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To provide a dynamic perspective on the evolution of Mendeley readership, this study conducts an 8‐year longitudinal analysis of approximately 3.4 million scholarly papers published in 2015. Mendeley readership data were collected annually from 2016 to 2023 for the sampled papers to analyze the temporal accumulation patterns of readership following publication. The results indicate that Mendeley readership exhibits a speed advantage compared to citations and a prevalence advantage compared to Twitter mentions, demonstrating both initial prevalence and sustained growth on a yearly basis. However, the patterns of accumulation vary across disciplines, with papers in Biomedical and Health Sciences showing the fastest accrual of extensive Mendeley readership data. Leveraging demographic data provided by Mendeley, this study further investigates how different user groups—categorized by academic status, disciplinary affiliation, and geographic location—engage with papers across various disciplines. The findings highlight Mendeley readership as a rapid and substantial altmetric, yet they also emphasize the need to interpret the nature of the attention captured by Mendeley readership with caution, considering its potential biases introduced by the varying engagement levels of different user groups across disciplines. [ABSTRACT FROM AUTHOR]

The data paper is an emerging academic genre that focuses on the description of research data objects. However, there is a lack of empirical knowledge about this rising genre in quantitative science studies, particularly from the perspective of its linguistic features. To fill this gap, this research aims to offer a first quantitative examination of which rhetorical moves—rhetorical units performing a coherent narrative function—are used in data paper abstracts, as well as how these moves are used. To this end, we developed a new classification scheme for rhetorical moves in data paper abstracts by expanding a well‐received system that focuses on English‐language research article abstracts. We used this expanded scheme to classify and analyze rhetorical moves used in two flagship data journals, Scientific Data and Data in Brief. We found that data papers exhibit a combination of introduction, method, results, and discussion‐ and data‐oriented moves and that the usage differences between the journals can be largely explained by journal policies concerning abstract and paper structure. This research offers a novel examination of how the data paper, a data‐oriented knowledge representation, is composed, which greatly contributes to a deeper understanding of research data and its publication in the scholarly communication system. [ABSTRACT FROM AUTHOR]

Over the past few years, the emergence of electrochemical wearable sensors has attracted considerable attention because of their promising application in point‐of‐care testing due to some features such as high sensitivity, simplicity, miniaturization, and low fabrication cost. Recent developments in new fabrication approaches and innovative substrates have resulted in sensors able to real‐time and on‐body measurements. Wearable electrochemical sensors have also been combined with paper‐based substrates and directly used on human skin for different applications for non‐invasive analyses. Furthermore, wearable electrochemical sensors enable monitoring analytes in different biofluids without complex procedures, such as pre‐treatment or sample manipulation. The coupling of IoT to various wearable sensors has also attracted attention due to real‐time data collection and handling in remote and resource‐limited conditions. This mini‐review presents the significant advances in developing wearable electrochemical devices, such as sampling, data collection, connection protocols, and power sources, and discusses some critical challenges for higher performance in this field. We also present an overview of the application of paper as an intelligent substrate for electrochemical wearable sensors and discuss their advantages and drawbacks. Lastly, conclude by highlighting the future advances in wearable sensors and diagnostics by coupling real‐time and on‐body measurements to multiplexed detection of different biomarkers simultaneously, reducing the cost and time of classical analysis to provide fast and complete overall physiological conditions to the wearer. [ABSTRACT FROM AUTHOR]

Ocean research currently relies heavily on bulky bioelectronic tags and sensory telemetry networks for data collection. Therefore, in this study, a compact and flexible waterproof bioelectronic tag with a kirigami (paper cutting)‐based design for underwater conductivity, temperature, depth, and strain sensing is designed and evaluated. Unlike invasive bioelectronic tags, the kirigami bioelectronic tag can be attached to robotic fish or aquatic animals without harming the host. The kirigami‐based design facilitates excellent stretchability and reduces stress within the sensor, thus inhibiting crosstalk induced by movement during multimodal sensing. A working bioelectronic tag is fabricated and tested. Notably, the performance of the kirigami sensors shows very little degradation even after >1000 stretching cycles. Specifically, the multimodal bioelectronic tag demonstrates a wide working pressure range of 0–5.0 MPa, and the kirigami design effectively suppresses signal coupling. The kirigami‐based bioelectronic tag is applied to a robotic dolphin and underwater environmental parameters and detailed movement parameters, such as swing angle, swing frequency, and typical gestures are detected simultaneously with high sensitivity and accuracy. Therefore, the device can be applied to a broad range of applications in various fields such as behavioral biology, ocean informatics, and underwater robotics. [ABSTRACT FROM AUTHOR]

In this paper, we propose a method of generating the elemental image array (EIA) for the integral imaging (InIm) based light field display (LFD). Firstly, we reveal the intrinsic voxel spatial distributions of the InIm‐based LFD and analyze how the voxel space affects the display performances such as spatial resolution, depth of field, and smoothness of parallax. Then, we present an algorithm to generate an EIA from a pair of RGB and depth (RGBD) images and an optimally selected voxel space. In the experiments, we tested the display performances of the voxels on different depth planes and obtained results consistent with the theoretical analyses. We also experimented with a computer 3D model and a real‐world scene on two InIm‐based LFD prototypes working in different modes, one in real mode and the other in virtual mode, and obtained favorable 3D display effects. The proposed method simplifies the light field data acquisition and image synthesis process, and supports handling both the virtual and the real‐world 3D scenes. We expect the proposed system to help the practical application of the InIm‐based LFD technology. [ABSTRACT FROM AUTHOR]

This study examined home country bias in the New England Journal of Medicine (NEJM). Bibliographic information of publications in the NEJM from 2000 to 2019 was collected as data. Bibliometric analyses were performed to investigate the number of papers with one or more US‐based authors in the NEJM and compare this to other journals. Citation counts of US‐based and non‐US papers were calculated and compared. The results show that US‐based papers account for 65.44% of the NEJM papers, and the US share of the NEJM papers has remained stable in the examined years whereas in other journals the percentage decreased. More importantly, US‐based papers in the NEJM display significantly lower research impact compared with non‐US papers. The results suggest that US‐based papers are favoured by the NEJM and a home country bias may exist in the publication process of the journal. [ABSTRACT FROM AUTHOR]

