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Working memory plays an important role in cognitive science and is a basic process for learning. While working memory is limited in regard to capacity and duration, different cognitive tasks are designed to overcome these difficulties. This study investigated information flow during a novel visual working memory task in which participants respond to exaggerated and normal pictures. Ten healthy men (mean age 28.5 ± 4.57 years) participated in two stages of the encoding and retrieval tasks. The electroencephalogram (EEG) signals are recorded. Moreover, the adaptive directed transfer function (ADTF) method is used as a computational tool to investigate the dynamic process of visual working memory retrieval on the extracted event-related potentials (ERPs) from the EEG signal. Network connectivity and P300 sub-components (P3a, P3b, and LPC) are also extracted during visual working memory retrieval. Then, the nonparametric Wilcoxon test and five classifiers are applied to network properties for features selection and classification between exaggerated-old and normal-old pictures. The Z-values of Ge is more distinctive rather than other network properties. In terms of the machine learning approach, the accuracy, F1-score, and specificity of the k-nearest neighbors (KNN), classifiers are 81%, 77%, and 81%, respectively. KNN classifier ranked first compared with other classifiers. Furthermore, the results of in-degree/out-degree matrices show that the information flows continuously in the right hemisphere during the retrieval of exaggerated pictures, from P3a to P3b. During the retrieval of visual working memory, the networks associated with attentional processes show greater activation for exaggerated pictures compared to normal pictures. This suggests that the exaggerated pictures may have captured more attention and thus required greater cognitive resources for retrieval. [ABSTRACT FROM AUTHOR]

Lakes are important in supporting ecosystem services and livelihoods. However, their food webs and ecological functioning are continuously threatened by anthropogenic influences. Food web models have been widely used in studying trophodynamics, fisheries impacts, and ecological functioning of temperate lakes, but less often in Afrotropical lake systems. We used Ecopath mass‐balanced trophic models annually in 1999, 2010, and 2020 to assess trends in ecosystem function, and the impact of fisheries on the Lake Baringo Ecosystem, a shallow freshwater lake in Kenya. Pre‐balance (PREBAL) and Pedigree analyses supplemented Ecopath models. Model input data were from field sampling, published and gray literature. Food web trophic models indicated a bottom‐up grazer and detrital food chains in all 3 years. Odum's ecosystem development indicators (total productivity to total biomass and total respiration ratios; TPP/TB and TPP/TR) showed that the lake was in a low to intermediate developmental stage, with room for bio‐manipulation, and a highly reduced mean transfer efficiency (TE) (6.4%–0.49%) indicated low trophic transfer of internal production. System omnivory (SOI) and connectance (CI) indices that varied among years indicated temporal variation in food web complexity. Indices of system resilience (overhead and ascendency) indicated an increasing potential for the lake to recover from perturbations. The mean trophic level of the catch (MTLc) increased from 1999 to 2010 and decreased in 2020, by fishing down the food chain as fishing pressure increased. Oreochromis niloticus, an endemic cichlid, was the keystone species (KSi >0) controlling community structure, while the lungfish Protopterus aethiopicus, the top predator in the lake, was not a keystone species (KSi <0). We recommend an integrated approach to lake management that incorporates watershed regulations, regulates fishing effort on the keystone species (O. niloticus), and monitors water quality for sustainable management of the Lake Baringo ecosystem. [ABSTRACT FROM AUTHOR]

Reactive inhibitory control is crucial for survival. Traditionally, this control in mammals was attributed solely to the hyperdirect pathway, with cortical control signals flowing unidirectionally from the subthalamic nucleus (STN) to basal ganglia output regions. Yet recent findings have put this model into question, suggesting that the STN is assisted in stopping actions through ascending control signals to the striatum mediated by the external globus pallidus (GPe). Here, we investigate this suggestion by harnessing a biologically constrained spiking model of the cortico-basal gangliathalamic (CBGT) circuit that includes pallidostriatal pathways originating from arkypallidal neurons. Through a series of experiments probing the interaction between three critical inhibitory nodes (the STN, arkypallidal cells, and indirect pathway spiny projection neurons), we find that the GPe acts as a critical mediator of both ascending and descending inhibitory signals in the CBGT circuit. In particular, pallidostriatal pathways regulate this process by weakening the direct pathway dominance of the evidence accumulation process driving decisions, which increases the relative suppressive influence of the indirect pathway on basal ganglia output. These findings delineate how pallidostriatal pathways can facilitate action cancellation by managing the bidirectional flow of information within CBGT circuits. [ABSTRACT FROM AUTHOR]

Despite being able to predict accurate user-item interactions, recommender systems also lead to homogeneous information flow, resulting in negative online experiences. However, users' coping processes for this stressful event remain basically unclear. Drawing on coping theory, this study examines how users appraise two stressors (information narrowing and information redundancy) in homogenous information flow, especially in different user experiences, and thus adopt algorithmic resistance and avoidance coping strategies. Data (N = 407) were collected based on a survey. The empirical results indicate that information narrowing and information redundancy are significantly and negatively related to challenge appraisal, and exert significant and positive effects on threat appraisal. The moderating effect denotes that user experience strengthens the relationship between information narrowing and information redundancy to threat appraisal. Threat appraisal further triggers algorithmic resistance and avoidance of users. The paper provides several implications for theory and research by revealing the mechanism through which recommender systems users cope with homogeneous information flow. Our findings also provide new insights for designers of recommender systems platforms. [ABSTRACT FROM AUTHOR]

Background: Adverse events occur frequently at emergency departments (ED) because of several risk factors related to varying conditions. It is still unclear, which factors lead to patient safety incident reports. The aim of this study was to explore the root causes behind ED-associated patient safety incidents reported by personnel, and based on the findings, to suggest learning objectives for improving patient safety. Methods: The study material included incident reports (n = 340) which concerned the ED of a teaching hospital over one year. We used a mixed method combining quantitative descriptive statistics and qualitative research by inductive content analysis and deductive Ishikawa root cause analysis. Results: Most (76.5%) incidents were reported after patient transfer from the ED. Nurses reported 70% of incidents and physicians 7.4%. Of the reports, 40% were related to information flow or management. Incidents were evaluated as no harm (29.4%), mild (46%), moderate (19.7%), and severe (1.2%) harm to the patient. The main consequences for the organization were reputation loss (44.1%) and extra work (38.9%). In the qualitative analysis, nine specific problem groups were found: insufficient introduction, adherence to guidelines and protocols, insufficient human resources, deficient professional skills, medication management deficiencies, incomplete information transfer from the ED, language proficiency, unprofessional behaviour, identification error, and patient-dependent problems. Six organizational themes were identified: medical staff orientation, onboarding and competence requirements; human resources; electronic medical records and information transfer; medication documentation system; interprofessional collaboration; resources for specific patient groups such as geriatric, mental health, and patients with substance abuse disorder. Entirely human factor-related themes could not be defined because their associations with system factors were complex and multifaceted. Individual and organizational learning objectives were addressed, such as adherence to the proper use of instructions and adequate onboarding. Conclusions: System factors caused most of the patient safety incidents reported concerning ED. The introduction and training of ED -processes is elementary, as is multiprofessional collaboration. More research is needed about teamwork skills, patients with special needs and non-critical patients, and the reporting of severe incidents. [ABSTRACT FROM AUTHOR]

