Information Streams Research Articles

Confidence and information usage: Evidence from soil testing in India

AbstractInformational barriers are often considered to be a major constraint to the adoption of improved farming practices, inputs, and technologies by smallholder farmers. In the Indian context, it is widely believed that farmers misapply chemical fertilizers because they lack scientific information on soil conditions and corresponding fertilizer recommendations, thus resulting in imbalanced and potentially detrimental fertilizer application. Policymakers are frequently interested in providing farmers with various streams of information to overcome these informational barriers to optimize farming activities. However, such informational interventions frequently fail either because generic recommendations may be ill‐suited for decision makers in highly heterogeneous agricultural environments or because farmers' beliefs may be so entrenched as to make them unresponsive to new information. We implemented a field experiment in Bihar, India to test whether plot‐specific fertilizer recommendations affect farmers' fertilizer use. We find little evidence for sizable impacts on fertilizer use in general, though impacts are more apparent for low cost or costless recommendations such as increasing the use of highly subsidized fertilizers or shifting the timing of application. Despite modest evidence of such effects, even those fall short of their potential magnitude. We show that treated farmers who are less confident in their subjective beliefs about optimal fertilizer application rates (i.e., with more disperse priors) are more responsive to the recommendations and have a higher ex ante willingness to pay for soil testing. These results suggest that heterogeneity in beliefs may constrain the overall effectiveness of information provision, even when the information is tailored to individual farms.

Subliminal visual stimulation produces behavioural oscillations in multiple frequencies in a visual integration task

We perceive our surrounding as a continuous stream of information. Yet, it is under debate, whether our brain processes the incoming information continuously or rather in a discontinuous way. In recent years, the idea of rhythmic perception has regained popularity, assuming that parieto-occipital alpha oscillations are the neural mechanism defining the rhythmicity of visual perception. Consequently, behavioural response should also fluctuate in the rhythm of alpha oscillations (i.e., at ~ 10 Hz). To test this hypothesis, we employed a visual integration task. Crucially we investigated if a subliminal stimulus preceding the target stimulus modulates behaviour. Our results show that behaviour fluctuates as a function of delay between subliminal and target stimuli. These fluctuations were found in the range of theta, alpha and beta oscillations. Our results further support the idea, that alpha oscillations are a functional rhythm for visual perception, leading to rhythmic fluctuations of perception and behaviour. In addition, other frequencies seem to play a role for temporal perception.

The neural basis of event segmentation: Stable features in the environment are reflected by neural states

Abstract Our senses receive a continuous stream of complex information. Parsing this information into meaningful events allows us to extract relevant information, remember it, and act upon it. Previous research has related these events to so-called neural states: temporally and regionally specific stable patterns of brain activity, which tend to coincide with events in the stimulus. Neural states show a temporal cortical hierarchy: short states are present in early sensory areas, while longer states can be found in higher-level areas. Here we investigated what these neural states represent. We hypothesized that states at different levels of the cortical hierarchy are shaped by aspects of the stimulus to which these brain areas are responsive. To test this hypothesis, we analyzed fMRI data of participants watching a movie, using a data-driven method to identify the neural states. We found support for the aforementioned hypothesis: specifically the parahippocampal place area and retrosplenial cortex, known to be sensitive to places, showed an alignment between neural state boundaries and moments in the movie with a change in location, independent of changes in visual features and other covariates. These findings suggest that neural states reflect stable features in the (internal model of) the external environment, and that the cortical temporal hierarchy partly reflects the temporal scales at which representations of the environment evolve.

A matter of complexity? The role of the dorsal posterior parietal cortex in processing changes in spatial information across time.