The collection and use of data on climate change and its impacts are crucial for effective climate adaptation and climate risk management. The revolution in internet access, technology and costs has led to a shift from using traditional paper‐based data collection to the use of Mobile Data Collection using Personal Digital Assistants (PDA) such as smartphones and tablets. In this paper, we report our experiences using both approaches for a household and business survey during a climate adaptation study in two Nigerian cities—Makurdi and Calabar. The focus of this paper is to evaluate and compare the effectiveness of using traditional paper‐based data collection and PDAs as data collection tools for climate change study in African societies. In Calabar, data were collected using paper questionnaires, while in Makurdi the questionnaires were developed on Open Data Kit (ODK) and administered using PDAs. Results show that data collection using PDA was faster, cheaper, more accurate and resulted in fewer omissions than paper‐based data collection. There was a time saving of four (4) minutes per questionnaire and a 24% cost saving when using PDA. PDA provides additional benefits where platforms can collect images, videos and coordinates. This significantly improved the credibility of the data collection process and provided further data that allowed for the mapping of environmental phenomena by linking survey research with geo‐referenced data in a geographic information systems platform to provide spatial representations of social and environmental system convergence. PDA offers a tool for collecting data that will make necessary socio‐environmental data available in a faster, reliable and cheaper manner; future research can build on this study by discovering other possible but less highlighted benefits of PDA. Although, with great benefits, there are lessons to be learnt and issues to consider when deploying PDA in large‐scale household surveys. [ABSTRACT FROM AUTHOR]

Background Paper food and gastrointestinal ( GI) symptom journals are used to help irritable bowel syndrome ( IBS) patients determine potential trigger foods. The primary aim of this study was to evaluate the feasibility, usability, and clinical utility of such journals as a data collection tool. A secondary aim was to explore a method for analyzing journal data to describe patterns of diet and symptoms. Methods Participants (N=17) were asked to log three sets of 3-day food and symptom journals over a 15-day period. Feasibility was evaluated by journal completion rates, symptom logging compliance, and logging fatigability. The feasibility, usability, and clinical utility of journaling were also assessed by a customized evaluation and exit interview. For each journal, regression analyses were conducted to examine relationships between key meal nutrients and subsequent symptoms. Key Results Most participants were young (mean age 35±12) Caucasian (N=13) women (N=14). Journal completion rates were 100% for all participants with no logging fatigability. Over half perceived paper journaling of food and symptoms as feasible, usable, and clinically useful. Thirteen participants demonstrated a strong association with at least one symptom and meal nutrient. Patterns of associations differed among participants. Conclusions and Inferences Paper journaling of food and GI symptoms for 9 days over a 15-day period appeared to be a feasible and usable data collection tool for IBS patients. Over half perceived journaling as at least somewhat clinically useful. Findings from this study support the anecdote that food trigger(s) and associated symptom(s) vary for each individual. [ABSTRACT FROM AUTHOR]

Background: Methodological problems have impeded successful epidemiological research into disorders of gut‐brain interactions (DGBI), as previous studies were limited in terms of study population, diagnostic criteria, number of disorders assessed, data collection methods, and geographic area. Most prevalence estimates were based on pooling data from heterogeneous studies using inappropriate pooling methods, seriously limiting the relevance of the results. The Rome Foundatiion Global Epidemiology Study (RFGES) aimed to rectify these limitations using rigorous methodology to survey the prevalence of 22 DGBI in large population samples in 33 countries. Its aims were to conduct a comprehensive, multinational epidemiological study using rigorous research methodology, gain a better understanding of the burden of the DGBI, gain reliable regional estimates of DGBI prevalence, and advance our understanding of the pathophysiology of IBS. The study questionnaire consisted of the 89‐item Rome IV Adult Diagnostic Questionnaire enabling the diagnosis of 22 DGBI, and an 80‐item supplemental questionnaire that enabled analyses of the association of multiple factors with DGBI diagnoses. Purpose for review article: This review paper introduces a special issue on the Rome Foundation Global Epidemiology study (RFGES) with a narrative description of its conception, development, and implementation, its outcomes to date, and its potential contribution to neurogastroenterology. It includes 15 papers that reflect the range of RFGES studies from single country papers to intra‐regional studies, to inter‐regional studies, and one global study. [ABSTRACT FROM AUTHOR]

Recently, deep learning (DL) based dynamic security assessment (DSA) methods have been very successful. However, although a DSA model can be trained well for a specific topology, it often does not perform well for other topologies. Since the topology in real‐world power systems is frequently changing, the performance reduction of DL‐based DSA methods is very serious, which is a challenging and urgent problem. This paper proposes a novel DSA method based on a convolutional neural network (CNN) to solve this problem. In the proposed method, a strong yet simple domain adaptation approach named adaptive batch normalization (AdaBN) is used, which significantly enhances the extensibility and generalizability of the DSA model when the topology changes and eliminates the need to train a large number of models. This approach achieves a deep adaptation effect by modulating the statistics from the source domain to the target domain in all batch normalization layers across the model. Unlike other domain adaptation methods, this method is parameter‐free, requires no additional components, and has advanced performance despite its simplicity. In addition, this paper introduces TGAN‐based data augmentation to deal with the difficulty of costly data collection and labelling. This data augmentation makes the proposed model applicable to small databases. The test results of the proposed method on IEEE 39‐bus and IEEE 118‐bus systems show that this method can evaluate system dynamic security during topology changes and in the face of data noise with high accuracy. [ABSTRACT FROM AUTHOR]

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Background and Aims: The Rome Foundation Global Epidemiology Study (RFGES) assessed the prevalence, burden, and associated factors of Disorders of Gut–Brain Interaction (DGBI) in 33 countries around the world. Achieving worldwide sampling necessitated use of two different surveying methods: In‐person household interviews (9 countries) and Internet surveys (26 countries). Two countries, China and Turkey, were surveyed with both methods. This paper examines the differences in the survey results with the two methods, as well as likely reasons for those differences. Methods: The two RFGES survey methods are described in detail, and differences in DGBI findings summarized for household versus Internet surveys globally, and in more detail for China and Turkey. Logistic regression analysis was used to elucidate factors contributing to these differences. Results: Overall, DGBI were only half as prevalent when assessed with household vs Internet surveys. Similar patterns of methodology‐related DGBI differences were seen within both China and Turkey, but prevalence differences between the survey methods were dramatically larger in Turkey. No clear reasons for outcome differences by survey method were identified, although greater relative reduction in bowel and anorectal versus upper gastrointestinal disorders when household versus Internet surveying was used suggests an inhibiting influence of social sensitivity. Conclusions: The findings strongly indicate that besides affecting data quality, manpower needs and data collection time and costs, the choice of survey method is a substantial determinant of symptom reporting and DGBI prevalence outcomes. This has important implications for future DGBI research and epidemiological research more broadly. [ABSTRACT FROM AUTHOR]

