Global View Research Articles

Sustainability in Hybrid Technologies for Heritage Preservation: A Scientometric Study

The use of augmented reality applied to museums to preserve and communicate cultural heritage sustainably is a topic of increasing relevance today. Museums play an essential role in preserving and disseminating culture and history, and augmented reality has emerged as a powerful technological tool to enrich the visitor experience and ensure the sustainable preservation of cultural heritage. The fundamental objective of this literature review is to explore and understand the key contributions that are being made in the field of augmented reality applied to museums, with a focus on sustainability. The literature related to this topic is dispersed in various sources of information, which motivates the need to carry out a detailed and systematic analysis incorporating sustainability aspects. To carry out this analysis, the metaphor of the “tree of science” is used. This metaphor provides a structured approach that is applied in two complementary ways. Firstly, it focuses on collecting and analyzing scientometric statistics that cover data on countries, authors, academic institutions, and research centers involved in developing augmented reality applications for museums with sustainable methodologies. This quantitative perspective offers a global view of the contributions and their geographical scope including their sustainability impact. Secondly, an evolutionary analysis based on the “tree of science” is carried out. This historical approach examines the origin and evolution of contributions in the field of augmented reality applied to museums, from its first manifestations to the most recent innovations, with an emphasis on sustainable practices. This historical approach is essential to understanding the trajectory and development of augmented reality applications in the museum context and their role in promoting sustainable cultural heritage preservation. This review aims to provide a complete and contextualized view of the use of augmented reality in museums for the sustainable preservation and communication of cultural heritage. Through a multidimensional approach encompassing scientometric statistics and historical analysis, we seek to shed light on this technology’s most significant contributions and evolution in the museum sector, with a particular focus on sustainability.

Boosting knowledge diversity, accuracy, and stability via tri-enhanced distillation for domain continual medical image segmentation

Domain continual medical image segmentation plays a crucial role in clinical settings. This approach enables segmentation models to continually learn from a sequential data stream across multiple domains. However, it faces the challenge of catastrophic forgetting. Existing methods based on knowledge distillation show potential to address this challenge via a three-stage process: distillation, transfer, and fusion. Yet, each stage presents its unique issues that, collectively, amplify the problem of catastrophic forgetting. To address these issues at each stage, we propose a tri-enhanced distillation framework. (1) Stochastic Knowledge Augmentation reduces redundancy in knowledge, thereby increasing both the diversity and volume of knowledge derived from the old network. (2) Adaptive Knowledge Transfer selectively captures critical information from the old knowledge, facilitating a more accurate knowledge transfer. (3) Global Uncertainty-Guided Fusion introduces a global uncertainty view of the dataset to fuse the old and new knowledge with reduced bias, promoting a more stable knowledge fusion. Our experimental results not only validate the feasibility of our approach, but also demonstrate its superior performance compared to state-of-the-art methods. We suggest that our innovative tri-enhanced distillation framework may establish a robust benchmark for domain continual medical image segmentation.

Landscape of RNA pseudouridylation in archaeon Sulfolobus islandicus.

Pseudouridine, one of the most abundant RNA modifications, is synthesized by stand-alone or RNA-guided pseudouridine synthases. Here, we comprehensively mapped pseudouridines in rRNAs, tRNAs and small RNAs in the archaeon Sulfolobus islandicus and identified Cbf5-associated H/ACA RNAs. Through genetic deletion and in vitro modification assays, we determined the responsible enzymes for these modifications. The pseudouridylation machinery in S. islandicus consists of the stand-alone enzymes aPus7 and aPus10, and six H/ACA RNA-guided enzymes that account for all identified pseudouridines. These H/ACA RNAs guide the modification of all eleven sites in rRNAs, two sites in tRNAs, and two sites in CRISPR RNAs. One H/ACA RNA shows exceptional versatility by targeting eight different sites. aPus7 and aPus10 are responsible for modifying positions 13, 54 and 55 in tRNAs. We identified four atypical H/ACA RNAs that lack the lower stem and the ACA motif and confirmed their function both in vivo and in vitro. Intriguingly, atypical H/ACA RNAs can be modified by Cbf5 in a guide-independent manner. Our data provide the first global view of pseudouridylation in archaea and reveal unexpected structures, substrates, and activities of archaeal H/ACA RNPs.

