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Quantum memories facilitate the storage and retrieval of quantum information for on-chip and long-distance quantum communications. Thus, they play a critical role in quantum information processing and have diverse applications ranging from aerospace to medical imaging fields. Bulk acoustic wave (BAW) phonons are attractive candidates for quantum memories because of their long lifetimes and high operating frequencies. In this study, we establish a modeling approach to design hybrid magnonic high-overtone bulk acoustic wave resonator (HBAR) structures for high-density, long-lasting quantum memories, and efficient quantum transduction devices. We illustrate the approach by investigating a hybrid magnonic system, consisting of a gadolinium iron garnet (GGG) thick film and a patterned yttrium iron garnet (YIG) thin film. The BAW phonons are excited in GGG thick film via coupling with magnons in the YIG thin film. We present theoretical and numerical analyses of the diffraction-limited BAW phonon lifetimes, modeshapes, and magnon–phonon coupling strengths in YIG/GGG planar and confocal HBAR (CHBAR) structures. We utilize Fourier beam propagation and Hankel transform eigenvalue problem methods and compare the two methods. We discuss strategies to improve the phonon lifetimes in the diffraction-limited regime, since increased lifetimes have direct implications on the storage times of quantum states for quantum memory applications. We find that ultra-high cooperativities and phonon lifetimes on the order of ∼ 10 5 and ∼ 10 milliseconds, respectively, could be achieved using a CHBAR structure with 10 μ m YIG lateral area. Additionally, high integration density of on-chip memory or transduction centers is naturally desired for high-density memory or transduction devices. The proposed CHBAR structure will offer more than 100-fold improvement of integration density relative to a recently demonstrated YIG/GGG device. Our results will have direct applicability for devices operating in the cryogenic or milliKelvin regimes. For example, our study will inform the design of HBAR devices that could couple with superconducting qubits for promising quantum information platforms. [ABSTRACT FROM AUTHOR]

In October 2017, in parallel to the viralization of the #MeToo hashtag, feminist movements in Peru flooded social media using another hashtag to confront rape culture. #PerúPaísDeVioladores – #PeruCountryOfRapists, in English – worked as a cry of outrage after a third case of sexual violence broke the news in the same month. This case study explores the role of the hashtag #PerúPaísDeVioladores in challenging hegemonic discourses on sexual violence and articulating asynchronous and multisited actions. By analysing Twitter posts and reviewing news and opinion columns associated with this social media campaign in three key moments in 2017 and 2020, I contend that the hashtag establishes an alternative interpretive framework that not only makes legible a range of cases as expressions of rape culture but also confronts dominant narratives that re-victimize survivors and conceal the systemic roots of sexual violence. Acting as a means of (dis)organization and overflowing of information, this hashtag creates a constellation in which digital content, in situ performances, and civil mobilizations integrate to denounce systemic violence against feminized bodies in Peru. [ABSTRACT FROM AUTHOR]

This study explores how exploitative leadership affects employees' work passion, a vital element for engagement, creativity, and productivity. It further delves into how trust in leaders mediates this relationship. By applying social exchange theory and conservation of resources theory and analyzing responses from 384 full-time employees through covariance-based structural equation modeling using SmartPLS, the findings confirm the negative effects of exploitative leadership on work passion. They also underscore the significant mediating role of trust in leaders. These insights underline the importance of addressing exploitative leadership in organizational policies and enhancing trust to improve work passion. The study not only provides valuable information for organizations but also lays the groundwork for future research on leadership styles, trust, and employee passion. [ABSTRACT FROM AUTHOR]

Scientific production is experiencing exponential growth, making it essential for professionals and the academic community to possess tools and skills for efficiently retrieving relevant information. To address this need, information must be reformulated into answerable questions, with the PICO format (an acronym for Patient, Intervention, Comparison, and Outcome) proving particularly useful. Utilizing this framework will facilitate the identification of critical elements within our question and serve as a guide throughout the information retrieval process, aiding in the development and structuring of search strategies. This paper outlines the principles for formulating questions using the PICO format to enhance the efficacy of literature searches. [ABSTRACT FROM AUTHOR]

Background: A barrier to evidence-informed exercise programming is locating studies of exercise training programs. The purpose of this study was to create a search filter for studies of exercise training programs for the PubMed electronic bibliographic database. Methods: Candidate search terms were identified from three sources: exercise-relevant MeSH terms and their corresponding Entry terms, word frequency analysis of articles in a gold-standard reference set curated from systematic reviews focused on exercise training, and retrospective searching of articles retrieved in the search filter development and testing steps. These terms were assembled into an exercise training search filter, and its performance was assessed against a basic search string applied to six case studies. Search string performance was measured as sensitivity (relative recall), precision, and number needed to read (NNR). We aimed to achieve relative recall ≥ 85%, and a NNR ≥ 2. Results: The reference set consisted of 71 articles drawn from six systematic reviews. Sixty-one candidate search terms were evaluated for inclusion, 21 of which were included in the finalized exercise-training search filter. The relative recall of the search filter was 96% for the reference set and the precision mean ± SD was 54 ± 16% across the case studies, with the corresponding NNR = ~ 2. The exercise training search filter consistently outperformed the basic search string. Conclusion: The exercise training search filter fosters more efficient searches for studies of exercise training programs in the PubMed electronic bibliographic database. This search string may therefore support evidence-informed practice in exercise programming. [ABSTRACT FROM AUTHOR]