Background: Liver disease is an increasing cause of morbidity and mortality in the United Kingdom and can be challenging to live with in the advanced stages. There has been little research exploring the healthcare experiences of UK individuals with decompensated disease when the liver cannot carry out its functions properly. A PhD research project was developed with people who have liver disease to explore care experiences in decompensated advanced liver disease. Public involvement (PI) is an essential aspect of meaningful health research, and this paper reports on the progression of our PI approach in this ongoing study. Objective: To embed PI throughout the research project to ensure that the study is meaningful to individuals with liver disease and the people who support them. Methods: The research adopts a Constructivist Grounded Theory methodology to develop a theory of care experience. Various PI approaches were considered in developing the PI strategy for this qualitative study. Initially, Embedded consultation was the preferred model, which has evolved to include aspects of collaboration and coproduction. A PI group was set up to oversee the project through the national public engagement website VOICE, and reflections on PI from three members of the group are included in this paper to illuminate the PI process. Results: Six individuals with liver disease and three carers from across the United Kingdom are part of an ongoing PI group. Their role includes commenting on the findings of the systematic literature review for this project and contributing to decisions about recruitment, data collection and data analysis. Additionally, they had a direct impact on changing the focus of the research. The PI group will continue involvement until the completion of the project. Conclusion: Successfully embedding PI into doctoral research, as demonstrated in this project, requires commitment, planning and dedication to reciprocal working for the benefit of PI contributors as well as the research. This approach could be adopted by other postgraduate researchers. Patient or Public Contribution: This project is overseen by the PI group, whose contribution is described throughout, including reflections from three PI group members. [ABSTRACT FROM AUTHOR]

Background Existing tools for rapid cognitive assessment in HIV-positive individuals with mild cognitive deficits lack sensitivity or do not meet psychometric requirements for tracking changes in cognitive ability over time. Methods Seventy-five nondemented HIV-positive patients were evaluated with the Montreal Cognitive Assessment (MoCA), a brief battery of standardized neuropsychological tests, and computerized tasks evaluating frontal-executive function and processing speed. Rasch analyses were applied to the MoCA data set and subsequently to the full set of data from all tests. Results The MoCA was found to adequately measure cognitive ability as a single, global construct in this HIV-positive cohort, although it showed poorer precision for measuring patients of higher ability. Combining the additional tests with the MoCA resulted in a battery with better psychometric properties that also better targeted the range of abilities in this cohort. Conclusion This application of modern test development techniques shows a path towards a quick, quantitative, global approach to cognitive assessment with promise both for initial detection and for longitudinal follow-up of cognitive impairment in patients with HIV infection. [ABSTRACT FROM AUTHOR]

Given the popularity of Big Data (BD), there can be an impression that fields such as design of experiments (DOE) are now irrelevant. We would like to thank the authors for starting the conversation about the possible relationship between these two fields. A key contribution of this paper is in showing how DOE principles, as summarized under the name designed data collection (DDC), can be applied throughout the BD process. This name is quite appropriate, demonstrating that these principles apply not just to designed experiments, but to any form of data collection. This is especially important for situations where designed experiments are either impossible (i.e., assessing how a country's economy may impact certain responses) or unethical (i.e., certain sensitive types of medical studies). It shows that DOE is more than a particular choice of design type, but is rather a methodology for approaching data collection. One that seeks to extract the most relevant information from the data while also taking into account the various nuances and constraints of physical and social processes, which are ever present, even in massive datasets. The paper divides BD efforts into three general phases: Before BD, During BD, and After BD. As such, we have grouped our discussion accordingly, with general comments provided for the suggested contributions of DDC in each phase. We then close with some additional thoughts. [ABSTRACT FROM AUTHOR]

This paper investigates the unmanned aerial vehicle (UAV)‐assisted wireless communication network that collects the data information of Internet of things (IoT) devices deployed in the region, where the cellular networks cannot cover. Due to the numerous variety and number of IoT devices, a large amount of data generated by IoT networks needs to be collected by UAV. The goal of this paper is to minimize the UAV's cruise time with the joint optimization of IoT devices communication scheduling, UAV trajectory, and transmit bandwidth allocation. To facilitate data collection by UAVs, the data‐distance‐k‐means (d2‐k‐means) algorithm is proposed to divide IoT devices into multiple initial clusters. However, the formulated problem is mixed‐integer joint non‐convex, so it is difficult to solve directly. Since it may be with relatively high computational complexity, as an alternative, a block coordinate descent (BCD)‐based method is designed. To tackle the non‐convex problem, a successive convex approximation (SCA)‐based algorithm is also proposed. Numerical results demonstrate that the proposed scheme is able to achieve significant performance over other schemes for scenarios of UAV‐assisted wireless IoT networks to collect massive amount of data. [ABSTRACT FROM AUTHOR]

Due to the ever‐increasing number of computer nodes in distributed systems, efficient and effective tools have become crucial for their analysis. Although several efficient methods have been proposed to monitor and profile distributed systems, tracing remains the most effective solution for in‐depth system analysis. Tracing is the act of collecting a trace, which is a sequence of low‐level events generated by the kernel or the userspace. After data collection, the most important part is the event analysis. The paradigm and choice of graphs determine the ability of the user to detect abnormal behaviors and identify their root cause. Although tracing is a highly effective approach to analyzing complex systems, the scalability of the current analysis tools is limited. As a consequence, tracing is often impractical for large distributed systems. This paper identifies the shortcomings of the current approaches, most notably the critical path computation and the trace file transfer between nodes. Then, this paper proposes new solutions to these drawbacks, most notably a distributed algorithm to compute the critical path, that does not aggregate all traces in a single node, and an efficient architecture to perform tracing on distributed systems. These new solutions are made publically available. [ABSTRACT FROM AUTHOR]

