Information Science Research Articles

The Application of Hybrid Instruction Mode in the Course of Geographic Information System Principles

Abstract. Geographic Information System Principles is one of the professional core courses for the students majoring in Geographic Information Science. It plays an important role in providing a theoretical foundation and technical support for subsequent professional courses. The course is offered in the second semester of the freshman year and is the first professional core course for students. There are four key issues that need to be addressed. Firstly, the main content of this course is extensive and the difficulty level is relatively high. Secondly,theory and software operation are disconnected in traditional classes. Thirdly, the traditional teaching mode can not well stimulate students' interest. Fourthly, the traditional teaching and learning evaluation method focuses on results but not process. Hence, we rely on the online teaching platform of our school to carry out Hybrid Instruction Mode, hoping to improve students' learning effect and improve teaching quality. Based on the outcome-based education (OBE) concept, we refine the teaching objectives, and subsequently enhance the teaching materials. Then, we have built a blended teaching mode. The whole teaching process is divided into four parts including "course guidance", "pre-class self-study", "in-class practice", and "post-class research". Online and offline teaching are connected with various activities. Discussions, exercises, reflections, assessments, critical thinking, paper reading and homework are online activities. Guidance, analysis and practice are offline activities. During the teaching process, we also reformed teaching method and carried out ecological civilization and scientific spirit education.We optimized the assessment method using the formative evaluation. The course objectives are almost achieved.

Tighter sum unitary uncertainty relation

Abstract Unitary uncertainty relations provide a theoretical framework that enhances our understanding of the principles underlying quantum mechanics and its applications in quantum information science. In this study, we derive both the unitary uncertainty relation and the weighted unitary uncertainty relation based on the sum variance for arbitrary pairs of unitary operators. By applying the arithmetic geometric mean inequality, we obtain a lower bound that is tighter than the one provided by Bagchi and Pati. [Physical Review A 94,042104] for two unitary operators. To illustrate our results, we include examples of both the unitary uncertainty relation and the weighted uncertainty relation based on sum variance.

Top 50 Most Cited Articles in Transplant Dermatology: A Bibliometric Analysis.

Solid organ transplant recipients are at high risk for developing skin malignancies due to prolonged immunosuppression. The field of transplant dermatology (TD) has experienced a surge in research and clinical advancements, yet there is no quantitative evaluation estimating the impact of TD literature. Identify and characterize the most frequently cited TD articles. Institute For Scientific Information Web of Science was used to identify the 50 most cited research articles in TD. Results were reviewed by 3 independent authors. A network analysis was performed to assess collaboration patterns among coauthors. Top articles held a combined total of 12,114 citations. The top-cited article was "Cancer incidence before and after kidney transplantation," by Vajdic and colleagues in the Journal of the American Medical Association (2006) with 872 citations. A total of 22 countries and 221 institutions were represented. This bibliometric analysis offers a detailed overview of the most cited manuscripts in TD and illustrates the discoveries steering TD research and practice.

Television and the Origins of Visual Pattern Recognition AI in Japan: a ‘Quest for a Seeing Machine’

Abstract This article traces the genealogy of contemporary data-driven computer vision to developments at the Japan Broadcasting Corporation (NHK) in the 1960s. Specifically, it examines NHK’s Visual and Auditory Information Science Unit and its role in the invention of the world’s first deep convolutional neural network. The use of television to collect viewer behaviour data enabled modelling of eye-brain information processing, in particular mechanisms of feature extraction. This, in turn, linked Fukushima Kunihiko’s formative work on signal compression to the development of a pattern recognition machine, resulting in the creation of the world’s first convolutional neural network. Recovering this history is important for two reasons. First, it helps counter a trend of ‘digital universalism’ that covertly homogenizes local differences into a single culture of artificial intelligence in the Cold-War-era US. Second, it reveals the largely ignored role of television in the genesis of digital image technologies and AI more broadly.

Emotional distress of adolescents from dysfunctional families as a subject of scientific research

The article provides a scientific justification for the relevance of studying emotional distress of adolescents from dysfunctional families. The social significance of the topic is noted: the emotional distress of adolescent children not only makes unhappy themselves, but also reduces the level of social health of the family and the whole society, affecting social security. The purpose of the research is a theoretical analysis of sources of scientific information which, presumably, can form a methodological basis for studying family predictors of the adolescent emotional distress. The material in the article is presented in accordance with four research questions concerning the formulation of this scientific problem, its current state in domestic and foreign social psychology, and its poorly studied aspects. The definition of the concept of the emotional distress is clarified, its similarity to the concept of emotional modality is shown; the already established features of the emotional sphere of adolescent children are noted. It is concluded that by now there are prerequisites for studying families with adolescents simultaneously from the standpoint of socio-psychological and systemic approaches. A model of empirical research of the family predictors of the emotional distress of adolescents from dysfunctional families is proposed. The prospects of practical application of the study results are outlined.