Ciliary rootlets are striated bundles of filaments that connect the base of cilia to internal cellular structures. Rootlets are critical for the sensory and motile functions of cilia. However, the mechanisms underlying these functions remain unknown, in part due to a lack of structural information of rootlet organization. In this study, we obtain 3D reconstructions of membrane-associated and purified rootlets from mouse retina using cryo-electron tomography. We show that flexible protrusions on the rootlet surface, which emanate from the cross-striations, connect to intracellular membranes. In purified rootlets, the striations were classified into amorphous (A)-bands, associated with accumulations on the rootlet surface, and discrete (D)-bands corresponding to punctate lines of density that run through the rootlet. These striations connect a flexible network of longitudinal filaments. Subtomogram averaging suggests the filaments consist of two intertwined coiled coils. The rootlet's filamentous architecture, with frequent membrane-connecting cross-striations, lends itself well for anchoring large membranes in the cell. [ABSTRACT FROM AUTHOR]

The authors consider the private information retrieval (PIR) problem, in particular, the problem of ensuring secure queries to a database. Previously, the authors considered this problem for a cloud database in the presence of an active adversary who does not interfere with the execution of the PIR protocol but can carry out an attack with known open queries. In the proposed algorithms, bit number i is represented as an l-ary number with d digits. An algorithm for database placement on the cloud and an algorithm for bit querying with the use of permutations in the digits of a bit number, where bit number i is defined in a base-l number system, are proposed. The permutations are regarded as secret encryption keys. The communication complexity and the probability of guessing the bit number in a single attack with a known open query for bit number i, as well as in an attack with an unlimited number of known open queries, are estimated. [ABSTRACT FROM AUTHOR]

This paper addresses the increasing complexity of challenges in the field of continuous nonlinear optimization by proposing an innovative algorithm called information acquisition optimizer (IAO), which is inspired by human information acquisition behaviors and consists of three crucial strategies: information collection, information filtering and evaluation, and information analysis and organization to accommodate diverse optimization requirements. Firstly, comparative assessments of performance are conducted between the IAO and 15 widely recognized algorithms using the standard test function suites from CEC2014, CEC2017, CEC2020, and CEC2022. The results demonstrate that IAO is robustly competitive regarding convergence rate, solution accuracy, and stability. Additionally, the outcomes of the Wilcoxon signed rank test and Friedman mean ranking strongly validate the effectiveness and reliability of IAO. Moreover, the time comparison analysis experiments indicate its high efficiency. Finally, comparative tests on five real-world optimization difficulties affirm the remarkable applicability of IAO in handling complex issues with unknown search spaces. The code for the IAO algorithm is available at https://ww2.mathworks.cn/matlabcentral/fileexchange/169331-information-acquisition-optimizer. [ABSTRACT FROM AUTHOR]

Advanced Persistent Threat (APT) attack is one of the most dangerous cyber-attack techniques nowadays. Therefore, the issue of detecting and predicting the spread of APT malware in the network is a very urgent issue to help the process of preventing this attack effectively. In this paper, we propose a new approach that is capable of predicting the spread of APT malware in the network based on the APT's own behaviors. Accordingly, to predict the spread of APT malicious code in the system, we propose to use a combination of two single Susceptible‐Infected‐Recovered (SIR) models. Specifically, the first SIR model was built to predict the spread of APT malicious code to devices and computers within the organization. These devices and computers are often used by APT malicious code as a basis to escalate privileges to devices or computers containing important and sensitive information of the organization. The second SIR model has the function of predicting the spread of APT malware to a group of computers containing sensitive information or potentially causing high risks to the organization. The two SIR models will provide information about infections between computer groups in the system to help accurately predict the spread of APT malware in the system. The proposal to combine two SIR models in the article is a new proposal based on the behavior of APT malware in practice. By combining two SIR models, the proposal in this article has opened up a new approach for a number of problems predicting the spread in the internet such as malicious code in wireless sensor networks or malicious information on the social network. [ABSTRACT FROM AUTHOR]

Living systems are capable on the one hand of eliciting a coordinated response to changing environments (also known as adaptation), and on the other hand, they are capable of reproducing themselves. Notably, adaptation to environmental change requires the monitoring of the surroundings, while reproduction requires monitoring oneself. These two tasks appear separate and make use of different sources of information. Yet, both the process of adaptation as well as that of reproduction are inextricably coupled to alterations in genomic DNA expression, while a cell behaves as an indivisible unity in which apparently independent processes and mechanisms are both integrated and coordinated. We argue that at the most basic level, this integration is enabled by the unique property of the DNA to act as a double coding device harboring two logically distinct types of information. We review biological systems of different complexities and infer that the inter-conversion of these two distinct types of DNA information represents a fundamental self-referential device underlying both systemic integration and coordinated adaptive responses. [ABSTRACT FROM AUTHOR]

While triple-negative breast cancer (TNBC) is known to be heterogeneous at the genomic and transcriptomic levels, spatial information on tumor organization and cell composition is still lacking. Here, we investigate TNBC tumor architecture including its microenvironment using spatial transcriptomics on a series of 92 patients. We perform an in-depth characterization of tumor and stroma organization and composition using an integrative approach combining histomorphological and spatial transcriptomics. Furthermore, a detailed molecular characterization of tertiary lymphoid structures leads to identify a gene signature strongly associated to disease outcome and response to immunotherapy in several tumor types beyond TNBC. A stepwise clustering analysis identifies nine TNBC spatial archetypes, further validated in external datasets. Several spatial archetypes are associated with disease outcome and characterized by potentially actionable features. In this work, we provide a comprehensive insight into the complexity of TNBC ecosystem with potential clinical relevance, opening avenues for treatment tailoring including immunotherapy. Triple-negative breast cancer (TNBC) is a heterogenous disease with several molecular subtypes previously described. Here the authors perform a spatial transcriptomics analysis on a series of 92 patients, providing additional insights into the heterogeneity of TNBC, with implications for clinical outcomes and therapy. [ABSTRACT FROM AUTHOR]