Introduction: Given the diversity of the scope for inquiry and methodologies used in nursing research, the synthesis of primary research may not be as straightforward as conducting a meta‐analysis or systematic review on clinical trials. Scoping reviews offer an option to nursing academics for inquiries involving a range of applications and interpretations. Given the continual advances in evidence‐based research, it is, therefore, crucial for nursing to constantly substantiate its research capabilities and uphold standards in its research inquiry. Accordingly, an updated overview would be timely to characterize scoping reviews in the nursing literature. Hence this review aimed to examine the characteristics of scoping reviews published in nursing journals and evaluate the methodological and reporting quality of the scoping reviews. Design: A systematic review. Methods: A comprehensive search of three electronic databases (PubMed, CINAHL, and Embase) were conducted. Scoping reviews published in English on or before December 31, 2020 were included, with the criterion that their publication had been in nursing journals indexed in the Journal Citation Reports (2020 Science Edition) of the Web of Science. Two reviewers independently screened the titles and abstracts for eligibility. A standardized data extraction form was used for data collection, and a 29‐item checklist was developed to assess the methodological and reporting quality of the scoping reviews. The methodological and reporting quality was assessed independently by four reviewers and subsequently counter‐checked by another two reviewers. Descriptive statistics were used to characterize the included papers, and narrative synthesis was undertaken to explain the results. Results: This review included 422 papers from 88 nursing journals. They were published between 2008 and 2021 (median year 2019). Only 15 (3.5%) reviews reported accessible protocols, and 63 (15.0%) presented data on their critical appraisal of the included sources of evidence. Poor reporting of the selection of sources of evidence and data extraction was also identified. Overall, the 422 included reviews had complied with 20 (median [range: 9–27]) of the 29 items on the checklist. Conclusions: Scoping reviews have garnered wider acceptance in nursing research, of which the scopes and methodologies exhibit much diversity. Our systematic review has provided insights into existing scoping reviews published in nursing journals through our characterization of them and appraisal of their methodological and reporting quality. However, our findings underline several areas needing improvement: the lack of transparency, the absence of critical appraisal, non‐compliance to established checklists, and inconsistencies in the data processing. Clinical Relevance: Appraising included sources of evidence and maintaining transparency in the conduct and reporting of scoping reviews increases the practical utility of scoping reviews. [ABSTRACT FROM AUTHOR]

In recent years, China's advanced light sources have entered a period of rapid construction and development. As modern X-ray detectors and data acquisition technologies advance, these facilities are expected to generate massive volumes of data annually, presenting significant challenges in data management and utilization. These challenges encompass data storage, metadata handling, data transfer and user data access. In response, the Data Organization Management Access Software (DOMAS) has been designed as a framework to address these issues. DOMAS encapsulates four fundamental modules of data management software, including metadata catalogue, metadata acquisition, data transfer and data service. For light source facilities, building a data management system only requires parameter configuration and minimal code development within DOMAS. This paper firstly discusses the development of advanced light sources in China and the associated demands and challenges in data management, prompting a reconsideration of data management software framework design. It then outlines the architecture of the framework, detailing its components and functions. Lastly, it highlights the application progress and effectiveness of DOMAS when deployed for the High Energy Photon Source (HEPS) and Beijing Synchrotron Radiation Facility (BSRF). [ABSTRACT FROM AUTHOR]

Computer-assisted data collection offers advantages over traditional paper and pencil measures; however, little guidance is available regarding the logistics of conducting computer-assisted data collection with adolescents in group settings. To address this gap, we draw on our experiences conducting a multi-site longitudinal study of adolescent development. Structured questionnaires programmed on laptop computers using Audio Computer Assisted Self-Interviewing (ACASI) were administered to groups of adolescents in community-based and afterschool programs. Although implementing ACASI required additional work before entering the field, we benefited from reduced data processing time, high data quality, and high levels of youth motivation. Preliminary findings from an ethnically diverse sample of 265 youth indicate favorable perceptions of using ACASI. Using our experiences as a case study, we provide recommendations on selecting an appropriate data collection device (including hardware and software), preparing and testing the ACASI, conducting data collection in the field, and managing data. [ABSTRACT FROM AUTHOR]

In many research studies, multiple objectives need to be considered simultaneously to ensure an effective and efficient investigation. A compound optimal design provides a viable solution to this problem, allowing for the maximization of overall benefits through the integration of several factors. The paper addresses the application of compound optimal designs in the context of progressive first‐failure censoring, with a particular focus on the Generalized Exponential distribution with two parameters. The paper provides an illustrative example of compound designs by considering the cost function along with trace, variance, and determinant of inverse Fisher information. The best design is determined using a graphical solution technique that is both comprehensible and precise. Using a simple example, we demonstrate the advantage of compound optimal designs over constraint optimal designs. Furthermore, the paper examines real‐world data collection to demonstrate the practical utility of compound optimal designs. [ABSTRACT FROM AUTHOR]

Background: Motion induced image artifacts have been the focus of many investigations for x‐ray computed tomography (CT). Methodologies of combating patient motion include the use of gating devices to optimize the data acquisition, reduction in patient scan time via faster gantry rotation and large detector coverage, and the development of advanced reconstruction and post‐processing algorithms to minimize motion artifacts. Purpose: Previously proposed approaches are generally "global" in nature in that motion is characterized for the entire image. It is well known, however, that the presence of motion artifact in a CT image is highly nonuniform. When there is a lack of automated and quantitative local measure indicating the presence and the severity of motion artifacts in a local region, the quality of the reconstructed images depends heavily on the CT operator's rigor and experience. Even when an operator is informed of the presence of motion, little information is provided about the nature of the motion artifact to understand its relevance to the clinical task at hand. In this paper, we propose an image‐space spatial‐ and temporal‐consistency metric (CM) to detect and characterize the local motion. Method: In a non‐rigid human organ, such as the lung, there are many small and rigid objects (target objects), such as blood vessels and nodules, distributed throughout the organ. If motion can be characterized for these target objects, we obtain a complete motion map for the organ. To accomplish this, a preliminary image reconstruction is carried out to identify the target objects and establish region‐of‐interests for consistency‐metric calculation. The CM is then obtained based on the backprojected intensity difference between the object region and its circular background. For a stationary object, the accumulation of this quantity over views is linear. When a target object moves, nonlinear behavior exhibits and a quantitative measure of linearity indicates the severity of motion. Results: Extensive computer simulation was utilized to confirm the validity of the theory. These tests stress the sensitivity of the proposed CM to the target object size, object shape, in‐plane motion, cross‐plane motion, cone‐beam effect, and complex background. Results confirm that the proposed approach is robust under different testing conditions. The proposed CM is further validated using a cardiac scan of a swine, and the proposed CM correlates well with the visual inspection of the artifact in the reconstructed images. Conclusions: In this paper, we have demonstrated the efficacy of the proposed CM for motion detection. Unlike previously proposed approaches where the consistency condition is derived for the entire image or the entire imaging volume, the proposed metric is well localized so that different zones in a patient anatomy can be individually characterized. In addition, the proposed CM provides a quantitative measure on a view‐by‐view basis so that the severity of motion is consistently estimated over time. Such information can be used to optimize the image reconstruction process and minimize the motion artifact. [ABSTRACT FROM AUTHOR]

