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Item Fact-checking(Edward Elgar Publishing) Amazeen, Michelle; Nai, Alessandro; Grömping, Max; Wirz, DominiqueItem Knowledge management as a catalyst for global marketing strategies in the age of business process digitalization(2021-02-25) Goncalves, MarcusItem Neuromarketing algorithms for digital marketing strategies: ethical considerations(2023-03-17) Goncalves, MarcusItem Reframing internationalization: a holistic framework for lusophone African entrepreneurs(2023-12-01) Goncalves, MarcusItem Neuromarketing algorithms’ consumer privacy and ethical considerations: challenges and opportunities(2023-12-06) Goncalves, MarcusItem Fostering innovation through venture capital in Kazakhstan(Research Publishing Academy, 2024-11-01) Smagulova, Gulnur; Goncalves, MarcusThis research explores Kazakhstan's venture capital (VC) landscape, focusing on its evolution, challenges, and strategies for sustainable development. Using a mixed-methods approach, the study combines qualitative interviews with quantitative market data to examine the VC ecosystem and its role in driving innovation and economic growth. Key findings reveal that Kazakhstan's VC sector has seen significant growth in recent years, supported by governmental initiatives, including establishing the Astana International Financial Centre (AIFC) and regional innovation hubs. However, challenges like market immaturity, regulatory hurdles, and limited late-stage funding persist. The study identifies critical success factors, including fostering international partnerships, streamlining regulations, and promoting entrepreneurship through targeted policies. The methodology involves snowball sampling and semistructured interviews with active venture capitalists to capture diverse perspectives. The thematic analysis highlights the importance of government support, collaboration among stakeholders, and the need for accessible data to drive informed decision-making. Survey responses further emphasize the reliance on early-stage investments, the lack of strategic investors, and difficulties securing funding for local startups. Comparative analysis with other Central Asian markets reveals that Kazakhstan's ecosystem is more advanced but still faces challenges in sustaining growth. Strategic recommendations to enhance the investment climate include aligning regulatory frameworks with international standards, improving access to finance, and expanding entrepreneurial education, underscoring the need for regional cooperation among Central Asian countries to foster VC investment across borders. By addressing these challenges and leveraging identified opportunities, Kazakhstan and neighboring countries can establish sustainable VC ecosystems to support economic diversification and innovation. This research contributes to understanding VC dynamics in developing economies and provides actionable insights for stakeholders aiming to optimize the venture capital environment in Central Asia. Keywords: Venture capital, Developing countries, VC investment culture, Innovation ecosystem, Entrepreneurial ecosystem, Kazakhstan.Item Vaccination equilibrium: externality and efficiency(Elsevier, 2024-10) Ma, Ching-ToItem The China Historical Christian Database: A Dataset Quantifying Christianity in China from 1550 to 1950(MDPI AG, 2024-06) Mayfield, Alex; Frei, Margaret; Ireland, Daryl; Menegon, EugenioThe era of digitization is revolutionizing traditional humanities research, presenting both novel methodologies and challenges. This field harnesses quantitative techniques to yield groundbreaking insights, contingent upon comprehensive datasets on historical subjects. The China Historical Christian Database (CHCD) exemplifies this trend, furnishing researchers with a rich repository of historical, relational, and geographical data about Christianity in China from 1550 to 1950. The study of Christianity in China confronts formidable obstacles, including the mobility of historical agents, fluctuating relational networks, and linguistic disparities among scattered sources. The CHCD addresses these challenges by curating an open-access database built in neo4j that records information about Christian institutions in China and those that worked inside of them. Drawing on historical sources, the CHCD contains temporal, relational, and geographic data. The database currently has over 40,000 nodes and 200,000 relationships, and continues to grow. Beyond its utility for religious studies, the CHCD encompasses broader interdisciplinary inquiries including social network analysis, geospatial visualization, and economic modeling. This article introduces the CHCD’s structure, and explains the data collection and curation process.Item Boston real estate residential rental trends(Kaggle, 2024-10-23) Stoller, GregoryProject for a doctoral business class (DBA 746 Artificial Intelligence Applications with Dr. Hunter Monroe) combining Python coding with industry researchItem Montevideo convention and CGTN: defining statehood for global outreach(USC Annenberg Press, 2023) Chen, Alex Keyu; Massignan, Virginia; Yachin, Mor; Winkler, Carol K.; Lokmanoglu, AyseItem ISIS media and troop withdrawal announcements: visualizing community and resilience(USC Annenberg Press, 2022) Lokmanoglu, Ayse; Winkler, Carol; McMinimy, Kayla; Almahmoud, MuniraItem Item Changing preferences: an experiment and estimation of market-incentive effects on altruism(Elsevier BV, 2023-12) Byambadalai, Undral; Ma, Ching-To Albert; Wiesen, DanielThis paper studies how altruistic preferences are changed by markets and incentives. We conduct a laboratory experiment with a within-subject design. Subjects are asked to choose health care qualities for hypothetical patients in monopoly, duopoly, and quadropoly. Prices, costs, and patient benefits are experimental incentive parameters. In monopoly, subjects choose quality by trading off between profits and altruistic patient benefits. In duopoly and quadropoly, subjects play a simultaneous-move game. Uncertain about an opponent's altruism, each subject competes for patients by choosing qualities. Bayes-Nash equilibria describe subjects' quality decisions as functions of altruism. Using a nonparametric method, we estimate the population altruism distributions from Bayes-Nash equilibrium qualities in different markets and incentive configurations. Competition tends to reduce altruism, but duopoly and quadropoly equilibrium qualities are much higher than monopoly. Although markets crowd out altruism, the disciplinary powers of market competition are stronger. Counterfactuals confirm markets change preferences.Item Shot noise-mitigated secondary electron imaging with ion count-aided microscopy(Proceedings of the National Academy of Sciences, 2024-07-30) Agarwal, Akshay; Kasaei, Leila; He, Xinglin; Kitichotkul, Ruangrawee; Hitit, Oğuz