Different Types Of Information Research Articles

Adaptive exchange protocol for multi-agent communication in augmented reality system

Augmented Reality (AR) is one of the modern ways of providing users with different types of information. In applications based on this technology, the main influence on the subjective assessment of product quality is the speed of interaction between the system and the user and between users of the system. The main purpose of the work series are creation and modification for algorithms to assessing and improving the quality of AR services. This paper describes and justifies an adaptive communication protocol for multi-agent interaction. We consider a general nonlinear dynamic system with introducing feedback control which is based on measurements under almost arbitrary noise. In practice, this control is realized as a superposition of neural networks with the estimation of the result of mutual additional learning based on the system identification method (M.K.Campi and E.Weyer’s LSCR is used). The prototype is built for a system with a distributed server architecture and multiagent behavior of both clients and servers in the system.

Comparison of two new chaos-based pseudorandom number generators implemented in microcontroller

Chaos-based encryption algorithms uses a pseudorandom number generator (PRNG) to generate chaotic dynamics to carry out the processes to encrypt different types of information. One of the main problems is that some chaotic systems do not present high randomness and uniformity in time series affecting directly the security of the chaos-based cryptosystem. In this work, we proposed two new 2D hyperchaotic maps designed from 1D chaotic maps to use in the design of two new PRNGs for cryptographic applications. The proposed PRNGs were implemented in Renesas RA4M1 32-bit microcontroller for first time in the literature. The chaotic sequences with double-precision floating-point format are also validated with different randomness and security analyses such as the Lyapunov exponent, key space, histograms, autocorrelation, information entropy and the NIST SP800-22 test. In addition, a comparison of the results with similar schemes in the literature about design, security and performance is made. The results achieved in this work can help scholars and designers to improve the effectiveness in randomness of new chaos-based PRNGs for cryptographic applications.

COVID-19 Crisis Management in Newspaper Articles: A Diachronic Analysis

Abstract The present study focuses on how the COVID-19 crisis was dealt with and represented in newspaper articles in the period January 2020-February 2022. To this end, a corpus of articles was compiled from the Times using Sketch Engine (https://www.sketchengine.eu/), in order to manage and investigate the corpus quantitatively; discourse and genre analyses were applied for the qualitative approach. After providing a definition of the coronavirus timespan and the term crisis, the paper explores how the language used changed over successive periods of crisis management and communication (Coombs 2010). It also shows how the unpredictable development of the pandemic had an effect on communication flows, which in turn affected how the crisis unfolded. Different types of information were conveyed through the media that played a crucial role in selecting what to convey (and what not to convey) to the readers and how to represent it. This significantly contributed (and continues to contribute) to the development of the readers’ opinions and sentiments, fuelling their worries and feelings of uncertainty, weakness and risk (Denti 2021; Wodak 2021). Future research will focus on metadiscursive features and the changes in rhetorical persuasion (Hyland 2005), and on the politicisation of the crisis (Musolff et al. 2022; Thielemann and Weiss 2023).

Use of animal fiber-reinforcement in construction materials: A review

Although natural fibers (NFs), among which animal fibers (AFs) are found, have been used for millennia as reinforcement scheme of some construction materials (CMs), it is not until recent decades when scientific studies have been carried out to quantitively evaluate the impact of adding NFs into CMs, but with a special focus on vegetal fibers (VFs) over AFs. Nevertheless, there have been several studies addressing the use of AFs in different CMs and, therefore, the need of a systematic review study is evident. To contribute to this research gap, this paper presents a comprehensive review study addressing available scientific information of different types of AFs (e.g., sheep wool fibers (SWFs), chicken feathers fibers (CFFs), human hair fibers (HHFs), pig hair fibers (PHFs), silk fibers (SFs), and dog hair fibers (DHFs)) and also their use in four specific different CMs matrices (i.e., cementitious, gypsum, soil and polymer matrices). This comprehensive search was conducted in Web of Science and Science Direct, two of the largest and more prestigious scientific databases, using specific keywords and Boolean operators and the selection of the papers was based on the provision of enough quantitative information of the mixtures (e.g., specific characteristic and dosages of AFs and matrix used) as well as experimental findings. As a result of this study, organized, summarized and sufficient information is provided to support the positive use of AF as reinforcement scheme to improve some physical/thermal/mechanical/damage/durability properties of CMs by taking advantage of the abundance of these resources worldwide. Moreover, the use of AFs might also provide environmental benefits and cost reductions, which are global objectives within the construction sector. Finally, this review study found that there are still several research gaps in the use of particular AFs (e.g., DHFs) as well as combinations between the AFs and the CMs addressed in this study (e.g., effects of PHFs in polymer matrices) and these gaps are recommended as future studies.