Aim: Evidence shows that 20%–30% of patients who aspirate do so silently. Research to date has not demonstrated clear evidence to indicate which patients are at higher risk of silent aspiration. Our aim was to use univariate logistic regression analysis of retrospective case review to determine potential patterns of silent aspiration. Materials and methods: We conducted a retrospective analysis of 455 fiberoptic endoscopic evaluation of swallowing (FEES) reports. The patients were divided into four groups: G1 – neurological diseases (n = 93), G2 – head and neck surgery (n = 200), G3 – gastroenterological diseases (n = 94) and G4 – other patients (n = 68). Data included the occurrence or absence of saliva penetration or aspiration, of silent fluid/solid food penetration or aspiration, type of penetration or aspiration, occurrence of cranial nerve paresis, radiotherapy and tracheostomy. Univariate logistic regression was used to evaluate independent risk factors of silent aspiration in the study population. Three models with different independent variables were considered. Results: There is a statistically significant difference in the frequency of occurrence of silent penetration and aspiration within the groups (p < 0.001), with intraglutative being most frequent. Fluid and food penetration and aspiration correlated with saliva penetration and aspiration in all groups (p < 0.001). Cranial nerve paresis (IX and X), radiotherapy and tracheostomy correlate with saliva penetration and aspiration (p = 0.020 for cranial nerve paresis; p = 0.004 for radiotherapy; p < 0.001 for tracheostomy). One hundred and fifteen patients (45.81%) in the subgroup of patients with intraglutative aspiration had cranial nerve paresis (IX, X or IX–X). Conclusions: Patients who should be prioritised or considered to be at a higher need of instrumental swallowing evaluation are those with IX and X cranial nerve paresis, tracheostomy and those who have had radiotherapy, with saliva swallowing problems, especially after paraganglioma, thyroid and parathyroid glands and middle and posterior fossa tumour surgery. WHAT THIS PAPER ADDS: What is already known on the subject: Clinical signs of penetration or aspiration include coughing, throat clearing and voice changes, while silent penetration or aspiration patients aspirate without demonstrating any clinical symptoms. The most common consequences of silent aspiration include aspiration pneumonia, recurrent lower respiratory tract infections and respiratory failure. Additionally, malnutrition and dehydration can be indicators of silent aspiration. Patients may unknowingly reduce their oral intake and lose weight. Retrospective studies have shown that 20%–30% of patients aspirate silently (e.g. patients after stroke, acquired brain injury, head and neck cancer treatment, prolonged intubation). Clinical examination of swallowing can miss up to 50% of cases of silent aspiration. What this paper adds to existing knowledge: Currently, silent aspiration is often discussed in neurological literature, but its applications to head and neck surgery are limited. In this study, we identify head and neck surgery patients who should be prioritised or considered to be in higher need of instrumental swallowing evaluation due to a higher risk of silent aspiration. What are the potential or actual clinical implications of this work?: Post‐treatment structural changes can result in lower cranial nerve paresis (IX, X, XII) and face injury, in which vagus and glossopharyngeal nerves are injured. After tracheostomy and radiotherapy, patients with problems swallowing saliva need careful clinical examination, particularly cranial nerve examination. [ABSTRACT FROM AUTHOR]

High-data-throughput and multimodal-acquisition experiments will prevail in next-generation synchrotron beamlines. Orchestrating dataflow pipelines connecting the data acquisition, processing, visualization and storage ends are becoming increasingly complex and essential for enhancing beamline performance. Mamba Data Worker (MDW) has been developed to address the data challenges for the forthcoming High Energy Photon Source (HEPS). It is an important component of the Mamba experimental control and data acquisition software ecosystem, which enables fast data acquisition and transmission, dynamic configuration of data processing pipelines, data multiplex in streaming, and customized data and metadata assembly. This paper presents the architecture and development plan of MDW, outlines the essential technologies involved, and illustrates its current application at the Beijing Synchrotron Radiation Facility (BSRF). [ABSTRACT FROM AUTHOR]

This paper addresses methodological approaches to comparative urban geography and the consequences of such approaches. It demonstrates three ways by which an imaginative comparison can be constructed and employed: letting the sites speak to one another, repeated instance analysis, and tracing. Successfully employing these methods requires adopting comparison as both an implicit ethos and explicit approach during data collection and analysis, answering "why is it different here?" Reflecting on the impact of utilising comparative approaches, I argue that comparative urbanism helps balance the unique and ubiquitous conclusions from research, and forces researchers to question the norms or assumptions they hold from doing singular case study research, which in turn foregrounds the situational nature of urban governance in analysis. In the specifics of this paper, it also helps uncover assumptions around the power of state and reveals (some) global elite urban networks. This paper addresses methodological approaches to comparative urban geography and the consequences of such approaches. It demonstrates three ways by which an imaginative comparison can be constructed and employed: letting the sites speak to one another, repeated instance analysis, and tracing. Successfully employing these methods requires adopting comparison as both an implicit ethos and explicit approach during data collection and analysis, answering "why is it different here?" [ABSTRACT FROM AUTHOR]

Motivation: Home range is a common measure of use of space by animals because it provides ecological information that is useful for conservation applications. In macroecological studies, values are typically aggregated to species means to examine general patterns of use of space by animals. However, this ignores the environmental context in which the home range was estimated and does not account for intraspecific variation in home range size. In addition, the focus of macroecological studies on home ranges has historically been biased towards terrestrial mammals. The use of aggregated numbers and the terrestrial focus limit our ability to examine home‐range patterns across different environments, their variation in time and variation between different levels of organization. Here, we introduce HomeRange, a global database with 75,611 home‐range values across 960 different species of mammals, including terrestrial, aquatic and aerial species. Main types of variables contained: The dataset contains estimates of home ranges of mammals, species names, methodological information on data collection, method of home‐range estimation, period of data collection, study coordinates and name of location, in addition to species traits derived from the studies, such as body mass, life stage, reproductive status and locomotor habit. Spatial location and grain: The collected data are distributed globally. Across studies, the spatial accuracy varies, with the coarsest resolution being 1°. Time period and grain: The data represent information published between 1939 and 2022. Across studies, the temporal accuracy varies; some studies report start and end dates specific to the day, whereas for other studies only the month or year is reported. Major taxa and level of measurement: Mammalian species from 24 of the 27 different taxonomic orders. Home‐range estimates range from individual‐level values to population‐level averages. Software format: Data are supplied as a comma‐delimited text file (.csv) and can be loaded directly into R using the "HomeRange" R package (https://github.com/SHoeks/HomeRange). [ABSTRACT FROM AUTHOR]

