Large-scale Quantitative Studies Research Articles

Spatial standardization of taxon occurrence data—a call to action

Abstract The fossil record is spatiotemporally heterogeneous: taxon occurrence data have patchy spatial distributions, and this patchiness varies through time. Large-scale quantitative paleobiology studies that fail to account for heterogeneous sampling coverage will generate uninformative inferences at best and confidently draw wrong conclusions at worst. Explicitly spatial methods of standardization are necessary for analyses of large-scale fossil datasets, because nonspatial sample standardization, such as diversity rarefaction, is insufficient to reduce the signal of varying spatial coverage through time or between environments and clades. Spatial standardization should control both geographic area and dispersion (spread) of fossil localities. In addition to standardizing the spatial distribution of data, other factors may be standardized, including environmental heterogeneity or the number of publications or field collecting units that report taxon occurrences. Using a case study of published global Paleobiology Database occurrences, we demonstrate strong signals of sampling; without spatial standardization, these sampling signatures could be misattributed to biological processes. We discuss practical issues of implementing spatial standardization via subsampling and present the new R package divvy to improve the accessibility of spatial analysis. The software provides three spatial subsampling approaches, as well as related tools to quantify spatial coverage. After reviewing the theory, practice, and history of equalizing spatial coverage between data comparison groups, we outline priority areas to improve related data collection, analysis, and reporting practices in paleobiology.

FAMILY BUSINESS INNOVATIVENESS: A QUANTITATIVE ANALYSIS OF THE INDIVIDUAL AND COMBINED EFFECT OF SIZE, AGE/GENERATION AND FAMILY OWNERSHIP

No large-scale quantitative studies exist on how the complex characteristics of the firm affect the innovativeness of family businesses. Our study is the first to quantitatively examine how size, age/generation and family ownership individually and in combination affect the innovativeness of family businesses, using data from 56 countries. Firstly, we found that medium and large family businesses are perceived by potential successors as more innovative than small businesses; secondly, that the trend of family business innovativeness changes over time and generations according to the U-shape line; and thirdly, that the most effective family ownership in terms of innovativeness seems to be that with exactly 50%. These results were subsequently confirmed by testing the combined effect of the above mentioned three characteristics. In contrast, small family businesses in which the second or any subsequent generation is involved and which are minority or majority family-owned are perceived as the least innovative family businesses. Our findings can help public authorities in deciding how to allocate public funds, investors in deciding how to co-finance projects, and family businesses in defining development and innovation strategies for their growth.

Exploring Chinese university English writing teachers’ emotions in providing feedback on student writing

Abstract Despite the growing interest in emotions in L2 writing education, empirical research on teachers’ emotions as feedback providers is limited. With 288 English writing teachers from 120 universities in 23 provinces of China, this study developed a 17-item scale to measure Chinese university English writing teachers’ feedback-giving emotions. Exploratory factor analysis revealed five kinds of emotions: cheerfulness, contentment, frustration, anxiety, and anger. Latent profile analysis identified four groups of teachers according to their diverse patterns of emotions: slight-positive-emotional teachers (N = 118, 40.97 % of the total sample), negative-emotional teachers (N = 35, 12.15 %), positive-emotional teachers (N = 50, 17.36 %), and mixed-emotional teachers (N = 85, 29.51 %). Most demographic variables, including teaching experience, student background, and institution prestige, had no correlation with teachers’ feedback-giving emotions. Only professional training experience had minimal influence on teachers’ group memberships concerning feedback-giving emotions. This study contributes to the literature on teachers’ emotions during the provision of feedback by developing an instrument for large-scale quantitative studies. It also confirms the complexity of feedback-giving emotions, particularly the identification of mixed-emotional teachers.

Generative artificial intelligence: University student awareness, experience, and confidence in use across disciplines

The global higher education sector has been significantly disrupted by the proliferation of generative artificial intelligence tools such as ChatGPT, especially in relation to its implications for assessment. However, few studies to date have explored student perspectives on these tools. This article reports on one of the first large-scale quantitative studies of student views on generative artificial intelligence at an Australian university (n = 1,135). When the survey was conducted, most students had low knowledge, experience, and confidence in using these tools. These results varied across disciplines and across some student sub-groups, such as mature-age students and international students. Confidence appeared to increase with experience, although the data also revealed a portion of students that have never used these tools yet still felt confident in using them. In exploring these results, this article aims to shed new light on this fast-evolving landscape and inform the future direction of supporting students to engage with generative artificial intelligence tools appropriately.