Integrating Knowledge Graphs into Distribution Grid Decision Support Systems

Distribution grids are complex networks containing multiple pieces of equipment. These components are interconnected, and each of them is described by various attributes. A knowledge graph is an interesting data format that represents pieces of information as nodes and relations between the pieces as edges. In this paper, we describe the proposed vocabulary used to build a distribution system knowledge graph. We identify the concepts used in such graphs and a set of relations to represent links between concepts. Both provide a semantically rich representation of a system. Additionally, we offer a few illustrative examples of how a distributed system knowledge graph can be utilized to gain more insight into the operations of the grid. We show a simplified analysis of how outages can influence customers based on their locations and how adding DERs can influence/change it. These demonstrative use cases show that the graph-based representation of a distribution grid allows for integrating information of different types and how such a repository can be efficiently utilized. Based on the experiments with distribution system knowledge graphs presented in this article, we postulate that graph-based representation enables a novel way of storing information about power grids and facilitates interactive methods for their visualization and analysis.

Corporate sustainability professionals: The landscape of sustainability job positions

AbstractSustainable development requires several stakeholders, including companies, to take action. For this, employees need to have their positions and sustainability roles defined so they can carry out activities. In turn, activities need alignment with corporate policies and strategy. However, the literature lacks discussion about job specifications and which activities relate to sustainability. Therefore, this article aims to explore the panorama of positions and professional activities of corporate sustainability professionals. To achieve this goal, we conducted a bibliometric assessment of terms related to corporate sustainability professionals and to understand what scholars have addressed in the area thus far. In the second stage, we tackle this problem by conducting a world survey of 143 professionals working in sustainability‐related positions. The methods are complementary because they provide different types of information that can be used to gain insights into research topics and trends. In this sense, this research contributes to the literature and practice in two main ways. First, the sustainability professionals' positions are still recent and under construction; few sustainability professionals are leaders. Second, this research identified that the sustainability professionals' actions focus on the environmental dimension, suggesting that companies have to invest more in social and governance dimensions. In addition, the findings evidence the need for more reporting on these dimensions as well as aligning all sustainability‐related policies, practices and activities with the strategy's company. Theoretical and practical implications, such as the need for more training on sustainability aspects, and the study's limitations are also addressed.

Reconfigurable MIMO antenna: previous advancements and the potential for future wireless communication

Abstract Future smart reconfigurable antennas (RAs) (Haupt R-L and Lanagan M (2013) Reconfigurable antennas. IEEE Antennas and Propagation Magazine 55, 49–61) will likely be fully multipurpose and controlled by software and equipped with machine learning skills that can discern and respond to alterations in the radio frequency environment. Cognitive radio utilizations will be accomplished using a new generation of antenna technology and communication protocols. The effective use of frequencies and the use of polarization diversity and radiation pattern reconfigurability to send data over existing congested frequencies will be major advantages for such applications. The usage of antennas that can be reconfigured in multiple-input multiple-output (MIMO) channels will enhance channel capacity while simultaneously improving channel efficiency and lowering costs (Christodoulou C-G, Tawk Y, Lane S-A and Erwin S-R (2012) Reconfigurable antennas for wireless and space applications. Proceedings of the IEEE 100, 2250–2261). There are a lot of antennas used both at the transmitter and at the receiver front end in a MIMO system. The benefit of employing such arrangements is that different types of information can be conveyed at a similar time, boosting the spectral efficiency of communication in a multipath situation. The coding rate, modulation level, and transmission signaling method of a MIMO system can all be changed in response to changing channel circumstances and user needs. In a MIMO context, polarization reconfigurable/frequency-reconfigurable/radiation pattern RA increase the degree of freedom and enhancing the system’s performance. The usage of such antennas greatly enhances capacity by enabling a choice of various polarization configurations and pattern diversity. Antenna arrays that can be reconfigured are also an appealing MIMO system solution that needs to retain robust communication channels, particularly in portable gadgets where the area is limited.

