Ising system, are difficult to implement in high-performance physical circuits. We propose a novel type of Ising spin based on an electrically-controlled magnetic tunnel junction (MTJ). Electrical operation imparts true randomness, great stability, precise control, compact size, and easy integration to the MTJ-based spin. In addition, simulations demonstrate that the frequency of electrically-controlled stochastic Ising spin (E-spin) is 50 times that of the thermal disturbance MTJ-based spin (p-bit). To develop a large-scale Ising annealing system, up to 64 E-spins are implemented. Our Ising annealing system demonstrates factorization of integers up to 264 with a temporal complexity of around O(n). The proposed E-spin shows superiority in constructing large-scale Ising annealing systems and solving CO problems.

Bibliometric and visualization analysis of global research trends on immunosenescence (1970–2021)

BackgroundImmunosenescence, the aging of the immune system, leads to a decline in the body's adaptability to the environment and plays an important role in various diseases. Immunosenescence has been widely studied in recent years. However, to date, no relevant bibliometric analyses have been conducted. This study aimed to analyze the foundation and frontiers of immunosenescence research through bibliometric analysis. MethodsArticles and reviews on immunosenescence from 1970 to 2021 were obtained from the Web of Science Core Collection. Countries, institutions, authors, journals, references, and keywords were analyzed and visualized using VOSviewer and CiteSpace. The R language and Microsoft Excel 365 were used for statistical analyses. ResultsIn total, 3763 publications were included in the study. The global literature on immunosenescence research has increased from 1970 to 2021. The United States was the most productive country with 1409 papers and the highest H-index. Italy had the highest average number of citations per article (58.50). Among the top 10 institutions, 50 % were in the United States. The University of California was the most productive institution, with 159 articles. Kroemer G, Franceschi C, Goronzy JJ, Solana R, and Fulop T were among the top 10 most productive and co-cited authors. Experimental Gerontology (n = 170) published the most papers on immunosenescence. The analysis of keywords found that current research focuses on “inflammaging”, “gut microbiota”, “cellular senescence”, and “COVID-19”. ConclusionsImmunosenescence research has increased over the years, and future cooperation and interaction between countries and institutions must be expanded. The connection between inflammaging, gut microbiota, age-related diseases, and immunosenescence is a current research priority. Individualized treatment of immunosenescence, reducing its negative effects, and promoting healthy longevity will become an emerging research direction.

Report on the First International Workshop on Data Systems Education (DataEd '22)

This report summarizes the outcomes of the first international workshop on Data Systems Education: Bridging Education Practice with Education Research (DataEd '22). The workshop was held in conjunction with the SIGMOD '22 conference in Philadelphia, USA on June 17, 2022. The aim of the workshop was to provide a dedicated venue for presenting and and discussing data management systems education experiences and research by bringing together the database and the computing education research communities to share findings, to crosspollinate perspectives and methods, and to shed light on opportunities for mutual progress in data systems education. The program featured two keynote talks, ten research paper presentations, a discussion session, and an industry panel discussion. In this report, we present the workshop's main results, observations, and emerging research directions.

Integrated safety and security enhancement of connected automated vehicles using DHR architecture

Safety and security are interrelated and both essential for connected automated vehicles (CAVs). They are usually investigated independently, followed by standards ISO 26262 and ISO/SAE 21434, respectively. However, more functional safety and security features of in-vehicle components make existing safety mechanisms weaken security mechanisms andvice versa. This results in a dilemma that the safety-critical and security-critical in-vehicle components cannot be protected. In this paper, we propose a dynamic heterogeneous redundancy (DHR) architecture to enhance the safety and security of CAVs simultaneously. We first investigate the current status of integrated safety and security analysis and explore the relationship between safety and security. Then, we propose a new taxonomy of in-vehicle components based on safety and security features. Finally, a dynamic heterogeneous redundancy (DHR) architecture is proposed to guarantee integrated functional safety and cyber security of connected vehicles for the first time. A case study on an automated bus shows that DHR architecture can not only detect unknown failures and ensure functional safety but also detect unknown attacks to protect cyber security. Furthermore, we provide an in-depth analysis of quantification for CAVs performance using DHR architecture and identify challenges and future research directions. Overall, integrated safety and security enhancement is an emerging research direction.