Large-scale weighted sequence alignment for the study of intertextuality in Finnic oral folk poetry

The digitization of large archival collections of oral folk poetry in Finland and Estonia has opened possibilities for large-scale quantitative studies of intertextuality. As an initial methodological step in this direction, I present a method for pairwise line-by-line comparison of poems using the weighted sequence alignment algorithm (a.k.a. ‘weighted edit distance’). The main contribution of the paper is a novel description of the algorithm in terms of matrix operations, which allows for much faster alignment of a poem against the entire corpus by utilizing modern numeric libraries and GPU capabilities. This way we are able to compute pairwise alignment scores between all pairs from among a corpus of over 280,000 poems. The resulting table of over 40 million pairwise poem similarities can be used in various ways to study the oral tradition. Some starting points for such research are sketched in the latter part of the article.

The effects of sample storage duration on tardigrade density and community composition in moss samples

In studies on micrometazoans, sample storage and processing methods are mostly decided based on sample quality (e.g., substrate type and moisture level), and the choice of methods may affect the reliability of the data. However, these methods are poorly studied and rarely reported in detail. Our aim was to determine the methodological compromise between efficiency and reliability required for large-scale quantitative meiofaunal ecological studies. Specifically, we tested whether storage duration (necessary for large number of samples) affects the density or community composition of tardigrades in moss samples. We focus on a largely unexplored limnoterrestrial ecosystem – boreal peatlands, where moss moisture levels are naturally variable across different microhabitats and moss species. We collected seven moss samples from a peatland in Central Finland, kept them in a refrigerator and extracted tardigrades using the Baermann wet funnel at 1, 24, 48 and 96 h post sampling. We found a significant decrease in tardigrade density (32 % on average), but no changes in community composition, after the first 24 h of storage. Based on these results, we recommend that samples collected from wet limnoterrestrial habitats should be processed within 24 h to ensure accuracy and comparability of large-scale quantitative data on tardigrade ecology.

The contribution of armed conflict to vulnerability to disaster: Empirical evidence from 1989 to 2018

Disasters and armed conflicts often occur together, leading to severe consequences for affected populations. While qualitative investigations have explored how conflict can influence vulnerability to disasters, there is still a lack of systematic quantitative studies that provide broader evidence on the contribution of conflict to vulnerability. Although existing qualitative work has made progress in understanding potential mechanisms, large-scale quantitative studies are crucial for comprehending the scope of this relationship and attempting to isolate associations between specific variables. This study presents a statistical model using extensive large-N, cross-country data to address this research gap and analyse the conflict-disaster relationship. Analysing data from 157 countries between 1989 and 2018, we found a strong positive correlation between armed conflict and disasters. The results remained consistent across various model specifications and robustness checks. In countries experiencing armed conflict, disaster occurrence was observed 5% more frequently, disaster-related mortality per year was 34% higher, and deaths per million inhabitants were 16% higher compared to countries without conflict. While there is evidence that conflict can occasionally intensify disaster hazards, there is a greater evidence suggesting that the relationship between conflict and disaster operates through mechanisms that negatively affect vulnerability and response capacity.

Досвід проведення онлайн-досліджень серед чоловіків, які мають секс з чоловіками, із застосуванням Respondent Driven Sampling в інших країнах (огляд літератури)

The proposed article describes the global experience of adapting the RDS (respondent-driven sample) methodology, used as a de facto standard in large-scale quantitative studies of social groups, to the world of web communications. The experience accumulated in global practice allows us to state that WebRDS is faster and cheaper, provides a greater diversity of the research population and the possibility of recruiting simultaneously at several sites without extensive contacts in local communities, works in countries with very different income levels of the population, and can be combined with traditional RDS, and other survey methods (e.g., with telephone survey). At the same time, WebRDS has its own characteristics, among which we note the vulnerability to fraud, the sensitivity of the response rate to the size of the questionnaire, the presence of biases caused by access to the Internet or mobile connection and the habit of using online tools, not always full control of the research team over the use of the collected data with the help of third-party Internet data platforms, as well as higher requirements for the technical competence of both researchers and ethics committees, etc. In Ukraine, the prerequisites for successfully implementing WebRDS have been created. Considering the challenges that have arisen due to the occupation of part of the territories and the large-scale migration of the population, it seems appropriate to adapt the available foreign experience in implementing such a recruiting system to the practice of biobehavioral research of vulnerable groups in Ukraine.

