Hasil untuk "Information resources (General)"

Balkar Yildirim, Alan Albert Coley, Diego Fernando López

We investigate whether black holes can persist through the bounce with a minimal scale factor in a non-singular cosmology, whereby black holes from a previous contracting phase survive into the current expanding one. We do so by studying a generalized McVittie spacetime which embeds a spherically symmetric black hole in a positive spatial curvature bouncing FLRW cosmological background within the modified theory of teleparallel new general relativity. There are no further assumptions on the spacetime (e.g., on the form of the scale factor) initially, and the local evolution is derived from the field equations of the theory, utilizing a perturbative scheme which is valid ``near the bounce". To leading order we obtain a simple bounce solution similar to that in general relativity for a closed FLRW model with a positive cosmological constant, but in which the curvature term in the Friedmann equation is re-normalized within new general relativity. Qualitatively the minimum of the bounce at $t=0$ changes, but near the bounce the evolution remains symmetric. The central inhomogeneity evolves at higher perturbative orders, where the details depend on the arbitrary constants of the perturbative solution. Hence the evolution of the local horizon during the bounce changes qualitatively, where the effects depend on the signs of the perturbation, and the symmetry across the bounce is disrupted due to a linear term.

Erica Machulak, Kath Burton

Given the virtually universal need for resources to support public scholarship, collaborative grant writing is critical to most partnership-based research in any discipline. And yet collaborative grant writing is more often seen as an administrative hoop than as a process to facilitate strong projects and partnerships. This article considers grant proposals as a genre of scholarly communication that embodies the opportunities and limitations of advancing meaningful public scholarship within our imperfect system. Collaborative grant writing and the creative dialogues it prompts are presented as pathways to collective flourishing that encourage curiosity, knowledge sharing, and pragmatic discussions about needs and priorities to facilitate authentic, rigorous, and transparent partnerships in tandem with stronger funding applications. The article concludes with core principles for co-crafting grant proposals with partners that strengthen relationships, foster effective projects, and develop compelling narratives for funders. The authors propose that the collaborative grant writing process itself can help facilitate those tough conversations by creating the space and imperative to plan and communicate clearly.

Zinat Mahal, Helmut Yabar

A significant amount of livestock manure is generated in Bangladesh, creating challenges for sustainable manure management. Bioenergy and organic fertilizer production from manure are expected to provide opportunities for renewable resources, including environmental benefits. Therefore, this research aimed to spatially assess the potential of manure for biogas and compost using GIS (geographic information system) symbology and hot spot analyses, based on theoretical estimations. This study identified hot spots for biogas and compost production from various types of livestock manure at the district and sub-district levels, whereas previous studies have only explored these at a national level. The estimated total biogas and compost potential was approximately 15,035.50 million m³ and 67.36 million tons, respectively, from livestock manure in 2024, distinguishing it as a feasible alternative to fossil fuels for electricity generation and synthetic fertilizers for crop production. Overall, the regional pattern maps of the socio-economic potential, hot spot identification, and environmental benefits assessments of manure will provide a more localized approach to planning sustainable manure management strategies for biogas and compost production in Bangladesh.

Meiying Wei, Bo Wang, Chaoqun Li et al.