The posterior parietal cortex (PPC) is an associative neocortical region that integrates multiple streams of information and is implicated in spatial cognition and decision making. In some cases, however, the PPC is not required for these functions. One possibility is that the PPC is recruited when spatial complexity is high. Yet, few studies of PPC function have explicitly manipulated environmental complexity, complexity of spatial changes, or the temporal structure of spatial tasks. To examine whether task complexity recruits PPC function, we tested rats with neurotoxic damage to the dorsal PPC on a series of tasks varying in spatial and temporal complexity. Recognition memory was first assessed in standard exploration tasks, including object recognition, object location, and object in place, as well as a more complex object task in which spatial changes occurred across multiple delays. Spatial navigation was assessed in the circular hole board maze (Barnes maze), and temporal processing was assessed in a temporal order task. PPC damage spared performance on standard recognition memory tasks but caused deficits on tasks involving changes in object configuration or multiple changes across time. PPC damage spared acquisition on the Barnes maze but impaired retention and decreased efficiency of search strategies. PPC damage did not impact temporal order memory. Overall, these results suggest that the PPC is necessary when spatial complexity of the task increases attentional and long-term memory demands. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Adaptive Probabilistic Neural Network based Edge Data Center Authentication for Secure Load Balancing in Fog Computing

The growth of current technological advances has promising of fog computing, that increases the processing capacity of devices and provides fresh approaches for conventional applications in industry. Fog computing has become increasingly vital given the huge and sophisticated system of sensors to manage the information stream. Node authentication and secure load balancing are important in fog computing. The rationale behind developing this model is that the existing deep learning models are affected by the node authentication performance and also generate issues like high latency developed by the cloud-based architecture while processing huge amount of data, and node employment. Thus, the objective of the developed model is to implement an advanced deep learning method for better node authentication and an appropriate enhanced optimization scheme for performing optimal resource allocation. Additionally, secure load balancing is done at edge node centers in fog computing to allocate the workload for each node securely. Initially, the network initialization attributes in fog computing are provided to the authentication process. Here, the deep learning-based Edge Data Centre (EDC) authentication takes place with the help of the Adaptive Probabilistic Neural Network (A-PNN) model. The major intention of introducing an A-PNN method is to check whether the node is authenticated or not. If the EDC node is authenticated, then the A-PNN model suggests the particular EDC node for the resource allocation process, or else the node will be ignored or removed from the process. Here, the new hybrid approaches as Hybrid Heap with African Buffalo Optimization Algorithm (HH-ABO) are suggested for execute the process of optimization. Here, the parameters of the A-PNN model are tuned for maximizing accuracy, precision, and NPV and also minimizing the False Positive Rate (FPR) rate. Then the authenticated node is subjected to the load-balancing scheme. The allocation of allocation is carried out in the load balancing scheme. Here, the diverse constraints like resource allocation, energy consumption, cost, the execution time of the task, security by authentication, latency, and task completion time are considered for formulating the objective function using the HH-ABO algorithm. At last, it is performed well than the traditional methods using diverse parameters. The outcome demonstrate that the developed model achieved better results on load balancing at edge nodes in fog computing. The proposed model effectively resolves the load balancing issues and also it distributes workload for each node accurately. It effectively resolves the latency and deployment issues. In addition, the modern applications based on the proposed scheme will allow million of workloads from one node to another in a fast and reliable manner.

Moving Ottawa's Department and Agency Reporting Forward: Encouraging Accountability and Sustaining Reform

AbstractGovernments produce a steady stream of data, reports, and other information to ministers, legislators, and the public, and generate enormous flows of administrative data. In the digital era the flows of information generated by departments and agencies have expanded by orders of magnitude. The paradox, though, is that much of this information is never used, but many decision makers believe there is insufficient information to meet their specific needs at any time. This note focuses on two streams of reporting by departments and agencies in the Government of Canada informed by “open government” principles—the streams of information supplied via the Canada InfoBase and other reporting, and the Management Accountability Framework—and considers if they are accessible and useful. After setting out options for making them both more useful, this note argues it will inform the work of spending reviews, Parliamentary committees, and engagement with experts and citizens.

Independent Journalism in the Digital Era: Combating Hate Speech for a Peaceful Society

Digital disruptions toward the promotion of peace in society have never been witnessed before: hate speech, disinformation, and polarized narratives are all on the rise on social media. This paper explores this complex interplay between these digital disruptions and societal cohesion. Independent journalism, in particular, performs an important role in serving the purpose of promoting peace; hate speech breeds hostility; and disinformation muddies perceptions, making mistrust, social fragmentation, and even escalations in conflict their eventual byproducts. Independent journalism is therefore committed to fact-based reporting and neutral narration as the only weapons against such disconnections. This study explores independent journalism as an intermediary and agent of mitigation in curbing such social damage caused by the effects of digital disinformation and hate speech. Through successful case studies and a critical review of methodologies in counter-narrative journalism, the paper underscores what truth-driven media may serve: the development of dialogue, empathy, and peace-building in digitally mediated societies. The very conclusion here highlights the importance of independent journalism as crucial in rebuilding public trust to develop a digitally literate society in information streams it creates toward peace-oriented results.