Disentangling the cultural evolution of ancient China: a digital humanities perspective

Being recognized among the cradles of human civilization, ancient China nurtured the longest continuous academic traditions and humanistic spirits, which continue to impact today’s society. With an unprecedented large-scale corpus spanning 3000 years, this paper presents a quantitative analysis of cultural evolution in ancient China. Millions of intertextual associations are identified and modelled with a hierarchical framework via deep neural network and graph computation, thus allowing us to answer three progressive questions quantitatively: (1) What is the interaction between individual scholars and philosophical schools? (2) What are the vicissitudes of schools in ancient Chinese history? (3) How did ancient China develop a cross-cultural exchange with an externally introduced religion such as Buddhism? The results suggest that the proposed hierarchical framework for intertextuality modelling can provide sound suggestions for large-scale quantitative studies of ancient literature. An online platform is developed for custom data analysis within this corpus, which encourages researchers and enthusiasts to gain insight into this work. This interdisciplinary study inspires the re-understanding of ancient Chinese culture from a digital humanities perspective and prompts the collaboration between humanities and computer science.

Exodus and Its Aftermath: Jewish Refugees in the Wartime Soviet Interior by Albert Kaganovitch

Reviewed by: Exodus and Its Aftermath: Jewish Refugees in the Wartime Soviet Interior by Albert Kaganovitch Serafima Velkovich Albert Kaganovitch. Exodus and Its Aftermath: Jewish Refugees in the Wartime Soviet Interior. Madison: University of Wisconsin Press, 2022. 336 pp. Albert Kaganovitch’s Exodus and Its Aftermath discusses the topic of Jewish refugees in the USSR during the Second World War. After the Nazi invasion in June 1941, millions of people fled to the inner territories, trying to escape the war and save their lives. According to various estimates, there were about two million Jewish refugees among them, who were evacuated by the authorities or fled on their own to the interior of the Soviet Union. Some of the refugees were Soviet citizens; others arrived forcibly from Poland, the former Baltic states, and Romania. The book is rich with examples from memoirs and a multitude of archival materials, which are accompanied by much statistical data, based on large-scale quantitative studies. All of these sources give a detailed picture of the situation regarding the places where Jewish refugees arrived. Kaganovitch reconstructs the circumstances from different perspectives: the official position and those of the refugees themselves. He raises important topics, including local situations of famine, diseases, epidemics, and deaths. The death rate of the population (Jews and non-Jews) in some places in Siberia and the Urals was almost 44 percent higher in comparison to previous years. In some places, the mortality was even higher than in forced labor camps. “The hotbeds of epidemics were the railway stations, where refugees spent long hours and days, waiting for the possibility to move somewhere” (107). At the same time, the author pays extensive attention to job conditions. The Soviet prewar slogan “He who doesn’t work, doesn’t eat” serves as the title of the chapter about employment problems, which were quite common. Only those who worked could receive some food and goods, but in many cases, it was impossible to obtain a job. As a result of the lack of work and the impossibility of buying anything, theft, bribes, and black market operations thrived. [End Page 236] Kaganovitch devotes a prominent place to a discussion of the authorities’ attitude and measures toward Jewish refugees. Quite a few sources show the antisemitic policies of top-ranking personnel of the Communist Party in various regions. At the same time, lower-level local functionaries demonstrated negative attitudes toward the refugees, not only because they were Jewish, but mostly because they were strangers. It is noteworthy that Communist Party officials spread the myth that they had successfully absorbed over ten million evacuees, including Jews. At the end of the book, Kaganovitch deals with the return to life after the liberation. When the war ended, the situation of Jewish refugees did not change dramatically. They coped with the reality of antisemitic propaganda, the absence of housing, and the lack of permission to return to their hometowns via bribes, changing names to less Jewish ones, and even sometimes traveling to distant regions of the USSR in order to find a new place to live (such as Birobidzhan in the Jewish Autonomous Region, for example). The author does not really differentiate between Soviet Jewish refugees and Jews who were deportees or refugees from Poland, the Baltic states, and Romania, each of which faced separate issues. The most salient difference was that the majority of Polish Jewish refugees had an opportunity to leave the Soviet Union in 1946, by the repatriation agreement, a feat that was almost impossible for Soviet Jews, who continued to suffer from antisemitic policies in the USSR. Traditional and religious Jewish life, or the lack thereof, also differentiated the experiences of the two groups of Jewish refugees. The plight of Jewish refugees in the Soviet Union has recently become a focus of attention in the field of Holocaust studies. Within just the last few years, several books, in a number of different languages, have been published on the topic. Kaganovitch’s book joins Polish Jews in the Soviet Union (1939–1959): History and Memory of Deportation, Exile, and Survival, edited by Katharina Friedla and Markus Nesselrodt; Syberiada Żydów polskich: Losy uchodźców z Zagłady...