IntroductionNitraria tangutorum Bobr., a prominent xerophytic shrub, exhibits remarkable adaptability to harsh environment and plays a significant part in preventing desertification in northwest China owing to its exceptional drought and salinity tolerance.MethodsTo investigate the drought-resistant mechanism underlying N. tangutorum, we treated 8-week-old seedlings with polyethylene glycol (PEG)-6000 (20%, m/m) to induce drought stress. 27 samples from different tissues (leaves, roots and stems) of N. tangutorum at 0, 6 and 24 h after drought stress treatment were sequenced using PacBio single-molecule real-time (SMRT) sequencing and Illumina RNA sequencing to obtain a comprehensive transcriptome.ResultsThe PacBio SMRT sequencing generated 44,829 non-redundant transcripts and provided valuable reference gene information. In leaves, roots and stems, we identified 1162, 2024 and 232 differentially expressed genes (DEGs), respectively. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that plant hormone signaling and mitogen-activated protein kinase (MAPK) cascade played a pivotal role in transmitting stress signals throughout the whole N. tangutorum plant following drought stress. The interconversion of starch and sucrose, as well as the biosynthesis of amino acid and lignin, may represent adaptive strategies employed by N. tangutorum to effectively cope with drought. Transcription factor analysis showed that AP2/ERF-ERF, WRKY, bHLH, NAC and MYB families were mainly involved in the regulation of drought response genes. Furthermore, eight physiological indexes, including content of proline, hydrogen peroxide (H2O2), malondialdehyde (MDA), total amino acid and soluble sugar, and activities of three antioxidant enzymes were all investigate after PEG treatment, elucidating the drought tolerance mechanism from physiological perspective. The weighted gene co-expression network analysis (WGCNA) identified several hub genes serve as key regulator in response to drought through hormone participation, ROS cleavage, glycolysis, TF regulation in N. tangutorum.DiscussionThese findings enlarge genomic resources and facilitate research in the discovery of novel genes research in N. tangutorum, thereby establishing a foundation for investigating the drought resistance mechanism of xerophyte.

Wenya Yu, Jiahe Tian, Panpan Li et al.

Abstract Background Missed or delayed child healthcare caused by the COVID-19 lockdown has threatened young children’s health and has had an unpredictable influence on caregivers’ child healthcare preferences. This study investigated caregivers’ child healthcare preferences and the factors that influence them among families with young children (0–3 years) during the lockdown in Shanghai. Methods Participants in this cross-sectional study were enrolled through random encounter sampling. Questionnaires were distributed online from June 1 to November 10, 2022, in Shanghai. A total of 477 valid questionnaires were received. The demographics of caregivers and their families, children’s characteristics, COVID-19-related information, and caregivers’ healthcare preferences were analyzed. The statistical analyses included frequency and percentage, chi-square tests, and multinomial logistic regression. Results Caregivers preferred child healthcare professionals in the community health service system (CHS; 47.6%) followed by hospital pediatricians (40.0%) during lockdown. Caregivers with the following characteristics preferred CHS: those with an annual household income of CNY 200,000–300,000, those whose youngest children were aged 8–12 months, and those who experienced early childhood physical development issues. Caregivers preferred hospitals if they had experienced healthcare-seeking-related difficulties in accessing professional guidance from hospital pediatricians. Conclusions During pandemic lockdowns, policymakers should allocate more resources to CHS to meet caregivers’ childcare demands. Moreover, special attention should be given to the healthcare needs for CHS among families with specific demographics. Trial registration Approval was obtained from the Ethics Committee of Shanghai Jiao Tong University School of Medicine School of Public Health (SJUPN-202,109; June 1, 2022).

Dharmesh Dhabliya, Shailesh V. Kulkarni, Netaji Jadhav et al.

In the field of healthcare, the intersection of Artificial Intelligence (AI) and Public Health has emerged as an essential component, presenting numerous opportunities for innovation that are one of a kind. The purpose of this research paper is to investigate the historical development, current patterns, and global repercussions of incorporating AI into healthcare systems. The paper provides a comprehensive analysis of the application of AI in the field of public health. It covers the progression of the field, beginning with the initial efforts to automate diagnostic procedures and ending with the most recent developments in predictive modeling and precision medicine. The research investigates the degree to which various nations have adopted AI, highlighting both successful implementations and ongoing challenges in the framework of the global landscape. The intentional incorporation of AI is presented as a driving force for the transformation of healthcare provision. This transformation has the potential to provide potential benefits such as improved precision in diagnosis, effectiveness in treatment, and efficient utilization of treatment resources. In addition, the paper places an emphasis on the proactive role that AI plays in identifying and mitigating emerging health risks. Providing useful information about the policies, practices, and frameworks that enable the efficient incorporation of AI into public health is the primary objective of this research. The purpose of this paper is to provide policymakers, healthcare practitioners, and researchers with suggestions that can be put into practice today by combining historical perspectives and analyzing patterns that are currently occurring. The purpose of this action is to have an impact on the conversation that is taking place about the future of healthcare delivery, with the intention of highlighting the significant impact that AI can have on improving the circumstances of public health.