Experiences and perceptions of acute testicular pain, with a focus on reasons for delayed presentation to hospital: a qualitative evidence synthesis

BackgroundThe annual incidence of testicular torsion is approximately 1 in 4000 males under the age of 25. Despite the 97% testicular salvage rate when surgical intervention is within 6 hours...

Eugene Garfield (1925 − 2017)—a high-impact information scientist

Eugene Garfield (1925 − 2017)—a high-impact information scientist

On the Impossibility of Convergence of Mixed Strategies with Optimal No-Regret Learning

We study the limiting behavior of the mixed strategies that result from optimal no-regret learning in a repeated game setting where the stage game is any 2 × 2 competitive game. We consider optimal no-regret algorithms that are mean-based and monotonic in their argument. We show that for any such algorithm, the limiting mixed strategies of the players cannot converge almost surely to any Nash equilibrium. This negative result is also shown to hold under a broad relaxation of these assumptions, including popular variants of Follow-the-Regularized Leader with optimism or adaptive step sizes. Finally, we provide partial evidence that the monotonicity and mean-based assumptions can be removed or relaxed. Our results identify the inherent stochasticity in players’ realizations as a critical factor underlying this divergence, and demonstrate a crucial difference in outcomes between using the opponent’s mixtures and realizations to make updates. Funding: V. Muthukumar was supported by a Simons-Berkeley Research Fellowship, NSF awards IIS-2212182 and CCF-2239151, and generous gifts from Amazon, Adobe, and Google. S. Phade acknowledges the support of the NSF [Grants CNS-1527846 and CCF-1618145] and the NSF Science & Technology Center [Grant CCF-0939370 (Science of Information)]. A. Sahai acknowledges the support of the ML4Wireless center member companies and the NSF [Grants AST-144078 and ECCS-1343398].

Ecologically and Biologically Significant Marine Protected Areas in the Caspian Sea: A Review

This paper provides a brief review of the ecologically and biologically significant marine protected areas in the Caspian Sea. As a result of the collaboration between the Tehran Convention and the Convention on Biological Diversity (CBD) the Regional Workshop to Facilitate the Description of Ecologically or Biologically Significant Marine Areas (EBSAs) in the Black Sea and the Caspian Sea took place from 25 to 29 April 2017 in Baku (Azerbaijan). The Regional Workshop compiled a list of areas in the above seas that meet the EBSA criteria with corresponding detailed description of each areas based on scientific information available at that time. We provide a brief information on each of these 16 EBSAs in the Caspian Sea in accordance with their descriptions. We discuss different definitions of specially protected areas given by different international organizations, as well as the fact that the EBSA is not a marine protected area by a definition. We discuss a possible evolution and transformation of the Caspian EBSAs in the modern period in connection with the continuing fall in the Caspian Sea level.

Are random price generators useful for health policy processes and analysis? effectiveness of random price generators in health policy processes and analysis

This paper discusses why using random price generators in an economic model for medical markets may be useful. It summarizes the different steps for the development of the model and describes an original contribution of the physicians’ choice model with random drug prices applied to Type 2 diabetes in the US. Pharmaceutical markets have been supply-driven to boost life science and medical technologies; however, with the widening inequalities inside national health systems and the global agenda for universal health coverage, more economic research is being done to strengthen the analysis of demand for healthcare services. Research, especially, examines more disaggregated levels of demand systems to understand the heterogeneity of physicians’ choices and better capture patient needs. It can also be an approach to calibrate supply and demand adjustments in medical markets. This paper argues that choice modeling is particularly relevant, using random price generators in a structural model where a demand approach is useful. If validated by additional experimental studies, this first study by Professors Huttin & Hausman (2021) could be used in advanced value assessment frameworks. Random price generators on medical markets could also be tested with additional models that fit oligopolistic market structures (e.g., models for differentiated product markets such as the Berry–Levinsohn–Pakes model). It may also help with a policy analysis process that addresses major disruptive transformations of market dynamics, evolving boundaries in science, fast digitalization, and artificial intelligence-based information systems.