Challenges in Understanding Western Economic and Financial Concepts from the Perspective of Young Adults with a Post-Soviet Migration Background in Germany—Findings from a Qualitative Interview Study

The content of economic education in Germany is based largely on the laws and ideals of the prevailing economic system. While Western concepts such as the competitive market typically are addressed in economic programs in Germany, they may be unfamiliar in Eastern European countries that were part of, or under the influence of, the former Soviet Union, where many youths living in Germany originate. Findings from large-scale quantitative studies of economic and financial literacy in Germany indicate that people who have a migration background (MB) perform worse on tests of economic literacy than those who do not; however, these studies do not provide sufficient insight into the underlying migration-related causes of the deficits in economic literacy. In this study we investigate the influence of family financial socialization on young adults’ understanding of economic and financial concepts. We interview eight young adults with a post-Soviet MB living in Germany using a two-part procedure: problem-centered and think-aloud interviews. We found that migrant parents directly and indirectly influenced their children’s understanding of economic and financial concepts in numerous ways, and we maintain that the best way to remedy the deficits in their understanding of such concepts is through targeted programs and teacher training.

Automatic Choroidal Segmentation in Optical Coherence Tomography Images Based on Curvelet Transform and Graph Theory.

Automatic segmentation of the choroid on optical coherence tomography (OCT) images helps ophthalmologists in diagnosing eye pathologies. Compared to manual segmentations, it is faster and is not affected by human errors. The presence of the large speckle noise in the OCT images limits the automatic segmentation and interpretation of them. To solve this problem, a new curvelet transform-based K-SVD method is proposed in this study. Furthermore, the dataset was manually segmented by a retinal ophthalmologist to draw a comparison with the proposed automatic segmentation technique. In this study, curvelet transform-based K-SVD dictionary learning and Lucy-Richardson algorithm were used to remove the speckle noise from OCT images. The Outer/Inner Choroidal Boundaries (O/ICB) were determined utilizing graph theory. The area between ICB and outer choroidal boundary was considered as the choroidal region. The proposed method was evaluated on our dataset and the average dice similarity coefficient (DSC) was calculated to be 92.14% ± 3.30% between automatic and manual segmented regions. Moreover, by applying the latest presented open-source algorithm by Mazzaferri et al. on our dataset, the mean DSC was calculated to be 55.75% ± 14.54%. A significant similarity was observed between automatic and manual segmentations. Automatic segmentation of the choroidal layer could be also utilized in large-scale quantitative studies of the choroid.

Quantification of Slip Band Distribution in Polycrystals: An Automated Fast Fourier Transform Decomposition Approach.

Plastic deformation is accumulated in slip bands in a wide variety of engineering alloys. Multiple material and loading conditions impact their distribution and degree of slip localization, but these effects are rarely quantified. To tackle this, the current work introduces a fast Fourier transform (FFT) decomposition method and applies it to a tensile-loaded polycrystalline nickel-based superalloy imaged via high-resolution digital image correlation and electron backscatter diffraction. This approach identifies active slip planes over the FFT images of individual grains and performs inverse transforms such that slip band traces with shared orientations are isolated. This technique enabled the largest quantification of slip band spacings and in-plane strains to date, with a total of 6,557 slip bands detected. The results show that the slip band spacings increase with grain size, with no evident dependence on grain orientation and Schmid factor. Slip bands are found to develop similar spacings along different octahedral planes and continue to spread over larger regions of the grain as the resolved shear stress of the active slip system increases. The FFT decomposition technique, which could be employed with multiple microscopy techniques, will allow for much-needed large-scale quantitative studies of slip localization.