Traversability Aware graph-based Subterranean Exploration with Unmanned Aerial Vehicles*

Subterranean exploration and mapping for search and rescue robotics have become an emerging research direction since the DARPA organized Subterranean Challenge. As part of development efforts within the team CoSTAR (Collaborative SubTerranean Autonomous Robots) in the Sub-T challenge, this work establishes a novel traversable graph-based exploration strategy that utilizes frontiers for local navigation and a fast collision risk-aware graph building for global navigation. The exploration strategy extracts frontiers in an unknown area that contribute to safe navigation while maximizing information gain for the robot. The exploration problem is further bifurcated into local and global exploration for faster decision-making at junctions with the goal of rapidly exploring the area. The local exploration guarantees collision-free straight-line paths to informative frontiers for rapid forward navigation, while global re-positioning utilizes a traversable graph subject to geometrical collision checks within the occupancy map. The pathfinding in a graph is addressed using a heuristic, which combines risk margins and travel costs to assist in short yet safe paths to the global frontier in case of a dead end in local exploration. The presented exploration strategy is developed with the goal of making exploration algorithms platform agnostic in order to be able to use it with aerial, as well as ground robots. The proposed method is also evaluated against different state-of-the-art exploration planners in simulated fixed-time budget-based exploration missions on an Unmanned Aerial Vehicle (UAV) in order to benchmark the capabilities and highlight the novelty.

Quantum layertronics in van der Waals systems

In van der Waals system, the interlayer van der Waals coupling between adjacent atomically thin layers makes the electronic wave function spread on more than one specific layer, turning spatial discrete layer degree of freedom into a quantum mechanical degree of freedom. The coupling of layer degree of freedom with the in-plane center-of-mass motion of electrons forms a nontrivial layer pseudospin structure in momentum space, resulting in various new quantum geometric properties in an extended parameter space, which is unique to the lattice mismatched van der Waals systems. They trigger off a plenty of novel transport and optical effects, linear and nonlinear responses, and offer new pathways towards device applications, becoming the research frontiers of quantum layertronics. This article briefly reviews this emerging research direction, and discusses possible development in the near future based on its crossing with other intensive research fields such as nonlinear electronics, twistronics and chiral electronics.

Nanomaterials and nanotechnology for biomedical soft robots

Soft robots have opened an emerging research direction in robotics due to their promising performance enabled by functional materials and fabrication technology. Recent progress of functional materials has brought soft robots with advanced functionalities and greatly expanded their potential applications in various fields. Biomedical applications have attracted significant research interests and become an emerging field. Particular trends have been shifted to the submillimeter-scale biomedical soft robots and the integrated manipulatable devices with well controllability and compatibility. Functionalities of these biomedical soft robots are dominated by nanomaterials and nanotechnology. However, lack of study has overviewed the promising development progress of functional nanomaterials and advanced nanotechnology in soft robots for biomedical applications. It is worthwhile to review such an important but not yet fully exposed research trend. To address such research gap, this review article focuses on the recent achievements, technological challenges and future trends of the nanomaterials and nanotechnology used in biomedical soft robots. We provide a state-of-the-art review on the current progress while mainly focusing on explaining the mechanism and functionality of the soft robots with respect to the nanomaterials and nanotechnology. In the end, we summarize the main challenges of biomedical soft robots and envision the future trends by outlooking the development of advanced nanomaterials and nanotechnology.

Research on hotspots and evolution paths in the field of health information behavior: a comparison study of bibliometrics based on CNKI and WoS data