ABSTRACT Current geographic knowledge graph research mainly focuses on static knowledge coupling through analysis of web text and maps, but its knowledge expression model fails to incorporate knowledge mechanisms such as process evolution and interactions. The geo‐scene is a synthesis of various geographic elements which prescribes spatial, temporal, semantic, attribute, and interrelationships. It has demonstrated its utility in facilitating geocomputation, spatiotemporal simulation and reasoning related to geo‐process. Therefore, developing a geo‐scene‐based knowledge graph is significant to improve the ability of spatiotemporal knowledge representation and service. In this study, we first analyze the basic characteristics of geo‐scenes and try to emphasize the evolution of geo‐scenes through redefining the ontologies ‘event’, ‘process’ and ‘state’. To describe the dynamic nested structure of geo‐scenes, we propose a geo‐scene knowledge representation framework, and illustrate the representation of a geo‐scene and its inner relationships. Moreover, to keep the integrity, interaction and dynamic of geo‐scenes, we develop a event‐process centered geo‐scene knowledge organization method. Furthermore, we have tested the utility of our proposed representation by the Beijing 731 heavy rainstorm. The case study represents heavy rainstorm to demonstrate the complicated structure of the disaster scene, and the support for precipitation process simulation, early warning information organization, and disaster situation information query. The proposed representation provides an idea for the construction of geo‐dynamic knowledge graphs, encodes both static and dynamic geographic knowledge, makes explicit the evolution and interaction knowledge in geo‐scenes, and expands the application service of geo‐scene knowledge graph in the era of GeoAI. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to design a conceptual model of the management information system for the Library Development and Reading Promotion Department within the Iran Public Libraries Foundation. Method: The present study was conducted with a specific purpose and utilized qualitative research methods for data collection, specifically qualitative content analysis. The statistical population for this study comprised the employees of the Development Office of the Public Libraries Institution. The research tool employed was a semi-structured interview, with the questions finalized after conducting three preliminary interviews. A total of 19 employees from the Development Office of the Institution were selected as the research sample using a purposive sampling method to ensure maximum diversity. Following each interview, the transcripts were created and coded. In the content analysis of the interviews, primary codes, subcategories, and main categories were identified. Findings: In the analysis of the interviews, twelve processes were identified for the Deputy for Institutional Development. The processes of the General Office of Resource Supply included two specific activities: assigning donated resources and identifying both book and non-book resources. The Office of Reading Promotion and Cultural Affairs undertakes three key initiatives: organizing national competitions, implementing digital advertising campaigns, and hosting library meetings. The General Office of Library Development and Partnerships encompasses seven primary processes: creating and designing libraries, developing library services, cataloging, the qualification process for positions, selecting national winners, updating guidelines and regulations related to libraries, and supporting and enhancing the Saman software. For each process, inputs were identified as the information required by experts to execute the process, while outputs were defined as process output reports intended for managers. Additionally, the characteristics of each piece of information were established. Conclusion: This study has identified the processes of the Library Development Department, compiling a list of essential information for experts and managers, characterized for each process. Based on these processes, inputs, outputs, and information characteristics, a hierarchical model of the management information system for the department can be constructed. It is recommended that the Library Development Department develop a management information system with proposed dashboards for various processes based on the conceptual model needs identified in this research. Additionally, this study offers a framework for the management information systems in organizations, aiding in the identification of their management information system components. [ABSTRACT FROM AUTHOR]

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

Currently, online learning systems in the education sector are widely used and have become a new trend, generating large amounts of educational data based on students' activities. In order to improve online learning experiences, sophisticated data analysis techniques are required. Adding value to E-learning platforms through the efficient processing of big learning data is possible with Big Data. With time, the E-learning management system's repository expands and becomes a rich source of learning materials. Subject matter experts may benefit from using E-learning resources to reuse previously created content when creating online content. In addition, it might be beneficial to the students by giving them access to the pertinent documents for achieving their learning objectives effectively. An improved intelligent information retrieval and reliable storage (OIIRS) scheme is proposed for E-learning using hybrid deep learning techniques. Assume that relevant E-learning documents are stored in cloud and dynamically updated according to users' status. First, we present a highly robust and lightweight crypto, i.e., optimized CLEFIA, for securely storing data in local repositories that improve the reliability of data loading. We develop an improved butterfly optimization algorithm to provide an optimal solution for CLEFIA that selects private keys. In addition, a hybrid deep learning method, i.e., backward diagonal search-based deep recurrent neural network (BD-DRNN) is introduced for optimal intelligent information retrieval based on keywords rather than semantics. Here, feature extraction and key feature matching are performed by the modified Hungarian optimization (MHO) algorithm that improves searching accuracy. Finally, we test our proposed OIIRS scheme with different benchmark datasets and use simulation results to test the performance. [ABSTRACT FROM AUTHOR]

Copyright of Journal of the Institute of Social Sciences Cankiri Karatekin University / Çankırı Karatekin Üniversitesi Sosyal Bilimler Enstitüsü Dergisi is the property of Cankiri Karatekin University, Institute of Social Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