MGSGA: Multi-grained and Semantic-Guided Alignment for Text-Video Retrieval

In the text-video retrieval task, the objective is to calculate the similarity between a text and a video, and rank the relevant candidates higher. Most existing methods only consider the text-video semantic alignment in the global view. But using mean-pooling to obtain global semantics and simply aligning text and video in the global view may lead to semantic bias. In addition, some methods utilize offline object detectors or sentence parsers to obtain entity-level information in text and video and achieve local alignment. However, inaccurate detection introduces possible errors and such approaches prevent models from being trained end-to-end for retrieval. To overcome these limitations, we propose multi-grained and semantic-guided alignment for text-video retrieval in this paper, which can achieve fine-grained alignment based on video frames and text words, local alignment based on semantic centers, and global alignment. Specially, we explore summary semantics of text and video to guide the local alignment based on semantic centers for we believe that the importance of each semantic center is determined by summary semantics. We evaluate our approach on four benchmark datasets of MSRVTT, MSVD, ActivityNet Captions, and DiDeMo, achieving better performance than most existing methods.

Visualization of translation reorganization upon persistent ribosome collision stress in mammalian cells

Aberrantly slow ribosomes incur collisions, a sentinel of stress that triggers quality control, signaling, and translation attenuation. Although each collision response has been studied in isolation, the net consequences of their collective actions in reshaping translation in cells is poorly understood. Here, we apply cryoelectron tomography to visualize the translation machinery in mammalian cells during persistent collision stress. We find that polysomes are compressed, with up to 30% of ribosomes in helical polysomes or collided disomes, some of which are bound to the stress effector GCN1. The native collision interface extends beyond the invitro-characterized 40S and includes the L1 stalk and eEF2, possibly contributing to translocation inhibition. The accumulation of unresolved tRNA-bound 80S and 60S and aberrant 40S configurations identifies potentially limiting steps in collision responses. Our work provides a global view of the translation machinery in response to persistent collisions and a framework for quantitative analysis of translation dynamics in situ.

Diversity and community structure of anaerobic gut fungi in the rumen of wild and domesticated herbivores.

The rumen houses a diverse community that plays a major role in the digestion process in ruminants. Anaerobic gut fungi (AGF) are key contributors to plant digestion in the rumen. Here, we present a global amplicon-based survey of the rumen AGF mycobiome by examining 206 samples from 15 animal species, 15 countries, and 6 continents. The rumen AGF mycobiome was highly diverse, with 81 out of 88 currently recognized AGF genera or candidate genera identified. However, only six genera (Neocallimastix, Orpinomyces, Caecomyces, Cyllamyces, NY9, and Piromyces) were present at >4% relative abundance. AGF diversity was higher in members of the families Antilocapridae and Cervidae compared to Bovidae. Community structure analysis identified a pattern of phylosymbiosis, where host family (10% of total variance) and species (13.5%) partially explained the rumen mycobiome composition. As well, diet composition (9%-19%), domestication (11.14%), and biogeography (14.1%) also partially explained AGF community structure; although sampling limitation, geographic range restrictions, and direct association between different factors hindered accurate elucidation of the relative contribution of each factor. Pairwise comparison of rumen and fecal samples obtained from the same subject (n = 13) demonstrated greater diversity and inter-sample variability in rumen versus fecal samples. The genera Neocallimastix and Orpinomyces were present in higher abundance in rumen samples, while Cyllamyces and Caecomyces were enriched in fecal samples. Comparative analysis of global rumen and feces data sets revealed a similar pattern. Our results provide a global view of AGF community in the rumen and identify patterns of AGF variability between rumen and feces in herbivores Gastrointestinal (GI) tract.IMPORTANCERuminants are highly successful and economically important mammalian suborder. Ruminants are herbivores that digest plant material with the aid of microorganisms residing in their GI tract. In ruminants, the rumen compartment represents the most important location where microbially mediated plant digestion occurs, and is known to house a bewildering array of microbial diversity. An important component of the rumen microbiome is the anaerobic gut fungi (AGF), members of the phylum Neocallimastigomycota. So far, studies examining AGF diversity have mostly employed fecal samples, and little is currently known regarding the identity of AGF residing in the rumen compartment, factors that impact the observed patterns of diversity and community structure of AGF in the rumen, and how AGF communities in the rumen compare to AGF communities in feces. Here, we examined the rumen AGF diversity using an amplicon-based survey targeting a wide range of wild and domesticated ruminants (n = 206, 15 different animal species) obtained from 15 different countries. Our results demonstrate that while highly diverse, no new AGF genera were identified in the rumen mycobiome samples examined. Our analysis also indicate that animal host phylogeny, diet, biogeography, and domestication status could play a role in shaping AGF community structure. Finally, we demonstrate that a greater level of diversity and higher inter-sample variability was observed in rumen compared to fecal samples, with two genera (Neocallimastix and Orpinomyces) present in higher abundance in rumen samples, and two others (Cyllamyces and Caecomyces) enriched in fecal samples. Our results provide a global view of the identity, diversity, and community structure of AGF in ruminants, elucidate factors impacting diversity and community structure of the rumen mycobiome, and identify patterns of AGF community variability between the rumen and feces in the herbivorous GI tract.