The inspection of roads for defects, as basic transportation infrastructure, is critical to maintain the efficient and safe operation of the transportation system. Visual perception-based pavement defect detection methods can efficiently and accurately identify pavement issues and provide data support for intelligent preventive maintenance. This paper summarizes the development of pavement defect detection technology, from feature extraction to automatic feature extraction. Deep learning-based pavement defect detection methods are analyzed and compared in three aspects: classification, object detection, and segmentation. By integrating recent research methods, the paper further reviews innovative approaches to pavement defect detection modeling in four areas: information flow models, Transformer models, attention mechanisms, and the application of 3D technology. Additionally, various defect types, pavement defect datasets, and defect detection systems are introduced. Finally, the paper provides an outlook on future trends and summarizes the key findings. [ABSTRACT FROM AUTHOR]

We present a relational program logic for reasoning about information flow properties formalised in an assertion language based on partial equivalence relations. We define and prove the soundness of the logic, a proof technique for precise, logic-based information flow properties. The logic extends Hoare logic and its unary state predicates to binary PER-based predicates for relating observationally equivalent states. A salient feature of the logic is that it is capable of reasoning about programs that test on secret data in a secure manner. [ABSTRACT FROM AUTHOR]

Digital well-being is related to people's abilities to process the information flow in such a way as to maintain a good level of psycho-physic functioning, to react to technostress adequately, and to filter the information flow to recognize cyberepta. The article reviews various studies that indicate good digital practices are related to learning and developing digital skills, ethical use of digital devices, and cyberthreat recognition. [ABSTRACT FROM AUTHOR]

Transparency, a value that must be built through organizational actions, is a challenge commonly faced by public administration. This challenge is addressed through specific actions embedded in the control environment, which become part of the routine and behavior of every public official to establish a constant flow of information within and outside an entity. To gather information supporting the above, a tool was designed (semi-structured interviews) and applied to eight public officials. The results revealed actions within their control environment dynamics, highlighting the interaction that gives organizational meaning to endogenize transparency. This exploration of actions not only opens up new possibilities for making a profound change in organizational culture, starting from managerial levels, but also instills hope and optimism for a more transparent public administration. It underscores the importance of addressing individual and organizational aspects, paving the way for a more transparent future. As a result, this research not only contributes to the development of investigations focused on analyzing the control environment in public organizations but also provides a beacon of hope for public administration professionals and policymakers. [ABSTRACT FROM AUTHOR]

The purpose of this study was to understand students' task value toward a class. Task value is the utility students see in the course material. As expected, good instructional practices (i.e. clarity, nonverbal immediate behaviors) were positive contributors of task value. However, the substantive impact on task value came from information flow, a variable borrowed from the organizational culture literature. The supported model showed instructor clarity and nonverbal immediate behaviors indirectly, positively influenced task value through the mediation of perceived immediacy and information flow. This indicates that a large proportion of whether students have task value in a course hinge upon whether students understand the rationale behind instructors' pedagogical choices. [ABSTRACT FROM AUTHOR]

Bigeye tuna Thunnus obesus is an important migratory species that forages deeply, and El Niño events highly influence its distribution in the eastern Pacific Ocean. While sea surface temperature is widely recognized as the main factor affecting bigeye tuna (BET) distribution during El Niño events, the roles of different types of El Niño and subsurface oceanic signals, such as ocean heat content and mixed layer depth, remain unclear. We conducted A spatial-temporal analysis to investigate the relationship among BET distribution, El Niño events, and the underlying oceanic signals to address this knowledge gap. We used monthly purse seine fisheries data of BET in the eastern tropical Pacific Ocean (ETPO) from 1994 to 2012 and extracted the central-Pacific El Niño (CPEN) indices based on Niño 3 and Niño 4 indexes. Furthermore, we employed Explainable Artificial Intelligence (XAI) models to identify the main patterns and feature importance of the six environmental variables and used information flow analysis to determine the causality between the selected factors and BET distribution. Finally, we analyzed Argo datasets to calculate the vertical, horizontal, and zonal mean temperature differences during CPEN and normal years to clarify the oceanic thermodynamic structure differences between the two types of years. Our findings reveal that BET distribution during the CPEN years is mainly driven by advection feedback of subsurface warmer thermal signals and vertically warmer habitats in the CPEN domain area, especially in high-yield fishing areas. The high frequency of CPEN events will likely lead to the westward shift of fisheries centers. [ABSTRACT FROM AUTHOR]

• Our multimodal quantitative method unveils directional dynamics of epileptic network during interictal to ictal transition. • Epileptogenic zone exhibits maximum outflow during preictal, and at seizure onset. • Regions that are hypoperfused during seizures exhibit maximum outflow during ictal evolution and can serve as a control network. Ictal Single Photon Emission Computed Tomography (SPECT) and stereo-electroencephalography (SEEG) are diagnostic techniques used for the management of patients with drug-resistant focal epilepsies. While hyperperfusion patterns in ictal SPECT studies reveal seizure onset and propagation pathways, the role of ictal hypoperfusion remains poorly understood. The goal of this study was to systematically characterize the spatio-temporal information flow dynamics between differently perfused brain regions using stereo-EEG recordings. We identified seizure-free patients after resective epilepsy surgery who had prior ictal SPECT and SEEG investigations. We estimated directional connectivity between the epileptogenic-zone (EZ), non-resected areas of hyperperfusion, hypoperfusion, and baseline perfusion during the interictal, preictal, ictal, and postictal periods. Compared to the background, we noted significant information flow (1) during the preictal period from the EZ to the baseline and hyperperfused regions, (2) during the ictal onset from the EZ to all three regions, and (3) during the period of seizure evolution from the area of hypoperfusion to all three regions. Hypoperfused brain regions were found to indirectly interact with the EZ during the ictal period. Our unique study, combining intracranial electrophysiology and perfusion imaging, presents compelling evidence of dynamic changes in directional connectivity between brain regions during the transition from interictal to ictal states. [ABSTRACT FROM AUTHOR]