Neri Merhav

This article stands as a tribute to the enduring legacy of Jacob Ziv and his landmark contributions to information theory. Specifically, it delves into the groundbreaking individual-sequence approach -- a cornerstone of Ziv's academic pursuits. Together with Abraham Lempel, Ziv pioneered the renowned Lempel-Ziv (LZ) algorithm, a beacon of innovation in various versions. Beyond its original domain of universal data compression, this article underscores the broad utility of the individual-sequence approach and the LZ algorithm across a wide spectrum of problem areas. As we traverse through the forthcoming pages, it will also become evident how Ziv's visionary approach has left an indelible mark on my own research journey, as well as on those of numerous colleagues and former students. We shall explore, not only the technical power of the LZ algorithm, but also its profound impact on shaping the landscape of information theory and its applications.

C. Emdad Haque, Jobaed Ragib Zaman, David Walker

In general, much is known about patterns relating to flood risk reduction, coping, and adaptation in various types of communities; however, knowledge of their drivers—which are critical for building community resilience to natural hazards—is limited. The present study investigates the influencing factors of coping and adaptation measures vis-a-vis flood hazards at the community level and examines their interrelationships. This work employs a “case study” approach and analyzes two towns—St. Adolphe and Ste. Agathe—in the Red River Valley in the province of Manitoba, Canada. Data collection consisted of in-depth interviews with key informants and obtaining oral histories from the locals, along with an examination of secondary official records and documents. The results revealed that the major drivers of local-level coping and adaptation include functioning partnerships among stakeholders, strong institutional structures that facilitate interactive learning, knowledge co-production, resources sharing, communication and information sharing, and infrastructure supports. It was observed that an institutional atmosphere conducive to spontaneous network development yields diverse coping and adaptation strategies. To improve the outcomes of coping and adaptation measures, close collaboration between community-based groups and formal and quasi-formal institutions, and transparency in decision-making processes are vital.

Stuart Aitken, Helen V. Firth, Caroline F. Wright et al.

Summary: Diagnosing rare developmental disorders using genome-wide sequencing data commonly necessitates review of multiple plausible candidate variants, often using ontologies of categorical clinical terms. We show that Integrating Multiple Phenotype Resources Optimizes Variant Evaluation in Developmental Disorders (IMPROVE-DD) by incorporating additional classes of data commonly available to clinicians and recorded in health records. In doing so, we quantify the distinct contributions of sex, growth, and development in addition to Human Phenotype Ontology (HPO) terms and demonstrate added value from these readily available information sources. We use likelihood ratios for nominal and quantitative data and propose a classifier for HPO terms in this framework. This Bayesian framework results in more robust diagnoses. Using data systematically collected in the Deciphering Developmental Disorders study, we considered 77 genes with pathogenic/likely pathogenic variants in ≥10 individuals. All genes showed at least a satisfactory prediction by receiver operating characteristic when testing on training data (AUC ≥ 0.6), and HPO terms were the best predictor for the majority of genes, though a minority (13/77) of genes were better predicted by other phenotypic data types. Overall, classifiers based upon multiple integrated phenotypic data sources performed better than those based upon any individual source, and importantly, integrated models produced notably fewer false positives. Finally, we show that IMPROVE-DD models with good predictive performance on cross-validation can be constructed from relatively few individuals. This suggests new strategies for candidate gene prioritization and highlights the value of systematic clinical data collection to support diagnostic programs.

Elisa C. Baek, Ryan Hyon, Karina López et al.