On the use of MiniCPS for conducting rigorous security experiments in Software-Defined Industrial Control Systems

AbstractSoftware-Defined Networking (SDN) offers a global view over the network and the ability of centrally and dynamically managing network flows, making them ideal for creating security threat detection and mitigation solutions. Industrial networks possess specific characteristics that make them well-suited for such solutions, leading to extensive research efforts in this area. However, due to the high economic cost and potential risks associated with real equipment interaction, most studies rely on testbeds for demonstration purposes. Therefore, it becomes crucial to understand the limitations and safe operating ranges of testbed environments to ensure the development of scientifically rigorous experiments and accurate result measurements. This study focuses on analyzing MiniCPS-based testbeds in terms of network performance, experiment replicability, and the effects of different attacker implementation modes. The findings demonstrate that utilizing MiniCPS on actual hardware enables the development of highly replicable and high-performance testbeds, as long as they operate within the predefined safe operating ranges. Additionally, this work provides an in-depth analysis of various attacker implementation techniques and their impact on the network.

Does education influence COVID-19 vaccination? A global view

After the recent hard attempts felt on a global scale, notably in the health sector, the steady efforts of scientists have been materialized in maybe one of the most expected findings of the last decades, i.e. the launching of the COVID-19 vaccines. Although it is not our goal to plead for vaccination, as the decision in this regard is a matter of individual choice, we believe it is necessary and enlightening to analyze how one's educational status interferes with COVID-19 vaccination. There are discrepancies between world states vis-à-vis their well-being and their feedback to crises, and from the collection of features that can segregate the states in handling vaccination, in this paper, the spotlight is on education. We are referring to this topic because, generally, researches converge rather on the linkage between economic issues and COVID-19 vaccination, while education levels are less tackled in relation to this. To notice the weight of each type of education (primary, secondary, tertiary) in this process, we employ an assortment of statistical methods, for three clusters: 45 low-income countries (LICs), 72 middle-income countries (MICs) and 53 high-income countries (HICs). The estimates suggest that education counts in the COVID-19 vaccination, the tertiary one having the greatest meaning in accepting it. It is also illustrated that the imprint of education on vaccination fluctuates across the country groups scrutinized, with HICs recording the upper rates. The heterogeneity of COVID-19 vaccination-related behaviors should determine health authorities to treat this subject differently. To expand the COVID-19 vaccines uptake, they should be in an ongoing dialogue with all population categories and, remarkably, with those belonging to vulnerable communities, originated mostly in LICs. Education is imperative for vaccination, and it would ought to be on the schedule of any state, for being assimilated into health strategies and policies.