Maintaining diversity in drug development in research into Alzheimer's disease (AD) is necessary to avoid over-reliance on targeting AD neuropathology. Treatments that reduce or prevent the generation of oxidative stress, frequently cited for its causal role in the aging process and AD, could be useful in at-risk populations or diagnosed AD patients. However, in this review, it is argued that clinical research into antioxidants in AD could provide more useful feedback as to the therapeutic value of the oxidative stress theory of AD. Improving comparability between randomized controlled trials (RCTs) is vital from a waste-reduction and priority-setting point of view for AD clinical research. For as well as attempting to improve meaningful outcomes for patients, RCTs of antioxidants in AD should strive to maximize the extraction of clinically useful information and actionable feedback from trial outcomes. Solutions to maximize information flow from RCTs of antioxidants in AD are offered here in the form of checklist questions to improve ongoing and future trials centered around the following dimensions: adhesion to reporting guidelines like CONSORT, biomarker enrichment, simple tests of treatment, and innovative trial design. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to examine the interaction between gatekeeping and trust in a public sector organization, where employees at lower hierarchical levels are expected to autonomously translate and transform directives into public services. This requires them to have access to operational steering information, i.e. information about directives and how to interpret and apply them. This study focuses on how gatekeeping structures regulate flows of operational steering information and how the gatekeeping structures affect the development of trust. Design/methodology/approach: The research design is qualitative. The data material consisted of semi-structured interviews with 26 employees in home care and schools and of eight complementary nonparticipant observations. Thematic analysis revealed the presence of static and dynamic gatekeeping structures, which are characterized by fixed and variable arrangements of information sources and channels, respectively. Findings: In static gatekeeping structures, managers or domain experts typically act as gatekeepers, and employees also perform gatekeeping activities collectively. Gatekeeping structures allow employees to switch between acting as gatekeepers and being gated, depending on the situation. The results show that gatekeeping structures for intermediation of operational steering information may support or impede employees' work, thus affecting their trust in their peers and their work organization. Research limitations/implications: Although the present study included both interviews and observations, these primarily occurred within scheduled and prearranged activities rather than capturing the nuances of the typical daily work of teachers and home care employees. As a result, certain perspectives may have been unintentionally omitted. Practical implications: The participants were recruited through the City of Oslo contact people, which may have impacted their status or perception in some way. Moreover, the study was conducted in the City of Oslo, a specific organization with its own unique set of values, norms and processes. The trust-based management in the City of Oslo is likely not representative of all public sector organizations. Originality/value: This study contributes conceptually by introducing gatekeeping structures and operational steering information and empirically by providing evidence of their relationship to trust development in public service delivery. Thus, it contributes to the research fields of information management and public administration. [ABSTRACT FROM AUTHOR]

Background: Working memory deficits in Alzheimer's disease (AD) are linked to impairments in the retrieval of stored memory information. However, research on the mechanism of impaired working memory retrieval in Alzheimer's disease is still lacking. Objective: The medial prefrontal cortex (mPFC) and mediodorsal thalamus (MD) are involved in memory retrieval. The purpose of this study is to investigate the functional interactions and information transmission between mPFC and MD in the AD model. Methods: We recorded local field potentials from mPFC and MD while the mice (APP/PS1 transgenic model and control) performed a T-maze spatial working memory task. The temporal dynamics of oscillatory activity and bidirectional information flow between mPFC and MD were assessed during the task phases. Results: We mainly found a significant decrease in theta flow from mPFC to MD in APP/PS1 mice during retrieval. Conclusions: Our results indicate an important role of the mPFC-MD input for retrieval and the disrupted information transfer from mPFC to MD may be the underlying mechanism of working memory deficits in APP/PS1 mice. [ABSTRACT FROM AUTHOR]

(1) Background: A current trend observed in the logistics sector is the use of Industry 4.0 tools to improve and enhance the efficiency of cargo handling processes. One of the popular solutions is an augmented reality system that supports operators in everyday tasks. The article aims to present design assumptions for implementing an augmented reality system to support air cargo handling at the warehouse. (2) Methods: Research was carried out based on a five-stage analytical procedure, aiming to analyze the current state and identify the potential for implementing the AR system. The following methods were used to collect data: co-participant observations, process analysis, direct interviews, analysis of internal documentation, and applicable legal regulations. (3) Results: The conducted research allowed for identifying information flows accompanying cargo flows and developing a project to automate selected information flows. The obtained results made it possible to identify operations for which the AR system's implementation will increase their effectiveness and efficiency. (4) Conclusions: The obtained results identified the need to develop a hybrid algorithm for arranging cargo in the warehouse and to build a system supporting self-verification of markings on air cargo. [ABSTRACT FROM AUTHOR]

Aim: To describe the contributing factors and types of reported medication incidents in home care related to the flow of information in different phases of the medication process, as reported by multi‐professional healthcare groups. Design: This descriptive, qualitative study used retrospective data. Methods: An incident‐reporting database was used to collect 14,289 incident reports from 2017 to 2019 in a city in Finland. We used this data to select medication incidents (n = 1027) related to the flow of information in home care and between home care and hospitals. Data were divided into five groups based on the medication phase: (1) prescribing, (2) dispensing, (3) administration, (4) documentation and (5) self‐administration. In addition, the types of medication‐related incidents were described. The data were examined using abductive content analysis. The EQUATOR SRQR checklist was used in this report. Results: Four main categories were identified from the data: (1) issues related to information management, (2) cooperation issues between different actors, (3) work environment and lack of resources and (4) factors related to healthcare workers. Cooperation issues contributed to medication‐related incidents during each phase. Incomplete communication was a contributing factor to medication incidents. This occurred between home care, remote care, hospital, the client and the client's relatives. Specifically, a lack of information‐sharing occurred in repatriation situations, where care transitioned between different healthcare professionals. Conclusion: Healthcare professionals, organisations, clients and their relatives should focus on the efficient and safe acquisition of medications. Specifically, the use of electronic communication systems, together with oral reports and checklists for discharge situations, and timely cooperation with pharmacists should be developed to manage information flows. Relevance to Clinical Practice: These findings demonstrate that healthcare professionals require uniform models and strategies to accurately and safely prescribe, dispense and administer medications in home care settings. No patient or public contributions. [ABSTRACT FROM AUTHOR]

The secure transmission of information is receiving more and more attention nowadays. Aeolus is a novel platform designed to enhance the development of distributed applications by preventing unauthorized disclosure of information. And one of the most representative systems for information transmission is the file system, therefore it is of great significance to formally analyze the Aeolus-based file system. In this paper, we use Communicating Sequential Processes (CSP) to model and formalize the file system based on Aeolus. Moreover, we utilize the Process Analysis Toolkit (PAT) to simulate and verify the CSP description of our established model. We specifically verify the validity of five properties: Deadlock Freedom, Divergence Freedom, Reachability, Secrecy, and Integrity. The verification results demonstrate that the model successfully satisfies these properties, affirming the effectiveness of the framework in ensuring file operations and guaranteeing the secure transmission of information. [ABSTRACT FROM AUTHOR]