Analysis of Adverse Event Reports in FDA’s MAUDE Database

Background and Objective: Medical devices (MDs) play a pivotal role in the modern healthcare environment. Adverse events are an expected part of an MD’s lifecycle. To prevent the recurrence of such events, various vigilance systems have been established worldwide. The Manufacturer and User facility Device Experience (MAUDE) database of the US Food and Drug Administration (FDA) is a publicly accessible database that contains data of medical device reports (MDRs) submitted to FDA since 1991. The aim of this study is to examine the evolution of MD adverse event reports and analyze several characteristic parameters, as they evolved during the last three decades.
 Material and Methods: An analysis of MAUDE data was performed to examine the outcomes and device characteristics of adverse event reports from 1991 up to 11/2022. These outcomes included the event type, remedial action, report source, reporter occupation and device evaluation by manufacturer. Specific MD groups were analyzed separately to examine their effect on the event outcomes. Segregated files of the database that contain different types of information on adverse event reports were combined to investigate the various aspects of these reports.
 Results: Event outcomes are presented as annual histograms. An overall of about 15 million reports have been submitted to MAUDE during the 30 years period examined with more than 2.5 million of them during the first 10 months of the year 2022. This number is growing at an increasing rate. Most of the events (63.5%) have resulted in simple device malfunction, without serious implications to the patient. Depending on the device type however, the health risks may be higher (98.4% injuries from specific dental implants and 3.2% deaths from implantable defibrillators). About 20% of the reports have led to recalls or other corrective actions. Most of the reports (96%) are submitted by manufacturers and over 70% of the devices returned to them are evaluated, following the requirements of FDA 21 CFR, 803. The reporter’s occupation was found to be related to the types of devices associated with the event. Finally, the average device age was found to be 4 years, with an increasing tendency observed over the years, while still most of the events occur during the first year of operation.
 Conclusion: A medical device adverse event reporting system is a critical component of safety in the use of medical technology in modern healthcare. The information available in MAUDE and its use continues to grow at an accelerated rate and allows critical improvements of MDs, especially in terms of risk prevention, as it gives perception about their safety issues. FDA has taken various steps to encourage and facilitate adverse event reporting and make the data available to the public.

How legislators define research evidence

Background:Understanding how policymakers define research and differentiate it from other sources of data is critical for scientists to improve how they conduct and communicate research to policy audiences. Yet, few studies have explicitly asked policymakers – particularly state legislators in the USA – how they define research evidence. Methods:We sought to fill this gap via in-depth interviews with 168 policymakers from two Midwestern states; 32 of whom were nominated by their colleagues as exemplar research users. Findings were triangulated via interviews with experienced key informants from both states. In-depth interviews were the preferred methodology for our research question, as they offered legislators the chance to describe research in their own words and elaborate on examples when needed. Findings:For many legislators, definitions of research largely aligned with how the scientific community might define research; both Republicans and Democrats defined research as peer-reviewed studies with specific qualities that distinguish research evidence from other types of information. However, some legislators defined research with a broader lens, including different types of information (for example, anecdotes) and qualities of information (for example, accessibility, relevance, credibility, and unbiased) as part of their definition. Discussion and conclusions:Researchers may better engage policy audiences by referring to the types and qualities legislators mentioned because policymakers prefer evidence from rigorous studies to those that are poorly executed or politically motivated. Legislators called this ‘bogus’ research, ‘party’ research or ‘pseudoscience’. Researchers can signal their credibility by being transparent regarding funding sources and reasons or motivation for conducting studies.

HYDRO: Optimizing interactive hybrid images for digital signage content

In modern society, digital signage installed in many large-scale facilities supports our daily life. However, with a limited screen size, it is difficult to provide different types of information for many viewers at varying distances from the screen simultaneously. Therefore, in this study, we extend existing research on the use of hybrid images for tiled displays. To facilitate smoother information selection, a new interactive display method is proposed that incorporates a touchactivated widget as a high-frequency part of the hybrid image; these widgets are novel in that they are more visible to the viewers near to the display. We develop an authoring tool that we call the Hybrid Image Display Resolutions Optimizer (HYDRO); it features two kinds of control functions by which to optimize the visibility of the touch-activated widgets in terms of placement and resolution. The effectiveness of the present method is shown empirically via a quantitative user study and an eye-tracking-based qualitative evaluation.