Systematic evaluation of Rutongshu oral liquid based on chromatographic fingerprinting and nontargeted metabolomic analysis

AbstractBased on chromatographic fingerprinting combined with quantitative analysis on characteristic chemical constituents as well as hierarchical cluster analysis, an easy and sensitive approach utilizing high performance liquid chromatography (HPLC) was developed for the identification and quality evaluation of Rutongshu oral liquid (ROL). What is more, nontargeted metabolomic analysis was conducted to gain a global view in terms of its chemical profile. In this study, 16 peaks from different batches (S1–S10) of ROL samples produced by Taihe Hospital of Chinese Medicine were selected as common peaks for the evaluation of their similarity whose values of all tested 10 batches exceeded 0.90 when compared with the control fingerprints. Meanwhile, simultaneous quantification of five markers in the oral solution, including albiflorin, paeoniflorin, chlorogenic acid, quercetin and ferulic acid was performed, and standard curves established for respective reference substances showed good regression in the linear range (r2 > 0.999) with recoveries in the range of 98.96–102.35%. The ultra-high performance liquid chromatography (UHPLC) combined with Orbitrap Exploris 120 mass spectrometer resulted in 88 identified compounds. The results of validation showed that the established method was reproducible, precise and stable. This study offers an effective, dependable and useful approach for the systematic evaluation of the hospital formulation ROL.

SperMD: the expression atlas of sperm maturation

The impairment of sperm maturation is one of the major pathogenic factors in male subfertility, a serious medical and social problem affecting millions of global couples. Regrettably, the existing research on sperm maturation is slow, limited, and fragmented, largely attributable to the lack of a global molecular view. To fill the data gap, we newly established a database, namely the Sperm Maturation Database (SperMD, http://bio-add.org/SperMD). SperMD integrates heterogeneous multi-omics data (170 transcriptomes, 91 proteomes, and five human metabolomes) to illustrate the transcriptional, translational, and metabolic manifestations during the entire lifespan of sperm maturation. These data involve almost all crucial scenarios related to sperm maturation, including the tissue components of the epididymal microenvironment, cell constituents of tissues, different pathological states, and so on. To the best of our knowledge, SperMD could be one of the limited repositories that provide focused and comprehensive information on sperm maturation. Easy-to-use web services are also implemented to enhance the experience of data retrieval and molecular comparison between humans and mice. Furthermore, the manuscript illustrates an example application demonstrated to systematically characterize novel gene functions in sperm maturation. Nevertheless, SperMD undertakes the endeavor to integrate the islanding omics data, offering a panoramic molecular view of how the spermatozoa gain full reproductive abilities. It will serve as a valuable resource for the systematic exploration of sperm maturation and for prioritizing the biomarkers and targets for precise diagnosis and therapy of male subfertility.

Research on Cross-Cultural Adaptation of International Students from Countries along the Belt and Road Initiative Route

With the implementation of the Belt and Road (B&R) Initiative, China has deepened economic and cultural exchanges and dialogue with the countries along the Belt and Road Initiative route, which has a direct influence on a significant increase in the number of international students in China. Thus, it has become an urgent need for colleges and universities in China to solve the problem of cultivating international students. The huge difference in cultural background, ideology and language between Chinese students and international students, and even among the international students is an important obstacle to the education of international students. In this paper, 160 international students from countries along the Belt and Road Initiative (BRI) route admitted by a Chinese university are selected as the objects to explore the cross-cultural adaptation difficulty confronted by international students. Additionally, this paper aims to put forward several measures in a bid to continuously improve the cross-cultural adaptation of international students and thus promote our economic and cultural exchanges with foreign countries. The B&R Initiative is a kind of global view that China puts forward beyond national and ideological barriers to conform to the historical development trend of human society. It is the inevitable by-product of economic globalization. With the deepening of the B&R initiative, China has deepened its economic and cultural exchanges with the countries along the Belt and Road initiative route, which has led to a significant increase in the number of international students in China. The Annual Report on the Development of Chinese Students Studying Abroad (2017) showed that among the top 15 countries from which international students in China came, most countries were those along the BRI route, among which Thailand, India, Pakistan, Laos, etc., showed a significant increase in the number of overseas students studying in China. This indicates the Initiative’s big role in promoting China's educational cooperation with the countries along the BRI route. However, different language systems, education systems, talent cultivation systems and other barriers have caused an obvious cross-cultural adaptation of international students in China. To this end, this paper aims at promoting international students to better adapt to China's education mode, by exploring the cross-cultural adaptation of international students from countries along the BRI route.

