Source Information Research Articles

UUV cluster navigation data extraction fusion positioning algorithm with information geometry

With the rapid development of the ocean economy, underwater unmanned vehicle (UUV) clusters have become the main tool for ocean development, but the complex interference and occlusion in the underwater environment have posed great challenges to the positioning of UUV clusters, becoming a key problem in the application of UUV clusters. To address this issue, this paper proposes a distributed heterogeneous navigation information geometric fusion positioning method for underwater unmanned vehicle clusters based on data extraction(DEFP-IG). This method converts the distributed navigation source information of UUVs into an information geometric probability model, and constructs a factor graph fusion architecture based on data extraction to improve the suppression of interference, thereby achieving high-precision positioning of UUV clusters. Comparing the method proposed in this paper with existing methods in different scenarios, the results show that the proposed method has higher positioning accuracy and good suppression capability for abrupt errors.

CNNCat: categorizing high-energy photons in a Compton/Pair telescope with convolutional neural networks

A Compton/Pair telescope, designed to provide spectral resolved images of cosmic photons from sub-MeV to GeV energies, records a wealth of data in a combination of tracking detector and calorimeter. Onboard event classification can be required to decide on which data to down-link with priority, given limited data-transfer bandwidth. Event classification is also the first and one of the most crucial steps in reconstructing data. Its outcome determines the further handling of the event, i.e., the type of reconstruction (Compton, pair) or, possibly, the decision to discard it. Errors at this stage result in misreconstruction and loss of source information. We present a classification algorithm driven by a Convolutional Neural Network. It provides classification of the type of electromagnetic interaction, based solely on low-level detector data. We introduce the task, describe the architecture and the dataset used, and present the performance of this method in the context of the proposed (e-)ASTROGAM and similar telescopes.

SiamVIT: A patchwise network for gamma-ray point source detection

Conventional point source detection methods generally work in a pixelwise manner and can hardly exploit the overall semantic information of sources; consequently, these methods usually suffer from low precision. In this work we achieve point source detection in fully patchwise mode by proposing a siamese network called SiamVIT that includes a visual transformer (VIT). SiamVIT can effectively and accurately locate point sources from gamma -ray maps with high purity not only in higher flux regions, but also in lower flux regions, which is extremely challenging to achieve with state-of-the-art methods. SiamVIT consists of two VIT branches and a matching block. In the feature extraction stage, gamma -ray maps are fed into one VIT branch to obtain patch representations with adequate semantic and contextual information, whereas detection templates with location information are fed into the other branch to produce template representations. In the location stage, a patch representation and all template representations are fed into the matching block to determine whether the associated gamma -ray map patch contains a point source and where that point source is located, if applicable. We compare our proposed SiamVIT with the current advanced methods and find that SiamVIT has significantly better purity and completeness and a superior Dice coefficient on the test set. In addition, when point sources overlap, SiamVIT can better distinguish different point sources.

Nursing students' knowledge and related factors towards skin cancer: A systematic review

This systematic review aims to examine the nursing students' knowledge and related factors towards skin cancer. In order to conduct this comprehensive and review study, articles were searched from the earliest to April 1, 2023 using keywords extracted from Medical Subject Headings such as "knowledge", "skin cancer", and "nursing students" in various international electronic databases such as Scopus, PubMed, Web of Science, and Persian electronic databases such as Iranmedex and Scientific Information Database. The appraisal tool for cross-sectional studies (AXIS tool) was used to evaluate the quality of the studies included in this article. In total, 2,841 nursing students participated in five cross-sectional studies. The average age of the students was 20.93 (SD=1.89). 78.07% of the students in this study were female. 19.70% of students had a history of skin cancer in their family member. The average nursing students' knowledge and related factors towards skin cancer was 14.78 (SD=2.68) out of 25 which suggests a moderate level of knowledge. Factors such as year of study, female gender, age, using cosmetics, using depilatory wax, using epilating appliance, skin cancer caused by sun exposure, and protection of information have a significant positive relationship with nursing students' knowledge about skin cancer. However, knowledge had a negative relationship with factors such as using shaving, having mole, and having swelling. Additionally, the factors of father education, place of residence, sunburn frequency, source information had a significant relationship with nursing students' knowledge about skin cancer. According to the results of this review, the knowledge of nursing students in skin cancer is moderate. Therefore, nursing professors may contribute to the development of nursing students' knowledge by providing an online or physical education platform related to skin cancer.