AbstractHead-up displays (HUDs) enable drivers to receive additional information while maintaining a forward view of the road. However, due to human cognitive resource limitations, improper HUD interface design can pose safety risks, especially when multiple pieces of information are presented simultaneously. This study involved 45 participants and conducted two driving simulation experiments. Study 1 explored the impact of different HUD interface positions on driver cognitive performance in single cognitive task conditions. Study 2 validated the findings of Study 1 under multiple cognitive task conditions and further compared drivers’ cognitive performance, workload, driving operation, and eye movement between grouped and disordered information layouts on the HUD. The results indicated that the central area of the HUD interface provided the best cognitive performance, followed by the left side, with the right side performing the poorest. Grouped information layouts on the HUD proved superior to disordered layouts in terms of cognitive performance, workload, driving operation, and eye movement. An XGBoost regression model was proposed to predict the drivers’ comprehensive cognitive responses. This study could provide empirical evidence and practical recommendations for HUD interface design. [ABSTRACT FROM AUTHOR]

The information resources of the Students' Scientific Society (SSS) at the University of Library Studies and Information Technologies (ULSIT) in Bulgaria are presented in the current article as an example of reference-information mapping. The retrospective channel of this modeling, structured in 29 e-libraries (2005–), designed for universities, libraries and civil society, was defined as an interdisciplinary cluster of the informatization in Bulgaria with wide international resonance. The methodology of development of the e-libraries and the used terminology define them as a secondary-documental resources. The semantic aspects of the е-libraries are shown as a unified system that is rooted in the universal humanitarian studies and virtually organized around the model of theoretical and practical methodological directions for organization of reference information retrieval databases. The perspectives of the development of similar information resources in the future are revealed. The creation of these e-libraries was part of a pedagogical practice through which students of Library Studies and Information Technologies learned information modeling in an open laboratory environment. [ABSTRACT FROM AUTHOR]

This paper aims to fulfill two objectives. The first one is presenting the linguistic and pedagogic theoretical foundations informing the design of a writing workshop for postgraduate students in Spanish, with focus on the domains of social sciences, arts and humanities. The second aim is to provide evidence of the impact of this workshop in the learning process of participants students. The workshop is organized around the thesis macrogenre, with a specific focus on the teaching of discursive and grammatical meaning-making resources, metafunctionally diversified. This provides students with specialized knowledge about language and about how it works in disciplinary contexts. The impact of this workshop in students' writing is exemplified with a case analysis, focusing on the organization of information. Both the workshop's theoretical foundations and the case analysis are grounded on Systemic functional linguistics (SFL). [ABSTRACT FROM AUTHOR]

Transparency is a complex and multifaceted communication phenomenon. In the current environment, demands for organizational transparency now come from a wide range of entities we term visibility agents, ranging from nongovernmental organizations (NGOs) and global networks, on one hand, to activist coalitions and automated surveillance agents, on the other. We develop a framework to conceive of such visibility agents and the range of transparency demands that they make in the context of environmental issues, positing that visibility agents significantly shape and diversify transparency practices. We identify four major relationships between visibility agents and organizations— inquisitorial, adversarial, associative, and advocative —which are associated with specific kinds of transparency demands, requests, and imperatives: accountability, monitoring, disclosure, and secrecy. We illustrate each set of relationships with examples of environmental reporting practices, one of the most prominent areas of transparency management. Implications for both theory and research on transparency are discussed. [ABSTRACT FROM AUTHOR]

The article substantiates that in modern conditions infocommunication technologies that use the wireless principle of data transmission are more developed. Approaches to the use of such technologies for the organization of information exchange with unmanned platforms are shown. This increases the efficiency of information processes in support and decision-making systems. At the same time, the article asserts the presence of problematic aspects. They are dictated by an imbalance between a certain level of intensity of the information flow that needs to be transmitted from the unmanned system and the level of throughput of on-board telecommunications facilities. To solve this problem, the article thoroughly proposes to use technologies for compressing video information flows. A study of modern methods of compression of video information streams is carried out. It is shown that they use platforms that are based on the encoding of transformed video fragments (VFR). One of the tested directions here is the formation of a spectralparametric description of transformants. An example of such an approach is the construction of two structural components: the vector of the lengths of spectral bands and the vector of their significant levels. However, existing image compression technologies based on the JPEG platform do not provide the necessary efficiency of delivery of compressed video streams for a given level of visual quality of their visual perception after decompression. A model for estimating the informativeness of the transformer has been developed, which is presented in the spectral-parametric description by two components: the vector of the length of the SSB; vector of significant levels of the SSB. In this case, a limited number of permissible states of the SPT is taken into account on the basis of taking into account the current power of the alphabets of its two structural components. It is substantiated that as a result of the establishment of restrictions on the components of the structural components of SPT, conditions are created to reduce the amount of redundancy. It is shown that the amount of redundancy that can be reduced will increase in the case of: a decrease in the number of spectral subbands; decrease in the current power of the alphabet of significant components of the SSB. [ABSTRACT FROM AUTHOR]

Promoting innovation and knowledge transfer are two fundamental processes that drive the growth and development of organizations in the information age. Innovation, whether it's new products, services, or processes, is a key driver of competitiveness and long-term success. Knowledge transfer, on the other hand, involves the dissemination of skills, experiences, and information within an organization. Project Managers (PMs), with their unique skills in terms of leadership, relationship management, and implementation strategies, are uniquely positioned to ease both innovation promotion and knowledge transfer. Through effective management of teams and projects, they can create an environment that encourages the sharing of ideas and the adoption of new practices. However, promoting innovation and knowledge transfer are not without challenges. These can include resistance to change, communication barriers, and lack of adequate resources. Therefore, it is crucial for PMs to understand these challenges and develop effective strategies to overcome them. [ABSTRACT FROM AUTHOR]