Introduction: by doing so, Twitter’s trending algorithm sets the benchmark for what online discussion and information flow look like. It must be clearly understood by the researchers and the users as to how it developed and impacted. Objective: this paper discusses the Twitter trending algorithm discussion until 2023, highlighting its aspects and ethical considerations. Method: to demonstrate trend identification, we adopted a cross-sectional approach that involved data mining of trends defined by the Twitter platform from January 2020 to October 2023, applying machine learning techniques. In total, 1,984,544 unique trends were identified in the two cities over the 1584 days of Twitter API research. Results: this research identified that there are many changes in the current trending algorithm regarding Twitter, and current real-time content and users’ participation are the major concerns. The assessed model, known as TrendDetector, predicts the trend of commercials to be 80 %, while the non-commercial trend is assessed to be 60 %. Trend selection was guided by the traffic of tweets, the number of users, and the extent of new content. Conclusions: user-generated activities, content, and spread, as well as the structure and design of the platform, are thus an intricate mix in the case of the trending algorithm on Twitter. It enhances the timely acquisition of information while being associated with preconditions of bias and manipulation. Future research must look at aspects such as the algorithm’s transparency and the ethicality of the trends it selects. [ABSTRACT FROM AUTHOR]

The features of various supply chain systems use at the enterprise are generalized in the article. The evolution of supply chain systems is studied starting from the material requirements planning (MRP) system, which became the basis for the construction of such systems, to the modern ERP II system with a CSRP unit, as well as DRP-I, DRP-II systems, which emphasize the distribution requirements planning taking into account the requirements and requests of consumers. The main advantages and a number of disadvantages in the context of using MRP, ERP and DRP supply chain systems are identified. The main advantages of the systems analyzed are the integration of data from different sources into a single digital environment, such as procurement plans, reports and other information bases; construction of a flexible system of planning and management of material flows, which provides an opportunity to quickly respond to the needs of supply chains in real time; automation of the main business processes related to the procurement system, production management and logistics, which contributes to the reduction of risks related to the human factor, which can negatively affect the company’s activities. The role of an ERP system is determined, enabling companies to gain a deeper understanding of their supply chain ecosystem. At the same time, the key tasks of the ERP system are the active management of various activities that take place throughout the product life cycle to maximize consumer value, the level of satisfaction of consumer expectations and achieving competitive advantage. The main stages of ERP implementation are studied and summarized. The necessity of resource planning in the ERP system, synchronized with customers, coverage of relations with customers by the formation of the CSRP concept, which involves the integration of the customer into the enterprise management system, is determined. The DRP-I and DRPII systems are characterized, which are implemented for the purpose of planning, accounting and management of transport operations related to the movement of material and technical resources and finished products. [ABSTRACT FROM AUTHOR]

The evolution of the communication process over the centuries highlights humanity's need to live in society. Legal language is complex due to its technical-legal application, the use of jargon, and expressions in Latin. In this context, this research aims to present Visual law and analyze its impact on legal communication processes in Brazil. To this end, it discusses legal communication, its elements, the democratization of information, and Visual law. The methodology adopts an integrative literature review, qualitative research, and exploratory and documentary research. The conclusion is that Visual law, in the context of legal communication, can be used as a tool to provide clarity and objectivity in legal communication for the entire society, contributing to the democratization of information. Studies in the field of Information Science that involve communication processes beyond legal communication are important. [ABSTRACT FROM AUTHOR]

This study investigates how financial sanctions packages targeting Russia influenced traditional information flow dynamics with other international financial markets and products. While providing empirical evidence regarding the use of payment systems and finance as weapons of war, it is crucial to understand if the market's response to international sanctions diminished as expectations shifted over time. Results, supported by robustness testing procedures, indicate important dynamic information flows relating to specific sanctions after the onset of the Russia-Ukraine war. In particular, those sanctions relating to the exclusion of Russia from the SWIFT payment system and those targeting banks and private wealth resulted in significant contagion effects sourced from all Russian markets examined. Such influence, however, is found to moderate and dilute as investors reconstruct their expectations and valuations. While targeted sanctions appear to impose intended market isolation, it is also associated with significant contagion effects. Although such secondary effects dissipate, they should be seen as important when implementing further targeted sanction packages. [ABSTRACT FROM AUTHOR]

This research used the newly developed tool of ICEEMDAN (improved complete ensemble empirical mode decomposition with adaptive noise) to decompose the Baidu index among 336 prefectural-level administrative units in China. Then this paper constructed directed networks to compare with undirected networks by analyzing the evolutionary characteristics of urban hierarchy structure, node asymmetry, spatial organization, and structural complexity in information networks between 2014 and 2019. The results show that: ① A large amount of noise interference exits in intercity Baidu search data, and noise reduction processing is necessary. After noise decomposition, the long-term trend data can better reveal the evolution characteristics of nodes. ② Considering the significant asymmetry of the information network, directed network analysis is a more effective method than undirected network analysis to identify the difference between node characteristics and their trends. ③ Node degree centrality shows a disproportional growth path, demonstrating growth dominance shifting from in-degree to out-degree at different stages. ④ Dominant flow analysis sheds light on two spatial organization patterns in the information network. One pattern is on the national scale, with disassortative network and scale-free network features. The other is on urban agglomerations and provincial scales and features assortative network and small-world network properties. The information network organization is a complex process, especially with the differences in long distance and geographic proximity interactions as two patterns indicate. This illustrates the characteristics of the spatial organization of two models, the Center Place Model and the Network Model, as well as the interaction between cyberspace and physical space. [ABSTRACT FROM AUTHOR]

Sleep is a highly stereotyped phenomenon, requiring robust spatiotemporal coordination of neural activity. Understanding how the brain coordinates neural activity with sleep onset can provide insights into the physiological functions subserved by sleep and the pathologic phenomena associated with sleep onset. We quantified whole-brain network changes in synchrony and information flow during the transition from wakefulness to light non-rapid eye movement (NREM) sleep, using MEG imaging in a convenient sample of 14 healthy human participants (11 female; mean 63.4 years [SD 11.8 years]). We furthermore performed computational modeling to infer excitatory and inhibitory properties of local neural activity. The transition from wakefulness to light NREM was identified to be encoded in spatially and temporally specific patterns of long-range synchrony. Within the delta band, there was a global increase in connectivity from wakefulness to light NREM, which was highest in frontoparietal regions. Within the theta band, there was an increase in connectivity in fronto-parieto-occipital regions and a decrease in temporal regions from wakefulness to Stage 1 sleep. Patterns of information flow revealed that mesial frontal regions receive hierarchically organized inputs from broad cortical regions upon sleep onset, including direct inflow from occipital regions and indirect inflow via parieto-temporal regions within the delta frequency band. Finally, biophysical neural mass modeling demonstrated changes in the anterior-to-posterior distribution of cortical excitation-to-inhibition with increased excitation-to-inhibition model parameters in anterior regions in light NREM compared with wakefulness. Together, these findings uncover whole-brain corticocortical structure and the orchestration of local and long-range, frequency-specific cortical interactions in the sleep-wake transition. [ABSTRACT FROM AUTHOR]