Artificial fingerprints engraved through block-copolymers as nanoscale physical unclonable functions for authentication and identification

Besides causing financial losses and damage to the brand’s reputation, counterfeiting can threaten the health system and global security. In this context, physical unclonable functions (PUFs) have been proposed to overcome limitations of current anti-counterfeiting technologies. Here, we report on artificial fingerprints that can be directly engraved on a wide range of substrates through self-assembled block-copolymer templating as nanoscale PUFs for secure authentication and identification. Results show that morphological features can be exploited to encode fingerprint-like nanopatterns in binary code matrices representing a unique bit stream of information characterized by high uniqueness and entropy. A strategy based on computer vision concepts for authentication/identification in real-world scenarios is reported. Long-term reliable operation and robust authentication/identification against thermal treatment at cryogenic and high temperatures of the PUF have been demonstrated. These results pave the way for the realization of PUFs embracing the inherent stochasticity of self-assembled materials at the nanoscale.

Real-Time E-commerce Insights with Mean Shift Clustering: A Dynamic Approach to Customer Understanding

In the high-speed universe of internet business, understanding client conduct progressively is urgent for customized encounters and ideal business results. This paper investigates the utilization of Mean Shift bunching, a strong non-parametric thickness-based calculation, for continuous examination in online business. By utilizing Mean Shift's capacity to progressively distinguish bunches of erratic shapes, organizations can acquire important bits of knowledge into client conduct, even as it advances. We show the way that Mean Shift can fragment clients in view of their ongoing perusing movement, search questions, item associations, and buy designs, making dynamic client profiles that mirror their ebb and flow interests and inclinations. This empowers organizations to convey profoundly customized proposals, upgrade valuing techniques, and designer promoting efforts in light of constant client needs. Moreover, we investigate how Mean Shift can be utilized to foresee future client conduct, empowering organizations to expect needs and proactively tailor the shopping experience. The paper additionally addresses the difficulties of carrying out ongoing Mean Shift grouping, including information streaming and adaptability, computational intricacy, and information protection concerns. We finish up by illustrating future exploration headings for improving the viability of Mean Change continuously online business examination, underscoring its capability to reform the manner in which organizations draw in with clients in a dynamic and consistently changing internet based commercial center.

Experiences with COVID-19 economic relief measures among low-wage worker families: a qualitative study

BackgroundEconomic stability is a core social determinant of health and a necessary condition for maintaining food security, housing stability, and both physical and mental health. Using a qualitative approach, we identified barriers, facilitators, and participant perceptions about utilizing these relief measures. This study aimed to understand experiences with COVID-19 economic relief measures among low-wage worker households with children during the COVID-19 pandemic.MethodsThe study conducted semi-structured qualitative interviews from low-wage workers in households with children in two U.S. cities in 2022 (n = 40). The sample was recruited from a larger study which included survey measures of demographics and receipt or utilization of a range of relief measures with both broad and narrow eligibility criteria (e.g., Economic Impact Payments, expanded Supplemental Nutrition Assistance Program (SNAP), Pandemic Electronic Benefit Transfer (P-EBT), expanded Child Tax Credit, expanded unemployment insurance, and the eviction moratorium). A thematic analysis of 40 interviews was conducted using a constructivist approach to grounded theory, from which barriers, facilitators, and participant perceptions were identified.ResultsInterviews identified burdensome administrative processes, administrative errors, and a lack of information as barriers to access among those who were eligible; automatic processes for distributing benefits was identified as a facilitator. Participants expressed positive perceptions about benefits, mixed with some ambivalence about the need to receive them and concern over their discontinuation.ConclusionsA segment of the population at risk of economic instability identified both barriers and facilitators to receiving an array of economic relief measures during the COVID-19 pandemic. Findings suggest that providing automatic processes for enrollment and reliable information streams for learning about benefits can bolster benefit receipt among those at risk of economic instability. These findings can contribute to the base of knowledge for policymakers involved in responding to the next public health emergency.