PurposeThis study aimed to examine the research hotspots and evolution paths in the field of health information behavior (HIB) in China and abroad, and conduct comparative analysis to better understand its development trajectory globally.Design/methodology/approachA keyword search of the relevant literature included in the China National Knowledge Infrastructure (CNKI) database and Web of Science (WoS) core collection database was conducted, using the visualized analysis tool CiteSpace V for bibliometric analyses.FindingsThe common research hotspots in China and abroad can be divided into related research on HIB, research on its influencing factors and health information research. Among these, health information-seeking behavior has been the focus of domestic and foreign scholars. From the subdivision perspective, the focus of Chinese and foreign research hotspots differs. In terms of evolutionary path, the initial stage of HIB research in China and abroad revolves around health information and health information-seeking behavior, followed by the influencing factors of HIB; however, the research breakthrough point is the reverse. Then, domestic and foreign research was conducted on different types of HIBs. Regarding the selection of research objects, Chinese and foreign research objects were increasingly diversified.Research limitations/implicationsThis study also has several limitations. First, the literature sample only selected the literature in the WoS and CNKI databases, and there may be many HIB-related works published in other databases. Therefore, future research should include other databases. Second, in terms of language, this study selected only Chinese and English literature, but in many countries, important research results on certain topics are usually published in native language, and future research should expand the language selection. Third, this study only conducted national and institutional collaboration network analysis, keyword co-occurrence analysis, cluster analysis and timeline chart analysis.Practical implicationsThe implication of practice can be divided into the following three points. (1) Analyzing the domestic and foreign literature on HIB and identifying highly cooperative institutions and countries in the field of HIB can reveal the research situation of HIB and help researchers establish new research networks in the future. (2) Analyzing the research hotspots and evolutionary paths of HIB at home and abroad is helpful for quickly understanding the development context of this field and grasping the emerging research directions such as HIB of people in close contact with patients, health information exchange behavior, health information avoidance behavior and health information discontinuation behavior, which can help researchers to explore the future research direction in this field, so as to determine the topic and fill the research gap. (3) Combining the analysis of HIB-related research at home and abroad is helpful for professionals to understand the characteristics and rules of HIB of users, consumers and other groups to further optimize and improve health information services.Originality/valueComparing and summarizing the research status of HIB in China and globally, and presenting the findings visually, will help researchers better grasp the research overview and hotspot changes in this field, as well as provide a follow-up reference.

Adversarial data hiding with only one pixel

Making adversarial samples to fool deep neural network (DNN) is an emerging research direction of privacy protection, since the output of the attacker's DNN can be easily changed by the well-designed tiny perturbation added to the input vector. However, the added perturbation is meaningless. Why not embed some useful information to generate adversarial samples while integrating the functions of copyright and integrity protection of data hiding? This paper solves the problem by modifying only one pixel of the image, that is, data hiding and adversarial sample generation are achieved simultaneously by the only one modified pixel. In CIFAR-10 dataset, 11 additional bits can be embedded into the host images sized 32 × 32, and the successful rate of adversarial attack is close to the state-of-the-art works. This paper proposes a new idea to combine data hiding and adversarial sample generation, and gives a new method for privacy-preserved processing of image big data.

Plant-Derived Polyphenols as Nrf2 Activators to Counteract Oxidative Stress and Intestinal Toxicity Induced by Deoxynivalenol in Swine: An Emerging Research Direction.

The contamination of deoxynivalenol (DON) in feed is a global problem, which seriously threatens the productivity efficiency and welfare of farm animals and the food security of humans. Pig is the most sensitive species to DON, and is readily exposed to DON through its grain-enriched diet. The intestine serves as the first biological barrier to ingested mycotoxin, and is, therefore, the first target of DON. In the past decade, a growing amount of attention has been paid to plant-derived polyphenols as functional compounds against DON-induced oxidative stress and intestinal toxicity in pigs. In this review, we systematically updated the latest research progress in plant polyphenols detoxifying DON-induced intestinal toxicity in swine. We also discussed the potential underlying mechanism of action of polyphenols as Nrf2 activators in protecting against DON-induced enterotoxicity of swine. The output of this update points out an emerging research direction, as polyphenols have great potential to be developed as feed additives for swine to counteract DON-induced oxidative stress and intestinal toxicity.

Machine learning and deep learning in phononic crystals and metamaterials – A review

Machine learning (ML), as a component of artificial intelligence, encourages structural design exploration which leads to new technological advancements. By developing and generating data-driven methodologies that supplement conventional physics and formula-based approaches, deep learning (DL), a subset of machine learning offers an efficient way to understand and harness artificial materials and structures. Recently, acoustic and mechanics communities have observed a surge of research interest in implementing machine learning and deep learning methods in the design and optimization of artificial materials. In this review we evaluate the recent developments and present a state-of-the-art literature survey in machine learning and deep learning based phononic crystals and metamaterial designs by giving historical context, discussing network architectures and working principles. We also explain the application of these network architectures adopted for design and optimization of artificial structures. Since this multidisciplinary research field is evolving, a summary of the future prospects is also covered. This review article serves to update the acoustics, mechanics, physics, material science and deep learning communities about the recent developments in this newly emerging research direction