As improved recording technologies have created new opportunities for neurophysiological investigation, emphasis has shifted from individual neurons to multiple populations that form circuits, and it has become important to provide evidence of cross-population coordinated activity. We review various methods for doing so, placing them in six major categories while avoiding technical descriptions and instead focusing on high-level motivations and concerns. Our aim is to indicate what the methods can achieve and the circumstances under which they are likely to succeed. Toward this end, we include a discussion of four crosscutting issues: the definition of neural populations, trial-to-trial variability and Poisson-like noise, time-varying dynamics, and causality. [ABSTRACT FROM AUTHOR]

Replay attacks are among the most well-known attacks against vote privacy. Many e-voting systems have been proven vulnerable to replay attacks, including systems like Helios that are used in real practical elections. Despite their popularity, it is commonly believed that replay attacks are inefficient but the actual threat that they pose to vote privacy has never been studied formally. Therefore, in this paper, we precisely analyze for the first time how efficient replay attacks really are. We study this question from commonly used and complementary perspectives on vote privacy, showing as an independent contribution that a simple extension of a popular game-based privacy definition corresponds to a strong entropy-based notion. Our results demonstrate that replay attacks can be devastating for a voter's privacy even when an adversary's resources are very limited. We illustrate our formal findings by applying them to a number of real-world elections, showing that a modest number of replays can result in significant privacy loss. Overall, our work reveals that, contrary to a common belief, replay attacks can be very efficient and must therefore be considered a serious threat. [ABSTRACT FROM AUTHOR]

There is a lack of knowledge of the interactions required over time among the members of a building project design team. Without a specific target, it is impossible to identify gaps to propose improvement plans in the coordination and management of projects in the early stages. Therefore, this study proposes a model of the required interaction among the members of a building project design team during the different phases of the design process. The research was divided into three stages: (1) design team interactions; (2) construction of ideal interaction networks and proposed evaluation model; and (3) pilot cases—evaluation and analysis. Through this study, eight ideal networks were constructed, four for each interaction (information flow, collaboration, and coordination) and one for each design phase. In addition, a series of metrics were proposed to evaluate the current state of a building project, which, together with the constructed model networks, allowed the development of an evaluation method for real projects. Finally, two pilot cases were used to exemplify the use of the proposed model tool. [ABSTRACT FROM AUTHOR]

As the important concepts in Systemic Functional Linguistics, theme and rheme form the thematic structure. The connections between themes and rhemes of the preceding sentences and those of the latter sentences constitute patterns of thematic progression. Both the relations among thematic structures and the various thematic progression patterns help construct coherent meaning in a text. Based on Halliday's theory of thematic structure and Martin's information flow theory, this study probes into the function of macro-theme, hyper-themes and themes in construction of the textual coherence in children's picture book "Sylvester and the Magic Pebble". The themes and rhemes are identified in every sentence of this children's picture book, at the same time, the percentage and usage of different types of themes and thematic progression patterns are calculated and analyzed. The result shows that the proportion of simple theme accounts to 68.1%. The simple themes are mainly undertaken by nouns and noun phrases. The textual coherence is also realized by other forms of cohesive ties, for example, reference, substitution, and lexical cohesion. The findings also show that there are four progression patterns adopted in the children's picture book, nevertheless, the parallel and continuous progression patterns are most frequently used. The predictive function between different hierarchical themes makes the cohesion and coherence more natural and concise. Besides helping writers create better picture books with effective coherence, the theories of thematic structure and information flow help children grasp the important information of the story and build their emotions. [ABSTRACT FROM AUTHOR]

Using functional neuroimaging, electrophysiological techniques and neural data processing techniques, neuroscientists have found that mathematically gifted adolescents exhibit unusual neurocognitive features in the activation of task-related brain regions. Hemispheric information interaction, functional reorganization of networks, and utilization of task-related brain regions are beneficial to rapid and efficient task processing. Based on Granger causality channel selection, the transfer entropy (TE) value between effective channels was computed, and the information flow patterns in the directed functional brain networks derived from electroencephalography (EEG) data during deductive reasoning tasks were explored. We evaluated the workspace configuration patterns of the brain network and the global integration characteristics of separated brain regions using node strength, motif, directed clustering coefficient and characteristic path length in the brain networks of mathematically gifted adolescents with effective connectivity. The empirical results demonstrated that a more integrated functional network at the global level and a more efficient clique at the local level support a pattern of workspace configuration in the mathematically gifted brain that is more conducive to task-related information processing. [ABSTRACT FROM AUTHOR]

Electroconvulsive therapy is effectively used for treatment-resistant depression; however, its neural mechanism is largely unknown. Resting-state functional magnetic resonance imaging is promising for monitoring outcomes of electroconvulsive therapy for depression. This study aimed to explore the imaging correlates of the electroconvulsive therapy effects on depression using Granger causality analysis and dynamic functional connectivity analyses. We performed advanced analyses of resting-state functional magnetic resonance imaging data at the beginning and intermediate stages and end of the therapeutic course to identify neural markers that reflect or predict the therapeutic effects of electroconvulsive therapy on depression. We demonstrated that information flow between the functional networks analyzed by Granger causality changes during electroconvulsive therapy, and this change was correlated with the therapeutic outcome. Information flow and the dwell time (an index reflecting the temporal stability of functional connectivity) before electroconvulsive therapy are correlated with depressive symptoms during and after treatment. First, the sample size was small. A larger group is needed to confirm our findings. Second, the influence of concomitant pharmacotherapy on our results was not fully addressed, although we expected it to be minimal because only minor changes in pharmacotherapy occurred during electroconvulsive therapy. Third, different scanners were used the groups, although the acquisition parameters were the same; a direct comparison between patient and healthy participant data was not possible. Thus, we presented the data of the healthy participants separately from that of the patients as a reference. These results show the specific properties of functional brain connectivity. • Information flow between networks changes during electroconvulsive therapy (ECT). • This change was correlated with the therapeutic outcome. • Information flow before ECT correlated with depressive symptoms during and after ECT. • Dwell time before ECT correlated with depressive symptoms during and after ECT. [ABSTRACT FROM AUTHOR]