The critical online diasporic infosphere and counter-public sustenance in an autocratizing society

ABSTRACT This article conceptualizes the critical online diasporic infosphere as an online space constituted by diasporic media, exile media, and overseas-based influencers who share an oppositional orientation toward the home state. The infosphere proffers a constant stream of critical information and perspectives to users in both the diaspora and the home country. Drawing upon theorizations of alternative media and counter-publicity, this study examines the role of the diasporic infosphere in sustaining a counter-public in a home country undergoing rapid autocratization. Analysis of an online survey in Hong Kong shows that a distinction between diasporic information sources and domestic information sources underlies people’s information consumption and sharing via social media. Consumption of diasporic information sources relates to lower levels of political trust, the pro-democracy stance, negative feelings about the contemporary political environment, and perceptions of legal and political risks. Consumption of domestic media sources relates to such variables in the opposite manner.

Managing Information Overload in a Pandemic: Influence of Social Media on Vaccine Attitudes in the Digital Age

Purpose: This study examined how social media influences public health decisions, focusing on how information overload during a pandemic impacts vaccine hesitancy and acceptance across demographics. It analyzed conflicting vaccine information to understand social media's role in shaping attitudes and identify strategies to mitigate its negative effects. Methodology: This study employed a multi-stage sampling method to gather data from diverse age groups, education levels, and occupations. This approach combines various techniques at different stages, making it suitable for large, geographically dispersed populations. By segmenting the population into manageable units, multi-stage sampling improves the accuracy, reliability, and representativeness of the data collected. Findings: The findings reveal that most respondents consider vaccine information on social media unreliable, underscoring the need for greater trust in online discussions. Many feel overwhelmed by conflicting messages, highlighting the necessity for clearer communication. Social media significantly shapes attitudes toward COVID-19 vaccines, with many shifting views after engaging with online content. Additionally, participants report mental health impacts from the constant stream of vaccine information, illustrating information overload. Unique Contributions to Theory, Policy and Practice: This study advances the information overload model by illustrating how excessive and conflicting vaccine information on social media disrupts comprehension and harms mental health. It emphasizes social media's role in shaping health attitudes and advocates for interdisciplinary approaches that incorporate psychological resilience into public health strategies. Findings highlight the need for regulations against misinformation to improve the credibility of online health information and promote trusted sources, particularly verified health organizations. The study also calls for health literacy initiatives to empower the public in navigating misinformation and suggests strategies for managing information overload through social media disengagement. Targeted initiatives that leverage trusted information sources can effectively combat vaccine hesitancy and boost community engagement in public health campaigns, ultimately improving health outcomes.

The human posterior parietal cortices orthogonalize the representation of different streams of information concurrently coded in visual working memory.

The key to adaptive visual processing lies in the ability to maintain goal-directed visual representation in the face of distraction. In visual working memory (VWM), distraction may come from the coding of distractors or other concurrently retained targets. This fMRI study reveals a common representational geometry that our brain uses to combat both types of distractions in VWM. Specifically, using fMRI pattern decoding, the human posterior parietal cortex is shown to orthogonalize the representations of different streams of information concurrently coded in VWM, whether they are targets and distractors, or different targets concurrently held in VWM. The latter is also seen in the human occipitotemporal cortex. Such a representational geometry provides an elegant and simple solution to enable independent information readout, effectively combating distraction from the different streams of information, while accommodating their concurrent representations. This representational scheme differs from mechanisms that actively suppress or block the encoding of distractors to reduce interference. It is likely a general neural representational principle that supports our ability to represent information beyond VWM in other situations where multiple streams of visual information are tracked and processed simultaneously.

Recall as a Window into Hippocampally Defined Events.