Kağan; Peng, Minxu; Schultz, J. Albert; Feldman, Leonard C.; Goyal, Vivek K.Modern science is dependent on imaging on the nanoscale, often achieved through processes that detect secondary electrons created by a highly focused incident charged particle beam. Multiple types of measurement noise limit the ultimate trade-off between the image quality and the incident particle dose, which can preclude useful imaging of dose-sensitive samples. Existing methods to improve image quality do not fundamentally mitigate the noise sources. Furthermore, barriers to assigning a physically meaningful scale make the images qualitative. Here, we introduce ion count-aided microscopy (ICAM), which is a quantitative imaging technique that uses statistically principled estimation of the secondary electron yield. With a readily implemented change in data collection, ICAM substantially reduces source shot noise. In helium ion microscopy, we demonstrate 3[Formula: see text] dose reduction and a good match between these empirical results and theoretical performance predictions. ICAM facilitates imaging of fragile samples and may make imaging with heavier particles more attractive.Item The particle of Haag's local quantum physics: a critical assessment(MDPI AG, 2024-09-01) Jaeger, GreggRudolf Haag's Local Quantum Physics (LQP) is an alternative framework to conventional relativistic quantum field theory for combining special relativity and quantum theory based on first principles, making it of great interest for the purposes of conceptual analysis despite currently being relatively limited as a tool for making experimental predictions. In LQP, the elementary particles are defined as species of causal link between interaction events, together with which they comprise its most fundamental entities. This notion of particle has yet to be independently assessed as such. Here, it is captured via a set of propositions specifying particle characteristics and then compared to previous particle notions. Haag's particle differs decisively with respect to mechanical intuitions about particles by lacking, among other things, even an approximate independent space-time location. This notion is thus found to differ greatly even from those of relativistic quantum mechanics and quantum field theory, which have been applied to the known elementary particles.Item On the Chinese Character 物 (Object)(The Commercial Press, Beijing China, 2024-07-01) Huang, Weijia; Pan, FengfanItem The price of privacy: a performance study of confidential virtual machines for database systems(ACM, 2024-06-09) Qiu, Lina; Kollios, George N.Confidential virtual machines (CVM) use trusted hardware to encrypt data being processed in memory to prevent unauthorized access. Applications can be migrated to CVM without changes, i.e., lift and shift, to handle sensitive workloads securely in public clouds. AMD Secure Encrypted Virtualization (SEV) is one of the prominent technologies that provides hardware support for CVM. In this paper, we investigate various system operations, including CPU, memory, and disk and network I/O, to understand the performance overheads of SEV-supported CVMs. Our findings indicate that memory and I/O-intensive workloads can incur significant overhead. We then study the performance implications of running unmodified database applications, specifically Cock-roachDB, on CVMs by examining typical data access patterns of OLTP and OLAP workloads. A notable performance overhead of up to 18% is observed for TPC-C workload running on multinode database clusters, and an overhead of up to 13% is observed for TPC-H workload running on single-node database instances. The non-negligible overhead suggests the potential and necessity for database optimizations with respect to CVM, particularly for time-sensitive workloads. We offer a glimpse of the effect that CVM overhead can have in query planning using a simple join query: the optimal join algorithm becomes suboptimal on CVM, along with discussion of potential optimizations for reducing CVM overhead in the realm of database applications.Item QueryShield: cryptographically secure analytics in the cloud(ACM, 2024-06-09) Seow, Ethan; Baum, Eli; Buxbaum, Sam; Faisal, Muhammad Sajid; Liagouris, John; Kalavri, Vasiliki; Varia, MayankWe present a demonstration of QueryShield, a service for streamlined, cryptographically secure data analytics in the cloud. With QueryShield, data analysts can advertise analysis descriptions to data owners, who may agree to participate in a computation for profit or for the greater good, provided that their data remain private. QueryShield supports relational and time series analytics with provable data privacy guarantees using secure multi-party computation (MPC). At the same time, it makes MPC accessible to non-expert users by offering a familiar web interface and fully-automated orchestration of cryptographic computations. We devise three demonstration scenarios for conference attendees: (i) an interactive survey of private employment information to estimate the industry-academia wage gap in the data management community, (ii) a relational analysis that identifies credit score anomalies in sensitive customer data from multiple credit agencies, and (iii) a medical use case that assesses the effectiveness of insulin dose frequency in a patient cohort.Item KVBench: a key-value benchmarking suite(ACM, 2024-06-09) Zhu, Zichen; Athanassoulis, ManosKey-value stores are at the core of several modern NoSQL-based data systems, and thus, a comprehensive benchmark tool is of paramount importance in evaluating their performance under different workloads. Prior research reveals that real-world workloads have a diverse range of characteristics, such as the fraction of point queries that target non-existing keys, point and range deletes, as well as, different distributions for queries and updates, all of which have very different performance implications. State-of-the-art key-value workload generators, such as YCSB and db_bench, fail to generate workloads that emulate these practical workloads, limiting the dimensions on which we can benchmark the systems' performance. In this paper, we present KVBench, a novel synthetic workload generator that fills the gap between classical key-value workload generators and more complex real-life workloads. KVBench supports a wide range of operations, including point queries, range queries, inserts, updates, deletes, range deletes, and among these options, inserts, queries, and updates can be customized by different distributions. Compared to state-of-the-art key-value workload generators, KVBench offers a richer array of knobs, including the proportion of empty point queries, customized distributions for updates and queries, and range deletes with specific selectivity, constituting a significantly flexible framework that can better emulate real-world workloads.