The advancement of information technology (IT) has become essential for organizations, including Bank Mandiri, where IT underpins critical business functions and supports operational stability. This study focuses on evaluating the implementation of IT governance at Bank Mandiri's Girian branch, using the COBIT 2019 framework. COBIT is a comprehensive tool for managing IT processes and ensuring they align with organizational goals. A qualitative case study approach, including interviews with key stakeholders, was used to assess 40 IT processes across 11 design factors. Each of these processes was assigned a score ranging from 75 to 100 to help prioritize their importance to the business process. The results revealed several high-priority processes, including Managed Solutions Identification and Build (BAI03), Managed Requirements Definition (BAI02), Managed IT Changes (BAI06), and Managed Projects (BAI11). These processes were identified as critical to maintaining operational stability, ensuring customer satisfaction, and aligning IT with Bank Mandiri's strategic objectives. By efficiently allocating resources, these processes help to streamline IT operations and improve customer service. Based on the findings, the study recommends that lower-scoring processes be deprioritized, allowing resources and focus to be directed towards high-priority areas. This approach ensures that IT governance is strategically aligned with organizational goals while optimizing resource usage. The study highlights the crucial role of IT in supporting business continuity, noting that any IT disruption could severely impact operations and customer satisfaction. Overall, it underscores the importance of robust IT governance practices in achieving better business outcomes and enhancing customer service at Bank Mandiri's Girian branch, ensuring long-term success. [ABSTRACT FROM AUTHOR]

Intelligent design has been the direction pursued by international electric vehicle (EV) research and development (R&D) teams in recent years. This paper analyzes the problems of unsustainable development in the current product design of EVs in China, such as high R&D investment, high innovation risks, and low R&D input–output ratios. It explores the issues related to intelligent design, R&D investment, car prices, and safety in the field of EVs in China, and it proposes the concept of optimizing intelligence to optimize the design investment of EVs in China. On the basis of the development situation and the existing problems of social organization standards that gather innovative technologies for EVs, this paper used data from the national social organization standard information platform as the research object and analyzed important data, such as the quantity of the information of relevant social organizations and professional fields of social organization standards, through mathematical methods. The article proposes an optimization design scheme for EV products in China, combining intelligence and practicality from the perspective of the optimizing intelligent design, and it models the construction of EV optimization design. The quantitative relationship between the two schemes before and after optimization design is compared in terms of cost savings in intelligent design, the improvement of social benefits, and the enhancement of EV cost performance. The comparative study found that intelligent optimization design reduced the R&D cost of EVs by 45.24%, and the social benefits of R&D investment increased by 29.51%. [ABSTRACT FROM AUTHOR]

Supply chain partners exchange information to achieve shared performance goals. However, information sharing is fraught with risks and concerns around organizational data privacy and security. Extant studies provide connectivity and supply chain partners' willingness to share information as factors driving information-sharing. In an Industry 4.0 supply chain, technology provides the capability to share information across organizations. Literature highlights the role of technological capabilities and privacy by design in addressing the risks and concerns in information sharing that may influence the willingness of supply chain partners to share information. We introduce the framework of organizational privacy calculus comprising privacy by design to balance the needs and willingness to share information against environmental dynamism, regulations, and data sensitivity risks that can impact information sharing in the supply chain and procurement. We use OIPT and privacy calculus as theoretical lenses to derive empirically the balancing framework. The contribution of our study is twofold: proposing an organizational privacy calculus that focuses on organizational information sharing and highlighting the importance of privacy by design to alleviate risks of sharing sensitive information. The study empirically establishes that technology capabilities and privacy protection measures are essential for enhancing inter-organizational willingness to share information to balance against concerns. [ABSTRACT FROM AUTHOR]

In today's organizational landscape, safeguarding information against both intentional and unintentional insider threats has become a paramount concern. To address this challenge, organizations formulate Information Security Policies (ISP) aimed at maximizing compliance regarding sensitive data and information. However, confining the analysis solely to compliance falls short, as even a minor fraction of non-compliant individuals can lead to significant organizational vulnerabilities. In such scenarios, it becomes imperative for organizations to delve into the intricacies that influence both ISP compliance and noncompliance. While numerous literature reviews have explored factors contributing to ISP compliance, they often treated compliance and noncompliance as mere opposites, neglecting their nuanced differences and the need for a combined perspective. Our study bridges this gap by conducting a comprehensive review of 50 peer-reviewed articles published between 2014 and 2022. This unique undertaking yields three crucial contributions: First, it elucidates the characteristics distinguishing ISP compliance and noncompliance within business contexts. Second, it provides an encompassing explication of the variables influencing both ISP compliance and noncompliance. Most notably, our review culminates in the development of a unified framework that amalgamates existing insights and charts a path for future inquiry. [ABSTRACT FROM AUTHOR]