Seismic Discrimination Using Regional Distance Coda-Wave Ratios

Abstract This study utilizes regional seismic coda-wave amplitude ratios to distinguish earthquakes and declared nuclear explosions in the Democratic People’s Republic of Korea (DPRK). We compute the coda spectral ratios at common stations to isolate source information from propagation and site effects. The resulting frequency-dependent amplitude ratios help identify differences between source types at DPRK. We use parametric models to validate observations, linking them to seismic source parameters. Our method effectively distinguishes the spectral signatures of explosions, nearby earthquakes, and a post-explosion collapse event. The measurements show clear differences between source-type combinations and agree with estimated seismic source models. Notably, the coda spectral ratios between explosions and earthquakes indicate that explosive sources exhibit relatively lower high-frequency S-wave energy and corner frequency compared to P waves. We leverage these spectral differences to develop a Bayesian inference framework for seismic source discrimination at the DPRK test site. This study demonstrates that spectral differences between source types can be exploited in coda spectral ratios to provide critical information for seismic discrimination.

Natural lighting production method using minimum spectral information for each light source

Natural lighting production method using minimum spectral information for each light source

Ultra‐Low BER Encrypted Communication Based on Self‐Powered Bipolar Photoresponse Ultraviolet Photodetector

AbstractUnderwater visible light communication often faces risks such as susceptibility to external light source interference, signal distortion, and information leakage. The cuprous oxide modified gallium oxide nanorod arrays detector prepared in this study can generate bipolar photocurrents under dual‐wavelength ultraviolet light without external bias voltage. Based on it, the constructed self‐powered ultraviolet ASCII code communication system not only reduce power consumption but also significantly enhance anti‐interference capability. Furthermore, the developed solar‐blind ultraviolet AMI and HDB3 ternary code communication systems can realize non‐visible light secure communication and automatic error correction. Notably, the encrypted communication system assembled using the additive property of bipolar photocurrents can also significantly improve communication security and reliability, whose bit error rate is only 0.26‰. This achievement contributes to technical advancements in underwater channel encryption and provides valuable insights for the further application of encrypted communication coding techniques.

Multi-Source Information-Based Bearing Fault Diagnosis Using Multi-Branch Selective Fusion Deep Residual Network.

Rolling bearing is the core component of industrial machines, but it is difficult for common single signal source-based fault diagnosis methods to ensure reliable results since sensor signals are vulnerable to the pollution of background noises and the attenuation of transmitted information. Recently, multi-source information-based fault diagnosis methods have become popular, but the information redundancy between multiple signals is a tough problem that will negatively impact the representational capacity of deep learning algorithms and the precision of fault diagnosis methods. Besides that, the characteristics of various signals are actually different, but this problem was usually omitted by researchers, and it has potential to further improve the diagnosing performance by adaptively adjusting the feature extraction process for every input signal source. Aimed at solving the above problems, a novel model for bearing fault diagnosis called multi-branch selective fusion deep residual network is proposed in this paper. The model adopts a multi-branch structure design to enable every input signal source to have a unique feature processing channel, avoiding the information of multiple signal sources blindly coupled by convolution kernels. And in each branch, different convolution kernel sizes are assigned according to the characteristics of every input signal, fully digging the precious fault components on respective information sources. Lastly, the dropout technique is used to randomly throw out some activated neurons, alleviating the redundancy and enhancing the quality of the multiscale features extracted from different signals. The proposed method was experimentally compared with other intelligent methods on two authoritative public bearing datasets, and the experimental results prove the feasibility and superiority of the proposed model.

Prioritization of Source Data Necessary for the Valuation of Real Estate with Mineral Deposits: The Case of Poland

Real estate valuation with mineral deposits in Poland can be conducted using comparative, income, and cost approaches. When determining the value of such real estate, a property valuer must obtain information from multiple sources. These sources not only help to establish the legal status but also allow for determining the type of geological and mining asset of the deposit, characterizing and assessing the quality of the deposit, describing the deposit's resources, and evaluating the exploitation potential. Analysis of the source documentation also enables the assessment of the environmental state post-exploitation and helps determine the external conditions related to the liquidation of deposits after exploitation. The need to include the above information in the appraisal report requires the property valuer to gather a large amount of source information scattered across private and institutional resources. Therefore, this study aims to identify and prioritize the source data necessary for the valuation process of land properties with mineral deposits in Poland using selected business techniques. As part of achieving the research goal, the method of valuing the subject special property will be recognized, and the source materials will be identified. Their prioritization will be performed using two business techniques: the MoSCoW method and the Action Priority Matrix. In the final stage of the study, utility classes of the source materials for the valuation of the subject property will be developed