The rapid expansion of low‐voltage distributed photovoltaic (PV) systems with decentralized layouts poses significant data collection challenges. The scarcity of data amplifies prediction complexities, affecting the operational security and stability of distribution networks. To enhance predictive accuracy for distributed regional PV power generation, including unmonitored low‐voltage systems, this paper proposes a novel prediction approach that combines weight optimization and transfer learning. Firstly, to more accurately extrapolate from neighbouring monitored PV to estimate unmonitored PV outputs, a novel SSA‐MLP‐XGBoost model is proposed for monitored PV power plants, in which the hyperparameters of multilayer perceptron (MLP) and (extreme gradient boosting) XGBoost models are fine‐tuned using the sparrow search algorithm (SSA), and the optimized models are synergistically integrated to heighten prediction precision for monitored plants. Secondly, based on the predicted power curves of monitored PV power plants, a weight optimization model is presented to optimize the combined weights between unmonitored and monitored power stations. Furthermore, the power generation model from monitored facilities is transplanted to unmonitored plants for power generation estimation. Ultimately, the authors combine the weight optimization and transfer learning model to get more accurate and robust model. Validation across three regional distributed photovoltaic clusters demonstrates a noteworthy improvement in prediction accuracy—20%, 7.5%, and 25% for the respective clusters compared to the existing methods. [ABSTRACT FROM AUTHOR]

Crowd‐based hydrological observations can supplement existing monitoring networks and allow data collection in regions where otherwise no data would be available. In the citizen science project CrowdWater, repeated water level observations using a virtual staff gauge approach result in time series of water level classes (WL‐classes). To investigate the quality of these observations, we compared the WL‐class data with "real" (i.e., measured) water levels from the same stream at a nearby gauging station. We did this for nine locations where citizen scientists reported multiple observations using a smartphone app and at 12 locations where signposts were set up to ask citizens to record observations on a paper form that could be left in a letterbox. The results indicate that the quality of the data collected with the app was better than for the forms. A possible explanation is that for each app location, a single person submitted the vast majority of the observations, whereas at the locations of the forms almost every observation was made by a different person. On average, there were more contributions between May and September than during the other months. Observations were submitted for a range of flow conditions, with a higher fraction of high flow observations for the locations were data were collected with the app. Overall, the results are encouraging for citizen science approaches in hydrology and demonstrate that the smartphone application and the virtual staff gauge are a promising approach for crowd‐based water level class observations. [ABSTRACT FROM AUTHOR]

Research data management (RDM) is needed to assist experimental advances and data collection in the chemical sciences. Many funders require RDM because experiments are often paid for by taxpayers and the resulting data should be deposited sustainably for posterity. However, paper notebooks are still common in laboratories and research data is often stored in proprietary and/or dead‐end file formats without experimental context. Data must mature beyond a mere supplement to a research paper. Electronic lab notebooks (ELN) and laboratory information management systems (LIMS) allow researchers to manage data better and they simplify research and publication. Thus, an agreement is needed on minimum information standards for data handling to support structured approaches to data reporting. As digitalization becomes part of curricular teaching, future generations of digital native chemists will embrace RDM and ELN as an organic part of their research. [ABSTRACT FROM AUTHOR]

Background: Polypharmacy in haemodialysis patients can not only manifest as the continued prescribing of unnecessary medications but also has the potential to increase medication‐related hospital admissions, morbidity, and mortality. A validated deprescribing algorithm has recently been developed, specifically targeted at dialysis patients. This paper audits the experience of implementing this algorithm in Australian dialysis settings. Aim: The aim of this paper was to evaluate the usefulness and applicability of the pharmacist‐led Toronto deprescribing tool in Australian haemodialysis settings. Method: The pharmacist‐led deprescribing algorithm was implemented across two metropolitan sites and one rural site. The audit focused on five medications that could potentially be deprescribed in the target patient group (diuretics, alpha blockers, statins, proton pump inhibitors [PPIs], and quinine). Between 1 and 12 months later, a reaudit was conducted, with patients followed up to confirm if medications remained deprescribed. Results: Two hundred and eleven patients across three sites were reviewed. Application of the algorithm resulted in 168 medications deemed appropriate to deprescribe. Of these 168 medications, 56 (33%) were initially deprescribed, with 50 medications (30%) remaining deprescribed on reaudit. The deprescribing rates varied between the three different services, with initial deprescribing rates ranging from 18% to 61%. After follow‐up, deprescribing changes across target medications were fairly static, with only a small number of patients restarting either their diuretic or PPI. Conclusion: The pharmacist‐led deprescribing algorithm resulted in substantial deprescribing across the three sites. Deprescribing rates varied between the sites due to differences in the team model that the pharmacist worked within and the method of the rollout. Further studies should draw on aspects such as finding enablers to overcome prescriber and patient concerns about deprescribing and the aspects of which team models lead to higher rates of successful deprescribing. [ABSTRACT FROM AUTHOR]

The Pitt Review of the 2007 summer floods in the UK, published in 2008, commended the potential of natural flood management (NFM) for reducing flood risk. NFM is a nature‐based approach that has since gained substantial interest from both practitioners and academics. The review further highlighted the need for catchment‐based flood management (CBFM) to enhance resilience to flooding and climate change by incorporating NFM and wider nature‐based solutions into hard flood protection systems. Such integrated approaches are considered to be more sustainable and adaptable than the traditional hard‐engineered measures. More recently, the European Commission's European Green Deal also highlighted the need for greater use of nature‐based solutions including NFM for managing flood risk. Whilst there have been many attempts to quantify the effects of NFM through hydraulic and hydrological modelling, there is still no systematic review conducted for these modelling works. This review aims to summarise the current NFM modelling approaches, as well as discussing their key limitations related to data, model methods, and real‐world applications. This paper then goes further to highlight potential solutions to some of these challenges and provides guidance to assist modellers to improve future modelling and data collection process. [ABSTRACT FROM AUTHOR]

This paper presents a successful application of the mise‐à‐la‐masse (MALM) or applied potential method in association with induced polarization (IP). MALM is known, since 1920, to be able to delimit electrically conductive massive mineralization. The method is used at the point where a drill hole intercepts a massive, mineralized body, to estimate its extent and shape. It is thus used as a complementary mineral exploration tool. IP is normally used in conjunction with resistivity. However, the acquisition of IP data together with the MALM method is rarely found in the literature. This survey shows that it is possible to successfully detect and delimit areas of disseminated sulphides using MALM with IP. In this paper, the MALM method is presented and discussed in detail. A short description of the IP method is also provided. Data are from the Camaquã Project (Caçapava do Sul, RS, Brazil) and the Santa Maria (lead, zinc and associated silver) deposit, 5 km south of Caçapava do Sul. In a well that intercepted a massive mineralization (borehole 8011) with electrical continuity, ∆V measurements delineated the extent, shape and orientation (NS) of a conductive sulphide body. Mineralization intercepted by other two wells (8011 and 8103) did not present enough electrical continuity to exhibit potential contours that could be associated to massive sulphides; it was, however, successfully detected by IP. [ABSTRACT FROM AUTHOR]