Copyright of European Journal of Applied Economics is the property of Singidunum University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Information security enforcement aims to reflect the organizational practices while ensuring the confidentiality and availability of the relevant information within the organization. Such acts also help make some strategic and efficient decision-making at different levels of the organization. Moreover, by using big data technologies, organizations make decisions more efficiently by allowing them to process and analyze large amounts of information quickly. This study focused on several indicators relating to information security enforcement, big data adoption, and decision-making efficiency by collecting data from eight industries in China. The study developed a concise questionnaire using the Fivepoint Likert scale, for which descriptive and regression analysis were applied. The study results show a significant relationship between information security enforcement, big data adoption and decision-making efficiency. Additionally, the study results revealed the reliability and monitoring of such initiatives like whistleblowing programs, disciplinary employees for security violations, quick investigations, and accountability for infractions, as key indicators of information security enforcement, which also cause an improvement in the decision-making efficiency of the targeted industries. The results further suggest policy implications and recommendations to improve decision-making using information security enforcement and extensive data adoption. A few limitations also discuss the future directions. [ABSTRACT FROM AUTHOR]

Over the last decade, a plethora of training datasets have been compiled for use in language-based machine perception and in human-centered AI, alongside research regarding their compilation methods. From a primarily linguistic perspective, we add to these studies in two ways. First, we provide an overview of sixty-six training datasets used in automatic image, video, and audio captioning, examining their compilation methods with a metadata analysis. Second, we delve into the annotation process of crowdsourced datasets with an interest in understanding the linguistic factors that affect the form and content of the captions, such as contextualization and perspectivation. With a qualitative content analysis, we examine annotator instructions with a selection of eleven datasets. Drawing from various theoretical frameworks that help assess the effectiveness of the instructions, we discuss the visual and textual presentation of the instructions, as well as the perspective-guidance that is an essential part of the language instructions. While our analysis indicates that some standards in the formulation of instructions seem to have formed in the field, we also identified various reoccurring issues potentially hindering readability and comprehensibility of the instructions, and therefore, caption quality. To enhance readability, we emphasize the importance of text structure, organization of the information, consistent use of typographical cues, and clarity of language use. Last, engaging with previous research, we assess the compilation of both web-sourced and crowdsourced captioning datasets from various perspectives, discussing factors affecting the diversity of the datasets. [ABSTRACT FROM AUTHOR]

Field trips enrich learning programs with out-of-school activities that can bring gains in students' academic content knowledge and personal growth. However, they are a source of anxiety for teachers because of the bureaucracy, pedagogy, etc., risks they imply. To address this issue, we propose FieldTripOrganizer, a field trip planner based on the mixed-initiative approach aimed at increasing teachers' autonomy and motivation in designing educational tours. The key aspects of our application are (i) the simultaneous provision of information filtering and automated scheduling support while the user designs the field trip, and (ii) the visual annotation of places and activities to show whether they can be included in the itinerary without violating its time constraints. Different from current tour planners, these functions enable the user to be in full control of the design process, delegating the system to manage difficult and burdensome tasks such as consistency checks and itinerary optimization. We evaluated FieldTripOrganizer in the use case of organizing a science field trip. In a preliminary user study involving 18 science teachers, our application turned up to be superior to a baseline tour planner in both usability and user experience. Moreover, the teachers declared that it was helpful, motivated them, and reduced their anxiety during the design of the field trips. [ABSTRACT FROM AUTHOR]

The cellular space robot (CSR) is a new type of self-reconfigurable robot. It can adapt the variety of on-orbit service tasks with large space spans through multi-level reconfiguration mechanisms. As the CSR has a large configuration space, kinematic solving becomes a key problem affecting on-orbit operation capability, and kinematic automatic solving research must be conducted. In order to solve this problem, firstly, the cellular space robot system capable of realizing multi-level self-reconfiguration is proposed for the demand of space on-orbit service, and the kinematic equations of modules are constructed by considering a single module function using screw theory. Secondly, the kinematics of the cellular space robot are encapsulated and divided into multiple levels, and the multilevel-assembly relationship-description method for robotic systems is proposed based on graph theory. On this basis, the pathway-solving algorithm is proposed to express the robot organization reachability information. Finally, the module–organ–robot multilevel kinematics solving algorithm is proposed in combination with screw theory. In order to verify the effectiveness of the algorithm in this paper, numerical simulation is used to compare with the proposed algorithm. The results show that compared with the traditional algorithm, the method in this paper only needs to update part of the assembly relations after organ migration, which simplifies the kinematic modeling operation and improves the efficiency of kinematic computation. [ABSTRACT FROM AUTHOR]

This study investigates whether the success of salary history bans could be limited by job-seekers volunteering their salaries unprompted. We survey American workers in 2019 and 2021 about their recent job searches, distinguishing when candidates were asked about salary history from when they were not. Historically well-paid workers may have an incentive to disclose, and employers who are aware of this could infer that nondisclosing workers are concealing low salaries. Through this mechanism, all workers could face pressure to avoid the stigma of silence. Our data shows a large percentage of workers (28%) volunteer salary history, even when a ban prevents employers from asking. An additional 47% will disclose if enough other job candidates disclose. Men are more likely than women to disclose their salaries unprompted, especially if they believe other candidates are disclosing. Over our 1.5-year sample covering jurisdictions with (and without) bans, unprompted volunteering of salary histories increased by about 6–8 percentage points. Funding: This work was supported by W.E. Upjohn Institute for Employment Research; Ewing Marion Kauffman Foundation (Emerging Scholars Program). Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2023.17384. [ABSTRACT FROM AUTHOR]