COVID and challenges in the context of family firms internationalisation: a review and emerging research pathways

PurposeThis study aims to fulfil a twofold purpose: first, to discuss the changes and unique challenges that family firms (FFs) face during the COVID-19 pandemic and/or they will face in the post-COVID era, and second, to reflect on emerging research directions and contextual factors that should be taken into account in future explorations for the benefit of FF scholars who will study post-COVID FF internationalisation.Design/methodology/approachTo address the twofold purpose of the study, we conduct an integrative review of 31 peer-reviewed journal articles in the international business (IB) and FF literature on COVID-19, FFs and internationalisation.FindingsCOVID-19 brought changes in IB strategies, IB relationships and human resource management. In responding and/or adapting to those changes, during and post-COVID, FFs face and are expected to face challenges that mainly refer to FFs’ transition to digitalisation and the simultaneous preservation of socio-emotional wealth dimensions while maintaining their international presence. The authors suggest that future research explores the role of digitalisation in achieving FFs’ internationalisation, IB relationship building activities and training and leading international employees. Further contextual factors (e.g. succession issues, family structures) should also be accounted for when exploring such post-COVID IB phenomena.Originality/valueThis study comprises an initial attempt to encompass the interface of FF internationalisation and COVID-19. It also proposes research directions that are likely to set the stage in FFs’ post-COVID internationalisation research.

Towards energy efficient autonomous exploration of Mars lava tube with a Martian coaxial quadrotor

Mapping and exploration of a Martian terrain with an aerial vehicle has become an emerging research direction, since the successful flight demonstration of the Mars helicopter Ingenuity. Although the autonomy and navigation capability of the state of the art Mars helicopter has proven to be efficient in an open environment, the next area of interest for exploration on Mars are caves or ancient lava tube like environments, especially towards the never-ending search of life on other planets. This article presents an autonomous exploration mission based on a modified frontier approach along with a risk aware planning and integrated collision avoidance scheme with a special focus on energy aspects of a custom designed Mars Coaxial Quadrotor (MCQ) in a Martian simulated lava tube. One of the biggest novelties of the article stems from addressing the exploration capability, while rapidly exploring in local areas and intelligently global re-positioning of the MCQ when reaching dead ends in order to efficiently use the battery based consumed energy, while increasing the volume of the exploration. The proposed novel algorithm for the Martian exploration is able to select the next way point of interest, such that the MCQ keeps its heading towards the local exploration direction where it will find maximum information about the surroundings. The proposed three layer cost based global re-position point selection assists in rapidly redirecting the MCQ to previously partially seen areas that could lead to more unexplored part of the lava tube. The Martian fully simulated mission presented in this article takes into consideration the fidelity of physics of Mars condition in terms of thin atmosphere, low surface pressure and low gravity of the planet, while proves the efficiency of the proposed scheme in exploring an area that is particularly challenging due to the subterranean-like environment. The proposed exploration-planning framework is also validated in simulation by comparing it against the graph based exploration planner. Intensive simulations with true Mars conditions are carried out in order to validate and benchmark our approach in a utmost realistic Mars lava tube exploration scenario using a Mars Coaxial Quadrotor.

A review of emerging research directions in Abstract Visual Reasoning

Abstract Visual Reasoning (AVR) problems are commonly used to approximate human intelligence. They test the ability of applying previously gained knowledge, experience and skills in a completely new setting, which makes them particularly well-suited for this task. Recently, the AVR problems have become popular as a proxy to study machine intelligence, which has led to emergence of new distinct types of problems and multiple benchmark sets. In this work we review this emerging AVR research and propose a taxonomy to categorise the AVR tasks along 5 dimensions: Input shapes, hidden rules, target task, cognitive function, and specific challenge. The perspective taken in this survey allows to characterise AVR problems with respect to their shared and distinct properties, provides a unified view on the existing approaches to solving AVR tasks, shows how the AVR problems relate to practical applications, and outlines promising directions for future work. One of them refers to the observation that in the machine learning literature different tasks are considered in isolation, which is in the stark contrast with the way the AVR tasks are used to measure human intelligence, where multiple types of problems are combined within a single IQ test.