Evidence for residential building retrofitting practices using explainable AI and socio-demographic data

Extensive retrofits and effective policy measures are needed to meet the ambitious climate goals, particularly in the UK, with the EU’s oldest residential building stock. Researchers must investigate the factors influencing retrofits to enable effective and targeted policy measures. To date, however, there is a lack of holistically large-scale quantitative studies accounting for such factors. At the same time, great potential is seen in data-driven solutions and the use of explainable artificial intelligence (XAI). We address this research gap by combining supervised machine learning with XAI employing a three-stage approach: First, we consolidate datasets of Energy Performance Certificates from England and Wales from which we extract conducted retrofits, house prices, and socio-demographic information. Second, we apply an eXtreme Gradient Boosting (XGBoost) model that predicts whether a building has been retrofitted or not. Lastly, we use SHapley Additive exPlanations values (SHAP) as an XAI technique to identify the key factors and relationships that influence the implementation of retrofits. We succeed in substantiating results previously obtained in qualitative or small-scale studies and also find that retrofit-related policies already implemented in regional cases, such as the ”Better Homes for Yorkshire” initiative, can successfully achieve large-scale success through replication in other regions. Further, our results suggest the implementation of income-based CO2 taxes as a reasonable and easy-to-implement policy measure.

Digital divides in access and use in literacy instruction in rural high schools

• Literacy instruction in rural schools varies widely in terms of technology use and access. • Large-scale quantitative studies fail to capture differences between local contexts. • Teacher technology training is essential but difficult to implement in rural schools. This article presents institutional case studies of technology use in language and literacy instruction at two rural high schools based on almost two months of classroom observations as well as interviews with teachers, administrators, and students. The first school presented faced a number of funding issues and clearly lacked in terms of access—the teachers regularly expressed frustration with district leadership and lamented their ability to have students do more computer-based literacy work. The second school presented had a very different issue—through a series of grants, they had secured computers for every student in their English classes but teachers had varying level of training on how to incorporate them in learning and consequently, the computers were often used in reductive ways. This research provides a perspective that shows the limitations of large-scale comparisons, emphasizing how local contextual factors (such as school leadership and teacher training) can shape both access and use. It also shows how access is only one piece of the picture—without sufficient teacher training and support, available technology may help perpetuate reductive educational practices in language and literacy instruction .

The Role of English Songs in Saudi Students’ Self-Learning of English

The present study aimed to explore the role of English songs in Saudi students’ self-learning of English as a foreign language. The study employed one data collection tool which was an online questionnaire. The questionnaire was completed by 38 Saudi students at the Community College of King Saud University in the second semester of the academic year 2020. The examination and analysis of the data showed that listening to English songs motivated the Saudi students to learn English in a self-study mode, augmented their English vocabulary, improved their speaking skill and developed their spelling or writing skill to a considerable extent. It is, therefore, recommended that more large-scale quantitative or qualitative studies on the role of English songs in Saudi students’ self-learning of English as a foreign language be conducted to confirm the findings of the present study, challenge them or yield new ones.

The (minority) stress of hiding: the effects of LGBT identities and social support on aging adults’ concern about housing

The lesbian, gay, bisexual, and/or transgender (LGBT) aging adult population is increasing rapidly in the United States. The literature reveals three shortcomings regarding research into the experiences of LGBT aging adults: (1) their needs have been largely overlooked, (2) there are few large-scale quantitative studies of this population, and (3) LGBT older adults are often treated as a monolith despite the potential for significant variations between subgroups under the umbrella. The current study addresses these issues by utilizing data from a nationwide AARP 2018 survey to study a central concern of LGBT aging adults: housing. Specifically, drawing upon the conceptual framework of minority stress, we examine how the LGBT identity of older people affects how concerned they are about having to hide their identity in order to find suitable housing as they age. Findings reveal (1) significant variations in the degree of worry among segments of the aging LGBT population, and (2) ameliorating factors such as social support may decrease the degree to which they worry about hiding their identity to access housing. These results may have implications for policies and practices aimed at increasing the community resilience available to support LGBT adults as they age.

Vegetable intake determinants in disadvantaged adolescents: systematic review of qualitative studies