Trajectory of MRI and FDG‐PET biomarkers in Alzheimer’s disease

AbstractBackgroundAlzheimer’s disease (AD) has a long preclinical phase, which is hypothesised to start with the accumulation of β‐amyloid (Aβ) plaques, followed by tau neurofibrillary tangles and neurodegeneration. Despite presenting quite different types of information, MRI‐derived volumetric measures and FDG‐PET‐derived metabolism are both commonly used as proxy of neurodegeneration in AD. The aim of this work is to assess the trajectory of both of these biomarkers in AD, relative to time to amyloid‐positivity.Method3289 MRI scans (682 participants) and 2472 FDG‐PET scans (1296 participants) were included from the ADNIGO, 1,2 and 3 cohorts. For MRI scans, total volume was calculated for a meta‐ROI consisting of entorhinal, inferior, middle temporal and fusiform gyri. For FDG‐PET, standardized uptake value ratios (SUVR) were calculated from 30‐60 min post injection for a meta‐ROI consisting of the angular, posterior cingulate and inferior temporal gyri, normalised to the pons. All metrices were transformed into z‐scores using the references values of the Aβ‐negative subjects. Age of amyloid‐positivity was determined by fitting a nonlinear mixed effects model to 3607 Centloid values corresponding to 1690 participants. Next, time to amyloid‐positivity was calculated for each scan. The relationship between time to amyloid‐positivity and (z‐scored) SUVR or cortical volume values was modelled using a non‐linear mixed effects model with spline function and trajectories from both modalities were compared.ResultsBaseline demographics can be found in Table 1. Figure 1 shows the trajectory of amyloid deposition that was used to determine age of amyloid‐positivity. Cortical volume and SUVR showed similar trajectories over time, with steeper decline in both measures after the event of amyloid‐positivity (Figure 2). The overlay of both biomarker trajectories shows that for the meta‐ROI, there is no difference in when these biomarkers become abnormal.ConclusionsThe present results suggest that measures of neurodegeneration from MRI and FDG‐PET scans corresponding to a meta‐ROI, follow very similar trajectories. Future work will investigate if this also holds true for smaller regions of interest.

Trajectory of MRI and FDG‐PET biomarkers in Alzheimer’s disease

AbstractBackgroundAlzheimer’s disease (AD) has a long preclinical phase, which is hypothesised to start with the accumulation of ß‐amyloid (Aß) plaques, followed by tau neurofibrillary tangles and neurodegeneration. Despite presenting quite different types of information, MRI‐derived volumetric measures and FDG‐PET‐derived metabolism are both commonly used as proxy of neurodegeneration in AD. The aim of this work is to assess the trajectory of both of these biomarkers in AD, relative to time to amyloid‐positivity.Method3289 MRI scans (682 participants) and 2472 FDG‐PET scans (1296 participants) were included from the ADNIGO, 1,2 and 3 cohorts. For MRI scans, total volume was calculated for a meta‐ROI consisting of entorhinal, inferior, middle temporal and fusiform gyri. For FDG‐PET, standardized uptake value ratios (SUVR) were calculated from 30‐60 min post injection for a meta‐ROI consisting of the angular, posterior cingulate and inferior temporal gyri, normalised to the pons. All metrices were transformed into z‐scores using the references values of the Aß‐negative subjects. Age of amyloid‐positivity was determined by fitting a nonlinear mixed effects model to 3607 Centloid values corresponding to 1690 participants. Next, time to amyloid‐positivity was calculated for each scan. The relationship between time to amyloid‐positivity and (z‐scored) SUVR or cortical volume values was modelled using a non‐linear mixed effects model with spline function and trajectories from both modalities were compared.ResultBaseline demographics can be found in Table 1. Figure 1 shows the trajectory of amyloid deposition that was used to determine age of amyloid‐positivity. Cortical volume and SUVR showed similar trajectories over time, with steeper decline in both measures after the event of amyloid‐positivity (Figure 2). The overlay of both biomarker trajectories shows that for the meta‐ROI, there is no difference in when these biomarkers become abnormal.ConclusionThe present results suggest that measures of neurodegeneration from MRI and FDG‐PET scans corresponding to a meta‐ROI, follow very similar trajectories. Future work will investigate if this also holds true for smaller regions of interest.