Impact of blockchain on deception of source information

Impact of blockchain on deception of source information

Origin and preservation mechanisms of organic matter in carbonate concretions from Lower Cambrian black shales in South China

Carbonate concretions are widely used in paleoclimate, paleoenvironmental, and paleontological studies, and even in the study of potential life on Mars. These petrological, elemental, isotopic, and lipid biomarker signals in Meso-Cenozoic carbonate concretions (relatively low thermal maturity) can effectively preserve details of seawater conditions and benthic ecosystems during the deposition of their host sediments/rocks. However, such research on Precambrian-Cambrian carbonate concretions under highly mature conditions remains scarce, and the ability of these ancient carbonate concretions to retain their original biogenic information remains uncertain. To achieve that, this study examines two Cambrian carbonate concretions, using samples from the center, transition, and rim of each, and their adjacent host black shales from the Lower Cambrian Qiongzhusi Formation in the Yangtze Block, South China. Organic and inorganic geochemical analyses were combined to elucidate the origin and preservation process of organic matter (OM) in these ancient Cambrian carbonate concretions. The results show that the thermal maturity of OM within these concretions (1.8 % EqVRo) is relatively low compared to their adjacent host shales (2.9 % EqVRo). Hopanes and steranes are detectable in both free and calcite-occluded hydrocarbons within these concretions, with concentrations of individual compounds ranging from 0.001 to 0.800 μg/g TOC, whereas kerogen-bound hydrocarbons lack detectable biomarkers. The results indicate that the two Cambrian carbonate concretions were formed mainly within the iron reduction and bacterial sulfate reduction zones, extending to depths of 10 to 38 m below the sediment-water interface. The OM within these concretions mainly inherited the initial unaltered signature of OM from the Qiongzhusi host shale. The carbonate concretions protected the internal OM from further thermal and secondary (e.g., biodegradation) alteration processes and might also prevent the formation of the conventional macromolecular skeletal kerogen manifested by the absence of bound biomarkers. The biomarkers, in both free and occluded forms, in the Cambrian carbonate concretions still retained their original source information, providing valuable insights into ancient biogeochemical processes during sediment burial and ancient seawater chemistry during the early Cambrian.

State and law of the Chaghadai Ulus and early Timurid state as they were seen by foreign contemporaries

Research objectives: An analysis of official documents and notes of foreign contemporaries to clarify some aspects of political and legal life of the Chaghadai Ulus and early Timurid state in the 13th– beginning of 15th centuries. Materials and methods of research: The basic materials are official documents (diplomatic correspondence), travelers’ reports and notes, diaries and memoirs of travelers from different countries of Europe and Asia who visited the Chaghadai Ulus with different missions in the analyzed period as well as some official documents (diplomatic correspondence) between foreign and Mongol rulers. The methods of research are formal and historical legal research of historical documents, comparative legal analysis as well as historical approach in general. Scientific novelty: The state structure and legal relations in the Chaghadai Ulus and early Timurid state still have not been objects of special research. The author proposes to use works of foreign contemporaries as a tool to clarify some questions of political and legal life in the Chaghadaid state, finding similarities with other Chinggisid states and specific features of the region, its traditions, etc. Results of the research: The information of the analyzed historical documents, naturally, doesn’t allow one to reconstruct all aspects of political structure of Chaghadai Ulus and early Timurid state and their legal system in general, but adds valuable details to the information of other sources on history of this state – that is, historical chronicles (mainly of Timurid age) and legal monuments (khans’ yarliks and other official documents of the ulus). At that, we cannot ignore the fact that the Chaghadai Ulus before Timur was not considered as a full and authoritative member of international relations which is why contemporaries paid more attention to other Chinggisid states: The Golden Horde, Ilkhanate, Yuan Empire. However, the analysis of contemporaries’ notes could stimulate scholars to study some specific aspects of the Chaghadai Ulus’ history which were not researched before.