We experience the present as a continuous stream of information, but often experience the past in parcels of unique events or episodes. Decades of research have helped to articulate how we perform this event segmentation in the moment, as well as how events and their boundaries influence what we later remember. More recently, neuroscientific research has suggested that the hippocampus plays a role at critical moments during event formation alongside its established role in enabling subsequent recall. Here, we review and explore the relationship between event processing and recall with the perspective that it can be uniquely characterized by the contributions of the hippocampus and its interactions with the rest of the brain. Specifically, we highlight a growing number of empirical studies suggesting that the hippocampus is important for processing events that have just ended, bridging the gap between the prior and current event, and influencing the contents and trajectories of recalled information. We also catalogue and summarize the multifaceted sets of findings concerning how recall is influenced by event structure. Lastly, we discuss several exciting directions for future research and how our understanding of events might be enriched by characterizing them in terms of the operations of different regions of the brain.

Encoding colors and tones into working memory concurrently: A developmental investigation.

Working memory serves as a means to accumulate information and reorganize it. Researchers have long assumed that the natural organization of information is one stream at a time. This logic leads to the expectation that, when two different series of stimuli are to be remembered, performance should be superior if the series are presented one before the other in succession, rather than concurrently. Moreover, different accounts of attentional limits lead to different expectations for the change in the ability to encode two sets across age groups in childhood. Testing children from first grade (6-7years) to adulthood, we presented sequences of colored objects and tones in succession or concurrently (with one color accompanying an unrelated tone) and found that performance was equally good no matter which presentation method was used. The results for both presentation methods closely matched the intricate pattern of development observed by Cowan etal. (2018), who used successive presentation only. We found marked developmental improvement in the ability to retain materials in each modality without an increasing cost of attention-sharing between modalities. Humans at least from the elementary school years through young adulthood thus display an ability to accommodate and organize two concurrent streams of information. RESEARCH HIGHLIGHTS: Memory for stimuli from multiple modalities is relevant to school performance and learning; here we investigate how attention is shared between remembering colors and tones. Participants received four colors and/or four tones for subsequent recognition on a trial, with dual modalities presented successively (0.5s per stimulus) or concurrently (0.5s per pair). Successive versus concurrent presentation had little effect on recognition, and the marked increase in memory performance with age did not come from dividing attention during encoding or maintenance. Children as young as first grade thus can encode and organize for later recognition colors and concurrently-presented, but unrelated, tones.

Initial Validation of the NOL Nociception Level Index® Monitoring System in Black and Multiracial People.

The NOL-Nociception Level Index® is a multiparameter index, based on artificial intelligence for the monitoring of nociception (physiological pain response) during anesthesia that has recently been authorized by the FDA. The monitor utilizes continuous streams of information from a finger probe comprising four sensors, including photoplethysmography, to provide a personalized nociception score on a scale of 0-100. Recent studies have suggested racial bias in pulse oximeter measurements due to the effect of melanin levels on photoplethysmography measurements. Therefore, there is a need to clinically validate new monitoring technologies in patients of all skin tones. The performance of the NOL scale in 8 patients that self-identified as Black or multiracial was compared to a database of 447 consented patients, assessing the response to surgical events at different levels of intensity. The descriptive, pilot data suggest that NOL performance in Black and multiracial patients is not different from the performance shown for the large database. Larger studies utilizing recognized skin tone scales to ensure accurate assessment of skin pigmentation are planned for the future.

TRRHA: A two-stream re-parameterized refocusing hybrid attention network for synthesized view quality enhancement

In multi-view video systems, the decoded texture video and its corresponding depth video are utilized to synthesize virtual views from different perspectives using the depth-image-based rendering (DIBR) technology in 3D-high efficiency video coding (3D-HEVC). However, the distortion of the compressed multi-view video and the disocclusion problem in DIBR can easily cause obvious holes and cracks in the synthesized views, degrading the visual quality of the synthesized views. To address this problem, a novel two-stream re-parameterized refocusing hybrid attention (TRRHA) network is proposed to significantly improve the quality of synthesized views. Firstly, a global multi-scale residual information stream is applied to extract the global context information by using refocusing attention module (RAM), and the RAM can detect the contextual feature and adaptively learn channel and spatial attention feature to selectively focus on different areas. Secondly, a local feature pyramid attention information stream is used to fully capture complex local texture details by using re-parameterized refocusing attention module (RRAM). The RRAM can effectively capture multi-scale texture details with different receptive fields, and adaptively adjust channel and spatial weights to adapt to information transformation at different sizes and levels. Finally, an efficient feature fusion module is proposed to effectively fuse the extracted global and local information streams. Extensive experimental results show that the proposed TRRHA achieves significantly better performance than the state-of-the-art methods. The source code will be available at https://github.com/647-bei/TRRHA.