It has been proposed that information sharing, which is a ubiquitous and consequential behavior, plays a critical role in cultivating and maintaining a sense of shared reality. Across three studies, we tested this theory by investigating whether or not people are especially likely to share information that they believe will be interpreted similarly by others in their social circles. Using neuroimaging while members of the same community viewed brief film clips, we found that more similar neural responding of participants was associated with a greater likelihood to share content. We then tested this relationship using two behavioral studies and found (1) that people were particularly likely to share content that they believed others in their social circles would interpret similarly and (2) that perceived similarity with others leads to increased sharing likelihood. In concert, our findings support the idea that people are driven to share information to create and reinforce shared understanding, which is critical to social connection.

Igor Khorozyan

The literature other than scientific journals (non-journals) is a valuable, but scattered and rarely used, source of evidence of the effectiveness of interventions applied for protection from mammalian predators. This study describes how journals and non-journals differ in relation to study designs, types of interventions, predator species, countries, and publication bias. I collected 411 journal cases (226 publications) and 97 non-journal cases (64 publications) covering the period 1955–2020, five study designs, six interventions, 28 species and 50 countries. Non-journals were important for two predators (leopard Panthera pardus and snow leopard P. uncia) and four countries (Canada, India, Russia and Sri Lanka). These species and countries have been affected by human-predator conflicts and the use of non-journals should become a habitual practice to mitigate conflicts. Information on other species and countries, and all study designs and interventions, was provided mostly or only in peer-reviewed journals. This study helps make the use of non-journals easier for researchers and conservation practitioners by providing and explaining a list of relevant literature and online resources.

Binbo Li, Ying Zhou, Donghai Xie et al.

Stripe noise is considered one of the largest issues in space-borne remote sensing. The features of stripe noise in high-resolution remote sensing images are varied in different spatiotemporal conditions, leading to limited detection capability. In this study, we proposed a new detection algorithm (LSND: a linear stripe noise detection algorithm) considering stripe noise as a typical linear target. A large-scale stripe noise dataset for remote sensing images was created through linear transformations, and the target recognition of stripe noise was performed using deep convolutional neural networks. The experimental results showed that for sub-meter high-resolution remote sensing images such as GF-2 (GaoFen-2), our model achieved a precision of 98.7%, recall of 93.8%, F1-score of 96.1%, AP of 92.1%, and FPS of 35.71 for high resolution remote sensing images. Furthermore, our model exceeded ~40% on the accuracy and ~20% on the speed of the general models. Stripe noise detection would be helpful to detect the qualities of space-borne remote sensing and improve the quality of the images.

Saleh Nasser Rashid Alismaili, Mohana Shanmugam, Hairoladenan Kasim et al.

Healthcare service institutions (HIS) seeking to motivate patient loyalty have identified Hospital Information Systems (HIS) as a potential solution to gather, measure, and analyze the healthcare data necessary for this goal. The purpose of this systematic review of the literature is to reveal how prevalent the use of HIS with respect to motivating patient loyalty, and to investigate the efficacy of HIS in doing so. To generate data, published empirical studies and conference papers from the past five years were compiled from the following online databases: Scopus, ACM Digital Library, IEEE Xplore, ScienceDirect, and Emerald Insight. The search results indicate that, while the use of HIS in motivating patient loyalty is rare relative to other topics within the general field of HIS, HIS use have a significant positive impact on patient satisfaction, which is understood in the literature to be directly related to patient loyalty. There remains a gap in empirical studies on the direct application of HIS with the purpose of increasing patient loyalty. Future research may be required on the development of an HIS focused on motivating patient loyalty, which can be empirically tested in a real-world HSI setting.

Michael X. Cao

[...] In this thesis, we are interested in generalizing factor graphs and the relevant methods toward describing quantum systems. Two generalizations of classical graphical models are investigated, namely double-edge factor graphs (DeFGs) and quantum factor graphs (QFGs). Conventionally, a factor in a factor graph represents a nonnegative real-valued local functions. Two different approaches to generalize factors in classical factor graphs yield DeFGs and QFGs, respectively. We proposed/re-proposed and analyzed generalized versions of belief-propagation algorithms for DeFGs/QFGs. As a particular application of the DeFGs, we investigate the information rate and their upper/lower bounds of classical communications over quantum channels with memory. In this study, we also propose a data-driven method for optimizing the upper/lower bounds on information rate.