A Novel Noise-Aware Classical Optimizer for Variational Quantum Algorithms

A key component of variational quantum algorithms (VQAs) is the choice of classical optimizer employed to update the parameterization of an ansatz. It is well recognized that quantum algorithms will, for the foreseeable future, necessarily be run on noisy devices with limited fidelities. Thus, the evaluation of an objective function (e.g., the guiding function in the quantum approximate optimization algorithm (QAOA) or the expectation of the electronic Hamiltonian in variational quantum eigensolver (VQE)) required by a classical optimizer is subject not only to stochastic error from estimating an expected value but also to error resulting from intermittent hardware noise. Model-based derivative-free optimization methods have emerged as popular choices of a classical optimizer in the noisy VQA setting, based on empirical studies. However, these optimization methods were not explicitly designed with the consideration of noise. In this work we adapt recent developments from the “noise-aware numerical optimization” literature to these commonly used derivative-free model-based methods. We introduce the key defining characteristics of these novel noise-aware derivative-free model-based methods that separate them from standard model-based methods. We study an implementation of such noise-aware derivative-free model-based methods and compare its performance on demonstrative VQA simulations to classical solvers packaged in scikit-quant. History: Accepted by Giacomo Nannicini, Area Editor for Quantum Computing and Operations Research. Accepted for Special Issue. Funding: This material is based upon work supported by the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers and the Office of Advanced Scientific Computing Research, Accelerated Research for Quantum Computing program under contract number DE-AC02-06CH11357. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.0177 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2023.0177 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

Kinetic inductance current sensor for visible to near-infrared wavelength transition-edge sensor readout

Single-photon detectors based on the superconducting transition-edge sensor are used in a number of visible to near-infrared applications, particularly for photon-number-resolving measurements in quantum information science. To be practical for large-scale spectroscopic imaging or photonic quantum computing applications, the size of visible to near-infrared transition-edge sensor arrays and their associated readouts must be increased from a few pixels to many thousands. In this manuscript, we introduce the kinetic inductance current sensor, a scalable readout technology that exploits the nonlinear kinetic inductance in a superconducting resonator to make sensitive current measurements. Kinetic inductance current sensors can replace superconducting quantum interference devices for many applications because of their ability to measure fast, high slew-rate signals, their compatibility with standard microwave frequency-division multiplexing techniques, and their relatively simple fabrication. Here, we demonstrate the readout of a visible to near-infrared transition-edge sensor using a kinetic inductance current sensor with 3.7 MHz of bandwidth. We measure a readout noise of 1.4pA/Hz\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$1.4\\,{{{\\rm{pA}}}}/\\sqrt{{{{\\rm{Hz}}}}}$$\\end{document}, considerably below the detector noise at frequencies of interest, and an energy resolution of (0.137 ± 0.001) eV at 0.8 eV, comparable to resolutions observed with non-multiplexed superconducting quantum interference device readouts.

Layered hybrid superlattices as designable quantum solids.

Crystalline solids typically show robust long-range structural ordering, vital for their remarkable electronic properties and use in functional electronics, albeit with limited customization space. By contrast, synthetic molecular systems provide highly tunable structural topologies and versatile functionalities but are often too delicate for scalable electronic integration. Combining these two systems could harness the strengths of both, yet realizing this integration is challenging owing to distinct chemical bonding structures and processing conditions. Two-dimensional atomic crystals comprise crystalline atomic layers separated by non-bonding van der Waals gaps, allowing diverse atomic or molecular intercalants to be inserted without disrupting existing covalent bonds. This enables the creation of a diverse set of layered hybrid superlattices (LHSLs) composed of alternating crystalline atomic layers of variable electronic properties and self-assembled atomic or molecular interlayers featuring customizable chemical compositions and structural motifs. Here we outline strategies to prepare LHSLs and discuss emergent properties. With the versatile molecular design strategies and modular assembly processes, LHSLs offer vast flexibility for weaving distinct chemical constituents and quantum properties into monolithic artificial solids with a designable three-dimensional potential landscape. This opens unprecedented opportunities to tailor charge correlations, quantum properties and topological phases, thereby defining a rich material platform for advancing quantum information science.

Quantum steering ellipsoids and quantum obesity in critical systems

Abstract Quantum obesity (QO) is a novel function introduced to quantify quantum correlations that go beyond traditional measures like entanglement, while also functioning as an entanglement witness. One of the key strengths of QO lies in its analyticity for arbitrary states of bipartite systems, making it a more accessible and versatile tool compared to other measures of quantum correlations, such as quantum discord. In this work, we highlight the importance of QO as a fundamental quantity for identifying signatures of quantum phase transitions, which are critical changes in the ground state of quantum systems driven by quantum fluctuations. We introduce a mechanism based on local filtering operations designed to enhance the critical behavior of QO near phase transition points, providing a deeper understanding of these phenomena. Furthermore, we present a theorem that characterizes how QO transforms under local quantum operations and classical communications (LOCC), which broadens its applicability to a wider range of quantum systems. This opens new avenues for exploring quantum criticality and other novel quantum phenomena by leveraging the analytically computable, pairwise QO, thus offering both theoretical insights and practical applications in quantum information science.