Recursive statistical process monitoring (RSPM) methods have superior monitoring performance for industrial processes, especially those with time‐varying characteristics, and have recently been studied by many researchers. However, there is no survey paper yet that summarizes and analyzes the existing RSPM methods. In this survey, approximately 60 papers related to RSPM methods are reviewed and categorized from different aspects. Existing RSPM methods are categorized using the classification criteria proposed in this study based on the ways of recursively collecting data and the stages of recursive updating. Three core algorithms that are most commonly used in RSPM methods are uniformly summarized and analyzed specifically for studying recursive computation problems in RSPM methods. Furthermore, different types of multivariate statistical process monitoring (MSPM) methods that combine recursive computation are reviewed. [ABSTRACT FROM AUTHOR]

The paper provides insights over the response of the Italian fashion companies to the pandemic between their willingness to help the country to face the emergency and their necessity to keep the business afloat. In an exploratory ethos and by relying on qualitative inductive research, the study investigates 11 fashion companies by also engaging in extensive secondary data collection at the industry level. By reconciling several theoretical lenses (i.e., strategic management, grand challenges and organizational ecology) into a systemic conceptual framework, the paper uncovers the underlying dynamics of the reconversion process by also unpacking the relevant dimensions that were leveraged by the companies to respond to the pandemic. Through the concept of adaptive resilience, the findings highlight how the Italian fashion companies were able to cope with the pandemic, with the reconversion process being implemented at the crossroads between exploring opportunities of a new (albeit often temporary) business and the exploitation of existing key resources and capabilities. [ABSTRACT FROM AUTHOR]

A major advance in global bathymetric observation occurred in 2018 with the launch of NASA's ICESat‐2 satellite, carrying a green‐wavelength, photon‐counting lidar, the Advanced Topographic Laser Altimeter System (ATLAS). Although bathymetric measurement was not initially a design goal for the mission, pre‐ and post‐launch studies revealed ATLAS's notable bathymetric mapping capability. ICESat‐2 bathymetry has been used to support a wide range of coastal and nearshore science objectives. However, analysis of ICESat‐2 bathymetry in numerous locations around the world revealed instances of missing or clipped bathymetry in areas where bathymetric measurement should be feasible. These missing data were due to the ATLAS receiver algorithms not being optimized for bathymetry capture. To address this, two updates have been made to ICESat‐2's receiver algorithm parameters with the goal of increasing the area for which ICESat‐2 can provide bathymetry. This paper details the parameter changes and presents the results of a two‐phased study designed to investigate ICESat‐2's bathymetry enhancements at both local and global scales. The results of both phases confirm that the new parameters achieved the intended goal of increasing the amount of bathymetry provided by ICESat‐2. The site‐specific phase demonstrates the ability to fill critical bathymetric data gaps in open ocean and coastal settings. The global analysis shows that the area of potential bathymetry approximately doubled, with 6.1 million km2 of new area in which bathymetric measurements may be feasible. These enhancements are anticipated to facilitate a range of science objectives and close the gap between ICESat‐2 bathymetry and offshore sonar data. Key Points: Recent updates to ICESat‐2's receiver algorithm parameters have boosted the bathymetric measurement capabilitiesThe new updates allow ICESat‐2 to consistently measure bathymetry up to 41 m deepThe updates allow ICESat‐2 to potentially measure over 6.1 million km2 of new bathymetry in both coastal and ocean settings [ABSTRACT FROM AUTHOR]

The concept of information quality is important to consider when thinking about the benefits of DDC in the BD era in that DDC efforts have the ability to purposely improve information quality and focus on quality aspects that are most important to the analysis goal. Initial phases of the current wave of ML/AI were fueled by the availability of BD coupled with large-scale computing.[12] However, more recent publications have begun to focus on the need for DDC in improving current ML/AI methodologies. EXTENSIONS TO MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE Finally, I will conclude with a few exciting intersections of BD and DDC in the context of machine learning (ML) and artificial intelligence (AI). I especially appreciate how the paper is structured to strategies that can be applied before BD, during actual BD, and after the collection of BD. [Extracted from the article]

Objectives: The study aimed at determining the factors that contributed to older people presenting from residential aged care facilities (RACFs) to the emergency department (ED) of a regional Victorian hospital located in MM3 regional area. Methods: Appropriateness of transfer was assessed based on predefined criteria, and associated costs for each presentation were calculated. Design: The study carried out a retrospective review of records between July and December 2021. Data were extracted in a MS Excel spreadsheet and transferred to STATA 15.0 for analysis. Setting: Large regional health service in Victoria. Participants: Residential aged care facilities residents presenting to the ED. Main Outcome Measures: Was transfer appropriate or avoidable, costs associated with avoidable transfer, characteristics of the patient and circumstances relating to presentation to hospital. Results: A total of 448 presentations were recorded, and 85% of residents were >75 years of age. More than 60% of presentations occurred during weekends or after hours, with the most common reason being falls (31.9%). Over half (55.6%) of all presentations were avoidable which incurred a cost of $777 200 in 6 months. In multiple logistic regression, higher ED presentations were observed in residents with no prior GP assessment (OR: 1.47, 95% CI: 1.02–2.11). Conclusions: Necessary interventions such as preventing falls and increasing primary care access along with improving the quality of advance care directives (ACD) may reduce RACF transfers to the regional ED. To the best of our knowledge, this is the first paper of this kind that provides new data from an Australian rural and regional perspective and adds value to the growing body of knowledge in the intersection of aged care and acute emergency care. [ABSTRACT FROM AUTHOR]