Profile of per- and polyfluoroalkyl substances, source appointment, and determinants in Argentinean postpartum women

BackgroundPer- and polyfluoroalkyl substances (PFAS) are a group of synthetic chemicals with potential adverse health effects. Information concerning PFAS concentrations in relation to pregnancy is scarce in South America and non-existent in Argentina. AimWe aimed to investigate an extended maternal PFAS profile herein serum concentrations in a regional and global view, source appointment, and determinants in Argentinean women. MethodsA cross-sectional study with a sampling period from 2011 to 2012 included 689 women from Ushuaia and Salta in Argentina. Serum samples collected two days postpartum were analyzed by ultra-high pressure liquid chromatography coupled to electrospray negative ionisation tandem-quadrupole mass-spectrometry. Principal Component Analysis (PCA) following absolute principal component score-multiple linear regression (APCS-MLR) was used for PFAS source appointments. Determinants of PFAS were explored through a MLR approach. A review of previous studies within the same period was conducted to compare with present levels. ResultsArgentinean PFAS concentrations were the lowest worldwide, with PFOS (0.74 ng/mL) and PFOA (0.11 ng/mL) as the dominant substances. Detection frequencies largely aligned with the compared studies, indicating the worldwide PFAS distribution considering the restrictions. The PCA revealed region-specific loading patterns of two component groups of PFAS, a mixture of replaced and legacy substances in Ushuaia and long-chain in Salta. This might relate to a mix of non-diet and diet exposure in Ushuaia and diet in Salta. Region, age, lactation, parity, household members, migration, bottled water, and freshwater fish were among the determinants of various PFAS. ConclusionThis is the first study to monitor human PFAS exposure in Argentina. Maternal PFAS concentrations were the lowest observed worldwide in the same period. Exposure contributions are suggested to be affected by restrictions and substitutions. Given the limited population-based studies and the emergence of PFAS, it is essential to conduct further monitoring of PFAS in Argentina and South America.

The Open Data Potential for the Geospatial Characterisation of Building Stock on an Urban Scale: Methodology and Implementation in a Case Study

Energy renovation in buildings is one of the major challenges for the decarbonisation of the building stock. To effectively prioritise decision making regarding the adoption of the most efficient solutions and strategies, it is imperative to develop agile methods to determine the energy performance of buildings on an urban scale, in order to evaluate the impact of these improvements. In this regard, the data collection for feeding building energy models plays a key role in the accuracy and reliability of this issue, and the significant increase in recent years of available data from open data sources offers great potential in this respect. Thus, this study focuses on proposing a systematised and automated method for obtaining information from open data sources so as to obtain the most relevant geometric and thermal characteristics of residential buildings on an urban scale. The criteria for selecting the parameters to be obtained are based on their potential use as input data in different energy demand models aimed at assessing the energy performance of the building stock in a given area and, eventually, to evaluate the potential for improvement and the mitigation of different strategies. Geometric characterisation relies on obtaining and processing open data from cadastres to extract envelope surfaces categorised by orientation through QGIS (Free and Open Source Geographic Information System). For thermal characterisation, an automated process assigns different parameter-based information obtained from cadastral data, such as the year of construction. Finally, the applicability of the method is demonstrated through its implementation in the case study of Bilbao (Spain). The obtained results show that, although additional data should be collected when a detailed analysis of a building or building cluster has to be carried out, the existing open data can provide a first approximation, providing a first global view of the building stock in a region. It demonstrates the usability of the proposed method as an effective way to obtain and process these relevant data.