Agrobiodiversity and food security: challenges and sustainable solutions

Objective: Agricultural biodiversity, also known as agrobiodiversity, encompasses the variety of plants, animals, and microorganisms that are directly or indirectly involved in agriculture. This diversity is the result of millennia of selection, management, and domestication of species, which has allowed societies to adapt to different environmental and cultural conditions. However, in recent decades, the loss of agrobiodiversity, accelerated by industrial agriculture, the expansion of monocultures, and the reduction of varieties, has put global food security at risk. This diversity is crucial to ensuring the resilience of agricultural systems in the face of challenges such as climate change, emerging pests, and the depletion of natural resources. This paper examines the importance of conserving agricultural biodiversity from the perspective of food security. It emphasizes how agrobiodiversity not only contributes to the stability of food production but also improves human diets by diversifying crops and providing essential micronutrients. Design/Methodology/Approach: A search was conducted on the following scientific information platforms: Web of Science database and Google Scholar. A systematic search for publications related to agrobiodiversity systems was carried out in the WoS database and Google Scholar over the last 49 years (1975–2024). Results: Genetic erosion is particularly concerning because genetic diversity is essential for crops to face environmental challenges such as climate change, pests, and diseases. The loss of traditional varieties, which are selected by local farmers to adapt to specific conditions, increases agriculture's vulnerability to external disruptions. These landraces, having been cultivated in genetically diverse mosaics, offer protection against catastrophic losses in the event of crop failures due to extreme conditions or diseases. Findings/Conclusions: Genetic diversity allows for the development of sustainable solutions to pests and diseases, reducing dependence on pesticides and promoting more environmentally friendly farming practices. However, challenges related to biodiversity conservation persist, making it essential to implement public policies that promote agrobiodiversity and address the socioeconomic issues that limit its adoption.

Analyzing Data Sharing Policies in Library and Information Science: Journal Metrics, Open Access Status, and Publisher Volume

The objective of this study is to explore the prevalence and characteristics of data sharing policies in library and information science (LIS) journals, focusing on their relationship with journal metrics, publisher volume (number of journals managed by the publisher), and open access (OA) status. The study examined the link between data sharing policies and journal metrics in LIS journals indexed in Scopus. Using secondary data from the SJR portal and qualitative data from author guidelines, the study revealed several key findings: First, a positive relationship existed between publisher volume and the presence of data sharing policies, with high-volume publishers consistently implementing such policies. Second, 50.2% of LIS journals lacked data sharing guidelines, indicating a significant gap. Third, journals that encouraged or required data sharing under certain conditions tended to perform better in metrics such as quartiles, h-index, and citation impact. Fourth, data sharing policies were more common in higher-ranked journals and were linked to better journal metrics. Fifth, higher-ranked journals were more likely to include details on data statements, DOIs, and repositories than lower-ranked journals. Lastly, non-OA journals were more likely to encourage practices such as including data repositories and supplementary files in submissions, compared to OA journals, revealing unexpected disparities. In conclusion, data sharing policies in LIS journals showed associations with journal ranking and publisher volume, with non-OA journals showing higher presence of certain data sharing practices.

Semidefinite programming in quantum information science

Semidefinite programming in quantum information science

Teaching quantum information science to secondary school students with photon polarization and which-path encoding

Teaching quantum information science to secondary school students with photon polarization and which-path encoding

Time-encoded photonic quantum states: Generation, processing, and applications

Encoding and processing quantum information in the time-of-arrival of photons offer significant advantages for quantum information science and technology. These advantages include ease of experimental realization, robustness over photon state transmission, and compatibility with existing telecommunication infrastructure. Additionally, time-of-arrival encoding has the potential for high-rate quantum communication and holds promise for the future development of quantum internet. This review explores the generation, processing, and applications of time-encoded quantum states, focusing on both single-photon states, energy–time entanglement, and time-bin entanglement. We summarize the nonlinear optics platforms and advanced laser and modulation techniques utilized for photon sources that enable quantum information encoding onto the photons' time-of-arrival. We also highlight advanced quantum state processing methods in the time domain, including the Franson interferometry, optical switch-based schemes, and state-of-the-art measurement and detection schemes that allow for high-speed and multi-dimensional quantum operations. Finally, we review the mainstream implementations mainly including the quantum communication demonstrations and outline future directions for developing practical quantum networks leveraging time-encoded photon states.

Conceptual models of the sociotechnical: Introduction to special issue

AbstractThis special issue of the “Journal of the Association for Information Science and Technology” examines conceptual models as products of, and tools for, critical inquiry in Information Science (IS). The papers included in this issue present diverse perspectives on how conceptual models impact sociotechnical systems, spanning topics such as knowledge organization, representation, and information system design. Key themes include the intersection of model development with ethical considerations, the historical and future implications of conceptual modeling decisions, and the potential for conceptual models to address issues of power, representation, and justice in emerging technologies. This introduction situates the contributions within broader discussions of conceptual modeling in IS and highlights the field's unique approach to reflexive critique and sociotechnical analysis.