Abstract Background Evidence available on the determinants of vegetable intake in young populations is inconsistent. No review has particularly focused on this topic in disadvantaged adolescents. This systematic review aimed to investigate the determinants of vegetable intake in disadvantaged adolescents reported in qualitative studies. Methods Five electronic databases were searched until October 2020 using combinations of synonyms for vegetable intake, adolescents, and qualitative methodologies. Studies published in peer-reviewed journals were included if they used qualitative methods (e.g., interviews, focus groups, etc.), targeted disadvantaged individuals aged 12-18 years, investigated determinants, motivators and barriers to vegetable intake, and were conducted in urban settings of high-income countries. Two reviewers independently and systematically summarized the papers, assessed their quality and synthesized the findings across studies. Results Sixteen studies meeting the inclusion criteria were included. The synthesis of findings identified the following determinants for vegetable intake: sensory attributes of vegetables; psychosocial factors (nutrition knowledge, preferences/liking, self-efficacy, motivation); lifestyle factors (cost/price, time, convenience); fast food properties (taste, cost, satiety); home environment; parental influence; encouragement/support outside the household; friends' influence; school nutrition education; teachers' support; school food environment; local produce; community nutrition knowledge; and availability and accessibility of vegetables in local stores, restaurants and fast-food outlets. Conclusions Multiple determinants of vegetable intake were identified which complement those investigated in quantitative studies. Future large scale quantitative studies should attempt to examine the relative importance of these determinants in order to guide the development of successful interventions in disadvantaged adolescents. Key messages Vegetable intake is influenced by multiple factors in disadvantaged adolescents. Main determinants are vegetable attributes, personal factors, friends, family, school and community environment.

Platforms and Ecosystems: Building and Sustaining Competitive Advantages

Over the last decade, platforms have become an indispensable form of economic transactions in many industries and attracted attention from academic scholars and policymakers alike. In this symposium, we bring together a group of panelists to share their insights on how platforms can design and implement efficient strategies to foster engagement and cooperation among third-party participants (i.e., users and complementors). The panelists come from diverse theoretical perspectives (e.g., the theory of the firm, economics, digitalization, strategic leadership, etc.) and employ diverse methodologies (large-scale quantitative studies and field / lab experiments). By sharing recent advances and ongoing research in the field, this symposium aims to advance our understanding on how platforms can build and sustain their competitive advantages by influencing and leveraging their participants. Promoting Platform Takeoff and Self-Fulfilling Expectations: Field Experimental Evidence Presenter: Kevin Boudreau; Northeastern & NBER How Incentive Structure Affects the Effectiveness of Referral Strategy Presenter: Qiang Li; Hong Kong U. of Science and Technology Presenter: Bo Zhao; U. of hong kong Presenter: Brian Wu; U. of Michigan Feeding Chickens: Anonymity in the Context of Organizational Resource Exchange Platforms Presenter: Maren Alana Mickeler; Ludwig Maximilian U. of Munich (LMU) Presenter: Pooyan Khashabi; LMU Munich Presenter: Marco Kleine; Max Planck Institute for Innovation and Competition Presenter: Tobias Kretschmer; LMU Munich Managing Ecosystem’s Innovation Trajectory through Sponsoring a few Complementary Products Presenter: Shiva Agarwal; U. of Texas at Austin Presenter: Cameron Miller; Syracuse U. Presenter: Martin Ganco; Wisconsin School of Business Technological Convergence or Divergence? Platform Standardization and Complementors' Search Presenter: Cameron Miller; Syracuse U. Presenter: PuayKhoon Toh; U. of Texas at Austin Presenter: Eugene Pyun; U. of Texas at Austin

Ultrafast and Reproducible Proteomics from Small Amounts of Heart Tissue Enabled by Azo and timsTOF Pro.

Global bottom-up mass spectrometry (MS)-based proteomics is widely used for protein identification and quantification to achieve a comprehensive understanding of the composition, structure, and function of the proteome. However, traditional sample preparation methods are time-consuming, typically including overnight tryptic digestion, extensive sample cleanup to remove MS-incompatible surfactants, and offline sample fractionation to reduce proteome complexity prior to online liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. Thus, there is a need for a fast, robust, and reproducible method for protein identification and quantification from complex proteomes. Herein, we developed an ultrafast bottom-up proteomics method enabled by Azo, a photocleavable, MS-compatible surfactant that effectively solubilizes proteins and promotes rapid tryptic digestion, combined with the Bruker timsTOF Pro, which enables deeper proteome coverage through trapped ion mobility spectrometry (TIMS) and parallel accumulation-serial fragmentation (PASEF) of peptides. We applied this method to analyze the complex human cardiac proteome and identified nearly 4000 protein groups from as little as 1 mg of human heart tissue in a single one-dimensional LC-TIMS-MS/MS run with high reproducibility. Overall, we anticipate this ultrafast, robust, and reproducible bottom-up method empowered by both Azo and the timsTOF Pro will be generally applicable and greatly accelerate the throughput of large-scale quantitative proteomic studies. Raw data are available via the MassIVE repository with identifier MSV000087476.