A learning and evolution-based intelligence algorithm for multi-objective heterogeneous cloud scheduling optimization

The multi-objective directed acyclic graph scheduling problem (MDAGSP) is prevalent in cloud scheduling systems, involving the selection, assignment, and execution of multiple tasks/jobs with complex coupling interdependencies. High-quality solutions can yield substantial economic benefits. However, prevailing methods face challenges in obtaining a set of superior solutions for MDAGSP, due to the multifaceted nature of its variables, objectives, constraints, and heterogeneity. Firstly, this paper formulates a three-objective MDAGSP that includes makespan, energy costs and revenue, to model cloud scheduling systems. Subsequently, we propose a composite algorithm consisting of a selection phase and an assignment phase to automatically generate an efficient scheduling policy for this model. During the selection phase, a graph convolutional neural network learns high-level features to extract complex dependencies between tasks. During the assignment phase, an adaptive evolutionary algorithm assigns tasks to the appropriate executors. Finally, a series of experiments are conducted to validate the model’s accuracy and assess the algorithm’s efficiency. Compared to heuristic approaches, the algorithm achieves at least a 20.1% makespan reduction and 3.17% revenue increase. Remarkably, the algorithm obtains at least an 8.86% reduction in energy costs over the eleven baselines. In conclusion, the proposed algorithm provides decision-makers with a global view of scheduling plan.

Market risk exposure determinants during the COVID-19 outbreak: between competitiveness and inequality

PurposeThe objective of this research is to identify the economic, demographic, sanitary and even cultural factors which explain the variability in the cross-section of returns in different markets globally during the first weeks after the outbreak of COVID-19.Design/methodology/approachBuilding on the event study methodology and using seemingly unrelated equations, the authors created several indicators on the impact of the pandemic in 75 different markets. Then, and using cross-sectional regressions robust to heteroscedasticity and using an algorithm to select independent variables from more than 30 factors, the authors determine which factors were behind the different stock market reactions to the pandemic.FindingsHigher currency depreciation, inflation, interest rate or government deficit led to higher returns, while higher life expectancy, ageing population, GDP per capita or health spending led to the opposite effect. However, the positive effect of competitiveness and the negative effect of income inequality stand out for their statistical and economic significance.Originality/valueThis research provides a global view of investors' reaction to an extreme and unique event. Using a sample of 75 capital markets and testing the relevance of more than 30 variables from all categories, it is, to the authors' knowledge, the largest and most ambitious study of its kind.

Critical Factors in Sample Collection and Preparation for Clinical Metabolomics of Underexplored Biological Specimens.

This review article compiles critical pre-analytical factors for sample collection and extraction of eight uncommon or underexplored biological specimens (human breast milk, ocular fluids, sebum, seminal plasma, sweat, hair, saliva, and cerebrospinal fluid) under the perspective of clinical metabolomics. These samples are interesting for metabolomics studies as they reflect the status of living organisms and can be applied for diagnostic purposes and biomarker discovery. Pre-collection and collection procedures are critical, requiring protocols to be standardized to avoid contamination and bias. Such procedures must consider cleaning the collection area, sample stimulation, diet, and food and drug intake, among other factors that impact the lack of homogeneity of the sample group. Precipitation of proteins and removal of salts and cell debris are the most used sample preparation procedures. This review intends to provide a global view of the practical aspects that most impact results, serving as a starting point for the designing of metabolomic experiments.

The New Wave of CSR-Related Mainstream Accounting Research: On the Performative Effects of Literature Reviews

ABSTRACT This commentary/reflection offers a critical analysis of four articles presenting literature reviews concerning Corporate Social Responsibility (CSR) research in accounting published in North American-based or inspired accounting research journals and of the research on which they focus. This analysis is presented against the backdrop of [Gond, J.P., S. Mena, and S. Mosonyi. 2023. The performativity of literature reviewing: Constituting the corporate social responsibility literature through re-presentation and intervention. Organizational Research Methods 26, no. 2: 195–228] conceptualisation of the performative effects of literature reviews, examinations of the recent resurgence of CSR research in top-tier North American-based accounting journals offered by well-established social and environmental accounting (SEA) researchers, as well as in light of some of the many reviews on the same or similar lines of research. Whilst previous examinations of such resurgence focused on regular articles, this reflection focuses on literature reviews, which I consider a negative development in view of what they represent in terms of the self-referencing behaviour already present in the literature they review. This commentary serves the purpose of cautioning those interested in becoming acquainted with accounting research on CSR-related topics that the reviews examined should not be used as an entry point, given that they offer a rather incomplete picture of such research. Rather, they should only be used after having acquired a global view of CSR-related literature.