Application of Physics-Informed Neural Networks Algorithm to Predict the Vorticity of a Moving Cylindrical Flow Field

Turbulence is a typical physical phenomenon which is involved in many engineering fields. The combination of machine learning and turbulence modeling is an emerging research direction in the field of fluid mechanics. The current achievements in this research direction have strongly verified its feasibility and indicated a positive prospect for the application of machine learning for the turbulence modeling. Machine learning can help discover models of complex dynamical systems from the data directly. In this work, we apply the machine learning algorithm called the physics-informed neural networks (PINNs) to predict the vorticity of a moving cylindrical flow field. Through the neural network method based on physical information, a neural network model is established to simulate the flow around a moving cylinder. Results demonstrate that the vorticity predicted by PINNs algorithm are in good agreement with the benchmark results.

Strongly Lensed Transient Sources: A Review

The past decades have witnessed a lot of progress in gravitational lensing with two main targets: stars and galaxies (with active galactic nuclei). The success is partially attributed to the continuous luminescence of these sources making the detection and monitoring relatively easy. With the running of ongoing and upcoming large facilities/surveys in various electromagnetic and gravitational-wave bands, the era of time-domain surveys would guarantee constant detection of strongly lensed explosive transient events, for example, supernovae in all types, gamma ray bursts with afterglows in all bands, fast radio bursts, and even gravitational waves. Lensed transients have many advantages over the traditional targets in studying the Universe, and magnification effect helps to understand the transients themselves at high redshifts. In this review article, on base of the recent achievements in literature, we summarize the methods of searching for different kinds of lensed transient signals, the latest results on detection and their applications in fundamental physics, astrophysics, and cosmology. At the same time, we give supplementary comments as well as prospects of this emerging research direction that may help readers who are interested in entering this field.

Decoding the Trends and the Emerging Research Directions of Digital Tourism in the Last Three Decades: A Bibliometric Analysis

Digital technologies have radically changed the tourism industry and gaining a lot of attention from the stakeholders. At present, there is voluminous but fragmented research to cover the various aspects of digital tourism, but a consolidated “big picture” of the extant research is missing. By performing a bibliometric analysis of 827 papers on digital tourism, an attempt has been made to fill this void. The investigation revealed that the management of smart destinations, the internet as a communication and marketing channel, technology and sustainability, and consumer behavior are emerging research directions in digital tourism. Observations regarding little scientific interest and collaborations in regions like Russia and Africa present an opportunity for researchers and businesses to set directions and strategies for the future. JEL Code M310, Z300, Z310, Z320, Z330

Emerging research problems in different business domains: An analytics perspective

In this paper, we provide brief summaries of the papers included in the special issue on “Business Analytics: Emerging Practice and Research Issues.” There are eight papers, including this study, published in the special issue. We also categorize papers across different themes and present emerging research directions for business analytics‐related problems in different domains.

A bibliometric analysis of autophagy in atherosclerosis from 2012 to 2021.

Background: Regulation of autophagy affects the progression of atherosclerosis. In recent years, research on autophagy in atherosclerosis has been widely concerned. However, there is no bibliometric analysis in this field. Objective: The purpose of this study was to explore the general situation, hot spots, and trends of the research in this field through bibliometric analysis. Methods: Articles related to autophagy in atherosclerosis from 2012 to 2021 were retrieved from the Web of Science Core Collection. VOSviewer and CiteSpace were used for data analysis and visualization of countries, institutions, authors, keywords, journals, and citations. Results: A total of 988 articles were obtained in the last 10 years. The number of publications and citations increased rapidly from 2012 to 2021, especially after 2019. The most productive countries, institutions, journals, and authors were the People’s Republic of China, Shandong University, Arteriosclerosis Thrombosis and Vascular Biology, and Wim Martinet, respectively. The primary keywords were “oxidative stress,” “apoptosis,” “activated protein kinase,” and “inflammation.” The burst detection analysis of keywords found that “SIRT1” and “long non-coding RNA” might be regarded as the focus of future research. Conclusion: This is the first bibliometric analysis of autophagy in atherosclerosis, which reports the hot spots and emerging trends. The interaction between oxidative stress and autophagy, programmed cell death, and activated protein kinases are considered to be the current research priorities. Molecular mechanisms and therapeutic target for the intervention of atherosclerosis by regulating autophagy will become an emerging research direction.