In a large-scale distributed network, a naming service is used to achieve location transparency and provide effective content discovery. However, fast and accurate name retrieval in the massive name set is laborious. Approximate set membership data structures, such as Bloom filter and Cuckoo filter, are very popular in distributed information systems. They obtain high query performance and reduce memory requirements through the abstract representation of information, but at the cost of introducing query error rates, which will ultimately affect content service quality. In this paper, in order to obtain higher space utilization and a lower query false positive rate, we propose a flexible fingerprint cuckoo filter (FFCF) for information storage and retrieval, which can change the length and type of fingerprints adaptively. In our scheme, FFCF uses longer fingerprints under low occupancy and has the ability to correct errors by changing the type of stored fingerprints. Moreover, we give a theoretical proof and evaluate the performance of FFCF by experimental simulations with synthetic data sets and real network packets. The results demonstrate that FFCF can improve memory utilization, significantly reduce false positive errors by nearly 90 % at 50 % occupancy and outperform Cuckoo filter in the full range of occupancy. [ABSTRACT FROM AUTHOR]

Copyright of Experimental Technology & Management is the property of Experimental Technology & Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

An issue in drug discovery research at pharmaceutical companies is the decline in the probability of market launch, and there is a need to improve the proof-of-concept (POC) acquisition rate by further improving clinical predictability. For this purpose, we need to deepen our understanding of human pathophysiology, and to make efficient of drug discovery research by utilizing human samples and data due to the change in mindset from "animals" to "humans" at the drug discovery research stage. In particular, with the aim of improving the efficiency of drug discovery research by utilizing human samples/data, we have established a human sample utilization support capability, then we are supporting the acquisition of appropriate human samples/data to meet each drug research need with collecting information on organizations that can provide various human samples and accumulating know-how on obtaining human samples/data. In addition, we have built a one-stop support system for surveying human samples/data, negotiating, and contracting with the organizations, obtaining ethical committee approvals, importing samples, and dealing with customs clearance. As results, our researchers can obtain high-quality human samples/data to meet their research needs rapidly/easily. By establishing this capability, the number of the research projects that implement target validation, pharmacological evaluation, BM identification, and patient stratification, etc. using human samples/data from the early stage of drug discovery, has increased, and then, the evidence obtained by using human samples/data contribute to create drug candidates with high probability of clinical effect. We will introduce our activities while showing the support flow that was actually constructed. [ABSTRACT FROM AUTHOR]

Background: In Canada, primary care reforms led to the implementation of various team-based care models to improve access and provide more comprehensive care for patients. Despite these advances, ongoing challenges remain. The aim of this scoping review is to explore current understanding of the functioning of these care models as well as the contexts in which they have emerged and their impact on the population, providers and healthcare costs. Methods: The Medline and CINAHL databases were consulted. To be included, team-based care models had to be co-located, involve a family physician, specify the other professionals included, and provide information about their organization, their relevance and their impact within a primary care context. Models based on inter-professional intervention programs were excluded. The organization and coordination of services, the emerging contexts and the impact on the population, providers and healthcare costs were analysed. Results: A total of 5952 studies were screened after removing duplicates; 15 articles were selected for final analysis. There was considerable variation in the information available as well as the terms used to describe the models. They are operationalized in various ways, generally consistent with the Patient's Medical Home vision. Except for nurses, the inclusion of other types of professionals is variable and tends to be associated with the specific nature of the services offered. The models primarily focus on individuals with mental health conditions and chronic diseases. They appear to generally satisfy the expectations of the overarching framework of a high-performing team-based primary care model at patient and provider levels. However, economic factors are seldom integrated in their evaluations. Conclusions: The studies rarely provide an overarching view that permits an understanding of the specific contexts, service organization, their impacts, and the broader context of implementation, making it difficult to establish universal guidelines for the operationalization of effective models. Negotiating the inherent complexity associated with implementing models requires a collaborative approach between various stakeholders, including patients, to tailor the models to the specific needs and characteristics of populations in given areas, and reflection about the professionals to be included in delivering these services. [ABSTRACT FROM AUTHOR]

In a trajectory management system, moving objects are typically equipped with GPS devices to report their locations to a data store. Given the potentially high frequency of location updates by multiple moving objects, these data stores often operate under write-intensive conditions. Existing trajectory indexing methods, such as XZ-ordering, which are geared towards static trajectory data, may experience considerable latency under such demanding workloads. In response, this paper introduces spatio-temporal index structures that can be constructed with low latency. Trajectories are categorized into two types for storage: 'live' and 'static'. Live trajectories are indexed by the Dual-Key Encoding (DKE) scheme, where each data point is represented by two key-value entries, facilitating both ID-temporal and spatial queries. Static trajectories, on the other hand, offer a more compact storage solution, reducing the overhead associated with live trajectories. Upon the completion of a trip, live trajectory data is transformed into a static trajectory entry through a compaction process. To augment the efficiency of spatial index construction for static trajectories, we introduce a new encoding scheme, XS2, coupled with an adaptive segmentation policy, AdaptSeg, to optimize trajectory segmentation, thereby enhancing index building and query processing efficiency. The indexing methods are demonstrated atop of LevelDB, an LSM-based key-value storage library, resulting the proposed LevelDBST system. Performance evaluations conducted using both synthetic and real-world datasets reveal that LevelDBST is capable of constructing spatial indexes for continuously updating trajectories with reduced latency, in comparison to traditional XZ-ordering methods. This efficiency is achieved while maintaining an acceptable balance in data accessing time and storage costs. [ABSTRACT FROM AUTHOR]