We investigate the effects of different stochastic noises on the dynamics of the edge-localised modes (ELMs) in magnetically confined fusion plasmas by using a time-dependent PDF method, path-dependent information geometry (information rate, information length), and entropy-related measures (entropy production, mutual information). The oscillation quenching occurs due to either stochastic particle or magnetic perturbations, although particle perturbation is more effective in this amplitude diminishment compared with magnetic perturbations. On the other hand, magnetic perturbations are more effective at altering the oscillation period; the stochastic noise acts to increase the frequency of explosive oscillations (large ELMs) while decreasing the frequency of more regular oscillations (small ELMs). These stochastic noises significantly reduce power and energy losses caused by ELMs and play a key role in reproducing the observed experimental scaling relation of the ELM power loss with the input power. Furthermore, the maximum power loss is closely linked to the maximum entropy production rate, involving irreversible energy dissipation in non-equilibrium. Notably, over one ELM cycle, the information rate appears to keep almost a constant value, indicative of a geodesic. The information rate is also shown to be useful for characterising the statistical properties of ELMs, such as distinguishing between explosive and regular oscillations and the regulation between the pressure gradient and magnetic fluctuations. [ABSTRACT FROM AUTHOR]

This paper introduces a design and analysis method of the intelligent multiple-vehicle system (IMVS) based on preview control in the environment of the vehicle to vehicle (V2V). Considering the time delay, the vehicle longitudinal dynamics system is constructed. The information flow between vehicles in the platoon is realized by the onboard sensors and V2V. Based on the actual data sampling and processing, the cooperative optimal preview control problem of the vehicle platoon stability system is discretized. The error is used as a term of the state vector to expand, and the original problem is transformed into an augmented global optimal control problem. The existence and stability of the controller solution are analyzed. The asymptotically stable optimal control law is obtained by using the state augmented matrix, and the global optimal preview controller of original platoon stability is obtained. The simulation results verify the effectiveness of the designed controller. The following error decreases with the increase of the preview step, which ensures the stability of the platoon. From the first follower to the tenth one, the average spacing error decreases by 92.9 %, and the average following error of velocity decreases from 3.97 to 1.56 %. [ABSTRACT FROM AUTHOR]

Production planners in construction face several problems related to the lack of information regarding construction project status, changes to resource availability, instability in production rates, design changes, and limited situational awareness (SA). Poor SA leads to uninformed and suboptimal resource allocation decisions. As a result, the construction workflow is negatively affected, degrading project performance. This study focuses specifically on possible relationships between production planners' SA and the resulting workflow quality. Such understanding can lead to the development of measures to improve production management in construction. Interviews with diverse production planners highlighted the nature of the information needed, issues related to the lack of SA, and the effect on workflow. A serious roleplaying game was devised to measure the correlation between production planners' SA and workflow, and 14 live simulation experiments were conducted with two teams of nine players each. Finally, a qualitative analysis of the information flow configurations applied in the experiments evaluated the expected effects of information flows in the live experiment. The study found a positive correlation between the quality of information flow and workflow in construction, indicating causation in line with theoretical expectations. Specifically, free communication among planners together with management tools such as formal weekly work planning and a digital planning tool reduced the assembly time, working time, and non-value-added time of the subcontractors in the experiments. Good information flows among production planners and an up-to-date jobsite status diminish uncertainty and increase SA, which lead to improved workflow and productivity. [ABSTRACT FROM AUTHOR]

Security-critical software applications contain confidential information which has to be protected from leaking to unauthorized systems. With language-based techniques, the confidentiality of applications can be enforced. Such techniques are for example type systems that enforce an information flow policy through typing rules. The precision of such type systems, especially in object-oriented languages, is an area of active research: an appropriate system should not reject too many secure programswhile soundly preserving noninterference. In this work, we introduce the language SIFO which supports information flow control for an object-oriented language with type modifiers. Typemodifiers increase the precision of the type system by utilizing immutability and uniqueness properties of objects for the detection of information leaks. We present SIFO informally by using examples to demonstrate the applicability of the language, formalize the type system, prove noninterference, implement SIFO as a pluggable type system in the programming language L42, and evaluate it with a feasibility study and a benchmark. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a nonlinear stochastic model to describe the propagation of information inside a computer processor. In this model, a computational task is divided into stages, and information can flow from one stage to another. The model is formulated as a spatially-extended, continuous-time Markov chain where space represents different stages. This model is equivalent to a spatially-extended version of the M/M/s queue. The main modeling feature is the throttling function which describes the processor slowdown when the amount of information falls below a certain threshold. We derive the stationary distribution for this stochastic model and develop a closure for a deterministic ODE system that approximates the evolution of the mean and variance of the stochastic model. We demonstrate the validity of the closure with numerical simulations. • Spatially-extended Markov chain modeling information flow is considered. • This model is equivalent to a tandem M/M/s queue. • A deterministic ODE closure model for the first two moments is developed. • The ODE model reproduces the first two moments in non-stationary regimes. • Negative binomial distribution is used to develop the closure model. [ABSTRACT FROM AUTHOR]

Predicting drug–drug interactions (DDIs) is crucial for understanding and preventing adverse drug reactions (ADRs). However, most existing methods inadequately explore the interactive information between drugs in a self-supervised manner, limiting our comprehension of drug–drug associations. This paper introduces EDDINet : E nhancing D rug- D rug I nteraction Prediction via Information Flow and Consensus-Constrained Multi-Graph Contrastive Learning for precise DDI prediction. We first present a cross-modal information-flow mechanism to integrate diverse drug features, enriching the structural insights conveyed by the drug feature vector. Next, we employ contrastive learning to filter various biological networks, enhancing the model's robustness. Additionally, we propose a consensus regularization framework that collaboratively trains multi-view models, producing high-quality drug representations. To unify drug representations derived from different biological information, we utilize an attention mechanism for DDI prediction. Extensive experiments demonstrate that EDDINet surpasses state-of-the-art unsupervised models and outperforms some supervised baseline models in DDI prediction tasks. Our approach shows significant advantages and holds promising potential for advancing DDI research and improving drug safety assessments. Our codes are available at: https://github.com/95LY/EDDINet_code. • EDDINet is proposed via Information Flow and Consensus-Constrained Multi-Graph Contrastive Learning. • Introduce the cross-modal information-flow mechanism to facilitate the information across various drug features. • EDDINet surpasses state-of-the-art unsupervised models and even outperforms some supervised baseline models in DDI prediction tasks. [ABSTRACT FROM AUTHOR]