Empirical Studies in Communication for Development in Nigeria: The Global View

Purpose: Communication is a vital catalyst for development, especially amidst global societal changes specifically in Nigeria. Engaging individuals actively becomes crucial for societal advancement, necessitating their awareness, involvement, and capacity-building for effective development programs. Establishing robust communication channels between the populace and the government is imperative. This paper examines empirical studies on communication for development within Nigeria and globally, emphasizing its pivotal role in progress and its impact on Nigeria’s socio-economic growth. It explores global perspectives on communication’s inherent advantages in fostering development and highlights challenges hindering the government’s use of communication for national development. Additionally, it analyzes communication for development’s influence on the Millennium Development Goals (MDGs), exploring communication tools used and barriers to their optimal achievement within set time frames. Design/Methodology & Approach: Using comprehensive contextual analysis, this study rigorously reviews publications, textbooks, and pertinent online resources. Findings: Communication significantly contributes to MDGs but faces persistent challenges such as insurgencies, insecurity, literacy gaps, ethnic diversity, and inadequate political will. Addressing these hurdles is crucial for maximizing communication’s developmental benefits. Implications: Neglecting these challenges and failing to fully embrace communication for development in Nigeria will impede anticipated national progress. Originality/Value: This paper underscores communication’s critical role in Nigeria and global development, essential for rapid societal advancement. Paper Type: Conceptual research.

Analyzing temporal coherence for deepfake video detection

<abstract><p>Current facial image manipulation techniques have caused public concerns while achieving impressive quality. However, these techniques are mostly bound to a single frame for synthesized videos and pay little attention to the most discriminatory temporal frequency artifacts between various frames. Detecting deepfake videos using temporal modeling still poses a challenge. To address this issue, we present a novel deepfake video detection framework in this paper that consists of two levels: temporal modeling and coherence analysis. At the first level, to fully capture temporal coherence over the entire video, we devise an efficient temporal facial pattern (TFP) mechanism that explores the color variations of forgery-sensitive facial areas by providing global and local-successive temporal views. The second level presents a temporal coherence analyzing network (TCAN), which consists of novel global temporal self-attention characteristics, high-resolution fine and low-resolution coarse feature extraction, and aggregation mechanisms, with the aims of long-range relationship modeling from a local-successive temporal perspective within a TFP and capturing the vital dynamic incoherence for robust detection. Thorough experiments on large-scale datasets, including FaceForensics++, DeepFakeDetection, DeepFake Detection Challenge, CelebDF-V2, and DeeperForensics, reveal that our paradigm surpasses current approaches and stays effective when detecting unseen sorts of deepfake videos.</p></abstract>

Relational Proxies: Fine-Grained Relationships as Zero-Shot Discriminators.

Visual categories that largely share the same set of local parts cannot be discriminated based on part information alone, as they mostly differ in the way the local parts relate to the overall global structure of the object. We propose Relational Proxies, a novel approach that leverages the relational information between the global and local views of an object for encoding its semantic label, even for categories it has not encountered during training. Starting with a rigorous formalization of the notion of distinguishability between categories that share attributes, we prove the necessary and sufficient conditions that a model must satisfy in order to learn the underlying decision boundaries to tell them apart. We design Relational Proxies based on our theoretical findings and evaluate it on seven challenging fine-grained benchmark datasets and achieve state-of-the-art results on all of them, surpassing the performance of all existing works with a margin exceeding 4% in some cases. We additionally show that Relational Proxies also generalizes to the zero-shot setting, where it can efficiently leverage emergent relationships among attributes and image views to generalize to unseen categories, surpassing current state-of-the-art in both the non-generative and generative settings. Implementation will be made public upon acceptance.