Seyi Amosun, Faheema Kimmie-Dhansay, Greta Geerts et al.

BackgroundGlobally, the demands on dental educators continue to diversify and expand. Due to their importance and value, mentoring programs have been acknowledged as a means of recruiting, developing, and retaining academics in dental education. ObjectiveThis protocol is for a scoping review that aims to identify the goals of mentoring programs for academic staff in dental faculties and determine how these programs were structured, delivered, and evaluated. MethodsThe review will be performed in accordance with the Joanna Briggs Institute’s methodology for scoping reviews, which covers both qualitative and quantitative scientific literature as well as grey literature written in English and published between 2000 and 2020. The databases will include PubMed, Ovid, the Educational Resources Information Center database, Science Direct, Scopus, Google Scholar, Trove, Web of Science, Openthesis.org, and the website of the American Dental Education Association. A manual search will also be conducted by using the reference lists of included studies to identify additional articles. Working independently, the authors will participate iteratively in literature screening, paper selection, and data extraction. Disagreements between the reviewers will be resolved by discussion until a consensus is reached or after consultation with the research team. Key information that is relevant to the review questions will be extracted from the selected articles and imported into a Microsoft Excel file. The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) will be used to guide the reporting of this protocol. ResultsThe search for appropriate literature has commenced, and we aim to present the results before the end of the 2021 academic year. ConclusionsThe development of formal mentorship programs for academics in dental education will enhance the retention of academic staff. International Registered Report Identifier (IRRID)PRR1-10.2196/27239

Robin Brochier, Frédéric Béchet

Wikipedia, the largest open-collaborative online encyclopedia, is a corpus of documents bound together by internal hyperlinks. These links form the building blocks of a large network whose structure contains important information on the concepts covered in this encyclopedia. The presence of a link between two articles, materialised by an anchor text in the source page pointing to the target page, can increase readers' understanding of a topic. However, the process of linking follows specific editorial rules to avoid both under-linking and over-linking. In this paper, we study the transductive and the inductive tasks of link prediction on several subsets of the English Wikipedia and identify some key challenges behind automatic linking based on anchor text information. We propose an appropriate evaluation sampling methodology and compare several algorithms. Moreover, we propose baseline models that provide a good estimation of the overall difficulty of the tasks.

I. Zakir Ahmed, Hamid Sadjadpour, Shahram Yousefi

We consider a class of resource allocation problems given a set of unconditional constraints whose objective function satisfies Bellman's optimality principle. Such problems are ubiquitous in wireless communication, signal processing, and networking. These constrained combinatorial optimization problems are, in general, NP-Hard. This paper proposes two algorithms to solve this class of problems using a dynamic programming framework assisted by an information-theoretic measure. We demonstrate that the proposed algorithms ensure optimal solutions under carefully chosen conditions and use significantly reduced computational resources. We substantiate our claims by solving the power-constrained bit allocation problem in 5G massive Multiple-Input Multiple-Output receivers using the proposed approach.

James P. Bagrow, Sune Lehmann

The full range of activity in a temporal network is captured in its edge activity data -- time series encoding the tie strengths or on-off dynamics of each edge in the network. However, in many practical applications, edge-level data are unavailable, and the network analyses must rely instead on node activity data which aggregates the edge-activity data and thus is less informative. This raises the question: Is it possible to use the static network to recover the richer edge activities from the node activities? Here we show that recovery is possible, often with a surprising degree of accuracy given how much information is lost, and that the recovered data are useful for subsequent network analysis tasks. Recovery is more difficult when network density increases, either topologically or dynamically, but exploiting dynamical and topological sparsity enables effective solutions to the recovery problem. We formally characterize the difficulty of the recovery problem both theoretically and empirically, proving the conditions under which recovery errors can be bounded and showing that, even when these conditions are not met, good quality solutions can still be derived. Effective recovery carries both promise and peril, as it enables deeper scientific study of complex systems but in the context of social systems also raises privacy concerns when social information can be aggregated across multiple data sources.