Identification, evolution and geological indications of solid bitumen in shales: A case study of the first member of Cretaceous Qingshankou Formation in Songliao Basin, NE China

On the basis of sorting out current understanding of solid bitumen (SB) in shales and taking organic-rich shales in the first member of the Cretaceous Qingshankou Formation in the Songliao Basin as an example, the definition, classification, occurrence and evolution path of SB are systemtically studied, and the indicative significance of SB reflectance (Rob) on maturity and its influence on the development of reservoir space are discussed and summarized. The results show that the difference of primary maceral types is primarily responsible for the different evolution paths of SB. Most of the pre-oil bitumen is in-situ SB with only a small amount being of migrated SB, while most of the post-oil bitumen and pyrobitumen are migrated SB. From the immature to early oil maturity stage, bituminite, vitrinite, and inertinite can be distinguished from SB based on their optical characteristics under reflected light, and alginite can be differentiated from SB by their fluorescence characteristics. Under scanning electron microscope, in-situ SB and migrated SB can be effectively identified. Rob increases linearly with increasing vitrinite reflectance (Ro), as a result of a decrease of aliphatic structure and the enhancement of aromatization of SB. Within the oil window three types of secondary pores may develop in SB, including modified mineral pores, devolatilization cracks and bubble holes. At a high maturity stage spongy pores may develop in pyrobitumen. Scanning electron microscopy combined with in-situ SEM-Raman spectroscopy can further reveal the structral information of different types of SB, thus providing crucial data for understanding for understanding OM migration paths, dynamics, and distances at micro-scale.

Digital Code as an Object Graphic Design for Dissemination and Promotion of Brand

Summary The article reveals the features of the graphic language of coded information by identifying, systematizing, and combining QR-codes and AR-codes at the present stage of graphic design development. The analysis of coded information in different types of graphic design is presented: advertising, environmental, motion, print, packaging, set prop, web, mobile app, art, and illustration graphic design. The role of a graphic designer in the development of digital codes of various types for various fields of application is described. It is proved that the coded information is a trigger between the online and offline worlds. The article also reveals the importance of using coded information for the formation, development, and improvement of the brand.

Biased beliefs about immigration and economic concerns: Evidence from representative experiments

We investigate the causal relationship between biased beliefs about immigrants and the host country's attitudes towards immigration. Using representative survey experiments with over 7000 respondents, we find substantial biases in respondents' beliefs about the immigrant population in several domains. Exposure to different types of information about immigrants reduces concerns about negative effects of immigration on the welfare state. On the contrary, different types of information offset their effects on concerns about increased competition in the labor market. Using a data-driven approach to uncover systematic heterogeneity in treatment effects, we find that prior beliefs about immigration and their distribution in the host country's population are crucial for the effectiveness of information interventions. We conclude that different distributions of beliefs therefore require appropriately targeted information policies.

Study on the influence of the information diffusion and vaccination behavior on disease transmission in multiplex networks

To investigate the influence of information diffusion and vaccination behavior on disease transmission. In this paper, a coupling model is proposed to describe the co-evolution process of information diffusion, vaccination behavior and disease transmission in multiplex network. In the information layer, two types of information are diffused, including the positive information and the negative information, respectively. During the process of information diffusion, the influence of mass media on information diffusion is considered, due to the herd effect, which type of information is believed to depend on the information state of the surrounding neighbors based on the Heaviside step function. In the behavioral layer, the individuals with different types of information will choose different immune behavioral responses, which in turn will influence the disease transmission. The coupling model was analyzed by using the Micro Markov Chain Approach (MMCA) to obtain state transition equations and the prevalence thresholds for disease. By simulating the simulation experiments, it demonstrates that the information diffusion has no direct effect on disease prevalence thresholds, but affects the proportion of infected; vaccination behavior has a significant effect on disease prevalence thresholds and also affects the proportion of infected. The results of the study suggest that when the disease transmission is within the controllable range, the stronger the diffusion of positive information, the higher the vaccination rate, which has a more positive influence on inhibiting disease transmission; once out of control, the official will lose trust, which is not conducive to disease control.