Background: Social annotation (SA) allows users to collaboratively highlight important texts, make comments and discuss with each other on the same online document. This would not only accelerate and deepen learners' cognitive understanding of information, but also help build a sense of rapport, which is critical especially because of the worldwide shift from face‐to‐face class to remote education as a response to the COVID‐19 pandemic. Objective: To provide a systematic review of empirical SA studies, so that current development as well as issues in SA practices and research are identified. Methods: A total of 32 studies were identified and bibliometrical, instructional, and methodological analysis were conducted. Results and Conclusions: The United States has published the most SA research and technology‐related journals are most receptive of SA research; one‐shot quantitative designs with a sample size between 30 and 100 have been adopted most often; there is a lack of theoretical support for SA studies; higher education settings have been more frequently researched than other educational levels; SA technological features and activities have focused more on student uses and outcomes than on those of instructors; self‐designed technologies were more preferred than commercial ones; both cognitive and affective outcomes were emphasized and nearly all studies reported positive findings. Implications: Future SA studies may conduct blended designs with larger sample sizes that is grounded upon solid theoretical frameworks; more customized and affordable SA technologies that support both students and teachers should be developed. Learning analytics and emotional design may be capitalized more to meet the demand of remote education during the pandemic. Lay Description: What is Already Known About this Topic: The behaviour of annotating often helps learners obtain deeper understanding and retain longer memorization of learning content.Social annotation, which capitalizes the advantage of digital tools and collaboration, allows learners to annotate on the same document, and view each other's annotations to ignite discussion and maximize their individual learning.Social annotation has been widely used in educational settings amongst all ages of learners. What this Paper Adds: Provides a systematic review of empirical social annotation studies between 2000 and 2020, highlighting the analysis of bibliometrics, research designs, and learning outcomes and effects.Proposes a conceptual framework (the WIRE model) to guide the design and assessment of social annotation activities.Identifies challenges and gaps in existing research designs as well as instructional practices. Implications for Practice: Instructors can use the results to locate desirable social annotation technologies and design effective activities.Researchers may utilize the trend and research gaps to design future social annotation studies.Programmers can use WIRE to make an initial assessment of social annotation tool designs, and develop more customized products for formal education. [ABSTRACT FROM AUTHOR]

Point cloud is an important expression form of three‐dimensional (3D) data. It has enjoyed continuous development and attracted increasing attention due to its wide applications in many areas, such as artificial intelligence, deep learning, autonomous driving and tracking. Recently, there is a large number of end‐to‐end point cloud‐based deep learning methods being proposed which are successful in the 3D domain. In order to better use point cloud data for analysis and to explore future research directions, this paper presents a comprehensive review of existing methods and publicly available datasets, with a focus on the methods and research status of using point cloud data as direct input. The background of point cloud is first introduced, including data acquisition methods, basic concepts, and challenges. Following that, the deep learning methods based on point cloud data are investigated and analysed according to classification, detection and tracking, and segmentation. Furthermore, the existing public datasets and evaluation metrics are introduced. Finally, promising research directions are proposed in conjunction with existing methods. [ABSTRACT FROM AUTHOR]

This paper, by looking at the role of Taiwanese citizens in civic organisations for marriage migrants, explores how women's agency and negotiation occur not only against masculine dominance within patriarchal family arrangements, but also in alliance with it, when oppression is located somewhere beyond the family. In contrast to literature that depicts marriage migration as a women's and migrants' issue, this paper explores the role of Taiwanese citizens (often husbands in cross‐border marriages) in shaping the evolution of the phenomenon in both the private and public spheres. The aim of this paper is to fill a gap in empirical literature on marriage migration in Taiwan and East Asia, as well as contribute to feminist debates on women's agency in the context of masculine dominance. Building on ethnographic data collected through fieldwork in Taiwan, including in‐depth interviews and participant observation within civil society organisations for marriage migrants, this paper reveals how Taiwanese male citizens and Chinese female migrants responded to the challenges brought by their decision to engage in cross‐border unions by creating a new narrative that could explain their condition of shared oppression and by developing joint actions to address the structural discrimination they faced as cross‐border couples in Taiwan. [ABSTRACT FROM AUTHOR]

This data paper reports vegetation census data collected in a network of 28 grassland sites in Japan. This is the largest grassland data set freely available in Japan. The network is the project "Grassland Dynamics in Japan" launched by the Ministry of the Agriculture and Forestry and Fisheries, Japan. It consists of semi‐natural and artificial grasslands (pasture and meadow) and covers from Hokkaido to Kyushu area in Japan. Twenty to 12 permanent plots were established in each grassland. Censuses of plant species emerged in 1 m2 quadrat were conducted every year from 1972 to 1982 at longest. The data provide species abundance, plant coverage (%) and length (cm) of 484 quadrats. The censuses adopted common census protocol, which provide good opportunities for meta‐analyses and comparative studies among grasslands. The data have been used for ecological studies as well as for animal production reports published by the National Agriculture and Food Research Organization in Japan. The detailed Metadata for this abstract published in the Data Paper section of the journal is available in MetaCat in JaLTER at http://db.cger.nies.go.jp/JaLTER/metacat/metacat/ERDP-2020-22.1/jalter-en. [ABSTRACT FROM AUTHOR]

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The primary purpose of this research is to look into the Impact of cash payment on Operating and Financial synergies generated post the merger. The two‐stage least squares method Instrumental‐variables regression technique is employed to test the hypothesis of impact of cash payment on the synergies gained by the acquirer post the merger. The uniqueness of this paper is that it develops an effective technique for evaluating the phenomena of M&As using a composite synergy variable that accurately reflects the dynamic phenomenon. The paper uses "Principal Component Analysis" (PCA) estimation to generate dependent variable which is a conglomerate of several factors. For all models, the findings of the study reveal that payment in cash has a favorable and significant relationship with Operational and Financial Synergy, demonstrating the increased viability of acquiring entities in post‐M&A stage. Synergistic advantages of M&A appear to be perceived by enhanced Operating Income, improvement in R&D expenditure (statistically significant) and a positive Return on Asset (non‐significant). The paper looks at a wide variety of domestic M&A transactions in India. So far, no systematic research has been done to determine the possible realization of synergistic gains for Indian firms undergoing M&As. [ABSTRACT FROM AUTHOR]

Summary: The massive demand for broadband mobile network services are quite successfully covered already by 3G and 4G cellular mobile systems. The challenges for 5G are more diverse: answering the demands of Ultra‐Reliable Low Latency Communications (URLLC) and massive Machine Type Communications (mMTC) users—besides elevating mobile broadband to the next level. While generic, high‐level targets for KPIs (Key Performance Indicators) are widely communicated, it is not yet well‐understood how the various demands can affect the traffic mixture. Both the radio‐ and the core‐domains of the cellular network have to cope with traffic peaks, and have to obey various QoS (Quality of Service) guarantees. In order to cover these gaps, traffic‐related characteristics (data volume, signaling message types, and traffic peaks) should be determined, and this knowledge should be used during network planning, optimization, and service shaping. This paper aims to provide insights into user behavioral patterns for these three key application areas: enhanced Mobile Broadband (eMBB), URLLC and mMTC. Since traffic volume‐ and burst‐related user behavior is not expected to change suddenly, current targeted data collection on legacy mobile network links would provide a good basic insight for future, 5G usage—at least as traffic patterns. We have collected live pre‐5G mobile network data then analyzed them throughout this paper in order to reveal traffic patterns—and their distinguishing features—for the three key 5G application areas. [ABSTRACT FROM AUTHOR]