Deciphering brain network topology can enhance the depth of neuroscientific knowledge and facilitate the development of neural engineering methods. Effective connectivity, which gauges the directional influences among brain regions, is pivotal for these studies. This research introduces InfoFlowNet, a novel self-supervised learning model designed to infer causal relationships in electroencephalogram (EEG) data, aiming at capturing the complex information flow among brain regions. Specifically, InfoFlowNet employs convolution operations and multi-head self-attention mechanisms with a masking feature, which ignores self-connections to focus on inter-regional dynamics. Additionally, a new causal magnitude estimation is introduced by assessing the impact of shuffled surrogate data on signal prediction to quantify causal influence. Experiments using synthetic data and real EEG datasets demonstrate that InfoFlowNet effectively uncovers time-varying causal relationships. Compared with the Granger causality model (GCM) and the temporal causal discovery framework (TCDF), InfoFlowNet shows superior sensitivity in detecting significant causal edges. For instance, in a psychomotor vigilance task, InfoFlowNet identified 8 out of 16 significant causal edges, significantly outperforming GCM and TCDF. Furthermore, InfoFlowNet successfully passes the whiteness test on the model's residuals, and advanced analyses illustrate the advantages of utilizing multi-head attention and masking mechanisms to capture effective connectivity. In sum, InfoFlowNet represents a significant advancement in the analysis of effective connectivity, offering a deeper understanding of brain network dynamics. The model's ability to discern complex causal interactions supports its potential application in broader neuroscientific research and applications. • InfoFlowNet is proposed to uncover brain effective connectivity. • InfoFlowNet's attention and masking mechanisms aid brain process reconstruction. • InfoFlowNet gauges information flow by loss from shuffling in model inference. [ABSTRACT FROM AUTHOR]

Low‐beta (13–23 Hz) event‐related desynchrony (ERD), a neural signature of expressive language, lateralizes from bilateral to left hemisphere in development. In contrast, low‐beta event‐related synchrony (ERS), thought to reflect inhibition, lateralizes from bilateral to the right hemisphere across development. Using whole‐brain directed connectivity analyses, we aimed to characterize hemispheric and regional contributions to expressive language, in childhood. We studied 80 children and adolescents, 4 to less than 19 years of age, performing covert auditory verb generation in magnetoencephalography. Outdegree, indegree, and betweenness centrality were used to differentiate regions acting as drivers, receivers, and bridging hubs, respectively. The number of suprathreshold connections significantly increased with age for delta band (p <.01). Delta outflow was mapped to left inferior frontal gyrus (IFG), while regions of right hemisphere, including right IFG, showed significant inflow. The right parietal cortex showed significant ERS, but without corresponding outdegree or indegree. Betweenness mapped to midline cortical and subcortical structures. Results suggest Broca's area develops a driving role in the language network, while Broca's homologue receives information without necessarily propagating it. Subcortical and midline hubs act as intrahemispheric relays. Findings suggest that Broca's homologue is inhibited during expressive language, in development. [ABSTRACT FROM AUTHOR]

The identification of city communities is essential for the regional planning and management of metropolitan areas. City communities could be identified from the perspective of mobile flows, and integrating the advantages of multisource flow data is essential to measure intercity connectivity. In this research, a multisource flow fusion method, which avoids the one-sidedness of a single flow, is proposed to combine the characteristics of population flow, traffic flow, and information flow. Moreover, the silhouette coefficient and hierarchical clustering algorithm are used to determine the number of city communities and the final clustering result. The results show that (1) although population flow, cargo flow, and information flow are positively correlated, there are also some differences among them; (2) the fusion flow between cities in China presents an obvious diamond structure, among which Beijing, Shanghai, Guangzhou, and Chengdu are the four points of the diamond, and Wuhan is located almost in the centre of the diamond structure; and (3) city communities are identified based on multisource flow and hierarchical clustering algorithm, which meet the principles that closely connected cities are in the same community and nonclosely connected cities are in different communities. [ABSTRACT FROM AUTHOR]

This paper investigates the fact that construction projects, due to their specificity, are complex, temporary and dynamic. Over their course, participants change, successive construction works are done and new information becomes available. This carries over to difficulties in communication. In the literature, numerous studies note the fact that a network-based approach to the analysis and monitoring of communication as a part of complex construction projects is commendable. Relations between agents, knowledge and tasks in the context of communication within a construction project can be visualized in the form of a meta-network, and suitably developed structural measures can be used to analyze them. In this paper, the authors used meta-network theory to analyze relations between project participants, knowledge and tasks in the context of communication within a construction project, on the basis of the construction of a housing estate located in Katowice, Poland. Meta-network structural analysis allowed for a deeper understanding of these relations and the detection of essential information about the level of communication in the project under investigation, which was a basis for further discussion. The authors also stress the benefits from the approach presented and argue that it should be a starting point for effective management in the sphere of communication in construction companies. [ABSTRACT FROM AUTHOR]

The study of the two-way information flow between cities is of great significance to promote regional coordinated development, but the current mainstream non-directional network analysis method cannot analyze it effectively. In this paper, the quantities of relevant media articles in WeChat and Weibo between cities are taken as the traffic indices to construct a directional and weighted urban network of the Chengdu-Chongqing Economic Circle in China. Based on this network construction method, which adds direction thinking, we analyze the characteristics of information interconnection between cities. According to the analysis, we find that the provincial boundary hinders information interconnection, and the imbalance of external information interconnection is more serious in Chongqing's central urban area, Liangping, Ya'an and Mianyang. In addition, we analyze the centrality status of different cities in the outward and inward perspective and further explore the factors that cause these differences in centrality. The results show that the centrality of the information network is not sensitive to the basic strength of the city, and it is the accessibility, including high-speed rail transportation access and telecommunication access, which controls the centrality of the city network. [ABSTRACT FROM AUTHOR]

This research identified and analyzed, by a systematic review of the literature, the relationship between information and values in supporting the decision making, in the corporate sustainability context. It was verified that the relationships between information and values, in the researched context, take place from three "macro processes": Information and Knowledge Management, Informational Strategy, and Dissemination of Information. These relationships range all the stages of the decision making, affecting the rationale applied by the decision-maker regarding the adherence of corporate sustainability practices. This suggests that the organizations may benefit themselves when developing information presentation strategies aligned, not only to the stakeholders' values, but also in the way that these values engage with the information. [ABSTRACT FROM AUTHOR]

Molecular motors, kinesin and myosin, are dimeric consisting of two linked identical monomeric globular proteins. Fueled by the free energy generated by ATP hydrolysis, they walk on polar tracks (microtubule or filamentous actin) processively, which means that only one head detaches and executes a mechanical step while the other stays bound to the track. One motor head must regulate the chemical state of the other, referred to as "gating", a concept that is still not fully understood. Inspired by experiments, showing that only a fraction of the energy from ATP hydrolysis is used to advance the kinesin motors against load, we demonstrate that the rest of the energy is associated with chemical transitions in the two heads. The coordinated chemical transitions involve communication between the two heads - a feature that characterizes gating. We develop a general framework, based on information theory and stochastic thermodynamics, and establish that gating could be quantified in terms of information flow between the motor heads. Applications tokinesin-1 and Myosin V show that information flow, with positive cooperativity, at external resistive loads less than a critical value, Fc. When force exceeds Fc, effective information flow ceases. Interestingly, Fc, which is independent of the input energy generated through ATP hydrolysis, coincides with the force at which the probability of backward steps starts to increase. Our findings suggest that transport efficiency is optimal only at forces less than Fc, which implies that these motors must operate at low loads under in vivo conditions. [ABSTRACT FROM AUTHOR]