A Statistical Analysis of Sentiment over Different Social Platforms on Drug Usage across High, Middle and Low-Income Countries

Social media serves as a platform for sharing information and connecting with others on various subjects, including healthcare and drugs. Analyzing drug sentiment from various social media like Twitter, reddit, quora etc are crucial for monitoring drug safety, identifying adverse reactions, and providing an early warning system for potential safety concerns, benefiting healthcare organizations and governments. This paper aims to study the opinions of people from all over the world by analyzing their messages, posts on social media. For this study 39,069 drug related message corpus were fetched making a comparison between the high income countries, and middle income and low income countries on the basis of drug consumption from 2021 to 2023. The dataset used for the study consisted of 41.63% text-corpus from high income countries out of which on an average from 2021 to 2023, 40.2% was found to have a positive sentiment. Whereas 34.65% of text-corpus are from middle-income countries out of which on an average 26.4% of was of a positive sentiment and 23.70% text-corpus are from low income countries with 23.6% having a positive sentiment. Furthermore, the primary factor for having such differences from people’s sentiment on drug consumption from high to low income countries includes Cultural and Social Norms, Legalization, availability etc therefore, In high-income countries, drug use is more socially accepted than in other regions. This proposed study gives an insight into people’s opinion on various drugs from different countries and regions. The results of this study attempted to understand how the public is responding to different types of information and to identify potential misinformation which can be used to formulate policies for existing and future drug prevention campaigns in order to improve public health and promote public education.

The microstructure of intra- and interpersonal coordination.

Movements are naturally composed of submovements, i.e. recurrent speed pulses (2-3 Hz), possibly reflecting intermittent feedback-based motor adjustments. In visuomotor (unimanual) synchronization tasks, partners alternate submovements over time, indicating mutual coregulation. However, it is unclear whether submovement coordination is organized differently between and within individuals. Indeed, different types of information may be variably exploited for intrapersonal and interpersonal coordination. Participants performed a series of bimanual tasks alone or in pairs, with or without visual feedback (solo task only). We analysed the relative timing of submovements between their own hands or between their own hands and those of their partner. Distinct coordinative structures emerged at the submovement level depending on the relevance of visual feedback. Specifically, the relative timing of submovements (between partners/effectors) shifts from alternation to simultaneity and a mixture of both when coordination is achieved using vision (interpersonal), proprioception/efference-copy only (intrapersonal, without vision) or all information sources (intrapersonal, with vision), respectively. These results suggest that submovement coordination represents a behavioural proxy for the adaptive weighting of different sources of information within action-perception loops. In sum, the microstructure of movement reveals common principles governing the dynamics of sensorimotor control to achieve both intra- and interpersonal coordination.

Multi-heterogeneous Data Synchronization Method for New Generation Substation Monitoring System

In principle, the new generation substation monitoring system no longer has duplicate data collection across safety partitions. To avoid information islands between nodes of different safety partitions and to realize efficient interconnection and interoperability of different types of information, this paper proposes a multivariate heterogeneous data synchronization method for the new generation substation monitoring system. Firstly, the overall framework of the structured data synchronization method, synchronization data encapsulation modeling, cache format construction, and subgroup and group packet processing are introduced; secondly, the overall architecture of the unstructured data synchronization method is introduced, including full data updating and difference data updating, and the latter improves the efficiency of data chunking and achieves the incremental synchronization process of the difference by the fast CDC method based on the identification of the local difference; finally, the test validation is carried out based on the actual data for testing and validation. The results show that the multivariate heterogeneous data synchronization methods are 100% correct, and the incremental difference synchronization saves more than 70% of the synchronization time.

Automatic detection of surface defects based on deep random chains

Defect detection is critical in production systems. The traditional methods are primarily manual, prohibiting its large-scale industrial application. The current deep learning methods usually require a large amount of data, which is challenging in some cases. This paper presents a novel deep learning method to detect a large variety of defects based on small datasets only. Specifically, the method is based on the deep random chain combined with the adaptive Faster R-CNN. The idea behind this method is to fuse both common and different types of information among candidate groups to each defect candidate, which thus improves the model’s generalization for small sample datasets with a wide variety of defects. Indeed, the deep random chains focus on learning the relationship among the pixels inside each defect, while many features are added to each defect using Faster R-CNN. Several experiments on industrial products demonstrate the merit of the proposed method for small sample datasets with yet a wide variety of defects.