Geologic Input Databases for the 2025 Puerto Rico—U.S. Virgin Islands National Seismic Hazard Model Update: Crustal Faults Component

Abstract The last National Seismic Hazard Model (NSHM) for Puerto Rico and the U.S. Virgin Islands (PRVI) was published in 2003. In advance of the 2025 PRVI NSHM update, we created three geologic input databases to summarize new onshore and offshore fault source information in the northern Caribbean region between 62°–70° W and 16°–21° N. These databases, of fault sections, fault-zone polygons, and geologic estimates of fault activity (fault-slip rate and earthquake recurrence intervals) at specific sites, document updates to fault parameters used in prior seismic hazard models in PRVI. Fault sources were reviewed from published studies since 2003, which document substantial changes to the understanding of fault location, geometry, or activity. New fault section sources were added for features that meet the criteria of (1) length ≥7 km, (2) unequivocal evidence of recurrent tectonic Quaternary activity, and (3) documentation that is publicly available in a peer-reviewed source. In addition, we revised several broad areal sources, such as the Mona and Anegada extensional zones. The 2003 model included three fault sections and two fault-zone polygons (areal sources). These databases include 35 fault sections, 6 fault-zone polygons, and 51 earthquake geology sites. To characterize fault activity rates, slip-rate bins were assigned based on landscape expression and paleoseismic trench observations for faults without published slip-rate sites. Additional fault sources were evaluated but not included in these databases due to a lack of published information about fault location, geometry, or recurrent Quaternary activity. The PRVI NSHM 2025 geologic input databases describe crustal faulting; the geometries and coupling of Puerto Rico subduction zone and Muertos Trough models are considered in a separate database. Updates to the fault sections, fault-zone polygons, and earthquake geology databases can help inform the location and recurrence rate of damaging earthquakes in the PRVI NSHM implementation.

Application of a novel visual representation method for urban noise source monitoring

Increasing urban mobility has led to a rise in the number of vehicles, resulting in urban noise pollution, which can cause health problems. Conventional methods for noise control can be adopted to reduce noise near the sources. However, this is not cost-effective to reduce overall noise level in the urban area. Therefore, it is preferable to encourage drivers to voluntarily reduce noise by applying methods such as cracking down on road noise sources. To this end, a real-time urban noise source monitoring system is needed, but processing large amounts of data can be difficult. In this study, a novel visual representation method, DoAgram, is applied for urban noise source monitoring. DoAgram can represent the time, frequency, and spatial information of the sound source within a 2D color graph. Therefore, the long-term spatial information of the sound source acquired from the sensor array node can be transmitted as a single image. Also, one can restore spatial information of the source from an image through a decoding process corresponding to the encoding method. One can find that the proposed method can be utilized as a database that can efficiently conduct urban noise source monitoring.

Information accumulation on the item versus source test of source monitoring: Insights from diffusion modeling.

Source monitoring involves attributing previous experiences (e.g., studied words as items) to their origins (e.g., screen positions as sources). The present study aimed toward a better understanding of temporal aspects of item and source processing. Participants made source decisions for recognized items either in succession (i.e., the standard format) or in separate test blocks providing independent measures of item and source decision speed. Comparable speeds of item and source decision across the test formats would suggest a full separation between item and source processing, whereas different speeds would imply their (partial) temporal overlap. To test these alternatives, we used the drift rate parameter of the diffusion model (Ratcliff, Psychological Review, 85, 59-108, 1978). We examined whether the drift rates, together with the other parameters, assessed separately for the item and source decision varied as a function of the test format. Threshold separation and nondecision time differed between the test formats, but item and source decision speeds represented by drift rates did not change significantly. Thus, despite facilitation on the source decision when the item decision was immediately followed by a test for source memory than when item and source were tested in separate blocks, findings did not suggest that source information already begins accumulating in the item test in the standard format. We discuss the temporal sequence of item and source processing in light of different assumptions about the contribution of familiarity and recollection.

Machine learning-Based method for gas leakage source term estimation in highway tunnels

Incidents involving the leakage of flammable and explosive chemicals in highway tunnels can lead to disastrous events such as fires and explosions. The distinctive features of highway tunnels, characterized by their confined and elongated structure, intensify the complexity of managing such accidents, potentially resulting in significant casualties and property damage. Rapid detection and acquisition of leakage source information during a flammable gas leak in a highway tunnel are of utmost importance for effective accident management. This study introduces a predictive model developed using a machine learning approach. The model uses time series data from gas concentration sensors and anemometers installed within the tunnel to predict parameters such as gas leakage velocity, source location, and initiation time. A computational fluid dynamics simulation of gas leakage within the tunnel was constructed, and a dataset was generated using sample generation and preprocessing methods. The results demonstrate that this method exhibits robust predictive performance. Furthermore, a prediction strategy is proposed to enhance the model’s predictive accuracy and resilience to data noise. This model offers valuable insights for improving accident management strategies for gas-related incidents in highway tunnels.