Positive and Negative Retinotopic Codes in the Human Hippocampus.

The hippocampus is thought to coordinate sensory-mnemonic information streams in the brain, representing both the apex of the visual processing hierarchy and the central hub of mnemonic processing. Yet, the mechanisms underlying sensory-mnemonic interactions in the hippocampus are poorly understood. Recent work in cortex suggests that a retinotopic code - typically thought to be exclusive to visual areas - may help organize internal and external information at the cortical apex via opponent interactions. Here, we leverage high-resolution 7T functional MRI to test whether a bivalent retinotopic code structures activity within the human hippocampus and mediates hippocampal-cortical interactions. In seven densely-sampled individuals, we defined the retinotopic preferences of individual voxels within the hippocampus and cortex during a visual mapping task, as well as their functional connectivity during independent runs of resting-state fixation. Our findings reveal a robust retinotopic code in the hippocampus, characterized by stable population receptive fields (pRFs) with consistent preferred visual field locations across experimental runs. Notably, this retinotopic code is comprised of roughly equal proportions of positive and negative pRFs, aligning with the hypothesized role of negative pRFs in mnemonic processing. Finally, the signed amplitude of hippocampal pRFs predicts functional connectivity between retinotopic hippocampal and cortical voxels. Taken together, these results suggest that retinotopic coding may scaffold internal mnemonic and external sensory information processing within the hippocampus, and across hippocampal-cortical interactions.

Self-Expression and Mental Wellbeing of Malaysian Youths on Social Media

In today's fast-changing technological era, the new generation of youths, namely Gen Z and Millennials, wholeheartedly embrace and are profoundly influenced by the rapid development of social media. It is important to recognize that the impact of VUCA on youth and social media is not solely negative. It is crucial to promote digital literacy, encourage healthy online habits, and foster open conversations and self-expression. Social media platforms provide a constant stream of information, including news, opinions, and updates from friends and peers. The volatility and uncertainty of this information can contribute to feelings of overwhelm and anxiety, especially when it involves negative or distressing content. This study focuses on the use of emoticons and symbols in self-expression as well as the emotional reaction regarding one’s own posts and others. A total of 500 participants were recruited for this study from various parts of Malaysia aged between 18 to 30 years old. Descriptive analysis of the study shows majority of the participants used emoticons and symbols for better self-expression. When it comes to emotional reactions, the Gen Z and Millennials generally show a preference for positive postings. However, they also demonstrate empathy and understanding towards those who share negative postings. This study enhances our understanding of how Malaysian youths express themselves on social media and sheds light on their emotional responses. Keywords: Self-expression, mental wellbeing, emotional responses, social media, youths.

Toward Long Form Audio-Visual Video Understanding

We live in a world filled with never-ending streams of multimodal information. As a more natural recording of the real scenario, long form audio-visual videos (LFAVs) are expected as an important bridge for better exploring and understanding the world. In this article, we propose the multisensory temporal event localization task in long form videos and strive to tackle the associated challenges. To facilitate this study, we first collect a large-scale LFAV dataset with 5,175 videos and an average video length of 210 seconds. Each collected video is elaborately annotated with diversified modality-aware events, in a long-range temporal sequence. We then propose an event-centric framework for localizing multisensory events as well as understanding their relations in long form videos. It includes three phases in different levels: snippet prediction phase to learn snippet features, event extraction phase to extract event-level features, and event interaction phase to study event relations. Experiments demonstrate that the proposed method, utilizing the new LFAV dataset, exhibits considerable effectiveness in localizing multiple modality-aware events within long form videos. We hope that our newly collected dataset and novel approach serve as a cornerstone for furthering research in the realm of LFAV understanding. Project page: https://gewu-lab.github.io/LFAV/ .