Compiler optimizations can be functionally correct but not secure. In this work, we attempt to quantify the information leakage in a program for the security verification of compiler optimizations. Our work has the following contributions. We demonstrate that static taint analysis is applicable for security verification of compile optimizations. We develop a completely automated approach for quantifying the information leak in a program in the context of compiler optimizations. Our method avoids many false-positives scenarios due to implicit flow. It can handle leaks in a loop and propagates leaks over paths using the leak propagation vector. With our quantification parameters, we verify the relative security of source and transformed programs considering the optimizations phase of a compiler as a black box. Our experimental evaluations on benchmarks for various compiler optimizations in SPARK show that the SPARK compiler is actually leaky. [ABSTRACT FROM AUTHOR]

Source activity was extracted from resting-state magnetoencephalography data of 103 subjects aged 18–60 years. The directionality of information flow was computed from the regional time courses using delay symbolic transfer entropy and phase entropy. The analysis yielded a dynamic source connectivity profile, disentangling the direction, strength, and time delay of the underlying causal interactions, producing independent time delays for cross-frequency amplitude-to-amplitude and phase-to-phase coupling. The computation of the dominant intrinsic coupling mode (DoCM) allowed me to estimate the probability distribution of the DoCM independently of phase and amplitude. The results support earlier observations of a posterior-to-anterior information flow for phase dynamics in {α1, α2, β, γ} and an opposite flow (anterior to posterior) in θ. Amplitude dynamics reveal posterior-to-anterior information flow in {α1, α2, γ}, a sensory-motor β-oriented pattern, and an anterior-to-posterior pattern in {δ, θ}. The DoCM between intra- and cross-frequency couplings (CFC) are reported here for the first time and independently for amplitude and phase; in both domains {δ, θ, α1}, frequencies are the main contributors to DoCM. Finally, a novel brain age index (BAI) is introduced, defined as the ratio of the probability distribution of inter- over intra-frequency couplings. This ratio shows a universal age trajectory: a rapid rise from the end of adolescence, reaching a peak in adulthood, and declining slowly thereafter. The universal pattern is seen in the BAI of each frequency studied and for both amplitude and phase domains. No such universal age dependence was previously reported. [ABSTRACT FROM AUTHOR]

Android security researchers utilize taint analysis to uncover apps' bugs and policy-violating behaviors. However, the investigations are unsafe because current taint trackers can be circumvented by apps that cause information flows across API calls. A context-tainting tracker (CTT) is devised to tackle the problem, but since the technique relies on a hand-picked list of flow-causing API methods, it will miss information flows when unlisted methods are exploited. It can also produce a large number of false positives and cannot be practically used. This paper presents a new taint-tracking technique operating value logging and matching based on the flows' characteristics to track them with reducing the dependency on the list of API methods. We implemented our approach into our taint tracker called VTDroid. We confirmed its effectiveness with our test suite consisting of 31 anti-taint analysis techniques compared to three current tools: CTT, TaintDroid, and FlowDroid. We also evaluated VTDroid and the current tools with popular apps collected from two major app stores. The results show that VTDroid outperforms CTT in precision and TaintDroid and FlowDroid in recall for privacy leak detection. Also, security analysts can utilize VTDroid to detect user input validations with slightly more false positives and fewer false negatives than FlowDroid in VTDroid's code coverage. [ABSTRACT FROM AUTHOR]

Aiming at the problem of complex and discrete parallel relationships among flexible units in the scheduling process of flexible production lines, a Petri net model applicable to the scheduling study of flexible production lines was proposed, taking the flexible production lines of machine tool holders as an example. Firstly, the composition structure of Petri net was analyzed, and the delay function of flexible unit variation was designed. Then, the production scheduling relationship of each flexible unit in the production line was analyzed, and the modular Petri net model of flexible unit was established. Finally, the scheduling Petri net model of modular flexible unit simplified seat class flexible production line was adopted, and the transfer relationship between multiple systems and flexible units in the production scheduling process was studied, and the Petri net model based on information flow was established. ‘The information transfer relationship between multiple systems and flexible u established. ‘The reachable tree analysis method was adopted to study all possible change sequences, and the reachable tree diagram of Petri net was designed to verify the feasibility of the established Petri net model. ‘The research results show that the flexible production scheduling, the production scheduling process was studied, and the Petri net model based on information flow was ‘model of machine tool seat class based on Petri net was feasible and reasonable, and the dynamic production scheduling of flexible production line can be further carried out on this basis. [ABSTRACT FROM AUTHOR]

In this review, we discuss various methods of reproducing life dynamics using a constructive approach. An increase in the structural complexity of a model protocell is accompanied by an increase in the stage of reproduction of a compartment (giant vesicle; GV) from simple reproduction to linked reproduction with the replication of information molecules (DNA), and eventually to recursive proliferation of a model protocell. An encounter between a plural protic catalyst (C) and DNA within a GV membrane containing a plural cationic lipid (V) spontaneously forms a supramolecular catalyst (C@DNA) that catalyzes the production of cationic membrane lipid V. The local formation of V causes budding deformation of the GV and equivolume divisions. The length of the DNA strand influences the frequency of proliferation, associated with the emergence of a primitive information flow that induces phenotypic plasticity in response to environmental conditions. A predominant protocell appears from the competitive proliferation of protocells containing DNA with different strand lengths, leading to an evolvable model protocell. Recently, peptides of amino acid thioesters have been used to construct peptide droplets through liquid–liquid phase separation. These droplets grew, owing to the supply of nutrients, and were divided repeatedly under a physical stimulus. This proposed chemical system demonstrates a new perspective of the origins of membraneless protocells, i.e., the "droplet world" hypothesis. Proliferative model protocells can be regarded as autonomous supramolecular machines. This concept of this review may open new horizons of "evolution" for intelligent supramolecular machines and robotics. [ABSTRACT FROM AUTHOR]

One shareholder may invest in different listed energy companies, so the information held by common shareholders can be transmitted among companies. Based on the two-mode complex network method, we construct an information flow shareholder-based network and employ different network indicators representing features of information flow as variables to construct panel regression models to analyze the impact of information flow among listed energy companies on the stock returns. The results indicate that the information flow of listed energy companies are increasingly important and play a significant role over a period. The efficiency of information flow among listed energy companies is increasingly high and the network information is concentrated among a few of these companies. The efficiency of information flow and the independence of listed energy companies are significantly positively related to stock returns, while the listed energy companies' ability to control information is not significantly related to stock returns. We employ a new perspective to analyze the information flow on how to influence stock returns, and offer some related suggestions for investors and policy makers in the future. [ABSTRACT FROM AUTHOR]