Age-related decline in source and associative memory.

This review explores the multifaceted nature of age-related decline in source memory and associative memory. The review highlights the potential effects of age-related decline in these types of memory. By integrating insights from behavioral, cognitive, and neuroscientific research, it examines how encoding, retrieval, and neural mechanisms influence this decline. Understanding these processes is critical to alleviate memory decline in older adults. Directing attention to source information during encoding, employing unitization techniques to strengthen memory associations, and utilizing metacognitive strategies to focus on relevant details show promise in enhancing memory retrieval for older adults. However, the review acknowledges limitations in processing resources and executive function, necessitating a nuanced approach to the complexities of age-related decline. In conclusion, this review underscores the importance of understanding the complexities of age-related source and associative memory decline and the potential benefits of specific cognitive strategies. It emphasizes the need for continued research on age-related memory function to improve the quality of life for aging populations.

Review of Enset (Tree Against Hunger and Drought) Value Chain Opportunities and Constraints in Agricultural Food Sector of Ethiopia

In sub-Saharan Africa Enset is widely dispersed wild plant species that ensures food security for many Africans. In similar view, in South and South-west parts of Ethiopia more than 20 million people depends on Enset as stable food and it is called drought tolerant food of root crop. Due to its multidimensional significant roles, its resilience and versatility during the times of famine Enset has earned the name 'The Tree against Hunger'. Besides, food items like ‘Amicho’, ’Kocho’, and ‘Bulla’ are obtained from Enset for home consumption and marketing. Besides, the value chain is the full range of activities which are required to bring a product or service from conception, through the different phase of production which involves a combination of physical transformation and the input of various producer services, delivery to final consumers, and final disposal after use. Thus, the main intent of this article was to review the value chain of Enset from its respective opportunities and challenges from perspective of Ethiopia. Regarding to this, the information used in this paper was the secondary source information that was extracted from journal articles and dissertation papers. Then the collected information were analyzed qualitatively and presented in narrative ways. Finally, based on the review results of this article conclusions and recommendations are given in advances.

News production on the arrival of migrants by sea to Spanish coasts: the case of the Balearic Islands

This article explores the communicative strategies of journalists and institutional offices onthe arrival of migrants by sea to Spanish coasts through a case study: the Balearic Islands. For this purpose,media studies and critical approaches to the performativity of borders are taken as a starting point. Theresults indicate the emission of numerical, serialized and single source information in the case of theinstitutions, reactive in the case of the managing organizations and conditioned by institutional processes ofsecuritization of migrations in the case of journalists, who focus their work on the reproduction of the numberof arrivals and on the procedural deployment associated with the immigration law, generating a redundantinformative effect on the procedures of “immigration management”. The study shows the need to analyze themedia representation of migration in terms of its governance.

Competence in Unsustainability Resolution—A New Paradigm

Environmental unsustainability in coupled human–nature systems is accumulating. Yet, there is no accreditation requirement for unsustainability resolution competency in higher education. Thus, a new and complete representation of the pedagogy for unsustainability resolution competence has been induced, using what is already available and working. The nature of unsustainability problems points to collaboration and holism attitudes. Resolution requires social skills, namely participation, perspective taking, and the generation of social capital, and cognitive skills, namely project management, knowledge building, and modeling. Resolution is scaffolded in three successive steps during the collaborative process within a systems approach: (i) collapse complexity; (ii) select a path/trajectory; and (iii) operationalize a plan. The hierarchically cumulative abilities toward unsustainability resolution competence are to source data and information about the coupled human–nature system (SEARCH); simplify the dynamics of the human–nature system (SIMULATE); generate and test alternative paths and end points for the coupled human–nature system (STRATEGIZE); chose a favorable path among the available alternatives (SELECT); operationalize the favorable path into a plan (strategy–program–project) with measurable management and policy objectives (IMPLEMENT); and develop criteria/indicators to monitor and adjust when necessary the implementation of the plan toward system goals (STEER). For each one of these learning objectives, the Bloom’s taxonomy and a progression from behaviorist through cognitivist to constructivist tools apply. The development of mastery requires the comparison and contrast of many similar cases with the same unsustainability problem and project-based learning with specific cases for deep learning. In this way, it is the resolutions of unsustainability in human–nature systems that will be accumulating.