Copyright of Service Industries Journal is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article explores the concept of muscle memory in skeletal muscle, focusing on myonuclear accretion and permanence as key mechanisms. The study by Cumming et al. investigates the retention of myonuclei in muscle fibers following strength training, detraining, and retraining phases. The research provides insights into the molecular underpinnings of muscle memory and highlights the potential implications for preserving muscle integrity during aging, injury recovery, and in the context of doping. Further research is needed to understand the relationship between muscle memory and recovery of muscle function after periods of inactivity, as well as the effects of performance-enhancing substances on these mechanisms. [Extracted from the article]

This study presents the results of an online survey that benchmarked the organization of information technology (IT) functions in academic library members of the Association of Research Libraries. The survey investigated whether responsibility for 14 key areas resided in the libraries or in an institution-level information technology department, whether responsibilities have shifted over the past 20 years, satisfaction with services provided, assessment methods used to evaluate information technology services, and top challenges facing library IT. This paper considers the survey results addressing where the responsibility lies, satisfaction with the support, and whether and when the responsibility changed. [ABSTRACT FROM AUTHOR]

Daily experiences often involve the processing of multiple sequences, yet storing them challenges the limited capacity of working memory (WM). To achieve efficient memory storage, relational structures shared by sequences would be leveraged to reorganize and compress information. Here, participants memorized a sequence of items with different colors and spatial locations and later reproduced the full color and location sequences one after another. Crucially, we manipulated the consistency between location and color sequence trajectories. First, sequences with consistent trajectories demonstrate improved memory performance and a trajectory correlation between reproduced color and location sequences. Second, sequences with consistent trajectories show neural reactivation of common trajectories, and display spontaneous replay of color sequences when recalling locations. Finally, neural reactivation correlates with WM behavior. Our findings suggest that a shared common structure is leveraged for the storage of multiple sequences through compressed encoding and neural replay, together facilitating efficient information organization in WM. [ABSTRACT FROM AUTHOR]

The paper shows the initial outcomes of the BIG_SMAART project aims to streamline the organization of information pertaining to the documentation and analysis of archaeological sites at spatial and territorial levels. By developing ontologies and utilizing specialized thesauri for archaeological structures, the project contributes to the creation of an information infrastructure that enhances interoperability between Geographic Information Systems (GIS) and Building Information Modeling (BIM). The research methodology leverages a multi-disciplinary approach, encompassing data collection, semantic analysis of Roman structures, the evaluation and integration of archaeological thesauri, the identification of parametric object properties for BIM-based archaeological semantics, adherence to FAIR principles, and the pursuit of relevant standards. This paper shows the methodological framework of the project for the integration of archaeological and architectural information. [ABSTRACT FROM AUTHOR]

Introduction: The aim of the study was to improve student skills in writing goodquality synthesis texts through a strategic, self-regulated instruction program aimed at ensuring that students properly activated reading and writing strategies required by the synthesis task. Methods: The sample consisted of 84 university students who were randomly assigned to experimental or control conditions. The experimental group received an instructional program based on the development and self-regulated implementation of reading and writing strategies for producing synthesis texts. The control group received a program involving metacognitive knowledge of various academic text types. Both programs involved eight 60-min sessions, taught by teachers in a compulsory degree subject. For the evaluations, students produced synthesis texts from different source texts. The syntheses were graded considering text product measures: information selection, idea connection, text organization, and holistic quality; and measures of reading (underlining and note-taking) and writing (planning and review) strategies. Results: The results show that the experimental group exhibited greater improvements in synthesis quality and greater improvements in activation of information organization processes, note-taking while reading, and text planning. Discussion: In conclusion, university students can, following implementation of a strategic instructional procedure in the context of a study plan, adapt and rework their own reading and writing strategies and apply them in a self-regulated manner to synthesis tasks, improving text quality and some of the cognitive processes involved. [ABSTRACT FROM AUTHOR]

In today's world where information is a valuable and vital resource, Information Management emerges as a fundamental discipline to deal with the growing volume of data and transform it into strategic knowledge. This article seeks to present the development of Information Management from the emergence of Information Science and its subareas and its contribution to the management of organizations. Thus, the work unfolds into four main sections: (1) discussion of the framework of the emergence of Information Science and its main milestones over the years; (2) different concepts and characteristics of IC and the emergence of different branched subareas of IC; (3) presentation of the definitions and characteristics of the Information Management subarea; (4) exposition of the various advantages resulting from the application of Information Management in organizations. From the research it was possible to identify that the main advantages arising from information management contribute especially to a better understanding of the different organizational areas and help in decision making. [ABSTRACT FROM AUTHOR]

Purpose: This paper aimed to analyze the technical efficiency of the Federal Network of Professional, Scientific and Technological Education for the year 2020, by comparing the data with the previous three years. By 2020, the institutions suspended face-to-face academic activities as a preventive measure to avoid contagion from Sars-CoV-2, a virus that causes the Covid-19. Methodology: The research presents a quantitative approach and examined 41 institutions between 2017 and 2020 using the Data Envoltory Analysis (DEA) method. Results: The technical efficiency of 2018 was the lowest among the analyzed years, but the 2020 numbers are less satisfactory than the years between 2017 and 2019. In 2020, 29,3% of the institutions were considered inefficient or with poor efficiency. However, on average, the units maintained the pattern of technical efficiency recorded since 2017. Contributions of the Study: The results contribute to the transparency of public organizations; information on the cost-benefit ratio of public services; identify best practices in the use of public resources, that can help decision-making in inefficient units; and show that there is a need for improvements in educational management. [ABSTRACT FROM AUTHOR]