Suzuki Ayala-Narváez

En México es escasa la infraestructura adecuada de espacios físicos que faciliten el acceso y movilidad de las personas con discapacidad motora. Por accesibilidad se entiende el garantizar el desplazamiento al entorno físico de las personas con esta discapacidad para que estén en igualdad de condiciones con las demás. Este estudio de tipo observacional, descriptivo y transversal tiene como objetivo evaluar las condiciones de infraestructura de 35 escuelas primarias públicas de la ciudad de Chihuahua, para determinar si permiten o no la accesibilidad de los alumnos o pacientes del Centro de Rehabilitación Infantil Teletón. Los datos e información se obtuvieron mediante la observación directa de estas características en las 35 escuelas; para su corroboración, se tomaron en cuenta los parámetros que establece la NOM-233-SSA1-2003 (Norma Oficial Mexicana) sobre aspectos arquitectónicos en instalaciones físicas para facilitar el acceso, tránsito, uso y permanencia de las personas con discapacidad en establecimientos de atención pública, atención médica ambulatoria y hospitalaria del Sistema Nacional de Salud. Las escuelas primarias cumplieron parcialmente con algunos de los requisitos arquitectónicos que establece la norma. El 31% de las primarias cuenta con espacio azul para estacionamiento, 57% no cuenta con un retrete adecuado y 29% tiene en sus instalaciones un mingitorio adaptado. Se concluye que la accesibilidad y movilidad en los centros escolares de los alumnos con discapacidad motora es limitada, pues las primarias evaluadas no cumplen con los requisitos mínimos para su desplazamiento. Abstract In Mexico, there is insufficient the adequate physical space infrastructure to facilitate access and mobility for people with motor disabilities. By ensuring, accessibility means the displacement of the physical environment for people with this disability so that they are on equal basis with others. This observational study, descriptive transversal aims to assess the infrastructure of 35 public elementary schools in the city of Chihuahua, to determine whether to allow accessibility for students or patients of Children’s Rehabilitation Center Telethon. The data and information obtained by direct observation of these features in 35 schools; for corroboration, we took into account the parameters established by NOM-233-SSA1-2003 (Norma Oficial Mexicana) on architectural aspects in physical facilities for easy access, transit, use and retention of people with disabilities in care settings public, outpatient hospital care and the NHS. Primary schools partially met some of the architectural requirements of the standard. 31% of the primary features blue parking space, 57% do not have adequate toilet and 29% has adapted its facilities a urinal. We conclude that accessibility and mobility in schools for students with physical disabilities is limited, as the primary assessed does not meet the minimum requirements for movement. Keywords: wheelchair accessible, inclusive education, adjustments, accessibility, inclusive schools, disability.

Milad Johnny, Alireza Vahid

The radiation pattern of transmit antennas varies and fluctuates as receivers change their location, other objects move around, and due to the antenna design itself. In this paper, we demonstrate how this observation can be exploited to align most of the interference signal power and significantly increase the average achievable communication rates. More precisely, in the context of $K$-user interference channels, we propose a blind interference alignment scheme that combines multi-layer coding at the transmitters and a post-processing methodology at the receivers to align a significant portion of the interference signal power. Our scheme does not rely on any channel state information (CSI), hence the term blind, and only relies on the statistics of the radiation pattern fluctuations. Our proposed communication methodology overcomes some of the barriers in practical implementation of the interference alignment concept. Due to the complexity of the expressions, in this work, we numerically evaluate the achievable rates in different scenarios, demonstrate the gains of our proposed strategy, and compare our results to the prior works with perfect CSI.